Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes

PubMed Central

Wason, James M. S.; Mander, Adrian P.

2012-01-01

Two-stage designs are commonly used for Phase II trials. Optimal two-stage designs have the lowest expected sample size for a specific treatment effect, for example, the null value, but can perform poorly if the true treatment effect differs. Here we introduce a design for continuous treatment responses that minimizes the maximum expected sample size across all possible treatment effects. The proposed design performs well for a wider range of treatment effects and so is useful for Phase II trials. We compare the design to a previously used optimal design and show it has superior expected sample size properties. PMID:22651118

[An investigation of the statistical power of the effect size in randomized controlled trials for the treatment of patients with type 2 diabetes mellitus using Chinese medicine].

PubMed

Ma, Li-Xin; Liu, Jian-Ping

2012-01-01

To investigate whether the power of the effect size was based on adequate sample size in randomized controlled trials (RCTs) for the treatment of patients with type 2 diabetes mellitus (T2DM) using Chinese medicine. China Knowledge Resource Integrated Database (CNKI), VIP Database for Chinese Technical Periodicals (VIP), Chinese Biomedical Database (CBM), and Wangfang Data were systematically recruited using terms like "Xiaoke" or diabetes, Chinese herbal medicine, patent medicine, traditional Chinese medicine, randomized, controlled, blinded, and placebo-controlled. Limitation was set on the intervention course > or = 3 months in order to identify the information of outcome assessement and the sample size. Data collection forms were made according to the checking lists found in the CONSORT statement. Independent double data extractions were performed on all included trials. The statistical power of the effects size for each RCT study was assessed using sample size calculation equations. (1) A total of 207 RCTs were included, including 111 superiority trials and 96 non-inferiority trials. (2) Among the 111 superiority trials, fasting plasma glucose (FPG) and glycosylated hemoglobin HbA1c (HbA1c) outcome measure were reported in 9% and 12% of the RCTs respectively with the sample size > 150 in each trial. For the outcome of HbA1c, only 10% of the RCTs had more than 80% power. For FPG, 23% of the RCTs had more than 80% power. (3) In the 96 non-inferiority trials, the outcomes FPG and HbA1c were reported as 31% and 36% respectively. These RCTs had a samples size > 150. For HbA1c only 36% of the RCTs had more than 80% power. For FPG, only 27% of the studies had more than 80% power. The sample size for statistical analysis was distressingly low and most RCTs did not achieve 80% power. In order to obtain a sufficient statistic power, it is recommended that clinical trials should establish clear research objective and hypothesis first, and choose scientific and evidence-based study design and outcome measurements. At the same time, calculate required sample size to ensure a precise research conclusion.

A Bayesian approach for incorporating economic factors in sample size design for clinical trials of individual drugs and portfolios of drugs.

PubMed

Patel, Nitin R; Ankolekar, Suresh

2007-11-30

Classical approaches to clinical trial design ignore economic factors that determine economic viability of a new drug. We address the choice of sample size in Phase III trials as a decision theory problem using a hybrid approach that takes a Bayesian view from the perspective of a drug company and a classical Neyman-Pearson view from the perspective of regulatory authorities. We incorporate relevant economic factors in the analysis to determine the optimal sample size to maximize the expected profit for the company. We extend the analysis to account for risk by using a 'satisficing' objective function that maximizes the chance of meeting a management-specified target level of profit. We extend the models for single drugs to a portfolio of clinical trials and optimize the sample sizes to maximize the expected profit subject to budget constraints. Further, we address the portfolio risk and optimize the sample sizes to maximize the probability of achieving a given target of expected profit.

Sample size requirements for separating out the effects of combination treatments: randomised controlled trials of combination therapy vs. standard treatment compared to factorial designs for patients with tuberculous meningitis.

PubMed

Wolbers, Marcel; Heemskerk, Dorothee; Chau, Tran Thi Hong; Yen, Nguyen Thi Bich; Caws, Maxine; Farrar, Jeremy; Day, Jeremy

2011-02-02

In certain diseases clinical experts may judge that the intervention with the best prospects is the addition of two treatments to the standard of care. This can either be tested with a simple randomized trial of combination versus standard treatment or with a 2 x 2 factorial design. We compared the two approaches using the design of a new trial in tuberculous meningitis as an example. In that trial the combination of 2 drugs added to standard treatment is assumed to reduce the hazard of death by 30% and the sample size of the combination trial to achieve 80% power is 750 patients. We calculated the power of corresponding factorial designs with one- to sixteen-fold the sample size of the combination trial depending on the contribution of each individual drug to the combination treatment effect and the strength of an interaction between the two. In the absence of an interaction, an eight-fold increase in sample size for the factorial design as compared to the combination trial is required to get 80% power to jointly detect effects of both drugs if the contribution of the less potent treatment to the total effect is at least 35%. An eight-fold sample size increase also provides a power of 76% to detect a qualitative interaction at the one-sided 10% significance level if the individual effects of both drugs are equal. Factorial designs with a lower sample size have a high chance to be underpowered, to show significance of only one drug even if both are equally effective, and to miss important interactions. Pragmatic combination trials of multiple interventions versus standard therapy are valuable in diseases with a limited patient pool if all interventions test the same treatment concept, it is considered likely that either both or none of the individual interventions are effective, and only moderate drug interactions are suspected. An adequately powered 2 x 2 factorial design to detect effects of individual drugs would require at least 8-fold the sample size of the combination trial. Current Controlled Trials ISRCTN61649292.

Addressing small sample size bias in multiple-biomarker trials: Inclusion of biomarker-negative patients and Firth correction.

PubMed

Habermehl, Christina; Benner, Axel; Kopp-Schneider, Annette

2018-03-01

In recent years, numerous approaches for biomarker-based clinical trials have been developed. One of these developments are multiple-biomarker trials, which aim to investigate multiple biomarkers simultaneously in independent subtrials. For low-prevalence biomarkers, small sample sizes within the subtrials have to be expected, as well as many biomarker-negative patients at the screening stage. The small sample sizes may make it unfeasible to analyze the subtrials individually. This imposes the need to develop new approaches for the analysis of such trials. With an expected large group of biomarker-negative patients, it seems reasonable to explore options to benefit from including them in such trials. We consider advantages and disadvantages of the inclusion of biomarker-negative patients in a multiple-biomarker trial with a survival endpoint. We discuss design options that include biomarker-negative patients in the study and address the issue of small sample size bias in such trials. We carry out a simulation study for a design where biomarker-negative patients are kept in the study and are treated with standard of care. We compare three different analysis approaches based on the Cox model to examine if the inclusion of biomarker-negative patients can provide a benefit with respect to bias and variance of the treatment effect estimates. We apply the Firth correction to reduce the small sample size bias. The results of the simulation study suggest that for small sample situations, the Firth correction should be applied to adjust for the small sample size bias. Additional to the Firth penalty, the inclusion of biomarker-negative patients in the analysis can lead to further but small improvements in bias and standard deviation of the estimates. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The choice of sample size: a mixed Bayesian / frequentist approach.

PubMed

Pezeshk, Hamid; Nematollahi, Nader; Maroufy, Vahed; Gittins, John

2009-04-01

Sample size computations are largely based on frequentist or classical methods. In the Bayesian approach the prior information on the unknown parameters is taken into account. In this work we consider a fully Bayesian approach to the sample size determination problem which was introduced by Grundy et al. and developed by Lindley. This approach treats the problem as a decision problem and employs a utility function to find the optimal sample size of a trial. Furthermore, we assume that a regulatory authority, which is deciding on whether or not to grant a licence to a new treatment, uses a frequentist approach. We then find the optimal sample size for the trial by maximising the expected net benefit, which is the expected benefit of subsequent use of the new treatment minus the cost of the trial.

Sample size calculations for comparative clinical trials with over-dispersed Poisson process data.

PubMed

Matsui, Shigeyuki

2005-05-15

This paper develops a new formula for sample size calculations for comparative clinical trials with Poisson or over-dispersed Poisson process data. The criteria for sample size calculations is developed on the basis of asymptotic approximations for a two-sample non-parametric test to compare the empirical event rate function between treatment groups. This formula can accommodate time heterogeneity, inter-patient heterogeneity in event rate, and also, time-varying treatment effects. An application of the formula to a trial for chronic granulomatous disease is provided. Copyright 2004 John Wiley & Sons, Ltd.

Reporting and methodological quality of sample size calculations in cluster randomized trials could be improved: a review.

PubMed

Rutterford, Clare; Taljaard, Monica; Dixon, Stephanie; Copas, Andrew; Eldridge, Sandra

2015-06-01

To assess the quality of reporting and accuracy of a priori estimates used in sample size calculations for cluster randomized trials (CRTs). We reviewed 300 CRTs published between 2000 and 2008. The prevalence of reporting sample size elements from the 2004 CONSORT recommendations was evaluated and a priori estimates compared with those observed in the trial. Of the 300 trials, 166 (55%) reported a sample size calculation. Only 36 of 166 (22%) reported all recommended descriptive elements. Elements specific to CRTs were the worst reported: a measure of within-cluster correlation was specified in only 58 of 166 (35%). Only 18 of 166 articles (11%) reported both a priori and observed within-cluster correlation values. Except in two cases, observed within-cluster correlation values were either close to or less than a priori values. Even with the CONSORT extension for cluster randomization, the reporting of sample size elements specific to these trials remains below that necessary for transparent reporting. Journal editors and peer reviewers should implement stricter requirements for authors to follow CONSORT recommendations. Authors should report observed and a priori within-cluster correlation values to enable comparisons between these over a wider range of trials. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

An imbalance in cluster sizes does not lead to notable loss of power in cross-sectional, stepped-wedge cluster randomised trials with a continuous outcome.

PubMed

Kristunas, Caroline A; Smith, Karen L; Gray, Laura J

2017-03-07

The current methodology for sample size calculations for stepped-wedge cluster randomised trials (SW-CRTs) is based on the assumption of equal cluster sizes. However, as is often the case in cluster randomised trials (CRTs), the clusters in SW-CRTs are likely to vary in size, which in other designs of CRT leads to a reduction in power. The effect of an imbalance in cluster size on the power of SW-CRTs has not previously been reported, nor what an appropriate adjustment to the sample size calculation should be to allow for any imbalance. We aimed to assess the impact of an imbalance in cluster size on the power of a cross-sectional SW-CRT and recommend a method for calculating the sample size of a SW-CRT when there is an imbalance in cluster size. The effect of varying degrees of imbalance in cluster size on the power of SW-CRTs was investigated using simulations. The sample size was calculated using both the standard method and two proposed adjusted design effects (DEs), based on those suggested for CRTs with unequal cluster sizes. The data were analysed using generalised estimating equations with an exchangeable correlation matrix and robust standard errors. An imbalance in cluster size was not found to have a notable effect on the power of SW-CRTs. The two proposed adjusted DEs resulted in trials that were generally considerably over-powered. We recommend that the standard method of sample size calculation for SW-CRTs be used, provided that the assumptions of the method hold. However, it would be beneficial to investigate, through simulation, what effect the maximum likely amount of inequality in cluster sizes would be on the power of the trial and whether any inflation of the sample size would be required.

A multi-stage drop-the-losers design for multi-arm clinical trials.

PubMed

Wason, James; Stallard, Nigel; Bowden, Jack; Jennison, Christopher

2017-02-01

Multi-arm multi-stage trials can improve the efficiency of the drug development process when multiple new treatments are available for testing. A group-sequential approach can be used in order to design multi-arm multi-stage trials, using an extension to Dunnett's multiple-testing procedure. The actual sample size used in such a trial is a random variable that has high variability. This can cause problems when applying for funding as the cost will also be generally highly variable. This motivates a type of design that provides the efficiency advantages of a group-sequential multi-arm multi-stage design, but has a fixed sample size. One such design is the two-stage drop-the-losers design, in which a number of experimental treatments, and a control treatment, are assessed at a prescheduled interim analysis. The best-performing experimental treatment and the control treatment then continue to a second stage. In this paper, we discuss extending this design to have more than two stages, which is shown to considerably reduce the sample size required. We also compare the resulting sample size requirements to the sample size distribution of analogous group-sequential multi-arm multi-stage designs. The sample size required for a multi-stage drop-the-losers design is usually higher than, but close to, the median sample size of a group-sequential multi-arm multi-stage trial. In many practical scenarios, the disadvantage of a slight loss in average efficiency would be overcome by the huge advantage of a fixed sample size. We assess the impact of delay between recruitment and assessment as well as unknown variance on the drop-the-losers designs.

Systematic review finds major deficiencies in sample size methodology and reporting for stepped-wedge cluster randomised trials

PubMed Central

Martin, James; Taljaard, Monica; Girling, Alan; Hemming, Karla

2016-01-01

Background Stepped-wedge cluster randomised trials (SW-CRT) are increasingly being used in health policy and services research, but unless they are conducted and reported to the highest methodological standards, they are unlikely to be useful to decision-makers. Sample size calculations for these designs require allowance for clustering, time effects and repeated measures. Methods We carried out a methodological review of SW-CRTs up to October 2014. We assessed adherence to reporting each of the 9 sample size calculation items recommended in the 2012 extension of the CONSORT statement to cluster trials. Results We identified 32 completed trials and 28 independent protocols published between 1987 and 2014. Of these, 45 (75%) reported a sample size calculation, with a median of 5.0 (IQR 2.5–6.0) of the 9 CONSORT items reported. Of those that reported a sample size calculation, the majority, 33 (73%), allowed for clustering, but just 15 (33%) allowed for time effects. There was a small increase in the proportions reporting a sample size calculation (from 64% before to 84% after publication of the CONSORT extension, p=0.07). The type of design (cohort or cross-sectional) was not reported clearly in the majority of studies, but cohort designs seemed to be most prevalent. Sample size calculations in cohort designs were particularly poor with only 3 out of 24 (13%) of these studies allowing for repeated measures. Discussion The quality of reporting of sample size items in stepped-wedge trials is suboptimal. There is an urgent need for dissemination of the appropriate guidelines for reporting and methodological development to match the proliferation of the use of this design in practice. Time effects and repeated measures should be considered in all SW-CRT power calculations, and there should be clarity in reporting trials as cohort or cross-sectional designs. PMID:26846897

Sample size requirements for separating out the effects of combination treatments: Randomised controlled trials of combination therapy vs. standard treatment compared to factorial designs for patients with tuberculous meningitis

PubMed Central

2011-01-01

Background In certain diseases clinical experts may judge that the intervention with the best prospects is the addition of two treatments to the standard of care. This can either be tested with a simple randomized trial of combination versus standard treatment or with a 2 × 2 factorial design. Methods We compared the two approaches using the design of a new trial in tuberculous meningitis as an example. In that trial the combination of 2 drugs added to standard treatment is assumed to reduce the hazard of death by 30% and the sample size of the combination trial to achieve 80% power is 750 patients. We calculated the power of corresponding factorial designs with one- to sixteen-fold the sample size of the combination trial depending on the contribution of each individual drug to the combination treatment effect and the strength of an interaction between the two. Results In the absence of an interaction, an eight-fold increase in sample size for the factorial design as compared to the combination trial is required to get 80% power to jointly detect effects of both drugs if the contribution of the less potent treatment to the total effect is at least 35%. An eight-fold sample size increase also provides a power of 76% to detect a qualitative interaction at the one-sided 10% significance level if the individual effects of both drugs are equal. Factorial designs with a lower sample size have a high chance to be underpowered, to show significance of only one drug even if both are equally effective, and to miss important interactions. Conclusions Pragmatic combination trials of multiple interventions versus standard therapy are valuable in diseases with a limited patient pool if all interventions test the same treatment concept, it is considered likely that either both or none of the individual interventions are effective, and only moderate drug interactions are suspected. An adequately powered 2 × 2 factorial design to detect effects of individual drugs would require at least 8-fold the sample size of the combination trial. Trial registration Current Controlled Trials ISRCTN61649292 PMID:21288326

Small studies may overestimate the effect sizes in critical care meta-analyses: a meta-epidemiological study

PubMed Central

2013-01-01

Introduction Small-study effects refer to the fact that trials with limited sample sizes are more likely to report larger beneficial effects than large trials. However, this has never been investigated in critical care medicine. Thus, the present study aimed to examine the presence and extent of small-study effects in critical care medicine. Methods Critical care meta-analyses involving randomized controlled trials and reported mortality as an outcome measure were considered eligible for the study. Component trials were classified as large (≥100 patients per arm) and small (<100 patients per arm) according to their sample sizes. Ratio of odds ratio (ROR) was calculated for each meta-analysis and then RORs were combined using a meta-analytic approach. ROR<1 indicated larger beneficial effect in small trials. Small and large trials were compared in methodological qualities including sequence generating, blinding, allocation concealment, intention to treat and sample size calculation. Results A total of 27 critical care meta-analyses involving 317 trials were included. Of them, five meta-analyses showed statistically significant RORs <1, and other meta-analyses did not reach a statistical significance. Overall, the pooled ROR was 0.60 (95% CI: 0.53 to 0.68); the heterogeneity was moderate with an I2 of 50.3% (chi-squared = 52.30; P = 0.002). Large trials showed significantly better reporting quality than small trials in terms of sequence generating, allocation concealment, blinding, intention to treat, sample size calculation and incomplete follow-up data. Conclusions Small trials are more likely to report larger beneficial effects than large trials in critical care medicine, which could be partly explained by the lower methodological quality in small trials. Caution should be practiced in the interpretation of meta-analyses involving small trials. PMID:23302257

Sample Size in Clinical Cardioprotection Trials Using Myocardial Salvage Index, Infarct Size, or Biochemical Markers as Endpoint.

PubMed

Engblom, Henrik; Heiberg, Einar; Erlinge, David; Jensen, Svend Eggert; Nordrehaug, Jan Erik; Dubois-Randé, Jean-Luc; Halvorsen, Sigrun; Hoffmann, Pavel; Koul, Sasha; Carlsson, Marcus; Atar, Dan; Arheden, Håkan

2016-03-09

Cardiac magnetic resonance (CMR) can quantify myocardial infarct (MI) size and myocardium at risk (MaR), enabling assessment of myocardial salvage index (MSI). We assessed how MSI impacts the number of patients needed to reach statistical power in relation to MI size alone and levels of biochemical markers in clinical cardioprotection trials and how scan day affect sample size. Controls (n=90) from the recent CHILL-MI and MITOCARE trials were included. MI size, MaR, and MSI were assessed from CMR. High-sensitivity troponin T (hsTnT) and creatine kinase isoenzyme MB (CKMB) levels were assessed in CHILL-MI patients (n=50). Utilizing distribution of these variables, 100 000 clinical trials were simulated for calculation of sample size required to reach sufficient power. For a treatment effect of 25% decrease in outcome variables, 50 patients were required in each arm using MSI compared to 93, 98, 120, 141, and 143 for MI size alone, hsTnT (area under the curve [AUC] and peak), and CKMB (AUC and peak) in order to reach a power of 90%. If average CMR scan day between treatment and control arms differed by 1 day, sample size needs to be increased by 54% (77 vs 50) to avoid scan day bias masking a treatment effect of 25%. Sample size in cardioprotection trials can be reduced 46% to 65% without compromising statistical power when using MSI by CMR as an outcome variable instead of MI size alone or biochemical markers. It is essential to ensure lack of bias in scan day between treatment and control arms to avoid compromising statistical power. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Impact of Different Visual Field Testing Paradigms on Sample Size Requirements for Glaucoma Clinical Trials.

PubMed

Wu, Zhichao; Medeiros, Felipe A

2018-03-20

Visual field testing is an important endpoint in glaucoma clinical trials, and the testing paradigm used can have a significant impact on the sample size requirements. To investigate this, this study included 353 eyes of 247 glaucoma patients seen over a 3-year period to extract real-world visual field rates of change and variability estimates to provide sample size estimates from computer simulations. The clinical trial scenario assumed that a new treatment was added to one of two groups that were both under routine clinical care, with various treatment effects examined. Three different visual field testing paradigms were evaluated: a) evenly spaced testing, b) United Kingdom Glaucoma Treatment Study (UKGTS) follow-up scheme, which adds clustered tests at the beginning and end of follow-up in addition to evenly spaced testing, and c) clustered testing paradigm, with clusters of tests at the beginning and end of the trial period and two intermediary visits. The sample size requirements were reduced by 17-19% and 39-40% using the UKGTS and clustered testing paradigms, respectively, when compared to the evenly spaced approach. These findings highlight how the clustered testing paradigm can substantially reduce sample size requirements and improve the feasibility of future glaucoma clinical trials.

Sample size determination in group-sequential clinical trials with two co-primary endpoints

PubMed Central

Asakura, Koko; Hamasaki, Toshimitsu; Sugimoto, Tomoyuki; Hayashi, Kenichi; Evans, Scott R; Sozu, Takashi

2014-01-01

We discuss sample size determination in group-sequential designs with two endpoints as co-primary. We derive the power and sample size within two decision-making frameworks. One is to claim the test intervention’s benefit relative to control when superiority is achieved for the two endpoints at the same interim timepoint of the trial. The other is when the superiority is achieved for the two endpoints at any interim timepoint, not necessarily simultaneously. We evaluate the behaviors of sample size and power with varying design elements and provide a real example to illustrate the proposed sample size methods. In addition, we discuss sample size recalculation based on observed data and evaluate the impact on the power and Type I error rate. PMID:24676799

Design and analysis of three-arm trials with negative binomially distributed endpoints.

PubMed

Mütze, Tobias; Munk, Axel; Friede, Tim

2016-02-20

A three-arm clinical trial design with an experimental treatment, an active control, and a placebo control, commonly referred to as the gold standard design, enables testing of non-inferiority or superiority of the experimental treatment compared with the active control. In this paper, we propose methods for designing and analyzing three-arm trials with negative binomially distributed endpoints. In particular, we develop a Wald-type test with a restricted maximum-likelihood variance estimator for testing non-inferiority or superiority. For this test, sample size and power formulas as well as optimal sample size allocations will be derived. The performance of the proposed test will be assessed in an extensive simulation study with regard to type I error rate, power, sample size, and sample size allocation. For the purpose of comparison, Wald-type statistics with a sample variance estimator and an unrestricted maximum-likelihood estimator are included in the simulation study. We found that the proposed Wald-type test with a restricted variance estimator performed well across the considered scenarios and is therefore recommended for application in clinical trials. The methods proposed are motivated and illustrated by a recent clinical trial in multiple sclerosis. The R package ThreeArmedTrials, which implements the methods discussed in this paper, is available on CRAN. Copyright © 2015 John Wiley & Sons, Ltd.

The effect of journal impact factor, reporting conflicts, and reporting funding sources, on standardized effect sizes in back pain trials: a systematic review and meta-regression.

PubMed

Froud, Robert; Bjørkli, Tom; Bright, Philip; Rajendran, Dévan; Buchbinder, Rachelle; Underwood, Martin; Evans, David; Eldridge, Sandra

2015-11-30

Low back pain is a common and costly health complaint for which there are several moderately effective treatments. In some fields there is evidence that funder and financial conflicts are associated with trial outcomes. It is not clear whether effect sizes in back pain trials relate to journal impact factor, reporting conflicts of interest, or reporting funding. We performed a systematic review of English-language papers reporting randomised controlled trials of treatments for non-specific low back pain, published between 2006-2012. We modelled the relationship using 5-year journal impact factor, and categories of reported of conflicts of interest, and categories of reported funding (reported none and reported some, compared to not reporting these) using meta-regression, adjusting for sample size, and publication year. We also considered whether impact factor could be predicted by the direction of outcome, or trial sample size. We could abstract data to calculate effect size in 99 of 146 trials that met our inclusion criteria. Effect size is not associated with impact factor, reporting of funding source, or reporting of conflicts of interest. However, explicitly reporting 'no trial funding' is strongly associated with larger absolute values of effect size (adjusted β=1.02 (95 % CI 0.44 to 1.59), P=0.001). Impact factor increases by 0.008 (0.004 to 0.012) per unit increase in trial sample size (P<0.001), but does not differ by reported direction of the LBP trial outcome (P=0.270). The absence of associations between effect size and impact factor, reporting sources of funding, and conflicts of interest reflects positively on research and publisher conduct in the field. Strong evidence of a large association between absolute magnitude of effect size and explicit reporting of 'no funding' suggests authors of unfunded trials are likely to report larger effect sizes, notwithstanding direction. This could relate in part to quality, resources, and/or how pragmatic a trial is.

The optimal design of stepped wedge trials with equal allocation to sequences and a comparison to other trial designs.

PubMed

Thompson, Jennifer A; Fielding, Katherine; Hargreaves, James; Copas, Andrew

2017-12-01

Background/Aims We sought to optimise the design of stepped wedge trials with an equal allocation of clusters to sequences and explored sample size comparisons with alternative trial designs. Methods We developed a new expression for the design effect for a stepped wedge trial, assuming that observations are equally correlated within clusters and an equal number of observations in each period between sequences switching to the intervention. We minimised the design effect with respect to (1) the fraction of observations before the first and after the final sequence switches (the periods with all clusters in the control or intervention condition, respectively) and (2) the number of sequences. We compared the design effect of this optimised stepped wedge trial to the design effects of a parallel cluster-randomised trial, a cluster-randomised trial with baseline observations, and a hybrid trial design (a mixture of cluster-randomised trial and stepped wedge trial) with the same total cluster size for all designs. Results We found that a stepped wedge trial with an equal allocation to sequences is optimised by obtaining all observations after the first sequence switches and before the final sequence switches to the intervention; this means that the first sequence remains in the control condition and the last sequence remains in the intervention condition for the duration of the trial. With this design, the optimal number of sequences is [Formula: see text], where [Formula: see text] is the cluster-mean correlation, [Formula: see text] is the intracluster correlation coefficient, and m is the total cluster size. The optimal number of sequences is small when the intracluster correlation coefficient and cluster size are small and large when the intracluster correlation coefficient or cluster size is large. A cluster-randomised trial remains more efficient than the optimised stepped wedge trial when the intracluster correlation coefficient or cluster size is small. A cluster-randomised trial with baseline observations always requires a larger sample size than the optimised stepped wedge trial. The hybrid design can always give an equally or more efficient design, but will be at most 5% more efficient. We provide a strategy for selecting a design if the optimal number of sequences is unfeasible. For a non-optimal number of sequences, the sample size may be reduced by allowing a proportion of observations before the first or after the final sequence has switched. Conclusion The standard stepped wedge trial is inefficient. To reduce sample sizes when a hybrid design is unfeasible, stepped wedge trial designs should have no observations before the first sequence switches or after the final sequence switches.

Exact tests using two correlated binomial variables in contemporary cancer clinical trials.

PubMed

Yu, Jihnhee; Kepner, James L; Iyer, Renuka

2009-12-01

New therapy strategies for the treatment of cancer are rapidly emerging because of recent technology advances in genetics and molecular biology. Although newer targeted therapies can improve survival without measurable changes in tumor size, clinical trial conduct has remained nearly unchanged. When potentially efficacious therapies are tested, current clinical trial design and analysis methods may not be suitable for detecting therapeutic effects. We propose an exact method with respect to testing cytostatic cancer treatment using correlated bivariate binomial random variables to simultaneously assess two primary outcomes. The method is easy to implement. It does not increase the sample size over that of the univariate exact test and in most cases reduces the sample size required. Sample size calculations are provided for selected designs.

Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials

PubMed Central

Verhey, Leonard H.; Signori, Alessio; Arnold, Douglas L.; Bar-Or, Amit; Sadovnick, A. Dessa; Marrie, Ruth Ann; Banwell, Brenda

2013-01-01

Objective: To estimate sample sizes for pediatric multiple sclerosis (MS) trials using new T2 lesion count, annualized relapse rate (ARR), and time to first relapse (TTFR) endpoints. Methods: Poisson and negative binomial models were fit to new T2 lesion and relapse count data, and negative binomial time-to-event and exponential models were fit to TTFR data of 42 children with MS enrolled in a national prospective cohort study. Simulations were performed by resampling from the best-fitting model of new T2 lesion count, number of relapses, or TTFR, under various assumptions of the effect size, trial duration, and model parameters. Results: Assuming a 50% reduction in new T2 lesions over 6 months, 90 patients/arm are required, whereas 165 patients/arm are required for a 40% treatment effect. Sample sizes for 2-year trials using relapse-related endpoints are lower than that for 1-year trials. For 2-year trials and a conservative assumption of overdispersion (ϑ), sample sizes range from 70 patients/arm (using ARR) to 105 patients/arm (TTFR) for a 50% reduction in relapses, and 230 patients/arm (ARR) to 365 patients/arm (TTFR) for a 30% relapse reduction. Assuming a less conservative ϑ, 2-year trials using ARR require 45 patients/arm (60 patients/arm for TTFR) for a 50% reduction in relapses and 145 patients/arm (200 patients/arm for TTFR) for a 30% reduction. Conclusion: Six-month phase II trials using new T2 lesion count as an endpoint are feasible in the pediatric MS population; however, trials powered on ARR or TTFR will need to be 2 years in duration and will require multicentered collaboration. PMID:23966255

Sample size calculations for the design of cluster randomized trials: A summary of methodology.

PubMed

Gao, Fei; Earnest, Arul; Matchar, David B; Campbell, Michael J; Machin, David

2015-05-01

Cluster randomized trial designs are growing in popularity in, for example, cardiovascular medicine research and other clinical areas and parallel statistical developments concerned with the design and analysis of these trials have been stimulated. Nevertheless, reviews suggest that design issues associated with cluster randomized trials are often poorly appreciated and there remain inadequacies in, for example, describing how the trial size is determined and the associated results are presented. In this paper, our aim is to provide pragmatic guidance for researchers on the methods of calculating sample sizes. We focus attention on designs with the primary purpose of comparing two interventions with respect to continuous, binary, ordered categorical, incidence rate and time-to-event outcome variables. Issues of aggregate and non-aggregate cluster trials, adjustment for variation in cluster size and the effect size are detailed. The problem of establishing the anticipated magnitude of between- and within-cluster variation to enable planning values of the intra-cluster correlation coefficient and the coefficient of variation are also described. Illustrative examples of calculations of trial sizes for each endpoint type are included. Copyright © 2015 Elsevier Inc. All rights reserved.

Does the low prevalence affect the sample size of interventional clinical trials of rare diseases? An analysis of data from the aggregate analysis of clinicaltrials.gov.

PubMed

Hee, Siew Wan; Willis, Adrian; Tudur Smith, Catrin; Day, Simon; Miller, Frank; Madan, Jason; Posch, Martin; Zohar, Sarah; Stallard, Nigel

2017-03-02

Clinical trials are typically designed using the classical frequentist framework to constrain type I and II error rates. Sample sizes required in such designs typically range from hundreds to thousands of patients which can be challenging for rare diseases. It has been shown that rare disease trials have smaller sample sizes than non-rare disease trials. Indeed some orphan drugs were approved by the European Medicines Agency based on studies with as few as 12 patients. However, some studies supporting marketing authorisation included several hundred patients. In this work, we explore the relationship between disease prevalence and other factors and the size of interventional phase 2 and 3 rare disease trials conducted in the US and/or EU. We downloaded all clinical trials from Aggregate Analysis of ClinialTrials.gov (AACT) and identified rare disease trials by cross-referencing MeSH terms in AACT with the list from Orphadata. We examined the effects of prevalence and phase of study in a multiple linear regression model adjusting for other statistically significant trial characteristics. Of 186941 ClinicalTrials.gov trials only 1567 (0.8%) studied a single rare condition with prevalence information from Orphadata. There were 19 (1.2%) trials studying disease with prevalence <1/1,000,000, 126 (8.0%) trials with 1-9/1,000,000, 791 (50.5%) trials with 1-9/100,000 and 631 (40.3%) trials with 1-5/10,000. Of the 1567 trials, 1160 (74%) were phase 2 trials. The fitted mean sample size for the rarest disease (prevalence <1/1,000,000) in phase 2 trials was the lowest (mean, 15.7; 95% CI, 8.7-28.1) but were similar across all the other prevalence classes; mean, 26.2 (16.1-42.6), 33.8 (22.1-51.7) and 35.6 (23.3-54.3) for prevalence 1-9/1,000,000, 1-9/100,000 and 1-5/10,000, respectively. Fitted mean size of phase 3 trials of rarer diseases, <1/1,000,000 (19.2, 6.9-53.2) and 1-9/1,000,000 (33.1, 18.6-58.9), were similar to those in phase 2 but were statistically significant lower than the slightly less rare diseases, 1-9/100,000 (75.3, 48.2-117.6) and 1-5/10,000 (77.7, 49.6-121.8), trials. We found that prevalence was associated with the size of phase 3 trials with trials of rarer diseases noticeably smaller than the less rare diseases trials where phase 3 rarer disease (prevalence <1/100,000) trials were more similar in size to those for phase 2 but were larger than those for phase 2 in the less rare disease (prevalence ≥1/100,000) trials.

An opportunity cost approach to sample size calculation in cost-effectiveness analysis.

PubMed

Gafni, A; Walter, S D; Birch, S; Sendi, P

2008-01-01

The inclusion of economic evaluations as part of clinical trials has led to concerns about the adequacy of trial sample size to support such analysis. The analytical tool of cost-effectiveness analysis is the incremental cost-effectiveness ratio (ICER), which is compared with a threshold value (lambda) as a method to determine the efficiency of a health-care intervention. Accordingly, many of the methods suggested to calculating the sample size requirements for the economic component of clinical trials are based on the properties of the ICER. However, use of the ICER and a threshold value as a basis for determining efficiency has been shown to be inconsistent with the economic concept of opportunity cost. As a result, the validity of the ICER-based approaches to sample size calculations can be challenged. Alternative methods for determining improvements in efficiency have been presented in the literature that does not depend upon ICER values. In this paper, we develop an opportunity cost approach to calculating sample size for economic evaluations alongside clinical trials, and illustrate the approach using a numerical example. We compare the sample size requirement of the opportunity cost method with the ICER threshold method. In general, either method may yield the larger required sample size. However, the opportunity cost approach, although simple to use, has additional data requirements. We believe that the additional data requirements represent a small price to pay for being able to perform an analysis consistent with both concept of opportunity cost and the problem faced by decision makers. Copyright (c) 2007 John Wiley & Sons, Ltd.

Kidney function endpoints in kidney transplant trials: a struggle for power.

PubMed

Ibrahim, A; Garg, A X; Knoll, G A; Akbari, A; White, C A

2013-03-01

Kidney function endpoints are commonly used in randomized controlled trials (RCTs) in kidney transplantation (KTx). We conducted this study to estimate the proportion of ongoing RCTs with kidney function endpoints in KTx where the proposed sample size is large enough to detect meaningful differences in glomerular filtration rate (GFR) with adequate statistical power. RCTs were retrieved using the key word "kidney transplantation" from the National Institute of Health online clinical trial registry. Included trials had at least one measure of kidney function tracked for at least 1 month after transplant. We determined the proportion of two-arm parallel trials that had sufficient sample sizes to detect a minimum 5, 7.5 and 10 mL/min difference in GFR between arms. Fifty RCTs met inclusion criteria. Only 7% of the trials were above a sample size of 562, the number needed to detect a minimum 5 mL/min difference between the groups should one exist (assumptions: α = 0.05; power = 80%, 10% loss to follow-up, common standard deviation of 20 mL/min). The result increased modestly to 36% of trials when a minimum 10 mL/min difference was considered. Only a minority of ongoing trials have adequate statistical power to detect between-group differences in kidney function using conventional sample size estimating parameters. For this reason, some potentially effective interventions which ultimately could benefit patients may be abandoned from future assessment. © Copyright 2013 The American Society of Transplantation and the American Society of Transplant Surgeons.

Novel joint selection methods can reduce sample size for rheumatoid arthritis clinical trials with ultrasound endpoints.

PubMed

Allen, John C; Thumboo, Julian; Lye, Weng Kit; Conaghan, Philip G; Chew, Li-Ching; Tan, York Kiat

2018-03-01

To determine whether novel methods of selecting joints through (i) ultrasonography (individualized-ultrasound [IUS] method), or (ii) ultrasonography and clinical examination (individualized-composite-ultrasound [ICUS] method) translate into smaller rheumatoid arthritis (RA) clinical trial sample sizes when compared to existing methods utilizing predetermined joint sites for ultrasonography. Cohen's effect size (ES) was estimated (ES^) and a 95% CI (ES^L, ES^U) calculated on a mean change in 3-month total inflammatory score for each method. Corresponding 95% CIs [nL(ES^U), nU(ES^L)] were obtained on a post hoc sample size reflecting the uncertainty in ES^. Sample size calculations were based on a one-sample t-test as the patient numbers needed to provide 80% power at α = 0.05 to reject a null hypothesis H 0 : ES = 0 versus alternative hypotheses H 1 : ES = ES^, ES = ES^L and ES = ES^U. We aimed to provide point and interval estimates on projected sample sizes for future studies reflecting the uncertainty in our study ES^S. Twenty-four treated RA patients were followed up for 3 months. Utilizing the 12-joint approach and existing methods, the post hoc sample size (95% CI) was 22 (10-245). Corresponding sample sizes using ICUS and IUS were 11 (7-40) and 11 (6-38), respectively. Utilizing a seven-joint approach, the corresponding sample sizes using ICUS and IUS methods were nine (6-24) and 11 (6-35), respectively. Our pilot study suggests that sample size for RA clinical trials with ultrasound endpoints may be reduced using the novel methods, providing justification for larger studies to confirm these observations. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

Sample size determination for a three-arm equivalence trial of Poisson and negative binomial responses.

PubMed

Chang, Yu-Wei; Tsong, Yi; Zhao, Zhigen

2017-01-01

Assessing equivalence or similarity has drawn much attention recently as many drug products have lost or will lose their patents in the next few years, especially certain best-selling biologics. To claim equivalence between the test treatment and the reference treatment when assay sensitivity is well established from historical data, one has to demonstrate both superiority of the test treatment over placebo and equivalence between the test treatment and the reference treatment. Thus, there is urgency for practitioners to derive a practical way to calculate sample size for a three-arm equivalence trial. The primary endpoints of a clinical trial may not always be continuous, but may be discrete. In this paper, the authors derive power function and discuss sample size requirement for a three-arm equivalence trial with Poisson and negative binomial clinical endpoints. In addition, the authors examine the effect of the dispersion parameter on the power and the sample size by varying its coefficient from small to large. In extensive numerical studies, the authors demonstrate that required sample size heavily depends on the dispersion parameter. Therefore, misusing a Poisson model for negative binomial data may easily lose power up to 20%, depending on the value of the dispersion parameter.

Re-estimating sample size in cluster randomised trials with active recruitment within clusters.

PubMed

van Schie, S; Moerbeek, M

2014-08-30

Often only a limited number of clusters can be obtained in cluster randomised trials, although many potential participants can be recruited within each cluster. Thus, active recruitment is feasible within the clusters. To obtain an efficient sample size in a cluster randomised trial, the cluster level and individual level variance should be known before the study starts, but this is often not the case. We suggest using an internal pilot study design to address this problem of unknown variances. A pilot can be useful to re-estimate the variances and re-calculate the sample size during the trial. Using simulated data, it is shown that an initially low or high power can be adjusted using an internal pilot with the type I error rate remaining within an acceptable range. The intracluster correlation coefficient can be re-estimated with more precision, which has a positive effect on the sample size. We conclude that an internal pilot study design may be used if active recruitment is feasible within a limited number of clusters. Copyright © 2014 John Wiley & Sons, Ltd.

Phase II Trials for Heterogeneous Patient Populations with a Time-to-Event Endpoint.

PubMed

Jung, Sin-Ho

2017-07-01

In this paper, we consider a single-arm phase II trial with a time-to-event end-point. We assume that the study population has multiple subpopulations with different prognosis, but the study treatment is expected to be similarly efficacious across the subpopulations. We review a stratified one-sample log-rank test and present its sample size calculation method under some practical design settings. Our sample size method requires specification of the prevalence of subpopulations. We observe that the power of the resulting sample size is not very sensitive to misspecification of the prevalence.

Design of the value of imaging in enhancing the wellness of your heart (VIEW) trial and the impact of uncertainty on power.

PubMed

Ambrosius, Walter T; Polonsky, Tamar S; Greenland, Philip; Goff, David C; Perdue, Letitia H; Fortmann, Stephen P; Margolis, Karen L; Pajewski, Nicholas M

2012-04-01

Although observational evidence has suggested that the measurement of coronary artery calcium (CAC) may improve risk stratification for cardiovascular events and thus help guide the use of lipid-lowering therapy, this contention has not been evaluated within the context of a randomized trial. The Value of Imaging in Enhancing the Wellness of Your Heart (VIEW) trial is proposed as a randomized study in participants at low intermediate risk of future coronary heart disease (CHD) events to evaluate whether CAC testing leads to improved patient outcomes. To describe the challenges encountered in designing a prototypical screening trial and to examine the impact of uncertainty on power. The VIEW trial was designed as an effectiveness clinical trial to examine the benefit of CAC testing to guide therapy on a primary outcome consisting of a composite of nonfatal myocardial infarction, probable or definite angina with revascularization, resuscitated cardiac arrest, nonfatal stroke (not transient ischemic attack (TIA)), CHD death, stroke death, other atherosclerotic death, or other cardiovascular disease (CVD) death. Many critical choices were faced in designing the trial, including (1) the choice of primary outcome, (2) the choice of therapy, (3) the target population with corresponding ethical issues, (4) specifications of assumptions for sample size calculations, and (5) impact of uncertainty in these assumptions on power/sample size determination. We have proposed a sample size of 30,000 (800 events), which provides 92.7% power. Alternatively, sample sizes of 20,228 (539 events), 23,138 (617 events), and 27,078 (722 events) provide 80%, 85%, and 90% power. We have also allowed for uncertainty in our assumptions by computing average power integrated over specified prior distributions. This relaxation of specificity indicates a reduction in power, dropping to 89.9% (95% confidence interval (CI): 89.8-89.9) for a sample size of 30,000. Samples sizes of 20,228, 23,138, and 27,078 provide power of 78.0% (77.9-78.0), 82.5% (82.5-82.6), and 87.2% (87.2-87.3), respectively. These power estimates are dependent on form and parameters of the prior distributions. Despite the pressing need for a randomized trial to evaluate the utility of CAC testing, conduct of such a trial requires recruiting a large patient population, making efficiency of critical importance. The large sample size is primarily due to targeting a study population at relatively low risk of a CVD event. Our calculations also illustrate the importance of formally considering uncertainty in power calculations of large trials as standard power calculations may tend to overestimate power.

Design of the Value of Imaging in Enhancing the Wellness of Your Heart (VIEW) Trial and the Impact of Uncertainty on Power

PubMed Central

Ambrosius, Walter T.; Polonsky, Tamar S.; Greenland, Philip; Goff, David C.; Perdue, Letitia H.; Fortmann, Stephen P.; Margolis, Karen L.; Pajewski, Nicholas M.

2014-01-01

Background Although observational evidence has suggested that the measurement of CAC may improve risk stratification for cardiovascular events and thus help guide the use of lipid-lowering therapy, this contention has not been evaluated within the context of a randomized trial. The Value of Imaging in Enhancing the Wellness of Your Heart (VIEW) trial is proposed as a randomized study in participants at low intermediate risk of future coronary heart disease (CHD) events to evaluate whether coronary artery calcium (CAC) testing leads to improved patient outcomes. Purpose To describe the challenges encountered in designing a prototypical screening trial and to examine the impact of uncertainty on power. Methods The VIEW trial was designed as an effectiveness clinical trial to examine the benefit of CAC testing to guide therapy on a primary outcome consisting of a composite of non-fatal myocardial infarction, probable or definite angina with revascularization, resuscitated cardiac arrest, non-fatal stroke (not transient ischemic attack (TIA)), CHD death, stroke death, other atherosclerotic death, or other cardiovascular disease (CVD) death. Many critical choices were faced in designing the trial, including: (1) the choice of primary outcome, (2) the choice of therapy, (3) the target population with corresponding ethical issues, (4) specifications of assumptions for sample size calculations, and (5) impact of uncertainty in these assumptions on power/sample size determination. Results We have proposed a sample size of 30,000 (800 events) which provides 92.7% power. Alternatively, sample sizes of 20,228 (539 events), 23,138 (617 events) and 27,078 (722 events) provide 80, 85, and 90% power. We have also allowed for uncertainty in our assumptions by computing average power integrated over specified prior distributions. This relaxation of specificity indicates a reduction in power, dropping to 89.9% (95% confidence interval (CI): 89.8 to 89.9) for a sample size of 30,000. Samples sizes of 20,228, 23,138, and 27,078 provide power of 78.0% (77.9 to 78.0), 82.5% (82.5 to 82.6), and 87.2% (87.2 to 87.3), respectively. Limitations These power estimates are dependent on form and parameters of the prior distributions. Conclusions Despite the pressing need for a randomized trial to evaluate the utility of CAC testing, conduct of such a trial requires recruiting a large patient population, making efficiency of critical importance. The large sample size is primarily due to targeting a study population at relatively low risk of a CVD event. Our calculations also illustrate the importance of formally considering uncertainty in power calculations of large trials as standard power calculations may tend to overestimate power. PMID:22333998

Recruitment and retention of participants in randomised controlled trials: a review of trials funded and published by the United Kingdom Health Technology Assessment Programme.

PubMed

Walters, Stephen J; Bonacho Dos Anjos Henriques-Cadby, Inês; Bortolami, Oscar; Flight, Laura; Hind, Daniel; Jacques, Richard M; Knox, Christopher; Nadin, Ben; Rothwell, Joanne; Surtees, Michael; Julious, Steven A

2017-03-20

Substantial amounts of public funds are invested in health research worldwide. Publicly funded randomised controlled trials (RCTs) often recruit participants at a slower than anticipated rate. Many trials fail to reach their planned sample size within the envisaged trial timescale and trial funding envelope. To review the consent, recruitment and retention rates for single and multicentre randomised control trials funded and published by the UK's National Institute for Health Research (NIHR) Health Technology Assessment (HTA) Programme. HTA reports of individually randomised single or multicentre RCTs published from the start of 2004 to the end of April 2016 were reviewed. Information was extracted, relating to the trial characteristics, sample size, recruitment and retention by two independent reviewers. Target sample size and whether it was achieved; recruitment rates (number of participants recruited per centre per month) and retention rates (randomised participants retained and assessed with valid primary outcome data). This review identified 151 individually RCTs from 787 NIHR HTA reports. The final recruitment target sample size was achieved in 56% (85/151) of the RCTs and more than 80% of the final target sample size was achieved for 79% of the RCTs (119/151). The median recruitment rate (participants per centre per month) was found to be 0.92 (IQR 0.43-2.79) and the median retention rate (proportion of participants with valid primary outcome data at follow-up) was estimated at 89% (IQR 79-97%). There is considerable variation in the consent, recruitment and retention rates in publicly funded RCTs. Investigators should bear this in mind at the planning stage of their study and not be overly optimistic about their recruitment projections. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Recruitment and retention of participants in randomised controlled trials: a review of trials funded and published by the United Kingdom Health Technology Assessment Programme

PubMed Central

Bonacho dos Anjos Henriques-Cadby, Inês; Bortolami, Oscar; Flight, Laura; Hind, Daniel; Knox, Christopher; Nadin, Ben; Rothwell, Joanne; Surtees, Michael; Julious, Steven A

2017-01-01

Background Substantial amounts of public funds are invested in health research worldwide. Publicly funded randomised controlled trials (RCTs) often recruit participants at a slower than anticipated rate. Many trials fail to reach their planned sample size within the envisaged trial timescale and trial funding envelope. Objectives To review the consent, recruitment and retention rates for single and multicentre randomised control trials funded and published by the UK's National Institute for Health Research (NIHR) Health Technology Assessment (HTA) Programme. Data sources and study selection HTA reports of individually randomised single or multicentre RCTs published from the start of 2004 to the end of April 2016 were reviewed. Data extraction Information was extracted, relating to the trial characteristics, sample size, recruitment and retention by two independent reviewers. Main outcome measures Target sample size and whether it was achieved; recruitment rates (number of participants recruited per centre per month) and retention rates (randomised participants retained and assessed with valid primary outcome data). Results This review identified 151 individually RCTs from 787 NIHR HTA reports. The final recruitment target sample size was achieved in 56% (85/151) of the RCTs and more than 80% of the final target sample size was achieved for 79% of the RCTs (119/151). The median recruitment rate (participants per centre per month) was found to be 0.92 (IQR 0.43–2.79) and the median retention rate (proportion of participants with valid primary outcome data at follow-up) was estimated at 89% (IQR 79–97%). Conclusions There is considerable variation in the consent, recruitment and retention rates in publicly funded RCTs. Investigators should bear this in mind at the planning stage of their study and not be overly optimistic about their recruitment projections. PMID:28320800

Designing clinical trials to test disease-modifying agents: application to the treatment trials of Alzheimer's disease.

PubMed

Xiong, Chengjie; van Belle, Gerald; Miller, J Philip; Morris, John C

2011-02-01

Therapeutic trials of disease-modifying agents on Alzheimer's disease (AD) require novel designs and analyses involving switch of treatments for at least a portion of subjects enrolled. Randomized start and randomized withdrawal designs are two examples of such designs. Crucial design parameters such as sample size and the time of treatment switch are important to understand in designing such clinical trials. The purpose of this article is to provide methods to determine sample sizes and time of treatment switch as well as optimum statistical tests of treatment efficacy for clinical trials of disease-modifying agents on AD. A general linear mixed effects model is proposed to test the disease-modifying efficacy of novel therapeutic agents on AD. This model links the longitudinal growth from both the placebo arm and the treatment arm at the time of treatment switch for these in the delayed treatment arm or early withdrawal arm and incorporates the potential correlation on the rate of cognitive change before and after the treatment switch. Sample sizes and the optimum time for treatment switch of such trials as well as optimum test statistic for the treatment efficacy are determined according to the model. Assuming an evenly spaced longitudinal design over a fixed duration, the optimum treatment switching time in a randomized start or a randomized withdrawal trial is half way through the trial. With the optimum test statistic for the treatment efficacy and over a wide spectrum of model parameters, the optimum sample size allocations are fairly close to the simplest design with a sample size ratio of 1:1:1 among the treatment arm, the delayed treatment or early withdrawal arm, and the placebo arm. The application of the proposed methodology to AD provides evidence that much larger sample sizes are required to adequately power disease-modifying trials when compared with those for symptomatic agents, even when the treatment switch time and efficacy test are optimally chosen. The proposed method assumes that the only and immediate effect of treatment switch is on the rate of cognitive change. Crucial design parameters for the clinical trials of disease-modifying agents on AD can be optimally chosen. Government and industry officials as well as academia researchers should consider the optimum use of the clinical trials design for disease-modifying agents on AD in their effort to search for the treatments with the potential to modify the underlying pathophysiology of AD.

Valuing Trial Designs from a Pharmaceutical Perspective Using Value-Based Pricing.

PubMed

Breeze, Penny; Brennan, Alan

2015-11-01

Our aim was to adapt the traditional framework for expected net benefit of sampling (ENBS) to be more compatible with drug development trials from the pharmaceutical perspective. We modify the traditional framework for conducting ENBS and assume that the price of the drug is conditional on the trial outcomes. We use a value-based pricing (VBP) criterion to determine price conditional on trial data using Bayesian updating of cost-effectiveness (CE) model parameters. We assume that there is a threshold price below which the company would not market the new intervention. We present a case study in which a phase III trial sample size and trial duration are varied. For each trial design, we sampled 10,000 trial outcomes and estimated VBP using a CE model. The expected commercial net benefit is calculated as the expected profits minus the trial costs. A clinical trial with shorter follow-up, and larger sample size, generated the greatest expected commercial net benefit. Increasing the duration of follow-up had a modest impact on profit forecasts. Expected net benefit of sampling can be adapted to value clinical trials in the pharmaceutical industry to optimise the expected commercial net benefit. However, the analyses can be very time consuming for complex CE models. © 2014 The Authors. Health Economics published by John Wiley & Sons Ltd.

Are There Scenarios When the Use of Non-Placebo-Control Groups in Experimental Trial Designs Increase Expected Value to Society?

PubMed

Uyei, Jennifer; Braithwaite, R Scott

2016-01-01

Despite the benefits of the placebo-controlled trial design, it is limited by its inability to quantify total benefits and harms. Such trials, for example, are not designed to detect an intervention's placebo or nocebo effects, which if detected could alter the benefit-to-harm balance and change a decision to adopt or reject an intervention. In this article, we explore scenarios in which alternative experimental trial designs, which differ in the type of control used, influence expected value across a range of pretest assumptions and study sample sizes. We developed a decision model to compare 3 trial designs and their implications for decision making: 2-arm placebo-controlled trial ("placebo-control"), 2-arm intervention v. do nothing trial ("null-control"), and an innovative 3-arm trial design: intervention v. do nothing v. placebo trial ("novel design"). Four scenarios were explored regarding particular attributes of a hypothetical intervention: 1) all benefits and no harm, 2) no biological effect, 3) only biological effects, and 4) surreptitious harm (no biological benefit or nocebo effect). Scenario 1: When sample sizes were very small, the null-control was preferred, but as sample sizes increased, expected value of all 3 designs converged. Scenario 2: The null-control was preferred regardless of sample size when the ratio of placebo to nocebo effect was >1; otherwise, the placebo-control was preferred. Scenario 3: When sample size was very small, the placebo-control was preferred when benefits outweighed harms, but the novel design was preferred when harms outweighed benefits. Scenario 4: The placebo-control was preferred when harms outweighed placebo benefits; otherwise, preference went to the null-control. Scenarios are hypothetical, study designs have not been tested in a real-world setting, blinding is not possible in all designs, and some may argue the novel design poses ethical concerns. We identified scenarios in which alternative experimental study designs would confer greater expected value than the placebo-controlled trial design. The likelihood and prevalence of such situations warrant further study. © The Author(s) 2015.

Single-arm phase II trial design under parametric cure models.

PubMed

Wu, Jianrong

2015-01-01

The current practice of designing single-arm phase II survival trials is limited under the exponential model. Trial design under the exponential model may not be appropriate when a portion of patients are cured. There is no literature available for designing single-arm phase II trials under the parametric cure model. In this paper, a test statistic is proposed, and a sample size formula is derived for designing single-arm phase II trials under a class of parametric cure models. Extensive simulations showed that the proposed test and sample size formula perform very well under different scenarios. Copyright © 2015 John Wiley & Sons, Ltd.

Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.

PubMed

You, Zhiying; Williams, O Dale; Aban, Inmaculada; Kabagambe, Edmond Kato; Tiwari, Hemant K; Cutter, Gary

2011-02-01

The statistical power of cluster randomized trials depends on two sample size components, the number of clusters per group and the numbers of individuals within clusters (cluster size). Variable cluster sizes are common and this variation alone may have significant impact on study power. Previous approaches have taken this into account by either adjusting total sample size using a designated design effect or adjusting the number of clusters according to an assessment of the relative efficiency of unequal versus equal cluster sizes. This article defines a relative efficiency of unequal versus equal cluster sizes using noncentrality parameters, investigates properties of this measure, and proposes an approach for adjusting the required sample size accordingly. We focus on comparing two groups with normally distributed outcomes using t-test, and use the noncentrality parameter to define the relative efficiency of unequal versus equal cluster sizes and show that statistical power depends only on this parameter for a given number of clusters. We calculate the sample size required for an unequal cluster sizes trial to have the same power as one with equal cluster sizes. Relative efficiency based on the noncentrality parameter is straightforward to calculate and easy to interpret. It connects the required mean cluster size directly to the required sample size with equal cluster sizes. Consequently, our approach first determines the sample size requirements with equal cluster sizes for a pre-specified study power and then calculates the required mean cluster size while keeping the number of clusters unchanged. Our approach allows adjustment in mean cluster size alone or simultaneous adjustment in mean cluster size and number of clusters, and is a flexible alternative to and a useful complement to existing methods. Comparison indicated that we have defined a relative efficiency that is greater than the relative efficiency in the literature under some conditions. Our measure of relative efficiency might be less than the measure in the literature under some conditions, underestimating the relative efficiency. The relative efficiency of unequal versus equal cluster sizes defined using the noncentrality parameter suggests a sample size approach that is a flexible alternative and a useful complement to existing methods.

Methodological issues with adaptation of clinical trial design.

PubMed

Hung, H M James; Wang, Sue-Jane; O'Neill, Robert T

2006-01-01

Adaptation of clinical trial design generates many issues that have not been resolved for practical applications, though statistical methodology has advanced greatly. This paper focuses on some methodological issues. In one type of adaptation such as sample size re-estimation, only the postulated value of a parameter for planning the trial size may be altered. In another type, the originally intended hypothesis for testing may be modified using the internal data accumulated at an interim time of the trial, such as changing the primary endpoint and dropping a treatment arm. For sample size re-estimation, we make a contrast between an adaptive test weighting the two-stage test statistics with the statistical information given by the original design and the original sample mean test with a properly corrected critical value. We point out the difficulty in planning a confirmatory trial based on the crude information generated by exploratory trials. In regards to selecting a primary endpoint, we argue that the selection process that allows switching from one endpoint to the other with the internal data of the trial is not very likely to gain a power advantage over the simple process of selecting one from the two endpoints by testing them with an equal split of alpha (Bonferroni adjustment). For dropping a treatment arm, distributing the remaining sample size of the discontinued arm to other treatment arms can substantially improve the statistical power of identifying a superior treatment arm in the design. A common difficult methodological issue is that of how to select an adaptation rule in the trial planning stage. Pre-specification of the adaptation rule is important for the practicality consideration. Changing the originally intended hypothesis for testing with the internal data generates great concerns to clinical trial researchers.

Linear Combinations of Multiple Outcome Measures to Improve the Power of Efficacy Analysis ---Application to Clinical Trials on Early Stage Alzheimer Disease

PubMed Central

Xiong, Chengjie; Luo, Jingqin; Morris, John C; Bateman, Randall

2018-01-01

Modern clinical trials on Alzheimer disease (AD) focus on the early symptomatic stage or even the preclinical stage. Subtle disease progression at the early stages, however, poses a major challenge in designing such clinical trials. We propose a multivariate mixed model on repeated measures to model the disease progression over time on multiple efficacy outcomes, and derive the optimum weights to combine multiple outcome measures by minimizing the sample sizes to adequately power the clinical trials. A cross-validation simulation study is conducted to assess the accuracy for the estimated weights as well as the improvement in reducing the sample sizes for such trials. The proposed methodology is applied to the multiple cognitive tests from the ongoing observational study of the Dominantly Inherited Alzheimer Network (DIAN) to power future clinical trials in the DIAN with a cognitive endpoint. Our results show that the optimum weights to combine multiple outcome measures can be accurately estimated, and that compared to the individual outcomes, the combined efficacy outcome with these weights significantly reduces the sample size required to adequately power clinical trials. When applied to the clinical trial in the DIAN, the estimated linear combination of six cognitive tests can adequately power the clinical trial. PMID:29546251

A novel sample size formula for the weighted log-rank test under the proportional hazards cure model.

PubMed

Xiong, Xiaoping; Wu, Jianrong

2017-01-01

The treatment of cancer has progressed dramatically in recent decades, such that it is no longer uncommon to see a cure or log-term survival in a significant proportion of patients with various types of cancer. To adequately account for the cure fraction when designing clinical trials, the cure models should be used. In this article, a sample size formula for the weighted log-rank test is derived under the fixed alternative hypothesis for the proportional hazards cure models. Simulation showed that the proposed sample size formula provides an accurate estimation of sample size for designing clinical trials under the proportional hazards cure models. Copyright © 2016 John Wiley & Sons, Ltd.

The Long-Term Oxygen Treatment Trial for Chronic Obstructive Pulmonary Disease: Rationale, Design, and Lessons Learned.

PubMed

Yusen, Roger D; Criner, Gerard J; Sternberg, Alice L; Au, David H; Fuhlbrigge, Anne L; Albert, Richard K; Casaburi, Richard; Stoller, James K; Harrington, Kathleen F; Cooper, J Allen D; Diaz, Philip; Gay, Steven; Kanner, Richard; MacIntyre, Neil; Martinez, Fernando J; Piantadosi, Steven; Sciurba, Frank; Shade, David; Stibolt, Thomas; Tonascia, James; Wise, Robert; Bailey, William C

2018-01-01

The Long-Term Oxygen Treatment Trial demonstrated that long-term supplemental oxygen did not reduce time to hospital admission or death for patients who have stable chronic obstructive pulmonary disease and resting and/or exercise-induced moderate oxyhemoglobin desaturation, nor did it provide benefit for any other outcome measured in the trial. Nine months after initiation of patient screening, after randomization of 34 patients to treatment, a trial design amendment broadened the eligible population, expanded the primary outcome, and reduced the goal sample size. Within a few years, the protocol underwent minor modifications, and a second trial design amendment lowered the required sample size because of lower than expected treatment group crossover rates. After 5.5 years of recruitment, the trial met its amended sample size goal, and 1 year later, it achieved its follow-up goal. The process of publishing the trial results brought renewed scrutiny of the study design and the amendments. This article expands on the previously published design and methods information, provides the rationale for the amendments, and gives insight into the investigators' decisions about trial conduct. The story of the Long-Term Oxygen Treatment Trial may assist investigators in future trials, especially those that seek to assess the efficacy and safety of long-term oxygen therapy. Clinical trial registered with clinicaltrials.gov (NCT00692198).

Using simulation to aid trial design: Ring-vaccination trials.

PubMed

Hitchings, Matt David Thomas; Grais, Rebecca Freeman; Lipsitch, Marc

2017-03-01

The 2014-6 West African Ebola epidemic highlights the need for rigorous, rapid clinical trial methods for vaccines. A challenge for trial design is making sample size calculations based on incidence within the trial, total vaccine effect, and intracluster correlation, when these parameters are uncertain in the presence of indirect effects of vaccination. We present a stochastic, compartmental model for a ring vaccination trial. After identification of an index case, a ring of contacts is recruited and either vaccinated immediately or after 21 days. The primary outcome of the trial is total vaccine effect, counting cases only from a pre-specified window in which the immediate arm is assumed to be fully protected and the delayed arm is not protected. Simulation results are used to calculate necessary sample size and estimated vaccine effect. Under baseline assumptions about vaccine properties, monthly incidence in unvaccinated rings and trial design, a standard sample-size calculation neglecting dynamic effects estimated that 7,100 participants would be needed to achieve 80% power to detect a difference in attack rate between arms, while incorporating dynamic considerations in the model increased the estimate to 8,900. This approach replaces assumptions about parameters at the ring level with assumptions about disease dynamics and vaccine characteristics at the individual level, so within this framework we were able to describe the sensitivity of the trial power and estimated effect to various parameters. We found that both of these quantities are sensitive to properties of the vaccine, to setting-specific parameters over which investigators have little control, and to parameters that are determined by the study design. Incorporating simulation into the trial design process can improve robustness of sample size calculations. For this specific trial design, vaccine effectiveness depends on properties of the ring vaccination design and on the measurement window, as well as the epidemiologic setting.

Cost-efficient designs for three-arm trials with treatment delivered by health professionals: Sample sizes for a combination of nested and crossed designs

PubMed Central

Moerbeek, Mirjam

2018-01-01

Background This article studies the design of trials that compare three treatment conditions that are delivered by two types of health professionals. The one type of health professional delivers one treatment, and the other type delivers two treatments, hence, this design is a combination of a nested and crossed design. As each health professional treats multiple patients, the data have a nested structure. This nested structure has thus far been ignored in the design of such trials, which may result in an underestimate of the required sample size. In the design stage, the sample sizes should be determined such that a desired power is achieved for each of the three pairwise comparisons, while keeping costs or sample size at a minimum. Methods The statistical model that relates outcome to treatment condition and explicitly takes the nested data structure into account is presented. Mathematical expressions that relate sample size to power are derived for each of the three pairwise comparisons on the basis of this model. The cost-efficient design achieves sufficient power for each pairwise comparison at lowest costs. Alternatively, one may minimize the total number of patients. The sample sizes are found numerically and an Internet application is available for this purpose. The design is also compared to a nested design in which each health professional delivers just one treatment. Results Mathematical expressions show that this design is more efficient than the nested design. For each pairwise comparison, power increases with the number of health professionals and the number of patients per health professional. The methodology of finding a cost-efficient design is illustrated using a trial that compares treatments for social phobia. The optimal sample sizes reflect the costs for training and supervising psychologists and psychiatrists, and the patient-level costs in the three treatment conditions. Conclusion This article provides the methodology for designing trials that compare three treatment conditions while taking the nesting of patients within health professionals into account. As such, it helps to avoid underpowered trials. To use the methodology, a priori estimates of the total outcome variances and intraclass correlation coefficients must be obtained from experts’ opinions or findings in the literature. PMID:29316807

An audit strategy for time-to-event outcomes measured with error: application to five randomized controlled trials in oncology.

PubMed

Dodd, Lori E; Korn, Edward L; Freidlin, Boris; Gu, Wenjuan; Abrams, Jeffrey S; Bushnell, William D; Canetta, Renzo; Doroshow, James H; Gray, Robert J; Sridhara, Rajeshwari

2013-10-01

Measurement error in time-to-event end points complicates interpretation of treatment effects in clinical trials. Non-differential measurement error is unlikely to produce large bias [1]. When error depends on treatment arm, bias is of greater concern. Blinded-independent central review (BICR) of all images from a trial is commonly undertaken to mitigate differential measurement-error bias that may be present in hazard ratios (HRs) based on local evaluations. Similar BICR and local evaluation HRs may provide reassurance about the treatment effect, but BICR adds considerable time and expense to trials. We describe a BICR audit strategy [2] and apply it to five randomized controlled trials to evaluate its use and to provide practical guidelines. The strategy requires BICR on a subset of study subjects, rather than a complete-case BICR, and makes use of an auxiliary-variable estimator. When the effect size is relatively large, the method provides a substantial reduction in the size of the BICRs. In a trial with 722 participants and a HR of 0.48, an average audit of 28% of the data was needed and always confirmed the treatment effect as assessed by local evaluations. More moderate effect sizes and/or smaller trial sizes required larger proportions of audited images, ranging from 57% to 100% for HRs ranging from 0.55 to 0.77 and sample sizes between 209 and 737. The method is developed for a simple random sample of study subjects. In studies with low event rates, more efficient estimation may result from sampling individuals with events at a higher rate. The proposed strategy can greatly decrease the costs and time associated with BICR, by reducing the number of images undergoing review. The savings will depend on the underlying treatment effect and trial size, with larger treatment effects and larger trials requiring smaller proportions of audited data.

Understanding the cluster randomised crossover design: a graphical illustraton of the components of variation and a sample size tutorial.

PubMed

Arnup, Sarah J; McKenzie, Joanne E; Hemming, Karla; Pilcher, David; Forbes, Andrew B

2017-08-15

In a cluster randomised crossover (CRXO) design, a sequence of interventions is assigned to a group, or 'cluster' of individuals. Each cluster receives each intervention in a separate period of time, forming 'cluster-periods'. Sample size calculations for CRXO trials need to account for both the cluster randomisation and crossover aspects of the design. Formulae are available for the two-period, two-intervention, cross-sectional CRXO design, however implementation of these formulae is known to be suboptimal. The aims of this tutorial are to illustrate the intuition behind the design; and provide guidance on performing sample size calculations. Graphical illustrations are used to describe the effect of the cluster randomisation and crossover aspects of the design on the correlation between individual responses in a CRXO trial. Sample size calculations for binary and continuous outcomes are illustrated using parameters estimated from the Australia and New Zealand Intensive Care Society - Adult Patient Database (ANZICS-APD) for patient mortality and length(s) of stay (LOS). The similarity between individual responses in a CRXO trial can be understood in terms of three components of variation: variation in cluster mean response; variation in the cluster-period mean response; and variation between individual responses within a cluster-period; or equivalently in terms of the correlation between individual responses in the same cluster-period (within-cluster within-period correlation, WPC), and between individual responses in the same cluster, but in different periods (within-cluster between-period correlation, BPC). The BPC lies between zero and the WPC. When the WPC and BPC are equal the precision gained by crossover aspect of the CRXO design equals the precision lost by cluster randomisation. When the BPC is zero there is no advantage in a CRXO over a parallel-group cluster randomised trial. Sample size calculations illustrate that small changes in the specification of the WPC or BPC can increase the required number of clusters. By illustrating how the parameters required for sample size calculations arise from the CRXO design and by providing guidance on both how to choose values for the parameters and perform the sample size calculations, the implementation of the sample size formulae for CRXO trials may improve.

Strategies for informed sample size reduction in adaptive controlled clinical trials

NASA Astrophysics Data System (ADS)

Arandjelović, Ognjen

2017-12-01

Clinical trial adaptation refers to any adjustment of the trial protocol after the onset of the trial. The main goal is to make the process of introducing new medical interventions to patients more efficient. The principal challenge, which is an outstanding research problem, is to be found in the question of how adaptation should be performed so as to minimize the chance of distorting the outcome of the trial. In this paper, we propose a novel method for achieving this. Unlike most of the previously published work, our approach focuses on trial adaptation by sample size adjustment, i.e. by reducing the number of trial participants in a statistically informed manner. Our key idea is to select the sample subset for removal in a manner which minimizes the associated loss of information. We formalize this notion and describe three algorithms which approach the problem in different ways, respectively, using (i) repeated random draws, (ii) a genetic algorithm, and (iii) what we term pair-wise sample compatibilities. Experiments on simulated data demonstrate the effectiveness of all three approaches, with a consistently superior performance exhibited by the pair-wise sample compatibilities-based method.

Estimation After a Group Sequential Trial.

PubMed

Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Kenward, Michael G; Tsiatis, Anastasios A; Davidian, Marie; Verbeke, Geert

2015-10-01

Group sequential trials are one important instance of studies for which the sample size is not fixed a priori but rather takes one of a finite set of pre-specified values, dependent on the observed data. Much work has been devoted to the inferential consequences of this design feature. Molenberghs et al (2012) and Milanzi et al (2012) reviewed and extended the existing literature, focusing on a collection of seemingly disparate, but related, settings, namely completely random sample sizes, group sequential studies with deterministic and random stopping rules, incomplete data, and random cluster sizes. They showed that the ordinary sample average is a viable option for estimation following a group sequential trial, for a wide class of stopping rules and for random outcomes with a distribution in the exponential family. Their results are somewhat surprising in the sense that the sample average is not optimal, and further, there does not exist an optimal, or even, unbiased linear estimator. However, the sample average is asymptotically unbiased, both conditionally upon the observed sample size as well as marginalized over it. By exploiting ignorability they showed that the sample average is the conventional maximum likelihood estimator. They also showed that a conditional maximum likelihood estimator is finite sample unbiased, but is less efficient than the sample average and has the larger mean squared error. Asymptotically, the sample average and the conditional maximum likelihood estimator are equivalent. This previous work is restricted, however, to the situation in which the the random sample size can take only two values, N = n or N = 2 n . In this paper, we consider the more practically useful setting of sample sizes in a the finite set { n 1 , n 2 , …, n L }. It is shown that the sample average is then a justifiable estimator , in the sense that it follows from joint likelihood estimation, and it is consistent and asymptotically unbiased. We also show why simulations can give the false impression of bias in the sample average when considered conditional upon the sample size. The consequence is that no corrections need to be made to estimators following sequential trials. When small-sample bias is of concern, the conditional likelihood estimator provides a relatively straightforward modification to the sample average. Finally, it is shown that classical likelihood-based standard errors and confidence intervals can be applied, obviating the need for technical corrections.

Using meta-analysis to inform the design of subsequent studies of diagnostic test accuracy.

PubMed

Hinchliffe, Sally R; Crowther, Michael J; Phillips, Robert S; Sutton, Alex J

2013-06-01

An individual diagnostic accuracy study rarely provides enough information to make conclusive recommendations about the accuracy of a diagnostic test; particularly when the study is small. Meta-analysis methods provide a way of combining information from multiple studies, reducing uncertainty in the result and hopefully providing substantial evidence to underpin reliable clinical decision-making. Very few investigators consider any sample size calculations when designing a new diagnostic accuracy study. However, it is important to consider the number of subjects in a new study in order to achieve a precise measure of accuracy. Sutton et al. have suggested previously that when designing a new therapeutic trial, it could be more beneficial to consider the power of the updated meta-analysis including the new trial rather than of the new trial itself. The methodology involves simulating new studies for a range of sample sizes and estimating the power of the updated meta-analysis with each new study added. Plotting the power values against the range of sample sizes allows the clinician to make an informed decision about the sample size of a new trial. This paper extends this approach from the trial setting and applies it to diagnostic accuracy studies. Several meta-analytic models are considered including bivariate random effects meta-analysis that models the correlation between sensitivity and specificity. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Sample size calculations for randomized clinical trials published in anesthesiology journals: a comparison of 2010 versus 2016.

PubMed

Chow, Jeffrey T Y; Turkstra, Timothy P; Yim, Edmund; Jones, Philip M

2018-06-01

Although every randomized clinical trial (RCT) needs participants, determining the ideal number of participants that balances limited resources and the ability to detect a real effect is difficult. Focussing on two-arm, parallel group, superiority RCTs published in six general anesthesiology journals, the objective of this study was to compare the quality of sample size calculations for RCTs published in 2010 vs 2016. Each RCT's full text was searched for the presence of a sample size calculation, and the assumptions made by the investigators were compared with the actual values observed in the results. Analyses were only performed for sample size calculations that were amenable to replication, defined as using a clearly identified outcome that was continuous or binary in a standard sample size calculation procedure. The percentage of RCTs reporting all sample size calculation assumptions increased from 51% in 2010 to 84% in 2016. The difference between the values observed in the study and the expected values used for the sample size calculation for most RCTs was usually > 10% of the expected value, with negligible improvement from 2010 to 2016. While the reporting of sample size calculations improved from 2010 to 2016, the expected values in these sample size calculations often assumed effect sizes larger than those actually observed in the study. Since overly optimistic assumptions may systematically lead to underpowered RCTs, improvements in how to calculate and report sample sizes in anesthesiology research are needed.

Operationalizing hippocampal volume as an enrichment biomarker for amnestic MCI trials: effect of algorithm, test-retest variability and cut-point on trial cost, duration and sample size

PubMed Central

Yu, P.; Sun, J.; Wolz, R.; Stephenson, D.; Brewer, J.; Fox, N.C.; Cole, P.E.; Jack, C.R.; Hill, D.L.G.; Schwarz, A.J.

2014-01-01

Objective To evaluate the effect of computational algorithm, measurement variability and cut-point on hippocampal volume (HCV)-based patient selection for clinical trials in mild cognitive impairment (MCI). Methods We used normal control and amnestic MCI subjects from ADNI-1 as normative reference and screening cohorts. We evaluated the enrichment performance of four widely-used hippocampal segmentation algorithms (FreeSurfer, HMAPS, LEAP and NeuroQuant) in terms of two-year changes in MMSE, ADAS-Cog and CDR-SB. We modeled the effect of algorithm, test-retest variability and cut-point on sample size, screen fail rates and trial cost and duration. Results HCV-based patient selection yielded not only reduced sample sizes (by ~40–60%) but also lower trial costs (by ~30–40%) across a wide range of cut-points. Overall, the dependence on the cut-point value was similar for the three clinical instruments considered. Conclusion These results provide a guide to the choice of HCV cut-point for aMCI clinical trials, allowing an informed trade-off between statistical and practical considerations. PMID:24211008

Blinded and unblinded internal pilot study designs for clinical trials with count data.

PubMed

Schneider, Simon; Schmidli, Heinz; Friede, Tim

2013-07-01

Internal pilot studies are a popular design feature to address uncertainties in the sample size calculations caused by vague information on nuisance parameters. Despite their popularity, only very recently blinded sample size reestimation procedures for trials with count data were proposed and their properties systematically investigated. Although blinded procedures are favored by regulatory authorities, practical application is somewhat limited by fears that blinded procedures are prone to bias if the treatment effect was misspecified in the planning. Here, we compare unblinded and blinded procedures with respect to bias, error rates, and sample size distribution. We find that both procedures maintain the desired power and that the unblinded procedure is slightly liberal whereas the actual significance level of the blinded procedure is close to the nominal level. Furthermore, we show that in situations where uncertainty about the assumed treatment effect exists, the blinded estimator of the control event rate is biased in contrast to the unblinded estimator, which results in differences in mean sample sizes in favor of the unblinded procedure. However, these differences are rather small compared to the deviations of the mean sample sizes from the sample size required to detect the true, but unknown effect. We demonstrate that the variation of the sample size resulting from the blinded procedure is in many practically relevant situations considerably smaller than the one of the unblinded procedures. The methods are extended to overdispersed counts using a quasi-likelihood approach and are illustrated by trials in relapsing multiple sclerosis. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

From Planning to Implementation: An Examination of Changes in the Research Design, Sample Size, and Precision of Group Randomized Trials Launched by the Institute of Education Sciences

ERIC Educational Resources Information Center

Spybrook, Jessaca; Puente, Anne Cullen; Lininger, Monica

2013-01-01

This article examines changes in the research design, sample size, and precision between the planning phase and implementation phase of group randomized trials (GRTs) funded by the Institute of Education Sciences. Thirty-eight GRTs funded between 2002 and 2006 were examined. Three studies revealed changes in the experimental design. Ten studies…

An internal pilot study for a randomized trial aimed at evaluating the effectiveness of iron interventions in children with non-anemic iron deficiency: the OptEC trial.

PubMed

Abdullah, Kawsari; Thorpe, Kevin E; Mamak, Eva; Maguire, Jonathon L; Birken, Catherine S; Fehlings, Darcy; Hanley, Anthony J; Macarthur, Colin; Zlotkin, Stanley H; Parkin, Patricia C

2015-07-14

The OptEC trial aims to evaluate the effectiveness of oral iron in young children with non-anemic iron deficiency (NAID). The initial sample size calculated for the OptEC trial ranged from 112-198 subjects. Given the uncertainty regarding the parameters used to calculate the sample, an internal pilot study was conducted. The objectives of this internal pilot study were to obtain reliable estimate of parameters (standard deviation and design factor) to recalculate the sample size and to assess the adherence rate and reasons for non-adherence in children enrolled in the pilot study. The first 30 subjects enrolled into the OptEC trial constituted the internal pilot study. The primary outcome of the OptEC trial is the Early Learning Composite (ELC). For estimation of the SD of the ELC, descriptive statistics of the 4 month follow-up ELC scores were assessed within each intervention group. The observed SD within each group was then pooled to obtain an estimated SD (S2) of the ELC. Correlation (ρ) between the ELC measured at baseline and follow-up was assessed. Recalculation of the sample size was performed using analysis of covariance (ANCOVA) method which uses the design factor (1- ρ(2)). Adherence rate was calculated using a parent reported rate of missed doses of the study intervention. The new estimate of the SD of the ELC was found to be 17.40 (S2). The design factor was (1- ρ2) = 0.21. Using a significance level of 5%, power of 80%, S2 = 17.40 and effect estimate (Δ) ranging from 6-8 points, the new sample size based on ANCOVA method ranged from 32-56 subjects (16-28 per group). Adherence ranged between 14% and 100% with 44% of the children having an adherence rate ≥ 86%. Information generated from our internal pilot study was used to update the design of the full and definitive trial, including recalculation of sample size, determination of the adequacy of adherence, and application of strategies to improve adherence. ClinicalTrials.gov Identifier: NCT01481766 (date of registration: November 22, 2011).

Evaluation of statistical designs in phase I expansion cohorts: the Dana-Farber/Harvard Cancer Center experience.

PubMed

Dahlberg, Suzanne E; Shapiro, Geoffrey I; Clark, Jeffrey W; Johnson, Bruce E

2014-07-01

Phase I trials have traditionally been designed to assess toxicity and establish phase II doses with dose-finding studies and expansion cohorts but are frequently exceeding the traditional sample size to further assess endpoints in specific patient subsets. The scientific objectives of phase I expansion cohorts and their evolving role in the current era of targeted therapies have yet to be systematically examined. Adult therapeutic phase I trials opened within Dana-Farber/Harvard Cancer Center (DF/HCC) from 1988 to 2012 were identified for sample size details. Statistical designs and study objectives of those submitted in 2011 were reviewed for expansion cohort details. Five hundred twenty-two adult therapeutic phase I trials were identified during the 25 years. The average sample size of a phase I study has increased from 33.8 patients to 73.1 patients over that time. The proportion of trials with planned enrollment of 50 or fewer patients dropped from 93.0% during the time period 1988 to 1992 to 46.0% between 2008 and 2012; at the same time, the proportion of trials enrolling 51 to 100 patients and more than 100 patients increased from 5.3% and 1.8%, respectively, to 40.5% and 13.5% (χ(2) test, two-sided P < .001). Sixteen of the 60 trials (26.7%) in 2011 enrolled patients to three or more sub-cohorts in the expansion phase. Sixty percent of studies provided no statistical justification of the sample size, although 91.7% of trials stated response as an objective. Our data suggest that phase I studies have dramatically changed in size and scientific scope within the last decade. Additional studies addressing the implications of this trend on research processes, ethical concerns, and resource burden are needed. © The Author 2014. Published by Oxford University Press. All rights reserved.

Sample size calculations for stepped wedge and cluster randomised trials: a unified approach

PubMed Central

Hemming, Karla; Taljaard, Monica

2016-01-01

Objectives To clarify and illustrate sample size calculations for the cross-sectional stepped wedge cluster randomized trial (SW-CRT) and to present a simple approach for comparing the efficiencies of competing designs within a unified framework. Study Design and Setting We summarize design effects for the SW-CRT, the parallel cluster randomized trial (CRT), and the parallel cluster randomized trial with before and after observations (CRT-BA), assuming cross-sectional samples are selected over time. We present new formulas that enable trialists to determine the required cluster size for a given number of clusters. We illustrate by example how to implement the presented design effects and give practical guidance on the design of stepped wedge studies. Results For a fixed total cluster size, the choice of study design that provides the greatest power depends on the intracluster correlation coefficient (ICC) and the cluster size. When the ICC is small, the CRT tends to be more efficient; when the ICC is large, the SW-CRT tends to be more efficient and can serve as an alternative design when the CRT is an infeasible design. Conclusion Our unified approach allows trialists to easily compare the efficiencies of three competing designs to inform the decision about the most efficient design in a given scenario. PMID:26344808

Sample size calculation in cost-effectiveness cluster randomized trials: optimal and maximin approaches.

PubMed

Manju, Md Abu; Candel, Math J J M; Berger, Martijn P F

2014-07-10

In this paper, the optimal sample sizes at the cluster and person levels for each of two treatment arms are obtained for cluster randomized trials where the cost-effectiveness of treatments on a continuous scale is studied. The optimal sample sizes maximize the efficiency or power for a given budget or minimize the budget for a given efficiency or power. Optimal sample sizes require information on the intra-cluster correlations (ICCs) for effects and costs, the correlations between costs and effects at individual and cluster levels, the ratio of the variance of effects translated into costs to the variance of the costs (the variance ratio), sampling and measuring costs, and the budget. When planning, a study information on the model parameters usually is not available. To overcome this local optimality problem, the current paper also presents maximin sample sizes. The maximin sample sizes turn out to be rather robust against misspecifying the correlation between costs and effects at the cluster and individual levels but may lose much efficiency when misspecifying the variance ratio. The robustness of the maximin sample sizes against misspecifying the ICCs depends on the variance ratio. The maximin sample sizes are robust under misspecification of the ICC for costs for realistic values of the variance ratio greater than one but not robust under misspecification of the ICC for effects. Finally, we show how to calculate optimal or maximin sample sizes that yield sufficient power for a test on the cost-effectiveness of an intervention.

Clinical decision making and the expected value of information.

PubMed

Willan, Andrew R

2007-01-01

The results of the HOPE study, a randomized clinical trial, provide strong evidence that 1) ramipril prevents the composite outcome of cardiovascular death, myocardial infarction or stroke in patients who are at high risk of a cardiovascular event and 2) ramipril is cost-effective at a threshold willingness-to-pay of $10,000 to prevent an event of the composite outcome. In this report the concept of the expected value of information is used to determine if the information provided by the HOPE study is sufficient for decision making in the US and Canada. and results Using the cost-effectiveness data from a clinical trial, or from a meta-analysis of several trials, one can determine, based on the number of future patients that would benefit from the health technology under investigation, the expected value of sample information (EVSI) of a future trial as a function of proposed sample size. If the EVSI exceeds the cost for any particular sample size then the current information is insufficient for decision making and a future trial is indicated. If, on the other hand, there is no sample size for which the EVSI exceeds the cost, then there is sufficient information for decision making and no future trial is required. Using the data from the HOPE study these concepts are applied for various assumptions regarding the fixed and variable cost of a future trial and the number of patients who would benefit from ramipril. Expected value of information methods provide a decision-analytic alternative to the standard likelihood methods for assessing the evidence provided by cost-effectiveness data from randomized clinical trials.

Embedding clinical interventions into observational studies

PubMed Central

Newman, Anne B.; Avilés-Santa, M. Larissa; Anderson, Garnet; Heiss, Gerardo; Howard, Wm. James; Krucoff, Mitchell; Kuller, Lewis H.; Lewis, Cora E.; Robinson, Jennifer G.; Taylor, Herman; Treviño, Roberto P.; Weintraub, William

2017-01-01

Novel approaches to observational studies and clinical trials could improve the cost-effectiveness and speed of translation of research. Hybrid designs that combine elements of clinical trials with observational registries or cohort studies should be considered as part of a long-term strategy to transform clinical trials and epidemiology, adapting to the opportunities of big data and the challenges of constrained budgets. Important considerations include study aims, timing, breadth and depth of the existing infrastructure that can be leveraged, participant burden, likely participation rate and available sample size in the cohort, required sample size for the trial, and investigator expertise. Community engagement and stakeholder (including study participants) support are essential for these efforts to succeed. PMID:26611435

Sample size allocation in multiregional equivalence studies.

PubMed

Liao, Jason J Z; Yu, Ziji; Li, Yulan

2018-06-17

With the increasing globalization of drug development, the multiregional clinical trial (MRCT) has gained extensive use. The data from MRCTs could be accepted by regulatory authorities across regions and countries as the primary sources of evidence to support global marketing drug approval simultaneously. The MRCT can speed up patient enrollment and drug approval, and it makes the effective therapies available to patients all over the world simultaneously. However, there are many challenges both operationally and scientifically in conducting a drug development globally. One of many important questions to answer for the design of a multiregional study is how to partition sample size into each individual region. In this paper, two systematic approaches are proposed for the sample size allocation in a multiregional equivalence trial. A numerical evaluation and a biosimilar trial are used to illustrate the characteristics of the proposed approaches. Copyright © 2018 John Wiley & Sons, Ltd.

How conservative is Fisher's exact test? A quantitative evaluation of the two-sample comparative binomial trial.

PubMed

Crans, Gerald G; Shuster, Jonathan J

2008-08-15

The debate as to which statistical methodology is most appropriate for the analysis of the two-sample comparative binomial trial has persisted for decades. Practitioners who favor the conditional methods of Fisher, Fisher's exact test (FET), claim that only experimental outcomes containing the same amount of information should be considered when performing analyses. Hence, the total number of successes should be fixed at its observed level in hypothetical repetitions of the experiment. Using conditional methods in clinical settings can pose interpretation difficulties, since results are derived using conditional sample spaces rather than the set of all possible outcomes. Perhaps more importantly from a clinical trial design perspective, this test can be too conservative, resulting in greater resource requirements and more subjects exposed to an experimental treatment. The actual significance level attained by FET (the size of the test) has not been reported in the statistical literature. Berger (J. R. Statist. Soc. D (The Statistician) 2001; 50:79-85) proposed assessing the conservativeness of conditional methods using p-value confidence intervals. In this paper we develop a numerical algorithm that calculates the size of FET for sample sizes, n, up to 125 per group at the two-sided significance level, alpha = 0.05. Additionally, this numerical method is used to define new significance levels alpha(*) = alpha+epsilon, where epsilon is a small positive number, for each n, such that the size of the test is as close as possible to the pre-specified alpha (0.05 for the current work) without exceeding it. Lastly, a sample size and power calculation example are presented, which demonstrates the statistical advantages of implementing the adjustment to FET (using alpha(*) instead of alpha) in the two-sample comparative binomial trial. 2008 John Wiley & Sons, Ltd

Practical characteristics of adaptive design in phase 2 and 3 clinical trials.

PubMed

Sato, A; Shimura, M; Gosho, M

2018-04-01

Adaptive design methods are expected to be ethical, reflect real medical practice, increase the likelihood of research and development success and reduce the allocation of patients into ineffective treatment groups by the early termination of clinical trials. However, the comprehensive details regarding which types of clinical trials will include adaptive designs remain unclear. We examined the practical characteristics of adaptive design used in clinical trials. We conducted a literature search of adaptive design clinical trials published from 2012 to 2015 using PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials, with common search terms related to adaptive design. We systematically assessed the types and characteristics of adaptive designs and disease areas employed in the adaptive design trials. Our survey identified 245 adaptive design clinical trials. The number of trials by the publication year increased from 2012 to 2013 and did not greatly change afterwards. The most frequently used adaptive design was group sequential design (n = 222, 90.6%), especially for neoplasm or cardiovascular disease trials. Among the other types of adaptive design, adaptive dose/treatment group selection (n = 21, 8.6%) and adaptive sample-size adjustment (n = 19, 7.8%) were frequently used. The adaptive randomization (n = 8, 3.3%) and adaptive seamless design (n = 6, 2.4%) were less frequent. Adaptive dose/treatment group selection and adaptive sample-size adjustment were frequently used (up to 23%) in "certain infectious and parasitic diseases," "diseases of nervous system," and "mental and behavioural disorders" in comparison with "neoplasms" (<6.6%). For "mental and behavioural disorders," adaptive randomization was used in two trials of eight trials in total (25%). Group sequential design and adaptive sample-size adjustment were used frequently in phase 3 trials or in trials where study phase was not specified, whereas the other types of adaptive designs were used more in phase 2 trials. Approximately 82% (202 of 245 trials) resulted in early termination at the interim analysis. Among the 202 trials, 132 (54% of 245 trials) had fewer randomized patients than initially planned. This result supports the motive to use adaptive design to make study durations shorter and include a smaller number of subjects. We found that adaptive designs have been applied to clinical trials in various therapeutic areas and interventions. The applications were frequently reported in neoplasm or cardiovascular clinical trials. The adaptive dose/treatment group selection and sample-size adjustment are increasingly common, and these adaptations generally follow the Food and Drug Administration's (FDA's) recommendations. © 2017 John Wiley & Sons Ltd.

ENHANCEMENT OF LEARNING ON SAMPLE SIZE CALCULATION WITH A SMARTPHONE APPLICATION: A CLUSTER-RANDOMIZED CONTROLLED TRIAL.

PubMed

Ngamjarus, Chetta; Chongsuvivatwong, Virasakdi; McNeil, Edward; Holling, Heinz

2017-01-01

Sample size determination usually is taught based on theory and is difficult to understand. Using a smartphone application to teach sample size calculation ought to be more attractive to students than using lectures only. This study compared levels of understanding of sample size calculations for research studies between participants attending a lecture only versus lecture combined with using a smartphone application to calculate sample sizes, to explore factors affecting level of post-test score after training sample size calculation, and to investigate participants’ attitude toward a sample size application. A cluster-randomized controlled trial involving a number of health institutes in Thailand was carried out from October 2014 to March 2015. A total of 673 professional participants were enrolled and randomly allocated to one of two groups, namely, 341 participants in 10 workshops to control group and 332 participants in 9 workshops to intervention group. Lectures on sample size calculation were given in the control group, while lectures using a smartphone application were supplied to the test group. Participants in the intervention group had better learning of sample size calculation (2.7 points out of maximnum 10 points, 95% CI: 24 - 2.9) than the participants in the control group (1.6 points, 95% CI: 1.4 - 1.8). Participants doing research projects had a higher post-test score than those who did not have a plan to conduct research projects (0.9 point, 95% CI: 0.5 - 1.4). The majority of the participants had a positive attitude towards the use of smartphone application for learning sample size calculation.

Operationalizing hippocampal volume as an enrichment biomarker for amnestic mild cognitive impairment trials: effect of algorithm, test-retest variability, and cut point on trial cost, duration, and sample size.

PubMed

Yu, Peng; Sun, Jia; Wolz, Robin; Stephenson, Diane; Brewer, James; Fox, Nick C; Cole, Patricia E; Jack, Clifford R; Hill, Derek L G; Schwarz, Adam J

2014-04-01

The objective of this study was to evaluate the effect of computational algorithm, measurement variability, and cut point on hippocampal volume (HCV)-based patient selection for clinical trials in mild cognitive impairment (MCI). We used normal control and amnestic MCI subjects from the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) as normative reference and screening cohorts. We evaluated the enrichment performance of 4 widely used hippocampal segmentation algorithms (FreeSurfer, Hippocampus Multi-Atlas Propagation and Segmentation (HMAPS), Learning Embeddings Atlas Propagation (LEAP), and NeuroQuant) in terms of 2-year changes in Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Clinical Dementia Rating Sum of Boxes (CDR-SB). We modeled the implications for sample size, screen fail rates, and trial cost and duration. HCV based patient selection yielded reduced sample sizes (by ∼40%-60%) and lower trial costs (by ∼30%-40%) across a wide range of cut points. These results provide a guide to the choice of HCV cut point for amnestic MCI clinical trials, allowing an informed tradeoff between statistical and practical considerations. Copyright © 2014 Elsevier Inc. All rights reserved.

A post hoc evaluation of a sample size re-estimation in the Secondary Prevention of Small Subcortical Strokes study.

PubMed

McClure, Leslie A; Szychowski, Jeff M; Benavente, Oscar; Hart, Robert G; Coffey, Christopher S

2016-10-01

The use of adaptive designs has been increasing in randomized clinical trials. Sample size re-estimation is a type of adaptation in which nuisance parameters are estimated at an interim point in the trial and the sample size re-computed based on these estimates. The Secondary Prevention of Small Subcortical Strokes study was a randomized clinical trial assessing the impact of single- versus dual-antiplatelet therapy and control of systolic blood pressure to a higher (130-149 mmHg) versus lower (<130 mmHg) target on recurrent stroke risk in a two-by-two factorial design. A sample size re-estimation was performed during the Secondary Prevention of Small Subcortical Strokes study resulting in an increase from the planned sample size of 2500-3020, and we sought to determine the impact of the sample size re-estimation on the study results. We assessed the results of the primary efficacy and safety analyses with the full 3020 patients and compared them to the results that would have been observed had randomization ended with 2500 patients. The primary efficacy outcome considered was recurrent stroke, and the primary safety outcomes were major bleeds and death. We computed incidence rates for the efficacy and safety outcomes and used Cox proportional hazards models to examine the hazard ratios for each of the two treatment interventions (i.e. the antiplatelet and blood pressure interventions). In the antiplatelet intervention, the hazard ratio was not materially modified by increasing the sample size, nor did the conclusions regarding the efficacy of mono versus dual-therapy change: there was no difference in the effect of dual- versus monotherapy on the risk of recurrent stroke hazard ratios (n = 3020 HR (95% confidence interval): 0.92 (0.72, 1.2), p = 0.48; n = 2500 HR (95% confidence interval): 1.0 (0.78, 1.3), p = 0.85). With respect to the blood pressure intervention, increasing the sample size resulted in less certainty in the results, as the hazard ratio for higher versus lower systolic blood pressure target approached, but did not achieve, statistical significance with the larger sample (n = 3020 HR (95% confidence interval): 0.81 (0.63, 1.0), p = 0.089; n = 2500 HR (95% confidence interval): 0.89 (0.68, 1.17), p = 0.40). The results from the safety analyses were similar to 3020 and 2500 patients for both study interventions. Other trial-related factors, such as contracts, finances, and study management, were impacted as well. Adaptive designs can have benefits in randomized clinical trials, but do not always result in significant findings. The impact of adaptive designs should be measured in terms of both trial results, as well as practical issues related to trial management. More post hoc analyses of study adaptations will lead to better understanding of the balance between the benefits and the costs. © The Author(s) 2016.

Time and expected value of sample information wait for no patient.

PubMed

Eckermann, Simon; Willan, Andrew R

2008-01-01

The expected value of sample information (EVSI) from prospective trials has previously been modeled as the product of EVSI per patient, and the number of patients across the relevant time horizon less those "used up" in trials. However, this implicitly assumes the eligible patient population to which information from a trial can be applied across a time horizon are independent of time for trial accrual, follow-up and analysis. This article demonstrates that in calculating the EVSI of a trial, the number of patients who benefit from trial information should be reduced by those treated outside as well as within the trial over the time until trial evidence is updated, including time for accrual, follow-up and analysis. Accounting for time is shown to reduce the eligible patient population: 1) independent of the size of trial in allowing for time of follow-up and analysis, and 2) dependent on the size of trial for time of accrual, where the patient accrual rate is less than incidence. Consequently, the EVSI and expected net gain (ENG) at any given trial size are shown to be lower when accounting for time, with lower ENG reinforced in the case of trials undertaken while delaying decisions by additional opportunity costs of time. Appropriately accounting for time reduces the EVSI of trial design and increase opportunity costs of trials undertaken with delay, leading to lower likelihood of trialing being optimal and smaller trial designs where optimal.

Accounting for between-study variation in incremental net benefit in value of information methodology.

PubMed

Willan, Andrew R; Eckermann, Simon

2012-10-01

Previous applications of value of information methods for determining optimal sample size in randomized clinical trials have assumed no between-study variation in mean incremental net benefit. By adopting a hierarchical model, we provide a solution for determining optimal sample size with this assumption relaxed. The solution is illustrated with two examples from the literature. Expected net gain increases with increasing between-study variation, reflecting the increased uncertainty in incremental net benefit and reduced extent to which data are borrowed from previous evidence. Hence, a trial can become optimal where current evidence is sufficient assuming no between-study variation. However, despite the expected net gain increasing, the optimal sample size in the illustrated examples is relatively insensitive to the amount of between-study variation. Further percentage losses in expected net gain were small even when choosing sample sizes that reflected widely different between-study variation. Copyright © 2011 John Wiley & Sons, Ltd.

A Meta-analytic Review of Non-specific Effects in Randomized Controlled Trials of Cognitive Remediation for Schizophrenia.

PubMed

Radhakrishnan, Rajiv; Kiluk, Brian D; Tsai, Jack

2016-03-01

Cognitive remediation (CR) has been found to improve cognitive performance among adults with schizophrenia in randomized controlled trials (RCTs). However, improvements in cognitive performance are often observed in the control groups of RCTs as well. There has been no comprehensive examination of change in control groups for CR, which may inform trial methodology and improve our understanding of measured outcomes for cognitive remediation. In this meta-analysis, we calculated pre-post change in cognitive test performance within control groups of RCTs in 32 CR trials (n = 794 participants) published between 1970 and 2011, and examined the association between pre-post change and sample size, duration of treatment, type of control group, and participants' age, intelligence, duration of illness, and psychiatric symptoms. Results showed that control groups in CR trials showed small effect size changes (Cohen's d = 0.12 ± 0.16) in cognitive test performance over the trial duration. Study characteristics associated with pre-post change included participant age and sample size. These findings suggest attention to change in control groups may help improve detection of cognitive remediation effects for schizophrenia.

On the repeated measures designs and sample sizes for randomized controlled trials.

PubMed

Tango, Toshiro

2016-04-01

For the analysis of longitudinal or repeated measures data, generalized linear mixed-effects models provide a flexible and powerful tool to deal with heterogeneity among subject response profiles. However, the typical statistical design adopted in usual randomized controlled trials is an analysis of covariance type analysis using a pre-defined pair of "pre-post" data, in which pre-(baseline) data are used as a covariate for adjustment together with other covariates. Then, the major design issue is to calculate the sample size or the number of subjects allocated to each treatment group. In this paper, we propose a new repeated measures design and sample size calculations combined with generalized linear mixed-effects models that depend not only on the number of subjects but on the number of repeated measures before and after randomization per subject used for the analysis. The main advantages of the proposed design combined with the generalized linear mixed-effects models are (1) it can easily handle missing data by applying the likelihood-based ignorable analyses under the missing at random assumption and (2) it may lead to a reduction in sample size, compared with the simple pre-post design. The proposed designs and the sample size calculations are illustrated with real data arising from randomized controlled trials. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Nonantibiotic prophylaxis for recurrent urinary tract infections: a systematic review and meta-analysis of randomized controlled trials.

PubMed

Beerepoot, M A J; Geerlings, S E; van Haarst, E P; van Charante, N Mensing; ter Riet, G

2013-12-01

Increasing antimicrobial resistance has stimulated interest in nonantibiotic prophylaxis of recurrent urinary tract infections. We assessed the effectiveness, tolerability and safety of nonantibiotic prophylaxis in adults with recurrent urinary tract infections. MEDLINE®, EMBASE™, the Cochrane Library and reference lists of relevant reviews were searched to April 2013 for relevant English language citations. Two reviewers selected randomized controlled trials that met the predefined criteria for population, interventions and outcomes. The difference in the proportions of patients with at least 1 urinary tract infection was calculated for individual studies, and pooled risk ratios were calculated using random and fixed effects models. Adverse event rates were also extracted. The Jadad score was used to assess risk of bias (0 to 2-high risk and 3 to 5-low risk). We identified 5,413 records and included 17 studies with data for 2,165 patients. The oral immunostimulant OM-89 decreased the rate of urinary tract infection recurrence (4 trials, sample size 891, median Jadad score 3, RR 0.61, 95% CI 0.48-0.78) and had a good safety profile. The vaginal vaccine Urovac® slightly reduced urinary tract infection recurrence (3 trials, sample size 220, Jadad score 3, RR 0.81, 95% CI 0.68-0.96) and primary immunization followed by booster immunization increased the time to reinfection. Vaginal estrogens showed a trend toward preventing urinary tract infection recurrence (2 trials, sample size 201, Jadad score 2.5, RR 0.42, 95% CI 0.16-1.10) but vaginal irritation occurred in 6% to 20% of women. Cranberries decreased urinary tract infection recurrence (2 trials, sample size 250, Jadad score 4, RR 0.53, 95% CI 0.33-0.83) as did acupuncture (2 open label trials, sample size 165, Jadad score 2, RR 0.48, 95% CI 0.29-0.79). Oral estrogens and lactobacilli prophylaxis did not decrease the rate of urinary tract infection recurrence. The evidence of the effectiveness of the oral immunostimulant OM-89 is promising. Although sometimes statistically significant, pooled findings for the other interventions should be considered tentative until corroborated by more research. Large head-to-head trials should be performed to optimally inform clinical decision making. Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Angiographic core laboratory reproducibility analyses: implications for planning clinical trials using coronary angiography and left ventriculography end-points.

PubMed

Steigen, Terje K; Claudio, Cheryl; Abbott, David; Schulzer, Michael; Burton, Jeff; Tymchak, Wayne; Buller, Christopher E; John Mancini, G B

2008-06-01

To assess reproducibility of core laboratory performance and impact on sample size calculations. Little information exists about overall reproducibility of core laboratories in contradistinction to performance of individual technicians. Also, qualitative parameters are being adjudicated increasingly as either primary or secondary end-points. The comparative impact of using diverse indexes on sample sizes has not been previously reported. We compared initial and repeat assessments of five quantitative parameters [e.g., minimum lumen diameter (MLD), ejection fraction (EF), etc.] and six qualitative parameters [e.g., TIMI myocardial perfusion grade (TMPG) or thrombus grade (TTG), etc.], as performed by differing technicians and separated by a year or more. Sample sizes were calculated from these results. TMPG and TTG were also adjudicated by a second core laboratory. MLD and EF were the most reproducible, yielding the smallest sample size calculations, whereas percent diameter stenosis and centerline wall motion require substantially larger trials. Of the qualitative parameters, all except TIMI flow grade gave reproducibility characteristics yielding sample sizes of many 100's of patients. Reproducibility of TMPG and TTG was only moderately good both within and between core laboratories, underscoring an intrinsic difficulty in assessing these. Core laboratories can be shown to provide reproducibility performance that is comparable to performance commonly ascribed to individual technicians. The differences in reproducibility yield huge differences in sample size when comparing quantitative and qualitative parameters. TMPG and TTG are intrinsically difficult to assess and conclusions based on these parameters should arise only from very large trials.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations.

PubMed

Kunz, Cornelia U; Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2017-03-01

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under- or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re-assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one-sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups. © 2016 The Authors. Biometrical Journal Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations

PubMed Central

Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2016-01-01

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under‐ or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re‐assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one‐sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups. PMID:27886393

Dimensions of design space: a decision-theoretic approach to optimal research design.

PubMed

Conti, Stefano; Claxton, Karl

2009-01-01

Bayesian decision theory can be used not only to establish the optimal sample size and its allocation in a single clinical study but also to identify an optimal portfolio of research combining different types of study design. Within a single study, the highest societal payoff to proposed research is achieved when its sample sizes and allocation between available treatment options are chosen to maximize the expected net benefit of sampling (ENBS). Where a number of different types of study informing different parameters in the decision problem could be conducted, the simultaneous estimation of ENBS across all dimensions of the design space is required to identify the optimal sample sizes and allocations within such a research portfolio. This is illustrated through a simple example of a decision model of zanamivir for the treatment of influenza. The possible study designs include: 1) a single trial of all the parameters, 2) a clinical trial providing evidence only on clinical endpoints, 3) an epidemiological study of natural history of disease, and 4) a survey of quality of life. The possible combinations, samples sizes, and allocation between trial arms are evaluated over a range of cost-effectiveness thresholds. The computational challenges are addressed by implementing optimization algorithms to search the ENBS surface more efficiently over such large dimensions.

Embedding clinical interventions into observational studies.

PubMed

Newman, Anne B; Avilés-Santa, M Larissa; Anderson, Garnet; Heiss, Gerardo; Howard, Wm James; Krucoff, Mitchell; Kuller, Lewis H; Lewis, Cora E; Robinson, Jennifer G; Taylor, Herman; Treviño, Roberto P; Weintraub, William

2016-01-01

Novel approaches to observational studies and clinical trials could improve the cost-effectiveness and speed of translation of research. Hybrid designs that combine elements of clinical trials with observational registries or cohort studies should be considered as part of a long-term strategy to transform clinical trials and epidemiology, adapting to the opportunities of big data and the challenges of constrained budgets. Important considerations include study aims, timing, breadth and depth of the existing infrastructure that can be leveraged, participant burden, likely participation rate and available sample size in the cohort, required sample size for the trial, and investigator expertise. Community engagement and stakeholder (including study participants) support are essential for these efforts to succeed. Copyright © 2015. Published by Elsevier Inc.

Methodological reporting quality of randomized controlled trials: A survey of seven core journals of orthopaedics from Mainland China over 5 years following the CONSORT statement.

PubMed

Zhang, J; Chen, X; Zhu, Q; Cui, J; Cao, L; Su, J

2016-11-01

In recent years, the number of randomized controlled trials (RCTs) in the field of orthopaedics is increasing in Mainland China. However, randomized controlled trials (RCTs) are inclined to bias if they lack methodological quality. Therefore, we performed a survey of RCT to assess: (1) What about the quality of RCTs in the field of orthopedics in Mainland China? (2) Whether there is difference between the core journals of the Chinese department of orthopedics and Orthopaedics Traumatology Surgery & Research (OTSR). This research aimed to evaluate the methodological reporting quality according to the CONSORT statement of randomized controlled trials (RCTs) in seven key orthopaedic journals published in Mainland China over 5 years from 2010 to 2014. All of the articles were hand researched on Chongqing VIP database between 2010 and 2014. Studies were considered eligible if the words "random", "randomly", "randomization", "randomized" were employed to describe the allocation way. Trials including animals, cadavers, trials published as abstracts and case report, trials dealing with subgroups analysis, or trials without the outcomes were excluded. In addition, eight articles selected from Orthopaedics Traumatology Surgery & Research (OTSR) between 2010 and 2014 were included in this study for comparison. The identified RCTs are analyzed using a modified version of the Consolidated Standards of Reporting Trials (CONSORT), including the sample size calculation, allocation sequence generation, allocation concealment, blinding and handling of dropouts. A total of 222 RCTs were identified in seven core orthopaedic journals. No trials reported adequate sample size calculation, 74 (33.4%) reported adequate allocation generation, 8 (3.7%) trials reported adequate allocation concealment, 18 (8.1%) trials reported adequate blinding and 16 (7.2%) trials reported handling of dropouts. In OTSR, 1 (12.5%) trial reported adequate sample size calculation, 4 (50.0%) reported adequate allocation generation, 1 (12.5%) trials reported adequate allocation concealment, 2 (25.0%) trials reported adequate blinding and 5 (62.5%) trials reported handling of dropouts. There were statistical differences as for sample size calculation and handling of dropouts between papers from Mainland China and OTSR (P<0.05). The findings of this study show that the methodological reporting quality of RCTs in seven core orthopaedic journals from the Mainland China is far from satisfaction and it needs to further improve to keep up with the standards of the CONSORT statement. Level III case control. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Modified Toxicity Probability Interval Design: A Safer and More Reliable Method Than the 3 + 3 Design for Practical Phase I Trials

PubMed Central

Ji, Yuan; Wang, Sue-Jane

2013-01-01

The 3 + 3 design is the most common choice among clinicians for phase I dose-escalation oncology trials. In recent reviews, more than 95% of phase I trials have been based on the 3 + 3 design. Given that it is intuitive and its implementation does not require a computer program, clinicians can conduct 3 + 3 dose escalations in practice with virtually no logistic cost, and trial protocols based on the 3 + 3 design pass institutional review board and biostatistics reviews quickly. However, the performance of the 3 + 3 design has rarely been compared with model-based designs in simulation studies with matched sample sizes. In the vast majority of statistical literature, the 3 + 3 design has been shown to be inferior in identifying true maximum-tolerated doses (MTDs), although the sample size required by the 3 + 3 design is often orders-of-magnitude smaller than model-based designs. In this article, through comparative simulation studies with matched sample sizes, we demonstrate that the 3 + 3 design has higher risks of exposing patients to toxic doses above the MTD than the modified toxicity probability interval (mTPI) design, a newly developed adaptive method. In addition, compared with the mTPI design, the 3 + 3 design does not yield higher probabilities in identifying the correct MTD, even when the sample size is matched. Given that the mTPI design is equally transparent, costless to implement with free software, and more flexible in practical situations, we highly encourage its adoption in early dose-escalation studies whenever the 3 + 3 design is also considered. We provide free software to allow direct comparisons of the 3 + 3 design with other model-based designs in simulation studies with matched sample sizes. PMID:23569307

Design, analysis and presentation of factorial randomised controlled trials

PubMed Central

Montgomery, Alan A; Peters, Tim J; Little, Paul

2003-01-01

Background The evaluation of more than one intervention in the same randomised controlled trial can be achieved using a parallel group design. However this requires increased sample size and can be inefficient, especially if there is also interest in considering combinations of the interventions. An alternative may be a factorial trial, where for two interventions participants are allocated to receive neither intervention, one or the other, or both. Factorial trials require special considerations, however, particularly at the design and analysis stages. Discussion Using a 2 × 2 factorial trial as an example, we present a number of issues that should be considered when planning a factorial trial. The main design issue is that of sample size. Factorial trials are most often powered to detect the main effects of interventions, since adequate power to detect plausible interactions requires greatly increased sample sizes. The main analytical issues relate to the investigation of main effects and the interaction between the interventions in appropriate regression models. Presentation of results should reflect the analytical strategy with an emphasis on the principal research questions. We also give an example of how baseline and follow-up data should be presented. Lastly, we discuss the implications of the design, analytical and presentational issues covered. Summary Difficulties in interpreting the results of factorial trials if an influential interaction is observed is the cost of the potential for efficient, simultaneous consideration of two or more interventions. Factorial trials can in principle be designed to have adequate power to detect realistic interactions, and in any case they are the only design that allows such effects to be investigated. PMID:14633287

A pilot randomized trial of two cognitive rehabilitation interventions for mild cognitive impairment: caregiver outcomes.

PubMed

Cuc, Andrea V; Locke, Dona E C; Duncan, Noah; Fields, Julie A; Snyder, Charlene Hoffman; Hanna, Sherrie; Lunde, Angela; Smith, Glenn E; Chandler, Melanie

2017-12-01

This study aims to provide effect size estimates of the impact of two cognitive rehabilitation interventions provided to patients with mild cognitive impairment: computerized brain fitness exercise and memory support system on support partners' outcomes of depression, anxiety, quality of life, and partner burden. A randomized controlled pilot trial was performed. At 6 months, the partners from both treatment groups showed stable to improved depression scores, while partners in an untreated control group showed worsening depression over 6 months. There were no statistically significant differences on anxiety, quality of life, or burden outcomes in this small pilot trial; however, effect sizes were moderate, suggesting that the sample sizes in this pilot study were not adequate to detect statistical significance. Either form of cognitive rehabilitation may help partners' mood, compared with providing no treatment. However, effect size estimates related to other partner outcomes (i.e., burden, quality of life, and anxiety) suggest that follow-up efficacy trials will need sample sizes of at least 30-100 people per group to accurately determine significance. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Sample Size Estimation in Cluster Randomized Educational Trials: An Empirical Bayes Approach

ERIC Educational Resources Information Center

Rotondi, Michael A.; Donner, Allan

2009-01-01

The educational field has now accumulated an extensive literature reporting on values of the intraclass correlation coefficient, a parameter essential to determining the required size of a planned cluster randomized trial. We propose here a simple simulation-based approach including all relevant information that can facilitate this task. An…

Does the rising placebo response impact antihypertensive clinical trial outcomes? An analysis of data from the Food and Drug Administration 1990-2016

PubMed Central

Fahl Mar, Kaysee; Schilling, Joshua; Brown, Walter A.

2018-01-01

Background Recent studies show that placebo response has grown significantly over time in clinical trials for antidepressants, ADHD medications, antiepileptics, and antidiabetics. Contrary to expectations, trial outcome measures and success rates have not been impacted. This study aimed to see if this trend of increasing placebo response and stable efficacy outcome measures is unique to the conditions previously studied or if it occurs in trials for conditions with physiologically-measured symptoms, such as hypertension. Method For this reason, we evaluated the efficacy data reported in the US Food and Drug Administration Medical and Statistical reviews for 23 antihypertensive programs (32,022 patients, 63 trials, 142 treatment arms). Placebo and medication response, effect sizes, and drug-placebo differences were calculated for each treatment arm and examined over time using meta-regression. We also explored the relationship of sample size, trial duration, baseline blood pressure, and number of treatment arms to placebo/drug response and efficacy outcome measures. Results Like trials of other conditions, placebo response has risen significantly over time (R2 = 0.093, p = 0.018) and effect size (R2 = 0.013, p = 0.187) drug-placebo difference (R2 = 0.013, p = 0.182) and success rate (134/142, 94.4%) have remained unaffected, likely due to a significant compensatory increase in antihypertensive response (R2 = 0.086, p<0.001). Treatment arms are likely overpowered with sample sizes increasing over time (R2 = 0.387, p<0.0001) and stable, large effect sizes (0.78 ±0.37). The exploratory analysis of sample size, trial duration, baseline blood pressure, and number of treatment arms yielded mixed results unlikely to explain the pattern of placebo response and efficacy outcomes over time. The magnitude of placebo response had no relationship to effect size (p = 0.877), antihypertensive-placebo differences (p = 0.752), or p-values (p = 0.963) but was correlated with antihypertensive response (R2 = 0.347, p<0.0001). Conclusions As hypothesized, this study shows that placebo response is increasing in clinical trials for hypertension without any evidence of this increase impacting trial outcomes. Attempting to control placebo response in clinical trials for hypertension may not be necessary for successful efficacy outcomes. In exploratory analysis, we noted that despite finding significant relationships, none of the trial or patient characteristics we examined offered a clear explanation of the rise in placebo and stability in outcome measures over time. Collectively, these data suggest that the phenomenon of increasing placebo response and stable efficacy outcomes may be a general trend, occurring across trials for various psychiatric and medical conditions with physiological and non-physiological endpoints. PMID:29489874

Comparison of Sample Size by Bootstrap and by Formulas Based on Normal Distribution Assumption.

PubMed

Wang, Zuozhen

2018-01-01

Bootstrapping technique is distribution-independent, which provides an indirect way to estimate the sample size for a clinical trial based on a relatively smaller sample. In this paper, sample size estimation to compare two parallel-design arms for continuous data by bootstrap procedure are presented for various test types (inequality, non-inferiority, superiority, and equivalence), respectively. Meanwhile, sample size calculation by mathematical formulas (normal distribution assumption) for the identical data are also carried out. Consequently, power difference between the two calculation methods is acceptably small for all the test types. It shows that the bootstrap procedure is a credible technique for sample size estimation. After that, we compared the powers determined using the two methods based on data that violate the normal distribution assumption. To accommodate the feature of the data, the nonparametric statistical method of Wilcoxon test was applied to compare the two groups in the data during the process of bootstrap power estimation. As a result, the power estimated by normal distribution-based formula is far larger than that by bootstrap for each specific sample size per group. Hence, for this type of data, it is preferable that the bootstrap method be applied for sample size calculation at the beginning, and that the same statistical method as used in the subsequent statistical analysis is employed for each bootstrap sample during the course of bootstrap sample size estimation, provided there is historical true data available that can be well representative of the population to which the proposed trial is planning to extrapolate.

Conservative Sample Size Determination for Repeated Measures Analysis of Covariance.

PubMed

Morgan, Timothy M; Case, L Douglas

2013-07-05

In the design of a randomized clinical trial with one pre and multiple post randomized assessments of the outcome variable, one needs to account for the repeated measures in determining the appropriate sample size. Unfortunately, one seldom has a good estimate of the variance of the outcome measure, let alone the correlations among the measurements over time. We show how sample sizes can be calculated by making conservative assumptions regarding the correlations for a variety of covariance structures. The most conservative choice for the correlation depends on the covariance structure and the number of repeated measures. In the absence of good estimates of the correlations, the sample size is often based on a two-sample t-test, making the 'ultra' conservative and unrealistic assumption that there are zero correlations between the baseline and follow-up measures while at the same time assuming there are perfect correlations between the follow-up measures. Compared to the case of taking a single measurement, substantial savings in sample size can be realized by accounting for the repeated measures, even with very conservative assumptions regarding the parameters of the assumed correlation matrix. Assuming compound symmetry, the sample size from the two-sample t-test calculation can be reduced at least 44%, 56%, and 61% for repeated measures analysis of covariance by taking 2, 3, and 4 follow-up measures, respectively. The results offer a rational basis for determining a fairly conservative, yet efficient, sample size for clinical trials with repeated measures and a baseline value.

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function.

PubMed

Pearce, Michael; Hee, Siew Wan; Madan, Jason; Posch, Martin; Day, Simon; Miller, Frank; Zohar, Sarah; Stallard, Nigel

2018-02-08

Most confirmatory randomised controlled clinical trials (RCTs) are designed with specified power, usually 80% or 90%, for a hypothesis test conducted at a given significance level, usually 2.5% for a one-sided test. Approval of the experimental treatment by regulatory agencies is then based on the result of such a significance test with other information to balance the risk of adverse events against the benefit of the treatment to future patients. In the setting of a rare disease, recruiting sufficient patients to achieve conventional error rates for clinically reasonable effect sizes may be infeasible, suggesting that the decision-making process should reflect the size of the target population. We considered the use of a decision-theoretic value of information (VOI) method to obtain the optimal sample size and significance level for confirmatory RCTs in a range of settings. We assume the decision maker represents society. For simplicity we assume the primary endpoint to be normally distributed with unknown mean following some normal prior distribution representing information on the anticipated effectiveness of the therapy available before the trial. The method is illustrated by an application in an RCT in haemophilia A. We explicitly specify the utility in terms of improvement in primary outcome and compare this with the costs of treating patients, both financial and in terms of potential harm, during the trial and in the future. The optimal sample size for the clinical trial decreases as the size of the population decreases. For non-zero cost of treating future patients, either monetary or in terms of potential harmful effects, stronger evidence is required for approval as the population size increases, though this is not the case if the costs of treating future patients are ignored. Decision-theoretic VOI methods offer a flexible approach with both type I error rate and power (or equivalently trial sample size) depending on the size of the future population for whom the treatment under investigation is intended. This might be particularly suitable for small populations when there is considerable information about the patient population.

Power analysis to detect treatment effects in longitudinal clinical trials for Alzheimer's disease.

PubMed

Huang, Zhiyue; Muniz-Terrera, Graciela; Tom, Brian D M

2017-09-01

Assessing cognitive and functional changes at the early stage of Alzheimer's disease (AD) and detecting treatment effects in clinical trials for early AD are challenging. Under the assumption that transformed versions of the Mini-Mental State Examination, the Clinical Dementia Rating Scale-Sum of Boxes, and the Alzheimer's Disease Assessment Scale-Cognitive Subscale tests'/components' scores are from a multivariate linear mixed-effects model, we calculated the sample sizes required to detect treatment effects on the annual rates of change in these three components in clinical trials for participants with mild cognitive impairment. Our results suggest that a large number of participants would be required to detect a clinically meaningful treatment effect in a population with preclinical or prodromal Alzheimer's disease. We found that the transformed Mini-Mental State Examination is more sensitive for detecting treatment effects in early AD than the transformed Clinical Dementia Rating Scale-Sum of Boxes and Alzheimer's Disease Assessment Scale-Cognitive Subscale. The use of optimal weights to construct powerful test statistics or sensitive composite scores/endpoints can reduce the required sample sizes needed for clinical trials. Consideration of the multivariate/joint distribution of components' scores rather than the distribution of a single composite score when designing clinical trials can lead to an increase in power and reduced sample sizes for detecting treatment effects in clinical trials for early AD.

Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials

PubMed Central

Gilbert, Peter B.; Janes, Holly E.; Huang, Yunda

2016-01-01

In a randomized controlled clinical trial that assesses treatment efficacy, a common objective is to assess the association of a measured biomarker response endpoint with the primary study endpoint in the active treatment group, using a case-cohort, case-control, or two-phase sampling design. Methods for power and sample size calculations for such biomarker association analyses typically do not account for the level of treatment efficacy, precluding interpretation of the biomarker association results in terms of biomarker effect modification of treatment efficacy, with detriment that the power calculations may tacitly and inadvertently assume that the treatment harms some study participants. We develop power and sample size methods accounting for this issue, and the methods also account for inter-individual variability of the biomarker that is not biologically relevant (e.g., due to technical measurement error). We focus on a binary study endpoint and on a biomarker subject to measurement error that is normally distributed or categorical with two or three levels. We illustrate the methods with preventive HIV vaccine efficacy trials, and include an R package implementing the methods. PMID:27037797

Bayesian methods for the design and interpretation of clinical trials in very rare diseases

PubMed Central

Hampson, Lisa V; Whitehead, John; Eleftheriou, Despina; Brogan, Paul

2014-01-01

This paper considers the design and interpretation of clinical trials comparing treatments for conditions so rare that worldwide recruitment efforts are likely to yield total sample sizes of 50 or fewer, even when patients are recruited over several years. For such studies, the sample size needed to meet a conventional frequentist power requirement is clearly infeasible. Rather, the expectation of any such trial has to be limited to the generation of an improved understanding of treatment options. We propose a Bayesian approach for the conduct of rare-disease trials comparing an experimental treatment with a control where patient responses are classified as a success or failure. A systematic elicitation from clinicians of their beliefs concerning treatment efficacy is used to establish Bayesian priors for unknown model parameters. The process of determining the prior is described, including the possibility of formally considering results from related trials. As sample sizes are small, it is possible to compute all possible posterior distributions of the two success rates. A number of allocation ratios between the two treatment groups can be considered with a view to maximising the prior probability that the trial concludes recommending the new treatment when in fact it is non-inferior to control. Consideration of the extent to which opinion can be changed, even by data from the best feasible design, can help to determine whether such a trial is worthwhile. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24957522

An analysis of adaptive design variations on the sequential parallel comparison design for clinical trials.

PubMed

Mi, Michael Y; Betensky, Rebecca A

2013-04-01

Currently, a growing placebo response rate has been observed in clinical trials for antidepressant drugs, a phenomenon that has made it increasingly difficult to demonstrate efficacy. The sequential parallel comparison design (SPCD) is a clinical trial design that was proposed to address this issue. The SPCD theoretically has the potential to reduce the sample-size requirement for a clinical trial and to simultaneously enrich the study population to be less responsive to the placebo. Because the basic SPCD already reduces the placebo response by removing placebo responders between the first and second phases of a trial, the purpose of this study was to examine whether we can further improve the efficiency of the basic SPCD and whether we can do so when the projected underlying drug and placebo response rates differ considerably from the actual ones. Three adaptive designs that used interim analyses to readjust the length of study duration for individual patients were tested to reduce the sample-size requirement or increase the statistical power of the SPCD. Various simulations of clinical trials using the SPCD with interim analyses were conducted to test these designs through calculations of empirical power. From the simulations, we found that the adaptive designs can recover unnecessary resources spent in the traditional SPCD trial format with overestimated initial sample sizes and provide moderate gains in power. Under the first design, results showed up to a 25% reduction in person-days, with most power losses below 5%. In the second design, results showed up to a 8% reduction in person-days with negligible loss of power. In the third design using sample-size re-estimation, up to 25% power was recovered from underestimated sample-size scenarios. Given the numerous possible test parameters that could have been chosen for the simulations, the study's results are limited to situations described by the parameters that were used and may not generalize to all possible scenarios. Furthermore, dropout of patients is not considered in this study. It is possible to make an already complex design such as the SPCD adaptive, and thus more efficient, potentially overcoming the problem of placebo response at lower cost. Ultimately, such a design may expedite the approval of future effective treatments.

An analysis of adaptive design variations on the sequential parallel comparison design for clinical trials

PubMed Central

Mi, Michael Y.; Betensky, Rebecca A.

2013-01-01

Background Currently, a growing placebo response rate has been observed in clinical trials for antidepressant drugs, a phenomenon that has made it increasingly difficult to demonstrate efficacy. The sequential parallel comparison design (SPCD) is a clinical trial design that was proposed to address this issue. The SPCD theoretically has the potential to reduce the sample size requirement for a clinical trial and to simultaneously enrich the study population to be less responsive to the placebo. Purpose Because the basic SPCD design already reduces the placebo response by removing placebo responders between the first and second phases of a trial, the purpose of this study was to examine whether we can further improve the efficiency of the basic SPCD and if we can do so when the projected underlying drug and placebo response rates differ considerably from the actual ones. Methods Three adaptive designs that used interim analyses to readjust the length of study duration for individual patients were tested to reduce the sample size requirement or increase the statistical power of the SPCD. Various simulations of clinical trials using the SPCD with interim analyses were conducted to test these designs through calculations of empirical power. Results From the simulations, we found that the adaptive designs can recover unnecessary resources spent in the traditional SPCD trial format with overestimated initial sample sizes and provide moderate gains in power. Under the first design, results showed up to a 25% reduction in person-days, with most power losses below 5%. In the second design, results showed up to a 8% reduction in person-days with negligible loss of power. In the third design using sample size re-estimation, up to 25% power was recovered from underestimated sample size scenarios. Limitations Given the numerous possible test parameters that could have been chosen for the simulations, the study’s results are limited to situations described by the parameters that were used, and may not generalize to all possible scenarios. Furthermore, drop-out of patients is not considered in this study. Conclusions It is possible to make an already complex design such as the SPCD adaptive, and thus more efficient, potentially overcoming the problem of placebo response at lower cost. Ultimately, such a design may expedite the approval of future effective treatments. PMID:23283576

Methods for flexible sample-size design in clinical trials: Likelihood, weighted, dual test, and promising zone approaches.

PubMed

Shih, Weichung Joe; Li, Gang; Wang, Yining

2016-03-01

Sample size plays a crucial role in clinical trials. Flexible sample-size designs, as part of the more general category of adaptive designs that utilize interim data, have been a popular topic in recent years. In this paper, we give a comparative review of four related methods for such a design. The likelihood method uses the likelihood ratio test with an adjusted critical value. The weighted method adjusts the test statistic with given weights rather than the critical value. The dual test method requires both the likelihood ratio statistic and the weighted statistic to be greater than the unadjusted critical value. The promising zone approach uses the likelihood ratio statistic with the unadjusted value and other constraints. All four methods preserve the type-I error rate. In this paper we explore their properties and compare their relationships and merits. We show that the sample size rules for the dual test are in conflict with the rules of the promising zone approach. We delineate what is necessary to specify in the study protocol to ensure the validity of the statistical procedure and what can be kept implicit in the protocol so that more flexibility can be attained for confirmatory phase III trials in meeting regulatory requirements. We also prove that under mild conditions, the likelihood ratio test still preserves the type-I error rate when the actual sample size is larger than the re-calculated one. Copyright © 2015 Elsevier Inc. All rights reserved.

A predictive approach to selecting the size of a clinical trial, based on subjective clinical opinion.

PubMed

Spiegelhalter, D J; Freedman, L S

1986-01-01

The 'textbook' approach to determining sample size in a clinical trial has some fundamental weaknesses which we discuss. We describe a new predictive method which takes account of prior clinical opinion about the treatment difference. The method adopts the point of clinical equivalence (determined by interviewing the clinical participants) as the null hypothesis. Decision rules at the end of the study are based on whether the interval estimate of the treatment difference (classical or Bayesian) includes the null hypothesis. The prior distribution is used to predict the probabilities of making the decisions to use one or other treatment or to reserve final judgement. It is recommended that sample size be chosen to control the predicted probability of the last of these decisions. An example is given from a multi-centre trial of superficial bladder cancer.

Generalized optimal design for two-arm, randomized phase II clinical trials with endpoints from the exponential dispersion family.

PubMed

Jiang, Wei; Mahnken, Jonathan D; He, Jianghua; Mayo, Matthew S

2016-11-01

For two-arm randomized phase II clinical trials, previous literature proposed an optimal design that minimizes the total sample sizes subject to multiple constraints on the standard errors of the estimated event rates and their difference. The original design is limited to trials with dichotomous endpoints. This paper extends the original approach to be applicable to phase II clinical trials with endpoints from the exponential dispersion family distributions. The proposed optimal design minimizes the total sample sizes needed to provide estimates of population means of both arms and their difference with pre-specified precision. Its applications on data from specific distribution families are discussed under multiple design considerations. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

An internal pilot design for prospective cancer screening trials with unknown disease prevalence.

PubMed

Brinton, John T; Ringham, Brandy M; Glueck, Deborah H

2015-10-13

For studies that compare the diagnostic accuracy of two screening tests, the sample size depends on the prevalence of disease in the study population, and on the variance of the outcome. Both parameters may be unknown during the design stage, which makes finding an accurate sample size difficult. To solve this problem, we propose adapting an internal pilot design. In this adapted design, researchers will accrue some percentage of the planned sample size, then estimate both the disease prevalence and the variances of the screening tests. The updated estimates of the disease prevalence and variance are used to conduct a more accurate power and sample size calculation. We demonstrate that in large samples, the adapted internal pilot design produces no Type I inflation. For small samples (N less than 50), we introduce a novel adjustment of the critical value to control the Type I error rate. We apply the method to two proposed prospective cancer screening studies: 1) a small oral cancer screening study in individuals with Fanconi anemia and 2) a large oral cancer screening trial. Conducting an internal pilot study without adjusting the critical value can cause Type I error rate inflation in small samples, but not in large samples. An internal pilot approach usually achieves goal power and, for most studies with sample size greater than 50, requires no Type I error correction. Further, we have provided a flexible and accurate approach to bound Type I error below a goal level for studies with small sample size.

Composite outcomes in randomized clinical trials: arguments for and against.

PubMed

Ross, Sue

2007-02-01

Composite outcomes that combine a number of individual outcomes (such as types of morbidity) are frequently used as primary outcomes in obstetrical trials. The main argument for their use is to ensure that trials can answer important clinical questions in a timely fashion, without needing huge sample sizes. Arguments against their use are that composite outcomes may be difficult to use and interpret, leading to errors in sample size estimation, possible contradictory trial results, and difficulty in interpreting findings. Such problems may reduce the credibility of the research, and may impact on the implementation of findings. Composite outcomes are an attractive solution to help to overcome the problem of limited available resources for clinical trials. However, future studies should carefully consider both the advantages and disadvantages before using composite outcomes. Rigorous development and reporting of composite outcomes is essential if the research is to be useful.

Sample Size Requirements and Study Duration for Testing Main Effects and Interactions in Completely Randomized Factorial Designs When Time to Event is the Outcome

PubMed Central

Moser, Barry Kurt; Halabi, Susan

2013-01-01

In this paper we develop the methodology for designing clinical trials with any factorial arrangement when the primary outcome is time to event. We provide a matrix formulation for calculating the sample size and study duration necessary to test any effect with a pre-specified type I error rate and power. Assuming that a time to event follows an exponential distribution, we describe the relationships between the effect size, the power, and the sample size. We present examples for illustration purposes. We provide a simulation study to verify the numerical calculations of the expected number of events and the duration of the trial. The change in the power produced by a reduced number of observations or by accruing no patients to certain factorial combinations is also described. PMID:25530661

Bayesian sample size calculations in phase II clinical trials using a mixture of informative priors.

PubMed

Gajewski, Byron J; Mayo, Matthew S

2006-08-15

A number of researchers have discussed phase II clinical trials from a Bayesian perspective. A recent article by Mayo and Gajewski focuses on sample size calculations, which they determine by specifying an informative prior distribution and then calculating a posterior probability that the true response will exceed a prespecified target. In this article, we extend these sample size calculations to include a mixture of informative prior distributions. The mixture comes from several sources of information. For example consider information from two (or more) clinicians. The first clinician is pessimistic about the drug and the second clinician is optimistic. We tabulate the results for sample size design using the fact that the simple mixture of Betas is a conjugate family for the Beta- Binomial model. We discuss the theoretical framework for these types of Bayesian designs and show that the Bayesian designs in this paper approximate this theoretical framework. Copyright 2006 John Wiley & Sons, Ltd.

Sample size calculation in economic evaluations.

PubMed

Al, M J; van Hout, B A; Michel, B C; Rutten, F F

1998-06-01

A simulation method is presented for sample size calculation in economic evaluations. As input the method requires: the expected difference and variance of costs and effects, their correlation, the significance level (alpha) and the power of the testing method and the maximum acceptable ratio of incremental effectiveness to incremental costs. The method is illustrated with data from two trials. The first compares primary coronary angioplasty with streptokinase in the treatment of acute myocardial infarction, in the second trial, lansoprazole is compared with omeprazole in the treatment of reflux oesophagitis. These case studies show how the various parameters influence the sample size. Given the large number of parameters that have to be specified in advance, the lack of knowledge about costs and their standard deviation, and the difficulty of specifying the maximum acceptable ratio of incremental effectiveness to incremental costs, the conclusion of the study is that from a technical point of view it is possible to perform a sample size calculation for an economic evaluation, but one should wonder how useful it is.

Sample size determinations for group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms.

PubMed

Heo, Moonseong; Litwin, Alain H; Blackstock, Oni; Kim, Namhee; Arnsten, Julia H

2017-02-01

We derived sample size formulae for detecting main effects in group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms. Such designs are necessary when experimental interventions need to be administered to groups of subjects whereas control conditions need to be administered to individual subjects. This type of trial, often referred to as a partially nested or partially clustered design, has been implemented for management of chronic diseases such as diabetes and is beginning to emerge more commonly in wider clinical settings. Depending on the research setting, the level of hierarchy of data structure for the experimental arm can be three or two, whereas that for the control arm is two or one. Such different levels of data hierarchy assume correlation structures of outcomes that are different between arms, regardless of whether research settings require two or three level data structure for the experimental arm. Therefore, the different correlations should be taken into account for statistical modeling and for sample size determinations. To this end, we considered mixed-effects linear models with different correlation structures between experimental and control arms to theoretically derive and empirically validate the sample size formulae with simulation studies.

Spine device clinical trials: design and sponsorship.

PubMed

Cher, Daniel J; Capobianco, Robyn A

2015-05-01

Multicenter prospective randomized clinical trials represent the best evidence to support the safety and effectiveness of medical devices. Industry sponsorship of multicenter clinical trials is purported to lead to bias. To determine what proportion of spine device-related trials are industry-sponsored and the effect of industry sponsorship on trial design. Analysis of data from a publicly available clinical trials database. Clinical trials of spine devices registered on ClinicalTrials.gov, a publicly accessible trial database, were evaluated in terms of design, number and location of study centers, and sample size. The relationship between trial design characteristics and study sponsorship was evaluated using logistic regression and general linear models. One thousand six hundred thrity-eight studies were retrieved from ClinicalTrials.gov using the search term "spine." Of the 367 trials that focused on spine surgery, 200 (54.5%) specifically studied devices for spine surgery and 167 (45.5%) focused on other issues related to spine surgery. Compared with nondevice trials, device trials were far more likely to be sponsored by the industry (74% vs. 22.2%, odds ratio (OR) 9.9 [95% confidence interval 6.1-16.3]). Industry-sponsored device trials were more likely multicenter (80% vs. 29%, OR 9.8 [4.8-21.1]) and had approximately four times as many participating study centers (p<.0001) and larger sample sizes. There were very few US-based multicenter randomized trials of spine devices not sponsored by the industry. Most device-related spine research is industry-sponsored. Multicenter trials are more likely to be industry-sponsored. These findings suggest that previously published studies showing larger effect sizes in industry-sponsored vs. nonindustry-sponsored studies may be biased as a result of failure to take into account the marked differences in design and purpose. Copyright © 2015 Elsevier Inc. All rights reserved.

A single test for rejecting the null hypothesis in subgroups and in the overall sample.

PubMed

Lin, Yunzhi; Zhou, Kefei; Ganju, Jitendra

2017-01-01

In clinical trials, some patient subgroups are likely to demonstrate larger effect sizes than other subgroups. For example, the effect size, or informally the benefit with treatment, is often greater in patients with a moderate condition of a disease than in those with a mild condition. A limitation of the usual method of analysis is that it does not incorporate this ordering of effect size by patient subgroup. We propose a test statistic which supplements the conventional test by including this information and simultaneously tests the null hypothesis in pre-specified subgroups and in the overall sample. It results in more power than the conventional test when the differences in effect sizes across subgroups are at least moderately large; otherwise it loses power. The method involves combining p-values from models fit to pre-specified subgroups and the overall sample in a manner that assigns greater weight to subgroups in which a larger effect size is expected. Results are presented for randomized trials with two and three subgroups.

A Bayesian sequential design with adaptive randomization for 2-sided hypothesis test.

PubMed

Yu, Qingzhao; Zhu, Lin; Zhu, Han

2017-11-01

Bayesian sequential and adaptive randomization designs are gaining popularity in clinical trials thanks to their potentials to reduce the number of required participants and save resources. We propose a Bayesian sequential design with adaptive randomization rates so as to more efficiently attribute newly recruited patients to different treatment arms. In this paper, we consider 2-arm clinical trials. Patients are allocated to the 2 arms with a randomization rate to achieve minimum variance for the test statistic. Algorithms are presented to calculate the optimal randomization rate, critical values, and power for the proposed design. Sensitivity analysis is implemented to check the influence on design by changing the prior distributions. Simulation studies are applied to compare the proposed method and traditional methods in terms of power and actual sample sizes. Simulations show that, when total sample size is fixed, the proposed design can obtain greater power and/or cost smaller actual sample size than the traditional Bayesian sequential design. Finally, we apply the proposed method to a real data set and compare the results with the Bayesian sequential design without adaptive randomization in terms of sample sizes. The proposed method can further reduce required sample size. Copyright © 2017 John Wiley & Sons, Ltd.

Group-sequential three-arm noninferiority clinical trial designs

PubMed Central

Ochiai, Toshimitsu; Hamasaki, Toshimitsu; Evans, Scott R.; Asakura, Koko; Ohno, Yuko

2016-01-01

We discuss group-sequential three-arm noninferiority clinical trial designs that include active and placebo controls for evaluating both assay sensitivity and noninferiority. We extend two existing approaches, the fixed margin and fraction approaches, into a group-sequential setting with two decision-making frameworks. We investigate the operating characteristics including power, Type I error rate, maximum and expected sample sizes, as design factors vary. In addition, we discuss sample size recalculation and its’ impact on the power and Type I error rate via a simulation study. PMID:26892481

Using e-mail recruitment and an online questionnaire to establish effect size: A worked example.

PubMed

Kirkby, Helen M; Wilson, Sue; Calvert, Melanie; Draper, Heather

2011-06-09

Sample size calculations require effect size estimations. Sometimes, effect size estimations and standard deviation may not be readily available, particularly if efficacy is unknown because the intervention is new or developing, or the trial targets a new population. In such cases, one way to estimate the effect size is to gather expert opinion. This paper reports the use of a simple strategy to gather expert opinion to estimate a suitable effect size to use in a sample size calculation. Researchers involved in the design and analysis of clinical trials were identified at the University of Birmingham and via the MRC Hubs for Trials Methodology Research. An email invited them to participate.An online questionnaire was developed using the free online tool 'Survey Monkey©'. The questionnaire described an intervention, an electronic participant information sheet (e-PIS), which may increase recruitment rates to a trial. Respondents were asked how much they would need to see recruitment rates increased by, based on 90%. 70%, 50% and 30% baseline rates, (in a hypothetical study) before they would consider using an e-PIS in their research.Analyses comprised simple descriptive statistics. The invitation to participate was sent to 122 people; 7 responded to say they were not involved in trial design and could not complete the questionnaire, 64 attempted it, 26 failed to complete it. Thirty-eight people completed the questionnaire and were included in the analysis (response rate 33%; 38/115). Of those who completed the questionnaire 44.7% (17/38) were at the academic grade of research fellow 26.3% (10/38) senior research fellow, and 28.9% (11/38) professor. Dependent upon the baseline recruitment rates presented in the questionnaire, participants wanted recruitment rate to increase from 6.9% to 28.9% before they would consider using the intervention. This paper has shown that in situations where effect size estimations cannot be collected from previous research, opinions from researchers and trialists can be quickly and easily collected by conducting a simple study using email recruitment and an online questionnaire. The results collected from the survey were successfully used in sample size calculations for a PhD research study protocol.

Quantification of errors in ordinal outcome scales using shannon entropy: effect on sample size calculations.

PubMed

Mandava, Pitchaiah; Krumpelman, Chase S; Shah, Jharna N; White, Donna L; Kent, Thomas A

2013-01-01

Clinical trial outcomes often involve an ordinal scale of subjective functional assessments but the optimal way to quantify results is not clear. In stroke, the most commonly used scale, the modified Rankin Score (mRS), a range of scores ("Shift") is proposed as superior to dichotomization because of greater information transfer. The influence of known uncertainties in mRS assessment has not been quantified. We hypothesized that errors caused by uncertainties could be quantified by applying information theory. Using Shannon's model, we quantified errors of the "Shift" compared to dichotomized outcomes using published distributions of mRS uncertainties and applied this model to clinical trials. We identified 35 randomized stroke trials that met inclusion criteria. Each trial's mRS distribution was multiplied with the noise distribution from published mRS inter-rater variability to generate an error percentage for "shift" and dichotomized cut-points. For the SAINT I neuroprotectant trial, considered positive by "shift" mRS while the larger follow-up SAINT II trial was negative, we recalculated sample size required if classification uncertainty was taken into account. Considering the full mRS range, error rate was 26.1%±5.31 (Mean±SD). Error rates were lower for all dichotomizations tested using cut-points (e.g. mRS 1; 6.8%±2.89; overall p<0.001). Taking errors into account, SAINT I would have required 24% more subjects than were randomized. We show when uncertainty in assessments is considered, the lowest error rates are with dichotomization. While using the full range of mRS is conceptually appealing, a gain of information is counter-balanced by a decrease in reliability. The resultant errors need to be considered since sample size may otherwise be underestimated. In principle, we have outlined an approach to error estimation for any condition in which there are uncertainties in outcome assessment. We provide the user with programs to calculate and incorporate errors into sample size estimation.

Sample size, confidence, and contingency judgement.

PubMed

Clément, Mélanie; Mercier, Pierre; Pastò, Luigi

2002-06-01

According to statistical models, the acquisition function of contingency judgement is due to confidence increasing with sample size. According to associative models, the function reflects the accumulation of associative strength on which the judgement is based. Which view is right? Thirty university students assessed the relation between a fictitious medication and a symptom of skin discoloration in conditions that varied sample size (4, 6, 8 or 40 trials) and contingency (delta P = .20, .40, .60 or .80). Confidence was also collected. Contingency judgement was lower for smaller samples, while confidence level correlated inversely with sample size. This dissociation between contingency judgement and confidence contradicts the statistical perspective.

Sample-size needs for forestry herbicide trials

Treesearch

S.M. Zedaker; T.G. Gregoire; James H. Miller

1994-01-01

Forest herbicide experiments are increasingly being designed to evaluate smaller treatment differences when comparing existing effective treatments, tank mix ratios, surfactants, and new low-rate products. The ability to detect small differences in efficacy is dependent upon the relationship among sample size. type I and II error probabilities, and the coefficients of...

Use of randomised controlled trials for producing cost-effectiveness evidence: potential impact of design choices on sample size and study duration.

PubMed

Backhouse, Martin E

2002-01-01

A number of approaches to conducting economic evaluations could be adopted. However, some decision makers have a preference for wholly stochastic cost-effectiveness analyses, particularly if the sampled data are derived from randomised controlled trials (RCTs). Formal requirements for cost-effectiveness evidence have heightened concerns in the pharmaceutical industry that development costs and times might be increased if formal requirements increase the number, duration or costs of RCTs. Whether this proves to be the case or not will depend upon the timing, nature and extent of the cost-effectiveness evidence required. To illustrate how different requirements for wholly stochastic cost-effectiveness evidence could have a significant impact on two of the major determinants of new drug development costs and times, namely RCT sample size and study duration. Using data collected prospectively in a clinical evaluation, sample sizes were calculated for a number of hypothetical cost-effectiveness study design scenarios. The results were compared with a baseline clinical trial design. The sample sizes required for the cost-effectiveness study scenarios were mostly larger than those for the baseline clinical trial design. Circumstances can be such that a wholly stochastic cost-effectiveness analysis might not be a practical proposition even though its clinical counterpart is. In such situations, alternative research methodologies would be required. For wholly stochastic cost-effectiveness analyses, the importance of prior specification of the different components of study design is emphasised. However, it is doubtful whether all the information necessary for doing this will typically be available when product registration trials are being designed. Formal requirements for wholly stochastic cost-effectiveness evidence based on the standard frequentist paradigm have the potential to increase the size, duration and number of RCTs significantly and hence the costs and timelines associated with new product development. Moreover, it is possible to envisage situations where such an approach would be impossible to adopt. Clearly, further research is required into the issue of how to appraise the economic consequences of alternative economic evaluation research strategies.

Monitoring disease progression with plasma creatinine in amyotrophic lateral sclerosis clinical trials

PubMed Central

van Eijk, Ruben P A; Eijkemans, Marinus J C; Ferguson, Toby A; Nikolakopoulos, Stavros; Veldink, Jan H; van den Berg, Leonard H

2018-01-01

Objectives Plasma creatinine is a predictor of survival in amyotrophic lateral sclerosis (ALS). It remains, however, to be established whether it can monitor disease progression and serve as surrogate endpoint in clinical trials. Methods We used clinical trial data from three cohorts of clinical trial participants in the LITRA, EMPOWER and PROACT studies. Longitudinal associations between functional decline, muscle strength and survival with plasma creatinine were assessed. Results were translated to trial design in terms of sample size and power. Results A total of 13 564 measurements were obtained for 1241 patients. The variability between patients in rate of decline was lower in plasma creatinine than in ALS functional rating scale–Revised (ALSFRS-R; p<0.001). The average rate of decline was faster in the ALSFRS-R, with less between-patient variability at baseline (p<0.001). Plasma creatinine had strong longitudinal correlations with the ALSFRS-R (0.43 (0.39–0.46), p<0.001), muscle strength (0.55 (0.51–0.58), p<0.001) and overall mortality (HR 0.88 (0.86–0.91, p<0.001)). Using plasma creatinine as outcome could reduce the sample size in trials by 21.5% at 18 months. For trials up to 10 months, the ALSFRS-R required a lower sample size. Conclusions Plasma creatinine is an inexpensive and easily accessible biomarker that exhibits less variability between patients with ALS over time and is predictive for the patient’s functional status, muscle strength and mortality risk. Plasma creatinine may, therefore, increase the power to detect treatment effects and could be incorporated in future ALS clinical trials as potential surrogate outcome. PMID:29084868

Quality of reporting of pilot and feasibility cluster randomised trials: a systematic review

PubMed Central

Chan, Claire L; Leyrat, Clémence; Eldridge, Sandra M

2017-01-01

Objectives To systematically review the quality of reporting of pilot and feasibility of cluster randomised trials (CRTs). In particular, to assess (1) the number of pilot CRTs conducted between 1 January 2011 and 31 December 2014, (2) whether objectives and methods are appropriate and (3) reporting quality. Methods We searched PubMed (2011–2014) for CRTs with ‘pilot’ or ‘feasibility’ in the title or abstract; that were assessing some element of feasibility and showing evidence the study was in preparation for a main effectiveness/efficacy trial. Quality assessment criteria were based on the Consolidated Standards of Reporting Trials (CONSORT) extensions for pilot trials and CRTs. Results Eighteen pilot CRTs were identified. Forty-four per cent did not have feasibility as their primary objective, and many (50%) performed formal hypothesis testing for effectiveness/efficacy despite being underpowered. Most (83%) included ‘pilot’ or ‘feasibility’ in the title, and discussed implications for progression from the pilot to the future definitive trial (89%), but fewer reported reasons for the randomised pilot trial (39%), sample size rationale (44%) or progression criteria (17%). Most defined the cluster (100%), and number of clusters randomised (94%), but few reported how the cluster design affected sample size (17%), whether consent was sought from clusters (11%), or who enrolled clusters (17%). Conclusions That only 18 pilot CRTs were identified necessitates increased awareness of the importance of conducting and publishing pilot CRTs and improved reporting. Pilot CRTs should primarily be assessing feasibility, avoiding formal hypothesis testing for effectiveness/efficacy and reporting reasons for the pilot, sample size rationale and progression criteria, as well as enrolment of clusters, and how the cluster design affects design aspects. We recommend adherence to the CONSORT extensions for pilot trials and CRTs. PMID:29122791

Maximum type I error rate inflation from sample size reassessment when investigators are blind to treatment labels.

PubMed

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

Consider a parallel group trial for the comparison of an experimental treatment to a control, where the second-stage sample size may depend on the blinded primary endpoint data as well as on additional blinded data from a secondary endpoint. For the setting of normally distributed endpoints, we demonstrate that this may lead to an inflation of the type I error rate if the null hypothesis holds for the primary but not the secondary endpoint. We derive upper bounds for the inflation of the type I error rate, both for trials that employ random allocation and for those that use block randomization. We illustrate the worst-case sample size reassessment rule in a case study. For both randomization strategies, the maximum type I error rate increases with the effect size in the secondary endpoint and the correlation between endpoints. The maximum inflation increases with smaller block sizes if information on the block size is used in the reassessment rule. Based on our findings, we do not question the well-established use of blinded sample size reassessment methods with nuisance parameter estimates computed from the blinded interim data of the primary endpoint. However, we demonstrate that the type I error rate control of these methods relies on the application of specific, binding, pre-planned and fully algorithmic sample size reassessment rules and does not extend to general or unplanned sample size adjustments based on blinded data. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Methods for specifying the target difference in a randomised controlled trial: the Difference ELicitation in TriAls (DELTA) systematic review.

PubMed

Hislop, Jenni; Adewuyi, Temitope E; Vale, Luke D; Harrild, Kirsten; Fraser, Cynthia; Gurung, Tara; Altman, Douglas G; Briggs, Andrew H; Fayers, Peter; Ramsay, Craig R; Norrie, John D; Harvey, Ian M; Buckley, Brian; Cook, Jonathan A

2014-05-01

Randomised controlled trials (RCTs) are widely accepted as the preferred study design for evaluating healthcare interventions. When the sample size is determined, a (target) difference is typically specified that the RCT is designed to detect. This provides reassurance that the study will be informative, i.e., should such a difference exist, it is likely to be detected with the required statistical precision. The aim of this review was to identify potential methods for specifying the target difference in an RCT sample size calculation. A comprehensive systematic review of medical and non-medical literature was carried out for methods that could be used to specify the target difference for an RCT sample size calculation. The databases searched were MEDLINE, MEDLINE In-Process, EMBASE, the Cochrane Central Register of Controlled Trials, the Cochrane Methodology Register, PsycINFO, Science Citation Index, EconLit, the Education Resources Information Center (ERIC), and Scopus (for in-press publications); the search period was from 1966 or the earliest date covered, to between November 2010 and January 2011. Additionally, textbooks addressing the methodology of clinical trials and International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) tripartite guidelines for clinical trials were also consulted. A narrative synthesis of methods was produced. Studies that described a method that could be used for specifying an important and/or realistic difference were included. The search identified 11,485 potentially relevant articles from the databases searched. Of these, 1,434 were selected for full-text assessment, and a further nine were identified from other sources. Fifteen clinical trial textbooks and the ICH tripartite guidelines were also reviewed. In total, 777 studies were included, and within them, seven methods were identified-anchor, distribution, health economic, opinion-seeking, pilot study, review of the evidence base, and standardised effect size. A variety of methods are available that researchers can use for specifying the target difference in an RCT sample size calculation. Appropriate methods may vary depending on the aim (e.g., specifying an important difference versus a realistic difference), context (e.g., research question and availability of data), and underlying framework adopted (e.g., Bayesian versus conventional statistical approach). Guidance on the use of each method is given. No single method provides a perfect solution for all contexts.

Sample size determination for GEE analyses of stepped wedge cluster randomized trials.

PubMed

Li, Fan; Turner, Elizabeth L; Preisser, John S

2018-06-19

In stepped wedge cluster randomized trials, intact clusters of individuals switch from control to intervention from a randomly assigned period onwards. Such trials are becoming increasingly popular in health services research. When a closed cohort is recruited from each cluster for longitudinal follow-up, proper sample size calculation should account for three distinct types of intraclass correlations: the within-period, the inter-period, and the within-individual correlations. Setting the latter two correlation parameters to be equal accommodates cross-sectional designs. We propose sample size procedures for continuous and binary responses within the framework of generalized estimating equations that employ a block exchangeable within-cluster correlation structure defined from the distinct correlation types. For continuous responses, we show that the intraclass correlations affect power only through two eigenvalues of the correlation matrix. We demonstrate that analytical power agrees well with simulated power for as few as eight clusters, when data are analyzed using bias-corrected estimating equations for the correlation parameters concurrently with a bias-corrected sandwich variance estimator. © 2018, The International Biometric Society.

Improving the analysis of composite endpoints in rare disease trials.

PubMed

McMenamin, Martina; Berglind, Anna; Wason, James M S

2018-05-22

Composite endpoints are recommended in rare diseases to increase power and/or to sufficiently capture complexity. Often, they are in the form of responder indices which contain a mixture of continuous and binary components. Analyses of these outcomes typically treat them as binary, thus only using the dichotomisations of continuous components. The augmented binary method offers a more efficient alternative and is therefore especially useful for rare diseases. Previous work has indicated the method may have poorer statistical properties when the sample size is small. Here we investigate small sample properties and implement small sample corrections. We re-sample from a previous trial with sample sizes varying from 30 to 80. We apply the standard binary and augmented binary methods and determine the power, type I error rate, coverage and average confidence interval width for each of the estimators. We implement Firth's adjustment for the binary component models and a small sample variance correction for the generalized estimating equations, applying the small sample adjusted methods to each sub-sample as before for comparison. For the log-odds treatment effect the power of the augmented binary method is 20-55% compared to 12-20% for the standard binary method. Both methods have approximately nominal type I error rates. The difference in response probabilities exhibit similar power but both unadjusted methods demonstrate type I error rates of 6-8%. The small sample corrected methods have approximately nominal type I error rates. On both scales, the reduction in average confidence interval width when using the adjusted augmented binary method is 17-18%. This is equivalent to requiring a 32% smaller sample size to achieve the same statistical power. The augmented binary method with small sample corrections provides a substantial improvement for rare disease trials using composite endpoints. We recommend the use of the method for the primary analysis in relevant rare disease trials. We emphasise that the method should be used alongside other efforts in improving the quality of evidence generated from rare disease trials rather than replace them.

Sample size calculation for a proof of concept study.

PubMed

Yin, Yin

2002-05-01

Sample size calculation is vital for a confirmatory clinical trial since the regulatory agencies require the probability of making Type I error to be significantly small, usually less than 0.05 or 0.025. However, the importance of the sample size calculation for studies conducted by a pharmaceutical company for internal decision making, e.g., a proof of concept (PoC) study, has not received enough attention. This article introduces a Bayesian method that identifies the information required for planning a PoC and the process of sample size calculation. The results will be presented in terms of the relationships between the regulatory requirements, the probability of reaching the regulatory requirements, the goalpost for PoC, and the sample size used for PoC.

Sample Size Calculations for Micro-randomized Trials in mHealth

PubMed Central

Liao, Peng; Klasnja, Predrag; Tewari, Ambuj; Murphy, Susan A.

2015-01-01

The use and development of mobile interventions are experiencing rapid growth. In “just-in-time” mobile interventions, treatments are provided via a mobile device and they are intended to help an individual make healthy decisions “in the moment,” and thus have a proximal, near future impact. Currently the development of mobile interventions is proceeding at a much faster pace than that of associated data science methods. A first step toward developing data-based methods is to provide an experimental design for testing the proximal effects of these just-in-time treatments. In this paper, we propose a “micro-randomized” trial design for this purpose. In a micro-randomized trial, treatments are sequentially randomized throughout the conduct of the study, with the result that each participant may be randomized at the 100s or 1000s of occasions at which a treatment might be provided. Further, we develop a test statistic for assessing the proximal effect of a treatment as well as an associated sample size calculator. We conduct simulation evaluations of the sample size calculator in various settings. Rules of thumb that might be used in designing a micro-randomized trial are discussed. This work is motivated by our collaboration on the HeartSteps mobile application designed to increase physical activity. PMID:26707831

A Bayesian-frequentist two-stage single-arm phase II clinical trial design.

PubMed

Dong, Gaohong; Shih, Weichung Joe; Moore, Dirk; Quan, Hui; Marcella, Stephen

2012-08-30

It is well-known that both frequentist and Bayesian clinical trial designs have their own advantages and disadvantages. To have better properties inherited from these two types of designs, we developed a Bayesian-frequentist two-stage single-arm phase II clinical trial design. This design allows both early acceptance and rejection of the null hypothesis ( H(0) ). The measures (for example probability of trial early termination, expected sample size, etc.) of the design properties under both frequentist and Bayesian settings are derived. Moreover, under the Bayesian setting, the upper and lower boundaries are determined with predictive probability of trial success outcome. Given a beta prior and a sample size for stage I, based on the marginal distribution of the responses at stage I, we derived Bayesian Type I and Type II error rates. By controlling both frequentist and Bayesian error rates, the Bayesian-frequentist two-stage design has special features compared with other two-stage designs. Copyright © 2012 John Wiley & Sons, Ltd.

A Bayesian sequential design using alpha spending function to control type I error.

PubMed

Zhu, Han; Yu, Qingzhao

2017-10-01

We propose in this article a Bayesian sequential design using alpha spending functions to control the overall type I error in phase III clinical trials. We provide algorithms to calculate critical values, power, and sample sizes for the proposed design. Sensitivity analysis is implemented to check the effects from different prior distributions, and conservative priors are recommended. We compare the power and actual sample sizes of the proposed Bayesian sequential design with different alpha spending functions through simulations. We also compare the power of the proposed method with frequentist sequential design using the same alpha spending function. Simulations show that, at the same sample size, the proposed method provides larger power than the corresponding frequentist sequential design. It also has larger power than traditional Bayesian sequential design which sets equal critical values for all interim analyses. When compared with other alpha spending functions, O'Brien-Fleming alpha spending function has the largest power and is the most conservative in terms that at the same sample size, the null hypothesis is the least likely to be rejected at early stage of clinical trials. And finally, we show that adding a step of stop for futility in the Bayesian sequential design can reduce the overall type I error and reduce the actual sample sizes.

Sample Size Requirements for Studies of Treatment Effects on Beta-Cell Function in Newly Diagnosed Type 1 Diabetes

PubMed Central

Lachin, John M.; McGee, Paula L.; Greenbaum, Carla J.; Palmer, Jerry; Gottlieb, Peter; Skyler, Jay

2011-01-01

Preservation of -cell function as measured by stimulated C-peptide has recently been accepted as a therapeutic target for subjects with newly diagnosed type 1 diabetes. In recently completed studies conducted by the Type 1 Diabetes Trial Network (TrialNet), repeated 2-hour Mixed Meal Tolerance Tests (MMTT) were obtained for up to 24 months from 156 subjects with up to 3 months duration of type 1 diabetes at the time of study enrollment. These data provide the information needed to more accurately determine the sample size needed for future studies of the effects of new agents on the 2-hour area under the curve (AUC) of the C-peptide values. The natural log(), log(+1) and square-root transformations of the AUC were assessed. In general, a transformation of the data is needed to better satisfy the normality assumptions for commonly used statistical tests. Statistical analysis of the raw and transformed data are provided to estimate the mean levels over time and the residual variation in untreated subjects that allow sample size calculations for future studies at either 12 or 24 months of follow-up and among children 8–12 years of age, adolescents (13–17 years) and adults (18+ years). The sample size needed to detect a given relative (percentage) difference with treatment versus control is greater at 24 months than at 12 months of follow-up, and differs among age categories. Owing to greater residual variation among those 13–17 years of age, a larger sample size is required for this age group. Methods are also described for assessment of sample size for mixtures of subjects among the age categories. Statistical expressions are presented for the presentation of analyses of log(+1) and transformed values in terms of the original units of measurement (pmol/ml). Analyses using different transformations are described for the TrialNet study of masked anti-CD20 (rituximab) versus masked placebo. These results provide the information needed to accurately evaluate the sample size for studies of new agents to preserve C-peptide levels in newly diagnosed type 1 diabetes. PMID:22102862

Sample size requirements for studies of treatment effects on beta-cell function in newly diagnosed type 1 diabetes.

PubMed

Lachin, John M; McGee, Paula L; Greenbaum, Carla J; Palmer, Jerry; Pescovitz, Mark D; Gottlieb, Peter; Skyler, Jay

2011-01-01

Preservation of β-cell function as measured by stimulated C-peptide has recently been accepted as a therapeutic target for subjects with newly diagnosed type 1 diabetes. In recently completed studies conducted by the Type 1 Diabetes Trial Network (TrialNet), repeated 2-hour Mixed Meal Tolerance Tests (MMTT) were obtained for up to 24 months from 156 subjects with up to 3 months duration of type 1 diabetes at the time of study enrollment. These data provide the information needed to more accurately determine the sample size needed for future studies of the effects of new agents on the 2-hour area under the curve (AUC) of the C-peptide values. The natural log(x), log(x+1) and square-root (√x) transformations of the AUC were assessed. In general, a transformation of the data is needed to better satisfy the normality assumptions for commonly used statistical tests. Statistical analysis of the raw and transformed data are provided to estimate the mean levels over time and the residual variation in untreated subjects that allow sample size calculations for future studies at either 12 or 24 months of follow-up and among children 8-12 years of age, adolescents (13-17 years) and adults (18+ years). The sample size needed to detect a given relative (percentage) difference with treatment versus control is greater at 24 months than at 12 months of follow-up, and differs among age categories. Owing to greater residual variation among those 13-17 years of age, a larger sample size is required for this age group. Methods are also described for assessment of sample size for mixtures of subjects among the age categories. Statistical expressions are presented for the presentation of analyses of log(x+1) and √x transformed values in terms of the original units of measurement (pmol/ml). Analyses using different transformations are described for the TrialNet study of masked anti-CD20 (rituximab) versus masked placebo. These results provide the information needed to accurately evaluate the sample size for studies of new agents to preserve C-peptide levels in newly diagnosed type 1 diabetes.

Methodological reporting of randomized clinical trials in respiratory research in 2010.

PubMed

Lu, Yi; Yao, Qiuju; Gu, Jie; Shen, Ce

2013-09-01

Although randomized controlled trials (RCTs) are considered the highest level of evidence, they are also subject to bias, due to a lack of adequately reported randomization, and therefore the reporting should be as explicit as possible for readers to determine the significance of the contents. We evaluated the methodological quality of RCTs in respiratory research in high ranking clinical journals, published in 2010. We assessed the methodological quality, including generation of the allocation sequence, allocation concealment, double-blinding, sample-size calculation, intention-to-treat analysis, flow diagrams, number of medical centers involved, diseases, funding sources, types of interventions, trial registration, number of times the papers have been cited, journal impact factor, journal type, and journal endorsement of the CONSORT (Consolidated Standards of Reporting Trials) rules, in RCTs published in 12 top ranking clinical respiratory journals and 5 top ranking general medical journals. We included 176 trials, of which 93 (53%) reported adequate generation of the allocation sequence, 66 (38%) reported adequate allocation concealment, 79 (45%) were double-blind, 123 (70%) reported adequate sample-size calculation, 88 (50%) reported intention-to-treat analysis, and 122 (69%) included a flow diagram. Multivariate logistic regression analysis revealed that journal impact factor ≥ 5 was the only variable that significantly influenced adequate allocation sequence generation. Trial registration and journal impact factor ≥ 5 significantly influenced adequate allocation concealment. Medical interventions, trial registration, and journal endorsement of the CONSORT statement influenced adequate double-blinding. Publication in one of the general medical journal influenced adequate sample-size calculation. The methodological quality of RCTs in respiratory research needs improvement. Stricter enforcement of the CONSORT statement should enhance the quality of RCTs.

The Influence of Experimental Design on the Detection of Performance Differences

ERIC Educational Resources Information Center

Bates, B. T.; Dufek, J. S.; James, C. R.; Harry, J. R.; Eggleston, J. D.

2016-01-01

We demonstrate the effect of sample and trial size on statistical outcomes for single-subject analyses (SSA) and group analyses (GA) for a frequently studied performance activity and common intervention. Fifty strides of walking data collected in two blocks of 25 trials for two shoe conditions were analyzed for samples of five, eight, 10, and 12…

Optimal design in pediatric pharmacokinetic and pharmacodynamic clinical studies.

PubMed

Roberts, Jessica K; Stockmann, Chris; Balch, Alfred; Yu, Tian; Ward, Robert M; Spigarelli, Michael G; Sherwin, Catherine M T

2015-03-01

It is not trivial to conduct clinical trials with pediatric participants. Ethical, logistical, and financial considerations add to the complexity of pediatric studies. Optimal design theory allows investigators the opportunity to apply mathematical optimization algorithms to define how to structure their data collection to answer focused research questions. These techniques can be used to determine an optimal sample size, optimal sample times, and the number of samples required for pharmacokinetic and pharmacodynamic studies. The aim of this review is to demonstrate how to determine optimal sample size, optimal sample times, and the number of samples required from each patient by presenting specific examples using optimal design tools. Additionally, this review aims to discuss the relative usefulness of sparse vs rich data. This review is intended to educate the clinician, as well as the basic research scientist, whom plan on conducting a pharmacokinetic/pharmacodynamic clinical trial in pediatric patients. © 2015 John Wiley & Sons Ltd.

GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic.

PubMed

Whitehead, John; Horby, Peter

2017-03-01

Conducting clinical trials to assess experimental treatments for potentially pandemic infectious diseases is challenging. Since many outbreaks of infectious diseases last only six to eight weeks, there is a need for trial designs that can be implemented rapidly in the face of uncertainty. Outbreaks are sudden and unpredictable and so it is essential that as much planning as possible takes place in advance. Statistical aspects of such trial designs should be evaluated and discussed in readiness for implementation. This paper proposes a generic ordinal sequential trial design (GOST) for a randomised clinical trial comparing an experimental treatment for an emerging infectious disease with standard care. The design is intended as an off-the-shelf, ready-to-use robust and flexible option. The primary endpoint is a categorisation of patient outcome according to an ordinal scale. A sequential approach is adopted, stopping as soon as it is clear that the experimental treatment has an advantage or that sufficient advantage is unlikely to be detected. The properties of the design are evaluated using large-sample theory and verified for moderate sized samples using simulation. The trial is powered to detect a generic clinically relevant difference: namely an odds ratio of 2 for better rather than worse outcomes. Total sample sizes (across both treatments) of between 150 and 300 patients prove to be adequate in many cases, but the precise value depends on both the magnitude of the treatment advantage and the nature of the ordinal scale. An advantage of the approach is that any erroneous assumptions made at the design stage about the proportion of patients falling into each outcome category have little effect on the error probabilities of the study, although they can lead to inaccurate forecasts of sample size. It is important and feasible to pre-determine many of the statistical aspects of an efficient trial design in advance of a disease outbreak. The design can then be tailored to the specific disease under study once its nature is better understood.

Statistical considerations in evaluating pharmacogenomics-based clinical effect for confirmatory trials.

PubMed

Wang, Sue-Jane; O'Neill, Robert T; Hung, Hm James

2010-10-01

The current practice for seeking genomically favorable patients in randomized controlled clinical trials using genomic convenience samples. To discuss the extent of imbalance, confounding, bias, design efficiency loss, type I error, and type II error that can occur in the evaluation of the convenience samples, particularly when they are small samples. To articulate statistical considerations for a reasonable sample size to minimize the chance of imbalance, and, to highlight the importance of replicating the subgroup finding in independent studies. Four case examples reflecting recent regulatory experiences are used to underscore the problems with convenience samples. Probability of imbalance for a pre-specified subgroup is provided to elucidate sample size needed to minimize the chance of imbalance. We use an example drug development to highlight the level of scientific rigor needed, with evidence replicated for a pre-specified subgroup claim. The convenience samples evaluated ranged from 18% to 38% of the intent-to-treat samples with sample size ranging from 100 to 5000 patients per arm. The baseline imbalance can occur with probability higher than 25%. Mild to moderate multiple confounders yielding the same directional bias in favor of the treated group can make treatment group incomparable at baseline and result in a false positive conclusion that there is a treatment difference. Conversely, if the same directional bias favors the placebo group or there is loss in design efficiency, the type II error can increase substantially. Pre-specification of a genomic subgroup hypothesis is useful only for some degree of type I error control. Complete ascertainment of genomic samples in a randomized controlled trial should be the first step to explore if a favorable genomic patient subgroup suggests a treatment effect when there is no clear prior knowledge and understanding about how the mechanism of a drug target affects the clinical outcome of interest. When stratified randomization based on genomic biomarker status cannot be implemented in designing a pharmacogenomics confirmatory clinical trial, if there is one genomic biomarker prognostic for clinical response, as a general rule of thumb, a sample size of at least 100 patients may be needed to be considered for the lower prevalence genomic subgroup to minimize the chance of an imbalance of 20% or more difference in the prevalence of the genomic marker. The sample size may need to be at least 150, 350, and 1350, respectively, if an imbalance of 15%, 10% and 5% difference is of concern.

Predicting and Tracking Short Term Disease Progression in Amnestic Mild Cognitive Impairment Patients with Prodromal Alzheimer's Disease: Structural Brain Biomarkers.

PubMed

Marizzoni, Moira; Ferrari, Clarissa; Jovicich, Jorge; Albani, Diego; Babiloni, Claudio; Cavaliere, Libera; Didic, Mira; Forloni, Gianluigi; Galluzzi, Samantha; Hoffmann, Karl-Titus; Molinuevo, José Luis; Nobili, Flavio; Parnetti, Lucilla; Payoux, Pierre; Ribaldi, Federica; Rossini, Paolo Maria; Schönknecht, Peter; Soricelli, Andrea; Hensch, Tilman; Tsolaki, Magda; Visser, Pieter Jelle; Wiltfang, Jens; Richardson, Jill C; Bordet, Régis; Blin, Olivier; Frisoni, Giovanni B

2018-06-09

Early Alzheimer's disease (AD) detection using cerebrospinal fluid (CSF) biomarkers has been recommended as enrichment strategy for trials involving mild cognitive impairment (MCI) patients. To model a prodromal AD trial for identifying MRI structural biomarkers to improve subject selection and to be used as surrogate outcomes of disease progression. APOE ɛ4 specific CSF Aβ42/P-tau cut-offs were used to identify MCI with prodromal AD (Aβ42/P-tau positive) in the WP5-PharmaCog (E-ADNI) cohort. Linear mixed models were performed 1) with baseline structural biomarker, time, and biomarker×time interaction as factors to predict longitudinal changes in ADAS-cog13, 2) with Aβ42/P-tau status, time, and Aβ42/P-tau status×time interaction as factors to explain the longitudinal changes in MRI measures, and 3) to compute sample size estimation for a trial implemented with the selected biomarkers. Only baseline lateral ventricle volume was able to identify a subgroup of prodromal AD patients who declined faster (interaction, p = 0.003). Lateral ventricle volume and medial temporal lobe measures were the biomarkers most sensitive to disease progression (interaction, p≤0.042). Enrichment through ventricular volume reduced the sample size that a clinical trial would require from 13 to 76%, depending on structural outcome variable. The biomarker needing the lowest sample size was the hippocampal subfield GC-ML-DG (granule cells of molecular layer of the dentate gyrus) (n = 82 per arm to demonstrate a 20% atrophy reduction). MRI structural biomarkers can enrich prodromal AD with fast progressors and significantly decrease group size in clinical trials of disease modifying drugs.

Efficient design and inference for multistage randomized trials of individualized treatment policies.

PubMed

Dawson, Ree; Lavori, Philip W

2012-01-01

Clinical demand for individualized "adaptive" treatment policies in diverse fields has spawned development of clinical trial methodology for their experimental evaluation via multistage designs, building upon methods intended for the analysis of naturalistically observed strategies. Because often there is no need to parametrically smooth multistage trial data (in contrast to observational data for adaptive strategies), it is possible to establish direct connections among different methodological approaches. We show by algebraic proof that the maximum likelihood (ML) and optimal semiparametric (SP) estimators of the population mean of the outcome of a treatment policy and its standard error are equal under certain experimental conditions. This result is used to develop a unified and efficient approach to design and inference for multistage trials of policies that adapt treatment according to discrete responses. We derive a sample size formula expressed in terms of a parametric version of the optimal SP population variance. Nonparametric (sample-based) ML estimation performed well in simulation studies, in terms of achieved power, for scenarios most likely to occur in real studies, even though sample sizes were based on the parametric formula. ML outperformed the SP estimator; differences in achieved power predominately reflected differences in their estimates of the population mean (rather than estimated standard errors). Neither methodology could mitigate the potential for overestimated sample sizes when strong nonlinearity was purposely simulated for certain discrete outcomes; however, such departures from linearity may not be an issue for many clinical contexts that make evaluation of competitive treatment policies meaningful.

Distribution of the two-sample t-test statistic following blinded sample size re-estimation.

PubMed

Lu, Kaifeng

2016-05-01

We consider the blinded sample size re-estimation based on the simple one-sample variance estimator at an interim analysis. We characterize the exact distribution of the standard two-sample t-test statistic at the final analysis. We describe a simulation algorithm for the evaluation of the probability of rejecting the null hypothesis at given treatment effect. We compare the blinded sample size re-estimation method with two unblinded methods with respect to the empirical type I error, the empirical power, and the empirical distribution of the standard deviation estimator and final sample size. We characterize the type I error inflation across the range of standardized non-inferiority margin for non-inferiority trials, and derive the adjusted significance level to ensure type I error control for given sample size of the internal pilot study. We show that the adjusted significance level increases as the sample size of the internal pilot study increases. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Directions for new developments on statistical design and analysis of small population group trials.

PubMed

Hilgers, Ralf-Dieter; Roes, Kit; Stallard, Nigel

2016-06-14

Most statistical design and analysis methods for clinical trials have been developed and evaluated where at least several hundreds of patients could be recruited. These methods may not be suitable to evaluate therapies if the sample size is unavoidably small, which is usually termed by small populations. The specific sample size cut off, where the standard methods fail, needs to be investigated. In this paper, the authors present their view on new developments for design and analysis of clinical trials in small population groups, where conventional statistical methods may be inappropriate, e.g., because of lack of power or poor adherence to asymptotic approximations due to sample size restrictions. Following the EMA/CHMP guideline on clinical trials in small populations, we consider directions for new developments in the area of statistical methodology for design and analysis of small population clinical trials. We relate the findings to the research activities of three projects, Asterix, IDeAl, and InSPiRe, which have received funding since 2013 within the FP7-HEALTH-2013-INNOVATION-1 framework of the EU. As not all aspects of the wide research area of small population clinical trials can be addressed, we focus on areas where we feel advances are needed and feasible. The general framework of the EMA/CHMP guideline on small population clinical trials stimulates a number of research areas. These serve as the basis for the three projects, Asterix, IDeAl, and InSPiRe, which use various approaches to develop new statistical methodology for design and analysis of small population clinical trials. Small population clinical trials refer to trials with a limited number of patients. Small populations may result form rare diseases or specific subtypes of more common diseases. New statistical methodology needs to be tailored to these specific situations. The main results from the three projects will constitute a useful toolbox for improved design and analysis of small population clinical trials. They address various challenges presented by the EMA/CHMP guideline as well as recent discussions about extrapolation. There is a need for involvement of the patients' perspective in the planning and conduct of small population clinical trials for a successful therapy evaluation.

Accounting for treatment by center interaction in sample size determinations and the use of surrogate outcomes in the pessary for the prevention of preterm birth trial: a simulation study.

PubMed

Willan, Andrew R

2016-07-05

The Pessary for the Prevention of Preterm Birth Study (PS3) is an international, multicenter, randomized clinical trial designed to examine the effectiveness of the Arabin pessary in preventing preterm birth in pregnant women with a short cervix. During the design of the study two methodological issues regarding power and sample size were raised. Since treatment in the Standard Arm will vary between centers, it is anticipated that so too will the probability of preterm birth in that arm. This will likely result in a treatment by center interaction, and the issue of how this will affect the sample size requirements was raised. The sample size requirements to examine the effect of the pessary on the baby's clinical outcome was prohibitively high, so the second issue is how best to examine the effect on clinical outcome. The approaches taken to address these issues are presented. Simulation and sensitivity analysis were used to address the sample size issue. The probability of preterm birth in the Standard Arm was assumed to vary between centers following a Beta distribution with a mean of 0.3 and a coefficient of variation of 0.3. To address the second issue a Bayesian decision model is proposed that combines the information regarding the between-treatment difference in the probability of preterm birth from PS3 with the data from the Multiple Courses of Antenatal Corticosteroids for Preterm Birth Study that relate preterm birth and perinatal mortality/morbidity. The approach provides a between-treatment comparison with respect to the probability of a bad clinical outcome. The performance of the approach was assessed using simulation and sensitivity analysis. Accounting for a possible treatment by center interaction increased the sample size from 540 to 700 patients per arm for the base case. The sample size requirements increase with the coefficient of variation and decrease with the number of centers. Under the same assumptions used for determining the sample size requirements, the simulated mean probability that pessary reduces the risk of perinatal mortality/morbidity is 0.98. The simulated mean decreased with coefficient of variation and increased with the number of clinical sites. Employing simulation and sensitivity analysis is a useful approach for determining sample size requirements while accounting for the additional uncertainty due to a treatment by center interaction. Using a surrogate outcome in conjunction with a Bayesian decision model is an efficient way to compare important clinical outcomes in a randomized clinical trial in situations where the direct approach requires a prohibitively high sample size.

Type-II generalized family-wise error rate formulas with application to sample size determination.

PubMed

Delorme, Phillipe; de Micheaux, Pierre Lafaye; Liquet, Benoit; Riou, Jérémie

2016-07-20

Multiple endpoints are increasingly used in clinical trials. The significance of some of these clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. The usual approach in multiple hypothesis testing is to control the family-wise error rate, which is defined as the probability that at least one type-I error is made. More recently, the q-generalized family-wise error rate has been introduced to control the probability of making at least q false rejections. For procedures controlling this global type-I error rate, we define a type-II r-generalized family-wise error rate, which is directly related to the r-power defined as the probability of rejecting at least r false null hypotheses. We obtain very general power formulas that can be used to compute the sample size for single-step and step-wise procedures. These are implemented in our R package rPowerSampleSize available on the CRAN, making them directly available to end users. Complexities of the formulas are presented to gain insight into computation time issues. Comparison with Monte Carlo strategy is also presented. We compute sample sizes for two clinical trials involving multiple endpoints: one designed to investigate the effectiveness of a drug against acute heart failure and the other for the immunogenicity of a vaccine strategy against pneumococcus. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Sample size re-estimation and other midcourse adjustments with sequential parallel comparison design.

PubMed

Silverman, Rachel K; Ivanova, Anastasia

2017-01-01

Sequential parallel comparison design (SPCD) was proposed to reduce placebo response in a randomized trial with placebo comparator. Subjects are randomized between placebo and drug in stage 1 of the trial, and then, placebo non-responders are re-randomized in stage 2. Efficacy analysis includes all data from stage 1 and all placebo non-responding subjects from stage 2. This article investigates the possibility to re-estimate the sample size and adjust the design parameters, allocation proportion to placebo in stage 1 of SPCD, and weight of stage 1 data in the overall efficacy test statistic during an interim analysis.

Sample size estimation for alternating logistic regressions analysis of multilevel randomized community trials of under-age drinking.

PubMed

Reboussin, Beth A; Preisser, John S; Song, Eun-Young; Wolfson, Mark

2012-07-01

Under-age drinking is an enormous public health issue in the USA. Evidence that community level structures may impact on under-age drinking has led to a proliferation of efforts to change the environment surrounding the use of alcohol. Although the focus of these efforts is to reduce drinking by individual youths, environmental interventions are typically implemented at the community level with entire communities randomized to the same intervention condition. A distinct feature of these trials is the tendency of the behaviours of individuals residing in the same community to be more alike than that of others residing in different communities, which is herein called 'clustering'. Statistical analyses and sample size calculations must account for this clustering to avoid type I errors and to ensure an appropriately powered trial. Clustering itself may also be of scientific interest. We consider the alternating logistic regressions procedure within the population-averaged modelling framework to estimate the effect of a law enforcement intervention on the prevalence of under-age drinking behaviours while modelling the clustering at multiple levels, e.g. within communities and within neighbourhoods nested within communities, by using pairwise odds ratios. We then derive sample size formulae for estimating intervention effects when planning a post-test-only or repeated cross-sectional community-randomized trial using the alternating logistic regressions procedure.

Methods for Specifying the Target Difference in a Randomised Controlled Trial: The Difference ELicitation in TriAls (DELTA) Systematic Review

PubMed Central

Hislop, Jenni; Adewuyi, Temitope E.; Vale, Luke D.; Harrild, Kirsten; Fraser, Cynthia; Gurung, Tara; Altman, Douglas G.; Briggs, Andrew H.; Fayers, Peter; Ramsay, Craig R.; Norrie, John D.; Harvey, Ian M.; Buckley, Brian; Cook, Jonathan A.

2014-01-01

Background Randomised controlled trials (RCTs) are widely accepted as the preferred study design for evaluating healthcare interventions. When the sample size is determined, a (target) difference is typically specified that the RCT is designed to detect. This provides reassurance that the study will be informative, i.e., should such a difference exist, it is likely to be detected with the required statistical precision. The aim of this review was to identify potential methods for specifying the target difference in an RCT sample size calculation. Methods and Findings A comprehensive systematic review of medical and non-medical literature was carried out for methods that could be used to specify the target difference for an RCT sample size calculation. The databases searched were MEDLINE, MEDLINE In-Process, EMBASE, the Cochrane Central Register of Controlled Trials, the Cochrane Methodology Register, PsycINFO, Science Citation Index, EconLit, the Education Resources Information Center (ERIC), and Scopus (for in-press publications); the search period was from 1966 or the earliest date covered, to between November 2010 and January 2011. Additionally, textbooks addressing the methodology of clinical trials and International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) tripartite guidelines for clinical trials were also consulted. A narrative synthesis of methods was produced. Studies that described a method that could be used for specifying an important and/or realistic difference were included. The search identified 11,485 potentially relevant articles from the databases searched. Of these, 1,434 were selected for full-text assessment, and a further nine were identified from other sources. Fifteen clinical trial textbooks and the ICH tripartite guidelines were also reviewed. In total, 777 studies were included, and within them, seven methods were identified—anchor, distribution, health economic, opinion-seeking, pilot study, review of the evidence base, and standardised effect size. Conclusions A variety of methods are available that researchers can use for specifying the target difference in an RCT sample size calculation. Appropriate methods may vary depending on the aim (e.g., specifying an important difference versus a realistic difference), context (e.g., research question and availability of data), and underlying framework adopted (e.g., Bayesian versus conventional statistical approach). Guidance on the use of each method is given. No single method provides a perfect solution for all contexts. Please see later in the article for the Editors' Summary PMID:24824338

A note on sample size calculation for mean comparisons based on noncentral t-statistics.

PubMed

Chow, Shein-Chung; Shao, Jun; Wang, Hansheng

2002-11-01

One-sample and two-sample t-tests are commonly used in analyzing data from clinical trials in comparing mean responses from two drug products. During the planning stage of a clinical study, a crucial step is the sample size calculation, i.e., the determination of the number of subjects (patients) needed to achieve a desired power (e.g., 80%) for detecting a clinically meaningful difference in the mean drug responses. Based on noncentral t-distributions, we derive some sample size calculation formulas for testing equality, testing therapeutic noninferiority/superiority, and testing therapeutic equivalence, under the popular one-sample design, two-sample parallel design, and two-sample crossover design. Useful tables are constructed and some examples are given for illustration.

Impact of non-uniform correlation structure on sample size and power in multiple-period cluster randomised trials.

PubMed

Kasza, J; Hemming, K; Hooper, R; Matthews, Jns; Forbes, A B

2017-01-01

Stepped wedge and cluster randomised crossover trials are examples of cluster randomised designs conducted over multiple time periods that are being used with increasing frequency in health research. Recent systematic reviews of both of these designs indicate that the within-cluster correlation is typically taken account of in the analysis of data using a random intercept mixed model, implying a constant correlation between any two individuals in the same cluster no matter how far apart in time they are measured: within-period and between-period intra-cluster correlations are assumed to be identical. Recently proposed extensions allow the within- and between-period intra-cluster correlations to differ, although these methods require that all between-period intra-cluster correlations are identical, which may not be appropriate in all situations. Motivated by a proposed intensive care cluster randomised trial, we propose an alternative correlation structure for repeated cross-sectional multiple-period cluster randomised trials in which the between-period intra-cluster correlation is allowed to decay depending on the distance between measurements. We present results for the variance of treatment effect estimators for varying amounts of decay, investigating the consequences of the variation in decay on sample size planning for stepped wedge, cluster crossover and multiple-period parallel-arm cluster randomised trials. We also investigate the impact of assuming constant between-period intra-cluster correlations instead of decaying between-period intra-cluster correlations. Our results indicate that in certain design configurations, including the one corresponding to the proposed trial, a correlation decay can have an important impact on variances of treatment effect estimators, and hence on sample size and power. An R Shiny app allows readers to interactively explore the impact of correlation decay.

Methodological quality of behavioural weight loss studies: a systematic review

PubMed Central

Lemon, S. C.; Wang, M. L.; Haughton, C. F.; Estabrook, D. P.; Frisard, C. F.; Pagoto, S. L.

2018-01-01

Summary This systematic review assessed the methodological quality of behavioural weight loss intervention studies conducted among adults and associations between quality and statistically significant weight loss outcome, strength of intervention effectiveness and sample size. Searches for trials published between January, 2009 and December, 2014 were conducted using PUBMED, MEDLINE and PSYCINFO and identified ninety studies. Methodological quality indicators included study design, anthropometric measurement approach, sample size calculations, intent-to-treat (ITT) analysis, loss to follow-up rate, missing data strategy, sampling strategy, report of treatment receipt and report of intervention fidelity (mean = 6.3). Indicators most commonly utilized included randomized design (100%), objectively measured anthropometrics (96.7%), ITT analysis (86.7%) and reporting treatment adherence (76.7%). Most studies (62.2%) had a follow-up rate >75% and reported a loss to follow-up analytic strategy or minimal missing data (69.9%). Describing intervention fidelity (34.4%) and sampling from a known population (41.1%) were least common. Methodological quality was not associated with reporting a statistically significant result, effect size or sample size. This review found the published literature of behavioural weight loss trials to be of high quality for specific indicators, including study design and measurement. Identified for improvement include utilization of more rigorous statistical approaches to loss to follow up and better fidelity reporting. PMID:27071775

Estimates of Intraclass Correlation Coefficients from Longitudinal Group-Randomized Trials of Adolescent HIV/STI/Pregnancy Prevention Programs

ERIC Educational Resources Information Center

Glassman, Jill R.; Potter, Susan C.; Baumler, Elizabeth R.; Coyle, Karin K.

2015-01-01

Introduction: Group-randomized trials (GRTs) are one of the most rigorous methods for evaluating the effectiveness of group-based health risk prevention programs. Efficiently designing GRTs with a sample size that is sufficient for meeting the trial's power and precision goals while not wasting resources exceeding them requires estimates of the…

The Importance and Role of Intracluster Correlations in Planning Cluster Trials

PubMed Central

Preisser, John S.; Reboussin, Beth A.; Song, Eun-Young; Wolfson, Mark

2008-01-01

There is increasing recognition of the critical role of intracluster correlations of health behavior outcomes in cluster intervention trials. This study examines the estimation, reporting, and use of intracluster correlations in planning cluster trials. We use an estimating equations approach to estimate the intracluster correlations corresponding to the multiple-time-point nested cross-sectional design. Sample size formulae incorporating 2 types of intracluster correlations are examined for the purpose of planning future trials. The traditional intracluster correlation is the correlation among individuals within the same community at a specific time point. A second type is the correlation among individuals within the same community at different time points. For a “time × condition” analysis of a pretest–posttest nested cross-sectional trial design, we show that statistical power considerations based upon a posttest-only design generally are not an adequate substitute for sample size calculations that incorporate both types of intracluster correlations. Estimation, reporting, and use of intracluster correlations are illustrated for several dichotomous measures related to underage drinking collected as part of a large nonrandomized trial to enforce underage drinking laws in the United States from 1998 to 2004. PMID:17879427

The size of a pilot study for a clinical trial should be calculated in relation to considerations of precision and efficiency.

PubMed

Sim, Julius; Lewis, Martyn

2012-03-01

To investigate methods to determine the size of a pilot study to inform a power calculation for a randomized controlled trial (RCT) using an interval/ratio outcome measure. Calculations based on confidence intervals (CIs) for the sample standard deviation (SD). Based on CIs for the sample SD, methods are demonstrated whereby (1) the observed SD can be adjusted to secure the desired level of statistical power in the main study with a specified level of confidence; (2) the sample for the main study, if calculated using the observed SD, can be adjusted, again to obtain the desired level of statistical power in the main study; (3) the power of the main study can be calculated for the situation in which the SD in the pilot study proves to be an underestimate of the true SD; and (4) an "efficient" pilot size can be determined to minimize the combined size of the pilot and main RCT. Trialists should calculate the appropriate size of a pilot study, just as they should the size of the main RCT, taking into account the twin needs to demonstrate efficiency in terms of recruitment and to produce precise estimates of treatment effect. Copyright © 2012 Elsevier Inc. All rights reserved.

The use of group sequential, information-based sample size re-estimation in the design of the PRIMO study of chronic kidney disease.

PubMed

Pritchett, Yili; Jemiai, Yannis; Chang, Yuchiao; Bhan, Ishir; Agarwal, Rajiv; Zoccali, Carmine; Wanner, Christoph; Lloyd-Jones, Donald; Cannata-Andía, Jorge B; Thompson, Taylor; Appelbaum, Evan; Audhya, Paul; Andress, Dennis; Zhang, Wuyan; Solomon, Scott; Manning, Warren J; Thadhani, Ravi

2011-04-01

Chronic kidney disease is associated with a marked increase in risk for left ventricular hypertrophy and cardiovascular mortality compared with the general population. Therapy with vitamin D receptor activators has been linked with reduced mortality in chronic kidney disease and an improvement in left ventricular hypertrophy in animal studies. PRIMO (Paricalcitol capsules benefits in Renal failure Induced cardia MOrbidity) is a multinational, multicenter randomized controlled trial to assess the effects of paricalcitol (a selective vitamin D receptor activator) on mild to moderate left ventricular hypertrophy in patients with chronic kidney disease. Subjects with mild-moderate chronic kidney disease are randomized to paricalcitol or placebo after confirming left ventricular hypertrophy using a cardiac echocardiogram. Cardiac magnetic resonance imaging is then used to assess left ventricular mass index at baseline, 24 and 48 weeks, which is the primary efficacy endpoint of the study. Because of limited prior data to estimate sample size, a maximum information group sequential design with sample size re-estimation is implemented to allow sample size adjustment based on the nuisance parameter estimated using the interim data. An interim efficacy analysis is planned at a pre-specified time point conditioned on the status of enrollment. The decision to increase sample size depends on the observed treatment effect. A repeated measures analysis model, using available data at Week 24 and 48 with a backup model of an ANCOVA analyzing change from baseline to the final nonmissing observation, are pre-specified to evaluate the treatment effect. Gamma-family of spending function is employed to control family-wise Type I error rate as stopping for success is planned in the interim efficacy analysis. If enrollment is slower than anticipated, the smaller sample size used in the interim efficacy analysis and the greater percent of missing week 48 data might decrease the parameter estimation accuracy, either for the nuisance parameter or for the treatment effect, which might in turn affect the interim decision-making. The application of combining a group sequential design with a sample-size re-estimation in clinical trial design has the potential to improve efficiency and to increase the probability of trial success while ensuring integrity of the study.

Using a business model approach and marketing techniques for recruitment to clinical trials

PubMed Central

2011-01-01

Randomised controlled trials (RCTs) are generally regarded as the gold standard for evaluating health care interventions. The level of uncertainty around a trial's estimate of effect is, however, frequently linked to how successful the trial has been in recruiting and retaining participants. As recruitment is often slower or more difficult than expected, with many trials failing to reach their target sample size within the timescale and funding originally envisaged, the results are often less reliable than they could have been. The high number of trials that require an extension to the recruitment period in order to reach the required sample size potentially delays the introduction of more effective therapies into routine clinical practice. Moreover, it may result in less research being undertaken as resources are redirected to extending existing trials rather than funding additional studies. Poor recruitment to publicly-funded RCTs has been much debated but there remains remarkably little clear evidence as to why many trials fail to recruit well, which recruitment methods work, in which populations and settings and for what type of intervention. One proposed solution to improving recruitment and retention is to adopt methodology from the business world to inform and structure trial management techniques. We review what is known about interventions to improve recruitment to trials. We describe a proposed business approach to trials and discuss the implementation of using a business model, using insights gained from three case studies. PMID:21396088

Using a business model approach and marketing techniques for recruitment to clinical trials.

PubMed

McDonald, Alison M; Treweek, Shaun; Shakur, Haleema; Free, Caroline; Knight, Rosemary; Speed, Chris; Campbell, Marion K

2011-03-11

Randomised controlled trials (RCTs) are generally regarded as the gold standard for evaluating health care interventions. The level of uncertainty around a trial's estimate of effect is, however, frequently linked to how successful the trial has been in recruiting and retaining participants. As recruitment is often slower or more difficult than expected, with many trials failing to reach their target sample size within the timescale and funding originally envisaged, the results are often less reliable than they could have been. The high number of trials that require an extension to the recruitment period in order to reach the required sample size potentially delays the introduction of more effective therapies into routine clinical practice. Moreover, it may result in less research being undertaken as resources are redirected to extending existing trials rather than funding additional studies.Poor recruitment to publicly-funded RCTs has been much debated but there remains remarkably little clear evidence as to why many trials fail to recruit well, which recruitment methods work, in which populations and settings and for what type of intervention. One proposed solution to improving recruitment and retention is to adopt methodology from the business world to inform and structure trial management techniques.We review what is known about interventions to improve recruitment to trials. We describe a proposed business approach to trials and discuss the implementation of using a business model, using insights gained from three case studies.

Testing non-inferiority of a new treatment in three-arm clinical trials with binary endpoints.

PubMed

Tang, Nian-Sheng; Yu, Bin; Tang, Man-Lai

2014-12-18

A two-arm non-inferiority trial without a placebo is usually adopted to demonstrate that an experimental treatment is not worse than a reference treatment by a small pre-specified non-inferiority margin due to ethical concerns. Selection of the non-inferiority margin and establishment of assay sensitivity are two major issues in the design, analysis and interpretation for two-arm non-inferiority trials. Alternatively, a three-arm non-inferiority clinical trial including a placebo is usually conducted to assess the assay sensitivity and internal validity of a trial. Recently, some large-sample approaches have been developed to assess the non-inferiority of a new treatment based on the three-arm trial design. However, these methods behave badly with small sample sizes in the three arms. This manuscript aims to develop some reliable small-sample methods to test three-arm non-inferiority. Saddlepoint approximation, exact and approximate unconditional, and bootstrap-resampling methods are developed to calculate p-values of the Wald-type, score and likelihood ratio tests. Simulation studies are conducted to evaluate their performance in terms of type I error rate and power. Our empirical results show that the saddlepoint approximation method generally behaves better than the asymptotic method based on the Wald-type test statistic. For small sample sizes, approximate unconditional and bootstrap-resampling methods based on the score test statistic perform better in the sense that their corresponding type I error rates are generally closer to the prespecified nominal level than those of other test procedures. Both approximate unconditional and bootstrap-resampling test procedures based on the score test statistic are generally recommended for three-arm non-inferiority trials with binary outcomes.

Methodological reporting of randomized trials in five leading Chinese nursing journals.

PubMed

Shi, Chunhu; Tian, Jinhui; Ren, Dan; Wei, Hongli; Zhang, Lihuan; Wang, Quan; Yang, Kehu

2014-01-01

Randomized controlled trials (RCTs) are not always well reported, especially in terms of their methodological descriptions. This study aimed to investigate the adherence of methodological reporting complying with CONSORT and explore associated trial level variables in the Chinese nursing care field. In June 2012, we identified RCTs published in five leading Chinese nursing journals and included trials with details of randomized methods. The quality of methodological reporting was measured through the methods section of the CONSORT checklist and the overall CONSORT methodological items score was calculated and expressed as a percentage. Meanwhile, we hypothesized that some general and methodological characteristics were associated with reporting quality and conducted a regression with these data to explore the correlation. The descriptive and regression statistics were calculated via SPSS 13.0. In total, 680 RCTs were included. The overall CONSORT methodological items score was 6.34 ± 0.97 (Mean ± SD). No RCT reported descriptions and changes in "trial design," changes in "outcomes" and "implementation," or descriptions of the similarity of interventions for "blinding." Poor reporting was found in detailing the "settings of participants" (13.1%), "type of randomization sequence generation" (1.8%), calculation methods of "sample size" (0.4%), explanation of any interim analyses and stopping guidelines for "sample size" (0.3%), "allocation concealment mechanism" (0.3%), additional analyses in "statistical methods" (2.1%), and targeted subjects and methods of "blinding" (5.9%). More than 50% of trials described randomization sequence generation, the eligibility criteria of "participants," "interventions," and definitions of the "outcomes" and "statistical methods." The regression analysis found that publication year and ITT analysis were weakly associated with CONSORT score. The completeness of methodological reporting of RCTs in the Chinese nursing care field is poor, especially with regard to the reporting of trial design, changes in outcomes, sample size calculation, allocation concealment, blinding, and statistical methods.

Designing group sequential randomized clinical trials with time to event end points using a R function.

PubMed

Filleron, Thomas; Gal, Jocelyn; Kramar, Andrew

2012-10-01

A major and difficult task is the design of clinical trials with a time to event endpoint. In fact, it is necessary to compute the number of events and in a second step the required number of patients. Several commercial software packages are available for computing sample size in clinical trials with sequential designs and time to event endpoints, but there are a few R functions implemented. The purpose of this paper is to describe features and use of the R function. plansurvct.func, which is an add-on function to the package gsDesign which permits in one run of the program to calculate the number of events, and required sample size but also boundaries and corresponding p-values for a group sequential design. The use of the function plansurvct.func is illustrated by several examples and validated using East software. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Clinical Trials of Potential Cognitive-Enhancing Drugs in Schizophrenia: What Have We Learned So Far?

PubMed Central

Keefe, Richard S. E.; Buchanan, Robert W.; Marder, Stephen R.; Schooler, Nina R.; Dugar, Ashish; Zivkov, Milana; Stewart, Michelle

2013-01-01

In light of the number of studies conducted to examine the treatment of cognitive impairment associated with schizophrenia (CIAS), we critically reviewed recent CIAS trials. Trials were identified through searches of the website “www.clinicaltrials.gov” using the terms “schizophrenia AND cognition,” “schizophrenia AND neurocognition,” “schizophrenia AND neurocognitive tests,” “schizophrenia AND MATRICS,” “schizophrenia AND MCCB,” “schizophrenia AND BACS,” “schizophrenia AND COGSTATE,” and “schizophrenia AND CANTAB” and “first-episode schizophrenia AND cognition.” The cutoff date was 20 April 2011. Included trials were conducted in people with schizophrenia, the effects on cognition were either a primary or secondary outcome, and the effect of a pharmacologically active substance was examined. Drug challenge, pharmacokinetic, pharmacodynamic, or prodrome of psychosis studies were excluded. We identified 118 trials, with 62% using an add-on parallel group design. The large majority of completed trials were underpowered to detect moderate effect sizes, had ≤8 weeks duration, and were performed in samples of participants with chronic stable schizophrenia. The ongoing add-on trials are longer, have larger sample sizes (with a number of them being adequately powered to detect moderate effect sizes), and are more likely to use a widely accepted standardized cognitive battery (eg, the MATRICS Consensus Cognitive Battery) and MATRICS guidelines. Ongoing studies performed in subjects with recent onset schizophrenia may help elucidate which subjects are most likely to show an effect in cognition. New insights into the demands of CIAS trial design and methodology may help increase the probability of identifying treatments with beneficial effect on cognitive impairment in schizophrenia. PMID:22114098

Testing homogeneity of proportion ratios for stratified correlated bilateral data in two-arm randomized clinical trials.

PubMed

Pei, Yanbo; Tian, Guo-Liang; Tang, Man-Lai

2014-11-10

Stratified data analysis is an important research topic in many biomedical studies and clinical trials. In this article, we develop five test statistics for testing the homogeneity of proportion ratios for stratified correlated bilateral binary data based on an equal correlation model assumption. Bootstrap procedures based on these test statistics are also considered. To evaluate the performance of these statistics and procedures, we conduct Monte Carlo simulations to study their empirical sizes and powers under various scenarios. Our results suggest that the procedure based on score statistic performs well generally and is highly recommended. When the sample size is large, procedures based on the commonly used weighted least square estimate and logarithmic transformation with Mantel-Haenszel estimate are recommended as they do not involve any computation of maximum likelihood estimates requiring iterative algorithms. We also derive approximate sample size formulas based on the recommended test procedures. Finally, we apply the proposed methods to analyze a multi-center randomized clinical trial for scleroderma patients. Copyright © 2014 John Wiley & Sons, Ltd.

Interim analysis: A rational approach of decision making in clinical trial.

PubMed

Kumar, Amal; Chakraborty, Bhaswat S

2016-01-01

Interim analysis of especially sizeable trials keeps the decision process free of conflict of interest while considering cost, resources, and meaningfulness of the project. Whenever necessary, such interim analysis can also call for potential termination or appropriate modification in sample size, study design, and even an early declaration of success. Given the extraordinary size and complexity today, this rational approach helps to analyze and predict the outcomes of a clinical trial that incorporate what is learned during the course of a study or a clinical development program. Such approach can also fill the gap by directing the resources toward relevant and optimized clinical trials between unmet medical needs and interventions being tested currently rather than fulfilling only business and profit goals.

A more powerful test based on ratio distribution for retention noninferiority hypothesis.

PubMed

Deng, Ling; Chen, Gang

2013-03-11

Rothmann et al. ( 2003 ) proposed a method for the statistical inference of fraction retention noninferiority (NI) hypothesis. A fraction retention hypothesis is defined as a ratio of the new treatment effect verse the control effect in the context of a time to event endpoint. One of the major concerns using this method in the design of an NI trial is that with a limited sample size, the power of the study is usually very low. This makes an NI trial not applicable particularly when using time to event endpoint. To improve power, Wang et al. ( 2006 ) proposed a ratio test based on asymptotic normality theory. Under a strong assumption (equal variance of the NI test statistic under null and alternative hypotheses), the sample size using Wang's test was much smaller than that using Rothmann's test. However, in practice, the assumption of equal variance is generally questionable for an NI trial design. This assumption is removed in the ratio test proposed in this article, which is derived directly from a Cauchy-like ratio distribution. In addition, using this method, the fundamental assumption used in Rothmann's test, that the observed control effect is always positive, that is, the observed hazard ratio for placebo over the control is greater than 1, is no longer necessary. Without assuming equal variance under null and alternative hypotheses, the sample size required for an NI trial can be significantly reduced if using the proposed ratio test for a fraction retention NI hypothesis.

Using pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategy.

PubMed

Laber, Eric B; Zhao, Ying-Qi; Regh, Todd; Davidian, Marie; Tsiatis, Anastasios; Stanford, Joseph B; Zeng, Donglin; Song, Rui; Kosorok, Michael R

2016-04-15

A personalized treatment strategy formalizes evidence-based treatment selection by mapping patient information to a recommended treatment. Personalized treatment strategies can produce better patient outcomes while reducing cost and treatment burden. Thus, among clinical and intervention scientists, there is a growing interest in conducting randomized clinical trials when one of the primary aims is estimation of a personalized treatment strategy. However, at present, there are no appropriate sample size formulae to assist in the design of such a trial. Furthermore, because the sampling distribution of the estimated outcome under an estimated optimal treatment strategy can be highly sensitive to small perturbations in the underlying generative model, sample size calculations based on standard (uncorrected) asymptotic approximations or computer simulations may not be reliable. We offer a simple and robust method for powering a single stage, two-armed randomized clinical trial when the primary aim is estimating the optimal single stage personalized treatment strategy. The proposed method is based on inverting a plugin projection confidence interval and is thereby regular and robust to small perturbations of the underlying generative model. The proposed method requires elicitation of two clinically meaningful parameters from clinical scientists and uses data from a small pilot study to estimate nuisance parameters, which are not easily elicited. The method performs well in simulated experiments and is illustrated using data from a pilot study of time to conception and fertility awareness. Copyright © 2015 John Wiley & Sons, Ltd.

Maximizing return on socioeconomic investment in phase II proof-of-concept trials.

PubMed

Chen, Cong; Beckman, Robert A

2014-04-01

Phase II proof-of-concept (POC) trials play a key role in oncology drug development, determining which therapeutic hypotheses will undergo definitive phase III testing according to predefined Go-No Go (GNG) criteria. The number of possible POC hypotheses likely far exceeds available public or private resources. We propose a design strategy for maximizing return on socioeconomic investment in phase II trials that obtains the greatest knowledge with the minimum patient exposure. We compare efficiency using the benefit-cost ratio, defined to be the risk-adjusted number of truly active drugs correctly identified for phase III development divided by the risk-adjusted total sample size in phase II and III development, for different POC trial sizes, powering schemes, and associated GNG criteria. It is most cost-effective to conduct small POC trials and set the corresponding GNG bars high, so that more POC trials can be conducted under socioeconomic constraints. If δ is the minimum treatment effect size of clinical interest in phase II, the study design with the highest benefit-cost ratio has approximately 5% type I error rate and approximately 20% type II error rate (80% power) for detecting an effect size of approximately 1.5δ. A Go decision to phase III is made when the observed effect size is close to δ. With the phenomenal expansion of our knowledge in molecular biology leading to an unprecedented number of new oncology drug targets, conducting more small POC trials and setting high GNG bars maximize the return on socioeconomic investment in phase II POC trials. ©2014 AACR.

Survival distributions impact the power of randomized placebo-phase design and parallel groups randomized clinical trials.

PubMed

Abrahamyan, Lusine; Li, Chuan Silvia; Beyene, Joseph; Willan, Andrew R; Feldman, Brian M

2011-03-01

The study evaluated the power of the randomized placebo-phase design (RPPD)-a new design of randomized clinical trials (RCTs), compared with the traditional parallel groups design, assuming various response time distributions. In the RPPD, at some point, all subjects receive the experimental therapy, and the exposure to placebo is for only a short fixed period of time. For the study, an object-oriented simulation program was written in R. The power of the simulated trials was evaluated using six scenarios, where the treatment response times followed the exponential, Weibull, or lognormal distributions. The median response time was assumed to be 355 days for the placebo and 42 days for the experimental drug. Based on the simulation results, the sample size requirements to achieve the same level of power were different under different response time to treatment distributions. The scenario where the response times followed the exponential distribution had the highest sample size requirement. In most scenarios, the parallel groups RCT had higher power compared with the RPPD. The sample size requirement varies depending on the underlying hazard distribution. The RPPD requires more subjects to achieve a similar power to the parallel groups design. Copyright © 2011 Elsevier Inc. All rights reserved.

Use of methods for specifying the target difference in randomised controlled trial sample size calculations: Two surveys of trialists' practice.

PubMed

Cook, Jonathan A; Hislop, Jennifer M; Altman, Doug G; Briggs, Andrew H; Fayers, Peter M; Norrie, John D; Ramsay, Craig R; Harvey, Ian M; Vale, Luke D

2014-06-01

Central to the design of a randomised controlled trial (RCT) is a calculation of the number of participants needed. This is typically achieved by specifying a target difference, which enables the trial to identify a difference of a particular magnitude should one exist. Seven methods have been proposed for formally determining what the target difference should be. However, in practice, it may be driven by convenience or some other informal basis. It is unclear how aware the trialist community is of these formal methods or whether they are used. To determine current practice regarding the specification of the target difference by surveying trialists. Two surveys were conducted: (1) Members of the Society for Clinical Trials (SCT): participants were invited to complete an online survey through the society's email distribution list. Respondents were asked about their awareness, use of, and willingness to recommend methods; (2) Leading UK- and Ireland-based trialists: the survey was sent to UK Clinical Research Collaboration registered Clinical Trials Units, Medical Research Council UK Hubs for Trial Methodology Research, and the Research Design Services of the National Institute for Health Research. This survey also included questions about the most recent trial developed by the respondent's group. Survey 1: Of the 1182 members on the SCT membership email distribution list, 180 responses were received (15%). Awareness of methods ranged from 69 (38%) for health economic methods to 162 (90%) for pilot study. Willingness to recommend among those who had used a particular method ranged from 56% for the opinion-seeking method to 89% for the review of evidence-base method. Survey 2: Of the 61 surveys sent out, 34 (56%) responses were received. Awareness of methods ranged from 33 (97%) for the review of evidence-base and pilot methods to 14 (41%) for the distribution method. The highest level of willingness to recommend among users was for the anchor method (87%). Based upon the most recent trial, the target difference was usually one viewed as important by a stakeholder group, mostly also viewed as a realistic difference given the interventions under evaluation, and sometimes one that led to an achievable sample size. The response rates achieved were relatively low despite the surveys being short, well presented, and having utilised reminders. Substantial variations in practice exist with awareness, use, and willingness to recommend methods varying substantially. The findings support the view that sample size calculation is a more complex process than would appear to be the case from trial reports and protocols. Guidance on approaches for sample size estimation may increase both awareness and use of appropriate formal methods. © The Author(s), 2014.

Baseline Characteristics and Generalizability of Participants in an Internet Smoking Cessation Randomized Trial

PubMed Central

Cha, Sarah; Erar, Bahar; Niaura, Raymond S.; Graham, Amanda L.

2016-01-01

Background The potential for sampling bias in Internet smoking cessation studies is widely recognized. However, few studies have explicitly addressed the issue of sample representativeness in the context of an Internet smoking cessation treatment trial. Purpose To examine the generalizability of participants enrolled in a randomized controlled trial of an Internet smoking cessation intervention using weighted data from the National Health Interview Survey (NHIS). Methods A total of 5,290 new users on a smoking cessation website enrolled in the trial between March 2012–January 2015. Descriptive statistics summarized baseline characteristics of screened and enrolled participants and multivariate analysis examined predictors of enrollment. Generalizability analyses compared demographic and smoking characteristics of trial participants to current smokers in the 2012–2014 waves of NHIS (n=19,043), and to an NHIS subgroup based on Internet use and cessation behavior (n=3,664). Effect sizes were obtained to evaluate the magnitude of differences across variables. Results Predictors of study enrollment were age, gender, race, education, and motivation to quit. Compared to NHIS smokers, trial participants were more likely to be female, college educated, daily smokers, and to have made a quit attempt in the past year (all effect sizes 0.25–0.60). In comparisons with the NHIS subgroup, differences in gender and education were attenuated while differences in daily smoking and smoking rate were amplified. Conclusions Few differences emerged between Internet trial participants and nationally representative samples of smokers, and all were in expected directions. This study highlights the importance of assessing generalizability in a focused and specific manner. PMID:27283295

Baseline Characteristics and Generalizability of Participants in an Internet Smoking Cessation Randomized Trial.

PubMed

Cha, Sarah; Erar, Bahar; Niaura, Raymond S; Graham, Amanda L

2016-10-01

The potential for sampling bias in Internet smoking cessation studies is widely recognized. However, few studies have explicitly addressed the issue of sample representativeness in the context of an Internet smoking cessation treatment trial. The purpose of the present study is to examine the generalizability of participants enrolled in a randomized controlled trial of an Internet smoking cessation intervention using weighted data from the National Health Interview Survey (NHIS). A total of 5290 new users on a smoking cessation website enrolled in the trial between March 2012 and January 2015. Descriptive statistics summarized baseline characteristics of screened and enrolled participants, and multivariate analysis examined predictors of enrollment. Generalizability analyses compared demographic and smoking characteristics of trial participants to current smokers in the 2012-2014 waves of NHIS (n = 19,043) and to an NHIS subgroup based on Internet use and cessation behavior (n = 3664). Effect sizes were obtained to evaluate the magnitude of differences across variables. Predictors of study enrollment were age, gender, race, education, and motivation to quit. Compared to NHIS smokers, trial participants were more likely to be female, college educated, and daily smokers and to have made a quit attempt in the past year (all effect sizes 0.25-0.60). In comparisons with the NHIS subgroup, differences in gender and education were attenuated, while differences in daily smoking and smoking rate were amplified. Few differences emerged between Internet trial participants and nationally representative samples of smokers, and all were in expected directions. This study highlights the importance of assessing generalizability in a focused and specific manner. CLINICALTRIALS.GOV: #NCT01544153.

Rethinking non-inferiority: a practical trial design for optimising treatment duration.

PubMed

Quartagno, Matteo; Walker, A Sarah; Carpenter, James R; Phillips, Patrick Pj; Parmar, Mahesh Kb

2018-06-01

Background Trials to identify the minimal effective treatment duration are needed in different therapeutic areas, including bacterial infections, tuberculosis and hepatitis C. However, standard non-inferiority designs have several limitations, including arbitrariness of non-inferiority margins, choice of research arms and very large sample sizes. Methods We recast the problem of finding an appropriate non-inferior treatment duration in terms of modelling the entire duration-response curve within a pre-specified range. We propose a multi-arm randomised trial design, allocating patients to different treatment durations. We use fractional polynomials and spline-based methods to flexibly model the duration-response curve. We call this a 'Durations design'. We compare different methods in terms of a scaled version of the area between true and estimated prediction curves. We evaluate sensitivity to key design parameters, including sample size, number and position of arms. Results A total sample size of ~ 500 patients divided into a moderate number of equidistant arms (5-7) is sufficient to estimate the duration-response curve within a 5% error margin in 95% of the simulations. Fractional polynomials provide similar or better results than spline-based methods in most scenarios. Conclusion Our proposed practical randomised trial 'Durations design' shows promising performance in the estimation of the duration-response curve; subject to a pending careful investigation of its inferential properties, it provides a potential alternative to standard non-inferiority designs, avoiding many of their limitations, and yet being fairly robust to different possible duration-response curves. The trial outcome is the whole duration-response curve, which may be used by clinicians and policymakers to make informed decisions, facilitating a move away from a forced binary hypothesis testing paradigm.

A community trial of the impact of improved sexually transmitted disease treatment on the HIV epidemic in rural Tanzania: 2. Baseline survey results.

PubMed

Grosskurth, H; Mosha, F; Todd, J; Senkoro, K; Newell, J; Klokke, A; Changalucha, J; West, B; Mayaud, P; Gavyole, A

1995-08-01

To determine baseline HIV prevalence in a trial of improved sexually transmitted disease (STD) treatment, and to investigate risk factors for HIV. To assess comparability of intervention and comparison communities with respect to HIV/STD prevalence and risk factors. To assess adequacy of sample size. Twelve communities in Mwanza Region, Tanzania: one matched pair of roadside communities, four pairs of rural communities, and one pair of island communities. One community from each pair was randomly allocated to receive the STD intervention following the baseline survey. Approximately 1000 adults aged 15-54 years were randomly sampled from each community. Subjects were interviewed, and HIV and syphilis serology performed. Men with a positive leucocyte esterase dipstick test on urine, or reporting a current STD, were tested for urethral infections. A total of 12,534 adults were enrolled. Baseline HIV prevalences were 7.7% (roadside), 3.8% (rural) and 1.8% (islands). Associations were observed with marital status, injections, education, travel, history of STD and syphilis serology. Prevalence was higher in circumcised men, but not significantly after adjusting for confounders. Intervention and comparison communities were similar in the prevalence of HIV (3.8 versus 4.4%), active syphilis (8.7 versus 8.2%), and most recorded risk factors. Within-pair variability in HIV prevalence was close to the value assumed for sample size calculations. The trial cohort was successfully established. Comparability of intervention and comparison communities at baseline was confirmed for most factors. Matching appears to have achieved a trial of adequate sample size. The apparent lack of a protective effect of male circumcision contrasts with other studies in Africa.

Evaluation of a multi-arm multi-stage Bayesian design for phase II drug selection trials - an example in hemato-oncology.

PubMed

Jacob, Louis; Uvarova, Maria; Boulet, Sandrine; Begaj, Inva; Chevret, Sylvie

2016-06-02

Multi-Arm Multi-Stage designs aim at comparing several new treatments to a common reference, in order to select or drop any treatment arm to move forward when such evidence already exists based on interim analyses. We redesigned a Bayesian adaptive design initially proposed for dose-finding, focusing our interest in the comparison of multiple experimental drugs to a control on a binary criterion measure. We redesigned a phase II clinical trial that randomly allocates patients across three (one control and two experimental) treatment arms to assess dropping decision rules. We were interested in dropping any arm due to futility, either based on historical control rate (first rule) or comparison across arms (second rule), and in stopping experimental arm due to its ability to reach a sufficient response rate (third rule), using the difference of response probabilities in Bayes binomial trials between the treated and control as a measure of treatment benefit. Simulations were then conducted to investigate the decision operating characteristics under a variety of plausible scenarios, as a function of the decision thresholds. Our findings suggest that one experimental treatment was less efficient than the control and could have been dropped from the trial based on a sample of approximately 20 instead of 40 patients. In the simulation study, stopping decisions were reached sooner for the first rule than for the second rule, with close mean estimates of response rates and small bias. According to the decision threshold, the mean sample size to detect the required 0.15 absolute benefit ranged from 63 to 70 (rule 3) with false negative rates of less than 2 % (rule 1) up to 6 % (rule 2). In contrast, detecting a 0.15 inferiority in response rates required a sample size ranging on average from 23 to 35 (rules 1 and 2, respectively) with a false positive rate ranging from 3.6 to 0.6 % (rule 3). Adaptive trial design is a good way to improve clinical trials. It allows removing ineffective drugs and reducing the trial sample size, while maintaining unbiased estimates. Decision thresholds can be set according to predefined fixed error decision rates. ClinicalTrials.gov Identifier: NCT01342692 .

Using historical control information for the design and analysis of clinical trials with overdispersed count data.

PubMed

Gsteiger, Sandro; Neuenschwander, Beat; Mercier, Francois; Schmidli, Heinz

2013-09-20

Results from clinical trials are never interpreted in isolation. Previous studies in a similar setting provide valuable information for designing a new trial. For the analysis, however, the use of trial-external information is challenging and therefore controversial, although it seems attractive from an ethical or efficiency perspective. Here, we consider the formal use of historical control data on lesion counts in a multiple sclerosis trial. The approach to incorporating historical data is Bayesian, in that historical information is captured in a prior that accounts for between-trial variability and hence leads to discounting of historical data. We extend the meta-analytic-predictive approach, a random-effects meta-analysis of historical data combined with the prediction of the parameter in the new trial, from normal to overdispersed count data of individual-patient or aggregate-trial format. We discuss the prior derivation for the lesion mean count in the control group of the new trial for two populations. For the general population (without baseline enrichment), with 1936 control patients from nine historical trials, between-trial variability was moderate to substantial, leading to a prior effective sample size of about 45 control patients. For the more homogenous population (with enrichment), with 412 control patients from five historical trials, the prior effective sample size was approximately 63 patients. Although these numbers are small relative to the historical data, they are fairly typical in settings where between-trial heterogeneity is moderate. For phase II, reducing the number of control patients by 45 or by 63 may be an attractive option in many multiple sclerosis trials. Copyright © 2013 John Wiley & Sons, Ltd.

Using re-randomization to increase the recruitment rate in clinical trials - an assessment of three clinical areas.

PubMed

Kahan, Brennan C

2016-12-13

Patient recruitment in clinical trials is often challenging, and as a result, many trials are stopped early due to insufficient recruitment. The re-randomization design allows patients to be re-enrolled and re-randomized for each new treatment episode that they experience. Because it allows multiple enrollments for each patient, this design has been proposed as a way to increase the recruitment rate in clinical trials. However, it is unknown to what extent recruitment could be increased in practice. We modelled the expected recruitment rate for parallel-group and re-randomization trials in different settings based on estimates from real trials and datasets. We considered three clinical areas: in vitro fertilization, severe asthma exacerbations, and acute sickle cell pain crises. We compared the two designs in terms of the expected time to complete recruitment, and the sample size recruited over a fixed recruitment period. Across the different scenarios we considered, we estimated that re-randomization could reduce the expected time to complete recruitment by between 4 and 22 months (relative reductions of 19% and 45%), or increase the sample size recruited over a fixed recruitment period by between 29% and 171%. Re-randomization can increase recruitment most for trials with a short follow-up period, a long trial recruitment duration, and patients with high rates of treatment episodes. Re-randomization has the potential to increase the recruitment rate in certain settings, and could lead to quicker and more efficient trials in these scenarios.

Bayesian selective response-adaptive design using the historical control.

PubMed

Kim, Mi-Ok; Harun, Nusrat; Liu, Chunyan; Khoury, Jane C; Broderick, Joseph P

2018-06-13

High quality historical control data, if incorporated, may reduce sample size, trial cost, and duration. A too optimistic use of the data, however, may result in bias under prior-data conflict. Motivated by well-publicized two-arm comparative trials in stroke, we propose a Bayesian design that both adaptively incorporates historical control data and selectively adapt the treatment allocation ratios within an ongoing trial responsively to the relative treatment effects. The proposed design differs from existing designs that borrow from historical controls. As opposed to reducing the number of subjects assigned to the control arm blindly, this design does so adaptively to the relative treatment effects only if evaluation of cumulated current trial data combined with the historical control suggests the superiority of the intervention arm. We used the effective historical sample size approach to quantify borrowed information on the control arm and modified the treatment allocation rules of the doubly adaptive biased coin design to incorporate the quantity. The modified allocation rules were then implemented under the Bayesian framework with commensurate priors addressing prior-data conflict. Trials were also more frequently concluded earlier in line with the underlying truth, reducing trial cost, and duration and yielded parameter estimates with smaller standard errors. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons, Ltd.

Leveraging prior quantitative knowledge in guiding pediatric drug development: a case study.

PubMed

Jadhav, Pravin R; Zhang, Jialu; Gobburu, Jogarao V S

2009-01-01

The manuscript presents the FDA's focus on leveraging prior knowledge in designing informative pediatric trial through this case study. In developing written request for Drug X, an anti-hypertensive for immediate blood pressure (BP) control, the sponsor and FDA conducted clinical trial simulations (CTS) to design trial with proper sample size and support the choice of dose range. The objective was to effectively use prior knowledge from adult patients for drug X, pediatric data from Corlopam (approved for a similar indication) trial and general experience in developing anti-hypertensive agents. Different scenarios governing the exposure response relationship in the pediatric population were simulated to perturb model assumptions. The choice of scenarios was based on the past observation that pediatric population is less responsive and sensitive compared with adults. The conceptual framework presented here should serve as an example on how the industry and FDA scientists can collaborate in designing the pediatric exclusivity trial. Using CTS, inter-disciplinary scientists with the sponsor and FDA can objectively discuss the choice of dose range, sample size, endpoints and other design elements. These efforts are believed to yield plausible trial design, qrational dosing recommendations and useful labeling information in pediatrics. Published in 2009 by John Wiley & Sons, Ltd.

Real-time dynamic modelling for the design of a cluster-randomized phase 3 Ebola vaccine trial in Sierra Leone.

PubMed

Camacho, A; Eggo, R M; Goeyvaerts, N; Vandebosch, A; Mogg, R; Funk, S; Kucharski, A J; Watson, C H; Vangeneugden, T; Edmunds, W J

2017-01-23

Declining incidence and spatial heterogeneity complicated the design of phase 3 Ebola vaccine trials during the tail of the 2013-16 Ebola virus disease (EVD) epidemic in West Africa. Mathematical models can provide forecasts of expected incidence through time and can account for both vaccine efficacy in participants and effectiveness in populations. Determining expected disease incidence was critical to calculating power and determining trial sample size. In real-time, we fitted, forecasted, and simulated a proposed phase 3 cluster-randomized vaccine trial for a prime-boost EVD vaccine in three candidate regions in Sierra Leone. The aim was to forecast trial feasibility in these areas through time and guide study design planning. EVD incidence was highly variable during the epidemic, especially in the declining phase. Delays in trial start date were expected to greatly reduce the ability to discern an effect, particularly as a trial with an effective vaccine would cause the epidemic to go extinct more quickly in the vaccine arm. Real-time updates of the model allowed decision-makers to determine how trial feasibility changed with time. This analysis was useful for vaccine trial planning because we simulated effectiveness as well as efficacy, which is possible with a dynamic transmission model. It contributed to decisions on choice of trial location and feasibility of the trial. Transmission models should be utilised as early as possible in the design process to provide mechanistic estimates of expected incidence, with which decisions about sample size, location, timing, and feasibility can be determined. Copyright © 2016. Published by Elsevier Ltd.

New approaches to trials in glomerulonephritis.

PubMed

Craig, Jonathan C; Tong, Allison; Strippoli, Giovanni F M

2017-01-01

Randomized controlled trials are required to reliably identify interventions to improve the outcomes for people with glomerulonephritis (GN). Unfortunately, although easier, observational studies are inherently unreliable even though the findings of both study designs agree most of the time. Currently there are ∼790 trials in GN, but suboptimal design and reporting, together with small sample sizes, mean that they may not be reliable for decision making. If the history is somewhat bleak, the future looks bright, with recent initiatives to improve the quality, size and relevance of clinical trials in nephrology, including greater patient engagement, trial networks, core outcome sets, registry-based trials and adaptive designs. Given the current state of the evidence informing the care of people with GN, disruptive technologies and pervasive culture change is required to ensure that the potential of trials to improve the health of people with this complex condition is to be realized. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Selecting promising treatments in randomized Phase II cancer trials with an active control.

PubMed

Cheung, Ying Kuen

2009-01-01

The primary objective of Phase II cancer trials is to evaluate the potential efficacy of a new regimen in terms of its antitumor activity in a given type of cancer. Due to advances in oncology therapeutics and heterogeneity in the patient population, such evaluation can be interpreted objectively only in the presence of a prospective control group of an active standard treatment. This paper deals with the design problem of Phase II selection trials in which several experimental regimens are compared to an active control, with an objective to identify an experimental arm that is more effective than the control or to declare futility if no such treatment exists. Conducting a multi-arm randomized selection trial is a useful strategy to prioritize experimental treatments for further testing when many candidates are available, but the sample size required in such a trial with an active control could raise feasibility concerns. In this study, we extend the sequential probability ratio test for normal observations to the multi-arm selection setting. The proposed methods, allowing frequent interim monitoring, offer high likelihood of early trial termination, and as such enhance enrollment feasibility. The termination and selection criteria have closed form solutions and are easy to compute with respect to any given set of error constraints. The proposed methods are applied to design a selection trial in which combinations of sorafenib and erlotinib are compared to a control group in patients with non-small-cell lung cancer using a continuous endpoint of change in tumor size. The operating characteristics of the proposed methods are compared to that of a single-stage design via simulations: The sample size requirement is reduced substantially and is feasible at an early stage of drug development.

Design of pilot studies to inform the construction of composite outcome measures.

PubMed

Edland, Steven D; Ard, M Colin; Li, Weiwei; Jiang, Lingjing

2017-06-01

Composite scales have recently been proposed as outcome measures for clinical trials. For example, the Prodromal Alzheimer's Cognitive Composite (PACC) is the sum of z-score normed component measures assessing episodic memory, timed executive function, and global cognition. Alternative methods of calculating composite total scores using the weighted sum of the component measures that maximize signal-to-noise of the resulting composite score have been proposed. Optimal weights can be estimated from pilot data, but it is an open question how large a pilot trial is required to calculate reliably optimal weights. In this manuscript, we describe the calculation of optimal weights, and use large-scale computer simulations to investigate the question of how large a pilot study sample is required to inform the calculation of optimal weights. The simulations are informed by the pattern of decline observed in cognitively normal subjects enrolled in the Alzheimer's Disease Cooperative Study (ADCS) Prevention Instrument cohort study, restricting to n=75 subjects age 75 and over with an ApoE E4 risk allele and therefore likely to have an underlying Alzheimer neurodegenerative process. In the context of secondary prevention trials in Alzheimer's disease, and using the components of the PACC, we found that pilot studies as small as 100 are sufficient to meaningfully inform weighting parameters. Regardless of the pilot study sample size used to inform weights, the optimally weighted PACC consistently outperformed the standard PACC in terms of statistical power to detect treatment effects in a clinical trial. Pilot studies of size 300 produced weights that achieved near-optimal statistical power, and reduced required sample size relative to the standard PACC by more than half. These simulations suggest that modestly sized pilot studies, comparable to that of a phase 2 clinical trial, are sufficient to inform the construction of composite outcome measures. Although these findings apply only to the PACC in the context of prodromal AD, the observation that weights only have to approximate the optimal weights to achieve near-optimal performance should generalize. Performing a pilot study or phase 2 trial to inform the weighting of proposed composite outcome measures is highly cost-effective. The net effect of more efficient outcome measures is that smaller trials will be required to test novel treatments. Alternatively, second generation trials can use prior clinical trial data to inform weighting, so that greater efficiency can be achieved as we move forward.

Auditory proactive interference in monkeys: The role of stimulus set size and intertrial interval

PubMed Central

Bigelow, James; Poremba, Amy

2013-01-01

We conducted two experiments to examine the influence of stimulus set size (the number of stimuli that are used throughout the session) and intertrial interval (ITI, the elapsed time between trials) in auditory short-term memory in monkeys. We used an auditory delayed matching-to-sample task wherein the animals had to indicate whether two sounds separated by a 5-s retention interval were the same (match trials) or different (non-match trials). In Experiment 1, we randomly assigned a stimulus set size of 2, 4, 8, 16, 32, 64, or 192 (trial unique) for each session of 128 trials. Consistent with previous visual studies, overall accuracy was consistently lower when smaller stimulus set sizes were used. Further analyses revealed that these effects were primarily caused by an increase in incorrect “same” responses on non-match trials. In Experiment 2, we held the stimulus set size constant at four for each session and alternately set the ITI at 5, 10, or 20 s. Overall accuracy improved by increasing the ITI from 5 to 10 s, but the 10 and 20 s conditions were the same. As in Experiment 1, the overall decrease in accuracy during the 5-s condition was caused by a greater number of false “match” responses on non-match trials. Taken together, Experiments 1 and 2 show that auditory short-term memory in monkeys is highly susceptible to PI caused by stimulus repetition. Additional analyses from Experiment 1 suggest that monkeys may make same/different judgments based on a familiarity criterion that is adjusted by error-related feedback. PMID:23526232

Functional Genomics in the Study of Mind-Body Therapies

PubMed Central

Niles, Halsey; Mehta, Darshan H.; Corrigan, Alexandra A.; Bhasin, Manoj K.; Denninger, John W.

2014-01-01

Background Mind-body therapies (MBTs) are used throughout the world in treatment, disease prevention, and health promotion. However, the mechanisms by which MBTs exert their positive effects are not well understood. Investigations into MBTs using functional genomics have revolutionized the understanding of MBT mechanisms and their effects on human physiology. Methods We searched the literature for the effects of MBTs on functional genomics determinants using MEDLINE, supplemented by a manual search of additional journals and a reference list review. Results We reviewed 15 trials that measured global or targeted transcriptomic, epigenomic, or proteomic changes in peripheral blood. Sample sizes ranged from small pilot studies (n=2) to large trials (n=500). While the reliability of individual genes from trial to trial was often inconsistent, genes related to inflammatory response, particularly those involved in the nuclear factor-kappa B (NF-κB) pathway, were consistently downregulated across most studies. Conclusion In general, existing trials focusing on gene expression changes brought about by MBTs have revealed intriguing connections to the immune system through the NF-κB cascade, to telomere maintenance, and to apoptotic regulation. However, these findings are limited to a small number of trials and relatively small sample sizes. More rigorous randomized controlled trials of healthy subjects and specific disease states are warranted. Future research should investigate functional genomics areas both upstream and downstream of MBT-related gene expression changes—from epigenomics to proteomics and metabolomics. PMID:25598735

Functional genomics in the study of mind-body therapies.

PubMed

Niles, Halsey; Mehta, Darshan H; Corrigan, Alexandra A; Bhasin, Manoj K; Denninger, John W

2014-01-01

Mind-body therapies (MBTs) are used throughout the world in treatment, disease prevention, and health promotion. However, the mechanisms by which MBTs exert their positive effects are not well understood. Investigations into MBTs using functional genomics have revolutionized the understanding of MBT mechanisms and their effects on human physiology. We searched the literature for the effects of MBTs on functional genomics determinants using MEDLINE, supplemented by a manual search of additional journals and a reference list review. We reviewed 15 trials that measured global or targeted transcriptomic, epigenomic, or proteomic changes in peripheral blood. Sample sizes ranged from small pilot studies (n=2) to large trials (n=500). While the reliability of individual genes from trial to trial was often inconsistent, genes related to inflammatory response, particularly those involved in the nuclear factor-kappa B (NF-κB) pathway, were consistently downregulated across most studies. In general, existing trials focusing on gene expression changes brought about by MBTs have revealed intriguing connections to the immune system through the NF-κB cascade, to telomere maintenance, and to apoptotic regulation. However, these findings are limited to a small number of trials and relatively small sample sizes. More rigorous randomized controlled trials of healthy subjects and specific disease states are warranted. Future research should investigate functional genomics areas both upstream and downstream of MBT-related gene expression changes-from epigenomics to proteomics and metabolomics.

Assessing methods to specify the target difference for a randomised controlled trial: DELTA (Difference ELicitation in TriAls) review.

PubMed

Cook, Jonathan A; Hislop, Jennifer; Adewuyi, Temitope E; Harrild, Kirsten; Altman, Douglas G; Ramsay, Craig R; Fraser, Cynthia; Buckley, Brian; Fayers, Peter; Harvey, Ian; Briggs, Andrew H; Norrie, John D; Fergusson, Dean; Ford, Ian; Vale, Luke D

2014-05-01

The randomised controlled trial (RCT) is widely considered to be the gold standard study for comparing the effectiveness of health interventions. Central to the design and validity of a RCT is a calculation of the number of participants needed (the sample size). The value used to determine the sample size can be considered the 'target difference'. From both a scientific and an ethical standpoint, selecting an appropriate target difference is of crucial importance. Determination of the target difference, as opposed to statistical approaches to calculating the sample size, has been greatly neglected though a variety of approaches have been proposed the current state of the evidence is unclear. The aim was to provide an overview of the current evidence regarding specifying the target difference in a RCT sample size calculation. The specific objectives were to conduct a systematic review of methods for specifying a target difference; to evaluate current practice by surveying triallists; to develop guidance on specifying the target difference in a RCT; and to identify future research needs. The biomedical and social science databases searched were MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), Cochrane Methodology Register, PsycINFO, Science Citation Index, EconLit, Education Resources Information Center (ERIC) and Scopus for in-press publications. All were searched from 1966 or the earliest date of the database coverage and searches were undertaken between November 2010 and January 2011. There were three interlinked components: (1) systematic review of methods for specifying a target difference for RCTs - a comprehensive search strategy involving an electronic literature search of biomedical and some non-biomedical databases and clinical trials textbooks was carried out; (2) identification of current trial practice using two surveys of triallists - members of the Society for Clinical Trials (SCT) were invited to complete an online survey and respondents were asked about their awareness and use of, and willingness to recommend, methods; one individual per triallist group [UK Clinical Research Collaboration (UKCRC)-registered Clinical Trials Units (CTUs), Medical Research Council (MRC) UK Hubs for Trials Methodology Research and National Institute for Health Research (NIHR) UK Research Design Services (RDS)] was invited to complete a survey; (3) production of a structured guidance document to aid the design of future trials - the draft guidance was developed utilising the results of the systematic review and surveys by the project steering and advisory groups. Methodological review incorporating electronic searches, review of books and guidelines, two surveys of experts (membership of an international society and UK- and Ireland-based triallists) and development of guidance. The two surveys were sent out to membership of the SCT and UK- and Ireland-based triallists. The review focused on methods for specifying the target difference in a RCT. It was not restricted to any type of intervention or condition. Methods for specifying the target difference for a RCT were considered. The search identified 11,485 potentially relevant studies. In total, 1434 were selected for full-text assessment and 777 were included in the review. Seven methods to specify the target difference for a RCT were identified - anchor, distribution, health economic, opinion-seeking, pilot study, review of evidence base (RoEB) and standardised effect size (SES) - each having important variations in implementation. A total of 216 of the included studies used more than one method. A total of 180 (15%) responses to the SCT survey were received, representing 13 countries. Awareness of methods ranged from 38% (n =69) for the health economic method to 90% (n =162) for the pilot study. Of the 61 surveys sent out to UK triallist groups, 34 (56%) responses were received. Awareness ranged from 97% (n =33) for the RoEB and pilot study methods to only 41% (n =14) for the distribution method. Based on the most recent trial, all bar three groups (91%, n =30) used a formal method. Guidance was developed on the use of each method and the reporting of the sample size calculation in a trial protocol and results paper. There is a clear need for greater use of formal methods to determine the target difference and better reporting of its specification. Raising the standard of RCT sample size calculations and the corresponding reporting of them would aid health professionals, patients, researchers and funders in judging the strength of the evidence and ensuring better use of scarce resources. The Medical Research Council UK and the National Institute for Health Research Joint Methodology Research programme.

Relative efficiency of unequal versus equal cluster sizes in cluster randomized trials using generalized estimating equation models.

PubMed

Liu, Jingxia; Colditz, Graham A

2018-05-01

There is growing interest in conducting cluster randomized trials (CRTs). For simplicity in sample size calculation, the cluster sizes are assumed to be identical across all clusters. However, equal cluster sizes are not guaranteed in practice. Therefore, the relative efficiency (RE) of unequal versus equal cluster sizes has been investigated when testing the treatment effect. One of the most important approaches to analyze a set of correlated data is the generalized estimating equation (GEE) proposed by Liang and Zeger, in which the "working correlation structure" is introduced and the association pattern depends on a vector of association parameters denoted by ρ. In this paper, we utilize GEE models to test the treatment effect in a two-group comparison for continuous, binary, or count data in CRTs. The variances of the estimator of the treatment effect are derived for the different types of outcome. RE is defined as the ratio of variance of the estimator of the treatment effect for equal to unequal cluster sizes. We discuss a commonly used structure in CRTs-exchangeable, and derive the simpler formula of RE with continuous, binary, and count outcomes. Finally, REs are investigated for several scenarios of cluster size distributions through simulation studies. We propose an adjusted sample size due to efficiency loss. Additionally, we also propose an optimal sample size estimation based on the GEE models under a fixed budget for known and unknown association parameter (ρ) in the working correlation structure within the cluster. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A review of reporting of participant recruitment and retention in RCTs in six major journals

PubMed Central

Toerien, Merran; Brookes, Sara T; Metcalfe, Chris; de Salis, Isabel; Tomlin, Zelda; Peters, Tim J; Sterne, Jonathan; Donovan, Jenny L

2009-01-01

Background Poor recruitment and retention of participants in randomised controlled trials (RCTs) is problematic but common. Clear and detailed reporting of participant flow is essential to assess the generalisability and comparability of RCTs. Despite improved reporting since the implementation of the CONSORT statement, important problems remain. This paper aims: (i) to update and extend previous reviews evaluating reporting of participant recruitment and retention in RCTs; (ii) to quantify the level of participation throughout RCTs. Methods We reviewed all reports of RCTs of health care interventions and/or processes with individual randomisation, published July–December 2004 in six major journals. Short, secondary or interim reports, and Phase I/II trials were excluded. Data recorded were: general RCT details; inclusion of flow diagram; participant flow throughout trial; reasons for non-participation/withdrawal; target sample sizes. Results 133 reports were reviewed. Overall, 79% included a flow diagram, but over a third were incomplete. The majority reported the flow of participants at each stage of the trial after randomisation. However, 40% failed to report the numbers assessed for eligibility. Percentages of participants retained at each stage were high: for example, 90% of eligible individuals were randomised, and 93% of those randomised were outcome assessed. On average, trials met their sample size targets. However, there were some substantial shortfalls: for example 21% of trials reporting a sample size calculation failed to achieve adequate numbers at randomisation, and 48% at outcome assessment. Reporting of losses to follow up was variable and difficult to interpret. Conclusion The majority of RCTs reported the flow of participants well after randomisation, although only two-thirds included a complete flow chart and there was great variability over the definition of "lost to follow up". Reporting of participant eligibility was poor, making assessments of recruitment practice and external validity difficult. Reporting of participant flow throughout RCTs could be improved by small changes to the CONSORT chart. PMID:19591685

A review of reporting of participant recruitment and retention in RCTs in six major journals.

PubMed

Toerien, Merran; Brookes, Sara T; Metcalfe, Chris; de Salis, Isabel; Tomlin, Zelda; Peters, Tim J; Sterne, Jonathan; Donovan, Jenny L

2009-07-10

Poor recruitment and retention of participants in randomised controlled trials (RCTs) is problematic but common. Clear and detailed reporting of participant flow is essential to assess the generalisability and comparability of RCTs. Despite improved reporting since the implementation of the CONSORT statement, important problems remain. This paper aims: (i) to update and extend previous reviews evaluating reporting of participant recruitment and retention in RCTs; (ii) to quantify the level of participation throughout RCTs. We reviewed all reports of RCTs of health care interventions and/or processes with individual randomisation, published July-December 2004 in six major journals. Short, secondary or interim reports, and Phase I/II trials were excluded. Data recorded were: general RCT details; inclusion of flow diagram; participant flow throughout trial; reasons for non-participation/withdrawal; target sample sizes. 133 reports were reviewed. Overall, 79% included a flow diagram, but over a third were incomplete. The majority reported the flow of participants at each stage of the trial after randomisation. However, 40% failed to report the numbers assessed for eligibility. Percentages of participants retained at each stage were high: for example, 90% of eligible individuals were randomised, and 93% of those randomised were outcome assessed. On average, trials met their sample size targets. However, there were some substantial shortfalls: for example 21% of trials reporting a sample size calculation failed to achieve adequate numbers at randomisation, and 48% at outcome assessment. Reporting of losses to follow up was variable and difficult to interpret. The majority of RCTs reported the flow of participants well after randomisation, although only two-thirds included a complete flow chart and there was great variability over the definition of "lost to follow up". Reporting of participant eligibility was poor, making assessments of recruitment practice and external validity difficult. Reporting of participant flow throughout RCTs could be improved by small changes to the CONSORT chart.

Trial Sequential Analysis in systematic reviews with meta-analysis.

PubMed

Wetterslev, Jørn; Jakobsen, Janus Christian; Gluud, Christian

2017-03-06

Most meta-analyses in systematic reviews, including Cochrane ones, do not have sufficient statistical power to detect or refute even large intervention effects. This is why a meta-analysis ought to be regarded as an interim analysis on its way towards a required information size. The results of the meta-analyses should relate the total number of randomised participants to the estimated required meta-analytic information size accounting for statistical diversity. When the number of participants and the corresponding number of trials in a meta-analysis are insufficient, the use of the traditional 95% confidence interval or the 5% statistical significance threshold will lead to too many false positive conclusions (type I errors) and too many false negative conclusions (type II errors). We developed a methodology for interpreting meta-analysis results, using generally accepted, valid evidence on how to adjust thresholds for significance in randomised clinical trials when the required sample size has not been reached. The Lan-DeMets trial sequential monitoring boundaries in Trial Sequential Analysis offer adjusted confidence intervals and restricted thresholds for statistical significance when the diversity-adjusted required information size and the corresponding number of required trials for the meta-analysis have not been reached. Trial Sequential Analysis provides a frequentistic approach to control both type I and type II errors. We define the required information size and the corresponding number of required trials in a meta-analysis and the diversity (D 2 ) measure of heterogeneity. We explain the reasons for using Trial Sequential Analysis of meta-analysis when the actual information size fails to reach the required information size. We present examples drawn from traditional meta-analyses using unadjusted naïve 95% confidence intervals and 5% thresholds for statistical significance. Spurious conclusions in systematic reviews with traditional meta-analyses can be reduced using Trial Sequential Analysis. Several empirical studies have demonstrated that the Trial Sequential Analysis provides better control of type I errors and of type II errors than the traditional naïve meta-analysis. Trial Sequential Analysis represents analysis of meta-analytic data, with transparent assumptions, and better control of type I and type II errors than the traditional meta-analysis using naïve unadjusted confidence intervals.

Sample size determination for equivalence assessment with multiple endpoints.

PubMed

Sun, Anna; Dong, Xiaoyu; Tsong, Yi

2014-01-01

Equivalence assessment between a reference and test treatment is often conducted by two one-sided tests (TOST). The corresponding power function and sample size determination can be derived from a joint distribution of the sample mean and sample variance. When an equivalence trial is designed with multiple endpoints, it often involves several sets of two one-sided tests. A naive approach for sample size determination in this case would select the largest sample size required for each endpoint. However, such a method ignores the correlation among endpoints. With the objective to reject all endpoints and when the endpoints are uncorrelated, the power function is the production of all power functions for individual endpoints. With correlated endpoints, the sample size and power should be adjusted for such a correlation. In this article, we propose the exact power function for the equivalence test with multiple endpoints adjusted for correlation under both crossover and parallel designs. We further discuss the differences in sample size for the naive method without and with correlation adjusted methods and illustrate with an in vivo bioequivalence crossover study with area under the curve (AUC) and maximum concentration (Cmax) as the two endpoints.

Prediction of accrual closure date in multi-center clinical trials with discrete-time Poisson process models.

PubMed

Tang, Gong; Kong, Yuan; Chang, Chung-Chou Ho; Kong, Lan; Costantino, Joseph P

2012-01-01

In a phase III multi-center cancer clinical trial or a large public health study, sample size is predetermined to achieve desired power, and study participants are enrolled from tens or hundreds of participating institutions. As the accrual is closing to the target size, the coordinating data center needs to project the accrual closure date on the basis of the observed accrual pattern and notify the participating sites several weeks in advance. In the past, projections were simply based on some crude assessment, and conservative measures were incorporated in order to achieve the target accrual size. This approach often resulted in excessive accrual size and subsequently unnecessary financial burden on the study sponsors. Here we proposed a discrete-time Poisson process-based method to estimate the accrual rate at time of projection and subsequently the trial closure date. To ensure that target size would be reached with high confidence, we also proposed a conservative method for the closure date projection. The proposed method was illustrated through the analysis of the accrual data of the National Surgical Adjuvant Breast and Bowel Project trial B-38. The results showed that application of the proposed method could help to save considerable amount of expenditure in patient management without compromising the accrual goal in multi-center clinical trials. Copyright © 2012 John Wiley & Sons, Ltd.

Noninferiority trial designs for odds ratios and risk differences.

PubMed

Hilton, Joan F

2010-04-30

This study presents constrained maximum likelihood derivations of the design parameters of noninferiority trials for binary outcomes with the margin defined on the odds ratio (ψ) or risk-difference (δ) scale. The derivations show that, for trials in which the group-specific response rates are equal under the point-alternative hypothesis, the common response rate, π(N), is a fixed design parameter whose value lies between the control and experimental rates hypothesized at the point-null, {π(C), π(E)}. We show that setting π(N) equal to the value of π(C) that holds under H(0) underestimates the overall sample size requirement. Given {π(C), ψ} or {π(C), δ} and the type I and II error rates, or algorithm finds clinically meaningful design values of π(N), and the corresponding minimum asymptotic sample size, N=n(E)+n(C), and optimal allocation ratio, γ=n(E)/n(C). We find that optimal allocations are increasingly imbalanced as ψ increases, with γ(ψ)<1 and γ(δ)≈1/γ(ψ), and that ranges of allocation ratios map to the minimum sample size. The latter characteristic allows trialists to consider trade-offs between optimal allocation at a smaller N and a preferred allocation at a larger N. For designs with relatively large margins (e.g. ψ>2.5), trial results that are presented on both scales will differ in power, with more power lost if the study is designed on the risk-difference scale and reported on the odds ratio scale than vice versa. 2010 John Wiley & Sons, Ltd.

Surrogate endpoints for overall survival in metastatic melanoma: a meta-analysis of randomised controlled trials

PubMed Central

Flaherty, Keith T; Hennig, Michael; Lee, Sandra J; Ascierto, Paolo A; Dummer, Reinhard; Eggermont, Alexander M M; Hauschild, Axel; Kefford, Richard; Kirkwood, John M; Long, Georgina V; Lorigan, Paul; Mackensen, Andreas; McArthur, Grant; O'Day, Steven; Patel, Poulam M; Robert, Caroline; Schadendorf, Dirk

2015-01-01

Summary Background Recent phase 3 trials have shown an overall survival benefit in metastatic melanoma. We aimed to assess whether progression-free survival (PFS) could be regarded as a reliable surrogate for overall survival through a meta-analysis of randomised trials. Methods We systematically reviewed randomised trials comparing treatment regimens in metastatic melanoma that included dacarbazine as the control arm, and which reported both PFS and overall survival with a standard hazard ratio (HR). We correlated HRs for overall survival and PFS, weighted by sample size or by precision of the HR estimate, assuming fixed and random effects. We did sensitivity analyses according to presence of crossover, trial size, and dacarbazine dose. Findings After screening 1649 reports and meeting abstracts published before Sept 8, 2013, we identified 12 eligible randomised trials that enrolled 4416 patients with metastatic melanoma. Irrespective of weighting strategy, we noted a strong correlation between the treatment effects for PFS and overall survival, which seemed independent of treatment type. Pearson correlation coefficients were 0.71 (95% CI 0.29–0.90) with a random-effects assumption, 0.85 (0.59–0.95) with a fixed-effects assumption, and 0.89 (0.68–0.97) with sample-size weighting. For nine trials without crossover, the correlation coefficient was 0.96 (0.81–0.99), which decreased to 0.93 (0.74–0.98) when two additional trials with less than 50% crossover were included. Inclusion of mature follow-up data after at least 50% crossover (in vemurafenib and dabrafenib phase 3 trials) weakened the PFS to overall survival correlation (0.55, 0.03–0.84). Inclusion of trials with no or little crossover with the random-effects assumption yielded a conservative statement of the PFS to overall survival correlation of 0.85 (0.51–0.96). Interpretation PFS can be regarded as a robust surrogate for overall survival in dacarbazine-controlled randomised trials of metastatic melanoma; we postulate that this association will hold as treatment standards evolve and are adopted as the control arm in future trials. Funding None. PMID:24485879

A U-statistics based approach to sample size planning of two-arm trials with discrete outcome criterion aiming to establish either superiority or noninferiority.

PubMed

Wellek, Stefan

2017-02-28

In current practice, the most frequently applied approach to the handling of ties in the Mann-Whitney-Wilcoxon (MWW) test is based on the conditional distribution of the sum of mid-ranks, given the observed pattern of ties. Starting from this conditional version of the testing procedure, a sample size formula was derived and investigated by Zhao et al. (Stat Med 2008). In contrast, the approach we pursue here is a nonconditional one exploiting explicit representations for the variances of and the covariance between the two U-statistics estimators involved in the Mann-Whitney form of the test statistic. The accuracy of both ways of approximating the sample sizes required for attaining a prespecified level of power in the MWW test for superiority with arbitrarily tied data is comparatively evaluated by means of simulation. The key qualitative conclusions to be drawn from these numerical comparisons are as follows: With the sample sizes calculated by means of the respective formula, both versions of the test maintain the level and the prespecified power with about the same degree of accuracy. Despite the equivalence in terms of accuracy, the sample size estimates obtained by means of the new formula are in many cases markedly lower than that calculated for the conditional test. Perhaps, a still more important advantage of the nonconditional approach based on U-statistics is that it can be also adopted for noninferiority trials. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Robustness of methods for blinded sample size re-estimation with overdispersed count data.

PubMed

Schneider, Simon; Schmidli, Heinz; Friede, Tim

2013-09-20

Counts of events are increasingly common as primary endpoints in randomized clinical trials. With between-patient heterogeneity leading to variances in excess of the mean (referred to as overdispersion), statistical models reflecting this heterogeneity by mixtures of Poisson distributions are frequently employed. Sample size calculation in the planning of such trials requires knowledge on the nuisance parameters, that is, the control (or overall) event rate and the overdispersion parameter. Usually, there is only little prior knowledge regarding these parameters in the design phase resulting in considerable uncertainty regarding the sample size. In this situation internal pilot studies have been found very useful and very recently several blinded procedures for sample size re-estimation have been proposed for overdispersed count data, one of which is based on an EM-algorithm. In this paper we investigate the EM-algorithm based procedure with respect to aspects of their implementation by studying the algorithm's dependence on the choice of convergence criterion and find that the procedure is sensitive to the choice of the stopping criterion in scenarios relevant to clinical practice. We also compare the EM-based procedure to other competing procedures regarding their operating characteristics such as sample size distribution and power. Furthermore, the robustness of these procedures to deviations from the model assumptions is explored. We find that some of the procedures are robust to at least moderate deviations. The results are illustrated using data from the US National Heart, Lung and Blood Institute sponsored Asymptomatic Cardiac Ischemia Pilot study. Copyright © 2013 John Wiley & Sons, Ltd.

Proof of concept demonstration of optimal composite MRI endpoints for clinical trials.

PubMed

Edland, Steven D; Ard, M Colin; Sridhar, Jaiashre; Cobia, Derin; Martersteck, Adam; Mesulam, M Marsel; Rogalski, Emily J

2016-09-01

Atrophy measures derived from structural MRI are promising outcome measures for early phase clinical trials, especially for rare diseases such as primary progressive aphasia (PPA), where the small available subject pool limits our ability to perform meaningfully powered trials with traditional cognitive and functional outcome measures. We investigated a composite atrophy index in 26 PPA participants with longitudinal MRIs separated by two years. Rogalski et al . [ Neurology 2014;83:1184-1191] previously demonstrated that atrophy of the left perisylvian temporal cortex (PSTC) is a highly sensitive measure of disease progression in this population and a promising endpoint for clinical trials. Using methods described by Ard et al . [ Pharmaceutical Statistics 2015;14:418-426], we constructed a composite atrophy index composed of a weighted sum of volumetric measures of 10 regions of interest within the left perisylvian cortex using weights that maximize signal-to-noise and minimize sample size required of trials using the resulting score. Sample size required to detect a fixed percentage slowing in atrophy in a two-year clinical trial with equal allocation of subjects across arms and 90% power was calculated for the PSTC and optimal composite surrogate biomarker endpoints. The optimal composite endpoint required 38% fewer subjects to detect the same percent slowing in atrophy than required by the left PSTC endpoint. Optimal composites can increase the power of clinical trials and increase the probability that smaller trials are informative, an observation especially relevant for PPA, but also for related neurodegenerative disorders including Alzheimer's disease.

A general approach for sample size calculation for the three-arm 'gold standard' non-inferiority design.

PubMed

Stucke, Kathrin; Kieser, Meinhard

2012-12-10

In the three-arm 'gold standard' non-inferiority design, an experimental treatment, an active reference, and a placebo are compared. This design is becoming increasingly popular, and it is, whenever feasible, recommended for use by regulatory guidelines. We provide a general method to calculate the required sample size for clinical trials performed in this design. As special cases, the situations of continuous, binary, and Poisson distributed outcomes are explored. Taking into account the correlation structure of the involved test statistics, the proposed approach leads to considerable savings in sample size as compared with application of ad hoc methods for all three scale levels. Furthermore, optimal sample size allocation ratios are determined that result in markedly smaller total sample sizes as compared with equal assignment. As optimal allocation makes the active treatment groups larger than the placebo group, implementation of the proposed approach is also desirable from an ethical viewpoint. Copyright © 2012 John Wiley & Sons, Ltd.

Selection of the effect size for sample size determination for a continuous response in a superiority clinical trial using a hybrid classical and Bayesian procedure.

PubMed

Ciarleglio, Maria M; Arendt, Christopher D; Peduzzi, Peter N

2016-06-01

When designing studies that have a continuous outcome as the primary endpoint, the hypothesized effect size ([Formula: see text]), that is, the hypothesized difference in means ([Formula: see text]) relative to the assumed variability of the endpoint ([Formula: see text]), plays an important role in sample size and power calculations. Point estimates for [Formula: see text] and [Formula: see text] are often calculated using historical data. However, the uncertainty in these estimates is rarely addressed. This article presents a hybrid classical and Bayesian procedure that formally integrates prior information on the distributions of [Formula: see text] and [Formula: see text] into the study's power calculation. Conditional expected power, which averages the traditional power curve using the prior distributions of [Formula: see text] and [Formula: see text] as the averaging weight, is used, and the value of [Formula: see text] is found that equates the prespecified frequentist power ([Formula: see text]) and the conditional expected power of the trial. This hypothesized effect size is then used in traditional sample size calculations when determining sample size for the study. The value of [Formula: see text] found using this method may be expressed as a function of the prior means of [Formula: see text] and [Formula: see text], [Formula: see text], and their prior standard deviations, [Formula: see text]. We show that the "naïve" estimate of the effect size, that is, the ratio of prior means, should be down-weighted to account for the variability in the parameters. An example is presented for designing a placebo-controlled clinical trial testing the antidepressant effect of alprazolam as monotherapy for major depression. Through this method, we are able to formally integrate prior information on the uncertainty and variability of both the treatment effect and the common standard deviation into the design of the study while maintaining a frequentist framework for the final analysis. Solving for the effect size which the study has a high probability of correctly detecting based on the available prior information on the difference [Formula: see text] and the standard deviation [Formula: see text] provides a valuable, substantiated estimate that can form the basis for discussion about the study's feasibility during the design phase. © The Author(s) 2016.

Published methodological quality of randomized controlled trials does not reflect the actual quality assessed in protocols

PubMed Central

Mhaskar, Rahul; Djulbegovic, Benjamin; Magazin, Anja; Soares, Heloisa P.; Kumar, Ambuj

2011-01-01

Objectives To assess whether reported methodological quality of randomized controlled trials (RCTs) reflect the actual methodological quality, and to evaluate the association of effect size (ES) and sample size with methodological quality. Study design Systematic review Setting Retrospective analysis of all consecutive phase III RCTs published by 8 National Cancer Institute Cooperative Groups until year 2006. Data were extracted from protocols (actual quality) and publications (reported quality) for each study. Results 429 RCTs met the inclusion criteria. Overall reporting of methodological quality was poor and did not reflect the actual high methodological quality of RCTs. The results showed no association between sample size and actual methodological quality of a trial. Poor reporting of allocation concealment and blinding exaggerated the ES by 6% (ratio of hazard ratio [RHR]: 0.94, 95%CI: 0.88, 0.99) and 24% (RHR: 1.24, 95%CI: 1.05, 1.43), respectively. However, actual quality assessment showed no association between ES and methodological quality. Conclusion The largest study to-date shows poor quality of reporting does not reflect the actual high methodological quality. Assessment of the impact of quality on the ES based on reported quality can produce misleading results. PMID:22424985

Cluster randomised crossover trials with binary data and unbalanced cluster sizes: application to studies of near-universal interventions in intensive care.

PubMed

Forbes, Andrew B; Akram, Muhammad; Pilcher, David; Cooper, Jamie; Bellomo, Rinaldo

2015-02-01

Cluster randomised crossover trials have been utilised in recent years in the health and social sciences. Methods for analysis have been proposed; however, for binary outcomes, these have received little assessment of their appropriateness. In addition, methods for determination of sample size are currently limited to balanced cluster sizes both between clusters and between periods within clusters. This article aims to extend this work to unbalanced situations and to evaluate the properties of a variety of methods for analysis of binary data, with a particular focus on the setting of potential trials of near-universal interventions in intensive care to reduce in-hospital mortality. We derive a formula for sample size estimation for unbalanced cluster sizes, and apply it to the intensive care setting to demonstrate the utility of the cluster crossover design. We conduct a numerical simulation of the design in the intensive care setting and for more general configurations, and we assess the performance of three cluster summary estimators and an individual-data estimator based on binomial-identity-link regression. For settings similar to the intensive care scenario involving large cluster sizes and small intra-cluster correlations, the sample size formulae developed and analysis methods investigated are found to be appropriate, with the unweighted cluster summary method performing well relative to the more optimal but more complex inverse-variance weighted method. More generally, we find that the unweighted and cluster-size-weighted summary methods perform well, with the relative efficiency of each largely determined systematically from the study design parameters. Performance of individual-data regression is adequate with small cluster sizes but becomes inefficient for large, unbalanced cluster sizes. When outcome prevalences are 6% or less and the within-cluster-within-period correlation is 0.05 or larger, all methods display sub-nominal confidence interval coverage, with the less prevalent the outcome the worse the coverage. As with all simulation studies, conclusions are limited to the configurations studied. We confined attention to detecting intervention effects on an absolute risk scale using marginal models and did not explore properties of binary random effects models. Cluster crossover designs with binary outcomes can be analysed using simple cluster summary methods, and sample size in unbalanced cluster size settings can be determined using relatively straightforward formulae. However, caution needs to be applied in situations with low prevalence outcomes and moderate to high intra-cluster correlations. © The Author(s) 2014.

Endorsement of the CONSORT guidelines, trial registration, and the quality of reporting randomised controlled trials in leading nursing journals: A cross-sectional analysis.

PubMed

Jull, Andrew; Aye, Phyu Sin

2015-06-01

To establish the reporting quality of trials published in leading nursing journals and investigate associations between CONSORT Statement or trial registration endorsment and reporting of design elements. The top 15 nursing journals were searched using Medline for randomised controlled trials published in 2012. Journals were categorised as CONSORT and trial registration promoting based on requirements of submitting authors or the journal's webpage as at January 2014. Data on sequence generation, allocation concealment, follow up, blinding, baseline equivalence and sample size calculation were extracted by one author and independently verified by the second author against source data. Seven journals were CONSORT promoting and three of these journals were also trial registration promoting. 114 citations were identified and 83 were randomised controlled trials. Eighteen trials (21.7%) were registered and those published in trial registration promoting journals were more likely to be registered (RR 2.64 95%CI 1.14-6.09). We assessed 68.7% of trials to be low risk of bias for sequence generation, 20.5% for allocation concealment, 38.6% for blinding, 55.4% for completeness of follow up and 79.5% for baseline equivalence. Trials published in CONSORT promoting journals were more likely to be at low risk of bias for blinding (RR 2.33, 95%CI 1.01-5.34) and completeness of follow up (RR 1.77, 95%CI 1.02-3.10), but journal endorsement of the CONSORT Statement or trial registration otherwise had no significant effect. Trials published in CONSORT and trial registration promoting journals were more likely to have high quality sample size calculations (RR 2.91, 95%CI 1.18-7.19 and RR 1.69, 95%CI 1.08-2.64, respectively). Simple endorsement of the CONSORT Statement and trials registration is insufficient action to encourage improvement of the quality of trial reporting across the most important of trial design elements. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis and design of randomised clinical trials involving competing risks endpoints.

PubMed

Tai, Bee-Choo; Wee, Joseph; Machin, David

2011-05-19

In randomised clinical trials involving time-to-event outcomes, the failures concerned may be events of an entirely different nature and as such define a classical competing risks framework. In designing and analysing clinical trials involving such endpoints, it is important to account for the competing events, and evaluate how each contributes to the overall failure. An appropriate choice of statistical model is important for adequate determination of sample size. We describe how competing events may be summarised in such trials using cumulative incidence functions and Gray's test. The statistical modelling of competing events using proportional cause-specific and subdistribution hazard functions, and the corresponding procedures for sample size estimation are outlined. These are illustrated using data from a randomised clinical trial (SQNP01) of patients with advanced (non-metastatic) nasopharyngeal cancer. In this trial, treatment has no effect on the competing event of loco-regional recurrence. Thus the effects of treatment on the hazard of distant metastasis were similar via both the cause-specific (unadjusted csHR = 0.43, 95% CI 0.25 - 0.72) and subdistribution (unadjusted subHR 0.43; 95% CI 0.25 - 0.76) hazard analyses, in favour of concurrent chemo-radiotherapy followed by adjuvant chemotherapy. Adjusting for nodal status and tumour size did not alter the results. The results of the logrank test (p = 0.002) comparing the cause-specific hazards and the Gray's test (p = 0.003) comparing the cumulative incidences also led to the same conclusion. However, the subdistribution hazard analysis requires many more subjects than the cause-specific hazard analysis to detect the same magnitude of effect. The cause-specific hazard analysis is appropriate for analysing competing risks outcomes when treatment has no effect on the cause-specific hazard of the competing event. It requires fewer subjects than the subdistribution hazard analysis for a similar effect size. However, if the main and competing events are influenced in opposing directions by an intervention, a subdistribution hazard analysis may be warranted.

Type I error probability spending for post-market drug and vaccine safety surveillance with binomial data.

PubMed

Silva, Ivair R

2018-01-15

Type I error probability spending functions are commonly used for designing sequential analysis of binomial data in clinical trials, but it is also quickly emerging for near-continuous sequential analysis of post-market drug and vaccine safety surveillance. It is well known that, for clinical trials, when the null hypothesis is not rejected, it is still important to minimize the sample size. Unlike in post-market drug and vaccine safety surveillance, that is not important. In post-market safety surveillance, specially when the surveillance involves identification of potential signals, the meaningful statistical performance measure to be minimized is the expected sample size when the null hypothesis is rejected. The present paper shows that, instead of the convex Type I error spending shape conventionally used in clinical trials, a concave shape is more indicated for post-market drug and vaccine safety surveillance. This is shown for both, continuous and group sequential analysis. Copyright © 2017 John Wiley & Sons, Ltd.

Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range.

PubMed

Wan, Xiang; Wang, Wenqian; Liu, Jiming; Tong, Tiejun

2014-12-19

In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.'s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations.

Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

PubMed

NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

2017-08-01

Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

Quantity, topics, methods and findings of randomised controlled trials published by German university departments of general practice - systematic review.

PubMed

Heinmüller, Stefan; Schneider, Antonius; Linde, Klaus

2016-04-23

Academic infrastructures and networks for clinical research in primary care receive little funding in Germany. We aimed to provide an overview of the quantity, topics, methods and findings of randomised controlled trials published by German university departments of general practice. We searched Scopus (last search done in April 2015), publication lists of institutes and references of included articles. We included randomised trials published between January 2000 and December 2014 with a first or last author affiliated with a German university department of general practice or family medicine. Risk of bias was assessed with the Cochrane tool, and study findings were quantified using standardised mean differences (SMDs). Thirty-three trials met the inclusion criteria. Seventeen were cluster-randomised trials, with a majority investigating interventions aimed at improving processes compared with usual care. Sample sizes varied between 6 and 606 clusters and 168 and 7807 participants. The most frequent methodological problem was risk of selection bias due to recruitment of individuals after randomisation of clusters. Effects of interventions over usual care were mostly small (SMD <0.3). Sixteen trials randomising individual participants addressed a variety of treatment and educational interventions. Sample sizes varied between 20 and 1620 participants. The methodological quality of the trials was highly variable. Again, effects of experimental interventions over controls were mostly small. Despite limited funding, German university institutes of general practice or family medicine are increasingly performing randomised trials. Cluster-randomised trials on practice improvement are a focus, but problems with allocation concealment are frequent.

A Model Based Approach to Sample Size Estimation in Recent Onset Type 1 Diabetes

PubMed Central

Bundy, Brian; Krischer, Jeffrey P.

2016-01-01

The area under the curve C-peptide following a 2-hour mixed meal tolerance test from 481 individuals enrolled on 5 prior TrialNet studies of recent onset type 1 diabetes from baseline to 12 months after enrollment were modelled to produce estimates of its rate of loss and variance. Age at diagnosis and baseline C-peptide were found to be significant predictors and adjusting for these in an ANCOVA resulted in estimates with lower variance. Using these results as planning parameters for new studies results in a nearly 50% reduction in the target sample size. The modelling also produces an expected C-peptide that can be used in Observed vs. Expected calculations to estimate the presumption of benefit in ongoing trials. PMID:26991448

Design and implementation of a dental caries prevention trial in remote Canadian Aboriginal communities

PubMed Central

2010-01-01

Background The goal of this cluster randomized trial is to test the effectiveness of a counseling approach, Motivational Interviewing, to control dental caries in young Aboriginal children. Motivational Interviewing, a client-centred, directive counseling style, has not yet been evaluated as an approach for promotion of behaviour change in indigenous communities in remote settings. Methods/design Aboriginal women were hired from the 9 communities to recruit expectant and new mothers to the trial, administer questionnaires and deliver the counseling to mothers in the test communities. The goal is for mothers to receive the intervention during pregnancy and at their child's immunization visits. Data on children's dental health status and family dental health practices will be collected when children are 30-months of age. The communities were randomly allocated to test or control group by a random "draw" over community radio. Sample size and power were determined based on an anticipated 20% reduction in caries prevalence. Randomization checks were conducted between groups. Discussion In the 5 test and 4 control communities, 272 of the original target sample size of 309 mothers have been recruited over a two-and-a-half year period. A power calculation using the actual attained sample size showed power to be 79% to detect a treatment effect. If an attrition fraction of 4% per year is maintained, power will remain at 80%. Power will still be > 90% to detect a 25% reduction in caries prevalence. The distribution of most baseline variables was similar for the two randomized groups of mothers. However, despite the random assignment of communities to treatment conditions, group differences exist for stage of pregnancy and prior tooth extractions in the family. Because of the group imbalances on certain variables, control of baseline variables will be done in the analyses of treatment effects. This paper explains the challenges of conducting randomized trials in remote settings, the importance of thorough community collaboration, and also illustrates the likelihood that some baseline variables that may be clinically important will be unevenly split in group-randomized trials when the number of groups is small. Trial registration This trial is registered as ISRCTN41467632. PMID:20465831

Phase II cancer clinical trials for biomarker-guided treatments.

PubMed

Jung, Sin-Ho

2018-01-01

The design and analysis of cancer clinical trials with biomarker depend on various factors, such as the phase of trials, the type of biomarker, whether the used biomarker is validated or not, and the study objectives. In this article, we demonstrate the design and analysis of two Phase II cancer clinical trials, one with a predictive biomarker and the other with an imaging prognostic biomarker. Statistical testing methods and their sample size calculation methods are presented for each trial. We assume that the primary endpoint of these trials is a time to event variable, but this concept can be used for any type of endpoint.

Morphological diversity of Trichuris spp. eggs observed during an anthelminthic drug trial in Yunnan, China, and relative performance of parasitologic diagnostic tools.

PubMed

Steinmann, Peter; Rinaldi, Laura; Cringoli, Giuseppe; Du, Zun-Wei; Marti, Hanspeter; Jiang, Jin-Yong; Zhou, Hui; Zhou, Xiao-Nong; Utzinger, Jürg

2015-01-01

The presence of large Trichuris spp. eggs in human faecal samples is occasionally reported. Such eggs have been described as variant Trichuris trichiura or Trichuris vulpis eggs. Within the frame of a randomised controlled trial, faecal samples collected from 115 Bulang individuals from Yunnan, People's Republic of China were subjected to the Kato-Katz technique (fresh stool samples) and the FLOTAC and ether-concentration techniques (sodium acetate-acetic acid-formalin (SAF)-fixed stool samples). Large Trichuris spp. eggs were noted in faecal samples with a prevalence of 6.1% before and 21.7% after anthelminthic drug administration. The observed prevalence of standard-sized T. trichiura eggs was reduced from 93.0% to 87.0% after treatment. Considerably more cases of large Trichuris spp. eggs and slightly more cases with normal-sized T. trichiura eggs were identified by FLOTAC compared to the ether-concentration technique. No large Trichuris spp. eggs were observed on the Kato-Katz thick smears. Copyright © 2014 Elsevier B.V. All rights reserved.

Prospective registration trends, reasons for retrospective registration and mechanisms to increase prospective registration compliance: descriptive analysis and survey

PubMed Central

Seidler, Anna Lene; Askie, Lisa M

2018-01-01

Objectives To analyse prospective versus retrospective trial registration trends on the Australian New Zealand Clinical Trials Registry (ANZCTR) and to evaluate the reasons for non-compliance with prospective registration. Design Part 1: Descriptive analysis of trial registration trends from 2006 to 2015. Part 2: Online registrant survey. Participants Part 1: All interventional trials registered on ANZCTR from 2006 to 2015. Part 2: Random sample of those who had retrospectively registered a trial on ANZCTR between 2010 and 2015. Main outcome measures Part 1: Proportion of prospective versus retrospective clinical trial registrations (ie, registration before versus after enrolment of the first participant) on the ANZCTR overall and by various key metrics, such as sponsor, funder, recruitment country and sample size. Part 2: Reasons for non-compliance with prospective registration and perceived usefulness of various proposed mechanisms to improve prospective registration compliance. Results Part 1: Analysis of the complete dataset of 9450 trials revealed that compliance with prospective registration increased from 48% (216 out of 446 trials) in 2006 to 63% (723/1148) in 2012 and has since plateaued at around 64%. Patterns of compliance were relatively consistent across sponsor and funder types (industry vs non-industry), type of intervention (drug vs non-drug) and size of trial (n<100, 100–500, >500). However, primary sponsors from Australia/New Zealand were almost twice as likely to register prospectively (62%; 4613/7452) compared with sponsors from other countries with a WHO Network Registry (35%; 377/1084) or sponsors from countries without a WHO Registry (29%; 230/781). Part 2: The majority (56%; 84/149) of survey respondents cited lack of awareness as a reason for not registering their study prospectively. Seventy-four per cent (111/149) stated that linking registration to ethics approval would facilitate prospective registration. Conclusions Despite some progress, compliance with prospective registration remains suboptimal. Linking registration to ethics approval was the favoured strategy among those sampled for improving compliance. PMID:29496896

Auditory proactive interference in monkeys: the roles of stimulus set size and intertrial interval.

PubMed

Bigelow, James; Poremba, Amy

2013-09-01

We conducted two experiments to examine the influences of stimulus set size (the number of stimuli that are used throughout the session) and intertrial interval (ITI, the elapsed time between trials) in auditory short-term memory in monkeys. We used an auditory delayed matching-to-sample task wherein the animals had to indicate whether two sounds separated by a 5-s retention interval were the same (match trials) or different (nonmatch trials). In Experiment 1, we randomly assigned stimulus set sizes of 2, 4, 8, 16, 32, 64, or 192 (trial-unique) for each session of 128 trials. Consistent with previous visual studies, overall accuracy was consistently lower when smaller stimulus set sizes were used. Further analyses revealed that these effects were primarily caused by an increase in incorrect "same" responses on nonmatch trials. In Experiment 2, we held the stimulus set size constant at four for each session and alternately set the ITI at 5, 10, or 20 s. Overall accuracy improved when the ITI was increased from 5 to 10 s, but it was the same across the 10- and 20-s conditions. As in Experiment 1, the overall decrease in accuracy during the 5-s condition was caused by a greater number of false "match" responses on nonmatch trials. Taken together, Experiments 1 and 2 showed that auditory short-term memory in monkeys is highly susceptible to proactive interference caused by stimulus repetition. Additional analyses of the data from Experiment 1 suggested that monkeys may make same-different judgments on the basis of a familiarity criterion that is adjusted by error-related feedback.

EFFECT OF SHORT-TERM ART INTERRUPTION ON LEVELS OF INTEGRATED HIV DNA.

PubMed

Strongin, Zachary; Sharaf, Radwa; VanBelzen, D Jake; Jacobson, Jeffrey M; Connick, Elizabeth; Volberding, Paul; Skiest, Daniel J; Gandhi, Rajesh T; Kuritzkes, Daniel R; O'Doherty, Una; Li, Jonathan Z

2018-03-28

Analytic treatment interruption (ATI) studies are required to evaluate strategies aimed at achieving ART-free HIV remission, but the impact of ATI on the viral reservoir remains unclear. We validated a DNA size selection-based assay for measuring levels of integrated HIV DNA and applied it to assess the effects of short-term ATI on the HIV reservoir. Samples from participants from four AIDS Clinical Trials Group (ACTG) ATI studies were assayed for integrated HIV DNA levels. Cryopreserved PBMCs were obtained for 12 participants with available samples pre-ATI and approximately 6 months after ART resumption. Four participants also had samples available during the ATI. The median duration of ATI was 12 weeks. Validation of the HIV Integrated DNA size-Exclusion (HIDE) assay was performed using samples spiked with unintegrated HIV DNA, HIV-infected cell lines, and participant PBMCs. The HIDE assay eliminated 99% of unintegrated HIV DNA species and strongly correlated with the established Alu- gag assay. For the majority of individuals, integrated DNA levels increased during ATI and subsequently declined upon ART resumption. There was no significant difference in levels of integrated HIV DNA between the pre- and post-ATI time points, with the median ratio of post:pre-ATI HIV DNA levels of 0.95. Using a new integrated HIV DNA assay, we found minimal change in the levels of integrated HIV DNA in participants who underwent an ATI followed by 6 months of ART. This suggests that short-term ATI can be conducted without a significant impact on levels of integrated proviral DNA in the peripheral blood. IMPORTANCE Interventions aimed at achieving sustained antiretroviral therapy (ART)-free HIV remission require treatment interruption trials to assess their efficacy. However, these trials are accompanied by safety concerns related to the expansion of the viral reservoir. We validated an assay that uses an automated DNA size-selection platform for quantifying levels of integrated HIV DNA and is less sample- and labor-intensive than current assays. Using stored samples from AIDS Clinical Trials Group studies, we found that short-term ART discontinuation had minimal impact on integrated HIV DNA levels after ART resumption, providing reassurance about the reservoir effects of short-term treatment interruption trials. Copyright © 2018 American Society for Microbiology.

Effect Size in Efficacy Trials of Women With Decreased Sexual Desire.

PubMed

Pyke, Robert E; Clayton, Anita H

2018-03-22

Regarding hypoactive sexual desire disorder (HSDD) in women, some reviewers judge the effect size small for medications vs placebo, but substantial for cognitive behavior therapy (CBT) or mindfulness meditation training (MMT) vs wait list. However, we lack comparisons of the effect sizes for the active intervention itself, for the control treatment, and for the differential between the two. For efficacy trials of HSDD in women, compare effect sizes for medications (testosterone/testosterone transdermal system, flibanserin, and bremelanotide) and placebo vs effect sizes for psychotherapy and wait-list control. We conducted a literature search for mean changes and SD on main measures of sexual desire and associated distress in trials of medications, CBT, or MMT. Effect size was used as it measures the magnitude of the intervention without confounding by sample size. Cohen d was used to determine effect sizes. For medications, mean (SD) effect size was 1.0 (0.34); for CBT and MMT, 1.0 (0.36); for placebo, 0.55 (0.16); and for wait list, 0.05 (0.26). Recommendations of psychotherapy over medication for treatment of HSDD are premature and not supported by data on effect sizes. Active participation in treatment conveys considerable non-specific benefits. Caregivers should attend to biological and psychosocial elements, and patient preference, to optimize response. Few clinical trials of psychotherapies were substantial in size or utilized adequate control paradigms. Medications and psychotherapies had similar, large effect sizes. Effect size of placebo was moderate. Effect size of wait-list control was very small, about one quarter that of placebo. Thus, a substantial non-specific therapeutic effect is associated with receiving placebo plus active care and evaluation. The difference in effect size between placebo and wait-list controls distorts the value of the subtraction of effect of the control paradigms to estimate intervention effectiveness. Pyke RE, Clayton AH. Effect Size in Efficacy Trials of Women With Decreased Sexual Desire. Sex Med Rev 2018;XX:XXX-XXX. Copyright © 2018 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Simulating recurrent event data with hazard functions defined on a total time scale.

PubMed

Jahn-Eimermacher, Antje; Ingel, Katharina; Ozga, Ann-Kathrin; Preussler, Stella; Binder, Harald

2015-03-08

In medical studies with recurrent event data a total time scale perspective is often needed to adequately reflect disease mechanisms. This means that the hazard process is defined on the time since some starting point, e.g. the beginning of some disease, in contrast to a gap time scale where the hazard process restarts after each event. While techniques such as the Andersen-Gill model have been developed for analyzing data from a total time perspective, techniques for the simulation of such data, e.g. for sample size planning, have not been investigated so far. We have derived a simulation algorithm covering the Andersen-Gill model that can be used for sample size planning in clinical trials as well as the investigation of modeling techniques. Specifically, we allow for fixed and/or random covariates and an arbitrary hazard function defined on a total time scale. Furthermore we take into account that individuals may be temporarily insusceptible to a recurrent incidence of the event. The methods are based on conditional distributions of the inter-event times conditional on the total time of the preceeding event or study start. Closed form solutions are provided for common distributions. The derived methods have been implemented in a readily accessible R script. The proposed techniques are illustrated by planning the sample size for a clinical trial with complex recurrent event data. The required sample size is shown to be affected not only by censoring and intra-patient correlation, but also by the presence of risk-free intervals. This demonstrates the need for a simulation algorithm that particularly allows for complex study designs where no analytical sample size formulas might exist. The derived simulation algorithm is seen to be useful for the simulation of recurrent event data that follow an Andersen-Gill model. Next to the use of a total time scale, it allows for intra-patient correlation and risk-free intervals as are often observed in clinical trial data. Its application therefore allows the simulation of data that closely resemble real settings and thus can improve the use of simulation studies for designing and analysing studies.

Increasing efficiency of preclinical research by group sequential designs

PubMed Central

Piper, Sophie K.; Rex, Andre; Florez-Vargas, Oscar; Karystianis, George; Schneider, Alice; Wellwood, Ian; Siegerink, Bob; Ioannidis, John P. A.; Kimmelman, Jonathan; Dirnagl, Ulrich

2017-01-01

Despite the potential benefits of sequential designs, studies evaluating treatments or experimental manipulations in preclinical experimental biomedicine almost exclusively use classical block designs. Our aim with this article is to bring the existing methodology of group sequential designs to the attention of researchers in the preclinical field and to clearly illustrate its potential utility. Group sequential designs can offer higher efficiency than traditional methods and are increasingly used in clinical trials. Using simulation of data, we demonstrate that group sequential designs have the potential to improve the efficiency of experimental studies, even when sample sizes are very small, as is currently prevalent in preclinical experimental biomedicine. When simulating data with a large effect size of d = 1 and a sample size of n = 18 per group, sequential frequentist analysis consumes in the long run only around 80% of the planned number of experimental units. In larger trials (n = 36 per group), additional stopping rules for futility lead to the saving of resources of up to 30% compared to block designs. We argue that these savings should be invested to increase sample sizes and hence power, since the currently underpowered experiments in preclinical biomedicine are a major threat to the value and predictiveness in this research domain. PMID:28282371

A studentized permutation test for three-arm trials in the 'gold standard' design.

PubMed

Mütze, Tobias; Konietschke, Frank; Munk, Axel; Friede, Tim

2017-03-15

The 'gold standard' design for three-arm trials refers to trials with an active control and a placebo control in addition to the experimental treatment group. This trial design is recommended when being ethically justifiable and it allows the simultaneous comparison of experimental treatment, active control, and placebo. Parametric testing methods have been studied plentifully over the past years. However, these methods often tend to be liberal or conservative when distributional assumptions are not met particularly with small sample sizes. In this article, we introduce a studentized permutation test for testing non-inferiority and superiority of the experimental treatment compared with the active control in three-arm trials in the 'gold standard' design. The performance of the studentized permutation test for finite sample sizes is assessed in a Monte Carlo simulation study under various parameter constellations. Emphasis is put on whether the studentized permutation test meets the target significance level. For comparison purposes, commonly used Wald-type tests, which do not make any distributional assumptions, are included in the simulation study. The simulation study shows that the presented studentized permutation test for assessing non-inferiority in three-arm trials in the 'gold standard' design outperforms its competitors, for instance the test based on a quasi-Poisson model, for count data. The methods discussed in this paper are implemented in the R package ThreeArmedTrials which is available on the comprehensive R archive network (CRAN). Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Cluster randomized trials utilizing primary care electronic health records: methodological issues in design, conduct, and analysis (eCRT Study)

PubMed Central

2014-01-01

Background There is growing interest in conducting clinical and cluster randomized trials through electronic health records. This paper reports on the methodological issues identified during the implementation of two cluster randomized trials using the electronic health records of the Clinical Practice Research Datalink (CPRD). Methods Two trials were completed in primary care: one aimed to reduce inappropriate antibiotic prescribing for acute respiratory infection; the other aimed to increase physician adherence with secondary prevention interventions after first stroke. The paper draws on documentary records and trial datasets to report on the methodological experience with respect to research ethics and research governance approval, general practice recruitment and allocation, sample size calculation and power, intervention implementation, and trial analysis. Results We obtained research governance approvals from more than 150 primary care organizations in England, Wales, and Scotland. There were 104 CPRD general practices recruited to the antibiotic trial and 106 to the stroke trial, with the target number of practices being recruited within six months. Interventions were installed into practice information systems remotely over the internet. The mean number of participants per practice was 5,588 in the antibiotic trial and 110 in the stroke trial, with the coefficient of variation of practice sizes being 0.53 and 0.56 respectively. Outcome measures showed substantial correlations between the 12 months before, and after intervention, with coefficients ranging from 0.42 for diastolic blood pressure to 0.91 for proportion of consultations with antibiotics prescribed, defining practice and participant eligibility for analysis requires careful consideration. Conclusions Cluster randomized trials may be performed efficiently in large samples from UK general practices using the electronic health records of a primary care database. The geographical dispersal of trial sites presents a difficulty for research governance approval and intervention implementation. Pretrial data analyses should inform trial design and analysis plans. Trial registration Current Controlled Trials ISRCTN 47558792 and ISRCTN 35701810 (both registered on 17 March 2010). PMID:24919485

Using Bayesian Adaptive Trial Designs for Comparative Effectiveness Research: A Virtual Trial Execution.

PubMed

Luce, Bryan R; Connor, Jason T; Broglio, Kristine R; Mullins, C Daniel; Ishak, K Jack; Saunders, Elijah; Davis, Barry R

2016-09-20

Bayesian and adaptive clinical trial designs offer the potential for more efficient processes that result in lower sample sizes and shorter trial durations than traditional designs. To explore the use and potential benefits of Bayesian adaptive clinical trial designs in comparative effectiveness research. Virtual execution of ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial) as if it had been done according to a Bayesian adaptive trial design. Comparative effectiveness trial of antihypertensive medications. Patient data sampled from the more than 42 000 patients enrolled in ALLHAT with publicly available data. Number of patients randomly assigned between groups, trial duration, observed numbers of events, and overall trial results and conclusions. The Bayesian adaptive approach and original design yielded similar overall trial conclusions. The Bayesian adaptive trial randomly assigned more patients to the better-performing group and would probably have ended slightly earlier. This virtual trial execution required limited resampling of ALLHAT patients for inclusion in RE-ADAPT (REsearch in ADAptive methods for Pragmatic Trials). Involvement of a data monitoring committee and other trial logistics were not considered. In a comparative effectiveness research trial, Bayesian adaptive trial designs are a feasible approach and potentially generate earlier results and allocate more patients to better-performing groups. National Heart, Lung, and Blood Institute.

Anomalies in the detection of change: When changes in sample size are mistaken for changes in proportions.

PubMed

Fiedler, Klaus; Kareev, Yaakov; Avrahami, Judith; Beier, Susanne; Kutzner, Florian; Hütter, Mandy

2016-01-01

Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductive-learning constraints imposed on decisions from experience.

Visual search by chimpanzees (Pan): assessment of controlling relations.

PubMed Central

Tomonaga, M

1995-01-01

Three experimentally sophisticated chimpanzees (Pan), Akira, Chloe, and Ai, were trained on visual search performance using a modified multiple-alternative matching-to-sample task in which a sample stimulus was followed by the search display containing one target identical to the sample and several uniform distractors (i.e., negative comparison stimuli were identical to each other). After they acquired this task, they were tested for transfer of visual search performance to trials in which the sample was not followed by the uniform search display (odd-item search). Akira showed positive transfer of visual search performance to odd-item search even when the display size (the number of stimulus items in the search display) was small, whereas Chloe and Ai showed a transfer only when the display size was large. Chloe and Ai used some nonrelational cues such as perceptual isolation of the target among uniform distractors (so-called pop-out). In addition to the odd-item search test, various types of probe trials were presented to clarify the controlling relations in multiple-alternative matching to sample. Akira showed a decrement of accuracy as a function of the display size when the search display was nonuniform (i.e., each "distractor" stimulus was not the same), whereas Chloe and Ai showed perfect performance. Furthermore, when the sample was identical to the uniform distractors in the search display, Chloe and Ai never selected an odd-item target, but Akira selected it when the display size was large. These results indicated that Akira's behavior was controlled mainly by relational cues of target-distractor oddity, whereas an identity relation between the sample and the target strongly controlled the performance of Chloe and Ai. PMID:7714449

Quetiapine versus aripiprazole in children and adolescents with psychosis - protocol for the randomised, blinded clinical Tolerability and Efficacy of Antipsychotics (TEA) trial

PubMed Central

2014-01-01

Background The evidence for choices between antipsychotics for children and adolescents with schizophrenia and other psychotic disorders is limited. The main objective of the Tolerability and Efficacy of Antipsychotics (TEA) trial is to compare the benefits and harms of quetiapine versus aripiprazole in children and adolescents with psychosis in order to inform rational, effective and safe treatment selections. Methods/Design The TEA trial is a Danish investigator-initiated, independently funded, multi-centre, randomised, blinded clinical trial. Based on sample size estimation, 112 patients aged 12-17 years with psychosis, antipsychotic-naïve or treated for a limited period are, 1:1 randomised to a 12- week, double-blind intervention with quetiapine versus aripiprazole. Effects on psychopathology, cognition, health-related quality of life, and adverse events are assessed 2, 4, and 12 weeks after randomisation. The primary outcome is change in the positive symptom score of the Positive and Negative Syndrome Scale. The recruitment period is 2010-2014. Discussion Antipsychotics are currently the only available pharmacologic treatments for psychotic disorders. However, information about head-to-head differences in efficacy and tolerability of antipsychotics are scarce in children and adolescents. The TEA trial aims at expanding the evidence base for the use of antipsychotics in early onset psychosis in order to inform more rational treatment decisions in this vulnerable population. Here, we account for the trial design, address methodological challenges, and discuss the estimation of sample size. Trial registration ClinicalTrials.gov: NCT01119014 PMID:25015535

Inclusion of trial functions in the Langevin equation path integral ground state method: Application to parahydrogen clusters and their isotopologues

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmidt, Matthew; Constable, Steve; Ing, Christopher

2014-06-21

We developed and studied the implementation of trial wavefunctions in the newly proposed Langevin equation Path Integral Ground State (LePIGS) method [S. Constable, M. Schmidt, C. Ing, T. Zeng, and P.-N. Roy, J. Phys. Chem. A 117, 7461 (2013)]. The LePIGS method is based on the Path Integral Ground State (PIGS) formalism combined with Path Integral Molecular Dynamics sampling using a Langevin equation based sampling of the canonical distribution. This LePIGS method originally incorporated a trivial trial wavefunction, ψ{sub T}, equal to unity. The present paper assesses the effectiveness of three different trial wavefunctions on three isotopes of hydrogen formore » cluster sizes N = 4, 8, and 13. The trial wavefunctions of interest are the unity trial wavefunction used in the original LePIGS work, a Jastrow trial wavefunction that includes correlations due to hard-core repulsions, and a normal mode trial wavefunction that includes information on the equilibrium geometry. Based on this analysis, we opt for the Jastrow wavefunction to calculate energetic and structural properties for parahydrogen, orthodeuterium, and paratritium clusters of size N = 4 − 19, 33. Energetic and structural properties are obtained and compared to earlier work based on Monte Carlo PIGS simulations to study the accuracy of the proposed approach. The new results for paratritium clusters will serve as benchmark for future studies. This paper provides a detailed, yet general method for optimizing the necessary parameters required for the study of the ground state of a large variety of systems.« less

Cluster randomized trials utilizing primary care electronic health records: methodological issues in design, conduct, and analysis (eCRT Study).

PubMed

Gulliford, Martin C; van Staa, Tjeerd P; McDermott, Lisa; McCann, Gerard; Charlton, Judith; Dregan, Alex

2014-06-11

There is growing interest in conducting clinical and cluster randomized trials through electronic health records. This paper reports on the methodological issues identified during the implementation of two cluster randomized trials using the electronic health records of the Clinical Practice Research Datalink (CPRD). Two trials were completed in primary care: one aimed to reduce inappropriate antibiotic prescribing for acute respiratory infection; the other aimed to increase physician adherence with secondary prevention interventions after first stroke. The paper draws on documentary records and trial datasets to report on the methodological experience with respect to research ethics and research governance approval, general practice recruitment and allocation, sample size calculation and power, intervention implementation, and trial analysis. We obtained research governance approvals from more than 150 primary care organizations in England, Wales, and Scotland. There were 104 CPRD general practices recruited to the antibiotic trial and 106 to the stroke trial, with the target number of practices being recruited within six months. Interventions were installed into practice information systems remotely over the internet. The mean number of participants per practice was 5,588 in the antibiotic trial and 110 in the stroke trial, with the coefficient of variation of practice sizes being 0.53 and 0.56 respectively. Outcome measures showed substantial correlations between the 12 months before, and after intervention, with coefficients ranging from 0.42 for diastolic blood pressure to 0.91 for proportion of consultations with antibiotics prescribed, defining practice and participant eligibility for analysis requires careful consideration. Cluster randomized trials may be performed efficiently in large samples from UK general practices using the electronic health records of a primary care database. The geographical dispersal of trial sites presents a difficulty for research governance approval and intervention implementation. Pretrial data analyses should inform trial design and analysis plans. Current Controlled Trials ISRCTN 47558792 and ISRCTN 35701810 (both registered on 17 March 2010).

Non-parametric methods for cost-effectiveness analysis: the central limit theorem and the bootstrap compared.

PubMed

Nixon, Richard M; Wonderling, David; Grieve, Richard D

2010-03-01

Cost-effectiveness analyses (CEA) alongside randomised controlled trials commonly estimate incremental net benefits (INB), with 95% confidence intervals, and compute cost-effectiveness acceptability curves and confidence ellipses. Two alternative non-parametric methods for estimating INB are to apply the central limit theorem (CLT) or to use the non-parametric bootstrap method, although it is unclear which method is preferable. This paper describes the statistical rationale underlying each of these methods and illustrates their application with a trial-based CEA. It compares the sampling uncertainty from using either technique in a Monte Carlo simulation. The experiments are repeated varying the sample size and the skewness of costs in the population. The results showed that, even when data were highly skewed, both methods accurately estimated the true standard errors (SEs) when sample sizes were moderate to large (n>50), and also gave good estimates for small data sets with low skewness. However, when sample sizes were relatively small and the data highly skewed, using the CLT rather than the bootstrap led to slightly more accurate SEs. We conclude that while in general using either method is appropriate, the CLT is easier to implement, and provides SEs that are at least as accurate as the bootstrap. (c) 2009 John Wiley & Sons, Ltd.

Further statistics in dentistry. Part 4: Clinical trials 2.

PubMed

Petrie, A; Bulman, J S; Osborn, J F

2002-11-23

The principles which underlie a well-designed clinical trial were introduced in a previous paper. The trial should be controlled (to ensure that the appropriate comparisons are made), randomised (to avoid allocation bias) and, preferably, blinded (to obviate assessment bias). However, taken in isolation, these concepts will not necessarily ensure that meaningful conclusions can be drawn from the study. It is essential that the sample size is large enough to enable the effects of interest to be estimated precisely, and to detect any real treatment differences.

Sample size calculation for studies with grouped survival data.

PubMed

Li, Zhiguo; Wang, Xiaofei; Wu, Yuan; Owzar, Kouros

2018-06-10

Grouped survival data arise often in studies where the disease status is assessed at regular visits to clinic. The time to the event of interest can only be determined to be between two adjacent visits or is right censored at one visit. In data analysis, replacing the survival time with the endpoint or midpoint of the grouping interval leads to biased estimators of the effect size in group comparisons. Prentice and Gloeckler developed a maximum likelihood estimator for the proportional hazards model with grouped survival data and the method has been widely applied. Previous work on sample size calculation for designing studies with grouped data is based on either the exponential distribution assumption or the approximation of variance under the alternative with variance under the null. Motivated by studies in HIV trials, cancer trials and in vitro experiments to study drug toxicity, we develop a sample size formula for studies with grouped survival endpoints that use the method of Prentice and Gloeckler for comparing two arms under the proportional hazards assumption. We do not impose any distributional assumptions, nor do we use any approximation of variance of the test statistic. The sample size formula only requires estimates of the hazard ratio and survival probabilities of the event time of interest and the censoring time at the endpoints of the grouping intervals for one of the two arms. The formula is shown to perform well in a simulation study and its application is illustrated in the three motivating examples. Copyright © 2018 John Wiley & Sons, Ltd.

Critical appraisal of fundamental items in approved clinical trial research proposals in Mashhad University of Medical Sciences

PubMed Central

Shakeri, Mohammad-Taghi; Taghipour, Ali; Sadeghi, Masoumeh; Nezami, Hossein; Amirabadizadeh, Ali-Reza; Bonakchi, Hossein

2017-01-01

Background: Writing, designing, and conducting a clinical trial research proposal has an important role in achieving valid and reliable findings. Thus, this study aimed at critically appraising fundamental information in approved clinical trial research proposals in Mashhad University of Medical Sciences (MUMS) from 2008 to 2014. Methods: This cross-sectional study was conducted on all 935 approved clinical trial research proposals in MUMS from 2008 to 2014. A valid and reliable as well as comprehensive, simple, and usable checklist in sessions with biostatisticians and methodologists, consisting of 11 main items as research tool, were used. Agreement rate between the reviewers of the proposals, who were responsible for data collection, was assessed during 3 sessions, and Kappa statistics was calculated at the last session as 97%. Results: More than 60% of the research proposals had a methodologist consultant, moreover, type of study or study design had been specified in almost all of them (98%). Appropriateness of study aims with hypotheses was not observed in a significant number of research proposals (585 proposals, 62.6%). The required sample size for 66.8% of the approved proposals was based on a sample size formula; however, in 25% of the proposals, sample size formula was not in accordance with the study design. Data collection tool was not selected appropriately in 55.2% of the approved research proposals. Type and method of randomization were unknown in 21% of the proposals and dealing with missing data had not been described in most of them (98%). Inclusion and exclusion criteria were (92%) fully and adequately explained. Moreover, 44% and 31% of the research proposals were moderate and weak in rank, respectively, with respect to the correctness of the statistical analysis methods. Conclusion: Findings of the present study revealed that a large portion of the approved proposals were highly biased or ambiguous with respect to randomization, blinding, dealing with missing data, data collection tool, sampling methods, and statistical analysis. Thus, it is essential to consult and collaborate with a methodologist in all parts of a proposal to control the possible and specific biases in clinical trials. PMID:29445703

Critical appraisal of fundamental items in approved clinical trial research proposals in Mashhad University of Medical Sciences.

PubMed

Shakeri, Mohammad-Taghi; Taghipour, Ali; Sadeghi, Masoumeh; Nezami, Hossein; Amirabadizadeh, Ali-Reza; Bonakchi, Hossein

2017-01-01

Background: Writing, designing, and conducting a clinical trial research proposal has an important role in achieving valid and reliable findings. Thus, this study aimed at critically appraising fundamental information in approved clinical trial research proposals in Mashhad University of Medical Sciences (MUMS) from 2008 to 2014. Methods: This cross-sectional study was conducted on all 935 approved clinical trial research proposals in MUMS from 2008 to 2014. A valid and reliable as well as comprehensive, simple, and usable checklist in sessions with biostatisticians and methodologists, consisting of 11 main items as research tool, were used. Agreement rate between the reviewers of the proposals, who were responsible for data collection, was assessed during 3 sessions, and Kappa statistics was calculated at the last session as 97%. Results: More than 60% of the research proposals had a methodologist consultant, moreover, type of study or study design had been specified in almost all of them (98%). Appropriateness of study aims with hypotheses was not observed in a significant number of research proposals (585 proposals, 62.6%). The required sample size for 66.8% of the approved proposals was based on a sample size formula; however, in 25% of the proposals, sample size formula was not in accordance with the study design. Data collection tool was not selected appropriately in 55.2% of the approved research proposals. Type and method of randomization were unknown in 21% of the proposals and dealing with missing data had not been described in most of them (98%). Inclusion and exclusion criteria were (92%) fully and adequately explained. Moreover, 44% and 31% of the research proposals were moderate and weak in rank, respectively, with respect to the correctness of the statistical analysis methods. Conclusion: Findings of the present study revealed that a large portion of the approved proposals were highly biased or ambiguous with respect to randomization, blinding, dealing with missing data, data collection tool, sampling methods, and statistical analysis. Thus, it is essential to consult and collaborate with a methodologist in all parts of a proposal to control the possible and specific biases in clinical trials.

Interpreting survival data from clinical trials of surgery versus stereotactic body radiation therapy in operable Stage I non-small cell lung cancer patients.

PubMed

Samson, Pamela; Keogan, Kathleen; Crabtree, Traves; Colditz, Graham; Broderick, Stephen; Puri, Varun; Meyers, Bryan

2017-01-01

To identify the variability of short- and long-term survival outcomes among closed Phase III randomized controlled trials with small sample sizes comparing SBRT (stereotactic body radiation therapy) and surgical resection in operable clinical Stage I non-small cell lung cancer (NSCLC) patients. Clinical Stage I NSCLC patients who underwent surgery at our institution meeting the inclusion/exclusion criteria for STARS (Randomized Study to Compare CyberKnife to Surgical Resection in Stage I Non-small Cell Lung Cancer), ROSEL (Trial of Either Surgery or Stereotactic Radiotherapy for Early Stage (IA) Lung Cancer), or both were identified. Bootstrapping analysis provided 10,000 iterations to depict 30-day mortality and three-year overall survival (OS) in cohorts of 16 patients (to simulate the STARS surgical arm), 27 patients (to simulate the pooled surgical arms of STARS and ROSEL), and 515 (to simulate the goal accrual for the surgical arm of STARS). From 2000 to 2012, 749/873 (86%) of clinical Stage I NSCLC patients who underwent resection were eligible for STARS only, ROSEL only, or both studies. When patients eligible for STARS only were repeatedly sampled with a cohort size of 16, the 3-year OS rates ranged from 27 to 100%, and 30-day mortality varied from 0 to 25%. When patients eligible for ROSEL or for both STARS and ROSEL underwent bootstrapping with n=27, the 3-year OS ranged from 46 to 100%, while 30-day mortality varied from 0 to 15%. Finally, when patients eligible for STARS were repeatedly sampled in groups of 515, 3-year OS narrowed to 70-85%, with 30-day mortality varying from 0 to 4%. Short- and long-term survival outcomes from trials with small sample sizes are extremely variable and unreliable for extrapolation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Design of a Phase III cluster randomized trial to assess the efficacy and safety of a malaria transmission blocking vaccine.

PubMed

Delrieu, Isabelle; Leboulleux, Didier; Ivinson, Karen; Gessner, Bradford D

2015-03-24

Vaccines interrupting Plasmodium falciparum malaria transmission targeting sexual, sporogonic, or mosquito-stage antigens (SSM-VIMT) are currently under development to reduce malaria transmission. An international group of malaria experts was established to evaluate the feasibility and optimal design of a Phase III cluster randomized trial (CRT) that could support regulatory review and approval of an SSM-VIMT. The consensus design is a CRT with a sentinel population randomly selected from defined inner and buffer zones in each cluster, a cluster size sufficient to assess true vaccine efficacy in the inner zone, and inclusion of ongoing assessment of vaccine impact stratified by distance of residence from the cluster edge. Trials should be conducted first in areas of moderate transmission, where SSM-VIMT impact should be greatest. Sample size estimates suggest that such a trial is feasible, and within the range of previously supported trials of malaria interventions, although substantial issues to implementation exist. Copyright © 2015 Elsevier Ltd. All rights reserved.

The effects of neutralized particles on the sampling efficiency of polyurethane foam used to estimate the extrathoracic deposition fraction.

PubMed

Tomyn, Ronald L; Sleeth, Darrah K; Thiese, Matthew S; Larson, Rodney R

2016-01-01

In addition to chemical composition, the site of deposition of inhaled particles is important for determining the potential health effects from an exposure. As a result, the International Organization for Standardization adopted a particle deposition sampling convention. This includes extrathoracic particle deposition sampling conventions for the anterior nasal passages (ET1) and the posterior nasal and oral passages (ET2). This study assessed how well a polyurethane foam insert placed in an Institute of Occupational Medicine (IOM) sampler can match an extrathoracic deposition sampling convention, while accounting for possible static buildup in the test particles. In this way, the study aimed to assess whether neutralized particles affected the performance of this sampler for estimating extrathoracic particle deposition. A total of three different particle sizes (4.9, 9.5, and 12.8 µm) were used. For each trial, one particle size was introduced into a low-speed wind tunnel with a wind speed set a 0.2 m/s (∼40 ft/min). This wind speed was chosen to closely match the conditions of most indoor working environments. Each particle size was tested twice either neutralized, using a high voltage neutralizer, or left in its normal (non neutralized) state as standard particles. IOM samplers were fitted with a polyurethane foam insert and placed on a rotating mannequin inside the wind tunnel. Foam sampling efficiencies were calculated for all trials to compare against the normalized ET1 sampling deposition convention. The foam sampling efficiencies matched well to the ET1 deposition convention for the larger particle sizes, but had a general trend of underestimating for all three particle sizes. The results of a Wilcoxon Rank Sum Test also showed that only at 4.9 µm was there a statistically significant difference (p-value = 0.03) between the foam sampling efficiency using the standard particles and the neutralized particles. This is interpreted to mean that static buildup may be occurring and neutralizing the particles that are 4.9 µm diameter in size did affect the performance of the foam sampler when estimating extrathoracic particle deposition.

A model-based approach to sample size estimation in recent onset type 1 diabetes.

PubMed

Bundy, Brian N; Krischer, Jeffrey P

2016-11-01

The area under the curve C-peptide following a 2-h mixed meal tolerance test from 498 individuals enrolled on five prior TrialNet studies of recent onset type 1 diabetes from baseline to 12 months after enrolment were modelled to produce estimates of its rate of loss and variance. Age at diagnosis and baseline C-peptide were found to be significant predictors, and adjusting for these in an ANCOVA resulted in estimates with lower variance. Using these results as planning parameters for new studies results in a nearly 50% reduction in the target sample size. The modelling also produces an expected C-peptide that can be used in observed versus expected calculations to estimate the presumption of benefit in ongoing trials. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Bayesian adaptive trials offer advantages in comparative effectiveness trials: an example in status epilepticus.

PubMed

Connor, Jason T; Elm, Jordan J; Broglio, Kristine R

2013-08-01

We present a novel Bayesian adaptive comparative effectiveness trial comparing three treatments for status epilepticus that uses adaptive randomization with potential early stopping. The trial will enroll 720 unique patients in emergency departments and uses a Bayesian adaptive design. The trial design is compared to a trial without adaptive randomization and produces an efficient trial in which a higher proportion of patients are likely to be randomized to the most effective treatment arm while generally using fewer total patients and offers higher power than an analogous trial with fixed randomization when identifying a superior treatment. When one treatment is superior to the other two, the trial design provides better patient care, higher power, and a lower expected sample size. Copyright © 2013 Elsevier Inc. All rights reserved.

[Methodological quality evaluation of randomized controlled trials for traditional Chinese medicines for treatment of sub-health].

PubMed

Zhao, Jun; Liao, Xing; Zhao, Hui; Li, Zhi-Geng; Wang, Nan-Yue; Wang, Li-Min

2016-11-01

To evaluate the methodological quality of the randomized controlled trials(RCTs) for traditional Chinese medicines for treatment of sub-health, in order to provide a scientific basis for the improvement of clinical trials and systematic review. Such databases as CNKI, CBM, VIP, Wanfang, EMbase, Medline, Clinical Trials, Web of Science and Cochrane Library were searched for RCTS for traditional Chinese medicines for treatment of sub-health between the time of establishment and February 29, 2016. Cochrane Handbook 5.1 was used to screen literatures and extract data, and CONSORT statement and CONSORT for traditional Chinese medicine statement were adopted as the basis for quality evaluation. Among the 72 RCTs included in this study, 67 (93.05%) trials described the inter-group baseline data comparability, 39(54.17%) trials described the unified diagnostic criteria, 28(38.89%) trials described the unified standards of efficacy, 4 (5.55%) trials mentioned the multi-center study, 19(26.38%) trials disclosed the random distribution method, 6(8.33%) trials used the random distribution concealment, 15(20.83%) trials adopted the method of blindness, 3(4.17%) study reported the sample size estimation in details, 5 (6.94%) trials showed a sample size of more than two hundred, 19(26.38%) trials reported the number of withdrawal, defluxion cases and those lost to follow-up, but only 2 trials adopted the ITT analysis,10(13.89%) trials reported the follow-up results, none of the trial reported the test registration and the test protocol, 48(66.7%) trials reported all of the indicators of expected outcomes, 26(36.11%) trials reported the adverse reactions and adverse events, and 4(5.56%) trials reported patient compliance. The overall quality of these randomized controlled trials for traditional Chinese medicines for treatment of sub-health is low, with methodological defects in different degrees. Therefore, it is still necessary to emphasize the correct application of principles such as blindness, randomization and control in RCTs, while requiring reporting in accordance with international standards. Copyright© by the Chinese Pharmaceutical Association.

[Sample size calculation in clinical post-marketing evaluation of traditional Chinese medicine].

PubMed

Fu, Yingkun; Xie, Yanming

2011-10-01

In recent years, as the Chinese government and people pay more attention on the post-marketing research of Chinese Medicine, part of traditional Chinese medicine breed has or is about to begin after the listing of post-marketing evaluation study. In the post-marketing evaluation design, sample size calculation plays a decisive role. It not only ensures the accuracy and reliability of post-marketing evaluation. but also assures that the intended trials will have a desired power for correctly detecting a clinically meaningful difference of different medicine under study if such a difference truly exists. Up to now, there is no systemic method of sample size calculation in view of the traditional Chinese medicine. In this paper, according to the basic method of sample size calculation and the characteristic of the traditional Chinese medicine clinical evaluation, the sample size calculation methods of the Chinese medicine efficacy and safety are discussed respectively. We hope the paper would be beneficial to medical researchers, and pharmaceutical scientists who are engaged in the areas of Chinese medicine research.

Are large clinical trials in orthopaedic trauma justified?

PubMed

Sprague, Sheila; Tornetta, Paul; Slobogean, Gerard P; O'Hara, Nathan N; McKay, Paula; Petrisor, Brad; Jeray, Kyle J; Schemitsch, Emil H; Sanders, David; Bhandari, Mohit

2018-04-20

The objective of this analysis is to evaluate the necessity of large clinical trials using FLOW trial data. The FLOW pilot study and definitive trial were factorial trials evaluating the effect of different irrigation solutions and pressures on re-operation. To explore treatment effects over time, we analyzed data from the pilot and definitive trial in increments of 250 patients until the final sample size of 2447 patients was reached. At each increment we calculated the relative risk (RR) and associated 95% confidence interval (CI) for the treatment effect, and compared the results that would have been reported at the smaller enrolments with those seen in the final, adequately powered study. The pilot study analysis of 89 patients and initial incremental enrolments in the FLOW definitive trial favored low pressure compared to high pressure (RR: 1.50, 95% CI: 0.75-3.04; RR: 1.39, 95% CI: 0.60-3.23, respectively), which is in contradiction to the final enrolment, which found no difference between high and low pressure (RR: 1.04, 95% CI: 0.81-1.33). In the soap versus saline comparison, the FLOW pilot study suggested that re-operation rate was similar in both the soap and saline groups (RR: 0.98, 95% CI: 0.50-1.92), whereas the FLOW definitive trial found that the re-operation rate was higher in the soap treatment arm (RR: 1.28, 95% CI: 1.04-1.57). Our findings suggest that studies with smaller sample sizes would have led to erroneous conclusions in the management of open fracture wounds. NCT01069315 (FLOW Pilot Study) Date of Registration: February 17, 2010, NCT00788398 (FLOW Definitive Trial) Date of Registration: November 10, 2008.

Published methodological quality of randomized controlled trials does not reflect the actual quality assessed in protocols.

PubMed

Mhaskar, Rahul; Djulbegovic, Benjamin; Magazin, Anja; Soares, Heloisa P; Kumar, Ambuj

2012-06-01

To assess whether the reported methodological quality of randomized controlled trials (RCTs) reflects the actual methodological quality and to evaluate the association of effect size (ES) and sample size with methodological quality. Systematic review. This is a retrospective analysis of all consecutive phase III RCTs published by eight National Cancer Institute Cooperative Groups up to 2006. Data were extracted from protocols (actual quality) and publications (reported quality) for each study. Four hundred twenty-nine RCTs met the inclusion criteria. Overall reporting of methodological quality was poor and did not reflect the actual high methodological quality of RCTs. The results showed no association between sample size and actual methodological quality of a trial. Poor reporting of allocation concealment and blinding exaggerated the ES by 6% (ratio of hazard ratio [RHR]: 0.94; 95% confidence interval [CI]: 0.88, 0.99) and 24% (RHR: 1.24; 95% CI: 1.05, 1.43), respectively. However, actual quality assessment showed no association between ES and methodological quality. The largest study to date shows that poor quality of reporting does not reflect the actual high methodological quality. Assessment of the impact of quality on the ES based on reported quality can produce misleading results. Copyright © 2012 Elsevier Inc. All rights reserved.

Nintendo Wii Fit as an adjunct to physiotherapy following lower limb fractures: preliminary feasibility, safety and sample size considerations.

PubMed

McPhail, S M; O'Hara, M; Gane, E; Tonks, P; Bullock-Saxton, J; Kuys, S S

2016-06-01

The Nintendo Wii Fit integrates virtual gaming with body movement, and may be suitable as an adjunct to conventional physiotherapy following lower limb fractures. This study examined the feasibility and safety of using the Wii Fit as an adjunct to outpatient physiotherapy following lower limb fractures, and reports sample size considerations for an appropriately powered randomised trial. Ambulatory patients receiving physiotherapy following a lower limb fracture participated in this study (n=18). All participants received usual care (individual physiotherapy). The first nine participants also used the Wii Fit under the supervision of their treating clinician as an adjunct to usual care. Adverse events, fracture malunion or exacerbation of symptoms were recorded. Pain, balance and patient-reported function were assessed at baseline and discharge from physiotherapy. No adverse events were attributed to either the usual care physiotherapy or Wii Fit intervention for any patient. Overall, 15 (83%) participants completed both assessments and interventions as scheduled. For 80% power in a clinical trial, the number of complete datasets required in each group to detect a small, medium or large effect of the Wii Fit at a post-intervention assessment was calculated at 175, 63 and 25, respectively. The Nintendo Wii Fit was safe and feasible as an adjunct to ambulatory physiotherapy in this sample. When considering a likely small effect size and the 17% dropout rate observed in this study, 211 participants would be required in each clinical trial group. A larger effect size or multiple repeated measures design would require fewer participants. Copyright © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

Designing clinical trials for amblyopia

PubMed Central

Holmes, Jonathan M.

2015-01-01

Randomized clinical trial (RCT) study design leads to one of the highest levels of evidence, and is a preferred study design over cohort studies, because randomization reduces bias and maximizes the chance that even unknown confounding factors will be balanced between treatment groups. Recent randomized clinical trials and observational studies in amblyopia can be taken together to formulate an evidence-based approach to amblyopia treatment, which is presented in this review. When designing future clinical studies of amblyopia treatment, issues such as regression to the mean, sample size and trial duration must be considered, since each may impact study results and conclusions. PMID:25752747

Design and implementation of a dental caries prevention trial in remote Canadian Aboriginal communities.

PubMed

Harrison, Rosamund; Veronneau, Jacques; Leroux, Brian

2010-05-13

The goal of this cluster randomized trial is to test the effectiveness of a counseling approach, Motivational Interviewing, to control dental caries in young Aboriginal children. Motivational Interviewing, a client-centred, directive counseling style, has not yet been evaluated as an approach for promotion of behaviour change in indigenous communities in remote settings. Aboriginal women were hired from the 9 communities to recruit expectant and new mothers to the trial, administer questionnaires and deliver the counseling to mothers in the test communities. The goal is for mothers to receive the intervention during pregnancy and at their child's immunization visits. Data on children's dental health status and family dental health practices will be collected when children are 30-months of age. The communities were randomly allocated to test or control group by a random "draw" over community radio. Sample size and power were determined based on an anticipated 20% reduction in caries prevalence. Randomization checks were conducted between groups. In the 5 test and 4 control communities, 272 of the original target sample size of 309 mothers have been recruited over a two-and-a-half year period. A power calculation using the actual attained sample size showed power to be 79% to detect a treatment effect. If an attrition fraction of 4% per year is maintained, power will remain at 80%. Power will still be > 90% to detect a 25% reduction in caries prevalence. The distribution of most baseline variables was similar for the two randomized groups of mothers. However, despite the random assignment of communities to treatment conditions, group differences exist for stage of pregnancy and prior tooth extractions in the family. Because of the group imbalances on certain variables, control of baseline variables will be done in the analyses of treatment effects. This paper explains the challenges of conducting randomized trials in remote settings, the importance of thorough community collaboration, and also illustrates the likelihood that some baseline variables that may be clinically important will be unevenly split in group-randomized trials when the number of groups is small. This trial is registered as ISRCTN41467632.

Big Data and Large Sample Size: A Cautionary Note on the Potential for Bias

PubMed Central

Chambers, David A.; Glasgow, Russell E.

2014-01-01

Abstract A number of commentaries have suggested that large studies are more reliable than smaller studies and there is a growing interest in the analysis of “big data” that integrates information from many thousands of persons and/or different data sources. We consider a variety of biases that are likely in the era of big data, including sampling error, measurement error, multiple comparisons errors, aggregation error, and errors associated with the systematic exclusion of information. Using examples from epidemiology, health services research, studies on determinants of health, and clinical trials, we conclude that it is necessary to exercise greater caution to be sure that big sample size does not lead to big inferential errors. Despite the advantages of big studies, large sample size can magnify the bias associated with error resulting from sampling or study design. Clin Trans Sci 2014; Volume #: 1–5 PMID:25043853

Social Stories in mainstream schools for children with autism spectrum disorder: a feasibility randomised controlled trial.

PubMed

Marshall, David; Wright, Barry; Allgar, Victoria; Adamson, Joy; Williams, Christine; Ainsworth, Hannah; Cook, Liz; Varley, Danielle; Hackney, Lisa; Dempster, Paul; Ali, Shehzad; Trepel, Dominic; Collingridge Moore, Danielle; Littlewood, Elizabeth; McMillan, Dean

2016-08-11

To assess the feasibility of recruitment, retention, outcome measures and intervention training/delivery among teachers, parents and children. To calculate a sample size estimation for full trial. A single-centre, unblinded, cluster feasibility randomised controlled trial examining Social Stories delivered within a school environment compared with an attentional control. 37 primary schools in York, UK. 50 participants were recruited and a cluster randomisation approach by school was examined. Participants were randomised into the treatment group (n=23) or a waiting list control group (n=27). Acceptability and feasibility of the trial, intervention and of measurements required to assess outcomes in a definitive trial. An assessment of the questionnaire completion rates indicated teachers would be most appropriate to complete the primary outcome measure. 2 outcome measures: the Social Responsiveness Scale (SRS)-2 and a goal-based measure showed both the highest levels of completion rates (above 80%) at the primary follow-up point (6 weeks postintervention) and captured relevant social and behaviour outcomes. Power calculations were based on these 2 outcome measures leading to a total proposed sample size of 180 participant groups. Results suggest that a future trial would be feasible to conduct and could inform the policy and practice of using Social Stories in mainstream schools. ISRCTN96286707; Results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Optimizing trial design in pharmacogenetics research: comparing a fixed parallel group, group sequential, and adaptive selection design on sample size requirements.

PubMed

Boessen, Ruud; van der Baan, Frederieke; Groenwold, Rolf; Egberts, Antoine; Klungel, Olaf; Grobbee, Diederick; Knol, Mirjam; Roes, Kit

2013-01-01

Two-stage clinical trial designs may be efficient in pharmacogenetics research when there is some but inconclusive evidence of effect modification by a genomic marker. Two-stage designs allow to stop early for efficacy or futility and can offer the additional opportunity to enrich the study population to a specific patient subgroup after an interim analysis. This study compared sample size requirements for fixed parallel group, group sequential, and adaptive selection designs with equal overall power and control of the family-wise type I error rate. The designs were evaluated across scenarios that defined the effect sizes in the marker positive and marker negative subgroups and the prevalence of marker positive patients in the overall study population. Effect sizes were chosen to reflect realistic planning scenarios, where at least some effect is present in the marker negative subgroup. In addition, scenarios were considered in which the assumed 'true' subgroup effects (i.e., the postulated effects) differed from those hypothesized at the planning stage. As expected, both two-stage designs generally required fewer patients than a fixed parallel group design, and the advantage increased as the difference between subgroups increased. The adaptive selection design added little further reduction in sample size, as compared with the group sequential design, when the postulated effect sizes were equal to those hypothesized at the planning stage. However, when the postulated effects deviated strongly in favor of enrichment, the comparative advantage of the adaptive selection design increased, which precisely reflects the adaptive nature of the design. Copyright © 2013 John Wiley & Sons, Ltd.

The correlation between the number of eligible patients in routine clinical practice and the low recruitment level in clinical trials: a retrospective study using electronic medical records.

PubMed

Sumi, Eriko; Teramukai, Satoshi; Yamamoto, Keiichi; Satoh, Motohiko; Yamanaka, Kenya; Yokode, Masayuki

2013-12-11

A number of clinical trials have encountered difficulties enrolling a sufficient number of patients upon initiating the trial. Recently, many screening systems that search clinical data warehouses for patients who are eligible for clinical trials have been developed. We aimed to estimate the number of eligible patients using routine electronic medical records (EMRs) and to predict the difficulty of enrolling sufficient patients prior to beginning a trial. Investigator-initiated clinical trials that were conducted at Kyoto University Hospital between July 2004 and January 2011 were included in this study. We searched the EMRs for eligible patients and calculated the eligible EMR patient index by dividing the number of eligible patients in the EMRs by the target sample size. Additionally, we divided the trial eligibility criteria into corresponding data elements in the EMRs to evaluate the completeness of mapping clinical manifestation in trial eligibility criteria into structured data elements in the EMRs. We evaluated the correlation between the index and the accrual achievement with Spearman's rank correlation coefficient. Thirteen of 19 trials did not achieve their original target sample size. Overall, 55% of the trial eligibility criteria were mapped into data elements in EMRs. The accrual achievement demonstrated a significant positive correlation with the eligible EMR patient index (r = 0.67, 95% confidence interval (CI), 0.42 to 0.92). The receiver operating characteristic analysis revealed an eligible EMR patient index cut-off value of 1.7, with a sensitivity of 69.2% and a specificity of 100.0%. Our study suggests that the eligible EMR patient index remains exploratory but could be a useful component of the feasibility study when planning a clinical trial. Establishing a step to check whether there are likely to be a sufficient number of eligible patients enables sponsors and investigators to concentrate their resources and efforts on more achievable trials.

Quality of Reporting Nutritional Randomized Controlled Trials in Patients With Cystic Fibrosis.

PubMed

Daitch, Vered; Babich, Tanya; Singer, Pierre; Leibovici, Leonard

2016-08-01

Randomized controlled trials (RCTs) have a major role in the making of evidence-based guidelines. The aim of the present study was to critically appraise the RCTs that addressed nutritional interventions in patients with cystic fibrosis. Embase, PubMed, and the Cochrane Library were systematically searched until July 2015. Methodology and reporting of nutritional RCTs were evaluated by the Consolidated Standards of Reporting Trials (CONSORT) checklist and additional dimensions relevant to patients with CF. Fifty-one RCTs were included. Full details on methods were provided in a minority of studies. The mean duration of intervention was <6 months. 56.9% of the RCTs did not define a primary outcome; 70.6% of studies did not provide details on sample size calculation; and only 31.4% reported on the subgroup or separated between important subgroups. The examined RCTs were characterized by a weak methodology, a small number of patients with no sample size calculations, a relatively short intervention, and many times did not examine the outcomes that are important to the patient. Improvement over the years has been minor.

The effect of waiting: A meta-analysis of wait-list control groups in trials for tinnitus distress.

PubMed

Hesser, Hugo; Weise, Cornelia; Rief, Winfried; Andersson, Gerhard

2011-04-01

The response rates and effects of being placed on a wait-list control condition are well documented in psychiatric populations. Despite the usefulness of such estimates and the frequent use of no-treatment controls in clinical trials for tinnitus, the effect of waiting in a tinnitus trial has not been investigated systematically. The aim of the present study was to quantify the overall effect of wait-list control groups on tinnitus distress. Studies were retrieved via a systematic review of randomised controlled trials of cognitive behaviour therapy for tinnitus distress. Outcomes of psychometrically robust tinnitus-specific measures (Tinnitus Handicap Inventory, Tinnitus Questionnaire, Tinnitus Reaction Questionnaire) from wait-list control groups were quantified using meta-analytic techniques. Percentage of change and standard mean difference effect sizes were calculated using the pre and post wait period. Eleven studies involving 314 wait-list subjects with tinnitus were located. The analysis for a waiting period of 6 to 12 weeks revealed a mean decrease in scores on tinnitus-specific measures of 3% to 8%. Across studies, a statically significant small mean within-group effect size was obtained (Hedges' g=.17). The effects were moderated by methodological quality of the trial, sample characteristics (i.e., age, tinnitus duration), time of the wait-list and how diagnosis was established. Subjects in a tinnitus trial improve in tinnitus distress over a short waiting phase. The effects of waiting are highly variable and depend on the characteristics of the sample and of the trial. Copyright © 2011 Elsevier Inc. All rights reserved.

Comparison of anticipated and actual control group outcomes in randomised trials in paediatric oncology provides evidence that historically controlled studies are biased in favour of the novel treatment.

PubMed

Moroz, Veronica; Wilson, Jayne S; Kearns, Pamela; Wheatley, Keith

2014-12-10

Historically controlled studies are commonly undertaken in paediatric oncology, despite their potential biases. Our aim was to compare the outcome of the control group in randomised controlled trials (RCTs) in paediatric oncology with those anticipated in the sample size calculations in the protocols. Our rationale was that, had these RCTs been performed as historical control studies instead, the available outcome data used to calculate the sample size in the RCT would have been used as the historical control outcome data. A systematic search was undertaken for published paediatric oncology RCTs using the Cochrane Central Register of Controlled Trials (CENTRAL) database from its inception up to July 2013. Data on sample size assumptions and observed outcomes (timetoevent and proportions) were extracted to calculate differences between randomised and historical control outcomes, and a one-sample t-test was employed to assess whether the difference between anticipated and observed control groups differed from zero. Forty-eight randomised questions were included. The median year of publication was 2005, and the range was from 1976 to 2010. There were 31 superiority and 11 equivalence/noninferiority randomised questions with time-to-event outcomes. The median absolute difference between observed and anticipated control outcomes was 5.0% (range: -23 to +34), and the mean difference was 3.8% (95% CI: +0.57 to +7.0; P = 0.022). Because the observed control group (that is, standard treatment arm) in RCTs performed better than anticipated, we found that historically controlled studies that used similar assumptions for the standard treatment were likely to overestimate the benefit of new treatments, potentially leading to children with cancer being given ineffective therapy that may have additional toxicity.

Applying Precision Medicine to Trial Design Using Physiology. Extracorporeal CO2 Removal for Acute Respiratory Distress Syndrome.

PubMed

Goligher, Ewan C; Amato, Marcelo B P; Slutsky, Arthur S

2017-09-01

In clinical trials of therapies for acute respiratory distress syndrome (ARDS), the average treatment effect in the study population may be attenuated because individual patient responses vary widely. This inflates sample size requirements and increases the cost and difficulty of conducting successful clinical trials. One solution is to enrich the study population with patients most likely to benefit, based on predicted patient response to treatment (predictive enrichment). In this perspective, we apply the precision medicine paradigm to the emerging use of extracorporeal CO 2 removal (ECCO 2 R) for ultraprotective ventilation in ARDS. ECCO 2 R enables reductions in tidal volume and driving pressure, key determinants of ventilator-induced lung injury. Using basic physiological concepts, we demonstrate that dead space and static compliance determine the effect of ECCO 2 R on driving pressure and mechanical power. This framework might enable prediction of individual treatment responses to ECCO 2 R. Enriching clinical trials by selectively enrolling patients with a significant predicted treatment response can increase treatment effect size and statistical power more efficiently than conventional enrichment strategies that restrict enrollment according to the baseline risk of death. To support this claim, we simulated the predicted effect of ECCO 2 R on driving pressure and mortality in a preexisting cohort of patients with ARDS. Our computations suggest that restricting enrollment to patients in whom ECCO 2 R allows driving pressure to be decreased by 5 cm H 2 O or more can reduce sample size requirement by more than 50% without increasing the total number of patients to be screened. We discuss potential implications for trial design based on this framework.

Statistical controversies in clinical research: building the bridge to phase II-efficacy estimation in dose-expansion cohorts.

PubMed

Boonstra, P S; Braun, T M; Taylor, J M G; Kidwell, K M; Bellile, E L; Daignault, S; Zhao, L; Griffith, K A; Lawrence, T S; Kalemkerian, G P; Schipper, M J

2017-07-01

Regulatory agencies and others have expressed concern about the uncritical use of dose expansion cohorts (DECs) in phase I oncology trials. Nonetheless, by several metrics-prevalence, size, and number-their popularity is increasing. Although early efficacy estimation in defined populations is a common primary endpoint of DECs, the types of designs best equipped to identify efficacy signals have not been established. We conducted a simulation study of six phase I design templates with multiple DECs: three dose-assignment/adjustment mechanisms multiplied by two analytic approaches for estimating efficacy after the trial is complete. We also investigated the effect of sample size and interim futility analysis on trial performance. Identifying populations in which the treatment is efficacious (true positives) and weeding out inefficacious treatment/populations (true negatives) are competing goals in these trials. Thus, we estimated true and false positive rates for each design. Adaptively updating the MTD during the DEC improved true positive rates by 8-43% compared with fixing the dose during the DEC phase while maintaining false positive rates. Inclusion of an interim futility analysis decreased the number of patients treated under inefficacious DECs without hurting performance. A substantial gain in efficiency is obtainable using a design template that statistically models toxicity and efficacy against dose level during expansion. Design choices for dose expansion should be motivated by and based upon expected performance. Similar to the common practice in single-arm phase II trials, cohort sample sizes should be justified with respect to their primary aim and include interim analyses to allow for early stopping. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Treatment of Middle East Respiratory Syndrome with a combination of lopinavir-ritonavir and interferon-β1b (MIRACLE trial): study protocol for a randomized controlled trial.

PubMed

Arabi, Yaseen M; Alothman, Adel; Balkhy, Hanan H; Al-Dawood, Abdulaziz; AlJohani, Sameera; Al Harbi, Shmeylan; Kojan, Suleiman; Al Jeraisy, Majed; Deeb, Ahmad M; Assiri, Abdullah M; Al-Hameed, Fahad; AlSaedi, Asim; Mandourah, Yasser; Almekhlafi, Ghaleb A; Sherbeeni, Nisreen Murad; Elzein, Fatehi Elnour; Memon, Javed; Taha, Yusri; Almotairi, Abdullah; Maghrabi, Khalid A; Qushmaq, Ismael; Al Bshabshe, Ali; Kharaba, Ayman; Shalhoub, Sarah; Jose, Jesna; Fowler, Robert A; Hayden, Frederick G; Hussein, Mohamed A

2018-01-30

It had been more than 5 years since the first case of Middle East Respiratory Syndrome coronavirus infection (MERS-CoV) was recorded, but no specific treatment has been investigated in randomized clinical trials. Results from in vitro and animal studies suggest that a combination of lopinavir/ritonavir and interferon-β1b (IFN-β1b) may be effective against MERS-CoV. The aim of this study is to investigate the efficacy of treatment with a combination of lopinavir/ritonavir and recombinant IFN-β1b provided with standard supportive care, compared to treatment with placebo provided with standard supportive care in patients with laboratory-confirmed MERS requiring hospital admission. The protocol is prepared in accordance with the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) guidelines. Hospitalized adult patients with laboratory-confirmed MERS will be enrolled in this recursive, two-stage, group sequential, multicenter, placebo-controlled, double-blind randomized controlled trial. The trial is initially designed to include 2 two-stage components. The first two-stage component is designed to adjust sample size and determine futility stopping, but not efficacy stopping. The second two-stage component is designed to determine efficacy stopping and possibly readjustment of sample size. The primary outcome is 90-day mortality. This will be the first randomized controlled trial of a potential treatment for MERS. The study is sponsored by King Abdullah International Medical Research Center, Riyadh, Saudi Arabia. Enrollment for this study began in November 2016, and has enrolled thirteen patients as of Jan 24-2018. ClinicalTrials.gov, ID: NCT02845843 . Registered on 27 July 2016.

How do you design randomised trials for smaller populations? A framework.

PubMed

Parmar, Mahesh K B; Sydes, Matthew R; Morris, Tim P

2016-11-25

How should we approach trial design when we can get some, but not all, of the way to the numbers required for a randomised phase III trial?We present an ordered framework for designing randomised trials to address the problem when the ideal sample size is considered larger than the number of participants that can be recruited in a reasonable time frame. Staying with the frequentist approach that is well accepted and understood in large trials, we propose a framework that includes small alterations to the design parameters. These aim to increase the numbers achievable and also potentially reduce the sample size target. The first step should always be to attempt to extend collaborations, consider broadening eligibility criteria and increase the accrual time or follow-up time. The second set of ordered considerations are the choice of research arm, outcome measures, power and target effect. If the revised design is still not feasible, in the third step we propose moving from two- to one-sided significance tests, changing the type I error rate, using covariate information at the design stage, re-randomising patients and borrowing external information.We discuss the benefits of some of these possible changes and warn against others. We illustrate, with a worked example based on the Euramos-1 trial, the application of this framework in designing a trial that is feasible, while still providing a good evidence base to evaluate a research treatment.This framework would allow appropriate evaluation of treatments when large-scale phase III trials are not possible, but where the need for high-quality randomised data is as pressing as it is for common diseases.

Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range.

PubMed

Luo, Dehui; Wan, Xiang; Liu, Jiming; Tong, Tiejun

2018-06-01

The era of big data is coming, and evidence-based medicine is attracting increasing attention to improve decision making in medical practice via integrating evidence from well designed and conducted clinical research. Meta-analysis is a statistical technique widely used in evidence-based medicine for analytically combining the findings from independent clinical trials to provide an overall estimation of a treatment effectiveness. The sample mean and standard deviation are two commonly used statistics in meta-analysis but some trials use the median, the minimum and maximum values, or sometimes the first and third quartiles to report the results. Thus, to pool results in a consistent format, researchers need to transform those information back to the sample mean and standard deviation. In this article, we investigate the optimal estimation of the sample mean for meta-analysis from both theoretical and empirical perspectives. A major drawback in the literature is that the sample size, needless to say its importance, is either ignored or used in a stepwise but somewhat arbitrary manner, e.g. the famous method proposed by Hozo et al. We solve this issue by incorporating the sample size in a smoothly changing weight in the estimators to reach the optimal estimation. Our proposed estimators not only improve the existing ones significantly but also share the same virtue of the simplicity. The real data application indicates that our proposed estimators are capable to serve as "rules of thumb" and will be widely applied in evidence-based medicine.

Impact of peer review on reports of randomised trials published in open peer review journals: retrospective before and after study

PubMed Central

Collins, Gary S; Boutron, Isabelle; Yu, Ly-Mee; Cook, Jonathan; Shanyinde, Milensu; Wharton, Rose; Shamseer, Larissa; Altman, Douglas G

2014-01-01

Objective To investigate the effectiveness of open peer review as a mechanism to improve the reporting of randomised trials published in biomedical journals. Design Retrospective before and after study. Setting BioMed Central series medical journals. Sample 93 primary reports of randomised trials published in BMC-series medical journals in 2012. Main outcome measures Changes to the reporting of methodological aspects of randomised trials in manuscripts after peer review, based on the CONSORT checklist, corresponding peer reviewer reports, the type of changes requested, and the extent to which authors adhered to these requests. Results Of the 93 trial reports, 38% (n=35) did not describe the method of random sequence generation, 54% (n=50) concealment of allocation sequence, 50% (n=46) whether the study was blinded, 34% (n=32) the sample size calculation, 35% (n=33) specification of primary and secondary outcomes, 55% (n=51) results for the primary outcome, and 90% (n=84) details of the trial protocol. The number of changes between manuscript versions was relatively small; most involved adding new information or altering existing information. Most changes requested by peer reviewers had a positive impact on the reporting of the final manuscript—for example, adding or clarifying randomisation and blinding (n=27), sample size (n=15), primary and secondary outcomes (n=16), results for primary or secondary outcomes (n=14), and toning down conclusions to reflect the results (n=27). Some changes requested by peer reviewers, however, had a negative impact, such as adding additional unplanned analyses (n=15). Conclusion Peer reviewers fail to detect important deficiencies in reporting of the methods and results of randomised trials. The number of these changes requested by peer reviewers was relatively small. Although most had a positive impact, some were inappropriate and could have a negative impact on reporting in the final publication. PMID:24986891

Global women's health: current clinical trials in low- and middle-income countries.

PubMed

Merriel, A; Harb, H M; Williams, H; Lilford, R; Coomarasamy, A

2015-01-01

Clinical trials in low- and middle-income countries (LMICs) are necessary to develop evidence-based approaches to improve women's health. Understanding what research is currently being conducted will allow the identification of research gaps, avoidance of duplication, planning of future studies, collaboration amongst research groups, and geographical targeting for research investments. To provide an overview of active women's health trials in LMICs. The World Health Organization's International Clinical Trials Registry Platform was searched for trials registered between 1 April 2012 and 31 March 2014. Selected trials were randomised, conducted in LMICs, active, and with a women's health intervention or a significant outcome for the woman. Two reviewers extracted data. Analysis included geographical spread, speciality areas, pre-enrolment registration, study size, and funders. Of the 8966 records, 509 were eligible for inclusion. Gynaecology trials made up 57% of the research, whereas the remaining 43% of trials were in obstetrics. Research activity focused on fertility (17%), the antenatal period (15%), benign gynaecology (14%), intrapartum care (9%), and pre-invasive disease and cancers (8%). The majority of trials (84%) took place in middle-income countries (MICs). In low-income countries (LICs) 83% of research investigated obstetrics, and in MICs 60% of research investigated gynaecology. Most trials (80%) had a sample size of 500 or fewer participants. The median size of trials in LICs was 815 compared with 128 in MICs. Pre-enrolment registration occurred in 54% of trials. The majority (62%) of trials were funded locally. Many LMICs are active in women's health research. The majority of registered trials are located in MICs; however, the trials in LICs are often larger. The focus of research in MICs may be driven by local priorities and funding, with fertility being highly researched. In LICs, pregnancy is the focus, perhaps reflecting the international prioritisation of maternal health. © 2014 Royal College of Obstetricians and Gynaecologists.

Complement pathway biomarkers and age-related macular degeneration

PubMed Central

Gemenetzi, M; Lotery, A J

2016-01-01

In the age-related macular degeneration (AMD) ‘inflammation model', local inflammation plus complement activation contributes to the pathogenesis and progression of the disease. Multiple genetic associations have now been established correlating the risk of development or progression of AMD. Stratifying patients by their AMD genetic profile may facilitate future AMD therapeutic trials resulting in meaningful clinical trial end points with smaller sample sizes and study duration. PMID:26493033

Coronary CT angiography using 64 detector rows: methods and design of the multi-centre trial CORE-64.

PubMed

Miller, Julie M; Dewey, Marc; Vavere, Andrea L; Rochitte, Carlos E; Niinuma, Hiroyuki; Arbab-Zadeh, Armin; Paul, Narinder; Hoe, John; de Roos, Albert; Yoshioka, Kunihiro; Lemos, Pedro A; Bush, David E; Lardo, Albert C; Texter, John; Brinker, Jeffery; Cox, Christopher; Clouse, Melvin E; Lima, João A C

2009-04-01

Multislice computed tomography (MSCT) for the noninvasive detection of coronary artery stenoses is a promising candidate for widespread clinical application because of its non-invasive nature and high sensitivity and negative predictive value as found in several previous studies using 16 to 64 simultaneous detector rows. A multi-centre study of CT coronary angiography using 16 simultaneous detector rows has shown that 16-slice CT is limited by a high number of nondiagnostic cases and a high false-positive rate. A recent meta-analysis indicated a significant interaction between the size of the study sample and the diagnostic odds ratios suggestive of small study bias, highlighting the importance of evaluating MSCT using 64 simultaneous detector rows in a multi-centre approach with a larger sample size. In this manuscript we detail the objectives and methods of the prospective "CORE-64" trial ("Coronary Evaluation Using Multidetector Spiral Computed Tomography Angiography using 64 Detectors"). This multi-centre trial was unique in that it assessed the diagnostic performance of 64-slice CT coronary angiography in nine centres worldwide in comparison to conventional coronary angiography. In conclusion, the multi-centre, multi-institutional and multi-continental trial CORE-64 has great potential to ultimately assess the per-patient diagnostic performance of coronary CT angiography using 64 simultaneous detector rows.

Two-stage phase II oncology designs using short-term endpoints for early stopping.

PubMed

Kunz, Cornelia U; Wason, James Ms; Kieser, Meinhard

2017-08-01

Phase II oncology trials are conducted to evaluate whether the tumour activity of a new treatment is promising enough to warrant further investigation. The most commonly used approach in this context is a two-stage single-arm design with binary endpoint. As for all designs with interim analysis, its efficiency strongly depends on the relation between recruitment rate and follow-up time required to measure the patients' outcomes. Usually, recruitment is postponed after the sample size of the first stage is achieved up until the outcomes of all patients are available. This may lead to a considerable increase of the trial length and with it to a delay in the drug development process. We propose a design where an intermediate endpoint is used in the interim analysis to decide whether or not the study is continued with a second stage. Optimal and minimax versions of this design are derived. The characteristics of the proposed design in terms of type I error rate, power, maximum and expected sample size as well as trial duration are investigated. Guidance is given on how to select the most appropriate design. Application is illustrated by a phase II oncology trial in patients with advanced angiosarcoma, which motivated this research.

Prospective registration trends, reasons for retrospective registration and mechanisms to increase prospective registration compliance: descriptive analysis and survey.

PubMed

Hunter, Kylie Elizabeth; Seidler, Anna Lene; Askie, Lisa M

2018-03-01

To analyse prospective versus retrospective trial registration trends on the Australian New Zealand Clinical Trials Registry (ANZCTR) and to evaluate the reasons for non-compliance with prospective registration. Part 1: Descriptive analysis of trial registration trends from 2006 to 2015. Part 2: Online registrant survey. Part 1: All interventional trials registered on ANZCTR from 2006 to 2015. Part 2: Random sample of those who had retrospectively registered a trial on ANZCTR between 2010 and 2015. Part 1: Proportion of prospective versus retrospective clinical trial registrations (ie, registration before versus after enrolment of the first participant) on the ANZCTR overall and by various key metrics, such as sponsor, funder, recruitment country and sample size. Part 2: Reasons for non-compliance with prospective registration and perceived usefulness of various proposed mechanisms to improve prospective registration compliance. Part 1: Analysis of the complete dataset of 9450 trials revealed that compliance with prospective registration increased from 48% (216 out of 446 trials) in 2006 to 63% (723/1148) in 2012 and has since plateaued at around 64%. Patterns of compliance were relatively consistent across sponsor and funder types (industry vs non-industry), type of intervention (drug vs non-drug) and size of trial (n<100, 100-500, >500). However, primary sponsors from Australia/New Zealand were almost twice as likely to register prospectively (62%; 4613/7452) compared with sponsors from other countries with a WHO Network Registry (35%; 377/1084) or sponsors from countries without a WHO Registry (29%; 230/781). Part 2: The majority (56%; 84/149) of survey respondents cited lack of awareness as a reason for not registering their study prospectively. Seventy-four per cent (111/149) stated that linking registration to ethics approval would facilitate prospective registration. Despite some progress, compliance with prospective registration remains suboptimal. Linking registration to ethics approval was the favoured strategy among those sampled for improving compliance. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Sample size considerations using mathematical models: an example with Chlamydia trachomatis infection and its sequelae pelvic inflammatory disease.

PubMed

Herzog, Sereina A; Low, Nicola; Berghold, Andrea

2015-06-19

The success of an intervention to prevent the complications of an infection is influenced by the natural history of the infection. Assumptions about the temporal relationship between infection and the development of sequelae can affect the predicted effect size of an intervention and the sample size calculation. This study investigates how a mathematical model can be used to inform sample size calculations for a randomised controlled trial (RCT) using the example of Chlamydia trachomatis infection and pelvic inflammatory disease (PID). We used a compartmental model to imitate the structure of a published RCT. We considered three different processes for the timing of PID development, in relation to the initial C. trachomatis infection: immediate, constant throughout, or at the end of the infectious period. For each process we assumed that, of all women infected, the same fraction would develop PID in the absence of an intervention. We examined two sets of assumptions used to calculate the sample size in a published RCT that investigated the effect of chlamydia screening on PID incidence. We also investigated the influence of the natural history parameters of chlamydia on the required sample size. The assumed event rates and effect sizes used for the sample size calculation implicitly determined the temporal relationship between chlamydia infection and PID in the model. Even small changes in the assumed PID incidence and relative risk (RR) led to considerable differences in the hypothesised mechanism of PID development. The RR and the sample size needed per group also depend on the natural history parameters of chlamydia. Mathematical modelling helps to understand the temporal relationship between an infection and its sequelae and can show how uncertainties about natural history parameters affect sample size calculations when planning a RCT.

Randomized clinical trials in dentistry: Risks of bias, risks of random errors, reporting quality, and methodologic quality over the years 1955–2013

PubMed Central

Armijo-Olivo, Susan; Cummings, Greta G.; Amin, Maryam; Flores-Mir, Carlos

2017-01-01

Objectives To examine the risks of bias, risks of random errors, reporting quality, and methodological quality of randomized clinical trials of oral health interventions and the development of these aspects over time. Methods We included 540 randomized clinical trials from 64 selected systematic reviews. We extracted, in duplicate, details from each of the selected randomized clinical trials with respect to publication and trial characteristics, reporting and methodologic characteristics, and Cochrane risk of bias domains. We analyzed data using logistic regression and Chi-square statistics. Results Sequence generation was assessed to be inadequate (at unclear or high risk of bias) in 68% (n = 367) of the trials, while allocation concealment was inadequate in the majority of trials (n = 464; 85.9%). Blinding of participants and blinding of the outcome assessment were judged to be inadequate in 28.5% (n = 154) and 40.5% (n = 219) of the trials, respectively. A sample size calculation before the initiation of the study was not performed/reported in 79.1% (n = 427) of the trials, while the sample size was assessed as adequate in only 17.6% (n = 95) of the trials. Two thirds of the trials were not described as double blinded (n = 358; 66.3%), while the method of blinding was appropriate in 53% (n = 286) of the trials. We identified a significant decrease over time (1955–2013) in the proportion of trials assessed as having inadequately addressed methodological quality items (P < 0.05) in 30 out of the 40 quality criteria, or as being inadequate (at high or unclear risk of bias) in five domains of the Cochrane risk of bias tool: sequence generation, allocation concealment, incomplete outcome data, other sources of bias, and overall risk of bias. Conclusions The risks of bias, risks of random errors, reporting quality, and methodological quality of randomized clinical trials of oral health interventions have improved over time; however, further efforts that contribute to the development of more stringent methodology and detailed reporting of trials are still needed. PMID:29272315

Randomized clinical trials in dentistry: Risks of bias, risks of random errors, reporting quality, and methodologic quality over the years 1955-2013.

PubMed

Saltaji, Humam; Armijo-Olivo, Susan; Cummings, Greta G; Amin, Maryam; Flores-Mir, Carlos

2017-01-01

To examine the risks of bias, risks of random errors, reporting quality, and methodological quality of randomized clinical trials of oral health interventions and the development of these aspects over time. We included 540 randomized clinical trials from 64 selected systematic reviews. We extracted, in duplicate, details from each of the selected randomized clinical trials with respect to publication and trial characteristics, reporting and methodologic characteristics, and Cochrane risk of bias domains. We analyzed data using logistic regression and Chi-square statistics. Sequence generation was assessed to be inadequate (at unclear or high risk of bias) in 68% (n = 367) of the trials, while allocation concealment was inadequate in the majority of trials (n = 464; 85.9%). Blinding of participants and blinding of the outcome assessment were judged to be inadequate in 28.5% (n = 154) and 40.5% (n = 219) of the trials, respectively. A sample size calculation before the initiation of the study was not performed/reported in 79.1% (n = 427) of the trials, while the sample size was assessed as adequate in only 17.6% (n = 95) of the trials. Two thirds of the trials were not described as double blinded (n = 358; 66.3%), while the method of blinding was appropriate in 53% (n = 286) of the trials. We identified a significant decrease over time (1955-2013) in the proportion of trials assessed as having inadequately addressed methodological quality items (P < 0.05) in 30 out of the 40 quality criteria, or as being inadequate (at high or unclear risk of bias) in five domains of the Cochrane risk of bias tool: sequence generation, allocation concealment, incomplete outcome data, other sources of bias, and overall risk of bias. The risks of bias, risks of random errors, reporting quality, and methodological quality of randomized clinical trials of oral health interventions have improved over time; however, further efforts that contribute to the development of more stringent methodology and detailed reporting of trials are still needed.

Pharmacist-led management of chronic pain in primary care: costs and benefits in a pilot randomised controlled trial.

PubMed

Neilson, Aileen R; Bruhn, Hanne; Bond, Christine M; Elliott, Alison M; Smith, Blair H; Hannaford, Philip C; Holland, Richard; Lee, Amanda J; Watson, Margaret; Wright, David; McNamee, Paul

2015-04-01

To explore differences in mean costs (from a UK National Health Service perspective) and effects of pharmacist-led management of chronic pain in primary care evaluated in a pilot randomised controlled trial (RCT), and to estimate optimal sample size for a definitive RCT. Regression analysis of costs and effects, using intention-to-treat and expected value of sample information analysis (EVSI). Six general practices: Grampian (3); East Anglia (3). 125 patients with complete resource use and short form-six-dimension questionnaire (SF-6D) data at baseline, 3 months and 6 months. Patients were randomised to either pharmacist medication review with face-to-face pharmacist prescribing or pharmacist medication review with feedback to general practitioner or treatment as usual (TAU). Differences in mean total costs and effects measured as quality-adjusted life years (QALYs) at 6 months and EVSI for sample size calculation. Unadjusted total mean costs per patient were £452 for prescribing (SD: £466), £570 for review (SD: £527) and £668 for TAU (SD: £1333). After controlling for baseline costs, the adjusted mean cost differences per patient relative to TAU were £77 for prescribing (95% CI -82 to 237) and £54 for review (95% CI -103 to 212). Unadjusted mean QALYs were 0.3213 for prescribing (SD: 0.0659), 0.3161 for review (SD: 0.0684) and 0.3079 for TAU (SD: 0.0606). Relative to TAU, the adjusted mean differences were 0.0069 for prescribing (95% CI -0.0091 to 0.0229) and 0.0097 for review (95% CI -0.0054 to 0.0248). The EVSI suggested the optimal future trial size was between 460 and 690, and between 540 and 780 patients per arm using a threshold of £30,000 and £20,000 per QALY gained, respectively. Compared with TAU, pharmacist-led interventions for chronic pain appear more costly and provide similar QALYs. However, these estimates are imprecise due to the small size of the pilot trial. The EVSI indicates that a larger trial is necessary to obtain more precise estimates of differences in mean effects and costs between treatment groups. ISRCTN06131530. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Testing for qualitative heterogeneity: An application to composite endpoints in survival analysis.

PubMed

Oulhaj, Abderrahim; El Ghouch, Anouar; Holman, Rury R

2017-01-01

Composite endpoints are frequently used in clinical outcome trials to provide more endpoints, thereby increasing statistical power. A key requirement for a composite endpoint to be meaningful is the absence of the so-called qualitative heterogeneity to ensure a valid overall interpretation of any treatment effect identified. Qualitative heterogeneity occurs when individual components of a composite endpoint exhibit differences in the direction of a treatment effect. In this paper, we develop a general statistical method to test for qualitative heterogeneity, that is to test whether a given set of parameters share the same sign. This method is based on the intersection-union principle and, provided that the sample size is large, is valid whatever the model used for parameters estimation. We propose two versions of our testing procedure, one based on a random sampling from a Gaussian distribution and another version based on bootstrapping. Our work covers both the case of completely observed data and the case where some observations are censored which is an important issue in many clinical trials. We evaluated the size and power of our proposed tests by carrying out some extensive Monte Carlo simulations in the case of multivariate time to event data. The simulations were designed under a variety of conditions on dimensionality, censoring rate, sample size and correlation structure. Our testing procedure showed very good performances in terms of statistical power and type I error. The proposed test was applied to a data set from a single-center, randomized, double-blind controlled trial in the area of Alzheimer's disease.

Optimizing image registration and infarct definition in stroke research.

PubMed

Harston, George W J; Minks, David; Sheerin, Fintan; Payne, Stephen J; Chappell, Michael; Jezzard, Peter; Jenkinson, Mark; Kennedy, James

2017-03-01

Accurate representation of final infarct volume is essential for assessing the efficacy of stroke interventions in imaging-based studies. This study defines the impact of image registration methods used at different timepoints following stroke, and the implications for infarct definition in stroke research. Patients presenting with acute ischemic stroke were imaged serially using magnetic resonance imaging. Infarct volume was defined manually using four metrics: 24-h b1000 imaging; 1-week and 1-month T2-weighted FLAIR; and automatically using predefined thresholds of ADC at 24 h. Infarct overlap statistics and volumes were compared across timepoints following both rigid body and nonlinear image registration to the presenting MRI. The effect of nonlinear registration on a hypothetical trial sample size was calculated. Thirty-seven patients were included. Nonlinear registration improved infarct overlap statistics and consistency of total infarct volumes across timepoints, and reduced infarct volumes by 4.0 mL (13.1%) and 7.1 mL (18.2%) at 24 h and 1 week, respectively, compared to rigid body registration. Infarct volume at 24 h, defined using a predetermined ADC threshold, was less sensitive to infarction than b1000 imaging. 1-week T2-weighted FLAIR imaging was the most accurate representation of final infarct volume. Nonlinear registration reduced hypothetical trial sample size, independent of infarct volume, by an average of 13%. Nonlinear image registration may offer the opportunity of improving the accuracy of infarct definition in serial imaging studies compared to rigid body registration, helping to overcome the challenges of anatomical distortions at subacute timepoints, and reducing sample size for imaging-based clinical trials.

Center-Within-Trial Versus Trial-Level Evaluation of Surrogate Endpoints.

PubMed

Renfro, Lindsay A; Shi, Qian; Xue, Yuan; Li, Junlong; Shang, Hongwei; Sargent, Daniel J

2014-10-01

Evaluation of candidate surrogate endpoints using individual patient data from multiple clinical trials is considered the gold standard approach to validate surrogates at both patient and trial levels. However, this approach assumes the availability of patient-level data from a relatively large collection of similar trials, which may not be possible to achieve for a given disease application. One common solution to the problem of too few similar trials involves performing trial-level surrogacy analyses on trial sub-units (e.g., centers within trials), thereby artificially increasing the trial-level sample size for feasibility of the multi-trial analysis. To date, the practical impact of treating trial sub-units (centers) identically to trials in multi-trial surrogacy analyses remains unexplored, and conditions under which this ad hoc solution may in fact be reasonable have not been identified. We perform a simulation study to identify such conditions, and demonstrate practical implications using a multi-trial dataset of patients with early stage colon cancer.

Center-Within-Trial Versus Trial-Level Evaluation of Surrogate Endpoints

PubMed Central

Renfro, Lindsay A.; Shi, Qian; Xue, Yuan; Li, Junlong; Shang, Hongwei; Sargent, Daniel J.

2014-01-01

Evaluation of candidate surrogate endpoints using individual patient data from multiple clinical trials is considered the gold standard approach to validate surrogates at both patient and trial levels. However, this approach assumes the availability of patient-level data from a relatively large collection of similar trials, which may not be possible to achieve for a given disease application. One common solution to the problem of too few similar trials involves performing trial-level surrogacy analyses on trial sub-units (e.g., centers within trials), thereby artificially increasing the trial-level sample size for feasibility of the multi-trial analysis. To date, the practical impact of treating trial sub-units (centers) identically to trials in multi-trial surrogacy analyses remains unexplored, and conditions under which this ad hoc solution may in fact be reasonable have not been identified. We perform a simulation study to identify such conditions, and demonstrate practical implications using a multi-trial dataset of patients with early stage colon cancer. PMID:25061255

Robust Covariate-Adjusted Log-Rank Statistics and Corresponding Sample Size Formula for Recurrent Events Data

PubMed Central

Song, Rui; Kosorok, Michael R.; Cai, Jianwen

2009-01-01

Summary Recurrent events data are frequently encountered in clinical trials. This article develops robust covariate-adjusted log-rank statistics applied to recurrent events data with arbitrary numbers of events under independent censoring and the corresponding sample size formula. The proposed log-rank tests are robust with respect to different data-generating processes and are adjusted for predictive covariates. It reduces to the Kong and Slud (1997, Biometrika 84, 847–862) setting in the case of a single event. The sample size formula is derived based on the asymptotic normality of the covariate-adjusted log-rank statistics under certain local alternatives and a working model for baseline covariates in the recurrent event data context. When the effect size is small and the baseline covariates do not contain significant information about event times, it reduces to the same form as that of Schoenfeld (1983, Biometrics 39, 499–503) for cases of a single event or independent event times within a subject. We carry out simulations to study the control of type I error and the comparison of powers between several methods in finite samples. The proposed sample size formula is illustrated using data from an rhDNase study. PMID:18162107

Small Sample Performance of Bias-corrected Sandwich Estimators for Cluster-Randomized Trials with Binary Outcomes

PubMed Central

Li, Peng; Redden, David T.

2014-01-01

SUMMARY The sandwich estimator in generalized estimating equations (GEE) approach underestimates the true variance in small samples and consequently results in inflated type I error rates in hypothesis testing. This fact limits the application of the GEE in cluster-randomized trials (CRTs) with few clusters. Under various CRT scenarios with correlated binary outcomes, we evaluate the small sample properties of the GEE Wald tests using bias-corrected sandwich estimators. Our results suggest that the GEE Wald z test should be avoided in the analyses of CRTs with few clusters even when bias-corrected sandwich estimators are used. With t-distribution approximation, the Kauermann and Carroll (KC)-correction can keep the test size to nominal levels even when the number of clusters is as low as 10, and is robust to the moderate variation of the cluster sizes. However, in cases with large variations in cluster sizes, the Fay and Graubard (FG)-correction should be used instead. Furthermore, we derive a formula to calculate the power and minimum total number of clusters one needs using the t test and KC-correction for the CRTs with binary outcomes. The power levels as predicted by the proposed formula agree well with the empirical powers from the simulations. The proposed methods are illustrated using real CRT data. We conclude that with appropriate control of type I error rates under small sample sizes, we recommend the use of GEE approach in CRTs with binary outcomes due to fewer assumptions and robustness to the misspecification of the covariance structure. PMID:25345738

Type I error probabilities based on design-stage strategies with applications to noninferiority trials.

PubMed

Rothmann, Mark

2005-01-01

When testing the equality of means from two different populations, a t-test or large sample normal test tend to be performed. For these tests, when the sample size or design for the second sample is dependent on the results of the first sample, the type I error probability is altered for each specific possibility in the null hypothesis. We will examine the impact on the type I error probabilities for two confidence interval procedures and procedures using test statistics when the design for the second sample or experiment is dependent on the results from the first sample or experiment (or series of experiments). Ways for controlling a desired maximum type I error probability or a desired type I error rate will be discussed. Results are applied to the setting of noninferiority comparisons in active controlled trials where the use of a placebo is unethical.

Longitudinal white matter change in frontotemporal dementia subtypes and sporadic late onset Alzheimer's disease.

PubMed

Elahi, Fanny M; Marx, Gabe; Cobigo, Yann; Staffaroni, Adam M; Kornak, John; Tosun, Duygu; Boxer, Adam L; Kramer, Joel H; Miller, Bruce L; Rosen, Howard J

2017-01-01

Degradation of white matter microstructure has been demonstrated in frontotemporal lobar degeneration (FTLD) and Alzheimer's disease (AD). In preparation for clinical trials, ongoing studies are investigating the utility of longitudinal brain imaging for quantification of disease progression. To date only one study has examined sample size calculations based on longitudinal changes in white matter integrity in FTLD. To quantify longitudinal changes in white matter microstructural integrity in the three canonical subtypes of frontotemporal dementia (FTD) and AD using diffusion tensor imaging (DTI). 60 patients with clinical diagnoses of FTD, including 27 with behavioral variant frontotemporal dementia (bvFTD), 14 with non-fluent variant primary progressive aphasia (nfvPPA), and 19 with semantic variant PPA (svPPA), as well as 19 patients with AD and 69 healthy controls were studied. We used a voxel-wise approach to calculate annual rate of change in fractional anisotropy (FA) and mean diffusivity (MD) in each group using two time points approximately one year apart. Mean rates of change in FA and MD in 48 atlas-based regions-of-interest, as well as global measures of cognitive function were used to calculate sample sizes for clinical trials (80% power, alpha of 5%). All FTD groups showed statistically significant baseline and longitudinal white matter degeneration, with predominant involvement of frontal tracts in the bvFTD group, frontal and temporal tracts in the PPA groups and posterior tracts in the AD group. Longitudinal change in MD yielded a larger number of regions with sample sizes below 100 participants per therapeutic arm in comparison with FA. SvPPA had the smallest sample size based on change in MD in the fornix (n = 41 participants per study arm to detect a 40% effect of drug), and nfvPPA and AD had their smallest sample sizes based on rate of change in MD within the left superior longitudinal fasciculus (n = 49 for nfvPPA, and n = 23 for AD). BvFTD generally showed the largest sample size estimates (minimum n = 140 based on MD in the corpus callosum). The corpus callosum appeared to be the best region for a potential study that would include all FTD subtypes. Change in global measure of functional status (CDR box score) yielded the smallest sample size for bvFTD (n = 71), but clinical measures were inferior to white matter change for the other groups. All three of the canonical subtypes of FTD are associated with significant change in white matter integrity over one year. These changes are consistent enough that drug effects in future clinical trials could be detected with relatively small numbers of participants. While there are some differences in regions of change across groups, the genu of the corpus callosum is a region that could be used to track progression in studies that include all subtypes.

The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method

PubMed Central

2014-01-01

Background The DerSimonian and Laird approach (DL) is widely used for random effects meta-analysis, but this often results in inappropriate type I error rates. The method described by Hartung, Knapp, Sidik and Jonkman (HKSJ) is known to perform better when trials of similar size are combined. However evidence in realistic situations, where one trial might be much larger than the other trials, is lacking. We aimed to evaluate the relative performance of the DL and HKSJ methods when studies of different sizes are combined and to develop a simple method to convert DL results to HKSJ results. Methods We evaluated the performance of the HKSJ versus DL approach in simulated meta-analyses of 2–20 trials with varying sample sizes and between-study heterogeneity, and allowing trials to have various sizes, e.g. 25% of the trials being 10-times larger than the smaller trials. We also compared the number of “positive” (statistically significant at p < 0.05) findings using empirical data of recent meta-analyses with > = 3 studies of interventions from the Cochrane Database of Systematic Reviews. Results The simulations showed that the HKSJ method consistently resulted in more adequate error rates than the DL method. When the significance level was 5%, the HKSJ error rates at most doubled, whereas for DL they could be over 30%. DL, and, far less so, HKSJ had more inflated error rates when the combined studies had unequal sizes and between-study heterogeneity. The empirical data from 689 meta-analyses showed that 25.1% of the significant findings for the DL method were non-significant with the HKSJ method. DL results can be easily converted into HKSJ results. Conclusions Our simulations showed that the HKSJ method consistently results in more adequate error rates than the DL method, especially when the number of studies is small, and can easily be applied routinely in meta-analyses. Even with the HKSJ method, extra caution is needed when there are = <5 studies of very unequal sizes. PMID:24548571

Aerostat-based sampling of emissions from open burning and open detonation of military ordnance.

PubMed

Aurell, Johanna; Gullett, Brian K; Tabor, Dennis; Williams, Ryan K; Mitchell, William; Kemme, Michael R

2015-03-02

Emissions from open detonation (OD), open burning (OB), and static firing (SF) of obsolete military munitions were collected using an aerostat-lofted sampling instrument maneuvered into the plumes with remotely controlled tether winches. PM2.5, PM10, metals, volatile organic compounds (VOCs), energetics, and polyaromatic hydrocarbons (PAHs) were characterized from 121 trials of three different munitions (Composition B (hereafter, "Comp B"), V453, V548), 152 trials of five different propellants (M31A1E1, M26, SPCF, Arc 451, 452A), and 12 trials with static firing of ammonium perchlorate-containing Sparrow rocket motors. Sampling was conducted with operational charge sizes and under open area conditions to determine emission levels representative of actual disposal practices. The successful application of the tethered aerostat and sampling instruments demonstrated the ability to sample for and determine the first ever emission factors for static firing of rocket motors and buried and metal-cased OD, as well as the first measurements of PM2.5 for OB and for surface OD. Published by Elsevier B.V.

Design and analysis of group-randomized trials in cancer: A review of current practices.

PubMed

Murray, David M; Pals, Sherri L; George, Stephanie M; Kuzmichev, Andrey; Lai, Gabriel Y; Lee, Jocelyn A; Myles, Ranell L; Nelson, Shakira M

2018-06-01

The purpose of this paper is to summarize current practices for the design and analysis of group-randomized trials involving cancer-related risk factors or outcomes and to offer recommendations to improve future trials. We searched for group-randomized trials involving cancer-related risk factors or outcomes that were published or online in peer-reviewed journals in 2011-15. During 2016-17, in Bethesda MD, we reviewed 123 articles from 76 journals to characterize their design and their methods for sample size estimation and data analysis. Only 66 (53.7%) of the articles reported appropriate methods for sample size estimation. Only 63 (51.2%) reported exclusively appropriate methods for analysis. These findings suggest that many investigators do not adequately attend to the methodological challenges inherent in group-randomized trials. These practices can lead to underpowered studies, to an inflated type 1 error rate, and to inferences that mislead readers. Investigators should work with biostatisticians or other methodologists familiar with these issues. Funders and editors should ensure careful methodological review of applications and manuscripts. Reviewers should ensure that studies are properly planned and analyzed. These steps are needed to improve the rigor and reproducibility of group-randomized trials. The Office of Disease Prevention (ODP) at the National Institutes of Health (NIH) has taken several steps to address these issues. ODP offers an online course on the design and analysis of group-randomized trials. ODP is working to increase the number of methodologists who serve on grant review panels. ODP has developed standard language for the Application Guide and the Review Criteria to draw investigators' attention to these issues. Finally, ODP has created a new Research Methods Resources website to help investigators, reviewers, and NIH staff better understand these issues. Published by Elsevier Inc.

A group sequential adaptive treatment assignment design for proof of concept and dose selection in headache trials.

PubMed

Hall, David B; Meier, Ulrich; Diener, Hans-Cristoph

2005-06-01

The trial objective was to test whether a new mechanism of action would effectively treat migraine headaches and to select a dose range for further investigation. The motivation for a group sequential, adaptive, placebo-controlled trial design was (1) limited information about where across the range of seven doses to focus attention, (2) a need to limit sample size for a complicated inpatient treatment and (3) a desire to reduce exposure of patients to ineffective treatment. A design based on group sequential and up and down designs was developed and operational characteristics were explored by trial simulation. The primary outcome was headache response at 2 h after treatment. Groups of four treated and two placebo patients were assigned to one dose. Adaptive dose selection was based on response rates of 60% seen with other migraine treatments. If more than 60% of treated patients responded, then the next dose was the next lower dose; otherwise, the dose was increased. A stopping rule of at least five groups at the target dose and at least four groups at that dose with more than 60% response was developed to ensure that a selected dose would be statistically significantly (p=0.05) superior to placebo. Simulations indicated good characteristics in terms of control of type 1 error, sufficient power, modest expected sample size and modest bias in estimation. The trial design is attractive for phase 2 clinical trials when response is acute and simple, ideally binary, placebo comparator is required, and patient accrual is relatively slow allowing for the collection and processing of results as a basis for the adaptive assignment of patients to dose groups. The acute migraine trial based on this design was successful in both proof of concept and dose range selection.

Influence of control group on effect size in trials of acupuncture for chronic pain: a secondary analysis of an individual patient data meta-analysis.

PubMed

MacPherson, Hugh; Vertosick, Emily; Lewith, George; Linde, Klaus; Sherman, Karen J; Witt, Claudia M; Vickers, Andrew J

2014-01-01

In a recent individual patient data meta-analysis, acupuncture was found to be superior to both sham and non-sham controls in patients with chronic pain. In this paper we identify variations in types of sham and non-sham controls used and analyze their impact on the effect size of acupuncture. Based on literature searches of acupuncture trials involving patients with headache and migraine, osteoarthritis, and back, neck and shoulder pain, 29 trials met inclusion criteria, 20 involving sham controls (n = 5,230) and 18 non-sham controls (n = 14,597). For sham controls, we analysed non-needle sham, penetrating sham needles and non-penetrating sham needles. For non-sham controls, we analysed non-specified routine care and protocol-guided care. Using meta-regression we explored impact of choice of control on effect of acupuncture. Acupuncture was significantly superior to all categories of control group. For trials that used penetrating needles for sham control, acupuncture had smaller effect sizes than for trials with non-penetrating sham or sham control without needles. The difference in effect size was -0.45 (95% C.I. -0.78, -0.12; p = 0.007), or -0.19 (95% C.I. -0.39, 0.01; p = 0.058) after exclusion of outlying studies showing very large effects of acupuncture. In trials with non-sham controls, larger effect sizes associated with acupuncture vs. non-specified routine care than vs. protocol-guided care. Although the difference in effect size was large (0.26), it was not significant with a wide confidence interval (95% C.I. -0.05, 0.57, p = 0.1). Acupuncture is significantly superior to control irrespective of the subtype of control. While the choice of control should be driven by the study question, our findings can help inform study design in acupuncture, particularly with respect to sample size. Penetrating needles appear to have important physiologic activity. We recommend that this type of sham be avoided.

Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications.

PubMed

Graf, Alexandra C; Bauer, Peter; Glimm, Ekkehard; Koenig, Franz

2014-07-01

Sample size modifications in the interim analyses of an adaptive design can inflate the type 1 error rate, if test statistics and critical boundaries are used in the final analysis as if no modification had been made. While this is already true for designs with an overall change of the sample size in a balanced treatment-control comparison, the inflation can be much larger if in addition a modification of allocation ratios is allowed as well. In this paper, we investigate adaptive designs with several treatment arms compared to a single common control group. Regarding modifications, we consider treatment arm selection as well as modifications of overall sample size and allocation ratios. The inflation is quantified for two approaches: a naive procedure that ignores not only all modifications, but also the multiplicity issue arising from the many-to-one comparison, and a Dunnett procedure that ignores modifications, but adjusts for the initially started multiple treatments. The maximum inflation of the type 1 error rate for such types of design can be calculated by searching for the "worst case" scenarios, that are sample size adaptation rules in the interim analysis that lead to the largest conditional type 1 error rate in any point of the sample space. To show the most extreme inflation, we initially assume unconstrained second stage sample size modifications leading to a large inflation of the type 1 error rate. Furthermore, we investigate the inflation when putting constraints on the second stage sample sizes. It turns out that, for example fixing the sample size of the control group, leads to designs controlling the type 1 error rate. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Critical appraisal of arguments for the delayed-start design proposed as alternative to the parallel-group randomized clinical trial design in the field of rare disease.

PubMed

Spineli, Loukia M; Jenz, Eva; Großhennig, Anika; Koch, Armin

2017-08-17

A number of papers have proposed or evaluated the delayed-start design as an alternative to the standard two-arm parallel group randomized clinical trial (RCT) design in the field of rare disease. However the discussion is felt to lack a sufficient degree of consideration devoted to the true virtues of the delayed start design and the implications either in terms of required sample-size, overall information, or interpretation of the estimate in the context of small populations. To evaluate whether there are real advantages of the delayed-start design particularly in terms of overall efficacy and sample size requirements as a proposed alternative to the standard parallel group RCT in the field of rare disease. We used a real-life example to compare the delayed-start design with the standard RCT in terms of sample size requirements. Then, based on three scenarios regarding the development of the treatment effect over time, the advantages, limitations and potential costs of the delayed-start design are discussed. We clarify that delayed-start design is not suitable for drugs that establish an immediate treatment effect, but for drugs with effects developing over time, instead. In addition, the sample size will always increase as an implication for a reduced time on placebo resulting in a decreased treatment effect. A number of papers have repeated well-known arguments to justify the delayed-start design as appropriate alternative to the standard parallel group RCT in the field of rare disease and do not discuss the specific needs of research methodology in this field. The main point is that a limited time on placebo will result in an underestimated treatment effect and, in consequence, in larger sample size requirements compared to those expected under a standard parallel-group design. This also impacts on benefit-risk assessment.

Value of information analysis optimizing future trial design from a pilot study on catheter securement devices.

PubMed

Tuffaha, Haitham W; Reynolds, Heather; Gordon, Louisa G; Rickard, Claire M; Scuffham, Paul A

2014-12-01

Value of information analysis has been proposed as an alternative to the standard hypothesis testing approach, which is based on type I and type II errors, in determining sample sizes for randomized clinical trials. However, in addition to sample size calculation, value of information analysis can optimize other aspects of research design such as possible comparator arms and alternative follow-up times, by considering trial designs that maximize the expected net benefit of research, which is the difference between the expected cost of the trial and the expected value of additional information. To apply value of information methods to the results of a pilot study on catheter securement devices to determine the optimal design of a future larger clinical trial. An economic evaluation was performed using data from a multi-arm randomized controlled pilot study comparing the efficacy of four types of catheter securement devices: standard polyurethane, tissue adhesive, bordered polyurethane and sutureless securement device. Probabilistic Monte Carlo simulation was used to characterize uncertainty surrounding the study results and to calculate the expected value of additional information. To guide the optimal future trial design, the expected costs and benefits of the alternative trial designs were estimated and compared. Analysis of the value of further information indicated that a randomized controlled trial on catheter securement devices is potentially worthwhile. Among the possible designs for the future trial, a four-arm study with 220 patients/arm would provide the highest expected net benefit corresponding to 130% return-on-investment. The initially considered design of 388 patients/arm, based on hypothesis testing calculations, would provide lower net benefit with return-on-investment of 79%. Cost-effectiveness and value of information analyses were based on the data from a single pilot trial which might affect the accuracy of our uncertainty estimation. Another limitation was that different follow-up durations for the larger trial were not evaluated. The value of information approach allows efficient trial design by maximizing the expected net benefit of additional research. This approach should be considered early in the design of randomized clinical trials. © The Author(s) 2014.

A systematic review of cluster randomised trials in residential facilities for older people suggests how to improve quality.

PubMed

Diaz-Ordaz, Karla; Froud, Robert; Sheehan, Bart; Eldridge, Sandra

2013-10-22

Previous reviews of cluster randomised trials have been critical of the quality of the trials reviewed, but none has explored determinants of the quality of these trials in a specific field over an extended period of time. Recent work suggests that correct conduct and reporting of these trials may require more than published guidelines. In this review, our aim was to assess the quality of cluster randomised trials conducted in residential facilities for older people, and to determine whether (1) statistician involvement in the trial and (2) strength of journal endorsement of the Consolidated Standards of Reporting Trials (CONSORT) statement influence quality. We systematically identified trials randomising residential facilities for older people, or parts thereof, without language restrictions, up to the end of 2010, using National Library of Medicine (Medline) via PubMed and hand-searching. We based quality assessment criteria largely on the extended CONSORT statement for cluster randomised trials. We assessed statistician involvement based on statistician co-authorship, and strength of journal endorsement of the CONSORT statement from journal websites. 73 trials met our inclusion criteria. Of these, 20 (27%) reported accounting for clustering in sample size calculations and 54 (74%) in the analyses. In 29 trials (40%), methods used to identify/recruit participants were judged by us to have potentially caused bias or reporting was unclear to reach a conclusion. Some elements of quality improved over time but this appeared not to be related to the publication of the extended CONSORT statement for these trials. Trials with statistician/epidemiologist co-authors were more likely to account for clustering in sample size calculations (unadjusted odds ratio 5.4, 95% confidence interval 1.1 to 26.0) and analyses (unadjusted OR 3.2, 1.2 to 8.5). Journal endorsement of the CONSORT statement was not associated with trial quality. Despite international attempts to improve methods in cluster randomised trials, important quality limitations remain amongst these trials in residential facilities. Statistician involvement on trial teams may be more effective in promoting quality than further journal endorsement of the CONSORT statement. Funding bodies and journals should promote statistician involvement and co-authorship in addition to adherence to CONSORT guidelines.

Simultaneous sequential monitoring of efficacy and safety led to masking of effects.

PubMed

van Eekelen, Rik; de Hoop, Esther; van der Tweel, Ingeborg

2016-08-01

Usually, sequential designs for clinical trials are applied on the primary (=efficacy) outcome. In practice, other outcomes (e.g., safety) will also be monitored and influence the decision whether to stop a trial early. Implications of simultaneous monitoring on trial decision making are yet unclear. This study examines what happens to the type I error, power, and required sample sizes when one efficacy outcome and one correlated safety outcome are monitored simultaneously using sequential designs. We conducted a simulation study in the framework of a two-arm parallel clinical trial. Interim analyses on two outcomes were performed independently and simultaneously on the same data sets using four sequential monitoring designs, including O'Brien-Fleming and Triangular Test boundaries. Simulations differed in values for correlations and true effect sizes. When an effect was present in both outcomes, competition was introduced, which decreased power (e.g., from 80% to 60%). Futility boundaries for the efficacy outcome reduced overall type I errors as well as power for the safety outcome. Monitoring two correlated outcomes, given that both are essential for early trial termination, leads to masking of true effects. Careful consideration of scenarios must be taken into account when designing sequential trials. Simulation results can help guide trial design. Copyright © 2016 Elsevier Inc. All rights reserved.

Consistency assessment with global and bridging development strategies in emerging markets.

PubMed

Li, Gang; Chen, Josh; Quan, Hui; Shentu, Yue

2013-11-01

Global trial strategy with the participation of all major regions including countries from emerging markets surely increases new drug development efficiency. Nevertheless, there are circumstances in which some countries in emerging markets cannot join the original global trial. To evaluate the extrapolability of the original trial results to a new country, a bridging trial in the country has to be conducted. In this paper, we first evaluate the efficiency loss of the bridging trial strategy compared to that of the global trial strategy as a function of between-study variability from consistency assessment perspective. The provided evidence should encourage countries in emerging markets to make a greater effort to participate in the original global trial. We then discuss sample size requirement for desired assurance probability for consistency assessment based on various approaches for both global and bridging trial strategies. Examples are presented for numerical demonstration and comparisons. Copyright © 2013 Elsevier Inc. All rights reserved.

A normative inference approach for optimal sample sizes in decisions from experience

PubMed Central

Ostwald, Dirk; Starke, Ludger; Hertwig, Ralph

2015-01-01

“Decisions from experience” (DFE) refers to a body of work that emerged in research on behavioral decision making over the last decade. One of the major experimental paradigms employed to study experience-based choice is the “sampling paradigm,” which serves as a model of decision making under limited knowledge about the statistical structure of the world. In this paradigm respondents are presented with two payoff distributions, which, in contrast to standard approaches in behavioral economics, are specified not in terms of explicit outcome-probability information, but by the opportunity to sample outcomes from each distribution without economic consequences. Participants are encouraged to explore the distributions until they feel confident enough to decide from which they would prefer to draw from in a final trial involving real monetary payoffs. One commonly employed measure to characterize the behavior of participants in the sampling paradigm is the sample size, that is, the number of outcome draws which participants choose to obtain from each distribution prior to terminating sampling. A natural question that arises in this context concerns the “optimal” sample size, which could be used as a normative benchmark to evaluate human sampling behavior in DFE. In this theoretical study, we relate the DFE sampling paradigm to the classical statistical decision theoretic literature and, under a probabilistic inference assumption, evaluate optimal sample sizes for DFE. In our treatment we go beyond analytically established results by showing how the classical statistical decision theoretic framework can be used to derive optimal sample sizes under arbitrary, but numerically evaluable, constraints. Finally, we critically evaluate the value of deriving optimal sample sizes under this framework as testable predictions for the experimental study of sampling behavior in DFE. PMID:26441720

[Immunological surrogate endpoints to evaluate vaccine efficacy].

PubMed

Jin, Pengfei; Li, Jingxin; Zhou, Yang; Zhu, Fengcai

2015-12-01

An immunological surrogate endpoints is a vaccine-induced immune response (either humoral or cellular immune) that predicts protection against clinical endpoints (infection or disease), and can be used to evaluate vaccine efficacy in clinical vaccine trials. Compared with field efficacy trials observing clinical endpoints, immunological vaccine trials could reduce the sample size or shorten the duration of a trial, which promote the license and development of new candidate vaccines. For these reasons, establishing immunological surrogate endpoints is one of 14 Grand Challenges of Global Health of the National Institutes of Health (NIH) and the Bill and Melinda Gates Foundation. From two parts of definition and statistical methods for evaluation of surrogate endpoints, this review provides a more comprehensive description.

Optimality, sample size, and power calculations for the sequential parallel comparison design.

PubMed

Ivanova, Anastasia; Qaqish, Bahjat; Schoenfeld, David A

2011-10-15

The sequential parallel comparison design (SPCD) has been proposed to increase the likelihood of success of clinical trials in therapeutic areas where high-placebo response is a concern. The trial is run in two stages, and subjects are randomized into three groups: (i) placebo in both stages; (ii) placebo in the first stage and drug in the second stage; and (iii) drug in both stages. We consider the case of binary response data (response/no response). In the SPCD, all first-stage and second-stage data from placebo subjects who failed to respond in the first stage of the trial are utilized in the efficacy analysis. We develop 1 and 2 degree of freedom score tests for treatment effect in the SPCD. We give formulae for asymptotic power and for sample size computations and evaluate their accuracy via simulation studies. We compute the optimal allocation ratio between drug and placebo in stage 1 for the SPCD to determine from a theoretical viewpoint whether a single-stage design, a two-stage design with placebo only in the first stage, or a two-stage design is the best design for a given set of response rates. As response rates are not known before the trial, a two-stage approach with allocation to active drug in both stages is a robust design choice. Copyright © 2011 John Wiley & Sons, Ltd.

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

Effects of sources of variability on sample sizes required for RCTs, applied to trials of lipid-altering therapies on carotid artery intima-media thickness.

PubMed

Gould, A Lawrence; Koglin, Joerg; Bain, Raymond P; Pinto, Cathy-Anne; Mitchel, Yale B; Pasternak, Richard C; Sapre, Aditi

2009-08-01

Studies measuring progression of carotid artery intima-media thickness (cIMT) have been used to estimate the effect of lipid-modifying therapies cardiovascular event risk. The likelihood that future cIMT clinical trials will detect a true treatment effect is estimated by leveraging results from prior studies. The present analyses assess the impact of between- and within-study variability based on currently published data from prior clinical studies on the likelihood that ongoing or future cIMT trials will detect the true treatment effect of lipid-modifying therapies. Published data from six contemporary cIMT studies (ASAP, ARBITER 2, RADIANCE 1, RADIANCE 2, ENHANCE, and METEOR) including data from a total of 3563 patients were examined. Bayesian and frequentist methods were used to assess the impact of between study variability on the likelihood of detecting true treatment effects on 1-year cIMT progression/regression and to provide a sample size estimate that would specifically compensate for the effect of between-study variability. In addition to the well-described within-study variability, there is considerable between-study variability associated with the measurement of annualized change in cIMT. Accounting for the additional between-study variability decreases the power for existing study designs. In order to account for the added between-study variability, it is likely that future cIMT studies would require a large increase in sample size in order to provide substantial probability (> or =90%) to have 90% power of detecting a true treatment effect.Limitation Analyses are based on study level data. Future meta-analyses incorporating patient-level data would be useful for confirmation. Due to substantial within- and between-study variability in the measure of 1-year change of cIMT, as well as uncertainty about progression rates in contemporary populations, future study designs evaluating the effect of new lipid-modifying therapies on atherosclerotic disease progression are likely to be challenged by large sample sizes in order to demonstrate a true treatment effect.

Randomization in clinical trials: stratification or minimization? The HERMES free simulation software.

PubMed

Fron Chabouis, Hélène; Chabouis, Francis; Gillaizeau, Florence; Durieux, Pierre; Chatellier, Gilles; Ruse, N Dorin; Attal, Jean-Pierre

2014-01-01

Operative clinical trials are often small and open-label. Randomization is therefore very important. Stratification and minimization are two randomization options in such trials. The first aim of this study was to compare stratification and minimization in terms of predictability and balance in order to help investigators choose the most appropriate allocation method. Our second aim was to evaluate the influence of various parameters on the performance of these techniques. The created software generated patients according to chosen trial parameters (e.g., number of important prognostic factors, number of operators or centers, etc.) and computed predictability and balance indicators for several stratification and minimization methods over a given number of simulations. Block size and proportion of random allocations could be chosen. A reference trial was chosen (50 patients, 1 prognostic factor, and 2 operators) and eight other trials derived from this reference trial were modeled. Predictability and balance indicators were calculated from 10,000 simulations per trial. Minimization performed better with complex trials (e.g., smaller sample size, increasing number of prognostic factors, and operators); stratification imbalance increased when the number of strata increased. An inverse correlation between imbalance and predictability was observed. A compromise between predictability and imbalance still has to be found by the investigator but our software (HERMES) gives concrete reasons for choosing between stratification and minimization; it can be downloaded free of charge. This software will help investigators choose the appropriate randomization method in future two-arm trials.

Assessing the Eventual Publication of Clinical Trial Abstracts Submitted to a Large Annual Oncology Meeting.

PubMed

Massey, Paul R; Wang, Ruibin; Prasad, Vinay; Bates, Susan E; Fojo, Tito

2016-03-01

Despite the ethical imperative to publish clinical trials when human subjects are involved, such data frequently remain unpublished. The objectives were to tabulate the rate and ascertain factors associated with eventual publication of clinical trial results reported as abstracts in the Proceedings of the American Society of Clinical Oncology (American Society of Clinical Oncology). Abstracts describing clinical trials for patients with breast, lung, colorectal, ovarian, and prostate cancer from 2009 to 2011 were identified by using a comprehensive online database (http://meetinglibrary.asco.org/abstracts). Abstracts included reported results of a treatment or intervention assessed in a discrete, prospective clinical trial. Publication status at 4-6 years was determined by using a standardized search of PubMed. Primary outcomes were the rate of publication for abstracts of randomized and nonrandomized clinical trials. Secondary outcomes included factors influencing the publication of results. A total of 1,075 abstracts describing 378 randomized and 697 nonrandomized clinical trials were evaluated. Across all years, 75% of randomized and 54% of nonrandomized trials were published, with an overall publication rate of 61%. Sample size was a statistically significant predictor of publication for both randomized and nonrandomized trials (odds ratio [OR] per increase of 100 participants = 1.23 [1.11-1.36], p < .001; and 1.64 [1.15-2.34], p = .006, respectively). Among randomized studies, an industry coauthor or involvement of a cooperative group increased the likelihood of publication (OR 2.37, p = .013; and 2.21, p = .01, respectively). Among nonrandomized studies, phase II trials were more likely to be published than phase I (p < .001). Use of an experimental agent was not a predictor of publication in randomized (OR 0.76 [0.38-1.52]; p = .441) or nonrandomized trials (OR 0.89 [0.61-1.29]; p = .532). This is the largest reported study examining why oncology trials are not published. The data show that 4-6 years after appearing as abstracts, 39% of oncology clinical trials remain unpublished. Larger sample size and advanced trial phase were associated with eventual publication; among randomized trials, an industry-affiliated author or a cooperative group increased likelihood of publication. Unfortunately, we found that, despite widespread recognition of the problem and the creation of central data repositories, timely publishing of oncology clinical trials results remains unsatisfactory. ©AlphaMed Press.

Detecting small-study effects and funnel plot asymmetry in meta-analysis of survival data: A comparison of new and existing tests.

PubMed

Debray, Thomas P A; Moons, Karel G M; Riley, Richard D

2018-03-01

Small-study effects are a common threat in systematic reviews and may indicate publication bias. Their existence is often verified by visual inspection of the funnel plot. Formal tests to assess the presence of funnel plot asymmetry typically estimate the association between the reported effect size and their standard error, the total sample size, or the inverse of the total sample size. In this paper, we demonstrate that the application of these tests may be less appropriate in meta-analysis of survival data, where censoring influences statistical significance of the hazard ratio. We subsequently propose 2 new tests that are based on the total number of observed events and adopt a multiplicative variance component. We compare the performance of the various funnel plot asymmetry tests in an extensive simulation study where we varied the true hazard ratio (0.5 to 1), the number of published trials (N=10 to 100), the degree of censoring within trials (0% to 90%), and the mechanism leading to participant dropout (noninformative versus informative). Results demonstrate that previous well-known tests for detecting funnel plot asymmetry suffer from low power or excessive type-I error rates in meta-analysis of survival data, particularly when trials are affected by participant dropout. Because our novel test (adopting estimates of the asymptotic precision as study weights) yields reasonable power and maintains appropriate type-I error rates, we recommend its use to evaluate funnel plot asymmetry in meta-analysis of survival data. The use of funnel plot asymmetry tests should, however, be avoided when there are few trials available for any meta-analysis. © 2017 The Authors. Research Synthesis Methods Published by John Wiley & Sons, Ltd.

A randomized controlled trial of long term effect of BCM guided fluid management in MHD patients (BOCOMO study): rationales and study design

PubMed Central

2012-01-01

Background Bioimpedance analysis (BIA) has been reported as helpful in identifying hypervolemia. Observation data showed that hypervolemic maintenance hemodialysis (MHD) patients identified using BIA methods have higher mortality risk. However, it is not known if BIA-guided fluid management can improve MHD patients’ survival. The objectives of the BOCOMO study are to evaluate the outcome of BIA guided fluid management compared with standard care. Methods This is a multicenter, prospective, randomized, controlled trial. More than 1300 participants from 16 clinical sites will be included in the study. The enrolment period will last 6 months, and minimum length of follow-up will be 36 months. MHD patients aged between 18 years and 80 years who have been on MHD for at least 3 months and meet eligibility criteria will be invited to participate in the study. Participants will be randomized to BIA arm or control arm in a 1:1 ratio. A portable whole body bioimpedance spectroscopy device (BCM—Fresenius Medical Care D GmbH) will be used for BIA measurement at baseline for both arms of the study. In the BIA arm, additional BCM measurements will be performed every 2 months. The primary intent-to-treat analysis will compare outcomes for a composite endpoint of death, acute myocardial infarction, stroke or incident peripheral arterial occlusive disease between groups. Secondary endpoints will include left ventricular wall thickness, blood pressure, medications, and incidence and length of hospitalization. Discussions Previous results regarding the benefit of strict fluid control are conflicting due to small sample sizes and unstable dry weight estimating methods. To our knowledge this is the first large-scale, multicentre, prospective, randomized controlled trial to assess whether BIS-guided volume management improves outcomes of MHD patients. The endpoints of the BOCOMO study are of utmost importance to health care providers. In order to obtain that aim, the study was designed with very careful important considerations related to the endpoints, sample size, inclusion criteria, exclusion criteria and so on. For example, annual mortality of Beijing MHD patients was around 10%. To reach statistical significance, the sample size will be very large. By using composite endpoint, the sample size becomes reasonable and feasible. Limiting inclusion to patients with urine volume less than 800 ml/day the day before dialysis session will limit confounding due to residual renal function effects on the measured parameters. Patients who had received BIS measurement within 3 months prior to enrolment are excluded as data from such measurements might lead to protocol violation. Although not all patients enrolled will be incident patients, we will record the vintage of dialysis in the multivariable analysis. Trial registration Current Controlled Trials NCT01509937 PMID:23006960

Physical micro-environment interventions for healthier eating in the workplace: protocol for a stepped wedge randomised controlled pilot trial.

PubMed

Vasiljevic, Milica; Cartwright, Emma; Pechey, Rachel; Hollands, Gareth J; Couturier, Dominique-Laurent; Jebb, Susan A; Marteau, Theresa M

2017-01-01

An estimated one third of energy is consumed in the workplace. The workplace is therefore an important context in which to reduce energy consumption to tackle the high rates of overweight and obesity in the general population. Altering environmental cues for food selection and consumption-physical micro-environment or 'choice architecture' interventions-has the potential to reduce energy intake. The first aim of this pilot trial is to estimate the potential impact upon energy purchased of three such environmental cues (size of portions, packages and tableware; availability of healthier vs. less healthy options; and energy labelling) in workplace cafeterias. A second aim of this pilot trial is to examine the feasibility of recruiting eligible worksites, and identify barriers to the feasibility and acceptability of implementing the interventions in preparation for a larger trial. Eighteen worksite cafeterias in England will be assigned to one of three intervention groups to assess the impact on energy purchased of altering (a) portion, package and tableware size ( n  = 6); (b) availability of healthier options ( n  = 6); and (c) energy (calorie) labelling ( n  = 6). Using a stepped wedge design, sites will implement allocated interventions at different time periods, as randomised. This pilot trial will examine the feasibility of recruiting eligible worksites, and the feasibility and acceptability of implementing the interventions in preparation for a larger trial. In addition, a series of linear mixed models will be used to estimate the impact of each intervention on total energy (calories) purchased per time frame of analysis (daily or weekly) controlling for the total sales/transactions adjusted for calendar time and with random effects for worksite. These analyses will allow an estimate of an effect size of each of the three proposed interventions, which will form the basis of the sample size calculations necessary for a larger trial. ISRCTN52923504.

Efficacy and safety of Suanzaoren decoction for primary insomnia: a systematic review of randomized controlled trials

PubMed Central

2013-01-01

Background Insomnia is a widespread human health problem, but there currently are the limitations of conventional therapies available. Suanzaoren decoction (SZRD) is a well known classic Chinese herbal prescription for insomnia and has been treating people’s insomnia for more than thousand years. The objective of this study was to evaluate the efficacy and safety of SZRD for insomnia. Methods A systematic literature search was performed for 6 databases up to July of 2012 to identify randomized control trials (RCTs) involving SZRD for insomniac patients. The methodological quality of RCTs was assessed independently using the Cochrane Handbook for Systematic Reviews of Interventions. Results Twelve RCTs with total of 1376 adult participants were identified. The methodological quality of all included trials are no more than 3/8 score. Majority of the RCTs concluded that SZRD was more significantly effective than benzodiazepines for treating insomnia. Despite these positive outcomes, there were many methodological shortcomings in the studies reviewed, including insufficient information about randomization generation and absence of allocation concealment, lack of blinding and no placebo control, absence of intention-to-treat analysis and lack of follow-ups, selective publishing and reporting, and small number of sample sizes. A number of clinical heterogeneity such as diagnosis, intervention, control, and outcome measures were also reviewed. Only 3 trials reported adverse events, whereas the other 9 trials did not provide the safety information. Conclusions Despite the apparent reported positive findings, there is insufficient evidence to support efficacy of SZRD for insomnia due to the poor methodological quality and the small number of trials of the included studies. SZRD seems generally safe, but is insufficient evidence to make conclusions on the safety because fewer studies reported the adverse events. Further large sample-size and well-designed RCTs are needed. PMID:23336848

Sequential sampling: a novel method in farm animal welfare assessment.

PubMed

Heath, C A E; Main, D C J; Mullan, S; Haskell, M J; Browne, W J

2016-02-01

Lameness in dairy cows is an important welfare issue. As part of a welfare assessment, herd level lameness prevalence can be estimated from scoring a sample of animals, where higher levels of accuracy are associated with larger sample sizes. As the financial cost is related to the number of cows sampled, smaller samples are preferred. Sequential sampling schemes have been used for informing decision making in clinical trials. Sequential sampling involves taking samples in stages, where sampling can stop early depending on the estimated lameness prevalence. When welfare assessment is used for a pass/fail decision, a similar approach could be applied to reduce the overall sample size. The sampling schemes proposed here apply the principles of sequential sampling within a diagnostic testing framework. This study develops three sequential sampling schemes of increasing complexity to classify 80 fully assessed UK dairy farms, each with known lameness prevalence. Using the Welfare Quality herd-size-based sampling scheme, the first 'basic' scheme involves two sampling events. At the first sampling event half the Welfare Quality sample size is drawn, and then depending on the outcome, sampling either stops or is continued and the same number of animals is sampled again. In the second 'cautious' scheme, an adaptation is made to ensure that correctly classifying a farm as 'bad' is done with greater certainty. The third scheme is the only scheme to go beyond lameness as a binary measure and investigates the potential for increasing accuracy by incorporating the number of severely lame cows into the decision. The three schemes are evaluated with respect to accuracy and average sample size by running 100 000 simulations for each scheme, and a comparison is made with the fixed size Welfare Quality herd-size-based sampling scheme. All three schemes performed almost as well as the fixed size scheme but with much smaller average sample sizes. For the third scheme, an overall association between lameness prevalence and the proportion of lame cows that were severely lame on a farm was found. However, as this association was found to not be consistent across all farms, the sampling scheme did not prove to be as useful as expected. The preferred scheme was therefore the 'cautious' scheme for which a sampling protocol has also been developed.

Decompressive Surgery for the Treatment of Malignant Infarction of the Middle Cerebral Artery (DESTINY): a randomized, controlled trial.

PubMed

Jüttler, Eric; Schwab, Stefan; Schmiedek, Peter; Unterberg, Andreas; Hennerici, Michael; Woitzik, Johannes; Witte, Steffen; Jenetzky, Ekkehart; Hacke, Werner

2007-09-01

Decompressive surgery (hemicraniectomy) for life-threatening massive cerebral infarction represents a controversial issue in neurocritical care medicine. We report here the 30-day mortality and 6- and 12-month functional outcomes from the DESTINY trial. DESTINY (ISRCTN01258591) is a prospective, multicenter, randomized, controlled, clinical trial based on a sequential design that used mortality after 30 days as the first end point. When this end point was reached, patient enrollment was interrupted as per protocol until recalculation of the projected sample size was performed on the basis of the 6-month outcome (primary end point=modified Rankin Scale score, dichotomized to 0 to 3 versus 4 to 6). All analyses were based on intention to treat. A statistically significant reduction in mortality was reached after 32 patients had been included: 15 of 17 (88%) patients randomized to hemicraniectomy versus 7 of 15 (47%) patients randomized to conservative therapy survived after 30 days (P=0.02). After 6 and 12 months, 47% of patients in the surgical arm versus 27% of patients in the conservative treatment arm had a modified Rankin Scale score of 0 to 3 (P=0.23). DESTINY showed that hemicraniectomy reduces mortality in large hemispheric stroke. With 32 patients included, the primary end point failed to demonstrate statistical superiority of hemicraniectomy, and the projected sample size was calculated to 188 patients. Despite this failure to meet the primary end point, the steering committee decided to terminate the trial in light of the results of the joint analysis of the 3 European hemicraniectomy trials.

Urn models for response-adaptive randomized designs: a simulation study based on a non-adaptive randomized trial.

PubMed

Ghiglietti, Andrea; Scarale, Maria Giovanna; Miceli, Rosalba; Ieva, Francesca; Mariani, Luigi; Gavazzi, Cecilia; Paganoni, Anna Maria; Edefonti, Valeria

2018-03-22

Recently, response-adaptive designs have been proposed in randomized clinical trials to achieve ethical and/or cost advantages by using sequential accrual information collected during the trial to dynamically update the probabilities of treatment assignments. In this context, urn models-where the probability to assign patients to treatments is interpreted as the proportion of balls of different colors available in a virtual urn-have been used as response-adaptive randomization rules. We propose the use of Randomly Reinforced Urn (RRU) models in a simulation study based on a published randomized clinical trial on the efficacy of home enteral nutrition in cancer patients after major gastrointestinal surgery. We compare results with the RRU design with those previously published with the non-adaptive approach. We also provide a code written with the R software to implement the RRU design in practice. In detail, we simulate 10,000 trials based on the RRU model in three set-ups of different total sample sizes. We report information on the number of patients allocated to the inferior treatment and on the empirical power of the t-test for the treatment coefficient in the ANOVA model. We carry out a sensitivity analysis to assess the effect of different urn compositions. For each sample size, in approximately 75% of the simulation runs, the number of patients allocated to the inferior treatment by the RRU design is lower, as compared to the non-adaptive design. The empirical power of the t-test for the treatment effect is similar in the two designs.

A low cost virtual reality system for home based rehabilitation of the arm following stroke: a randomised controlled feasibility trial

PubMed Central

Standen, PJ; Threapleton, K; Richardson, A; Connell, L; Brown, DJ; Battersby, S; Platts, F; Burton, A

2016-01-01

Objective: To assess the feasibility of conducting a randomised controlled trial of a home-based virtual reality system for rehabilitation of the arm following stroke. Design: Two group feasibility randomised controlled trial of intervention versus usual care. Setting: Patients’ homes. Participants: Patients aged 18 or over, with residual arm dysfunction following stroke and no longer receiving any other intensive rehabilitation. Interventions: Eight weeks’ use of a low cost home-based virtual reality system employing infra-red capture to translate the position of the hand into game play or usual care. Main measures: The primary objective was to collect information on the feasibility of a trial, including recruitment, collection of outcome measures and staff support required. Patients were assessed at three time points using the Wolf Motor Function Test, Nine-Hole Peg Test, Motor Activity Log and Nottingham Extended Activities of Daily Living. Results: Over 15 months only 47 people were referred to the team. Twenty seven were randomised and 18 (67%) of those completed final outcome measures. Sample size calculation based on data from the Wolf Motor Function Test indicated a requirement for 38 per group. There was a significantly greater change from baseline in the intervention group on midpoint Wolf Grip strength and two subscales of the final Motor Activity Log. Training in the use of the equipment took a median of 230 minutes per patient. Conclusions: To achieve the required sample size, a definitive home-based trial would require additional strategies to boost recruitment rates and adequate resources for patient support. PMID:27029939

Virtual planning in orthognathic surgery.

PubMed

Stokbro, K; Aagaard, E; Torkov, P; Bell, R B; Thygesen, T

2014-08-01

Numerous publications regarding virtual surgical planning protocols have been published, most reporting only one or two case reports to emphasize the hands-on planning. None have systematically reviewed the data published from clinical trials. This systematic review analyzes the precision and accuracy of three-dimensional (3D) virtual surgical planning of orthognathic procedures compared with the actual surgical outcome following orthognathic surgery reported in clinical trials. A systematic search of the current literature was conducted to identify clinical trials with a sample size of more than five patients, comparing the virtual surgical plan with the actual surgical outcome. Search terms revealed a total of 428 titles, out of which only seven articles were included, with a combined sample size of 149 patients. Data were presented in three different ways: intra-class correlation coefficient, 3D surface area with a difference <2mm, and linear and angular differences in three dimensions. Success criteria were set at 2mm mean difference in six articles; 125 of the 133 patients included in these articles were regarded as having had a successful outcome. Due to differences in the presentation of data, meta-analysis was not possible. Virtual planning appears to be an accurate and reproducible method for orthognathic treatment planning. A more uniform presentation of the data is necessary to allow the performance of a meta-analysis. Currently, the software system most often used for 3D virtual planning in clinical trials is SimPlant (Materialise). More independent clinical trials are needed to further validate the precision of virtual planning. Copyright © 2014 International Association of Oral and Maxillofacial Surgeons. All rights reserved.

A clinical trial design using the concept of proportional time using the generalized gamma ratio distribution.

PubMed

Phadnis, Milind A; Wetmore, James B; Mayo, Matthew S

2017-11-20

Traditional methods of sample size and power calculations in clinical trials with a time-to-event end point are based on the logrank test (and its variations), Cox proportional hazards (PH) assumption, or comparison of means of 2 exponential distributions. Of these, sample size calculation based on PH assumption is likely the most common and allows adjusting for the effect of one or more covariates. However, when designing a trial, there are situations when the assumption of PH may not be appropriate. Additionally, when it is known that there is a rapid decline in the survival curve for a control group, such as from previously conducted observational studies, a design based on the PH assumption may confer only a minor statistical improvement for the treatment group that is neither clinically nor practically meaningful. For such scenarios, a clinical trial design that focuses on improvement in patient longevity is proposed, based on the concept of proportional time using the generalized gamma ratio distribution. Simulations are conducted to evaluate the performance of the proportional time method and to identify the situations in which such a design will be beneficial as compared to the standard design using a PH assumption, piecewise exponential hazards assumption, and specific cases of a cure rate model. A practical example in which hemorrhagic stroke patients are randomized to 1 of 2 arms in a putative clinical trial demonstrates the usefulness of this approach by drastically reducing the number of patients needed for study enrollment. Copyright © 2017 John Wiley & Sons, Ltd.

A low cost virtual reality system for home based rehabilitation of the arm following stroke: a randomised controlled feasibility trial.

PubMed

Standen, P J; Threapleton, K; Richardson, A; Connell, L; Brown, D J; Battersby, S; Platts, F; Burton, A

2017-03-01

To assess the feasibility of conducting a randomised controlled trial of a home-based virtual reality system for rehabilitation of the arm following stroke. Two group feasibility randomised controlled trial of intervention versus usual care. Patients' homes. Patients aged 18 or over, with residual arm dysfunction following stroke and no longer receiving any other intensive rehabilitation. Eight weeks' use of a low cost home-based virtual reality system employing infra-red capture to translate the position of the hand into game play or usual care. The primary objective was to collect information on the feasibility of a trial, including recruitment, collection of outcome measures and staff support required. Patients were assessed at three time points using the Wolf Motor Function Test, Nine-Hole Peg Test, Motor Activity Log and Nottingham Extended Activities of Daily Living. Over 15 months only 47 people were referred to the team. Twenty seven were randomised and 18 (67%) of those completed final outcome measures. Sample size calculation based on data from the Wolf Motor Function Test indicated a requirement for 38 per group. There was a significantly greater change from baseline in the intervention group on midpoint Wolf Grip strength and two subscales of the final Motor Activity Log. Training in the use of the equipment took a median of 230 minutes per patient. To achieve the required sample size, a definitive home-based trial would require additional strategies to boost recruitment rates and adequate resources for patient support.

Nurse Family Partnership: Comparing Costs per Family in Randomized Trials Versus Scale-Up.

PubMed

Miller, Ted R; Hendrie, Delia

2015-12-01

The literature that addresses cost differences between randomized trials and full-scale replications is quite sparse. This paper examines how costs differed among three randomized trials and six statewide scale-ups of nurse family partnership (NFP) intensive home visitation to low income first-time mothers. A literature review provided data on pertinent trials. At our request, six well-established programs reported their total expenditures. We adjusted the costs to national prices based on mean hourly wages for registered nurses and then inflated them to 2010 dollars. A centralized data system provided utilization. Replications had fewer home visits per family than trials (25 vs. 31, p = .05), lower costs per client ($8860 vs. $12,398, p = .01), and lower costs per visit ($354 vs. $400, p = .30). Sample size limited the significance of these differences. In this type of labor intensive program, costs probably were lower in scale-up than in randomized trials. Key cost drivers were attrition and the stable caseload size possible in an ongoing program. Our estimates reveal a wide variation in cost per visit across six state programs, which suggests that those planning replications should not expect a simple rule to guide cost estimations for scale-ups. Nevertheless, NFP replications probably achieved some economies of scale.

Immunization Strategies Producing a Humoral IgG Immune Response against Devil Facial Tumor Disease in the Majority of Tasmanian Devils Destined for Wild Release

PubMed Central

Pye, Ruth; Patchett, Amanda; McLennan, Elspeth; Thomson, Russell; Carver, Scott; Fox, Samantha; Pemberton, David; Kreiss, Alexandre; Baz Morelli, Adriana; Silva, Anabel; Pearse, Martin J.; Corcoran, Lynn M.; Belov, Katherine; Hogg, Carolyn J.; Woods, Gregory M; Lyons, A. Bruce

2018-01-01

Devil facial tumor disease (DFTD) is renowned for its successful evasion of the host immune system. Down regulation of the major histocompatabilty complex class I molecule (MHC-I) on the DFTD cells is a primary mechanism of immune escape. Immunization trials on captive Tasmanian devils have previously demonstrated that an immune response against DFTD can be induced, and that immune-mediated tumor regression can occur. However, these trials were limited by their small sample sizes. Here, we describe the results of two DFTD immunization trials on cohorts of devils prior to their wild release as part of the Tasmanian Government’s Wild Devil Recovery project. 95% of the devils developed anti-DFTD antibody responses. Given the relatively large sample sizes of the trials (N = 19 and N = 33), these responses are likely to reflect those of the general devil population. DFTD cells manipulated to express MHC-I were used as the antigenic basis of the immunizations in both trials. Although the adjuvant composition and number of immunizations differed between trials, similar anti-DFTD antibody levels were obtained. The first trial comprised DFTD cells and the adjuvant combination of ISCOMATRIX™, polyIC, and CpG with up to four immunizations given at monthly intervals. This compared to the second trial whereby two immunizations comprising DFTD cells and the adjuvant combination ISCOMATRIX™, polyICLC (Hiltonol®) and imiquimod were given a month apart, providing a shorter and, therefore, more practical protocol. Both trials incorporated a booster immunization given up to 5 months after the primary course. A key finding was that devils in the second trial responded more quickly and maintained their antibody levels for longer compared to devils in the first trial. The different adjuvant combination incorporating the RNAase resistant polyICLC and imiquimod used in the second trial is likely to be responsible. The seroconversion in the majority of devils in these anti-DFTD immunization trials was remarkable, especially as DFTD is hallmarked by its immune evasion mechanisms. Microsatellite analyzes of MHC revealed that some MHC-I microsatellites correlated to stronger immune responses. These trials signify the first step in the long-term objective of releasing devils with immunity to DFTD into the wild. PMID:29515577

Controlled trials in children: quantity, methodological quality and descriptive characteristics of pediatric controlled trials published 1948-2006.

PubMed

Thomson, Denise; Hartling, Lisa; Cohen, Eyal; Vandermeer, Ben; Tjosvold, Lisa; Klassen, Terry P

2010-09-30

The objective of this study was to describe randomized controlled trials (RCTs) and controlled clinical trials (CCTs) in child health published between 1948 and 2006, in terms of quantity, methodological quality, and publication and trial characteristics. We used the Trials Register of the Cochrane Child Health Field for overall trends and a sample from this to explore trial characteristics in more detail. We extracted descriptive data on a random sample of 578 trials. Ninety-six percent of the trials were published in English; the percentage of child-only trials was 90.5%. The most frequent diagnostic categories were infectious diseases (13.2%), behavioural and psychiatric disorders (11.6%), neonatal critical care (11.4%), respiratory disorders (8.9%), non-critical neonatology (7.9%), and anaesthesia (6.5%). There were significantly fewer child-only studies (i.e., more mixed child and adult studies) over time (P = 0.0460). The proportion of RCTs to CCTs increased significantly over time (P<0.0001), as did the proportion of multicentre trials (P = 0.002). Significant increases over time were found in methodological quality (Jadad score) (P<0.0001), the proportion of double-blind studies (P<0.0001), and studies with adequate allocation concealment (P<0.0001). Additionally, we found an improvement in reporting over time: adequate description of withdrawals and losses to follow-up (P<0.0001), sample size calculations (P<0.0001), and intention-to-treat analysis (P<0.0001). However, many trials still do not describe their level of blinding, and allocation concealment was inadequately reported in the majority of studies across the entire time period. The proportion of studies with industry funding decreased slightly over time (P = 0.003), and these studies were more likely to report positive conclusions (P = 0.028). The quantity and quality of pediatric controlled trials has increased over time; however, much work remains to be done, particularly in improving methodological issues around conduct and reporting of trials.

Using Mechanical Turk to recruit participants for internet intervention research: experience from recruitment for four trials targeting hazardous alcohol consumption.

PubMed

Cunningham, John A; Godinho, Alexandra; Kushnir, Vladyslav

2017-12-01

Mechanical Turk (MTurk) is an online portal operated by Amazon where 'requesters' (individuals or businesses) can submit jobs for 'workers.' MTurk is used extensively by academics as a quick and cheap means of collecting questionnaire data, including information on alcohol consumption, from a diverse sample of participants. We tested the feasibility of recruiting for alcohol Internet intervention trials through MTurk. Participants, 18 years or older, who drank at least weekly were recruited for four intervention trials (combined sample size, N = 11,107). The same basic recruitment strategy was employed for each trial - invite participants to complete a survey about alcohol consumption (less than 15 min in length, US$1.50 payment), identify eligible participants who drank in a hazardous fashion, invite those eligible to complete a follow-up survey ($10 payment), randomize participants to be sent or not sent information to access an online intervention for hazardous alcohol use. Procedures where put in place to optimize the chances that participants could only complete the baseline survey once. There was a substantially slower rate of recruitment by the fourth trial compared to the earlier trials. Demographic characteristics also varied across trials (age, sex, employment and marital status). Patterns of alcohol consumption, while displaying some differences, did not appear to vary in a linear fashion between trials. It is possible to recruit large (but not inexhaustible) numbers of people who drink in a hazardous fashion. Issues for online intervention research when employing this sample are discussed.

Efficient design of cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances.

PubMed

van Breukelen, Gerard J P; Candel, Math J J M

2018-06-10

Cluster randomized trials evaluate the effect of a treatment on persons nested within clusters, where treatment is randomly assigned to clusters. Current equations for the optimal sample size at the cluster and person level assume that the outcome variances and/or the study costs are known and homogeneous between treatment arms. This paper presents efficient yet robust designs for cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances, and compares these with 2 practical designs. First, the maximin design (MMD) is derived, which maximizes the minimum efficiency (minimizes the maximum sampling variance) of the treatment effect estimator over a range of treatment-to-control variance ratios. The MMD is then compared with the optimal design for homogeneous variances and costs (balanced design), and with that for homogeneous variances and treatment-dependent costs (cost-considered design). The results show that the balanced design is the MMD if the treatment-to control cost ratio is the same at both design levels (cluster, person) and within the range for the treatment-to-control variance ratio. It still is highly efficient and better than the cost-considered design if the cost ratio is within the range for the squared variance ratio. Outside that range, the cost-considered design is better and highly efficient, but it is not the MMD. An example shows sample size calculation for the MMD, and the computer code (SPSS and R) is provided as supplementary material. The MMD is recommended for trial planning if the study costs are treatment-dependent and homogeneity of variances cannot be assumed. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

A randomized double-blind trial of two low dose combined oral contraceptives.

PubMed

Bounds, W; Vessey, M; Wiggins, P

1979-04-01

Fifty-five women using Loestrin-20 (20 microgram ethinyl oestradiol and 1 mg norethisterone acetate) as an oral contraceptive have been compared with a like number using Microgynon-30 (30 microgram ethinyl oestradiol and 150 microgram levonorgestrel) in a randomized, double-blind trial. Despite the small sample size, the main finding in the trial is clear-cut; Loestrin-20 provides poor cycle control and is thus less acceptable as an oral contraceptive than Microgynon-30. Although there is also a suggestion that Loestrin-20 may be less effective than Microgynon-30, the difference in the accidental pregnancy rates is not statistically significant.

Funding source and the quality of reports of chronic wounds trials: 2004 to 2011

PubMed Central

2014-01-01

Background Critical commentaries suggest that wound care randomised controlled trials (RCTs) are often poorly reported with many methodological flaws. Furthermore, interventions in chronic wounds, rather than being drugs, are often medical devices for which there are no requirements for RCTs to bring products to market. RCTs in wounds trials therefore potentially represent a form of marketing. This study presents a methodological overview of chronic wound trials published between 2004 and 2011 and investigates the influence of industry funding on methodological quality. Methods A systematic search for RCTs for the treatment of chronic wounds published in the English language between 2004 and 2011 (inclusive) in the Cochrane Wounds Group Specialised Register of Trials was carried out. Data were extracted on aspects of trial design, conduct and quality including sample size, duration of follow-up, specification of a primary outcome, use of surrogate outcomes, and risks of bias. In addition, the prevalence of industry funding was assessed and its influence on the above aspects of trial design, conduct and quality was assessed. Results A total of 167 RCTs met our inclusion criteria. We found chronic wound trials often have short durations of follow-up (median 12 weeks), small sample sizes (median 63), fail to define a primary outcome in 41% of cases, and those that do define a primary outcome, use surrogate measures of healing in 40% of cases. Only 40% of trials used appropriate methods of randomisation, 25% concealed allocation and 34% blinded outcome assessors. Of the included trials, 41% were wholly or partially funded by industry, 33% declared non-commercial funding and 26% did not report a funding source. Industry funding was not statistically significantly associated with any measure of methodological quality, though this analysis was probably underpowered. Conclusions This overview confirms concerns raised about the methodological quality of RCTs in wound care and illustrates that greater efforts must be made to follow international standards for conducting and reporting RCTs. There is currently minimal evidence of an influence of industry funding on methodological quality although analyses had limited power and funding source was not reported for a quarter of studies. PMID:24422753

Funding source and the quality of reports of chronic wounds trials: 2004 to 2011.

PubMed

Hodgson, Robert; Allen, Richard; Broderick, Ellen; Bland, J Martin; Dumville, Jo C; Ashby, Rebecca; Bell-Syer, Sally; Foxlee, Ruth; Hall, Jill; Lamb, Karen; Madden, Mary; O'Meara, Susan; Stubbs, Nikki; Cullum, Nicky

2014-01-14

Critical commentaries suggest that wound care randomised controlled trials (RCTs) are often poorly reported with many methodological flaws. Furthermore, interventions in chronic wounds, rather than being drugs, are often medical devices for which there are no requirements for RCTs to bring products to market. RCTs in wounds trials therefore potentially represent a form of marketing. This study presents a methodological overview of chronic wound trials published between 2004 and 2011 and investigates the influence of industry funding on methodological quality. A systematic search for RCTs for the treatment of chronic wounds published in the English language between 2004 and 2011 (inclusive) in the Cochrane Wounds Group Specialised Register of Trials was carried out.Data were extracted on aspects of trial design, conduct and quality including sample size, duration of follow-up, specification of a primary outcome, use of surrogate outcomes, and risks of bias. In addition, the prevalence of industry funding was assessed and its influence on the above aspects of trial design, conduct and quality was assessed. A total of 167 RCTs met our inclusion criteria. We found chronic wound trials often have short durations of follow-up (median 12 weeks), small sample sizes (median 63), fail to define a primary outcome in 41% of cases, and those that do define a primary outcome, use surrogate measures of healing in 40% of cases. Only 40% of trials used appropriate methods of randomisation, 25% concealed allocation and 34% blinded outcome assessors. Of the included trials, 41% were wholly or partially funded by industry, 33% declared non-commercial funding and 26% did not report a funding source. Industry funding was not statistically significantly associated with any measure of methodological quality, though this analysis was probably underpowered. This overview confirms concerns raised about the methodological quality of RCTs in wound care and illustrates that greater efforts must be made to follow international standards for conducting and reporting RCTs. There is currently minimal evidence of an influence of industry funding on methodological quality although analyses had limited power and funding source was not reported for a quarter of studies.

A reanalysis of the Cu-7 intrauterine contraceptive device clinical trial and the incidence of pelvic inflammatory disease: a paradigm for assessing intrauterine contraceptive device safety.

PubMed

Roy, S; Azen, C

1994-06-01

We calculated and compared the incidence of pelvic inflammatory disease in a 10% random sample of the Cu-7 intrauterine contraceptive device (G.D. Searle & Co., Skokie, Ill.) clinical trial with the rates reported to the Food and Drug Administration and those in subsequent trials published in the world literature. A 10% random sample of the Cu-7 clinical trial was examined because calculations had demonstrated this random sample to be sufficient in size (n = 1614) to detect a difference in rates of pelvic inflammatory disease from those reported to the Food and Drug Administration. An audit of a subset of the patient files, compared with the original files in Skokie, Illinois, confirmed that the files available for analysis were complete. Standard definitions were used to identify cases of pelvic inflammatory disease and to calculate rates of pelvic inflammatory disease. The world literature on Cu-7 clinical trials was reviewed. The calculated crude and Pearl index rates of pelvic inflammatory disease were consistent with those rates previously reported to the Food and Drug Administration and published in the medical literature. Life-table pelvic inflammatory disease rates were not different between nulliparous and parous women and pelvic inflammatory disease did not differ from basal annual rates in fecund women. On the basis of the analysis of this 10% sample, the pelvic inflammatory disease patient rates reported to the Food and Drug Administration for the entire Cu-7 clinical trial are accurate and are similar to those published in the world literature.

A randomized controlled trial to evaluate the feasibility of the Wii Fit for improving walking in older adults with lower limb amputation.

PubMed

Imam, Bita; Miller, William C; Finlayson, Heather; Eng, Janice J; Jarus, Tal

2017-01-01

To assess the feasibility of Wii.n.Walk for improving walking capacity in older adults with lower limb amputation. A parallel, evaluator-blind randomized controlled feasibility trial. Community-living. Individuals who were ⩾50 years old with a unilateral lower limb amputation. Wii.n.Walk consisted of Wii Fit training, 3x/week (40 minute sessions), for 4 weeks. Training started in the clinic in groups of 3 and graduated to unsupervised home training. Control group were trained using cognitive games. Feasibility indicators: trial process (recruitment, retention, participants' perceived benefit from the Wii.n.Walk intervention measured by exit questionnaire), resources (adherence), management (participant processing, blinding), and treatment (adverse event, and Cohen's d effect size and variance). Primary clinical outcome: walking capacity measured using the 2 Minute Walk Test at baseline, end of treatment, and 3-week retention. Of 28 randomized participants, 24 completed the trial (12/arm). Median (range) age was 62.0 (50-78) years. Mean (SD) score for perceived benefit from the Wii.n.Walk intervention was 38.9/45 (6.8). Adherence was 83.4%. The effect sizes for the 2 Minute Walk Test were 0.5 (end of treatment) and 0.6 (3-week retention) based on intention to treat with imputed data; and 0.9 (end of treatment) and 1.2 (3-week retention) based on per protocol analysis. The required sample size for a future larger RCT was deemed to be 72 (36 per arm). The results suggested the feasibility of the Wii.n.Walk with a medium effect size for improving walking capacity. Future larger randomized controlled trials investigating efficacy are warranted.

Twenty-year perspective of randomized controlled trials for surgery of chronic nonspecific low back pain: citation bias and tangential knowledge.

PubMed

Andrade, Nicholas S; Flynn, John P; Bartanusz, Viktor

2013-11-01

After decades of clinical research, the role of surgery for chronic nonspecific low back pain (CNLBP) remains equivocal. Despite significant intellectual, human, and economic investments into randomized controlled trials (RCTs) in the past two decades, the role of surgery in the treatment for CNLBP has not been clarified. To delineate the historical research agenda of surgical RCTs for CNLBP performed between 1993 and 2012 investigating whether conclusions from earlier published trials influenced the choice of research questions of subsequent RCTs on elucidating the role of surgery in the management of CNLBP. Literature review. We searched the literature for all RCTs involving surgery for CNLBP. We reviewed relevant studies to identify the study question, comparator arms, and sample size. Randomized controlled trials were classified as "indication" trials if they evaluated the effectiveness of surgical therapy versus nonoperative care or as "technical" if they compared different surgical techniques, adjuncts, or procedures. We used citation analysis to determine the impact of trials on subsequent research in the field. Altogether 33 technical RCTs (3,790 patients) and 6 indication RCTs (981 patients) have been performed. Since 2007, despite the unclear benefits of surgery reported by the first four indication trials published in 2001 to 2006, technical trials have continued to predominate (16 vs. 2). Of the technical trials, types of instrumentation (13 trials, 1,332 patients), bone graft materials and substitutes (11 trials, 833 patients), and disc arthroplasty versus fusion (5 trials, 1,337 patients) were the most common comparisons made. Surgeon authors have predominantly cited one of the indication trials that reported more favorable results for surgery, despite a lack of superior methodology or sample size. Trials evaluating bone morphogenic protein, instrumentation, and disc arthroplasty were all cited more frequently than the largest trial of surgical versus nonsurgical therapy. The research agenda of RCTs for surgery of CNLBP has not changed substantially in the last 20 years. Technical trials evaluating nuances of surgical techniques significantly predominate. Despite the publication of four RCTs reporting equivocal benefits of surgery for CNLBP between 2001 and 2006, there was no change in the research agenda of subsequent RCTs, and technical trials continued to outnumber indication trials. Rather than clarifying what, if any, indications for surgery exist, investigators in the field continue to analyze variations in surgical technique, which will probably have relatively little impact on patient outcomes. As a result, clinicians unfortunately have little evidence to advise patients regarding surgical intervention for CNLBP. Copyright © 2013 Elsevier Inc. All rights reserved.

Does packaging with a calendar feature improve adherence to self-administered medication for long-term use? A systematic review.

PubMed

Zedler, Barbara K; Kakad, Priyanka; Colilla, Susan; Murrelle, Lenn; Shah, Nirav R

2011-01-01

The therapeutic benefit of self-administered medications for long-term use is limited by an average 50% nonadherence rate. Patient forgetfulness is a common factor in unintentional nonadherence. Unit-of-use packaging that incorporates a simple day-and-date feature (calendar packaging) is designed to improve adherence by prompting patients to maintain the prescribed dosing schedule. To review systematically, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, randomized controlled trial evidence of the adherence benefits and harms of calendar blister packaging (CBP) and calendar pill organizers (CPO) for self-administered, long-term medication use. Data sources included the MEDLINE and Web of Science and Cochrane Library databases from their inception to September 2010 and communication with researchers in the field. Key search terms included blister-calendar pack, blister pack, drug packaging, medication adherence, medication compliance, medication compliance devices, medication containers, medication organizers, multicompartment compliance aid, persistence, pill-box organizers, prescription refill, randomized controlled trials, and refill compliance. Selected studies had an English-language title; a randomized controlled design; medication packaged in CBP or CPO; a requirement of solid, oral medication self-administered daily for longer than 1 month in community-dwelling adults; and at least 1 quantitative outcome measure of adherence. Two reviewers extracted data independently on study design, sample size, type of intervention and control, and outcomes. Ten trials with a total of 1045 subjects met the inclusion criteria, and 9 also examined clinical outcomes (seizures, blood pressure, psychiatric symptoms) or health care resource utilization. Substantial heterogeneity among trials precluded meta-analysis. In 3 studies, calendar packaging was part of a multicomponent adherence intervention. Six of 10 trials reported higher adherence, but it was associated with clinically significant improvement in only 1 study: 50% decreased seizure frequency with a CPO-based, multicomponent intervention. No study reported sufficient information to examine conclusively potential harms related to calendar packaging. All trials had significant methodological limitations, such as inadequate randomization or blinding, or reported insufficient information regarding enrolled subjects and attrition, which resulted in a moderate-to-high risk of bias and, in 2 studies, unevaluable outcome data. Trials were generally short and sample sizes small, with heterogeneous adherence outcome measures. Calendar packaging, especially in combination with education and reminder strategies, may improve medication adherence. Methodological limitations preclude definitive conclusions about the effect size of adherence and clinical benefits or harms associated with CBP and CPO. High-quality trials of adequate size and duration are needed to assess the clinical effectiveness of such interventions. Copyright © 2011 Elsevier HS Journals, Inc. All rights reserved.

Premature trial discontinuation often not accurately reflected in registries: comparison of registry records with publications.

PubMed

Alturki, Reem; Schandelmaier, Stefan; Olu, Kelechi Kalu; von Niederhäusern, Belinda; Agarwal, Arnav; Frei, Roy; Bhatnagar, Neera; Hooft, Lotty; von Elm, Erik; Briel, Matthias

2017-01-01

One quarter of randomized clinical trials (RCTs) are prematurely discontinued and frequently remain unpublished. Trial registries can document whether a trial is ongoing, suspended, discontinued, or completed and therefore represent an important source for trial status information. The accuracy of this information is unclear. To examine the accuracy of completion status and reasons for discontinuation documented in trial registries as compared to corresponding publications of discontinued RCTs and to investigate potential predictors for accurate trial status information in registries. We conducted a cross-sectional study comparing information provided in publications (reference standard) to corresponding registry entries. First, we reviewed publications of RCTs providing information on both discontinuation and registration. We identified eligible publications through systematic searches of MEDLINE and EMBASE (2010-2014) and an international cohort of 1,017 RCTs initiated between 2000 and 2003. Second, pairs of investigators independently and in duplicate extracted data from publications and corresponding registry records. Third, for each discontinued RCT, we compared publication information to registry information. We used multivariable regression to examine whether accurate labeling of trials as discontinued (vs. other status) in the registry was associated with recent initiation of RCT, industry sponsorship, multicenter design, or larger sample size. We identified 173 publications of RCTs that were discontinued due to slow recruitment (55%), harm (16%), futility (11%), benefit (5%), other reasons (3%), or multiple reasons (9%). Trials were registered with clinicaltrials.gov (77%), isrctn.com (14%), or other registries (8%). Of the 173 corresponding registry records, 77 (45%) trials were labeled as discontinued and 57 (33%) provided a reason for discontinuation (of which 53, 93%, provided the same reason as in the publication). Labeling of discontinued trials as discontinued (vs. other label) in corresponding trial registry records improved over time (adjusted odds ratio 1.16 per year, confidence interval 1.04-1.30) and was possibly associated with industry sponsorship (2.01, 0.99-4.07) but unlikely with multicenter status (0.81, 0.32-2.04) or sample size (1.07, 0.89-1.29). Less than half of published discontinued RCTs were accurately labelled as discontinued in corresponding registry records. One-third of registry records provided a reason for discontinuation. Current trial status information in registries should be viewed with caution. Copyright © 2016 Elsevier Inc. All rights reserved.

Are There Differences in Gait Mechanics in Patients With A Fixed Versus Mobile Bearing Total Ankle Arthroplasty? A Randomized Trial.

PubMed

Queen, Robin M; Franck, Christopher T; Schmitt, Daniel; Adams, Samuel B

2017-10-01

Total ankle arthroplasty (TAA) is an alternative to arthrodesis, but no randomized trial has examined whether a fixed bearing or mobile bearing implant provides improved gait mechanics. We wished to determine if fixed- or mobile-bearing TAA results in a larger improvement in pain scores and gait mechanics from before surgery to 1 year after surgery, and to quantify differences in outcomes using statistical analysis and report the standardized effect sizes for such comparisons. Patients with end-stage ankle arthritis who were scheduled for TAA between November 2011 and June 2013 (n = 40; 16 men, 24 women; average age, 63 years; age range, 35-81 years) were prospectively recruited for this study from a single foot and ankle orthopaedic clinic. During this period, 185 patients underwent TAA, with 144 being eligible to participate in this study. Patients were eligible to participate if they were able to meet all study inclusion criteria, which were: no previous diagnosis of rheumatoid arthritis, a contralateral TAA, bilateral ankle arthritis, previous revision TAA, an ankle fusion revision, or able to walk without the use of an assistive device, weight less than 250 pounds (114 kg), a sagittal or coronal plane deformity less than 15°, no presence of avascular necrosis of the distal tibia, no current neuropathy, age older than 35 years, no history of a talar neck fracture, or an avascular talus. Of the 144 eligible patients, 40 consented to participate in our randomized trial. These 40 patients were randomly assigned to either the fixed (n = 20) or mobile bearing implant group (n = 20). Walking speed, bilateral peak dorsiflexion angle, peak plantar flexion angle, sagittal plane ankle ROM, peak ankle inversion angle, peak plantar flexion moment, peak plantar flexion power during stance, peak weight acceptance, and propulsive vertical ground reaction force were analyzed during seven self-selected speed level walking trials for 33 participants using an eight-camera motion analysis system and four force plates. Seven patients were not included in the analysis owing to cancelled surgery (one from each group) and five were lost to followup (four with fixed bearing and one with mobile bearing implants). A series of effect-size calculations and two-sample t-tests comparing postoperative and preoperative increases in outcome variables between implant types were used to determine the differences in the magnitude of improvement between the two patient cohorts from before surgery to 1 year after surgery. The sample size in this study enabled us to detect a standardized shift of 1.01 SDs between group means with 80% power and a type I error rate of 5% for all outcome variables in the study. This randomized trial did not reveal any differences in outcomes between the two implant types under study at the sample size collected. In addition to these results, effect size analysis suggests that changes in outcome differ between implant types by less than 1 SD. Detection of the largest change score or observed effect (propulsive vertical ground reaction force [Fixed: 0.1 ± 0.1; 0.0-1.0; Mobile: 0.0 ± 0.1; 0.0-0.0; p = 0.0.051]) in this study would require a future trial to enroll 66 patients. However, the smallest change score or observed effect (walking speed [Fixed: 0.2 ± 0.3; 0.1-0.4; Mobile: 0.2 ± 0.3; 0.0-0.3; p = 0.742]) requires a sample size of 2336 to detect a significant difference with 80% power at the observed effect sizes. To our knowledge, this is the first randomized study to report the observed effect size comparing improvements in outcome measures between fixed and mobile bearing implant types. This study was statistically powered to detect large effects and descriptively analyze observed effect sizes. Based on our results there were no statistically or clinically meaningful differences between the fixed and mobile bearing implants when examining gait mechanics and pain 1 year after TAA. Level II, therapeutic study.

Effect of ticagrelor with clopidogrel on high on-treatment platelet reactivity in acute stroke or transient ischemic attack (PRINCE) trial: Rationale and design.

PubMed

Wang, Yilong; Lin, Yi; Meng, Xia; Chen, Weiqi; Chen, Guohua; Wang, Zhimin; Wu, Jialing; Wang, Dali; Li, Jianhua; Cao, Yibin; Xu, Yuming; Zhang, Guohua; Li, Xiaobo; Pan, Yuesong; Li, Hao; Liu, Liping; Zhao, Xingquan; Wang, Yongjun

2017-04-01

Rationale and aim Little is known about the safety and efficacy of the combination of ticagrelor and aspirin in acute ischemic stroke. This study aimed to evaluate whether the combination of ticagrelor and aspirin was superior to that of clopidogrel and aspirin in reducing the 90-day high on-treatment platelet reactivity for acute minor stroke or transient ischemic attack, especially for carriers of cytochrome P450 2C19 loss-of-function allele. Sample size and design This study was designed as a prospective, multicenter, randomized, open-label, active-controlled, and blind-endpoint, phase II b trial. The required sample size was 952 patients. It was registered with ClinicalTrials.gov (NCT02506140). Study outcomes The primary outcome was the proportion of patients with high on-treatment platelet reactivity at 90 days. High on-treatment platelet reactivity is defined as the P2Y12 reaction unit >208 measured using the VerifyNow P2Y12 assay. Conclusion The Platelet Reactivity in Acute Non-disabling Cerebrovascular Events study explored whether ticagrelor combined with aspirin could reduce further the proportion of patients with high on-treatment platelet reactivity at 90 days after acute minor stroke or transient ischemic attack compared with clopidogrel and aspirin.

Comparison of global versus Asian clinical trial strategies supportive of registration of drugs in Japan.

PubMed

Shirotani, Mari; Kurokawa, Tatsuo; Chiba, Koji

2014-07-01

The number of worldwide and Asian multiregional clinical trials (MRCTs) submitted for Japanese New Drug Applications increased markedly between 2009 and 2013, with an increasing number performed for simultaneously submission in the USA, EU, and Japan. Asian studies accounted for 32% of MRCTs (14/44 studies) and had comparatively small sample sizes (<500 subjects). Moreover, the number of Japanese subjects in Asian studies was 2.1- to 13.4-fold larger than the sample size estimated using the method described in Japanese MRCT guidelines, whereas the ratio for worldwide studies was 0.05- to 4.9-fold. Before the introduction of this guidelines, bridging or domestic clinical development strategies were used as the regional development strategy in accordance with ICH E5 guidelines. The results presented herein suggest that Asian studies were conducted when the drug had already been approved in the US/EU, when phase 3 clinical trials were not be planned in the USA/EU, when there was insufficient knowledge of ethnic differences in drug efficacy and safety, or when Caucasian data could not be extrapolated to the Japanese population. New strategies with Asian studies including the Japanese population could be conducted instead of Japanese domestic development strategy. © 2014, The American College of Clinical Pharmacology.

Changing cluster composition in cluster randomised controlled trials: design and analysis considerations

PubMed Central

2014-01-01

Background There are many methodological challenges in the conduct and analysis of cluster randomised controlled trials, but one that has received little attention is that of post-randomisation changes to cluster composition. To illustrate this, we focus on the issue of cluster merging, considering the impact on the design, analysis and interpretation of trial outcomes. Methods We explored the effects of merging clusters on study power using standard methods of power calculation. We assessed the potential impacts on study findings of both homogeneous cluster merges (involving clusters randomised to the same arm of a trial) and heterogeneous merges (involving clusters randomised to different arms of a trial) by simulation. To determine the impact on bias and precision of treatment effect estimates, we applied standard methods of analysis to different populations under analysis. Results Cluster merging produced a systematic reduction in study power. This effect depended on the number of merges and was most pronounced when variability in cluster size was at its greatest. Simulations demonstrate that the impact on analysis was minimal when cluster merges were homogeneous, with impact on study power being balanced by a change in observed intracluster correlation coefficient (ICC). We found a decrease in study power when cluster merges were heterogeneous, and the estimate of treatment effect was attenuated. Conclusions Examples of cluster merges found in previously published reports of cluster randomised trials were typically homogeneous rather than heterogeneous. Simulations demonstrated that trial findings in such cases would be unbiased. However, simulations also showed that any heterogeneous cluster merges would introduce bias that would be hard to quantify, as well as having negative impacts on the precision of estimates obtained. Further methodological development is warranted to better determine how to analyse such trials appropriately. Interim recommendations include avoidance of cluster merges where possible, discontinuation of clusters following heterogeneous merges, allowance for potential loss of clusters and additional variability in cluster size in the original sample size calculation, and use of appropriate ICC estimates that reflect cluster size. PMID:24884591

Anti-Depressants, Suicide, and Drug Regulation

ERIC Educational Resources Information Center

Ludwig, Jens; Marcotte, Dave E.

2005-01-01

Policymakers are increasingly concerned that a relatively new class of anti-depressant drugs, selective serotonin re-uptake inhibitors (SSRI), may increase the risk of suicide for at least some patients, particularly children. Prior randomized trials are not informative on this question because of small sample sizes and other limitations. Using…

Intraclass Correlation Values for Planning Group-Randomized Trials in Education

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, E. C.

2007-01-01

Experiments that assign intact groups to treatment conditions are increasingly common in social research. In educational research, the groups assigned are often schools. The design of group-randomized experiments requires knowledge of the intraclass correlation structure to compute statistical power and sample sizes required to achieve adequate…

Comparison of futility monitoring guidelines using completed phase III oncology trials.

PubMed

Zhang, Qiang; Freidlin, Boris; Korn, Edward L; Halabi, Susan; Mandrekar, Sumithra; Dignam, James J

2017-02-01

Futility (inefficacy) interim monitoring is an important component in the conduct of phase III clinical trials, especially in life-threatening diseases. Desirable futility monitoring guidelines allow timely stopping if the new therapy is harmful or if it is unlikely to demonstrate to be sufficiently effective if the trial were to continue to its final analysis. There are a number of analytical approaches that are used to construct futility monitoring boundaries. The most common approaches are based on conditional power, sequential testing of the alternative hypothesis, or sequential confidence intervals. The resulting futility boundaries vary considerably with respect to the level of evidence required for recommending stopping the study. We evaluate the performance of commonly used methods using event histories from completed phase III clinical trials of the Radiation Therapy Oncology Group, Cancer and Leukemia Group B, and North Central Cancer Treatment Group. We considered published superiority phase III trials with survival endpoints initiated after 1990. There are 52 studies available for this analysis from different disease sites. Total sample size and maximum number of events (statistical information) for each study were calculated using protocol-specified effect size, type I and type II error rates. In addition to the common futility approaches, we considered a recently proposed linear inefficacy boundary approach with an early harm look followed by several lack-of-efficacy analyses. For each futility approach, interim test statistics were generated for three schedules with different analysis frequency, and early stopping was recommended if the interim result crossed a futility stopping boundary. For trials not demonstrating superiority, the impact of each rule is summarized as savings on sample size, study duration, and information time scales. For negative studies, our results show that the futility approaches based on testing the alternative hypothesis and repeated confidence interval rules yielded less savings (compared to the other two rules). These boundaries are too conservative, especially during the first half of the study (<50% of information). The conditional power rules are too aggressive during the second half of the study (>50% of information) and may stop a trial even when there is a clinically meaningful treatment effect. The linear inefficacy boundary with three or more interim analyses provided the best results. For positive studies, we demonstrated that none of the futility rules would have stopped the trials. The linear inefficacy boundary futility approach is attractive from statistical, clinical, and logistical standpoints in clinical trials evaluating new anti-cancer agents.

Defining standardized protocols for determining the efficacy of a postmilking teat disinfectant following experimental exposure of teats to mastitis pathogens.

PubMed

Schukken, Y H; Rauch, B J; Morelli, J

2013-04-01

The objective of this paper was to define standardized protocols for determining the efficacy of a postmilking teat disinfectant following experimental exposure of teats to both Staphylococcus aureus and Streptococcus agalactiae. The standardized protocols describe the selection of cows and herds and define the critical points in performing experimental exposure, performing bacterial culture, evaluating the culture results, and finally performing statistical analyses and reporting of the results. The protocols define both negative control and positive control trials. For negative control trials, the protocol states that an efficacy of reducing new intramammary infections (IMI) of at least 40% is required for a teat disinfectant to be considered effective. For positive control trials, noninferiority to a control disinfectant with a published efficacy of reducing new IMI of at least 70% is required. Sample sizes for both negative and positive control trials are calculated. Positive control trials are expected to require a large trial size. Statistical analysis methods are defined and, in the proposed methods, the rate of IMI may be analyzed using generalized linear mixed models. The efficacy of the test product can be evaluated while controlling for important covariates and confounders in the trial. Finally, standards for reporting are defined and reporting considerations are discussed. The use of the defined protocol is shown through presentation of the results of a recent trial of a test product against a negative control. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Augmenting the logrank test in the design of clinical trials in which non-proportional hazards of the treatment effect may be anticipated.

PubMed

Royston, Patrick; Parmar, Mahesh K B

2016-02-11

Most randomized controlled trials with a time-to-event outcome are designed assuming proportional hazards (PH) of the treatment effect. The sample size calculation is based on a logrank test. However, non-proportional hazards are increasingly common. At analysis, the estimated hazards ratio with a confidence interval is usually presented. The estimate is often obtained from a Cox PH model with treatment as a covariate. If non-proportional hazards are present, the logrank and equivalent Cox tests may lose power. To safeguard power, we previously suggested a 'joint test' combining the Cox test with a test of non-proportional hazards. Unfortunately, a larger sample size is needed to preserve power under PH. Here, we describe a novel test that unites the Cox test with a permutation test based on restricted mean survival time. We propose a combined hypothesis test based on a permutation test of the difference in restricted mean survival time across time. The test involves the minimum of the Cox and permutation test P-values. We approximate its null distribution and correct it for correlation between the two P-values. Using extensive simulations, we assess the type 1 error and power of the combined test under several scenarios and compare with other tests. We investigate powering a trial using the combined test. The type 1 error of the combined test is close to nominal. Power under proportional hazards is slightly lower than for the Cox test. Enhanced power is available when the treatment difference shows an 'early effect', an initial separation of survival curves which diminishes over time. The power is reduced under a 'late effect', when little or no difference in survival curves is seen for an initial period and then a late separation occurs. We propose a method of powering a trial using the combined test. The 'insurance premium' offered by the combined test to safeguard power under non-PH represents about a single-digit percentage increase in sample size. The combined test increases trial power under an early treatment effect and protects power under other scenarios. Use of restricted mean survival time facilitates testing and displaying a generalized treatment effect.

Extracorporeal shock wave therapy for calcific and noncalcific tendonitis of the rotator cuff: a systematic review.

PubMed

Harniman, Elaine; Carette, Simon; Kennedy, Carol; Beaton, Dorcas

2004-01-01

The authors conducted a systematic review to assess the effectiveness of extracorporeal shock wave therapy (ESWT) for the treatment of calcific and noncalcific tendonitis of the rotator cuff. Conservative treatment for rotator cuff tendonitis includes physiotherapy, nonsteroidal antiinflammatory drugs, and corticosteroid injections. If symptoms persist with conservative treatment, surgery is often considered. Extracorporeal shock wave therapy has been suggested as a treatment alternative for chronic rotator cuff tendonitis, which may decrease the need for surgery. Articles for this review were identified by electronically searching Medline, EMBASE, Cumulative Index to Nursing & Allied Health Literature (CINAHL), and Evidence Based Medicine (EBM) and hand-screening references. Two reviewers selected the trials that met the inclusion criteria, extracted the data, and assessed the methodological quality of the selected trials. Finally, the strength of scientific evidence was appraised. Evidence was classified as strong, moderate, limited, or conflicting. Sixteen trials met the inclusion criteria. There were only five randomized, controlled trials and all involved chronic (>/=3 months) conditions, three for calcific tendonitis and two for noncalcific tendonitis. For randomized, controlled trials, two (40%) were of high quality, one (33%) for calcific tendonitis and one (50%) for noncalcific tendonitis. The 11 nonrandomized trials included nine that involved calcific tendonitis and two that involved both calcific and noncalcific tendonitis. Common problem areas were sample size, randomization, blinding, treatment provider bias, and outcome measures. There is moderate evidence that high-energy ESWT is effective in treating chronic calcific rotator cuff tendonitis when the shock waves are focused at the calcified deposit. There is moderate evidence that low-energy ESWT is not effective for treating chronic noncalcific rotator cuff tendonitis, although this conclusion is based on only one high-quality study, which was underpowered. High-quality randomized, controlled trials are needed with larger sample sizes, better randomization and blinding, and better outcome measures.

Head-to-head randomized trials are mostly industry sponsored and almost always favor the industry sponsor.

PubMed

Flacco, Maria Elena; Manzoli, Lamberto; Boccia, Stefania; Capasso, Lorenzo; Aleksovska, Katina; Rosso, Annalisa; Scaioli, Giacomo; De Vito, Corrado; Siliquini, Roberta; Villari, Paolo; Ioannidis, John P A

2015-07-01

To map the current status of head-to-head comparative randomized evidence and to assess whether funding may impact on trial design and results. From a 50% random sample of the randomized controlled trials (RCTs) published in journals indexed in PubMed during 2011, we selected the trials with ≥ 100 participants, evaluating the efficacy and safety of drugs, biologics, and medical devices through a head-to-head comparison. We analyzed 319 trials. Overall, 238,386 of the 289,718 randomized subjects (82.3%) were included in the 182 trials funded by companies. Of the 182 industry-sponsored trials, only 23 had two industry sponsors and only three involved truly antagonistic comparisons. Industry-sponsored trials were larger, more commonly registered, used more frequently noninferiority/equivalence designs, had higher citation impact, and were more likely to have "favorable" results (superiority or noninferiority/equivalence for the experimental treatment) than nonindustry-sponsored trials. Industry funding [odds ratio (OR) 2.8; 95% confidence interval (CI): 1.6, 4.7] and noninferiority/equivalence designs (OR 3.2; 95% CI: 1.5, 6.6), but not sample size, were strongly associated with "favorable" findings. Fifty-five of the 57 (96.5%) industry-funded noninferiority/equivalence trials got desirable "favorable" results. The literature of head-to-head RCTs is dominated by the industry. Industry-sponsored comparative assessments systematically yield favorable results for the sponsors, even more so when noninferiority designs are involved. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Empirical analysis shows reduced cost data collection may be an efficient method in economic clinical trials

PubMed Central

2012-01-01

Background Data collection for economic evaluation alongside clinical trials is burdensome and cost-intensive. Limiting both the frequency of data collection and recall periods can solve the problem. As a consequence, gaps in survey periods arise and must be filled appropriately. The aims of our study are to assess the validity of incomplete cost data collection and define suitable resource categories. Methods In the randomised KORINNA study, cost data from 234 elderly patients were collected quarterly over a 1-year period. Different strategies for incomplete data collection were compared with complete data collection. The sample size calculation was modified in response to elasticity of variance. Results Resource categories suitable for incomplete data collection were physiotherapy, ambulatory clinic in hospital, medication, consultations, outpatient nursing service and paid household help. Cost estimation from complete and incomplete data collection showed no difference when omitting information from one quarter. When omitting information from two quarters, costs were underestimated by 3.9% to 4.6%. With respect to the observed increased standard deviation, a larger sample size would be required, increased by 3%. Nevertheless, more time was saved than extra time would be required for additional patients. Conclusion Cost data can be collected efficiently by reducing the frequency of data collection. This can be achieved by incomplete data collection for shortened periods or complete data collection by extending recall windows. In our analysis, cost estimates per year for ambulatory healthcare and non-healthcare services in terms of three data collections was as valid and accurate as a four complete data collections. In contrast, data on hospitalisation, rehabilitation stays and care insurance benefits should be collected for the entire target period, using extended recall windows. When applying the method of incomplete data collection, sample size calculation has to be modified because of the increased standard deviation. This approach is suitable to enable economic evaluation with lower costs to both study participants and investigators. Trial registration The trial registration number is ISRCTN02893746 PMID:22978572

Inference and sample size calculation for clinical trials with incomplete observations of paired binary outcomes.

PubMed

Zhang, Song; Cao, Jing; Ahn, Chul

2017-02-20

We investigate the estimation of intervention effect and sample size determination for experiments where subjects are supposed to contribute paired binary outcomes with some incomplete observations. We propose a hybrid estimator to appropriately account for the mixed nature of observed data: paired outcomes from those who contribute complete pairs of observations and unpaired outcomes from those who contribute either pre-intervention or post-intervention outcomes. We theoretically prove that if incomplete data are evenly distributed between the pre-intervention and post-intervention periods, the proposed estimator will always be more efficient than the traditional estimator. A numerical research shows that when the distribution of incomplete data is unbalanced, the proposed estimator will be superior when there is moderate-to-strong positive within-subject correlation. We further derive a closed-form sample size formula to help researchers determine how many subjects need to be enrolled in such studies. Simulation results suggest that the calculated sample size maintains the empirical power and type I error under various design configurations. We demonstrate the proposed method using a real application example. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Points to consider: efficacy and safety evaluations in the clinical development of ultra-orphan drugs.

PubMed

Maeda, Kojiro; Kaneko, Masayuki; Narukawa, Mamoru; Arato, Teruyo

2017-08-23

The unmet medical needs of individuals with very rare diseases are high. The clinical trial designs and evaluation methods used for 'regular' drugs are not applicable in the clinical development of ultra-orphan drugs (<1000 patients) in many cases. In order to improve the clinical development of ultra-orphan drugs, we examined several points regarding the efficient evaluations of drug efficacy and safety that could be conducted even with very small sample sizes, based on the review reports of orphan drugs approved in Japan. The clinical data packages of 43 ultra-orphan drugs approved in Japan from January 2001 to December 2014 were investigated. Japanese clinical trial data were not included in the clinical data package for eight ultra-orphan drugs, and non-Japanese clinical trial data were included for six of these eight drug. Japanese supportive data that included retrospective studies, published literature, clinical research and Japanese survey results were clinical data package attachments in 22 of the 43 ultra-orphan drugs. Multinational trials were conducted for three ultra-orphan drugs. More than two randomized controlled trials (RCTs) were conducted for only 11 of the 43 ultra-orphan drugs. The smaller the number of patients, the greater the proportion of forced titration and optional titration trials were conducted. Extension trials were carried out for enzyme preparations and monoclonal antibodies with high ratio. Post-marketing surveillance of all patients was required in 36 of the 43 ultra-orphan drugs. For ultra-orphan drugs, clinical endpoints were used as the primary efficacy endpoint of the pivotal trial only for two drugs. The control groups in RCTs were classified as follows: placebo groups different dosage groups, and active controls groups. Sample sizes have been determined on the basis of feasibility for some ultra-orphan drugs. We provide "Draft Guidance on the Clinical Development of Ultra-Orphan Drugs" based on this research. The development of ultra-orphan drugs requires various arrangements regarding evidence collection, data sources and the clinical trial design. We expect that this draft guidance is useful for ultra-orphan drugs developments in future.

The Septic Shock 3.0 Definition and Trials: A Vasopressin and Septic Shock Trial Experience.

PubMed

Russell, James A; Lee, Terry; Singer, Joel; Boyd, John H; Walley, Keith R

2017-06-01

The Septic Shock 3.0 definition could alter treatment comparisons in randomized controlled trials in septic shock. Our first hypothesis was that the vasopressin versus norepinephrine comparison and 28-day mortality of patients with Septic Shock 3.0 definition (lactate > 2 mmol/L) differ from vasopressin versus norepinephrine and mortality in Vasopressin and Septic Shock Trial. Our second hypothesis was that there are differences in plasma cytokine levels in Vasopressin and Septic Shock Trial for lactate less than or equal to 2 versus greater than 2 mmol/L. Retrospective analysis of randomized controlled trial. Multicenter ICUs. We compared vasopressin-to-norepinephrine group 28- and 90-day mortality in Vasopressin and Septic Shock Trial in lactate subgroups. We measured 39 cytokines to compare patients with lactate less than or equal to 2 versus greater than 2 mmol/L. Patients with septic shock with lactate greater than 2 mmol/L or less than or equal to 2 mmol/L, randomized to vasopressin or norepinephrine. Concealed vasopressin (0.03 U/min.) or norepinephrine infusions. The Septic Shock 3.0 definition would have decreased sample size by about half. The 28- and 90-day mortality rates were 10-12 % higher than the original Vasopressin and Septic Shock Trial mortality. There was a significantly (p = 0.028) lower mortality with vasopressin versus norepinephrine in lactate less than or equal to 2 mmol/L but no difference between treatment groups in lactate greater than 2 mmol/L. Nearly all cytokine levels were significantly higher in patients with lactate greater than 2 versus less than or equal to 2 mmol/L. The Septic Shock 3.0 definition decreased sample size by half and increased 28-day mortality rates by about 10%. Vasopressin lowered mortality versus norepinephrine if lactate was less than or equal to 2 mmol/L. Patients had higher plasma cytokines in lactate greater than 2 versus less than or equal to 2 mmol/L, a brisker cytokine response to infection. The Septic Shock 3.0 definition and our findings have important implications for trial design in septic shock.

Affected States Soft Independent Modeling by Class Analogy from the Relation Between Independent Variables, Number of Independent Variables and Sample Size

PubMed Central

Kanık, Emine Arzu; Temel, Gülhan Orekici; Erdoğan, Semra; Kaya, İrem Ersöz

2013-01-01

Objective: The aim of study is to introduce method of Soft Independent Modeling of Class Analogy (SIMCA), and to express whether the method is affected from the number of independent variables, the relationship between variables and sample size. Study Design: Simulation study. Material and Methods: SIMCA model is performed in two stages. In order to determine whether the method is influenced by the number of independent variables, the relationship between variables and sample size, simulations were done. Conditions in which sample sizes in both groups are equal, and where there are 30, 100 and 1000 samples; where the number of variables is 2, 3, 5, 10, 50 and 100; moreover where the relationship between variables are quite high, in medium level and quite low were mentioned. Results: Average classification accuracy of simulation results which were carried out 1000 times for each possible condition of trial plan were given as tables. Conclusion: It is seen that diagnostic accuracy results increase as the number of independent variables increase. SIMCA method is a method in which the relationship between variables are quite high, the number of independent variables are many in number and where there are outlier values in the data that can be used in conditions having outlier values. PMID:25207065

Affected States soft independent modeling by class analogy from the relation between independent variables, number of independent variables and sample size.

PubMed

Kanık, Emine Arzu; Temel, Gülhan Orekici; Erdoğan, Semra; Kaya, Irem Ersöz

2013-03-01

The aim of study is to introduce method of Soft Independent Modeling of Class Analogy (SIMCA), and to express whether the method is affected from the number of independent variables, the relationship between variables and sample size. Simulation study. SIMCA model is performed in two stages. In order to determine whether the method is influenced by the number of independent variables, the relationship between variables and sample size, simulations were done. Conditions in which sample sizes in both groups are equal, and where there are 30, 100 and 1000 samples; where the number of variables is 2, 3, 5, 10, 50 and 100; moreover where the relationship between variables are quite high, in medium level and quite low were mentioned. Average classification accuracy of simulation results which were carried out 1000 times for each possible condition of trial plan were given as tables. It is seen that diagnostic accuracy results increase as the number of independent variables increase. SIMCA method is a method in which the relationship between variables are quite high, the number of independent variables are many in number and where there are outlier values in the data that can be used in conditions having outlier values.

Is Ginkgo biloba a cognitive enhancer in healthy individuals? A meta-analysis.

PubMed

Laws, Keith R; Sweetnam, Hilary; Kondel, Tejinder K

2012-11-01

We conducted a meta-analysis to examine whether Ginkgo biloba (G. biloba) enhances cognitive function in healthy individuals. Scopus, Medline, Google Scholar databases and recent qualitative reviews were searched for studies examining the effects of G. biloba on cognitive function in healthy individuals. We identified randomised controlled trials containing data on memory (K = 13), executive function (K = 7) and attention (K = 8) from which effect sizes could be derived. The analyses provided measures of memory, executive function and attention in 1132, 534 and 910 participants, respectively. Effect sizes were non-significant and close to zero for memory (d = -0.04: 95%CI -0.17 to 0.07), executive function (d = -0.05: 95%CI -0.17 to 0.05) and attention (d = -0.08: 95%CI -0.21 to 0.02). Meta-regressions showed that effect sizes were not related to participant age, duration of the trial, daily dose, total dose or sample size. We report that G. biloba had no ascertainable positive effects on a range of targeted cognitive functions in healthy individuals. Copyright © 2012 John Wiley & Sons, Ltd.

Sample size and power considerations in network meta-analysis

PubMed Central

2012-01-01

Background Network meta-analysis is becoming increasingly popular for establishing comparative effectiveness among multiple interventions for the same disease. Network meta-analysis inherits all methodological challenges of standard pairwise meta-analysis, but with increased complexity due to the multitude of intervention comparisons. One issue that is now widely recognized in pairwise meta-analysis is the issue of sample size and statistical power. This issue, however, has so far only received little attention in network meta-analysis. To date, no approaches have been proposed for evaluating the adequacy of the sample size, and thus power, in a treatment network. Findings In this article, we develop easy-to-use flexible methods for estimating the ‘effective sample size’ in indirect comparison meta-analysis and network meta-analysis. The effective sample size for a particular treatment comparison can be interpreted as the number of patients in a pairwise meta-analysis that would provide the same degree and strength of evidence as that which is provided in the indirect comparison or network meta-analysis. We further develop methods for retrospectively estimating the statistical power for each comparison in a network meta-analysis. We illustrate the performance of the proposed methods for estimating effective sample size and statistical power using data from a network meta-analysis on interventions for smoking cessation including over 100 trials. Conclusion The proposed methods are easy to use and will be of high value to regulatory agencies and decision makers who must assess the strength of the evidence supporting comparative effectiveness estimates. PMID:22992327

Sperm count as a surrogate endpoint for male fertility control.

PubMed

Benda, Norbert; Gerlinger, Christoph

2007-11-30

When assessing the effectiveness of a hormonal method of fertility control in men, the classical approach used for the assessment of hormonal contraceptives in women, by estimating the pregnancy rate or using a life-table analysis for the time to pregnancy, is difficult to apply in a clinical development program. The main reasons are the dissociation of the treated unit, i.e. the man, and the observed unit, i.e. his female partner, the high variability in the frequency of male intercourse, the logistical cost and ethical concerns related to the monitoring of the trial. A reasonable surrogate endpoint of the definite endpoint time to pregnancy is sperm count. In addition to the avoidance of the mentioned problems, trials that compare different treatments are possible with reasonable sample sizes, and study duration can be shorter. However, current products do not suppress sperm production to 100 per cent in all men and the sperm count is only observed with measurement error. Complete azoospermia might not be necessary in order to achieve an acceptable failure rate compared with other forms of male fertility control. Therefore, the use of sperm count as a surrogate endpoint must rely on the results of a previous trial in which both the definitive- and surrogate-endpoint results were assessed. The paper discusses different estimation functions of the mean pregnancy rate (corresponding to the cumulative hazard) that are based on the results of sperm count trial and a previous trial in which both sperm count and time to pregnancy were assessed, as well as the underlying assumptions. Sample size estimations are given for pregnancy rate estimation with a given precision.

Meditation and Yoga for Posttraumatic Stress Disorder: A Meta-Analytic Review of Randomized Controlled Trials

PubMed Central

Gallegos, Autumn M.; Crean, Hugh F.; Pigeon, Wilfred R.; Heffner, Kathi L.

2018-01-01

Posttraumatic stress disorder (PTSD) is a chronic and debilitating disorder that affects the lives of 7-8% of adults in the U.S. Although several interventions demonstrate clinical effectiveness for treating PTSD, many patients continue to have residual symptoms and ask for a variety of treatment options. Complementary health approaches, such as meditation and yoga, hold promise for treating symptoms of PTSD. This meta-analysis evaluates the effect size (ES) of yoga and meditation on PTSD outcomes in adult patients. We also examined whether the intervention type, PTSD outcome measure, study population, sample size, or control condition moderated the effects of complementary approaches on PTSD outcomes. The studies included were 19 randomized control trials with data on 1,173 participants. A random effects model yielded a statistically significant ES in the small to medium range (ES = −.39, p < .001, 95% CI [−.57, −.22]). There were no appreciable differences between intervention types, study population, outcome measures, or control condition. There was, however, a marginally significant higher ES for sample size ≤ 30 (ES = −.78, k = 5). These findings suggest that meditation and yoga are promising complementary approaches in the treatment of PTSD among adults and warrant further study. PMID:29100863

Influence of feed intake, forage physical form, and forage fiber content on particle size of masticated forage, ruminal digesta, and feces of dairy cows.

PubMed

Shaver, R D; Nytes, A J; Satter, L D; Jorgensen, N A

1988-06-01

Two trials were conducted to determine particle size of masticates, ruminal digesta, and feces of dairy cows. In Trial 1, three Holstein cows with ruminal cannulae were fed prebloom alfalfa hay in long, chopped, or pelleted form in a Latin square design (21-d periods) conducted in early lactation (wk 3 to 11) and again during the dry period to attain high (3.75) and low (1.95% of BW) feed consumption. In trial 2, prebloom, midbloom, and full bloom alfalfa hay, mature bromegrass hay, and corn silage were fed to early lactation (wk 5 to 15) Holsteins in a 5 X 5 Latin square design (15-d periods). All diets (Trials 1 and 2) were formulated to 17% CP and contained forage:grain in a 60:40 ratio (DM basis). Similar particle distributions of digesta from long and chopped hay diets suggest little influence of chopping forage on particle size reduction when high quality forage is fed. The large proportion of DM in the small particle (less than .6 mm) pool in the rumen in both trials suggests that rate of escape of small particles from the rumen is an important factor influencing ruminal retention time. Increased proportion of coarse (greater than or equal to 2.36-mm screen) fecal particles at high intake and with fine grinding appears related to a reduction in chewing per unit feed consumed. Soluble DM and particulate matter passing a .063-mm screen made up a significant portion (30 to 50%) of the total DM sieved from all sampling sites in both trials.

Failure Rate of Direct High-Viscosity Glass-Ionomer Versus Hybrid Resin Composite Restorations in Posterior Permanent Teeth - a Systematic Review

PubMed Central

Mickenautsch, Steffen; Yengopal, Veerasamy

2015-01-01

Purpose Traditionally, resin composite restorations are claimed by reviews of the dental literature as being superior to glass-ionomer fillings in terms of restoration failures in posterior permanent teeth. The aim of this systematic review is to answer the clinical question, whether conventional high-viscosity glass-ionomer restorations, in patients with single and/or multi-surface cavities in posterior permanent teeth, have indeed a higher failure rate than direct hybrid resin composite restorations. Methods Eight databases were searched until December 02, 2013. Trials were assessed for bias risks, in-between datasets heterogeneity and statistical sample size power. Effects sizes were computed and statistically compared. A total of 55 citations were identified through systematic literature search. From these, 46 were excluded. No trials related to high-viscosity glass-ionomers versus resin composite restorations for direct head-to-head comparison were found. Three trials related to high-viscosity glass-ionomers versus amalgam and three trials related to resin composite versus amalgam restorations could be included for adjusted indirect comparison, only. Results The available evidence suggests no difference in the failure rates between both types of restoration beyond the play of chance, is limited by lack of head-to-head comparisons and an insufficient number of trials, as well as by high bias and in-between-dataset heterogeneity risk. The current clinical evidence needs to be regarded as too poor in order to justify superiority claims regarding the failure rates of both restoration types. Sufficiently large-sized, parallel-group, randomised control trials with high internal validity are needed, in order to justify any clinically meaningful judgment to this topic. PMID:26962372

Refinement of the magnetic resonance diffusion-perfusion mismatch concept for thrombolytic patient selection: insights from the desmoteplase in acute stroke trials.

PubMed

Warach, Steven; Al-Rawi, Yasir; Furlan, Anthony J; Fiebach, Jochen B; Wintermark, Max; Lindstén, Annika; Smyej, Jamal; Bharucha, David B; Pedraza, Salvador; Rowley, Howard A

2012-09-01

The DIAS-2 study was the only large, randomized, intravenous, thrombolytic trial that selected patients based on the presence of ischemic penumbra. However, DIAS-2 did not confirm the positive findings of the smaller DEDAS and DIAS trials, which also used penumbral selection. Therefore, a reevaluation of the penumbra selection strategy is warranted. In post hoc analyses we assessed the relationships of magnetic resonance imaging-measured lesion volumes with clinical measures in DIAS-2, and the relationships of the presence and size of the diffusion-perfusion mismatch with the clinical effect of desmoteplase in DIAS-2 and in pooled data from DIAS, DEDAS, and DIAS-2. In DIAS-2, lesion volumes correlated with National Institutes of Health Stroke Scale (NIHSS) at both baseline and final time points (P<0.0001), and lesion growth was inversely related to good clinical outcome (P=0.004). In the pooled analysis, desmoteplase was associated with 47% clinical response rate (n=143) vs 34% in placebo (n=73; P=0.08). For both the pooled sample and for DIAS-2, increasing the minimum baseline mismatch volume (MMV) for inclusion increased the desmoteplase effect size. The odds ratio for good clinical response between desmoteplase and placebo treatment was 2.83 (95% confidence interval, 1.16-6.94; P=0.023) for MMV >60 mL. Increasing the minimum NIHSS score for inclusion did not affect treatment effect size. Pooled across all desmoteplase trials, desmoteplase appears beneficial in patients with large MMV and ineffective in patients with small MMV. These results support a modified diffusion-perfusion mismatch hypothesis for patient selection in later time-window thrombolytic trials. Clinical Trial Registration- URL: http://www.clinicaltrials.gov. Unique Identifiers: NCT00638781, NCT00638248, NCT00111852.

Field trials of line transect methods applied to estimation of desert tortoise abundance

USGS Publications Warehouse

Anderson, David R.; Burnham, Kenneth P.; Lubow, Bruce C.; Thomas, L. E. N.; Corn, Paul Stephen; Medica, Philip A.; Marlow, R.W.

2001-01-01

We examine the degree to which field observers can meet the assumptions underlying line transect sampling to monitor populations of desert tortoises (Gopherus agassizii). We present the results of 2 field trials using artificial tortoise models in 3 size classes. The trials were conducted on 2 occasions on an area south of Las Vegas, Nevada, where the density of the test population was known. In the first trials, conducted largely by experienced biologists who had been involved in tortoise surveys for many years, the density of adult tortoise models was well estimated (-3.9% bias), while the bias was higher (-20%) for subadult tortoise models. The bias for combined data was -12.0%. The bias was largely attributed to the failure to detect all tortoise models on or near the transect centerline. The second trials were conducted with a group of largely inexperienced student volunteers and used somewhat different searching methods, and the results were similar to the first trials. Estimated combined density of subadult and adult tortoise models had a negative bias (-7.3%), again attributable to failure to detect some models on or near the centerline. Experience in desert tortoise biology, either comparing the first and second trials or in the second trial with 2 experienced biologists versus 16 novices, did not have an apparent effect on the quality of the data or the accuracy of the estimates. Observer training, specific to line transect sampling, and field testing are important components of a reliable survey. Line transect sampling represents a viable method for large-scale monitoring of populations of desert tortoise; however, field protocol must be improved to assure the key assumptions are met.

[Design requirements for clinical trials on re-evaluation of safety and efficacy of post-marketed Chinese herbs].

PubMed

Xie, Yanming; Wei, Xu

2011-10-01

Re-evaluation of post-marketed based on pharmacoepidemiology is to study and collect clinical medicine safety in large population under practical applications for a long time. It is necessary to conduct re-evaluation of clinical effectiveness because of particularity of traditional Chinese medicine (TCM). Right before carrying out clinical trials on re-evaluation of post-marketed TCM, we should determine the objective of the study and progress it in the assessment mode of combination of disease and syndrome. Specical population, involving children and seniors who were excluded in pre-marketed clinical trial, were brought into drug monitoring. Sample size needs to comply with statistical requirement. We commonly use cohort study, case-control study, nested case-control, pragmatic randomized controlled trials.

Conditional estimation using prior information in 2-stage group sequential designs assuming asymptotic normality when the trial terminated early.

PubMed

Shimura, Masashi; Maruo, Kazushi; Gosho, Masahiko

2018-04-23

Two-stage designs are widely used to determine whether a clinical trial should be terminated early. In such trials, a maximum likelihood estimate is often adopted to describe the difference in efficacy between the experimental and reference treatments; however, this method is known to display conditional bias. To reduce such bias, a conditional mean-adjusted estimator (CMAE) has been proposed, although the remaining bias may be nonnegligible when a trial is stopped for efficacy at the interim analysis. We propose a new estimator for adjusting the conditional bias of the treatment effect by extending the idea of the CMAE. This estimator is calculated by weighting the maximum likelihood estimate obtained at the interim analysis and the effect size prespecified when calculating the sample size. We evaluate the performance of the proposed estimator through analytical and simulation studies in various settings in which a trial is stopped for efficacy or futility at the interim analysis. We find that the conditional bias of the proposed estimator is smaller than that of the CMAE when the information time at the interim analysis is small. In addition, the mean-squared error of the proposed estimator is also smaller than that of the CMAE. In conclusion, we recommend the use of the proposed estimator for trials that are terminated early for efficacy or futility. Copyright © 2018 John Wiley & Sons, Ltd.

[Basic requirements on post-marketing clinical re-evaluation of chinese medicine and phase IV clinical trials].

PubMed

Xie, Yanming; Wang, Yanping; Tian, Feng; Wang, Yongyan

2011-10-01

As information on safety and effectiveness is not comprehensive, gained from the researches for listing approval of Chinese medicine, it is very necessary to conduct post-marketing clinical re-evaluation of Chinese medicine. Effectiveness, safety and economic evaluation are three main aspects of post-marketing clinical re-evaluation. In this paper, the difference and relations between the post-marketing clinical re-evaluation and the phase IV clinical trials were discussed, and the basic requests and suggestions were proposed, according to the domestic and foreign relevant regulations and experts' suggestions, and discussed the requirements of the phase IV clinical trials on indications, design methods, inclusion and exclusion criteria, sample size, etc.

Omnibus Tests for Interactions in Repeated Measures Designs with Dichotomous Dependent Variables.

ERIC Educational Resources Information Center

Serlin, Ronald C.; Marascuilo, Leonard A.

When examining a repeated measures design with independent groups for a significant group by trial interaction, classical analysis of variance or multivariate procedures can be used if the assumptions underlying the tests are met. Neither procedure may be justified for designs with small sample sizes and dichotomous dependent variables. An omnibus…

A simple two-stage design for quantitative responses with application to a study in diabetic neuropathic pain.

PubMed

Whitehead, John; Valdés-Márquez, Elsa; Lissmats, Agneta

2009-01-01

Two-stage designs offer substantial advantages for early phase II studies. The interim analysis following the first stage allows the study to be stopped for futility, or more positively, it might lead to early progression to the trials needed for late phase II and phase III. If the study is to continue to its second stage, then there is an opportunity for a revision of the total sample size. Two-stage designs have been implemented widely in oncology studies in which there is a single treatment arm and patient responses are binary. In this paper the case of two-arm comparative studies in which responses are quantitative is considered. This setting is common in therapeutic areas other than oncology. It will be assumed that observations are normally distributed, but that there is some doubt concerning their standard deviation, motivating the need for sample size review. The work reported has been motivated by a study in diabetic neuropathic pain, and the development of the design for that trial is described in detail. Copyright 2008 John Wiley & Sons, Ltd.

The reliability and stability of visual working memory capacity.

PubMed

Xu, Z; Adam, K C S; Fang, X; Vogel, E K

2018-04-01

Because of the central role of working memory capacity in cognition, many studies have used short measures of working memory capacity to examine its relationship to other domains. Here, we measured the reliability and stability of visual working memory capacity, measured using a single-probe change detection task. In Experiment 1, the participants (N = 135) completed a large number of trials of a change detection task (540 in total, 180 each of set sizes 4, 6, and 8). With large numbers of both trials and participants, reliability estimates were high (α > .9). We then used an iterative down-sampling procedure to create a look-up table for expected reliability in experiments with small sample sizes. In Experiment 2, the participants (N = 79) completed 31 sessions of single-probe change detection. The first 30 sessions took place over 30 consecutive days, and the last session took place 30 days later. This unprecedented number of sessions allowed us to examine the effects of practice on stability and internal reliability. Even after much practice, individual differences were stable over time (average between-session r = .76).

Fragility of Results in Ophthalmology Randomized Controlled Trials: A Systematic Review.

PubMed

Shen, Carl; Shamsudeen, Isabel; Farrokhyar, Forough; Sabri, Kourosh

2018-05-01

Evidence-based medicine is guided by our interpretation of randomized controlled trials (RCTs) that address important clinical questions. Evaluation of the robustness of statistically significant outcomes adds a crucial element to the global assessment of trial findings. The purpose of this systematic review was to determine the robustness of ophthalmology RCTs through application of the Fragility Index (FI), a novel metric of the robustness of statistically significant outcomes. Systematic review. A literature search (MEDLINE) was performed for all RCTs published in top ophthalmology journals and ophthalmology-related RCTs published in high-impact journals in the past 10 years. Two reviewers independently screened 1811 identified articles for inclusion if they (1) were a human ophthalmology-related trial, (2) had a 1:1 prospective study design, and (3) reported a statistically significant dichotomous outcome in the abstract. All relevant data, including outcome, P value, number of patients in each group, number of events in each group, number of patients lost to follow-up, and trial characteristics, were extracted. The FI of each RCT was calculated and multivariate regression applied to determine predictive factors. The 156 trials had a median sample size of 91.5 (range, 13-2593) patients/eyes, and a median of 28 (range, 4-2217) events. The median FI of the included trials was 2 (range, 0-48), meaning that if 2 non-events were switched to events in the treatment group, the result would lose its statistical significance. A quarter of all trials had an FI of 1 or less, and 75% of trials had an FI of 6 or less. The FI was less than the number of missing data points in 52.6% of trials. Predictive factors for FI by multivariate regression included smaller P value (P < 0.001), larger sample size (P = 0.001), larger number of events (P = 0.011), and journal impact factor (P = 0.029). In ophthalmology trials, statistically significant dichotomous results are often fragile, meaning that a difference of only a couple of events can change the statistical significance. An application of the FI in RCTs may aid in the interpretation of results and assessment of quality of evidence. Copyright © 2017 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Is the placebo powerless? Update of a systematic review with 52 new randomized trials comparing placebo with no treatment.

PubMed

Hróbjartsson, A; Gøtzsche, P C

2004-08-01

It is widely believed that placebo interventions induce powerful effects. We could not confirm this in a systematic review of 114 randomized trials that compared placebo-treated with untreated patients. To study whether a new sample of trials would reproduce our earlier findings, and to update the review. Systematic review of trials that were published since our last search (or not previously identified), and of all available trials. Data was available in 42 out of 52 new trials (3212 patients). The results were similar to our previous findings. The updated review summarizes data from 156 trials (11 737 patients). We found no statistically significant pooled effect in 38 trials with binary outcomes, relative risk 0.95 (95% confidence interval 0.89-1.01). The effect on continuous outcomes decreased with increasing sample size, and there was considerable variation in effect also between large trials; the effect estimates should therefore be interpreted cautiously. If this bias is disregarded, the pooled standardized mean difference in 118 trials with continuous outcomes was -0.24 (-0.31 to -0.17). For trials with patient-reported outcomes the effect was -0.30 (-0.38 to -0.21), but only -0.10 (-0.20 to 0.01) for trials with observer-reported outcomes. Of 10 clinical conditions investigated in three trials or more, placebo had a statistically significant pooled effect only on pain or phobia on continuous scales. We found no evidence of a generally large effect of placebo interventions. A possible small effect on patient-reported continuous outcomes, especially pain, could not be clearly distinguished from bias.

Clinical Trials Targeting Aging and Age-Related Multimorbidity

PubMed Central

Crimmins, Eileen M; Grossardt, Brandon R; Crandall, Jill P; Gelfond, Jonathan A L; Harris, Tamara B; Kritchevsky, Stephen B; Manson, JoAnn E; Robinson, Jennifer G; Rocca, Walter A; Temprosa, Marinella; Thomas, Fridtjof; Wallace, Robert; Barzilai, Nir

2017-01-01

Abstract Background There is growing interest in identifying interventions that may increase health span by targeting biological processes underlying aging. The design of efficient and rigorous clinical trials to assess these interventions requires careful consideration of eligibility criteria, outcomes, sample size, and monitoring plans. Methods Experienced geriatrics researchers and clinical trialists collaborated to provide advice on clinical trial design. Results Outcomes based on the accumulation and incidence of age-related chronic diseases are attractive for clinical trials targeting aging. Accumulation and incidence rates of multimorbidity outcomes were developed by selecting at-risk subsets of individuals from three large cohort studies of older individuals. These provide representative benchmark data for decisions on eligibility, duration, and assessment protocols. Monitoring rules should be sensitive to targeting aging-related, rather than disease-specific, outcomes. Conclusions Clinical trials targeting aging are feasible, but require careful design consideration and monitoring rules. PMID:28364543

Hierarchical Commensurate and Power Prior Models for Adaptive Incorporation of Historical Information in Clinical Trials

PubMed Central

Hobbs, Brian P.; Carlin, Bradley P.; Mandrekar, Sumithra J.; Sargent, Daniel J.

2011-01-01

Summary Bayesian clinical trial designs offer the possibility of a substantially reduced sample size, increased statistical power, and reductions in cost and ethical hazard. However when prior and current information conflict, Bayesian methods can lead to higher than expected Type I error, as well as the possibility of a costlier and lengthier trial. This motivates an investigation of the feasibility of hierarchical Bayesian methods for incorporating historical data that are adaptively robust to prior information that reveals itself to be inconsistent with the accumulating experimental data. In this paper, we present several models that allow for the commensurability of the information in the historical and current data to determine how much historical information is used. A primary tool is elaborating the traditional power prior approach based upon a measure of commensurability for Gaussian data. We compare the frequentist performance of several methods using simulations, and close with an example of a colon cancer trial that illustrates a linear models extension of our adaptive borrowing approach. Our proposed methods produce more precise estimates of the model parameters, in particular conferring statistical significance to the observed reduction in tumor size for the experimental regimen as compared to the control regimen. PMID:21361892

A comprehensive algorithm for determining whether a run-in strategy will be a cost-effective design modification in a randomized clinical trial.

PubMed

Schechtman, K B; Gordon, M E

1993-01-30

In randomized clinical trials, poor compliance and treatment intolerance lead to reduced between-group differences, increased sample size requirements, and increased cost. A run-in strategy is intended to reduce these problems. In this paper, we develop a comprehensive set of measures specifically sensitive to the effect of a run-in on cost and sample size requirements, both before and after randomization. Using these measures, we describe a step-by-step algorithm through which one can estimate the cost-effectiveness of a potential run-in. Because the cost-effectiveness of a run-in is partly mediated by its effect on sample size, we begin by discussing the likely impact of a planned run-in on the required number of randomized, eligible, and screened subjects. Run-in strategies are most likely to be cost-effective when: (1) per patient costs during the post-randomization as compared to the screening period are high; (2) poor compliance is associated with a substantial reduction in response to treatment; (3) the number of screened patients needed to identify a single eligible patient is small; (4) the run-in is inexpensive; (5) for most patients, the run-in compliance status is maintained following randomization and, most importantly, (6) many subjects excluded by the run-in are treatment intolerant or non-compliant to the extent that we expect little or no treatment response. Our analysis suggests that conditions for the cost-effectiveness of run-in strategies are stringent. In particular, if the only purpose of a run-in is to exclude ordinary partial compliers, the run-in will frequently add to the cost of the trial. Often, the cost-effectiveness of a run-in requires that one can identify and exclude a substantial number of treatment intolerant or otherwise unresponsive subjects.

An approach to trial design and analysis in the era of non-proportional hazards of the treatment effect.

PubMed

Royston, Patrick; Parmar, Mahesh K B

2014-08-07

Most randomized controlled trials with a time-to-event outcome are designed and analysed under the proportional hazards assumption, with a target hazard ratio for the treatment effect in mind. However, the hazards may be non-proportional. We address how to design a trial under such conditions, and how to analyse the results. We propose to extend the usual approach, a logrank test, to also include the Grambsch-Therneau test of proportional hazards. We test the resulting composite null hypothesis using a joint test for the hazard ratio and for time-dependent behaviour of the hazard ratio. We compute the power and sample size for the logrank test under proportional hazards, and from that we compute the power of the joint test. For the estimation of relevant quantities from the trial data, various models could be used; we advocate adopting a pre-specified flexible parametric survival model that supports time-dependent behaviour of the hazard ratio. We present the mathematics for calculating the power and sample size for the joint test. We illustrate the methodology in real data from two randomized trials, one in ovarian cancer and the other in treating cellulitis. We show selected estimates and their uncertainty derived from the advocated flexible parametric model. We demonstrate in a small simulation study that when a treatment effect either increases or decreases over time, the joint test can outperform the logrank test in the presence of both patterns of non-proportional hazards. Those designing and analysing trials in the era of non-proportional hazards need to acknowledge that a more complex type of treatment effect is becoming more common. Our method for the design of the trial retains the tools familiar in the standard methodology based on the logrank test, and extends it to incorporate a joint test of the null hypothesis with power against non-proportional hazards. For the analysis of trial data, we propose the use of a pre-specified flexible parametric model that can represent a time-dependent hazard ratio if one is present.

The effects of pilates on mental health outcomes: A meta-analysis of controlled trials.

PubMed

Fleming, Karl M; Herring, Matthew P

2018-04-01

This meta-analysis estimated the population effect size for Pilates effects on mental health outcomes. Articles published prior to August 2017 were located with searches of Pubmed, Medline, Cinahl, SportDiscus, Science Direct, PsychINFO, Web of Science, and Cochrane Controlled Trial Register using combinations of: Pilates, Pilates method, mental health, anxiety, and depression. Eight English-language publications that included allocation to a Pilates intervention or non-active control and a measure of anxiety and/or depressive symptoms at baseline and after the Pilates intervention were selected. Participant and intervention characteristics, anxiety and depressive symptoms and other mental health outcomes, including feelings of energy and fatigue and quality of life, were extracted. Hedges' d effect sizes were computed, study quality was assessed, and random effects models estimated sampling error and population variance. Pilates resulted in significant, large, heterogeneous reductions in depressive (Δ = 1.27, 95%CI: 0.44, 2.09; z = 3.02, p ≤ 0.003; N = 6, n = 261) and anxiety symptoms (Δ = 1.29, 95%CI: 0.24, 2.33; z = 2.40, p ≤ 0.02; N = 5, n = 231) and feelings of fatigue (Δ = 0.93, 95%CI: 0.21, 1.66; z = 2.52, p ≤ 0.012; N = 3, n = 161), and increases in feelings of energy (Δ = 1.49, 95%CI: 0.67, 2.30; z = 3.57, p < 0.001; N = 2, n = 116). Though this review included a small number of controlled trials with small sample sizes and non-active control conditions of variable quality, the available evidence reviewed here supports that Pilates improves mental health outcomes. Rigorously designed randomized controlled trials, including those that compare Pilates to other empirically-supported therapies, are needed to better understand Pilates' clinical effectiveness and plausible mechanisms of effects. Copyright © 2018 Elsevier Ltd. All rights reserved.

C-MAC videolaryngoscope versus Macintosh laryngoscope for tracheal intubation: A systematic review and meta-analysis with trial sequential analysis.

PubMed

Hoshijima, Hiroshi; Mihara, Takahiro; Maruyama, Koichi; Denawa, Yohei; Mizuta, Kentaro; Shiga, Toshiya; Nagasaka, Hiroshi

2018-06-09

The C-MAC laryngoscope (C-MAC) is a videolaryngoscope that uses a modified Macintosh blade. Although several anecdotal reports exist, it remains unclear whether the C-MAC is superior to the Macintosh laryngoscope for tracheal intubation in the adult population. Systematic review, meta-analysis. Operating room, intensive care unit. For inclusion in our analysis, studies had to be prospective randomised trials which compared the C-MAC with the Macintosh laryngoscope for tracheal intubation in the adult population. Data on success rates, intubation time, glottic visualisation and incidence of external laryngeal manipulations (ELM) during tracheal intubation were extracted from the identified studies. In subgroup analysis, we separated those parameters to assess the influence of the airway condition (normal or difficult) and laryngoscopists (novice or experienced). We conducted a trial sequential analysis (TSA). Sixteen articles with 18 trials met the inclusion criteria. The C-MAC provided better glottic visualisation compared to the Macintosh (RR, 1.08; 95% CI, 1.03-1.14). TSA corrected the CI to 1.01-1.19; thus, total sample size reached the required information size (RIS). Success rates and intubation time did not differ significantly between the laryngoscopes. TSA showed that total sample size reached the RIS for success rates. The TSA Z curve surpassed the futility boundary. The C-MAC required less ELM compared to the Macintosh (RR, 0.83; 95% CI, 0.72-0.96). TSA corrected the CI to 0.67-1.03; 52.3% of the RIS was achieved. In difficult airways, the C-MAC showed superior success rates, glottic visualisation, and less ELM compared to the Macintosh. Among experienced laryngoscopists, the C-MAC offered better glottic visualisation with less ELM than the Macintosh. The C-MAC provided better glottic visualisation and less ELM (GRADE: Very Low or Moderate), with improved success rates, glottic visualisation, and less ELM in difficult airways. Copyright © 2018 Elsevier Inc. All rights reserved.

Feasibility randomised controlled trial of Recovery-focused Cognitive Behavioural Therapy for Older Adults with bipolar disorder (RfCBT-OA): study protocol.

PubMed

Tyler, Elizabeth; Lobban, Fiona; Sutton, Chris; Depp, Colin; Johnson, Sheri; Laidlaw, Ken; Jones, Steven H

2016-03-03

Bipolar disorder is a severe and chronic mental health problem that persists into older adulthood. The number of people living with this condition is set to rise as the UK experiences a rapid ageing of its population. To date, there has been very little research or service development with respect to psychological therapies for this group of people. A parallel two-arm randomised controlled trial comparing a 14-session, 6-month Recovery-focused Cognitive-Behavioural Therapy for Older Adults with bipolar disorder (RfCBT-OA) plus treatment as usual (TAU) versus TAU alone. Participants will be recruited in the North-West of England via primary and secondary mental health services and through self-referral. The primary objective of the study is to evaluate the feasibility and acceptability of RfCBT-OA; therefore, a formal power calculation is not appropriate. It has been estimated that randomising 25 participants per group will be sufficient to be able to reliably determine the primary feasibility outcomes (eg, recruitment and retention rates), in line with recommendations for sample sizes for feasibility/pilot trials. Participants in both arms will complete assessments at baseline and then every 3 months, over the 12-month follow-up period. We will gain an estimate of the likely effect size of RfCBT-OA on a range of clinical outcomes and estimate parameters needed to determine the appropriate sample size for a definitive, larger trial to evaluate the effectiveness and cost-effectiveness of RfCBT-OA. Data analysis is discussed further in the Analysis section in the main paper. This protocol was approved by the UK National Health Service (NHS) Ethics Committee process (REC ref: 15/NW/0330). The findings of the trial will be disseminated through peer-reviewed journals, national and international conference presentations and local, participating NHS trusts. ISRCTN13875321; Pre-results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Do fixed-dose combination pills or unit-of-use packaging improve adherence? A systematic review.

PubMed Central

Connor, Jennie; Rafter, Natasha; Rodgers, Anthony

2004-01-01

Adequate adherence to medication regimens is central to the successful treatment of communicable and noncommunicable disease. Fixed-dose combination pills and unit-of-use packaging are therapy-related interventions that are designed to simplify medication regimens and so potentially improve adherence. We conducted a systematic review of relevant randomized trials in order to quantify the effects of fixed-dose combination pills and unit-of-use packaging, compared with medications as usually presented, in terms of adherence to treatment and improved outcomes. Only 15 trials met the inclusion criteria; fixed-dose combination pills were investigated in three of these, while unit-of-use packaging was studied in 12 trials. The trials involved treatments for communicable diseases (n = 5), blood pressure lowering medications (n = 3), diabetic patients (n = 1), vitamin supplementation (n = 1) and management of multiple medications by the elderly (n = 5). The results of the trials suggested that there were trends towards improved adherence and/or clinical outcomes in all but three of the trials; this reached statistical significance in four out of seven trials reporting a clinically relevant or intermediate end-point, and in seven out of thirteen trials reporting medication adherence. Measures of outcome were, however, heterogeneous, and interpretation was further limited by methodological issues, particularly small sample size, short duration and loss to follow-up. Overall, the evidence suggests that fixed-dose combination pills and unit-of-use packaging are likely to improve adherence in a range of settings, but the limitations of the available evidence means that uncertainty remains about the size of these benefits. PMID:15654408

Controlled Trials in Children: Quantity, Methodological Quality and Descriptive Characteristics of Pediatric Controlled Trials Published 1948-2006

PubMed Central

Thomson, Denise; Hartling, Lisa; Cohen, Eyal; Vandermeer, Ben; Tjosvold, Lisa; Klassen, Terry P.

2010-01-01

Background The objective of this study was to describe randomized controlled trials (RCTs) and controlled clinical trials (CCTs) in child health published between 1948 and 2006, in terms of quantity, methodological quality, and publication and trial characteristics. We used the Trials Register of the Cochrane Child Health Field for overall trends and a sample from this to explore trial characteristics in more detail. Methodology/Principal Findings We extracted descriptive data on a random sample of 578 trials. Ninety-six percent of the trials were published in English; the percentage of child-only trials was 90.5%. The most frequent diagnostic categories were infectious diseases (13.2%), behavioural and psychiatric disorders (11.6%), neonatal critical care (11.4%), respiratory disorders (8.9%), non-critical neonatology (7.9%), and anaesthesia (6.5%). There were significantly fewer child-only studies (i.e., more mixed child and adult studies) over time (P = 0.0460). The proportion of RCTs to CCTs increased significantly over time (P<0.0001), as did the proportion of multicentre trials (P = 0.002). Significant increases over time were found in methodological quality (Jadad score) (P<0.0001), the proportion of double-blind studies (P<0.0001), and studies with adequate allocation concealment (P<0.0001). Additionally, we found an improvement in reporting over time: adequate description of withdrawals and losses to follow-up (P<0.0001), sample size calculations (P<0.0001), and intention-to-treat analysis (P<0.0001). However, many trials still do not describe their level of blinding, and allocation concealment was inadequately reported in the majority of studies across the entire time period. The proportion of studies with industry funding decreased slightly over time (P = 0.003), and these studies were more likely to report positive conclusions (P = 0.028). Conclusions/Significance The quantity and quality of pediatric controlled trials has increased over time; however, much work remains to be done, particularly in improving methodological issues around conduct and reporting of trials. PMID:20927344

The Quality of Reporting of Measures of Precision in Animal Experiments in Implant Dentistry: A Methodological Study.

PubMed

Faggion, Clovis Mariano; Aranda, Luisiana; Diaz, Karla Tatiana; Shih, Ming-Chieh; Tu, Yu-Kang; Alarcón, Marco Antonio

2016-01-01

Information on precision of treatment-effect estimates is pivotal for understanding research findings. In animal experiments, which provide important information for supporting clinical trials in implant dentistry, inaccurate information may lead to biased clinical trials. The aim of this methodological study was to determine whether sample size calculation, standard errors, and confidence intervals for treatment-effect estimates are reported accurately in publications describing animal experiments in implant dentistry. MEDLINE (via PubMed), Scopus, and SciELO databases were searched to identify reports involving animal experiments with dental implants published from September 2010 to March 2015. Data from publications were extracted into a standardized form with nine items related to precision of treatment estimates and experiment characteristics. Data selection and extraction were performed independently and in duplicate, with disagreements resolved by discussion-based consensus. The chi-square and Fisher exact tests were used to assess differences in reporting according to study sponsorship type and impact factor of the journal of publication. The sample comprised reports of 161 animal experiments. Sample size calculation was reported in five (2%) publications. P values and confidence intervals were reported in 152 (94%) and 13 (8%) of these publications, respectively. Standard errors were reported in 19 (12%) publications. Confidence intervals were better reported in publications describing industry-supported animal experiments (P = .03) and with a higher impact factor (P = .02). Information on precision of estimates is rarely reported in publications describing animal experiments in implant dentistry. This lack of information makes it difficult to evaluate whether the translation of animal research findings to clinical trials is adequate.

Naltrexone and Cognitive Behavioral Therapy for the Treatment of Alcohol Dependence

PubMed Central

Baros, AM; Latham, PK; Anton, RF

2008-01-01

Background Sex differences in regards to pharmacotherapy for alcoholism is a topic of concern following publications suggesting naltrexone, one of the longest approved treatments of alcoholism, is not as effective in women as in men. This study was conducted by combining two randomized placebo controlled clinical trials utilizing similar methodologies and personnel in which the data was amalgamated to evaluate sex effects in a reasonable sized sample. Methods 211 alcoholics (57 female; 154 male) were randomized to the naltrexone/CBT or placebo/CBT arm of the two clinical trials analyzed. Baseline variables were examined for differences between sex and treatment groups via analysis of variance (ANOVA) for continuous variable or chi-square test for categorical variables. All initial outcome analysis was conducted under an intent-to-treat analysis plan. Effect sizes for naltrexone over placebo were determined by Cohen’s D (d). Results The effect size of naltrexone over placebo for the following outcome variables was similar in men and women (%days abstinent (PDA) d=0.36, %heavy drinking days (PHDD) d=0.36 and total standard drinks (TSD) d=0.36). Only for men were the differences significant secondary to the larger sample size (PDA p=0.03; PHDD p=0.03; TSD p=0.04). There were a few variables (GGT at wk-12 change from baseline to week-12: men d=0.36, p=0.05; women d=0.20, p=0.45 and drinks per drinking day: men d=0.36, p=0.05; women d=0.28, p=0.34) where the naltrexone effect size for men was greater than women. In women, naltrexone tended to increase continuous abstinent days before a first drink (women d-0.46, p=0.09; men d=0.00, p=0.44). Conclusions The effect size of naltrexone over placebo appeared similar in women and men in our hands suggesting the findings of sex differences in naltrexone response might have to do with sample size and/or endpoint drinking variables rather than any inherent pharmacological or biological differences in response. PMID:18336635

Effects of whole body vibration on muscle spasticity for people with central nervous system disorders: a systematic review.

PubMed

Huang, Meizhen; Liao, Lin-Rong; Pang, Marco Yc

2017-01-01

To examine the effects of whole-body vibration on spasticity among people with central nervous system disorders. Electronic searches were conducted using CINAHL, Cochrane Library, MEDLINE, Physiotherapy Evidence Database, PubMed, PsycINFO, SPORTDiscus and Scopus to identify randomized controlled trials that investigated the effect of whole-body vibration on spasticity among people with central nervous system disorders (last search in August 2015). The methodological quality and level of evidence were rated using the PEDro scale and guidelines set by the Oxford Centre for Evidence-Based Medicine. Nine trials with totally 266 subjects (three in cerebral palsy, one in multiple sclerosis, one in spinocerebellar ataxia, and four in stroke) fulfilled all selection criteria. One study was level 1b (PEDro⩾6 and sample size>50) and eight were level 2b (PEDro<6 or sample size ⩽50). All three cerebral palsy trials (level 2b) reported some beneficial effects of whole-body vibration on reducing leg muscle spasticity. Otherwise, the results revealed no consistent benefits on spasticity in other neurological conditions studied. There is little evidence that change in spasticity was related to change in functional performance. The optimal protocol could not be identified. Many reviewed studies were limited by weak methodological and reporting quality. Adverse events were minor and rare. Whole-body vibration may be useful in reducing leg muscle spasticity in cerebral palsy but this needs to be verified by future high quality trials. There is insufficient evidence to support or refute the notion that whole-body vibration can reduce spasticity in stroke, spinocerebellar ataxia or multiple sclerosis.

Electroacupuncture for Tinnitus: A Systematic Review

PubMed Central

Liu, Yang; Zhong, Juan; Jiang, Luyun; Liu, Ying; Chen, Qing; Xie, Yan; Zhang, Qinxiu

2016-01-01

Background Treatment effects of electroacupuncture for patients with subjective tinnitus has yet to be clarified. Objectives To assess the effect of electroacupuncutre for alleviating the symptoms of subjective tinnitus. Methods Extensive literature searches were carried out in three English and four Chinese databases (PubMed, EMBASE, Cochrane Library, CNKI, Wanfang Chinese Digital Periodical and Conference Database, VIP, and ChiCTR).The date of the most recent search was 1 June 2014. Randomized controlled trials (RCTs) or quasi-RCTs were included. The titles, abstracts, and keywords of all records were reviewed by two authors independently. The data were collected and extracted by three authors. The risk of bias in the trials was assessed in accordance with the Cochrane Handbook, version 5.1.0. (http://www.handbook.cochrane.org). Eighty-nine studies were retrieved. After discarding 84 articles, five studies with 322 participants were identified. Assessment of the methodological quality of the studies identified weaknesses in all five studies. All studies were judged as having a high risk of selection and performance bias. The attrition bias was high in four studies. Incompleteness bias was low in all studies. Reporting bias was unclear in all studies. Because of the limited number of trials included and the various types of interventions and outcomes, we were unable to conduct pooled analyses. Conclusions Due to the poor methodological quality of the primary studies and the small sample sizes, no convincing evidence that electroacupuncture is beneficial for treating tinnitus could be found. There is an urgent need for more high-quality trials with large sample sizes for the investigation of electroacupuncture treatment for tinnitus. PMID:26938213

Systematic review on randomized controlled trials of coronary heart disease complicated with depression treated with Chinese herbal medicines.

PubMed

Wang, An-Lu; Chen, Zhuo; Luo, Jing; Shang, Qing-Hua; Xu, Hao

2016-01-01

This systemic review evaluated the efficacy and safety of Chinese herbal medicines (CHMs) in patients with coronary heart disease (CHD) complicated with depression. All databases were retrieved till September 30, 2014. Randomized controlled trials (RCTs) comparing CHMs with placebo or conventional Western medicine were retrieved. Data extraction, analyses and quality assessment were performed according to the Cochrane standards. RevMan 5.3 was used to synthesize the results. Thirteen RCTs enrolling 1,095 patients were included. Subgroup analysis was used to assess data. In reducing the degree of depression, CHMs showed no statistic difference in the 4th week [mean difference (MD)=-1.06; 95% confidence interval (CI)-2.38 to 0.26; n=501; I(2)=73%], but it was associated with a statistically significant difference in the 8th week (MD=-1.00; 95% CI-1.64 to-0.36; n=436; I(2)=48%). Meanwhile, the combination therapy (CHMs together with antidepressants) showed significant statistic differences both in the 4th week (MD=-1.99; 95% CI-3.80 to-0.18; n=90) and in the 8th week (MD=-5.61; 95% CI-6.26 to-4.97; n=242; I(2)=87%). In CHD-related clinical evaluation, 3 trials reported the intervention group was superior to the control group. Four trials showed adverse events in the intervention group was less than that in the control group. CHMs showed potentially benefits on patients with CHD complicated with depression. Moreover, the effect of CHMs may be similar to or better than antidepressant in certain fields but with less side effects. However, because of small sample size and potential bias of most trials, this result should be interpreted with caution. More rigorous trials with larger sample size and higher quality are warranted to give high quality of evidence to support the use of CHMs for CHD complicated with depression.

Preventing childhood obesity, phase II feasibility study focusing on South Asians: BEACHeS

PubMed Central

Adab, Peymané; Pallan, Miranda J; Cade, Janet; Ekelund, Ulf; Barrett, Timothy; Daley, Amanda; Deeks, Jonathan; Duda, Joan; Gill, Paramjit; Parry, Jayne; Bhopal, Raj; Cheng, K K

2014-01-01

Objective To assess feasibility and acceptability of a multifaceted, culturally appropriate intervention for preventing obesity in South Asian children, and to obtain data to inform sample size for a definitive trial. Design Phase II feasibility study of a complex intervention. Setting 8 primary schools in inner city Birmingham, UK, within populations that are predominantly South Asian. Participants 1090 children aged 6–8 years took part in the intervention. 571 (85.9% from South Asian background) underwent baseline measures. 85.5% (n=488) were followed up 2 years later. Interventions The 1-year intervention consisted of school-based and family-based activities, targeting dietary and physical activity behaviours. The intervention was modified and refined throughout the period of delivery. Main outcome measures Acceptability and feasibility of the intervention and of measurements required to assess outcomes in a definitive trial. The difference in body mass index (BMI) z-score between arms was used to inform sample size calculations for a definitive trial. Results Some intervention components (increasing school physical activity opportunities, family cooking skills workshops, signposting of local leisure facilities and attending day event at a football club) were feasible and acceptable. Other components were acceptable, but not feasible. Promoting walking groups was neither acceptable nor feasible. At follow-up, children in the intervention compared with the control group were less likely to be obese (OR 0.41; 0.19 to 0.89), and had lower adjusted BMI z-score (−0.15 kg/m2; 95% CI −0.27 to −0.03). Conclusions The feasibility study informed components for an intervention programme. The favourable direction of outcome for weight status in the intervention group supports the need for a definitive trial. A cluster randomised controlled trial is now underway to assess the clinical and cost-effectiveness of the intervention. Trial registration number ISRCTN51016370. PMID:24722198

Evaluating biomarkers for prognostic enrichment of clinical trials.

PubMed

Kerr, Kathleen F; Roth, Jeremy; Zhu, Kehao; Thiessen-Philbrook, Heather; Meisner, Allison; Wilson, Francis Perry; Coca, Steven; Parikh, Chirag R

2017-12-01

A potential use of biomarkers is to assist in prognostic enrichment of clinical trials, where only patients at relatively higher risk for an outcome of interest are eligible for the trial. We investigated methods for evaluating biomarkers for prognostic enrichment. We identified five key considerations when considering a biomarker and a screening threshold for prognostic enrichment: (1) clinical trial sample size, (2) calendar time to enroll the trial, (3) total patient screening costs and the total per-patient trial costs, (4) generalizability of trial results, and (5) ethical evaluation of trial eligibility criteria. Items (1)-(3) are amenable to quantitative analysis. We developed the Biomarker Prognostic Enrichment Tool for evaluating biomarkers for prognostic enrichment at varying levels of screening stringency. We demonstrate that both modestly prognostic and strongly prognostic biomarkers can improve trial metrics using Biomarker Prognostic Enrichment Tool. Biomarker Prognostic Enrichment Tool is available as a webtool at http://prognosticenrichment.com and as a package for the R statistical computing platform. In some clinical settings, even biomarkers with modest prognostic performance can be useful for prognostic enrichment. In addition to the quantitative analysis provided by Biomarker Prognostic Enrichment Tool, investigators must consider the generalizability of trial results and evaluate the ethics of trial eligibility criteria.

Efficacy of an internet-based intervention for burnout: a randomized controlled trial in the German working population.

PubMed

Jonas, Benjamin; Leuschner, Fabian; Tossmann, Peter

2017-03-01

Internet-based interventions are a viable treatment option for various mental problems. However, their effects on the burnout syndrome yielded mixed results. In this paper, we examine the efficacy of a structured and therapist-guided internet intervention, based on solution-focused and cognitive-behavioral therapy, for individuals with symptoms of burnout. Two-arm, Internet-based, randomized, wait-list controlled trial (RCT). Participants were recruited through in-house events and online advertising. They were randomly assigned to the intervention or a wait-list. Group comparison was conducted three months after randomization. Outcomes were the burnout level according to the Maslach Burnout Inventory (MBI-GS) and the levels of depression, anxiety and stress according to the DASS-21. Thirty-nine participants were included in the trial; 36 (92.3%) took part at the 3-months-follow-up. Intention-to-treat analyses revealed significant group differences in favor of the intervention group in depression (d = 0.66), cynicism (d = 0.87) and personal accomplishment (d = 0.75). The intervention helped ameliorate symptoms of work-related stress and burnout. Although limited by a small sample size, the study suggests that the program provides effective support for affected individuals. However, further studies with bigger sample sizes should be conducted to examine the effects of such programs more precisely.

Randomized trials are frequently fragmented in multiple secondary publications.

PubMed

Ebrahim, Shanil; Montoya, Luis; Kamal El Din, Mostafa; Sohani, Zahra N; Agarwal, Arnav; Bance, Sheena; Saquib, Juliann; Saquib, Nazmus; Ioannidis, John P A

2016-11-01

To assess the frequency and features of secondary publications of randomized controlled trials (RCTs). For 191 RCTs published in high-impact journals in 2009, we searched for secondary publications coauthored by at least one same author of the primary trial publication. We evaluated the probability of having secondary publications, characteristics of the primary trial publication that predict having secondary publications, types of secondary analyses conducted, and statistical significance of those analyses. Of 191 primary trials, 88 (46%) had a total of 475 secondary publications by 2/2014. Eight trials had >10 (up to 51) secondary publications each. In multivariable modeling, the risk of having subsequent secondary publications increased 1.32-fold (95% CI 1.05-1.68) per 10-fold increase in sample size, and 1.71-fold (95% CI 1.19-2.45) in the presence of a design article. In a sample of 197 secondary publications examined in depth, 193 tested different hypotheses than the primary publication. Of the 193, 43 tested differences between subgroups, 85 assessed predictive factors associated with an outcome of interest, 118 evaluated different outcomes than the original article, 71 had differences in eligibility criteria, and 21 assessed different durations of follow-up; 176 (91%) presented at least one analysis with statistically significant results. Approximately half of randomized trials in high-impact journals have secondary publications published with a few trials followed by numerous secondary publications. Almost all of these publications report some statistically significant results. Copyright © 2016 Elsevier Inc. All rights reserved.

Paradigms for adaptive statistical information designs: practical experiences and strategies.

PubMed

Wang, Sue-Jane; Hung, H M James; O'Neill, Robert

2012-11-10

In the last decade or so, interest in adaptive design clinical trials has gradually been directed towards their use in regulatory submissions by pharmaceutical drug sponsors to evaluate investigational new drugs. Methodological advances of adaptive designs are abundant in the statistical literature since the 1970s. The adaptive design paradigm has been enthusiastically perceived to increase the efficiency and to be more cost-effective than the fixed design paradigm for drug development. Much interest in adaptive designs is in those studies with two-stages, where stage 1 is exploratory and stage 2 depends upon stage 1 results, but where the data of both stages will be combined to yield statistical evidence for use as that of a pivotal registration trial. It was not until the recent release of the US Food and Drug Administration Draft Guidance for Industry on Adaptive Design Clinical Trials for Drugs and Biologics (2010) that the boundaries of flexibility for adaptive designs were specifically considered for regulatory purposes, including what are exploratory goals, and what are the goals of adequate and well-controlled (A&WC) trials (2002). The guidance carefully described these distinctions in an attempt to minimize the confusion between the goals of preliminary learning phases of drug development, which are inherently substantially uncertain, and the definitive inference-based phases of drug development. In this paper, in addition to discussing some aspects of adaptive designs in a confirmatory study setting, we underscore the value of adaptive designs when used in exploratory trials to improve planning of subsequent A&WC trials. One type of adaptation that is receiving attention is the re-estimation of the sample size during the course of the trial. We refer to this type of adaptation as an adaptive statistical information design. Specifically, a case example is used to illustrate how challenging it is to plan a confirmatory adaptive statistical information design. We highlight the substantial risk of planning the sample size for confirmatory trials when information is very uninformative and stipulate the advantages of adaptive statistical information designs for planning exploratory trials. Practical experiences and strategies as lessons learned from more recent adaptive design proposals will be discussed to pinpoint the improved utilities of adaptive design clinical trials and their potential to increase the chance of a successful drug development. Published 2012. This article is a US Government work and is in the public domain in the USA.

Toward onset prevention of cognitive decline in adults with Down syndrome (the TOP-COG study): study protocol for a randomized controlled trial.

PubMed

Cooper, Sally-Ann; Caslake, Muriel; Evans, Jonathan; Hassiotis, Angela; Jahoda, Andrew; McConnachie, Alex; Morrison, Jill; Ring, Howard; Starr, John; Stiles, Ciara; Sullivan, Frank

2014-06-03

Early-onset dementia is common in Down syndrome adults, who have trisomy 21. The amyloid precursor protein gene is on chromosome 21, and so is over-expressed in Down syndrome, leading to amyloid β (Aβ) over-production, a major upstream pathway leading to Alzheimer disease (AD). Statins (microsomal 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors), have pleiotropic effects including potentially increasing brain amyloid clearance, making them plausible agents to reduce AD risk. Animal models, human observational studies, and small scale trials support this rationale, however, there are no AD primary prevention trials in Down syndrome adults. In this study we study aim to inform the design of a full-scale primary prevention trial. TOP-COG is a feasibility and pilot double-blind randomized controlled trial (RCT), with a nested qualitative study, conducted in the general community. About 60 Down syndrome adults, aged ≥50 will be included. The intervention is oral simvastatin 40 mg at night for 12 months, versus placebo. The primary endpoint is recruitment and retention rates. Secondary endpoints are (1) tolerability and safety; (2) detection of the most sensitive neurocognitive instruments; (3) perceptions of Down syndrome adults and caregivers on whether to participate, and assessment experiences; (4) distributions of cognitive decline, adaptive behavior, general health/quality of life, service use, caregiver strain, and sample size implications; (5) whether Aβ42/Aβ40 is a cognitive decline biomarker. We will describe percentages recruited from each source, the number of contacts to achieve this, plus recruitment rate by general population size. We will calculate summary statistics with 90% confidence limits where appropriate, for each study outcome as a whole, by treatment group and in relation to baseline age, cognitive function, cholesterol and other characteristics. Changes over time will be summarized graphically. The sample size for a definitive RCT will be estimated under alternative assumptions. This study is important, as AD is a major problem for Down syndrome adults, for whom there are currently no effective preventions or treatments. It will also delineate the most suitable assessment instruments for this population. Recruitment of intellectually disabled adults is notoriously difficult, and we shall provide valuable information on this, informing future studies. Current Controlled Trials ISRCTN Register ID: ISRCTN67338640 (17 November 2011).

The efficacy of anticonvulsants on orofacial pain: a systematic review.

PubMed

Martin, Wilhelmus J J M; Forouzanfar, Tymour

2011-05-01

Controversy exists about the effectiveness of anticonvulsants for the management of orofacial pain disorders. To ascertain appropriate therapies, a systematic review was conducted of existing randomized controlled trials. Trials were identified from PubMed, Cochrane, and Ovid Medline databases from 1962 through March 2010, from references in retrieved reports, and from references in review articles. Eight useful trials were identified for this review. Six studies were randomized placebo-controlled trials and 2 studies were randomized active-controlled. Two independent investigators reviewed these articles by using a 15-item checklist. Four studies were classified as "high quality." However, heterogeneity of the trials and the small sample sizes precluded the drawing of firm conclusions about the efficacy of the interventions studied on orofacial pain patients. There is limited to moderate evidence supporting the efficacy of commonly used anticonvulsants for treatment of patients with orofacial pain disorders. More randomized controlled trials are needed on the efficacy of anticonvulsants. Copyright © 2011 Mosby, Inc. All rights reserved.

More ethical and more efficient clinical research: multiplex trial design.

PubMed

Keus, Frederik; van der Horst, Iwan C C; Nijsten, Maarten W

2014-08-14

Today's clinical research faces challenges such as a lack of clinical equipoise between treatment arms, reluctance in randomizing for multiple treatments simultaneously, inability to address interactions and increasingly restricted resources. Furthermore, many trials are biased by extensive exclusion criteria, relatively small sample size and less appropriate outcome measures. We propose a 'Multiplex' trial design that preserves clinical equipoise with a continuous and factorial trial design that will also result in more efficient use of resources. This multiplex design accommodates subtrials with appropriate choice of treatment arms within each subtrial. Clinical equipoise should increase consent rates while the factorial design is the best way to identify interactions. The multiplex design may evolve naturally from today's research limitations and challenges, while principal objections seem absent. However this new design poses important infrastructural, organisational and psychological challenges that need in depth consideration.

Effect of field view size and lighting on unique-hue selection using Natural Color System object colors.

PubMed

Shamey, Renzo; Zubair, Muhammad; Cheema, Hammad

2015-08-01

The aim of this study was twofold, first to determine the effect of field view size and second of illumination conditions on the selection of unique hue samples (UHs: R, Y, G and B) from two rotatable trays, each containing forty highly chromatic Natural Color System (NCS) samples, on one tray corresponding to 1.4° and on the other to 5.7° field of view size. UH selections were made by 25 color-normal observers who repeated assessments three times with a gap of at least 24h between trials. Observers separately assessed UHs under four illumination conditions simulating illuminants D65, A, F2 and F11. An apparent hue shift (statistically significant for UR) was noted for UH selections at 5.7° field of view compared to those at 1.4°. Observers' overall variability was found to be higher for UH stimuli selections at the larger field of view. Intra-observer variability was found to be approximately 18.7% of inter-observer variability in selection of samples for both sample sizes. The highest intra-observer variability was under simulated illuminant D65, followed by A, F11, and F2. Copyright © 2015 Elsevier Ltd. All rights reserved.

Association of funding and conclusions in randomized drug trials: a reflection of treatment effect or adverse events?

PubMed

Als-Nielsen, Bodil; Chen, Wendong; Gluud, Christian; Kjaergard, Lise L

2003-08-20

Previous studies indicate that industry-sponsored trials tend to draw proindustry conclusions. To explore whether the association between funding and conclusions in randomized drug trials reflects treatment effects or adverse events. Observational study of 370 randomized drug trials included in meta-analyses from Cochrane reviews selected from the Cochrane Library, May 2001. From a random sample of 167 Cochrane reviews, 25 contained eligible meta-analyses (assessed a binary outcome; pooled at least 5 full-paper trials of which at least 1 reported adequate and 1 reported inadequate allocation concealment). The primary binary outcome from each meta-analysis was considered the primary outcome for all trials included in each meta-analysis. The association between funding and conclusions was analyzed by logistic regression with adjustment for treatment effect, adverse events, and additional confounding factors (methodological quality, control intervention, sample size, publication year, and place of publication). Conclusions in trials, classified into whether the experimental drug was recommended as the treatment of choice or not. The experimental drug was recommended as treatment of choice in 16% of trials funded by nonprofit organizations, 30% of trials not reporting funding, 35% of trials funded by both nonprofit and for-profit organizations, and 51% of trials funded by for-profit organizations (P<.001; chi2 test). Logistic regression analyses indicated that funding, treatment effect, and double blinding were the only significant predictors of conclusions. Adjusted analyses showed that trials funded by for-profit organizations were significantly more likely to recommend the experimental drug as treatment of choice (odds ratio, 5.3; 95% confidence interval, 2.0-14.4) compared with trials funded by nonprofit organizations. This association did not appear to reflect treatment effect or adverse events. Conclusions in trials funded by for-profit organizations may be more positive due to biased interpretation of trial results. Readers should carefully evaluate whether conclusions in randomized trials are supported by data.

Optimizing adaptive design for Phase 2 dose-finding trials incorporating long-term success and financial considerations: A case study for neuropathic pain.

PubMed

Gao, Jingjing; Nangia, Narinder; Jia, Jia; Bolognese, James; Bhattacharyya, Jaydeep; Patel, Nitin

2017-06-01

In this paper, we propose an adaptive randomization design for Phase 2 dose-finding trials to optimize Net Present Value (NPV) for an experimental drug. We replace the traditional fixed sample size design (Patel, et al., 2012) by this new design to see if NPV from the original paper can be improved. Comparison of the proposed design to the previous design is made via simulations using a hypothetical example based on a Diabetic Neuropathic Pain Study. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of bias-corrected covariance estimators for MMRM analysis in longitudinal data with dropouts.

PubMed

Gosho, Masahiko; Hirakawa, Akihiro; Noma, Hisashi; Maruo, Kazushi; Sato, Yasunori

2017-10-01

In longitudinal clinical trials, some subjects will drop out before completing the trial, so their measurements towards the end of the trial are not obtained. Mixed-effects models for repeated measures (MMRM) analysis with "unstructured" (UN) covariance structure are increasingly common as a primary analysis for group comparisons in these trials. Furthermore, model-based covariance estimators have been routinely used for testing the group difference and estimating confidence intervals of the difference in the MMRM analysis using the UN covariance. However, using the MMRM analysis with the UN covariance could lead to convergence problems for numerical optimization, especially in trials with a small-sample size. Although the so-called sandwich covariance estimator is robust to misspecification of the covariance structure, its performance deteriorates in settings with small-sample size. We investigated the performance of the sandwich covariance estimator and covariance estimators adjusted for small-sample bias proposed by Kauermann and Carroll ( J Am Stat Assoc 2001; 96: 1387-1396) and Mancl and DeRouen ( Biometrics 2001; 57: 126-134) fitting simpler covariance structures through a simulation study. In terms of the type 1 error rate and coverage probability of confidence intervals, Mancl and DeRouen's covariance estimator with compound symmetry, first-order autoregressive (AR(1)), heterogeneous AR(1), and antedependence structures performed better than the original sandwich estimator and Kauermann and Carroll's estimator with these structures in the scenarios where the variance increased across visits. The performance based on Mancl and DeRouen's estimator with these structures was nearly equivalent to that based on the Kenward-Roger method for adjusting the standard errors and degrees of freedom with the UN structure. The model-based covariance estimator with the UN structure under unadjustment of the degrees of freedom, which is frequently used in applications, resulted in substantial inflation of the type 1 error rate. We recommend the use of Mancl and DeRouen's estimator in MMRM analysis if the number of subjects completing is ( n + 5) or less, where n is the number of planned visits. Otherwise, the use of Kenward and Roger's method with UN structure should be the best way.

Clinical trial designs for testing biomarker-based personalized therapies

PubMed Central

Lai, Tze Leung; Lavori, Philip W; Shih, Mei-Chiung I; Sikic, Branimir I

2014-01-01

Background Advances in molecular therapeutics in the past decade have opened up new possibilities for treating cancer patients with personalized therapies, using biomarkers to determine which treatments are most likely to benefit them, but there are difficulties and unresolved issues in the development and validation of biomarker-based personalized therapies. We develop a new clinical trial design to address some of these issues. The goal is to capture the strengths of the frequentist and Bayesian approaches to address this problem in the recent literature and to circumvent their limitations. Methods We use generalized likelihood ratio tests of the intersection null and enriched strategy null hypotheses to derive a novel clinical trial design for the problem of advancing promising biomarker-guided strategies toward eventual validation. We also investigate the usefulness of adaptive randomization (AR) and futility stopping proposed in the recent literature. Results Simulation studies demonstrate the advantages of testing both the narrowly focused enriched strategy null hypothesis related to validating a proposed strategy and the intersection null hypothesis that can accommodate to a potentially successful strategy. AR and early termination of ineffective treatments offer increased probability of receiving the preferred treatment and better response rates for patients in the trial, at the expense of more complicated inference under small-to-moderate total sample sizes and some reduction in power. Limitations The binary response used in the development phase may not be a reliable indicator of treatment benefit on long-term clinical outcomes. In the proposed design, the biomarker-guided strategy (BGS) is not compared to ‘standard of care’, such as physician’s choice that may be informed by patient characteristics. Therefore, a positive result does not imply superiority of the BGS to ‘standard of care’. The proposed design and tests are valid asymptotically. Simulations are used to examine small-to-moderate sample properties. Conclusion Innovative clinical trial designs are needed to address the difficulties and issues in the development and validation of biomarker-based personalized therapies. The article shows the advantages of using likelihood inference and interim analysis to meet the challenges in the sample size needed and in the constantly evolving biomarker landscape and genomic and proteomic technologies. PMID:22397801

INVESTIGATE-I (INVasive Evaluation before Surgical Treatment of Incontinence Gives Added Therapeutic Effect?): study protocol for a mixed methods study to assess the feasibility of a future randomised controlled trial of the clinical utility of invasive urodynamic testing

PubMed Central

2011-01-01

Background Urinary incontinence is an important health problem to the individual sufferer and to health services. Stress and stress predominant mixed urinary incontinence are increasingly managed by surgery due to advances in surgical techniques. Despite the lack of evidence for its clinical utility, most clinicians undertake invasive urodynamic testing (IUT) to confirm a functional diagnosis of urodynamic stress incontinence before offering surgery for this condition. IUT is expensive, embarrassing and uncomfortable for women and carries a small risk. Recent systematic reviews have confirmed the lack of high quality evidence of effectiveness. The aim of this pilot study is to test the feasibility of a future definitive randomised control trial that would address whether IUT alters treatment decisions and treatment outcome in these women and would test its clinical and cost effectiveness. Methods/design This is a mixed methods pragmatic multicentre feasibility pilot study with four components:- (a) A multicentre, external pilot randomised trial comparing basic clinical assessment with non-invasive tests and IUT. The outcome measures are rates of recruitment, randomisation and data completion. Data will be used to estimate sample size necessary for the definitive trial. (b) Qualitative interviews of a purposively sampled sub-set of women eligible for the pilot trial will explore willingness to participate, be randomised and their overall trial experience. (c) A national survey of clinicians to determine their views of IUT in this context, the main outcome being their willingness to randomise patients into the definitive trial. (d) Qualitative interviews of a purposively sampled group of these clinicians will explore whether and how they use IUT to inform their decisions. Discussion The pilot trial will provide evidence of feasibility and acceptability and therefore inform the decision whether to proceed to the definitive trial. Results will inform the design and conduct of the definitive trial and ensure its effectiveness in achieving its research aim. Trial registration number Current Controlled Trials ISRCTN71327395 assigned 7th June 2010. PMID:21733166

Early prenatal food supplementation ameliorates the negative association of maternal stress with birth size in a randomised trial.

PubMed

Frith, Amy L; Naved, Ruchira T; Persson, Lars Ake; Frongillo, Edward A

2015-10-01

Low birthweight increases the risk of infant mortality, morbidity and poor development. Maternal nutrition and stress influence birth size, but their combined effect is not known. We hypothesised that an early-invitation time to start a prenatal food supplementation programme could reduce the negative influence of prenatal maternal stress on birth size, and that effect would differ by infant sex. A cohort of 1041 pregnant women, who had delivered an infant, June 2003-March 2004, was sampled from among 3267 in the randomised controlled trial, Maternal Infant Nutritional Interventions Matlab, conducted in Matlab, Bangladesh. At 8 weeks gestation, women were randomly assigned an invitation to start food supplements (2.5 MJ d(-1) ; 6 days a week) either early (∼9 weeks gestation; early-invitation group) or at usual start time for the governmental programme (∼20 weeks gestation; usual-invitation group). Morning concentration of cortisol was measured from one saliva sample/woman at 28-32 weeks gestation to assess stress. Birth-size measurements for 90% of infants were collected within 4 days of birth. In a general linear model, there was an interaction between invitation time to start the food supplementation programme and cortisol with birthweight, length and head circumference of male infants, but not female infants. Among the usual-invitation group only, male infants whose mothers had higher prenatal cortisol weighed less than those whose mothers had lower prenatal cortisol. Prenatal food supplementation programmes that begin first trimester may support greater birth size of male infants despite high maternal stress where low birthweight is a public health concern. © 2013 John Wiley & Sons Ltd.

Multicenter Clinical Trials Using 18F-FDG PET to Measure Early Response to Oncologic Therapy: Effects of Injection-to-Acquisition Time Variability on Required Sample Size.

PubMed

Kurland, Brenda F; Muzi, Mark; Peterson, Lanell M; Doot, Robert K; Wangerin, Kristen A; Mankoff, David A; Linden, Hannah M; Kinahan, Paul E

2016-02-01

Uptake time (interval between tracer injection and image acquisition) affects the SUV measured for tumors in (18)F-FDG PET images. With dissimilar uptake times, changes in tumor SUVs will be under- or overestimated. This study examined the influence of uptake time on tumor response assessment using a virtual clinical trials approach. Tumor kinetic parameters were estimated from dynamic (18)F-FDG PET scans of breast cancer patients and used to simulate time-activity curves for 45-120 min after injection. Five-minute uptake time frames followed 4 scenarios: the first was a standardized static uptake time (the SUV from 60 to 65 min was selected for all scans), the second was uptake times sampled from an academic PET facility with strict adherence to standardization protocols, the third was a distribution similar to scenario 2 but with greater deviation from standards, and the fourth was a mixture of hurried scans (45- to 65-min start of image acquisition) and frequent delays (58- to 115-min uptake time). The proportion of out-of-range scans (<50 or >70 min, or >15-min difference between paired scans) was 0%, 20%, 44%, and 64% for scenarios 1, 2, 3, and 4, respectively. A published SUV correction based on local linearity of uptake-time dependence was applied in a separate analysis. Influence of uptake-time variation was assessed as sensitivity for detecting response (probability of observing a change of ≥30% decrease in (18)F-FDG PET SUV given a true decrease of 40%) and specificity (probability of observing an absolute change of <30% given no true change). Sensitivity was 96% for scenario 1, and ranged from 73% for scenario 4 (95% confidence interval, 70%-76%) to 92% (90%-93%) for scenario 2. Specificity for all scenarios was at least 91%. Single-arm phase II trials required an 8%-115% greater sample size for scenarios 2-4 than for scenario 1. If uptake time is known, SUV correction methods may raise sensitivity to 87%-95% and reduce the sample size increase to less than 27%. Uptake-time deviations from standardized protocols occur frequently, potentially decreasing the performance of (18)F-FDG PET response biomarkers. Correcting SUV for uptake time improves sensitivity, but algorithm refinement is needed. Stricter uptake-time control and effective correction algorithms could improve power and decrease costs for clinical trials using (18)F-FDG PET endpoints. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Attention has memory: priming for the size of the attentional focus.

PubMed

Fuggetta, Giorgio; Lanfranchi, Silvia; Campana, Gianluca

2009-01-01

Repeating the same target's features or spatial position, as well as repeating the same context (e.g. distractor sets) in visual search leads to a decrease of reaction times. This modulation can occur on a trial by trial basis (the previous trial primes the following one), but can also occur across multiple trials (i.e. performance in the current trial can benefit from features, position or context seen several trials earlier), and includes inhibition of different features, position or contexts besides facilitation of the same ones. Here we asked whether a similar implicit memory mechanism exists for the size of the attentional focus. By manipulating the size of the attentional focus with the repetition of search arrays with the same vs. different size, we found both facilitation for the same array size and inhibition for a different array size, as well as a progressive improvement in performance with increasing the number of repetition of search arrays with the same size. These results show that implicit memory for the size of the attentional focus can guide visual search even in the absence of feature or position priming, or distractor's contextual effects.

Comparison of rheumatoid arthritis clinical trial outcome measures: a simulation study.

PubMed

Anderson, Jennifer J; Bolognese, James A; Felson, David T

2003-11-01

Isolated studies have suggested that continuous measures of response may be better than predefined, dichotomous definitions (e.g., the American College of Rheumatology 20% improvement criteria [ACR20]) for discriminating between rheumatoid arthritis (RA) treatments. Our goal was to determine the statistical power of predefined dichotomous outcome measures (termed "a priori"), compared with that of continuous measures derived from trial data in which there was no predefined response threshold (termed "data driven"), and to evaluate the sensitivity to change of these measures in the context of different treatments and early versus later-stage disease. In order to generalize beyond results from a single trial, we performed simulation studies. We obtained summary data from trials comparing disease-modifying antirheumatic drugs (DMARDs) and from comparative coxib-placebo trials to test the power of 2 a priori outcomes, the ACR20 and improvement of the Disease Activity Score (DDAS), as well as 2 data-driven outcomes. We studied patients with early RA and those with later-stage RA (duration of <4 years and 4-9 years, respectively). We performed simulation studies, using the interrelationship of ACR core set measures in the trials to generate multiple trial data sets consistent with the original data. The data-driven outcomes had greater power than did the a priori measures. The DMARD comparison was more powerful in early disease than in later-stage disease (the sample sizes needed to achieve 80% power for the most powerful test were 64 for early disease versus 100 for later disease), but the coxib-versus-placebo comparison was less powerful in early disease than in later disease (the sample sizes needed to achieve 80% power were 200 and 100, respectively). When the effects of treatment on core set items were small and/or inconsistent, power was reduced, particularly for a less broadly based outcome (e.g., DDAS) compared with the ACR20. The simulation studies demonstrate that data-driven outcome definitions can provide better sensitivity to change than does the ACR20 or DDAS. Using such methods would improve power, but at the expense of trial standardization. The studies also show how patient population and treatment characteristics affect the power of specific outcome measures in RA clinical trials, and provide quantification of those effects.

Clinical trials for authorized biosimilars in the European Union: a systematic review

PubMed Central

Mielke, Johanna; Koenig, Franz; Jones, Byron

2016-01-01

Aim In 2006, Omnitrope (by Sandoz) was the first approved biosimilar in Europe. To date, 21 biosimilars for seven different biologics are on the market. The present study compared the clinical trials undertaken to obtain market authorization. Methods We summarized the findings of a comprehensive review of all clinical trials up to market authorization of approved biosimilars, using the European public assessment reports (EPARs) published by the European Medicines Agency (EMA). The features compared were, among others, the number of patients enrolled, the number of trials, the types of trial design, choice of endpoints and equivalence margins for pharmacokinetic (PK)/pharmacodynamic (PD) and phase III trials. Results The variability between the clinical development strategies is high. Some differences are explainable by the characteristics of the product; if, for example, the PD marker can be assumed to predict the clinical outcome, no efficacy trials might be necessary. However, even for products with the same reference product, the sample size, endpoints and statistical models are not always the same. Conclusions There seems to be flexibility for sponsors regarding the decision as to how best to prove biosimilarity. PMID:27580073

Compliance with the CONSORT checklist in obstetric anaesthesia randomised controlled trials.

PubMed

Halpern, S H; Darani, R; Douglas, M J; Wight, W; Yee, J

2004-10-01

The Consolidated Standards for Reporting of Trials (CONSORT) checklist is an evidence-based approach to help improve the quality of reporting randomised controlled trials. The purpose of this study was to determine how closely randomised controlled trials in obstetric anaesthesia adhere to the CONSORT checklist. We retrieved all randomised controlled trials pertaining to the practice of obstetric anaesthesia and summarised in Obstetric Anesthesia Digest between March 2001 and December 2002 and compared the quality of reporting to the CONSORT checklist. The median number of correctly described CONSORT items was 65% (range 36% to 100%). Information pertaining to randomisation, blinding of the assessors, sample size calculation, reliability of measurements and reporting of the analysis were often omitted. It is difficult to determine the value and quality of many obstetric anaesthesia clinical trials because journal editors do not insist that this important information is made available to readers. Both clinicians and clinical researchers would benefit from uniform reporting of randomised trials in a manner that allows rapid data retrieval and easy assessment for relevance and quality.

A critical appraisal of the reporting quality of published randomized controlled trials in the fall injuries.

PubMed

Asghari Jafarabadi, Mohammad; Sadeghi-Bazrgani, Homayoun; Dianat, Iman

2018-06-01

To evaluate the quality of reporting in published randomized controlled trials (RTCs) in the field of fall injuries. The 188 RTCs published between 2001 and 2011, indexed in EMBASE and Medline databases were extracted through searching by appropriate keywords and EMTree classification terms. The evaluation trustworthiness was assured through parallel evaluations of two experts in epidemiology and biostatistics. About 40%-75% of papers had problems in reporting random allocation method, allocation concealment, random allocation implementation, blinding and similarity among groups, intention to treat and balancing benefits and harms. Moreover, at least 10% of papers inappropriately/not reported the design, protocol violations, sample size justification, subgroup/adjusted analyses, presenting flow diagram, drop outs, recruitment time, baseline data, suitable effect size on outcome, ancillary analyses, limitations and generalizability. Considering the shortcomings found and due to the importance of the RCTs for fall injury prevention programmes, their reporting quality should be improved.

White spot syndrome virus isolates of tiger shrimp Penaeus monodon (Fabricious) in India are similar to exotic isolates as revealed by polymerase chain reaction and electron microscopy.

PubMed

Mishra, S S; Shekhar, M S

2005-07-01

Microbiological analysis of samples collected from cases of white spot disease outbreaks in cultured shrimp in different farms located in three regions along East Coast of India viz. Chidambram (Tamil Nadu), Nellore (Andhra Pradesh) and Balasore (Orissa), revealed presence of Vibrio alginolyticus, Vibrio parahaemolyticus, and Aeromonas spp. but experimental infection trials in Penaeus monodon with these isolates did not induce any acute mortality or formation of white spots on carapace. Infection trials using filtered tissue extracts by oral and injection method induced mortality in healthy P. monodon with all samples and 100% mortality was noted by the end of 7 day post-inoculation. Histopathological analysis demonstrated degenerated cells characterized by hypertrophied nuclei in gills, hepatopancreas and lymphoid organ with presence of intranuclear basophilic or eosino-basophilic bodies in tubular cells and intercellular spaces. Analysis of samples using 3 different primer sets as used by other for detection of white spot syndrome virus (WSSV) generated 643, 1447 and 520bp amplified DNA products in all samples except in one instance. Variable size virions with mean size in the range of 110 x 320 +/- 20 nm were observed under electron microscope. It could be concluded that the viral isolates in India involved with white spot syndrome in cultured shrimp are similar to RV-PJ and SEMBV in Japan, WSBV in Taiwan and WSSV in Malaysia, Indonesia, Thailand, China and Japan.

An evaluation of inferential procedures for adaptive clinical trial designs with pre-specified rules for modifying the sample size.

PubMed

Levin, Gregory P; Emerson, Sarah C; Emerson, Scott S

2014-09-01

Many papers have introduced adaptive clinical trial methods that allow modifications to the sample size based on interim estimates of treatment effect. There has been extensive commentary on type I error control and efficiency considerations, but little research on estimation after an adaptive hypothesis test. We evaluate the reliability and precision of different inferential procedures in the presence of an adaptive design with pre-specified rules for modifying the sampling plan. We extend group sequential orderings of the outcome space based on the stage at stopping, likelihood ratio statistic, and sample mean to the adaptive setting in order to compute median-unbiased point estimates, exact confidence intervals, and P-values uniformly distributed under the null hypothesis. The likelihood ratio ordering is found to average shorter confidence intervals and produce higher probabilities of P-values below important thresholds than alternative approaches. The bias adjusted mean demonstrates the lowest mean squared error among candidate point estimates. A conditional error-based approach in the literature has the benefit of being the only method that accommodates unplanned adaptations. We compare the performance of this and other methods in order to quantify the cost of failing to plan ahead in settings where adaptations could realistically be pre-specified at the design stage. We find the cost to be meaningful for all designs and treatment effects considered, and to be substantial for designs frequently proposed in the literature. © 2014, The International Biometric Society.

Online alcohol interventions: a systematic review.

PubMed

White, Angela; Kavanagh, David; Stallman, Helen; Klein, Britt; Kay-Lambkin, Frances; Proudfoot, Judy; Drennan, Judy; Connor, Jason; Baker, Amanda; Hines, Emily; Young, Ross

2010-12-19

There has been a significant increase in the availability of online programs for alcohol problems. A systematic review of the research evidence underpinning these programs is timely. Our objective was to review the efficacy of online interventions for alcohol misuse. Systematic searches of Medline, PsycINFO, Web of Science, and Scopus were conducted for English abstracts (excluding dissertations) published from 1998 onward. Search terms were: (1) Internet, Web*; (2) online, computer*; (3) alcohol*; and (4) E\\effect*, trial*, random* (where * denotes a wildcard). Forward and backward searches from identified papers were also conducted. Articles were included if (1) the primary intervention was delivered and accessed via the Internet, (2) the intervention focused on moderating or stopping alcohol consumption, and (3) the study was a randomized controlled trial of an alcohol-related screen, assessment, or intervention. The literature search initially yielded 31 randomized controlled trials (RCTs), 17 of which met inclusion criteria. Of these 17 studies, 12 (70.6%) were conducted with university students, and 11 (64.7%) specifically focused on at-risk, heavy, or binge drinkers. Sample sizes ranged from 40 to 3216 (median 261), with 12 (70.6%) studies predominantly involving brief personalized feedback interventions. Using published data, effect sizes could be extracted from 8 of the 17 studies. In relation to alcohol units per week or month and based on 5 RCTs where a measure of alcohol units per week or month could be extracted, differential effect sizes to posttreatment ranged from 0.02 to 0.81 (mean 0.42, median 0.54). Pre-post effect sizes for brief personalized feedback interventions ranged from 0.02 to 0.81, and in 2 multi-session modularized interventions, a pre-post effect size of 0.56 was obtained in both. Pre-post differential effect sizes for peak blood alcohol concentrations (BAC) ranged from 0.22 to 0.88, with a mean effect size of 0.66. The available evidence suggests that users can benefit from online alcohol interventions and that this approach could be particularly useful for groups less likely to access traditional alcohol-related services, such as women, young people, and at-risk users. However, caution should be exercised given the limited number of studies allowing extraction of effect sizes, the heterogeneity of outcome measures and follow-up periods, and the large proportion of student-based studies. More extensive RCTs in community samples are required to better understand the efficacy of specific online alcohol approaches, program dosage, the additive effect of telephone or face-to-face interventions, and effective strategies for their dissemination and marketing.

Online Alcohol Interventions: A Systematic Review

PubMed Central

Kavanagh, David; Stallman, Helen; Klein, Britt; Kay-Lambkin, Frances; Proudfoot, Judy; Drennan, Judy; Connor, Jason; Baker, Amanda; Hines, Emily; Young, Ross

2010-01-01

Background There has been a significant increase in the availability of online programs for alcohol problems. A systematic review of the research evidence underpinning these programs is timely. Objectives Our objective was to review the efficacy of online interventions for alcohol misuse. Systematic searches of Medline, PsycINFO, Web of Science, and Scopus were conducted for English abstracts (excluding dissertations) published from 1998 onward. Search terms were: (1) Internet, Web*; (2) online, computer*; (3) alcohol*; and (4) E\\effect*, trial*, random* (where * denotes a wildcard). Forward and backward searches from identified papers were also conducted. Articles were included if (1) the primary intervention was delivered and accessed via the Internet, (2) the intervention focused on moderating or stopping alcohol consumption, and (3) the study was a randomized controlled trial of an alcohol-related screen, assessment, or intervention. Results The literature search initially yielded 31 randomized controlled trials (RCTs), 17 of which met inclusion criteria. Of these 17 studies, 12 (70.6%) were conducted with university students, and 11 (64.7%) specifically focused on at-risk, heavy, or binge drinkers. Sample sizes ranged from 40 to 3216 (median 261), with 12 (70.6%) studies predominantly involving brief personalized feedback interventions. Using published data, effect sizes could be extracted from 8 of the 17 studies. In relation to alcohol units per week or month and based on 5 RCTs where a measure of alcohol units per week or month could be extracted, differential effect sizes to posttreatment ranged from 0.02 to 0.81 (mean 0.42, median 0.54). Pre-post effect sizes for brief personalized feedback interventions ranged from 0.02 to 0.81, and in 2 multi-session modularized interventions, a pre-post effect size of 0.56 was obtained in both. Pre-post differential effect sizes for peak blood alcohol concentrations (BAC) ranged from 0.22 to 0.88, with a mean effect size of 0.66. Conclusions The available evidence suggests that users can benefit from online alcohol interventions and that this approach could be particularly useful for groups less likely to access traditional alcohol-related services, such as women, young people, and at-risk users. However, caution should be exercised given the limited number of studies allowing extraction of effect sizes, the heterogeneity of outcome measures and follow-up periods, and the large proportion of student-based studies. More extensive RCTs in community samples are required to better understand the efficacy of specific online alcohol approaches, program dosage, the additive effect of telephone or face-to-face interventions, and effective strategies for their dissemination and marketing. PMID:21169175

Bayesian Phase II optimization for time-to-event data based on historical information.

PubMed

Bertsche, Anja; Fleischer, Frank; Beyersmann, Jan; Nehmiz, Gerhard

2017-01-01

After exploratory drug development, companies face the decision whether to initiate confirmatory trials based on limited efficacy information. This proof-of-concept decision is typically performed after a Phase II trial studying a novel treatment versus either placebo or an active comparator. The article aims to optimize the design of such a proof-of-concept trial with respect to decision making. We incorporate historical information and develop pre-specified decision criteria accounting for the uncertainty of the observed treatment effect. We optimize these criteria based on sensitivity and specificity, given the historical information. Specifically, time-to-event data are considered in a randomized 2-arm trial with additional prior information on the control treatment. The proof-of-concept criterion uses treatment effect size, rather than significance. Criteria are defined on the posterior distribution of the hazard ratio given the Phase II data and the historical control information. Event times are exponentially modeled within groups, allowing for group-specific conjugate prior-to-posterior calculation. While a non-informative prior is placed on the investigational treatment, the control prior is constructed via the meta-analytic-predictive approach. The design parameters including sample size and allocation ratio are then optimized, maximizing the probability of taking the right decision. The approach is illustrated with an example in lung cancer.

Intraclass Correlation Coefficients for Obesity Indicators and Energy Balance-Related Behaviors among New York City Public Elementary Schools

ERIC Educational Resources Information Center

Gray, Heewon Lee; Burgermaster, Marissa; Tipton, Elizabeth; Contento, Isobel R.; Koch, Pamela A.; Di Noia, Jennifer

2016-01-01

Objective: Sample size and statistical power calculation should consider clustering effects when schools are the unit of randomization in intervention studies. The objective of the current study was to investigate how student outcomes are clustered within schools in an obesity prevention trial. Method: Baseline data from the Food, Health &…

Prospective Evaluation of Intraprostatic Inflammation and Focal Atrophy as a Predictor of Risk of High-Grade Prostate Cancer and Recurrence after Prostatectomy

DTIC Science & Technology

2014-07-01

the two trials. The expected sample size for this work was 100 cases and 200 controls. Tissue was sufficient for 291 of the men (Task 2 completed in...not collected in SELECT), physical activity (PCPT [not collected in SELECT), cigarette smoking status at randomization (SELECT), use of aspirin

Systematic review of the cost-effectiveness of sample size maintenance programs in studies involving postal questionnaires reveals insufficient economic information.

PubMed

David, Michael C; Bensink, Mark; Higashi, Hideki; Boyd, Roslyn; Williams, Lesley; Ware, Robert S

2012-10-01

To identify and assess the existing cost-effectiveness evidence for sample size maintenance programs. Articles were identified by searching Cochrane Central Register of Controlled Trials Embase, CINAHL, PubMed, and Web of Science from 1966 to July 2011. Randomized controlled trials in which investigators evaluated program cost-effectiveness in postal questionnaires were eligible for inclusion. Fourteen studies from 13 articles, with 11,165 participants met the inclusion criteria. Thirty-one distinct programs were identified; each incorporated at least one strategy (reminders, incentives, modified questionnaires, or types of postage) aimed at minimizing attrition. Reminders, in the form of replacement questionnaires and cards, were the most commonly used strategies, with 15 and 11 studies reporting their usage, respectively. All strategies improved response, with financial incentives being the most costly. Heterogeneity between studies was too great to allow for meta-analysis of the results. The implementation of strategies such as no-obligation incentives, modified questionnaires, and personalized reply paid postage improved program cost-effectiveness. Analyses of attrition minimization programs need to consider both cost and effect in their evaluation. Copyright © 2012 Elsevier Inc. All rights reserved.

Interactive Video Gaming compared to Health Education in Older Adults with MCI: A Feasibility Study

PubMed Central

Hughes, Tiffany F.; Flatt, Jason D.; Fu, Bo; Butters, Meryl A.; Chang, Chung-Chou H.; Ganguli, Mary

2014-01-01

Objective We evaluated the feasibility of a trial of Wii interactive video gaming, and its potential efficacy at improving cognitive functioning compared to health education, in a community sample of older adults with neuropsychologically defined mild cognitive impairment (MCI). Methods Twenty older adults were equally randomized to either group-based interactive video gaming or health education for 90 minutes each week for 24 weeks. Although the primary outcomes were related to study feasibility, we also explored the effect of the intervention on neuropsychological performance and other secondary outcomes. Results All 20 participants completed the intervention, and 18 attended at least 80% of the sessions. The majority (80%) of participants were “very much” satisfied with the intervention. Bowling was enjoyed by the most participants, and was also the rated highest among the games for mental, social and physical stimulation. We observed medium effect sizes for cognitive and physical functioning in favor of the interactive video gaming condition, but these effects were not statistically significant in this small sample. Conclusion Interactive video gaming is feasible for older adults with MCI and medium effects sizes in favor of the Wii group warrant a larger efficacy trial. PMID:24452845

Constructing common cohorts from trials with overlapping eligibility criteria: implications for comparing effect sizes between trials.

PubMed

Mount, David L; Feeney, Patricia; Fabricatore, Anthony N; Coday, Mace; Bahnson, Judy; Byington, Robert; Phelan, Suzanne; Wilmoth, Sharon; Knowler, William C; Hramiak, Irene; Osei, Kwame; Sweeney, Mary Ellen; Espeland, Mark A

2009-10-01

Comparing findings from separate trials is necessary to choose among treatment options, however differences among study cohorts may impede these comparisons. As a case study, to examine the overlap of study cohorts in two large randomized controlled clinical trials that assess interventions to reduce risk of major cardiovascular disease events in adults with type 2 diabetes in order to explore the feasibility of cross-trial comparisons The Action for Health in Diabetes (Look AHEAD) and The Action to Control Cardiovascular Risk in Diabetes (ACCORD) trials enrolled 5145 and 10,251 adults with type 2 diabetes, respectively. Look AHEAD assesses the efficacy of an intensive lifestyle intervention designed to produce weight loss; ACCORD tests pharmacological therapies for control of glycemia, hyperlipidemia, and hypertension. Incidence of major cardiovascular disease events is the primary outcome for both trials. A sample was constructed to include participants from each trial who appeared to meet eligibility criteria and be appropriate candidates for the other trial's interventions. Demographic characteristics, health status, and outcomes of members and nonmembers of this constructed sample were compared. Nearly 80% of Look AHEAD participants were projected to be ineligible for ACCORD; ineligibility was primarily due to better glycemic control or no early history of cardiovascular disease. Approximately 30% of ACCORD participants were projected to be ineligible for Look AHEAD, often for reasons linked to poorer health. The characteristics of participants projected to be jointly eligible for both trials continued to reflect differences between trials according to factors likely linked to retention, adherence, and study outcomes. Accurate ascertainment of cross-trial eligibility was hampered by differences between protocols. Despite several similarities, the Look AHEAD and ACCORD cohorts represent distinct populations. Even within the subsets of participants who appear to be eligible and appropriate candidates for trials of both modes of intervention, differences remained. Direct comparisons of results from separate trials of lifestyle and pharmacologic interventions are compromised by marked differences in enrolled cohorts.

Beyond the Randomized Controlled Trial: A Review of Alternatives in mHealth Clinical Trial Methods

PubMed Central

Wiljer, David; Cafazzo, Joseph A

2016-01-01

Background Randomized controlled trials (RCTs) have long been considered the primary research study design capable of eliciting causal relationships between health interventions and consequent outcomes. However, with a prolonged duration from recruitment to publication, high-cost trial implementation, and a rigid trial protocol, RCTs are perceived as an impractical evaluation methodology for most mHealth apps. Objective Given the recent development of alternative evaluation methodologies and tools to automate mHealth research, we sought to determine the breadth of these methods and the extent that they were being used in clinical trials. Methods We conducted a review of the ClinicalTrials.gov registry to identify and examine current clinical trials involving mHealth apps and retrieved relevant trials registered between November 2014 and November 2015. Results Of the 137 trials identified, 71 were found to meet inclusion criteria. The majority used a randomized controlled trial design (80%, 57/71). Study designs included 36 two-group pretest-posttest control group comparisons (51%, 36/71), 16 posttest-only control group comparisons (23%, 16/71), 7 one-group pretest-posttest designs (10%, 7/71), 2 one-shot case study designs (3%, 2/71), and 2 static-group comparisons (3%, 2/71). A total of 17 trials included a qualitative component to their methodology (24%, 17/71). Complete trial data collection required 20 months on average to complete (mean 21, SD 12). For trials with a total duration of 2 years or more (31%, 22/71), the average time from recruitment to complete data collection (mean 35 months, SD 10) was 2 years longer than the average time required to collect primary data (mean 11, SD 8). Trials had a moderate sample size of 112 participants. Two trials were conducted online (3%, 2/71) and 7 trials collected data continuously (10%, 7/68). Onsite study implementation was heavily favored (97%, 69/71). Trials with four data collection points had a longer study duration than trials with two data collection points: F4,56=3.2, P=.021, η2=0.18. Single-blinded trials had a longer data collection period compared to open trials: F2,58=3.8, P=.028, η2=0.12. Academic sponsorship was the most common form of trial funding (73%, 52/71). Trials with academic sponsorship had a longer study duration compared to industry sponsorship: F2,61=3.7, P=.030, η2=0.11. Combined, data collection frequency, study masking, sample size, and study sponsorship accounted for 32.6% of the variance in study duration: F4,55=6.6, P<.01, adjusted r2=.33. Only 7 trials had been completed at the time this retrospective review was conducted (10%, 7/71). Conclusions mHealth evaluation methodology has not deviated from common methods, despite the need for more relevant and timely evaluations. There is a need for clinical evaluation to keep pace with the level of innovation of mHealth if it is to have meaningful impact in informing payers, providers, policy makers, and patients. PMID:27613084

Beyond the Randomized Controlled Trial: A Review of Alternatives in mHealth Clinical Trial Methods.

PubMed

Pham, Quynh; Wiljer, David; Cafazzo, Joseph A

2016-09-09

Randomized controlled trials (RCTs) have long been considered the primary research study design capable of eliciting causal relationships between health interventions and consequent outcomes. However, with a prolonged duration from recruitment to publication, high-cost trial implementation, and a rigid trial protocol, RCTs are perceived as an impractical evaluation methodology for most mHealth apps. Given the recent development of alternative evaluation methodologies and tools to automate mHealth research, we sought to determine the breadth of these methods and the extent that they were being used in clinical trials. We conducted a review of the ClinicalTrials.gov registry to identify and examine current clinical trials involving mHealth apps and retrieved relevant trials registered between November 2014 and November 2015. Of the 137 trials identified, 71 were found to meet inclusion criteria. The majority used a randomized controlled trial design (80%, 57/71). Study designs included 36 two-group pretest-posttest control group comparisons (51%, 36/71), 16 posttest-only control group comparisons (23%, 16/71), 7 one-group pretest-posttest designs (10%, 7/71), 2 one-shot case study designs (3%, 2/71), and 2 static-group comparisons (3%, 2/71). A total of 17 trials included a qualitative component to their methodology (24%, 17/71). Complete trial data collection required 20 months on average to complete (mean 21, SD 12). For trials with a total duration of 2 years or more (31%, 22/71), the average time from recruitment to complete data collection (mean 35 months, SD 10) was 2 years longer than the average time required to collect primary data (mean 11, SD 8). Trials had a moderate sample size of 112 participants. Two trials were conducted online (3%, 2/71) and 7 trials collected data continuously (10%, 7/68). Onsite study implementation was heavily favored (97%, 69/71). Trials with four data collection points had a longer study duration than trials with two data collection points: F4,56=3.2, P=.021, η(2)=0.18. Single-blinded trials had a longer data collection period compared to open trials: F2,58=3.8, P=.028, η(2)=0.12. Academic sponsorship was the most common form of trial funding (73%, 52/71). Trials with academic sponsorship had a longer study duration compared to industry sponsorship: F2,61=3.7, P=.030, η(2)=0.11. Combined, data collection frequency, study masking, sample size, and study sponsorship accounted for 32.6% of the variance in study duration: F4,55=6.6, P<.01, adjusted r(2)=.33. Only 7 trials had been completed at the time this retrospective review was conducted (10%, 7/71). mHealth evaluation methodology has not deviated from common methods, despite the need for more relevant and timely evaluations. There is a need for clinical evaluation to keep pace with the level of innovation of mHealth if it is to have meaningful impact in informing payers, providers, policy makers, and patients.

The effect of bronchodilators on forced vital capacity measurement in patients with idiopathic pulmonary fibrosis

PubMed Central

Assayag, Deborah; Vittinghoff, Eric; Ryerson, Christopher J.; Cocconcelli, Elisabetta; Tonelli, Roberto; Hu, Xiaowen; Elicker, Brett M.; Golden, Jeffrey A.; Jones, Kirk D.; King, Talmadge E.; Koth, Laura L.; Lee, Joyce S.; Ley, Brett; Shum, Anthony K.; Wolters, Paul J.; Ryu, Jay H.; Collard, Harold R.

2015-01-01

Background Forced vital capacity (FVC) is a key measure of disease severity in patients with idiopathic pulmonary fibrosis (IPF) and is an important clinical trial endpoint. We hypothesize that reversible airflow limitation co-exists in a subgroup of patients with IPF, and that bronchodilator use will improve the performance characteristics of FVC. Methods IPF patients with pre and post-bronchodilator spirometry testing performed were identified from two tertiary referral cohorts. The difference between pre and post-bronchodilator FVC (intra-test difference) was calculated. The test characteristics of pre and post-bronchodilator FVC change over time (inter-test difference) were assessed in patients with sequential spirometry, and were used to generate sample size estimates for hypothetical clinical trials using change in FVC as the primary endpoint. Results There were 551 patients, contributing 967 unique spirometry tests. The mean intra-test increase in FVC with bronchodilator use was 0.04 liters (2.71 vs. 2.75 liters, p <0.001). Reversible airflow limitation (increase in FEV1 or FVC of ≥12% and ≥200 milliliters) occurred in 9.1% of patients. The inter-test difference in change in FVC over time were equivalent for pre and post-bronchodilator (p = 0.65), leading to similar sample size estimates in a hypothetical clinical trial using change in FVC as the primary endpoint. Conclusion Approximately one in ten patients with IPF has physiological evidence of reversible airflow limitation, and bronchodilator use in these patients may improve the assessment of disease progression based on FVC change over time. Bronchodilator use does not appear to meaningfully impact the precision of FVC as an endpoint in clinical trials. PMID:26140806

Meaningful change and responsiveness in common physical performance measures in older adults.

PubMed

Perera, Subashan; Mody, Samir H; Woodman, Richard C; Studenski, Stephanie A

2006-05-01

To estimate the magnitude of small meaningful and substantial individual change in physical performance measures and evaluate their responsiveness. Secondary data analyses using distribution- and anchor-based methods to determine meaningful change. Secondary analysis of data from an observational study and clinical trials of community-dwelling older people and subacute stroke survivors. Older adults with mobility disabilities in a strength training trial (n=100), subacute stroke survivors in an intervention trial (n=100), and a prospective cohort of community-dwelling older people (n=492). Gait speed, Short Physical Performance Battery (SPPB), 6-minute-walk distance (6MWD), and self-reported mobility. Most small meaningful change estimates ranged from 0.04 to 0.06 m/s for gait speed, 0.27 to 0.55 points for SPPB, and 19 to 22 m for 6MWD. Most substantial change estimates ranged from 0.08 to 0.14 m/s for gait speed, 0.99 to 1.34 points for SPPB, and 47 to 49 m for 6MWD. Based on responsiveness indices, per-group sample sizes for clinical trials ranged from 13 to 42 for substantial change and 71 to 161 for small meaningful change. Best initial estimates of small meaningful change are near 0.05 m/s for gait speed, 0.5 points for SPPB, and 20 m for 6MWD and of substantial change are near 0.10 m/s for gait speed, 1.0 point for SPPB, and 50 m for 6MWD. For clinical use, substantial change in these measures and small change in gait speed and 6MWD, but not SPPB, are detectable. For research use, these measures yield feasible sample sizes for detecting meaningful change.

Recruitment and enrollment of African Americans into health promoting programs: the effects of health promoting programs on cardiovascular disease risk study.

PubMed

Okhomina, Victoria I; Seals, Samantha R; Marshall, Gailen D

2018-04-03

Randomized controlled trials (RCT) often employ multiple recruitment methods to attract participants, however, special care must be taken to be inclusive of under-represented populations. We examine how recruiting from an existing observational study affected the recruitment of African Americans into a RCT that included yoga-based interventions. In particular, we report the recruitment success of The Effects of Health Promoting Programs (HPP) on Cardiovascular Disease Risk (NCT02019953), the first yoga-based clinical trial to focus only on African Americans. To recruit participants, a multifaceted recruitment strategy was implemented exclusively in the Jackson Heart Study (JHS) cohort. The HPP recruited from the JHS cohort using direct mailings, signs and flyers placed around JHS study facilities, and through JHS annual follow-up interviews. Enrollment into HPP was open to all active JHS participants that were eligible to return for the third clinic exam (n = 4644). The target sample size was 375 JHS participants over a 24 month recruitment and enrollment period. From the active members of the JHS cohort, 503 were pre-screened for eligibility in HPP. More than 90% of those pre-screened were provisionally eligible for the study. The enrollment goal of 375 was completed after a 16-month enrollment period with over 25% (n = 97) of the required sample size enrolling during the second month of recruitment. The findings show that participants in observational studies can be successfully recruited into RCT. Observational studies provide researchers with a well-defined population that may be of interest when designing clinical trials. This is particularly useful in the recruitment of a high-risk, traditionally underrepresented populations for non-pharmacological clinical trials where traditional recruitment methods may prolong enrollment periods and extend study budgets.

Conducting non-commercial international clinical trials: the ICR-CTSU experience.

PubMed

Fox, Lisa; Toms, Christy; Kernaghan, Sarah; Snowdon, Claire; Bliss, Judith M

2017-09-26

Academic clinical trials play a fundamental role in the development of new treatments, the repurposing of existing treatments and in addressing areas of unmet clinical need. With cancer treatments increasingly targeted at molecular subtypes, and with priority placed on developing new treatments for rare tumour types, the need for international trial participation to access sufficient patient numbers for successful trial conduct is growing. However, lack of harmonisation of international legal, ethical and financial systems can make this challenging and the cost and effort of conducting trials internationally can be considered prohibitive, particularly where the sample size is comparatively small. The Institute of Cancer Research - Clinical Trials and Statistics Unit (ICR-CTSU) is a UK-based academic clinical trials unit that specialises in the design, conduct and analysis of clinical trials of cancer treatments with an expanding portfolio of trials in molecular subtypes of breast and urological cancers and in other rare cancer types. Implementing appropriate mechanisms to enable international participation has therefore been imperative. In this article, we explain how we have approached the challenges involved and describe examples of successful international trial conduct, achieved through robust collaborations with academic and industry partners. Conducting academic trials internationally is challenging but can and should be achieved through appropriate governance mechanisms and strong collaborations.

A modified Wald interval for the area under the ROC curve (AUC) in diagnostic case-control studies

PubMed Central

2014-01-01

Background The area under the receiver operating characteristic (ROC) curve, referred to as the AUC, is an appropriate measure for describing the overall accuracy of a diagnostic test or a biomarker in early phase trials without having to choose a threshold. There are many approaches for estimating the confidence interval for the AUC. However, all are relatively complicated to implement. Furthermore, many approaches perform poorly for large AUC values or small sample sizes. Methods The AUC is actually a probability. So we propose a modified Wald interval for a single proportion, which can be calculated on a pocket calculator. We performed a simulation study to compare this modified Wald interval (without and with continuity correction) with other intervals regarding coverage probability and statistical power. Results The main result is that the proposed modified Wald intervals maintain and exploit the type I error much better than the intervals of Agresti-Coull, Wilson, and Clopper-Pearson. The interval suggested by Bamber, the Mann-Whitney interval without transformation and also the interval of the binormal AUC are very liberal. For small sample sizes the Wald interval with continuity has a comparable coverage probability as the LT interval and higher power. For large sample sizes the results of the LT interval and of the Wald interval without continuity correction are comparable. Conclusions If individual patient data is not available, but only the estimated AUC and the total sample size, the modified Wald intervals can be recommended as confidence intervals for the AUC. For small sample sizes the continuity correction should be used. PMID:24552686

A modified Wald interval for the area under the ROC curve (AUC) in diagnostic case-control studies.

PubMed

Kottas, Martina; Kuss, Oliver; Zapf, Antonia

2014-02-19

The area under the receiver operating characteristic (ROC) curve, referred to as the AUC, is an appropriate measure for describing the overall accuracy of a diagnostic test or a biomarker in early phase trials without having to choose a threshold. There are many approaches for estimating the confidence interval for the AUC. However, all are relatively complicated to implement. Furthermore, many approaches perform poorly for large AUC values or small sample sizes. The AUC is actually a probability. So we propose a modified Wald interval for a single proportion, which can be calculated on a pocket calculator. We performed a simulation study to compare this modified Wald interval (without and with continuity correction) with other intervals regarding coverage probability and statistical power. The main result is that the proposed modified Wald intervals maintain and exploit the type I error much better than the intervals of Agresti-Coull, Wilson, and Clopper-Pearson. The interval suggested by Bamber, the Mann-Whitney interval without transformation and also the interval of the binormal AUC are very liberal. For small sample sizes the Wald interval with continuity has a comparable coverage probability as the LT interval and higher power. For large sample sizes the results of the LT interval and of the Wald interval without continuity correction are comparable. If individual patient data is not available, but only the estimated AUC and the total sample size, the modified Wald intervals can be recommended as confidence intervals for the AUC. For small sample sizes the continuity correction should be used.

Standardization of pathologic evaluation and reporting of postneoadjuvant specimens in clinical trials of breast cancer: recommendations from an international working group.

PubMed

Provenzano, Elena; Bossuyt, Veerle; Viale, Giuseppe; Cameron, David; Badve, Sunil; Denkert, Carsten; MacGrogan, Gaëtan; Penault-Llorca, Frédérique; Boughey, Judy; Curigliano, Giuseppe; Dixon, J Michael; Esserman, Laura; Fastner, Gerd; Kuehn, Thorsten; Peintinger, Florentia; von Minckwitz, Gunter; White, Julia; Yang, Wei; Symmans, W Fraser

2015-09-01

Neoadjuvant systemic therapy is being used increasingly in the treatment of early-stage breast cancer. Response, in the form of pathological complete response, is a validated and evaluable surrogate end point of survival after neoadjuvant therapy. Thus, pathological complete response has become a primary end point for clinical trials. However, there is a current lack of uniformity in the definition of pathological complete response. A review of standard operating procedures used by 28 major neoadjuvant breast cancer trials and/or 25 sites involved in such trials identified marked variability in specimen handling and histologic reporting. An international working group was convened to develop practical recommendations for the pathologic assessment of residual disease in neoadjuvant clinical trials of breast cancer and information expected from pathology reports. Systematic sampling of areas identified by informed mapping of the specimen and close correlation with radiological findings is preferable to overly exhaustive sampling, and permits taking tissue samples for translational research. Controversial areas are discussed, including measurement of lesion size, reporting of lymphovascular space invasion and the presence of isolated tumor cells in lymph nodes after neoadjuvant therapy, and retesting of markers after treatment. If there has been a pathological complete response, this must be clearly stated, and the presence/absence of residual ductal carcinoma in situ must be described. When there is residual invasive carcinoma, a comment must be made as to the presence/absence of chemotherapy effect in the breast and lymph nodes. The Residual Cancer Burden is the preferred method for quantifying residual disease in neoadjuvant clinical trials in breast cancer; other methods can be included per trial protocols and regional preference. Posttreatment tumor staging using the Tumor-Node-Metastasis system should be included. These recommendations for standardized pathological evaluation and reporting of neoadjuvant breast cancer specimens should improve prognostication for individual patients and allow comparison of treatment outcomes within and across clinical trials.

Power Calculations and Placebo Effect for Future Clinical Trials in Progressive Supranuclear Palsy

PubMed Central

Stamelou, Maria; Schöpe, Jakob; Wagenpfeil, Stefan; Ser, Teodoro Del; Bang, Jee; Lobach, Iryna Y.; Luong, Phi; Respondek, Gesine; Oertel, Wolfgang H.; Boxer, Adam L.; Höglinger, Günter U.

2016-01-01

Background Two recent randomized, placebo-controlled trials of putative disease-modifying agents (davunetide, tideglusib) in progressive supranuclear palsy (PSP) failed to show efficacy, but generated data relevant for future trials. Methods We provide sample size calculations based on data collected in 187 PSP patients assigned to placebo in these trials. A placebo effect was calculated. Results The total PSP-Rating Scale required the least number of patients per group (N = 51) to detect a 50% change in the 1-year progression and 39 when including patients with ≤ 5 years disease duration. The Schwab and England Activities of Daily Living required 70 patients per group and was highly correlated with the PSP-Rating Scale. A placebo effect was not detected in these scales. Conclusions We propose the 1-year PSP-Rating Scale score change as the single primary readout in clinical neuroprotective or disease-modifying trials. The Schwab and England Activities of Daily Living could be used as a secondary outcome. PMID:26948290

The utility of Bayesian predictive probabilities for interim monitoring of clinical trials

PubMed Central

Connor, Jason T.; Ayers, Gregory D; Alvarez, JoAnn

2014-01-01

Background Bayesian predictive probabilities can be used for interim monitoring of clinical trials to estimate the probability of observing a statistically significant treatment effect if the trial were to continue to its predefined maximum sample size. Purpose We explore settings in which Bayesian predictive probabilities are advantageous for interim monitoring compared to Bayesian posterior probabilities, p-values, conditional power, or group sequential methods. Results For interim analyses that address prediction hypotheses, such as futility monitoring and efficacy monitoring with lagged outcomes, only predictive probabilities properly account for the amount of data remaining to be observed in a clinical trial and have the flexibility to incorporate additional information via auxiliary variables. Limitations Computational burdens limit the feasibility of predictive probabilities in many clinical trial settings. The specification of prior distributions brings additional challenges for regulatory approval. Conclusions The use of Bayesian predictive probabilities enables the choice of logical interim stopping rules that closely align with the clinical decision making process. PMID:24872363

Myocardial Infarct Size by CMR in Clinical Cardioprotection Studies: Insights From Randomized Controlled Trials.

PubMed

Bulluck, Heerajnarain; Hammond-Haley, Matthew; Weinmann, Shane; Martinez-Macias, Roberto; Hausenloy, Derek J

2017-03-01

The aim of this study was to review randomized controlled trials (RCTs) using cardiac magnetic resonance (CMR) to assess myocardial infarct (MI) size in reperfused patients with ST-segment elevation myocardial infarction (STEMI). There is limited guidance on the use of CMR in clinical cardioprotection RCTs in patients with STEMI treated by primary percutaneous coronary intervention. All RCTs in which CMR was used to quantify MI size in patients with STEMI treated with primary percutaneous coronary intervention were identified and reviewed. Sixty-two RCTs (10,570 patients, January 2006 to November 2016) were included. One-third did not report CMR vendor or scanner strength, the contrast agent and dose used, and the MI size quantification technique. Gadopentetate dimeglumine was most commonly used, followed by gadoterate meglumine and gadobutrol at 0.20 mmol/kg each, with late gadolinium enhancement acquired at 10 min; in most RCTs, MI size was quantified manually, followed by the 5 standard deviation threshold; dropout rates were 9% for acute CMR only and 16% for paired acute and follow-up scans. Weighted mean acute and chronic MI sizes (≤12 h, initial TIMI [Thrombolysis in Myocardial Infarction] flow grade 0 to 3) from the control arms were 21 ± 14% and 15 ± 11% of the left ventricle, respectively, and could be used for future sample-size calculations. Pre-selecting patients most likely to benefit from the cardioprotective therapy (≤6 h, initial TIMI flow grade 0 or 1) reduced sample size by one-third. Other suggested recommendations for standardizing CMR in future RCTs included gadobutrol at 0.15 mmol/kg with late gadolinium enhancement at 15 min, manual or 6-SD threshold for MI quantification, performing acute CMR at 3 to 5 days and follow-up CMR at 6 months, and adequate reporting of the acquisition and analysis of CMR. There is significant heterogeneity in RCT design using CMR in patients with STEMI. The authors provide recommendations for standardizing the assessment of MI size using CMR in future clinical cardioprotection RCTs. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Assessing quality of reports on randomized clinical trials in nursing journals.

PubMed

Parent, Nicole; Hanley, James A

2009-01-01

Several surveys have presented the quality of reports on randomized clinical trials (RCTs) published in general and specialty medical journals. The aim of these surveys was to raise scientific consciousness on methodological aspects pertaining to internal and external validity. These reviews have suggested that the methodological quality could be improved. We conducted a survey of reports on RCTs published in nursing journals to assess their methodological quality. The features we considered included sample size, flow of participants, assessment of baseline comparability, randomization, blinding, and statistical analysis. We collected data from all reports of RCTs published between January 1994 and December 1997 in Applied Nursing Research, Heart & Lung and Nursing Research. We hand-searched the journals and included all 54 articles in which authors reported that individuals have been randomly allocated to distinct groups. We collected data using a condensed form of the Consolidated Standards of Reporting Trials (CONSORT) statement for structured reporting of RCTs (Begg et al., 1996). Sample size calculations were included in only 22% of the reports. Only 48% of the reports provided information about the type of randomization, and a mere 22% described blinding strategies. Comparisons of baseline characteristics using hypothesis tests were abusively produced in more than 76% of the reports. Excessive use and unstructured reports of significance testing were common (59%), and all reports failed to provide magnitude of treatment differences with confidence intervals. Better methodological quality in reports of RCTs will contribute to increase the standards of nursing research.

Evaluation of agile designs in first-in-human (FIH) trials--a simulation study.

PubMed

Perlstein, Itay; Bolognese, James A; Krishna, Rajesh; Wagner, John A

2009-12-01

The aim of the investigation was to evaluate alternatives to standard first-in-human (FIH) designs in order to optimize the information gained from such studies by employing novel agile trial designs. Agile designs combine adaptive and flexible elements to enable optimized use of prior information either before and/or during conduct of the study to seamlessly update the study design. A comparison of the traditional 6 + 2 (active + placebo) subjects per cohort design with alternative, reduced sample size, agile designs was performed by using discrete event simulation. Agile designs were evaluated for specific adverse event models and rates as well as dose-proportional, saturated, and steep-accumulation pharmacokinetic profiles. Alternative, reduced sample size (hereafter referred to as agile) designs are proposed for cases where prior knowledge about pharmacokinetics and/or adverse event relationships are available or appropriately assumed. Additionally, preferred alternatives are proposed for a general case when prior knowledge is limited or unavailable. Within the tested conditions and stated assumptions, some agile designs were found to be as efficient as traditional designs. Thus, simulations demonstrated that the agile design is a robust and feasible approach to FIH clinical trials, with no meaningful loss of relevant information, as it relates to PK and AE assumptions. In some circumstances, applying agile designs may decrease the duration and resources required for Phase I studies, increasing the efficiency of early clinical development. We highlight the value and importance of useful prior information when specifying key assumptions related to safety, tolerability, and PK.

Efficacy of a strategy for implementing a guideline for the control of cardiovascular risk in a primary healthcare setting: the SIRVA2 study a controlled, blinded community intervention trial randomised by clusters

PubMed Central

2011-01-01

This work describes the methodology used to assess a strategy for implementing clinical practice guidelines (CPG) for cardiovascular risk control in a health area of Madrid. Background The results on clinical practice of introducing CPGs have been little studied in Spain. The strategy used to implement a CPG is known to influence its final use. Strategies based on the involvement of opinion leaders and that are easily executed appear to be among the most successful. Aim The main aim of the present work was to compare the effectiveness of two strategies for implementing a CPG designed to reduce cardiovascular risk in the primary healthcare setting, measured in terms of improvements in the recording of calculated cardiovascular risk or specific risk factors in patients' medical records, the control of cardiovascular risk factors, and the incidence of cardiovascular events. Methods This study involved a controlled, blinded community intervention in which the 21 health centres of the Number 2 Health Area of Madrid were randomly assigned by clusters to be involved in either a proposed CPG implementation strategy to reduce cardiovascular risk, or the normal dissemination strategy. The study subjects were patients ≥ 45 years of age whose health cards showed them to belong to the studied health area. The main variable examined was the proportion of patients whose medical histories included the calculation of their cardiovascular risk or that explicitly mentioned the presence of variables necessary for its calculation. The sample size was calculated for a comparison of proportions with alpha = 0.05 and beta = 0.20, and assuming that the intervention would lead to a 15% increase in the measured variables. Corrections were made for the design effect, assigning a sample size to each cluster proportional to the size of the population served by the corresponding health centre, and assuming losses of 20%. This demanded a final sample size of 620 patients. Data were analysed using summary measures for each cluster, both in making estimates and for hypothesis testing. Analysis of the variables was made on an intention-to-treat basis. Trial Registration ClinicalTrials.gov: NCT01270022 PMID:21504570

Optimal cost-effective designs of Phase II proof of concept trials and associated go-no go decisions.

PubMed

Chen, Cong; Beckman, Robert A

2009-01-01

This manuscript discusses optimal cost-effective designs for Phase II proof of concept (PoC) trials. Unlike a confirmatory registration trial, a PoC trial is exploratory in nature, and sponsors of such trials have the liberty to choose the type I error rate and the power. The decision is largely driven by the perceived probability of having a truly active treatment per patient exposure (a surrogate measure to development cost), which is naturally captured in an efficiency score to be defined in this manuscript. Optimization of the score function leads to type I error rate and power (and therefore sample size) for the trial that is most cost-effective. This in turn leads to cost-effective go-no go criteria for development decisions. The idea is applied to derive optimal trial-level, program-level, and franchise-level design strategies. The study is not meant to provide any general conclusion because the settings used are largely simplified for illustrative purposes. However, through the examples provided herein, a reader should be able to gain useful insight into these design problems and apply them to the design of their own PoC trials.

Systemic Sclerosis Disease Modification Clinical Trials Design: Quo Vadis?

PubMed Central

Mendoza, Fabian A.; Keyes-Elstein, Lynette L.; Jimenez, Sergio A.

2012-01-01

The purpose of this manuscript is to discuss relevant aspects of clinical trials for Systemic Sclerosis (SSc) and to identify important considerations for the design of SSc disease modification clinical trials. Placebo randomized controlled trials with appropriate identification of SSc patients with diffuse progressive SSc skin involvement of recent onset, along with a rescue strategy for patients with worsening lung and skin involvement are suggested. If change in skin thickening is a major outcome of the study, the selection of patients with recent onset of disease and a predetermined degree of skin involvement are crucial requirements. The trial duration should be of at least 12 months. Sample size calculations should consider differences that exceed the Minimal Important Difference. Other relevant trial designs and potential threats to study validity are also discussed. Previous SSc-disease modifying trials have been beset by high dropout rates. Analyses on the subset of subjects completing the trial or applying the last-observation-carried-forward approach can potentially lead to biased estimates and false conclusions. Strategies for retention of subjects should be included at the design stage and analyses to account for missing data should be performed. PMID:22422541

MEDUCATE trial: effectiveness of an intensive EDUCATional intervention for IT-mediated MEDication management in the outpatient clinic - study protocol for a cluster randomized controlled trial.

PubMed

van Stiphout, F; Zwart-van Rijkom, J E F; Aarts, J E C M; Koffijberg, H; Klarenbeek-deJonge, E; Krulder, M; Roes, K C B; Egberts, A C G; ter Braak, E W M T

2015-05-22

Using information technology for medication management is an opportunity to help physicians to improve the quality of their documentation and communication and ultimately to improve patient care and patient safety. Physician education is necessary to take full advantage of information technology systems. In this trial, we seek to determine the effectiveness of an intensive educational intervention compared with the standard approach in improving information technology-mediated medication management and in reducing potential adverse drug events in the outpatient clinic. We are conducting a multicenter, cluster randomized controlled trial. The participants are specialists and residents working in the outpatient clinic of internal medicine, cardiology, pulmonology, geriatrics, gastroenterology and rheumatology. The intensive educational intervention is composed of a small-group session and e-learning. The primary outcome is discrepancies between registered medication (by physicians) and actually used medication (by patients). The key secondary outcomes are potential adverse events caused by missed drug-drug interactions. The primary and key secondary endpoints are being assessed shortly after the educational intervention is completed. Sample size will be calculated to ensure sufficient power. A sample size of 40 physicians per group and 20 patients per physician will ensure a power of >90 %, which means we will need a total of 80 physicians and 1,600 patients. We performed an exploratory trial wherein we tested the recruitment process, e-learning, time schedule, and methods for data collection, data management and data analysis. Accordingly, we refined the processes and content: the recruitment strategy was intensified, extra measures were taken to facilitate smooth conductance of the e-learning and parts were made optional. First versions of the procedures for data collection were determined. Data entry and analysis was further standardized by using the G-standard database in the telephone questionnaire. ISRCTN registry: ISRCTN50890124 . Registered 10 June 2013.

Designing trials for pressure ulcer risk assessment research: methodological challenges.

PubMed

Balzer, K; Köpke, S; Lühmann, D; Haastert, B; Kottner, J; Meyer, G

2013-08-01

For decades various pressure ulcer risk assessment scales (PURAS) have been developed and implemented into nursing practice despite uncertainty whether use of these tools helps to prevent pressure ulcers. According to current methodological standards, randomised controlled trials (RCTs) are required to conclusively determine the clinical efficacy and safety of this risk assessment strategy. In these trials, PURAS-aided risk assessment has to be compared to nurses' clinical judgment alone in terms of its impact on pressure ulcer incidence and adverse outcomes. However, RCTs evaluating diagnostic procedures are prone to specific risks of bias and threats to the statistical power which may challenge their validity and feasibility. This discussion paper critically reflects on the rigour and feasibility of experimental research needed to substantiate the clinical efficacy of PURAS-aided risk assessment. Based on reflections of the methodological literature, a critical appraisal of available trials on this subject and an analysis of a protocol developed for a methodologically robust cluster-RCT, this paper arrives at the following conclusions: First, available trials do not provide reliable estimates of the impact of PURAS-aided risk assessment on pressure ulcer incidence compared to nurses' clinical judgement alone due to serious risks of bias and insufficient sample size. Second, it seems infeasible to assess this impact by means of rigorous experimental studies since sample size would become extremely high if likely threats to validity and power are properly taken into account. Third, means of evidence linkages seem to currently be the most promising approaches for evaluating the clinical efficacy and safety of PURAS-aided risk assessment. With this kind of secondary research, the downstream effect of use of PURAS on pressure ulcer incidence could be modelled by combining best available evidence for single parts of this pathway. However, to yield reliable modelling results, more robust experimental research evaluating specific parts of the pressure ulcer risk assessment-prevention pathway is needed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Overview of registered studies in orthodontics: Evaluation of the ClinicalTrials.gov registry.

PubMed

Allareddy, Veerasathpurush; Rampa, Sankeerth; Masoud, Mohamed I; Lee, Min Kyeong; Nalliah, Romesh; Allareddy, Veerajalandhar

2014-11-01

The Food and Drug Administration Modernization Act of 1997 made it mandatory for all phase II through IV trials regulated by this Act to be registered. After this, the National Institutes of Health created ClinicalTrials.gov, which is a registry of publicly and privately supported clinical studies of human participants. The objective of this study was to examine the characteristics of registered studies in orthodontics. The ClinicalTrials.gov Web site was used to query all registered orthodontic studies. The search term used was "orthodontics." No limitations were placed for the time period. All registered studies regardless of their recruitment status, study results, and study type were selected for analysis. A total of 64 orthodontic studies were registered as of January 1, 2014. Of these, 52 were interventional, and 12 were observational. Close to 60% of the interventional studies and 66.7% of the observational studies had sample sizes of 50 or fewer subjects. About 21.2% of the interventional studies and 16.7% of the observational studies had sample sizes greater than 100. Only 1 study was funded by the National Institutes of Health, and the rest were funded by "other" or "industry" sources. Close to 87.7% of the interventional studies were randomized. Interventional model assignments included factorial assignment (3.9%), parallel assignments (74.5%), crossover assignment (7.8%), and single-group assignment (13.7%). Most studies were treatment oriented (80.4%). The types of masking used by the interventional studies included open label (28.9%), single blind (44.2%), and double blind (26.9%). Outcome assessors were blinded in only 6 studies. Orthodontic studies registered in ClinicalTrials.gov are dominated by small single-center studies. There are wide variations with regard to treatment allocation approaches and randomization methods in the studies. These results also indicate the need for multicenter clinical studies in orthodontics. Copyright © 2014 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Assessment and Implication of Prognostic Imbalance in Randomized Controlled Trials with a Binary Outcome – A Simulation Study

PubMed Central

Chu, Rong; Walter, Stephen D.; Guyatt, Gordon; Devereaux, P. J.; Walsh, Michael; Thorlund, Kristian; Thabane, Lehana

2012-01-01

Background Chance imbalance in baseline prognosis of a randomized controlled trial can lead to over or underestimation of treatment effects, particularly in trials with small sample sizes. Our study aimed to (1) evaluate the probability of imbalance in a binary prognostic factor (PF) between two treatment arms, (2) investigate the impact of prognostic imbalance on the estimation of a treatment effect, and (3) examine the effect of sample size (n) in relation to the first two objectives. Methods We simulated data from parallel-group trials evaluating a binary outcome by varying the risk of the outcome, effect of the treatment, power and prevalence of the PF, and n. Logistic regression models with and without adjustment for the PF were compared in terms of bias, standard error, coverage of confidence interval and statistical power. Results For a PF with a prevalence of 0.5, the probability of a difference in the frequency of the PF≥5% reaches 0.42 with 125/arm. Ignoring a strong PF (relative risk = 5) leads to underestimating the strength of a moderate treatment effect, and the underestimate is independent of n when n is >50/arm. Adjusting for such PF increases statistical power. If the PF is weak (RR = 2), adjustment makes little difference in statistical inference. Conditional on a 5% imbalance of a powerful PF, adjustment reduces the likelihood of large bias. If an absolute measure of imbalance ≥5% is deemed important, including 1000 patients/arm provides sufficient protection against such an imbalance. Two thousand patients/arm may provide an adequate control against large random deviations in treatment effect estimation in the presence of a powerful PF. Conclusions The probability of prognostic imbalance in small trials can be substantial. Covariate adjustment improves estimation accuracy and statistical power, and hence should be performed when strong PFs are observed. PMID:22629322

Comparative effectiveness and cost-effectiveness of Chuna manual therapy versus conventional usual care for nonacute low back pain: study protocol for a pilot multicenter, pragmatic randomized controlled trial (pCRN study).

PubMed

Shin, Byung-Cheul; Kim, Me-Riong; Cho, Jae-Heung; Jung, Jae-Young; Kim, Koh-Woon; Lee, Jun-Hwan; Nam, Kibong; Lee, Min Ho; Hwang, Eui-Hyoung; Heo, Kwang-Ho; Kim, Namkwen; Ha, In-Hyuk

2017-01-17

While Chuna manual therapy is a Korean manual therapy widely used primarily for low back pain (LBP)-related disorders in Korea, well-designed studies on the comparative effectiveness of Chuna manual therapy are scarce. This study is the protocol for a three-armed, multicenter, pragmatic randomized controlled pilot trial. Sixty severe nonacute LBP patients (pain duration of at least 3 weeks, Numeric Rating Scale (NRS) ≥5) will be recruited at four Korean medicine hospitals. Participants will be randomly allocated to the Chuna group (n = 20), usual care group (n = 20), or Chuna plus usual care group (n = 20) for 6 weeks of treatment. Usual care will consist of orally administered conventional medicine, physical therapy, and back pain care education. The trial will be conducted with outcome assessor and statistician blinding. The primary endpoint will be NRS of LBP at week 7 post randomization. Secondary outcomes include NRS of leg pain, the Oswestry Disability Index (ODI), the Patient Global Impression of Change (PGIC), the Credibility and Expectancy Questionnaire, lumbar range of motion (ROM), the EuroQol-5 Dimension (EQ-5D) health survey, the Health Utility Index III (HUI-III), and economic evaluation and safety data. Post-treatment follow-ups will be conducted at 1, 4, and 10 weeks after conclusion of treatment. This study will assess the comparative effectiveness of Chuna manual therapy compared to conventional usual care. Costs and effectiveness (utility) data will be analyzed for exploratory cost-effectiveness analysis. If this pilot study does not reach a definite conclusion due to its small sample size, these results will be used as preliminary results to calculate sample size for future large-scale clinical trials and contribute in the assessment of feasibility of a full-scale multicenter trial. Clinical Research Information Service (CRIS), KCT0001850 . Registered on 17 March 2016.

Two-sample binary phase 2 trials with low type I error and low sample size

PubMed Central

Litwin, Samuel; Basickes, Stanley; Ross, Eric A.

2017-01-01

Summary We address design of two-stage clinical trials comparing experimental and control patients. Our end-point is success or failure, however measured, with null hypothesis that the chance of success in both arms is p0 and alternative that it is p0 among controls and p1 > p0 among experimental patients. Standard rules will have the null hypothesis rejected when the number of successes in the (E)xperimental arm, E, sufficiently exceeds C, that among (C)ontrols. Here, we combine one-sample rejection decision rules, E ≥ m, with two-sample rules of the form E – C > r to achieve two-sample tests with low sample number and low type I error. We find designs with sample numbers not far from the minimum possible using standard two-sample rules, but with type I error of 5% rather than 15% or 20% associated with them, and of equal power. This level of type I error is achieved locally, near the stated null, and increases to 15% or 20% when the null is significantly higher than specified. We increase the attractiveness of these designs to patients by using 2:1 randomization. Examples of the application of this new design covering both high and low success rates under the null hypothesis are provided. PMID:28118686

Immune-directed therapy for type 1 diabetes at the clinical level: the Immune Tolerance Network (ITN) experience.

PubMed

Ehlers, Mario R; Nepom, Gerald T

2012-01-01

Reestablishing immune tolerance in type 1 diabetes (T1D), a chronic autoimmune disease, is a major goal. The Immune Tolerance Network (ITN) has initiated eight clinical trials of immunomodulatory therapies in recent-onset T1D over the past decade. Results have been mixed in terms of clinical efficacy, but the studies have provided valuable mechanistic insight that are enhancing our understanding of the disease and guiding the design of future trials. Trials of non-Fc-binding anti-CD3 mAbs have revealed that modulation of this target leads to partial responses, and ITN's AbATE trial led to identification of a robust responder group that could be distinguished from non-responders by baseline metabolic and immunologic features. A pilot study of the combination of IL-2 and rapamycin gave the first demonstration that frequency and function of regulatory T cells (Tregs) can be enhanced in T1D subjects, although the therapy triggered the activation of effectors with transient β-cell dysfunction. Similarly, therapy with anti-thymocyte globulin led to substantial lymphocyte depletion, but also to the activation of the acute-phase response with no clinical benefit during preliminary analyses. These and other results provide mechanistic tools that can be used as biomarkers for safety and efficacy in future trials. Furthermore, our results, together with those of other organizations, notably TrialNet, delineate the roles of the major components of the immune response in T1D. This information is setting the stage for future combination therapy trials. The development of disease-relevant biomarkers will also enable the implementation of innovative trial designs, notably adaptive trials, which will increase efficiencies in terms of study duration and sample size, and which will expedite the conduct of trials in which there are uncertainties about dose response and effect size.

Greater carbon stocks and faster turnover rates with increasing agricultural productivity

NASA Astrophysics Data System (ADS)

Sanderman, J.; Fallon, S.; Baisden, T. W.

2013-12-01

H.H. Janzen (2006) eloquently argued that from an agricultural perspective there is a tradeoff between storing carbon as soil organic matter (SOM) and the soil nutrient and energy benefit provided during SOM mineralization. Here we report on results from the Permanent Rotation Trial at the Waite Agricultural Institute, South Australia, indicating that shifting to an agricultural management strategy which returns more carbon to the soil, not only leads to greater carbon stocks but also increases the rate of carbon cycling through the soil. The Permanent Rotation Trial was established on a red Chromosol in 1925 with upgrades made to several treatments in 1948. Decadal soil samples were collected starting in 1963 at two depths, 0-10 and 10-22.5 cm, by compositing 20 soil cores taken along the length of each plot. We have chosen to analyze five trials representing a gradient in productivity: permanent pasture (Pa), wheat-pasture rotation (2W4Pa), continuous wheat (WW), wheat-oats-fallow rotation (WOF) and wheat-fallow (WF). For each of the soil samples (40 in total), the radiocarbon activity in the bulk soil as well as size-fractionated samples was measured by accelerator mass spectrometry at ANU's Radiocarbon Dating Laboratory (Fallon et al. 2010). After nearly 70 years under each rotation, SOC stocks increased linearly with productivity data across the trials from 24 to 58 tC ha-1. Importantly, these differences were due to greater losses over time in the low productivity trials rather than gains in SOC in any of the trials. Uptake of the bomb-spike in atmospheric 14C into the soil was greatest in the trials with the greatest productivity. The coarse size fraction always had greater Δ14C values than the bulk soil samples. Several different multi-pool steady state and non-steady state models were used to interpret the Δ14C data in terms of SOC turnover rates. Regardless of model choice, either the decay rates of all pools needed to increase or the allocation of C to more actively cycling pools needed to increase in order to fit the model to the measured Δ14C data as productivity of the trial increased. In model formulations with a non-cycling passive pool (i.e. Rothamsted Carbon Model, Jenkinson 1990), the best fit solution for the 14C age of the passive pool decreased from > 2000 years in the WF trial to < 100 years in the Pa trial. The modeling analysis suggests that decay constants are not constant and that there are important feedbacks between C input rate and the turnover rate of SOC. References: Fallon S et al. (2010) The next chapter in radiocarbon dating at the Australian National University: Status report on the single stage AMS. Nuclear Instruments and Methods in Physics Research: Section B, 268: 298-901. Grace PR et al. (1995) Trends in wheat yields and soil organic carbon in the Permanent Rotation Trial at the Waite Agricultural Research Institute, South Australia. Australian Journal of Experimental Agriculture 35: 857-864. Janzen HH (2006) The soil carbon dilemma: Shall we hoard it or use it? Soil Biology and Biochemistry 38:419-424. Jenkinson DS (1990) The turnover of organic carbon and nitrogen in soil. Philosophical transactions of the Royal Society, Series B 329: 361-368

Pharmacotherapy for trichotillomania.

PubMed

Rothbart, Rachel; Amos, Taryn; Siegfried, Nandi; Ipser, Jonathan C; Fineberg, Naomi; Chamberlain, Samuel R; Stein, Dan J

2013-11-08

Trichotillomania (TTM) (hair-pulling disorder) is a prevalent and disabling disorder characterised by recurrent hair-pulling. The effect of medication on trichotillomania has not been systematically evaluated. To assess the effects of medication for trichotillomania in adults compared with placebo or other active agents. We searched the Cochrane Central Register of Controlled Trials and the Cochrane Depression, Anxiety and Neurosis Group Register (to 31 July 2013), which includes relevant randomised controlled trials from the following bibliographic databases: The Cochrane Library (all years); EMBASE (1974 to date); MEDLINE (1950 to date) and PsycINFO (1967 to date). Two review authors identified relevant trials by assessing the abstracts of all possible studies. We selected randomised controlled trials (RCTs) of a medication versus placebo or active agent for TTM in adults. Two review authors independently performed the data extraction and 'Risk of bias' assessments, and disagreements were resolved through discussion with a third review author. Primary outcomes included the mean difference (MD) in reduction of trichotillomania symptoms on a continuous measure of trichotillomania symptom severity, and the risk ratio (RR) of the clinical response based on a dichotomous measure, with 95% confidence intervals (CIs). We identified eight studies with a total of 204 participants and a mean sample size of 25. All trials were single-centre trials, and participants seen on an outpatient basis. Seven studies compared medication and placebo (n = 184); one study compared medication and another active agent (n = 13). Duration of the studies was six to twelve weeks. Meta-analysis was not undertaken because of the methodological heterogeneity of the trials. The studies did not employ intention-to-treat analyses and were at a high risk of attrition bias. Adverse events were not well-documented in the studies.None of the three studies of selective serotonin reuptake inhibitors (SSRIs) demonstrated strong evidence of a treatment effect on any of the outcomes of interest. The unpublished naltrexone study did not provide strong evidence of a treatment effect. Two studies, an olanzapine study and a N-acetylcysteine (NAC) study, reported statistically significant treatment effects. One study of clomipramine demonstrated a treatment effect on two out of three measures of response to treatment. No particular medication class definitively demonstrates efficacy in the treatment of trichotillomania. Preliminary evidence suggests treatment effects of clomipramine, NAC and olanzapine based on three individual trials, albeit with very small sample sizes.

Dopamine Transporter Neuroimaging as an Enrichment Biomarker in Early Parkinson's Disease Clinical Trials: A Disease Progression Modeling Analysis

PubMed Central

Nicholas, Timothy; Tsai, Kuenhi; Macha, Sreeraj; Sinha, Vikram; Stone, Julie; Corrigan, Brian; Bani, Massimo; Muglia, Pierandrea; Watson, Ian A.; Kern, Volker D.; Sheveleva, Elena; Marek, Kenneth; Stephenson, Diane T.; Romero, Klaus

2017-01-01

Abstract Given the recognition that disease‐modifying therapies should focus on earlier Parkinson's disease stages, trial enrollment based purely on clinical criteria poses significant challenges. The goal herein was to determine the utility of dopamine transporter neuroimaging as an enrichment biomarker in early motor Parkinson's disease clinical trials. Patient‐level longitudinal data of 672 subjects with early‐stage Parkinson's disease in the Parkinson's Progression Markers Initiative (PPMI) observational study and the Parkinson Research Examination of CEP‐1347 Trial (PRECEPT) clinical trial were utilized in a linear mixed‐effects model analysis. The rate of worsening in the motor scores between subjects with or without a scan without evidence of dopamine transporter deficit was different both statistically and clinically. The average difference in the change from baseline of motor scores at 24 months between biomarker statuses was –3.16 (90% confidence interval [CI] = –0.96 to –5.42) points. Dopamine transporter imaging could identify subjects with a steeper worsening of the motor scores, allowing trial enrichment and 24% reduction of sample size. PMID:28749580

P-value interpretation and alpha allocation in clinical trials.

PubMed

Moyé, L A

1998-08-01

Although much value has been placed on type I error event probabilities in clinical trials, interpretive difficulties often arise that are directly related to clinical trial complexity. Deviations of the trial execution from its protocol, the presence of multiple treatment arms, and the inclusion of multiple end points complicate the interpretation of an experiment's reported alpha level. The purpose of this manuscript is to formulate the discussion of P values (and power for studies showing no significant differences) on the basis of the event whose relative frequency they represent. Experimental discordance (discrepancies between the protocol's directives and the experiment's execution) is linked to difficulty in alpha and beta interpretation. Mild experimental discordance leads to an acceptable adjustment for alpha or beta, while severe discordance results in their corruption. Finally, guidelines are provided for allocating type I error among a collection of end points in a prospectively designed, randomized controlled clinical trial. When considering secondary end point inclusion in clinical trials, investigators should increase the sample size to preserve the type I error rates at acceptable levels.

Weight change in control group participants in behavioural weight loss interventions: a systematic review and meta-regression study

PubMed Central

2012-01-01

Background Unanticipated control group improvements have been observed in intervention trials targeting various health behaviours. This phenomenon has not been studied in the context of behavioural weight loss intervention trials. The purpose of this study is to conduct a systematic review and meta-regression of behavioural weight loss interventions to quantify control group weight change, and relate the size of this effect to specific trial and sample characteristics. Methods Database searches identified reports of intervention trials meeting the inclusion criteria. Data on control group weight change and possible explanatory factors were abstracted and analysed descriptively and quantitatively. Results 85 trials were reviewed and 72 were included in the meta-regression. While there was no change in control group weight, control groups receiving usual care lost 1 kg more than control groups that received no intervention, beyond measurement. Conclusions There are several possible explanations why control group changes occur in intervention trials targeting other behaviours, but not for weight loss. Control group participation may prevent weight gain, although more research is needed to confirm this hypothesis. PMID:22873682

Weight change in control group participants in behavioural weight loss interventions: a systematic review and meta-regression study.

PubMed

Waters, Lauren; George, Alexis S; Chey, Tien; Bauman, Adrian

2012-08-08

Unanticipated control group improvements have been observed in intervention trials targeting various health behaviours. This phenomenon has not been studied in the context of behavioural weight loss intervention trials. The purpose of this study is to conduct a systematic review and meta-regression of behavioural weight loss interventions to quantify control group weight change, and relate the size of this effect to specific trial and sample characteristics. Database searches identified reports of intervention trials meeting the inclusion criteria. Data on control group weight change and possible explanatory factors were abstracted and analysed descriptively and quantitatively. 85 trials were reviewed and 72 were included in the meta-regression. While there was no change in control group weight, control groups receiving usual care lost 1 kg more than control groups that received no intervention, beyond measurement. There are several possible explanations why control group changes occur in intervention trials targeting other behaviours, but not for weight loss. Control group participation may prevent weight gain, although more research is needed to confirm this hypothesis.

Imaging outcome measures for progressive multiple sclerosis trials

PubMed Central

Moccia, Marcello; de Stefano, Nicola; Barkhof, Frederik

2017-01-01

Imaging markers that are reliable, reproducible and sensitive to neurodegenerative changes in progressive multiple sclerosis (MS) can enhance the development of new medications with a neuroprotective mode-of-action. Accordingly, in recent years, a considerable number of imaging biomarkers have been included in phase 2 and 3 clinical trials in primary and secondary progressive MS. Brain lesion count and volume are markers of inflammation and demyelination and are important outcomes even in progressive MS trials. Brain and, more recently, spinal cord atrophy are gaining relevance, considering their strong association with disability accrual; ongoing improvements in analysis methods will enhance their applicability in clinical trials, especially for cord atrophy. Advanced magnetic resonance imaging (MRI) techniques (e.g. magnetization transfer ratio (MTR), diffusion tensor imaging (DTI), spectroscopy) have been included in few trials so far and hold promise for the future, as they can reflect specific pathological changes targeted by neuroprotective treatments. Position emission tomography (PET) and optical coherence tomography have yet to be included. Applications, limitations and future perspectives of these techniques in clinical trials in progressive MS are discussed, with emphasis on measurement sensitivity, reliability and sample size calculation. PMID:29041865

Assessing the Eventual Publication of Clinical Trial Abstracts Submitted to a Large Annual Oncology Meeting

PubMed Central

Wang, Ruibin; Prasad, Vinay; Bates, Susan E.; Fojo, Tito

2016-01-01

Background. Despite the ethical imperative to publish clinical trials when human subjects are involved, such data frequently remain unpublished. The objectives were to tabulate the rate and ascertain factors associated with eventual publication of clinical trial results reported as abstracts in the Proceedings of the American Society of Clinical Oncology (American Society of Clinical Oncology). Materials and Methods. Abstracts describing clinical trials for patients with breast, lung, colorectal, ovarian, and prostate cancer from 2009 to 2011 were identified by using a comprehensive online database (http://meetinglibrary.asco.org/abstracts). Abstracts included reported results of a treatment or intervention assessed in a discrete, prospective clinical trial. Publication status at 4−6 years was determined by using a standardized search of PubMed. Primary outcomes were the rate of publication for abstracts of randomized and nonrandomized clinical trials. Secondary outcomes included factors influencing the publication of results. Results. A total of 1,075 abstracts describing 378 randomized and 697 nonrandomized clinical trials were evaluated. Across all years, 75% of randomized and 54% of nonrandomized trials were published, with an overall publication rate of 61%. Sample size was a statistically significant predictor of publication for both randomized and nonrandomized trials (odds ratio [OR] per increase of 100 participants = 1.23 [1.11–1.36], p < .001; and 1.64 [1.15–2.34], p = .006, respectively). Among randomized studies, an industry coauthor or involvement of a cooperative group increased the likelihood of publication (OR 2.37, p = .013; and 2.21, p = .01, respectively). Among nonrandomized studies, phase II trials were more likely to be published than phase I (p < .001). Use of an experimental agent was not a predictor of publication in randomized (OR 0.76 [0.38–1.52]; p = .441) or nonrandomized trials (OR 0.89 [0.61–1.29]; p = .532). Conclusion. This is the largest reported study examining why oncology trials are not published. The data show that 4−6 years after appearing as abstracts, 39% of oncology clinical trials remain unpublished. Larger sample size and advanced trial phase were associated with eventual publication; among randomized trials, an industry-affiliated author or a cooperative group increased likelihood of publication. Unfortunately, we found that, despite widespread recognition of the problem and the creation of central data repositories, timely publishing of oncology clinical trials results remains unsatisfactory. Implications for Practice: The Declaration of Helsinki Ethical Principles for Medical Research Involving Human Subjects notes the ethical obligation to report clinical trial data, whether positive or negative. This obligation is listed alongside requirements for risk minimization, access, confidentiality, and informed consent, all bedrocks of the clinical trial system, yet clinical trials are often not published, particularly if negative or difficult to complete. This study found that among American Society for Clinical Oncology (ASCO) Annual Meeting abstracts, 2009–2011, only 61% were published 4–6 years later: 75% of randomized trials and 54% of nonrandomized trials. Clinicians need to insist that every study in which they participate is published. PMID:26888691

Smartphone App Using Mindfulness Meditation for Women With Chronic Pelvic Pain (MEMPHIS): Protocol for a Randomized Feasibility Trial

PubMed Central

Newton, Sian; Kahan, Brennan C; Forbes, Gordon; Wright, Neil; Cantalapiedra Calvete, Clara; Gibson, Harry A L; Rogozinska, Ewelina; Rivas, Carol; Taylor, Stephanie J C; Birch, Judy; Dodds, Julie

2018-01-01

Background Female chronic pelvic pain (CPP) is defined as intermittent or constant pelvic or lower abdominal pain occurring in a woman for at least 6 months. Up to a quarter of women are estimated to be affected by CPP worldwide and it is responsible for one fifth of specialist gynecological referrals in the United Kingdom. Psychological interventions are commonly utilized. As waiting times and funding capacity impede access to face-to-face consultations, supported self-management (SSM) has emerged as a viable alternative. Mindfulness meditation is a potentially valuable SSM tool, and in the era of mobile technology, this can be delivered to the individual user via a smartphone app. Objective To assess the feasibility of conducting a trial of a mindfulness meditation intervention delivered by a mobile phone app for patients with CPP. The main feasibility objectives were to assess patient recruitment and app adherence, to obtain information to be used in the sample size estimate of a future trial, and to receive feedback on usability of the app. Methods Mindfulness Meditation for Women With Chronic Pelvic Pain (MEMPHIS) is a three-arm feasibility trial, that took place in two hospitals in the United Kingdom. Eligible participants were randomized in a 1:1:1 ratio to one of three treatment arms: (1) the intervention arm, consisting of a guided, spoken mindfulness meditation app; (2) an active control arm, consisting of a progressive muscle relaxation app; and (3) usual care (no app). Participants were followed-up for 6 months. Key feasibility outcomes included the time taken to recruit all patients for the study, adherence, and estimates to be used in the sample size calculation for a subsequent full-scale trial. Upon completion of the feasibility trial we will conduct focus groups to explore app usability and reasons for noncompliance. Results Recruitment for MEMPHIS took place between May 2016 and September 2016. The study was closed March 2017 and the report was submitted to the NIHR on October 26, 2017. Conclusions This feasibility trial will inform the design of a large multicentered trial to assess the clinical effectiveness of mindfulness meditation delivered via a smartphone app for the treatment of CPP. Trial Registration ClinicalTrials.gov: NCT02721108; https://clinicaltrials.gov/ct2/show/NCT02721108 (Archived by WebCite at http://www.webcitation.org/6wLMAkuaU); BioMed Central: ISRCTN10925965; https://www.isrctn.com/ISRCTN10925965 (Archived by WebCite at http://www.webcitation.org/6wLMVLuys) PMID:29335232

Interventions to Improve Medication Adherence in Hypertensive Patients: Systematic Review and Meta-analysis.

PubMed

Conn, Vicki S; Ruppar, Todd M; Chase, Jo-Ana D; Enriquez, Maithe; Cooper, Pamela S

2015-12-01

This systematic review applied meta-analytic procedures to synthesize medication adherence interventions that focus on adults with hypertension. Comprehensive searching located trials with medication adherence behavior outcomes. Study sample, design, intervention characteristics, and outcomes were coded. Random-effects models were used in calculating standardized mean difference effect sizes. Moderator analyses were conducted using meta-analytic analogues of ANOVA and regression to explore associations between effect sizes and sample, design, and intervention characteristics. Effect sizes were calculated for 112 eligible treatment-vs.-control group outcome comparisons of 34,272 subjects. The overall standardized mean difference effect size between treatment and control subjects was 0.300. Exploratory moderator analyses revealed interventions were most effective among female, older, and moderate- or high-income participants. The most promising intervention components were those linking adherence behavior with habits, giving adherence feedback to patients, self-monitoring of blood pressure, using pill boxes and other special packaging, and motivational interviewing. The most effective interventions employed multiple components and were delivered over many days. Future research should strive for minimizing risks of bias common in this literature, especially avoiding self-report adherence measures.

Design of a Bayesian adaptive phase 2 proof-of-concept trial for BAN2401, a putative disease-modifying monoclonal antibody for the treatment of Alzheimer's disease.

PubMed

Satlin, Andrew; Wang, Jinping; Logovinsky, Veronika; Berry, Scott; Swanson, Chad; Dhadda, Shobha; Berry, Donald A

2016-01-01

Recent failures in phase 3 clinical trials in Alzheimer's disease (AD) suggest that novel approaches to drug development are urgently needed. Phase 3 risk can be mitigated by ensuring that clinical efficacy is established before initiating confirmatory trials, but traditional phase 2 trials in AD can be lengthy and costly. We designed a Bayesian adaptive phase 2, proof-of-concept trial with a clinical endpoint to evaluate BAN2401, a monoclonal antibody targeting amyloid protofibrils. The study design used dose response and longitudinal modeling. Simulations were used to refine study design features to achieve optimal operating characteristics. The study design includes five active treatment arms plus placebo, a clinical outcome, 12-month primary endpoint, and a maximum sample size of 800. The average overall probability of success is ≥80% when at least one dose shows a treatment effect that would be considered clinically meaningful. Using frequent interim analyses, the randomization ratios are adapted based on the clinical endpoint, and the trial can be stopped for success or futility before full enrollment. Bayesian statistics can enhance the efficiency of analyzing the study data. The adaptive randomization generates more data on doses that appear to be more efficacious, which can improve dose selection for phase 3. The interim analyses permit stopping as soon as a predefined signal is detected, which can accelerate decision making. Both features can reduce the size and duration of the trial. This study design can mitigate some of the risks associated with advancing to phase 3 in the absence of data demonstrating clinical efficacy. Limitations to the approach are discussed.

Pharmacologic Treatment of Repetitive Behaviors in Autism Spectrum Disorders: Evidence of Publication Bias

PubMed Central

Volkmar, Fred R.; Bloch, Michael H.

2012-01-01

OBJECTIVE: The goal of this study was to examine the efficacy of serotonin receptor inhibitors (SRIs) for the treatment of repetitive behaviors in autism spectrum disorders (ASD). METHODS: Two reviewers searched PubMed and Clinicaltrials.gov for randomized, double-blind, placebo-controlled trials evaluating the efficacy of SRIs for repetitive behaviors in ASD. Our primary outcome was mean improvement in ratings scales of repetitive behavior. Publication bias was assessed by using a funnel plot, the Egger’s test, and a meta-regression of sample size and effect size. RESULTS: Our search identified 5 published and 5 unpublished but completed trials eligible for meta-analysis. Meta-analysis of 5 published and 1 unpublished trial (which provided data) demonstrated a small but significant effect of SRI for the treatment of repetitive behaviors in ASD (standardized mean difference: 0.22 [95% confidence interval: 0.07–0.37], z score = 2.87, P < .005). There was significant evidence of publication bias in all analyses. When Duval and Tweedie's trim and fill method was used to adjust for the effect of publication bias, there was no longer a significant benefit of SRI for the treatment of repetitive behaviors in ASD (standardized mean difference: 0.12 [95% confidence interval: –0.02 to 0.27]). Secondary analyses demonstrated no significant effect of type of medication, patient age, method of analysis, trial design, or trial duration on reported SRI efficacy. CONCLUSIONS: Meta-analysis of the published literature suggests a small but significant effect of SRI in the treatment of repetitive behaviors in ASD. This effect may be attributable to selective publication of trial results. Without timely, transparent, and complete disclosure of trial results, it remains difficult to determine the efficacy of available medications. PMID:22529279

Duration of treatment for asymptomatic bacteriuria during pregnancy.

PubMed

Villar, J; Lydon-Rochelle, M T; Gülmezoglu, A M; Roganti, A

2000-01-01

A Cochrane systematic review has shown that drug treatment of asymptomatic bacteriuria in pregnant women substantially decreases the risk of pyelonephritis and reduces the risk of preterm delivery. However, it is not clear whether single dose therapy is as effective as longer conventional antibiotic treatment. The objective of this review was to assess the effects of different durations of treatment for asymptomatic bacteriuria in pregnancy. We searched the Cochrane Pregnancy and Childbirth Group trials register, the Cochrane Controlled Trials Register and the reference lists of articles. Randomised and quasi-randomised trials comparing antimicrobial therapeutic regimens that differed in duration (particularly comparing single dose with longer duration regimens) in pregnant women diagnosed with asymptomatic bacteriuria. Trial quality was assessed and data were extracted independently by the reviewers. Eight studies involving over 400 women were included. All were comparisons of single dose treatment with four to seven day treatments. The trials were generally of poor quality. No difference in 'no-cure' rate was detected between single dose and short course (4-7 day) treatment for asymptomatic bacteriuria in pregnant women (relative risk 1.13, 95% confidence interval 0.82 to 1.54) as well as in the recurrent asymptomtic bacteriuria (relative risk 1.08, 95% confidence interval 0.70 to 1.66). However these results showed significant heterogeneity. No differences were detected for preterm births and pyelonephritis although sample size of trials was small. Longer duration treatment was associated with an increase in reports of adverse effects (relative risk 0.53, 95% confidence interval 0.31 to 0.91). There is not enough evidence to evaluate whether single dose or longer duration doses are more effective in treating asymptomatic bacteriuria in pregnant women. Because single dose has lower cost and increases compliance, this comparison should be explored in a properly sized randomized controlled trial.

Magnetic Resonance Biomarkers in Neonatal Encephalopathy (MARBLE): a prospective multicountry study.

PubMed

Lally, Peter J; Pauliah, Shreela; Montaldo, Paolo; Chaban, Badr; Oliveira, Vania; Bainbridge, Alan; Soe, Aung; Pattnayak, Santosh; Clarke, Paul; Satodia, Prakash; Harigopal, Sundeep; Abernethy, Laurence J; Turner, Mark A; Huertas-Ceballos, Angela; Shankaran, Seetha; Thayyil, Sudhin

2015-09-30

Despite cooling, adverse outcomes are seen in up to half of the surviving infants after neonatal encephalopathy. A number of novel adjunct drug therapies with cooling have been shown to be highly neuroprotective in animal studies, and are currently awaiting clinical translation. Rigorous evaluation of these therapies in phase II trials using surrogate MR biomarkers may speed up their bench to bedside translation. A recent systematic review of single-centre studies has suggested that MR spectroscopy biomarkers offer the best promise; however, the prognostic accuracy of these biomarkers in cooled encephalopathic babies in a multicentre setting using different MR scan makers is not known. The MR scanners (3 T; Philips, Siemens, GE) in all the participating sites will be harmonised using phantom experiments and healthy adult volunteers before the start of the study. We will then recruit 180 encephalopathic infants treated with whole body cooling from the participating centres. MRI and spectroscopy will be performed within 2 weeks of birth. Neurodevelopmental outcomes will be assessed at 18-24 months of age. Agreement between MR cerebral biomarkers and neurodevelopmental outcome will be reported. The sample size is calculated using the 'rule of 10', generally used to calculate the sample size requirements for developing prognostic models. Considering 9 parameters, we require 9×10 adverse events, which suggest that a total sample size of 180 is required. Human Research Ethics Committee approvals have been received from Brent Research Ethics Committee (London), and from Imperial College London (Sponsor). We will submit the results of the study to relevant journals and offer national and international presentations. Clinical Trials.gov Number: NCT01309711. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Suitable Stimuli to Obtain (No) Gender Differences in the Speed of Cognitive Processes Involved in Mental Rotation

ERIC Educational Resources Information Center

Jansen-Osmann, Petra; Heil, Martin

2007-01-01

Gender differences in speed of perceptual comparison, of picture-plane mental rotation, and in switching costs between trials that do and do not require mental rotation, were investigated as a function of stimulus material with a total sample size of N=360. Alphanumeric characters, PMA symbols, animal drawings, polygons and 3D cube figures were…

CHAracteristics of research studies that iNfluence practice: a GEneral survey of Canadian orthopaedic Surgeons (CHANGES): a pilot survey.

PubMed

de Sa, Darren; Thornley, Patrick; Evaniew, Nathan; Madden, Kim; Bhandari, Mohit; Ghert, Michelle

2015-01-01

Evidence Based Medicine (EBM) is increasingly being applied to inform clinical decision-making in orthopaedic surgery. Despite the promotion of EBM in Orthopaedic Surgery, the adoption of results from high quality clinical research seems highly unpredictable and does not appear to be driven strictly by randomized trial data. The objective of this study was to pilot a survey to determine if we could identify surgeon opinions on the characteristics of research studies that are perceived as being most likely to influence clinical decision-making among orthopaedic surgeons in Canada. A 28-question electronic survey was distributed to active members of the Canadian Orthopaedic Association (COA) over a period of 11 weeks. The questionnaire sought to analyze the influence of both extrinsic and intrinsic characteristics of research studies and their potential to influence practice patterns. Extrinsic factors included the perceived journal quality and investigator profiles, economic impact, peer/patient/industry influence and individual surgeon residency/fellowship training experiences. Intrinsic factors included study design, sample size, and outcomes reported. Descriptive statistics are provided. Of the 109 members of the COA who opened the survey, 95 (87%) completed the survey in its entirety. The overall response rate was 11% (95/841). Surgeons achieved consensus on the influence of three key designs on their practices: 1) randomized controlled trials 94 (99%), 2) meta-analysis 83 (87%), and 3) systematic reviews 81 (85%). Sixty-seven percent of surgeons agreed that studies with sample sizes of 101-500 or more were more likely to influence clinical practice than smaller studies (n = <100). Factors other than design influencing adoption included 1) reputation of the investigators (99%) and 2) perceived quality of the journal (75%). Although study design and sample size (i.e. minimum of 100 patients) have some influence on clinical decision making, surgeon respondents are equally influenced by investigator reputation and perceived journal quality. At present, continued emphasis on the generation of large, methodologically sound clinical trials remains paramount to translating research findings to clinical practice changes. Specific to this pilot survey, strategies to solicit more widespread responses will be pursued.

Adjusting for multiple prognostic factors in the analysis of randomised trials

PubMed Central

2013-01-01

Background When multiple prognostic factors are adjusted for in the analysis of a randomised trial, it is unclear (1) whether it is necessary to account for each of the strata, formed by all combinations of the prognostic factors (stratified analysis), when randomisation has been balanced within each stratum (stratified randomisation), or whether adjusting for the main effects alone will suffice, and (2) the best method of adjustment in terms of type I error rate and power, irrespective of the randomisation method. Methods We used simulation to (1) determine if a stratified analysis is necessary after stratified randomisation, and (2) to compare different methods of adjustment in terms of power and type I error rate. We considered the following methods of analysis: adjusting for covariates in a regression model, adjusting for each stratum using either fixed or random effects, and Mantel-Haenszel or a stratified Cox model depending on outcome. Results Stratified analysis is required after stratified randomisation to maintain correct type I error rates when (a) there are strong interactions between prognostic factors, and (b) there are approximately equal number of patients in each stratum. However, simulations based on real trial data found that type I error rates were unaffected by the method of analysis (stratified vs unstratified), indicating these conditions were not met in real datasets. Comparison of different analysis methods found that with small sample sizes and a binary or time-to-event outcome, most analysis methods lead to either inflated type I error rates or a reduction in power; the lone exception was a stratified analysis using random effects for strata, which gave nominal type I error rates and adequate power. Conclusions It is unlikely that a stratified analysis is necessary after stratified randomisation except in extreme scenarios. Therefore, the method of analysis (accounting for the strata, or adjusting only for the covariates) will not generally need to depend on the method of randomisation used. Most methods of analysis work well with large sample sizes, however treating strata as random effects should be the analysis method of choice with binary or time-to-event outcomes and a small sample size. PMID:23898993

Effect of Industry Sponsorship on Dental Restorative Trials.

PubMed

Schwendicke, F; Tu, Y-K; Blunck, U; Paris, S; Göstemeyer, G

2016-01-01

Industry sponsorship was found to potentially introduce bias into clinical trials. We assessed the effects of industry sponsorship on the design, comparator choice, and findings of randomized controlled trials on dental restorative materials. A systematic review was performed via MEDLINE, CENTRAL, and EMBASE. Randomized trials on dental restorative and adhesive materials published 2005 to 2015 were included. The design of sponsored and nonsponsored trials was compared statistically (risk of bias, treatment indication, setting, transferability, sample size). Comparator choice and network geometry of sponsored and nonsponsored trials were assessed via network analysis. Material performance rankings in different trial types were estimated via Bayesian network meta-analysis. Overall, 114 studies were included (15,321 restorations in 5,232 patients). We found 21 and 41 (18% and 36%) trials being clearly or possibly industry sponsored, respectively. Trial design of sponsored and nonsponsored trials did not significantly differ for most assessed items. Sponsored trials evaluated restorations of load-bearing cavities significantly more often than nonsponsored trials, had longer follow-up periods, and showed significantly increased risk of detection bias. Regardless of sponsorship status, comparisons were mainly performed within material classes. The proportion of trials comparing against gold standard restorative or adhesive materials did not differ between trial types. If ranked for performance according to the need to re-treat (best: least re-treatments), most material combinations were ranked similarly in sponsored and nonsponsored trials. The effect of industry sponsorship on dental restorative trials seems limited. © International & American Associations for Dental Research 2015.

Attrition in trials evaluating complex interventions for schizophrenia: Systematic review and meta-analysis.

PubMed

Szymczynska, P; Walsh, S; Greenberg, L; Priebe, S

2017-07-01

Essential criteria for the methodological quality and validity of randomized controlled trials are the drop-out rates from both the experimental intervention and the study as a whole. This systematic review and meta-analysis assessed these drop-out rates in non-pharmacological schizophrenia trials. A systematic literature search was used to identify relevant trials with ≥100 sample size and to extract the drop-out data. The rates of drop-out from the experimental intervention and study were calculated with meta-analysis of proportions. Meta-regression was applied to explore the association between the study and sample characteristics and the drop-out rates. 43 RCTs were found, with drop-out from intervention ranging from 0% to 63% and study drop-out ranging from 4% to 71%. Meta-analyses of proportions showed an overall drop-out rate of 14% (95% CI: 13-15%) at the experimental intervention level and 20% (95% CI: 17-24%) at the study level. Meta-regression showed that the active intervention drop-out rates were predicted by the number of intervention sessions. In non-pharmacological schizophrenia trials, drop-out rates of less than 20% can be achieved for both the study and the experimental intervention. A high heterogeneity of drop-out rates across studies shows that even lower rates are achievable. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Psychostimulants for late life depression].

PubMed

Delsalle, P; Schuster, J-P; von Gunten, A; Limosin, F

2017-11-28

The use of psychostimulants in the treatment of depressive disorders is receiving renewed interest. Recent publications suggest a particular interest of psychostimulants in the treatment of depression in the elderly. The aim of this article is to review the literature on the role of psychostimulants in the treatment of depression in older adults. The literature review focused on efficacy and tolerability studies of psychostimulants in the treatment of depression for the elderly that were published between 1980 and 2016. The only inclusion criterion applied was an average age of the sample studied greater than or equal to 60 years. Overall, 12 trials were selected: 3 controlled trials and 9 uncontrolled trials. Of the 3 controlled trials, one compared parallel groups and the other two were cross-tests. Among the psychostimulants, methylphenidate was the most studied molecule. The trials demonstrate an efficacy of this molecule in particular as an add-on therapy in old-age depression but for the most part with a level of proof that remains insufficient. The small size of the samples and the methodological limitations of the studies obviate the possibility of extracting definitive conclusions concerning the place of psychostimulants in the treatment of depression in the elderly. Further studies are required in particular in the treatment of resistant depressive episodes. Copyright © 2017 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Mindfulness-based stress reduction for treating chronic headache: A systematic review and meta-analysis.

PubMed

Anheyer, Dennis; Leach, Matthew J; Klose, Petra; Dobos, Gustav; Cramer, Holger

2018-01-01

Background Mindfulness-based stress reduction/cognitive therapy are frequently used for pain-related conditions, but their effects on headache remain uncertain. This review aimed to assess the efficacy and safety of mindfulness-based stress reduction/cognitive therapy in reducing the symptoms of chronic headache. Data sources and study selection MEDLINE/PubMed, Scopus, CENTRAL, and PsychINFO were searched to 16 June 2017. Randomized controlled trials comparing mindfulness-based stress reduction/cognitive therapy with usual care or active comparators for migraine and/or tension-type headache, which assessed headache frequency, duration or intensity as a primary outcome, were eligible for inclusion. Risk of bias was assessed using the Cochrane Tool. Results Five randomized controlled trials (two on tension-type headache; one on migraine; two with mixed samples) with a total of 185 participants were included. Compared to usual care, mindfulness-based stress reduction/cognitive therapy did not improve headache frequency (three randomized controlled trials; standardized mean difference = 0.00; 95% confidence interval = -0.33,0.32) or headache duration (three randomized controlled trials; standardized mean difference = -0.08; 95% confidence interval = -1.03,0.87). Similarly, no significant difference between groups was found for pain intensity (five randomized controlled trials; standardized mean difference = -0.78; 95% confidence interval = -1.72,0.16). Conclusions Due to the low number, small scale and often high or unclear risk of bias of included randomized controlled trials, the results are imprecise; this may be consistent with either an important or negligible effect. Therefore, more rigorous trials with larger sample sizes are needed.

Polyethylene glycol intestinal lavage in addition to usual antibiotic treatment for severe Clostridium difficile colitis: a randomised controlled pilot study

PubMed Central

McCreery, Greig; Jones, Philip M; Kidane, Biniam; DeMelo, Vanessa

2017-01-01

Introduction Clostridium difficile infections (CDI) are common, costly and potentially life threatening. Most CDI will respond to antibiotic therapy, but 3%–10% of all patients with CDI will progress to a severe, life-threatening course. Complete removal of the large bowel is indicated for severe CDI. However, the 30-day mortality following surgical intervention for severe CDI ranges from 20% to 70%. A less invasive approach using surgical faecal diversion and direct colonic lavage with polyethylene glycol (PEG) and vancomycin has demonstrated a relative mortality reduction of approximately 50%. As an alternative to these operative approaches, we propose to treat patients with bedside intestinal lavage with PEG and vancomycin instillation via nasojejunal tube, in addition to usual antibiotic management. Preliminary data collected by our research group are encouraging. Methods and analysis We will conduct a 1-year, single-centre, pilot randomised controlled trial to study this new treatment strategy for patients with severe CDI and additional risk factors for fulminant or complicated infection. After informed consent, patients with severe-complicated CDI without immediate indication for surgery will be randomised to either usual antibiotic treatment or usual antibiotic treatment with the addition of 8 L of PEG lavage via nasojejunal tube. This pilot trial will evaluate our eligibility and enrolment rate, protocol compliance and adverse event rates and provide further data to inform a more robust sample size calculation and protocol modifications for a definitive multicentre trial design. Based on historical data, we anticipate enrolling approximately 24 patients during the 1-year pilot study period. As a pilot study, data will be reported in aggregate. Between-group differences will be assessed in a blinded fashion for evidence of harm, and to further refine our sample size calculation. Ethics and dissemination This study protocol has been reviewed and approved by our local institutional review board. Results of the pilot trial and subsequent main trial will be submitted for publication in a peer-reviewed journal. Trial registration number NCT02466698; Pre-results. PMID:28760801

Learned perceptual associations influence visuomotor programming under limited conditions: kinematic consistency.

PubMed

Haffenden, Angela M; Goodale, Melvyn A

2002-12-01

Previous findings have suggested that visuomotor programming can make use of learned size information in experimental paradigms where movement kinematics are quite consistent from trial to trial. The present experiment was designed to test whether or not this conclusion could be generalized to a different manipulation of kinematic variability. As in previous work, an association was established between the size and colour of square blocks (e.g. red = large; yellow = small, or vice versa). Associating size and colour in this fashion has been shown to reliably alter the perceived size of two test blocks halfway in size between the large and small blocks: estimations of the test block matched in colour to the group of large blocks are smaller than estimations of the test block matched to the group of small blocks. Subjects grasped the blocks, and on other trials estimated the size of the blocks. These changes in perceived block size were incorporated into grip scaling only when movement kinematics were highly consistent from trial to trial; that is, when the blocks were presented in the same location on each trial. When the blocks were presented in different locations grip scaling remained true to the metrics of the test blocks despite the changes in perceptual estimates of block size. These results support previous findings suggesting that kinematic consistency facilitates the incorporation of learned perceptual information into grip scaling.

Is overestimation of body size associated with neuropsychological weaknesses in anorexia nervosa?

PubMed

Øverås, Maria; Kapstad, Hilde; Brunborg, Cathrine; Landrø, Nils Inge; Rø, Øyvind

2017-03-01

Recent research indicates some evidence of neuropsychological weaknesses in visuospatial memory, central coherence and set-shifting in adults with anorexia nervosa (AN). The growing interest in neuropsychological functioning of patients with AN is based upon the assumption that neuropsychological weaknesses contribute to the clinical features of the illness. However, due to a paucity of research on the connection between neuropsychological difficulties and the clinical features of AN, this link remains hypothetical. The main objective of this study was to explore the association between specific areas of neuropsychological functioning and body size estimation in patients with AN and healthy controls. The sample consisted of 36 women diagnosed with AN and 34 healthy female controls. Participants were administered the continuous visual memory test and the recall trials of Rey Complex Figure Test to assess visual memory. Central coherence was assessed using the copy trial of Rey Complex Figure Test, and the Wisconsin Card Sorting Test was used to assess set-shifting. Body size estimation was assessed with a computerized morphing programme. The analyses showed no significant correlations between any of the neuropsychological measures and body size estimation. The results suggest that there is no association between these areas of neuropsychological difficulties and body size estimation among patients with AN. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association.

Alzheimer Disease Biomarkers as Outcome Measures for Clinical Trials in MCI.

PubMed

Caroli, Anna; Prestia, Annapaola; Wade, Sara; Chen, Kewei; Ayutyanont, Napatkamon; Landau, Susan M; Madison, Cindee M; Haense, Cathleen; Herholz, Karl; Reiman, Eric M; Jagust, William J; Frisoni, Giovanni B

2015-01-01

The aim of this study was to compare the performance and power of the best-established diagnostic biological markers as outcome measures for clinical trials in patients with mild cognitive impairment (MCI). Magnetic resonance imaging, F-18 fluorodeoxyglucose positron emission tomography markers, and Alzheimer's Disease Assessment Scale-cognitive subscale were compared in terms of effect size and statistical power over different follow-up periods in 2 MCI groups, selected from Alzheimer's Disease Neuroimaging Initiative data set based on cerebrospinal fluid (abnormal cerebrospinal fluid Aβ1-42 concentration-ABETA+) or magnetic resonance imaging evidence of Alzheimer disease (positivity to hippocampal atrophy-HIPPO+). Biomarkers progression was modeled through mixed effect models. Scaled slope was chosen as measure of effect size. Biomarkers power was estimated using simulation algorithms. Seventy-four ABETA+ and 51 HIPPO+ MCI patients were included in the study. Imaging biomarkers of neurodegeneration, especially MR measurements, showed highest performance. For all biomarkers and both MCI groups, power increased with increasing follow-up time, irrespective of biomarker assessment frequency. These findings provide information about biomarker enrichment and outcome measurements that could be employed to reduce MCI patient samples and treatment duration in future clinical trials.

Need for common internal controls when assessing the relative efficacy of pharmacologic agents using a meta-analytic approach: case study of cyclooxygenase 2-selective inhibitors for the treatment of osteoarthritis.

PubMed

Lee, Chin; Hunsche, Elke; Balshaw, Robert; Kong, Sheldon X; Schnitzer, Thomas J

2005-08-15

To evaluate the role of common internal controls in a meta-analysis of the relative efficacy of cyclooxygenase 2-selective inhibitors (coxibs) in the treatment of osteoarthritis (OA). A systematic search of Medline and US Food and Drug Administration electronic databases was performed to identify randomized, placebo-controlled clinical trials of coxibs (etoricoxib, celecoxib, rofecoxib, valdecoxib) in patients with hip and/or knee OA. The effect size for coxibs and common active internal controls (nonsteroidal antiinflammatory drugs [NSAIDs], naproxen) were determined by the mean changes from baseline in Western Ontario and McMaster Universities Osteoarthritis Index pain subscores as compared with placebo. The effect size for all coxib groups combined (0.44) indicated greater efficacy as compared with placebo, but significant heterogeneity (P < 0.0001) was observed. Rofecoxib at dosages of 12.5 mg/day and 25 mg/day and etoricoxib at a dosage of 60 mg/day had similar effect sizes (0.68 and 0.73, respectively), but these effect sizes were comparatively greater than those for both celecoxib at dosages of 200 mg/day and 100 mg twice daily or valdecoxib at a dosage of 10 mg/day (0.26 and 0.16, respectively). The effect sizes for NSAIDs or naproxen versus placebo, as determined using data from rofecoxib/etoricoxib trials, were consistently higher than the effect sizes derived from trials of celecoxib/valdecoxib. Significant heterogeneity was present in the overall effect size for NSAIDs (P = 0.007) and naproxen (P = 0.04) groups based on data available from all coxib trials. Coxibs and common active internal controls showed larger effect sizes versus placebo in the rofecoxib/etoricoxib trials than in the celecoxib/valdecoxib trials. These findings suggest systematic differences among published coxib trials and emphasize the need for direct-comparison trials. In the absence of such trials, common internal controls should be assessed when performing indirect meta-analytic comparisons.

Pilot and Repeat Trials as Development Tools Associated with Demonstration of Bioequivalence.

PubMed

Fuglsang, Anders

2015-05-01

The purpose of this work is to use simulated trials to study how pilot trials can be implemented in relation to bioequivalence testing, and how the use of the information obtained at the pilot stage can influence the overall chance of showing bioequivalence (power) or the chance of approving a truly bioinequivalent product (type I error). The work also covers the use of repeat pivotal trials since the difference between a pilot trial followed by a pivotal trial and a pivotal trial followed by a repeat trial is mainly a question of whether a conclusion of bioequivalence can be allowed after the first trial. Repeating a pivotal trial after a failed trial involves dual or serial testing of the bioequivalence null hypothesis, and the paper illustrates how this may inflate the type I error up to almost 10%. Hence, it is questioned if such practice is in the interest of patients. Tables for power, type I error, and sample sizes are provided for a total of six different decision trees which allow the developer to use either the observed geometric mean ratio (GMR) from the first or trial or to assume that the GMR is 0.95. In cases when the true GMR can be controlled so as not to deviate more from unity than 0.95, sequential design methods ad modum Potvin may be superior to pilot trials. The tables provide a quantitative basis for choosing between sequential designs and pivotal trials preceded by pilot trials.

Simulation program for estimating statistical power of Cox's proportional hazards model assuming no specific distribution for the survival time.

PubMed

Akazawa, K; Nakamura, T; Moriguchi, S; Shimada, M; Nose, Y

1991-07-01

Small sample properties of the maximum partial likelihood estimates for Cox's proportional hazards model depend on the sample size, the true values of regression coefficients, covariate structure, censoring pattern and possibly baseline hazard functions. Therefore, it would be difficult to construct a formula or table to calculate the exact power of a statistical test for the treatment effect in any specific clinical trial. The simulation program, written in SAS/IML, described in this paper uses Monte-Carlo methods to provide estimates of the exact power for Cox's proportional hazards model. For illustrative purposes, the program was applied to real data obtained from a clinical trial performed in Japan. Since the program does not assume any specific function for the baseline hazard, it is, in principle, applicable to any censored survival data as long as they follow Cox's proportional hazards model.

A Systematic Review of Herbal Medicine for Chemotherapy Induced Peripheral Neuropathy

PubMed Central

Noh, Hyeonseok

2018-01-01

Background Chemotherapy-induced peripheral neuropathy (CIPN) is a common adverse effect in cancer patients. The aim of this review was to assess the effectiveness of herbal medicine in preventing and treating CIPN. Methods Randomised controlled trials were included in this review. Extracting and assessing the data independently, two authors searched 13 databases. Results Twenty-eight trials involving 2174 patients met the inclusion criteria. Although there were some exceptions, the methodological quality was typically low. Seventeen trials reported the incidence rate of CIPN assessed by various tools and 14 showed a significant difference regarding the decrease of the incidence rate between the two groups. For clinical improvement, 12 trials reported it using various tools and 10 showed a significant difference between two groups. Two cases of adverse events occurred in one trial; the other nine trials reported no adverse events. Conclusions We found that herbal medicines in combination with and/or without other therapies potentially have preventive or therapeutic effects on CIPN. However, conclusions cannot be drawn because of the generally low quality of the methodology, the clinical heterogeneity, and the small sample size for each single herbal medicine. Trials that are more rigorous and report sufficient methodological data are needed. PMID:29636782

Recruitment of subjects for clinical trials after informed consent: does gender and educational status make a difference?

PubMed

Gitanjali, B; Raveendran, R; Pandian, D G; Sujindra, S

2003-01-01

Researchers and investigators have argued that getting fully informed written consent may not be possible in the developing countries where illiteracy is widespread. To determine the percentage of patients who agree to participate in a trial after receiving either complete or partial information regarding a trial and to find out whether there were gender or educational status-related differences. To assess reasons for consenting or refusing and their depth of understanding of informed consent. A simulated clinical trial in two tertiary health care facilities on in-patients. An informed consent form for a mock clinical trial of a drug was prepared. The detailed / partial procedure was explained to a purposive sample of selected in-patients and their consent was asked for. Patients were asked to free list the reasons for giving or withholding consent. Their depth of understanding was assessed using a questionnaire. Chi-square test was used for statistical analyses. The percentages of those consenting after full disclosure 29/102 (30%) and after partial disclosure 15/50 (30%) were the same. There was a significant (p=0.043) gender difference with a lesser percentage of females (30%) consenting to participation in a trial. Educational status did not alter this percentage. Most patients withheld consent because they did not want to give blood or take a new drug. Understanding of informed consent was poor in those who consented. The fact that only one-third of subjects are likely to give consent to participate in a trial needs to be considered while planning clinical trials with a large sample size. Gender but not educational status influences the number of subjects consenting for a study. Poor understanding of the elements of informed consent in patients necessitates evolving better methods of implementing consent procedures in India.

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

Simultaneous contrast: evidence from licking microstructure and cross-solution comparisons.

PubMed

Dwyer, Dominic M; Lydall, Emma S; Hayward, Andrew J

2011-04-01

The microstructure of rats' licking responses was analyzed to investigate both "classic" simultaneous contrast (e.g., Flaherty & Largen, 1975) and a novel discrete-trial contrast procedure where access to an 8% test solution of sucrose was preceded by a sample of either 2%, 8%, or 32% sucrose (Experiments 1 and 2, respectively). Consumption of a given concentration of sucrose was higher when consumed alongside a low rather than high concentration comparison solution (positive contrast) and consumption of a given concentration of sucrose was lower when consumed alongside a high rather than a low concentration comparison solution (negative contrast). Furthermore, positive contrast increased the size of lick clusters while negative contrast decreased the size of lick clusters. Lick cluster size has a positive monotonic relationship with the concentration of palatable solutions and so positive and negative contrasts produced changes in lick cluster size that were analogous to raising or lowering the concentration of the test solution respectively. Experiment 3 utilized the discrete-trial procedure and compared contrast between two solutions of the same type (sucrose-sucrose or maltodextrin-maltodextrin) or contrast across solutions (sucrose-maltodextrin or maltodextrin-sucrose). Contrast effects on consumption were present, but reduced in size, in the cross-solution conditions. Moreover, lick cluster sizes were not affected at all by cross-solution contrasts as they were by same-solution contrasts. These results are consistent with the idea that simultaneous contrast effects depend, at least partially, on sensory mechanisms.

Depression severity in electroconvulsive therapy (ECT) versus pharmacotherapy trials.

PubMed

Kellner, Charles H; Kaicher, David C; Banerjee, Hiya; Knapp, Rebecca G; Shapiro, Rachael J; Briggs, Mimi C; Pasculli, Rosa M; Popeo, Dennis M; Ahle, Gabriella M; Liebman, Lauren S

2015-03-01

We sought to compare the level of severity of depressive symptoms on entry into electroconvulsive therapy (ECT) clinical trials versus pharmacotherapy clinical trials. English-language MEDLINE/PubMed publication databases were searched for ECT literature (search terms: ECT, electroconvulsive therapy, depression, and Hamilton) for clinical trials in which depressed patients had baseline Hamilton Rating Scale for Depression (HRSD) scores. For comparison, we used a convenience sample of 7 large pharmacotherapy trials in major depression (N = 3677). The search included articles from 1960 to 2011. We included 100 studies that met the following criteria: ECT trial for depression, patients adequately characterized by diagnosis at baseline, and patients rated at baseline by 15-item HRSD (HRSD15), HRSD17, HRSD21, HRSD24, or HRSD28, with mean (SD) and sample size (n) reported. For the comparator pharmacotherapy trials, we chose to use a subset of the studies (excluding one study of minor depression) in the widely publicized meta-analysis of Fournier et al, as well as the STAR*D study and one additional study by Shelton et al. This provided 7 studies of major depression using HRSD17 (total N = 3677). Data extracted included number of subjects and baseline and final HRSD scores, with mean (SD) values. Of 100 ECT studies, 56 studies (N = 2243) used the HRSD17 version. The mean baseline HRSD17 score in the ECT trials was 27.6, the mean in the pharmacotherapy trials was 21.94, a statistically, and clinically, significant difference. In a subanalysis of the 16 ECT studies that used the HRSD24 version, the mean baseline score was 32.2. This selective literature review confirms that patients who entered ECT clinical trials were more severely ill than those who entered the selected comparator pharmacotherapy trials. Such data highlight the critical role of ECT in the treatment of severe and treatment-resistant mood disorders.

A practical Bayesian stepped wedge design for community-based cluster-randomized clinical trials: The British Columbia Telehealth Trial.

PubMed

Cunanan, Kristen M; Carlin, Bradley P; Peterson, Kevin A

2016-12-01

Many clinical trial designs are impractical for community-based clinical intervention trials. Stepped wedge trial designs provide practical advantages, but few descriptions exist of their clinical implementational features, statistical design efficiencies, and limitations. Enhance efficiency of stepped wedge trial designs by evaluating the impact of design characteristics on statistical power for the British Columbia Telehealth Trial. The British Columbia Telehealth Trial is a community-based, cluster-randomized, controlled clinical trial in rural and urban British Columbia. To determine the effect of an Internet-based telehealth intervention on healthcare utilization, 1000 subjects with an existing diagnosis of congestive heart failure or type 2 diabetes will be enrolled from 50 clinical practices. Hospital utilization is measured using a composite of disease-specific hospital admissions and emergency visits. The intervention comprises online telehealth data collection and counseling provided to support a disease-specific action plan developed by the primary care provider. The planned intervention is sequentially introduced across all participating practices. We adopt a fully Bayesian, Markov chain Monte Carlo-driven statistical approach, wherein we use simulation to determine the effect of cluster size, sample size, and crossover interval choice on type I error and power to evaluate differences in hospital utilization. For our Bayesian stepped wedge trial design, simulations suggest moderate decreases in power when crossover intervals from control to intervention are reduced from every 3 to 2 weeks, and dramatic decreases in power as the numbers of clusters decrease. Power and type I error performance were not notably affected by the addition of nonzero cluster effects or a temporal trend in hospitalization intensity. Stepped wedge trial designs that intervene in small clusters across longer periods can provide enhanced power to evaluate comparative effectiveness, while offering practical implementation advantages in geographic stratification, temporal change, use of existing data, and resource distribution. Current population estimates were used; however, models may not reflect actual event rates during the trial. In addition, temporal or spatial heterogeneity can bias treatment effect estimates. © The Author(s) 2016.

Viability of the World Health Organization quality of life measure to assess changes in quality of life following treatment for alcohol use disorder.

PubMed

Kirouac, Megan; Stein, Elizabeth R; Pearson, Matthew R; Witkiewitz, Katie

2017-11-01

Quality of life is an outcome often examined in treatment research contexts such as biomedical trials, but has been studied less often in alcohol use disorder (AUD) treatment. The importance of considering QoL in substance use treatment research has recently been voiced, and measures of QoL have been administered in large AUD treatment trials. Yet, the viability of popular QoL measures has never been evaluated in AUD treatment samples. Accordingly, the present manuscript describes a psychometric examination of and prospective changes in the World Health Organization Quality of Life measure (WHOQOL-BREF) in a large sample (N = 1383) of patients with AUD recruited for the COMBINE Study. Specifically, we examined the construct validity (via confirmatory factor analyses), measurement invariance across time, internal consistency reliability, convergent validity, and effect sizes of post-treatment changes in the WHOQOL-BREF. Confirmatory factor analyses of the WHOQOL-BREF provided acceptable fit to the current data and this model was invariant across time. Internal consistency reliability was excellent (α > .9) for the full WHOQOL-BREF for each timepoint; the WHOQOL-BREF had good convergent validity, and medium effect size improvements were found in the full COMBINE sample across time. These findings suggest that the WHOQOL-BREF is an appropriate measure to use in samples with AUD, that the WHOQOL-BREF scores may be examined over time (e.g., from pre- to post-treatment), and the WHOQOL-BREF may be used to assess improvements in quality of life in AUD research.

Enhancing pediatric clinical trial feasibility through the use of Bayesian statistics.

PubMed

Huff, Robin A; Maca, Jeff D; Puri, Mala; Seltzer, Earl W

2017-11-01

BackgroundPediatric clinical trials commonly experience recruitment challenges including limited number of patients and investigators, inclusion/exclusion criteria that further reduce the patient pool, and a competitive research landscape created by pediatric regulatory commitments. To overcome these challenges, innovative approaches are needed.MethodsThis article explores the use of Bayesian statistics to improve pediatric trial feasibility, using pediatric Type-2 diabetes as an example. Data for six therapies approved for adults were used to perform simulations to determine the impact on pediatric trial size.ResultsWhen the number of adult patients contributing to the simulation was assumed to be the same as the number of patients to be enrolled in the pediatric trial, the pediatric trial size was reduced by 75-78% when compared with a frequentist statistical approach, but was associated with a 34-45% false-positive rate. In subsequent simulations, greater control was exerted over the false-positive rate by decreasing the contribution of the adult data. A 30-33% reduction in trial size was achieved when false-positives were held to less than 10%.ConclusionReducing the trial size through the use of Bayesian statistics would facilitate completion of pediatric trials, enabling drugs to be labeled appropriately for children.

Effect of Study Design on Sample Size in Studies Intended to Evaluate Bioequivalence of Inhaled Short‐Acting β‐Agonist Formulations

PubMed Central

Zeng, Yaohui; Singh, Sachinkumar; Wang, Kai

2017-01-01

Abstract Pharmacodynamic studies that use methacholine challenge to assess bioequivalence of generic and innovator albuterol formulations are generally designed per published Food and Drug Administration guidance, with 3 reference doses and 1 test dose (3‐by‐1 design). These studies are challenging and expensive to conduct, typically requiring large sample sizes. We proposed 14 modified study designs as alternatives to the Food and Drug Administration–recommended 3‐by‐1 design, hypothesizing that adding reference and/or test doses would reduce sample size and cost. We used Monte Carlo simulation to estimate sample size. Simulation inputs were selected based on published studies and our own experience with this type of trial. We also estimated effects of these modified study designs on study cost. Most of these altered designs reduced sample size and cost relative to the 3‐by‐1 design, some decreasing cost by more than 40%. The most effective single study dose to add was 180 μg of test formulation, which resulted in an estimated 30% relative cost reduction. Adding a single test dose of 90 μg was less effective, producing only a 13% cost reduction. Adding a lone reference dose of either 180, 270, or 360 μg yielded little benefit (less than 10% cost reduction), whereas adding 720 μg resulted in a 19% cost reduction. Of the 14 study design modifications we evaluated, the most effective was addition of both a 90‐μg test dose and a 720‐μg reference dose (42% cost reduction). Combining a 180‐μg test dose and a 720‐μg reference dose produced an estimated 36% cost reduction. PMID:29281130

Planning multi-arm screening studies within the context of a drug development program

PubMed Central

Wason, James M S; Jaki, Thomas; Stallard, Nigel

2013-01-01

Screening trials are small trials used to decide whether an intervention is sufficiently promising to warrant a large confirmatory trial. Previous literature examined the situation where treatments are tested sequentially until one is considered sufficiently promising to take forward to a confirmatory trial. An important consideration for sponsors of clinical trials is how screening trials should be planned to maximize the efficiency of the drug development process. It has been found previously that small screening trials are generally the most efficient. In this paper we consider the design of screening trials in which multiple new treatments are tested simultaneously. We derive analytic formulae for the expected number of patients until a successful treatment is found, and propose methodology to search for the optimal number of treatments, and optimal sample size per treatment. We compare designs in which only the best treatment proceeds to a confirmatory trial and designs in which multiple treatments may proceed to a multi-arm confirmatory trial. We find that inclusion of a large number of treatments in the screening trial is optimal when only one treatment can proceed, and a smaller number of treatments is optimal when more than one can proceed. The designs we investigate are compared on a real-life set of screening designs. Copyright © 2013 John Wiley & Sons, Ltd. PMID:23529936

Perioperative antibiotics for prevention of acute endophthalmitis after cataract surgery

PubMed Central

Gower, Emily W; Lindsley, Kristina; Nanji, Afshan A; Leyngold, Ilya; McDonnell, Peter J

2014-01-01

Background Endophthalmitis is a severe inflammation of the anterior and/or posterior chambers of the eye that may be sterile or associated with infection. It is a potentially vision-threatening complication of cataract surgery. Prophylactic measures for endophthalmitis are targeted against various sources of infection. Objectives The objective of this review was to evaluate the effects of perioperative antibiotic prophylaxis for endophthalmitis following cataract surgery. Search methods We searched CENTRAL (which contains the Cochrane Eyes and Vision Group Trials Register) (The Cochrane Library 2012, Issue 10), Ovid MEDLINE, Ovid MEDLINE In-Process and Other Non-Indexed Citations, Ovid MEDLINE Daily, Ovid OLDMEDLINE, (January 1950 to October 2012), EMBASE (January 1980 to October 2012), Latin American and Caribbean Literature on Health Sciences (LILACS) (January 1982 to October 2012), the metaRegister of Controlled Trials (mRCT) (www.controlled-trials.com), ClinicalTrials.gov (www.clinicaltrials.gov) and the WHO International Clinical Trials Registry Platform (ICTRP) (www.who.int/ictrp/search/en). We did not use any date or language restrictions in the electronic searches for trials. We last searched the electronic databases on 25 October 2012. We also searched for additional studies that cited any included trials using the Science Citation Index. Selection criteria We included randomized controlled trials that enrolled adults undergoing cataract surgery (any method and incision type) for lens opacities due to any origin. Trials that evaluated preoperative antibiotics, intraoperative (intracameral, subconjunctival or systemic) or postoperative antibiotic prophylaxis for acute endophthalmitis were included. We did not include studies that evaluated antiseptic preoperative preparations using agents such as povidone iodine, nor did we include studies that evaluated antibiotics for treating acute endophthalmitis after cataract surgery. Data collection and analysis Two review authors independently reviewed abstracts and full-text articles for eligibility, assessed the risk of bias for each included study, and abstracted data. Main results Four studies met the inclusion criteria for this review, including 100,876 adults and 131 endophthalmitis cases. While the sample size is very large, the heterogeneity of the study designs and modes of antibiotic delivery made it impossible to conduct a formal meta-analysis. Interventions investigated in the studies included the utility of adding vancomycin and gentamycin to the irrigating solution compared with standard balanced saline solution irrigation alone, use of intracameral cefuroxime and/or topical levofloxacin perioperatively, periocular penicillin injections and topical chloramphenicol-sulphadimidine drops compared with topical antibiotics alone, and mode of antibiotic delivery (subconjunctival versus retrobulbar injections). Two studies with adequate sample sizes to evaluate a rare outcome found reduced risk of endophthalmitis with antibiotic injections during surgery compared with topical antibiotics alone: risk ratio (RR) 0.33, 95% confidence interval (CI) 0.12 to 0.92 (periocular penicillin versus topical chloramphenicol-sulphadimidine) and RR 0.21, 95% CI 0.06 to 0.74 (intracameral cefuroxime versus topical levofloxacin). Another study found no significant difference in endophthalmitis when comparing subconjunctival versus retrobulbar antibiotic injections (RR 0.85, 95% CI 0.55 to 1.32). The fourth study which compared irrigation with balanced salt solution (BSS) alone versus BSS with antibiotics was not sufficiently powered to detect differences in endophthalmitis between groups. The risk of bias among studies was low to unclear due to information not being reported. Authors' conclusions Multiple measures for preventing endophthalmitis following cataract surgery have been studied. One of the included studies, the ESCRS (European Society of Cataract and Refractive Surgeons) study, was performed using contemporary surgical technique and employed cefuroxime, an antibiotic commonly used in many parts of the world. Clinical trials with rare outcomes require very large sample sizes and are quite costly to conduct; thus, it is unlikely that additional clinical trials will be conducted to evaluate currently available prophylaxis. Practitioners should rely on current evidence to make informed decisions regarding prophylaxis choices. PMID:23857416

B-cell-targeted therapies in systemic lupus erythematosus and ANCA-associated vasculitis: current progress.

PubMed

Md Yusof, Md Yuzaiful; Vital, Edward M J; Emery, Paul

2013-08-01

B cells play a central role in the pathogenesis of systemic lupus erythematosus and anti-neutrophil cytoplasmic antibody-associated vasculitis. There are various strategies for targeting B cells including depletion, inhibition of survival factors, activation and inhibition of co-stimulatory molecules. Controlled trials in systemic lupus erythematosus have shown positive results for belimumab, promising results for epratuzumab and negative results for rituximab. The failure of rituximab in controlled trials has been attributed to trial design, sample size and outcome measures rather than true inefficacy. In anti-neutrophil cytoplasmic antibody-associated vasculitis, rituximab is effective for remission induction and in relapsing disease. However, the optimal long-term re-treatment strategy remains to be determined. Over the next 5 years, evidence will be available regarding the clinical efficacy of these novel therapies, biomarkers and their long-term safety.

Conditional analysis of mixed Poisson processes with baseline counts: implications for trial design and analysis.

PubMed

Cook, Richard J; Wei, Wei

2003-07-01

The design of clinical trials is typically based on marginal comparisons of a primary response under two or more treatments. The considerable gains in efficiency afforded by models conditional on one or more baseline responses has been extensively studied for Gaussian models. The purpose of this article is to present methods for the design and analysis of clinical trials in which the response is a count or a point process, and a corresponding baseline count is available prior to randomization. The methods are based on a conditional negative binomial model for the response given the baseline count and can be used to examine the effect of introducing selection criteria on power and sample size requirements. We show that designs based on this approach are more efficient than those proposed by McMahon et al. (1994).

Impact of Probiotics on Necrotizing Enterocolitis

PubMed Central

Underwood, Mark A.

2016-01-01

A large number of randomized placebo-controlled clinical trials and cohort studies have demonstrated a decrease in the incidence of necrotizing enterocolitis with administration of probiotic microbes. These studies have prompted many neonatologists to adopt routine prophylactic administration of probiotics while others await more definitive studies and/or probiotic products with demonstrated purity and stable numbers of live organisms. Cross-contamination and inadequate sample size limit the value of further traditional placebo-controlled randomized controlled trials. Key areas for future research include mechanisms of protection, optimum probiotic species or strains (or combinations thereof) and duration of treatment, interactions between diet and the administered probiotic, and the influence of genetic polymorphisms in the mother and infant on probiotic response. Next generation probiotics selected based on bacterial genetics rather than ease of production and large cluster-randomized clinical trials hold great promise for NEC prevention. PMID:27836423

A new sampler design for measuring sedimentation in streams

USGS Publications Warehouse

Hedrick, Lara B.; Welsh, S.A.; Hedrick, J.D.

2005-01-01

Sedimentation alters aquatic habitats and negatively affects fish and invertebrate communities but is difficult to quantify. To monitor bed load sedimentation, we designed a sampler with a 10.16-cm polyvinyl chloride coupling and removable sediment trap. We conducted a trial study of our samplers in riffle and pool habitats upstream and downstream of highway construction on a first-order Appalachian stream. Sediment samples were collected over three 6-week intervals, dried, and separated into five size-classes by means of nested sieves (U.S. standard sieve numbers 4, 8, 14, and 20). Downstream sediment accumulated in size-classes 1 and 2, and the total amount accumulated was significantly greater during all three sampling periods. Size-classes 3 and 4 had significantly greater amounts of sediment for the first two sampling periods at the downstream site. Differences between upstream and downstream sites narrowed during the 5-month sampling period. This probably reflects changes in site conditions, including the addition of more effective sediment control measures after the first 6-week period of the study. The sediment sampler design allowed for long-term placement of traps without continual disturbance of the streambed and was successful at providing repeat measures of sediment at paired sites. ?? Copyright by the American Fisheries Society 2005.

Internet-Based, Culturally Sensitive, Problem-Solving Therapy for Turkish Migrants With Depression: Randomized Controlled Trial

PubMed Central

van 't Hof, Edith; van Ballegooijen, Wouter; Christensen, Helen; Riper, Heleen

2013-01-01

Background Turkish migrants living in the Netherlands have a high prevalence of depressive disorders, but experience considerable obstacles to accessing professional help. Providing easily accessible Internet treatments may help to overcome these barriers. Objective The aim of this study was to evaluate the effectiveness of a culturally sensitive, guided, self-help, problem-solving intervention through the Internet for reducing depressive symptoms in Turkish migrants. Methods A two-armed randomized controlled trial was conducted. The primary outcome measure was the severity of depressive symptoms; secondary outcome measures were somatic symptoms, anxiety, quality of life, and satisfaction with the treatment. Participants were assessed online at baseline, posttest (6 weeks after baseline), and 4 months after baseline. Posttest results were analyzed on the intention-to-treat sample. Missing values were estimated by means of multiple imputation. Differences in clinical outcome between groups were analyzed with a t test. Cohen’s d was used to determine the between-groups effect size at posttreatment and follow-up. Results Turkish adults (N=96) with depressive symptoms were randomized to the experimental group (n=49) or to a waitlist control group (n=47). High attrition rates were found among the 96 participants of which 42% (40/96) did not complete the posttest (6 weeks) and 62% (59/96) participants did not complete the follow-up assessment at 4 months. No significant difference between the experimental group and the control group was found for depression at posttest. Recovery occurred significantly more often in the experimental group (33%, 16/49) than in the control group (9%, 4/47) at posttest (P=.02). Because of the high attrition rate, a completers-only analysis was conducted at follow-up. The experimental group showed significant improvement in depression compared to the control group both at posttest (P=.01) and follow-up (P=.01). Conclusions The results of this study did not show a significant effect on the reduction of depressive symptoms. However, the effect size at posttest was high, which might be an indicator of the possible effectiveness of the intervention when assessed in a larger sample and robust trial. Future research should replicate our study with adequately powered samples. Trial Registration Dutch Trial Register: NTR2303. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2303 (Archived by WebCite at http://www.webcitation.org/6IOxNgoDu). PMID:24121307

Use of Bayesian Decision Analysis to Minimize Harm in Patient-Centered Randomized Clinical Trials in Oncology.

PubMed

Montazerhodjat, Vahid; Chaudhuri, Shomesh E; Sargent, Daniel J; Lo, Andrew W

2017-09-14

Randomized clinical trials (RCTs) currently apply the same statistical threshold of alpha = 2.5% for controlling for false-positive results or type 1 error, regardless of the burden of disease or patient preferences. Is there an objective and systematic framework for designing RCTs that incorporates these considerations on a case-by-case basis? To apply Bayesian decision analysis (BDA) to cancer therapeutics to choose an alpha and sample size that minimize the potential harm to current and future patients under both null and alternative hypotheses. We used the National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) database and data from the 10 clinical trials of the Alliance for Clinical Trials in Oncology. The NCI SEER database was used because it is the most comprehensive cancer database in the United States. The Alliance trial data was used owing to the quality and breadth of data, and because of the expertise in these trials of one of us (D.J.S.). The NCI SEER and Alliance data have already been thoroughly vetted. Computations were replicated independently by 2 coauthors and reviewed by all coauthors. Our prior hypothesis was that an alpha of 2.5% would not minimize the overall expected harm to current and future patients for the most deadly cancers, and that a less conservative alpha may be necessary. Our primary study outcomes involve measuring the potential harm to patients under both null and alternative hypotheses using NCI and Alliance data, and then computing BDA-optimal type 1 error rates and sample sizes for oncology RCTs. We computed BDA-optimal parameters for the 23 most common cancer sites using NCI data, and for the 10 Alliance clinical trials. For RCTs involving therapies for cancers with short survival times, no existing treatments, and low prevalence, the BDA-optimal type 1 error rates were much higher than the traditional 2.5%. For cancers with longer survival times, existing treatments, and high prevalence, the corresponding BDA-optimal error rates were much lower, in some cases even lower than 2.5%. Bayesian decision analysis is a systematic, objective, transparent, and repeatable process for deciding the outcomes of RCTs that explicitly incorporates burden of disease and patient preferences.

The BRAIN TRIAL: a randomised, placebo controlled trial of a Bradykinin B2 receptor antagonist (Anatibant) in patients with traumatic brain injury.

PubMed

Shakur, Haleema; Andrews, Peter; Asser, Toomas; Balica, Laura; Boeriu, Cristian; Quintero, Juan Diego Ciro; Dewan, Yashbir; Druwé, Patrick; Fletcher, Olivia; Frost, Chris; Hartzenberg, Bennie; Mantilla, Jorge Mejia; Murillo-Cabezas, Francisco; Pachl, Jan; Ravi, Ramalingam R; Rätsep, Indrek; Sampaio, Cristina; Singh, Manmohan; Svoboda, Petr; Roberts, Ian

2009-12-03

Cerebral oedema is associated with significant neurological damage in patients with traumatic brain injury. Bradykinin is an inflammatory mediator that may contribute to cerebral oedema by increasing the permeability of the blood-brain barrier. We evaluated the safety and effectiveness of the non-peptide bradykinin B2 receptor antagonist Anatibant in the treatment of patients with traumatic brain injury. During the course of the trial, funding was withdrawn by the sponsor. Adults with traumatic brain injury and a Glasgow Coma Scale score of 12 or less, who had a CT scan showing an intracranial abnormality consistent with trauma, and were within eight hours of their injury were randomly allocated to low, medium or high dose Anatibant or to placebo. Outcomes were Serious Adverse Events (SAE), mortality 15 days following injury and in-hospital morbidity assessed by the Glasgow Coma Scale (GCS), the Disability Rating Scale (DRS) and a modified version of the Oxford Handicap Scale (HIREOS). 228 patients out of a planned sample size of 400 patients were randomised. The risk of experiencing one or more SAEs was 26.4% (43/163) in the combined Anatibant treated group, compared to 19.3% (11/57) in the placebo group (relative risk = 1.37; 95% CI 0.76 to 2.46). All cause mortality in the Anatibant treated group was 19% and in the placebo group 15.8% (relative risk 1.20, 95% CI 0.61 to 2.36). The mean GCS at discharge was 12.48 in the Anatibant treated group and 13.0 in the placebo group. Mean DRS was 11.18 Anatibant versus 9.73 placebo, and mean HIREOS was 3.94 Anatibant versus 3.54 placebo. The differences between the mean levels for GCS, DRS and HIREOS in the Anatibant and placebo groups, when adjusted for baseline GCS, showed a non-significant trend for worse outcomes in all three measures. This trial did not reach the planned sample size of 400 patients and consequently, the study power to detect an increase in the risk of serious adverse events was reduced. This trial provides no reliable evidence of benefit or harm and a larger trial would be needed to establish safety and effectiveness. This study is registered as an International Standard Randomised Controlled Trial, number ISRCTN23625128.

Use of Bayesian Decision Analysis to Minimize Harm in Patient-Centered Randomized Clinical Trials in Oncology

PubMed Central

Montazerhodjat, Vahid; Chaudhuri, Shomesh E.; Sargent, Daniel J.

2017-01-01

Importance Randomized clinical trials (RCTs) currently apply the same statistical threshold of alpha = 2.5% for controlling for false-positive results or type 1 error, regardless of the burden of disease or patient preferences. Is there an objective and systematic framework for designing RCTs that incorporates these considerations on a case-by-case basis? Objective To apply Bayesian decision analysis (BDA) to cancer therapeutics to choose an alpha and sample size that minimize the potential harm to current and future patients under both null and alternative hypotheses. Data Sources We used the National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) database and data from the 10 clinical trials of the Alliance for Clinical Trials in Oncology. Study Selection The NCI SEER database was used because it is the most comprehensive cancer database in the United States. The Alliance trial data was used owing to the quality and breadth of data, and because of the expertise in these trials of one of us (D.J.S.). Data Extraction and Synthesis The NCI SEER and Alliance data have already been thoroughly vetted. Computations were replicated independently by 2 coauthors and reviewed by all coauthors. Main Outcomes and Measures Our prior hypothesis was that an alpha of 2.5% would not minimize the overall expected harm to current and future patients for the most deadly cancers, and that a less conservative alpha may be necessary. Our primary study outcomes involve measuring the potential harm to patients under both null and alternative hypotheses using NCI and Alliance data, and then computing BDA-optimal type 1 error rates and sample sizes for oncology RCTs. Results We computed BDA-optimal parameters for the 23 most common cancer sites using NCI data, and for the 10 Alliance clinical trials. For RCTs involving therapies for cancers with short survival times, no existing treatments, and low prevalence, the BDA-optimal type 1 error rates were much higher than the traditional 2.5%. For cancers with longer survival times, existing treatments, and high prevalence, the corresponding BDA-optimal error rates were much lower, in some cases even lower than 2.5%. Conclusions and Relevance Bayesian decision analysis is a systematic, objective, transparent, and repeatable process for deciding the outcomes of RCTs that explicitly incorporates burden of disease and patient preferences. PMID:28418507

Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis.

PubMed

Cervera, María A; Soekadar, Surjo R; Ushiba, Junichi; Millán, José Del R; Liu, Meigen; Birbaumer, Niels; Garipelli, Gangadhar

2018-05-01

Brain-computer interfaces (BCIs) can provide sensory feedback of ongoing brain oscillations, enabling stroke survivors to modulate their sensorimotor rhythms purposefully. A number of recent clinical studies indicate that repeated use of such BCIs might trigger neurological recovery and hence improvement in motor function. Here, we provide a first meta-analysis evaluating the clinical effectiveness of BCI-based post-stroke motor rehabilitation. Trials were identified using MEDLINE, CENTRAL, PEDro and by inspection of references in several review articles. We selected randomized controlled trials that used BCIs for post-stroke motor rehabilitation and provided motor impairment scores before and after the intervention. A random-effects inverse variance method was used to calculate the summary effect size. We initially identified 524 articles and, after removing duplicates, we screened titles and abstracts of 473 articles. We found 26 articles corresponding to BCI clinical trials, of these, there were nine studies that involved a total of 235 post-stroke survivors that fulfilled the inclusion criterion (randomized controlled trials that examined motor performance as an outcome measure) for the meta-analysis. Motor improvements, mostly quantified by the upper limb Fugl-Meyer Assessment (FMA-UE), exceeded the minimal clinically important difference (MCID=5.25) in six BCI studies, while such improvement was reached only in three control groups. Overall, the BCI training was associated with a standardized mean difference of 0.79 (95% CI: 0.37 to 1.20) in FMA-UE compared to control conditions, which is in the range of medium to large summary effect size. In addition, several studies indicated BCI-induced functional and structural neuroplasticity at a subclinical level. This suggests that BCI technology could be an effective intervention for post-stroke upper limb rehabilitation. However, more studies with larger sample size are required to increase the reliability of these results.

Interactive video gaming compared with health education in older adults with mild cognitive impairment: a feasibility study.

PubMed

Hughes, Tiffany F; Flatt, Jason D; Fu, Bo; Butters, Meryl A; Chang, Chung-Chou H; Ganguli, Mary

2014-09-01

We evaluated the feasibility of a trial of Wii interactive video gaming, and its potential efficacy at improving cognitive functioning compared with health education, in a community sample of older adults with neuropsychologically defined mild cognitive impairment. Twenty older adults were equally randomized to either group-based interactive video gaming or health education for 90 min each week for 24 weeks. Although the primary outcomes were related to study feasibility, we also explored the effect of the intervention on neuropsychological performance and other secondary outcomes. All 20 participants completed the intervention, and 18 attended at least 80% of the sessions. The majority (80%) of participants were "very much" satisfied with the intervention. Bowling was enjoyed by the most participants and was also rated the highest among the games for mental, social, and physical stimulation. We observed medium effect sizes for cognitive and physical functioning in favor of the interactive video gaming condition, but these effects were not statistically significant in this small sample. Interactive video gaming is feasible for older adults with mild cognitive impairment, and medium effect sizes in favor of the Wii group warrant a larger efficacy trial. Copyright © 2014 John Wiley & Sons, Ltd.

Quantitative comparison of randomization designs in sequential clinical trials based on treatment balance and allocation randomness.

PubMed

Zhao, Wenle; Weng, Yanqiu; Wu, Qi; Palesch, Yuko

2012-01-01

To evaluate the performance of randomization designs under various parameter settings and trial sample sizes, and identify optimal designs with respect to both treatment imbalance and allocation randomness, we evaluate 260 design scenarios from 14 randomization designs under 15 sample sizes range from 10 to 300, using three measures for imbalance and three measures for randomness. The maximum absolute imbalance and the correct guess (CG) probability are selected to assess the trade-off performance of each randomization design. As measured by the maximum absolute imbalance and the CG probability, we found that performances of the 14 randomization designs are located in a closed region with the upper boundary (worst case) given by Efron's biased coin design (BCD) and the lower boundary (best case) from the Soares and Wu's big stick design (BSD). Designs close to the lower boundary provide a smaller imbalance and a higher randomness than designs close to the upper boundary. Our research suggested that optimization of randomization design is possible based on quantified evaluation of imbalance and randomness. Based on the maximum imbalance and CG probability, the BSD, Chen's biased coin design with imbalance tolerance method, and Chen's Ehrenfest urn design perform better than popularly used permuted block design, EBCD, and Wei's urn design. Copyright © 2011 John Wiley & Sons, Ltd.

Rationale and design of the IMPACT EU-trial: improve management of heart failure with procalcitonin biomarkers in cardiology (BIC)-18.

PubMed

Möckel, Martin; Slagman, Anna; Vollert, Jörn Ole; Ebmeyer, Stefan; Wiemer, Jan C; Searle, Julia; Giannitsis, Evangelos; Kellum, John A; Maisel, Alan

2018-02-01

To evaluate the effectiveness of procalcitonin (PCT)-guided antibiotic treatment compared to current treatment practice to reduce 90-day all-cause mortality in emergency patients with shortness of breath (SOB) and suspected acute heart failure (AHF). Concomitant AHF and lower respiratory tract (or other bacterial) infection in emergency patients with dyspnea are common and can be difficult to diagnose. Early and adequate initiation of antibiotic therapy (ABX) significantly improves patient outcome, but superfluous prescription of ABX maybe harmful. In a multicentre, prospective, randomized, controlled process trial with an open intervention, adult emergency patients with SOB and increased levels of natriuretic peptides will be randomized to either a standard care group or a PCT-guided group with respect to the initiation of antibiotic treatment. In the PCT-guided group, the initiation of antibiotic therapy is based on the results of acute PCT measurements at admission, using a cut-off of 0.2 ng/ml. A two-stage sample-size adaptive design is used; an interim analysis was done after completion of 50% of patients and the final sample size remained unchanged. Primary endpoint is 90-day all-cause mortality. The current study will provide evidence, whether the routine use of PCT in patients with suspected AHF improves outcome.

Testing Pneumonia Vaccines in the Elderly: Determining a Case Definition for Pneumococcal Pneumonia in the Absence of a Gold Standard.

PubMed

Jokinen, Jukka; Snellman, Marja; Palmu, Arto A; Saukkoriipi, Annika; Verlant, Vincent; Pascal, Thierry; Devaster, Jeanne-Marie; Hausdorff, William P; Kilpi, Terhi M

2018-06-01

Clinical assessments of vaccines to prevent pneumococcal community-acquired pneumonia (CAP) require sensitive and specific case definitions, but there is no gold standard diagnostic test. To develop a new case definition suitable for vaccine efficacy studies, we applied latent class analysis (LCA) to the results from 7 diagnostic tests for pneumococcal etiology on clinical specimens from 323 elderly persons with radiologically confirmed pneumonia enrolled in the Finnish Community-Acquired Pneumonia Epidemiology study during 2005-2007. Compared with the conventional use of LCA, which is mainly to determine sensitivities and specificities of different tests, we instead used LCA as an appropriate instrument to predict the probability of pneumococcal etiology for each CAP case based on individual test profiles, and we used the predictions to minimize the sample size that would be needed for a vaccine efficacy trial. When compared with the conventional laboratory criteria of encapsulated pneumococci in culture, in blood culture or high-quality sputum culture, or urine antigen positivity, our optimized case definition for pneumococcal CAP resulted in a trial sample size that was almost 20,000 subjects smaller. We believe that the novel application of LCA detailed here to determine a case definition for pneumococcal CAP could also be similarly applied to other diseases without a gold standard.

Update on the effects of graded motor imagery and mirror therapy on complex regional pain syndrome type 1: A systematic review.

PubMed

Méndez-Rebolledo, Guillermo; Gatica-Rojas, Valeska; Torres-Cueco, Rafael; Albornoz-Verdugo, María; Guzmán-Muñoz, Eduardo

2017-01-01

Graded motor imagery (GMI) and mirror therapy (MT) is thought to improve pain in patients with complex regional pain syndrome (CRPS) types 1 and 2. However, the evidence is limited and analysis are not independent between types of CRPS. The purpose of this review was to analyze the effects of GMI and MT on pain in independent groups of patients with CRPS types 1 and 2. Searches for literature published between 1990 and 2016 were conducted in databases. Randomized controlled trials that compared GMI or MT with other treatments for CRPS types 1 and 2 were included. Six articles met the inclusion criteria and were classified from moderate to high quality. The total sample was composed of 171 participants with CRPS type 1. Three studies presented GMI with 3 components and three studies only used the MT. The studies were heterogeneous in terms of sample size and the disorders that triggered CRPS type 1. There were no trials that included participants with CRPS type 2. GMI and MT can improve pain in patients with CRPS type 1; however, there is not sufficient evidence to recommend these therapies over other treatments given the small size and heterogeneity of the studied population.

Systematic review with network meta-analysis: the efficacy of anti-tumour necrosis factor-alpha agents for the treatment of ulcerative colitis.

PubMed

Stidham, R W; Lee, T C H; Higgins, P D R; Deshpande, A R; Sussman, D A; Singal, A G; Elmunzer, B J; Saini, S D; Vijan, S; Waljee, A K

2014-04-01

Antibodies against tumour necrosis factor-alpha (anti-TNF) are effective therapies in the treatment of ulcerative colitis (UC), but their comparative efficacy is unknown. To perform a network meta-analysis comparing the efficacy of anti-TNF agents in UC. After screening 506 studies, reviewers extracted information on seven studies. Traditional meta-analysis (TMA) was used to compare each anti-TNF agent to placebo. Bayesian network meta-analysis (NMA) was performed to compare the effects of anti-TNF agents to placebo. In addition, sample sizes for comparative efficacy trials were calculated. Compared to placebo, TMA revealed that anti-TNF agents result in a higher likelihood of induction of remission and response (RR: 2.45, 95% CI: 1.72-3.47 and RR: 1.65, 95% CI: 1.37-1.99 respectively) as well as maintenance of remission and response (RR: 2.00, 95% CI: 1.52-2.62 and RR: 1.76, 95% CI: 1.46-2.14 respectively). Individually, infliximab, adalimumab and goliumumab resulted in a higher likelihood of induction and maintenance for both remission and response. NMA found nonsignificant trends in comparisons of the individual agents. The required sample sizes for direct head-to-head trials between infliximab and adalimumab for induction and maintenance are 174 and 204 subjects respectively. This study demonstrates that, compared to placebo, infliximab, adalimumab and golimumab are all effective for the induction and maintenance of remission in ulcerative colitis. However, network meta-analysis demonstrates that no single agent is clinically superior to the others and therefore, other factors such as cost, safety, route of administration and patient preference should dictate our choice of anti-TNF agents. A randomised comparative efficacy trial between infliximab and adalimumab in UC is of practical size and should be performed. © 2014 John Wiley & Sons Ltd.

Journal impact factor and methodological quality of surgical randomized controlled trials: an empirical study.

PubMed

Ahmed Ali, Usama; Reiber, Beata M M; Ten Hove, Joren R; van der Sluis, Pieter C; Gooszen, Hein G; Boermeester, Marja A; Besselink, Marc G

2017-11-01

The journal impact factor (IF) is often used as a surrogate marker for methodological quality. The objective of this study is to evaluate the relation between the journal IF and methodological quality of surgical randomized controlled trials (RCTs). Surgical RCTs published in PubMed in 1999 and 2009 were identified. According to IF, RCTs were divided into groups of low (<2), median (2-3) and high IF (>3), as well as into top-10 vs all other journals. Methodological quality characteristics and factors concerning funding, ethical approval and statistical significance of outcomes were extracted and compared between the IF groups. Additionally, a multivariate regression was performed. The median IF was 2.2 (IQR 2.37). The percentage of 'low-risk of bias' RCTs was 13% for top-10 journals vs 4% for other journals in 1999 (P < 0.02), and 30 vs 12% in 2009 (P < 0.02). Similar results were observed for high vs low IF groups. The presence of sample-size calculation, adequate generation of allocation and intention-to-treat analysis were independently associated with publication in higher IF journals; as were multicentre trials and multiple authors. Publication of RCTs in high IF journals is associated with moderate improvement in methodological quality compared to RCTs published in lower IF journals. RCTs with adequate sample-size calculation, generation of allocation or intention-to-treat analysis were associated with publication in a high IF journal. On the other hand, reporting a statistically significant outcome and being industry funded were not independently associated with publication in a higher IF journal.

Hypolipidemic, Antioxidant and Antiinflammatory Activities of Microalgae Spirulina

PubMed Central

Deng, Ruitang; Chow, Te-Jin

2010-01-01

Spirulina is free-floating filamentous microalgae growing in alkaline water bodies. With its high nutritional value, Spirulina has been consumed as food for centuries in Central Africa. It is now widely used as nutraceutical food supplement worldwide. Recently, great attention and extensive studies have been devoted to evaluate its therapeutic benefits on an array of diseased conditions including hypercholesterolemia, hyperglycerolemia, cardiovascular diseases, inflammatory diseases, cancer and viral infections. The cardiovascular benefits of Spirulina are primarily resulted from its hypolipidemic, antioxidant and antiinflammatory activities. Data from preclinical studies with various animal models consistently demonstrate the hypolipidemic activity of Spirulina. Although differences in study design, sample size and patient conditions resulting in minor inconsistency in response to Spirulina supplementation, the findings from human clinical trials are largely consistent with the hypolipidemic effects of Spirulina observed in the preclinical studies. However, most of the human clinical trials are suffered with limited sample size and some with poor experimental design. The antioxidant and/or antiinflammatory activities of Spirulina were demonstrated in a large number of preclinical studies. However, a limited number of clinical trials have been carried out so far to confirm such activities in human. Currently, our understanding on the underlying mechanisms for Spirulina’s activities, especially the hypolipidemic effect, is limited. Spirulina is generally considered safe for human consumption supported by its long history of use as food source and its favorable safety profile in animal studies. However, rare cases of side-effects in human have been reported. Quality control in the growth and process of Spirulina to avoid contamination is mandatory to guarantee the safety of Spirulina products. PMID:20633020

Systematic review on randomized controlled clinical trials of acupuncture therapy for neurovascular headache.

PubMed

Zhao, Lei; Guo, Yi; Wang, Wei; Yan, Li-juan

2011-08-01

To evaluate the effectiveness of acupuncture as a treatment for neurovascular headache and to analyze the current situation related to acupuncture treatment. PubMed database (1966-2010), EMBASE database (1986-2010), Cochrane Library (Issue 1, 2010), Chinese Biomedical Literature Database (1979-2010), China HowNet Knowledge Database (1979-2010), VIP Journals Database (1989-2010), and Wanfang database (1998-2010) were retrieved. Randomized or quasi-randomized controlled studies were included. The priority was given to high-quality randomized, controlled trials. Statistical outcome indicators were measured using RevMan 5.0.20 software. A total of 16 articles and 1 535 cases were included. Meta-analysis showed a significant difference between the acupuncture therapy and Western medicine therapy [combined RR (random efficacy model)=1.46, 95% CI (1.21, 1.75), Z=3.96, P<0.0001], indicating an obvious superior effect of the acupuncture therapy; significant difference also existed between the comprehensive acupuncture therapy and acupuncture therapy alone [combined RR (fixed efficacy model)=3.35, 95% CI (1.92, 5.82), Z=4.28, P<0.0001], indicating that acupuncture combined with other therapies, such as points injection, scalp acupuncture, auricular acupuncture, etc., were superior to the conventional body acupuncture therapy alone. The inclusion of limited clinical studies had verified the efficacy of acupuncture in the treatment of neurovascular headache. Although acupuncture or its combined therapies provides certain advantages, most clinical studies are of small sample sizes. Large sample size, randomized, controlled trials are needed in the future for more definitive results.

The effect of newborn vitamin A supplementation on infant immune functions: trial design, interventions, and baseline data.

PubMed

Ahmad, Shaikh Meshbahuddin; Raqib, Rubhana; Qadri, Firdausi; Stephensen, Charles B

2014-11-01

In recent years, neonatal vitamin A supplementation is considered as an essential infant-survival intervention but the evidence is not conclusive. This randomized controlled clinical trial was conducted to evaluate the effect of vitamin A on immune competence in early infancy. Results would provide a mechanistic basis for understanding the effect of this intervention on infant survival. Within 2 days of birth, infants born at one maternity clinic located in a poor slum area of Dhaka city were supplemented with either 50,000 IU vitamin A or placebo. Live attenuated oral polio vaccine (OPV) and BCG vaccine were provided after supplementation. Infants also receive diphtheria, pertussis, tetanus (TT), hepatitis B (HBV) and Haemophilus influenzae B vaccines (pentavalent combination) along with OPV at 6, 10 and 14 weeks of age. Infant thymus size, anthropometry, feeding practice and morbidity data were collected at regular interval. Infant blood samples were collected to determine T-cell-receptor excision circle (TREC), total, naïve and memory T cells and mucosal targeting lymphocytes including Treg cells. TT-, HBV-, BCG- and OPV-specific T cell blastogenic, cytokine and plasma cell antibody responses were also measured. In 16 mo enrollment period, 306 newborns, equal number of boys and girls, were enrolled. ~95% completed the 4-month follow-up period. Baseline characteristics are presented here. Anthropometry and immune assays with fresh blood samples were completed immediately while stored samples were analyzed in single batches at the end of the trial. Connecting different aspects of immunological data in early infancy will help elucidate immune competence for protecting infection. Trial registration ClinicalTrials.gov: NCT01583972. Copyright © 2014 Elsevier Inc. All rights reserved.

How individual participant data meta-analyses have influenced trial design, conduct, and analysis.

PubMed

Tierney, Jayne F; Pignon, Jean-Pierre; Gueffyier, Francois; Clarke, Mike; Askie, Lisa; Vale, Claire L; Burdett, Sarah

2015-11-01

To demonstrate how individual participant data (IPD) meta-analyses have impacted directly on the design and conduct of trials and highlight other advantages IPD might offer. Potential examples of the impact of IPD meta-analyses on trials were identified at an international workshop, attended by individuals with experience in the conduct of IPD meta-analyses and knowledge of trials in their respective clinical areas. Experts in the field who did not attend were asked to provide any further examples. We then examined relevant trial protocols, publications, and Web sites to verify the impacts of the IPD meta-analyses. A subgroup of workshop attendees sought further examples and identified other aspects of trial design and conduct that may inform IPD meta-analyses. We identified 52 examples of IPD meta-analyses thought to have had a direct impact on the design or conduct of trials. After screening relevant trial protocols and publications, we identified 28 instances where IPD meta-analyses had clearly impacted on trials. They have influenced the selection of comparators and participants, sample size calculations, analysis and interpretation of subsequent trials, and the conduct and analysis of ongoing trials, sometimes in ways that would not possible with systematic reviews of aggregate data. We identified additional potential ways that IPD meta-analyses could be used to influence trials. IPD meta-analysis could be better used to inform the design, conduct, analysis, and interpretation of trials. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

How individual participant data meta-analyses have influenced trial design, conduct, and analysis

PubMed Central

Tierney, Jayne F.; Pignon, Jean-Pierre; Gueffyier, Francois; Clarke, Mike; Askie, Lisa; Vale, Claire L.; Burdett, Sarah; Alderson, P.; Askie, L.; Bennett, D.; Burdett, S.; Clarke, M.; Dias, S.; Emberson, J.; Gueyffier, F.; Iorio, A.; Macleod, M.; Mol, B.W.; Moons, C.; Parmar, M.; Perera, R.; Phillips, R.; Pignon, J.P.; Rees, J.; Reitsma, H.; Riley, R.; Rovers, M.; Rydzewska, L.; Schmid, C.; Shepperd, S.; Stenning, S.; Stewart, L.; Tierney, J.; Tudur Smith, C.; Vale, C.; Welge, J.; White, I.; Whiteley, W.

2015-01-01

Objectives To demonstrate how individual participant data (IPD) meta-analyses have impacted directly on the design and conduct of trials and highlight other advantages IPD might offer. Study Design and Setting Potential examples of the impact of IPD meta-analyses on trials were identified at an international workshop, attended by individuals with experience in the conduct of IPD meta-analyses and knowledge of trials in their respective clinical areas. Experts in the field who did not attend were asked to provide any further examples. We then examined relevant trial protocols, publications, and Web sites to verify the impacts of the IPD meta-analyses. A subgroup of workshop attendees sought further examples and identified other aspects of trial design and conduct that may inform IPD meta-analyses. Results We identified 52 examples of IPD meta-analyses thought to have had a direct impact on the design or conduct of trials. After screening relevant trial protocols and publications, we identified 28 instances where IPD meta-analyses had clearly impacted on trials. They have influenced the selection of comparators and participants, sample size calculations, analysis and interpretation of subsequent trials, and the conduct and analysis of ongoing trials, sometimes in ways that would not possible with systematic reviews of aggregate data. We identified additional potential ways that IPD meta-analyses could be used to influence trials. Conclusions IPD meta-analysis could be better used to inform the design, conduct, analysis, and interpretation of trials. PMID:26186982

Cognitive Behavioral Therapy: A Meta-Analysis of Race and Substance Use Outcomes

PubMed Central

Windsor, Liliane Cambraia; Jemal, Alexis; Alessi, Edward

2015-01-01

Cognitive behavioral therapy (CBT) is an effective intervention for reducing substance use. However, because CBT trials have included predominantly White samples caution must be used when generalizing these effects to Blacks and Hispanics. This meta-analysis compared the impact of CBT in reducing substance use between studies with a predominantly non-Hispanic White sample (hereafter NHW studies) and studies with a predominantly Black and/or Hispanic sample (hereafter BH studies). From 322 manuscripts identified in the literature, 17 met criteria for inclusion. Effect sizes between CBT and comparison group at posttest had similar effects on substance abuse across NHW and BH studies. However, when comparing pre-posttest effect sizes from groups receiving CBT between NHW and BH studies, CBT’s impact was significantly stronger in NHW studies. T-test comparisons indicated reduced retention/engagement in BH studies, albeit failing to reach statistical significance. Results highlight the need for further research testing CBT’s impact on substance use among Blacks and Hispanics. PMID:25285527

Test-retest reliability of pulse amplitude tonometry measures of vascular endothelial function: implications for clinical trial design.

PubMed

McCrea, Cindy E; Skulas-Ray, Ann C; Chow, Mosuk; West, Sheila G

2012-02-01

Endothelial dysfunction is an important outcome for assessing vascular health in intervention studies. However, reliability of the standard non-invasive method (flow-mediated dilation) is a significant challenge for clinical applications and multicenter trials. We evaluated the repeatability of pulse amplitude tonometry (PAT) to measure change in pulse wave amplitude during reactive hyperemia (Itamar Medical Ltd, Caesarea, Israel). Twenty healthy adults completed two PAT tests (mean interval = 19.5 days) under standardized conditions. PAT-derived measures of endothelial function (reactive hyperemia index, RHI) and arterial stiffness (augmentation index, AI) showed strong repeatability (intra-class correlations = 0.74 and 0.83, respectively). To guide future research, we also analyzed sample size requirements for a range of effect sizes. A crossover design powered at 0.90 requires 28 participants to detect a 15% change in RHI. Our study is the first to show that PAT measurements are repeatable in adults over an interval greater than 1 week.

A randomized control trial of a chronic care intervention for homeless women with alcohol use problems.

PubMed

Upshur, Carole; Weinreb, Linda; Bharel, Monica; Reed, George; Frisard, Christine

2015-04-01

A clinician-randomized trial was conducted using the chronic care model for disease management for alcohol use problems among n = 82 women served in a health care for the homeless clinic. Women with problem alcohol use received either usual care or an intervention consisting of a primary care provider (PCP) brief intervention, referral to addiction services, and on-going support from a care manager (CM) for 6 months. Both groups significantly reduced their alcohol consumption, with a small effect size favoring intervention at 3 months, but there were no significant differences between groups in reductions in drinking or in housing stability, or mental or physical health. However, intervention women had significantly more frequent participation in substance use treatment services. Baseline differences and small sample size limit generalizability, although substantial reductions in drinking for both groups suggest that screening and PCP brief treatment are promising interventions for homeless women with alcohol use problems. Copyright © 2015 Elsevier Inc. All rights reserved.

Two-sample binary phase 2 trials with low type I error and low sample size.

PubMed

Litwin, Samuel; Basickes, Stanley; Ross, Eric A

2017-04-30

We address design of two-stage clinical trials comparing experimental and control patients. Our end point is success or failure, however measured, with null hypothesis that the chance of success in both arms is p 0 and alternative that it is p 0 among controls and p 1  > p 0 among experimental patients. Standard rules will have the null hypothesis rejected when the number of successes in the (E)xperimental arm, E, sufficiently exceeds C, that among (C)ontrols. Here, we combine one-sample rejection decision rules, E⩾m, with two-sample rules of the form E - C > r to achieve two-sample tests with low sample number and low type I error. We find designs with sample numbers not far from the minimum possible using standard two-sample rules, but with type I error of 5% rather than 15% or 20% associated with them, and of equal power. This level of type I error is achieved locally, near the stated null, and increases to 15% or 20% when the null is significantly higher than specified. We increase the attractiveness of these designs to patients by using 2:1 randomization. Examples of the application of this new design covering both high and low success rates under the null hypothesis are provided. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Evaluation of Automated and Semi-Automated Scoring of Polysomnographic Recordings from a Clinical Trial Using Zolpidem in the Treatment of Insomnia

PubMed Central

Svetnik, Vladimir; Ma, Junshui; Soper, Keith A.; Doran, Scott; Renger, John J.; Deacon, Steve; Koblan, Ken S.

2007-01-01

Objective: To evaluate the performance of 2 automated systems, Morpheus and Somnolyzer24X7, with various levels of human review/editing, in scoring polysomnographic (PSG) recordings from a clinical trial using zolpidem in a model of transient insomnia. Methods: 164 all-night PSG recordings from 82 subjects collected during 2 nights of sleep, one under placebo and one under zolpidem (10 mg) treatment were used. For each recording, 6 different methods were used to provide sleep stage scores based on Rechtschaffen & Kales criteria: 1) full manual scoring, 2) automated scoring by Morpheus 3) automated scoring by Somnolyzer24X7, 4) automated scoring by Morpheus with full manual review, 5) automated scoring by Morpheus with partial manual review, 6) automated scoring by Somnolyzer24X7 with partial manual review. Ten traditional clinical efficacy measures of sleep initiation, maintenance, and architecture were calculated. Results: Pair-wise epoch-by-epoch agreements between fully automated and manual scores were in the range of intersite manual scoring agreements reported in the literature (70%-72%). Pair-wise epoch-by-epoch agreements between automated scores manually reviewed were higher (73%-76%). The direction and statistical significance of treatment effect sizes using traditional efficacy endpoints were essentially the same whichever method was used. As the degree of manual review increased, the magnitude of the effect size approached those estimated with fully manual scoring. Conclusion: Automated or semi-automated sleep PSG scoring offers valuable alternatives to costly, time consuming, and intrasite and intersite variable manual scoring, especially in large multicenter clinical trials. Reduction in scoring variability may also reduce the sample size of a clinical trial. Citation: Svetnik V; Ma J; Soper KA; Doran S; Renger JJ; Deacon S; Koblan KS. Evaluation of automated and semi-automated scoring of polysomnographic recordings from a clinical trial using zolpidem in the treatment of insomnia. SLEEP 2007;30(11):1562-1574. PMID:18041489

A Double Blind, Placebo- controlled Trial of Rosiglitazone for Clozapine induced Glucose Metabolism Impairment in patients with Schizophrenia

PubMed Central

Henderson, David C.; Fan, Xiaoduo; Sharma, Bikash; Copeland, Paul M.; Borba, Christina P; Boxill, Ryan; Freudenreich, Oliver; Cather, Corey; Evins, A. Eden; Goff, Donald C.

2014-01-01

Objective The primary purpose of this eight week double blind, placebo-controlled trial of rosiglitazone 4 mg/day was to examine its effect on insulin sensitivity index (SI) and glucose utilization (SG) in clozapine-treated schizophrenia subjects with insulin resistance. Methods Eighteen subjects were randomized and accessed with a Frequently Sampled Intravenous Glucose Tolerance Test (FSIVGTT) at the baseline and week 8 to estimate SG, and SI. Results Controlling for the baseline, comparing the rosiglitazone group to placebo group, there was a non-significant improvement of SG (0.016± 0.006 to 0.018± 0.008, effect size= 0.23, p= 0.05) with a trend of improvement in SI in the rosiglitazone group (4.6± 2.8 to 7.8± 6.7, effect size= 0.18, p= 0.08). There was a significant reduction in small low-density-lipoprotein cholesterol (LDL-C)- particle number (987± 443 to 694± 415, effect size= 0.30, p= 0.04). Conclusion Rosiglitazone may have a role in addressing the insulin resistance and lipid abnormalities associated with clozapine. PMID:19183127

A Simulation Study of Methods for Selecting Subgroup-Specific Doses in Phase I Trials

PubMed Central

Morita, Satoshi; Thall, Peter F.; Takeda, Kentaro

2016-01-01

Summary Patient heterogeneity may complicate dose-finding in phase I clinical trials if the dose-toxicity curves differ between subgroups. Conducting separate trials within subgroups may lead to infeasibly small sample sizes in subgroups having low prevalence. Alternatively, it is not obvious how to conduct a single trial while accounting for heterogeneity. To address this problem, we consider a generalization of the continual reassessment method (O’Quigley, et al., 1990) based on a hierarchical Bayesian dose-toxicity model that borrows strength between subgroups under the assumption that the subgroups are exchangeable. We evaluate a design using this model that includes subgroup-specific dose selection and safety rules. A simulation study is presented that includes comparison of this method to three alternative approaches, based on non-hierarchical models, that make different types of assumptions about within-subgroup dose-toxicity curves. The simulations show that the hierarchical model-based method is recommended in settings where the dose-toxicity curves are exchangeable between subgroups. We present practical guidelines for application, and provide computer programs for trial simulation and conduct. PMID:28111916

Increasing the occupational therapy mental health workforce through innovative practice education: a pilot project.

PubMed

Rodger, Sylvia; Thomas, Yvonne; Holley, Sue; Springfield, Elizabeth; Edwards, Ann; Broadbridge, Jacqui; Greber, Craig; McBryde, Cathy; Banks, Rebecca; Hawkins, Rachel

2009-12-01

This paper describes the evaluation of a pilot trial of two innovative placement models in the area of mental health, namely role emerging and collaborative supervision. The Queensland Occupational Therapy Fieldwork Collaborative conducted this trial in response to workforce shortages in mental health. Six occupational therapy students and eight practice educators were surveyed pre- and post-placements regarding implementation of these innovative models. Students participating in these placements reported that they were highly likely to work in mental health upon graduation, and practice educators were positive about undertaking innovative placements in future. An overview of the placement sites, trials, outcomes and limitations of this pilot trial is provided. Though limited by its small sample size, this pilot trial has demonstrated the potential of innovative placement models to provide valuable student learning experiences in mental health. The profession needs to develop expertise in the use of innovative placement models if students are to be adequately prepared to work with the mental health issues of the Australian community now and in the future.

Do Contemporary Randomized Controlled Trials Meet ESMO Thresholds for Meaningful Clinical Benefit?

PubMed

Del Paggio, J C; Azariah, B; Sullivan, R; Hopman, W M; James, F V; Roshni, S; Tannock, I F; Booth, C M

2017-01-01

The European Society for Medical Oncology (ESMO) recently released a magnitude of clinical benefit scale (ESMO-MCBS) for systemic therapies for solid cancers. Here, we evaluate contemporary randomized controlled trials (RCTs) against the proposed ESMO thresholds for meaningful clinical benefit. RCTs evaluating systemic therapy for breast cancer, nonsmall cell lung cancer (NSCLC), colorectal cancer (CRC), and pancreatic cancer published 2011-2015 were reviewed. Data were abstracted regarding trial characteristics and outcomes, and these were applied to the ESMO-MCBS. We also determined whether RCTs were designed to detect an effect that would meet clinical benefit as defined by the ESMO-MCBS. About 277 eligible RCTs were included (40% breast, 31% NSCLC, 22% CRC, 6% pancreas). Median sample size was 532 and 83% were funded by industry. Among all 277 RCTs, the experimental therapy was statistically superior to the control arm in 138 (50%) trials: results of only 31% (43/138) of these trials met the ESMO-MCBS clinical benefit threshold. RCTs with curative intent were more likely to meet clinically meaningful thresholds than those with palliative intent [61% (19/31) versus 22% (24/107), P < 0.001]. Among the 226 RCTs for which the ESMO-MCBS could be applied, 31% (70/226) were designed to detect an effect size that could meet ESMO-MCBS thresholds. Less than one-third of contemporary RCTs with statistically significant results meet ESMO thresholds for meaningful clinical benefit, and this represents only 15% of all published trials. Investigators, funding agencies, regulatory agencies, and industry should adopt more stringent thresholds for meaningful benefit in the design of future RCTs. © The Author 2016. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Meta-analysis: aerobic exercise for the treatment of anxiety disorders.

PubMed

Bartley, Christine A; Hay, Madeleine; Bloch, Michael H

2013-08-01

This meta-analysis investigates the efficacy of exercise as a treatment for DSM-IV diagnosed anxiety disorders. We searched PubMED and PsycINFO for randomized, controlled trials comparing the anxiolytic effects of aerobic exercise to other treatment conditions for DSM-IV defined anxiety disorders. Seven trials were included in the final analysis, totaling 407 subjects. The control conditions included non-aerobic exercise, waitlist/placebo, cognitive-behavioral therapy, psychoeducation and meditation. A fixed-effects model was used to calculate the standardized mean difference of change in anxiety rating scale scores of aerobic exercise compared to control conditions. Subgroup analyses were performed to examine the effects of (1) comparison condition; (2) whether comparison condition controlled for time spent exercising and (3) diagnostic indication. Aerobic exercise demonstrated no significant effect for the treatment of anxiety disorders (SMD=0.02 (95%CI: -0.20-0.24), z = 0.2, p = 0.85). There was significant heterogeneity between trials (χ(2) test for heterogeneity = 22.7, df = 6, p = 0.001). The reported effect size of aerobic exercise was highly influenced by the type of control condition. Trials utilizing waitlist/placebo controls and trials that did not control for exercise time reported large effects of aerobic exercise while other trials report no effect of aerobic exercise. Current evidence does not support the use of aerobic exercise as an effective treatment for anxiety disorders as compared to the control conditions. This remains true when controlling for length of exercise sessions and type of anxiety disorder. Future studies evaluating the efficacy of aerobic exercise should employ larger sample sizes and utilize comparison interventions that control for exercise time. Copyright © 2013. Published by Elsevier Inc.

Efficacy and acceptability of high frequency repetitive transcranial magnetic stimulation (rTMS) versus electroconvulsive therapy (ECT) for major depression: a systematic review and meta-analysis of randomized trials.

PubMed

Berlim, Marcelo T; Van den Eynde, Frederique; Daskalakis, Zafiris J

2013-07-01

Clinical trials comparing the efficacy and acceptability of high frequency repetitive transcranial magnetic stimulation (HF-rTMS) and electroconvulsive therapy (ECT) for treating major depression (MD) have yielded conflicting results. As this may have been the result of limited statistical power, we have carried out this meta-analysis to examine this issue. We searched the literature for randomized trials on head-to-head comparisons between HF-rTMS and ECT from January 1995 through September 2012 using MEDLINE, EMBASE, PsycINFO, Cochrane Central Register of Controlled Trials, and SCOPUS. The main outcome measures were remission rates, pre-post changes in depression ratings, as well as overall dropout rates at study end. We used a random-effects model, Odds Ratios (OR), Number Needed to Treat (NNT), and Hedges' g effect sizes. Data were obtained from 7 randomized trials, totalling 294 subjects with MD. After an average of 15.2 HF-rTMS and 8.2 ECT sessions, 33.6% (38/113) and 52% (53/102) of subjects were classified as remitters (OR = 0.46; p = 0.04), respectively. The associated NNT for remission was 6 and favoured ECT. Also, reduction of depressive symptomatology was significantly more pronounced in the ECT group (Hedges' g = -0.93; p = 0.007). No differences on dropout rates for HF-rTMS and ECT groups were found. In conclusion, ECT seems to be more effective than HF-rTMS for treating MD, although they did not differ in terms of dropout rates. Nevertheless, future comparative trials with larger sample sizes and better matching at baseline, longer follow-ups and more intense stimulation protocols are warranted. © 2013 Wiley Periodicals, Inc.

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2.

PubMed

Jack, Clifford R; Barnes, Josephine; Bernstein, Matt A; Borowski, Bret J; Brewer, James; Clegg, Shona; Dale, Anders M; Carmichael, Owen; Ching, Christopher; DeCarli, Charles; Desikan, Rahul S; Fennema-Notestine, Christine; Fjell, Anders M; Fletcher, Evan; Fox, Nick C; Gunter, Jeff; Gutman, Boris A; Holland, Dominic; Hua, Xue; Insel, Philip; Kantarci, Kejal; Killiany, Ron J; Krueger, Gunnar; Leung, Kelvin K; Mackin, Scott; Maillard, Pauline; Malone, Ian B; Mattsson, Niklas; McEvoy, Linda; Modat, Marc; Mueller, Susanne; Nosheny, Rachel; Ourselin, Sebastien; Schuff, Norbert; Senjem, Matthew L; Simonson, Alix; Thompson, Paul M; Rettmann, Dan; Vemuri, Prashanthi; Walhovd, Kristine; Zhao, Yansong; Zuk, Samantha; Weiner, Michael

2015-07-01

Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders. We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3. Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials. Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Methodological Issues in Trials of Complementary and Alternative Medicine Interventions

PubMed Central

Sikorskii, Alla; Wyatt, Gwen; Victorson, David; Faulkner, Gwen; Rahbar, Mohammad Hossein

2010-01-01

Background Complementary and alternative medicine (CAM) use is widespread among cancer patients. Information on safety and efficacy of CAM therapies is needed for both patients and health care providers. Well-designed randomized clinical trials (RCTs) of CAM therapy interventions can inform both clinical research and practice. Objectives To review important issues that affect the design of RCTs for CAM interventions. Methods Using the methods component of the Consolidated Standards for Reporting Trials (CONSORT) as a guiding framework, and a National Cancer Institute-funded reflexology study as an exemplar, methodological issues related to participants, intervention, objectives, outcomes, sample size, randomization, blinding, and statistical methods were reviewed. Discussion Trials of CAM interventions designed and implemented according to appropriate methodological standards will facilitate the needed scientific rigor in CAM research. Interventions in CAM can be tested using proposed methodology, and the results of testing will inform nursing practice in providing safe and effective supportive care and improving the well-being of patients. PMID:19918155

Confidence intervals for a difference between lognormal means in cluster randomization trials.

PubMed

Poirier, Julia; Zou, G Y; Koval, John

2017-04-01

Cluster randomization trials, in which intact social units are randomized to different interventions, have become popular in the last 25 years. Outcomes from these trials in many cases are positively skewed, following approximately lognormal distributions. When inference is focused on the difference between treatment arm arithmetic means, existent confidence interval procedures either make restricting assumptions or are complex to implement. We approach this problem by assuming log-transformed outcomes from each treatment arm follow a one-way random effects model. The treatment arm means are functions of multiple parameters for which separate confidence intervals are readily available, suggesting that the method of variance estimates recovery may be applied to obtain closed-form confidence intervals. A simulation study showed that this simple approach performs well in small sample sizes in terms of empirical coverage, relatively balanced tail errors, and interval widths as compared to existing methods. The methods are illustrated using data arising from a cluster randomization trial investigating a critical pathway for the treatment of community acquired pneumonia.

Research methods to change clinical practice for patients with rare cancers.

PubMed

Billingham, Lucinda; Malottki, Kinga; Steven, Neil

2016-02-01

Rare cancers are a growing group as a result of reclassification of common cancers by molecular markers. There is therefore an increasing need to identify methods to assess interventions that are sufficiently robust to potentially affect clinical practice in this setting. Methods advocated for clinical trials in rare diseases are not necessarily applicable in rare cancers. This Series paper describes research methods that are relevant for rare cancers in relation to the range of incidence levels. Strategies that maximise recruitment, minimise sample size, or maximise the usefulness of the evidence could enable the application of conventional clinical trial design to rare cancer populations. Alternative designs that address specific challenges for rare cancers with the aim of potentially changing clinical practice include Bayesian designs, uncontrolled n-of-1 trials, and umbrella and basket trials. Pragmatic solutions must be sought to enable some level of evidence-based health care for patients with rare cancers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Mixture-based gatekeeping procedures in adaptive clinical trials.

PubMed

Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji

2018-01-01

Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.

Generic versus brand-name drugs used in cardiovascular diseases.

PubMed

Manzoli, Lamberto; Flacco, Maria Elena; Boccia, Stefania; D'Andrea, Elvira; Panic, Nikola; Marzuillo, Carolina; Siliquini, Roberta; Ricciardi, Walter; Villari, Paolo; Ioannidis, John P A

2016-04-01

This meta-analysis aimed to compare the efficacy and adverse events, either serious or mild/moderate, of all generic versus brand-name cardiovascular medicines. We searched randomized trials in MEDLINE, Scopus, EMBASE, Cochrane Controlled Clinical Trial Register, and ClinicalTrials.gov (last update December 1, 2014). Attempts were made to contact the investigators of all potentially eligible trials. Two investigators independently extracted and analyzed soft (including systolic blood pressure, LDL cholesterol, and others) and hard efficacy outcomes (including major cardiovascular adverse events and death), minor/moderate and serious adverse events. We included 74 randomized trials; 53 reported ≥1 efficacy outcome (overall sample 3051), 32 measured mild/moderate adverse events (n = 2407), and 51 evaluated serious adverse events (n = 2892). We included trials assessing ACE inhibitors (n = 12), anticoagulants (n = 5), antiplatelet agents (n = 17), beta-blockers (n = 11), calcium channel blockers (n = 7); diuretics (n = 13); statins (n = 6); and others (n = 3). For both soft and hard efficacy outcomes, 100 % of the trials showed non-significant differences between generic and brand-name drugs. The aggregate effect size was 0.01 (95 % CI -0.05; 0.08) for soft outcomes; -0.06 (-0.71; 0.59) for hard outcomes. All but two trials showed non-significant differences in mild/moderate adverse events, and aggregate effect size was 0.07 (-0.06; 0.20). Comparable results were observed for each drug class and in each stratified meta-analysis. Overall, 8 serious possibly drug-related adverse events were reported: 5/2074 subjects on generics; 3/2076 subjects on brand-name drugs (OR 1.69; 95 % CI 0.40-7.20). This meta-analysis strengthens the evidence for clinical equivalence between brand-name and generic cardiovascular drugs. Physicians could be reassured about prescribing generic cardiovascular drugs, and health care organization about endorsing their wider use.

Timely and complete publication of economic evaluations alongside randomized controlled trials.

PubMed

Thorn, Joanna C; Noble, Sian M; Hollingworth, William

2013-01-01

Little is known about the extent and nature of publication bias in economic evaluations. Our objective was to determine whether economic evaluations are subject to publication bias by considering whether economic data are as likely to be reported, and reported as promptly, as effectiveness data. Trials that intended to conduct an economic analysis and ended before 2008 were identified in the International Standard Randomised Controlled Trial Number (ISRCTN) register; a random sample of 100 trials was retrieved. Fifty comparator trials were randomly drawn from those not identified as intending to conduct an economic study. The trial start and end dates, estimated sample size and funder type were extracted. For trials planning economic evaluations, effectiveness and economic publications were sought; publication dates and journal impact factors were extracted. Effectiveness abstracts were assessed for whether they reached a firm conclusion that one intervention was most effective. Primary investigators were contacted about reasons for non-publication of results, or reasons for differential publication strategies for effectiveness and economic results. Trials planning an economic study were more likely to be funded by government (p = 0.01) and larger (p = 0.003) than other trials. The trials planning an economic evaluation had a mean of 6.5 (range 2.7-13.2) years since the trial end in which to publish their results. Effectiveness results were reported by 70 %, while only 43 % published economic evaluations (p < 0.001). Reasons for non-publication of economic results included the intervention being ineffective, and staffing issues. Funding source, time since trial end and length of study were not associated with a higher probability of publishing the economic evaluation. However, studies that were small or of unknown size were significantly less likely to publish economic evaluations than large studies (p < 0.001). The authors' confidence in labelling one intervention clearly most effective did not affect the probability of publication. The mean time to publication was 0.7 years longer for cost-effectiveness data than for effectiveness data where both were published (p = 0.001). The median journal impact factor was 1.6 points higher for effectiveness publications than for the corresponding economic publications (p = 0.01). Reasons for publishing in different journals included editorial decision making and the additional time that economic evaluation takes to conduct. Trials that intend to conduct an economic analysis are less likely to report economic data than effectiveness data. Where economic results do appear, they are published later, and in journals with lower impact factors. These results suggest that economic output may be more susceptible than effectiveness data to publication bias. Funders, grant reviewers and trialists themselves should ensure economic evaluations are prioritized and adequately staffed to avoid potential problems with bias.

Evidence-Base Update of Psychosocial Treatments for Child and Adolescent Depression

PubMed Central

Weersing, V. Robin; Jeffreys, Megan; Do, Minh-Chau T.; Schwartz, Karen T. G.; Bolano, Carl

2017-01-01

Depression in youth is prevalent and disabling and tends to presage a chronic and recurrent course of illness and impairment in adulthood. Clinical trial research in youth depression has a 30 year history, and evidence-based treatment reviews appeared in 1998 and 2008. The current review of 42 randomized controlled trials (RCTs) updates these reviews to include RCTs published between 2008 and 2014 (N = 14) and re-evaluates previously reviewed literature. Given the growing maturity of the field, this review utilized a stringent set of methodological criteria for trial inclusion, most notable for excluding trials based in sub-clinical samples of youth that had been included in previous reviews (N = 12) and including well-designed RCTs with null and negative findings (N = 8). Findings from the current review suggest that evidence for child treatments is notably weaker than for adolescent interventions, with no child treatments achieving well-established status and the evidentiary basis of treatments downgraded from previous reports. Cognitive behavioral therapy (CBT) for clinically depressed children appears to be possibly efficacious, with mixed findings across trials. For depressed adolescents, both CBT and Interpersonal Psychotherapy (IPT) are well-established interventions, with evidence of efficacy in multiple trials by independent investigative teams. This positive conclusion is tempered by the small size of the IPT literature (N = 6) and concern that CBT effects may be attenuated in clinically complicated samples and when compared against active control conditions. In conclusion, data on predictors, moderators, and mediators are examined and priorities for future research discussed. PMID:27870579

Post Hoc Analyses of ApoE Genotype-Defined Subgroups in Clinical Trials.

PubMed

Kennedy, Richard E; Cutter, Gary R; Wang, Guoqiao; Schneider, Lon S

2016-01-01

Many post hoc analyses of clinical trials in Alzheimer's disease (AD) and mild cognitive impairment (MCI) are in small Phase 2 trials. Subject heterogeneity may lead to statistically significant post hoc results that cannot be replicated in larger follow-up studies. We investigated the extent of this problem using simulation studies mimicking current trial methods with post hoc analyses based on ApoE4 carrier status. We used a meta-database of 24 studies, including 3,574 subjects with mild AD and 1,171 subjects with MCI/prodromal AD, to simulate clinical trial scenarios. Post hoc analyses examined if rates of progression on the Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) differed between ApoE4 carriers and non-carriers. Across studies, ApoE4 carriers were younger and had lower baseline scores, greater rates of progression, and greater variability on the ADAS-cog. Up to 18% of post hoc analyses for 18-month trials in AD showed greater rates of progression for ApoE4 non-carriers that were statistically significant but unlikely to be confirmed in follow-up studies. The frequency of erroneous conclusions dropped below 3% with trials of 100 subjects per arm. In MCI, rates of statistically significant differences with greater progression in ApoE4 non-carriers remained below 3% unless sample sizes were below 25 subjects per arm. Statistically significant differences for ApoE4 in post hoc analyses often reflect heterogeneity among small samples rather than true differential effect among ApoE4 subtypes. Such analyses must be viewed cautiously. ApoE genotype should be incorporated into the design stage to minimize erroneous conclusions.