Accounting for heterogeneity in meta-analysis using a multiplicative model-an empirical study.

PubMed

Mawdsley, David; Higgins, Julian P T; Sutton, Alex J; Abrams, Keith R

2017-03-01

In meta-analysis, the random-effects model is often used to account for heterogeneity. The model assumes that heterogeneity has an additive effect on the variance of effect sizes. An alternative model, which assumes multiplicative heterogeneity, has been little used in the medical statistics community, but is widely used by particle physicists. In this paper, we compare the two models using a random sample of 448 meta-analyses drawn from the Cochrane Database of Systematic Reviews. In general, differences in goodness of fit are modest. The multiplicative model tends to give results that are closer to the null, with a narrower confidence interval. Both approaches make different assumptions about the outcome of the meta-analysis. In our opinion, the selection of the more appropriate model will often be guided by whether the multiplicative model's assumption of a single effect size is plausible. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Introduction, comparison, and validation of Meta-Essentials: A free and simple tool for meta-analysis.

PubMed

Suurmond, Robert; van Rhee, Henk; Hak, Tony

2017-12-01

We present a new tool for meta-analysis, Meta-Essentials, which is free of charge and easy to use. In this paper, we introduce the tool and compare its features to other tools for meta-analysis. We also provide detailed information on the validation of the tool. Although free of charge and simple, Meta-Essentials automatically calculates effect sizes from a wide range of statistics and can be used for a wide range of meta-analysis applications, including subgroup analysis, moderator analysis, and publication bias analyses. The confidence interval of the overall effect is automatically based on the Knapp-Hartung adjustment of the DerSimonian-Laird estimator. However, more advanced meta-analysis methods such as meta-analytical structural equation modelling and meta-regression with multiple covariates are not available. In summary, Meta-Essentials may prove a valuable resource for meta-analysts, including researchers, teachers, and students. © 2017 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.

Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models.

PubMed

Riley, Richard D; Ensor, Joie; Jackson, Dan; Burke, Danielle L

2017-01-01

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher's information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis).

A refined method for multivariate meta-analysis and meta-regression.

PubMed

Jackson, Daniel; Riley, Richard D

2014-02-20

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects' standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. Copyright © 2013 John Wiley & Sons, Ltd.

Multilevel mixed effects parametric survival models using adaptive Gauss-Hermite quadrature with application to recurrent events and individual participant data meta-analysis.

PubMed

Crowther, Michael J; Look, Maxime P; Riley, Richard D

2014-09-28

Multilevel mixed effects survival models are used in the analysis of clustered survival data, such as repeated events, multicenter clinical trials, and individual participant data (IPD) meta-analyses, to investigate heterogeneity in baseline risk and covariate effects. In this paper, we extend parametric frailty models including the exponential, Weibull and Gompertz proportional hazards (PH) models and the log logistic, log normal, and generalized gamma accelerated failure time models to allow any number of normally distributed random effects. Furthermore, we extend the flexible parametric survival model of Royston and Parmar, modeled on the log-cumulative hazard scale using restricted cubic splines, to include random effects while also allowing for non-PH (time-dependent effects). Maximum likelihood is used to estimate the models utilizing adaptive or nonadaptive Gauss-Hermite quadrature. The methods are evaluated through simulation studies representing clinically plausible scenarios of a multicenter trial and IPD meta-analysis, showing good performance of the estimation method. The flexible parametric mixed effects model is illustrated using a dataset of patients with kidney disease and repeated times to infection and an IPD meta-analysis of prognostic factor studies in patients with breast cancer. User-friendly Stata software is provided to implement the methods. Copyright © 2014 John Wiley & Sons, Ltd.

Methods for network meta-analysis of continuous outcomes using individual patient data: a case study in acupuncture for chronic pain.

PubMed

Saramago, Pedro; Woods, Beth; Weatherly, Helen; Manca, Andrea; Sculpher, Mark; Khan, Kamran; Vickers, Andrew J; MacPherson, Hugh

2016-10-06

Network meta-analysis methods, which are an extension of the standard pair-wise synthesis framework, allow for the simultaneous comparison of multiple interventions and consideration of the entire body of evidence in a single statistical model. There are well-established advantages to using individual patient data to perform network meta-analysis and methods for network meta-analysis of individual patient data have already been developed for dichotomous and time-to-event data. This paper describes appropriate methods for the network meta-analysis of individual patient data on continuous outcomes. This paper introduces and describes network meta-analysis of individual patient data models for continuous outcomes using the analysis of covariance framework. Comparisons are made between this approach and change score and final score only approaches, which are frequently used and have been proposed in the methodological literature. A motivating example on the effectiveness of acupuncture for chronic pain is used to demonstrate the methods. Individual patient data on 28 randomised controlled trials were synthesised. Consistency of endpoints across the evidence base was obtained through standardisation and mapping exercises. Individual patient data availability avoided the use of non-baseline-adjusted models, allowing instead for analysis of covariance models to be applied and thus improving the precision of treatment effect estimates while adjusting for baseline imbalance. The network meta-analysis of individual patient data using the analysis of covariance approach is advocated to be the most appropriate modelling approach for network meta-analysis of continuous outcomes, particularly in the presence of baseline imbalance. Further methods developments are required to address the challenge of analysing aggregate level data in the presence of baseline imbalance.

Simulation-based power calculations for planning a two-stage individual participant data meta-analysis.

PubMed

Ensor, Joie; Burke, Danielle L; Snell, Kym I E; Hemming, Karla; Riley, Richard D

2018-05-18

Researchers and funders should consider the statistical power of planned Individual Participant Data (IPD) meta-analysis projects, as they are often time-consuming and costly. We propose simulation-based power calculations utilising a two-stage framework, and illustrate the approach for a planned IPD meta-analysis of randomised trials with continuous outcomes where the aim is to identify treatment-covariate interactions. The simulation approach has four steps: (i) specify an underlying (data generating) statistical model for trials in the IPD meta-analysis; (ii) use readily available information (e.g. from publications) and prior knowledge (e.g. number of studies promising IPD) to specify model parameter values (e.g. control group mean, intervention effect, treatment-covariate interaction); (iii) simulate an IPD meta-analysis dataset of a particular size from the model, and apply a two-stage IPD meta-analysis to obtain the summary estimate of interest (e.g. interaction effect) and its associated p-value; (iv) repeat the previous step (e.g. thousands of times), then estimate the power to detect a genuine effect by the proportion of summary estimates with a significant p-value. In a planned IPD meta-analysis of lifestyle interventions to reduce weight gain in pregnancy, 14 trials (1183 patients) promised their IPD to examine a treatment-BMI interaction (i.e. whether baseline BMI modifies intervention effect on weight gain). Using our simulation-based approach, a two-stage IPD meta-analysis has < 60% power to detect a reduction of 1 kg weight gain for a 10-unit increase in BMI. Additional IPD from ten other published trials (containing 1761 patients) would improve power to over 80%, but only if a fixed-effect meta-analysis was appropriate. Pre-specified adjustment for prognostic factors would increase power further. Incorrect dichotomisation of BMI would reduce power by over 20%, similar to immediately throwing away IPD from ten trials. Simulation-based power calculations could inform the planning and funding of IPD projects, and should be used routinely.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

A hands-on practical tutorial on performing meta-analysis with Stata.

PubMed

Chaimani, Anna; Mavridis, Dimitris; Salanti, Georgia

2014-11-01

Statistical synthesis of research findings via meta-analysis is widely used to assess the relative effectiveness of competing interventions. A series of three papers aimed at familiarising mental health scientists with the key statistical concepts and problems in meta-analysis was recently published in this journal. One paper focused on the selection and interpretation of the appropriate model to synthesise results (fixed effect or random effects model) whereas the other two papers focused on two major threats that compromise the validity of meta-analysis results, namely publication bias and missing outcome data. In this paper we provide guidance on how to undertake meta-analysis using Stata, one of the most commonly used software packages for meta-analysis. We address the three topics covered in the previous issues of the journal, focusing on their implementation in Stata using a working example from mental health research. 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.

A Meta-Meta-Analysis: Empirical Review of Statistical Power, Type I Error Rates, Effect Sizes, and Model Selection of Meta-Analyses Published in Psychology

ERIC Educational Resources Information Center

Cafri, Guy; Kromrey, Jeffrey D.; Brannick, Michael T.

2010-01-01

This article uses meta-analyses published in "Psychological Bulletin" from 1995 to 2005 to describe meta-analyses in psychology, including examination of statistical power, Type I errors resulting from multiple comparisons, and model choice. Retrospective power estimates indicated that univariate categorical and continuous moderators, individual…

Effect of High-Frequency Transcranial Magnetic Stimulation on Craving in Substance Use Disorder: A Meta-Analysis.

PubMed

Maiti, Rituparna; Mishra, Biswa Ranjan; Hota, Debasish

2017-01-01

Repetitive transcranial magnetic stimulation (rTMS), a noninvasive, neuromodulatory tool, has been used to reduce craving in different substance use disorders. There are some studies that have reported conflicting and inconclusive results; therefore, this meta-analysis was conducted to evaluate the effect of high-frequency rTMS on craving in substance use disorder and to investigate the reasons behind the inconsistency across the studies. The authors searched clinical trials from MEDLINE, Cochrane databases, and International Clinical Trials Registry Platform. The PRISMA guidelines, as well as recommended meta-analysis practices, were followed in the selection process, analysis, and reporting of the findings. The effect estimate used was the standardized mean difference (Hedge's g), and heterogeneity across the considered studies was explored using subgroup analyses. The quality assessment was done using the Cochrane risk of bias tool, and sensitivity analysis was performed to check the influences on effect size by statistical models. After screening and assessment of eligibility, finally 10 studies were included for meta-analysis, which includes six studies on alcohol and four studies on nicotine use disorder. The random-model analysis revealed a pooled effect size of 0.75 (95% CI=0.29 to 1.21, p=0.001), whereas the fixed-model analysis showed a large effect size of 0.87 (95% CI=0.63 to 1.12, p<0.00001). Subgroup analysis for alcohol use disorder showed an effect size of -0.06 (95% CI=-0.89 to 0.77, p=0.88). In the case of nicotine use disorder, random-model analysis revealed an effect size of 1.00 (95% CI=0.48 to 1.55, p=0.0001), whereas fixed-model analysis also showed a large effect size of 0.96 (95% CI=0.71 to 1.22). The present meta-analysis identified a beneficial effect of high-frequency rTMS on craving associated with nicotine use disorder but not alcohol use disorder.

A General Model for Estimating and Correcting the Effects of Nonindependence in Meta-Analysis.

ERIC Educational Resources Information Center

Strube, Michael J.

A general model is described which can be used to represent the four common types of meta-analysis: (1) estimation of effect size by combining study outcomes; (2) estimation of effect size by contrasting study outcomes; (3) estimation of statistical significance by combining study outcomes; and (4) estimation of statistical significance by…

Meta-analysis of individual registry results enhances international registry collaboration.

PubMed

Paxton, Elizabeth W; Mohaddes, Maziar; Laaksonen, Inari; Lorimer, Michelle; Graves, Stephen E; Malchau, Henrik; Namba, Robert S; Kärrholm, John; Rolfson, Ola; Cafri, Guy

2018-03-28

Background and purpose - Although common in medical research, meta-analysis has not been widely adopted in registry collaborations. A meta-analytic approach in which each registry conducts a standardized analysis on its own data followed by a meta-analysis to calculate a weighted average of the estimates allows collaboration without sharing patient-level data. The value of meta-analysis as an alternative to individual patient data analysis is illustrated in this study by comparing the risk of revision of porous tantalum cups versus other uncemented cups in primary total hip arthroplasties from Sweden, Australia, and a US registry (2003-2015). Patients and methods - For both individual patient data analysis and meta-analysis approaches a Cox proportional hazard model was fit for time to revision, comparing porous tantalum (n = 23,201) with other uncemented cups (n = 128,321). Covariates included age, sex, diagnosis, head size, and stem fixation. In the meta-analysis approach, treatment effect size (i.e., Cox model hazard ratio) was calculated within each registry and a weighted average for the individual registries' estimates was calculated. Results - Patient-level data analysis and meta-analytic approaches yielded the same results with the porous tantalum cups having a higher risk of revision than other uncemented cups (HR (95% CI) 1.6 (1.4-1.7) and HR (95% CI) 1.5 (1.4-1.7), respectively). Adding the US cohort to the meta-analysis led to greater generalizability, increased precision of the treatment effect, and similar findings (HR (95% CI) 1.6 (1.4-1.7)) with increased risk of porous tantalum cups. Interpretation - The meta-analytic technique is a viable option to address privacy, security, and data ownership concerns allowing more expansive registry collaboration, greater generalizability, and increased precision of treatment effects.

Angry Birds, Angry Children, and Angry Meta-Analysts: A Reanalysis.

PubMed

Furuya-Kanamori, Luis; Doi, Suhail A R

2016-05-01

Ferguson's (2015a) meta-analysis assessed a very important and controversial topic about children's mental health and video games. In response to the concerns raised by researchers about the appropriateness of the meta-analytical methods used by Ferguson; we decided to reanalyze the data and discuss two major misconceptions about meta-analysis. We argue that partial correlations can (and should) be meta-analyzed instead of zero-order bivariate correlations if the predictors included in the partial correlation represent a similar construct. We also discuss the fallacy by which the conventional meta-analytical model assumes that the studies' effect sizes came into being according to the same random effect construct used by the analysis. Our replication results using partial correlations, standardized (valid and reliable) outcomes, and an improved meta-analytical model (that does not assume a random effect is the mechanism of data generation) confirmed the main results of Ferguson's meta-analysis. There was a significant yet very small effect on aggressive behavior of exposure to both general, rp = 0.062, 95% CI [0.012, 0.112], and violent, rp = 0.055, 95% CI [0.019, 0.091], video games. A very small effect was seen on reduced prosocial behavior, but this was only in the general video game exposure category, rp = 0.072, 95% CI [0.045, 0.100]. © The Author(s) 2016.

The evaluation of meta-analysis techniques for quantifying prescribed fire effects on fuel loadings.

Treesearch

Karen E. Kopper; Donald McKenzie; David L. Peterson

2009-01-01

Models and effect-size metrics for meta-analysis were compared in four separate meta-analyses quantifying surface fuels after prescribed fires in ponderosa pine (Pinus ponderosa Dougl. ex Laws.) forests of the Western United States. An aggregated data set was compiled from eight published reports that contained data from 65 fire treatment units....

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

PubMed

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

Predicting Pilot Performance in Off-Nominal Conditions: A Meta-Analysis and Model Validation

NASA Technical Reports Server (NTRS)

Wickens, C.D.; Hooey, B.L.; Gore, B.F.; Sebok, A.; Koenecke, C.; Salud, E.

2009-01-01

Pilot response to off-nominal (very rare) events represents a critical component to understanding the safety of next generation airspace technology and procedures. We describe a meta-analysis designed to integrate the existing data regarding pilot accuracy of detecting rare, unexpected events such as runway incursions in realistic flight simulations. Thirty-five studies were identified and pilot responses were categorized by expectancy, event location, and whether the pilot was flying with a highway-in-the-sky display. All three dichotomies produced large, significant effects on event miss rate. A model of human attention and noticing, N-SEEV, was then used to predict event noticing performance as a function of event salience and expectancy, and retinal eccentricity. Eccentricity is predicted from steady state scanning by the SEEV model of attention allocation. The model was used to predict miss rates for the expectancy, location and highway-in-the-sky (HITS) effects identified in the meta-analysis. The correlation between model-predicted results and data from the meta-analysis was 0.72.

Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

PubMed Central

Haitsma, Jack J.; Furmli, Suleiman; Masoom, Hussain; Liu, Mingyao; Imai, Yumiko; Slutsky, Arthur S.; Beyene, Joseph; Greenwood, Celia M. T.; dos Santos, Claudia

2012-01-01

Objectives To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans. Methods We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients. Results Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis. Conclusion Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of “injury" gene predictors that can classify lung injury samples and identify patients at risk for clinically relevant lung injury complications. PMID:23071521

Meta-Analysis of Effect Sizes Reported at Multiple Time Points Using General Linear Mixed Model.

PubMed

Musekiwa, Alfred; Manda, Samuel O M; Mwambi, Henry G; Chen, Ding-Geng

2016-01-01

Meta-analysis of longitudinal studies combines effect sizes measured at pre-determined time points. The most common approach involves performing separate univariate meta-analyses at individual time points. This simplistic approach ignores dependence between longitudinal effect sizes, which might result in less precise parameter estimates. In this paper, we show how to conduct a meta-analysis of longitudinal effect sizes where we contrast different covariance structures for dependence between effect sizes, both within and between studies. We propose new combinations of covariance structures for the dependence between effect size and utilize a practical example involving meta-analysis of 17 trials comparing postoperative treatments for a type of cancer, where survival is measured at 6, 12, 18 and 24 months post randomization. Although the results from this particular data set show the benefit of accounting for within-study serial correlation between effect sizes, simulations are required to confirm these results.

Get Real in Individual Participant Data (IPD) Meta-Analysis: A Review of the Methodology

ERIC Educational Resources Information Center

Debray, Thomas P. A.; Moons, Karel G. M.; van Valkenhoef, Gert; Efthimiou, Orestis; Hummel, Noemi; Groenwold, Rolf H. H.; Reitsma, Johannes B.

2015-01-01

Individual participant data (IPD) meta-analysis is an increasingly used approach for synthesizing and investigating treatment effect estimates. Over the past few years, numerous methods for conducting an IPD meta-analysis (IPD-MA) have been proposed, often making different assumptions and modeling choices while addressing a similar research…

Accounting for Heterogeneity in Relative Treatment Effects for Use in Cost-Effectiveness Models and Value-of-Information Analyses

PubMed Central

Soares, Marta O.; Palmer, Stephen; Ades, Anthony E.; Harrison, David; Shankar-Hari, Manu; Rowan, Kathy M.

2015-01-01

Cost-effectiveness analysis (CEA) models are routinely used to inform health care policy. Key model inputs include relative effectiveness of competing treatments, typically informed by meta-analysis. Heterogeneity is ubiquitous in meta-analysis, and random effects models are usually used when there is variability in effects across studies. In the absence of observed treatment effect modifiers, various summaries from the random effects distribution (random effects mean, predictive distribution, random effects distribution, or study-specific estimate [shrunken or independent of other studies]) can be used depending on the relationship between the setting for the decision (population characteristics, treatment definitions, and other contextual factors) and the included studies. If covariates have been measured that could potentially explain the heterogeneity, then these can be included in a meta-regression model. We describe how covariates can be included in a network meta-analysis model and how the output from such an analysis can be used in a CEA model. We outline a model selection procedure to help choose between competing models and stress the importance of clinical input. We illustrate the approach with a health technology assessment of intravenous immunoglobulin for the management of adult patients with severe sepsis in an intensive care setting, which exemplifies how risk of bias information can be incorporated into CEA models. We show that the results of the CEA and value-of-information analyses are sensitive to the model and highlight the importance of sensitivity analyses when conducting CEA in the presence of heterogeneity. The methods presented extend naturally to heterogeneity in other model inputs, such as baseline risk. PMID:25712447

Accounting for Heterogeneity in Relative Treatment Effects for Use in Cost-Effectiveness Models and Value-of-Information Analyses.

PubMed

Welton, Nicky J; Soares, Marta O; Palmer, Stephen; Ades, Anthony E; Harrison, David; Shankar-Hari, Manu; Rowan, Kathy M

2015-07-01

Cost-effectiveness analysis (CEA) models are routinely used to inform health care policy. Key model inputs include relative effectiveness of competing treatments, typically informed by meta-analysis. Heterogeneity is ubiquitous in meta-analysis, and random effects models are usually used when there is variability in effects across studies. In the absence of observed treatment effect modifiers, various summaries from the random effects distribution (random effects mean, predictive distribution, random effects distribution, or study-specific estimate [shrunken or independent of other studies]) can be used depending on the relationship between the setting for the decision (population characteristics, treatment definitions, and other contextual factors) and the included studies. If covariates have been measured that could potentially explain the heterogeneity, then these can be included in a meta-regression model. We describe how covariates can be included in a network meta-analysis model and how the output from such an analysis can be used in a CEA model. We outline a model selection procedure to help choose between competing models and stress the importance of clinical input. We illustrate the approach with a health technology assessment of intravenous immunoglobulin for the management of adult patients with severe sepsis in an intensive care setting, which exemplifies how risk of bias information can be incorporated into CEA models. We show that the results of the CEA and value-of-information analyses are sensitive to the model and highlight the importance of sensitivity analyses when conducting CEA in the presence of heterogeneity. The methods presented extend naturally to heterogeneity in other model inputs, such as baseline risk. © The Author(s) 2015.

A Noncentral "t" Regression Model for Meta-Analysis

ERIC Educational Resources Information Center

Camilli, Gregory; de la Torre, Jimmy; Chiu, Chia-Yi

2010-01-01

In this article, three multilevel models for meta-analysis are examined. Hedges and Olkin suggested that effect sizes follow a noncentral "t" distribution and proposed several approximate methods. Raudenbush and Bryk further refined this model; however, this procedure is based on a normal approximation. In the current research literature, this…

Meta-analysis using Dirichlet process.

PubMed

Muthukumarana, Saman; Tiwari, Ram C

2016-02-01

This article develops a Bayesian approach for meta-analysis using the Dirichlet process. The key aspect of the Dirichlet process in meta-analysis is the ability to assess evidence of statistical heterogeneity or variation in the underlying effects across study while relaxing the distributional assumptions. We assume that the study effects are generated from a Dirichlet process. Under a Dirichlet process model, the study effects parameters have support on a discrete space and enable borrowing of information across studies while facilitating clustering among studies. We illustrate the proposed method by applying it to a dataset on the Program for International Student Assessment on 30 countries. Results from the data analysis, simulation studies, and the log pseudo-marginal likelihood model selection procedure indicate that the Dirichlet process model performs better than conventional alternative methods. © The Author(s) 2012.

A refined method for multivariate meta-analysis and meta-regression

PubMed Central

Jackson, Daniel; Riley, Richard D

2014-01-01

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects’ standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:23996351

Alternative Measures of Between-Study Heterogeneity in Meta-Analysis: Reducing the Impact of Outlying Studies

PubMed Central

Lin, Lifeng; Chu, Haitao; Hodges, James S.

2016-01-01

Summary Meta-analysis has become a widely used tool to combine results from independent studies. The collected studies are homogeneous if they share a common underlying true effect size; otherwise, they are heterogeneous. A fixed-effect model is customarily used when the studies are deemed homogeneous, while a random-effects model is used for heterogeneous studies. Assessing heterogeneity in meta-analysis is critical for model selection and decision making. Ideally, if heterogeneity is present, it should permeate the entire collection of studies, instead of being limited to a small number of outlying studies. Outliers can have great impact on conventional measures of heterogeneity and the conclusions of a meta-analysis. However, no widely accepted guidelines exist for handling outliers. This article proposes several new heterogeneity measures. In the presence of outliers, the proposed measures are less affected than the conventional ones. The performance of the proposed and conventional heterogeneity measures are compared theoretically, by studying their asymptotic properties, and empirically, using simulations and case studies. PMID:27167143

Conducting indirect-treatment-comparison and network-meta-analysis studies: report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: part 2.

PubMed

Hoaglin, David C; Hawkins, Neil; Jansen, Jeroen P; Scott, David A; Itzler, Robbin; Cappelleri, Joseph C; Boersma, Cornelis; Thompson, David; Larholt, Kay M; Diaz, Mireya; Barrett, Annabel

2011-06-01

Evidence-based health care decision making requires comparison of all relevant competing interventions. In the absence of randomized controlled trials involving a direct comparison of all treatments of interest, indirect treatment comparisons and network meta-analysis provide useful evidence for judiciously selecting the best treatment(s). Mixed treatment comparisons, a special case of network meta-analysis, combine direct evidence and indirect evidence for particular pairwise comparisons, thereby synthesizing a greater share of the available evidence than traditional meta-analysis. This report from the International Society for Pharmacoeconomics and Outcomes Research Indirect Treatment Comparisons Good Research Practices Task Force provides guidance on technical aspects of conducting network meta-analyses (our use of this term includes most methods that involve meta-analysis in the context of a network of evidence). We start with a discussion of strategies for developing networks of evidence. Next we briefly review assumptions of network meta-analysis. Then we focus on the statistical analysis of the data: objectives, models (fixed-effects and random-effects), frequentist versus Bayesian approaches, and model validation. A checklist highlights key components of network meta-analysis, and substantial examples illustrate indirect treatment comparisons (both frequentist and Bayesian approaches) and network meta-analysis. A further section discusses eight key areas for future research. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Dealing with Feeling: A Meta-Analysis of the Effectiveness of Strategies Derived from the Process Model of Emotion Regulation

ERIC Educational Resources Information Center

Webb, Thomas L.; Miles, Eleanor; Sheeran, Paschal

2012-01-01

The present meta-analysis investigated the effectiveness of strategies derived from the process model of emotion regulation in modifying emotional outcomes as indexed by experiential, behavioral, and physiological measures. A systematic search of the literature identified 306 experimental comparisons of different emotion regulation (ER)…

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

A Comprehensive Meta-Analysis of Triple P-Positive Parenting Program Using Hierarchical Linear Modeling: Effectiveness and Moderating Variables

ERIC Educational Resources Information Center

Nowak, Christoph; Heinrichs, Nina

2008-01-01

A meta-analysis encompassing all studies evaluating the impact of the Triple P-Positive Parenting Program on parent and child outcome measures was conducted in an effort to identify variables that moderate the program's effectiveness. Hierarchical linear models (HLM) with three levels of data were employed to analyze effect sizes. The results (N =…

Effect of Metformin on Plasma Fibrinogen Concentrations: A Systematic Review and Meta-Analysis of Randomized Placebo-Controlled Trials.

PubMed

Simental-Mendia, Luis E; Pirro, Matteo; Atkin, Stephen L; Banach, Maciej; Mikhailidis, Dimitri P; Sahebkar, Amirhossein

2018-01-01

Fibrinogen is a key mediator of thrombosis and it has been implicated in the pathogenesis of atherosclerosis. Because metformin has shown a potential protective effect on different atherothrombotic risk factors, we assessed in this meta-analysis its effect on plasma fibrinogen concentrations. A systematic review and meta-analysis was carried out to identify randomized placebo-controlled trials evaluating the effect of metformin administration on fibrinogen levels. The search included PubMed-Medline, Scopus, ISI Web of Knowledge and Google Scholar databases (by June 2, 2017) and quality of studies was performed according to Cochrane criteria. Quantitative data synthesis was conducted using a random-effects model and sensitivity analysis by the leave-one-out method. Meta-regression analysis was performed to assess the modifiers of treatment response. Meta-analysis of data from 9 randomized placebo-controlled clinical trials with 2302 patients comprising 10 treatment arms did not suggest a significant change in plasma fibrinogen concentrations following metformin therapy (WMD: -0.25 g/L, 95% CI: -0.53, 0.04, p = 0.092). The effect size was robust in the leave-one-out sensitivity analysis and remained non-significant after omission of each single study from the meta-analysis. No significant effect of metformin on plasma fibrinogen concentrations was demonstrated in the current meta-analysis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Meta-analysis of Gaussian individual patient data: Two-stage or not two-stage?

PubMed

Morris, Tim P; Fisher, David J; Kenward, Michael G; Carpenter, James R

2018-04-30

Quantitative evidence synthesis through meta-analysis is central to evidence-based medicine. For well-documented reasons, the meta-analysis of individual patient data is held in higher regard than aggregate data. With access to individual patient data, the analysis is not restricted to a "two-stage" approach (combining estimates and standard errors) but can estimate parameters of interest by fitting a single model to all of the data, a so-called "one-stage" analysis. There has been debate about the merits of one- and two-stage analysis. Arguments for one-stage analysis have typically noted that a wider range of models can be fitted and overall estimates may be more precise. The two-stage side has emphasised that the models that can be fitted in two stages are sufficient to answer the relevant questions, with less scope for mistakes because there are fewer modelling choices to be made in the two-stage approach. For Gaussian data, we consider the statistical arguments for flexibility and precision in small-sample settings. Regarding flexibility, several of the models that can be fitted only in one stage may not be of serious interest to most meta-analysis practitioners. Regarding precision, we consider fixed- and random-effects meta-analysis and see that, for a model making certain assumptions, the number of stages used to fit this model is irrelevant; the precision will be approximately equal. Meta-analysts should choose modelling assumptions carefully. Sometimes relevant models can only be fitted in one stage. Otherwise, meta-analysts are free to use whichever procedure is most convenient to fit the identified model. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Sequential change detection and monitoring of temporal trends in random-effects meta-analysis.

PubMed

Dogo, Samson Henry; Clark, Allan; Kulinskaya, Elena

2017-06-01

Temporal changes in magnitude of effect sizes reported in many areas of research are a threat to the credibility of the results and conclusions of meta-analysis. Numerous sequential methods for meta-analysis have been proposed to detect changes and monitor trends in effect sizes so that meta-analysis can be updated when necessary and interpreted based on the time it was conducted. The difficulties of sequential meta-analysis under the random-effects model are caused by dependencies in increments introduced by the estimation of the heterogeneity parameter τ 2 . In this paper, we propose the use of a retrospective cumulative sum (CUSUM)-type test with bootstrap critical values. This method allows retrospective analysis of the past trajectory of cumulative effects in random-effects meta-analysis and its visualization on a chart similar to CUSUM chart. Simulation results show that the new method demonstrates good control of Type I error regardless of the number or size of the studies and the amount of heterogeneity. Application of the new method is illustrated on two examples of medical meta-analyses. © 2016 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. © 2016 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.

A Practical Guide to Conducting a Systematic Review and Meta-analysis of Health State Utility Values.

PubMed

Petrou, Stavros; Kwon, Joseph; Madan, Jason

2018-05-10

Economic analysts are increasingly likely to rely on systematic reviews and meta-analyses of health state utility values to inform the parameter inputs of decision-analytic modelling-based economic evaluations. Beyond the context of economic evaluation, evidence from systematic reviews and meta-analyses of health state utility values can be used to inform broader health policy decisions. This paper provides practical guidance on how to conduct a systematic review and meta-analysis of health state utility values. The paper outlines a number of stages in conducting a systematic review, including identifying the appropriate evidence, study selection, data extraction and presentation, and quality and relevance assessment. The paper outlines three broad approaches that can be used to synthesise multiple estimates of health utilities for a given health state or condition, namely fixed-effect meta-analysis, random-effects meta-analysis and mixed-effects meta-regression. Each approach is illustrated by a synthesis of utility values for a hypothetical decision problem, and software code is provided. The paper highlights a number of methodological issues pertinent to the conduct of meta-analysis or meta-regression. These include the importance of limiting synthesis to 'comparable' utility estimates, for example those derived using common utility measurement approaches and sources of valuation; the effects of reliance on limited or poorly reported published data from primary utility assessment studies; the use of aggregate outcomes within analyses; approaches to generating measures of uncertainty; handling of median utility values; challenges surrounding the disentanglement of utility estimates collected serially within the context of prospective observational studies or prospective randomised trials; challenges surrounding the disentanglement of intervention effects; and approaches to measuring model validity. Areas of methodological debate and avenues for future research are highlighted.

Comprehensive School Reform and Achievement: A Meta-Analysis

ERIC Educational Resources Information Center

Borman, Geoffrey D.; Hewes, Gina M.; Overman, Laura T.; Brown, Shelly

2003-01-01

This meta-analysis reviews research on the achievement effects of comprehensive school reform (CSR) and summarizes the specific effects of 29 widely implemented models. There are limitations on the overall quantity and quality of the research base, but the overall effects of CSR appear promising. The combined quantity, quality, and statistical…

Meta-Analysis of Planetarium Efficacy Research

ERIC Educational Resources Information Center

Brazell, Bruce D.; Espinoza, Sue

2009-01-01

In this study, the instructional effectiveness of the planetarium in astronomy education was explored through a meta-analysis of 19 studies. This analysis resulted in a heterogeneous distribution of 24 effect sizes with a mean of +0.28, p less than 0.05. The variability in this distribution was not fully explained under a fixed effect model. As a…

A Meta-Analysis of Dunn and Dunn Model Correlational Research with Adult Populations

ERIC Educational Resources Information Center

Mangino, Christine

2004-01-01

The purpose of this investigation was to conduct a quantitative synthesis of correlational research that focused on the Dunn and Dunn Learning-Style Model and was concerned with adult populations. A total of 8,661 participants from the 47 original investigations provided 386 individual effect sizes for this meta-analysis. The mean effect size was…

Meta-analysis of sex-specific genome-wide association studies.

PubMed

Magi, Reedik; Lindgren, Cecilia M; Morris, Andrew P

2010-12-01

Despite the success of genome-wide association studies, much of the genetic contribution to complex human traits is still unexplained. One potential source of genetic variation that may contribute to this "missing heritability" is that which differs in magnitude and/or direction between males and females, which could result from sexual dimorphism in gene expression. Such sex-differentiated effects are common in model organisms, and are becoming increasingly evident in human complex traits through large-scale male- and female-specific meta-analyses. In this article, we review the methodology for meta-analysis of sex-specific genome-wide association studies, and propose a sex-differentiated test of association with quantitative or dichotomous traits, which allows for heterogeneity of allelic effects between males and females. We perform detailed simulations to compare the power of the proposed sex-differentiated meta-analysis with the more traditional "sex-combined" approach, which is ambivalent to gender. The results of this study highlight only a small loss in power for the sex-differentiated meta-analysis when the allelic effects of the causal variant are the same in males and females. However, over a range of models of heterogeneity in allelic effects between genders, our sex-differentiated meta-analysis strategy offers substantial gains in power, and thus has the potential to discover novel loci contributing effects to complex human traits with existing genome-wide association data. © 2010 Wiley-Liss, Inc.

Measuring the statistical validity of summary meta-analysis and meta-regression results for use in clinical practice.

PubMed

Willis, Brian H; Riley, Richard D

2017-09-20

An important question for clinicians appraising a meta-analysis is: are the findings likely to be valid in their own practice-does the reported effect accurately represent the effect that would occur in their own clinical population? To this end we advance the concept of statistical validity-where the parameter being estimated equals the corresponding parameter for a new independent study. Using a simple ('leave-one-out') cross-validation technique, we demonstrate how we may test meta-analysis estimates for statistical validity using a new validation statistic, Vn, and derive its distribution. We compare this with the usual approach of investigating heterogeneity in meta-analyses and demonstrate the link between statistical validity and homogeneity. Using a simulation study, the properties of Vn and the Q statistic are compared for univariate random effects meta-analysis and a tailored meta-regression model, where information from the setting (included as model covariates) is used to calibrate the summary estimate to the setting of application. Their properties are found to be similar when there are 50 studies or more, but for fewer studies Vn has greater power but a higher type 1 error rate than Q. The power and type 1 error rate of Vn are also shown to depend on the within-study variance, between-study variance, study sample size, and the number of studies in the meta-analysis. Finally, we apply Vn to two published meta-analyses and conclude that it usefully augments standard methods when deciding upon the likely validity of summary meta-analysis estimates in clinical practice. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Advances in the meta-analysis of heterogeneous clinical trials I: The inverse variance heterogeneity model.

PubMed

Doi, Suhail A R; Barendregt, Jan J; Khan, Shahjahan; Thalib, Lukman; Williams, Gail M

2015-11-01

This article examines an improved alternative to the random effects (RE) model for meta-analysis of heterogeneous studies. It is shown that the known issues of underestimation of the statistical error and spuriously overconfident estimates with the RE model can be resolved by the use of an estimator under the fixed effect model assumption with a quasi-likelihood based variance structure - the IVhet model. Extensive simulations confirm that this estimator retains a correct coverage probability and a lower observed variance than the RE model estimator, regardless of heterogeneity. When the proposed IVhet method is applied to the controversial meta-analysis of intravenous magnesium for the prevention of mortality after myocardial infarction, the pooled OR is 1.01 (95% CI 0.71-1.46) which not only favors the larger studies but also indicates more uncertainty around the point estimate. In comparison, under the RE model the pooled OR is 0.71 (95% CI 0.57-0.89) which, given the simulation results, reflects underestimation of the statistical error. Given the compelling evidence generated, we recommend that the IVhet model replace both the FE and RE models. To facilitate this, it has been implemented into free meta-analysis software called MetaXL which can be downloaded from www.epigear.com. Copyright © 2015 Elsevier Inc. All rights reserved.

Quantifying the impact of between-study heterogeneity in multivariate meta-analyses

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2012-01-01

Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R2 statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I2, which we call . We also provide a multivariate H2 statistic, the ratio of a generalisation of Cochran's heterogeneity statistic and its associated degrees of freedom, with an accompanying generalisation of the usual I2 statistic, . Our proposed heterogeneity statistics can be used alongside all the usual estimates and inferential procedures used in multivariate meta-analysis. We apply our methods to some real datasets and show how our statistics are equally appropriate in the context of multivariate meta-regression, where study level covariate effects are included in the model. Our heterogeneity statistics may be used when applying any procedure for fitting the multivariate random effects model. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22763950

Meta-analysis of the efficacy of psychological and educational interventions to improve academic performance of students with learning disabilities in Iran

PubMed Central

Faramarzi, Salar; Shamsi, Abdolhossein; Samadi, Maryam; Ahmadzade, Maryam

2015-01-01

Introduction: with due attention to the importance of learning disabilities and necessity of presenting interventions for improvement of these disorders in order to prevent future problems, this study used meta-analysis of the research model on the impact of psychological and educational interventions to improve academic performance of students with learning disabilities. Methods: with the use of meta-analysis method by integrating the results of various researches, this study specifies the effect of psychological and educational interventions. In this order, 57 studies, which their methodology was accepted, were selected and meta-analysis was performed on them. The research instrument was a meta-analysis checklist. Results: The effect size for the effectiveness of psychological-educational interventions on improving the academic performance of students with mathematics disorder (0.57), impaired writing (0.50) and dyslexia (0.55) were reported. Conclusions: The result of meta-analysis showed that according to Cohen's table, the effect size is above average, and it can be said that educational and psychological interventions improve the academic performance of students with learning disabilities. PMID:26430685

Meta-analysis of the efficacy of psychological and educational interventions to improve academic performance of students with learning disabilities in Iran.

PubMed

Faramarzi, Salar; Shamsi, Abdolhossein; Samadi, Maryam; Ahmadzade, Maryam

2015-01-01

with due attention to the importance of learning disabilities and necessity of presenting interventions for improvement of these disorders in order to prevent future problems, this study used meta-analysis of the research model on the impact of psychological and educational interventions to improve academic performance of students with learning disabilities. with the use of meta-analysis method by integrating the results of various researches, this study specifies the effect of psychological and educational interventions. In this order, 57 studies, which their methodology was accepted, were selected and meta-analysis was performed on them. The research instrument was a meta-analysis checklist. The effect size for the effectiveness of psychological-educational interventions on improving the academic performance of students with mathematics disorder (0.57), impaired writing (0.50) and dyslexia (0.55) were reported. The result of meta-analysis showed that according to Cohen's table, the effect size is above average, and it can be said that educational and psychological interventions improve the academic performance of students with learning disabilities.

Collaborative Chronic Care Models for Mental Health Conditions: Cumulative Meta-Analysis and Meta-Regression to Guide Future Research and Implementation

PubMed Central

Grogan-Kaylor, Andrew; Perron, Brian E.; Kilbourne, Amy M.; Woltmann, Emily; Bauer, Mark S.

2013-01-01

Objective Prior meta-analysis indicates that collaborative chronic care models (CCMs) improve mental and physical health outcomes for individuals with mental disorders. This study aimed to investigate the stability of evidence over time and identify patient and intervention factors associated with CCM effects in order to facilitate implementation and sustainability of CCMs in clinical practice. Method We reviewed 53 CCM trials that analyzed depression, mental quality of life (QOL), or physical QOL outcomes. Cumulative meta-analysis and meta-regression were supplemented by descriptive investigations across and within trials. Results Most trials targeted depression in the primary care setting, and cumulative meta-analysis indicated that effect sizes favoring CCM quickly achieved significance for depression outcomes, and more recently achieved significance for mental and physical QOL. Four of six CCM elements (patient self-management support, clinical information systems, system redesign, and provider decision support) were common among reviewed trials, while two elements (healthcare organization support and linkages to community resources) were rare. No single CCM element was statistically associated with the success of the model. Similarly, meta-regression did not identify specific factors associated with CCM effectiveness. Nonetheless, results within individual trials suggest that increased illness severity predicts CCM outcomes. Conclusions Significant CCM trials have been derived primarily from four original CCM elements. Nonetheless, implementing and sustaining this established model will require healthcare organization support. While CCMs have typically been tested as population-based interventions, evidence supports stepped care application to more severely ill individuals. Future priorities include developing implementation strategies to support adoption and sustainability of the model in clinical settings while maximizing fit of this multi-component framework to local contextual factors. PMID:23938600

Digital Games, Design, and Learning: A Systematic Review and Meta-Analysis

ERIC Educational Resources Information Center

Clark, Douglas B.; Tanner-Smith, Emily E.; Killingsworth, Stephen S.

2016-01-01

In this meta-analysis, we systematically reviewed research on digital games and learning for K-16 students. We synthesized comparisons of game versus nongame conditions (i.e., media comparisons) and comparisons of augmented games versus standard game designs (i.e., value-added comparisons). We used random-effects meta-regression models with robust…

Statin use and the risk of Clostridium difficile infection: a systematic review with meta-analysis.

PubMed

Tariq, Raseen; Mukhija, Dhruvika; Gupta, Arjun; Singh, Siddharth; Pardi, Darrell S; Khanna, Sahil

2018-01-01

Statins have pleiotropic effects beyond cholesterol lowering by immune modulation. The association of statins with primary Clostridium difficile infection (CDI) is unclear as studies have reported conflicting findings. We performed a systematic review and meta-analysis to evaluate the association between statin use and CDI. We searched MEDLINE, Embase, and Web of Science from January 1978 to December 2016 for studies assessing the association between statin use and CDI. The Newcastle-Ottawa Scale was used to assess the methodologic quality of included studies. Weighted summary estimates were calculated using generalized inverse variance with random-effects model. Eight studies (6 case-control and 2 cohort) were included in the meta-analysis, which comprised 156,722 patients exposed to statins and 356,185 controls, with 34,849 total cases of CDI available in 7 studies. The rate of CDI in patients with statin use was 4.3%, compared with 7.8% in patients without statin use. An overall meta-analysis of 8 studies using the random-effects model demonstrated that statins may be associated with a decreased risk of CDI (maximally adjusted odds ratio [OR], 0.80; 95% CI, 0.66-0.97; P =0.02). There was significant heterogeneity among the studies, with an I 2 of 79%. No publication bias was seen. Meta-analysis of studies that adjusted for confounders revealed no protective effect of statins (adjusted OR, 0.84; 95% CI, 0.70-1.01; P =0.06, I 2 =75%). However, a meta-analysis of only full-text studies using the random-effects model demonstrated a decreased risk of CDI with the use of statins (OR 0.77; 95% CI, 0.61-0.99; P =0.04, I 2 =85%). Meta-analyses of existing studies suggest that patients prescribed a statin may be at decreased risk for CDI. The results must be interpreted with caution given the significant heterogeneity and lack of benefit on analysis of studies that adjusted for confounders.

The Effect of Learning Cycle Models on Achievement of Students: A Meta-Analysis Study

ERIC Educational Resources Information Center

Sarac, Hakan

2018-01-01

In the study, a meta-analysis was conducted to determine the effect of the use of the learning cycle model on the achievements of the students. Doctorate and master theses, made between 2007 and 2016, were searched using the keywords in Turkish and English. As a result of the screening, a total of 123 dissertations, which used learning cycle…

Counseling Outcomes from 1990 to 2008 for School-Age Youth with Depression: A Meta-Analysis

ERIC Educational Resources Information Center

Erford, Bradley T.; Erford, Breann M.; Lattanzi, Gina; Weller, Janet; Schein, Hallie; Wolf, Emily; Hughes, Meredith; Darrow, Jenna; Savin-Murphy, Janet; Peacock, Elizabeth

2011-01-01

Clinical trials exploring the effectiveness of counseling and psychotherapy in treatment of depression in school-age youth composed this meta-analysis. Results were synthesized using a random effects model for mean difference and mean gain effect size estimates. No effects of moderating variables were evident. Counseling and psychotherapy are…

Evidence synthesis for medical decision making and the appropriate use of quality scores.

PubMed

Doi, Suhail A R

2014-09-01

Meta-analyses today continue to be run using conventional random-effects models that ignore tangible information from studies such as the quality of the studies involved, despite the expectation that results of better quality studies reflect more valid results. Previous research has suggested that quality scores derived from such quality appraisals are unlikely to be useful in meta-analysis, because they would produce biased estimates of effects that are unlikely to be offset by a variance reduction within the studied models. However, previous discussions took place in the context of such scores viewed in terms of their ability to maximize their association with both the magnitude and direction of bias. In this review, another look is taken at this concept, this time asserting that probabilistic bias quantification is not possible or even required of quality scores when used in meta-analysis for redistribution of weights. The use of such a model is contrasted with the conventional random effects model of meta-analysis to demonstrate why the latter is inadequate in the face of a properly specified quality score weighting method. © 2014 Marshfield Clinic.

A Bayesian approach to meta-analysis of plant pathology studies.

PubMed

Mila, A L; Ngugi, H K

2011-01-01

Bayesian statistical methods are used for meta-analysis in many disciplines, including medicine, molecular biology, and engineering, but have not yet been applied for quantitative synthesis of plant pathology studies. In this paper, we illustrate the key concepts of Bayesian statistics and outline the differences between Bayesian and classical (frequentist) methods in the way parameters describing population attributes are considered. We then describe a Bayesian approach to meta-analysis and present a plant pathological example based on studies evaluating the efficacy of plant protection products that induce systemic acquired resistance for the management of fire blight of apple. In a simple random-effects model assuming a normal distribution of effect sizes and no prior information (i.e., a noninformative prior), the results of the Bayesian meta-analysis are similar to those obtained with classical methods. Implementing the same model with a Student's t distribution and a noninformative prior for the effect sizes, instead of a normal distribution, yields similar results for all but acibenzolar-S-methyl (Actigard) which was evaluated only in seven studies in this example. Whereas both the classical (P = 0.28) and the Bayesian analysis with a noninformative prior (95% credibility interval [CRI] for the log response ratio: -0.63 to 0.08) indicate a nonsignificant effect for Actigard, specifying a t distribution resulted in a significant, albeit variable, effect for this product (CRI: -0.73 to -0.10). These results confirm the sensitivity of the analytical outcome (i.e., the posterior distribution) to the choice of prior in Bayesian meta-analyses involving a limited number of studies. We review some pertinent literature on more advanced topics, including modeling of among-study heterogeneity, publication bias, analyses involving a limited number of studies, and methods for dealing with missing data, and show how these issues can be approached in a Bayesian framework. Bayesian meta-analysis can readily include information not easily incorporated in classical methods, and allow for a full evaluation of competing models. Given the power and flexibility of Bayesian methods, we expect them to become widely adopted for meta-analysis of plant pathology studies.

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Effect of soy isoflavone supplementation on plasma lipoprotein(a) concentrations: A meta-analysis.

PubMed

Simental-Mendía, Luis E; Gotto, Antonio M; Atkin, Stephen L; Banach, Maciej; Pirro, Matteo; Sahebkar, Amirhossein

Soy supplementation has been shown to reduce total and low-density lipoprotein cholesterol, while increasing high-density lipoprotein cholesterol. However, contradictory effects of soy isoflavone supplementation on lipoprotein(a) [Lp(a)] have been reported suggesting the need for a meta-analysis to be undertaken. The aim of the study was to investigate the impact of supplementation with soy isoflavones on plasma Lp(a) levels through a systematic review and meta-analysis of eligible randomized placebo-controlled trials. The search included PubMed-Medline, Scopus, ISI Web of Knowledge, and Google Scholar databases (by March 26, 2017), and quality of studies was evaluated according to Cochrane criteria. Quantitative data synthesis was performed using a random-effects model, with standardized mean difference and 95% confidence interval as summary statistics. Meta-regression and leave-one-out sensitivity analysis were performed to assess the modifiers of treatment response. Ten eligible studies comprising 11 treatment arms with 973 subjects were selected for the meta-analysis. Meta-analysis did not suggest any significant alteration of plasma Lp(a) levels after supplementation with soy isoflavones (standardized mean difference: 0.08, 95% confidence interval: -0.05, 0.20, P = .228). The effect size was robust in the leave-one-out sensitivity analysis. In meta-regression analysis, neither dose nor duration of supplementation with soy isoflavones was significantly associated with the effect size. This meta-analysis of the 10 available randomized placebo-controlled trials revealed no significant effect of soy isoflavones treatment on plasma Lp(a) concentrations. Copyright © 2017 National Lipid Association. Published by Elsevier Inc. All rights reserved.

Meta-analysis of diagnostic test data: a bivariate Bayesian modeling approach.

PubMed

Verde, Pablo E

2010-12-30

In the last decades, the amount of published results on clinical diagnostic tests has expanded very rapidly. The counterpart to this development has been the formal evaluation and synthesis of diagnostic results. However, published results present substantial heterogeneity and they can be regarded as so far removed from the classical domain of meta-analysis, that they can provide a rather severe test of classical statistical methods. Recently, bivariate random effects meta-analytic methods, which model the pairs of sensitivities and specificities, have been presented from the classical point of view. In this work a bivariate Bayesian modeling approach is presented. This approach substantially extends the scope of classical bivariate methods by allowing the structural distribution of the random effects to depend on multiple sources of variability. Meta-analysis is summarized by the predictive posterior distributions for sensitivity and specificity. This new approach allows, also, to perform substantial model checking, model diagnostic and model selection. Statistical computations are implemented in the public domain statistical software (WinBUGS and R) and illustrated with real data examples. Copyright © 2010 John Wiley & Sons, Ltd.

Video Modeling for Children and Adolescents with Autism Spectrum Disorder: A Meta-Analysis

ERIC Educational Resources Information Center

Thompson, Teresa Lynn

2014-01-01

The objective of this research was to conduct a meta-analysis to examine existing research studies on video modeling as an effective teaching tool for children and adolescents diagnosed with Autism Spectrum Disorder (ASD). Study eligibility criteria included (a) single case research design using multiple baselines, alternating treatment designs,…

Advances in the meta-analysis of heterogeneous clinical trials II: The quality effects model.

PubMed

Doi, Suhail A R; Barendregt, Jan J; Khan, Shahjahan; Thalib, Lukman; Williams, Gail M

2015-11-01

This article examines the performance of the updated quality effects (QE) estimator for meta-analysis of heterogeneous studies. It is shown that this approach leads to a decreased mean squared error (MSE) of the estimator while maintaining the nominal level of coverage probability of the confidence interval. Extensive simulation studies confirm that this approach leads to the maintenance of the correct coverage probability of the confidence interval, regardless of the level of heterogeneity, as well as a lower observed variance compared to the random effects (RE) model. The QE model is robust to subjectivity in quality assessment down to completely random entry, in which case its MSE equals that of the RE estimator. When the proposed QE method is applied to a meta-analysis of magnesium for myocardial infarction data, the pooled mortality odds ratio (OR) becomes 0.81 (95% CI 0.61-1.08) which favors the larger studies but also reflects the increased uncertainty around the pooled estimate. In comparison, under the RE model, the pooled mortality OR is 0.71 (95% CI 0.57-0.89) which is less conservative than that of the QE results. The new estimation method has been implemented into the free meta-analysis software MetaXL which allows comparison of alternative estimators and can be downloaded from www.epigear.com. Copyright © 2015 Elsevier Inc. All rights reserved.

Interventions to Improve Medication Adherence among Older Adults: Meta-Analysis of Adherence Outcomes among Randomized Controlled Trials

ERIC Educational Resources Information Center

Conn, Vicki S.; Hafdahl, Adam R.; Cooper, Pamela S.; Ruppar, Todd M.; Mehr, David R.; Russell, Cynthia L.

2009-01-01

Purpose: This study investigated the effectiveness of interventions to improve medication adherence (MA) in older adults. Design and Methods: Meta-analysis was used to synthesize results of 33 published and unpublished randomized controlled trials. Random-effects models were used to estimate overall mean effect sizes (ESs) for MA, knowledge,…

Effect of Whey Supplementation on Circulating C-Reactive Protein: A Meta-Analysis of Randomized Controlled Trials

PubMed Central

Zhou, Ling-Mei; Xu, Jia-Ying; Rao, Chun-Ping; Han, Shufen; Wan, Zhongxiao; Qin, Li-Qiang

2015-01-01

Whey supplementation is beneficial for human health, possibly by reducing the circulating C-reactive protein (CRP) level, a sensitive marker of inflammation. Thus, a meta-analysis of randomized controlled trials was conducted to evaluate their relationship. A systematic literature search was conducted in July, 2014, to identify eligible studies. Either a fixed-effects model or a random-effects model was used to calculate pooled effects. The meta-analysis results of nine trials showed a slight, but no significant, reduction of 0.42 mg/L (95% CI −0.96, 0.13) in CRP level with the supplementation of whey protein and its derivates. Relatively high heterogeneity across studies was observed. Subgroup analyses showed that whey significantly lowered CRP by 0.72 mg/L (95% CI −0.97, −0.47) among trials with a daily whey dose ≥20 g/day and by 0.67 mg/L (95% CI −1.21, −0.14) among trials with baseline CRP ≥3 mg/L. Meta-regression analysis revealed that the baseline CRP level was a potential effect modifier of whey supplementation in reducing CRP. In conclusion, our meta-analysis did not find sufficient evidence that whey and its derivates elicited a beneficial effect in reducing circulating CRP. However, they may significantly reduce CRP among participants with highly supplemental doses or increased baseline CRP levels. PMID:25671415

SLC6A3 polymorphism and response to methylphenidate in children with ADHD: A systematic review and meta-analysis.

PubMed

Soleimani, Robabeh; Salehi, Zivar; Soltanipour, Soheil; Hasandokht, Tolou; Jalali, Mir Mohammad

2018-04-01

Methylphenidate (MPH) is the most commonly used treatment for attention-deficit hyperactivity disorder (ADHD) in children. However, the response to MPH is not similar in all patients. This meta-analysis investigated the potential role of SLC6A3 polymorphisms in response to MPH in children with ADHD. Clinical trials or naturalistic studies were selected from electronic databases. A meta-analysis was conducted using a random-effects model. Cohen's d effect size and 95% confidence intervals (CIs) were determined. Sensitivity analysis and meta-regression were performed. Q-statistic and Egger's tests were conducted to evaluate heterogeneity and publication bias, respectively. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was used to assess the quality of evidence. Sixteen studies with follow-up periods of 1-28 weeks were eligible. The mean treatment acceptability of MPH was 97.2%. In contrast to clinical trials, the meta-analysis of naturalistic studies indicated that children without 10/10 repeat carriers had better response to MPH (Cohen's d: -0.09 and 0.44, respectively). The 9/9 repeat polymorphism had no effect on the response rate (Cohen's d: -0.43). In the meta-regression, a significant association was observed between baseline severity of ADHD, MPH dosage, and combined type of ADHD in some genetic models. Sensitivity analysis indicated the robustness of our findings. No publication bias was observed in our meta-analysis. The GRADE evaluations revealed very low levels of confidence for each outcome of response to MPH. The results of clinical trials and naturalistic studies regarding the effect size between different polymorphisms of SLC6A3 were contradictory. Therefore, further research is recommended. © 2017 Wiley Periodicals, Inc.

Complement factor H Y402H variant and risk of age-related macular degeneration in Asians: a systematic review and meta-analysis.

PubMed

Kondo, Naoshi; Bessho, Hiroaki; Honda, Shigeru; Negi, Akira

2011-02-01

To investigate whether the Y402H variant in the complement factor H gene is associated with age-related macular degeneration (AMD) in Asian populations. Meta-analysis of previous publications. Case-control groups of subjects with AMD and controls from 13 association studies. We performed a meta-analysis of the association between Y402H and AMD in Asian populations using data available from 13 case-control studies involving 3973 subjects. Summary odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using fixed- and random-effects models. The Q-statistic test was used to assess heterogeneity, and Egger's test was used to evaluate publication bias. Sensitivity analysis, cumulative meta-analysis, and meta-regression analysis were also performed. Allele and genotype frequencies of the Y402H variant. The Y402H variant showed a significant summary OR of 1.97 (95% CI, 1.54-2.52; P<0.001; allelic contrast model) per allele. Possession of at least 1 copy of the C allele increased the disease risk by 1.97-fold (95% CI, 1.63-2.39; P<0.001; dominant model) and accounted for 8.8% of the attributable risk of AMD in Asian populations. Sensitivity analysis indicated the robustness of our findings, and evidence of publication bias was not observed in our meta-analysis. Meta-regression analysis indicated no significant effect of baseline study characteristics on the summary effect size. Cumulative meta-analysis revealed that the summary ORs were stable and the 95% CIs narrowed with the accumulation of data over time. Our analysis provides substantial evidence that the Y402H variant is significantly associated with AMD in Asian populations. Our results expand the number of confirmed AMD susceptibility loci for Asians populations, which provide a better understanding of the genetic architecture underlying disease susceptibility and may advance the potential for preclinical prediction in future genetic tests by a combined evaluation of inherited susceptibility with previously established loci. Copyright © 2011 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

The impact of pneumatic tube system on routine laboratory parameters: a systematic review and meta-analysis.

PubMed

Kapoula, Georgia V; Kontou, Panagiota I; Bagos, Pantelis G

2017-10-26

Pneumatic tube system (PTS) is a widely used method of transporting blood samples in hospitals. The aim of this study was to evaluate the effects of the PTS transport in certain routine laboratory parameters as it has been implicated with hemolysis. A systematic review and a meta-analysis were conducted. PubMed and Scopus databases were searched (up until November 2016) to identify prospective studies evaluating the impact of PTS transport in hematological, biochemical and coagulation measurements. The random-effects model was used in the meta-analysis utilizing the mean difference (MD). Heterogeneity was quantitatively assessed using the Cohran's Q and the I2 index. Subgroup analysis, meta-regression analysis, sensitivity analysis, cumulative meta-analysis and assessment of publication bias were performed for all outcomes. From a total of 282 studies identified by the searching procedure, 24 were finally included in the meta-analysis. The meta-analysis yielded statistically significant results for potassium (K) [MD=0.04 mmol/L; 95% confidence interval (CI)=0.015-0.065; p=0.002], lactate dehydrogenase (LDH) (MD=10.343 U/L; 95% CI=6.132-14.554; p<10-4) and aspartate aminotransferase (AST) (MD=1.023 IU/L; 95% CI=0.344-1.702; p=0.003). Subgroup analysis and random-effects meta-regression analysis according to the speed and distance of the samples traveled via the PTS revealed that there is relation between the rate and the distance of PTS with the measurements of K, LDH, white blood cells and red blood cells. This meta-analysis suggests that PTS may be associated with alterations in K, LDH and AST measurements. Although these findings may not have any significant clinical effect on laboratory results, it is wise that each hospital validates their PTS.

Uncertainty in the Bayesian meta-analysis of normally distributed surrogate endpoints

PubMed Central

Thompson, John R; Spata, Enti; Abrams, Keith R

2015-01-01

We investigate the effect of the choice of parameterisation of meta-analytic models and related uncertainty on the validation of surrogate endpoints. Different meta-analytical approaches take into account different levels of uncertainty which may impact on the accuracy of the predictions of treatment effect on the target outcome from the treatment effect on a surrogate endpoint obtained from these models. A range of Bayesian as well as frequentist meta-analytical methods are implemented using illustrative examples in relapsing–remitting multiple sclerosis, where the treatment effect on disability worsening is the primary outcome of interest in healthcare evaluation, while the effect on relapse rate is considered as a potential surrogate to the effect on disability progression, and in gastric cancer, where the disease-free survival has been shown to be a good surrogate endpoint to the overall survival. Sensitivity analysis was carried out to assess the impact of distributional assumptions on the predictions. Also, sensitivity to modelling assumptions and performance of the models were investigated by simulation. Although different methods can predict mean true outcome almost equally well, inclusion of uncertainty around all relevant parameters of the model may lead to less certain and hence more conservative predictions. When investigating endpoints as candidate surrogate outcomes, a careful choice of the meta-analytical approach has to be made. Models underestimating the uncertainty of available evidence may lead to overoptimistic predictions which can then have an effect on decisions made based on such predictions. PMID:26271918

Uncertainty in the Bayesian meta-analysis of normally distributed surrogate endpoints.

PubMed

Bujkiewicz, Sylwia; Thompson, John R; Spata, Enti; Abrams, Keith R

2017-10-01

We investigate the effect of the choice of parameterisation of meta-analytic models and related uncertainty on the validation of surrogate endpoints. Different meta-analytical approaches take into account different levels of uncertainty which may impact on the accuracy of the predictions of treatment effect on the target outcome from the treatment effect on a surrogate endpoint obtained from these models. A range of Bayesian as well as frequentist meta-analytical methods are implemented using illustrative examples in relapsing-remitting multiple sclerosis, where the treatment effect on disability worsening is the primary outcome of interest in healthcare evaluation, while the effect on relapse rate is considered as a potential surrogate to the effect on disability progression, and in gastric cancer, where the disease-free survival has been shown to be a good surrogate endpoint to the overall survival. Sensitivity analysis was carried out to assess the impact of distributional assumptions on the predictions. Also, sensitivity to modelling assumptions and performance of the models were investigated by simulation. Although different methods can predict mean true outcome almost equally well, inclusion of uncertainty around all relevant parameters of the model may lead to less certain and hence more conservative predictions. When investigating endpoints as candidate surrogate outcomes, a careful choice of the meta-analytical approach has to be made. Models underestimating the uncertainty of available evidence may lead to overoptimistic predictions which can then have an effect on decisions made based on such predictions.

On the Multilevel Nature of Meta-Analysis: A Tutorial, Comparison of Software Programs, and Discussion of Analytic Choices.

PubMed

Pastor, Dena A; Lazowski, Rory A

2018-01-01

The term "multilevel meta-analysis" is encountered not only in applied research studies, but in multilevel resources comparing traditional meta-analysis to multilevel meta-analysis. In this tutorial, we argue that the term "multilevel meta-analysis" is redundant since all meta-analysis can be formulated as a special kind of multilevel model. To clarify the multilevel nature of meta-analysis the four standard meta-analytic models are presented using multilevel equations and fit to an example data set using four software programs: two specific to meta-analysis (metafor in R and SPSS macros) and two specific to multilevel modeling (PROC MIXED in SAS and HLM). The same parameter estimates are obtained across programs underscoring that all meta-analyses are multilevel in nature. Despite the equivalent results, not all software programs are alike and differences are noted in the output provided and estimators available. This tutorial also recasts distinctions made in the literature between traditional and multilevel meta-analysis as differences between meta-analytic choices, not between meta-analytic models, and provides guidance to inform choices in estimators, significance tests, moderator analyses, and modeling sequence. The extent to which the software programs allow flexibility with respect to these decisions is noted, with metafor emerging as the most favorable program reviewed.

A Systematic Review and Meta-analysis of the Association Between Giardia lamblia and Endemic Pediatric Diarrhea in Developing Countries

PubMed Central

Muhsen, Khitam; Levine, Myron M.

2012-01-01

We performed a systematic literature review and meta-analysis examining the association between diarrhea in young children in nonindustrialized settings and Giardia lamblia infection. Eligible were case/control and longitudinal studies that defined the outcome as acute or persistent (>14 days) diarrhea, adjusted for confounders and lasting for at least 1 year. Data on G. lamblia detection (mainly in stools) from diarrhea patients and controls without diarrhea were abstracted. Random effects model meta-analysis obtained pooled odds ratios (ORs) and 95% confidence intervals (CIs). Twelve nonindustrialized-setting acute pediatric diarrhea studies met the meta-analysis inclusion criteria. Random-effects model meta-analysis of combined results (9774 acute diarrhea cases and 8766 controls) yielded a pooled OR of 0.60 (95% CI, .38–.94; P = .03), indicating that G. lamblia was not associated with acute diarrhea. However, limited data suggest that initial Giardia infections in early infancy may be positively associated with diarrhea. Meta-analysis of 5 persistent diarrhea studies showed a pooled OR of 3.18 (95% CI, 1.50–6.76; P < .001), positively linking Giardia with that syndrome. The well-powered Global Enteric Multicenter Study (GEMS) is prospectively addressing the association between G. lamblia infection and diarrhea in children in developing countries. PMID:23169940

Meta-analysis for genome-wide association studies using case-control design: application and practice

PubMed Central

2016-01-01

This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy–Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The ‘genhwcci’ and ‘metan’ commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the ‘metareg’ command of STATA should be conducted to evaluate related factors of heterogeneities. PMID:28092928

[On the effectiveness of the homeopathic remedy Arnica montana].

PubMed

Lüdtke, Rainer; Hacke, Daniela

2005-11-01

Arnica montana is a homeopathic remedy often prescribed after traumata and injuries. To assess whether Arnica is effective beyond placebo and to identify factors which support or contradict this effectiveness. All prospective, controlled trials on the effectiveness of homeopathic Arnica were included. Overall effectiveness was assessed by meta-analysis and meta-regression techniques. 68 comparisons from 49 clinical trials show a significant effectiveness of Arnica in traumatic injuries in random effects meta-analysis (odds ratio [OR], 0.36; 95% confidence interval [CI], 0.24-0.55), but not in meta-regression models (OR, 0.37; CI, 0.11-1.24). We found no evidence for publication bias. Studies from Medline-listed journals and high-quality studies are less likely to report positive results (p = 0.0006 and p = 0.0167). The hypothesis that homeopathic Arnica is effective could neither be proved nor rejected. All trials were highly heterogeneous, meta-regression does not help to explain this heterogeneity substantially.

Dialectical Behavior Therapy for Borderline Personality Disorder: A Meta-Analysis Using Mixed-Effects Modeling

ERIC Educational Resources Information Center

Kliem, Soren; Kroger, Christoph; Kosfelder, Joachim

2010-01-01

Objective: At present, the most frequently investigated psychosocial intervention for borderline personality disorder (BPD) is dialectical behavior therapy (DBT). We conducted a meta-analysis to examine the efficacy and long-term effectiveness of DBT. Method: Systematic bibliographic research was undertaken to find relevant literature from online…

Maternal Employment and Children's Achievement in Context: A Meta-Analysis of Four Decades of Research

ERIC Educational Resources Information Center

Goldberg, Wendy A.; Prause, JoAnn; Lucas-Thompson, Rachel; Himsel, Amy

2008-01-01

This meta-analysis of 68 studies (770 effect sizes) used random effects models to examine whether children's achievement differed depending on whether their mothers were employed. Four achievement outcomes were emphasized: formal tests of achievement and intellectual functioning, grades, and teacher ratings of cognitive competence. When all…

A Meta-Analysis of Smoking Cessation Interventions With Individuals in Substance Abuse Treatment or Recovery

ERIC Educational Resources Information Center

Prochaska, Judith J.; Delucchi, Kevin; Hall, Sharon M.

2004-01-01

This meta-analysis examined outcomes of smoking cessation interventions evaluated in 19 randomized controlled trials with individuals in current addictions treatment or recovery. Smoking and substance use outcomes at posttreatment and long-term follow-up (? 6 months) were summarized with random effects models. Intervention effects for smoking…

A Critical Meta-Analysis of Lens Model Studies in Human Judgment and Decision-Making

PubMed Central

Kaufmann, Esther; Reips, Ulf-Dietrich; Wittmann, Werner W.

2013-01-01

Achieving accurate judgment (‘judgmental achievement’) is of utmost importance in daily life across multiple domains. The lens model and the lens model equation provide useful frameworks for modeling components of judgmental achievement and for creating tools to help decision makers (e.g., physicians, teachers) reach better judgments (e.g., a correct diagnosis, an accurate estimation of intelligence). Previous meta-analyses of judgment and decision-making studies have attempted to evaluate overall judgmental achievement and have provided the basis for evaluating the success of bootstrapping (i.e., replacing judges by linear models that guide decision making). However, previous meta-analyses have failed to appropriately correct for a number of study design artifacts (e.g., measurement error, dichotomization), which may have potentially biased estimations (e.g., of the variability between studies) and led to erroneous interpretations (e.g., with regards to moderator variables). In the current study we therefore conduct the first psychometric meta-analysis of judgmental achievement studies that corrects for a number of study design artifacts. We identified 31 lens model studies (N = 1,151, k = 49) that met our inclusion criteria. We evaluated overall judgmental achievement as well as whether judgmental achievement depended on decision domain (e.g., medicine, education) and/or the level of expertise (expert vs. novice). We also evaluated whether using corrected estimates affected conclusions with regards to the success of bootstrapping with psychometrically-corrected models. Further, we introduce a new psychometric trim-and-fill method to estimate the effect sizes of potentially missing studies correct psychometric meta-analyses for effects of publication bias. Comparison of the results of the psychometric meta-analysis with the results of a traditional meta-analysis (which only corrected for sampling error) indicated that artifact correction leads to a) an increase in values of the lens model components, b) reduced heterogeneity between studies, and c) increases the success of bootstrapping. We argue that psychometric meta-analysis is useful for accurately evaluating human judgment and show the success of bootstrapping. PMID:24391781

A critical meta-analysis of lens model studies in human judgment and decision-making.

PubMed

Kaufmann, Esther; Reips, Ulf-Dietrich; Wittmann, Werner W

2013-01-01

Achieving accurate judgment ('judgmental achievement') is of utmost importance in daily life across multiple domains. The lens model and the lens model equation provide useful frameworks for modeling components of judgmental achievement and for creating tools to help decision makers (e.g., physicians, teachers) reach better judgments (e.g., a correct diagnosis, an accurate estimation of intelligence). Previous meta-analyses of judgment and decision-making studies have attempted to evaluate overall judgmental achievement and have provided the basis for evaluating the success of bootstrapping (i.e., replacing judges by linear models that guide decision making). However, previous meta-analyses have failed to appropriately correct for a number of study design artifacts (e.g., measurement error, dichotomization), which may have potentially biased estimations (e.g., of the variability between studies) and led to erroneous interpretations (e.g., with regards to moderator variables). In the current study we therefore conduct the first psychometric meta-analysis of judgmental achievement studies that corrects for a number of study design artifacts. We identified 31 lens model studies (N = 1,151, k = 49) that met our inclusion criteria. We evaluated overall judgmental achievement as well as whether judgmental achievement depended on decision domain (e.g., medicine, education) and/or the level of expertise (expert vs. novice). We also evaluated whether using corrected estimates affected conclusions with regards to the success of bootstrapping with psychometrically-corrected models. Further, we introduce a new psychometric trim-and-fill method to estimate the effect sizes of potentially missing studies correct psychometric meta-analyses for effects of publication bias. Comparison of the results of the psychometric meta-analysis with the results of a traditional meta-analysis (which only corrected for sampling error) indicated that artifact correction leads to a) an increase in values of the lens model components, b) reduced heterogeneity between studies, and c) increases the success of bootstrapping. We argue that psychometric meta-analysis is useful for accurately evaluating human judgment and show the success of bootstrapping.

Game-based digital interventions for depression therapy: a systematic review and meta-analysis.

PubMed

Li, Jinhui; Theng, Yin-Leng; Foo, Schubert

2014-08-01

The aim of this study was to review the existing literature on game-based digital interventions for depression systematically and examine their effectiveness through a meta-analysis of randomized controlled trials (RCTs). Database searching was conducted using specific search terms and inclusion criteria. A standard meta-analysis was also conducted of available RCT studies with a random effects model. The standard mean difference (Cohen's d) was used to calculate the effect size of each study. Nineteen studies were included in the review, and 10 RCTs (eight studies) were included in the meta-analysis. Four types of game interventions-psycho-education and training, virtual reality exposure therapy, exercising, and entertainment-were identified, with various types of support delivered and populations targeted. The meta-analysis revealed a moderate effect size of the game interventions for depression therapy at posttreatment (d=-0.47 [95% CI -0.69 to -0.24]). A subgroup analysis showed that interventions based on psycho-education and training had a smaller effect than those based on the other forms, and that self-help interventions yielded better outcomes than supported interventions. A higher effect was achieved when a waiting list was used as the control. The review and meta-analysis support the effectiveness of game-based digital interventions for depression. More large-scale, high-quality RCT studies with sufficient long-term data for treatment evaluation are needed.

Game-Based Digital Interventions for Depression Therapy: A Systematic Review and Meta-Analysis

PubMed Central

Theng, Yin-Leng; Foo, Schubert

2014-01-01

Abstract The aim of this study was to review the existing literature on game-based digital interventions for depression systematically and examine their effectiveness through a meta-analysis of randomized controlled trials (RCTs). Database searching was conducted using specific search terms and inclusion criteria. A standard meta-analysis was also conducted of available RCT studies with a random effects model. The standard mean difference (Cohen's d) was used to calculate the effect size of each study. Nineteen studies were included in the review, and 10 RCTs (eight studies) were included in the meta-analysis. Four types of game interventions—psycho-education and training, virtual reality exposure therapy, exercising, and entertainment—were identified, with various types of support delivered and populations targeted. The meta-analysis revealed a moderate effect size of the game interventions for depression therapy at posttreatment (d=−0.47 [95% CI −0.69 to −0.24]). A subgroup analysis showed that interventions based on psycho-education and training had a smaller effect than those based on the other forms, and that self-help interventions yielded better outcomes than supported interventions. A higher effect was achieved when a waiting list was used as the control. The review and meta-analysis support the effectiveness of game-based digital interventions for depression. More large-scale, high-quality RCT studies with sufficient long-term data for treatment evaluation are needed. PMID:24810933

Meta-analysis in clinical trials revisited.

PubMed

DerSimonian, Rebecca; Laird, Nan

2015-11-01

In this paper, we revisit a 1986 article we published in this Journal, Meta-Analysis in Clinical Trials, where we introduced a random-effects model to summarize the evidence about treatment efficacy from a number of related clinical trials. Because of its simplicity and ease of implementation, our approach has been widely used (with more than 12,000 citations to date) and the "DerSimonian and Laird method" is now often referred to as the 'standard approach' or a 'popular' method for meta-analysis in medical and clinical research. The method is especially useful for providing an overall effect estimate and for characterizing the heterogeneity of effects across a series of studies. Here, we review the background that led to the original 1986 article, briefly describe the random-effects approach for meta-analysis, explore its use in various settings and trends over time and recommend a refinement to the method using a robust variance estimator for testing overall effect. We conclude with a discussion of repurposing the method for Big Data meta-analysis and Genome Wide Association Studies for studying the importance of genetic variants in complex diseases. Published by Elsevier Inc.

Meta-Analysis in Clinical Trials Revisited

PubMed Central

Laird, Nan

2015-01-01

In this paper, we revisit a 1986 article we published in this Journal, Meta-Analysis in Clinical Trials, where we introduced a random-effect model to summarize the evidence about treatment efficacy from a number of related clinical trials. Because of its simplicity and ease of implementation, our approach has been widely used (with more than 12,000 citations to date) and the “DerSimonian and Laird method” is now often referred to as the ‘standard approach’ or a ‘popular’ method for meta-analysis in medical and clinical research. The method is especially useful for providing an overall effect estimate and for characterizing the heterogeneity of effects across a series of studies. Here, we review the background that led to the original 1986 article, briefly describe the random-effects approach for meta-analysis, explore its use in various settings and trends over time and recommend a refinement to the method using a robust variance estimator for testing overall effect. We conclude with a discussion of repurposing the method for Big Data meta-analysis and Genome Wide Association Studies for studying the importance of genetic variants in complex diseases. PMID:26343745

Interaction between the FTO gene, body mass index and depression: meta-analysis of 13701 individuals†

PubMed Central

Rivera, Margarita; Locke, Adam E.; Corre, Tanguy; Czamara, Darina; Wolf, Christiane; Ching-Lopez, Ana; Milaneschi, Yuri; Kloiber, Stefan; Cohen-Woods, Sara; Rucker, James; Aitchison, Katherine J.; Bergmann, Sven; Boomsma, Dorret I.; Craddock, Nick; Gill, Michael; Holsboer, Florian; Hottenga, Jouke-Jan; Korszun, Ania; Kutalik, Zoltan; Lucae, Susanne; Maier, Wolfgang; Mors, Ole; Müller-Myhsok, Bertram; Owen, Michael J.; Penninx, Brenda W. J. H.; Preisig, Martin; Rice, John; Rietschel, Marcella; Tozzi, Federica; Uher, Rudolf; Vollenweider, Peter; Waeber, Gerard; Willemsen, Gonneke; Craig, Ian W.; Farmer, Anne E.; Lewis, Cathryn M.; Breen, Gerome; McGuffin, Peter

2017-01-01

Background Depression and obesity are highly prevalent, and major impacts on public health frequently co-occur. Recently, we reported that having depression moderates the effect of the FTO gene, suggesting its implication in the association between depression and obesity. Aims To confirm these findings by investigating the FTO polymorphism rs9939609 in new cohorts, and subsequently in a meta-analysis. Method The sample consists of 6902 individuals with depression and 6799 controls from three replication cohorts and two original discovery cohorts. Linear regression models were performed to test for association between rs9939609 and body mass index (BMI), and for the interaction between rs9939609 and depression status for an effect on BMI. Fixed and random effects meta-analyses were performed using METASOFT. Results In the replication cohorts, we observed a significant interaction between FTO, BMI and depression with fixed effects meta-analysis (β = 0.12, P = 2.7 × 10−4) and with the Han/Eskin random effects method (P = 1.4 × 10−7) but not with traditional random effects (β = 0.1, P = 0.35). When combined with the discovery cohorts, random effects meta-analysis also supports the interaction (β = 0.12, P = 0.027) being highly significant based on the Han/Eskin model (P = 6.9 × 10−8). On average, carriers of the risk allele who have depression have a 2.2% higher BMI for each risk allele, over and above the main effect of FTO. Conclusions This meta-analysis provides additional support for a significant interaction between FTO, depression and BMI, indicating that depression increases the effect of FTO on BMI. The findings provide a useful starting point in understanding the biological mechanism involved in the association between obesity and depression. PMID:28642257

The Effects of Mathematical Modelling on Students' Achievement-Meta-Analysis of Research

ERIC Educational Resources Information Center

Sokolowski, Andrzej

2015-01-01

Using meta-analytic techniques this study examined the effects of applying mathematical modelling to support student math knowledge acquisition at the high school and college levels. The research encompassed experimental studies published in peer-reviewed journals between January 1, 2000, and February 27, 2013. Such formulated orientation called…

Meta-Analyses of Diagnostic Accuracy in Imaging Journals: Analysis of Pooling Techniques and Their Effect on Summary Estimates of Diagnostic Accuracy.

PubMed

McGrath, Trevor A; McInnes, Matthew D F; Korevaar, Daniël A; Bossuyt, Patrick M M

2016-10-01

Purpose To determine whether authors of systematic reviews of diagnostic accuracy studies published in imaging journals used recommended methods for meta-analysis, and to evaluate the effect of traditional methods on summary estimates of sensitivity and specificity. Materials and Methods Medline was searched for published systematic reviews that included meta-analysis of test accuracy data limited to imaging journals published from January 2005 to May 2015. Two reviewers independently extracted study data and classified methods for meta-analysis as traditional (univariate fixed- or random-effects pooling or summary receiver operating characteristic curve) or recommended (bivariate model or hierarchic summary receiver operating characteristic curve). Use of methods was analyzed for variation with time, geographical location, subspecialty, and journal. Results from reviews in which study authors used traditional univariate pooling methods were recalculated with a bivariate model. Results Three hundred reviews met the inclusion criteria, and in 118 (39%) of those, authors used recommended meta-analysis methods. No change in the method used was observed with time (r = 0.54, P = .09); however, there was geographic (χ(2) = 15.7, P = .001), subspecialty (χ(2) = 46.7, P < .001), and journal (χ(2) = 27.6, P < .001) heterogeneity. Fifty-one univariate random-effects meta-analyses were reanalyzed with the bivariate model; the average change in the summary estimate was -1.4% (P < .001) for sensitivity and -2.5% (P < .001) for specificity. The average change in width of the confidence interval was 7.7% (P < .001) for sensitivity and 9.9% (P ≤ .001) for specificity. Conclusion Recommended methods for meta-analysis of diagnostic accuracy in imaging journals are used in a minority of reviews; this has not changed significantly with time. Traditional (univariate) methods allow overestimation of diagnostic accuracy and provide narrower confidence intervals than do recommended (bivariate) methods. (©) RSNA, 2016 Online supplemental material is available for this article.

Ego Depletion and the Strength Model of Self-Control: A Meta-Analysis

ERIC Educational Resources Information Center

Hagger, Martin S.; Wood, Chantelle; Stiff, Chris; Chatzisarantis, Nikos L. D.

2010-01-01

According to the strength model, self-control is a finite resource that determines capacity for effortful control over dominant responses and, once expended, leads to impaired self-control task performance, known as "ego depletion". A meta-analysis of 83 studies tested the effect of ego depletion on task performance and related outcomes,…

The Effectiveness of Physical Models in Teaching Anatomy: A Meta-Analysis of Comparative Studies

ERIC Educational Resources Information Center

Yammine, Kaissar; Violato, Claudio

2016-01-01

There are various educational methods used in anatomy teaching. While three dimensional (3D) visualization technologies are gaining ground due to their ever-increasing realism, reports investigating physical models as a low-cost 3D traditional method are still the subject of considerable interest. The aim of this meta-analysis is to quantitatively…

Dietary interventions to prevent and manage diabetes in worksite settings: a meta-analysis.

PubMed

Shrestha, Archana; Karmacharya, Biraj Man; Khudyakov, Polyna; Weber, Mary Beth; Spiegelman, Donna

2018-01-25

The translation of lifestyle intervention to improve glucose tolerance into the workplace has been rare. The objective of this meta-analysis is to summarize the evidence for the effectiveness of dietary interventions in worksite settings on lowering blood sugar levels. We searched for studies in PubMed, Embase, Econlit, Ovid, Cochrane, Web of Science, and Cumulative Index to Nursing and Allied Health Literature. Search terms were as follows: (1) Exposure-based: nutrition/diet/dietary intervention/health promotion/primary prevention/health behavior/health education/food /program evaluation; (2) Outcome-based: diabetes/hyperglycemia/glucose/HbA1c/glycated hemoglobin; and (3) Setting-based: workplace/worksite/occupational/industry/job/employee. We manually searched review articles and reference lists of articles identified from 1969 to December 2016. We tested for between-studies heterogeneity and calculated the pooled effect sizes for changes in HbA1c (%) and fasting glucose (mg/dl) using random effect models for meta-analysis in 2016. A total of 17 articles out of 1663 initially selected articles were included in the meta-analysis. With a random-effects model, worksite dietary interventions led to a pooled -0.18% (95% CI, -0.29 to -0.06; P<0.001) difference in HbA1c. With the random-effects model, the interventions resulted in 2.60 mg/dl lower fasting glucose with borderline significance (95% CI: -5.27 to 0.08, P=0.06). In the multivariate meta-regression model, the interventions with high percent of female participants and that used the intervention directly delivered to individuals, rather the environment changes, were associated with more effective interventions. Workplace dietary interventions can improve HbA1c. The effects were larger for the interventions with greater number of female participants and with individual-level interventions.

Robust variance estimation with dependent effect sizes: practical considerations including a software tutorial in Stata and spss.

PubMed

Tanner-Smith, Emily E; Tipton, Elizabeth

2014-03-01

Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and spss (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding the practical application and implementation of those macros. This paper provides a brief tutorial on the implementation of the Stata and spss macros and discusses practical issues meta-analysts should consider when estimating meta-regression models with robust variance estimates. Two example databases are used in the tutorial to illustrate the use of meta-analysis with robust variance estimates. Copyright © 2013 John Wiley & Sons, Ltd.

Meta-analyses on intra-aortic balloon pump in cardiogenic shock complicating acute myocardial infarction may provide biased results.

PubMed

Acconcia, M C; Caretta, Q; Romeo, F; Borzi, M; Perrone, M A; Sergi, D; Chiarotti, F; Calabrese, C M; Sili Scavalli, A; Gaudio, C

2018-04-01

Intra-aortic balloon pump (IABP) is the device most commonly investigated in patients with cardiogenic shock (CS) complicating acute myocardial infarction (AMI). Recently meta-analyses on this topic showed opposite results: some complied with the actual guideline recommendations, while others did not, due to the presence of bias. We investigated the reasons for the discrepancy among meta-analyses and strategies employed to avoid the potential source of bias. Scientific databases were searched for meta-analyses of IABP support in AMI complicated by CS. The presence of clinical diversity, methodological diversity and statistical heterogeneity were analyzed. When we found clinical or methodological diversity, we reanalyzed the data by comparing the patients selected for homogeneous groups. When the fixed effect model was employed despite the presence of statistical heterogeneity, the meta-analysis was repeated adopting the random effect model, with the same estimator used in the original meta-analysis. Twelve meta-analysis were selected. Six meta-analyses of randomized controlled trials (RCTs) were inconclusive because underpowered to detect the IABP effect. Five included RCTs and observational studies (Obs) and one only Obs. Some meta-analyses on RCTs and Obs had biased results due to presence of clinical and/or methodological diversity. The reanalysis of data reallocated for homogeneous groups was no more in contrast with guidelines recommendations. Meta-analyses performed without controlling for clinical and/or methodological diversity, represent a confounding message against a good clinical practice. The reanalysis of data demonstrates the validity of the current guidelines recommendations in addressing clinical decision making in providing IABP support in AMI complicated by CS.

Meta-analysis of diagnostic accuracy studies accounting for disease prevalence: alternative parameterizations and model selection.

PubMed

Chu, Haitao; Nie, Lei; Cole, Stephen R; Poole, Charles

2009-08-15

In a meta-analysis of diagnostic accuracy studies, the sensitivities and specificities of a diagnostic test may depend on the disease prevalence since the severity and definition of disease may differ from study to study due to the design and the population considered. In this paper, we extend the bivariate nonlinear random effects model on sensitivities and specificities to jointly model the disease prevalence, sensitivities and specificities using trivariate nonlinear random-effects models. Furthermore, as an alternative parameterization, we also propose jointly modeling the test prevalence and the predictive values, which reflect the clinical utility of a diagnostic test. These models allow investigators to study the complex relationship among the disease prevalence, sensitivities and specificities; or among test prevalence and the predictive values, which can reveal hidden information about test performance. We illustrate the proposed two approaches by reanalyzing the data from a meta-analysis of radiological evaluation of lymph node metastases in patients with cervical cancer and a simulation study. The latter illustrates the importance of carefully choosing an appropriate normality assumption for the disease prevalence, sensitivities and specificities, or the test prevalence and the predictive values. In practice, it is recommended to use model selection techniques to identify a best-fitting model for making statistical inference. In summary, the proposed trivariate random effects models are novel and can be very useful in practice for meta-analysis of diagnostic accuracy studies. Copyright 2009 John Wiley & Sons, Ltd.

A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2013-01-01

Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. PMID:23401213

Multivariate meta-analysis using individual participant data.

PubMed

Riley, R D; Price, M J; Jackson, D; Wardle, M; Gueyffier, F; Wang, J; Staessen, J A; White, I R

2015-06-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment-covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Borrowing of strength and study weights in multivariate and network meta-analysis.

PubMed

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2017-12-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of 'borrowing of strength'. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis).

Borrowing of strength and study weights in multivariate and network meta-analysis

PubMed Central

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2016-01-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of ‘borrowing of strength’. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis). PMID:26546254

Combinations of techniques that effectively change health behavior: evidence from Meta-CART analysis.

PubMed

Dusseldorp, Elise; van Genugten, Lenneke; van Buuren, Stef; Verheijden, Marieke W; van Empelen, Pepijn

2014-12-01

Many health-promoting interventions combine multiple behavior change techniques (BCTs) to maximize effectiveness. Although, in theory, BCTs can amplify each other, the available meta-analyses have not been able to identify specific combinations of techniques that provide synergistic effects. This study overcomes some of the shortcomings in the current methodology by applying classification and regression trees (CART) to meta-analytic data in a special way, referred to as Meta-CART. The aim was to identify particular combinations of BCTs that explain intervention success. A reanalysis of data from Michie, Abraham, Whittington, McAteer, and Gupta (2009) was performed. These data included effect sizes from 122 interventions targeted at physical activity and healthy eating, and the coding of the interventions into 26 BCTs. A CART analysis was performed using the BCTs as predictors and treatment success (i.e., effect size) as outcome. A subgroup meta-analysis using a mixed effects model was performed to compare the treatment effect in the subgroups found by CART. Meta-CART identified the following most effective combinations: Provide information about behavior-health link with Prompt intention formation (mean effect size ḡ = 0.46), and Provide information about behavior-health link with Provide information on consequences and Use of follow-up prompts (ḡ = 0.44). Least effective interventions were those using Provide feedback on performance without using Provide instruction (ḡ = 0.05). Specific combinations of BCTs increase the likelihood of achieving change in health behavior, whereas other combinations decrease this likelihood. Meta-CART successfully identified these combinations and thus provides a viable methodology in the context of meta-analysis.

Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

PubMed Central

Turner, Rebecca M; Davey, Jonathan; Clarke, Mike J; Thompson, Simon G; Higgins, Julian PT

2012-01-01

Background Many meta-analyses contain only a small number of studies, which makes it difficult to estimate the extent of between-study heterogeneity. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, and offers advantages over conventional random-effects meta-analysis. To assist in this, we provide empirical evidence on the likely extent of heterogeneity in particular areas of health care. Methods Our analyses included 14 886 meta-analyses from the Cochrane Database of Systematic Reviews. We classified each meta-analysis according to the type of outcome, type of intervention comparison and medical specialty. By modelling the study data from all meta-analyses simultaneously, using the log odds ratio scale, we investigated the impact of meta-analysis characteristics on the underlying between-study heterogeneity variance. Predictive distributions were obtained for the heterogeneity expected in future meta-analyses. Results Between-study heterogeneity variances for meta-analyses in which the outcome was all-cause mortality were found to be on average 17% (95% CI 10–26) of variances for other outcomes. In meta-analyses comparing two active pharmacological interventions, heterogeneity was on average 75% (95% CI 58–95) of variances for non-pharmacological interventions. Meta-analysis size was found to have only a small effect on heterogeneity. Predictive distributions are presented for nine different settings, defined by type of outcome and type of intervention comparison. For example, for a planned meta-analysis comparing a pharmacological intervention against placebo or control with a subjectively measured outcome, the predictive distribution for heterogeneity is a log-normal (−2.13, 1.582) distribution, which has a median value of 0.12. In an example of meta-analysis of six studies, incorporating external evidence led to a smaller heterogeneity estimate and a narrower confidence interval for the combined intervention effect. Conclusions Meta-analysis characteristics were strongly associated with the degree of between-study heterogeneity, and predictive distributions for heterogeneity differed substantially across settings. The informative priors provided will be very beneficial in future meta-analyses including few studies. PMID:22461129

Multivariate meta-analysis of prognostic factor studies with multiple cut-points and/or methods of measurement.

PubMed

Riley, Richard D; Elia, Eleni G; Malin, Gemma; Hemming, Karla; Price, Malcolm P

2015-07-30

A prognostic factor is any measure that is associated with the risk of future health outcomes in those with existing disease. Often, the prognostic ability of a factor is evaluated in multiple studies. However, meta-analysis is difficult because primary studies often use different methods of measurement and/or different cut-points to dichotomise continuous factors into 'high' and 'low' groups; selective reporting is also common. We illustrate how multivariate random effects meta-analysis models can accommodate multiple prognostic effect estimates from the same study, relating to multiple cut-points and/or methods of measurement. The models account for within-study and between-study correlations, which utilises more information and reduces the impact of unreported cut-points and/or measurement methods in some studies. The applicability of the approach is improved with individual participant data and by assuming a functional relationship between prognostic effect and cut-point to reduce the number of unknown parameters. The models provide important inferential results for each cut-point and method of measurement, including the summary prognostic effect, the between-study variance and a 95% prediction interval for the prognostic effect in new populations. Two applications are presented. The first reveals that, in a multivariate meta-analysis using published results, the Apgar score is prognostic of neonatal mortality but effect sizes are smaller at most cut-points than previously thought. In the second, a multivariate meta-analysis of two methods of measurement provides weak evidence that microvessel density is prognostic of mortality in lung cancer, even when individual participant data are available so that a continuous prognostic trend is examined (rather than cut-points). © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

A Meta-Analysis on the Effect of Instructional Designs Based on the Learning Styles Models on Academic Achievement, Attitude and Retention

ERIC Educational Resources Information Center

Kanadli, Sedat

2016-01-01

The purpose of this study is to calculate the effect size, by running a meta-analysis, of the experimental studies carried out in Turkey between 2004 and 2014 that investigate the effect of learning styles on academic achievement, attitude, retention, and to define whether the academic achievement shows a significant difference in terms of…

Links between physical fitness and cardiovascular reactivity and recovery to psychological stressors: A meta-analysis.

PubMed

Forcier, Kathleen; Stroud, Laura R; Papandonatos, George D; Hitsman, Brian; Reiches, Meredith; Krishnamoorthy, Jenelle; Niaura, Raymond

2006-11-01

A meta-analysis of published studies with adult human participants was conducted to evaluate whether physical fitness attenuates cardiovascular reactivity and improves recovery from acute psychological stressors. Thirty-three studies met selection criteria; 18 were included in recovery analyses. Effect sizes and moderator influences were calculated by using meta-analysis software. A fixed effects model was fit initially; however, between-studies heterogeneity could not be explained even after inclusion of moderators. Therefore, to account for residual heterogeneity, a random effects model was estimated. Under this model, fit individuals showed significantly attenuated heart rate and systolic blood pressure reactivity and a trend toward attenuated diastolic blood pressure reactivity. Fit individuals also showed faster heart rate recovery, but there were no significant differences in systolic blood pressure or diastolic blood pressure recovery. No significant moderators emerged. Results have important implications for elucidating mechanisms underlying effects of fitness on cardiovascular disease and suggest that fitness may be an important confound in studies of stress reactivity. Copyright 2006 APA, all rights reserved.

Observational studies using propensity score analysis underestimated the effect sizes in critical care medicine.

PubMed

Zhang, Zhongheng; Ni, Hongying; Xu, Xiao

2014-08-01

Propensity score (PS) analysis has been increasingly used in critical care medicine; however, its validation has not been systematically investigated. The present study aimed to compare effect sizes in PS-based observational studies vs. randomized controlled trials (RCTs) (or meta-analysis of RCTs). Critical care observational studies using PS were systematically searched in PubMed from inception to April 2013. Identified PS-based studies were matched to one or more RCTs in terms of population, intervention, comparison, and outcome. The effect sizes of experimental treatments were compared for PS-based studies vs. RCTs (or meta-analysis of RCTs) with sign test. Furthermore, ratio of odds ratio (ROR) was calculated from the interaction term of treatment × study type in a logistic regression model. A ROR < 1 indicates greater benefit for experimental treatment in RCTs compared with PS-based studies. RORs of each comparison were pooled by using meta-analytic approach with random-effects model. A total of 20 PS-based studies were identified and matched to RCTs. Twelve of the 20 comparisons showed greater beneficial effect for experimental treatment in RCTs than that in PS-based studies (sign test P = 0.503). The difference was statistically significant in four comparisons. ROR can be calculated from 13 comparisons, of which four showed significantly greater beneficial effect for experimental treatment in RCTs. The pooled ROR was 0.71 (95% CI: 0.63, 0.79; P = 0.002), suggesting that RCTs (or meta-analysis of RCTs) were more likely to report beneficial effect for the experimental treatment than PS-based studies. The result remained unchanged in sensitivity analysis and meta-regression. In critical care literature, PS-based observational study is likely to report less beneficial effect of experimental treatment compared with RCTs (or meta-analysis of RCTs). Copyright © 2014 Elsevier Inc. All rights reserved.

On meta- and mega-analyses for gene-environment interactions.

PubMed

Huang, Jing; Liu, Yulun; Vitale, Steve; Penning, Trevor M; Whitehead, Alexander S; Blair, Ian A; Vachani, Anil; Clapper, Margie L; Muscat, Joshua E; Lazarus, Philip; Scheet, Paul; Moore, Jason H; Chen, Yong

2017-12-01

Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a "mega" data set, which can be fit by a joint "mega-analysis." Alternatively, analyses can be done at each site, and results across sites can be combined through a "meta-analysis" procedure without integrating individual level data across sites. Although mega-analysis has been advocated in several recent initiatives, meta-analysis has the advantages of simplicity and feasibility, and has recently led to several important findings in identifying main genetic effects. In this paper, we conducted empirical and simulation studies, using data from a G × E study of lung cancer, to compare the mega- and meta-analyses in four commonly used G × E analyses under the scenario that the number of studies is small and sample sizes of individual studies are relatively large. We compared the two data integration approaches in the context of fixed effect models and random effects models separately. Our investigations provide valuable insights in understanding the differences between mega- and meta-analyses in practice of combining small number of studies in identifying G × E interactions. © 2017 WILEY PERIODICALS, INC.

Using meta-analytic path analysis to test theoretical predictions in health behavior: An illustration based on meta-analyses of the theory of planned behavior.

PubMed

Hagger, Martin S; Chan, Derwin K C; Protogerou, Cleo; Chatzisarantis, Nikos L D

2016-08-01

Synthesizing research on social cognitive theories applied to health behavior is an important step in the development of an evidence base of psychological factors as targets for effective behavioral interventions. However, few meta-analyses of research on social cognitive theories in health contexts have conducted simultaneous tests of theoretically-stipulated pattern effects using path analysis. We argue that conducting path analyses of meta-analytic effects among constructs from social cognitive theories is important to test nomological validity, account for mediation effects, and evaluate unique effects of theory constructs independent of past behavior. We illustrate our points by conducting new analyses of two meta-analyses of a popular theory applied to health behaviors, the theory of planned behavior. We conducted meta-analytic path analyses of the theory in two behavioral contexts (alcohol and dietary behaviors) using data from the primary studies included in the original meta-analyses augmented to include intercorrelations among constructs and relations with past behavior missing from the original analysis. Findings supported the nomological validity of the theory and its hypotheses for both behaviors, confirmed important model processes through mediation analysis, demonstrated the attenuating effect of past behavior on theory relations, and provided estimates of the unique effects of theory constructs independent of past behavior. Our analysis illustrates the importance of conducting a simultaneous test of theory-stipulated effects in meta-analyses of social cognitive theories applied to health behavior. We recommend researchers adopt this analytic procedure when synthesizing evidence across primary tests of social cognitive theories in health. Copyright © 2016 Elsevier Inc. All rights reserved.

Handling incomplete correlated continuous and binary outcomes in meta-analysis of individual participant data.

PubMed

Gomes, Manuel; Hatfield, Laura; Normand, Sharon-Lise

2016-09-20

Meta-analysis of individual participant data (IPD) is increasingly utilised to improve the estimation of treatment effects, particularly among different participant subgroups. An important concern in IPD meta-analysis relates to partially or completely missing outcomes for some studies, a problem exacerbated when interest is on multiple discrete and continuous outcomes. When leveraging information from incomplete correlated outcomes across studies, the fully observed outcomes may provide important information about the incompleteness of the other outcomes. In this paper, we compare two models for handling incomplete continuous and binary outcomes in IPD meta-analysis: a joint hierarchical model and a sequence of full conditional mixed models. We illustrate how these approaches incorporate the correlation across the multiple outcomes and the between-study heterogeneity when addressing the missing data. Simulations characterise the performance of the methods across a range of scenarios which differ according to the proportion and type of missingness, strength of correlation between outcomes and the number of studies. The joint model provided confidence interval coverage consistently closer to nominal levels and lower mean squared error compared with the fully conditional approach across the scenarios considered. Methods are illustrated in a meta-analysis of randomised controlled trials comparing the effectiveness of implantable cardioverter-defibrillator devices alone to implantable cardioverter-defibrillator combined with cardiac resynchronisation therapy for treating patients with chronic heart failure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Confidence Intervals for the Between-Study Variance in Random Effects Meta-Analysis Using Generalised Cochran Heterogeneity Statistics

ERIC Educational Resources Information Center

Jackson, Dan

2013-01-01

Statistical inference is problematic in the common situation in meta-analysis where the random effects model is fitted to just a handful of studies. In particular, the asymptotic theory of maximum likelihood provides a poor approximation, and Bayesian methods are sensitive to the prior specification. Hence, less efficient, but easily computed and…

One-stage individual participant data meta-analysis models: estimation of treatment-covariate interactions must avoid ecological bias by separating out within-trial and across-trial information.

PubMed

Hua, Hairui; Burke, Danielle L; Crowther, Michael J; Ensor, Joie; Tudur Smith, Catrin; Riley, Richard D

2017-02-28

Stratified medicine utilizes individual-level covariates that are associated with a differential treatment effect, also known as treatment-covariate interactions. When multiple trials are available, meta-analysis is used to help detect true treatment-covariate interactions by combining their data. Meta-regression of trial-level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta-analyses are preferable to examine interactions utilizing individual-level information. However, one-stage IPD models are often wrongly specified, such that interactions are based on amalgamating within- and across-trial information. We compare, through simulations and an applied example, fixed-effect and random-effects models for a one-stage IPD meta-analysis of time-to-event data where the goal is to estimate a treatment-covariate interaction. We show that it is crucial to centre patient-level covariates by their mean value in each trial, in order to separate out within-trial and across-trial information. Otherwise, bias and coverage of interaction estimates may be adversely affected, leading to potentially erroneous conclusions driven by ecological bias. We revisit an IPD meta-analysis of five epilepsy trials and examine age as a treatment effect modifier. The interaction is -0.011 (95% CI: -0.019 to -0.003; p = 0.004), and thus highly significant, when amalgamating within-trial and across-trial information. However, when separating within-trial from across-trial information, the interaction is -0.007 (95% CI: -0.019 to 0.005; p = 0.22), and thus its magnitude and statistical significance are greatly reduced. We recommend that meta-analysts should only use within-trial information to examine individual predictors of treatment effect and that one-stage IPD models should separate within-trial from across-trial information to avoid ecological bias. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Sequential sentinel SNP Regional Association Plots (SSS-RAP): an approach for testing independence of SNP association signals using meta-analysis data.

PubMed

Zheng, Jie; Gaunt, Tom R; Day, Ian N M

2013-01-01

Genome-Wide Association Studies (GWAS) frequently incorporate meta-analysis within their framework. However, conditional analysis of individual-level data, which is an established approach for fine mapping of causal sites, is often precluded where only group-level summary data are available for analysis. Here, we present a numerical and graphical approach, "sequential sentinel SNP regional association plot" (SSS-RAP), which estimates regression coefficients (beta) with their standard errors using the meta-analysis summary results directly. Under an additive model, typical for genes with small effect, the effect for a sentinel SNP can be transformed to the predicted effect for a possibly dependent SNP through a 2×2 2-SNP haplotypes table. The approach assumes Hardy-Weinberg equilibrium for test SNPs. SSS-RAP is available as a Web-tool (http://apps.biocompute.org.uk/sssrap/sssrap.cgi). To develop and illustrate SSS-RAP we analyzed lipid and ECG traits data from the British Women's Heart and Health Study (BWHHS), evaluated a meta-analysis for ECG trait and presented several simulations. We compared results with existing approaches such as model selection methods and conditional analysis. Generally findings were consistent. SSS-RAP represents a tool for testing independence of SNP association signals using meta-analysis data, and is also a convenient approach based on biological principles for fine mapping in group level summary data. © 2012 Blackwell Publishing Ltd/University College London.

In Sync and in Control: A Meta-Analysis of Parent-Child Positive Behavioral Synchrony and Youth Self-Regulation.

PubMed

Davis, Molly; Bilms, Joanie; Suveg, Cynthia

2017-12-01

A growing body of research has highlighted the connection between parent-child positive behavioral synchrony and youth self-regulation; however, this association has yet to be the focus of a meta-analytic review. Therefore, the present meta-analysis aimed to estimate the magnitude of the relation between parent-child positive behavioral synchrony and youth self-regulation and to identify moderator variables that can explain the variability in the degree of this association across the extant literature. A thorough literature search of two major databases, in addition to scanning the reference sections of relevant articles, yielded a total of 10 peer-reviewed articles (24 effect sizes, 658 children) that were eligible for inclusion in the current meta-analysis. Results from the overall mean effect size calculation using a random-effects model indicated that parent-child positive behavioral synchrony was significantly, positively correlated with youth self-regulation and the effect size was medium. Children's ages at the time of synchrony and self-regulation measurements, as well as parent gender, served as significant moderator variables. Findings from the present meta-analysis can help to refine existing theoretical models on the role of the parent-child relationship in youth adjustment. Prevention and intervention efforts may benefit from an increased emphasis on building parent-child positive behavioral synchrony to promote youth self-regulation and thus children's overall well-being. © 2016 Family Process Institute.

A brain-region-based meta-analysis method utilizing the Apriori algorithm.

PubMed

Niu, Zhendong; Nie, Yaoxin; Zhou, Qian; Zhu, Linlin; Wei, Jieyao

2016-05-18

Brain network connectivity modeling is a crucial method for studying the brain's cognitive functions. Meta-analyses can unearth reliable results from individual studies. Meta-analytic connectivity modeling is a connectivity analysis method based on regions of interest (ROIs) which showed that meta-analyses could be used to discover brain network connectivity. In this paper, we propose a new meta-analysis method that can be used to find network connectivity models based on the Apriori algorithm, which has the potential to derive brain network connectivity models from activation information in the literature, without requiring ROIs. This method first extracts activation information from experimental studies that use cognitive tasks of the same category, and then maps the activation information to corresponding brain areas by using the automatic anatomical label atlas, after which the activation rate of these brain areas is calculated. Finally, using these brain areas, a potential brain network connectivity model is calculated based on the Apriori algorithm. The present study used this method to conduct a mining analysis on the citations in a language review article by Price (Neuroimage 62(2):816-847, 2012). The results showed that the obtained network connectivity model was consistent with that reported by Price. The proposed method is helpful to find brain network connectivity by mining the co-activation relationships among brain regions. Furthermore, results of the co-activation relationship analysis can be used as a priori knowledge for the corresponding dynamic causal modeling analysis, possibly achieving a significant dimension-reducing effect, thus increasing the efficiency of the dynamic causal modeling analysis.

A Meta-Analysis of the Relation between RAN and Mathematics

ERIC Educational Resources Information Center

Koponen, Tuire; Georgiou, George; Salmi, Paula; Leskinen, Markku; Aro, Mikko

2017-01-01

Several studies have shown that rapid automatized naming (RAN) is a significant predictor of mathematics, but the nature of their relationship remains elusive. Thus, the purpose of this meta-analysis was to estimate the size of their relationship and determine the conditions under which they correlate. We used a random-effects model analysis of…

The value of a statistical life: a meta-analysis with a mixed effects regression model.

PubMed

Bellavance, François; Dionne, Georges; Lebeau, Martin

2009-03-01

The value of a statistical life (VSL) is a very controversial topic, but one which is essential to the optimization of governmental decisions. We see a great variability in the values obtained from different studies. The source of this variability needs to be understood, in order to offer public decision-makers better guidance in choosing a value and to set clearer guidelines for future research on the topic. This article presents a meta-analysis based on 39 observations obtained from 37 studies (from nine different countries) which all use a hedonic wage method to calculate the VSL. Our meta-analysis is innovative in that it is the first to use the mixed effects regression model [Raudenbush, S.W., 1994. Random effects models. In: Cooper, H., Hedges, L.V. (Eds.), The Handbook of Research Synthesis. Russel Sage Foundation, New York] to analyze studies on the value of a statistical life. We conclude that the variability found in the values studied stems in large part from differences in methodologies.

Effect of Desflurane versus Sevoflurane in Pediatric Anesthesia: A Meta-Analysis.

PubMed

He, Jiaxuan; Zhang, Yong; Xue, Rongliang; Lv, Jianrui; Ding, Xiaoying; Zhang, Zhenni

2015-01-01

To compare the effect of desflurane versus sevoflurane in pediatric anesthesia by conducting meta-analysis. Studies were searched from PubMed, Medline, Springer, Elsevier Science Direct, Cochrane Library and Google Scholar up to July 2014. Weighted mean difference (WMD) or risk ratio (RR) and 95% confidence intervals (CIs) were considered as effect sizes. Heterogeneity across studies was assessed by Cochran Q test and I2 statistic. The random effects model was performed in the meta-analysis when heterogeneity was observed, or the fixed effect model was used. Review Manager 5.1 software was applied for the meta-analysis. A total of 11 studies (13 comparisons) involving 1,273 objects were included in this meta-analysis. No heterogeneity was observed between studies for any comparison but for postoperative extubation time. The results showed significant differences between desflurane and sevoflurane groups for postoperative extubation time (WMD = -3.87, 95%CI = -6.14 to -1.60, P < 0.01), eye opening time (WMD = -1.11, 95%CI = -1.49 to -0.72, P < 0.01), awakening time (WMD = -4.27, 95%CI = -5.28 to -3.26, P < 0.01) and agitation (RR = 1.44, 95%CI = 1.05 to 1.96, P = 0.02). No significant differences (P > 0.05) were detected for discharge from the recovery room, oculocardiac reflex, nausea and vomiting and severe pain. Desflurane may have less adverse effects than sevoflurane when used in pediatric anesthesia with significantly shorter postoperative extubation time, eye opening time and awakening time as well as slighter agitation.

Lipid emulsion improves survival in animal models of local anesthetic toxicity: a meta-analysis.

PubMed

Fettiplace, Michael R; McCabe, Daniel J

2017-08-01

The Lipid Emulsion Therapy workgroup, organized by the American Academy of Clinical Toxicology, recently conducted a systematic review, which subjectively evaluated lipid emulsion as a treatment for local anesthetic toxicity. We re-extracted data and conducted a meta-analysis of survival in animal models. We extracted survival data from 26 publications and conducted a random-effect meta-analysis based on odds ratio weighted by inverse variance. We assessed the benefit of lipid emulsion as an independent variable in resuscitative models (16 studies). We measured Cochran's Q for heterogeneity and I 2 to determine variance contributed by heterogeneity. Finally, we conducted a funnel plot analysis and Egger's test to assess for publication bias in studies. Lipid emulsion reduced the odds of death in resuscitative models (OR =0.24; 95%CI: 0.1-0.56, p = .0012). Heterogeneity analysis indicated a homogenous distribution. Funnel plot analysis did not indicate publication bias in experimental models. Meta-analysis of animal data supports the use of lipid emulsion (in combination with other resuscitative measures) for the treatment of local anesthetic toxicity, specifically from bupivacaine. Our conclusion differed from the original review. Analysis of outliers reinforced the need for good life support measures (securement of airway and chest compressions) along with prompt treatment with lipid.

The effectiveness and safety of aminocaproic acid for reducing blood loss in total knee and hip arthroplasty: A meta-analysis.

PubMed

Dong, Qiang; Zhang, Yinguang; Sun, Xiang; Hu, Fangke

2018-04-01

This meta-analysis aimed to evaluate the safety and efficacy of aminocaproic acid in total knee arthroplasty (TKA) and total hip arthroplasty (THA). The electronic databases include PubMed, Medline, Embase, Web of Science and the Cochrane Library from inception to January, 2018. Two reviewers abstracted total blood loss, hemoglobin drop, transfusion requirements, and postoperative complications. Data were using fixed-effects or random-effects models with weighted mean differences and risk difference for continuous and dichotomous variables, respectively. STATA 14.0 was used to perform the meta-analysis. Six studies encompassing 756 participants were retrieved for this meta-analysis. Our study indicated that intravenous aminocaproic acid was associated with a significantly reduction in total blood loss, hemoglobin drop and need for transfusion. Additionally, no increased risk of thromboembolic events were identified. Based on the present meta-analysis, intravenous aminocaproic acid is effective and safe in total knee and hip arthroplasty without increasing the incidence of thromboembolic events. Further studies should focus on the comparison of aminocaproic acid and TXA in arthroplasties. Copyright © 2018 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

The Effectiveness of Teamwork Training on Teamwork Behaviors and Team Performance: A Systematic Review and Meta-Analysis of Controlled Interventions

PubMed Central

McEwan, Desmond; Ruissen, Geralyn R.; Eys, Mark A.; Zumbo, Bruno D.; Beauchamp, Mark R.

2017-01-01

The objective of this study was to conduct a systematic review and meta-analysis of teamwork interventions that were carried out with the purpose of improving teamwork and team performance, using controlled experimental designs. A literature search returned 16,849 unique articles. The meta-analysis was ultimately conducted on 51 articles, comprising 72 (k) unique interventions, 194 effect sizes, and 8439 participants, using a random effects model. Positive and significant medium-sized effects were found for teamwork interventions on both teamwork and team performance. Moderator analyses were also conducted, which generally revealed positive and significant effects with respect to several sample, intervention, and measurement characteristics. Implications for effective teamwork interventions as well as considerations for future research are discussed. PMID:28085922

Residual disease at the bronchial stump is positively associated with the risk of bronchoplerual fistula in patients undergoing lung cancer surgery: a meta-analysis

PubMed Central

Li, Shuangjiang; Fan, Jun; Zhou, Jian; Ren, Yutao; Shen, Cheng; Che, Guowei

2016-01-01

OBJECTIVES Residual disease at the bronchial stump (RDBS) is regarded as an important factor possibly resulting in bronchopleural fistula (BPF) after lung cancer surgery, but this has not been confirmed. We conducted this meta-analysis to evaluate the effects of RDBS on BPF formation in patients undergoing lung cancer surgery. METHODS PubMed and EMBASE databases were searched for full-text articles that met our eligibility criteria. Odds ratios (ORs) with 95% confidence interval (95% CI) served as the summarized outcomes. Q-test and I2 statistic were used to evaluate the level of heterogeneity, determining the fixed-effect model or random-effect model for quantitative synthesis. Sensitivity analysis was conducted to identify the possible origins of heterogeneity. The publication bias was assessed by Begg's test. RESULTS A total of eight retrospective observational studies were included in our meta-analysis. In overall analysis, the pooled outcomes indicated that RDBS was significantly associated with BPF formation after lung cancer surgery (OR: 3.12; 95% CI: 1.72–5.64; P < 0.001). In subgroup analysis, the pooled outcomes revealed a significantly increased risk of post-pneumonectomy BPF in patients with RDBS (OR: 2.78; 95% CI: 1.06–7.28; P = 0.037). The subgroup analysis assessing the effects of RDBS on post-lobectomy BPF was given up due to the scarcity of available data. No heterogeneity was revealed within this meta-analysis. No evidence for publication bias was detected by Begg's test. CONCLUSIONS Our meta-analysis indicates that RDBS is positively associated with the increased risk of BPF in patients undergoing lung cancer surgery. The further analysis also reveals an increased risk of post-pneumonectomy BPF in patients with RDBS. More accurate and comprehensive evidence should be collected and summarized in updated meta-analyses. PMID:26614527

Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C-statistic and calibration measures?

PubMed

Snell, Kym Ie; Ensor, Joie; Debray, Thomas Pa; Moons, Karel Gm; Riley, Richard D

2017-01-01

If individual participant data are available from multiple studies or clusters, then a prediction model can be externally validated multiple times. This allows the model's discrimination and calibration performance to be examined across different settings. Random-effects meta-analysis can then be used to quantify overall (average) performance and heterogeneity in performance. This typically assumes a normal distribution of 'true' performance across studies. We conducted a simulation study to examine this normality assumption for various performance measures relating to a logistic regression prediction model. We simulated data across multiple studies with varying degrees of variability in baseline risk or predictor effects and then evaluated the shape of the between-study distribution in the C-statistic, calibration slope, calibration-in-the-large, and E/O statistic, and possible transformations thereof. We found that a normal between-study distribution was usually reasonable for the calibration slope and calibration-in-the-large; however, the distributions of the C-statistic and E/O were often skewed across studies, particularly in settings with large variability in the predictor effects. Normality was vastly improved when using the logit transformation for the C-statistic and the log transformation for E/O, and therefore we recommend these scales to be used for meta-analysis. An illustrated example is given using a random-effects meta-analysis of the performance of QRISK2 across 25 general practices.

Maternal Work Early in the Lives of Children and Its Distal Associations with Achievement and Behavior Problems: A Meta-Analysis

ERIC Educational Resources Information Center

Lucas-Thompson, Rachel G.; Goldberg, Wendy A.; Prause, JoAnn

2010-01-01

This meta-analysis of 69 studies (1,483 effect sizes) used random effects models to examine maternal employment during infancy/early childhood in relation to 2 major domains of child functioning: achievement and behavior problems. Analyses of studies that spanned 5 decades indicated that, with a few exceptions, early employment was not…

Who Benefits From Supported Employment: A Meta-analytic Study

PubMed Central

Campbell, Kikuko; Drake, Robert E.

2011-01-01

Aims: This meta-analysis sought to identify which subgroups of clients with severe mental illness (SMI) benefited from evidence-based supported employment. Methods: We used meta-analysis to pool the samples from 4 randomized controlled trials comparing the Individual Placement and Support (IPS) model of supported employment to well-regarded vocational approaches using stepwise models and brokered services. Meta-analysis was used to determine the magnitude of effects for IPS/control group differences within specific client subgroups (defined by 2 work history, 7 sociodemographic, and 8 clinical variables) on 3 competitive employment outcomes (obtaining a job, total weeks worked, and job tenure). Results: The findings strongly favored IPS, with large effect sizes across all outcomes: 0.96 for job acquisition, 0.79 for total weeks worked, and 0.74 for job tenure. Overall, 90 (77%) of the 117 effect sizes calculated for the 39 subgroups exceeded 0.70, and all 117 favored IPS. Conclusions: IPS produces better competitive employment outcomes for persons with SMI than alternative vocational programs regardless of background demographic, clinical, and employment characteristics. PMID:19661196

Random effects coefficient of determination for mixed and meta-analysis models

PubMed Central

Demidenko, Eugene; Sargent, James; Onega, Tracy

2011-01-01

The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, Rr2, that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If Rr2 is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of Rr2 apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects—the model can be estimated using the dummy variable approach. We derive explicit formulas for Rr2 in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine. PMID:23750070

On meta- and mega-analyses for gene–environment interactions

PubMed Central

Huang, Jing; Liu, Yulun; Vitale, Steve; Penning, Trevor M.; Whitehead, Alexander S.; Blair, Ian A.; Vachani, Anil; Clapper, Margie L.; Muscat, Joshua E.; Lazarus, Philip; Scheet, Paul; Moore, Jason H.; Chen, Yong

2017-01-01

Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a “mega” data set, which can be fit by a joint “mega-analysis.” Alternatively, analyses can be done at each site, and results across sites can be combined through a “meta-analysis” procedure without integrating individual level data across sites. Although mega-analysis has been advocated in several recent initiatives, meta-analysis has the advantages of simplicity and feasibility, and has recently led to several important findings in identifying main genetic effects. In this paper, we conducted empirical and simulation studies, using data from a G × E study of lung cancer, to compare the mega- and meta-analyses in four commonly used G × E analyses under the scenario that the number of studies is small and sample sizes of individual studies are relatively large. We compared the two data integration approaches in the context of fixed effect models and random effects models separately. Our investigations provide valuable insights in understanding the differences between mega- and meta-analyses in practice of combining small number of studies in identifying G × E interactions. PMID:29110346

Dietary interventions to prevent and manage diabetes in worksite settings: a meta-analysis

PubMed Central

Shrestha, Archana; Karmacharya, Biraj Man; Khudyakov, Polyna; Weber, Mary Beth; Spiegelman, Donna

2017-01-01

Objectives: The translation of lifestyle intervention to improve glucose tolerance into the workplace has been rare. The objective of this meta-analysis is to summarize the evidence for the effectiveness of dietary interventions in worksite settings on lowering blood sugar levels. Methods: We searched for studies in PubMed, Embase, Econlit, Ovid, Cochrane, Web of Science, and Cumulative Index to Nursing and Allied Health Literature. Search terms were as follows: (1) Exposure-based: nutrition/diet/dietary intervention/health promotion/primary prevention/health behavior/health education/food /program evaluation; (2) Outcome-based: diabetes/hyperglycemia/glucose/HbA1c/glycated hemoglobin; and (3) Setting-based: workplace/worksite/occupational/industry/job/employee. We manually searched review articles and reference lists of articles identified from 1969 to December 2016. We tested for between-studies heterogeneity and calculated the pooled effect sizes for changes in HbA1c (%) and fasting glucose (mg/dl) using random effect models for meta-analysis in 2016. Results: A total of 17 articles out of 1663 initially selected articles were included in the meta-analysis. With a random-effects model, worksite dietary interventions led to a pooled -0.18% (95% CI, -0.29 to -0.06; P<0.001) difference in HbA1c. With the random-effects model, the interventions resulted in 2.60 mg/dl lower fasting glucose with borderline significance (95% CI: -5.27 to 0.08, P=0.06). In the multivariate meta-regression model, the interventions with high percent of female participants and that used the intervention directly delivered to individuals, rather the environment changes, were associated with more effective interventions. Conclusion: Workplace dietary interventions can improve HbA1c. The effects were larger for the interventions with greater number of female participants and with individual-level interventions. PMID:29187673

Model-driven meta-analyses for informing health care: a diabetes meta-analysis as an exemplar.

PubMed

Brown, Sharon A; Becker, Betsy Jane; García, Alexandra A; Brown, Adama; Ramírez, Gilbert

2015-04-01

A relatively novel type of meta-analysis, a model-driven meta-analysis, involves the quantitative synthesis of descriptive, correlational data and is useful for identifying key predictors of health outcomes and informing clinical guidelines. Few such meta-analyses have been conducted and thus, large bodies of research remain unsynthesized and uninterpreted for application in health care. We describe the unique challenges of conducting a model-driven meta-analysis, focusing primarily on issues related to locating a sample of published and unpublished primary studies, extracting and verifying descriptive and correlational data, and conducting analyses. A current meta-analysis of the research on predictors of key health outcomes in diabetes is used to illustrate our main points. © The Author(s) 2014.

MODEL-DRIVEN META-ANALYSES FOR INFORMING HEALTH CARE: A DIABETES META-ANALYSIS AS AN EXEMPLAR

PubMed Central

Brown, Sharon A.; Becker, Betsy Jane; García, Alexandra A.; Brown, Adama; Ramírez, Gilbert

2015-01-01

A relatively novel type of meta-analysis, a model-driven meta-analysis, involves the quantitative synthesis of descriptive, correlational data and is useful for identifying key predictors of health outcomes and informing clinical guidelines. Few such meta-analyses have been conducted and thus, large bodies of research remain unsynthesized and uninterpreted for application in health care. We describe the unique challenges of conducting a model-driven meta-analysis, focusing primarily on issues related to locating a sample of published and unpublished primary studies, extracting and verifying descriptive and correlational data, and conducting analyses. A current meta-analysis of the research on predictors of key health outcomes in diabetes is used to illustrate our main points. PMID:25142707

Improvement of endothelial function by pitavastatin: a meta-analysis.

PubMed

Katsiki, Niki; Reiner, Željko; Tedeschi Reiner, Eugenia; Al-Rasadi, Khalid; Pirro, Matteo; Mikhailidis, Dimitri P; Sahebkar, Amirhossein

2018-02-01

Dyslipidemia is commonly associated with endothelial dysfunction and increased cardiovascular risk. Pitavastatin has been shown to reduce total and low-density lipoprotein cholesterol, to increase high-density lipoprotein (HDL)-cholesterol and improve HDL function. Furthermore, several trials explored its effects on flow-mediated dilation (FMD), as an index of endothelial function. The authors evaluated the effect of pitavastatin therapy on FMD. The authors performed a systematic review and meta-analysis of all clinical trials exploring the impact of pitavastatin on FMD. The search included PubMed-Medline, Scopus, ISI Web of Knowledge and Google Scholar databases. Quantitative data synthesis was performed using a random-effects model, with weighted mean difference (WMD) and 95% confidence interval (CI) as summary statistics. Six eligible studies comprising 7 treatment arms were selected for this meta-analysis. Overall, WMD was significant for the effect of pitavastatin on FMD (2.45%, 95% CI: 1.31, 3.60, p < 0.001) and the effect size was robust in the leave-one-out sensitivity analysis. This meta-analysis of all available clinical trials revealed a significant increase of FMD induced by pitavastatin.

Comparison of intervention effects in split-mouth and parallel-arm randomized controlled trials: a meta-epidemiological study

PubMed Central

2014-01-01

Background Split-mouth randomized controlled trials (RCTs) are popular in oral health research. Meta-analyses frequently include trials of both split-mouth and parallel-arm designs to derive combined intervention effects. However, carry-over effects may induce bias in split- mouth RCTs. We aimed to assess whether intervention effect estimates differ between split- mouth and parallel-arm RCTs investigating the same questions. Methods We performed a meta-epidemiological study. We systematically reviewed meta- analyses including both split-mouth and parallel-arm RCTs with binary or continuous outcomes published up to February 2013. Two independent authors selected studies and extracted data. We used a two-step approach to quantify the differences between split-mouth and parallel-arm RCTs: for each meta-analysis. First, we derived ratios of odds ratios (ROR) for dichotomous data and differences in standardized mean differences (∆SMD) for continuous data; second, we pooled RORs or ∆SMDs across meta-analyses by random-effects meta-analysis models. Results We selected 18 systematic reviews, for 15 meta-analyses with binary outcomes (28 split-mouth and 28 parallel-arm RCTs) and 19 meta-analyses with continuous outcomes (28 split-mouth and 28 parallel-arm RCTs). Effect estimates did not differ between split-mouth and parallel-arm RCTs (mean ROR, 0.96, 95% confidence interval 0.52–1.80; mean ∆SMD, 0.08, -0.14–0.30). Conclusions Our study did not provide sufficient evidence for a difference in intervention effect estimates derived from split-mouth and parallel-arm RCTs. Authors should consider including split-mouth RCTs in their meta-analyses with suitable and appropriate analysis. PMID:24886043

The effectiveness and safety of antifibrinolytics in patients with acute intracranial haemorrhage: statistical analysis plan for an individual patient data meta-analysis.

PubMed

Ker, Katharine; Prieto-Merino, David; Sprigg, Nikola; Mahmood, Abda; Bath, Philip; Kang Law, Zhe; Flaherty, Katie; Roberts, Ian

2017-01-01

Introduction : The Antifibrinolytic Trialists Collaboration aims to increase knowledge about the effectiveness and safety of antifibrinolytic treatment by conducting individual patient data (IPD) meta-analyses of randomised trials. This article presents the statistical analysis plan for an IPD meta-analysis of the effects of antifibrinolytics for acute intracranial haemorrhage. Methods : The protocol for the IPD meta-analysis has been registered with PROSPERO (CRD42016052155). We will conduct an individual patient data meta-analysis of randomised controlled trials with 1000 patients or more assessing the effects of antifibrinolytics in acute intracranial haemorrhage. We will assess the effect on two co-primary outcomes: 1) death in hospital at end of trial follow-up, and 2) death in hospital or dependency at end of trial follow-up. The co-primary outcomes will be limited to patients treated within three hours of injury or stroke onset. We will report treatment effects using odds ratios and 95% confidence intervals. We use logistic regression models to examine how the effect of antifibrinolytics vary by time to treatment, severity of intracranial bleeding, and age. We will also examine the effect of antifibrinolytics on secondary outcomes including death, dependency, vascular occlusive events, seizures, and neurological outcomes. Secondary outcomes will be assessed in all patients irrespective of time of treatment. All analyses will be conducted on an intention-to-treat basis. Conclusions : This IPD meta-analysis will examine important clinical questions about the effects of antifibrinolytic treatment in patients with intracranial haemorrhage that cannot be answered using aggregate data. With IPD we can examine how effects vary by time to treatment, bleeding severity, and age, to gain better understanding of the balance of benefit and harms on which to base recommendations for practice.

Threatening communication: a critical re-analysis and a revised meta-analytic test of fear appeal theory.

PubMed

Peters, Gjalt-Jorn Ygram; Ruiter, Robert A C; Kok, Gerjo

2013-05-01

Despite decades of research, consensus regarding the dynamics of fear appeals remains elusive. A meta-analysis was conducted that was designed to resolve this controversy. Publications that were included in previous meta-analyses were re-analysed, and a number of additional publications were located. The inclusion criteria were full factorial orthogonal manipulations of threat and efficacy, and measurement of behaviour as an outcome. Fixed and random effects models were used to compute mean effect size estimates. Meta-analysis of the six studies that satisfied the inclusion criteria clearly showed a significant interaction between threat and efficacy, such that threat only had an effect under high efficacy (d = 0.31), and efficacy only had an effect under high threat (d = 0.71). Inconsistency in results regarding the effectiveness of threatening communication can likely be attributed to flawed methodology. Proper tests of fear appeal theory yielded the theoretically hypothesised interaction effect. Threatening communication should exclusively be used when pilot studies indicate that an intervention successfully enhances efficacy.

Threatening communication: a critical re-analysis and a revised meta-analytic test of fear appeal theory

PubMed Central

Peters, Gjalt-Jorn Ygram; Ruiter, Robert A.C.; Kok, Gerjo

2013-01-01

Despite decades of research, consensus regarding the dynamics of fear appeals remains elusive. A meta-analysis was conducted that was designed to resolve this controversy. Publications that were included in previous meta-analyses were re-analysed, and a number of additional publications were located. The inclusion criteria were full factorial orthogonal manipulations of threat and efficacy, and measurement of behaviour as an outcome. Fixed and random effects models were used to compute mean effect size estimates. Meta-analysis of the six studies that satisfied the inclusion criteria clearly showed a significant interaction between threat and efficacy, such that threat only had an effect under high efficacy (d = 0.31), and efficacy only had an effect under high threat (d = 0.71). Inconsistency in results regarding the effectiveness of threatening communication can likely be attributed to flawed methodology. Proper tests of fear appeal theory yielded the theoretically hypothesised interaction effect. Threatening communication should exclusively be used when pilot studies indicate that an intervention successfully enhances efficacy. PMID:23772231

Association between the BRCA2 rs144848 polymorphism and cancer susceptibility: a meta-analysis.

PubMed

Li, Qiuyan; Guan, Rongwei; Qiao, Yuandong; Liu, Chang; He, Ning; Zhang, Xuelong; Jia, Xueyuan; Sun, Haiming; Yu, Jingcui; Xu, Lidan

2017-06-13

The BRCA2 gene plays an important role in cancer carcinogenesis, and polymorphisms in this gene have been associated with cancer risk. The BRCA2 rs144848 polymorphism has been associated with several cancers, but results have been inconsistent. In the present study, a meta-analysis was performed to assess the association between the rs144848 polymorphism and cancer risk. Literature was searched from the databases of PubMed, Embase and Google Scholar before April 2016. The fixed or random effects model was used to calculate pooled odd ratios on the basis of heterogeneity. Meta-regression, sensitivity analysis, subgroup analysis and publication bias assessment were also performed using STATA 11.0 software according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2009. A total of 40 relevant studies from 30 publications including 34,911 cases and 48,329 controls were included in the final meta-analysis. Among them, 22 studies focused on breast cancer, seven on ovarian cancer, five on non-Hodgkin lymphoma, and the remaining six studies examined various other cancers. The meta-analysis results showed that there were significant associations between the rs144848 polymorphism and cancer risk in all genetic models. Stratified by cancer type, the rs144848 polymorphism was associated with non-Hodgkin lymphoma. Stratified by study design, the allele model was associated with breast cancer risk in population-based studies. The meta-analysis suggests that the BRCA2 rs144848 polymorphism may play a role in cancer risk. Further well-designed studies are warranted to confirm these results.

Methods to increase reproducibility in differential gene expression via meta-analysis

PubMed Central

Sweeney, Timothy E.; Haynes, Winston A.; Vallania, Francesco; Ioannidis, John P.; Khatri, Purvesh

2017-01-01

Findings from clinical and biological studies are often not reproducible when tested in independent cohorts. Due to the testing of a large number of hypotheses and relatively small sample sizes, results from whole-genome expression studies in particular are often not reproducible. Compared to single-study analysis, gene expression meta-analysis can improve reproducibility by integrating data from multiple studies. However, there are multiple choices in designing and carrying out a meta-analysis. Yet, clear guidelines on best practices are scarce. Here, we hypothesized that studying subsets of very large meta-analyses would allow for systematic identification of best practices to improve reproducibility. We therefore constructed three very large gene expression meta-analyses from clinical samples, and then examined meta-analyses of subsets of the datasets (all combinations of datasets with up to N/2 samples and K/2 datasets) compared to a ‘silver standard’ of differentially expressed genes found in the entire cohort. We tested three random-effects meta-analysis models using this procedure. We showed relatively greater reproducibility with more-stringent effect size thresholds with relaxed significance thresholds; relatively lower reproducibility when imposing extraneous constraints on residual heterogeneity; and an underestimation of actual false positive rate by Benjamini–Hochberg correction. In addition, multivariate regression showed that the accuracy of a meta-analysis increased significantly with more included datasets even when controlling for sample size. PMID:27634930

Meta-analysis inside and outside particle physics: two traditions that should converge?

PubMed

Baker, Rose D; Jackson, Dan

2013-06-01

The use of meta-analysis in medicine and epidemiology really took off in the 1970s. However, in high-energy physics, the Particle Data Group has been carrying out meta-analyses of measurements of particle masses and other properties since 1957. Curiously, there has been virtually no interaction between those working inside and outside particle physics. In this paper, we use statistical models to study two major differences in practice. The first is the usefulness of systematic errors, which physicists are now beginning to quote in addition to statistical errors. The second is whether it is better to treat heterogeneity by scaling up errors as do the Particle Data Group or by adding a random effect as does the rest of the community. Besides fitting models, we derive and use an exact test of the error-scaling hypothesis. We also discuss the other methodological differences between the two streams of meta-analysis. Our conclusion is that systematic errors are not currently very useful and that the conventional random effects model, as routinely used in meta-analysis, has a useful role to play in particle physics. The moral we draw for statisticians is that we should be more willing to explore 'grassroots' areas of statistical application, so that good statistical practice can flow both from and back to the statistical mainstream. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

[Comparison of simple pooling and bivariate model used in meta-analyses of diagnostic test accuracy published in Chinese journals].

PubMed

Huang, Yuan-sheng; Yang, Zhi-rong; Zhan, Si-yan

2015-06-18

To investigate the use of simple pooling and bivariate model in meta-analyses of diagnostic test accuracy (DTA) published in Chinese journals (January to November, 2014), compare the differences of results from these two models, and explore the impact of between-study variability of sensitivity and specificity on the differences. DTA meta-analyses were searched through Chinese Biomedical Literature Database (January to November, 2014). Details in models and data for fourfold table were extracted. Descriptive analysis was conducted to investigate the prevalence of the use of simple pooling method and bivariate model in the included literature. Data were re-analyzed with the two models respectively. Differences in the results were examined by Wilcoxon signed rank test. How the results differences were affected by between-study variability of sensitivity and specificity, expressed by I2, was explored. The 55 systematic reviews, containing 58 DTA meta-analyses, were included and 25 DTA meta-analyses were eligible for re-analysis. Simple pooling was used in 50 (90.9%) systematic reviews and bivariate model in 1 (1.8%). The remaining 4 (7.3%) articles used other models pooling sensitivity and specificity or pooled neither of them. Of the reviews simply pooling sensitivity and specificity, 41(82.0%) were at the risk of wrongly using Meta-disc software. The differences in medians of sensitivity and specificity between two models were both 0.011 (P<0.001, P=0.031 respectively). Greater differences could be found as I2 of sensitivity or specificity became larger, especially when I2>75%. Most DTA meta-analyses published in Chinese journals(January to November, 2014) combine the sensitivity and specificity by simple pooling. Meta-disc software can pool the sensitivity and specificity only through fixed-effect model, but a high proportion of authors think it can implement random-effect model. Simple pooling tends to underestimate the results compared with bivariate model. The greater the between-study variance is, the more likely the simple pooling has larger deviation. It is necessary to increase the knowledge level of statistical methods and software for meta-analyses of DTA data.

Systematic review and meta-analysis of efficacy of mesenchymal stem cells on locomotor recovery in animal models of traumatic brain injury.

PubMed

Peng, Weijun; Sun, Jing; Sheng, Chenxia; Wang, Zhe; Wang, Yang; Zhang, Chunhu; Fan, Rong

2015-03-26

The therapeutic potential of mesenchymal stem cells (MSCs) for traumatic brain injury (TBI) is attractive. Conducting systematic review and meta-analyses based on data from animal studies can be used to inform clinical trial design. To conduct a systematic review and meta-analysis to (i) systematically review the literatures describing the effect of MSCs therapy in animal models of TBI, (ii) determine the estimated effect size of functional locomotor recovery after experimental TBI, and (iii) to provide empirical evidence of biological factors associated with greater efficacy. We conducted a systematic search of PubMed, EMBASE, and Web of Science and hand searched related references. Studies were selected if they reported the efficacy of MSCs in animal models of TBI. Two investigators independently assessed the identified studies. We extracted the details of individual study characteristics from each publication, assessed study quality, evaluated the effect sizes of MSCs treatment, and performed stratified meta-analysis and meta-regression, to assess the influence of study design on the estimated effect size. The presence of small effect sizes was investigated using funnel plots and Egger's tests. Twenty-eight eligible controlled studies were identified. The study quality was modest. Between-study heterogeneity was large. Meta-analysis showed that MSCs exert statistically significant positive effects on sensorimotor and neurological motor function. For sensorimotor function, maximum effect size in studies with a quality score of 5 was found in the weight-drop impact injury TBI model established in male SD rats, to which syngeneic umbilical cord-derived MSCs intracerebrally at cell dose of (1-5)×10(6) was administered r 6 hours following TBI, using ketamine as anesthetic agent. For neurological motor function, effect size was maximum for studies with a quality score of 5, in which the weight-drop impact injury TBI models of the female Wistar rats were adopted, with administration syngeneic bone marrow-derived MSCs intravenously at cell dose of 5×10(6) at 2 months after TBI, using sevofluorane as anesthetic agent. We conclude that MSCs therapy may improve locomotor recovery after TBI. However, additional well-designed and well-reported animal studies are needed to guide further clinical studies.

A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence.

PubMed

Nikoloulopoulos, Aristidis K

2017-10-01

A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context. Here, we call trivariate vine copulas to extend the bivariate meta-analysis of diagnostic test accuracy studies by accounting for disease prevalence. Our vine copula mixed model includes the trivariate generalized linear mixed model as a special case and can also operate on the original scale of sensitivity, specificity, and disease prevalence. Our general methodology is illustrated by re-analyzing the data of two published meta-analyses. Our study suggests that there can be an improvement on trivariate generalized linear mixed model in fit to data and makes the argument for moving to vine copula random effects models especially because of their richness, including reflection asymmetric tail dependence, and computational feasibility despite their three dimensionality.

Testing moderation in network meta-analysis with individual participant data

PubMed Central

Dagne, Getachew A.; Brown, C. Hendricks; Howe, George; Kellam, Sheppard G.; Liu, Lei

2016-01-01

Summary Meta-analytic methods for combining data from multiple intervention trials are commonly used to estimate the effectiveness of an intervention. They can also be extended to study comparative effectiveness, testing which of several alternative interventions is expected to have the strongest effect. This often requires network meta-analysis (NMA), which combines trials involving direct comparison of two interventions within the same trial and indirect comparisons across trials. In this paper, we extend existing network methods for main effects to examining moderator effects, allowing for tests of whether intervention effects vary for different populations or when employed in different contexts. In addition, we study how the use of individual participant data (IPD) may increase the sensitivity of NMA for detecting moderator effects, as compared to aggregate data NMA that employs study-level effect sizes in a meta-regression framework. A new network meta-analysis diagram is proposed. We also develop a generalized multilevel model for NMA that takes into account within- and between-trial heterogeneity, and can include participant-level covariates. Within this framework we present definitions of homogeneity and consistency across trials. A simulation study based on this model is used to assess effects on power to detect both main and moderator effects. Results show that power to detect moderation is substantially greater when applied to IPD as compared to study-level effects. We illustrate the use of this method by applying it to data from a classroom-based randomized study that involved two sub-trials, each comparing interventions that were contrasted with separate control groups. PMID:26841367

Care management for Type 2 diabetes in the United States: a systematic review and meta-analysis.

PubMed

Egginton, Jason S; Ridgeway, Jennifer L; Shah, Nilay D; Balasubramaniam, Saranya; Emmanuel, Joann R; Prokop, Larry J; Montori, Victor M; Murad, Mohammad Hassan

2012-03-22

This systematic review and meta-analysis aims at assessing the composition and performance of care management models evaluated in the last decade and their impact on patient important outcomes. A comprehensive literature search of electronic bibliographic databases was performed to identify care management trials in type 2 diabetes. Random effects meta-analysis was used when feasible to pool outcome measures. Fifty-two studies were eligible. Most commonly reported were surrogate outcomes (such as HbA1c and LDL), followed by process measures (clinic visit or testing frequency). Less frequently reported were quality of life, patient satisfaction, self-care, and healthcare utilization. Most care management modalities were carved out from primary care. Meta-analysis demonstrated a statistically significant but trivial reduction of HbA1c (weighted difference in means -0.21%, 95% confidence interval -0.40 to -0.03, p < .03) and LDL-cholesterol (weighted difference in means -3.38 mg/dL, 95% confidence interval -6.27 to -0.49, p < .02). Most care management programs for patients with type 2 diabetes are 'carved-out', accomplish limited effects on metabolic outcomes, and have unknown effects on patient important outcomes. Comparative effectiveness research of different models of care management is needed to inform the design of medical homes for patients with chronic conditions.

The correlation of social support with mental health: A meta-analysis.

PubMed

Harandi, Tayebeh Fasihi; Taghinasab, Maryam Mohammad; Nayeri, Tayebeh Dehghan

2017-09-01

Social support is an important factor that can affect mental health. In recent decades, many studies have been done on the impact of social support on mental health. The purpose of the present study is to investigate the effect size of the relationship between social support and mental health in studies in Iran. This meta-analysis was carried out in studies that were performed from 1996 through 2015. Databases included SID and Magiran, the comprehensive portal of human sciences, Noor specialized magazine databases, IRANDOC, Proquest, PubMed, Scopus, ERIC, Iranmedex and Google Scholar. The keywords used to search these websites included "mental health or general health," and "Iran" and "social support." In total, 64 studies had inclusion criteria meta-analysis. In order to collect data used from a meta-analysis worksheet that was made by the researcher and for data analysis software, CMA-2 was used. The mean of effect size of the 64 studies in the fixed-effect model and random-effect model was obtained respectively as 0.356 and 0.330, which indicated the moderate effect size of social support on mental health. The studies did not have publication bias, and enjoyed a heterogeneous effect size. The target population and social support questionnaire were moderator variables, but sex, sampling method, and mental health questionnaire were not moderator variables. Regarding relatively high effect size of the correlation between social support and mental health, it is necessary to predispose higher social support, especially for women, the elderly, patients, workers, and students.

Should in-line filters be used in peripheral intravenous catheters to prevent infusion-related phlebitis? A systematic review of randomized controlled trials.

PubMed

Niël-Weise, Barbara S; Stijnen, Theo; van den Broek, Peterhans J

2010-06-01

In this systematic review, we assessed the effect of in-line filters on infusion-related phlebitis associated with peripheral IV catheters. The study was designed as a systematic review and meta-analysis of randomized controlled trials. We used MEDLINE and the Cochrane Controlled Trial Register up to August 10, 2009. Two reviewers independently assessed trial quality and extracted data. Data on phlebitis were combined when appropriate, using a random-effects model. The impact of the risk of phlebitis in the control group (baseline risk) on the effect of in-line filters was studied by using meta-regression based on the bivariate meta-analysis model. The quality of the evidence was determined by using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) method. Eleven trials (1633 peripheral catheters) were included in this review to compare the effect of in-line filters on the incidence of phlebitis in hospitalized patients. Baseline risks across trials ranged from 23% to 96%. Meta-analysis of all trials showed that in-line filters reduced the risk of infusion-related phlebitis (relative risk, 0.66; 95% confidence interval, 0.43-1.00). This benefit, however, is very uncertain, because the trials had serious methodological shortcomings and meta-analysis revealed marked unexplained statistical heterogeneity (P < 0.0000, I(2) = 90.4%). The estimated benefit did not depend on baseline risk. In-line filters in peripheral IV catheters cannot be recommended routinely, because evidence of their benefit is uncertain.

Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Q statistics

PubMed Central

2011-01-01

Background Clinical researchers have often preferred to use a fixed effects model for the primary interpretation of a meta-analysis. Heterogeneity is usually assessed via the well known Q and I2 statistics, along with the random effects estimate they imply. In recent years, alternative methods for quantifying heterogeneity have been proposed, that are based on a 'generalised' Q statistic. Methods We review 18 IPD meta-analyses of RCTs into treatments for cancer, in order to quantify the amount of heterogeneity present and also to discuss practical methods for explaining heterogeneity. Results Differing results were obtained when the standard Q and I2 statistics were used to test for the presence of heterogeneity. The two meta-analyses with the largest amount of heterogeneity were investigated further, and on inspection the straightforward application of a random effects model was not deemed appropriate. Compared to the standard Q statistic, the generalised Q statistic provided a more accurate platform for estimating the amount of heterogeneity in the 18 meta-analyses. Conclusions Explaining heterogeneity via the pre-specification of trial subgroups, graphical diagnostic tools and sensitivity analyses produced a more desirable outcome than an automatic application of the random effects model. Generalised Q statistic methods for quantifying and adjusting for heterogeneity should be incorporated as standard into statistical software. Software is provided to help achieve this aim. PMID:21473747

Random effects coefficient of determination for mixed and meta-analysis models.

PubMed

Demidenko, Eugene; Sargent, James; Onega, Tracy

2012-01-01

The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, [Formula: see text], that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If [Formula: see text] is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of [Formula: see text] apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects-the model can be estimated using the dummy variable approach. We derive explicit formulas for [Formula: see text] in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine.

The revelation effect: A meta-analytic test of hypotheses.

PubMed

Aßfalg, André; Bernstein, Daniel M; Hockley, William

2017-12-01

Judgments can depend on the activity directly preceding them. An example is the revelation effect whereby participants are more likely to claim that a stimulus is familiar after a preceding task, such as solving an anagram, than without a preceding task. We test conflicting predictions of four revelation-effect hypotheses in a meta-analysis of 26 years of revelation-effect research. The hypotheses' predictions refer to three subject areas: (1) the basis of judgments that are subject to the revelation effect (recollection vs. familiarity vs. fluency), (2) the degree of similarity between the task and test item, and (3) the difficulty of the preceding task. We use a hierarchical multivariate meta-analysis to account for dependent effect sizes and variance in experimental procedures. We test the revelation-effect hypotheses with a model selection procedure, where each model corresponds to a prediction of a revelation-effect hypothesis. We further quantify the amount of evidence for one model compared to another with Bayes factors. The results of this analysis suggest that none of the extant revelation-effect hypotheses can fully account for the data. The general vagueness of revelation-effect hypotheses and the scarcity of data were the major limiting factors in our analyses, emphasizing the need for formalized theories and further research into the puzzling revelation effect.

Univariate and bivariate likelihood-based meta-analysis methods performed comparably when marginal sensitivity and specificity were the targets of inference.

PubMed

Dahabreh, Issa J; Trikalinos, Thomas A; Lau, Joseph; Schmid, Christopher H

2017-03-01

To compare statistical methods for meta-analysis of sensitivity and specificity of medical tests (e.g., diagnostic or screening tests). We constructed a database of PubMed-indexed meta-analyses of test performance from which 2 × 2 tables for each included study could be extracted. We reanalyzed the data using univariate and bivariate random effects models fit with inverse variance and maximum likelihood methods. Analyses were performed using both normal and binomial likelihoods to describe within-study variability. The bivariate model using the binomial likelihood was also fit using a fully Bayesian approach. We use two worked examples-thoracic computerized tomography to detect aortic injury and rapid prescreening of Papanicolaou smears to detect cytological abnormalities-to highlight that different meta-analysis approaches can produce different results. We also present results from reanalysis of 308 meta-analyses of sensitivity and specificity. Models using the normal approximation produced sensitivity and specificity estimates closer to 50% and smaller standard errors compared to models using the binomial likelihood; absolute differences of 5% or greater were observed in 12% and 5% of meta-analyses for sensitivity and specificity, respectively. Results from univariate and bivariate random effects models were similar, regardless of estimation method. Maximum likelihood and Bayesian methods produced almost identical summary estimates under the bivariate model; however, Bayesian analyses indicated greater uncertainty around those estimates. Bivariate models produced imprecise estimates of the between-study correlation of sensitivity and specificity. Differences between methods were larger with increasing proportion of studies that were small or required a continuity correction. The binomial likelihood should be used to model within-study variability. Univariate and bivariate models give similar estimates of the marginal distributions for sensitivity and specificity. Bayesian methods fully quantify uncertainty and their ability to incorporate external evidence may be useful for imprecisely estimated parameters. Copyright © 2017 Elsevier Inc. All rights reserved.

Association between obesity with disease-free survival and overall survival in triple-negative breast cancer: A meta-analysis.

PubMed

Mei, Lin; He, Lin; Song, Yuhua; Lv, Yang; Zhang, Lijiu; Hao, Fengxi; Xu, Mengmeng

2018-05-01

To investigate the relationship between obesity and disease-free survival (DFS) and overall survival (OS) of triple-negative breast cancer. Citations were searched in PubMed, Cochrane Library, and Web of Science. Random effect model meta-analysis was conducted by using Revman software version 5.0, and publication bias was evaluated by creating Egger regression with STATA software version 12. Nine studies (4412 patients) were included for DFS meta-analysis, 8 studies (4392 patients) include for OS meta-analysis. There were no statistical significances between obesity with DFS (P = .60) and OS (P = .71) in triple-negative breast cancer (TNBC) patients. Obesity has no impact on DFS and OS in patients with TNBC.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

A Meta-Analysis of Peer-Mediated Interventions for Young Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Zhang, Jie; Wheeler, John J.

2011-01-01

This meta-analysis investigated the efficacy of peer-mediated interventions for promoting social interactions among children from birth to eight years of age diagnosed with ASD. Forty-five single-subject design studies were analyzed and the effect sizes were calculated by the regression model developed by Allison and Gorman (1993). The overall…

CrossFit Overview: Systematic Review and Meta-analysis.

PubMed

Claudino, João Gustavo; Gabbett, Tim J; Bourgeois, Frank; Souza, Helton de Sá; Miranda, Rafael Chagas; Mezêncio, Bruno; Soncin, Rafael; Cardoso Filho, Carlos Alberto; Bottaro, Martim; Hernandez, Arnaldo Jose; Amadio, Alberto Carlos; Serrão, Julio Cerca

2018-02-26

CrossFit is recognized as one of the fastest growing high-intensity functional training modes in the world. However, scientific data regarding the practice of CrossFit is sparse. Therefore, the objective of this study is to analyze the findings of scientific literature related to CrossFit via systematic review and meta-analysis. Systematic searches of the PubMed, Web of Science, Scopus, Bireme/MedLine, and SciELO online databases were conducted for articles reporting the effects of CrossFit training. The systematic review followed the PRISMA guidelines. The Oxford Levels of Evidence was used for all included articles, and only studies that investigated the effects of CrossFit as a training program were included in the meta-analysis. For the meta-analysis, effect sizes (ESs) with 95% confidence interval (CI) were calculated and heterogeneity was assessed using a random-effects model. Thirty-one articles were included in the systematic review and four were included in the meta-analysis. However, only two studies had a high level of evidence at low risk of bias. Scientific literature related to CrossFit has reported on body composition, psycho-physiological parameters, musculoskeletal injury risk, life and health aspects, and psycho-social behavior. In the meta-analysis, significant results were not found for any variables. The current scientific literature related to CrossFit has few studies with high level of evidence at low risk of bias. However, preliminary data has suggested that CrossFit practice is associated with higher levels of sense of community, satisfaction, and motivation.

Long non-coding RNA CCAT1 as a diagnostic and prognostic molecular marker in various cancers: a meta-analysis.

PubMed

Zhang, Zhihui; Xie, Haibiao; Liang, Daqiang; Huang, Lanbing; Liang, Feiguo; Qi, Qiang; Yang, Xinjian

2018-05-04

Long non-coding RNA colon cancer-associated transcript-1 (CCAT1) is newly found to be related with diagnoses and prognosis of cancer. This meta-analysis was performed to investigate the relationship between CCAT1 expression and clinical parameters, including survival condition, lymph node metastasis and tumor node metastasis grade. The primary literatures were collected through initial search criteria from electronic databases, including PubMed, OVID Evidence-based medicine Reviews and others (up to May 12, 2017). Eligible studies were identified and selected by the inclusion and exclusion criteria. Data was extracted and computed into Hazard ratio (HR) for the assessment of overall survival, subgroup analyses were prespecified based on the digestive tract cancer or others. Analysis of different CCAT1 expression related with lymph node metastasis or tumor node metastasis grade was conducted. Risk of bias was assessed by the Newcastle-Ottawa Scale. 9 studies were included. This meta-analysis showed that high CCAT1 expression level was related to poor overall survival, the pooled HR was 2.42 (95% confidence interval, CI: 1.86-3.16; P < 0.001; fix- effects model), similarly in the cancer type subgroups: digestive tract cancer (HR, 2.42; 95% CI, 1.79-3.29; P < 0.001; fix- effects model) and others (HR, 2.42; 95% CI, 1.42-4.13; P = 0.001; fix- effects model). The analysis showed that high CCAT1 was strongly related to positive lymph node metastasis (Odds ratio, OR: 3.24; 95% CI, 2.04-5.16; P < 0.001; fix- effects model), high tumor node metastasis stage (OR, 3.87; 95% CI, 2.53-5.92; P < 0.001; fix- effects model). In conclusion, this meta-analysis revealed that CCAT1 had potential as a diagnostic and prognostic biomarker in various cancers.

Evidence-based mapping of design heterogeneity prior to meta-analysis: a systematic review and evidence synthesis.

PubMed

Althuis, Michelle D; Weed, Douglas L; Frankenfeld, Cara L

2014-07-23

Assessment of design heterogeneity conducted prior to meta-analysis is infrequently reported; it is often presented post hoc to explain statistical heterogeneity. However, design heterogeneity determines the mix of included studies and how they are analyzed in a meta-analysis, which in turn can importantly influence the results. The goal of this work is to introduce ways to improve the assessment and reporting of design heterogeneity prior to statistical summarization of epidemiologic studies. In this paper, we use an assessment of sugar-sweetened beverages (SSB) and type 2 diabetes (T2D) as an example to show how a technique called 'evidence mapping' can be used to organize studies and evaluate design heterogeneity prior to meta-analysis.. Employing a systematic and reproducible approach, we evaluated the following elements across 11 selected cohort studies: variation in definitions of SSB, T2D, and co-variables, design features and population characteristics associated with specific definitions of SSB, and diversity in modeling strategies. Evidence mapping strategies effectively organized complex data and clearly depicted design heterogeneity. For example, across 11 studies of SSB and T2D, 7 measured diet only once (with 7 to 16 years of disease follow-up), 5 included primarily low SSB consumers, and 3 defined the study variable (SSB) as consumption of either sugar or artificially-sweetened beverages. This exercise also identified diversity in analysis strategies, such as adjustment for 11 to 17 co-variables and a large degree of fluctuation in SSB-T2D risk estimates depending on variables selected for multivariable models (2 to 95% change in the risk estimate from the age-adjusted model). Meta-analysis seeks to understand heterogeneity in addition to computing a summary risk estimate. This strategy effectively documents design heterogeneity, thus improving the practice of meta-analysis by aiding in: 1) protocol and analysis planning, 2) transparent reporting of differences in study designs, and 3) interpretation of pooled estimates. We recommend expanding the practice of meta-analysis reporting to include a table that summarizes design heterogeneity. This would provide readers with more evidence to interpret the summary risk estimates.

Evidence-based mapping of design heterogeneity prior to meta-analysis: a systematic review and evidence synthesis

PubMed Central

2014-01-01

Background Assessment of design heterogeneity conducted prior to meta-analysis is infrequently reported; it is often presented post hoc to explain statistical heterogeneity. However, design heterogeneity determines the mix of included studies and how they are analyzed in a meta-analysis, which in turn can importantly influence the results. The goal of this work is to introduce ways to improve the assessment and reporting of design heterogeneity prior to statistical summarization of epidemiologic studies. Methods In this paper, we use an assessment of sugar-sweetened beverages (SSB) and type 2 diabetes (T2D) as an example to show how a technique called ‘evidence mapping’ can be used to organize studies and evaluate design heterogeneity prior to meta-analysis.. Employing a systematic and reproducible approach, we evaluated the following elements across 11 selected cohort studies: variation in definitions of SSB, T2D, and co-variables, design features and population characteristics associated with specific definitions of SSB, and diversity in modeling strategies. Results Evidence mapping strategies effectively organized complex data and clearly depicted design heterogeneity. For example, across 11 studies of SSB and T2D, 7 measured diet only once (with 7 to 16 years of disease follow-up), 5 included primarily low SSB consumers, and 3 defined the study variable (SSB) as consumption of either sugar or artificially-sweetened beverages. This exercise also identified diversity in analysis strategies, such as adjustment for 11 to 17 co-variables and a large degree of fluctuation in SSB-T2D risk estimates depending on variables selected for multivariable models (2 to 95% change in the risk estimate from the age-adjusted model). Conclusions Meta-analysis seeks to understand heterogeneity in addition to computing a summary risk estimate. This strategy effectively documents design heterogeneity, thus improving the practice of meta-analysis by aiding in: 1) protocol and analysis planning, 2) transparent reporting of differences in study designs, and 3) interpretation of pooled estimates. We recommend expanding the practice of meta-analysis reporting to include a table that summarizes design heterogeneity. This would provide readers with more evidence to interpret the summary risk estimates. PMID:25055879

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.

PubMed

Achana, Felix A; Cooper, Nicola J; Bujkiewicz, Sylwia; Hubbard, Stephanie J; Kendrick, Denise; Jones, David R; Sutton, Alex J

2014-07-21

Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis. Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately.

Design and Analysis of an X-Ray Mirror Assembly Using the Meta-Shell Approach

NASA Technical Reports Server (NTRS)

McClelland, Ryan S.; Bonafede, Joseph; Saha, Timo T.; Solly, Peter M.; Zhang, William W.

2016-01-01

Lightweight and high resolution optics are needed for future space-based x-ray telescopes to achieve advances in high-energy astrophysics. Past missions such as Chandra and XMM-Newton have achieved excellent angular resolution using a full shell mirror approach. Other missions such as Suzaku and NuSTAR have achieved lightweight mirrors using a segmented approach. This paper describes a new approach, called meta-shells, which combines the fabrication advantages of segmented optics with the alignment advantages of full shell optics. Meta-shells are built by layering overlapping mirror segments onto a central structural shell. The resulting optic has the stiffness and rotational symmetry of a full shell, but with an order of magnitude greater collecting area. Several meta-shells so constructed can be integrated into a large x-ray mirror assembly by proven methods used for Chandra and XMM-Newton. The mirror segments are mounted to the meta-shell using a novel four point semi-kinematic mount. The four point mount deterministically locates the segment in its most performance sensitive degrees of freedom. Extensive analysis has been performed to demonstrate the feasibility of the four point mount and meta-shell approach. A mathematical model of a meta-shell constructed with mirror segments bonded at four points and subject to launch loads has been developed to determine the optimal design parameters, namely bond size, mirror segment span, and number of layers per meta-shell. The parameters of an example 1.3 m diameter mirror assembly are given including the predicted effective area. To verify the mathematical model and support opto-mechanical analysis, a detailed finite element model of a meta-shell was created. Finite element analysis predicts low gravity distortion and low sensitivity to thermal gradients.

Meta-analysis of two studies in the presence of heterogeneity with applications in rare diseases.

PubMed

Friede, Tim; Röver, Christian; Wandel, Simon; Neuenschwander, Beat

2017-07-01

Random-effects meta-analyses are used to combine evidence of treatment effects from multiple studies. Since treatment effects may vary across trials due to differences in study characteristics, heterogeneity in treatment effects between studies must be accounted for to achieve valid inference. The standard model for random-effects meta-analysis assumes approximately normal effect estimates and a normal random-effects model. However, standard methods based on this model ignore the uncertainty in estimating the between-trial heterogeneity. In the special setting of only two studies and in the presence of heterogeneity, we investigate here alternatives such as the Hartung-Knapp-Sidik-Jonkman method (HKSJ), the modified Knapp-Hartung method (mKH, a variation of the HKSJ method) and Bayesian random-effects meta-analyses with priors covering plausible heterogeneity values; R code to reproduce the examples is presented in an appendix. The properties of these methods are assessed by applying them to five examples from various rare diseases and by a simulation study. Whereas the standard method based on normal quantiles has poor coverage, the HKSJ and mKH generally lead to very long, and therefore inconclusive, confidence intervals. The Bayesian intervals on the whole show satisfying properties and offer a reasonable compromise between these two extremes. © 2016 The Authors. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Intermittent Cervical Traction for Treating Neck Pain: A Meta-analysis of Randomized Controlled Trials.

PubMed

Yang, Jheng-Dao; Tam, Ka-Wai; Huang, Tsai-Wei; Huang, Shih-Wei; Liou, Tsan-Hon; Chen, Hung-Chou

2017-07-01

A meta-analysis. The aim of this study was to perform a comprehensive search of current literature and conduct a meta-analysis of randomized controlled trials (RCTs) to assess the neck pain relieving effect of intermittent cervical traction (ICT). Neck pain is a common and disabling problem with a high prevalence in general population. It causes a considerable burden on the health care system with a substantial expenditure. ICT is a common component of physical therapy for neck pain in the outpatient clinic. However, the evidence regarding the effectiveness of ICT for neck pain is insufficient. Data were obtained from the PubMed, Cochrane Library, Embase, and Scopus databases from the database inception date to July 02, 2016. RCTs reporting the effects of ICT on neck pain, including those comparing the effects of ICT with those of a placebo treatment, were included. Two reviewers independently reviewed the studies, conducted a risk of bias assessment, and extracted data. The data were pooled in a meta-analysis by using a random-effects model. The meta-analysis included seven RCTs. The results indicated that patients who received ICT for neck pain had significantly lower pain scores than those receiving placebos did immediately after treatment (standardized mean difference = -0.26, 95% confidence interval = -0.46 to -0.07). The pain scores during the follow-up period and the neck disability index scores immediately after treatment and during the follow-up period did not differ significantly. ICT may have a short-term neck pain-relieving effect. Some risks of bias were noted in the included studies, reducing the evidence level of this meta-analysis. Additional high-quality RCTs are required to clarify the long-term effects of ICT on neck pain. 1.

Lipid profile changes after pomegranate consumption: A systematic review and meta-analysis of randomized controlled trials.

PubMed

Sahebkar, Amirhossein; Simental-Mendía, Luis E; Giorgini, Paolo; Ferri, Claudio; Grassi, Davide

2016-10-15

Transport of oxidized low-density lipoprotein across the endothelium into the artery wall is considered a fundamental priming step for the atherosclerotic process. Recent studies reported potential therapeutic effects of micronutrients found in natural products, indicating positive applications for controlling the pathogenesis of chronic cardiovascular disease driven by cardiovascular risk factors and oxidative stress. A particular attention has been recently addressed to pomegranate; however findings of clinical studies have been contrasting. To evaluate the effects of pomegranate consumption on plasma lipid concentrations through a systematic review and meta-analysis of randomized controlled trials (RCTs). The study was designed according to the preferred reporting items for systematic reviews and meta-analysis (PRISMA) statement. Scopus and Medline databases were searched to identify randomized placebo-controlled trials investigating the impact of pomegranate on plasma lipid concentrations. A fixed-effects model and the generic inverse variance method were used for quantitative data synthesis. Sensitivity analysis was conducted using the one-study remove approach. Random-effects meta-regression was performed to assess the impact of potential confounders on the estimated effect sizes. A total of 545 individuals were recruited from the 12 RCTs. Fixed-effect meta-analysis of data from 12 RCTs (13 treatment arms) did not show any significant effect of pomegranate consumption on plasma lipid concentrations. The results of meta-regression did not suggest any significant association between duration of supplementation and impact of pomegranate on total cholesterol and HDL-C, while an inverse association was found with changes in triglycerides levels (slope: -1.07; 95% CI: -2.03 to -0.11; p = 0.029). There was no association between the amount of pomegranate juice consumed per day and respective changes in plasma total cholesterol, LDL-C, HDL-C and triglycerides. The present meta-analysis of RCTs did not suggest any effect of pomegranate consumption on lipid profile in human. Copyright © 2016. Published by Elsevier GmbH.

Effect of dipeptidyl peptidase-4 inhibitors on circulating tumor necrosis factor-α concentrations: A systematic review and meta-analysis of controlled trials.

PubMed

Atkin, Stephen L; Katsiki, Niki; Banach, Maciej; Mikhailidis, Dimitri P; Pirro, Matteo; Sahebkar, Amirhossein

2017-09-01

Dipeptidyl peptidase-4 (DPP-4) inhibitors improve glycemic control in patients with type 2 diabetes mellitus. There are also reports of an effect of these drugs in reducing inflammation through inhibition of tumor necrosis factor-α (TNF-α) that is an important mediator for several inflammatory processes. The present systematic review and meta-analysis were performed to evaluate the effect of DPP-4 inhibitors on circulating TNF-α levels in T2DM patients. A systematic review and a meta-analysis were undertaken on all controlled trials of DPP-4 inhibitors that included measurement of TNF-α. The search included PubMed-Medline, Scopus, ISI Web of Knowledge and Google Scholar databases. Quantitative data synthesis was performed using a random-effects model, with standardized mean difference (SMD) and 95% confidence interval (CI) as summary statistics. Meta-regression and leave-one-out sensitivity analysis were performed to assess the modifiers of treatment response. Eight eligible articles (6 with sitagliptin and 2 with vildagliptin) comprising 9 treatment arms were selected for this meta-analysis. Meta-analysis suggested a significant reduction of circulating TNF-α concentrations following treatment with DPP-4 inhibitors (SMD: -1.84, 95% CI: -2.88, -0.80, p=0.001). The effect size was robust in the sensitivity analysis and not mainly driven by a single study. A subgroup analysis did not suggest any significant difference between the TNF-α-lowering activity of sitagliptin (SMD: -1.49, 95% CI: -2.89, -0.10) and vildagliptin (SMD: -2.80, 95% CI: -4.98, -0.61) (p=0.326). This meta-analysis of the 8 available controlled trials showed that DPP-4 inhibition in patients with type 2 diabetes mellitus was associated with significant reductions in plasma TNF-α levels with no apparent difference between sitagliptin and vildagliptin. Copyright © 2017 Elsevier Inc. All rights reserved.

Association between diabetes mellitus and gastroesophageal reflux disease: A meta-analysis

PubMed Central

Sun, Xiao-Meng; Tan, Jia-Cheng; Zhu, Ying; Lin, Lin

2015-01-01

AIM: To investigate whether there is a link between diabetes mellitus (DM) and gastroesophageal reflux disease (GERD). METHODS: We conducted a systematic search of PubMed and Web of Science databases, from their respective inceptions until December 31, 2013, for articles evaluating the relationship between DM and GERD. Studies were selected for analysis based on certain inclusion and exclusion criteria. Data were extracted from each study on the basis of predefined items. A meta-analysis was performed to compare the odds ratio (OR) in DM between individuals with and without GERD using a fixed effect or random effect model, depending on the absence or presence of significant heterogeneity. Subgroup analyses were used to identify sources of heterogeneity. Publication bias was assessed by Begg’s test. To evaluate the results, we also performed a sensitivity analysis. RESULTS: When the electronic database and hand searches were combined, a total of nine eligible articles involving 9067 cases and 81 968 controls were included in our meta-analysis. Based on the random-effects model, these studies identified a significant association between DM and the risk of GERD (overall OR = 1.61; 95%CI: 1.36-1.91; P = 0.003). Subgroup analyses indicated that this result persisted in studies on populations from Eastern countries (OR = 1.71; 95%CI: 1.38-2.12; P = 0.003) and in younger patients (mean age < 50 years) (OR = 1.70; 95%CI: 1.22-2.37; P = 0.001). No significant publication bias was observed in this meta-analysis using Begg’s test (P = 0.175). The sensitivity analysis also confirmed the stability of our results. CONCLUSION: This meta-analysis suggests that patients with DM are at greater risk of GERD than those who do not have DM. PMID:25780309

Comparison of intra-articular hyaluronic acid and methylprednisolone for pain management in knee osteoarthritis: A meta-analysis of randomized controlled trials.

PubMed

Ran, Jian; Yang, Xiaohui; Ren, Zheng; Wang, Jian; Dong, Hui

2018-05-01

We performed a meta-analysis of randomized controlled trials (RCTs) to compare the efficacy and safety of intra-articular methylprednisolone and hyaluronic acid (HA) in term of pain reduction and improvements of knee function in patients with knee osteoarthritis (OA). The PubMed, EMBASE, ScienceDirect, and Cochrane Library databases were systematically searched for literature up to January 2018. RCTs involving HA and methylprednisolone in knee OA were included. Two independent reviewers performed independent data abstraction. The I 2 statistic was used to assess heterogeneity. A fixed or random effects model was adopted for meta-analysis. All meta-analyses were performed by using STATA 14.0. Five RCTs with 1004 patients were included in the meta-analysis. The present meta-analysis indicated that there were no significant differences in terms of WOMAC pain, physical function and stiffness at 4 week, 12 weeks and 26 weeks between HA and methylprednisolone groups. No increased risk of adverse events were identified in both groups. Both HA and methylprednisolone injections were effective therapies for patients with knee OA. Methylprednisolone showed comparable efficacy in reducing pain and improving functional recovery to HA. And no significant difference was found in long-term of follow-up in terms of adverse effects. Copyright © 2018 IJS Publishing Group Ltd. All rights reserved.

Indirect health costs in ulcerative colitis and Crohn's disease: a systematic review and meta-analysis.

PubMed

Kawalec, Paweł; Malinowski, Krzysztof Piotr

2015-04-01

The aim of this systematic review was to collect all current data on indirect costs related to inflammatory bowel disease as well as assessing homogeneity and comparability, and conducting a meta-analysis. Costs were collected using databases from Medline, Embase and Centre for Reviews and Dissemination databases, then average annual cost per patient was calculated and expressed in 2013-rate USD using the consumer price index and purchasing power parity (scenario 1) and then adjusted to specific gross domestic product (scenario 2) to make them comparable. The studies were then included in quantitative synthesis using the meta-analysis and bootstrap methods. This systematic review was carried out and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. From 18 publications, overall annual indirect costs per patient as a result of the quantitative synthesis among all studies eligible for meta-analysis ranged from US$2425.01-US$9622.15 depending on the scenario and model used for analysis. The cost of presenteeism was assessed in only two studies. Considering heterogeneity among all identified studies random-effect model presented the most accurate results of meta-analysis equal to US$7189.27 and US$9622.15 per patient per year for scenario 1 and scenario 2, respectively. This systematic review revealed the existence of a relatively small number of studies that reported on the great economic burden of the disease upon society. A great variety of methodologies and cost components resulted in a very large discrepancy in indirect costs and made meta-analysis difficult to perform, so two scenarios were considered and meta-analysis conducted in subgroups to make data more comparable.

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta-analysis and group level studies.

PubMed

Bakbergenuly, Ilyas; Kulinskaya, Elena; Morgenthaler, Stephan

2016-07-01

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group-level studies or in meta-analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log-odds and arcsine transformations of the estimated probability p̂, both for single-group studies and in combining results from several groups or studies in meta-analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta-analysis and result in abysmal coverage of the combined effect for large K. We also propose bias-correction for the arcsine transformation. Our simulations demonstrate that this bias-correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta-analyses of prevalence. © 2016 The Authors. Biometrical Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis.

PubMed

Sudell, Maria; Kolamunnage-Dona, Ruwanthi; Tudur-Smith, Catrin

2016-12-05

Joint models for longitudinal and time-to-event data are commonly used to simultaneously analyse correlated data in single study cases. Synthesis of evidence from multiple studies using meta-analysis is a natural next step but its feasibility depends heavily on the standard of reporting of joint models in the medical literature. During this review we aim to assess the current standard of reporting of joint models applied in the literature, and to determine whether current reporting standards would allow or hinder future aggregate data meta-analyses of model results. We undertook a literature review of non-methodological studies that involved joint modelling of longitudinal and time-to-event medical data. Study characteristics were extracted and an assessment of whether separate meta-analyses for longitudinal, time-to-event and association parameters were possible was made. The 65 studies identified used a wide range of joint modelling methods in a selection of software. Identified studies concerned a variety of disease areas. The majority of studies reported adequate information to conduct a meta-analysis (67.7% for longitudinal parameter aggregate data meta-analysis, 69.2% for time-to-event parameter aggregate data meta-analysis, 76.9% for association parameter aggregate data meta-analysis). In some cases model structure was difficult to ascertain from the published reports. Whilst extraction of sufficient information to permit meta-analyses was possible in a majority of cases, the standard of reporting of joint models should be maintained and improved. Recommendations for future practice include clear statement of model structure, of values of estimated parameters, of software used and of statistical methods applied.

Effects of exposure to malathion on blood glucose concentration: a meta-analysis.

PubMed

Ramirez-Vargas, Marco Antonio; Flores-Alfaro, Eugenia; Uriostegui-Acosta, Mayrut; Alvarez-Fitz, Patricia; Parra-Rojas, Isela; Moreno-Godinez, Ma Elena

2018-02-01

Exposure to malathion (an organophosphate pesticide widely used around the world) has been associated with alterations in blood glucose concentration in animal models. However, the results are inconsistent. The aim of this meta-analysis was to evaluate whether malathion exposure can disturb the concentrations of blood glucose in exposed rats. We performed a literature search of online databases including PubMed, EBSCO, and Google Scholar and reviewed original articles that analyzed the relation between malathion exposure and glucose levels in animal models. The selection of articles was based on inclusion and exclusion criteria. The database search identified thirty-five possible articles, but only eight fulfilled our inclusion criteria, and these studies were included in the meta-analysis. The effect of malathion on blood glucose concentration showed a non-monotonic dose-response curve. In addition, pooled analysis showed that blood glucose concentrations were 3.3-fold higher in exposed rats than in the control group (95% CI, 2-5; Z = 3.9; p < 0.0001) in a random-effect model. This result suggested that alteration of glucose homeostasis is a possible mechanism of toxicity associated with exposure to malathion.

Lysergic acid diethylamide (LSD) for alcoholism: meta-analysis of randomized controlled trials.

PubMed

Krebs, Teri S; Johansen, Pål-Ørjan

2012-07-01

Assessments of lysergic acid diethylamide (LSD) in the treatment of alcoholism have not been based on quantitative meta-analysis. Hence, we performed a meta-analysis of randomized controlled trials in order to evaluate the clinical efficacy of LSD in the treatment of alcoholism. Two reviewers independently extracted the data, pooling the effects using odds ratios (ORs) by a generic inverse variance, random effects model. We identified six eligible trials, including 536 participants. There was evidence for a beneficial effect of LSD on alcohol misuse (OR, 1.96; 95% CI, 1.36-2.84; p = 0.0003). Between-trial heterogeneity for the treatment effects was negligible (I² = 0%). Secondary outcomes, risk of bias and limitations are discussed. A single dose of LSD, in the context of various alcoholism treatment programs, is associated with a decrease in alcohol misuse.

Treatment with GLP1 receptor agonists reduce serum CRP concentrations in patients with type 2 diabetes mellitus: A systematic review and meta-analysis of randomized controlled trials.

PubMed

Mazidi, Mohsen; Karimi, Ehsan; Rezaie, Peyman; Ferns, Gordon A

2017-07-01

To undertake a systematic review and meta-analysis of randomized controlled trials of the effect of glucagon-like peptide-1 receptor agonist (GLP-1 RAs) therapy on serum C-reactive protein (CRP) concentrations. PubMed-Medline, SCOPUS, Web of Science and Google Scholar databases were searched for the period up until March 16, 2016. Prospective studies evaluating the impact of GLP-1 RAs on serum CRP were identified. A random effects model (using the DerSimonian-Laird method) and generic inverse variance methods were used for quantitative data synthesis. Sensitivity analysis was conducted using the leave-one-out method. Heterogeneity was quantitatively assessed using the I 2 index. Random effects meta-regression was performed using unrestricted maximum likelihood method to evaluate the impact of potential moderator. International Prospective Register for Systematic Reviews (PROSPERO) number CRD42016036868. Meta-analysis of the data from 7 treatment arms revealed a significant reduction in serum CRP concentrations following treatment with GLP-1 RAs (WMD -2.14 (mg/dL), 95% CI -3.51, -0.78, P=0.002; I 2 96.1%). Removal of one study in the meta-analysis did not change the result in the sensitivity analysis (WMD -2.14 (mg/dL), 95% CI -3.51, -0.78, P=0.002; I 2 96.1%), indicating that our results could not be solely attributed to the effect of a single study. Random effects meta-regression was performed to evaluate the impact of potential moderator on the estimated effect size. Changes in serum CRP concentration were associated with the duration of treatment (slope -0.097, 95% CI -0.158, -0.042, P<0.001). This meta-analysis suggests that GLP-1 RAs therapy causes a significant reduction in CRP. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of Pro12Ala polymorphism in peroxisome proliferator-activated receptor-γ2 gene on metabolic syndrome risk: a meta-analysis.

PubMed

Zhang, Ruyi; Wang, Jiao; Yang, Rui; Sun, Jia; Chen, Rongping; Luo, Haizhao; Liu, Duan; Cai, Dehong

2014-02-01

Associations between peroxisome proliferator-activated receptor γ2 (PPARγ2) gene polymorphism and metabolic syndrome risk remained controversial and ambiguous. Thus, we performed a meta-analysis to assess the association between Pro12Ala polymorphism in PPARγ2 gene and metabolic syndrome susceptibility. An electronic literature search was conducted on Medline, OVID, Cochrane Library database, and the China National Knowledge Internet up to March 2013. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to calculate the strength of association in the fixed or random effects model. Ten studies involving a total of 4456 cases and 10343 controls were included in this meta-analysis. No statistical evidence of association was found between Pro12Ala polymorphism and metabolic syndrome risk in all genetic models (homozygote model: OR=0.83, 95% CI=0.62-1.12; heterozygote model: OR=1.04, 95% CI=0.94-1.14; dominant model: OR=1.02, 95% CI=0.93-1.12; recessive model: OR=0.83, 95% CI=0.62-1.11). No statistical evidence of significant association was observed when stratified by ethnicity, definition of metabolic syndrome, source of control groups and quality score of the selected articles. All in all, the results did not support a major role of the Pro12Ala variant of the PPARγ2 gene in metabolic syndrome risk. This meta-analysis suggested that the effect of Pro12Ala polymorphism in PPARγ2 gene may not be related to metabolic syndrome as an entity. However, Pro12Ala may affect the single component of metabolic syndrome. A large, well designed study is required to more adequately assess the role for Pro12Ala polymorphism on metabolic syndrome. © 2013 Elsevier B.V. All rights reserved.

A Comparative Meta-Analysis of 5E and Traditional Approaches in Turkey

ERIC Educational Resources Information Center

Anil, Özgür; Batdi, Veli

2015-01-01

The aim of this study is to compare the 5E learning model with traditional learning methods in terms of their effect on students' academic achievement, retention and attitude scores. In this context, the meta-analytic method known as the "analysis of analyses" was used and a review undertaken of the studies and theses (N = 14) executed…

Maternal Smoking and Autism Spectrum Disorder: A Meta-Analysis

ERIC Educational Resources Information Center

Rosen, Brittany N.; Lee, Brian K.; Lee, Nora L.; Yang, Yunwen; Burstyn, Igor

2015-01-01

We conducted a meta-analysis of 15 studies on maternal prenatal smoking and ASD risk in offspring. Using a random-effects model, we found no evidence of an association (summary OR 1.02, 95% CI 0.93-1.12). Stratifying by study design, birth year, type of healthcare system, and adjustment for socioeconomic status or psychiatric history did not alter…

A Finite Mixture Method for Outlier Detection and Robustness in Meta-Analysis

ERIC Educational Resources Information Center

Beath, Ken J.

2014-01-01

When performing a meta-analysis unexplained variation above that predicted by within study variation is usually modeled by a random effect. However, in some cases, this is not sufficient to explain all the variation because of outlier or unusual studies. A previously described method is to define an outlier as a study requiring a higher random…

A Quantitative Review and Meta-Models of the Variability and Factors Affecting Oral Drug Absorption-Part I: Gastrointestinal pH.

PubMed

Abuhelwa, Ahmad Y; Foster, David J R; Upton, Richard N

2016-09-01

This study aimed to conduct a quantitative meta-analysis for the values of, and variability in, gastrointestinal (GI) pH in the different GI segments; characterize the effect of food on the values and variability in these parameters; and present quantitative meta-models of distributions of GI pH to help inform models of oral drug absorption. The literature was systemically reviewed for the values of, and the variability in, GI pH under fed and fasted conditions. The GI tract was categorized into the following 10 distinct regions: stomach (proximal, mid-distal), duodenum (proximal, mid-distal), jejunum and ileum (proximal, mid, and distal small intestine), and colon (ascending, transverse, and descending colon). Meta-analysis used the "metafor" package of the R language. The time course of postprandial stomach pH was modeled using NONMEM. Food significantly influenced the estimated meta-mean stomach and duodenal pH but had no significant influence on small intestinal and colonic pH. The time course of postprandial pH was described using an exponential model. Increased meal caloric content increased the extent and duration of postprandial gastric pH buffering. The different parts of the small intestine had significantly different pH. Colonic pH was significantly different for descending but not for ascending and transverse colon. Knowledge of GI pH is important for the formulation design of the pH-dependent dosage forms and in understanding the dissolution and absorption of orally administered drugs. The meta-models of GI pH may also be used as part of semi-physiological pharmacokinetic models to characterize the effect of GI pH on the in vivo drug release and pharmacokinetics.

The correlation of social support with mental health: A meta-analysis

PubMed Central

Harandi, Tayebeh Fasihi; Taghinasab, Maryam Mohammad; Nayeri, Tayebeh Dehghan

2017-01-01

Background and aim Social support is an important factor that can affect mental health. In recent decades, many studies have been done on the impact of social support on mental health. The purpose of the present study is to investigate the effect size of the relationship between social support and mental health in studies in Iran. Methods This meta-analysis was carried out in studies that were performed from 1996 through 2015. Databases included SID and Magiran, the comprehensive portal of human sciences, Noor specialized magazine databases, IRANDOC, Proquest, PubMed, Scopus, ERIC, Iranmedex and Google Scholar. The keywords used to search these websites included “mental health or general health,” and “Iran” and “social support.” In total, 64 studies had inclusion criteria meta-analysis. In order to collect data used from a meta-analysis worksheet that was made by the researcher and for data analysis software, CMA-2 was used. Results The mean of effect size of the 64 studies in the fixed-effect model and random-effect model was obtained respectively as 0.356 and 0.330, which indicated the moderate effect size of social support on mental health. The studies did not have publication bias, and enjoyed a heterogeneous effect size. The target population and social support questionnaire were moderator variables, but sex, sampling method, and mental health questionnaire were not moderator variables. Conclusion Regarding relatively high effect size of the correlation between social support and mental health, it is necessary to predispose higher social support, especially for women, the elderly, patients, workers, and students. PMID:29038699

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

A Bayesian Network Meta-Analysis to Synthesize the Influence of Contexts of Scaffolding Use on Cognitive Outcomes in STEM Education.

PubMed

Belland, Brian R; Walker, Andrew E; Kim, Nam Ju

2017-12-01

Computer-based scaffolding provides temporary support that enables students to participate in and become more proficient at complex skills like problem solving, argumentation, and evaluation. While meta-analyses have addressed between-subject differences on cognitive outcomes resulting from scaffolding, none has addressed within-subject gains. This leaves much quantitative scaffolding literature not covered by existing meta-analyses. To address this gap, this study used Bayesian network meta-analysis to synthesize within-subjects (pre-post) differences resulting from scaffolding in 56 studies. We generated the posterior distribution using 20,000 Markov Chain Monte Carlo samples. Scaffolding has a consistently strong effect across student populations, STEM (science, technology, engineering, and mathematics) disciplines, and assessment levels, and a strong effect when used with most problem-centered instructional models (exception: inquiry-based learning and modeling visualization) and educational levels (exception: secondary education). Results also indicate some promising areas for future scaffolding research, including scaffolding among students with learning disabilities, for whom the effect size was particularly large (ḡ = 3.13).

A Bayesian Network Meta-Analysis to Synthesize the Influence of Contexts of Scaffolding Use on Cognitive Outcomes in STEM Education

PubMed Central

Belland, Brian R.; Walker, Andrew E.; Kim, Nam Ju

2017-01-01

Computer-based scaffolding provides temporary support that enables students to participate in and become more proficient at complex skills like problem solving, argumentation, and evaluation. While meta-analyses have addressed between-subject differences on cognitive outcomes resulting from scaffolding, none has addressed within-subject gains. This leaves much quantitative scaffolding literature not covered by existing meta-analyses. To address this gap, this study used Bayesian network meta-analysis to synthesize within-subjects (pre–post) differences resulting from scaffolding in 56 studies. We generated the posterior distribution using 20,000 Markov Chain Monte Carlo samples. Scaffolding has a consistently strong effect across student populations, STEM (science, technology, engineering, and mathematics) disciplines, and assessment levels, and a strong effect when used with most problem-centered instructional models (exception: inquiry-based learning and modeling visualization) and educational levels (exception: secondary education). Results also indicate some promising areas for future scaffolding research, including scaffolding among students with learning disabilities, for whom the effect size was particularly large (ḡ = 3.13). PMID:29200508

Detecting and correcting for publication bias in meta-analysis - A truncated normal distribution approach.

PubMed

Zhu, Qiaohao; Carriere, K C

2016-01-01

Publication bias can significantly limit the validity of meta-analysis when trying to draw conclusion about a research question from independent studies. Most research on detection and correction for publication bias in meta-analysis focus mainly on funnel plot-based methodologies or selection models. In this paper, we formulate publication bias as a truncated distribution problem, and propose new parametric solutions. We develop methodologies of estimating the underlying overall effect size and the severity of publication bias. We distinguish the two major situations, in which publication bias may be induced by: (1) small effect size or (2) large p-value. We consider both fixed and random effects models, and derive estimators for the overall mean and the truncation proportion. These estimators will be obtained using maximum likelihood estimation and method of moments under fixed- and random-effects models, respectively. We carried out extensive simulation studies to evaluate the performance of our methodology, and to compare with the non-parametric Trim and Fill method based on funnel plot. We find that our methods based on truncated normal distribution perform consistently well, both in detecting and correcting publication bias under various situations.

The correlation analysis of tumor necrosis factor-alpha-308G/A polymorphism and venous thromboembolism risk: A meta-analysis.

PubMed

Gao, Quangen; Zhang, Peijin; Wang, Wei; Ma, He; Tong, Yue; Zhang, Jing; Lu, Zhaojun

2016-10-01

Venous thromboembolism is a common complex disorder, being the resultant of gene-gene and gene-environment interactions. Tumor necrosis factor-alpha is a proinflammatory cytokine which has been implicated in venous thromboembolism risk. A promoter 308G/A polymorphism in the tumor necrosis factor-alpha gene has been suggested to modulate the risk for venous thromboembolism. However, the published findings remain inconsistent. In this study, we conducted a meta-analysis of all available data regarding this issue. Eligible studies were identified through search of Pubmed, EBSCO Medline, Web of Science, and China National Knowledge Infrastructure (CNKI, Chinese) databases up to June 2014. Pooled Odd ratios (ORs) with 95% confidence intervals were applied to estimating the strength of the genetic association in the random-effects model or fixed-effects model. A total of 10 studies involving 1999 venous thromboembolism cases and 2166 controls were included in this meta-analysis to evaluate the association between tumor necrosis factor-alpha-308G/A polymorphism and venous thromboembolism risk. Overall, no significantly increased risk venous thromboembolism was observed in all comparison models when all studies were pooled into the meta-analysis. However, in stratified analyses by ethnicity, there was a pronounced association with venous thromboembolism risk among West Asians in three genetic models (A vs. G: OR = 1.82, 95%CI = 1.13-2.94; GA vs. GG: OR = 1.82, 95%CI = 1.08-3.06; AA/GA vs. GG: OR = 1.88, 95%CI = 1.12-3.16). When stratifying by source of controls, no significant result was detected in all genetic models. This meta-analysis demonstrates that tumor necrosis factor-alpha 308G/A polymorphism may contribute to susceptibility to venous thromboembolism among West Asians. Studies are needed to ascertain these findings in larger samples and different racial groups. © The Author(s) 2015.

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes.

PubMed

Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P

2017-01-11

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

Ataxia Telangiectasia–Mutated Gene Polymorphisms and Acute Normal Tissue Injuries in Cancer Patients After Radiation Therapy: A Systematic Review and Meta-analysis

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

Dong, Lihua; Cui, Jingkun; Tang, Fengjiao

Purpose: Studies of the association between ataxia telangiectasia–mutated (ATM) gene polymorphisms and acute radiation injuries are often small in sample size, and the results are inconsistent. We conducted the first meta-analysis to provide a systematic review of published findings. Methods and Materials: Publications were identified by searching PubMed up to April 25, 2014. Primary meta-analysis was performed for all acute radiation injuries, and subgroup meta-analyses were based on clinical endpoint. The influence of sample size and radiation injury incidence on genetic effects was estimated in sensitivity analyses. Power calculations were also conducted. Results: The meta-analysis was conducted on the ATMmore » polymorphism rs1801516, including 5 studies with 1588 participants. For all studies, the cut-off for differentiating cases from controls was grade 2 acute radiation injuries. The primary meta-analysis showed a significant association with overall acute radiation injuries (allelic model: odds ratio = 1.33, 95% confidence interval: 1.04-1.71). Subgroup analyses detected an association between the rs1801516 polymorphism and a significant increase in urinary and lower gastrointestinal injuries and an increase in skin injury that was not statistically significant. There was no between-study heterogeneity in any meta-analyses. In the sensitivity analyses, small studies did not show larger effects than large studies. In addition, studies with high incidence of acute radiation injuries showed larger effects than studies with low incidence. Power calculations revealed that the statistical power of the primary meta-analysis was borderline, whereas there was adequate power for the subgroup analysis of studies with high incidence of acute radiation injuries. Conclusions: Our meta-analysis showed a consistency of the results from the overall and subgroup analyses. We also showed that the genetic effect of the rs1801516 polymorphism on acute radiation injuries was dependent on the incidence of the injury. These support the evidence of an association between the rs1801516 polymorphism and acute radiation injuries, encouraging further research of this topic.« less

Saving lives: A meta-analysis of team training in healthcare.

PubMed

Hughes, Ashley M; Gregory, Megan E; Joseph, Dana L; Sonesh, Shirley C; Marlow, Shannon L; Lacerenza, Christina N; Benishek, Lauren E; King, Heidi B; Salas, Eduardo

2016-09-01

As the nature of work becomes more complex, teams have become necessary to ensure effective functioning within organizations. The healthcare industry is no exception. As such, the prevalence of training interventions designed to optimize teamwork in this industry has increased substantially over the last 10 years (Weaver, Dy, & Rosen, 2014). Using Kirkpatrick's (1956, 1996) training evaluation framework, we conducted a meta-analytic examination of healthcare team training to quantify its effectiveness and understand the conditions under which it is most successful. Results demonstrate that healthcare team training improves each of Kirkpatrick's criteria (reactions, learning, transfer, results; d = .37 to .89). Second, findings indicate that healthcare team training is largely robust to trainee composition, training strategy, and characteristics of the work environment, with the only exception being the reduced effectiveness of team training programs that involve feedback. As a tertiary goal, we proposed and found empirical support for a sequential model of healthcare team training where team training affects results via learning, which leads to transfer, which increases results. We find support for this sequential model in the healthcare industry (i.e., the current meta-analysis) and in training across all industries (i.e., using meta-analytic estimates from Arthur, Bennett, Edens, & Bell, 2003), suggesting the sequential benefits of training are not unique to medical teams. Ultimately, this meta-analysis supports the expanded use of team training and points toward recommendations for optimizing its effectiveness within healthcare settings. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Curcumin downregulates human tumor necrosis factor-α levels: A systematic review and meta-analysis ofrandomized controlled trials.

PubMed

Sahebkar, Amirhossein; Cicero, Arrigo F G; Simental-Mendía, Luis E; Aggarwal, Bharat B; Gupta, Subash C

2016-05-01

Tumor necrosis factor-α (TNF-α) is a key inflammatory mediator and its reduction is a therapeutic target in several inflammatory diseases. Curcumin, a bioactive polyphenol from turmeric, has been shown in several preclinical studies to block TNF-α effectively. However, clinical evidence has not been fully conclusive. The aim of the present meta-analysis was to evaluate the efficacy of curcumin supplementation on circulating levels of TNF-α in randomized controlled trials (RCTs). The search included PubMed-Medline, Scopus, Web of Science and Google Scholar databases by up to September 21, 2015, to identify RCTs investigating the impact of curcumin on circulating TNF-α concentration. Quantitative data synthesis was performed using a random-effects model, with weighed mean difference (WMD) and 95% confidence interval (CI) as summary statistics. Meta-regression and leave-one-out sensitivity analyses were performed to assess the modifiers of treatment response. Eight RCTs comprising nine treatment arms were finally selected for the meta-analysis. There was a significant reduction of circulating TNF-α concentrations following curcumin supplementation (WMD: -4.69pg/mL, 95% CI: -7.10, -2.28, p<0.001). This effect size was robust in sensitivity analysis. Meta-regression did not suggest any significant association between the circulating TNF-α-lowering effects of curcumin with either dose or duration (slope: 0.197; 95% CI: -1.73, 2.12; p=0.841) of treatment. This meta-analysis of RCTs suggested a significant effect of curcumin in lowering circulating TNF-α concentration. Copyright © 2016 Elsevier Ltd. All rights reserved.

How to Make Nothing Out of Something: Analyses of the Impact of Study Sampling and Statistical Interpretation in Misleading Meta-Analytic Conclusions

PubMed Central

Cunningham, Michael R.; Baumeister, Roy F.

2016-01-01

The limited resource model states that self-control is governed by a relatively finite set of inner resources on which people draw when exerting willpower. Once self-control resources have been used up or depleted, they are less available for other self-control tasks, leading to a decrement in subsequent self-control success. The depletion effect has been studied for over 20 years, tested or extended in more than 600 studies, and supported in an independent meta-analysis (Hagger et al., 2010). Meta-analyses are supposed to reduce bias in literature reviews. Carter et al.’s (2015) meta-analysis, by contrast, included a series of questionable decisions involving sampling, methods, and data analysis. We provide quantitative analyses of key sampling issues: exclusion of many of the best depletion studies based on idiosyncratic criteria and the emphasis on mini meta-analyses with low statistical power as opposed to the overall depletion effect. We discuss two key methodological issues: failure to code for research quality, and the quantitative impact of weak studies by novice researchers. We discuss two key data analysis issues: questionable interpretation of the results of trim and fill and Funnel Plot Asymmetry test procedures, and the use and misinterpretation of the untested Precision Effect Test and Precision Effect Estimate with Standard Error (PEESE) procedures. Despite these serious problems, the Carter et al. (2015) meta-analysis results actually indicate that there is a real depletion effect – contrary to their title. PMID:27826272

Association between KCNJ11 gene polymorphisms and risk of type 2 diabetes mellitus in East Asian populations: a meta-analysis in 42,573 individuals.

PubMed

Yang, Lijuan; Zhou, Xianghai; Luo, Yingying; Sun, Xiuqin; Tang, Yong; Guo, Wulan; Han, Xueyao; Ji, Linong

2012-01-01

A number of studies have been performed to identify the association between potassium inwardly-rectifying channel, subfamily J, member 11 (KCNJ11) gene and type 2 diabetes mellitus (T2DM) in East Asian populations, with inconsistent results. The main aim of this work was to evaluate more precisely the genetic influence of KCNJ11 on T2DM in East Asian populations by means of a meta-analysis. We identified 20 articles for qualitative analysis and 16 were eligible for quantitative analysis (meta-analysis) by database searching up to May 2010. The association was assessed under different genetic models, and the pooled odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated. The allelic and genotypic contrast demonstrated that the association between KCNJ11 and T2DM was significant for rs5210. However, not all results for rs5215 and rs5218 showed significant associations. For rs5219, the combined ORs (95% CIs) for allelic contrast, dominant and recessive models contrast (with allelic frequency and genotypic distribution data) were 1.139 (1.093-1.188), 1.177 (1.099-1.259) and 1.207 (1.094-1.332), respectively (random effect model). The analysis on the most completely adjusted ORs (95% CIs) by the covariates of rs5219 all presented significant associations under different genetic models. Population-stratified analysis (Korean, Japanese and Chinese) and sensitivity analysis verified the significant results. Cumulative meta-analysis including publication time and sample size illustrated the exaggerated genetic effect in the earliest studies. Heterogeneity and publication bias were assessed. Our study verified that single nucleotide polymorphisms (SNPs) of KCNJ11 gene were significantly associated with the risk of T2DM in East Asian populations.

Optimal patient education for cancer pain: a systematic review and theory-based meta-analysis.

PubMed

Marie, N; Luckett, T; Davidson, P M; Lovell, M; Lal, S

2013-12-01

Previous systematic reviews have found patient education to be moderately efficacious in decreasing the intensity of cancer pain, but variation in results warrants analysis aimed at identifying which strategies are optimal. A systematic review and meta-analysis was undertaken using a theory-based approach to classifying and comparing educational interventions for cancer pain. The reference lists of previous reviews and MEDLINE, PsycINFO, and CENTRAL were searched in May 2012. Studies had to be published in a peer-reviewed English language journal and compare the effect on cancer pain intensity of education with usual care. Meta-analyses used standardized effect sizes (ES) and a random effects model. Subgroup analyses compared intervention components categorized using the Michie et al. (Implement Sci 6:42, 2011) capability, opportunity, and motivation behavior (COM-B) model. Fifteen randomized controlled trials met the criteria. As expected, meta-analysis identified a small-moderate ES favoring education versus usual care (ES, 0.27 [-0.47, -0.07]; P = 0.007) with substantial heterogeneity (I² = 71 %). Subgroup analyses based on the taxonomy found that interventions using "enablement" were efficacious (ES, 0.35 [-0.63, -0.08]; P = 0.01), whereas those lacking this component were not (ES, 0.18 [-0.46, 0.10]; P = 0.20). However, the subgroup effect was nonsignificant (P = 0.39), and heterogeneity was not reduced. Factoring in the variable of individualized versus non-individualized influenced neither efficacy nor heterogeneity. The current meta-analysis follows a trend in using theory to understand the mechanisms of complex interventions. We suggest that future efforts focus on interventions that target patient self-efficacy. Authors are encouraged to report comprehensive details of interventions and methods to inform synthesis, replication, and refinement.

General Framework for Meta-analysis of Rare Variants in Sequencing Association Studies

PubMed Central

Lee, Seunggeun; Teslovich, Tanya M.; Boehnke, Michael; Lin, Xihong

2013-01-01

We propose a general statistical framework for meta-analysis of gene- or region-based multimarker rare variant association tests in sequencing association studies. In genome-wide association studies, single-marker meta-analysis has been widely used to increase statistical power by combining results via regression coefficients and standard errors from different studies. In analysis of rare variants in sequencing studies, region-based multimarker tests are often used to increase power. We propose meta-analysis methods for commonly used gene- or region-based rare variants tests, such as burden tests and variance component tests. Because estimation of regression coefficients of individual rare variants is often unstable or not feasible, the proposed method avoids this difficulty by calculating score statistics instead that only require fitting the null model for each study and then aggregating these score statistics across studies. Our proposed meta-analysis rare variant association tests are conducted based on study-specific summary statistics, specifically score statistics for each variant and between-variant covariance-type (linkage disequilibrium) relationship statistics for each gene or region. The proposed methods are able to incorporate different levels of heterogeneity of genetic effects across studies and are applicable to meta-analysis of multiple ancestry groups. We show that the proposed methods are essentially as powerful as joint analysis by directly pooling individual level genotype data. We conduct extensive simulations to evaluate the performance of our methods by varying levels of heterogeneity across studies, and we apply the proposed methods to meta-analysis of rare variant effects in a multicohort study of the genetics of blood lipid levels. PMID:23768515

Effect of sour tea (Hibiscus sabdariffa L.) on arterial hypertension: a systematic review and meta-analysis of randomized controlled trials.

PubMed

Serban, Corina; Sahebkar, Amirhossein; Ursoniu, Sorin; Andrica, Florina; Banach, Maciej

2015-06-01

Hibiscus sabdariffa L. is a tropical wild plant rich in organic acids, polyphenols, anthocyanins, polysaccharides, and volatile constituents that are beneficial for the cardiovascular system. Hibiscus sabdariffa beverages are commonly consumed to treat arterial hypertension, yet the evidence from randomized controlled trials (RCTs) has not been fully conclusive. Therefore, we aimed to assess the potential antihypertensive effects of H. sabdariffa through systematic review of literature and meta-analysis of available RCTs. The search included PUBMED, Cochrane Library, Scopus, and EMBASE (up to July 2014) to identify RCTs investigating the efficacy of H. sabdariffa supplementation on SBP and DBP values. Two independent reviewers extracted data on the study characteristics, methods, and outcomes. Quantitative data synthesis and meta-regression were performed using a fixed-effect model, and sensitivity analysis using leave-one-out method. Five RCTs (comprising seven treatment arms) were selected for the meta-analysis. In total, 390 participants were randomized, of whom 225 were allocated to the H. sabdariffa supplementation group and 165 to the control group in the selected studies. Fixed-effect meta-regression indicated a significant effect of H. sabdariffa supplementation in lowering both SBP (weighed mean difference -7.58 mmHg, 95% confidence interval -9.69 to -5.46, P < 0.00001) and DBP (weighed mean difference -3.53 mmHg, 95% confidence interval -5.16 to -1.89, P < 0.0001). These effects were inversely associated with baseline BP values, and were robust in sensitivity analyses. This meta-analysis of RCTs showed a significant effect of H. sabdariffa in lowering both SBP and DBP. Further well designed trials are necessary to validate these results.

A Meta-Analysis of Acculturation/Enculturation and Mental Health

ERIC Educational Resources Information Center

Yoon, Eunju; Chang, Chih-Ting; Kim, Soyeon; Clawson, Angela; Cleary, Sarah Elizabeth; Hansen, Meghan; Bruner, John P.; Chan, Theresa K.; Gomes, Alexandrina M.

2013-01-01

This meta-analytic study examined the relationship among the constructs of acculturation, enculturation, and acculturation strategies (i.e., integration, assimilation, separation, marginalization), and mental health. Data from 325 studies (163 journal articles and 162 dissertation studies) were analyzed using a random-effects model, across a broad…

Meta-shell Approach for Constructing Lightweight and High Resolution X-Ray Optics

NASA Technical Reports Server (NTRS)

McClelland, Ryan S.

2016-01-01

Lightweight and high resolution optics are needed for future space-based x-ray telescopes to achieve advances in high-energy astrophysics. Past missions such as Chandra and XMM-Newton have achieved excellent angular resolution using a full shell mirror approach. Other missions such as Suzaku and NuSTAR have achieved lightweight mirrors using a segmented approach. This paper describes a new approach, called meta-shells, which combines the fabrication advantages of segmented optics with the alignment advantages of full shell optics. Meta-shells are built by layering overlapping mirror segments onto a central structural shell. The resulting optic has the stiffness and rotational symmetry of a full shell, but with an order of magnitude greater collecting area. Several meta-shells so constructed can be integrated into a large x-ray mirror assembly by proven methods used for Chandra and XMM-Newton. The mirror segments are mounted to the meta-shell using a novel four point semi-kinematic mount. The four point mount deterministically locates the segment in its most performance sensitive degrees of freedom. Extensive analysis has been performed to demonstrate the feasibility of the four point mount and meta-shell approach. A mathematical model of a meta-shell constructed with mirror segments bonded at four points and subject to launch loads has been developed to determine the optimal design parameters, namely bond size, mirror segment span, and number of layers per meta-shell. The parameters of an example 1.3 m diameter mirror assembly are given including the predicted effective area. To verify the mathematical model and support opto-mechanical analysis, a detailed finite element model of a meta-shell was created. Finite element analysis predicts low gravity distortion and low thermal distortion. Recent results are discussed including Structural Thermal Optical Performance (STOP) analysis as well as vibration and shock testing of prototype meta-shells.

The effects of aromatherapy on sleep improvement: a systematic literature review and meta-analysis.

PubMed

Hwang, Eunhee; Shin, Sujin

2015-02-01

To evaluate the existing data on aromatherapy interventions for improvement of sleep quality. Systematic literature review and meta-analysis on the effects of aromatherapy. Study Sources: Electronic databases, including the Korea Education and Research Information Service (KERIS), Korean studies Information Service System (KISS), National Assembly Library, and eight academies within the Korean Society of Nursing Science, were searched to identify studies published between 2000 and August 2013. Randomized controlled and quasi-experimental trials that included aromatherapy for the improvement of sleep quality. Of the 245 publications identified, 13 studies met the inclusion and exclusion criteria, and 12 studies were used in the meta-analysis. Meta-analysis of the 12 studies using a random-effects model revealed that the use of aromatherapy was effective in improving sleep quality (95% confidence interval [CI], 0.540-1.745; Z=3.716). Subgroup analysis revealed that inhalation aromatherapy (95% CI, 0.792-1.541; Z=6.107) was more effective than massage therapy (95% CI, 0.128-2.166; Z=2.205) in unhealthy (95% CI, 0.248-1.100; Z=3.100) and healthy (95% CI, 0.393-5.104; Z=2.287) participants, respectively. Readily available aromatherapy treatments appear to be effective and promote sleep. Thus, it is essential to develop specific guidelines for the efficient use of aromatherapy.

Can statistic adjustment of OR minimize the potential confounding bias for meta-analysis of case-control study? A secondary data analysis.

PubMed

Liu, Tianyi; Nie, Xiaolu; Wu, Zehao; Zhang, Ying; Feng, Guoshuang; Cai, Siyu; Lv, Yaqi; Peng, Xiaoxia

2017-12-29

Different confounder adjustment strategies were used to estimate odds ratios (ORs) in case-control study, i.e. how many confounders original studies adjusted and what the variables are. This secondary data analysis is aimed to detect whether there are potential biases caused by difference of confounding factor adjustment strategies in case-control study, and whether such bias would impact the summary effect size of meta-analysis. We included all meta-analyses that focused on the association between breast cancer and passive smoking among non-smoking women, as well as each original case-control studies included in these meta-analyses. The relative deviations (RDs) of each original study were calculated to detect how magnitude the adjustment would impact the estimation of ORs, compared with crude ORs. At the same time, a scatter diagram was sketched to describe the distribution of adjusted ORs with different number of adjusted confounders. Substantial inconsistency existed in meta-analysis of case-control studies, which would influence the precision of the summary effect size. First, mixed unadjusted and adjusted ORs were used to combine individual OR in majority of meta-analysis. Second, original studies with different adjustment strategies of confounders were combined, i.e. the number of adjusted confounders and different factors being adjusted in each original study. Third, adjustment did not make the effect size of original studies trend to constringency, which suggested that model fitting might have failed to correct the systematic error caused by confounding. The heterogeneity of confounder adjustment strategies in case-control studies may lead to further bias for summary effect size in meta-analyses, especially for weak or medium associations so that the direction of causal inference would be even reversed. Therefore, further methodological researches are needed, referring to the assessment of confounder adjustment strategies, as well as how to take this kind of bias into consideration when drawing conclusion based on summary estimation of meta-analyses.

The Sleeper Effect in Persuasion: A Meta-Analytic Review

PubMed Central

Kumkale, G. Tarcan; Albarracín, Dolores

2009-01-01

A meta-analysis of the available judgment and memory data on the sleeper effect in persuasion is presented. According to this effect, when people receive a communication associated with a discounting cue, such as a noncredible source, they are less persuaded immediately after exposure than they are later in time. Findings from this meta-analysis indicate that recipients of discounting cues were more persuaded over time when the message arguments and the cue had a strong initial impact. In addition, the increase in persuasion was stronger when recipients of discounting cues had higher ability or motivation to think about the message and received the discounting cue after the message. These results are discussed in light of classic and contemporary models of attitudes and persuasion. PMID:14717653

Impact of L-carnitine on plasma lipoprotein(a) concentrations: A systematic review and meta-analysis of randomized controlled trials

PubMed Central

Serban, Maria-Corina; Sahebkar, Amirhossein; Mikhailidis, Dimitri P.; Toth, Peter P.; Jones, Steven R.; Muntner, Paul; Blaha, Michael J.; Andrica, Florina; Martin, Seth S.; Borza, Claudia; Lip, Gregory Y. H.; Ray, Kausik K.; Rysz, Jacek; Hazen, Stanley L.; Banach, Maciej

2016-01-01

We aimed to assess the impact of L-carnitine on plasma Lp(a) concentrations through systematic review and meta-analysis of available RCTs. The literature search included selected databases up to 31st January 2015. Meta-analysis was performed using fixed-effects or random-effect model according to I2 statistic. Effect sizes were expressed as weighted mean difference (WMD) and 95% confidence interval (CI). The meta-analysis showed a significant reduction of Lp(a) levels following L-carnitine supplementation (WMD: −8.82 mg/dL, 95% CI: −10.09, −7.55, p < 0.001). When the studies were categorized according to the route of administration, a significant reduction in plasma Lp(a) concentration was observed with oral (WMD: −9.00 mg/dL, 95% CI: −10.29, −7.72, p < 0.001) but not intravenous L-carnitine (WMD: −2.91 mg/dL, 95% CI: −10.22, 4.41, p = 0.436). The results of the meta-regression analysis showed that the pooled estimate is independent of L-carnitine dose (slope: −0.30; 95% CI: −4.19, 3.59; p = 0.878) and duration of therapy (slope: 0.18; 95% CI: −0.22, 0.59; p = 0.374). In conclusion, the meta-analysis suggests a significant Lp(a) lowering by oral L-carnitine supplementation. Taking into account the limited number of available Lp(a)-targeted drugs, L-carnitine might be an effective alternative to effectively reduce Lp(a). Prospective outcome trials will be required to fully elucidate the clinical value and safety of oral L-carnitine supplementation. PMID:26754058

Video game training does not enhance cognitive ability: A comprehensive meta-analytic investigation.

PubMed

Sala, Giovanni; Tatlidil, K Semir; Gobet, Fernand

2018-02-01

As a result of considerable potential scientific and societal implications, the possibility of enhancing cognitive ability by training has been one of the most influential topics of cognitive psychology in the last two decades. However, substantial research into the psychology of expertise and a recent series of meta-analytic reviews have suggested that various types of cognitive training (e.g., working memory training) benefit performance only in the trained tasks. The lack of skill generalization from one domain to different ones-that is, far transfer-has been documented in various fields of research such as working memory training, music, brain training, and chess. Video game training is another activity that has been claimed by many researchers to foster a broad range of cognitive abilities such as visual processing, attention, spatial ability, and cognitive control. We tested these claims with three random-effects meta-analytic models. The first meta-analysis (k = 310) examined the correlation between video game skill and cognitive ability. The second meta-analysis (k = 315) dealt with the differences between video game players and nonplayers in cognitive ability. The third meta-analysis (k = 359) investigated the effects of video game training on participants' cognitive ability. Small or null overall effect sizes were found in all three models. These outcomes show that overall cognitive ability and video game skill are only weakly related. Importantly, we found no evidence of a causal relationship between playing video games and enhanced cognitive ability. Video game training thus represents no exception to the general difficulty of obtaining far transfer. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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.

Selenium and Preeclampsia: a Systematic Review and Meta-analysis.

PubMed

Xu, Min; Guo, Dan; Gu, Hao; Zhang, Li; Lv, Shuyan

2016-06-01

Conflicting results exist between selenium concentration and preeclampsia. The role of selenium in the development of preeclampsia is unclear. We conducted a meta-analysis to compare the blood selenium level in patients with preeclampsia and healthy pregnant women, and to determine the effectiveness of selenium supplementation in preventing preeclampsia. We searched PubMed, ScienceDirect, the Cochrane Library, and relevant references for English language literature up to November 25, 2014. Mean difference from observational studies and relative risk from randomized controlled trials were meta-analyzed by a random-effect model. Thirteen observational studies with 1515 participants and 3 randomized controlled trials with 439 participants were included in the meta-analysis. Using a random-effect model, a statistically significant difference in blood selenium concentration of -6.47 μg/l (95 % confidence interval (CI) -11.24 to -1.7, p = 0.008) was seen after comparing the mean difference of observational studies. In randomized controlled trials, using a random-effect model, the relative risk for preeclampsia was 0.28 (0.09 to 0.84) for selenium supplementation (p = 0.02). Evidence from observational studies indicates an inverse association of blood selenium level and the risk of preeclampsia. Supplementation with selenium significantly reduces the incidence of preeclampsia. However, more prospective clinical trials are required to assess the association between selenium supplementation and preeclampsia and to determine the dose, beginning time, and duration of selenium supplementation.

Does the use of consumer health information technology improve outcomes in the patient self-management of diabetes? A meta-analysis and narrative review of randomized controlled trials.

PubMed

Or, Calvin K L; Tao, Da

2014-05-01

To assess whether the use of consumer health information technologies (CHITs) improves outcomes in the patient self-management of diabetes. The evidence from randomized controlled trials (RCTs) on the effects of CHITs on patient outcomes was analyzed using either meta-analysis or a narrative synthesis approach. A systematic search of seven electronic databases was conducted to identify relevant reports of RCTs for the analysis. In the meta-analyses, standardized mean differences in patient outcomes were calculated and random-effects models were applied in cases where the heterogeneity of the results was moderate or high, otherwise fixed-effects models were used. Sixty-two studies, representing 67 RCTs, met the inclusion criteria. The results of the meta-analyses showed that the use of CHITs was associated with significant reductions in HbA1c, blood pressure, total cholesterol, and triglycerides levels when compared with the usual care. The findings from the narrative synthesis indicated that only a small proportion of the trials reported positive effects of CHITs on patient outcomes. The use of CHITs in supporting diabetes self-management appears to have potential benefits for patients' self-management of diabetes. However, the effectiveness of the technologies in improving patient outcomes still awaits confirmation in future studies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Curcuminoids Lower Plasma Leptin Concentrations: A Meta-analysis.

PubMed

Atkin, Stephen L; Katsiki, Niki; Derosa, Giuseppe; Maffioli, Pamela; Sahebkar, Amirhossein

2017-12-01

Curcumin is a naturally occurring polyphenol that has been suggested to improve several metabolic diseases. Leptin is an adipokine involved in metabolic status and appetite, with marked crosstalk with other systems. Available data suggest that curcumin may affect leptin levels; therefore, this meta-analysis was performed to evaluate this. A systematic review and meta-analysis were undertaken on all randomized controlled trials of curcumin studies that included the measurement of leptin. The search included PubMed-Medline, Scopus, ISI Web of Knowledge, and Google Scholar databases. Quantitative data synthesis was performed by using a random-effects model, with standardized mean difference and 95% confidence interval as summary statistics. A funnel plot, Begg's rank correlation, and Egger's weighted regression tests assessed the presence of publication bias. Four eligible articles comprising five treatment arms were selected for the meta-analysis. Meta-analysis showed a significant decrease in plasma leptin concentrations following curcumin treatment (standardized mean difference: -0.69, 95% confidence interval: -1.16, -0.23, p = 0.003; I 2  = 76.53%). There was no evidence of publication bias. This meta-analysis showed that curcumin supplementation is associated with a decrease in leptin levels that may be regarded as a potential mechanism for the metabolic effects of curcumin. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

The impact of bariatric surgery on pulmonary function: a meta-analysis.

PubMed

Alsumali, Adnan; Al-Hawag, Ali; Bairdain, Sigrid; Eguale, Tewodros

2018-02-01

Morbid obesity may affect several body systems and cause ill effects to the cardiovascular, hepatobiliary, endocrine, and mental health systems. However, the impact on the pulmonary system and pulmonary function has been debated in the literature. A systematic review and meta-analysis for studies that have evaluated the impact of bariatric surgery on pulmonary function were pooled for this analysis. PubMed, Cochrane, and Embase databases were evaluated through September 31, 2016. They were used as the primary search engine for studies evaluating the impact pre- and post-bariatric surgery on pulmonary function. Pooled effect estimates were calculated using random-effects model. Twenty-three studies with 1013 participants were included in the final meta-analysis. Only 8 studies had intervention and control groups with different time points, but 15 studies had matched groups with different time points. Overall, pulmonary function score was significantly improved after bariatric surgery, with a pooled standardized mean difference of .59 (95% confidence interval: .46-.73). Heterogeneity test was performed by using Cochran's Q test (I 2 = 46%; P heterogeneity = .10). Subgroup analysis and univariate meta-regression based on study quality, age, presurgery body mass index, postsurgery body mass index, study design, female patients only, study continent, asthmatic patients in the study, and the type of bariatric surgery confirmed no statistically significant difference among these groups (P value>.05 for all). A multivariate meta-regression model, which adjusted simultaneously for these same covariates, did not change the results (P value > .05 overall). Assessment of publication bias was done visually and by Begg's rank correlation test and indicated the absence of publication bias (asymmetric shape was observed and P = .34). This meta-analysis shows that bariatric surgery significantly improved overall pulmonary functions score for morbid obesity. Copyright © 2018 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Risk of metabolic syndrome in adolescents with polycystic ovarian syndrome: A systematic review and meta-analysis.

PubMed

Fazleen, Nur Ezza; Whittaker, Maxine; Mamun, Abdullah

2018-03-16

Polycystic ovarian syndrome (PCOS) is the commonest reproductive disorder in women and is closely associated with the development of metabolic syndrome (MetS). The objective of this systematic review and meta-analysis was to describe the risk of MetS in adolescent with PCOS to help diagnosing and preventing of morbidity and mortality later in life. Pubmed, Medline, EMBASE, CINAHL and other sources were searched for metabolic syndrome in adolescents with polycystic ovarian syndrome using PRISMA guidelines (Moher et al., 2009). All type of study design of women aged 10-20 reported association of PCOS with metabolic syndrome was included in this study. Meta-analysis was conducted for MetS and its individual component using bias adjusted quality effect model and we compare the results from quality effects with random effects and IVhet model. Data were presented as prevalence, odds ratio (95% confidence interval and mean difference (95% confidence interval). This systematic review included 9 studies while the meta-analysis included 7 studies. Meta-analysis showed that the odds of being experiencing MetS in PCOS groups was 2.69 (1.29, 5.60) times than girls without PCOS. The mean difference between girls with PCOS and without PCOS for systolic blood pressure was 5.00 (1.28, 8.72), diastolic blood pressure was 3.50 (0.48, 6.56), triglycerides level was 4.20 (-3.99, 12.45), glucose level was 1.30 (-0.46, 3.05), HDL level was -1.40 (-4.85, 2.00). This systematic review and meta-analysis support the hypothesis that the risk of MetS is much greater in adolescents with PCOS compared to the normal population. It is important to screen PCOS in early age to prevent MetS and its complications which lead to morbidity and mortality later in life. Copyright © 2018. Published by Elsevier Ltd.

Lucid dreaming incidence: A quality effects meta-analysis of 50years of research.

PubMed

Saunders, David T; Roe, Chris A; Smith, Graham; Clegg, Helen

2016-07-01

We report a quality effects meta-analysis on studies from the period 1966-2016 measuring either (a) lucid dreaming prevalence (one or more lucid dreams in a lifetime); (b) frequent lucid dreaming (one or more lucid dreams in a month) or both. A quality effects meta-analysis allows for the minimisation of the influence of study methodological quality on overall model estimates. Following sensitivity analysis, a heterogeneous lucid dreaming prevalence data set of 34 studies yielded a mean estimate of 55%, 95% C. I. [49%, 62%] for which moderator analysis showed no systematic bias for suspected sources of variability. A heterogeneous lucid dreaming frequency data set of 25 studies yielded a mean estimate of 23%, 95% C. I. [20%, 25%], moderator analysis revealed no suspected sources of variability. These findings are consistent with earlier estimates of lucid dreaming prevalence and frequent lucid dreaming in the population but are based on more robust evidence. Copyright © 2016 Elsevier Inc. All rights reserved.

Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype

DOE PAGES

Patti, Gary J.; Tautenhahn, Ralf; Fonslow, Bryan R.; ...

2011-01-01

Global metabolomics has emerged as a powerful tool to interrogate cellular biochemistry at the systems level by tracking alterations in the levels of small molecules. One approach to define cellular dynamics with respect to this dysregulation of small molecules has been to consider metabolic flux as a function of time. While flux measurements have proven effective for model organisms, acquiring multiple time points at appropriate temporal intervals for many sample types (e.g., clinical specimens) is challenging. As an alternative, meta-analysis provides another strategy for delineating metabolic cause and effect perturbations. That is, the combination of untargeted metabolomic data from multiplemore » pairwise comparisons enables the association of specific changes in small molecules with unique phenotypic alterations. We recently developed metabolomic software called metaXCMS to automate these types of higher order comparisons. Here we discuss the potential of metaXCMS for analyzing proteomic datasets and highlight the biological value of combining meta-results from both metabolomic and proteomic analyses. The combined meta-analysis has the potential to facilitate efforts in functional genomics and the identification of metabolic disruptions related to disease pathogenesis.« less

Trans-ethnic meta-regression of genome-wide association studies accounting for ancestry increases power for discovery and improves fine-mapping resolution

PubMed Central

Mägi, Reedik; Horikoshi, Momoko; Sofer, Tamar; Mahajan, Anubha; Kitajima, Hidetoshi; Franceschini, Nora; McCarthy, Mark I.; Morris, Andrew P.

2017-01-01

Abstract Trans-ethnic meta-analysis of genome-wide association studies (GWAS) across diverse populations can increase power to detect complex trait loci when the underlying causal variants are shared between ancestry groups. However, heterogeneity in allelic effects between GWAS at these loci can occur that is correlated with ancestry. Here, a novel approach is presented to detect SNP association and quantify the extent of heterogeneity in allelic effects that is correlated with ancestry. We employ trans-ethnic meta-regression to model allelic effects as a function of axes of genetic variation, derived from a matrix of mean pairwise allele frequency differences between GWAS, and implemented in the MR-MEGA software. Through detailed simulations, we demonstrate increased power to detect association for MR-MEGA over fixed- and random-effects meta-analysis across a range of scenarios of heterogeneity in allelic effects between ethnic groups. We also demonstrate improved fine-mapping resolution, in loci containing a single causal variant, compared to these meta-analysis approaches and PAINTOR, and equivalent performance to MANTRA at reduced computational cost. Application of MR-MEGA to trans-ethnic GWAS of kidney function in 71,461 individuals indicates stronger signals of association than fixed-effects meta-analysis when heterogeneity in allelic effects is correlated with ancestry. Application of MR-MEGA to fine-mapping four type 2 diabetes susceptibility loci in 22,086 cases and 42,539 controls highlights: (i) strong evidence for heterogeneity in allelic effects that is correlated with ancestry only at the index SNP for the association signal at the CDKAL1 locus; and (ii) 99% credible sets with six or fewer variants for five distinct association signals. PMID:28911207

A joint frailty-copula model between tumour progression and death for meta-analysis.

PubMed

Emura, Takeshi; Nakatochi, Masahiro; Murotani, Kenta; Rondeau, Virginie

2017-12-01

Dependent censoring often arises in biomedical studies when time to tumour progression (e.g., relapse of cancer) is censored by an informative terminal event (e.g., death). For meta-analysis combining existing studies, a joint survival model between tumour progression and death has been considered under semicompeting risks, which induces dependence through the study-specific frailty. Our paper here utilizes copulas to generalize the joint frailty model by introducing additional source of dependence arising from intra-subject association between tumour progression and death. The practical value of the new model is particularly evident for meta-analyses in which only a few covariates are consistently measured across studies and hence there exist residual dependence. The covariate effects are formulated through the Cox proportional hazards model, and the baseline hazards are nonparametrically modeled on a basis of splines. The estimator is then obtained by maximizing a penalized log-likelihood function. We also show that the present methodologies are easily modified for the competing risks or recurrent event data, and are generalized to accommodate left-truncation. Simulations are performed to examine the performance of the proposed estimator. The method is applied to a meta-analysis for assessing a recently suggested biomarker CXCL12 for survival in ovarian cancer patients. We implement our proposed methods in R joint.Cox package.

Eliciting mixed emotions: a meta-analysis comparing models, types, and measures.

PubMed

Berrios, Raul; Totterdell, Peter; Kellett, Stephen

2015-01-01

The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model-dimensional or discrete-as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative). The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (d IG+ = 0.77), which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects) resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought.

Shift work, night work, and the risk of prostate cancer: A meta-analysis based on 9 cohort studies.

PubMed

Du, Hong-Bing; Bin, Kai-Yun; Liu, Wen-Hong; Yang, Feng-Sheng

2017-11-01

Epidemiology studies suggested that shift work or night work may be linked to prostate cancer (PCa); the relationship, however, remains controversy. PubMed, ScienceDirect, and Embase (Ovid) databases were searched before (started from the building of the databases) February 4, 2017 for eligible cohort studies. We pooled the evidence included by a random- or fixed-effect model, according to the heterogeneity. A predefined subgroup analysis was conducted to see the potential discrepancy between groups. Sensitivity analysis was used to test whether our results were stale. Nine cohort studies were eligible for meta-analysis with 2,570,790 male subjects. Our meta-analysis showed that, under the fixed-effect model, the pooled relevant risk (RR) of PCa was 1.05 (95% confidence interval [CI]: 1.00, 1.11; P = .06; I = 24.00%) for men who had ever engaged in night shift work; and under the random-effect model, the pooled RR was 1.08 (0.99, 1.17; P = .08; I = 24.00%). Subgroup analysis showed the RR of PCa among males in western countries was 1.05 (95% CI: 0.99, 1.11; P = .09; I = 0.00%), while among Asian countries it was 2.45 (95% CI: 1.19, 5.04; P = .02; I = 0.00%); and the RR was 1.04 (95% CI: 0.95, 1.14; P = .40; I = 29.20%) for the high-quality group compared with 1.21 (95% CI: 1.03, 1.41; P = .02; I = 0.00%) for the moderate/low-quality group. Sensitivity analysis showed robust results. Based on the current evidence of cohort studies, we found no obvious association between night shift work and PCa. However, our subgroup analysis suggests that night shift work may increase the risk of PCa in Asian men. Some evidence of a small study effect was observed in this meta-analysis.

Managing Complexity in Evidence Analysis: A Worked Example in Pediatric Weight Management.

PubMed

Parrott, James Scott; Henry, Beverly; Thompson, Kyle L; Ziegler, Jane; Handu, Deepa

2018-05-02

Nutrition interventions are often complex and multicomponent. Typical approaches to meta-analyses that focus on individual causal relationships to provide guideline recommendations are not sufficient to capture this complexity. The objective of this study is to describe the method of meta-analysis used for the Pediatric Weight Management (PWM) Guidelines update and provide a worked example that can be applied in other areas of dietetics practice. The effects of PWM interventions were examined for body mass index (BMI), body mass index z-score (BMIZ), and waist circumference at four different time periods. For intervention-level effects, intervention types were identified empirically using multiple correspondence analysis paired with cluster analysis. Pooled effects of identified types were examined using random effects meta-analysis models. Differences in effects among types were examined using meta-regression. Context-level effects are examined using qualitative comparative analysis. Three distinct types (or families) of PWM interventions were identified: medical nutrition, behavioral, and missing components. Medical nutrition and behavioral types showed statistically significant improvements in BMIZ across all time points. Results were less consistent for BMI and waist circumference, although four distinct patterns of weight status change were identified. These varied by intervention type as well as outcome measure. Meta-regression indicated statistically significant differences between the medical nutrition and behavioral types vs the missing component type for both BMIZ and BMI, although the pattern varied by time period and intervention type. Qualitative comparative analysis identified distinct configurations of context characteristics at each time point that were consistent with positive outcomes among the intervention types. Although analysis of individual causal relationships is invaluable, this approach is inadequate to capture the complexity of dietetics practice. An alternative approach that integrates intervention-level with context-level meta-analyses may provide deeper understanding in the development of practice guidelines. Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

A systematic review and meta-analysis of the efficacy of piracetam and piracetam-like compounds in experimental stroke.

PubMed

Wheble, Philippa C R; Sena, Emily S; Macleod, Malcolm R

2008-01-01

Piracetam was a candidate neuroprotective drug for acute stroke ineffective in clinical trial. Here we use systematic review and meta-analysis to describe the evidence supporting a protective effect of piracetam and its derivatives in animal models of stroke. We present a systematic review of reports describing the use of piracetam and its derivatives in animal models of focal ischaemia, where the outcome was measured as an infarct size or neurological score (Der Simonian and Laird random effects meta-analysis). Only 2 studies, published 10 years after the first clinical trial of piracetam had been initiated, described its efficacy in animal models of stroke. A further 4 studies described the efficacy of related compounds. Piracetam and its derivatives improved the outcome by 30.2% (95% CI = 16.1-44.4). The median study quality was 4/10 (inter-quartile range = 4-6). Piracetam and its derivatives demonstrate neuroprotective efficacy in experimental stroke, but our findings raise concerns about the amount of available data, the quality of the studies and publication bias. (c) 2007 S. Karger AG, Basel.

Clinical Outcomes of Specific Immunotherapy in Advanced Pancreatic Cancer: A Systematic Review and Meta-Analysis

PubMed Central

Qi, Xing-Shun

2017-01-01

Specific immunotherapies, including vaccines with autologous tumor cells and tumor antigen-specific monoclonal antibodies, are important treatments for PC patients. To evaluate the clinical outcomes of PC-specific immunotherapy, we performed a systematic review and meta-analysis of the relevant published clinical trials. The effects of specific immunotherapy were compared with those of nonspecific immunotherapy and the meta-analysis was executed with results regarding the overall survival (OS), immune responses data, and serum cancer markers data. The pooled analysis was performed by using the random-effects model. We found that significantly improved OS was noted for PC patients utilizing specific immunotherapy and an improved immune response was also observed. In conclusion, specific immunotherapy was superior in prolonging the survival time and enhancing immunological responses in PC patients. PMID:28265583

A tutorial on Bayesian bivariate meta-analysis of mixed binary-continuous outcomes with missing treatment effects.

PubMed

Gajic-Veljanoski, Olga; Cheung, Angela M; Bayoumi, Ahmed M; Tomlinson, George

2016-05-30

Bivariate random-effects meta-analysis (BVMA) is a method of data synthesis that accounts for treatment effects measured on two outcomes. BVMA gives more precise estimates of the population mean and predicted values than two univariate random-effects meta-analyses (UVMAs). BVMA also addresses bias from incomplete reporting of outcomes. A few tutorials have covered technical details of BVMA of categorical or continuous outcomes. Limited guidance is available on how to analyze datasets that include trials with mixed continuous-binary outcomes where treatment effects on one outcome or the other are not reported. Given the advantages of Bayesian BVMA for handling missing outcomes, we present a tutorial for Bayesian BVMA of incompletely reported treatment effects on mixed bivariate outcomes. This step-by-step approach can serve as a model for our intended audience, the methodologist familiar with Bayesian meta-analysis, looking for practical advice on fitting bivariate models. To facilitate application of the proposed methods, we include our WinBUGS code. As an example, we use aggregate-level data from published trials to demonstrate the estimation of the effects of vitamin K and bisphosphonates on two correlated bone outcomes, fracture, and bone mineral density. We present datasets where reporting of the pairs of treatment effects on both outcomes was 'partially' complete (i.e., pairs completely reported in some trials), and we outline steps for modeling the incompletely reported data. To assess what is gained from the additional work required by BVMA, we compare the resulting estimates to those from separate UVMAs. We discuss methodological findings and make four recommendations. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Meta-analyses and Forest plots using a microsoft excel spreadsheet: step-by-step guide focusing on descriptive data analysis.

PubMed

Neyeloff, Jeruza L; Fuchs, Sandra C; Moreira, Leila B

2012-01-20

Meta-analyses are necessary to synthesize data obtained from primary research, and in many situations reviews of observational studies are the only available alternative. General purpose statistical packages can meta-analyze data, but usually require external macros or coding. Commercial specialist software is available, but may be expensive and focused in a particular type of primary data. Most available softwares have limitations in dealing with descriptive data, and the graphical display of summary statistics such as incidence and prevalence is unsatisfactory. Analyses can be conducted using Microsoft Excel, but there was no previous guide available. We constructed a step-by-step guide to perform a meta-analysis in a Microsoft Excel spreadsheet, using either fixed-effect or random-effects models. We have also developed a second spreadsheet capable of producing customized forest plots. It is possible to conduct a meta-analysis using only Microsoft Excel. More important, to our knowledge this is the first description of a method for producing a statistically adequate but graphically appealing forest plot summarizing descriptive data, using widely available software.

Meta-analyses and Forest plots using a microsoft excel spreadsheet: step-by-step guide focusing on descriptive data analysis

PubMed Central

2012-01-01

Background Meta-analyses are necessary to synthesize data obtained from primary research, and in many situations reviews of observational studies are the only available alternative. General purpose statistical packages can meta-analyze data, but usually require external macros or coding. Commercial specialist software is available, but may be expensive and focused in a particular type of primary data. Most available softwares have limitations in dealing with descriptive data, and the graphical display of summary statistics such as incidence and prevalence is unsatisfactory. Analyses can be conducted using Microsoft Excel, but there was no previous guide available. Findings We constructed a step-by-step guide to perform a meta-analysis in a Microsoft Excel spreadsheet, using either fixed-effect or random-effects models. We have also developed a second spreadsheet capable of producing customized forest plots. Conclusions It is possible to conduct a meta-analysis using only Microsoft Excel. More important, to our knowledge this is the first description of a method for producing a statistically adequate but graphically appealing forest plot summarizing descriptive data, using widely available software. PMID:22264277

Impact of palm olein in infant formulas on stool consistency and frequency: a meta-analysis of randomized clinical trials

PubMed Central

Lasekan, John B.; Hustead, Deborah S.; Masor, Marc; Murray, Robert

2017-01-01

ABSTRACT Background: Meta-analysis studies have documented that palm olein (PALM) predominant formulas reduce calcium and fat absorption, and bone mineralization in infants, but none have been documented for stool consistency and frequency. Objective: The study objective was to conduct a meta-analysis of published randomized clinical trials (RCTs) on the effect of PALM-based formulas on stool consistency and frequency in infants. Design: A literature search was conducted in BIOSIS Previews®, Embase®, Embase® Alert, MEDLINE® and Cochrane databases. PALM-based RCTs with available stool outcomes were selected and meta-analyzed. Mean rank stool consistency (MRSC, primary outcome) and stool frequency (secondary outcome) were compared between infants fed PALM-based and PALM-free formulas (NoPALM), using random effects model. Results: Nine out of identified16 studies were meta-analyzed. The mean MRSC (scale of 1 = watery to 5 = hard) in the NoPALM-fed infants was lower (softer stools) compared to the PALM-fed infants (mean difference ‒0.355, 95% Confidence Interval [CI] of ‒0.472 to ‒0.239, p < 0.001). Difference for stool frequency was not significant (p = 0.613). Conclusion: Meta-analysis of RCTs indicated that NoPALM-fed infants have significantly softer stools but similar stool frequencies versus PALM-fed infants, despite differences in study types and design. Future meta-analysis could benefit from including comparison with human milk-fed infants. PMID:28659741

Effect of Probiotics on Depression: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

PubMed

Huang, Ruixue; Wang, Ke; Hu, Jianan

2016-08-06

It has been reported that gut probiotics play a major role in the bidirectional communication between the gut and the brain. Probiotics may be essential to people with depression, which remains a global health challenge, as depression is a metabolic brain disorder. However, the efficacy of probiotics for depression is controversial. This study aimed to systematically review the existing evidence on the effect of probiotics-based interventions on depression. Randomized, controlled trials, identified through screening multiple databases and grey literature, were included in the meta-analysis. The meta-analysis was performed using Review Manager 5.3 software using a fixed-effects model. The meta-analysis showed that probiotics significantly decreased the depression scale score (MD (depressive disorder) = -0.30, 95% CI (-0.51--0.09), p = 0.005) in the subjects. Probiotics had an effect on both the healthy population (MD = -0.25, 95% CI (-0.47--0.03), p = 0.03) and patients with major depressive disorder (MDD) (MD = -0.73, 95% CI (-1.37--0.09), p = 0.03). Probiotics had an effect on the population aged under 60 (MD = -0.43, 95% CI (-0.72--0.13), p = 0.005), while it had no effect on people aged over 65 (MD = -0.18, 95% CI (-0.47-0.11), p = 0.22). This is the first systematic review and meta-analysis with the goal of determining the effect of probiotics on depression. We found that probiotics were associated with a significant reduction in depression, underscoring the need for additional research on this potential preventive strategy for depression.

Multivariate meta-analysis: potential and promise.

PubMed

Jackson, Dan; Riley, Richard; White, Ian R

2011-09-10

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day 'Multivariate meta-analysis' event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Modelling multiple sources of dissemination bias in meta-analysis.

PubMed

Bowden, Jack; Jackson, Dan; Thompson, Simon G

2010-03-30

Asymmetry in the funnel plot for a meta-analysis suggests the presence of dissemination bias. This may be caused by publication bias through the decisions of journal editors, by selective reporting of research results by authors or by a combination of both. Typically, study results that are statistically significant or have larger estimated effect sizes are more likely to appear in the published literature, hence giving a biased picture of the evidence-base. Previous statistical approaches for addressing dissemination bias have assumed only a single selection mechanism. Here we consider a more realistic scenario in which multiple dissemination processes, involving both the publishing authors and journals, are operating. In practical applications, the methods can be used to provide sensitivity analyses for the potential effects of multiple dissemination biases operating in meta-analysis.

The influence of stereotype threat on immigrants: review and meta-analysis

PubMed Central

Appel, Markus; Weber, Silvana; Kronberger, Nicole

2015-01-01

In many regions around the world students with certain immigrant backgrounds underachieve in educational settings. This paper provides a review and meta-analysis on one potential source of the immigrant achievement gap: stereotype threat, a situational predicament that may prevent students to perform up to their full abilities. A meta-analysis of 19 experiments suggests an overall mean effect size of 0.63 (random effects model) in support of stereotype threat theory. The results are complemented by moderator analyses with regard to circulation (published or unpublished research), cultural context (US versus Europe), age of immigrants, type of stereotype threat manipulation, dependent measures, and means for identification of immigrant status; evidence on the role of ethnic identity strength is reviewed. Theoretical and practical implications of the findings are discussed. PMID:26217256

Panning for the gold in health research: incorporating studies' methodological quality in meta-analysis.

PubMed

Johnson, Blair T; Low, Robert E; MacDonald, Hayley V

2015-01-01

Systematic reviews now routinely assess methodological quality to gauge the validity of the included studies and of the synthesis as a whole. Although trends from higher quality studies should be clearer, it is uncertain how often meta-analyses incorporate methodological quality in models of study results either as predictors, or, more interestingly, in interactions with theoretical moderators. We survey 200 meta-analyses in three health promotion domains to examine when and how meta-analyses incorporate methodological quality. Although methodological quality assessments commonly appear in contemporary meta-analyses (usually as scales), they are rarely incorporated in analyses, and still more rarely analysed in interaction with theoretical determinants of the success of health promotions. The few meta-analyses (2.5%) that did include such an interaction analysis showed that moderator results remained significant in higher quality studies or were present only among higher quality studies. We describe how to model quality interactively with theoretically derived moderators and discuss strengths and weaknesses of this approach and in relation to current meta-analytic practice. In large literatures exhibiting heterogeneous effects, meta-analyses can incorporate methodological quality and generate conclusions that enable greater confidence not only about the substantive phenomenon but also about the role that methodological quality itself plays.

The effectiveness of the problem-based learning teaching model for use in introductory Chinese undergraduate medical courses: a systematic review and meta-analysis.

PubMed

Zhang, Yanqi; Zhou, Liang; Liu, Xiaoyu; Liu, Ling; Wu, Yazhou; Zhao, Zengwei; Yi, Dali; Yi, Dong

2015-01-01

Although the problem-based learning (PBL) emerged in 1969 and was soon widely applied internationally, the rapid development in China only occurred in the last 10 years. This study aims to compare the effect of PBL and lecture-based learning (LBL) on student course examination results for introductory Chinese undergraduate medical courses. Randomized and nonrandomized controlled trial studies on PBL use in Chinese undergraduate medical education were retrieved through PubMed, the Excerpta Medica Database (EMBASE), Chinese National Knowledge Infrastructure (CNKI) and VIP China Science and Technology Journal Database (VIP-CSTJ) with publication dates from 1st January 1966 till 31 August 2014. The pass rate, excellence rate and examination scores of course examination were collected. Methodological quality was evaluated based on the modified Jadad scale. The I-square statistic and Chi-square test of heterogeneity were used to assess the statistical heterogeneity. Overall RRs or SMDs with their 95% CIs were calculated in meta-analysis. Meta-regression and subgroup meta-analyses were also performed based on comparators and other confounding factors. Funnel plots and Egger's tests were performed to assess degrees of publication bias. The meta-analysis included 31studies and 4,699 subjects. Fourteen studies were of high quality with modified Jadad scores of 4 to 6, and 17 studies were of low quality with scores of 1 to 3. Relative to the LBL model, the PBL model yielded higher course examination pass rates [RR = 1.09, 95%CI (1.03, 1.17)], excellence rates [RR = 1.66, 95%CI (1.33, 2.06)] and examination scores [SMD = 0.82, 95%CI (0.63, 1.01)]. The meta-regression results show that course type was the significant confounding factor that caused heterogeneity in the examination-score meta-analysis (t = 0.410, P<0.001). The examination score SMD in "laboratory course" subgroup [SMD = 2.01, 95% CI: (1.50, 2.52)] was higher than that in "theory course" subgroup [SMD = 0.72, 95% CI: (0.56, 0.89)]. PBL teaching model application in introductory undergraduate medical courses can increase course examination excellence rates and scores in Chinese medical education system. It is more effective when applied to laboratory courses than to theory-based courses.

The Effectiveness of the Problem-Based Learning Teaching Model for Use in Introductory Chinese Undergraduate Medical Courses: A Systematic Review and Meta-Analysis

PubMed Central

Zhang, Yanqi; Zhou, Liang; Liu, Xiaoyu; Liu, Ling; Wu, Yazhou; Zhao, Zengwei; Yi, Dali; Yi, Dong

2015-01-01

Background Although the problem-based learning (PBL) emerged in 1969 and was soon widely applied internationally, the rapid development in China only occurred in the last 10 years. This study aims to compare the effect of PBL and lecture-based learning (LBL) on student course examination results for introductory Chinese undergraduate medical courses. Methods Randomized and nonrandomized controlled trial studies on PBL use in Chinese undergraduate medical education were retrieved through PubMed, the Excerpta Medica Database (EMBASE), Chinese National Knowledge Infrastructure (CNKI) and VIP China Science and Technology Journal Database (VIP-CSTJ) with publication dates from 1st January 1966 till 31 August 2014. The pass rate, excellence rate and examination scores of course examination were collected. Methodological quality was evaluated based on the modified Jadad scale. The I-square statistic and Chi-square test of heterogeneity were used to assess the statistical heterogeneity. Overall RRs or SMDs with their 95% CIs were calculated in meta-analysis. Meta-regression and subgroup meta-analyses were also performed based on comparators and other confounding factors. Funnel plots and Egger’s tests were performed to assess degrees of publication bias. Results The meta-analysis included 31studies and 4,699 subjects. Fourteen studies were of high quality with modified Jadad scores of 4 to 6, and 17 studies were of low quality with scores of 1 to 3. Relative to the LBL model, the PBL model yielded higher course examination pass rates [RR = 1.09, 95%CI (1.03, 1.17)], excellence rates [RR = 1.66, 95%CI (1.33, 2.06)] and examination scores [SMD = 0.82, 95%CI (0.63, 1.01)]. The meta-regression results show that course type was the significant confounding factor that caused heterogeneity in the examination-score meta-analysis (t = 0.410, P<0.001). The examination score SMD in “laboratory course” subgroup [SMD = 2.01, 95% CI: (1.50, 2.52)] was higher than that in “theory course” subgroup [SMD = 0.72, 95% CI: (0.56, 0.89)]. Conclusions PBL teaching model application in introductory undergraduate medical courses can increase course examination excellence rates and scores in Chinese medical education system. It is more effective when applied to laboratory courses than to theory-based courses. PMID:25822653

Folate intake, serum folate levels and esophageal cancer risk: an overall and dose-response meta-analysis.

PubMed

Zhao, Yan; Guo, Chenyang; Hu, Hongtao; Zheng, Lin; Ma, Junli; Jiang, Li; Zhao, Erjiang; Li, Hailiang

2017-02-07

Previously reported findings on the association between folate intake or serum folate levels and esophageal cancer risk have been inconsistent. This study aims to summarize the evidence regarding these relationships using a dose-response meta-analysis approach. We performed electronic searches of the Pubmed, Medline and Cochrane Library electronic databases to identify studies examining the effect of folate on the risk of esophageal cancer. Ultimately, 19 studies were included in the meta-analysis. Summary odds ratios (ORs) were estimated using a random effects model. A linear regression analysis of the natural logarithm of the OR was carried out to assess the possible dose-response relationship between folate intake and esophageal cancer risk. The pooled ORs for esophageal cancer in the highest vs. lowest levels of dietary folate intake and serum folate were 0.63 (95% CI: 0.56-0.71) and 0.71 (95% CI: 0.55-0.92), respectively. The dose-response meta-analysis indicated that a 100 μg/day increment in dietary folate intake reduced the estimate risk of esophageal cancer by 12%. These findings suggest that dietary and serum folate exert a protective effect against esophageal carcinogenesis.

Planetarium instructional efficacy: A research synthesis

NASA Astrophysics Data System (ADS)

Brazell, Bruce D.

The purpose of the current study was to explore the instructional effectiveness of the planetarium in astronomy education using meta-analysis. A review of the literature revealed 46 studies related to planetarium efficacy. However, only 19 of the studies satisfied selection criteria for inclusion in the meta-analysis. Selected studies were then subjected to coding procedures, which extracted information such as subject characteristics, experimental design, and outcome measures. From these data, 24 effect sizes were calculated in the area of student achievement and five effect sizes were determined in the area of student attitudes using reported statistical information. Mean effect sizes were calculated for both the achievement and the attitude distributions. Additionally, each effect size distribution was subjected to homogeneity analysis. The attitude distribution was found to be homogeneous with a mean effect size of -0.09, which was not significant, p = .2535. The achievement distribution was found to be heterogeneous with a statistically significant mean effect size of +0.28, p < .05. Since the achievement distribution was heterogeneous, the analog to the ANOVA procedure was employed to explore variability in this distribution in terms of the coded variables. The analog to the ANOVA procedure revealed that the variability introduced by the coded variables did not fully explain the variability in the achievement distribution beyond subject-level sampling error under a fixed effects model. Therefore, a random effects model analysis was performed which resulted in a mean effect size of +0.18, which was not significant, p = .2363. However, a large random effect variance component was determined indicating that the differences between studies were systematic and yet to be revealed. The findings of this meta-analysis showed that the planetarium has been an effective instructional tool in astronomy education in terms of student achievement. However, the meta-analysis revealed that the planetarium has not been a very effective tool for improving student attitudes towards astronomy.

Effects of vicarious punishment: a meta-analysis.

PubMed

Malouff, John; Thorsteinsson, Einar; Schutte, Nicola; Rooke, Sally Erin

2009-07-01

Vicarious punishment involves observing a model exhibit a behavior that leads to punishment for the model. If observers then exhibit the behavior at a lower rate than do individuals in a control group, vicarious punishment occurred. The authors report the results of a meta-analysis of studies that tested for vicarious-punishment effects. Across 21 research samples and 876 participants, the viewing of a model experiencing punishment for a behavior led to a significantly lower level of the behavior by the observers, d = 0.58. Vicarious punishment occurred consistently with (a) live and filmed models, (b) severe and nonsevere punishment for the model, (c) positive punishment alone or positive plus negative punishment, (d) various types of behavior, (e) adults and children, and (f) male and female participants. The findings have implications for the use of models in reducing undesirable behavior.

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes

PubMed Central

2014-01-01

Background Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. Methods The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Results Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis. Conclusions Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately. PMID:25047164

Off-pump versus on-pump coronary artery bypass surgery: meta-analysis and meta-regression of 13,524 patients from randomized trials.

PubMed

Sá, Michel Pompeu Barros de Oliveira; Ferraz, Paulo Ernando; Escobar, Rodrigo Renda; Martins, Wendell Nunes; Lustosa, Pablo César; Nunes, Eliobas de Oliveira; Vasconcelos, Frederico Pires; Lima, Ricardo Carvalho

2012-12-01

Most recent published meta-analysis of randomized controlled trials (RCTs) showed that off-pump coronary artery bypass graft surgery (CABG) reduces incidence of stroke by 30% compared with on-pump CABG, but showed no difference in other outcomes. New RCTs were published, indicating need of new meta-analysis to investigate pooled results adding these further studies. MEDLINE, EMBASE, CENTRAL/CCTR, SciELO, LILACS, Google Scholar and reference lists of relevant articles were searched for RCTs that compared outcomes (30-day mortality for all-cause, myocardial infarction or stroke) between off-pump versus on-pump CABG until May 2012. The principal summary measures were relative risk (RR) with 95% Confidence Interval (CI) and P values (considered statistically significant when <0.05). The RR's were combined across studies using DerSimonian-Laird random effects weighted model. Meta-analysis and meta-regression were completed using the software Comprehensive Meta-Analysis version 2 (Biostat Inc., Englewood, New Jersey, USA). Forty-seven RCTs were identified and included 13,524 patients (6,758 for off-pump and 6,766 for on-pump CABG). There was no significant difference between off-pump and on-pump CABG groups in RR for 30-day mortality or myocardial infarction, but there was difference about stroke in favor to off-pump CABG (RR 0.793, 95% CI 0.660-0.920, P=0.049). It was observed no important heterogeneity of effects about any outcome, but it was observed publication bias about outcome "stroke". Meta-regression did not demonstrate influence of female gender, number of grafts or age in outcomes. Off-pump CABG reduces the incidence of post-operative stroke by 20.7% and has no substantial effect on mortality or myocardial infarction in comparison to on-pump CABG. Patient gender, number of grafts performed and age do not seem to explain the effect of off-pump CABG on mortality, myocardial infarction or stroke, respectively.

Mesenchymal stem cells improve locomotor recovery in traumatic spinal cord injury: systematic review with meta-analyses of rat models.

PubMed

Oliveri, Roberto S; Bello, Segun; Biering-Sørensen, Fin

2014-02-01

Traumatic spinal cord injury (SCI) is a devastating event with huge personal and societal costs. A limited number of treatments exist to ameliorate the progressive secondary damage that rapidly follows the primary mechanical impact. Mesenchymal stem or stromal cells (MSCs) have anti-inflammatory and neuroprotective effects and may thus reduce secondary damage after administration. We performed a systematic review with quantitative syntheses to assess the evidence of MSCs versus controls for locomotor recovery in rat models of traumatic SCI, and identified 83 eligible controlled studies comprising a total of 1,568 rats. Between-study heterogeneity was large. Fifty-three studies (64%) were reported as randomised, but only four reported adequate methodologies for randomisation. Forty-eight studies (58%) reported the use of a blinded outcome assessment. A random-effects meta-analysis yielded a difference in behavioural Basso-Beattie-Bresnahan (BBB) locomotor score means of 3.9 (95% confidence interval [CI] 3.2 to 4.7; P<0.001) in favour of MSCs. Trial sequential analysis confirmed the findings of the meta-analyses with the upper monitoring boundary for benefit being crossed by the cumulative Z-curve before reaching the diversity-adjusted required information size. Only time from intervention to last follow-up remained statistically significant after adjustment using multivariate random-effects meta-regression modelling. Lack of other demonstrable explanatory variables could be due to insufficient meta-analytic study power. MSCs would seem to demonstrate a substantial beneficial effect on locomotor recovery in a widely-used animal model of traumatic SCI. However, the animal results should be interpreted with caution concerning the internal and external validity of the studies in relation to the design of future clinical trials. © 2013.

An investigation of the impact of using different methods for network meta-analysis: a protocol for an empirical evaluation.

PubMed

Karahalios, Amalia Emily; Salanti, Georgia; Turner, Simon L; Herbison, G Peter; White, Ian R; Veroniki, Areti Angeliki; Nikolakopoulou, Adriani; Mckenzie, Joanne E

2017-06-24

Network meta-analysis, a method to synthesise evidence from multiple treatments, has increased in popularity in the past decade. Two broad approaches are available to synthesise data across networks, namely, arm- and contrast-synthesis models, with a range of models that can be fitted within each. There has been recent debate about the validity of the arm-synthesis models, but to date, there has been limited empirical evaluation comparing results using the methods applied to a large number of networks. We aim to address this gap through the re-analysis of a large cohort of published networks of interventions using a range of network meta-analysis methods. We will include a subset of networks from a database of network meta-analyses of randomised trials that have been identified and curated from the published literature. The subset of networks will include those where the primary outcome is binary, the number of events and participants are reported for each direct comparison, and there is no evidence of inconsistency in the network. We will re-analyse the networks using three contrast-synthesis methods and two arm-synthesis methods. We will compare the estimated treatment effects, their standard errors, treatment hierarchy based on the surface under the cumulative ranking (SUCRA) curve, the SUCRA value, and the between-trial heterogeneity variance across the network meta-analysis methods. We will investigate whether differences in the results are affected by network characteristics and baseline risk. The results of this study will inform whether, in practice, the choice of network meta-analysis method matters, and if it does, in what situations differences in the results between methods might arise. The results from this research might also inform future simulation studies.

Cognitive Appraisals and Emotions Predict Cortisol and Immune Responses: A Meta-Analysis of Acute Laboratory Social Stressors and Emotion Inductions

ERIC Educational Resources Information Center

Denson, Thomas F.; Spanovic, Marija; Miller, Norman

2009-01-01

Models of stress and health suggest that emotions mediate the effects of stress on health; yet meta-analytic reviews have not confirmed these relationships. Categorizations of emotions along broad dimensions such as valence (e.g., positive and negative affect) may obscure important information about the effects of specific emotions on physiology.…

Association of fruit and vegetables with the risk of nasopharyngeal cancer: Evidence from a meta-analysis

PubMed Central

Jin, Jian; Ouyang, Zhiguo; Wang, Zhaoyan

2014-01-01

Quantification of the association between the intake of vegetables and fruit and risk of nasopharyngeal cancer (NPC) is controversial. Thus, we conducted a meta-analysis to assess the relationship between vegetables and fruit and NPC risk. Pertinent studies were identified by a search in PubMed, Web of Knowledge and Wan Fang Med Online. Random-effects models were used to calculate summary relative risks (RRs) and the corresponding 95% confidence intervals (CIs). Publication bias was estimated using Egger's regression asymmetry test. Finally, 15 articles comprising 8208 NPC cases were included in this meta-analysis. The combined results showed that there was significant association between vegetables and fruit intake and NPC risk. The pooled RRs were 0.60 (95% CI = 0.47–0.76) for vegetables and 0.63 (95% CI = 0.56–0.70) for fruit. No publication bias was detected. Our analysis indicated that intake of vegetables and fruit may have a protective effect on NPC. Since the potential biases and confounders could not be ruled out completely in this meta-analysis, further studies are needed. PMID:25008797

Combining multiple imputation and meta-analysis with individual participant data

PubMed Central

Burgess, Stephen; White, Ian R; Resche-Rigon, Matthieu; Wood, Angela M

2013-01-01

Multiple imputation is a strategy for the analysis of incomplete data such that the impact of the missingness on the power and bias of estimates is mitigated. When data from multiple studies are collated, we can propose both within-study and multilevel imputation models to impute missing data on covariates. It is not clear how to choose between imputation models or how to combine imputation and inverse-variance weighted meta-analysis methods. This is especially important as often different studies measure data on different variables, meaning that we may need to impute data on a variable which is systematically missing in a particular study. In this paper, we consider a simulation analysis of sporadically missing data in a single covariate with a linear analysis model and discuss how the results would be applicable to the case of systematically missing data. We find in this context that ensuring the congeniality of the imputation and analysis models is important to give correct standard errors and confidence intervals. For example, if the analysis model allows between-study heterogeneity of a parameter, then we should incorporate this heterogeneity into the imputation model to maintain the congeniality of the two models. In an inverse-variance weighted meta-analysis, we should impute missing data and apply Rubin's rules at the study level prior to meta-analysis, rather than meta-analyzing each of the multiple imputations and then combining the meta-analysis estimates using Rubin's rules. We illustrate the results using data from the Emerging Risk Factors Collaboration. PMID:23703895

Resveratrol supplementation and plasma adipokines concentrations? A systematic review and meta-analysis of randomized controlled trials.

PubMed

Mohammadi-Sartang, Mohsen; Mazloom, Zohreh; Sohrabi, Zahra; Sherafatmanesh, Saeed; Barati-Boldaji, Reza

2017-03-01

The results of human clinical trials have revealed that the effects of resveratrol on adipokines are inconsistent. Our objective was to elucidate the role of resveratrol supplementation on adipokines through a systematic review and a meta-analysis of available randomized placebo-controlled trials (RCTs). 1 The search included PubMed-MEDLINE, SCOPUS and ISI web of sciences database till up to 6th November 2016. Weight mean differences (WMD) 2 were calculated for net changes in adipokines using fixed-effects or random-effects models; meta-regression analysis and publication bias were conducted in accordance with standard methods. Nine RCTs with 11 treatment arms were eligible for inclusion in this systematic review and meta-analysis. Meta-analysis of data from 10 treatment arms showed a significant change in plasma adiponectin concentrations following resveratrol supplementation (WMD: 1.10μg/ml, 95%CI: 0.88, 1.33, p<0.001); Q=11.43, I 2 =21.29%, p=0.247). There was a significant greater adiponectin-reducing effect in trials with higher than or equal to 100mg/day (WMD: 1.11μg/ml, 95%CI: 0.88, 1.34, p<0.001), versus those with less than 100 mg/day dosage (WMD: 0.84μg/ml, 95%CI: -0.62, 2.31, p=0.260). Meta-analysis of data from 5 treatment arms did not find any significant change in plasma leptin concentrations following resveratrol supplementation (WMD: 3.77ng/ml, 95% CI: -2.28, 9.83, p=0.222; Q=8.00, I 2 =50.01%). Resveratrol significantly improves adiponectin but does not affect leptin concentrations. Additional studies are required to further evaluate the potential benefits of resveratrol on adipokines in humans. Copyright © 2017. Published by Elsevier Ltd.

Do community specialist palliative care services that provide home nursing increase rates of home death for people with life-limiting illnesses? A systematic review and meta-analysis of comparative studies.

PubMed

Luckett, Tim; Davidson, Patricia M; Lam, Lawrence; Phillips, Jane; Currow, David C; Agar, Meera

2013-02-01

Systematic reviews and meta-analyses suggest that community specialist palliative care services (SPCSs) can avoid hospitalizations and enable home deaths. But more information is needed regarding the relative efficacies of different models. Family caregivers highlight home nursing as the most important service, but it is also likely the most costly. To establish whether community SPCSs offering home nursing increase rates of home death compared with other models. We searched MEDLINE, AMED, Embase, CINAHL, the Cochrane Database of Systematic Reviews, and CENTRAL on March 2 and 3, 2011. To be eligible, articles had to be published in English-language peer-reviewed journals and report original research comparing the effect on home deaths of SPCSs providing home nursing vs. any alternative. Study quality was independently rated using Cochrane grades. Maximum likelihood estimation of heterogeneity was used to establish the method for meta-analysis (fixed or random effects). Potential biases were assessed. Of 1492 articles screened, 10 articles were found eligible, reporting nine studies that yielded data for 10 comparisons. Study quality was high in two cases, moderate in three and low in four. Meta-analysis indicated a significant effect for SPCSs with home nursing (odds ratio 4.45, 95% CI 3.24-6.11; P<0.001). However, the high-quality studies found no effect (odds ratio 1.40, 95% CI 0.97-2.02; P=0.071). Bias was minimal. A meta-analysis found evidence to be inconclusive that community SPCSs that offer home nursing increase home deaths without compromising symptoms or increasing costs. But a compelling trend warrants further confirmatory studies. Future trials should compare the relative efficacy of different models and intensities of SPCSs. Copyright © 2013 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

Network meta-analysis: a technique to gather evidence from direct and indirect comparisons

PubMed Central

2017-01-01

Systematic reviews and pairwise meta-analyses of randomized controlled trials, at the intersection of clinical medicine, epidemiology and statistics, are positioned at the top of evidence-based practice hierarchy. These are important tools to base drugs approval, clinical protocols and guidelines formulation and for decision-making. However, this traditional technique only partially yield information that clinicians, patients and policy-makers need to make informed decisions, since it usually compares only two interventions at the time. In the market, regardless the clinical condition under evaluation, usually many interventions are available and few of them have been studied in head-to-head studies. This scenario precludes conclusions to be drawn from comparisons of all interventions profile (e.g. efficacy and safety). The recent development and introduction of a new technique – usually referred as network meta-analysis, indirect meta-analysis, multiple or mixed treatment comparisons – has allowed the estimation of metrics for all possible comparisons in the same model, simultaneously gathering direct and indirect evidence. Over the last years this statistical tool has matured as technique with models available for all types of raw data, producing different pooled effect measures, using both Frequentist and Bayesian frameworks, with different software packages. However, the conduction, report and interpretation of network meta-analysis still poses multiple challenges that should be carefully considered, especially because this technique inherits all assumptions from pairwise meta-analysis but with increased complexity. Thus, we aim to provide a basic explanation of network meta-analysis conduction, highlighting its risks and benefits for evidence-based practice, including information on statistical methods evolution, assumptions and steps for performing the analysis. PMID:28503228

META-ANALYSIS OF ACUTE EXERCISE EFFECTS ON STATE ANXIETY: AN UPDATE OF RANDOMIZED CONTROLLED TRIALS OVER THE PAST 25 YEARS.

PubMed

Ensari, Ipek; Greenlee, Tina A; Motl, Robert W; Petruzzello, Steven J

2015-08-01

One prominent and well-cited meta-analysis published nearly 25 years ago reported that an acute or single bout of exercise reduced state anxiety by approximately ¼ standard deviation. We conducted a meta-analysis of randomized controlled trials (RCTs) published after that meta-analysis for updating our understanding of the acute effects of exercise on state anxiety. We searched PubMed, EBSCOHost, Medline, PsycINFO, ERIC, and ScienceDirect for RCTs of acute exercise and state anxiety as an outcome. There were 36 RCTs that met inclusion criteria and yielded data for effect size (ES) generation (Cohen's d). An overall ES was calculated using a random effects model and expressed as Hedge's g. The weighted mean ES was small (Hedge's g = 0.16, standard error (SE) = 0.06), but statistically significant (P < 0.05), and indicated that a single bout of exercise resulted in an improvement in state anxiety compared with control. The overall ES was heterogeneous and post hoc, exploratory analyses using both random- and fixed-effects models identified several variables as moderators including sample age, sex and health status, baseline activity levels, exercise intensity, modality and control condition, randomization, overall study quality, and the anxiety measure (P < 0.05). The cumulative evidence from high quality studies indicates that acute bouts of exercise can yield a small reduction in state anxiety. The research is still plagued by floor effects associated with recruiting persons with normal or lower levels of state anxiety, and this should be overcome in subsequent trials. © 2015 Wiley Periodicals, Inc.

Meta-STEPP: subpopulation treatment effect pattern plot for individual patient data meta-analysis.

PubMed

Wang, Xin Victoria; Cole, Bernard; Bonetti, Marco; Gelber, Richard D

2016-09-20

We have developed a method, called Meta-STEPP (subpopulation treatment effect pattern plot for meta-analysis), to explore treatment effect heterogeneity across covariate values in the meta-analysis setting for time-to-event data when the covariate of interest is continuous. Meta-STEPP forms overlapping subpopulations from individual patient data containing similar numbers of events with increasing covariate values, estimates subpopulation treatment effects using standard fixed-effects meta-analysis methodology, displays the estimated subpopulation treatment effect as a function of the covariate values, and provides a statistical test to detect possibly complex treatment-covariate interactions. Simulation studies show that this test has adequate type-I error rate recovery as well as power when reasonable window sizes are chosen. When applied to eight breast cancer trials, Meta-STEPP suggests that chemotherapy is less effective for tumors with high estrogen receptor expression compared with those with low expression. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Quasi-experimental study designs series-paper 10: synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges.

PubMed

Becker, Betsy Jane; Aloe, Ariel M; Duvendack, Maren; Stanley, T D; Valentine, Jeffrey C; Fretheim, Atle; Tugwell, Peter

2017-09-01

To outline issues of importance to analytic approaches to the synthesis of quasi-experiments (QEs) and to provide a statistical model for use in analysis. We drew on studies of statistics, epidemiology, and social-science methodology to outline methods for synthesis of QE studies. The design and conduct of QEs, effect sizes from QEs, and moderator variables for the analysis of those effect sizes were discussed. Biases, confounding, design complexities, and comparisons across designs offer serious challenges to syntheses of QEs. Key components of meta-analyses of QEs were identified, including the aspects of QE study design to be coded and analyzed. Of utmost importance are the design and statistical controls implemented in the QEs. Such controls and any potential sources of bias and confounding must be modeled in analyses, along with aspects of the interventions and populations studied. Because of such controls, effect sizes from QEs are more complex than those from randomized experiments. A statistical meta-regression model that incorporates important features of the QEs under review was presented. Meta-analyses of QEs provide particular challenges, but thorough coding of intervention characteristics and study methods, along with careful analysis, should allow for sound inferences. Copyright © 2017 Elsevier Inc. All rights reserved.

Pesticide exposure and risk of Alzheimer’s disease: a systematic review and meta-analysis

NASA Astrophysics Data System (ADS)

Yan, Dandan; Zhang, Yunjian; Liu, Liegang; Yan, Hong

2016-09-01

Evidence suggests that lifelong cumulative exposure to pesticides may generate lasting toxic effects on the central nervous system and contribute to the development of Alzheimer’s disease (AD). A number of reports indicate a potential association between long-term/low-dose pesticide exposure and AD, but the results are inconsistent. Therefore, we conducted a meta-analysis to clarify this association. Relevant studies were identified according to inclusion criteria. Summary odds ratios (ORs) were calculated using fixed-effects models. A total of seven studies were included in our meta-analysis. A positive association was observed between pesticide exposure and AD (OR = 1.34 95% confidence interval [CI] = 1.08, 1.67; n = 7). The summary ORs with 95% CIs from the crude and adjusted effect size studies were 1.14 (95% CI = 0.94, 1.38; n = 7) and 1.37 (95% CI = 1.09, 1.71; n = 5), respectively. The sensitivity analyses of the present meta-analysis did not substantially modify the association between pesticide exposure and AD. Subgroup analyses revealed that high-quality studies tended to show significant relationships. The present meta-analysis suggested a positive association between pesticide exposure and AD, confirming the hypothesis that pesticide exposure is a risk factor for AD. Further high-quality cohort and case-control studies are required to validate a causal relationship.

A note on the use of the generalized odds ratio in meta-analysis of association studies involving bi- and tri-allelic polymorphisms.

PubMed

Pereira, Tiago V; Mingroni-Netto, Regina C

2011-06-06

The generalized odds ratio (GOR) was recently suggested as a genetic model-free measure for association studies. However, its properties were not extensively investigated. We used Monte Carlo simulations to investigate type-I error rates, power and bias in both effect size and between-study variance estimates of meta-analyses using the GOR as a summary effect, and compared these results to those obtained by usual approaches of model specification. We further applied the GOR in a real meta-analysis of three genome-wide association studies in Alzheimer's disease. For bi-allelic polymorphisms, the GOR performs virtually identical to a standard multiplicative model of analysis (e.g. per-allele odds ratio) for variants acting multiplicatively, but augments slightly the power to detect variants with a dominant mode of action, while reducing the probability to detect recessive variants. Although there were differences among the GOR and usual approaches in terms of bias and type-I error rates, both simulation- and real data-based results provided little indication that these differences will be substantial in practice for meta-analyses involving bi-allelic polymorphisms. However, the use of the GOR may be slightly more powerful for the synthesis of data from tri-allelic variants, particularly when susceptibility alleles are less common in the populations (≤10%). This gain in power may depend on knowledge of the direction of the effects. For the synthesis of data from bi-allelic variants, the GOR may be regarded as a multiplicative-like model of analysis. The use of the GOR may be slightly more powerful in the tri-allelic case, particularly when susceptibility alleles are less common in the populations.

Effects of coenzyme Q10 supplementation on plasma C-reactive protein concentrations: A systematic review and meta-analysis of randomized controlled trials.

PubMed

Mazidi, Mohsen; Kengne, Andre Pascal; Banach, Maciej

2018-02-01

The aim of this systematic review and meta-analysis of prospective interventional studies was to investigate the effects of coenzyme Q10 (CQ10) on plasma C-reactive protein (CRP) levels. PubMed/Medline, Web of Science (WoS), Cochrane Database and Google Scholar databases were searched (up to December 2016) to identify prospective studies evaluating the impact of CQ10 supplementation on CRP. Random effects models meta-analysis was used for quantitative data synthesis. Sensitivity analysis used the leave-one-out method, and heterogeneity was quantitatively assessed using the I 2 index. Systematic review PROSPERO database registration: CRD42016038155. From a total of 119 entries identified via searches, 7 studies were finally included to the analysis. The results of the meta-analysis indicated a non-significant reduction in CRP concentrations following supplementation with CQ10 with a weighted mean difference [WMD] of -0.25mg/l (95% confidence intervals [CI] -0.56 to 0.06, I 2 =42.0%). The WMD for the effects on interleukin 6 (IL6) was -0.72pg/dl, (95% CI -1.24 to -0.24, I 2 =51.8%). These findings were robust in sensitivity analyses. Random-effects meta-regression revealed that changes in plasma CRP levels were independent of the dosage of CQ10 (slope: -0.0005; 95% CI: -0.005, 0.004; p=0.832) while duration of supplementation was the dependent mediator (slope: slope: -0.111; 95% CI: -0.21, -0.004; p=0.042). In conclusion, CQ10 supplementation has a borderline favourable effect on CRP levels, and a significant effect on IL-6 level. This suggests that CQ10 supplementation likely attenuates subclinical inflammation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Antecedents and Consequences of Retirement Planning and Decision-Making: A Meta-Analysis and Model

ERIC Educational Resources Information Center

Topa, Gabriela; Moriano, Juan Antonio; Depolo, Marco; Alcover, Carlos-Maria; Morales, J. Francisco

2009-01-01

In this study, meta-analytic procedures were used to examine the relationships between retirement planning, retirement decision and their antecedent and consequences. Our review of the literature generated 341 independent samples obtained from 99 primary studies with 188,222 participants. A small effect size (ES) for antecedents of retirement…

Meta-analysis of genome-wide association from genomic prediction models

USDA-ARS?s Scientific Manuscript database

A limitation of many genome-wide association studies (GWA) in animal breeding is that there are many loci with small effect sizes; thus, larger sample sizes (N) are required to guarantee suitable power of detection. To increase sample size, results from different GWA can be combined in a meta-analys...

Therapy of bovine endometritis with prostaglandin F2α: a meta-analysis.

PubMed

Haimerl, P; Heuwieser, W; Arlt, S

2013-05-01

The objective of the conducted meta-analysis was to assess the efficacy of the treatment of bovine endometritis with PGF(2α) by statistical means. Postpartum uterine infections have a high prevalence and a very negative effect on reproductive performance in dairy cattle. Because of a wide discordance between research results, a meta-analysis of the efficacy of the treatment of bovine endometritis with PGF(2α) was conducted. A comprehensive literature search was performed using online databases to reveal a total of 2,307 references. In addition, 5 articles were retrieved by reviewing citations. After applying specific exclusion criteria and evaluating specific evidence parameters, 5 publications, comprising 6 trials, were eligible for being analyzed by means of meta-analysis. Data for each trial were extracted and analyzed using meta-analysis software Review Manager (version 5.1; The Nordic Cochrane Centre, Copenhagen, Denmark). Estimated effect sizes of PGF(2α) were calculated on calving to first service and calving to conception interval. Prostaglandin F(2α) treatment of cows with chronic endometritis had a negative effect on both reproductive performance parameters. Heterogeneity was substantial for calving to first service and calving to conception interval [I(2) (measure of variation beyond chance)=100 and 87%, respectively]; therefore, random-effects models were used. Sensitivity analysis as well as subgroup analysis showed that the performance of randomization was influential in modifying effect size of PGF(2α) treatment. The funnel plot illustrated a publication bias toward smaller studies that reported a prolonged calving to conception interval after a PGF(2α) treatment. We conclude that the investigation of this subject by means of meta-analysis did not reveal an improvement of reproductive performance of cows with endometritis after treatment with PGF(2α). Furthermore, there is a shortage of comparable high quality studies investigating reproductive performance after PGF(2α) treatment of cows with chronic endometritis. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Early outcome of early-goal directed therapy for patients with sepsis or septic shock: a systematic review and meta-analysis of randomized controlled trials.

PubMed

Chen, Xiaofan; Zhu, Weifeng; Tan, Jing; Nie, Heyun; Liu, Liangming; Yan, Dongmei; Zhou, Xu; Sun, Xin

2017-04-18

Various trials and meta-analyses have reported conflicting results concerning the application of early goal-directed therapy (EGDT) for sepsis and septic shock. The aim of this study was to update the evidence by performing a systematic review and meta-analysis. Multiple databases were searched from initial through August, 2016 for randomized controlled trials (RCTs) which investigated the associations between the use of EGDT and mortality in patients with sepsis or septic shock. Meta-analysis was performed using random-effects model and heterogeneity was examined through subgroup analyses. The primary outcome of interest was patient all-cause mortality including hospital or ICU mortality. Seventeen RCTs including 6207 participants with 3234 in the EGDT group and 2973 in the control group were eligible for this study. Meta-analysis showed that EGDT did not significantly reduce hospital or intensive care unit (ICU) mortality (relative risk [RR] 0.89, 95% CI 0.78 to 1.02) compared with control group for patients with sepsis or septic shock. The findings of subgroup analyses stratified by study region, number of research center, year of enrollment, clinical setting, sample size, timing of EGDT almost remained constant with that of the primary analysis. Our findings provide evidence that EGDT offers neutral survival effects for patients with sepsis or septic shock. Further meta-analyses based on larger well-designed RCTs or individual patient data meta-analysis are required to explore the survival benefits of EDGT in patients with sepsis or septic shock.

Estimating Information Processing in a Memory System: The Utility of Meta-analytic Methods for Genetics.

PubMed

Yildizoglu, Tugce; Weislogel, Jan-Marek; Mohammad, Farhan; Chan, Edwin S-Y; Assam, Pryseley N; Claridge-Chang, Adam

2015-12-01

Genetic studies in Drosophila reveal that olfactory memory relies on a brain structure called the mushroom body. The mainstream view is that each of the three lobes of the mushroom body play specialized roles in short-term aversive olfactory memory, but a number of studies have made divergent conclusions based on their varying experimental findings. Like many fields, neurogenetics uses null hypothesis significance testing for data analysis. Critics of significance testing claim that this method promotes discrepancies by using arbitrary thresholds (α) to apply reject/accept dichotomies to continuous data, which is not reflective of the biological reality of quantitative phenotypes. We explored using estimation statistics, an alternative data analysis framework, to examine published fly short-term memory data. Systematic review was used to identify behavioral experiments examining the physiological basis of olfactory memory and meta-analytic approaches were applied to assess the role of lobular specialization. Multivariate meta-regression models revealed that short-term memory lobular specialization is not supported by the data; it identified the cellular extent of a transgenic driver as the major predictor of its effect on short-term memory. These findings demonstrate that effect sizes, meta-analysis, meta-regression, hierarchical models and estimation methods in general can be successfully harnessed to identify knowledge gaps, synthesize divergent results, accommodate heterogeneous experimental design and quantify genetic mechanisms.

Meta-analysis in Stata using gllamm.

PubMed

Bagos, Pantelis G

2015-12-01

There are several user-written programs for performing meta-analysis in Stata (Stata Statistical Software: College Station, TX: Stata Corp LP). These include metan, metareg, mvmeta, and glst. However, there are several cases for which these programs do not suffice. For instance, there is no software for performing univariate meta-analysis with correlated estimates, for multilevel or hierarchical meta-analysis, or for meta-analysis of longitudinal data. In this work, we show with practical applications that many disparate models, including but not limited to the ones mentioned earlier, can be fitted using gllamm. The software is very versatile and can handle a wide variety of models with applications in a wide range of disciplines. The method presented here takes advantage of these modeling capabilities and makes use of appropriate transformations, based on the Cholesky decomposition of the inverse of the covariance matrix, known as generalized least squares, in order to handle correlated data. The models described earlier can be thought of as special instances of a general linear mixed-model formulation, but to the author's knowledge, a general exposition in order to incorporate all the available models for meta-analysis as special cases and the instructions to fit them in Stata has not been presented so far. Source code is available at http:www.compgen.org/tools/gllamm. Copyright © 2015 John Wiley & Sons, Ltd.

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol lowering drugs

PubMed Central

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin

2013-01-01

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs.

PubMed

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G; Shah, Arvind K; Lin, Jianxin

2013-10-15

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the deviance information criterion is used to select the best transformation model. Because the model is quite complex, we develop a novel Monte Carlo Markov chain sampling scheme to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol-lowering drugs where the goal is to jointly model the three-dimensional response consisting of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). Because the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately; however, a multivariate approach would be more appropriate because these variables are correlated with each other. We carry out a detailed analysis of these data by using the proposed methodology. Copyright © 2013 John Wiley & Sons, Ltd.

Rigorous control conditions diminish treatment effects in weight loss randomized controlled trials

PubMed Central

Dawson, John A.; Kaiser, Kathryn A.; Affuso, Olivia; Cutter, Gary R.; Allison, David B.

2015-01-01

Background It has not been established whether control conditions with large weight losses (WLs) diminish expected treatment effects in WL or prevention of weight gain (PWG) randomized controlled trials (RCTs). Subjects/Methods We performed a meta-analysis of 239 WL/PWG RCTs that include a control group and at least one treatment group. A maximum likelihood meta-analysis framework is used in order to model and understand the relationship between treatment effects and control group outcomes. Results Under the informed model, an increase in control group WL of one kilogram corresponds with an expected shrinkage of the treatment effect by 0.309 kg [95% CI (−0.480, −0.138), p = 0.00081]; this result is robust against violations of the model assumptions. Conclusions We find that control conditions with large weight losses diminish expected treatment effects. Our investigation may be helpful to clinicians as they design future WL/PWG studies. PMID:26449419

Do antipsychotics lead to cognitive impairment in dementia? A meta-analysis of randomised placebo-controlled trials.

PubMed

Wolf, Alexander; Leucht, Stefan; Pajonk, Frank-Gerald

2017-04-01

Behavioural and psychological symptoms in dementia (BPSD) are common and often treated with antipsychotics, which are known to have small efficacy and to cause many side effects. One potential side effect might be cognitive decline. We searched MEDLINE, Scopus, CENTRAL and www.ClincalStudyResult.org for randomized, double-blind, placebo-controlled trials using antipsychotics for treating BPSD and evaluated cognitive functioning. The studies identified were summarized in a meta-analysis with the standardized mean difference (SMD, Hedges's g) as the effect size. Meta-regression was additionally performed to identify associated factors. Ten studies provided data on the course of cognitive functioning. The random effects model of the pooled analysis showed a not significant effect (SMD = -0.065, 95 % CI -0.186 to 0.057, I 2  = 41 %). Meta-regression revealed a significant correlation between cognitive impairment and treatment duration (R 2  = 0.78, p < 0.02) as well as baseline MMSE (R 2  = 0.92, p < 0.005). These correlations depend on only two out of ten studies and should interpret cautiously.

Methods for the Joint Meta-Analysis of Multiple Tests

ERIC Educational Resources Information Center

Trikalinos, Thomas A.; Hoaglin, David C.; Small, Kevin M.; Terrin, Norma; Schmid, Christopher H.

2014-01-01

Existing methods for meta-analysis of diagnostic test accuracy focus primarily on a single index test. We propose models for the joint meta-analysis of studies comparing multiple index tests on the same participants in paired designs. These models respect the grouping of data by studies, account for the within-study correlation between the tests'…

Is chronic toxoplasmosis a risk factor for diabetes mellitus? A systematic review and meta-analysis of case-control studies.

PubMed

Majidiani, Hamidreza; Dalvand, Sahar; Daryani, Ahmad; Galvan-Ramirez, Ma de la Luz; Foroutan-Rad, Masoud

The global protozoan parasite, Toxoplasma gondii, infects many warm-blooded animals and humans by employing different transmission routes. There have been some recent studies on the probable relevance of infectious agents and diabetes. Therefore, we conducted a systematic review and meta-analysis to identify the possible association between chronic toxoplasmosis and diabetes mellitus. This study was conducted following the general methodology recommended for systematic reviews and meta-analysis. Nine English literature databases (Google scholar, PubMed, Scopus, Web of science, Science Direct, Ovid, ProQuest, IngentaConnect, and Wiley Online Library) were searched, up to January 2016. Random effects model was used to determine odds ratios and their 95% confidence intervals. Our review resulted in a total of seven publications meeting the inclusion criteria. Because of significant heterogeneity, we estimated a common OR by a random effects model at 1.10 (95% CI=0.13-9.57) with p=0.929 and 2.39 (95% CI=1.20-4.75) with p=0.013 for type 1 and type 2 diabetes mellitus, respectively. Despite the limitations such as low number of studies, this meta-analysis suggests chronic toxoplasmosis as a possible risk factor for type 2 DM. However, based on random effects model no statistically significant association was observed between T. gondii and type 1 DM. It is highly recommended for researchers to carry out more accurate studies aiming to better understand this association. Copyright © 2016 Sociedade Brasileira de Infectologia. Published by Elsevier Editora Ltda. All rights reserved.

Illustration of a Multilevel Model for Meta-Analysis

ERIC Educational Resources Information Center

de la Torre, Jimmy; Camilli, Gregory; Vargas, Sadako; Vernon, R. Fox

2007-01-01

In this article, the authors present a multilevel (or hierarchical linear) model that illustrates issues in the application of the model to data from meta-analytic studies. In doing so, several issues are discussed that typically arise in the course of a meta-analysis. These include the presence of non-zero between-study variability, how multiple…

Probiotics Prevent Late-Onset Sepsis in Human Milk-Fed, Very Low Birth Weight Preterm Infants: Systematic Review and Meta-Analysis.

PubMed

Aceti, Arianna; Maggio, Luca; Beghetti, Isadora; Gori, Davide; Barone, Giovanni; Callegari, Maria Luisa; Fantini, Maria Pia; Indrio, Flavia; Meneghin, Fabio; Morelli, Lorenzo; Zuccotti, Gianvincenzo; Corvaglia, Luigi

2017-08-22

Growing evidence supports the role of probiotics in reducing the risk of necrotizing enterocolitis, time to achieve full enteral feeding, and late-onset sepsis (LOS) in preterm infants. As reported for several neonatal clinical outcomes, recent data have suggested that nutrition might affect probiotics' efficacy. Nevertheless, the currently available literature does not explore the relationship between LOS prevention and type of feeding in preterm infants receiving probiotics. Thus, the aim of this systematic review and meta-analysis was to evaluate the effect of probiotics for LOS prevention in preterm infants according to type of feeding (exclusive human milk (HM) vs. exclusive formula or mixed feeding). Randomized-controlled trials involving preterm infants receiving probiotics and reporting on LOS were included in the systematic review. Only trials reporting on outcome according to feeding type were included in the meta-analysis. Fixed-effects models were used and random-effects models were used when significant heterogeneity was found. The results were expressed as risk ratio (RR) with 95% confidence interval (CI). Twenty-five studies were included in the meta-analysis. Overall, probiotic supplementation resulted in a significantly lower incidence of LOS (RR 0.79 (95% CI 0.71-0.88), p < 0.0001). According to feeding type, the beneficial effect of probiotics was confirmed only in exclusively HM-fed preterm infants (RR 0.75 (95% CI 0.65-0.86), p < 0.0001). Among HM-fed infants, only probiotic mixtures, and not single-strain products, were effective in reducing LOS incidence (RR 0.68 (95% CI 0.57-0.80) p < 0.00001). The results of the present meta-analysis show that probiotics reduce LOS incidence in exclusively HM-fed preterm infants. Further efforts are required to clarify the relationship between probiotics supplementation, HM, and feeding practices in preterm infants.

Probiotics Prevent Late-Onset Sepsis in Human Milk-Fed, Very Low Birth Weight Preterm Infants: Systematic Review and Meta-Analysis

PubMed Central

Aceti, Arianna; Maggio, Luca; Beghetti, Isadora; Barone, Giovanni; Callegari, Maria Luisa; Fantini, Maria Pia; Indrio, Flavia; Meneghin, Fabio; Morelli, Lorenzo; Corvaglia, Luigi

2017-01-01

Growing evidence supports the role of probiotics in reducing the risk of necrotizing enterocolitis, time to achieve full enteral feeding, and late-onset sepsis (LOS) in preterm infants. As reported for several neonatal clinical outcomes, recent data have suggested that nutrition might affect probiotics’ efficacy. Nevertheless, the currently available literature does not explore the relationship between LOS prevention and type of feeding in preterm infants receiving probiotics. Thus, the aim of this systematic review and meta-analysis was to evaluate the effect of probiotics for LOS prevention in preterm infants according to type of feeding (exclusive human milk (HM) vs. exclusive formula or mixed feeding). Randomized-controlled trials involving preterm infants receiving probiotics and reporting on LOS were included in the systematic review. Only trials reporting on outcome according to feeding type were included in the meta-analysis. Fixed-effects models were used and random-effects models were used when significant heterogeneity was found. The results were expressed as risk ratio (RR) with 95% confidence interval (CI). Twenty-five studies were included in the meta-analysis. Overall, probiotic supplementation resulted in a significantly lower incidence of LOS (RR 0.79 (95% CI 0.71–0.88), p < 0.0001). According to feeding type, the beneficial effect of probiotics was confirmed only in exclusively HM-fed preterm infants (RR 0.75 (95% CI 0.65–0.86), p < 0.0001). Among HM-fed infants, only probiotic mixtures, and not single-strain products, were effective in reducing LOS incidence (RR 0.68 (95% CI 0.57–0.80) p < 0.00001). The results of the present meta-analysis show that probiotics reduce LOS incidence in exclusively HM-fed preterm infants. Further efforts are required to clarify the relationship between probiotics supplementation, HM, and feeding practices in preterm infants. PMID:28829405

Effectiveness of problem-based learning in Chinese dental education: a meta-analysis.

PubMed

Huang, Beilei; Zheng, Liwei; Li, Chunjie; Li, Li; Yu, Haiyang

2013-03-01

This article provides a critical overview of problem-based learning (PBL) practice in dental education in China. Because the application of PBL has not been carried out on a large scale in Chinese dental education, this review was performed to investigate its effectiveness. Databases were searched for studies that met the inclusion criteria, with study identification and data extraction performed by two reviewers independently. Meta-analysis was done with Revman 5.1. Eleven randomized controlled trials were included. The meta-analysis found that PBL had a positive effect on gaining higher theoretical (SMD=0.88, 95% CI [0.46, 1.31], p<0.0001) and practical scores (SMD=1.48, 95% CI [0.95, 2.00], p<0.0001). However, the pooled result did not show any positive effect on gaining higher pass rates (RR=1.06, 95% CI [0.97, 1.16], p=0.21). This meta-analysis suggests that the PBL pedagogy is considered superior to the traditional lecture-based teaching in this setting. PBL methods could be an optional supplementary method of dental teaching models in China. However, Chinese dental schools should devise PBL curricula according to their own conditions. The effectiveness of PBL should be optimized maximally with all these limitations.

Subjective Socioeconomic Status and Adolescent Health: A Meta-Analysis

PubMed Central

Quon, Elizabeth C.; McGrath, Jennifer J.

2017-01-01

Objective To comprehensively and quantitatively examine the association between subjective socioeconomic status (SES) and health outcomes during adolescence. Methods Forty-four studies met criteria for inclusion in the meta-analysis. Information on study quality, demographics, subjective SES, health outcomes, and covariates were extracted from each study. Fisher’s Z was selected as the common effect size metric across studies. Random-effect meta-analytic models were employed and fail-safe numbers were generated to address publication bias. Results Overall, subjective SES was associated with health during adolescence (Fisher’s Z = .10). The magnitude of the effect varied by type of health outcome, with larger effects observed for mental health outcomes, self-rated health, and general health symptoms; and nonsignificant effects observed for biomarkers of health and substance-use-related health behaviors. Of the measures of subjective SES employed in the reviewed studies, perception of financial constraints, was most strongly associated with adolescent health outcomes. Analysis of covariates indicated that inclusion of objective SES covariates did not affect the association between subjective SES and health. Conclusions This meta-analysis has implications for the measurement of subjective SES in adolescents, for the conceptualization of subjective and objective SES, and for the pathways between SES and health in adolescents. PMID:24245837

A meta-analysis of the effect of angiotensin receptor blockers and calcium channel blockers on blood pressure, glycemia and the HOMA-IR index in non-diabetic patients.

PubMed

Yang, Yue; Wei, Ri-bao; Xing, Yue; Tang, Lu; Zheng, Xiao-yong; Wang, Zi-cheng; Gao, Yu-wei; Li, Min-xia; Chen, Xiang-mei

2013-12-01

This study compared the efficacy of angiotensin receptor blockers (ARBs) and calcium channel blockers (CCBs) in the effect of insulin resistance (IR) as assessed using the homeostasis model assessment of insulin resistance (HOMA-IR) in non-diabetic patients. The MEDLINE, EMBASE, and Cochrane Library databases were searched to identify studies published before December 2012 that investigated the use of ARBs and CCBs to determine the effect on the HOMA-IR index in non-diabetics. Parameters on IR and blood pressure were collected. Review Manager 5.2 and Stata 12.0 were used to perform the meta-analysis. Fixed and random effects models were applied to various aspects of the meta-analysis, which assessed the therapeutic effects of the two types of drug using the HOMA-IR index in non-diabetic patients. The meta-analysis included five clinical trials. Patient comparisons before and after treatment with ARBs and CCBs revealed that ARBs reduced the HOMA-IR index (weighted mean difference (WMD) -0.65, 95% confidence interval (CI) -0.93 to -0.38) and fasting plasma insulin (FPI) (WMD -2.01, 95% CI -3.27 to -0.74) significantly more than CCBs. No significant differences in the therapeutic effects of these two types of drug on blood pressure were observed. Given that there are no significant differences in the therapeutic effects of ARBs and CCBs on blood pressure, as ARBs are superior to CCBs in their effect on the HOMA-IR index in non-diabetics, they might be a better choice in hypertension patients without diabetes. © 2013.

Consumption of fruit, but not vegetables, may reduce risk of gastric cancer: results from a meta-analysis of cohort studies.

PubMed

Wang, Qingbing; Chen, Yi; Wang, Xiaolin; Gong, Gaoquan; Li, Guoping; Li, Changyu

2014-05-01

Quantification of the association between consumption of fruit and vegetables and risk of gastric cancer (GC) is controversial. We aimed to conduct a meta-analysis of cohort studies to evaluate the associations. Eligible studies published up to 31st August 2013 were retrieved via both computer searches of PubMed and EMBASE and a manual review of references. Random-effects models were used to calculate summary relative risk (SRR). Heterogeneity among studies was assessed using Cochran's Q and I(2) statistics. A total of 17 articles (24 studies), were included in this meta-analysis. There were >2.4 million individuals (6632 GC events) with a median follow-up of 10years. Based on the high versus low analysis, consumption of fruit, but not vegetables, may reduce risk of gastric cancer (fruit: SRR=0.90, 95% confidence interval (CI): 0.83-0.98, Pheterogeneity=0.450; vegetable: SRR=0.96, 95% CI: 0.88-1.06, Pheterogeneity=0.150). Meta regression analysis suggested that outcome (incidence versus mortality) and study quality (high versus low) contributed significantly to heterogeneity. The same results were also shown in the linear dose-response analysis (per 100-g/day) (fruit: SRR=0.95, 95% CI: 0.91-0.99; vegetable: SRR=0.96, 95% CI: 0.91-1.01). Significant inverse associations emerged in non-linear models for consumption of fruit (Pnon-linearity=0.04), but not for consumption of vegetables (Pnon-linearity=0.551). Findings from this meta-analysis indicate a significant protective effect for the consumption of fruit on GC risk, but not for the consumption of vegetables. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multivariate meta-analysis: Potential and promise

PubMed Central

Jackson, Dan; Riley, Richard; White, Ian R

2011-01-01

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

High Prevalence of Vitamin D Deficiency among Iranian Population: A Systematic Review and Meta-Analysis

PubMed Central

Tabrizi, Reza; Moosazadeh, Mahmood; Akbari, Maryam; Dabbaghmanesh, Mohammad Hossein; Mohamadkhani, Minoo; Asemi, Zatollah; Heydari, Seyed Taghi; Akbari, Mojtaba; Lankarani, Kamran B

2018-01-01

Background The prevention and correction of vitamin D deficiency requires a precise depiction of the current situation and identification of risk factors in each region. The present study attempted to determine these entities using a systematic review and meta-analysis in Iran. Methods Articles published online in Persian and English between 2000 and November 1, 2016, were reviewed. This was carried out using national databases such as SID, IranMedex, Magiran, and IranDoc and international databases such as PubMed, Google Scholar, and Scopus. The heterogeneity index among the studies was determined using the Cochran (Q) and I2 test. Based on the heterogeneity results, the random-effect model was applied to estimate the prevalence of vitamin D deficiency. In addition, meta-regression analysis was used to determine heterogeneity-suspected factors, and the Egger test was applied to identify publication bias. Results The meta-analysis of 48 studies identified 18531 individuals with vitamin D deficiency. According to the random-effect model, the prevalence of vitamin D deficiency among male, female, and pregnant women was estimated to be 45.64% (95% CI: 29.63 to 61.65), 61.90% (95% CI: 48.85 to 74.96), and 60.45% (95% CI: 23.73 to 97.16), respectively. The results of the meta-regression analysis indicated that the prevalence of vitamin D deficiency was significantly different in various geographical regions (β=4.4; P=0.023). Conclusion The results obtained showed a significant prevalence of vitamin D deficiency among the Iranian population, a condition to be addressed by appropriate planning. PMID:29749981

Statin treatment and functional outcome after ischemic stroke: case-control and meta-analysis.

PubMed

Biffi, Alessandro; Devan, William J; Anderson, Christopher D; Cortellini, Lynelle; Furie, Karen L; Rosand, Jonathan; Rost, Natalia S

2011-05-01

Multiple studies suggest that statin use before acute ischemic stroke is associated with improved functional outcome. However, available evidence is conflicting, and several published reports are limited by small sample sizes. We therefore investigated the effect of antecedent use of statins on stroke outcome by performing a meta-analysis of all results from published studies as well as our own unpublished data. We performed a systematic literature search and meta-analysis of studies investigating the association between prestroke statin use and clinical outcome and included additional data from 126 prestroke statin users and 767 nonusers enrolled at our institution. A total of 12 studies, comprising 2013 statin users and 9682 nonusers, was meta-analyzed using a random effects model. We also meta-analyzed results for individual Trial of ORG 10172 in Acute Stroke Treatment stroke subtypes to determine whether the effect of statin use differed across subtypes using the Breslow-Day test. Meta-analysis of all available data identified an association between prestroke statin use and improved functional outcome (OR, 1.62; 95% CI, 1.39 to 1.88), but we uncovered evidence of publication bias. The effect of statin use on functional outcome was found to be larger for small vessel strokes compared with other subtypes (Breslow-Day P=0.008). Antecedent use of statins is associated with improved outcome in patients with acute ischemic stroke. This association appears to be stronger in patients with small vessel stroke subtype. However, evidence of publication bias in the existing literature suggests these findings should be interpreted with caution.

Statin Treatment and Functional Outcome after Ischemic Stroke: Case-control and Meta-analysis

PubMed Central

Biffi, A; Devan, WJ; Anderson, CD; Cortellini, L; Furie, KL; Rosand, J; Rost, NS

2011-01-01

Background and Purpose Multiple studies suggest that statin use prior to acute ischemic stroke (AIS) is associated with improved functional outcome. However, available evidence is conflicting, and several published reports are limited by small sample sizes. We therefore investigated the effect of antecedent use of statins on stroke outcome by performing a meta-analysis of all results from published studies as well as our own unpublished data. Methods We performed a systematic literature search and meta-analysis of studies investigating the association between pre-stroke statin use and clinical outcome, and included additional data from 126 pre-stroke statin users and 767 non-users enrolled at our Institution. A total of 12 studies, comprising 2013 statin users and 9682 non- users were meta-analyzed using a random effects model. We also meta-analyzed results for individual TOAST stroke subtypes to determine whether the effect of statin use differed across subtypes, using the Breslow-Day (BD) test. Results Meta-analysis of all available data identified an association between pre-stroke statin use and improved functional outcome (Odds Ratio = 1.62, 95% Confidence Interval: 1.39 -1.88), but we uncovered evidence of publication bias. The effect of statin use on functional outcome was found to be larger for small vessel strokes compared to other subtypes (BD p = 0.008). Conclusions Antecedent use of statins is associated with improved outcome in AIS patients. This association appears to be stronger in patients with small vessel stroke subtype. However, evidence of publication bias in the existing literature suggests these findings should be interpreted with caution. PMID:21415396

Systematic review, network meta-analysis and economic evaluation of biological therapy for the management of active psoriatic arthritis.

PubMed

Cawson, Matthew Richard; Mitchell, Stephen Andrew; Knight, Chris; Wildey, Henry; Spurden, Dean; Bird, Alex; Orme, Michelle Elaine

2014-01-20

An updated economic evaluation was conducted to compare the cost-effectiveness of the four tumour necrosis factor (TNF)-α inhibitors adalimumab, etanercept, golimumab and infliximab in active, progressive psoriatic arthritis (PsA) where response to standard treatment has been inadequate. A systematic review was conducted to identify relevant, recently published studies and the new trial data were synthesised, via a Bayesian network meta-analysis (NMA), to estimate the relative efficacy of the TNF-α inhibitors in terms of Psoriatic Arthritis Response Criteria (PsARC) response, Health Assessment Questionnaire (HAQ) scores and Psoriasis Area and Severity Index (PASI). A previously developed economic model was updated with the new meta-analysis results and current cost data. The model was adapted to delineate patients by PASI 50%, 75% and 90% response rates to differentiate between psoriasis outcomes. All four licensed TNF-α inhibitors were significantly more effective than placebo in achieving PsARC response in patients with active PsA. Adalimumab, etanercept and infliximab were significantly more effective than placebo in improving HAQ scores in patients who had achieved a PsARC response and in improving HAQ scores in PsARC non-responders. In an analysis using 1,000 model simulations, on average etanercept was the most cost-effective treatment and, at the National Institute for Health and Care Excellence willingness-to-pay threshold of between £20,000 to £30,000, etanercept is the preferred option. The economic analysis agrees with the conclusions from the previous models, in that biologics are shown to be cost-effective for treating patients with active PsA compared with the conventional management strategy. In particular, etanercept is cost-effective compared with the other biologic treatments.

Efficacy of synbiotic supplementation in patients with nonalcoholic fatty liver disease: A systematic review and meta-analysis of clinical trials: Synbiotic supplementation and NAFLD.

PubMed

Hadi, Amir; Mohammadi, Hamed; Miraghajani, Maryam; Ghaedi, Ehsan

2018-03-27

We systematically reviewed available randomized clinical trials (RCTs) to elucidate the overall effects of synbiotic supplementation in patients with nonalcoholic fatty liver disease (NAFLD). PubMed, Scopus, ISI Web of science and Google Scholar were searched up to December, 2017. All RCTs using synbiotic supplements to treat NAFLD included in this systematic review and meta-analysis. Mean Difference (MD) was pooled using a random-effects model. Eleven eligible databases from seven RCTs were identified for the present meta-analysis. Our results showed that synbiotic supplementation can decrease body weight, fasting blood sugar, insulin, low density lipoprotein cholesterol, total cholesterol, triglyceride, high-sensitivity C-reactive protein, tumor necrosis factor alpha, alanine transaminase and aspartate transaminase levels among patients with NAFLD. In contrast, synbiotic did not have favorable effects on body mass index (BMI), waist circumference, homeostasis model assessment for insulin resistance (HOMA-IR), and high density lipoprotein cholesterol (HDL) levels compared with the placebo group. The current study revealed that synbiotic supplementation has favorable effect on inflammatory factors, liver enzymes and some anthropometric indices, lipid profiles and glucose homeostasis parameters in patients with NAFLD.

Interventions for reducing fear of childbirth: A systematic review and meta-analysis of clinical trials.

PubMed

MoghaddamHosseini, Vahideh; Nazarzadeh, Milad; Jahanfar, Shayesteh

2017-11-07

Fear of childbirth is a problematic mental health issue during pregnancy. But, effective interventions to reduce this problem are not well understood. To examine effective interventions for reducing fear of childbirth. The Cochrane Central Register of Controlled Trials, PubMed, Embase and PsycINFO were searched since inception till September 2017 without any restriction. Randomised controlled trials and quasi-randomised controlled trials comparing interventions for treatment of fear of childbirth were included. The standardized mean differences were pooled using random and fixed effect models. The heterogeneity was determined using the Cochran's test and I 2 index and was further explored in meta-regression model and subgroup analyses. Ten studies inclusive of 3984 participants were included in the meta-analysis (2 quasi-randomized and 8 randomized clinical trials). Eight studies investigated education and two studies investigated hypnosis-based intervention. The pooled standardized mean differences of fear for the education intervention and hypnosis group in comparison with control group were -0.46 (95% CI -0.73 to -0.19) and -0.22 (95% CI -0.34 to -0.10), respectively. Both types of interventions were effective in reducing fear of childbirth; however our pooled results revealed that educational interventions may reduce fear with double the effect of hypnosis. Further large scale randomized clinical trials and individual patient data meta-analysis are warranted for assessing the association. Copyright © 2017 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

Serious Games for Mental Health: Are They Accessible, Feasible, and Effective? A Systematic Review and Meta-analysis.

PubMed

Lau, Ho Ming; Smit, Johannes H; Fleming, Theresa M; Riper, Heleen

2016-01-01

The development and use of serious games for mental health disorders are on the rise. Yet, little is known about the impact of these games on clinical mental health symptoms. We conducted a systematic review and meta-analysis of randomized controlled trials that evaluated the effectiveness of serious games on symptoms of mental disorder. We conducted a systematic search in the PubMed, PsycINFO, and Embase databases, using mental health and serious games-related keywords. Ten studies met the inclusion criteria and were included in the review, and nine studies were included in the meta-analysis. All of the serious games were provided via personal computer, mostly on CD-ROM without the need for an internet connection. The studies targeted age groups ranging from 7 to 80 years old. The serious games focused on symptoms of depression ( n  = 2), post-traumatic stress disorder ( n  = 2), autism spectrum disorder ( n  = 2), attention deficit hyperactivity disorder ( n  = 1), cognitive functioning ( n  = 2), and alcohol use disorder ( n  = 1). The studies used goal-oriented ( n  = 4) and cognitive training games ( n  = 6). A total of 674 participants were included in the meta-analysis (380 in experimental and 294 in control groups). A meta-analysis of 9 studies comprising 10 comparisons, using a random effects model, showed a moderate effect on improvement of symptoms [ g  = 0.55 (95% confidence interval 0.28-0.83); P  < 0.001], favoring serious games over no intervention controls. Though the number of comparisons in the meta-analysis was small, these findings suggest that serious gaming interventions may be effective for reducing disorder-related symptoms. More studies are needed in order to attain deeper knowledge of the efficacy for specific mental disorders and the longer term effects of this new type of treatment for mental disorders.

The efficacy and safety of medical leech therapy for osteoarthritis of the knee: A meta-analysis of randomized controlled trials.

PubMed

Wang, Haixia; Zhang, Jing; Chen, Liyan

2018-06-01

It is controversial on whether medical leech therapy is effective in improving pain and functional outcome in patients with knee osteoarthritis (OA). Therefore, we perform a meta-analysis from randomized controlled trials (RCTs) to evaluate the efficacy and safety of medical leech therapy in patients with knee OA. The PubMed, EMBASE, ScienceDirect, and Cochrane Library databases were systematically searched for literature up to January 2018. RCTs involving medical leech therapy in patients with knee OA were included. Two independent reviewers performed independent data abstraction. The I 2 statistic was used to assess heterogeneity. A fixed or random effects model was adopted for meta-analysis. All meta-analyses were performed by using STATA 12.0. Four RCTs with 264 patients were included in this meta-analysis. The current meta-analysis showed that there were significant differences in terms of visual analogue scale (VAS) scores and WOMAC scores at 1 week, 4weeks and 7 weeks compared with control groups. However, leech therapy was associated with a significantly higher incidence of adverse events. The overall evidence quality is moderate, which means that further research is likely to significantly change confidence in the effect estimate but may change the estimate. Medical leech therapy was associated with a significantly improved outcome in pain relief and functional recovery in patients with symptomatic knee OA. However, given the inherent limitations in the included studies, this conclusion should be interpreted cautiously. Copyright © 2018 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Evaluating the Effect of Virtual Reality Temporal Bone Simulation on Mastoidectomy Performance: A Meta-analysis.

PubMed

Lui, Justin T; Hoy, Monica Y

2017-06-01

Background The increasing prevalence of virtual reality simulation in temporal bone surgery warrants an investigation to assess training effectiveness. Objectives To determine if temporal bone simulator use improves mastoidectomy performance. Data Sources Ovid Medline, Embase, and PubMed databases were systematically searched per the PRISMA guidelines. Review Methods Inclusion criteria were peer-reviewed publications that utilized quantitative data of mastoidectomy performance following the use of a temporal bone simulator. The search was restricted to human studies published in English. Studies were excluded if they were in non-peer-reviewed format, were descriptive in nature, or failed to provide surgical performance outcomes. Meta-analysis calculations were then performed. Results A meta-analysis based on the random-effects model revealed an improvement in overall mastoidectomy performance following training on the temporal bone simulator. A standardized mean difference of 0.87 (95% CI, 0.38-1.35) was generated in the setting of a heterogeneous study population ( I 2 = 64.3%, P < .006). Conclusion In the context of a diverse population of virtual reality simulation temporal bone surgery studies, meta-analysis calculations demonstrate an improvement in trainee mastoidectomy performance with virtual simulation training.

Caffeinated and decaffeinated coffee consumption and melanoma risk: a dose-response meta-analysis of prospective cohort studies.

PubMed

Micek, Agnieszka; Godos, Justyna; Lafranconi, Alessandra; Marranzano, Marina; Pajak, Andrzej

2018-06-01

To determine the association between total, caffeinated and decaffeinated coffee consumption and melanoma risk a dose-response meta-analysis on prospective cohort studies were performed. Eligible studies were identified searching PubMed and EMBASE databases from the earliest available online indexing year to March 2017. The dose-response relationship was assessed by random-effects meta-analysis and the shape of the exposure-outcome curve was modelled linearly and using restricted cubic splines. A total of seven studies eligible for meta-analysis were identified that comprised 1,418,779 participants and 9211 melanoma cases. A linear dose-response meta-analysis showed a significant association between total coffee consumption and melanoma risk. An increase in coffee consumption of one cup per day was associated with a 3% reduction in melanoma risk (RR 0.97; 95% CI 0.95-0.99). Our findings suggest that coffee intake may be inversely associated with incidence of melanoma. Nevertheless, further studies exploring also the role of confounding factors are needed to explain the heterogeneity among studies.

A Bayesian Meta-Analysis of the Effect of Alcohol Use on HCV-Treatment Outcomes with a Comparison of Resampling Methods to Assess Uncertainty in Parameter Estimates.

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

Cauthen, Katherine Regina; Lambert, Gregory Joseph; Finley, Patrick D.

There is mounting evidence that alcohol use is significantly linked to lower HCV treatment response rates in interferon-based therapies, though some of the evidence is conflicting. Furthermore, although health care providers recommend reducing or abstaining from alcohol use prior to treatment, many patients do not succeed in doing so. The goal of this meta-analysis was to systematically review and summarize the Englishlanguage literature up through January 30, 2015 regarding the relationship between alcohol use and HCV treatment outcomes, among patients who were not required to abstain from alcohol use in order to receive treatment. Seven pertinent articles studying 1,751 HCV-infectedmore » patients were identified. Log-ORs of HCV treatment response for heavy alcohol use and light alcohol use were calculated and compared. We employed a hierarchical Bayesian meta-analytic model to accommodate the small sample size. The summary estimate for the log-OR of HCV treatment response was -0.775 with a 95% credible interval of (-1.397, -0.236). The results of the Bayesian meta-analysis are slightly more conservative compared to those obtained from a boot-strapped, random effects model. We found evidence of heterogeneity (Q = 14.489, p = 0.025), accounting for 60.28% of the variation among log-ORs. Meta-regression to capture the sources of this heterogeneity did not identify any of the covariates investigated as significant. This meta-analysis confirms that heavy alcohol use is associated with decreased HCV treatment response compared to lighter levels of alcohol use. Further research is required to characterize the mechanism by which alcohol use affects HCV treatment response.« less

Efficacy of febuxostat in hyperuricemic patients with mild-to-moderate chronic kidney disease: a meta-analysis of randomized clinical trials

PubMed Central

Zeng, Xiang Xia; Tang, Yunliang; Hu, Kaixiang; Zhou, Xi; Wang, Jiao; Zhu, Lingyan; Liu, Jianying; Xu, Jixiong

2018-01-01

Abstract Background: To investigate the efficacy of febuxostat in hyperuricemic patients with chronic kidney disease (CKD), relevant randomized clinical trials (RCTs) were analyzed. Methods: We used PubMed, Medline, ISI Web of Science, CBMdisc, and Cochrane Library databases to conduct a systematic literature research. A fixed-effects model was used to evaluate the standardized mean differences (SMDs) with 95% confidence intervals (CIs). We conducted subgroup analysis, sensitivity analysis, and analyzed publication bias, to comprehensively estimate the renoprotective effects of febuxostat in hyperuricemic patients with CKD. Results: Among 296 retrieved studies, 5 relevant RCTs were included in the meta-analysis. The result showed that serum estimated glomerular filtration rate (eGFR) was improved after febuxostat treatment in hyperuricemic patients with CKD, with an SMD (95% CI) of 0.24 [−0.17 to 0.43] and P = .67 (fixed-effects model). No heterogeneity was observed across studies (I2 = 0% and P = .67). Subgroup analysis suggested that treatment-related reductions in serum eGFR levels were not related to drug doses, intervention times, or region. Conclusions: The present meta-analysis suggests that febuxostat may slow the progression of mild-to-moderate CKD. Given the limited number of included studies, additional large sample-size RCTs are required to determine the long-term renoprotective effects of febuxostat in hyperuricemic patients with CKD. PMID:29595642

Efficacy of febuxostat in hyperuricemic patients with mild-to-moderate chronic kidney disease: a meta-analysis of randomized clinical trials: A PRISMA-compliant article.

PubMed

Zeng, Xiang Xia; Tang, Yunliang; Hu, Kaixiang; Zhou, Xi; Wang, Jiao; Zhu, Lingyan; Liu, Jianying; Xu, Jixiong

2018-03-01

To investigate the efficacy of febuxostat in hyperuricemic patients with chronic kidney disease (CKD), relevant randomized clinical trials (RCTs) were analyzed. We used PubMed, Medline, ISI Web of Science, CBMdisc, and Cochrane Library databases to conduct a systematic literature research. A fixed-effects model was used to evaluate the standardized mean differences (SMDs) with 95% confidence intervals (CIs). We conducted subgroup analysis, sensitivity analysis, and analyzed publication bias, to comprehensively estimate the renoprotective effects of febuxostat in hyperuricemic patients with CKD. Among 296 retrieved studies, 5 relevant RCTs were included in the meta-analysis. The result showed that serum estimated glomerular filtration rate (eGFR) was improved after febuxostat treatment in hyperuricemic patients with CKD, with an SMD (95% CI) of 0.24 [-0.17 to 0.43] and P = .67 (fixed-effects model). No heterogeneity was observed across studies (I  = 0% and P = .67). Subgroup analysis suggested that treatment-related reductions in serum eGFR levels were not related to drug doses, intervention times, or region. The present meta-analysis suggests that febuxostat may slow the progression of mild-to-moderate CKD. Given the limited number of included studies, additional large sample-size RCTs are required to determine the long-term renoprotective effects of febuxostat in hyperuricemic patients with CKD.

A Multivariate Model for the Meta-Analysis of Study Level Survival Data at Multiple Times

ERIC Educational Resources Information Center

Jackson, Dan; Rollins, Katie; Coughlin, Patrick

2014-01-01

Motivated by our meta-analytic dataset involving survival rates after treatment for critical leg ischemia, we develop and apply a new multivariate model for the meta-analysis of study level survival data at multiple times. Our data set involves 50 studies that provide mortality rates at up to seven time points, which we model simultaneously, and…

Meta-analysis and meta-regression of omega-3 polyunsaturated fatty acid supplementation for major depressive disorder.

PubMed

Mocking, R J T; Harmsen, I; Assies, J; Koeter, M W J; Ruhé, H G; Schene, A H

2016-03-15

Omega-3 polyunsaturated fatty acid (PUFA) supplementation has been proposed as (adjuvant) treatment for major depressive disorder (MDD). In the present meta-analysis, we pooled randomized placebo-controlled trials assessing the effects of omega-3 PUFA supplementation on depressive symptoms in MDD. Moreover, we performed meta-regression to test whether supplementation effects depended on eicosapentaenoic acid (EPA) or docosahexaenoic acid dose, their ratio, study duration, participants' age, percentage antidepressant users, baseline MDD symptom severity, publication year and study quality. To limit heterogeneity, we only included studies in adult patients with MDD assessed using standardized clinical interviews, and excluded studies that specifically studied perinatal/perimenopausal or comorbid MDD. Our PubMED/EMBASE search resulted in 1955 articles, from which we included 13 studies providing 1233 participants. After taking potential publication bias into account, meta-analysis showed an overall beneficial effect of omega-3 PUFAs on depressive symptoms in MDD (standardized mean difference=0.398 (0.114-0.682), P=0.006, random-effects model). As an explanation for significant heterogeneity (I(2)=73.36, P<0.001), meta-regression showed that higher EPA dose (β=0.00037 (0.00009-0.00065), P=0.009), higher percentage antidepressant users (β=0.0058 (0.00017-0.01144), P=0.044) and earlier publication year (β=-0.0735 (-0.143 to 0.004), P=0.04) were significantly associated with better outcome for PUFA supplementation. Additional sensitivity analyses were performed. In conclusion, present meta-analysis suggested a beneficial overall effect of omega-3 PUFA supplementation in MDD patients, especially for higher doses of EPA and in participants taking antidepressants. Future precision medicine trials should establish whether possible interactions between EPA and antidepressants could provide targets to improve antidepressant response and its prediction. Furthermore, potential long-term biochemical side effects of high-dosed add-on EPA supplementation should be carefully monitored.

Effect of vitamin B supplementation on cancer incidence, death due to cancer, and total mortality: A PRISMA-compliant cumulative meta-analysis of randomized controlled trials.

PubMed

Zhang, Sui-Liang; Chen, Ting-Song; Ma, Chen-Yun; Meng, Yong-Bin; Zhang, Yu-Fei; Chen, Yi-Wei; Zhou, Yu-Hao

2016-08-01

Observational studies have suggested that vitamin B supplementation is associated with cancer risk, but this association remains controversial. A pooled data-based meta-analysis was conducted to summarize the evidence from randomized controlled trials (RCTs) investigating the effects of vitamin B supplementation on cancer incidence, death due to cancer, and total mortality. PubMed, EmBase, and the Cochrane Library databases were searched to identify trials to fit our analysis through August 2015. Relative risk (RR) was used to measure the effect of vitamin B supplementation on the risk of cancer incidence, death due to cancer, and total mortality using a random-effect model. Cumulative meta-analysis, sensitivity analysis, subgroup analysis, heterogeneity tests, and tests for publication bias were also conducted. Eighteen RCTs reporting the data on 74,498 individuals were included in the meta-analysis. Sixteen of these trials included 4103 cases of cancer; in 6 trials, 731 cancer-related deaths occurred; and in 15 trials, 7046 deaths occurred. Vitamin B supplementation had little or no effect on the incidence of cancer (RR: 1.04; 95% confidence interval [CI]: 0.98-1.10; P = 0.216), death due to cancer (RR, 1.05; 95% CI: 0.90-1.22; P = 0.521), and total mortality (RR, 1.00; 95% CI: 0.94-1.06; P = 0.952). Upon performing a cumulative meta-analysis for cancer incidence, death due to cancer, and total mortality, the nonsignificance of the effect of vitamin B persisted. With respect to specific types of cancer, vitamin B supplementation significantly reduced the risk of skin melanoma (RR, 0.47; 95% CI: 0.23-0.94; P = 0.032). Vitamin B supplementation does not have an effect on cancer incidence, death due to cancer, or total mortality. It is associated with a lower risk of skin melanoma, but has no effect on other cancers.

Eliciting mixed emotions: a meta-analysis comparing models, types, and measures

PubMed Central

Berrios, Raul; Totterdell, Peter; Kellett, Stephen

2015-01-01

The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model—dimensional or discrete—as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative). The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (dIG+ = 0.77), which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects) resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought. PMID:25926805

Effect of Probiotics on Depression: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

PubMed Central

Huang, Ruixue; Wang, Ke; Hu, Jianan

2016-01-01

It has been reported that gut probiotics play a major role in the bidirectional communication between the gut and the brain. Probiotics may be essential to people with depression, which remains a global health challenge, as depression is a metabolic brain disorder. However, the efficacy of probiotics for depression is controversial. This study aimed to systematically review the existing evidence on the effect of probiotics-based interventions on depression. Randomized, controlled trials, identified through screening multiple databases and grey literature, were included in the meta-analysis. The meta-analysis was performed using Review Manager 5.3 software using a fixed-effects model. The meta-analysis showed that probiotics significantly decreased the depression scale score (MD (depressive disorder) = −0.30, 95% CI (−0.51–−0.09), p = 0.005) in the subjects. Probiotics had an effect on both the healthy population (MD = −0.25, 95% CI (−0.47–−0.03), p = 0.03) and patients with major depressive disorder (MDD) (MD = −0.73, 95% CI (−1.37–−0.09), p = 0.03). Probiotics had an effect on the population aged under 60 (MD = −0.43, 95% CI (−0.72–−0.13), p = 0.005), while it had no effect on people aged over 65 (MD = −0.18, 95% CI (−0.47–0.11), p = 0.22). This is the first systematic review and meta-analysis with the goal of determining the effect of probiotics on depression. We found that probiotics were associated with a significant reduction in depression, underscoring the need for additional research on this potential preventive strategy for depression. PMID:27509521

Methylenetetrahydrofolate reductase polymorphism C677T is a protective factor for pediatric acute lymphoblastic leukemia in the Chinese population: a meta-analysis.

PubMed

Wang, Haigang; Meng, Lujing; Zhao, Lixia; Wang, Jiali; Liu, Xinchun; Mi, Wenjie

2012-12-01

Two polymorphisms in the methylenetetrahydrofolate reductase (MTHFR) gene, C677T and A1298C, were hypothesized to decrease the risk of acute lymphoblastic leukemia (ALL). Studies examining the associations between these two polymorphisms and ALL susceptibility drew inconsistent results. To obtain a reliable conclusion in a Chinese population, we carried out a meta-analysis. In total, 11 studies on C677T polymorphism (1597 cases and 2295 controls) and 10 studies on A1298C polymorphism (1553 cases and 2224 controls) were included in the meta-analysis. We found a significant association between the 677T variant and reduced ALL risk in Chinese children (Dominant model: odds ratio [OR(FE)]=0.73, 95% confidence interval [CI]: 0.63-0.86, p<0.01). Heterogeneity between the studies in the children subgroup was weak and vanished after excluding one study deviating from HWE in the control group (p>0.1). In the adult subgroup, there was no significant association between the C677T variant and ALL risk (Dominant model: OR(RE)=0.88, 95% CI: 0.45-1.72, p=0.72). Significant heterogeneity was found in the adult subgroup in all the genetic model tests (p<0.1). The A1298C polymorphism had an effect on ALL risk neither in adults (Dominant model: OR(FE)=0.95, 95% CI: 0.71-1.27, p=0.72) nor in children (Dominant model: OR(FE)=1.02, 95% CI: 0.87-1.21, p=0.77). No significant heterogeneity between studies on A1298C polymorphism was found in the meta-analysis (p>0.1). The results showed that there was a protective effect of the MTHFR C677T variant on ALL risk in Chinese children.

Effects of Expository Text Structure Interventions on Comprehension: A Meta-Analysis

ERIC Educational Resources Information Center

Pyle, Nicole; Vasquez, Ariana C.; Lignugaris/Kraft, Benjamin; Gillam, Sandra L.; Reutzel, D. Ray; Olszewski, Abbie; Segura, Hugo; Hartzheim, Daphne; Laing, Woodrow; Pyle, Daniel

2017-01-01

This meta-analysis synthesizes results from expository text structure interventions designed to increase comprehension for students in kindergarten to grade 12 published between 1970 and 2013. Twenty-one studies were identified, 19 of which met criteria for a meta-analysis, including 48 studywise effect sizes that were meta-analyzed to determine…

Association of Catechol-O-methyltransferase polymorphism Val158Met and mammographic density: A meta-analysis.

PubMed

Kallionpää, Roope A; Uusitalo, Elina; Peltonen, Juha

2017-08-15

The Val158Met polymorphism in catechol-O-methyltransferase (COMT) enzyme reduces the methylation of catechol estrogens, which may affect mammographic density. High mammographic density is a known risk factor of breast cancer. Our aim was to perform meta-analysis of the effect of COMT Val158Met polymorphism on mammographic density. Original studies reporting data on mammographic density, stratified by the presence of COMT Val158Met polymorphism, were identified and combined using genetic models Met/Val vs. Val/Val, Met/Met vs. Val/Val, Val/Met+Met/Met vs. Val/Val (dominant model) and Met/Met vs. Val/Met+Val/Val (recessive model). Subgroup analyses by breast cancer status, menopausal status and use of hormone replacement therapy (HRT) were also performed. Eight studies were included in the meta-analysis. The overall effect in percent mammographic density was -1.41 (CI -2.86 to 0.05; P=0.06) in the recessive model. Exclusion of breast cancer patients increased the effect size to -1.93 (CI -3.49 to -0.37; P=0.02). The results suggested opposite effect of COMT Val158Met for postmenopausal users of HRT versus premenopausal women or postmenopausal non-users of HRT. COMT Val158Met polymorphism may be associated with mammographic density at least in healthy women. Menopausal status and HRT should be taken into account in future studies to avoid masking of the underlying effects. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of Instructional Decisions on the Effectiveness of Cooperative Learning in Chemistry through Meta-Analysis

ERIC Educational Resources Information Center

Apugliese, Andrew; Lewis, Scott E.

2017-01-01

Meta-analysis can provide a robust description of the impact of educational reforms and also offer an opportunity to explore the conditions where such reforms are more or less effective. This article describes a meta-analysis on the impact of cooperative learning on students' chemistry understanding. Modifiers in the meta-analysis are purposefully…

Factors Related to Instructional Leadership Perception and Effect of Instructional Leadership on Organizational Variables: A Meta-Analysis

ERIC Educational Resources Information Center

Sisman, Mehmet

2016-01-01

In this meta-analysis, effects of teacher characteristics on instructional leadership perceptions and some organizational variables is tested. Findings of the total of 67 independent studies are gathered in the meta-analysis which represents a population of 36,756. According to the findings of this meta-analysis performed by using random effects…

Multidrug resistance 1 (MDR1/ABCB1) gene polymorphism (rs1045642 C > T) and susceptibility to multiple myeloma: a systematic review and meta-analysis.

PubMed

Razi, Bahman; Anani Sarab, Gholamreza; Omidkhoda, Azadeh; Alizadeh, Shahab

2018-03-01

Several studies have evaluated the association between the multidrug resistance 1 (MDR1) polymorphism (rs1045642 C > T) and multiple myeloma (MM). However, the results were not consistent. Therefore, to reach a comprehensive and reliable answer we determined the association of the MDR1 (rs1045642 C > T) polymorphism and MM in the context of meta-analysis. All eligible studies published in EMBASE, PubMed, and Web of Science databases before July 2017 were reviewed. Subsequently, to assess the strength of association in the dominant model, recessive model, allelic model, homozygotes contrast, and heterozygotes contrast, pooled odds ratios and 95% confidence intervals (CIs) were calculated by the fixed effects model. A total of four case-control studies with 395 MM cases and 418 healthy controls were included in the meta-analysis. The overall results showed no significant association between the MDR1 (rs1045642 C > T) polymorphism and the risk of MM in genetic models (dominant model: OR = 1.04, 95% CI = 0.78-1.38; recessive model: OR = 0.74, 95% CI = 0.52-1.06; allelic model: OR = 0.90, 95% CI = 0.73-1.11; TT vs. CC: OR = 0.80, 95% CI = 0.51-1.25; and CT vs. CC: OR = 1.12, 95% CI = 0.77-1.62). No evidence of publication bias was detected except for the analysis of the recessive model. This meta-analysis suggests that the MDR1 C > T polymorphism was not associated with the risk of MM. To confirm these findings, further comprehensive and well-designed studies are needed.

Prevalence of binge and loss of control eating among children and adolescents with overweight and obesity: An exploratory meta-analysis.

PubMed

He, Jinbo; Cai, Zhihui; Fan, Xitao

2017-02-01

Due to the inconsistency of the research findings in the current literature, the prevalence of binge and loss of control (LOC) eating among children and adolescents with overweight and obesity remains unclear. By using the meta-analytic approach, this article aimed at exploring the prevalence of binge/LOC eating among children and adolescents with overweight and obesity, and at identifying potential moderators, which may have contributed to the heterogeneity of the existing research findings. Four electronic databases (PubMed, Web of Science, EBSCOhost, and ProQuest Dissertations & Theses Global) were searched. The search period covered the research literature up to April 2016. A random-effects meta-analysis model was used to estimate the overall prevalence. Weighted random-effects model ANOVAs and univariate random-effects meta-regression were applied for the analysis of categorical moderators and continuous moderators, respectively. Thirty-six studies were identified. The overall prevalence of binge/LOC eating was estimated to be 26.3% (95% CI: 23.1-29.7%), with 22.2% (95% CI: 18.6-26.3%) and 31.2% (95% CI: 26.1-36.9%) for binge eating and LOC eating, respectively. Treatment status, binge eating vs. LOC eating and assessment methods appeared to be associated with the inconsistencies of the prevalence rates across the studies. The findings of this meta-analysis indicated that binge/LOC eating was prevalent among more than one quarter of children and adolescents with overweight and obesity. Considering the close relationship between disordered eating behaviors and obesity, future research concerning overweight and obesity among children and adolescents needs to take binge/LOC eating into consideration. © 2016 Wiley Periodicals, Inc.(Int J Eat Disord 2017; 50:91-103). © 2016 Wiley Periodicals, Inc.

Prevalence of hyperphagia in Alzheimer's disease: a meta-analysis.

PubMed

Shea, Yat-Fung; Lee, Shui-Ching; Chu, Leung-Wing

2018-02-06

Unlike other behavioural and psychological symptoms of dementia, hyperphagia is less recognized among patients with Alzheimer's disease (AD). The prevalence of hyperphagia varies among studies, but there has been no systematic review or meta-analysis. An extensive search on the literature on hyperphagia in AD published between 1 January 1980 and 30 October 2017 was conducted. Data on the prevalence were retrieved. Meta-analysis with a random effect model was performed to determine the pooled estimate of prevalence. Meta-regression analysis was performed based on study characteristics, population demographics, or condition information. Results from 20 studies were extracted. Twenty-six reported cases of hyperphagia were identified. The mean age of onset was 70.7 ± 8.9 years, with a male predominance (68.4%). Hyperphagia occurred in all stages of AD. Only eight studies reported the prevalence of hyperphagia. Meta-analysis showed a pooled prevalence of hyperphagia of 18.6%. Publication bias may have been present. Meta-regression showed that ethnicity accounted for the variance among studies (coefficient: -1.247 (95% confidence interval: -1.978 to -0.516), R 2 analogue: 0.77, P < 0.001). Hyperphagia occurs in all stages of AD. In this meta-analysis of eight published studies, the prevalence of hyperphagia was 18.6%. In view of the possible publication bias, a large-scale study on hyperphagia is recommended in the future. © 2018 Japanese Psychogeriatric Society.

The Effects of Synchronous and Asynchronous Distance Education: A Meta-Analytical Assessment of Simonson's "Equivalency Theory"

ERIC Educational Resources Information Center

Bernard, Robert M.; Abrami, Philip C.; Wade, Anne; Borokhovski, Evgueni; Lou, Yiping

2004-01-01

Simonson, Schlosser and Hanson (1999) argue that a new theory called "equivalency theory" is needed to account for the unique features of the "teleconferencing" (synchronous) model of DE that is prevalent in many North American universities. Based on a comprehensive meta-analysis of the comparative literature of DE (Bernard,…

Evaluating the Quality of Evidence from a Network Meta-Analysis

PubMed Central

Salanti, Georgia; Del Giovane, Cinzia; Chaimani, Anna; Caldwell, Deborah M.; Higgins, Julian P. T.

2014-01-01

Systematic reviews that collate data about the relative effects of multiple interventions via network meta-analysis are highly informative for decision-making purposes. A network meta-analysis provides two types of findings for a specific outcome: the relative treatment effect for all pairwise comparisons, and a ranking of the treatments. It is important to consider the confidence with which these two types of results can enable clinicians, policy makers and patients to make informed decisions. We propose an approach to determining confidence in the output of a network meta-analysis. Our proposed approach is based on methodology developed by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group for pairwise meta-analyses. The suggested framework for evaluating a network meta-analysis acknowledges (i) the key role of indirect comparisons (ii) the contributions of each piece of direct evidence to the network meta-analysis estimates of effect size; (iii) the importance of the transitivity assumption to the validity of network meta-analysis; and (iv) the possibility of disagreement between direct evidence and indirect evidence. We apply our proposed strategy to a systematic review comparing topical antibiotics without steroids for chronically discharging ears with underlying eardrum perforations. The proposed framework can be used to determine confidence in the results from a network meta-analysis. Judgements about evidence from a network meta-analysis can be different from those made about evidence from pairwise meta-analyses. PMID:24992266

Depression and risk of fracture and bone loss: an updated meta-analysis of prospective studies.

PubMed

Wu, Q; Liu, B; Tonmoy, S

2018-03-12

This meta-analysis pooled results from 23 qualifying individual cohort studies and found that depression was significantly associated with an increased risk of fractures and bone loss. The association between depression and risk of fracture remains controversial. We conducted a comprehensive meta-analysis to examine the effect of depression on the risk of osteoporotic fractures and bone loss. We searched databases and reviewed citations in relevant articles for eligible cohort studies. Two investigators independently conducted study selection, appraisal, and data abstraction through the use of a standardized protocol. Random effect models were used for meta-analysis. Cochrane Q and I 2 statistics were used to assess heterogeneity. Funnel plots and rank correlation tests were used to evaluate publication bias. Twenty-three studies were included for meta-analysis. In studies that reported hazard ratio (HR) as the outcome (nine studies [n = 309,862]), depression was associated with 26% increase in fracture risk (HR = 1.26, 95% CI, 1.10-1.43, p < 0.001). Studies that reported risk ratio (RR) as the outcome (seven studies [n = 64,975]) suggested that depression was associated with 39% increase in fracture risk (RR = 1.39, 95% CI, 1.19-1.62, p < 0.001). Among studies that reported hip bone mineral density (BMD) as an outcome (eight studies [n = 15,442]), depression was associated with a reduced mean annual bone loss rate of 0.35% (0.18-0.53%, p < 0.001). The increased risk of fracture and bone loss associated with depression was consistent in all meta-analysis having modified inclusion criteria and in different subgroup analyses as well. Significant heterogeneity was observed in the meta-analysis; however, no significant publication bias was detected. Depression is associated with a significant increased risk in fracture and bone loss. Effective prevention may decrease such risk.

Network meta-analysis of lorcaserin and oral hypoglycaemics for patients with type 2 diabetes mellitus and obesity.

PubMed

Neff, L M; Broder, M S; Beenhouwer, D; Chang, E; Papoyan, E; Wang, Z W

2017-12-01

In addition to weight loss, randomized controlled trials have shown improvement in glycaemic control in patients taking lorcaserin. The aim of this study aim was to compare adding lorcaserin or other glucose lowering medications to metformin on weight and glycaemic control. A systematic review and network meta-analysis of randomized controlled trials were conducted. Included studies (published 1990-2014) were of lorcaserin or glucose lowering medications in type 2 diabetic patients compared to placebo or different active treatments. Studies had to report ≥1 key outcome (change in weight or HbA1c, % HbA1c <7, hypoglycaemia). Direct meta-analysis was performed using DerSimonian and Laird random effects models, and network meta-analysis with Bayesian Markov-chain Monte Carlo random effects models; 6552 articles were screened and 41 included. Lorcaserin reduced weight significantly more than thiazolidinediones, glinides, sulphonylureas and dipeptidyl peptidase-4 inhibitors, some of which may have led to weight gain. There were no significant differences in weight change between lorcaserin and alpha-glucoside inhibitors, glucagon-like peptide-1 agonists and sodium/glucose cotransporter 2 inhibitors. Network meta-analysis showed lorcaserin was non-inferior to all other agents on HbA1c reduction and % achieving HbA1c of <7%. The risk of hypoglycaemia was not significantly different among studied agents except that sulphonylureas were associated with higher risk of hypoglycaemia than lorcaserin. Although additional studies are needed, this analysis suggests in a population of patients with a body mas index of ≥27 who do not achieve glycaemic control on a single agent, lorcaserin may be added as an alternative to an add-on glucose lowering medication. © 2017 World Obesity Federation.

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the sample size is relatively small, we recommend the use of the robust method under the working independence assumption. We illustrate the proposed method through 2 meta-analyses. Copyright © 2017 John Wiley & Sons, Ltd.

Predictors of persistent pain after total knee arthroplasty: a systematic review and meta-analysis.

PubMed

Lewis, G N; Rice, D A; McNair, P J; Kluger, M

2015-04-01

Several studies have identified clinical, psychosocial, patient characteristic, and perioperative variables that are associated with persistent postsurgical pain; however, the relative effect of these variables has yet to be quantified. The aim of the study was to provide a systematic review and meta-analysis of predictor variables associated with persistent pain after total knee arthroplasty (TKA). Included studies were required to measure predictor variables prior to or at the time of surgery, include a pain outcome measure at least 3 months post-TKA, and include a statistical analysis of the effect of the predictor variable(s) on the outcome measure. Counts were undertaken of the number of times each predictor was analysed and the number of times it was found to have a significant relationship with persistent pain. Separate meta-analyses were performed to determine the effect size of each predictor on persistent pain. Outcomes from studies implementing uni- and multivariable statistical models were analysed separately. Thirty-two studies involving almost 30 000 patients were included in the review. Preoperative pain was the predictor that most commonly demonstrated a significant relationship with persistent pain across uni- and multivariable analyses. In the meta-analyses of data from univariate models, the largest effect sizes were found for: other pain sites, catastrophizing, and depression. For data from multivariate models, significant effects were evident for: catastrophizing, preoperative pain, mental health, and comorbidities. Catastrophizing, mental health, preoperative knee pain, and pain at other sites are the strongest independent predictors of persistent pain after TKA. © The Author 2014. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Empirical evidence about inconsistency among studies in a pair-wise meta-analysis.

PubMed

Rhodes, Kirsty M; Turner, Rebecca M; Higgins, Julian P T

2016-12-01

This paper investigates how inconsistency (as measured by the I 2 statistic) among studies in a meta-analysis may differ, according to the type of outcome data and effect measure. We used hierarchical models to analyse data from 3873 binary, 5132 continuous and 880 mixed outcome meta-analyses within the Cochrane Database of Systematic Reviews. Predictive distributions for inconsistency expected in future meta-analyses were obtained, which can inform priors for between-study variance. Inconsistency estimates were highest on average for binary outcome meta-analyses of risk differences and continuous outcome meta-analyses. For a planned binary outcome meta-analysis in a general research setting, the predictive distribution for inconsistency among log odds ratios had median 22% and 95% CI: 12% to 39%. For a continuous outcome meta-analysis, the predictive distribution for inconsistency among standardized mean differences had median 40% and 95% CI: 15% to 73%. Levels of inconsistency were similar for binary data measured by log odds ratios and log relative risks. Fitted distributions for inconsistency expected in continuous outcome meta-analyses using mean differences were almost identical to those using standardized mean differences. The empirical evidence on inconsistency gives guidance on which outcome measures are most likely to be consistent in particular circumstances and facilitates Bayesian meta-analysis with an informative prior for heterogeneity. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

A Systematic Review and Quantitative Meta-Analysis of Oxytocin's Effects on Feeding.

PubMed

Leslie, Monica; Silva, Paulo; Paloyelis, Yannis; Blevins, James; Treasure, Janet

2018-02-26

Oxytocin's anorexigenic effects have been widely documented and accepted; however, no paper has yet used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to compile previous findings in a single systematic review and quantitative meta-analysis. The current paper aimed to identify published and unpublished studies examining the effects of oxytocin on energy intake in animals and humans, and the factors that moderate this effect. Web of Science, Pub Med, and Ovid were searched for published and unpublished studies reporting the effects of oxytocin on energy intake in wild-type animals and in humans, when administered in the absence of other active drugs or surgery. 2049 articles were identified through the original systematic literature search, from which 54 articles were identified as relevant for inclusion in this review. An additional 3 relevant articles were identified in a later update of the literature search. Overall, a single-dose of oxytocin was found to reduce feeding in animals. Despite several individual studies which found that this effect persists to the end of the third week of chronic administration in rodent models, overall, this anorexigenic effect did not hold in the meta-analyses testing the effects of chronic administration. There was no overall effect of oxytocin on energy intake in humans, although a trend was identified for oxytocin to reduce consumption of solid foods. Oxytocin reduces energy intake when administered as a single dose. Oxytocin can inhibit feeding over two- to three-week periods in rodent models. These effects typically do not persist beyond the third week of treatment. The anorexigenic effect of oxytocin is moderated by pregnant status, dose, method of administration, and diet composition. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Valuation of National Park System Visitation: The Efficient Use of Count Data Models, Meta-Analysis, and Secondary Visitor Survey Data

NASA Astrophysics Data System (ADS)

Neher, Christopher; Duffield, John; Patterson, David

2013-09-01

The National Park Service (NPS) currently manages a large and diverse system of park units nationwide which received an estimated 279 million recreational visits in 2011. This article uses park visitor data collected by the NPS Visitor Services Project to estimate a consistent set of count data travel cost models of park visitor willingness to pay (WTP). Models were estimated using 58 different park unit survey datasets. WTP estimates for these 58 park surveys were used within a meta-regression analysis model to predict average and total WTP for NPS recreational visitation system-wide. Estimated WTP per NPS visit in 2011 averaged 102 system-wide, and ranged across park units from 67 to 288. Total 2011 visitor WTP for the NPS system is estimated at 28.5 billion with a 95% confidence interval of 19.7-43.1 billion. The estimation of a meta-regression model using consistently collected data and identical specification of visitor WTP models greatly reduces problems common to meta-regression models, including sample selection bias, primary data heterogeneity, and heteroskedasticity, as well as some aspects of panel effects. The article provides the first estimate of total annual NPS visitor WTP within the literature directly based on NPS visitor survey data.

A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification.

PubMed

Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang

2017-08-23

Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.

Protocol of GLUcose COntrol Safety and Efficacy in type 2 DIabetes, a NETwork meta-analysis: GLUCOSE DINET protocol-Rational and design.

PubMed

Grenet, Guillaume; Lajoinie, Audrey; Ribault, Shams; Nguyen, Gia Bao; Linet, Thomas; Metge, Augustin; Cornu, Catherine; Cucherat, Michel; Moulin, Philippe; Gueyffier, François

2017-06-01

The aim of this study was to propose a ranking of the currently available antidiabetic drugs, regarding vascular clinical outcomes, in patients with type 2 diabetes, through a network meta-analysis approach. Randomized clinical trials, regardless of the blinding design, testing contemporary antidiabetic drugs, and considering clinically relevant outcomes in patients with type 2 diabetes mellitus will be included. The primary outcomes of this analysis will be overall mortality, cardiovascular mortality, and major cardiovascular events. Diabetic microangiopathy will be a secondary outcome. Adverse events, hypoglycemia, weight evolution, bariatric surgery, and discontinuation of the treatment will also be recorded. Each drug will be analyzed according to its therapeutic class: biguanide, alpha-glucosidase inhibitors, sulfonylureas, glitazones, glinides, insulin, DPP-4 inhibitors, GLP-1 analogs, and gliflozins. The treatment effect of each drug class will be compared using pairwise meta-analysis and a Bayesian random model network meta-analysis. Sensitivity analyses will be conducted according to the quality of the studies and the glycemic control. The report will follow the PRISMA checklist for network meta-analysis. Results of the search strategy and of the study selection will be presented in a PRISMA compliant flowchart. The treatment effects will be summarized with odds ratio (OR) estimates and their 95% credible intervals. A ranking of the drugs will be proposed. Our network meta-analysis should allow a clinically relevant ranking of the contemporary antidiabetic drugs. © 2016 Société Française de Pharmacologie et de Thérapeutique.

Impact of including or excluding both-armed zero-event studies on using standard meta-analysis methods for rare event outcome: a simulation study

PubMed Central

Cheng, Ji; Pullenayegum, Eleanor; Marshall, John K; Thabane, Lehana

2016-01-01

Objectives There is no consensus on whether studies with no observed events in the treatment and control arms, the so-called both-armed zero-event studies, should be included in a meta-analysis of randomised controlled trials (RCTs). Current analytic approaches handled them differently depending on the choice of effect measures and authors' discretion. Our objective is to evaluate the impact of including or excluding both-armed zero-event (BA0E) studies in meta-analysis of RCTs with rare outcome events through a simulation study. Method We simulated 2500 data sets for different scenarios varying the parameters of baseline event rate, treatment effect and number of patients in each trial, and between-study variance. We evaluated the performance of commonly used pooling methods in classical meta-analysis—namely, Peto, Mantel-Haenszel with fixed-effects and random-effects models, and inverse variance method with fixed-effects and random-effects models—using bias, root mean square error, length of 95% CI and coverage. Results The overall performance of the approaches of including or excluding BA0E studies in meta-analysis varied according to the magnitude of true treatment effect. Including BA0E studies introduced very little bias, decreased mean square error, narrowed the 95% CI and increased the coverage when no true treatment effect existed. However, when a true treatment effect existed, the estimates from the approach of excluding BA0E studies led to smaller bias than including them. Among all evaluated methods, the Peto method excluding BA0E studies gave the least biased results when a true treatment effect existed. Conclusions We recommend including BA0E studies when treatment effects are unlikely, but excluding them when there is a decisive treatment effect. Providing results of including and excluding BA0E studies to assess the robustness of the pooled estimated effect is a sensible way to communicate the results of a meta-analysis when the treatment effects are unclear. PMID:27531725

Predicted effect size of lisdexamfetamine treatment of attention deficit/hyperactivity disorder (ADHD) in European adults: Estimates based on indirect analysis using a systematic review and meta-regression analysis.

PubMed

Fridman, M; Hodgkins, P S; Kahle, J S; Erder, M H

2015-06-01

There are few approved therapies for adults with attention-deficit/hyperactivity disorder (ADHD) in Europe. Lisdexamfetamine (LDX) is an effective treatment for ADHD; however, no clinical trials examining the efficacy of LDX specifically in European adults have been conducted. Therefore, to estimate the efficacy of LDX in European adults we performed a meta-regression of existing clinical data. A systematic review identified US- and Europe-based randomized efficacy trials of LDX, atomoxetine (ATX), or osmotic-release oral system methylphenidate (OROS-MPH) in children/adolescents and adults. A meta-regression model was then fitted to the published/calculated effect sizes (Cohen's d) using medication, geographical location, and age group as predictors. The LDX effect size in European adults was extrapolated from the fitted model. Sensitivity analyses performed included using adult-only studies and adding studies with placebo designs other than a standard pill-placebo design. Twenty-two of 2832 identified articles met inclusion criteria. The model-estimated effect size of LDX for European adults was 1.070 (95% confidence interval: 0.738, 1.401), larger than the 0.8 threshold for large effect sizes. The overall model fit was adequate (80%) and stable in the sensitivity analyses. This model predicts that LDX may have a large treatment effect size in European adults with ADHD. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Quantifying the dose-response relationship between circulating folate concentrations and colorectal cancer in cohort studies: a meta-analysis based on a flexible meta-regression model.

PubMed

Chuang, Shu-Chun; Rota, Matteo; Gunter, Marc J; Zeleniuch-Jacquotte, Anne; Eussen, Simone J P M; Vollset, Stein Emil; Ueland, Per Magne; Norat, Teresa; Ziegler, Regina G; Vineis, Paolo

2013-10-01

Most epidemiologic studies on folate intake suggest that folate may be protective against colorectal cancer, but the results on circulating (plasma or serum) folate are mostly inconclusive. We conducted a meta-analysis of case-control studies nested within prospective studies on circulating folate and colorectal cancer risk by using flexible meta-regression models to test the linear and nonlinear dose-response relationships. A total of 8 publications (10 cohorts, representing 3,477 cases and 7,039 controls) were included in the meta-analysis. The linear and nonlinear models corresponded to relative risks of 0.96 (95% confidence interval (CI): 0.91, 1.02) and 0.99 (95% CI: 0.96, 1.02), respectively, per 10 nmol/L of circulating folate in contrast to the reference value. The pooled relative risks when comparing the highest with the lowest category were 0.80 (95% CI: 0.61, 0.99) for radioimmunoassay and 1.03 (95% CI: 0.83, 1.22) for microbiological assay. Overall, our analyses suggest a null association between circulating folate and colorectal cancer risk. The stronger association for the radioimmunoassay-based studies could reflect differences in cohorts and study designs rather than assay performance. Further investigations need to integrate more accurate measurements and flexible modeling to explore the effects of folate in the presence of genetic, lifestyle, dietary, and hormone-related factors.

Social Cognitive Predictors of College Students' Academic Performance and Persistence: A Meta-Analytic Path Analysis

ERIC Educational Resources Information Center

Brown, Steven D.; Tramayne, Selena; Hoxha, Denada; Telander, Kyle; Fan, Xiaoyan; Lent, Robert W.

2008-01-01

This study tested Social Cognitive Career Theory's (SCCT) academic performance model using a two-stage approach that combined meta-analytic and structural equation modeling methodologies. Unbiased correlations obtained from a previously published meta-analysis [Robbins, S. B., Lauver, K., Le, H., Davis, D., & Langley, R. (2004). Do psychosocial…

Meta-analysis of the effect of road safety campaigns on accidents.

PubMed

Phillips, Ross Owen; Ulleberg, Pål; Vaa, Truls

2011-05-01

A meta-analysis of 67 studies evaluating the effect of road safety campaigns on accidents is reported. A total of 119 results were extracted from the studies, which were reported in 12 different countries between 1975 and 2007. After allowing for publication bias and heterogeneity of effects, the weighted average effect of road safety campaigns is a 9% reduction in accidents (with 95% confidence that the weighted average is between -12 and -6%). To account for the variability of effects measured across studies, data were collected to characterise aspects of the campaign and evaluation design associated with each effect, and analysed to identify a model of seven campaign factors for testing by meta-regression. The model was tested using both fixed and random effect meta-regression, and dependency among effects was accounted for by aggregation. These analyses suggest positive associations between accident reduction and the use of personal communication or roadside media as part of a campaign delivery strategy. Campaigns with a drink-driving theme were also associated with greater accident reductions, while some of the analyses suggested that accompanying enforcement and short campaign duration (less than one month) are beneficial. Overall the results are consistent with the idea that campaigns can be more effective in the short term if the message is delivered with personal communication in a way that is proximal in space and time to the behaviour targeted by the campaign. Copyright © 2011 Elsevier Ltd. All rights reserved.

The efficacy of chimeric antigen receptor (CAR) immunotherapy in animal models for solid tumors: A systematic review and meta-analysis.

PubMed

Wu, Yingcheng; Xu, Ran; Jia, Keren; Shi, Hui

2017-01-01

Most recently, an emerging theme in the field of tumor immunology predominates: chimeric antigen receptor (CAR) therapy in treating solid tumors. The number of related preclinical trials was surging. However, an evaluation of the effects of preclinical studies remained absent. Hence, a meta-analysis was conducted on the efficacy of CAR in animal models for solid tumors. The authors searched PubMed/Medline, Embase, and Google scholar up to April 2017. HR for survival was extracted based on the survival curve. The authors used fixed effect models to combine the results of all the trials. Heterogeneity was assessed by I-square statistic. Quality assessment was conducted following the Stroke Therapy Academic Industry Roundtable standard. Publication bias was assessed using Egger's test. Eleven trials were included, including 54 experiments with a total of 362 animals involved. CAR immunotherapy significantly improved the survival of animals (HR: 0.25, 95% CI: 0.13-0.37, P < 0.001). The quality assessment revealed that no study reported whether allocation concealment and blinded outcome assessment were conducted, and only five studies implemented randomization. This meta-analysis indicated that CAR therapy may be a potential clinical strategy in treating solid tumors.

The Impact of Aortic Occlusion Balloon on Mortality After Endovascular Repair of Ruptured Abdominal Aortic Aneurysms: A Meta-analysis and Meta-regression Analysis.

PubMed

Karkos, Christos D; Papadimitriou, Christina T; Chatzivasileiadis, Theodoros N; Kapsali, Nikoletta S; Kalogirou, Thomas E; Giagtzidis, Ioakeim T; Papazoglou, Konstantinos O

2015-12-01

We aimed to investigate whether the use of aortic occlusion balloon (AOB) has an impact on mortality of patients undergoing endovascular repair of ruptured abdominal aortic aneurysms (RAAAs). A meta-analysis of the English-language literature was undertaken through February 2013. Articles reporting data on outcome after endovascular repair of RAAAs were identified and information regarding the use of AOB was sought. Included in this meta-analysis were 39 eligible studies reporting 1277 patients. The pooled perioperative mortality was 21.6% (95% CI 18.1-25.1%). There was significant within-study heterogeneity (I(2) 50.2%, P < 0.001). A total of 200 patients required AOB with an estimated pooled proportion of 14.1% (8.9-19.3%). Individual random-effects meta-regression investigating the effect of AOB and other risk factors on mortality revealed a significant linear association of hemodynamic instability, bifurcated endograft approach, and primary conversion to open repair with mortality and a nonlinear (second degree polynomial) association of AOB with mortality. On multivariable meta-regression models, both hemodynamic instability and AOB were found to be statistically significant, independent predictors of mortality. In particular, there was a statistically significant negative correlation between AOB and mortality and a positive effect of hemodynamic instability on mortality. In practical terms, mortality was significantly higher in studies with a higher proportion of hemodynamically unstable patients and lower in studies with a higher rate of AOB use. This study provides meta-analytical evidence that the use of an AOB in unstable RAAA patients undergoing endovascular repair may improve the results.

Effect of oral isoflavone supplementation on vascular endothelial function in postmenopausal women: a meta-analysis of randomized placebo-controlled trials.

PubMed

Li, Shao-Hua; Liu, Xu-Xia; Bai, Yong-Yi; Wang, Xiao-Jian; Sun, Kai; Chen, Jing-Zhou; Hui, Ru-Tai

2010-02-01

The effect of isoflavone on endothelial function in postmenopausal women is controversial. The objective of this study was to evaluate the effect of oral isoflavone supplementation on endothelial function, as measured by flow-mediated dilation (FMD), in postmenopausal women. A meta-analysis of randomized placebo-controlled trials was conducted to evaluate the effect of oral isoflavone supplementation on endothelial function in postmenopausal women. Trials were searched in PubMed, Embase, the Cochrane Library database, and reviews and reference lists of relevant articles. Summary estimates of weighted mean differences (WMDs) and 95% CIs were obtained by using random-effects models. Meta-regression and subgroup analyses were performed to identify the source of heterogeneity. A total of 9 trials were reviewed in the present meta-analysis. Overall, the results of the 9 trials showed that isoflavone significantly increased FMD (WMD: 1.75%; 95% CI: 0.83%, 2.67%; P = 0.0002). Meta-regression analysis indicated that the age-adjusted baseline FMD was inversely related to effect size. Subgroup analysis showed that oral supplementation of isoflavone had no influence on FMD if the age-adjusted baseline FMD was > or = 5.2% (4 trials; WMD: 0.24%; 95% CI: -0.94%, 1.42%; P = 0.69). This improvement seemed to be significant when the age-adjusted baseline FMD levels were <5.2% (5 trials; WMD: 2.22%; 95% CI: 1.15%, 3.30%; P < 0.0001), although significant heterogeneity was still detected in this low-baseline-FMD subgroup. Oral isoflavone supplementation does not improve endothelial function in postmenopausal women with high baseline FMD levels but leads to significant improvement in women with low baseline FMD levels.

Personal and psychosocial predictors of doping use in physical activity settings: a meta-analysis.

PubMed

Ntoumanis, Nikos; Ng, Johan Y Y; Barkoukis, Vassilis; Backhouse, Susan

2014-11-01

There is a growing body of empirical evidence on demographic and psychosocial predictors of doping intentions and behaviors utilizing a variety of variables and conceptual models. However, to date there has been no attempt to quantitatively synthesize the available evidence and identify the strongest predictors of doping. Using meta-analysis, we aimed to (i) determine effect sizes of psychological (e.g. attitudes) and social-contextual factors (e.g. social norms), and demographic (e.g. sex and age) variables on doping intentions and use; (ii) examine variables that moderate such effect sizes; and (iii) test a path analysis model, using the meta-analyzed effect sizes, based on variables from the theory of planned behavior (TPB). Articles were identified from online databases, by contacting experts in the field, and searching the World Anti-Doping Agency website. Studies that measured doping behaviors and/or doping intentions, and at least one other demographic, psychological, or social-contextual variable were included. We identified 63 independent datasets. Study information was extracted by using predefined data fields and taking into account study quality indicators. A random effects meta-analysis was carried out, correcting for sampling and measurement error, and identifying moderator variables. Path analysis was conducted on a subset of studies that utilized the TPB. Use of legal supplements, perceived social norms, and positive attitudes towards doping were the strongest positive correlates of doping intentions and behaviors. In contrast, morality and self-efficacy to refrain from doping had the strongest negative association with doping intentions and behaviors. Furthermore, path analysis suggested that attitudes, perceived norms, and self-efficacy to refrain from doping predicted intentions to dope and, indirectly, doping behaviors. Various meta-analyzed effect sizes were based on a small number of studies, which were correlational in nature. This is a limitation of the extant literature. This review identifies a number of important correlates of doping intention and behavior, many of which were measured via self-reports and were drawn from an extended TPB framework. Future research might benefit from embracing other conceptual models of doping behavior and adopting experimental methodologies that will test some of the identified correlates in an effort to develop targeted anti-doping policies and programs.

Dietary fiber intake reduces risk of inflammatory bowel disease: result from a meta-analysis.

PubMed

Liu, Xiaoqin; Wu, Yili; Li, Fang; Zhang, Dongfeng

2015-09-01

Several epidemiological investigations have been conducted to evaluate the relationship between dietary fiber intake and inflammatory bowel diseases, but the results are inconsistent. This meta-analysis was performed to quantitatively summarize the evidence from observational studies. PubMed, Embase, and Web of Knowledge were searched for relevant articles published up to November 2014. The combined relative risks were calculated with the fixed- or random-effects model. Dose-response relationship was assessed using restricted cubic spline model. We hypothesized that the meta-analysis could yield a summary effect, which would indicate that dietary fiber intake could decrease the risk of ulcerative colitis and Crohn disease (CD). Overall, 8 articles involving 2 cohort studies, 1 nested case-control study, and 5 case-control studies were finally included in this study. The pooled relative risks with 95% confidence intervals of ulcerative colitis and CD for the highest vs lowest categories of dietary fiber intake were 0.80 (0.64-1.00) and 0.44 (0.29-0.69), respectively. A linear dose-response relationship was found between dietary fiber and CD risk, and the risk of CD decreased by 13% (P < .05) for every 10 g/d increment in fiber intake. The results from this meta-analysis indicated that the intake of dietary fiber was significantly associated with a decreased risk of inflammatory bowel disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Polymorphisms of three genes (ACE, AGT and CYP11B2) in the renin-angiotensin-aldosterone system are not associated with blood pressure salt sensitivity: A systematic meta-analysis.

PubMed

Sun, Jiahong; Zhao, Min; Miao, Song; Xi, Bo

2016-01-01

Many studies have suggested that polymorphisms of three key genes (ACE, AGT and CYP11B2) in the renin-angiotensin-aldosterone system (RAAS) play important roles in the development of blood pressure (BP) salt sensitivity, but they have revealed inconsistent results. Thus, we performed a meta-analysis to clarify the association. PubMed and Embase databases were searched for eligible published articles. Fixed- or random-effect models were used to pool odds ratios and 95% confidence intervals based on whether there was significant heterogeneity between studies. In total, seven studies [237 salt-sensitive (SS) cases and 251 salt-resistant (SR) controls] for ACE gene I/D polymorphism, three studies (130 SS cases and 221 SR controls) for AGT gene M235T polymorphism and three studies (113 SS cases and 218 SR controls) for CYP11B2 gene C344T polymorphism were included in this meta-analysis. The results showed that there was no significant association between polymorphisms of these three polymorphisms in the RAAS and BP salt sensitivity under three genetic models (all p > 0.05). The meta-analysis suggested that three polymorphisms (ACE gene I/D, AGT gene M235T, CYP11B2 gene C344T) in the RAAS have no significant effect on BP salt sensitivity.

Hemihepatic versus total hepatic inflow occlusion during hepatectomy: a systematic review and meta-analysis.

PubMed

Wang, Hai-Qing; Yang, Jia-Yin; Yan, Lu-Nan

2011-07-14

To evaluate the clinical outcomes of patients undergoing hepatectomy with hemihepatic vascular occlusion (HHO) compared with total hepatic inflow occlusion (THO). Randomized controlled trials (RCTs) comparing hemihepatic vascular occlusion and total hepatic inflow occlusion were included by a systematic literature search. Two authors independently assessed the trials for inclusion and extracted the data. A meta-analysis was conducted to estimate blood loss, transfusion requirement, and liver injury based on the levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Either the fixed effects model or random effects model was used. Four RCTs including 338 patients met the predefined inclusion criteria. A total of 167 patients were treated with THO and 171 with HHO. Meta-analysis of AST levels on postoperative day 1 indicated higher levels in the THO group with weighted mean difference (WMD) 342.27; 95% confidence intervals (CI) 217.28-467.26; P = 0.00 001; I(2) = 16%. Meta-analysis showed no significant difference between THO group and HHO group on blood loss, transfusion requirement, mortality, morbidity, operating time, ischemic duration, hospital stay, ALT levels on postoperative day 1, 3 and 7 and AST levels on postoperative day 3 and 7. Hemihepatic vascular occlusion does not offer satisfying benefit to the patients undergoing hepatic resection. However, they have less liver injury after liver resections.

Hemihepatic versus total hepatic inflow occlusion during hepatectomy: A systematic review and meta-analysis

PubMed Central

Wang, Hai-Qing; Yang, Jia-Yin; Yan, Lu-Nan

2011-01-01

AIM: To evaluate the clinical outcomes of patients undergoing hepatectomy with hemihepatic vascular occlusion (HHO) compared with total hepatic inflow occlusion (THO). METHODS: Randomized controlled trials (RCTs) comparing hemihepatic vascular occlusion and total hepatic inflow occlusion were included by a systematic literature search. Two authors independently assessed the trials for inclusion and extracted the data. A meta-analysis was conducted to estimate blood loss, transfusion requirement, and liver injury based on the levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Either the fixed effects model or random effects model was used. RESULTS: Four RCTs including 338 patients met the predefined inclusion criteria. A total of 167 patients were treated with THO and 171 with HHO. Meta-analysis of AST levels on postoperative day 1 indicated higher levels in the THO group with weighted mean difference (WMD) 342.27; 95% confidence intervals (CI) 217.28-467.26; P = 0.00 001; I2 = 16%. Meta-analysis showed no significant difference between THO group and HHO group on blood loss, transfusion requirement, mortality, morbidity, operating time, ischemic duration, hospital stay, ALT levels on postoperative day 1, 3 and 7 and AST levels on postoperative day 3 and 7. CONCLUSION: Hemihepatic vascular occlusion does not offer satisfying benefit to the patients undergoing hepatic resection. However, they have less liver injury after liver resections. PMID:21912460

Statistical strategies for averaging EC50 from multiple dose-response experiments.

PubMed

Jiang, Xiaoqi; Kopp-Schneider, Annette

2015-11-01

In most dose-response studies, repeated experiments are conducted to determine the EC50 value for a chemical, requiring averaging EC50 estimates from a series of experiments. Two statistical strategies, the mixed-effect modeling and the meta-analysis approach, can be applied to estimate average behavior of EC50 values over all experiments by considering the variabilities within and among experiments. We investigated these two strategies in two common cases of multiple dose-response experiments in (a) complete and explicit dose-response relationships are observed in all experiments and in (b) only in a subset of experiments. In case (a), the meta-analysis strategy is a simple and robust method to average EC50 estimates. In case (b), all experimental data sets can be first screened using the dose-response screening plot, which allows visualization and comparison of multiple dose-response experimental results. As long as more than three experiments provide information about complete dose-response relationships, the experiments that cover incomplete relationships can be excluded from the meta-analysis strategy of averaging EC50 estimates. If there are only two experiments containing complete dose-response information, the mixed-effects model approach is suggested. We subsequently provided a web application for non-statisticians to implement the proposed meta-analysis strategy of averaging EC50 estimates from multiple dose-response experiments.

Multivariate meta-analysis for non-linear and other multi-parameter associations

PubMed Central

Gasparrini, A; Armstrong, B; Kenward, M G

2012-01-01

In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure–response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22807043

Meta-epidemiologic study showed frequent time trends in summary estimates from meta-analyses of diagnostic accuracy studies.

PubMed

Cohen, Jérémie F; Korevaar, Daniël A; Wang, Junfeng; Leeflang, Mariska M; Bossuyt, Patrick M

2016-09-01

To evaluate changes over time in summary estimates from meta-analyses of diagnostic accuracy studies. We included 48 meta-analyses from 35 MEDLINE-indexed systematic reviews published between September 2011 and January 2012 (743 diagnostic accuracy studies; 344,015 participants). Within each meta-analysis, we ranked studies by publication date. We applied random-effects cumulative meta-analysis to follow how summary estimates of sensitivity and specificity evolved over time. Time trends were assessed by fitting a weighted linear regression model of the summary accuracy estimate against rank of publication. The median of the 48 slopes was -0.02 (-0.08 to 0.03) for sensitivity and -0.01 (-0.03 to 0.03) for specificity. Twelve of 96 (12.5%) time trends in sensitivity or specificity were statistically significant. We found a significant time trend in at least one accuracy measure for 11 of the 48 (23%) meta-analyses. Time trends in summary estimates are relatively frequent in meta-analyses of diagnostic accuracy studies. Results from early meta-analyses of diagnostic accuracy studies should be considered with caution. Copyright © 2016 Elsevier Inc. All rights reserved.

Multivariate meta-analysis: a robust approach based on the theory of U-statistic.

PubMed

Ma, Yan; Mazumdar, Madhu

2011-10-30

Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.

MitiGate; an online meta-analysis database for quantification of mitigation strategies for enteric methane emissions.

PubMed

Veneman, Jolien B; Saetnan, Eli R; Clare, Amanda J; Newbold, Charles J

2016-12-01

The body of peer-reviewed papers on enteric methane mitigation strategies in ruminants is rapidly growing and allows for better estimation of the true effect of each strategy though the use of meta-analysis methods. Here we present the development of an online database of measured methane mitigation strategies called MitiGate, currently comprising 412 papers. The database is accessible through an online user-friendly interface that allows data extraction with various levels of aggregation on one hand and data-uploading for submission to the database allowing for future refinement and updates of mitigation estimates as well as providing easy access to relevant data for integration into modelling efforts or policy recommendations. To demonstrate and verify the usefulness of the MitiGate database those studies where methane emissions were expressed per unit of intake (293 papers resulting in 845 treatment comparisons) were used in a meta-analysis. The meta-analysis of the current database estimated the effect size of each of the mitigation strategies as well as the associated variance and measure of heterogeneity. Currently, under-representation of certain strategies, geographic regions and long term studies are the main limitations in providing an accurate quantitative estimation of the mitigation potential of each strategy under varying animal production systems. We have thus implemented the facility for researchers to upload meta-data of their peer reviewed research through a simple input form in the hope that MitiGate will grow into a fully inclusive resource for those wishing to model methane mitigation strategies in ruminants. Copyright © 2016 Elsevier B.V. All rights reserved.

Does patent foramen ovale closure have an anti-arrhythmic effect? A meta-analysis.

PubMed

Jarral, Omar A; Saso, Srdjan; Vecht, Joshua A; Harling, Leanne; Rao, Christopher; Ahmed, Kamran; Gatzoulis, Michael A; Malik, Iqbal S; Athanasiou, Thanos

2011-11-17

Atrial tachyarrhythmias are associated with patent foramen ovale. The objective was to determine the anti-arrhythmic effect of patent foramen ovale closure on pre-existing atrial tachyarrhythmias. Medline, EMBASE, Cochrane Library, and Google Scholar databases were searched between 1967 and 2010. The search was expanded using the 'related articles' function and reference lists of key studies. All studies reporting pre- and post-closure incidence (or prevalence) of atrial tachyarrhythmia in the same patient population were included. Random and fixed effect meta-analyses were used to aggregate the data. Six studies were identified including 2570 patients who underwent percutaneous closure. Atrial fibrillation was in fact the only AT reported in all studies. Meta-analysis using a fixed effects model demonstrated a significant reduction in the prevalence of atrial fibrillation with an OR of 0.43 (95% CI 0.26-0.71). When using the random-effects model, OR was 0.44 (95% CI 0.18-1.04) with a statistically significant trend demonstrated (test for overall effect: Z=1.87, p=0.06). Closure of a patent foramen ovale may be associated with reduction in the prevalence of atrial fibrillation. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A pooled analysis of the IL-10-1082 A/G polymorphism and the nasopharyngeal carcinoma susceptibility.

PubMed

Ma, Liping; Li, Shan; Lu, Yu; Zhang, Xiaolian; Zhao, Jiangyang; Qin, Xue

2016-04-01

It has been reported that IL-10-1082 A/G polymorphism might influence the transcription and secretion of IL10 and tumor development. While many studies have been conducted to investigate the association between IL-10-1082 A/G polymorphism and risk of nasopharyngeal carcinoma (NPC) in various populations, the results of these studies are still controversial. We aimed to explore this relationship through a cumulative meta-analysis. A search of the literature was performed using the Cochrane Library, PubMed, and EMBASE databases. The odds ratio (OR) and corresponding 95 % confidence interval (CI) were calculated to assess this possible association. Six studies were included in the study. The meta-analysis reveals a significant effect in the allelic model (G vs. A: OR 1.516, 95 % CI 1.077-2.133, P heterogeneity = 0.003), dominant model (AG + GG vs. AA: OR = 1.770, 95 % CI 1.415-2.212, P heterogeneity = 0.169), and co-dominant model (AG vs. AA: OR = 1.747, 95 % CI 1.377-2.216, P heterogeneity = 0.491). Similarly, in the stratified analyses, significant effects were reported in studies of Asian populations. Our meta-analysis results suggest that the IL-10-1082 A/G variant is associated with increased risk of NPC in Asian populations.

Caffeine and diuresis during rest and exercise: A meta-analysis

PubMed Central

Coca, Aitor; Casa, Douglas J.; Antonio, Jose; Green, James M.; Bishop, Phillip A.

2016-01-01

Objectives Although ergogenic, acute caffeine ingestion may increase urine volume, prompting concerns about fluid balance during exercise and sport events. This meta-analysis evaluated caffeine induced diuresis in adults during rest and exercise. Design Meta-analysis. Methods A search of three databases was completed on November 1, 2013. Only studies that involved healthy adults and provided sufficient information concerning the effect size (ES) of caffeine ingestion on urine volume were included. Sixteen studies met the inclusion criteria, providing a total of 28 ESs for the meta-analysis. Heterogeneity was assessed using a random-effects model. Results The median caffeine dosage was 300 mg. The overall ES of 0.29 (95% confidence interval (CI) = 0.11-0.48, p = 0.001) corresponds to an increase in urine volume of 109 ± 195 mL or 16.0 ± 19.2% for caffeine ingestion vs. non-caffeine conditions. Subgroup meta-analysis confirmed exercise as a strong moderator: active ES = 0.10, 95% CI = −0.07 to 0.27, p = 0.248 vs. resting ES = 0.54, 95% CI = 0.22–0.85, p = 0.001 (Cochran's Q, p = 0.019). Females (ES = 0.75,95% CI = 0.38–1.13, p< 0.001) were more susceptible to diuretic effects than males (ES = 0.13,95% CI = −0.05 to 0.31, p = 0.158) (Cochran's Q, p = 0.003). Conclusions Caffeine exerted a minor diuretic effect which was negated by exercise. Concerns regarding unwanted fluid loss associated with caffeine consumption are unwarranted particularly when ingestion precedes exercise. PMID:25154702

Effects of quercetin supplementation on endurance performance and maximal oxygen consumption: a meta-analysis.

PubMed

Pelletier, Denis M; Lacerte, Guillaume; Goulet, Eric D B

2013-02-01

Lately, the effect of quercetin supplementation (QS) on endurance performance (EP) and maximal oxygen consumption (VO2max) has been receiving much scientific and media attention. Therefore, a meta-analysis was performed to determine QS's ergogenic value on these variables. Studies were located with database searches (PubMed and SPORTDiscus) and cross-referencing. Outcomes represent mean percentage changes in EP (measured via power output) and VO2max between QS and placebo. Random-effects model meta-regression, mixed-effects model analog to the ANOVA, random-effects weighted mean effect summary, and magnitude-based inferences analyses were used to delineate the effects of QS. Seven research articles (representing 288 subjects) were included, producing 4 VO2max and 10 EP effect estimates. Mean QS daily intake and duration were, respectively, 960 ± 127 mg and 26 ± 24 d for the EP outcome and 1,000 ± 0 mg and 8 ± 23 d for the VO2max outcome. EP was assessed during exercise with a mean duration of 79 ± 82 min. Overall, QS improved EP by 0.74% (95% CI: 0.10-1.39, p = .02) compared with placebo. However, only in untrained individuals (0.83% ± 0.78%, p = .02) did QS significantly improve EP (trained individuals: 0.09% ± 2.15%, p = .92). There was no relationship between QS duration and EP (p = .69). Overall, QS increased VO2max by 1.94% (95% CI: 0.30-3.59, p = .02). Magnitude-based inferences suggest that the effect of QS on EP and VO2max is likely to be trivial for both trained and untrained individuals. In conclusion, this meta-analysis indicates that QS is unlikely to prove ergogenic for aerobic-oriented exercises in trained and untrained individuals.

What we have learned about minimized extracorporeal circulation versus conventional extracorporeal circulation: an updated meta-analysis.

PubMed

Sun, Yanhua; Gong, Bing; Yuan, Xin; Zheng, Zhe; Wang, Guyan; Chen, Guo; Zhou, Chenghui; Wang, Wei; Ji, Bingyang

2015-08-01

The benefits of minimized extracorporeal circulation (MECC) compared with conventional extracorporeal circulation (CECC) are still in debate. PubMed, EMBASE and the Cochrane Library were searched until November 10, 2014. After quality assessment, we chose a fixed-effects model when the trials showed low heterogeneity, otherwise a random-effects model was used. We performed univariate meta-regression and sensitivity analysis to search for the potential sources of heterogeneity. Cumulative meta-analysis was performed to access the evolution of outcome over time. 41 RCTs enrolling 3744 patients were included after independent article review by 2 authors. MECC significantly reduced atrial fibrillation (RR, 0.76; 95% CI, 0.66 to 0.89; P < 0.001; I2 = 0%), and myocardial infarction (RR, 0.43; 95% CI, 0.26 to 0.71; P = 0.001; I2 = 0%). In addition, the results regarding chest tube drainage, transfusion rate, blood loss, red blood cell transfusion volume, and platelet count favored MECC as well. MECC diminished morbidity of cardiovascular complications postoperatively, conserved blood cells, and reduced allogeneic blood transfusion.

A meta-analysis of the effects of preweaned calf nutrition and growth on first-lactation performance.

PubMed

Gelsinger, S L; Heinrichs, A J; Jones, C M

2016-08-01

Several studies and a 2013 meta-analysis have proposed that increased feeding of milk or milk replacer to neonatal calves may improve subsequent milk production. However, data from individual studies are conflicting, and the meta-analysis was unable to assess the influence of calf starter intake. The objective of the current meta-analysis was to review newly published data and evaluate the effects of preweaning diet (including calf starter intake) and growth rate on first-lactation milk, fat, and protein yield. Data from 9 studies representing 21 treatment groups were included in the analysis. We created separate models for each outcome variable using regression methods in SAS (version 9.4, SAS Institute Inc., Cary, NC) to determine the effects of intake and growth rate. We then selected the best-fitting models using Akaike's information criterion. The effect of study explained 98, 85, and 96% of the variance in 305-d milk, fat, and protein yield in first lactation, respectively, indicating that other aspects of management are more important for determining first-lactation production than preweaning intake and growth rate. However, we found a synergistic relationship between preweaning liquid and starter dry matter intake for improving milk, fat, and protein production, and a positive relationship between first-lactation performance and preweaning average daily gain. These data indicate that provision of adequate nutrients from liquid and solid feeds and maintaining average daily gain above 0.5kg/d can enhance the first-lactation performance of heifers when combined with proper postweaning practices. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Red and processed meat consumption and the risk of lung cancer: a dose-response meta-analysis of 33 published studies

PubMed Central

Xue, Xiu-Juan; Gao, Qing; Qiao, Jian-Hong; Zhang, Jie; Xu, Cui-Ping; Liu, Ju

2014-01-01

This meta-analysis was to summarize the published studies about the association between red/processed meat consumption and the risk of lung cancer. 5 databases were systematically reviewed, and random-effect model was used to pool the study results and to assess dose-response relationships. Results shown that six cohort studies and twenty eight case-control studies were included in this meat-analysis. The pooled Risk Radios (RR) for total red meat and processed meat were 1.44 (95% CI, 1.29-1.61) and 1.23 (95% CI, 1.10-1.37), respectively. Dose-response analysis revealed that for every increment of 120 grams red meat per day the risk of lung cancer increases 35% and for every increment of 50 grams red meat per day the risk of lung cancer increases 20%. The present dose-response meta-analysis suggested that both red and processed meat consumption showed a positive effect on lung cancer risk. PMID:25035778

Moderating factors of video-modeling with other as model: a meta-analysis of single-case studies.

PubMed

Mason, Rose A; Ganz, Jennifer B; Parker, Richard I; Burke, Mack D; Camargo, Siglia P

2012-01-01

Video modeling with other as model (VMO) is a more practical method for implementing video-based modeling techniques, such as video self-modeling, which requires significantly more editing. Despite this, identification of contextual factors such as participant characteristics and targeted outcomes that moderate the effectiveness of VMO has not previously been explored. The purpose of this study was to meta-analytically evaluate the evidence base of VMO with individuals with disabilities to determine if participant characteristics and targeted outcomes moderate the effectiveness of the intervention. Findings indicate that VMO is highly effective for participants with autism spectrum disorder (IRD=.83) and moderately effective for participants with developmental disabilities (IRD=.68). However, differential effects are indicated across levels of moderators for diagnoses and targeted outcomes. Implications for practice and future research are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Meta-Analysis of the Relative Risk of Mortality for Type 1 Diabetes Patients Compared to the General Population: Exploring Temporal Changes in Relative Mortality

PubMed Central

Lung, Tom W. C.; Hayes, Alison J.; Herman, William H.; Si, Lei; Palmer, Andrew J.; Clarke, Philip M.

2014-01-01

Aims Type 1 diabetes has been associated with an elevated relative risk (RR) of mortality compared to the general population. To review published studies on the RR of mortality of Type 1 diabetes patients compared to the general population, we conducted a meta-analysis and examined the temporal changes in the RR of mortality over time. Methods Systematic review of studies reporting RR of mortality for Type 1 diabetes compared to the general population. We conducted meta-analyses using a DerSimonian and Laird random effects model to obtain the average effect and the distribution of RR estimates. Sub-group meta-analyses and multivariate meta-regression analysis was performed to examine heterogeneity. Summary RR with 95% CIs was calculated using a random-effects model. Results 26 studies with a total of 88 subpopulations were included in the meta-analysis and overall RR of mortality was 3.82 (95% CI 3.41, 3.4.29) compared to the general population. Observations using data prior to 1971 had a much larger estimated RR (5.80 (95% CI 4.20, 8.01)) when compared to: data between; 1971 and 1980 (5.06 (95% CI 3.44, 7.45)); 1981–90 (3.59 (95% CI 3.15, 4.09)); and those after 1990 (3.11 (95% CI 2.47, 3.91)); suggesting mortality of Type 1 diabetes patients when compared to the general population have been improving over time. Similarly, females (4.54 (95% CI 3.79–5.45)) had a larger RR estimate when compared to males (3.25 (95% CI 2.82–3.73) and the meta-regression found evidence for temporal trends and sex (p<0.01) accounting for heterogeneity between studies. Conclusions Type 1 diabetes patients’ mortality has declined at a faster rate than the general population. However, the largest relative improvements have occurred prior to 1990. Emphasis on intensive blood glucose control alongside blood pressure control and statin therapy may translate into further reductions in mortality in coming years. PMID:25426948

Effect of biotin on milk performance of dairy cattle: a meta-analysis.

PubMed

Chen, B; Wang, C; Wang, Y M; Liu, J X

2011-07-01

A meta-analysis of the effect of biotin on production outcomes of dairy cattle was conducted following a literature review. A total of 11 studies from 9 papers, with information on the milk production and composition data from a total number of 238 cows were extracted and analyzed using meta-analysis software in Stata. Estimated size of effect of biotin was calculated for dry matter intake (DMI), milk production, and composition. Heterogeneity was not significant for all of the parameters (the highest I(2)=12%). Therefore, fixed effects models were used for analysis. With the addition of biotin to lactating dairy cattle, DMI and milk production increased by 0.87 and 1.66 kg/d. No significant effect on percentage of milk fat and milk protein was observed. Additionally, Begg's test indicated no evidence of substantial publication bias for all variables. The influence analysis shows that the removal of any study did not change the direction or significance of the point estimates. It can be concluded that the use of biotin supplements increases DMI and milk yield in lactating dairy cows. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Multivariate meta-analysis with an increasing number of parameters

PubMed Central

Boca, Simina M.; Pfeiffer, Ruth M.; Sampson, Joshua N.

2017-01-01

Summary Meta-analysis can average estimates of multiple parameters, such as a treatment’s effect on multiple outcomes, across studies. Univariate meta-analysis (UVMA) considers each parameter individually, while multivariate meta-analysis (MVMA) considers the parameters jointly and accounts for the correlation between their estimates. The performance of MVMA and UVMA has been extensively compared in scenarios with two parameters. Our objective is to compare the performance of MVMA and UVMA as the number of parameters, p, increases. Specifically, we show that (i) for fixed-effect meta-analysis, the benefit from using MVMA can substantially increase as p increases; (ii) for random effects meta-analysis, the benefit from MVMA can increase as p increases, but the potential improvement is modest in the presence of high between-study variability and the actual improvement is further reduced by the need to estimate an increasingly large between study covariance matrix; and (iii) when there is little to no between study variability, the loss of efficiency due to choosing random effects MVMA over fixed-effect MVMA increases as p increases. We demonstrate these three features through theory, simulation, and a meta-analysis of risk factors for Non-Hodgkin Lymphoma. PMID:28195655

Standardized Regression Coefficients as Indices of Effect Sizes in Meta-Analysis

ERIC Educational Resources Information Center

Kim, Rae Seon

2011-01-01

When conducting a meta-analysis, it is common to find many collected studies that report regression analyses, because multiple regression analysis is widely used in many fields. Meta-analysis uses effect sizes drawn from individual studies as a means of synthesizing a collection of results. However, indices of effect size from regression analyses…

Meta-analyses of the Association of Sleep Apnea with Insulin Resistance, and the Effects of CPAP on HOMA-IR, Adiponectin, and Visceral Adipose Fat.

PubMed

Iftikhar, Imran H; Hoyos, Camilla M; Phillips, Craig L; Magalang, Ulysses J

2015-04-15

We sought to conduct an updated meta-analysis of randomized controlled trials (RCTs) on the effect of continuous positive airway pressure (CPAP) on insulin resistance, as measured by homeostasis model assessment of insulin resistance (HOMA-IR), visceral abdominal fat (VAF), and adiponectin. Additionally, we performed a separate meta-analysis and meta-regression of studies on the association of insulin resistance and obstructive sleep apnea (OSA). All included studies were searched from PubMed (from conception to March 15, 2014). Data were pooled across all included RCTs as the mean difference in HOMA-IR and VAF, and as the standardized mean difference in the case of adiponectin analysis. From the included case-control studies, data on the difference of HOMA-IR between cases and controls were pooled across all studies, as the standardized mean difference (SMD). There was a significant difference in HOMA-IR (-0.43 [95% CIs: -0.75 to -0.11], p = 0.008) between CPAP treated and non CPAP treated participants. However, there was no significant difference in VAF or adiponectin; (-47.93 [95% CI: -112.58 to 16.72], p = 0.14) and (-0.06 [95% CI: -0.28 to 0.15], p = 0.56), respectively. Meta-analysis of 16 case-control studies showed a pooled SMD in HOMA-IR of 0.51 (95% CI: 0.28 to 0.75), p ≤ 0.001, between cases and controls. The results of our meta-analyses show that CPAP has a favorable effect on insulin resistance. This effect is not associated with any significant changes in total adiponectin levels or amount of VAF. Our findings also confirm a significant association between OSA and insulin resistance. © 2015 American Academy of Sleep Medicine.

Sham transcranial electrical stimulation and its effects on corticospinal excitability: a systematic review and meta-analysis.

PubMed

Dissanayaka, Thusharika D; Zoghi, Maryam; Farrell, Michael; Egan, Gary F; Jaberzadeh, Shapour

2018-02-23

Sham stimulation is used in randomized controlled trials (RCTs) to assess the efficacy of active stimulation and placebo effects. It should mimic the characteristics of active stimulation to achieve blinding integrity. The present study was a systematic review and meta-analysis of the published literature to identify the effects of sham transcranial electrical stimulation (tES) - including anodal and cathodal transcranial direct current stimulation (a-tDCS, c-tDCS), transcranial alternating current stimulation (tACS), transcranial random noise stimulation (tRNS) and transcranial pulsed current stimulation (tPCS) - on corticospinal excitability (CSE), compared to baseline in healthy individuals. Electronic databases - PubMed, CINAHL, Scopus, Science Direct and MEDLINE (Ovid) - were searched for RCTs of tES from 1990 to March 2017. Thirty RCTs were identified. Using a random-effects model, meta-analysis of a-tDCS, c-tDCS, tACS, tRNS and tPCS studies showed statistically non-significant pre-post effects of sham interventions on CSE. This review found evidence for statically non-significant effects of sham tES on CSE.

Serum Uric Acid Levels and Diabetic Peripheral Neuropathy in Type 2 Diabetes: a Systematic Review and Meta-analysis.

PubMed

Yu, Shuai; Chen, Ying; Hou, Xu; Xu, Donghua; Che, Kui; Li, Changgui; Yan, Shengli; Wang, Yangang; Wang, Bin

2016-03-01

Previous studies suggested a possible association between serum uric acid levels and peripheral neuropathy in patients with type 2 diabetes, but no definite evidence was available. A systematic review and meta-analysis of relevant studies were performed to comprehensively estimate the association. Pubmed, Web of Science, Embase, and China Biology Medicine (CBM) databases were searched for eligible studies. Study-specific data were combined using random-effect or fixed-effect models of meta-analysis according to between-study heterogeneity. Twelve studies were finally included into the meta-analysis, which involved a total of 1388 type 2 diabetic patients with peripheral neuropathy and 4746 patients without peripheral neuropathy. Meta-analysis showed that there were obvious increased serum uric acid levels in diabetic patients with peripheral neuropathy (weighted mean difference [WMD] = 50.03 μmol/L, 95% confidence interval [95%CI] 22.14-77.93, P = 0.0004). Hyperuricemia was also significantly associated with increased risk of peripheral neuropathy in patients with type 2 diabetes (risk ratio [RR] = 2.83, 95%CI 2.13-3.76, P < 0.00001). Meta-analysis of two studies with adjusted risk estimates showed that hyperuricemia was independently associated with increased risk of peripheral neuropathy in type 2 diabetic patients (RR = 1.95, 95%CI 1.23-3.11, P = 0.005). Type 2 diabetic patients with peripheral neuropathy have obvious increased serum uric acid levels, and hyperuricemia is associated with increased risk of peripheral neuropathy. Further prospective cohort studies are needed to validate the impact of serum uric acid levels on peripheral neuropathy risk.

A meta-analysis of MTHFR C677T and A1298C polymorphisms and risk of acute lymphoblastic leukemia in children.

PubMed

Yan, Jingrong; Yin, Ming; Dreyer, ZoAnn E; Scheurer, Michael E; Kamdar, Kala; Wei, Qingyi; Okcu, M Fatih

2012-04-01

Methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C polymorphisms have been implicated in childhood acute lymphoblastic leukemia (ALL) risk, but previously published studies were inconsistent and recent meta-analyses were not adequate. In a meta-analysis of 21 publications with 4,706 cases and 7,414 controls, we used more stringent inclusion method and summarized data on associations between MTHFR C677T and A1298C polymorphisms and childhood ALL risk. We found an overall association between 677T variant genotypes and reduced childhood ALL risk. Specifically, in the dominant genetic model, an association was found in a fixed-effect (TT + CT vs. CC: OR = 0.92; 95% CI = 0.85-0.99) but not random-effect model, whereas such an association was observed in both homozygote genetic model (TT vs. CC: OR = 0.80; 95% CI = 0.70-0.93 by fixed effects and OR = 0.78; 95% CI = 0.65-0.93 by random effects) and recessive genetic model (TT vs. CC + CT: OR = 0.83; 95% CI = 0.72-0.95 by fixed effects and OR = 0.84; 95% CI = 0.73-0.97 by random effects). These associations were also observed in subgroups by ethnicity: for Asians in all models except for the dominant genetic model by random effect and for Caucasians in all models except for the recessive genetic model. However, the A1298C polymorphism did not appear to have an effect on childhood ALL risk. These results suggest that the MTHFR C677T, but not A1298C, polymorphism is a potential biomarker for childhood ALL risk. Copyright © 2011 Wiley Periodicals, Inc.

The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

PubMed

Thompson, Christopher Glen; Becker, Betsy Jane

2014-09-01

A common assumption in meta-analysis is that effect sizes are independent. When correlated effect sizes are analyzed using traditional univariate techniques, this assumption is violated. This research assesses the impact of dependence arising from treatment-control studies with multiple endpoints on homogeneity measures Q and I(2) in scenarios using the unbiased standardized-mean-difference effect size. Univariate and multivariate meta-analysis methods are examined. Conditions included different overall outcome effects, study sample sizes, numbers of studies, between-outcomes correlations, dependency structures, and ways of computing the correlation. The univariate approach used typical fixed-effects analyses whereas the multivariate approach used generalized least-squares (GLS) estimates of a fixed-effects model, weighted by the inverse variance-covariance matrix. Increased dependence among effect sizes led to increased Type I error rates from univariate models. When effect sizes were strongly dependent, error rates were drastically higher than nominal levels regardless of study sample size and number of studies. In contrast, using GLS estimation to account for multiple-endpoint dependency maintained error rates within nominal levels. Conversely, mean I(2) values were not greatly affected by increased amounts of dependency. Last, we point out that the between-outcomes correlation should be estimated as a pooled within-groups correlation rather than using a full-sample estimator that does not consider treatment/control group membership. Copyright © 2014 John Wiley & Sons, Ltd.

Does vitamin D supplementation improve bone density in vitamin D-deficient children? Protocol for an individual patient data meta-analysis.

PubMed

Winzenberg, Tania; Lamberg-Allardt, Christel; El-Hajj Fuleihan, Ghada; Mølgaard, Christian; Zhu, Kun; Wu, Feitong; Riley, Richard D

2018-01-23

Our previous study-level (aggregate data) meta-analysis suggested that vitamin D supplements may be beneficial for bone density specifically in children with vitamin D deficiency. However, the misclassification of vitamin D status inherent in study-level data means that the results are not definitive and cannot provide an accurate assessment of the size of any effect. Therefore, we propose to undertake an individual patient data (IPD) meta-analysis to determine whether the effect of vitamin D supplementation on bone density in children differs according to baseline vitamin D status, and to specifically estimate the effect of vitamin D in children who are vitamin D deficient. This study has been designed to adhere to the Preferred Reporting Items for Systematic Review and Meta-Analyses of IPD statement. We will include randomised placebo-controlled trials of vitamin D supplementation reporting bone density outcomes at least 6 months after the study commenced in children and adolescents (aged <20 years) without coexistent medical conditions or treatments causing osteoporosis. We will update the search of the original review to cover the period 2009-2017, using the same methods as the original review. Fully anonymised data on all randomised patients will be requested. Outcomes will be femoral neck, total hip, lumbar spine and proximal and distal forearm bone mineral density, and total body bone mineral content. A two-stage IPD meta-analysis will be used to examine the effect of baseline serum 25-hydroxyvitamin D (25(OH)D) on treatment effect for each bone density outcome. Restricted maximum likelihood will be used to estimate the random-effects meta-analysis models, with 95% CI for summary effects. Heterogeneity will be assessed by I 2 and potential publication bias (small-study effects) and availability bias by funnel plots, Egger's test and Peter's test. Ethics approval will not be required as the data are to be used for the primary purpose for which they were collected and all original individual studies had ethics approval. Results of the IPD meta-analysis will be submitted for publication in a peer-reviewed journal. CRD42017068772. © 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.

Should Perioperative Supplemental Oxygen Be Routinely Recommended for Surgical Patients? A Bayesian Meta-analysis

PubMed Central

Kao, Lillian S.; Millas, Stefanos G.; Pedroza, Claudia; Tyson, Jon E.; Lally, Kevin P.

2012-01-01

Objective The purpose of this study is to use updated data and Bayesian methods to evaluate the effectiveness of hyperoxia to reduce surgical site infections (SSIs) and/or mortality in both colorectal and all surgical patients. Because few trials assessed potential harms of hyperoxia, hazards were not included. Background Use of hyperoxia to reduce SSIs is controversial. Three recent meta-analyses have had conflicting conclusions. Methods A systematic literature search and review were performed. Traditional fixed-effect and random-effects meta-analyses and Bayesian meta-analysis were performed to evaluate SSIs and mortality. Results Traditional meta-analysis yielded a relative risk of an SSI with hyperoxia among all surgery patients of 0.84 (95% confidence interval, CI, 0.73–0.97) and 0.84 (95% CI 0.61–1.16) for the fixed-effect and random effects models respectively. The probabilities of any risk reduction in SSIs among all surgery patients were 77%, 81%, and 83% for skeptical, neutral, and enthusiastic priors. Subset analysis of colorectal surgery patients increased the probabilities to 86%, 89%, and 92%. The probabilities of at least a 10% reduction were 57%, 62%, and 68% for all surgical patients and 71%, 75%, and 80% among the colorectal surgery subset. Conclusions There is a moderately high probability of a benefit to hyperoxia in reducing SSIs in colorectal surgery patients; however, the magnitude of benefit is relatively small and might not exceed treatment hazards. Further studies should focus on generalizability to other patient populations or on treatment hazards and other outcomes. PMID:23160100

A Meta-Analytic Review of the Efficacy of Physical Exercise Interventions on Cognition in Individuals with Autism Spectrum Disorder and ADHD

ERIC Educational Resources Information Center

Tan, Beron W. Z.; Pooley, Julie A.; Speelman, Craig P.

2016-01-01

This review evaluates the efficacy of using physical exercise interventions on improving cognitive functions in individuals with autism spectrum disorder (ASD) and/or attention deficit hyperactivity disorder (ADHD). This review includes a meta-analysis based on a random-effects model of data reported in 22 studies with 579 participants aged…

The countermovement jump to monitor neuromuscular status: A meta-analysis.

PubMed

Claudino, João Gustavo; Cronin, John; Mezêncio, Bruno; McMaster, Daniel Travis; McGuigan, Michael; Tricoli, Valmor; Amadio, Alberto Carlos; Serrão, Julio Cerca

2017-04-01

The primary objective of this meta-analysis was to compare countermovement jump (CMJ) performance in studies that reported the highest value as opposed to average value for the purposes of monitoring neuromuscular status (i.e., fatigue and supercompensation). The secondary aim was to determine the sensitivity of the dependent variables. Systematic review with meta-analysis. The meta-analysis was conducted on the highest or average of a number of CMJ variables. Multiple literature searches were undertaken in Pubmed, Scopus, and Web of Science to identify articles utilizing CMJ to monitor training status. Effect sizes (ES) with 95% confidence interval (95% CI) were calculated using the mean and standard deviation of the pre- and post-testing data. The coefficient of variation (CV) with 95% CI was also calculated to assess the level of instability of each variable. Heterogeneity was assessed using a random-effects model. 151 articles were included providing a total of 531 ESs for the meta-analyses; 85.4% of articles used highest CMJ height, 13.2% used average and 1.3% used both when reporting changes in CMJ performance. Based on the meta-analysis, average CMJ height was more sensitive than highest CMJ height in detecting CMJ fatigue and supercompensation. Furthermore, other CMJ variables such as peak power, mean power, peak velocity, peak force, mean impulse, and power were sensitive in tracking the supercompensation effects of training. The average CMJ height was more sensitive than highest CMJ height in monitoring neuromuscular status; however, further investigation is needed to determine the sensitivity of other CMJ performance variables. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Effects of Perceived Discrimination on Depressive Symptoms Among Black Men Residing in the United States: A Meta-Analysis

PubMed Central

Britt-Spells, Angelitta M.; Slebodnik, Maribeth; Sands, Laura P.; Rollock, David

2016-01-01

Research reports that perceived discrimination is positively associated with depressive symptoms. The literature is limited when examining this relationship among Black men. This meta-analysis systematically examines the current literature and investigates the relationship of perceived discrimination on depressive symptoms among Black men residing in the United States. Using a random-effects model, study findings indicate a positive association between perceived discrimination and depressive symptoms among Black men (r = .29). Several potential moderators were also examined in this study; however, there were no significant moderation effects detected. Recommendations and implications for future research and practice are discussed. PMID:26742988

HFE gene C282Y variant is associated with colorectal cancer in Caucasians: a meta-analysis.

PubMed

Chen, Weidong; Zhao, Hua; Li, Tiegang; Yao, Hongliang

2013-08-01

The HFE gene has been suggested to play an important role in the pathogenesis of colorectal cancer. However, the results have been conflicting. In this study, we performed a meta-analysis to clarify the association of HFE gene C282Y variant with colorectal cancer. PubMed and Embase were retrieved to identify the potential literature. Pooled odds ratio (OR) with 95 % confidence interval (CI) was calculated using fixed- or random-effects model. A total of eight papers including nine studies (7,588 colorectal cancer cases and 81,571 controls) for HFE gene C282Y variant were included in the meta-analysis. The result indicated that HFE gene C282Y variant was significantly associated with colorectal cancer under recessive model (OR = 2.00, 95 % CI = 1.32-3.04), with no evidence of between-study heterogeneity (I (2) = 0.2 %, p = 0.432). Further subgroup analysis by number of cases suggested the effect was significant in studies with more than 500 cases (OR = 2.51, 95 % CI = 1.58-3.98, I (2) = 0.0 %, p = 0.921), but not in studies with less than 500 cases (OR = 0.75, 95 % CI = 0.28-1.97, I (2) = 0.0 %, p = 0.622). The current meta-analysis supported the positive association of HFE gene C282Y variant with colorectal cancer. Further large-scale studies with the consideration for gene-gene/gene-environment interactions should be conducted to investigate the association.

A Healthy Dietary Pattern Reduces Lung Cancer Risk: A Systematic Review and Meta-Analysis.

PubMed

Sun, Yanlai; Li, Zhenxiang; Li, Jianning; Li, Zengjun; Han, Jianjun

2016-03-04

Diet and nutrients play an important role in cancer development and progress; a healthy dietary pattern has been found to be associated with several types of cancer. However, the association between a healthy eating pattern and lung cancer risk is still unclear. Therefore, we conducted a systematic review with meta-analysis to evaluate whether a healthy eating pattern might reduce lung cancer risk. We identified relevant studies from the PubMed and Embase databases up to October 2015, and the relative risks were extracted and combined by the fixed-effects model when no substantial heterogeneity was observed; otherwise, the random-effects model was employed. Subgroup and publication bias analyses were also performed. Finally, eight observational studies were included in the meta-analysis. The pooled relative risk of lung cancer for the highest vs. lowest category of healthy dietary pattern was 0.81 (95% confidence interval, CI: 0.75-0.86), and no significant heterogeneity was detected. The relative risks (RRs) for non-smokers, former smokers and current smokers were 0.89 (95% CI: 0.63-1.27), 0.74 (95% CI: 0.62-0.89) and 0.86 (95% CI: 0.79-0.93), respectively. The results remained stable in subgroup analyses by other confounders and sensitivity analysis. The results of our meta-analysis suggest that a healthy dietary pattern is associated with a lower lung cancer risk, and they provide more beneficial evidence for changing the diet pattern in the general population.

Association between serum uric acid level and multiple system atrophy: A meta-analysis.

PubMed

Zhang, Xi; Liu, De-Shan; An, Chun-Yao; Liu, Yu-Zhao; Liu, Xiao-Hong; Zhang, Fang; Ning, Lu-Ning; Li, Chang-Ling; Ma, Chun-Mei; Hu, Rui-Ting

2018-06-01

Lower serum uric acid (UA) levels are considered to be related to the risk to develop many neurodegenerative disorders. However, the association between serum UA level and multiple system atrophy (MSA) remains controversial. The aim of this meta-analysis was to evaluate the relationship between serum UA level and MSA. PubMed, Web of Science, Embase, Cochrane Library and China National Knowledge Infrastructure (CNKI) were searched for eligible studies. Standardized mean difference (SMD) and 95% confidence intervals (95% CI) were calculated in a fixed-effects model or a random-effects model when appropriate. Subgroup analyses were carried out based on gender. A total of 6 eligible studies involving 547 MSA patients and 637 healthy individuals were identified. Meta-analysis results revealed that individuals with MSA had lower sera levels of UA as compared with healthy controls (pooled SMD is -0.51, 95%CI: -0.88 to -0.14; p = 0.006). The subgroup analysis to detect sex differences showed that the pooled SMD was -0.61 (95% CI: -0.82 to -0.40; p < 0.0001) for males and -0.22 (95% CI: -0.55 to 0.10; p = 0.18) for females compared with healthy controls. Our meta-analysis revealed that lower serum level of UA is associated with an increased risk of MSA and the relationship is significant in men but not in women. Copyright © 2018 Elsevier B.V. All rights reserved.

The effectiveness of physical models in teaching anatomy: a meta-analysis of comparative studies.

PubMed

Yammine, Kaissar; Violato, Claudio

2016-10-01

There are various educational methods used in anatomy teaching. While three dimensional (3D) visualization technologies are gaining ground due to their ever-increasing realism, reports investigating physical models as a low-cost 3D traditional method are still the subject of considerable interest. The aim of this meta-analysis is to quantitatively assess the effectiveness of such models based on comparative studies. Eight studies (7 randomized trials; 1 quasi-experimental) including 16 comparison arms and 820 learners met the inclusion criteria. Primary outcomes were defined as factual, spatial and overall percentage scores. The meta-analytical results are: educational methods using physical models yielded significantly better results when compared to all other educational methods for the overall knowledge outcome (p < 0.001) and for spatial knowledge acquisition (p < 0.001). Significantly better results were also found with regard to the long-retention knowledge outcome (p < 0.01). No significance was found for the factual knowledge acquisition outcome. The evidence in the present systematic review was found to have high internal validity and at least an acceptable strength. In conclusion, physical anatomical models offer a promising tool for teaching gross anatomy in 3D representation due to their easy accessibility and educational effectiveness. Such models could be a practical tool to bring up the learners' level of gross anatomy knowledge at low cost.

The Effects of Anti-inflammatory Drug Treatment in Gastric Cancer Prevention: an Update of a Meta-analysis

PubMed Central

Kong, Pengfei; Wu, Ruiyan; Liu, Xuechao; Liu, Jianjun; Chen, Shangxiang; Ye, Minting; Yang, Chenlu; Song, Ze; He, Wenzhuo; Yin, Chenxi; Yang, Qiong; Jiang, Chang; Liao, Fangxin; Peng, Roujun; Zhou, Zhiwei; Xu, Dazhi; Xia, Liangping

2016-01-01

Gastric cancer has high incidence and fatality rates, making chemoprevention agents necessary. There is an ongoing debate about aspirin/nonsteroidal anti-inflammatory drugs (NSAIDs) use can significant reduce the risk of GC. We conducted a meta-analysis of existing studies evaluating the association of anti-inflammatory drug and GC. We performed a systematic literature search of PubMed, Web of Science, Embase, OVID, Cochrane Library and Clincialtrials.gov up to August 31, 2015. Either a fixed-effects or a random-effects model using was based on the result of homogeneity analysis. Subgroup, sensitivity, meta-regression, and publication bias analyses were evaluated. Forty-seven studies were finally included in this meta-analysis. The overall GC risk reduction benefit associated with anti-inflammatory drug use represented an RR of 0.78 (95% CI 0.71 to 0.85) and an adjusted RR of 0.74 (95% CI 0.71 to 0.77). Besides, the prevention benefit of aspirin/NSAIDs ingestion appeared to be confined to those patients with regiment of short or middle-term (≤5 years), high-frequency (>30 times per month) and low dose (<200 mg per day). Further, our data also suggest that COX-2 inhibitors use is a more effective approach in GC prevention (RR, 0.45; 95% CI, 0.29-0.70). In this meta-analysis, our finding support short or middle-term (≤5 years), high-frequency (>30 times per month) and low dose (<200 mg per day) aspirin/NSAIDs intake is a well method for GC prevention and also confirm the inverse association between aspirin/NSAIDs use and GC risk. Additionally, selective COX-2 inhibitors use probably a more effective approach to reduce GC risk. PMID:27994661

Efficacy of rasagiline in early Parkinson's disease: a meta-analysis of data from the TEMPO and ADAGIO studies.

PubMed

Hauser, Robert A; Abler, Victor; Eyal, Eli; Eliaz, Rom E

2016-10-01

To evaluate the efficacy of rasagiline versus placebo in a pooled population of patients with early Parkinson's disease (PD). TEMPO and ADAGIO were Phase III studies that evaluated the symptomatic efficacy of rasagiline versus placebo in patients with early PD. This meta-analysis included Unified Parkinson's Disease Rating Scale (UPDRS) observations from weeks 12, 24 and 36 in ADAGIO and from weeks 14 and 26 in TEMPO; TEMPO visits were recoded to weeks 12 and 24, respectively. The present analysis includes all patients who received rasagiline 1 mg/day, 2 mg/day or placebo, and had ≥1 post-baseline observations and a subgroup of patients whose baseline UPDRS Total scores were ≥27 (Upper Quartile population). Change from baseline in UPDRS scores were evaluated using mixed models repeated measures analyses. Of the 1578 patients randomized to the two studies, 1546 patients met criteria for inclusion in the meta-analysis. Effects on UPDRS Total, motor and activities of daily living scores were significantly better for both doses of rasagiline compared with placebo at all time periods. The Upper Quartile population included 402 patients with a UPDRS Total score ≥27 at baseline. These patients generally demonstrated a larger magnitude of treatment effect than was seen in the full population. This meta-analysis confirms the efficacy of rasagiline monotherapy over 36 weeks. Although TEMPO and ADAGIO are considered studies of "very early" PD, both contained a sizeable pool of patients with more severe disease. In addition, the meta-analysis showed a larger magnitude of effect in patients with more severe baseline disease.

Self-reported interoceptive deficits in eating disorders: A meta-analysis of studies using the eating disorder inventory.

PubMed

Jenkinson, Paul M; Taylor, Lauren; Laws, Keith R

2018-07-01

An impairment of the ability to sense the physiological condition of the body - interoception - has long been proposed as central to the onset and maintenance of eating disorders. More recent attention to this topic has generally indicated the presence of interoceptive deficits in individuals with an eating disorder diagnosis; however, possible links with specific diagnosis, BMI, age, illness duration, depression, and alexithymia remain unclear from individual studies. This meta-analysis aimed to provide a necessary quantitative overview of self-reported interoceptive deficits in eating disorder populations, and the relationship between these deficits and the previously mentioned factors. Using a random effects model, our meta-analysis assessed the magnitude of differences in interoceptive abilities as measured using the Eating Disorder Inventory in 41 samples comparing people with eating disorders (n = 4308) and healthy controls (n = 3459). Follow-up and moderator analysis was conducted, using group comparisons and meta-regressions. We report a large pooled effect size of 1.62 for eating disorders with some variation between diagnostic groups. Further moderator analysis showed that BMI, age and alexithymia were significant predictors of overall effect size. This meta-analysis is the first to confirm that large interoceptive deficits occur in a variety of eating disorders and crucially, in those who have recovered. These deficits may be useful in identifying and distinguishing eating disorders. Future research needs to consider both objective and subjective measures of interoception across different types of eating disorders and may fruitfully examine interoception as a possible endophenotype and target for treatment. Copyright © 2018 Elsevier Inc. All rights reserved.

Pharmacoeconomics of parenteral nutrition in surgical and critically ill patients receiving structured triglycerides in China.

PubMed

Wu, Guo Hao; Ehm, Alexandra; Bellone, Marco; Pradelli, Lorenzo

2017-01-01

A prior meta-analysis showed favorable metabolic effects of structured triglyceride (STG) lipid emulsions in surgical and critically ill patients compared with mixed medium-chain/long-chain triglycerides (MCT/LCT) emulsions. Limited data on clinical outcomes precluded pharmacoeconomic analysis. We performed an updated meta-analysis and developed a cost model to compare overall costs for STGs vs MCT/LCTs in Chinese hospitals. We searched Medline, Embase, Wanfang Data, the China Hospital Knowledge Database, and Google Scholar for clinical trials comparing STGs to mixed MCT/LCTs in surgical or critically ill adults published between October 10, 2013 and September 19, 2015. Newly identified studies were pooled with the prior studies and an updated meta-analysis was performed. A deterministic simulation model was used to compare the effects of STGs and mixed MCT/LCT's on Chinese hospital costs. The literature search identified six new trials, resulting in a total of 27 studies in the updated meta-analysis. Statistically significant differences favoring STGs were observed for cumulative nitrogen balance, pre- albumin and albumin concentrations, plasma triglycerides, and liver enzymes. STGs were also associated with a significant reduction in the length of hospital stay (mean difference, -1.45 days; 95% confidence interval, -2.48 to -0.43; p=0.005) versus mixed MCT/LCTs. Cost analysis demonstrated a net cost benefit of ¥675 compared with mixed MCT/LCTs. STGs are associated with improvements in metabolic function and reduced length of hospitalization in surgical and critically ill patients compared with mixed MCT/LCT emulsions. Cost analysis using data from Chinese hospitals showed a corresponding cost benefit.

Node-Splitting Generalized Linear Mixed Models for Evaluation of Inconsistency in Network Meta-Analysis.

PubMed

Yu-Kang, Tu

2016-12-01

Network meta-analysis for multiple treatment comparisons has been a major development in evidence synthesis methodology. The validity of a network meta-analysis, however, can be threatened by inconsistency in evidence within the network. One particular issue of inconsistency is how to directly evaluate the inconsistency between direct and indirect evidence with regard to the effects difference between two treatments. A Bayesian node-splitting model was first proposed and a similar frequentist side-splitting model has been put forward recently. Yet, assigning the inconsistency parameter to one or the other of the two treatments or splitting the parameter symmetrically between the two treatments can yield different results when multi-arm trials are involved in the evaluation. We aimed to show that a side-splitting model can be viewed as a special case of design-by-treatment interaction model, and different parameterizations correspond to different design-by-treatment interactions. We demonstrated how to evaluate the side-splitting model using the arm-based generalized linear mixed model, and an example data set was used to compare results from the arm-based models with those from the contrast-based models. The three parameterizations of side-splitting make slightly different assumptions: the symmetrical method assumes that both treatments in a treatment contrast contribute to inconsistency between direct and indirect evidence, whereas the other two parameterizations assume that only one of the two treatments contributes to this inconsistency. With this understanding in mind, meta-analysts can then make a choice about how to implement the side-splitting method for their analysis. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Consumption of garlic and risk of colorectal cancer: An updated meta-analysis of prospective studies

PubMed Central

Hu, Ji-Yi; Hu, Yi-Wang; Zhou, Jiao-Jiao; Zhang, Meng-Wen; Li, Dan; Zheng, Shu

2014-01-01

AIM: To conduct an updated meta-analysis of prospective studies addressing the association between garlic consumption and colorectal cancer. METHODS: Eligible cohort studies were identified by searching MEDLINE (PubMed) and screening the references of related articles published up to October 2013. Meta-analyses were conducted for colorectal cancer in relation to consumption of raw and cooked (RC) garlic and garlic supplements, separately. The summary relative risks (RR) with 95%CI were calculated using fixed-effects or random-effects model depending on the heterogeneity among studies. RESULTS: A total of 5 prospective cohort studies were identified. In contrast to the previous meta-analysis, no significant associations were found between consumption of RC garlic (RR: 1.06; 95%CI: 0.95-1.19) or garlic supplements (RR: 1.12; 95%CI: 0.96-1.31) and risk of colorectal cancer. A non-significant protective effect of garlic supplement intake against colorectal cancer was observed in females (RR: 0.84; 95%CI: 0.64-1.11), but the opposite was the case in males (RR: 1.24; 95%CI: 0.96-1.59). CONCLUSION: Consumption of RC garlic or garlic supplements is not significantly associated with reduced colorectal cancer risk. PMID:25386091

Consumption of garlic and risk of colorectal cancer: an updated meta-analysis of prospective studies.

PubMed

Hu, Ji-Yi; Hu, Yi-Wang; Zhou, Jiao-Jiao; Zhang, Meng-Wen; Li, Dan; Zheng, Shu

2014-11-07

To conduct an updated meta-analysis of prospective studies addressing the association between garlic consumption and colorectal cancer. Eligible cohort studies were identified by searching MEDLINE (PubMed) and screening the references of related articles published up to October 2013. Meta-analyses were conducted for colorectal cancer in relation to consumption of raw and cooked (RC) garlic and garlic supplements, separately. The summary relative risks (RR) with 95%CI were calculated using fixed-effects or random-effects model depending on the heterogeneity among studies. A total of 5 prospective cohort studies were identified. In contrast to the previous meta-analysis, no significant associations were found between consumption of RC garlic (RR: 1.06; 95%CI: 0.95-1.19) or garlic supplements (RR: 1.12; 95%CI: 0.96-1.31) and risk of colorectal cancer. A non-significant protective effect of garlic supplement intake against colorectal cancer was observed in females (RR: 0.84; 95%CI: 0.64-1.11), but the opposite was the case in males (RR: 1.24; 95%CI: 0.96-1.59). Consumption of RC garlic or garlic supplements is not significantly associated with reduced colorectal cancer risk.

The Success of Linear Bootstrapping Models: Decision Domain-, Expertise-, and Criterion-Specific Meta-Analysis

PubMed Central

Kaufmann, Esther; Wittmann, Werner W.

2016-01-01

The success of bootstrapping or replacing a human judge with a model (e.g., an equation) has been demonstrated in Paul Meehl’s (1954) seminal work and bolstered by the results of several meta-analyses. To date, however, analyses considering different types of meta-analyses as well as the potential dependence of bootstrapping success on the decision domain, the level of expertise of the human judge, and the criterion for what constitutes an accurate decision have been missing from the literature. In this study, we addressed these research gaps by conducting a meta-analysis of lens model studies. We compared the results of a traditional (bare-bones) meta-analysis with findings of a meta-analysis of the success of bootstrap models corrected for various methodological artifacts. In line with previous studies, we found that bootstrapping was more successful than human judgment. Furthermore, bootstrapping was more successful in studies with an objective decision criterion than in studies with subjective or test score criteria. We did not find clear evidence that the success of bootstrapping depended on the decision domain (e.g., education or medicine) or on the judge’s level of expertise (novice or expert). Correction of methodological artifacts increased the estimated success of bootstrapping, suggesting that previous analyses without artifact correction (i.e., traditional meta-analyses) may have underestimated the value of bootstrapping models. PMID:27327085

Maternal dietary nitrate intake and risk of neural tube defects: A systematic review and dose-response meta-analysis.

PubMed

Kakavandi, Nader Rahimi; Hasanvand, Amin; Ghazi-Khansari, Mahmoud; Sezavar, Ahmad Habibian; Nabizadeh, Hassan; Parohan, Mohammad

2018-05-12

Despite growing evidence for the potential teratogenicity of nitrate, knowledge about the dose-response relationship of dietary nitrate intake and risk of specific birth defects such as neural tube defects (NTDs) is limited. Therefore, the aim of this meta-analysis was to synthesize the knowledge about the dose-response relation between maternal dietary nitrate intake and the risk of NTDs. We conducted a systematic search in PubMed, ISI Web of Science and Scopus up to February 2018 for observational studies. Risk ratios (RRs) and 95% confidence intervals (95% CI) were calculated using a random-effects model for highest versus lowest intake categories. The linear and non-linear relationships between nitrate intake and risk of NTDs were also investigated. Overall, 5 studies were included in the meta-analyses. No association was observed between nitrate intake and NTDs risk in high versus low intake (RR: 1.33; 95% CI: 0.89-1.99, p = 0.158) and linear dose-response (RR: 1.03; 95% CI: 0.99-1.07, p = 0.141) meta-analysis. However, there were positive relationships between nitrate intake and risk of NTDs in non-linear (p non-linearity <0.05) model. Findings from this dose-response meta-analysis indicate that maternal nitrate intake higher than ∼3 mg/day is positively associated with NTDs risk. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Influence of Judgment Calls on Meta-Analytic Findings.

PubMed

Tarrahi, Farid; Eisend, Martin

2016-01-01

Previous research has suggested that judgment calls (i.e., methodological choices made in the process of conducting a meta-analysis) have a strong influence on meta-analytic findings and question their robustness. However, prior research applies case study comparison or reanalysis of a few meta-analyses with a focus on a few selected judgment calls. These studies neglect the fact that different judgment calls are related to each other and simultaneously influence the outcomes of a meta-analysis, and that meta-analytic findings can vary due to non-judgment call differences between meta-analyses (e.g., variations of effects over time). The current study analyzes the influence of 13 judgment calls in 176 meta-analyses in marketing research by applying a multivariate, multilevel meta-meta-analysis. The analysis considers simultaneous influences from different judgment calls on meta-analytic effect sizes and controls for alternative explanations based on non-judgment call differences between meta-analyses. The findings suggest that judgment calls have only a minor influence on meta-analytic findings, whereas non-judgment call differences between meta-analyses are more likely to explain differences in meta-analytic findings. The findings support the robustness of meta-analytic results and conclusions.

Prophylactic intra-aortic balloon pump in high-risk patients undergoing coronary artery bypass surgery: a meta-analysis of randomized controlled trials.

PubMed

Sá, Michel Pompeu B O; Ferraz, Paulo E; Escobar, Rodrigo R; Martins, Wendell N; Nunes, Eliobas O; Vasconcelos, Frederico P; Lima, Ricardo C

2012-11-01

The aim of this study was to assess the efficacy of a prophylactic intra-aortic balloon pump (IABP) in high-risk patients undergoing coronary artery bypass graft surgery. MEDLINE, EMBASE, CENTRAL/CCTR, SciELO, LILACS, Google Scholar, and reference lists of relevant articles were searched. We included only randomized controlled trials. Assessments for eligibility, relevance, and study validity and data extraction were performed in duplicate using prespecified criteria. Meta-analysis was carried out using fixed-effect and random-effect models. Seven publications fulfilled our eligibility criteria. There was no important statistical heterogeneity or publication bias among included studies. In total, 177 patients received prophylactic IABP and 168 did not. Overall relative risk (RR) for hospital mortality in patients treated with prophylactic IABP was 0.255 [95% confidence interval (CI), 0.122-0.533; P<0.001; same results for both effect models]. Pooled RR for postoperative low cardiac output syndrome was 0.206 (95% CI, 0.109-0.389; P<0.001) for the fixed-effect model and 0.219 (95% CI, 0.095-0.504; P<0.001) for the random-effect model. Patients treated with prophylactic IABP presented an overall difference in means for length of intensive care unit stay and hospital stay, which was lower than that in the control group (P<0.001 for both effect models). Only 7.4% (13/177) of patients who received prophylactic IABP developed complications at an insertion site, with no IABP-related death. This meta-analysis supports the use of prophylactic IABP in high-risk patients to reduce hospital mortality. © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins.

The effectiveness of theory- and model-based lifestyle interventions on HbA1c among patients with type 2 diabetes: a systematic review and meta-analysis.

PubMed

Doshmangir, P; Jahangiry, L; Farhangi, M A; Doshmangir, L; Faraji, L

2018-02-01

The prevalence of type 2 diabetes is rising rapidly around the world. A number of systematic reviews have provided evidence for the effectiveness of lifestyle interventions on diabetic patients. The effectiveness of theory- and model-based education-lifestyle interventions for diabetic patients are unclear. The systematic review and meta-analysis aimed to evaluate and quantify the impact of theory-based lifestyle interventions on type 2 diabetes. A literature search of authentic electronic resources including PubMed, Scopus, and Cochrane collaboration was performed to identify published papers between January 2002 and July 2016. The PICOs (participants, intervention, comparison, and outcomes) elements were used for the selection of studies to meet the inclusion and exclusion criteria. Mean differences and standard deviations of hemoglobin A1c (HbA1c [mmol/mol]) level in baseline and follow-up measures of studies in intervention and control groups were considered for data synthesis. A random-effects model was used for estimating pooled effect sizes. To investigate the source of heterogeneity, predefined subgroup analyses were performed using trial duration, baseline HbA1c (mmol/mol) level, and the age of participants. Meta-regression was performed to examine the contribution of trial duration, baseline HbA1c (mmol/mol) level, the age of participants, and mean differences of HbA1c (mmol/mol) level. The significant level was considered P < 0.05. Eighteen studies with 2384 participants met the inclusion criteria. The pooled main outcomes by random-effects model showed significant improvements in HbA1c (mmol/mol) -5.35% (95% confidence interval = -6.3, -4.40; P < 0.001) with the evidence of heterogeneity across studies. The findings of this meta-analysis suggest that theory- and model-based lifestyle interventions have positive effects on HbA1c (mmol/mol) indices in patients with type 2 diabetes. Health education theories have been applied as a useful tool for lifestyle change among people with type 2 diabetes. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

The RTEL1 rs6010620 polymorphism and glioma risk: a meta-analysis based on 12 case-control studies.

PubMed

Du, Shu-Li; Geng, Ting-Ting; Feng, Tian; Chen, Cui-Ping; Jin, Tian-Bo; Chen, Chao

2014-01-01

The association between the RTEL1 rs6010620 single nucleotide polymorphism (SNP) and glioma risk has been extensively studied. However, the results remain inconclusive. To further examine this association, we performed a meta-analysis. A computerized search of the PubMed and Embase databases for publications regarding the RTEL1 rs6010620 polymorphism and glioma cancer risk was performed. Genotype data were analyzed in a meta-analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated to assess the association. Sensitivity analyses, tests of heterogeneity, cumulative meta-analyses, and assessments of bias were performed in our meta-analysis. Our meta-analysis confirmed that risk with allele A is lower than with allele G for glioma. The A allele of rs6010620 in RTEL1 decreased the risk of developing glioma in the 12 case-control studies for all genetic models: the allele model (OR=0.752, 95%CI: 0.715-0.792), the dominant model (OR=0.729, 95%CI: 0.685-0.776), the recessive model (OR=0.647, 95%CI: 0.569-0.734), the homozygote comparison (OR=0.528, 95%CI: 0.456-0.612), and the heterozygote comparison (OR=0.761, 95%CI: 0.713-0.812). In all genetic models, the association between the RTEL1 rs6010620 polymorphism and glioma risk was significant. This meta-analysis suggests that the RTEL1 rs6010620 polymorphism may be a risk factor for glioma. Further functional studies evaluating this polymorphism and glioma risk are warranted.

Modeling Longitudinal Data with Generalized Additive Models: Applications to Single-Case Designs

ERIC Educational Resources Information Center

Sullivan, Kristynn J.; Shadish, William R.

2013-01-01

Single case designs (SCDs) are short time series that assess intervention effects by measuring units repeatedly over time both in the presence and absence of treatment. For a variety of reasons, interest in the statistical analysis and meta-analysis of these designs has been growing in recent years. This paper proposes modeling SCD data with…

A hybrid Bayesian hierarchical model combining cohort and case-control studies for meta-analysis of diagnostic tests: Accounting for partial verification bias.

PubMed

Ma, Xiaoye; Chen, Yong; Cole, Stephen R; Chu, Haitao

2016-12-01

To account for between-study heterogeneity in meta-analysis of diagnostic accuracy studies, bivariate random effects models have been recommended to jointly model the sensitivities and specificities. As study design and population vary, the definition of disease status or severity could differ across studies. Consequently, sensitivity and specificity may be correlated with disease prevalence. To account for this dependence, a trivariate random effects model had been proposed. However, the proposed approach can only include cohort studies with information estimating study-specific disease prevalence. In addition, some diagnostic accuracy studies only select a subset of samples to be verified by the reference test. It is known that ignoring unverified subjects may lead to partial verification bias in the estimation of prevalence, sensitivities, and specificities in a single study. However, the impact of this bias on a meta-analysis has not been investigated. In this paper, we propose a novel hybrid Bayesian hierarchical model combining cohort and case-control studies and correcting partial verification bias at the same time. We investigate the performance of the proposed methods through a set of simulation studies. Two case studies on assessing the diagnostic accuracy of gadolinium-enhanced magnetic resonance imaging in detecting lymph node metastases and of adrenal fluorine-18 fluorodeoxyglucose positron emission tomography in characterizing adrenal masses are presented. © The Author(s) 2014.

A Hybrid Bayesian Hierarchical Model Combining Cohort and Case-control Studies for Meta-analysis of Diagnostic Tests: Accounting for Partial Verification Bias

PubMed Central

Ma, Xiaoye; Chen, Yong; Cole, Stephen R.; Chu, Haitao

2014-01-01

To account for between-study heterogeneity in meta-analysis of diagnostic accuracy studies, bivariate random effects models have been recommended to jointly model the sensitivities and specificities. As study design and population vary, the definition of disease status or severity could differ across studies. Consequently, sensitivity and specificity may be correlated with disease prevalence. To account for this dependence, a trivariate random effects model had been proposed. However, the proposed approach can only include cohort studies with information estimating study-specific disease prevalence. In addition, some diagnostic accuracy studies only select a subset of samples to be verified by the reference test. It is known that ignoring unverified subjects may lead to partial verification bias in the estimation of prevalence, sensitivities and specificities in a single study. However, the impact of this bias on a meta-analysis has not been investigated. In this paper, we propose a novel hybrid Bayesian hierarchical model combining cohort and case-control studies and correcting partial verification bias at the same time. We investigate the performance of the proposed methods through a set of simulation studies. Two case studies on assessing the diagnostic accuracy of gadolinium-enhanced magnetic resonance imaging in detecting lymph node metastases and of adrenal fluorine-18 fluorodeoxyglucose positron emission tomography in characterizing adrenal masses are presented. PMID:24862512

Publication bias and the limited strength model of self-control: has the evidence for ego depletion been overestimated?

PubMed

Carter, Evan C; McCullough, Michael E

2014-01-01

Few models of self-control have generated as much scientific interest as has the limited strength model. One of the entailments of this model, the depletion effect, is the expectation that acts of self-control will be less effective when they follow prior acts of self-control. Results from a previous meta-analysis concluded that the depletion effect is robust and medium in magnitude (d = 0.62). However, when we applied methods for estimating and correcting for small-study effects (such as publication bias) to the data from this previous meta-analysis effort, we found very strong signals of publication bias, along with an indication that the depletion effect is actually no different from zero. We conclude that until greater certainty about the size of the depletion effect can be established, circumspection about the existence of this phenomenon is warranted, and that rather than elaborating on the model, research efforts should focus on establishing whether the basic effect exists. We argue that the evidence for the depletion effect is a useful case study for illustrating the dangers of small-study effects as well as some of the possible tools for mitigating their influence in psychological science.

Nerve growth factor for Bell’s palsy: A meta-analysis

PubMed Central

SU, YIPENG; DONG, XIAOMENG; LIU, JUAN; HU, YAOZHI; CHEN, JINBO

2015-01-01

A meta-analysis was performed to evaluate the efficacy and safety of nerve growth factor (NGF) in the treatment of Bell’s palsy. PubMed, the Cochrane Central Register of Controlled Trials, Embase and a number of Chinese databases, including the China National Knowledge Infrastructure, China Biology Medicine disc, VIP Database for Chinese Technical Periodicals and Wan Fang Data, were used to collect randomised controlled trials (RCTs) of NGF for Bell’s palsy. The span of the search covered data from the date of database establishment until December 2013. The included trials were screened comprehensively and rigorously. The efficacies of NGF were pooled via meta-analysis performed using Review Manager 5.2 software. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using the fixed-effects model. The meta-analysis of eight RCTs showed favorable effects of NGF on the disease response rate (n=642; OR, 3.87; 95% CI, 2.13–7.03; P<0.01; I2=0%). However, evidence supporting the effectiveness of NGF for the treatment of Bell’s palsy is limited. The number and quality of trials are too low to form solid conclusions. Further meticulous RCTs are required to overcome the limitations identified in the present study. PMID:25574223

Hypothyroidism as a risk factor for open angle glaucoma: A systematic review and meta-analysis

PubMed Central

Liu, Yue; Zheng, Guangying

2017-01-01

Purpose The relationship between hypothyroidism and primary open angle glaucoma (POAG) has attracted intense interest recently, but the reported results have been controversial. This meta-analysis was carried out to determine the association between hypothyroidism and POAG. Methods The literature was identified from three databases (Web of Science, Embase, and PubMed). The meta-analyses were performed using random-effects models, with results reported as adjusted odds ratios (ORs) with 95% confidence intervals (CI 95%). Results A total of 11 studies meeting the inclusion criteria were included in the final meta-analysis. The pooled OR based on 11 risk estimates showed a statistically significant increased risk of POAG prevalence among individuals with hypothyroidism (OR = 1.64, 95% CI = 1.27–2.13). Substantial heterogeneity among these studies was detected (P < 0.001; I2 = 83.2%). Sub-group analysis revealed that the cohort studies and case–control studies showed a significant association between hypothyroidism and POAG, which was not observed in cross-sectional studies. There was no significant publication bias in this study. Conclusions The findings of this meta-analysis indicate that individuals with hypothyroidism have an increased risk of developing POAG. PMID:29069095

Using aggregate data to estimate the standard error of a treatment-covariate interaction in an individual patient data meta-analysis.

PubMed

Kovalchik, Stephanie A; Cumberland, William G

2012-05-01

Subgroup analyses are important to medical research because they shed light on the heterogeneity of treatment effectts. A treatment-covariate interaction in an individual patient data (IPD) meta-analysis is the most reliable means to estimate how a subgroup factor modifies a treatment's effectiveness. However, owing to the challenges in collecting participant data, an approach based on aggregate data might be the only option. In these circumstances, it would be useful to assess the relative efficiency and power loss of a subgroup analysis without patient-level data. We present methods that use aggregate data to estimate the standard error of an IPD meta-analysis' treatment-covariate interaction for regression models of a continuous or dichotomous patient outcome. Numerical studies indicate that the estimators have good accuracy. An application to a previously published meta-regression illustrates the practical utility of the methodology. © 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Health utility of patients with Crohn's disease and ulcerative colitis: a systematic review and meta-analysis.

PubMed

Malinowski, Krzysztof Piotr; Kawalec, Paweł

2016-08-01

The aim of this systematic review was to collect and summarize the current data on the utilities of patients with Crohn's disease (CD) and ulcerative colitis (UC). A meta-analysis of the obtained utilities was performed using a random-effects model and meta-regression by the disease type and severity. A bootstrap analysis was performed as it does not require assumption on distribution of the data. The highest utility among patients with CD and UC was observed when the diseases were in remission. The meta-regression analysis showed that both disease severity and an instrument/method/questionnaire used to obtain utilities were significant predictors of utility. Utility was the lowest for severe disease and the highest for disease in remission, the association was more notable in patients with CD compared with UC. Expert commentary: The issue of patients' utility is important for healthcare decision makers but it has not been fully investigated and requires further study.

Meta-Analysis of the Relation Between IL10 Promoter Polymorphisms and Autoimmune Liver Disease Risk.

PubMed

Qian, Bao-Xin; Ye, Qing; Zhao, Xin-Yu; Han, Tao; Wang, Feng-Mei; Yang, Jie

2018-05-01

Single nucleotide polymorphisms of the IL10 gene have been linked to the occurrence of autoimmune liver disease. We performed a meta-analysis to assess the association between three IL10 promoter polymorphisms (rs1800896, rs1800871, and rs1800872) and the risk of autoimmune hepatitis, primary biliary cholangitis, and primary sclerosing cholangitis. In total, 1420 articles were initially identified through database retrieval. After screening, seven eligible articles were ultimately included in the meta-analysis. A fixed-effect model was used for all Mantel-Haenszel statistics due to the absence of large between-study heterogeneity (all I 2 < 50%, p > 0.1). No association between any of the studied polymorphisms and risk of autoimmune liver disease was detected in the allele, homozygote, heterozygote, dominant, recessive, or carrier genetic models (p association > 0.05). Potential publication bias was excluded using Begg's and Egger's tests. Similar negative results were observed in subgroup analyses and in an analysis of the three haplotypes of rs1800896/rs1800871/rs1800872 (G/C/C, A/C/C, and A/T/A). Our meta-analysis strongly suggests that the IL10 rs1800896, rs1800871, and rs1800872 polymorphisms are not associated with the risk of autoimmune liver disease.

Living network meta-analysis compared with pairwise meta-analysis in comparative effectiveness research: empirical study

PubMed Central

Nikolakopoulou, Adriani; Mavridis, Dimitris; Furukawa, Toshi A; Cipriani, Andrea; Tricco, Andrea C; Straus, Sharon E; Siontis, George C M; Egger, Matthias

2018-01-01

Abstract Objective To examine whether the continuous updating of networks of prospectively planned randomised controlled trials (RCTs) (“living” network meta-analysis) provides strong evidence against the null hypothesis in comparative effectiveness of medical interventions earlier than the updating of conventional, pairwise meta-analysis. Design Empirical study of the accumulating evidence about the comparative effectiveness of clinical interventions. Data sources Database of network meta-analyses of RCTs identified through searches of Medline, Embase, and the Cochrane Database of Systematic Reviews until 14 April 2015. Eligibility criteria for study selection Network meta-analyses published after January 2012 that compared at least five treatments and included at least 20 RCTs. Clinical experts were asked to identify in each network the treatment comparison of greatest clinical interest. Comparisons were excluded for which direct and indirect evidence disagreed, based on side, or node, splitting test (P<0.10). Outcomes and analysis Cumulative pairwise and network meta-analyses were performed for each selected comparison. Monitoring boundaries of statistical significance were constructed and the evidence against the null hypothesis was considered to be strong when the monitoring boundaries were crossed. A significance level was defined as α=5%, power of 90% (β=10%), and an anticipated treatment effect to detect equal to the final estimate from the network meta-analysis. The frequency and time to strong evidence was compared against the null hypothesis between pairwise and network meta-analyses. Results 49 comparisons of interest from 44 networks were included; most (n=39, 80%) were between active drugs, mainly from the specialties of cardiology, endocrinology, psychiatry, and rheumatology. 29 comparisons were informed by both direct and indirect evidence (59%), 13 by indirect evidence (27%), and 7 by direct evidence (14%). Both network and pairwise meta-analysis provided strong evidence against the null hypothesis for seven comparisons, but for an additional 10 comparisons only network meta-analysis provided strong evidence against the null hypothesis (P=0.002). The median time to strong evidence against the null hypothesis was 19 years with living network meta-analysis and 23 years with living pairwise meta-analysis (hazard ratio 2.78, 95% confidence interval 1.00 to 7.72, P=0.05). Studies directly comparing the treatments of interest continued to be published for eight comparisons after strong evidence had become evident in network meta-analysis. Conclusions In comparative effectiveness research, prospectively planned living network meta-analyses produced strong evidence against the null hypothesis more often and earlier than conventional, pairwise meta-analyses. PMID:29490922

Meta-Analytic Structural Equation Modeling (MASEM): Comparison of the Multivariate Methods

ERIC Educational Resources Information Center

Zhang, Ying

2011-01-01

Meta-analytic Structural Equation Modeling (MASEM) has drawn interest from many researchers recently. In doing MASEM, researchers usually first synthesize correlation matrices across studies using meta-analysis techniques and then analyze the pooled correlation matrix using structural equation modeling techniques. Several multivariate methods of…

Short-term effects of air quality and thermal stress on non-accidental morbidity-a multivariate meta-analysis comparing indices to single measures.

PubMed

Lokys, Hanna Leona; Junk, Jürgen; Krein, Andreas

2018-01-01

Air quality and thermal stress lead to increased morbidity and mortality. Studies on morbidity and the combined impact of air pollution and thermal stress are still rare. To analyse the correlations between air quality, thermal stress and morbidity, we used a two-stage meta-analysis approach, consisting of a Poisson regression model combined with distributed lag non-linear models (DLNMs) and a meta-analysis investigating whether latitude or the number of inhabitants significantly influence the correlations. We used air pollution, meteorological and hospital admission data from 28 administrative districts along a north-south gradient in western Germany from 2001 to 2011. We compared the performance of the single measure particulate matter (PM10) and air temperature to air quality indices (MPI and CAQI) and the biometeorological index UTCI. Based on the Akaike information criterion (AIC), it can be shown that using air quality indices instead of single measures increases the model strength. However, using the UTCI in the model does not give additional information compared to mean air temperature. Interaction between the 3-day average of air quality (max PM10, max CAQI and max MPI) and meteorology (mean air temperature and mean UTCI) did not improve the models. Using the mean air temperature, we found immediate effects of heat stress (RR 1.0013, 95% CI: 0.9983-1.0043) and by 3 days delayed effects of cold stress (RR: 1.0184, 95% CI: 1.0117-1.0252). The results for air quality differ between both air quality indices and PM10. CAQI and MPI show a delayed impact on morbidity with a maximum RR after 2 days (MPI 1.0058, 95% CI: 1.0013-1.0102; CAQI 1.0068, 95% CI: 1.0030-1.0107). Latitude was identified as a significant meta-variable, whereas the number of inhabitants was not significant in the model.

Short-term effects of air quality and thermal stress on non-accidental morbidity—a multivariate meta-analysis comparing indices to single measures

NASA Astrophysics Data System (ADS)

Lokys, Hanna Leona; Junk, Jürgen; Krein, Andreas

2018-01-01

Air quality and thermal stress lead to increased morbidity and mortality. Studies on morbidity and the combined impact of air pollution and thermal stress are still rare. To analyse the correlations between air quality, thermal stress and morbidity, we used a two-stage meta-analysis approach, consisting of a Poisson regression model combined with distributed lag non-linear models (DLNMs) and a meta-analysis investigating whether latitude or the number of inhabitants significantly influence the correlations. We used air pollution, meteorological and hospital admission data from 28 administrative districts along a north-south gradient in western Germany from 2001 to 2011. We compared the performance of the single measure particulate matter (PM10) and air temperature to air quality indices (MPI and CAQI) and the biometeorological index UTCI. Based on the Akaike information criterion (AIC), it can be shown that using air quality indices instead of single measures increases the model strength. However, using the UTCI in the model does not give additional information compared to mean air temperature. Interaction between the 3-day average of air quality (max PM10, max CAQI and max MPI) and meteorology (mean air temperature and mean UTCI) did not improve the models. Using the mean air temperature, we found immediate effects of heat stress (RR 1.0013, 95% CI: 0.9983-1.0043) and by 3 days delayed effects of cold stress (RR: 1.0184, 95% CI: 1.0117-1.0252). The results for air quality differ between both air quality indices and PM10. CAQI and MPI show a delayed impact on morbidity with a maximum RR after 2 days (MPI 1.0058, 95% CI: 1.0013-1.0102; CAQI 1.0068, 95% CI: 1.0030-1.0107). Latitude was identified as a significant meta-variable, whereas the number of inhabitants was not significant in the model.

The Effect of 7E Learning Cycle on Learning in Science Teaching: A Meta-Analysis Study

ERIC Educational Resources Information Center

Balta, Nuri; Sarac, Hakan

2016-01-01

This article reports the results of a meta-analysis of the effectiveness of 7E learning cycle in science teaching. Totally 35 different effect sizes from 24 experimental studies, comprising 2918 students were included in the meta-analysis. The results confirmed that 7E learning cycle have a positive effect on students' achievement. The overall…

Neither fixed nor random: weighted least squares meta-analysis.

PubMed

Stanley, T D; Doucouliagos, Hristos

2015-06-15

This study challenges two core conventional meta-analysis methods: fixed effect and random effects. We show how and explain why an unrestricted weighted least squares estimator is superior to conventional random-effects meta-analysis when there is publication (or small-sample) bias and better than a fixed-effect weighted average if there is heterogeneity. Statistical theory and simulations of effect sizes, log odds ratios and regression coefficients demonstrate that this unrestricted weighted least squares estimator provides satisfactory estimates and confidence intervals that are comparable to random effects when there is no publication (or small-sample) bias and identical to fixed-effect meta-analysis when there is no heterogeneity. When there is publication selection bias, the unrestricted weighted least squares approach dominates random effects; when there is excess heterogeneity, it is clearly superior to fixed-effect meta-analysis. In practical applications, an unrestricted weighted least squares weighted average will often provide superior estimates to both conventional fixed and random effects. Copyright © 2015 John Wiley & Sons, Ltd.

Does Bruxism Contribute to Dental Implant Failure? A Systematic Review and Meta-Analysis.

PubMed

Zhou, Yi; Gao, Jinxia; Luo, Le; Wang, Yining

2016-04-01

Bruxism was usually considered as a contraindication for oral implanting. The causal relationship between bruxism and dental implant failure was remained controversial in existing literatures. This meta-analysis was performed to investigate the relationship between them. This review conducted an electronic systematic literature search in MEDLINE (PubMed) and EmBase in November 2013 without time and language restrictions. Meanwhile, a hand searching for all the relevant references of included studies was also conducted. Study information extraction and methodological quality assessments were accomplished by two reviewers independently. A discussion ensued if any disagreement occurred, and unresolved issues were solved by consulting a third reviewer. Methodological quality was assessed by using the Newcastle-Ottawa Scale tool. Odds ratio (OR) with 95% confidence interval (CI) was pooled to estimate the relative effect of bruxism on dental implant failures. Fixed effects model was used initially; if the heterogeneity was high, random effects model was chosen for meta-analysis. Statistical analyses were carried out by using Review Manager 5.1. In this meta-analysis review, extracted data were classified into two groups based on different units. Units were based on the number of prostheses (group A) and the number of patients (group B). In group A, the total pooled OR of bruxers versus nonbruxers for all subgroups was 4.72 (95% CI: 2.66-8.36, p = .07). In group B, the total pooled OR of bruxers versus nonbruxers for all subgroups was 3.83 (95% CI: 2.12-6.94, p = .22). This meta-analysis was performed to evaluate the relationship between bruxism and dental implant failure. In contrast to nonbruxers, prostheses in bruxers had a higher failure rate. It suggests that bruxism is a contributing factor of causing the occurrence of dental implant technical/biological complications and plays a role in dental implant failure. © 2015 Wiley Periodicals, Inc.

Oxidative Damage Induced by Arsenic in Mice or Rats: A Systematic Review and Meta-Analysis.

PubMed

Xu, Mengchuan; Rui, Dongsheng; Yan, Yizhong; Xu, Shangzhi; Niu, Qiang; Feng, Gangling; Wang, Yan; Li, Shugang; Jing, Mingxia

2017-03-01

In this meta-analysis, studies reporting arsenic-induced oxidative damage in mouse models were systematically evaluated to provide a scientific understanding of oxidative stress mechanisms associated with arsenic poisoning. Fifty-eight relevant peer-reviewed publications were identified through exhaustive database searching. Oxidative stress indexes assessed included superoxide dismutase (SOD), catalase (CAT), glutathione (GSH), glutathione peroxidase (GPx), glutathione-s-transferase (GST), glutathione reductase (GR), oxidized glutathione (GSSG), malondialdehyde (MDA), and reactive oxygen species (ROS). Our meta-analysis showed that arsenic exposure generally suppressed measured levels of the antioxidants, SOD, CAT, GSH, GPx, GST, and GR, but increased levels of the oxidants, GSSG, MDA, and ROS. Arsenic valence was important and GR and MDA levels increased to a significantly (P < 0.05) greater extent upon exposure to As 3+ than to As 5+ . Other factors that contributed to a greater overall oxidative effect from arsenic exposure included intervention time, intervention method, dosage, age of animals, and the sample source from which the indexes were estimated. Our meta-analysis effectively summarized a wide range of studies and detected a positive relationship between arsenic exposure and oxidative damage. These data provide a scientific basis for the prevention and treatment of arsenic poisoning.

Effect of 3-Hydroxy-3-Methylglutaryl-Coenzyme A Reductase Inhibitor on Disease Activity in Patients With Rheumatoid Arthritis

PubMed Central

Xing, Bin; Yin, Yu-Feng; Zhao, Li-Dan; Wang, Li; Zheng, Wen-Jie; Chen, Hua; Wu, Qing-Jun; Tang, Fu-Lin; Zhang, Feng-Chun; Shan, Guangliang; Zhang, Xuan

2015-01-01

Abstract HMG-CoA reductase inhibitors (also known as statins) are widely used as lipid-lowering agents in patients with rheumatoid arthritis (RA) to reduce their cardiovascular risk. However, whether they have an effect on RA disease activity is controversial. This study aimed to investigate the effect of statins on disease activity in RA patients. A systematic literature review was performed using the MEDLINE, EMBASE, Cochrane Library, ISI WEB of Knowledge, Scopus, and Clinical Trials Register databases. Only prospective randomized controlled trials or controlled clinical trials comparing the efficacy of statins with placebo on adult RA patients were included. The efficacy was measured according to the ACR criteria, EULAR criteria, DAS28, HAQ score, ESR, or CRP. The Jadad score was used for quality assessment. The inverse variance method was used to analyze continuous outcomes. A fixed-effects model was used when there was no significant heterogeneity; otherwise, a random-effects model was used. For stability of results, we performed leave-one-study-out sensitivity analysis by omitting individual studies one at a time from the meta-analysis. Publication bias was assessed using Egger test. A total 13 studies involving 737 patients were included in the meta-analysis; 11 studies were included in the meta-analysis based on DAS28, while the other 2 studies were only included in the meta-analysis based on ESR or CRP. The standardized mean difference (SMD) in DAS28 between the statin group and the placebo group was −0.55 (95% CI [−0.83, −0.26], P = 0.0002), with an I2 value of 68%. Subgroup analysis showed that patients with more active disease tended to benefit more from statin therapy (SMD −0.73, P = 0.01) than patients with moderate or low disease activity (SMD −0.38, P = 0.03). Statin therapy also significantly reduced tender joint counts, swollen joint counts, ESR, and CRP compared with placebo, but the reduction in HAQ score and VAS was not significant (P > 0.05). This meta-analysis suggested that statin therapy might be effective in the reduction of RA disease activity measured by DAS28, TJC, SJC, as well as ESR and CRP. PMID:25715256

Association of inorganic arsenic exposure with liver cancer mortality: A meta-analysis.

PubMed

Wang, Weijing; Cheng, Shuo; Zhang, Dongfeng

2014-11-01

The association of long-term inorganic arsenic (iAs) exposure through drinking water with risk of liver cancer mortality remains controversial. Therefore, we reviewed and quantitatively summarized the evidence from observational studies with a meta-analysis. Pertinent studies were identified by searching PubMed and China National Knowledge Infrastructure through May 2014 and by reviewing the reference lists of retrieved articles. Studies that reported standardized mortality ratios (SMRs) with 95% confidence interval (95% CIs) for the association of iAs in drinking water with liver cancer were eligible. The random effect model was adopted as the pooling method to generate summary effect estimates (meta-SMRs). Of the 4851 articles identified through searching databases, 7 articles including 12 studies were included in the meta-analysis. The meta-SMR with 95% CI of liver cancer for the highest versus lowest category of iAs exposure level in drinking water was 1.80 (1.61 to 2.02). Furthermore, an increased risk of liver cancer mortality was found in both females [1.80 (1.45 to 2.24)] and males [1.84 (1.56 to 2.16)]. In subgroup analysis, the meta-SMRs were 1.93 (1.72 to 2.15) for cohort studies, 1.60 (1.22 to 2.10) for ecological studies, 1.93 (1.72 to 2.15) for studies conducted in Asia, and 1.60 (1.22 to 2.10) for studies conducted in South America, respectively. After removing the 3 studies conducted by Smith et al. (having two studies separately for males and females) and Chen et al. that had a strong effect on heterogeneity, a significant association was also found [1.85 (1.72 to 1.99)]. This meta-analysis indicates that long-term iAs exposure through drinking water increases the risk of liver cancer mortality. Copyright © 2014 Elsevier Inc. All rights reserved.

A Systematic Review and Meta-Analysis of Baseline Ohip-Edent Scores.

PubMed

Duale, J M J; Patel, Y A; Wu, J; Hyde, T P

2018-03-01

OHIP-EDENT is widely used in the literature to assess Oral-Health-Related-Quality-of-Life (OHRQoL) for edentulous patients. However the normal variance and mean of the baseline OHIP scores has not been reported. It would facilitate critical appraisal of studies if we had knowledge of the normal variation and mean of baseline OHIP-EDENT scores. An established figure for baseline OHIP-EDENT, obtained from a meta-analysis, would simplify comparisons of studies and quantify variations in initial OHRQoL of the trial participants. The aim of this study is to quantify a normal baseline value for pre-operative OHIP-EDENT scores by a systematic review and meta-analysis of the available literature. A systematic literature review was carried. 83 papers were identified that included OHIP-EDENT values. After screening and eligibility assessment, 7 papers were selected and included in the meta-analysis. A meta-analysis for the 7 papers by a random-effect model yielded a mean baseline OHIP-EDENT score of 28.63 with a 95% Confidence intervals from 21.93 to 35.34. A pre-operative baseline OHIP-EDENT has been established by meta-analysis of published papers. This will facilitate the comparison of the initial OHRQoL of one study population to that found elsewhere in the published literature. Copyright© 2018 Dennis Barber Ltd.

Fruit and vegetable intake and breast cancer prognosis: a meta-analysis of prospective cohort studies.

PubMed

Peng, Chen; Luo, Wei-Ping; Zhang, Cai-Xia

2017-03-01

The effect of fruit and vegetable intake on breast cancer prognosis is controversial. Thus, a meta-analysis was carried out to explore their associations. A comprehensive search was conducted in PubMed, Web of Science, OVID, ProQuest and Chinese databases from inception to April 2016. The summary hazard ratios (HR) and 95 % CI were estimated using a random effects model if substantial heterogeneity existed and using a fixed effects model if not. Subgroup analyses and sensitivity analyses were also performed. In total, twelve studies comprising 41 185 participants were included in the meta-analysis. Comparing the highest with the lowest, the summary HR for all-cause mortality were 1·01 (95 % CI 0·72, 1·42) for fruits and vegetables combined, 0·96 (95 % CI 0·83, 1·12) for total vegetable intake, 0·99 (95 % CI 0·89, 1·11) for cruciferous vegetable intake and 0·88 (95 % CI 0·74, 1·05) for fruit intake; those for breast cancer-specific mortality were 1·05 (95 % CI 0·77, 1·43) for total vegetable intake and 0·94 (95 % CI 0·69, 1·26) for fruit intake; and those for breast cancer recurrence were 0·89 (95 % CI 0·53, 1·50) for total vegetable intake and 0·98 (95 % CI 0·76, 1·26) for cruciferous vegetable intake. This meta-analysis found no significant associations between fruit and vegetable intake and breast cancer prognosis.

Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model.

PubMed

Snell, Kym I E; Hua, Harry; Debray, Thomas P A; Ensor, Joie; Look, Maxime P; Moons, Karel G M; Riley, Richard D

2016-01-01

Our aim was to improve meta-analysis methods for summarizing a prediction model's performance when individual participant data are available from multiple studies for external validation. We suggest multivariate meta-analysis for jointly synthesizing calibration and discrimination performance, while accounting for their correlation. The approach estimates a prediction model's average performance, the heterogeneity in performance across populations, and the probability of "good" performance in new populations. This allows different implementation strategies (e.g., recalibration) to be compared. Application is made to a diagnostic model for deep vein thrombosis (DVT) and a prognostic model for breast cancer mortality. In both examples, multivariate meta-analysis reveals that calibration performance is excellent on average but highly heterogeneous across populations unless the model's intercept (baseline hazard) is recalibrated. For the cancer model, the probability of "good" performance (defined by C statistic ≥0.7 and calibration slope between 0.9 and 1.1) in a new population was 0.67 with recalibration but 0.22 without recalibration. For the DVT model, even with recalibration, there was only a 0.03 probability of "good" performance. Multivariate meta-analysis can be used to externally validate a prediction model's calibration and discrimination performance across multiple populations and to evaluate different implementation strategies. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Non-invasive brain stimulation to investigate language production in healthy speakers: A meta-analysis.

PubMed

Klaus, Jana; Schutter, Dennis J L G

2018-06-01

Non-invasive brain stimulation (NIBS) has become a common method to study the interrelations between the brain and language functioning. This meta-analysis examined the efficacy of transcranial magnetic stimulation (TMS) and direct current stimulation (tDCS) in the study of language production in healthy volunteers. Forty-five effect sizes from 30 studies which investigated the effects of NIBS on picture naming or verbal fluency in healthy participants were meta-analysed. Further sub-analyses investigated potential influences of stimulation type, control, target site, task, online vs. offline application, and current density of the target electrode. Random effects modelling showed a small, but reliable effect of NIBS on language production. Subsequent analyses indicated larger weighted mean effect sizes for TMS as compared to tDCS studies. No statistical differences for the other sub-analyses were observed. We conclude that NIBS is a useful method for neuroscientific studies on language production in healthy volunteers. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Does cocoa/dark chocolate supplementation have favorable effect on body weight, body mass index and waist circumference? A systematic review, meta-analysis and dose-response of randomized clinical trials.

PubMed

Kord-Varkaneh, Hamed; Ghaedi, Ehsan; Nazary-Vanani, Ali; Mohammadi, Hamed; Shab-Bidar, Sakineh

2018-03-19

Cocoa and dark chocolate (DC) have been reported to be effective for health promotion; however the exact effect of cocoa/DC on anthropometric measures have not been yet defined. A comprehensive search to identify randomized clinical trials investigating the impact of cocoa/DC on body weight, body mass index (BMI) and waist circumference (WC) was performed up to December 2017. A meta-analysis of eligible studies was performed using random effects model to estimate pooled effect size. Fractional polynominal modeling was used to explore dose-response relationships. A total of 35 RCTs investigated the effects of cocoa/DC on weight, BMI and WC were included. Meta-analysis did not suggest any significant effect of cocoa/DC supplementation on body weight (-0.108 kg, 95% CI -0.262, 0.046 P = 0.168), BMI (-0.014 kg/m 2 95% CI -0.105, 0.077, P: 0.759,) and WC (0.025 cm 95% CI -0.083, 0.129, P = 0.640). Subgroup analysis revealed that that weight and BMI were reduced with cocoa/DC supplementation ≥ 30 g chocolate per day in trials between 4-8 weeks. Cocoa/DC consumption resulted in WC reduction in non-linear fashion (r = 0.042, P-nonlinearity = 0.008). Cocoa/DC supplementation does not reduce anthropometric measures significantly. However subgroup analysis regarding dose (≥ 30 g/day) and duration (between 4 to 8 weeks) revealed significant reduction of body weight and BMI.

Cost-effectiveness of drug-eluting stents versus bare-metal stents in patients undergoing percutaneous coronary intervention.

PubMed

Baschet, Louise; Bourguignon, Sandrine; Marque, Sébastien; Durand-Zaleski, Isabelle; Teiger, Emmanuel; Wilquin, Fanny; Levesque, Karine

2016-01-01

To determine the cost-effectiveness of drug-eluting stents (DES) compared with bare-metal stents (BMS) in patients requiring a percutaneous coronary intervention in France, using a recent meta-analysis including second-generation DES. A cost-effectiveness analysis was performed in the French National Health Insurance setting. Effectiveness settings were taken from a meta-analysis of 117 762 patient-years with 76 randomised trials. The main effectiveness criterion was major cardiac event-free survival. Effectiveness and costs were modelled over a 5-year horizon using a three-state Markov model. Incremental cost-effectiveness ratios and a cost-effectiveness acceptability curve were calculated for a range of thresholds for willingness to pay per year without major cardiac event gain. Deterministic and probabilistic sensitivity analyses were performed. Base case results demonstrated that DES are dominant over BMS, with an increase in event-free survival and a cost-reduction of €184, primarily due to a diminution of second revascularisations, and an absence of myocardial infarction and stent thrombosis. These results are robust for uncertainty on one-way deterministic and probabilistic sensitivity analyses. Using a cost-effectiveness threshold of €7000 per major cardiac event-free year gained, DES has a >95% probability of being cost-effective versus BMS. Following DES price decrease, new-generation DES development and taking into account recent meta-analyses results, the DES can now be considered cost-effective regardless of selective indication in France, according to European recommendations.

The prevalence, metabolic risk and effects of lifestyle intervention for metabolically healthy obesity: a systematic review and meta-analysis: A PRISMA-compliant article.

PubMed

Lin, Hanli; Zhang, Liqun; Zheng, Ruizhi; Zheng, Yishan

2017-11-01

We conducted a systematic review and meta-analysis to firstly obtain a reliable estimation of the prevalence of metabolically healthy obese (MHO) individuals in obesity, then assessed the risk of developing metabolic abnormalities (MA) among MHO individuals. At last, we evaluated the effects of traditional lifestyle interventions on metabolic level for MHO subjects. A systematic review and meta-analysis (PRISMA) guideline were conducted, and original studies were searched up to December 31, 2016. The prevalence of MHO in obesity from each study was pooled using random effects models. The relative risks (RRs) were pooled to determine the risk of developing MA for MHO compared with metabolically healthy normal-weight (MHNW) subjects. For the meta-analysis of intervention studies, the mean difference and standardized mean differences were both estimated for each metabolic parameter within each study, and then pooled using a random-effects model. Overall, 40 population-based studies reported the prevalence of MHO in obesity, 12 cohort studies and 7 intervention studies were included in the meta-analysis. About 35.0% obese individuals were metabolically healthy in the obese subjects. There were dramatic differences in the prevalence among different areas. However, 0.49 (95% confidence intervals [CI]: 0.38 to 0.60) of the MHO individuals would develop one or more MA within 10 years. Compared with MHNW subjects, the MHO subjects presented higher risk of incident MA (pooled RR = 1.80, 95%CI: 1.53-2.11). Following intervention, there was certain and significant improvement of metabolic state for metabolically abnormal obesity (MAO) subjects. Only diastolic blood pressure had reduced for MHO individuals after intervention. Almost one-third of the obese individuals are in metabolic health. However, they are still at higher risk of advancing to unhealthy state. Therefore, it is still needed to advise MHO individuals to maintain or adopt a healthy lifestyle, so as to counterbalance the adverse effects of obesity. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

Genetic association of COL1A1 polymorphisms with high myopia in Asian population: a Meta-analysis

PubMed Central

Gong, Bo; Qu, Chao; Huang, Xiao-Fang; Ye, Zi-Meng; Zhang, Ding-Ding; Shi, Yi; Chen, Rong; Liu, Yu-Ping; Shuai, Ping

2016-01-01

AIM To comprehensively evaluate the potential association of COL1A1 polymorphisms with high myopia by a systematic review and Meta-analysis. METHODS All association studies on COL1A1 and high myopia reported up to June 10, 2014 in PubMed, Embase, Web of Science, and the Chinese Biomedical Database were retrieved. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were analyzed for single-nucleotide polymorphisms (SNPs) using fixed- and random- effects models according to between-study heterogeneity. Publication bias analyses were conducted by Egger's test. RESULTS A total of four studies from reported papers were included in this analysis. The Meta-analyses for COL1A1 rs2075555, composed of 2304 high myopia patients and 2272 controls, failed to detect any significant association with high myopia. A total of 971 cases and 649 controls were tested for COL1A1 rs2269336. The association of COL1A1 rs2269336 with high myopia was observed in recessive model (CC vs CG+GG, P=0.03) and in heterozygous model (CG vs GG, P=0.04), but not in other models. CONCLUSION This Meta-analysis shows that COL1A1 rs2269336 (CC vs CG+GG) affects individual susceptibility to high myopia, whereas there is no association detected between SNPs rs2075555 and high myopia. Given the limited sample size, further investigations including more ethnic groups are required to validate the association. PMID:27588274

Combining evidence from multiple electronic health care databases: performances of one-stage and two-stage meta-analysis in matched case-control studies.

PubMed

La Gamba, Fabiola; Corrao, Giovanni; Romio, Silvana; Sturkenboom, Miriam; Trifirò, Gianluca; Schink, Tania; de Ridder, Maria

2017-10-01

Clustering of patients in databases is usually ignored in one-stage meta-analysis of multi-database studies using matched case-control data. The aim of this study was to compare bias and efficiency of such a one-stage meta-analysis with a two-stage meta-analysis. First, we compared the approaches by generating matched case-control data under 5 simulated scenarios, built by varying: (1) the exposure-outcome association; (2) its variability among databases; (3) the confounding strength of one covariate on this association; (4) its variability; and (5) the (heterogeneous) confounding strength of two covariates. Second, we made the same comparison using empirical data from the ARITMO project, a multiple database study investigating the risk of ventricular arrhythmia following the use of medications with arrhythmogenic potential. In our study, we specifically investigated the effect of current use of promethazine. Bias increased for one-stage meta-analysis with increasing (1) between-database variance of exposure effect and (2) heterogeneous confounding generated by two covariates. The efficiency of one-stage meta-analysis was slightly lower than that of two-stage meta-analysis for the majority of investigated scenarios. Based on ARITMO data, there were no evident differences between one-stage (OR = 1.50, CI = [1.08; 2.08]) and two-stage (OR = 1.55, CI = [1.12; 2.16]) approaches. When the effect of interest is heterogeneous, a one-stage meta-analysis ignoring clustering gives biased estimates. Two-stage meta-analysis generates estimates at least as accurate and precise as one-stage meta-analysis. However, in a study using small databases and rare exposures and/or outcomes, a correct one-stage meta-analysis becomes essential. Copyright © 2017 John Wiley & Sons, Ltd.

Acute effects of tea constituents L-theanine, caffeine, and epigallocatechin gallate on cognitive function and mood: a systematic review and meta-analysis.

PubMed

Camfield, David A; Stough, Con; Farrimond, Jonathon; Scholey, Andrew B

2014-08-01

A systematic review and meta-analysis was conducted on 11 randomized placebo-controlled human studies of acute effects of tea constituents L-theanine and epigallocatechin gallate, administered alone or in combination with caffeine, on cognitive function and mood. The outcome measures of mood were alertness, calmness, and contentedness, derived from the Bond-Lader scales, and state anxiety, from the State-Trait Anxiety Inventory. Cognitive measures assessed were attentional switch, intersensory attention, and rapid visual information processing. Standardized mean differences between placebo and treatment groups are presented for each study and outcome measure. Meta-analysis using a random-effects model was conducted when data were available for three or more studies. Evidence of moderate effect sizes in favor of combined caffeine and L-theanine in the first 2 hours postdose were found for outcome measures Bond-Lader alertness, attentional switching accuracy, and, to a lesser extent, some unisensory and multisensory attentional outcomes. Moderator analysis of caffeine and L-theanine doses revealed trends toward greater change in effect size for caffeine dose than for L-theanine dose, particularly during the first hour postdose. © 2014 International Life Sciences Institute.

Living network meta-analysis compared with pairwise meta-analysis in comparative effectiveness research: empirical study.

PubMed

Nikolakopoulou, Adriani; Mavridis, Dimitris; Furukawa, Toshi A; Cipriani, Andrea; Tricco, Andrea C; Straus, Sharon E; Siontis, George C M; Egger, Matthias; Salanti, Georgia

2018-02-28

To examine whether the continuous updating of networks of prospectively planned randomised controlled trials (RCTs) ("living" network meta-analysis) provides strong evidence against the null hypothesis in comparative effectiveness of medical interventions earlier than the updating of conventional, pairwise meta-analysis. Empirical study of the accumulating evidence about the comparative effectiveness of clinical interventions. Database of network meta-analyses of RCTs identified through searches of Medline, Embase, and the Cochrane Database of Systematic Reviews until 14 April 2015. Network meta-analyses published after January 2012 that compared at least five treatments and included at least 20 RCTs. Clinical experts were asked to identify in each network the treatment comparison of greatest clinical interest. Comparisons were excluded for which direct and indirect evidence disagreed, based on side, or node, splitting test (P<0.10). Cumulative pairwise and network meta-analyses were performed for each selected comparison. Monitoring boundaries of statistical significance were constructed and the evidence against the null hypothesis was considered to be strong when the monitoring boundaries were crossed. A significance level was defined as α=5%, power of 90% (β=10%), and an anticipated treatment effect to detect equal to the final estimate from the network meta-analysis. The frequency and time to strong evidence was compared against the null hypothesis between pairwise and network meta-analyses. 49 comparisons of interest from 44 networks were included; most (n=39, 80%) were between active drugs, mainly from the specialties of cardiology, endocrinology, psychiatry, and rheumatology. 29 comparisons were informed by both direct and indirect evidence (59%), 13 by indirect evidence (27%), and 7 by direct evidence (14%). Both network and pairwise meta-analysis provided strong evidence against the null hypothesis for seven comparisons, but for an additional 10 comparisons only network meta-analysis provided strong evidence against the null hypothesis (P=0.002). The median time to strong evidence against the null hypothesis was 19 years with living network meta-analysis and 23 years with living pairwise meta-analysis (hazard ratio 2.78, 95% confidence interval 1.00 to 7.72, P=0.05). Studies directly comparing the treatments of interest continued to be published for eight comparisons after strong evidence had become evident in network meta-analysis. In comparative effectiveness research, prospectively planned living network meta-analyses produced strong evidence against the null hypothesis more often and earlier than conventional, pairwise meta-analyses. 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.

Effectiveness of online mindfulness-based interventions in improving mental health: A review and meta-analysis of randomised controlled trials.

PubMed

Spijkerman, M P J; Pots, W T M; Bohlmeijer, E T

2016-04-01

Mindfulness-based interventions (MBIs) are increasingly being delivered through the Internet. Whereas numerous meta-analyses have investigated the effectiveness of face-to-face MBIs in the context of mental health and well-being, thus far a quantitative synthesis of the effectiveness of online MBIs is lacking. The aim of this meta-analysis was to estimate the overall effects of online MBIs on mental health. Fifteen randomised controlled trials were included in this study. A random effects model was used to compute pre-post between-group effect sizes, and the study quality of each of the included trials was rated. Results showed that online MBIs have a small but significant beneficial impact on depression (g=0.29), anxiety (g=0.22), well-being (g=0.23) and mindfulness (g=0.32). The largest effect was found for stress, with a moderate effect size (g=0.51). For stress and mindfulness, exploratory subgroup analyses demonstrated significantly higher effect sizes for guided online MBIs than for unguided online MBIs. In addition, meta-regression analysis showed that effect sizes for stress were significantly moderated by the number of intervention sessions. Effect sizes, however, were not significantly related to study quality. The findings indicate that online MBIs have potential to contribute to improving mental health outcomes, particularly stress. Limitations, directions for future research and practical implications are discussed. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Adjunctive Corticosteroids for Pneumocystis jirovecii Pneumonia in Non-HIV-infected Patients: A Systematic Review and Meta-analysis of Observational Studies.

PubMed

Fujikura, Yuji; Manabe, Toshie; Kawana, Akihiko; Kohno, Shigeru

2017-02-01

The clinical benefits of adjunctive corticosteroids for Pneumocystis jirovecii (P. jirovecii) pneumonia in patients not infected with the human immunodeficiency virus (HIV) has not been evaluated by meta-analysis. We conducted a systematic review of published studies describing the effects of adjunctive corticosteroids on outcome in non-HIV P. jirovecii pneumonia patients. Two investigators independently searched the PubMed and Cochrane databases for eligible articles written in English. A meta-analysis was performed using a random-effects model for measuring mortality as the primary outcome, and the need for intubation or mechanical ventilation as the secondary outcome. Seven observational studies were eligible. In these studies, adjunctive corticosteroids did not affect mortality in non-HIV patients (odds ratio [OR] 1.26; 95% CI 0.60-2.67) and there was no beneficial effect in patients with severe hypoxemia (PaO 2 <70mmHg) (OR 0.90; 95% CI 0.44-1.83). No significant effect on the secondary outcome was observed (OR 1.34; 95% CI 0.44-4.11). Although the studies were observational, meta-analysis showed that adjunctive corticosteroids did not improve the outcome of P. jirovecii pneumonia in non-HIV patients. The results warrant a randomized controlled trial. Copyright © 2016 SEPAR. Publicado por Elsevier España, S.L.U. All rights reserved.

Pharmacological Control of Complications Following to Third Molar Removal: Evidence Based on A Meta-Analysis.

PubMed

Isiordia-Espinoza, Mario Alberto; Bologna-Molina, Ronell Eduardo; Hernández-Miramontes, Ycenna Ailed; Zapata-Morales, Juan Ramón; Alonso-Castro, Angel Jobsabad; Martínez-Morales, Flavio; Sánchez-Enriquez, Sergio; Serafín-Higuera, Nicolás Addiel; Pérez-Cortez, Guillermo; Franco-de la Torre, Lorenzo

2018-06-26

The purpose of this meta-analysis was to evaluate the clinical efficacy of non-steroidal anti-inflammatory drugs and dexamethasone on the trismus, postsurgical pain, facial swelling, as well as the analgesic consumption after third molar surgery. The reports were identified in the most important medical databases. Those studies that met the requirements were fully assessed according to the inclusion and exclusion criteria. The quality of each report was evaluated with the Oxford Quality Scale and using the Cochrane Collaboration's risk of bias tool. Each meta-analysis was done using the technique of mean difference and 95% confidence intervals employing a random effects model with the Review Manager 5.3., from the Cochrane Library. Significant statistical difference was accepted when the p value was less than 0.05 on the test of overall effect (Z value). Qualitative evaluation was done using the data of 330 patients extracted from seven articles and the quantitative assessment with data of 200 patients from three reports. It was not observed difference among non-steroidal anti-inflammatory drugs and dexamethasone in any of the clinical effectiveness indicators. The outcomes of our meta-analysis indicate that non-steroidal anti-inflammatory drugs and dexamethasone have good therapeutic effect for the management of inflammatory complications following to third molar surgery. © Georg Thieme Verlag KG Stuttgart · New York.

Robustness of meta-analyses in finding gene × environment interactions

PubMed Central

Shi, Gang; Nehorai, Arye

2017-01-01

Meta-analyses that synthesize statistical evidence across studies have become important analytical tools for genetic studies. Inspired by the success of genome-wide association studies of the genetic main effect, researchers are searching for gene × environment interactions. Confounders are routinely included in the genome-wide gene × environment interaction analysis as covariates; however, this does not control for any confounding effects on the results if covariate × environment interactions are present. We carried out simulation studies to evaluate the robustness to the covariate × environment confounder for meta-regression and joint meta-analysis, which are two commonly used meta-analysis methods for testing the gene × environment interaction or the genetic main effect and interaction jointly. Here we show that meta-regression is robust to the covariate × environment confounder while joint meta-analysis is subject to the confounding effect with inflated type I error rates. Given vast sample sizes employed in genome-wide gene × environment interaction studies, non-significant covariate × environment interactions at the study level could substantially elevate the type I error rate at the consortium level. When covariate × environment confounders are present, type I errors can be controlled in joint meta-analysis by including the covariate × environment terms in the analysis at the study level. Alternatively, meta-regression can be applied, which is robust to potential covariate × environment confounders. PMID:28362796

Formalizing the definition of meta-analysis in Molecular Ecology.

PubMed

ArchMiller, Althea A; Bauer, Eric F; Koch, Rebecca E; Wijayawardena, Bhagya K; Anil, Ammu; Kottwitz, Jack J; Munsterman, Amelia S; Wilson, Alan E

2015-08-01

Meta-analysis, the statistical synthesis of pertinent literature to develop evidence-based conclusions, is relatively new to the field of molecular ecology, with the first meta-analysis published in the journal Molecular Ecology in 2003 (Slate & Phua 2003). The goal of this article is to formalize the definition of meta-analysis for the authors, editors, reviewers and readers of Molecular Ecology by completing a review of the meta-analyses previously published in this journal. We also provide a brief overview of the many components required for meta-analysis with a more specific discussion of the issues related to the field of molecular ecology, including the use and statistical considerations of Wright's FST and its related analogues as effect sizes in meta-analysis. We performed a literature review to identify articles published as 'meta-analyses' in Molecular Ecology, which were then evaluated by at least two reviewers. We specifically targeted Molecular Ecology publications because as a flagship journal in this field, meta-analyses published in Molecular Ecology have the potential to set the standard for meta-analyses in other journals. We found that while many of these reviewed articles were strong meta-analyses, others failed to follow standard meta-analytical techniques. One of these unsatisfactory meta-analyses was in fact a secondary analysis. Other studies attempted meta-analyses but lacked the fundamental statistics that are considered necessary for an effective and powerful meta-analysis. By drawing attention to the inconsistency of studies labelled as meta-analyses, we emphasize the importance of understanding the components of traditional meta-analyses to fully embrace the strengths of quantitative data synthesis in the field of molecular ecology. © 2015 John Wiley & Sons Ltd.

The effect of laser-assisted hatching on pregnancy outcomes of cryopreserved-thawed embryo transfer: a meta-analysis of randomized controlled trials.

PubMed

Zeng, MeiFang; Su, SuQin; Li, LiuMing

2018-04-01

It is well known that laser-assisted hatching (LAH) is the most popular and ideal embryo hatching technology, but the relevance to pregnancy outcomes of cryopreserved-thawed embryo transfer (ET) is controversial. The purpose of this meta-analysis was to evaluate the effects of LAH on pregnancy outcomes of cryopreserved-thawed ET. We searched for relevant studies published in the PubMed, EMBASE, and Cochrane Central databases up to March 2017. This meta-analysis was primarily used to evaluate the effect of laser-assisted hatching on assisted reproductive outcomes: clinical pregnancy, embryo implantation, multiple pregnancy, miscarriage, and live birth. Using the Mantel-Haenszel fixed effects model and random effects model, we determined the summary odds ratios (OR) with 95% confidence intervals (CIs). There were 12 randomized controlled trials (more than 2574 participants) included in our analysis. The rates of clinical pregnancy (OR = 1.65, 95% CI = 1.24-2.19, I 2  = 49), implantation (OR = 1.59, 95% CI = 1.06-2.38, I 2  = 82%), multiple pregnancy (OR = 2.30, 95% CI = 1.30-4.07, I 2  = 33%), miscarriage (OR = 0.86, 95% CI = 0.50-1.48, I 2  = 0%), and live birth (OR = 1.09, 95% CI = 0.77-1.54, I 2  = 0%) revealed comparable results for both groups. In summary, this meta-analysis demonstrates that LAH is related to a higher clinical pregnancy rate, embryo implantation rate, and multiple pregnancy rate in women with cryopreserved-thawed embryos. However, LAH is unlikely to increase live birth rates and miscarriage rates. Due to the small sample evaluated in the pool of included studies, large-scale, prospective, randomized, controlled trials are required to determine if these small effects are clinically relevant.

Effects of Different Levels of Intra-Abdominal Pressure on the Postoperative Hepatic Function of Patients Undergoing Laparoscopic Cholecystectomy: A Systematic Review and Meta-Analysis.

PubMed

Cheng, Zheng-Jun; Wang, Yun-Bing; Chen, Long; Gong, Jian-Ping; Zhang, Wei

2018-04-18

The aim of this meta-analysis is to compare the differences in postoperative markers of the hepatic function under different intra-abdominal pressures in laparoscopic cholecystectomy (LC). Several databases were searched for control studies, and then the weighted data were pooled with random-effect models. A total of 11 studies involving 865 patients were included. The meta-analysis reveals that the level of the aspartate aminotransferase and alanine transaminase of the low-pressure group has a lower postoperative increase than the moderate-pressure group (P<0.001). The level of the aspartate aminotransferase and alanine transaminase of the moderate-pressure group has a lower postoperative increase than the high-pressure group (P<0.001). Totally, the effect of lower pressure LC on postoperative hepatic functions is less significant than that of the higher one. Potential subgroup analysis does not modify these results. The recommended pressure in LC is suggested to be lower so as to result in a better surgical safety, especially for special populations.

Significant Effect of Valproate Augmentation Therapy in Patients With Schizophrenia

PubMed Central

Tseng, Ping-Tao; Chen, Yen-Wen; Chung, Weilun; Tu, Kun-Yu; Wang, Hung-Yu; Wu, Ching-Kuan; Lin, Pao-Yen

2016-01-01

Abstract Valproate is an anticonvulsant, which is also widely used for treating psychiatric disorders. Some clinical trials have demonstrated benefits of valproate augmentation therapy in schizophrenia. Previous meta-analysis showed inconsistent findings because of limited literature at that time. The aim of this study is to update the newer published data by conducting a meta-analysis of clinical efficacy of valproate augmentation therapy in patients with schizophrenia or schizoaffective disorder. Data sources include electronic research through platform of PubMed. Study eligibility criteria, participants, and interventions were as follows: the inclusion criteria included articles discussing comparisons of the treatment effect in schizophrenic patients treated with antipsychotic augmented with valproate and antipsychotics with/without placebo; articles on clinical trials in humans. The exclusion criteria were case reports or series and nonclinical trials. We compared the effect between antipsychotic treatment with valproate augmentation and antipsychotic monotherapy. Data from clinical trials were pooled by random-effects model, and possible confounding variables were examined through meta-regression and subgroup analysis. Data from 11 articles including 889 patients were included into current meta-analysis. We found patients treated with antipsychotics with valproate augmentation showed significantly more improvement in total psychopathology than those treated with antipsychotics only (P = 0.02). Results from open trials, but not from randomized controlled trials (P = 0.20), showed significant improvement (P = 0.01). In addition, the significance only persisted in the studies conducted with a shorter treatment duration (P < 0.001) rather than longer treatment duration (P = 0.23). There is no difference in the dropout rate between valproate augmentation and antipsychotic treatment only (P = 0.14). We could not perform a detailed meta-analysis for every category of antipsychotics, long-term effect, and safety profiles of valproate augmentation therapy in maintenance treatment, safety in pregnant patients, and subtype of schizophrenia. Our meta-analysis highlights the significantly better treatment effect with valproate augmentation therapy in patients with schizophrenia or schizoaffective disorder, and provides important evidence for supporting the practice of valproate augmentation therapy in these patients. PMID:26825886

The effect of music therapy on cognitive functioning among older adults: a systematic review and meta-analysis.

PubMed

Li, Hui-Chi; Wang, Hsiu-Hung; Chou, Fan-Hao; Chen, Kuei-Min

2015-01-01

To conduct a systematic review and a meta-analysis of current studies to determine whether music therapy affects the cognitive function of older people. The databases surveyed include PsycINFO, PsycARTICLES, PubMed, MEDLINE, CINAHL, AgeLine, Cochrane Library, and the Chinese Electronic Periodical Services (CEPS) as well as the reference lists of the included studies. The Consolidated Standards of Reporting Trials (CONSORT) extension checklist for nonpharmacologic treatment was used to evaluate the literature. Music therapy intervention offered in nursing homes, hospitals, or communities. A total of 234 participants from 5 studies were assessed in the meta-analysis, with a mean age per study of 71.4 to 82.0 years. Cognitive outcome domains were analyzed in a systematic review. The short-term effects of music therapy in Mini-Mental State Examination data for meta-analysis were compiled. A forest plot was constructed using a fixed effect model to obtain a pooled mean difference. Active music therapy comprising singing and other musical activities was generally determined to effect a significant improvement in the Mini-Mental State Examination according to individual retrieval studies. However, this study showed no significant improvement in the short-term effects of music therapy when all related studies in meta-analysis were combined. The pooled mean difference was 0.73 (95% confidence interval -0.07 to 1.54; Z = 1.79; P = .07) for using music therapy overall and 0.74 (95% confidence interval -0.08 to 1.56; Z = 1.76; P = .08) for using active music therapy. The findings of the meta-analysis indicate that the short-term effects of music therapy do not improve the cognitive function of older people. Future studies that utilize a good quality methodology with a long-term design and diversified active music therapy are recommended. Copyright © 2015 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Antioxidant therapy for patients with chronic pancreatitis: A systematic review and meta-analysis.

PubMed

Zhou, Dongkai; Wang, Weilin; Cheng, Xiaofei; Wei, Jianfeng; Zheng, Shusen

2015-08-01

Chronic pancreatitis is a progressive, inflammatory disease of pancreas characterized by significant abdominal pain, malabsorption, and diabetes mellitus. Antioxidant therapy has been proposed as an effective treatment for painful chronic pancreatitis. We performed a meta-analysis of trials in which antioxidant therapy was compared with placebo in chronic pancreatitis. We searched six databases to identify relevant trials. Results are expressed as risk ratio (RR) or standardized mean difference (SMD) with accompanying 95% confidence intervals (CI). The meta-analysis was performed with the fixed-effects model or random-effects model according to heterogeneity. Eight studies including 573 patients met the inclusion criteria. A meta-analysis of these studies revealed that the intervention of antioxidants was associated with a significant increase in patients with pain relief (RR, 2.15; 95% CI, 1.72-2.69; P < 0.00001), and a significant decrease in patients' need for analgesics (RR, 0.56; 95% CI, 0.40-0.78; P = 0.0006). For pain score, antioxidants improved pain tolerance in chronic pancreatitis patients (SMD: -0.41; 95% CI: -0.83 to -0.10; P = 0.0005). Additionally, antioxidants may cause some adverse reactions (RR, 4.22; 95% CI: 2.17-8.20; P < 0.0001). Based on current evidence, oxidative stress may play an important role in the pathophysiology of chronic pancreatitis, and administration of antioxidants to patients with painful chronic pancreatitis is effective in relieving pain. Antioxidant supplements may be advocated as one medical therapy for chronic pancreatitis patients with low antioxidant capacity in their blood. Copyright © 2014 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Examining the Impact of Inference Instruction on the Literal and Inferential Comprehension of Skilled and Less Skilled Readers: A Meta-Analytic Review

ERIC Educational Resources Information Center

Elleman, Amy M.

2017-01-01

Inference ability is considered central to discourse processing and has been shown to be important across models of reading comprehension. To evaluate the impact of inference instruction, a meta-analysis of 25 inference studies in Grades K-12 was conducted. Results showed that inference instruction was effective for increasing students' general…

Single balloon versus double balloon bipedicular kyphoplasty: a systematic review and meta-analysis.

PubMed

Jing, Zehao; Dong, Jianli; Li, Zhengwei; Nan, Feng

2018-06-19

Kyphoplasty has been widely used to treat vertebral compression fractures (VCFs). In standard procedure of kyphoplasty, two balloons were inserted into the vertebral body through bipedicular and inflated simultaneously, while using a single balloon two times is also a common method in clinic to lessen the financial burden of patients. However, the effect and safety of single balloon versus double balloon bipedicular kyphoplasty are still controversy. In this systematic review and meta-analysis, eligible studies were identified through a comprehensive literature search of PubMed, Cochrane library EMBASE, Web of Science, Wanfang, CNKI, VIP and CBM until January 1, 2018. Results from individual studies were pooled using a random or fixed effects model. Seven articles were included in the systematic review and five studies were consisted in meta-analysis. We observed no significant difference between single balloon and double balloon bipedicular kyphoplasty in visual analog scale (VAS), angle (kyphotic angle and Cobb angle), consumption (operation time, cement volume and volume of bleeding), vertebral height (anterior height, medium height and posterior height) and complications (cement leakage and new VCFs), while the cost of single balloon bipedicular kyphoplasty is lower than that of double balloon bipedicular kyphoplasty. The results of our meta-analysis also demonstrated that single balloon can significantly improve the VAS, angle and vertebral height of patients suffering from VCFs. This systematic review and meta-analysis collectively concludes that single balloon bipedicular kyphoplasty is as effective as double balloon bipedicular kyphoplasty in improving clinical symptoms, deformity and complications of VCFs but not so expensive. These slides can be retrieved under Electronic Supplementary Material.

Meta-analyses are no substitute for registered replications: a skeptical perspective on religious priming

PubMed Central

van Elk, Michiel; Matzke, Dora; Gronau, Quentin F.; Guan, Maime; Vandekerckhove, Joachim; Wagenmakers, Eric-Jan

2015-01-01

According to a recent meta-analysis, religious priming has a positive effect on prosocial behavior (Shariff et al., 2015). We first argue that this meta-analysis suffers from a number of methodological shortcomings that limit the conclusions that can be drawn about the potential benefits of religious priming. Next we present a re-analysis of the religious priming data using two different meta-analytic techniques. A Precision-Effect Testing–Precision-Effect-Estimate with Standard Error (PET-PEESE) meta-analysis suggests that the effect of religious priming is driven solely by publication bias. In contrast, an analysis using Bayesian bias correction suggests the presence of a religious priming effect, even after controlling for publication bias. These contradictory statistical results demonstrate that meta-analytic techniques alone may not be sufficiently robust to firmly establish the presence or absence of an effect. We argue that a conclusive resolution of the debate about the effect of religious priming on prosocial behavior – and about theoretically disputed effects more generally – requires a large-scale, preregistered replication project, which we consider to be the sole remedy for the adverse effects of experimenter bias and publication bias. PMID:26441741

Allowing for uncertainty due to missing continuous outcome data in pairwise and network meta-analysis.

PubMed

Mavridis, Dimitris; White, Ian R; Higgins, Julian P T; Cipriani, Andrea; Salanti, Georgia

2015-02-28

Missing outcome data are commonly encountered in randomized controlled trials and hence may need to be addressed in a meta-analysis of multiple trials. A common and simple approach to deal with missing data is to restrict analysis to individuals for whom the outcome was obtained (complete case analysis). However, estimated treatment effects from complete case analyses are potentially biased if informative missing data are ignored. We develop methods for estimating meta-analytic summary treatment effects for continuous outcomes in the presence of missing data for some of the individuals within the trials. We build on a method previously developed for binary outcomes, which quantifies the degree of departure from a missing at random assumption via the informative missingness odds ratio. Our new model quantifies the degree of departure from missing at random using either an informative missingness difference of means or an informative missingness ratio of means, both of which relate the mean value of the missing outcome data to that of the observed data. We propose estimating the treatment effects, adjusted for informative missingness, and their standard errors by a Taylor series approximation and by a Monte Carlo method. We apply the methodology to examples of both pairwise and network meta-analysis with multi-arm trials. © 2014 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Genetic Polymorphism of Angiotensin-Converting Enzyme and Chronic Obstructive Pulmonary Disease Risk: An Updated Meta-Analysis

PubMed Central

Kang, Sang Wook; Kim, Su Kang; Jung, Hee-Jae; Kim, Kwan-Il; Kim, Jinju

2016-01-01

The relationship between polymorphism of the angiotensin I converting enzyme (ACE) gene and chronic obstructive pulmonary disease (COPD) has been examined in many previous studies. However, their results were controversial. Therefore, we performed a meta-analysis to evaluate the relationship between the ACE gene and the risk of COPD. Fourteen case-control studies were included in this meta-analysis. The pooled p value, odds ratio (OR), and 95% confidence interval (95% CI) were used to investigate the strength of the association. The meta-analysis was performed using comprehensive meta-analysis software. Our meta-analysis results revealed that ACE polymorphisms were not related to the risk of COPD (p > 0.05 in each model). In further analyses based on ethnicity, we observed an association between insertion/deletion polymorphism of the ACE gene and risk of COPD in the Asian population (codominant 2, OR = 3.126, 95% CI = 1.919–5.093, p < 0.001; recessive, OR = 3.326, 95% CI = 2.190–5.050, p < 0.001) but not in the Caucasian population (p > 0.05 in each model). In conclusion, the present meta-analysis indicated that the insertion/deletion polymorphism of the ACE gene may be associated with susceptibility to COPD in the Asian population but not in the Caucasian population. However, the results of the present meta-analysis need to be confirmed in a larger sample. PMID:27830153

A meta-analysis of serious digital games for healthy lifestyle promotion

USDA-ARS?s Scientific Manuscript database

Several systematic reviews have described health-promoting effects of serious games, but so far no meta-analysis has been reported. This paper presents a meta-analysis of 54 serious digital game studies for healthy lifestyle promotion, in which we investigated the overall effectiveness of serious di...

Depression and Oxidative Stress: Results From a Meta-Analysis of Observational Studies

PubMed Central

Palta, Priya; Samuel, Laura J.; Miller, Edgar R.; Szanton, Sarah L.

2014-01-01

Objective To perform a systematic review and meta-analysis that quantitatively tests and summarizes the hypothesis that depression results in elevated oxidative stress and lower antioxidant levels. Methods We performed a meta-analysis of studies that reported an association between depression and oxidative stress and/or antioxidant status markers. PubMed and EMBASE databases were searched for articles published from January 1980 through December 2012. A random-effects model, weighted by inverse variance, was performed to pool standard deviation (Cohen’s d) effect size estimates across studies for oxidative stress and antioxidant status measures, separately. Results Twenty-three studies with 4980 participants were included in the meta-analysis. Depression was most commonly measured using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria. A Cohen’s d effect size of 0.55 (95% confidence interval = 0.47–0.63) was found for the association between depression and oxidative stress, indicating a roughly 0.55 of 1-standard-deviation increase in oxidative stress among individuals with depression compared with those without depression. The results of the studies displayed significant heterogeneity (I2 = 80.0%, p < .001). A statistically significant effect was also observed for the association between depression and antioxidant status markers (Cohen’s d = −0.24, 95% confidence interval = −0.33 to −0.15). Conclusions This meta-analysis observed an association between depression and oxidative stress and antioxidant status across many different studies. Differences in measures of depression and markers of oxidative stress and antioxidant status markers could account for the observed heterogeneity. These findings suggest that well-established associations between depression and poor heath outcomes may be mediated by high oxidative stress. PMID:24336428

Depression and oxidative stress: results from a meta-analysis of observational studies.

PubMed

Palta, Priya; Samuel, Laura J; Miller, Edgar R; Szanton, Sarah L

2014-01-01

To perform a systematic review and meta-analysis that quantitatively tests and summarizes the hypothesis that depression results in elevated oxidative stress and lower antioxidant levels. We performed a meta-analysis of studies that reported an association between depression and oxidative stress and/or antioxidant status markers. PubMed and EMBASE databases were searched for articles published from January 1980 through December 2012. A random-effects model, weighted by inverse variance, was performed to pool standard deviation (Cohen's d) effect size estimates across studies for oxidative stress and antioxidant status measures, separately. Twenty-three studies with 4980 participants were included in the meta-analysis. Depression was most commonly measured using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria. A Cohen's d effect size of 0.55 (95% confidence interval = 0.47-0.63) was found for the association between depression and oxidative stress, indicating a roughly 0.55 of 1-standard-deviation increase in oxidative stress among individuals with depression compared with those without depression. The results of the studies displayed significant heterogeneity (I(2) = 80.0%, p < .001). A statistically significant effect was also observed for the association between depression and antioxidant status markers (Cohen's d = -0.24, 95% confidence interval = -0.33 to -0.15). This meta-analysis observed an association between depression and oxidative stress and antioxidant status across many different studies. Differences in measures of depression and markers of oxidative stress and antioxidant status markers could account for the observed heterogeneity. These findings suggest that well-established associations between depression and poor heath outcomes may be mediated by high oxidative stress.

Religion and Completed Suicide: a Meta-Analysis.

PubMed

Wu, Andrew; Wang, Jing-Yu; Jia, Cun-Xian

2015-01-01

Suicide is a major public health concern and a leading cause of death around the world. How religion influences the risk of completed suicide in different settings across the world requires clarification in order to best inform suicide prevention strategies. A meta-analysis using search results from Pubmed and Web of Science databases was conducted following PRISMA protocol and using the keywords "religion" or "religious" or "religiosity" or "spiritual" or "spirituality" plus "suicide" or "suicidality" or "suicide attempt". Random and fixed effects models were used to generate pooled ORs and I2 values. Sub-analyses were conducted among the following categories: young age (<45 yo), older age (≥45 yo), western culture, eastern culture, and religious homogeneity. Nine studies that altogether evaluated 2339 suicide cases and 5252 comparison participants met all selection criteria and were included in the meta-analysis. The meta-analysis suggested an overall protective effect of religiosity from completed suicide with a pooled OR of 0.38 (95% CI: 0.21-0.71) and I2 of 91%. Sub-analyses similarly revealed significant protective effects for studies performed in western cultures (OR = 0.29, 95% CI: 0.18-0.46), areas with religious homogeneity (OR = 0.18, 95% CI: 0.13-0.26), and among older populations (OR = 0.42, 95% CI: 0.21-0.84). High heterogeneity of our meta-analysis was attributed to three studies in which the methods varied from the other six. Religion plays a protective role against suicide in a majority of settings where suicide research is conducted. However, this effect varies based on the cultural and religious context. Therefore, public health professionals need to strongly consider the current social and religious atmosphere of a given population when designing suicide prevention strategies.

Sleep, Cognitive impairment, and Alzheimer's disease: A Systematic Review and Meta-Analysis.

PubMed

Bubu, Omonigho M; Brannick, Michael; Mortimer, James; Umasabor-Bubu, Ogie; Sebastião, Yuri V; Wen, Yi; Schwartz, Skai; Borenstein, Amy R; Wu, Yougui; Morgan, David; Anderson, William M

2017-01-01

Mounting evidence implicates disturbed sleep or lack of sleep as one of the risk factors for Alzheimer's disease (AD), but the extent of the risk is uncertain. We conducted a broad systematic review and meta-analysis to quantify the effect of sleep problems/disorders on cognitive impairment and AD. Original published literature assessing any association of sleep problems or disorders with cognitive impairment or AD was identified by searching PubMed, Embase, Web of Science, and the Cochrane library. Effect estimates of individual studies were pooled and relative risks (RR) and 95% confidence intervals (CI) were calculated using random effects models. We also estimated the population attributable risk. Twenty-seven observational studies (n = 69216 participants) that provided 52 RR estimates were included in the meta-analysis. Individuals with sleep problems had a 1.55 (95% CI: 1.25-1.93), 1.65 (95% CI: 1.45-1.86), and 3.78 (95% CI: 2.27-6.30) times higher risk of AD, cognitive impairment, and preclinical AD than individuals without sleep problems, respectively. The overall meta-analysis revealed that individuals with sleep problems had a 1.68 (95% CI: 1.51-1.87) times higher risk for the combined outcome of cognitive impairment and/or AD. Approximately 15% of AD in the population may be attributed to sleep problems. This meta-analysis confirmed the association between sleep and cognitive impairment or AD and, for the first time, consolidated the evidence to provide an "average" magnitude of effect. As sleep problems are of a growing concern in the population, these findings are of interest for potential prevention of AD. © Sleep Research Society 2016. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Erythropoietin levels in patients with sleep apnea: a meta-analysis.

PubMed

Zhang, Xiao-Bin; Zeng, Yi-Ming; Zeng, Hui-Qing; Zhang, Hua-Ping; Wang, Hui-Ling

2017-06-01

Currently available data regarding the blood levels of erythropoietin (EPO) in sleep apnea (SA) patients are contradictory. The aim of the present meta-analysis was to evaluate the EPO levels in SA patients via quantitative analysis. A systematic search of Pubmed, Embase, and Web of Science were performed. EPO levels in SA group and control group were extracted from each eligible study. Weight mean difference (WMD) or Standard mean difference (SMD) with 95% confidence interval (CI) was calculated by using fixed-effects or random effect model analysis according to the degree of heterogeneity between studies. A total of 9 studies involving 407 participants were enrolled. The results indicated that EPO levels in SA group were significantly higher than that in control group (SMD 0.61, 95% CI 0.11-1.11, p = 0.016). Significantly higher EPO levels were found in patients with body mass index <30 kg/m 2 , and cardiovascular complications in the subsequent subgroup analysis (both p < 0.05). High blood EPO levels were found in SA patients in the present meta-analysis.

Coffee and caffeine intake and breast cancer risk: an updated dose-response meta-analysis of 37 published studies.

PubMed

Jiang, Wenjie; Wu, Yili; Jiang, Xiubo

2013-06-01

We conducted an updated meta-analysis to summarize the evidence from published studies regarding the association of coffee and caffeine intake with breast cancer risk. Pertinent studies were identified by a search of PubMed and by reviewing the reference lists of retrieved articles. The fixed or random effect model was used based on heterogeneity test. The dose-response relationship was assessed by restricted cubic spline model and multivariate random-effect meta-regression. 37 published articles, involving 59,018 breast cancer cases and 966,263 participants, were included in the meta-analysis. No significant association was found between breast cancer risk and coffee (RR=0.97, P=0.09), decaffeinated coffee (RR=0.98, P=0.55) and caffeine (RR=0.99, P=0.73), respectively. And the association was still not significant when combining coffee and caffeine (coffee/caffeine) (RR=0.97, P=0.09). However, an inverse association of coffee/caffeine with breast cancer risk was found for postmenopausal women (RR=0.94, P=0.02), and a strong and significant association of coffee with breast cancer risk was found for BRCA1 mutation carriers (RR=0.69, P<0.01). A linear dose-response relationship was found for breast cancer risk with coffee and caffeine, and the risk of breast cancer decreased by 2% (P=0.05) for every 2 cups/day increment in coffee intake, and 1% (P=0.52) for every 200mg/day increment in caffeine intake, respectively. Findings from this meta-analysis suggested that coffee/caffeine might be weakly associated with breast cancer risk for postmenopausal women, and the association for BRCA1 mutation carriers deserves further investigation. Copyright © 2013 Elsevier Inc. All rights reserved.

GWAR: robust analysis and meta-analysis of genome-wide association studies.

PubMed

Dimou, Niki L; Tsirigos, Konstantinos D; Elofsson, Arne; Bagos, Pantelis G

2017-05-15

In the context of genome-wide association studies (GWAS), there is a variety of statistical techniques in order to conduct the analysis, but, in most cases, the underlying genetic model is usually unknown. Under these circumstances, the classical Cochran-Armitage trend test (CATT) is suboptimal. Robust procedures that maximize the power and preserve the nominal type I error rate are preferable. Moreover, performing a meta-analysis using robust procedures is of great interest and has never been addressed in the past. The primary goal of this work is to implement several robust methods for analysis and meta-analysis in the statistical package Stata and subsequently to make the software available to the scientific community. The CATT under a recessive, additive and dominant model of inheritance as well as robust methods based on the Maximum Efficiency Robust Test statistic, the MAX statistic and the MIN2 were implemented in Stata. Concerning MAX and MIN2, we calculated their asymptotic null distributions relying on numerical integration resulting in a great gain in computational time without losing accuracy. All the aforementioned approaches were employed in a fixed or a random effects meta-analysis setting using summary data with weights equal to the reciprocal of the combined cases and controls. Overall, this is the first complete effort to implement procedures for analysis and meta-analysis in GWAS using Stata. A Stata program and a web-server are freely available for academic users at http://www.compgen.org/tools/GWAR. pbagos@compgen.org. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Meta-analysis on shift work and risks of specific obesity types.

PubMed

Sun, M; Feng, W; Wang, F; Li, P; Li, Z; Li, M; Tse, G; Vlaanderen, J; Vermeulen, R; Tse, L A

2018-01-01

This systematic review and meta-analysis evaluated the associations between shift work patterns and risks of specific types of obesity. PubMed was searched until March 2017 for observational studies that examined the relationships between shift work patterns and obesity. Odds ratio for obesity was extracted using a fixed-effects or random-effects model. Subgroup meta-analyses were carried out for study design, specific obesity types and characteristics of shift work pattern. A total of 28 studies were included in this meta-analysis. The overall odds ratio of night shift work was 1.23 (95% confidence interval = 1.17-1.29) for risk of obesity/overweight. Cross-sectional studies showed a higher risk of 1.26 than those with the cohort design (risk ratio = 1.10). Shift workers had a higher frequency of developing abdominal obesity (odds ratio = 1.35) than other obesity types. Permanent night workers demonstrated a 29% higher risk than rotating shift workers (odds ratio 1.43 vs. 1.14). This meta-analysis confirmed the risks of night shift work for the development of overweight and obesity with a potential gradient association suggested, especially for abdominal obesity. Modification of working schedules is recommended, particularly for prolonged permanent night work. More accurate and detailed measurements on shift work patterns should be conducted in future research. © 2017 World Obesity Federation.

Quantifying the dose-response of walking in reducing coronary heart disease risk: meta-analysis.

PubMed

Zheng, Henry; Orsini, Nicola; Amin, Janaki; Wolk, Alicja; Nguyen, Van Thi Thuy; Ehrlich, Fred

2009-01-01

The evidence for the efficacy of walking in reducing the risk of and preventing coronary heart disease (CHD) is not completely understood. This meta-analysis aimed to quantify the dose-response relationship between walking and CHD risk reduction for both men and women in the general population. Studies on walking and CHD primary prevention between 1954 and 2007 were identified through Medline, SportDiscus and the Cochrane Database of Systematic Reviews. Random-effect meta-regression models were used to pool the relative risks from individual studies. A total of 11 prospective cohort studies and one randomized control trial study met the inclusion criteria, with 295,177 participants free of CHD at baseline and 7,094 cases at follow-up. The meta-analysis indicated that an increment of approximately 30 min of normal walking a day for 5 days a week was associated with 19% CHD risk reduction (95% CI = 14-23%; P-heterogeneity = 0.56; I (2) = 0%). We found no evidence of heterogeneity between subgroups of studies defined by gender (P = 0.67); age of the study population (P = 0.52); or follow-up duration (P = 0.77). The meta-analysis showed that the risk for developing CHD decreases as walking dose increases. Walking should be prescribed as an evidence-based effective exercise modality for CHD prevention in the general population.

Survival rates and prognostic predictors of high grade brain stem gliomas in childhood: a systematic review and meta-analysis.

PubMed

Hassan, Hadeel; Pinches, Anne; Picton, Susan V; Phillips, Robert S

2017-10-01

Diagnosis of a pediatric high grade brain stem glioma is devastating with dismal outcomes. This systematic review and meta-analysis was undertaken to determine the survival rates and assess potential prognostic factors including selected interventions. Studies included involved pediatric participants with high grade brain stem gliomas diagnosed by magnetic resonance imaging or biopsy reporting overall survival rates. Meta-analysis was undertaken using a binomial random effects model. Sixty-five studies (2336 participants) were included. Meta-analysis showed 1 year overall survival (OS) of 41% (95% confidence interval (CI) 38-44%, I-sq 52%, 2083 participants), 2 year OS of 15.3% (95% confidence interval 12-20%, I-sq 73.1%, 1329 participants) and 3 year OS of 7.3% (95% confidence interval 5.2-10%, I-sq 26%, 584 participants). Meta-analyses of median overall survival results was not possible due to the lack of reported measures of variance. Subgroup analysis comparing date of study, classification of tumor, use of temozolomide, non-standard interventions or phase 1/2 versus other studies demonstrated no difference in survival outcomes. There was insufficient data to undertake subgroup meta-analysis of patient age, duration of symptoms, K27M histone mutations and AVCR1 mutations. Survival outcomes of high grade brain stem gliomas have remained very poor, and do not clearly vary according to classification, phase of study or use of different therapeutic interventions. Future studies should harmonize outcome and prognostic variable reporting to enable accurate meta-analysis and better exploration of prognosis.

An overview of meta-analysis for clinicians.

PubMed

Lee, Young Ho

2018-03-01

The number of medical studies being published is increasing exponentially, and clinicians must routinely process large amounts of new information. Moreover, the results of individual studies are often insufficient to provide confident answers, as their results are not consistently reproducible. A meta-analysis is a statistical method for combining the results of different studies on the same topic and it may resolve conflicts among studies. Meta-analysis is being used increasingly and plays an important role in medical research. This review introduces the basic concepts, steps, advantages, and caveats of meta-analysis, to help clinicians understand it in clinical practice and research. A major advantage of a meta-analysis is that it produces a precise estimate of the effect size, with considerably increased statistical power, which is important when the power of the primary study is limited because of a small sample size. A meta-analysis may yield conclusive results when individual studies are inconclusive. Furthermore, meta-analyses investigate the source of variation and different effects among subgroups. In summary, a meta-analysis is an objective, quantitative method that provides less biased estimates on a specific topic. Understanding how to conduct a meta-analysis aids clinicians in the process of making clinical decisions.

MTLRP genetic polymorphism (214C>A) was associated with Type 2 diabetes in Caucasian population: a meta-analysis

PubMed Central

2014-01-01

Background Previous studies reported the relation between MTLRP genetic polymorphism and type 2 diabetes, however, the conclusion were conflicting. In the present study, we performed a meta-analysis to reveal this association. Methods Literature retrieval, selection and assessment, data extraction, and meta-analyses were performed according to the RevMan 5.0 guidelines. In the meta-analysis, we utilized random-effect model or fixed-effect model to pool the Odds ratio (OR) according to the test of heterogeneity. Results A total of nine case–control studies included 4460 type 2 diabetes patients and 4114 healthy control subjects were analyzed. We did not found association between the MTLRP polymorphism and type 2 diabetes risk in the overall population (CC vs CA + AA: OR = 1.02; 95% CI: 0.89-1.17, P = 0.77; A vs C: OR = 1.02; 95% CI: 0.84-0.96, P = 0.62). However, in subgroup analyses stratified by ethnicity, we found significant association of MTLRP polymorphism with type 2 diabetes in Caucasians (CC vs CA + AA: OR = 1.27; 95% CI: 1.02-1.57, P = 0.03; A vs C: OR = 0.74, 95% CI: 0.60–0.91, P = 0.005). Conclusion The MTLRP polymorphism was associated with type 2 diabetes in Caucasians. PMID:25095788

MTLRP genetic polymorphism (214C>A) was associated with Type 2 diabetes in Caucasian population: a meta-analysis.

PubMed

Chen, Li-Li; Han, Song-Mei; Tang, Fei-Fei; Li, Qiang

2014-08-05

Previous studies reported the relation between MTLRP genetic polymorphism and type 2 diabetes, however, the conclusion were conflicting. In the present study, we performed a meta-analysis to reveal this association. Literature retrieval, selection and assessment, data extraction, and meta-analyses were performed according to the RevMan 5.0 guidelines. In the meta-analysis, we utilized random-effect model or fixed-effect model to pool the Odds ratio (OR) according to the test of heterogeneity. A total of nine case-control studies included 4460 type 2 diabetes patients and 4114 healthy control subjects were analyzed. We did not found association between the MTLRP polymorphism and type 2 diabetes risk in the overall population (CC vs CA + AA: OR = 1.02; 95% CI: 0.89-1.17, P = 0.77; A vs C: OR = 1.02; 95% CI: 0.84-0.96, P = 0.62). However, in subgroup analyses stratified by ethnicity, we found significant association of MTLRP polymorphism with type 2 diabetes in Caucasians (CC vs CA + AA: OR = 1.27; 95% CI: 1.02-1.57, P = 0.03; A vs C: OR = 0.74, 95% CI: 0.60-0.91, P = 0.005). The MTLRP polymorphism was associated with type 2 diabetes in Caucasians.

Immunotherapy in advanced melanoma: a network meta-analysis.

PubMed

Pyo, Jung-Soo; Kang, Guhyun

2017-05-01

The aim of this study was to compare the effects of various immunotherapeutic agents and chemotherapy for unresected or metastatic melanomas. We performed a network meta-analysis using a Bayesian statistical model to compare objective response rate (ORR) of various immunotherapies from 12 randomized controlled studies. The estimated ORRs of immunotherapy and chemotherapy were 0.224 and 0.108, respectively. The ORRs of immunotherapy in untreated and pretreated patients were 0.279 and 0.176, respectively. In network meta-analysis, the odds ratios for ORR of nivolumab (1 mg/kg)/ipilmumab (3 mg/kg), pembrolizumab 10 mg/kg and nivolumab 3 mg/kg were 8.54, 5.39 and 4.35, respectively, compared with chemotherapy alone. Our data showed that various immunotherapies had higher ORRs rather than chemotherapy alone.

MetaGenyo: a web tool for meta-analysis of genetic association studies.

PubMed

Martorell-Marugan, Jordi; Toro-Dominguez, Daniel; Alarcon-Riquelme, Marta E; Carmona-Saez, Pedro

2017-12-16

Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise. We have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results. MetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at http://bioinfo.genyo.es/metagenyo/ .

Estrogen receptor β expression and colorectal cancer: a systematic review and meta-analysis.

PubMed

Niv, Yaron

2015-12-01

Estrogen receptor β (ERβ) is a potential tumor-suppressor gene in colorectal cancer (CRC). This hypothesis is supported by clinical and laboratory observations. In this meta-analysis, we looked at studies that investigated the relationship between ERβ protein expression and CRC, comparing the lesion with normal adjacent mucosa. English medical literature searches were performed for ERβ expression in patients with CRC, tumor tissue versus normal mucosa. Searches were performed up to 31 May 2015, using MEDLINE, PubMed, EMBASE, Scopus, and CENTRAL. Meta-analysis was carried out using Comprehensive Meta-analysis Software. Pooled odds ratios and 95% confidence intervals were calculated and ERβ expression was compared in individual studies using the fixed-effects model. The odds ratio of ERβ expression was 0.216 (95% confidence interval 0.152-0.307, P<0.0001), lower in cancer tissue than normal mucosa. Funnel plot did not indicate a significant publication bias. There was no significant heterogeneity in the studies included: Q=5.897, d.f.(Q)=9, I=0.000, P=0.750. In this meta-analysis, we confirm the observation of decreased ERβ expression in CRC. Our results support the hypothesis of ERβ being a tumor-suppressor gene in the large bowel, and the ERβ protein protects against carcinogenesis and development of CRC when activated by estrogen. Further studies are needed to examine the potential of selective/specific ligands to activate ERβ without the side effects found with estrogen and without activating ERα. In this meta-analysis, we looked at studies that investigated the relationship between CRC and ERβ expression in the tumor and normal mucosa of CRC patients. English medical literature searches were performed for studies comparing ERβ expression in the cancer and normal colonic mucosa in patients with CRC. Meta-analysis was carried out, pooled odds ratios were calculated, and ERβ expression was compared in individual studies.

How Efficacious is Danshen (Salvia miltiorrhiza) Dripping Pill in Treating Angina Pectoris? Evidence Assessment for Meta-Analysis of Randomized Controlled Trials.

PubMed

Jia, Yongliang; Leung, Siu-Wai

2017-09-01

More than 230 randomized controlled trials (RCTs) of danshen dripping pill (DSP) and isosorbide dinitrate (ISDN) in treating angina pectoris after the first preferred reporting items for systematic reviews and meta-analyses-compliant comprehensive meta-analysis were published in 2010. Other meta-analyses had flaws in study selection, statistical meta-analysis, and evidence assessment. This study completed the meta-analysis with an extensive assessment of the evidence. RCTs published from 1994 to 2016 on DSP and ISDN in treating angina pectoris for at least 4 weeks were included. The risk of bias (RoB) of included RCTs was assessed with the Cochrane's tool for assessing RoB. Meta-analyses based on a random-effects model were performed on two outcome measures: symptomatic (SYM) and electrocardiography (ECG) improvements. Subgroup analysis, sensitivity analysis, metaregression, and publication bias analysis were also conducted. The evidence strength was evaluated with the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) method. Among the included 109 RCTs with 11,973 participants, 49 RCTs and 5042 participants were new (after 2010). The RoB of included RCTs was high in randomization and blinding. Overall effect sizes in odds ratios for DSP over ISDN were 2.94 (95% confidence interval [CI]: 2.53-3.41) on SYM (n = 108) and 2.37 (95% CI: 2.08-2.69) by ECG (n = 81) with significant heterogeneities (I 2  = 41%, p < 0.0001 on SYM and I 2  = 44%, p < 0.0001 on ECG). Subgroup, sensitivity, and metaregression analyses showed consistent results without publication bias. However, the evidence strength was low in GRADE. The efficacy of DSP was still better than ISDN in treating angina pectoris, but the confidence decreased due to high RoB and heterogeneities.

Graphical tools for network meta-analysis in STATA.

PubMed

Chaimani, Anna; Higgins, Julian P T; Mavridis, Dimitris; Spyridonos, Panagiota; Salanti, Georgia

2013-01-01

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.

Graphical Tools for Network Meta-Analysis in STATA

PubMed Central

Chaimani, Anna; Higgins, Julian P. T.; Mavridis, Dimitris; Spyridonos, Panagiota; Salanti, Georgia

2013-01-01

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results. PMID:24098547

Epidemiology and socio-demographic risk factors of self-immolation: A systematic review and meta-analysis.

PubMed

Parvareh, Maryam; Hajizadeh, Mohammad; Rezaei, Satar; Nouri, Bijan; Moradi, Ghobad; Esmail Nasab, Nader

2018-06-01

Self-immolation or self-inflicted burn is the most tragic and violent method of suicide. The higher prevalence of this dramatic phenomenon in Iran is a serious social and health problem. In this study, we conducted a meta-analysis to combine the results from available studies to examine the epidemiology and socio-demographic characteristics of individuals who attempted self-immolation in Iran. Pertinent studies were identified by searching the electronic bibliographic databases including PubMed, Scopus, Science Direct, Iran Medex, Magiran, Medlib and Scientific Information Database (SID) (2000-October 2016). Meta-analysis was used to summarize the research results on socio-demographic risk factors of self-immolation in Iran. The STROBE checklist was used to assess quality of the study. The random effect model was employed in the meta-analysis to account for the observed heterogeneity among the selected studies. Twenty-nine studies (sample size=5717) were included in the meta-analysis. The estimated average age of individuals who attempted self-immolation was 27.31 (95% confidence interval [CI]: 25.81-28.81) years. Women account for 70% (95% CI: 64-77) of all self-immolation attempts in Iran. Thirty-nine (95% CI: 34-43) per cent of all self-immolation were among singles. Nineteen (95% CI: 16-22) per cent of self-immolators had mental disorder. Meta-regression model showed that the average age of individuals who attempted self-immolation increased significantly over the period between 2000 to 2016 (P-value=0.006). Our study indicated that individuals who attempted self-immolation in Iran were mainly women, married and young adults. Copyright © 2017 Elsevier Ltd and ISBI. All rights reserved.

Dermatological manifestations in hemodialysis patients in Iran: A systematic review and meta-analysis.

PubMed

Asayesh, Hamid; Peykari, Niloofar; Pavaresh-Masoud, Mohammad; Esmaeili Abdar, Mohammad; Tajbakhsh, Ramin; Mousavi, Seyed Mojtaba; Djalalinia, Shirin; Noroozi, Mehdi; Qorbani, Mostafa; Mahdavi-Gorabi, Armita

2018-03-25

Dermatologic complications are common in patients with end-stage renal disease and also have a high diversity. This meta-analysis reviews prevalence of dermatological manifestations among hemodialysis patients in Iran. Using PubMed and NLM Gateway (for MEDLINE), Institute of Scientific Information (ISI), and SCOPUS as the main international electronic data sources, and Iran-Medex, Irandoc, and Scientific Information Database, as the main domestic databases with systematic search capability, we systematically searched surveys, papers, and reports on the prevalence of dermatological manifestations (until February 2016). Heterogeneity of reported prevalence's between studies was assessed using the Q test; overall prevalence of dermatological manifestations was estimated using random-effect meta-analysis model. We found 1229 records; from them, a total of eight studies comprising 917 hemodialysis patients were included. In all of studies, skin discoloration, pruritus and xerosis have the highest prevalence. According to random-effect meta-analysis model, the pooled prevalence of skin discoloration, pruritus, ecchymosis, xerosis, and half-and-half nail in hemodialysis patients were 48.03% (95% CI: 45.09-51.01), 52.85% (95%CI: 49.23-56.47), 19.88 (95% CI: 17.57-22.19), 51.14% (95% CI: 48.25-54.02), and 18.50% (95% CI: 16.0-21.0), respectively. his study shows that the prevalence of dermatological manifestations seems high among the hemodialysis patients in Iran, and skin discoloration, pruritus, and xerosis are more common. © 2018 Wiley Periodicals, Inc.

Meta-analysis of the effect of road work zones on crash occurrence.

PubMed

Theofilatos, Athanasios; Ziakopoulos, Apostolos; Papadimitriou, Eleonora; Yannis, George; Diamandouros, Konstantinos

2017-11-01

There is strong evidence that work zones pose increased risk of crashes and injuries. The two most common risk factors associated with increased crash frequencies are work zone duration and length. However, relevant research on the topic is relatively limited. For that reason, this paper presents formal meta-analyses of studies that have estimated the relationship between the number of crashes and work zone duration and length, in order to provide overall estimates of those effects on crash frequencies. All studies presented in this paper are crash prediction models with similar specifications. According to the meta-analyses and after correcting for publication bias when it was considered appropriate, the summary estimates of regression coefficients were found to be 0.1703 for duration and 0.862 for length. These effects were significant for length but not for duration. However, the overall estimate of duration was significant before correcting for publication bias. Separate meta-analyses on the studies examining both duration and length was also carried out in order to have rough estimates of the combined effects. The estimate of duration was found to be 0.953, while for length was 0.847. Similar to previous meta-analyses the effect of duration after correcting for publication bias is not significant, while the effect of length was significant at a 95% level. Meta-regression findings indicate that the main factors influencing the overall estimates of the beta coefficients are study year and region for duration and study year and model specification for length. Copyright © 2017 Elsevier Ltd. All rights reserved.

A meta-analytic investigation of the relation between interpersonal attraction and enacted behavior.

PubMed

Montoya, R Matthew; Kershaw, Christine; Prosser, Julie L

2018-05-07

We present a meta-analysis that investigated the relation between self-reported interpersonal attraction and enacted behavior. Our synthesis focused on (a) identifying the behaviors related to attraction; (b) evaluating the efficacy of models of the relation between attraction and behavior; (c) testing the impact of several moderators, including evaluative threat salience, cognitive appraisal salience, and the sex composition of the social interaction; and (d) investigating the degree of agreement between the meta-analytic findings and an ethnographic analysis. Using a multilevel modeling approach, an analysis of 309 effect sizes (N = 5,422) revealed a significant association (z = .20) between self-reported attraction and enacted behavior. Key findings include: (a) that the specific behaviors associated with attraction (e.g., eye contact, smiling, laughter, mimicry) are those behaviors research has linked to the development of trust/rapport; (b) direct behaviors (e.g., physical proximity, talking to), compared with indirect behaviors (e.g., eye contact, smiling, mimicry), were more strongly related to self-reported attraction; and (c) evaluative threat salience (e.g., fear of rejection) reduced the magnitude of the relation between direct behavior and affective attraction. Moreover, an ethnographic analysis revealed consistency between the behaviors identified by the meta-analysis and those behaviors identified by ethnographers as predictive of attraction. We discuss the implications of our findings for models of the relation between attraction and behavior, for the behavioral expressions of emotions, and for how attraction is measured and conceptualized. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Biogeochemical Responses and Feedbacks to Climate Change: Synthetic Meta-Analyses Relevant to Earth System Models

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

van Gestel, Natasja; Jan van Groenigen, Kees; Osenberg, Craig

This project examined the sensitivity of carbon in land ecosystems to environmental change, focusing on carbon contained in soil, and the role of carbon-nitrogen interactions in regulating ecosystem carbon storage. The project used a combination of empirical measurements, mathematical models, and statistics to partition effects of climate change on soil into processes enhancing soil carbon and processes through which it decomposes. By synthesizing results from experiments around the world, the work provided novel insight on ecological controls and responses across broad spatial and temporal scales. The project developed new approaches in meta-analysis using principles of element mass balance and largemore » datasets to derive metrics of ecosystem responses to environmental change. The project used meta-analysis to test how nutrients regulate responses of ecosystems to elevated CO2 and warming, in particular responses of nitrogen fixation, critical for regulating long-term C balance.« less

Prevalence of antepartum hemorrhage in women with placenta previa: a systematic review and meta-analysis

PubMed Central

Fan, Dazhi; Wu, Song; Liu, Li; Xia, Qing; Wang, Wen; Guo, Xiaoling; Liu, Zhengping

2017-01-01

Antepartum hemorrhage (APH) is an important cause of perinatal mortality and maternal morbidity in pregnant women with placenta previa in the world. However, the epidemiological characteristics are not completely understood. We performed an initial systematic review and meta-analysis to assess the prevalence of APH in pregnant women with placenta previa. It was totally performed following the Preferred Reporting Items for Systematic reviews and Meta-Analysis statement. PubMed, Elsevier Science Direct, and the Cochrane Library were searched before April 2016. A meta-analysis with a random-effects model based on a proportions approach was performed to determine the prevalence. Stratified analyses, meta-regression method, and sensitivity analysis were utilized to analyze the heterogeneity. A total of 29 articles were included. The pooled overall prevalence of APH among pregnant women with placenta previa was 51.6% (95% CI 42.7–60.6) in a heterogeneous set of studies (I2 = 97.9). Correlation analysis found that there was a positive correlation between prevalence and percentage of multiparous (r = 0.534, P = 0.027) and a negative correlation between prevalence and survey year (r = −0.400, P = 0.031). In conclusion, the prevalence of APH was a high condition among pregnant women with placenta previa. PMID:28067303

Association between metabolic syndrome and bone fractures: a meta-analysis of observational studies.

PubMed

Sun, Kan; Liu, Jianmin; Lu, Nan; Sun, Hanxiao; Ning, Guang

2014-02-09

Emerging epidemiological evidence suggest an association between metabolic syndrome and fractures. However, whether metabolic syndrome is an independent risk or protective factor of fractures remains controversial. Our goal is to provide a quantitative assessment of the association between metabolic syndrome and bone fractures by conducting a meta-analysis of observational studies. The PubMed and Embase database were searched through to March 2013 to identify studies that met pre-established inclusion criteria. Reference lists of retrieved articles were also reviewed. Summary effect estimates with 95% confidence intervals (CI) were derived using a fixed or random effects model, depending on the heterogeneity of the included studies. Eight epidemiologic studies involving 39,938 participants were included in the meta-analysis. In overall analysis, metabolic syndrome was not associated with prevalent fractures [pooled odds ratio (OR) 0.93, 95% CI 0.84 - 1.03] in cross-sectional studies or incident fractures [pooled relative risk (RR) 0.88, 95% CI 0.37 - 2.12] in prospective cohort studies. No evidence of heterogeneity was found in cross-sectional studies (p = 0.786, I2 = 0.0%). A substantial heterogeneity was detected in cohort studies (p = 0.001, I2 = 85.7%). No indication of significant publication bias was found either from Begg's test or Egger's test. Estimates of total effects were substantially consistent in the sensitivity and stratification analyses. The present meta-analysis of observational studies suggests that the metabolic syndrome has no explicit effect on bone fractures.

The Effects of Text Structure Instruction on Expository Reading Comprehension: A Meta-Analysis

ERIC Educational Resources Information Center

Hebert, Michael; Bohaty, Janet J.; Nelson, J. Ron; Brown, Jessica

2016-01-01

In this meta-analysis of 45 studies involving students in Grades 2-12, the authors present evidence on the effects of text structure instruction on the expository reading comprehension of students. The meta-analysis was deigned to answer 2 sets of questions. The first set of questions examined the effectiveness of text structure instruction on…

A systematic review and meta-analysis of the ability of analgesic drugs to reduce metastasis in experimental cancer models

PubMed Central

Hooijmans, Carlijn R.; Geessink, Florentine J.; Ritskes-Hoitinga, Merel; Scheffer, Gert-Jan

2015-01-01

Abstract Analgesics are commonly used to manage pain in cancer patients. It has been suggested that there might be a relation between analgesics and the outgrowth of metastases. Opioids might increase and non-steroidal anti-inflammatory drugs decrease the risk of metastasis. Robust analysis of all preclinical evidence, however, has so far been lacking. Therefore, we conducted a systematic review and meta-analysis on the effect of treatment with analgesics on metastasis in experimental animal models. One hundred forty-seven studies met the inclusion criteria. Study characteristics, outcome data on the number, and incidence of metastases were extracted, and methodological quality was assessed. In the meta-analysis, we included 215 (±4000 animals) and 137 (±3000 animals) comparisons between analgesic vs control treatment, respectively, on the number and incidence of metastases. Overall, treatment with analgesics significantly decreases the number and risk of metastasis. This effect appears mainly to be the consequence of the efficacy of NSAIDs. Other factors that modify the efficacy are species, type of NSAIDs administered, timing, and duration of treatment. There is no evidence indicating that treatment with any analgesics increases the occurrence of metastases. Our findings appear robust for the various animal models and designs included in this review, which increases our confidence in the result and translatability to the clinical situation. PMID:26181303

Association of coffee drinking with all-cause mortality: a systematic review and meta-analysis.

PubMed

Zhao, Yimin; Wu, Kejian; Zheng, Jusheng; Zuo, Ruiting; Li, Duo

2015-05-01

We aimed to use the meta-analysis method to assess the relationship between coffee drinking and all-cause mortality. Categorical and dose-response meta-analyses were conducted using random-effects models. We systematically searched and identified eligible literature in the PubMed and Scopus databases. Seventeen studies including 1 054 571 participants and 131 212 death events from all causes were included in the present study. Seventeen studies were included and evaluated in the meta-analysis. A U-shaped dose-response relationship was found between coffee consumption and all-cause mortality (P for non-linearity <0.001). Compared with non/occasional coffee drinkers, the relative risks for all-cause mortality were 0.89 (95 % CI 0.85, 0.93) for 1-<3 cups/d, 0.87 (95 % CI 0.83, 0.91) for 3-<5 cups/d and 0.90 (95 % CI 0.87, 0.94) for ≥5 cups/d, and the relationship was more marked in females than in males. The present meta-analysis of prospective cohort studies indicated that light to moderate coffee intake is associated with a reduced risk of death from all causes, particularly in women.

Illness representations, coping, and illness outcomes in people with cancer: a systematic review and meta-analysis.

PubMed

Richardson, Emma M; Schüz, Natalie; Sanderson, Kristy; Scott, Jennifer L; Schüz, Benjamin

2017-06-01

Cancer is associated with negative health and emotional outcomes in those affected by it, suggesting the need to better understand the psychosocial determinants of illness outcomes and coping. The common sense model is the leading psychological model of self-regulation in the face of illness and assumes that subjective illness representations explain how people attempt to cope with illness. This systematic review and meta-analysis examines the associations of the common sense model's illness representation dimensions with health and coping outcomes in people with cancer. A systematic literature search located 54 studies fulfilling the inclusion criteria, with 38 providing sufficient data for meta-analysis. A narrative review of the remaining studies was also conducted. Random-effects models revealed small to moderate effect sizes (Fisher Z) for the relations between illness representations and coping behaviors (in particular between control perceptions, problem-focused coping, and cognitive reappraisal) and moderate to large effect sizes between illness representations and illness outcomes (in particular between identity, consequences, emotional representations, and psychological distress). The narrative review of studies with insufficient data provided similar results. The results indicate how illness representations relate to illness outcomes in people with cancer. However, more high-quality studies are needed to examine causal effects of illness representations on coping and outcomes. High heterogeneity indicates potential moderators of the relationships between illness representations and health and coping outcomes, including diagnostic, prognostic, and treatment-related variables. This review can inform the design of interventions to improve coping strategies and mental health outcomes in people with cancer. Copyright © 2016 John Wiley & Sons, Ltd.

Evaluating Web-Based Nursing Education's Effects: A Systematic Review and Meta-Analysis.

PubMed

Kang, Jiwon; Seomun, GyeongAe

2017-09-01

This systematic review and meta-analysis investigated whether using web-based nursing educational programs increases a participant's knowledge and clinical performance. We performed a meta-analysis of studies published between January 2000 and July 2016 and identified through RISS, CINAHL, ProQuest Central, Embase, the Cochrane Library, and PubMed. Eleven studies were eligible for inclusion in this analysis. The results of the meta-analysis demonstrated significant differences not only for the overall effect but also specifically for blended programs and short (2 weeks or 4 weeks) intervention periods. To present more evidence supporting the effectiveness of web-based nursing educational programs, further research is warranted.

Digital Games, Design, and Learning: A Systematic Review and Meta-Analysis.

PubMed

Clark, Douglas B; Tanner-Smith, Emily E; Killingsworth, Stephen S

2016-03-01

In this meta-analysis, we systematically reviewed research on digital games and learning for K-16 students. We synthesized comparisons of game versus nongame conditions (i.e., media comparisons) and comparisons of augmented games versus standard game designs (i.e., value-added comparisons). We used random-effects meta-regression models with robust variance estimates to summarize overall effects and explore potential moderator effects. Results from media comparisons indicated that digital games significantly enhanced student learning relative to nongame conditions ([Formula: see text] = 0.33, 95% confidence interval [0.19, 0.48], k = 57, n = 209). Results from value-added comparisons indicated significant learning benefits associated with augmented game designs ([Formula: see text] = 0.34, 95% confidence interval [0.17, 0.51], k = 20, n = 40). Moderator analyses demonstrated that effects varied across various game mechanics characteristics, visual and narrative characteristics, and research quality characteristics. Taken together, the results highlight the affordances of games for learning as well as the key role of design beyond medium.

Meta-analysis of the role of delivery mode in postpartum depression (Iran 1997-2011)

PubMed Central

Bahadoran, Parvin; Oreizi, Hamid Reza; Safari, Saeideh

2014-01-01

Background: Postpartum period is the riskiest time for mood disorders and psychosis. Postpartum depression is the most important mood disorder after delivery, which can be accompanied by mother-child and family relationship disorders. Meta-analysis with the integration of research results demonstrates to investigate the association between the mode of delivery and postpartum depression. Materials and Methods: This meta-analysis uses the Rosenthal and Robin approach. For this purpose, 18 studies which were acceptable in terms of methodology were selected and meta-analysis was conducted on them. Research instrument was a checklist of meta-analysis. After summarizing the results of the studies, effect sizes were calculated manually and combined based on meta-analysis method. Results: The findings showed that the amount of effect size (in term of Cohen d) of delivery mode on postpartum depression was 0/30 (P < 0.001). Conclusion: Delivery mode on maternal mental health is assessed medium. Meta analysis also indicates moderator variables role, and researcher must focus in these variables. PMID:25540791

Unique effects and moderators of effects of sources on self-efficacy: A model-based meta-analysis.

PubMed

Byars-Winston, Angela; Diestelmann, Jacob; Savoy, Julia N; Hoyt, William T

2017-11-01

Self-efficacy beliefs are strong predictors of academic pursuits, performance, and persistence, and in theory are developed and maintained by 4 classes of experiences Bandura (1986) referred to as sources: performance accomplishments (PA), vicarious learning (VL), social persuasion (SP), and affective arousal (AA). The effects of sources on self-efficacy vary by performance domain and individual difference factors. In this meta-analysis (k = 61 studies of academic self-efficacy; N = 8,965), we employed B. J. Becker's (2009) model-based approach to examine cumulative effects of the sources as a set and unique effects of each source, controlling for the others. Following Becker's recommendations, we used available data to create a correlation matrix for the 4 sources and self-efficacy, then used these meta-analytically derived correlations to test our path model. We further examined moderation of these associations by subject area (STEM vs. non-STEM), grade, sex, and ethnicity. PA showed by far the strongest unique association with self-efficacy beliefs. Subject area was a significant moderator, with sources collectively predicting self-efficacy more strongly in non-STEM (k = 14) compared with STEM (k = 47) subjects (R2 = .37 and .22, respectively). Within studies of STEM subjects, grade level was a significant moderator of the coefficients in our path model, as were 2 continuous study characteristics (percent non-White and percent female). Practical implications of the findings and future research directions are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The Effect of Hypnosis on Anxiety in Patients With Cancer: A Meta-Analysis.

PubMed

Chen, Pei-Ying; Liu, Ying-Mei; Chen, Mei-Ling

2017-06-01

Anxiety is a common form of psychological distress in patients with cancer. One recognized nonpharmacological intervention to reduce anxiety for various populations is hypnotherapy or hypnosis. However, its effect in reducing anxiety in cancer patients has not been systematically evaluated. This meta-analysis was designed to synthesize the immediate and sustained effects of hypnosis on anxiety of cancer patients and to identify moderators for these hypnosis effects. Qualified studies including randomized controlled trials (RCT) and pre-post design studies were identified by searching seven electronic databases: Scopus, Medline Ovidsp, PubMed, PsycInfo-Ovid, Academic Search Premier, CINAHL Plus with FT-EBSCO, and SDOL. Effect size (Hedges' g) was computed for each study. Random-effect modeling was used to combine effect sizes across studies. All statistical analyses were conducted with Comprehensive Meta-Analysis, version 2 (Biostat, Inc., Englewood, NJ, USA). Our meta-analysis of 20 studies found that hypnosis had a significant immediate effect on anxiety in cancer patients (Hedges' g: 0.70-1.41, p < .01) and the effect was sustained (Hedges' g: 0.61-2.77, p < .01). The adjusted mean effect size (determined by Duvan and Tweedie's trim-and-fill method) was 0.46. RCTs had a significantly higher effect size than non-RCT studies. Higher mean effect sizes were also found with pediatric study samples, hematological malignancy, studies on procedure-related stressors, and with mixed-gender samples. Hypnosis delivered by a therapist was significantly more effective than self-hypnosis. Hypnosis can reduce anxiety of cancer patients, especially for pediatric cancer patients who experience procedure-related stress. We recommend therapist-delivered hypnosis should be preferred until more effective self-hypnosis strategies are developed. © 2017 Sigma Theta Tau International.

The associations between PD-1, CTLA-4 gene polymorphisms and susceptibility to ankylosing spondylitis: a meta-analysis and systemic review.

PubMed

Chen, Si; Li, Yuan; Deng, Chuiwen; Li, Jing; Wen, Xiaoting; Wu, Ziyan; Hu, Chaojun; Zhang, Shulan; Li, Ping; Zhang, Xuan; Zhang, Fengchun; Li, Yongzhe

2016-01-01

Previous surveys had evaluated the effects of the PD-1, CTLA-4 gene polymorphisms on susceptibility to ankylosing spondylitis (AS), but the results remained controversial. To briefly examine these consequences, a comprehensive meta-analysis was conducted to estimate the relationships between PD-1 rs11568821, rs2227982, rs2227981, CTLA-4 +49 A/G and -318 C/T polymorphisms and AS risk. The available articles dated to December 2014 were searched in the PUBMED, MEDLINE and EMBASE databases. The data of the genotypes and/or alleles for the PD-1 rs11568821, rs2227982, rs2227981, CTLA-4 +49 A/G and -318 C/T polymorphisms in the AS and control subjects were extracted, and statistical analysis was conducted by STATA 11.2 software. Summary odds ratios (ORs) with their 95 % confidence intervals (95 % CIs) were calculated to determine the strength of associations with fixed-effects or random-effects models. A total of eight published studies were finally involved in this meta-analysis. Meta-analysis of PD-1 rs2227982 polymorphism under the T allele versus C allele (OR 1.744, 95 % CI 1.477-2.059, P < 0.0001), TT+TC versus CC (OR 2.292, 95 % CI 1.654-3.175, P < 0.0001), TT versus CC (OR 1.883, 95 % CI 1.299-2.729, P = 0.001) revealed a significant association with AS. Our meta-analysis demonstrated that the rs2227982 polymorphism in the PD-1 gene might contribute to AS susceptibility. However, further studies with large sample sizes and among different ethnicity populations should be required to confirm this association.

Association between type 1 diabetes mellitus and risk of epilepsy: A meta-analysis of observational studies.

PubMed

Yan, Dandan; Zhao, Enfa; Zhang, Hong; Luo, Xiaohui; Du, Yajuan

2017-01-01

A potential association between type 1 diabetes mellitus and subsequent epilepsy emerged in recent studies. This study aimed to evaluate the possible relationship between type 1 diabetes mellitus and epilepsy using meta-analysis. Pubmed, ISI Web of Knowledge, Embase and Cochrane Library were searched for potential studies of the association between type 1 diabetes mellitus and epilepsy from inception to February 1, 2017. Two investigators independently screened studies for inclusion and extracted related data; discrepancies were solved by consensus. Random effects model of Hazard Ratio (HR) was used to estimate the strength of association. We identified 13 papers from potentially relevant articles of which 3 cohort studies met the inclusion criteria. Random effects meta-analysis showed that type 1 diabetes mellitus was associated with an increased risk of epilepsy with HR = 3.29 (95% CI: 2.61-4.14; I 2 = 0, p = 0.689). Similar results were observed in type 1 diabetes mellitus patents younger than 18-years-old with HR = 2.96 (95% CI: 2.28-3.84; I 2 = 0, p = 0.571). Meta-analysis of 2 studies that adjusted for potential confounders yielded an increased risk of epilepsy with HR = 2.89 (95% CI: 2.26-3.70; I 2 = 0, p = 0.831). The meta-analysis indicates that type 1 diabetes mellitus is associated with a statistically significant increased risk for epilepsy compared to those without type 1 diabetes mellitus.

Melatonin for Atypical Antipsychotic-Induced Metabolic Adverse Effects: A Meta-Analysis of Randomized Controlled Trials.

PubMed

Kamath, Ashwin; Rather, Zahoor Ahmad

2018-01-01

The objective of our study was to determine the effect of melatonin administration on atypical antipsychotic-induced metabolic adverse effects in patients with psychiatric disorders. A systematic search was performed in PUBMED, Cochrane Library, Scopus, Web of Science, and EBSCOhost electronic databases. Randomized controlled trials studying the effect of melatonin on antipsychotic-induced metabolic adverse effects were identified and subjected to meta-analysis. Four studies were included in the meta-analysis, including 57 patients on melatonin and 61 patients on placebo. Melatonin produced a significant decrease in the diastolic blood pressure compared with placebo (mean difference = -4.44 [95% CI, -7.00 to -1.88]; p = 0.0007; I 2 = 13%), but not the systolic blood pressure (mean difference = -4.23 [95% CI, -8.11 to -0.36]; p = 0.03; I 2 = 0%). Although a decrease in the body mass index was seen in the melatonin group, the difference was not significant in the random-effects analysis model. To conclude, in patients on atypical antipsychotics, melatonin at a dose of up to 5 mg/day for a treatment duration of up to 12 weeks attenuated the rise in diastolic blood pressure compared with placebo but had no significant effects on other metabolic parameters.

Investigation of 2-stage meta-analysis methods for joint longitudinal and time-to-event data through simulation and real data application.

PubMed

Sudell, Maria; Tudur Smith, Catrin; Gueyffier, François; Kolamunnage-Dona, Ruwanthi

2018-04-15

Joint modelling of longitudinal and time-to-event data is often preferred over separate longitudinal or time-to-event analyses as it can account for study dropout, error in longitudinally measured covariates, and correlation between longitudinal and time-to-event outcomes. The joint modelling literature focuses mainly on the analysis of single studies with no methods currently available for the meta-analysis of joint model estimates from multiple studies. We propose a 2-stage method for meta-analysis of joint model estimates. These methods are applied to the INDANA dataset to combine joint model estimates of systolic blood pressure with time to death, time to myocardial infarction, and time to stroke. Results are compared to meta-analyses of separate longitudinal or time-to-event models. A simulation study is conducted to contrast separate versus joint analyses over a range of scenarios. Using the real dataset, similar results were obtained by using the separate and joint analyses. However, the simulation study indicated a benefit of use of joint rather than separate methods in a meta-analytic setting where association exists between the longitudinal and time-to-event outcomes. Where evidence of association between longitudinal and time-to-event outcomes exists, results from joint models over standalone analyses should be pooled in 2-stage meta-analyses. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Effectiveness of Mobile Devices on Vocabulary Learning: A Meta-Analysis

ERIC Educational Resources Information Center

Mahdi, Hassan Saleh

2018-01-01

Mobile devices are considered as the most widely used information and communication technologies. They have provided great advantages in language learning. This study reports a meta-analysis of the effectiveness of using mobile devices on vocabulary learning. A meta-analysis was conducted on research that compared the outcomes from students…

The Five-Factor Model personality traits in schizophrenia: A meta-analysis.

PubMed

Ohi, Kazutaka; Shimada, Takamitsu; Nitta, Yusuke; Kihara, Hiroaki; Okubo, Hiroaki; Uehara, Takashi; Kawasaki, Yasuhiro

2016-06-30

Personality is one of important factors in the pathogenesis of schizophrenia because it affects patients' symptoms, cognition and social functioning. Several studies have reported specific personality traits in patients with schizophrenia compared with healthy subjects. However, the results were inconsistent among studies. The NEO Five-Factor Inventory (NEO-FFI) measures five personality traits: Neuroticism (N), Extraversion (E), Openness (O), Agreeableness (A) and Conscientiousness (C). Here, we performed a meta-analysis of these personality traits assessed by the NEO-FFI in 460 patients with schizophrenia and 486 healthy subjects from the published literature and investigated possible associations between schizophrenia and these traits. There was no publication bias for any traits. Because we found evidence of significant heterogeneity in all traits among the studies, we applied a random-effect model to perform the meta-analysis. Patients with schizophrenia showed a higher score for N and lower scores for E, O, A and C compared with healthy subjects. The effect sizes of these personality traits ranged from moderate to large. These differences were not affected by possible moderator factors, such as gender distribution and mean age in each study, expect for gender effect for A. These findings suggest that patients with schizophrenia have a different personality profile compared with healthy subjects. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Meta-analyses of Adverse Effects Data Derived from Randomised Controlled Trials as Compared to Observational Studies: Methodological Overview

PubMed Central

Golder, Su; Loke, Yoon K.; Bland, Martin

2011-01-01

Background There is considerable debate as to the relative merits of using randomised controlled trial (RCT) data as opposed to observational data in systematic reviews of adverse effects. This meta-analysis of meta-analyses aimed to assess the level of agreement or disagreement in the estimates of harm derived from meta-analysis of RCTs as compared to meta-analysis of observational studies. Methods and Findings Searches were carried out in ten databases in addition to reference checking, contacting experts, citation searches, and hand-searching key journals, conference proceedings, and Web sites. Studies were included where a pooled relative measure of an adverse effect (odds ratio or risk ratio) from RCTs could be directly compared, using the ratio of odds ratios, with the pooled estimate for the same adverse effect arising from observational studies. Nineteen studies, yielding 58 meta-analyses, were identified for inclusion. The pooled ratio of odds ratios of RCTs compared to observational studies was estimated to be 1.03 (95% confidence interval 0.93–1.15). There was less discrepancy with larger studies. The symmetric funnel plot suggests that there is no consistent difference between risk estimates from meta-analysis of RCT data and those from meta-analysis of observational studies. In almost all instances, the estimates of harm from meta-analyses of the different study designs had 95% confidence intervals that overlapped (54/58, 93%). In terms of statistical significance, in nearly two-thirds (37/58, 64%), the results agreed (both studies showing a significant increase or significant decrease or both showing no significant difference). In only one meta-analysis about one adverse effect was there opposing statistical significance. Conclusions Empirical evidence from this overview indicates that there is no difference on average in the risk estimate of adverse effects of an intervention derived from meta-analyses of RCTs and meta-analyses of observational studies. This suggests that systematic reviews of adverse effects should not be restricted to specific study types. Please see later in the article for the Editors' Summary PMID:21559325

Meta-analysis of high-latitude nitrogen-addition and warming studies implies ecological mechanisms overlooked by land models

NASA Astrophysics Data System (ADS)

Bouskill, N. J.; Riley, W. J.; Tang, J. Y.

2014-12-01

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the climate. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the aboveground and belowground responses to warming and nitrogen addition in high-latitude ecosystems, and identified absent or poorly parameterized mechanisms in CLM4.5. While the two model versions predicted similar soil carbon stock trajectories following both warming and nitrogen addition, other predicted variables (e.g., belowground respiration) differed from observations in both magnitude and direction, indicating that CLM4.5 has inadequate underlying mechanisms for representing high-latitude ecosystems. On the basis of observational synthesis, we attribute the model-observation differences to missing representations of microbial dynamics, aboveground and belowground coupling, and nutrient cycling, and we use the observational meta-analysis to discuss potential approaches to improving the current models. However, we also urge caution concerning the selection of data sets and experiments for meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average = 72 kg ha-1 yr-1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which precludes a rigorous evaluation of the model responses to likely nitrogen perturbations. Overall, we demonstrate that elucidating ecological mechanisms via meta-analysis can identify deficiencies in ecosystem models and empirical experiments.

The Big Picture: A Meta-Analysis of Program Effectiveness Research on English Language Learners

ERIC Educational Resources Information Center

Rolstad, Kellie; Mahoney, Kate; Glass, Gene V.

2005-01-01

This article presents a meta-analysis of program effectiveness research on English language learners. The study includes a corpus of 17 studies conducted since Willig's earlier meta-analysis and uses Glass, McGaw, and Smith's strategy of including as many studies as possible in the analysis rather than excluding some on the basis of a priori…

Determining job satisfaction of nurses working in hospitals of Iran: A systematic review and meta-analysis.

PubMed

Amiresmaili, Mohammadreza; Moosazadeh, Mahmood

2013-09-01

Employees feeling and attitude to their job has a significant role on their performance. Present study sought to investigate documents related to nurses job satisfaction, using systematic review and meta-analysis to estimate nurses job satisfaction in Iran. Papers on nurses job satisfaction were identified by searching different data bases using appropriate key words. Seventeen studies were extracted using inclusuion criteria. Data were analyzed using Meta-analysis command in STATA 11. Considerable hetrogenecity is apparent in results of nurses job satisfaction studies. Although, according to random effect model, nurses total job satisfaction was estimated at 46.3 (CI: 32.1-60.4), this was estimated at 51.9 (CI = 51.1-52.8) using fixed effect model. Additionally, a reverse relationship was observed between nurses overall job satisfaction and their age. Nurses' job satisfaction in Iran is at a good level compared with other countries. The more satisfied the nurses are with their working conditions, the less is their intention to leave their job. Dissatisfaction is associated with higher resignment and turnover, paying deep attention to efficient factors on nurses dissatisfaction and trying to overcome them is important to improve nurses' working conditions.

Recombinant Tissue Plasminogen Activator Induces Neurological Side Effects Independent on Thrombolysis in Mechanical Animal Models of Focal Cerebral Infarction: A Systematic Review and Meta-Analysis.

PubMed

Dong, Mei-Xue; Hu, Qing-Chuan; Shen, Peng; Pan, Jun-Xi; Wei, You-Dong; Liu, Yi-Yun; Ren, Yi-Fei; Liang, Zi-Hong; Wang, Hai-Yang; Zhao, Li-Bo; Xie, Peng

2016-01-01

Recombinant tissue plasminogen activator (rtPA) is the only effective drug approved by US FDA to treat ischemic stroke, and it contains pleiotropic effects besides thrombolysis. We performed a meta-analysis to clarify effect of tissue plasminogen activator (tPA) on cerebral infarction besides its thrombolysis property in mechanical animal stroke. Relevant studies were identified by two reviewers after searching online databases, including Pubmed, Embase, and ScienceDirect, from 1979 to 2016. We identified 6, 65, 17, 12, 16, 12 and 13 comparisons reporting effect of endogenous tPA on infarction volume and effects of rtPA on infarction volume, blood-brain barrier, brain edema, intracerebral hemorrhage, neurological function and mortality rate in all 47 included studies. Standardized mean differences for continuous measures and risk ratio for dichotomous measures were calculated to assess the effects of endogenous tPA and rtPA on cerebral infarction in animals. The quality of included studies was assessed using the Stroke Therapy Academic Industry Roundtable score. Subgroup analysis, meta-regression and sensitivity analysis were performed to explore sources of heterogeneity. Funnel plot, Trim and Fill method and Egger's test were obtained to detect publication bias. We found that both endogenous tPA and rtPA had not enlarged infarction volume, or deteriorated neurological function. However, rtPA would disrupt blood-brain barrier, aggravate brain edema, induce intracerebral hemorrhage and increase mortality rate. This meta-analysis reveals rtPA can lead to neurological side effects besides thrombolysis in mechanical animal stroke, which may account for clinical exacerbation for stroke patients that do not achieve vascular recanalization with rtPA.

Recombinant Tissue Plasminogen Activator Induces Neurological Side Effects Independent on Thrombolysis in Mechanical Animal Models of Focal Cerebral Infarction: A Systematic Review and Meta-Analysis

PubMed Central

Wei, You-Dong; Liu, Yi-Yun; Ren, Yi-Fei; Liang, Zi-Hong; Wang, Hai-Yang; Zhao, Li-Bo; Xie, Peng

2016-01-01

Background and Purpose Recombinant tissue plasminogen activator (rtPA) is the only effective drug approved by US FDA to treat ischemic stroke, and it contains pleiotropic effects besides thrombolysis. We performed a meta-analysis to clarify effect of tissue plasminogen activator (tPA) on cerebral infarction besides its thrombolysis property in mechanical animal stroke. Methods Relevant studies were identified by two reviewers after searching online databases, including Pubmed, Embase, and ScienceDirect, from 1979 to 2016. We identified 6, 65, 17, 12, 16, 12 and 13 comparisons reporting effect of endogenous tPA on infarction volume and effects of rtPA on infarction volume, blood-brain barrier, brain edema, intracerebral hemorrhage, neurological function and mortality rate in all 47 included studies. Standardized mean differences for continuous measures and risk ratio for dichotomous measures were calculated to assess the effects of endogenous tPA and rtPA on cerebral infarction in animals. The quality of included studies was assessed using the Stroke Therapy Academic Industry Roundtable score. Subgroup analysis, meta-regression and sensitivity analysis were performed to explore sources of heterogeneity. Funnel plot, Trim and Fill method and Egger’s test were obtained to detect publication bias. Results We found that both endogenous tPA and rtPA had not enlarged infarction volume, or deteriorated neurological function. However, rtPA would disrupt blood-brain barrier, aggravate brain edema, induce intracerebral hemorrhage and increase mortality rate. Conclusions This meta-analysis reveals rtPA can lead to neurological side effects besides thrombolysis in mechanical animal stroke, which may account for clinical exacerbation for stroke patients that do not achieve vascular recanalization with rtPA. PMID:27387385

Conducting meta-analyses of HIV prevention literatures from a theory-testing perspective.

PubMed

Marsh, K L; Johnson, B T; Carey, M P

2001-09-01

Using illustrations from HIV prevention research, the current article advocates approaching meta-analysis as a theory-testing scientific method rather than as merely a set of rules for quantitative analysis. Like other scientific methods, meta-analysis has central concerns with internal, external, and construct validity. The focus of a meta-analysis should only rarely be merely describing the effects of health promotion, but rather should be on understanding and explaining phenomena and the processes underlying them. The methodological decisions meta-analysts make in conducting reviews should be guided by a consideration of the underlying goals of the review (e.g., simply effect size estimation or, preferably theory testing). From the advocated perspective that a health behavior meta-analyst should test theory, the authors present a number of issues to be considered during the conduct of meta-analyses.

Transfemoral, transapical and transcatheter aortic valve implantation and surgical aortic valve replacement: a meta-analysis of direct and adjusted indirect comparisons of early and mid-term deaths.

PubMed

Ando, Tomo; Takagi, Hisato; Grines, Cindy L

2017-09-01

Clinical outcomes of transfemoral-transcatheter aortic valve implantation (TF-TAVI) versus surgical aortic valve replacement (SAVR) or transapical (TA)-TAVI are limited to a few randomized clinical trials (RCTs). Because previous meta-analyses only included a limited number of adjusted studies or several non-adjusted studies, our goal was to compare and summarize the outcomes of TF-TAVI vs SAVR and TF-TAVI vs TA-TAVI exclusively with the RCT and propensity-matched cohort studies with direct and adjusted indirect comparisons to reach more precise conclusions. We hypothesized that TF-TAVI would offer surgical candidates a better outcome compared with SAVR and TA-TAVI because of its potential for fewer myocardial injuries. A literature search was conducted through PUBMED and EMBASE through June 2016. Only RCTs and propensity-matched cohort studies were included. A direct meta-analysis of TF-TAVI vs SAVR, TA-TAVI vs SAVR and TF-TAVI vs TA-TAVI was conducted. Then, the effect size of an indirect meta-analysis was calculated from the direct meta-analysis. The effect sizes of direct and indirect meta-analyses were then combined. A random-effects model was used to calculate the hazards ratio and the odds ratio with 95% confidence intervals. Early (in-hospital or 30 days) and mid-term (≥1 year) all-cause mortality rates were assessed. Our search resulted in 4 RCTs (n = 2319) and 14 propensity-matched cohort (n = 7217) studies with 9536 patients of whom 3471, 1769 and 4296 received TF, TA and SAVR, respectively. Direct meta-analyses and combined direct and indirect meta-analyses of early and mid-term deaths with TF-TAVI and SAVR were similar. Early deaths with TF-TAVI vs TA-TAVI were comparable in direct meta-analyses (odds ratio 0.64, P = 0.35) and direct and indirect meta-analyses combined (odds ratio 0.73, P = 0.24). Mid-term deaths with TF-TAVI vs TA-TAVI were increased (hazard ratio 0.83, P = 0.07) in a direct meta-analysis and became significant after addition of the indirect meta-analysis (hazard ratio 0.78, 95% confidence interval 0.67-0.92, P = 0.003). In conclusion, TF-TAVI was associated with similar early and mid-term deaths compared with SAVR. The number of early deaths was not significantly different between TF-TAVI and TA-TAVI, whereas there were fewer mid-term deaths with TF-TAVI than with TA-TAVI. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Myopia and/or longer axial length are protective against diabetic retinopathy: a meta-analysis.

PubMed

Fu, Yu; Geng, Dengfeng; Liu, Hua; Che, Huixin

2016-06-01

To evaluate the current evidence of the relationship between myopia, together with its structural and refractive component, and diabetic retinopathy (DR) risk. A systematic search was performed up to April, 2015. Summary odds ratios (ORs) and 95% confidence intervals (CIs) were calculated employing random-effects models. Three models were used to assess the association between myopia and risk of DR: axial length (AL) (per millimetre increase) and DR; myopia (myopia versus non-myopia) and DR; refractive error (RE) (per D decrease) and DR. Publication bias of the literature was evaluated using Begg's funnel plots and Egger's test. A total of 11 studies that met the predefined criteria were included in this meta-analysis. Overall, longer AL (per millimetre increase) was associa-ted with a significantly decreased risk of DR (combined OR, 0.75; 95% CI, 0.65-0.86; p < 0.001); myopic eyes (myopia versus non-myopia) showed a lower risk of DR (combined OR, 0.70; 95% CI, 0.58-0.85; p < 0.001). A greater degree of myopic RE (per D decrease) also revealed a significantly decreased risk of DR (combined OR, 0.89; 95% CI, 0.85-0.93; p < 0.001). The sensitivity analyses and cumulative meta-analysis showed similar results. No publication bias was detected in any of the three models. This meta-analysis suggests that both myopic refraction and longer AL are associated with a lower risk of DR. Further studies are needed to determine exact mechanisms underpinning the protective effect of myopia against DR. © 2015 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Meta-analysis in evidence-based healthcare: a paradigm shift away from random effects is overdue.

PubMed

Doi, Suhail A R; Furuya-Kanamori, Luis; Thalib, Lukman; Barendregt, Jan J

2017-12-01

Each year up to 20 000 systematic reviews and meta-analyses are published whose results influence healthcare decisions, thus making the robustness and reliability of meta-analytic methods one of the world's top clinical and public health priorities. The evidence synthesis makes use of either fixed-effect or random-effects statistical methods. The fixed-effect method has largely been replaced by the random-effects method as heterogeneity of study effects led to poor error estimation. However, despite the widespread use and acceptance of the random-effects method to correct this, it too remains unsatisfactory and continues to suffer from defective error estimation, posing a serious threat to decision-making in evidence-based clinical and public health practice. We discuss here the problem with the random-effects approach and demonstrate that there exist better estimators under the fixed-effect model framework that can achieve optimal error estimation. We argue for an urgent return to the earlier framework with updates that address these problems and conclude that doing so can markedly improve the reliability of meta-analytical findings and thus decision-making in healthcare.

Effects of caffeine intake on muscle strength and power: a systematic review and meta-analysis.

PubMed

Grgic, Jozo; Trexler, Eric T; Lazinica, Bruno; Pedisic, Zeljko

2018-01-01

Caffeine is commonly used as an ergogenic aid. Literature about the effects of caffeine ingestion on muscle strength and power is equivocal. The aim of this systematic review and meta-analysis was to summarize results from individual studies on the effects of caffeine intake on muscle strength and power. A search through eight databases was performed to find studies on the effects of caffeine on: (i) maximal muscle strength measured using 1 repetition maximum tests; and (ii) muscle power assessed by tests of vertical jump. Meta-analyses of standardized mean differences (SMD) between placebo and caffeine trials from individual studies were conducted using the random effects model. Ten studies on the strength outcome and ten studies on the power outcome met the inclusion criteria for the meta-analyses. Caffeine ingestion improved both strength (SMD = 0.20; 95% confidence interval [CI]: 0.03, 0.36; p  = 0.023) and power (SMD = 0.17; 95% CI: 0.00, 0.34; p  = 0.047). A subgroup analysis indicated that caffeine significantly improves upper (SMD = 0.21; 95% CI: 0.02, 0.39; p  = 0.026) but not lower body strength (SMD = 0.15; 95% CI: -0.05, 0.34; p  = 0.147). The meta-analyses showed significant ergogenic effects of caffeine ingestion on maximal muscle strength of upper body and muscle power. Future studies should more rigorously control the effectiveness of blinding. Due to the paucity of evidence, additional findings are needed in the female population and using different forms of caffeine, such as gum and gel.

Plasma ET-1 Concentrations are Elevated in Patients with Hypertension - Meta-Analysis of Clinical Studies.

PubMed

Xu, Mei; Lu, Yong-Ping; Hasan, Ahmed Abdallah; Hocher, Berthold

2017-01-01

A recent study revealed that global overexpression of ET-1 causes a slight reduction in systemic blood pressure. Moreover, heterozygous ET-1 knockout mice are hypertensive. The role of ET-1 in human hypertension was so far not addressed by a strict meta-analysis of published human clinical studies. We included studies published between January 1, 1990 and February 28, 2017. We included case control studies analyzing untreated essential hypertension or hypertensive patients where antihypertensive medication was discontinued for at least two weeks. Based on the principle of Cochrane systematic reviews, case control studies (CCSs) in PubMed (Medline) and Google Scholar designed to identify the role of endothelin-1 (ET-1) in the pathophysiological of hypertension were screened. Review Manager Version 5.0 (Rev-Man 5.0) was applied for statistical analysis. Mean difference and 95% confidence interval (CI) were shown in inverse variance (IV) fixed-effects model or IV random-effects models. Eleven studies fulfilling our in- and exclusion criteria were eligible for this meta-analysis. These studies included 450 hypertensive patients and 328 controls. Our meta-analysis revealed that ET-1 plasma concentrations were higher in hypertensive patients as compared to the control patients [mean difference between groups 1.57 pg/mL, 95%CI [0.47∼2.68, P = 0.005]. These finding were driven by patients having systolic blood pressure higher than 160 mmHg and diastolic blood pressure higher than 100 mmHg. This meta-analysis showed that hypertensive patients do have elevated plasma ET-1 concentrations. This finding is driven by those patients with high systolic/diastolic blood pressure. Given that the ET-1 gene did not appear in any of the whole genome association studies searching for hypertension associated gene loci, it is very likely that the elevated plasma ET-1 concentrations in hypertensive patients are secondary to hypertension and may reflect endothelial cell damage. © 2017 The Author(s). Published by S. Karger AG, Basel.

Systematic Review and Cost Analysis Comparing Use of Chlorhexidine with Use of Iodine for Preoperative Skin Antisepsis to Prevent Surgical Site Infection

PubMed Central

Lee, Ingi; Agarwal, Rajender K.; Lee, Bruce Y.; Fishman, Neil O.; Umscheid, Craig A.

2013-01-01

Objective To compare use of chlorhexidine with use of iodine for preoperative skin antisepsis with respect to effectiveness in preventing surgical site infections (SSIs) and cost. Methods We searched the Agency for Healthcare Research and Quality website, the Cochrane Library, Medline, and EMBASE up to January 2010 for eligible studies. Included studies were systematic reviews, meta-analyses, or randomized controlled trials (RCTs) comparing preoperative skin antisepsis with chlorhexidine and with iodine and assessing for the outcomes of SSI or positive skin culture result after application. One reviewer extracted data and assessed individual study quality, quality of evidence for each outcome, and publication bias. Meta-analyses were performed using a fixed-effects model. Using results from the meta-analysis and cost data from the Hospital of the University of Pennsylvania, we developed a decision analytic cost-benefit model to compare the economic value, from the hospital perspective, of antisepsis with iodine versus antisepsis with 2 preparations of chlorhexidine (ie, 4% chlorhexidine bottle and single-use applicators of a 2% chlorhexidine gluconate [CHG] and 70% isopropyl alcohol [IPA] solution), and also performed sensitivity analyses. Results Nine RCTs with a total of 3,614 patients were included in the meta-analysis. Meta-analysis revealed that chlorhexidine antisepsis was associated with significantly fewer SSIs (adjusted risk ratio, 0.64 [95% confidence interval, [0.51–0.80]) and positive skin culture results (adjusted risk ratio, 0.44 [95% confidence interval, 0.35–0.56]) than was iodine antisepsis. In the cost-benefit model baseline scenario, switching from iodine to chlorhexidine resulted in a net cost savings of $16–$26 per surgical case and $349,904–$568,594 per year for the Hospital of the University of Pennsylvania. Sensitivity analyses showed that net cost savings persisted under most circumstances. Conclusions Preoperative skin antisepsis with chlorhexidine is more effective than preoperative skin antisepsis with iodine for preventing SSI and results in cost savings. PMID:20969449

Testing moderation in network meta-analysis with individual participant data.

PubMed

Dagne, Getachew A; Brown, C Hendricks; Howe, George; Kellam, Sheppard G; Liu, Lei

2016-07-10

Meta-analytic methods for combining data from multiple intervention trials are commonly used to estimate the effectiveness of an intervention. They can also be extended to study comparative effectiveness, testing which of several alternative interventions is expected to have the strongest effect. This often requires network meta-analysis (NMA), which combines trials involving direct comparison of two interventions within the same trial and indirect comparisons across trials. In this paper, we extend existing network methods for main effects to examining moderator effects, allowing for tests of whether intervention effects vary for different populations or when employed in different contexts. In addition, we study how the use of individual participant data may increase the sensitivity of NMA for detecting moderator effects, as compared with aggregate data NMA that employs study-level effect sizes in a meta-regression framework. A new NMA diagram is proposed. We also develop a generalized multilevel model for NMA that takes into account within-trial and between-trial heterogeneity and can include participant-level covariates. Within this framework, we present definitions of homogeneity and consistency across trials. A simulation study based on this model is used to assess effects on power to detect both main and moderator effects. Results show that power to detect moderation is substantially greater when applied to individual participant data as compared with study-level effects. We illustrate the use of this method by applying it to data from a classroom-based randomized study that involved two sub-trials, each comparing interventions that were contrasted with separate control groups. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Meta-analyses of the Association of Sleep Apnea with Insulin Resistance, and the Effects of CPAP on HOMA-IR, Adiponectin, and Visceral Adipose Fat

PubMed Central

Iftikhar, Imran H.; Hoyos, Camilla M.; Phillips, Craig L.; Magalang, Ulysses J.

2015-01-01

Objective: We sought to conduct an updated meta-analysis of randomized controlled trials (RCTs) on the effect of continuous positive airway pressure (CPAP) on insulin resistance, as measured by homeostasis model assessment of insulin resistance (HOMA-IR), visceral abdominal fat (VAF), and adiponectin. Additionally, we performed a separate meta-analysis and meta-regression of studies on the association of insulin resistance and obstructive sleep apnea (OSA). Methods: All included studies were searched from PubMed (from conception to March 15, 2014). Data were pooled across all included RCTs as the mean difference in HOMA-IR and VAF, and as the standardized mean difference in the case of adiponectin analysis. From the included case-control studies, data on the difference of HOMA-IR between cases and controls were pooled across all studies, as the standardized mean difference (SMD). Results: There was a significant difference in HOMA-IR (−0.43 [95% CIs: −0.75 to −0.11], p = 0.008) between CPAP treated and non CPAP treated participants. However, there was no significant difference in VAF or adiponectin; (−47.93 [95% CI: −112.58 to 16.72], p = 0.14) and (−0.06 [95% CI: −0.28 to 0.15], p = 0.56), respectively. Meta-analysis of 16 case-control studies showed a pooled SMD in HOMA-IR of 0.51 (95% CI: 0.28 to 0.75), p ≤ 0.001, between cases and controls. Conclusions: The results of our meta-analyses show that CPAP has a favorable effect on insulin resistance. This effect is not associated with any significant changes in total adiponectin levels or amount of VAF. Our findings also confirm a significant association between OSA and insulin resistance. Citation: Iftikhar IH, Hoyos CM, Phillips CL, Magalang UJ. Meta-analyses of the association of sleep apnea with insulin resistance, and the effects of CPAP on HOMA-IR, adiponectin, and visceral adipose fat. J Clin Sleep Med 2015;11(4):475–485. PMID:25700870

Effects of Teacher Professional Development on Gains in Student Achievement: How Meta Analysis Provides Scientific Evidence Useful to Education Leaders

ERIC Educational Resources Information Center

Blank, Rolf K.; de las Alas, Nina

2010-01-01

This meta analysis study focused on identifying and analyzing research studies that measured effects of teacher professional development with a content focus on math or science. This meta analysis was carried out to address two primary questions: (1) What are the effects of content-focused professional development for math and science teachers on…

Meta-analytic approaches to determine gender differences in the age-incidence characteristics of schizophrenia and related psychoses.

PubMed

Jackson, Dan; Kirkbride, James; Croudace, Tim; Morgan, Craig; Boydell, Jane; Errazuriz, Antonia; Murray, Robin M; Jones, Peter B

2013-03-01

A recent systematic review and meta-analysis of the incidence and prevalence of schizophrenia and other psychoses in England investigated the variation in the rates of psychotic disorders. However, some of the questions of interest, and the data collected to answer these, could not be adequately addressed using established meta-analysis techniques. We developed a novel statistical method, which makes combined use of fractional polynomials and meta-regression. This was used to quantify the evidence of gender differences and a secondary peak onset in women, where the outcome of interest is the incidence of schizophrenia. Statistically significant and epidemiologically important effects were obtained using our methods. Our analysis is based on data from four studies that provide 50 incidence rates, stratified by age and gender. We describe several variations of our method, in particular those that might be used where more data is available, and provide guidance for assessing the model fit. Copyright © 2013 John Wiley & Sons, Ltd.

Statistical Analysis of Individual Participant Data Meta-Analyses: A Comparison of Methods and Recommendations for Practice

PubMed Central

Stewart, Gavin B.; Altman, Douglas G.; Askie, Lisa M.; Duley, Lelia; Simmonds, Mark C.; Stewart, Lesley A.

2012-01-01

Background Individual participant data (IPD) meta-analyses that obtain “raw” data from studies rather than summary data typically adopt a “two-stage” approach to analysis whereby IPD within trials generate summary measures, which are combined using standard meta-analytical methods. Recently, a range of “one-stage” approaches which combine all individual participant data in a single meta-analysis have been suggested as providing a more powerful and flexible approach. However, they are more complex to implement and require statistical support. This study uses a dataset to compare “two-stage” and “one-stage” models of varying complexity, to ascertain whether results obtained from the approaches differ in a clinically meaningful way. Methods and Findings We included data from 24 randomised controlled trials, evaluating antiplatelet agents, for the prevention of pre-eclampsia in pregnancy. We performed two-stage and one-stage IPD meta-analyses to estimate overall treatment effect and to explore potential treatment interactions whereby particular types of women and their babies might benefit differentially from receiving antiplatelets. Two-stage and one-stage approaches gave similar results, showing a benefit of using anti-platelets (Relative risk 0.90, 95% CI 0.84 to 0.97). Neither approach suggested that any particular type of women benefited more or less from antiplatelets. There were no material differences in results between different types of one-stage model. Conclusions For these data, two-stage and one-stage approaches to analysis produce similar results. Although one-stage models offer a flexible environment for exploring model structure and are useful where across study patterns relating to types of participant, intervention and outcome mask similar relationships within trials, the additional insights provided by their usage may not outweigh the costs of statistical support for routine application in syntheses of randomised controlled trials. Researchers considering undertaking an IPD meta-analysis should not necessarily be deterred by a perceived need for sophisticated statistical methods when combining information from large randomised trials. PMID:23056232

Mindfulness meditation for insomnia: A meta-analysis of randomized controlled trials.

PubMed

Gong, Hong; Ni, Chen-Xu; Liu, Yun-Zi; Zhang, Yi; Su, Wen-Jun; Lian, Yong-Jie; Peng, Wei; Jiang, Chun-Lei

2016-10-01

Insomnia is a widespread and debilitating condition that affects sleep quality and daily productivity. Although mindfulness meditation (MM) has been suggested as a potentially effective supplement to medical treatment for insomnia, no comprehensively quantitative research has been conducted in this field. Therefore, we performed a meta-analysis on the findings of related randomized controlled trials (RCTs) to evaluate the effects of MM on insomnia. Related publications in PubMed, EMBASE, the Cochrane Library and PsycINFO were searched up to July 2015. To calculate the standardized mean differences (SMDs) and 95% confidence intervals (CIs), we used a fixed effect model when heterogeneity was negligible and a random effect model when heterogeneity was significant. A total of 330 participants in 6 RCTs that met the selection criteria were included in this meta-analysis. Analysis of overall effect revealed that MM significantly improved total wake time and sleep quality, but had no significant effects on sleep onset latency, total sleep time, wake after sleep onset, sleep efficiency, total wake time, ISI, PSQI and DBAS. Subgroup analyses showed that although there were no significant differences between MM and control groups in terms of total sleep time, significant effects were found in total wake time, sleep onset latency, sleep quality, sleep efficiency, and PSQI global score (absolute value of SMD range: 0.44-1.09, all p<0.05). The results suggest that MM may mildly improve some sleep parameters in patients with insomnia. MM can serve as an auxiliary treatment to medication for sleep complaints. Copyright © 2016 Elsevier Inc. All rights reserved.

Testing for Questionable Research Practices in a Meta-Analysis: An Example from Experimental Parapsychology.

PubMed

Bierman, Dick J; Spottiswoode, James P; Bijl, Aron

2016-01-01

We describe a method of quantifying the effect of Questionable Research Practices (QRPs) on the results of meta-analyses. As an example we simulated a meta-analysis of a controversial telepathy protocol to assess the extent to which these experimental results could be explained by QRPs. Our simulations used the same numbers of studies and trials as the original meta-analysis and the frequencies with which various QRPs were applied in the simulated experiments were based on surveys of experimental psychologists. Results of both the meta-analysis and simulations were characterized by 4 metrics, two describing the trial and mean experiment hit rates (HR) of around 31%, where 25% is expected by chance, one the correlation between sample-size and hit-rate, and one the complete P-value distribution of the database. A genetic algorithm optimized the parameters describing the QRPs, and the fitness of the simulated meta-analysis was defined as the sum of the squares of Z-scores for the 4 metrics. Assuming no anomalous effect a good fit to the empirical meta-analysis was found only by using QRPs with unrealistic parameter-values. Restricting the parameter space to ranges observed in studies of QRP occurrence, under the untested assumption that parapsychologists use comparable QRPs, the fit to the published Ganzfeld meta-analysis with no anomalous effect was poor. We allowed for a real anomalous effect, be it unidentified QRPs or a paranormal effect, where the HR ranged from 25% (chance) to 31%. With an anomalous HR of 27% the fitness became F = 1.8 (p = 0.47 where F = 0 is a perfect fit). We conclude that the very significant probability cited by the Ganzfeld meta-analysis is likely inflated by QRPs, though results are still significant (p = 0.003) with QRPs. Our study demonstrates that quantitative simulations of QRPs can assess their impact. Since meta-analyses in general might be polluted by QRPs, this method has wide applicability outside the domain of experimental parapsychology.

Aspirin as a potential modality for the chemoprevention of breast cancer: A dose-response meta-analysis of cohort studies from 857,831 participants

PubMed Central

Lu, Liming; Shi, Leiyu; Zeng, Jingchun; Wen, Zehuai

2017-01-01

Background Previous meta-analyses on the relationship between aspirin use and breast cancer risk have drawn inconsistent results. In addition, the threshold effect of different doses, frequencies and durations of aspirin use in preventing breast cancer have yet to be established. Results The search yielded 13 prospective cohort studies (N=857,831 participants) that reported an average of 7.6 cases/1,000 person-years of breast cancer during a follow-up period of from 4.4 to 14 years. With a random effects model, a borderline significant inverse association was observed between overall aspirin use and breast cancer risk, with a summarized RR = 0.94 (P = 0.051, 95% CI 0.87-1.01). The linear regression model was a better fit for the dose-response relationship, which displayed a potential relationship between the frequency of aspirin use and breast cancer risk (RR = 0.97, 0.95 and 0.90 for 5, 10 and 20 times/week aspirin use, respectively). It was also a better fit for the duration of aspirin use and breast cancer risk (RR = 0.86, 0.73 and 0.54 for 5, 10 and 20 years of aspirin use). Methods We searched MEDLINE, EMBASE and CENTRAL databases through early October 2016 for relevant prospective cohort studies of aspirin use and breast cancer risk. Meta-analysis of relative risks (RR) estimates associated with aspirin intake were presented by fixed or random effects models. The dose-response meta-analysis was performed by linear trend regression and restricted cubic spline regression. Conclusion Our study confirmed a dose-response relationship between aspirin use and breast cancer risk. For clinical prevention, long term (>5 years) consistent use (2-7 times/week) of aspirin appears to be more effective in achieving a protective effect against breast cancer. PMID:28418881

Aspirin as a potential modality for the chemoprevention of breast cancer: A dose-response meta-analysis of cohort studies from 857,831 participants.

PubMed

Lu, Liming; Shi, Leiyu; Zeng, Jingchun; Wen, Zehuai

2017-06-20

Previous meta-analyses on the relationship between aspirin use and breast cancer risk have drawn inconsistent results. In addition, the threshold effect of different doses, frequencies and durations of aspirin use in preventing breast cancer have yet to be established. The search yielded 13 prospective cohort studies (N=857,831 participants) that reported an average of 7.6 cases/1,000 person-years of breast cancer during a follow-up period of from 4.4 to 14 years. With a random effects model, a borderline significant inverse association was observed between overall aspirin use and breast cancer risk, with a summarized RR = 0.94 (P = 0.051, 95% CI 0.87-1.01). The linear regression model was a better fit for the dose-response relationship, which displayed a potential relationship between the frequency of aspirin use and breast cancer risk (RR = 0.97, 0.95 and 0.90 for 5, 10 and 20 times/week aspirin use, respectively). It was also a better fit for the duration of aspirin use and breast cancer risk (RR = 0.86, 0.73 and 0.54 for 5, 10 and 20 years of aspirin use). We searched MEDLINE, EMBASE and CENTRAL databases through early October 2016 for relevant prospective cohort studies of aspirin use and breast cancer risk. Meta-analysis of relative risks (RR) estimates associated with aspirin intake were presented by fixed or random effects models. The dose-response meta-analysis was performed by linear trend regression and restricted cubic spline regression. Our study confirmed a dose-response relationship between aspirin use and breast cancer risk. For clinical prevention, long term (>5 years) consistent use (2-7 times/week) of aspirin appears to be more effective in achieving a protective effect against breast cancer.

The Energy Content and Composition of Meals Consumed after an Overnight Fast and Their Effects on Diet Induced Thermogenesis: A Systematic Review, Meta-Analyses and Meta-Regressions

PubMed Central

Quatela, Angelica; Callister, Robin; Patterson, Amanda; MacDonald-Wicks, Lesley

2016-01-01

This systematic review investigated the effects of differing energy intakes, macronutrient compositions, and eating patterns of meals consumed after an overnight fast on Diet Induced Thermogenesis (DIT). The initial search identified 2482 records; 26 papers remained once duplicates were removed and inclusion criteria were applied. Studies (n = 27) in the analyses were randomized crossover designs comparing the effects of two or more eating events on DIT. Higher energy intake increased DIT; in a mixed model meta-regression, for every 100 kJ increase in energy intake, DIT increased by 1.1 kJ/h (p < 0.001). Meals with a high protein or carbohydrate content had a higher DIT than high fat, although this effect was not always significant. Meals with medium chain triglycerides had a significantly higher DIT than long chain triglycerides (meta-analysis, p = 0.002). Consuming the same meal as a single bolus eating event compared to multiple small meals or snacks was associated with a significantly higher DIT (meta-analysis, p = 0.02). Unclear or inconsistent findings were found by comparing the consumption of meals quickly or slowly, and palatability was not significantly associated with DIT. These findings indicate that the magnitude of the increase in DIT is influenced by the energy intake, macronutrient composition, and eating pattern of the meal. PMID:27792142

Model-Driven Approach for Body Area Network Application Development.

PubMed

Venčkauskas, Algimantas; Štuikys, Vytautas; Jusas, Nerijus; Burbaitė, Renata

2016-05-12

This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN) applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level) and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS)). We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD) variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD)) and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor) is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application.

Model-Driven Approach for Body Area Network Application Development

PubMed Central

Venčkauskas, Algimantas; Štuikys, Vytautas; Jusas, Nerijus; Burbaitė, Renata

2016-01-01

This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN) applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level) and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS)). We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD) variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD)) and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor) is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application. PMID:27187394

The Effectiveness of Different Interventions to Promote Poison Prevention Behaviours in Households with Children: A Network Meta-Analysis

PubMed Central

Achana, Felix A.; Sutton, Alex J.; Kendrick, Denise; Wynn, Persephone; Young, Ben; Jones, David R.; Hubbard, Stephanie J.; Cooper, Nicola J.

2015-01-01

Background There is evidence from 2 previous meta-analyses that interventions to promote poison prevention behaviours are effective in increasing a range of poison prevention practices in households with children. The published meta-analyses compared any intervention against a “usual care or no intervention” which potentially limits the usefulness of the analysis to decision makers. We aim to use network meta-analysis to simultaneously evaluate the effectiveness of different interventions to increase prevalence of safe storage of i) Medicines only, ii) Other household products only, iii) Poisons (both medicines and non-medicines), iv) Poisonous plants; and v) Possession of poison control centre (PCC) telephone number in households with children. Methods Data on the effectiveness of poison prevention interventions was extracted from primary studies identified in 2 newly-undertaken systematic reviews. Effect estimates were pooled across studies using a random effects network meta-analysis model. Results 28 of the 47 primary studies identified were included in the analysis. Compared to usual care intervention, the intervention with education and low cost/free equipment elements was most effective in promoting safe storage of medicines (odds ratio 2.51, 95% credible interval 1.01 to 6.00) while interventions with education, low cost/free equipment, home safety inspection and fitting components were most effective in promoting safe storage of other household products (2.52, 1.12 to 7.13), safe storage of poisons (11.10, 1.60 to 141.50) and possession of PCC number (38.82, 2.19 to 687.10). No one intervention package was more effective than the others in promoting safe storage of poisonous plants. Conclusion The most effective interventions varied by poison prevention practice, but education alone was not the most effective intervention for any poison prevention practice. Commissioners and providers of poison prevention interventions should tailor the interventions they commission or provide to the poison prevention practices they wish to promote. Highlights Network meta-analysis is useful for comparing multiple injury-prevention interventions. More intensive poison prevention interventions were more effective than education alone. Education and low cost/free equipment was most effective in promoting safe storage of medicines. Education, low cost/free equipment, home safety inspection and fitting was most effective in promoting safe storage of household products and poisons. Education, low cost/free equipment and home inspection were most effective in promoting possession of a poison control centre number. None of the intervention packages was more effective than the others in promoting safe storage of poisonous plants. PMID:25894385

The effectiveness of different interventions to promote poison prevention behaviours in households with children: a network meta-analysis.

PubMed

Achana, Felix A; Sutton, Alex J; Kendrick, Denise; Wynn, Persephone; Young, Ben; Jones, David R; Hubbard, Stephanie J; Cooper, Nicola J

2015-01-01

There is evidence from 2 previous meta-analyses that interventions to promote poison prevention behaviours are effective in increasing a range of poison prevention practices in households with children. The published meta-analyses compared any intervention against a "usual care or no intervention" which potentially limits the usefulness of the analysis to decision makers. We aim to use network meta-analysis to simultaneously evaluate the effectiveness of different interventions to increase prevalence of safe storage of i) Medicines only, ii) Other household products only, iii) Poisons (both medicines and non-medicines), iv) Poisonous plants; and v) Possession of poison control centre (PCC) telephone number in households with children. Data on the effectiveness of poison prevention interventions was extracted from primary studies identified in 2 newly-undertaken systematic reviews. Effect estimates were pooled across studies using a random effects network meta-analysis model. 28 of the 47 primary studies identified were included in the analysis. Compared to usual care intervention, the intervention with education and low cost/free equipment elements was most effective in promoting safe storage of medicines (odds ratio 2.51, 95% credible interval 1.01 to 6.00) while interventions with education, low cost/free equipment, home safety inspection and fitting components were most effective in promoting safe storage of other household products (2.52, 1.12 to 7.13), safe storage of poisons (11.10, 1.60 to 141.50) and possession of PCC number (38.82, 2.19 to 687.10). No one intervention package was more effective than the others in promoting safe storage of poisonous plants. The most effective interventions varied by poison prevention practice, but education alone was not the most effective intervention for any poison prevention practice. Commissioners and providers of poison prevention interventions should tailor the interventions they commission or provide to the poison prevention practices they wish to promote. Network meta-analysis is useful for comparing multiple injury-prevention interventions. More intensive poison prevention interventions were more effective than education alone. Education and low cost/free equipment was most effective in promoting safe storage of medicines. Education, low cost/free equipment, home safety inspection and fitting was most effective in promoting safe storage of household products and poisons. Education, low cost/free equipment and home inspection were most effective in promoting possession of a poison control centre number. None of the intervention packages was more effective than the others in promoting safe storage of poisonous plants.

Mega-Analysis of School Psychology Blueprint for Training and Practice Domains

ERIC Educational Resources Information Center

Burns, Matthew K.; Kanive, Rebecca; Zaslofsky, Anne F.; Parker, David C.

2013-01-01

Meta-analytic research is an effective method for synthesizing existing research and for informing practice and policy. Hattie (2009) suggested that meta-analytic procedures could be employed to existing meta-analyses to create a mega-analysis. The current mega-analysis examined a sample of 47 meta-analyses according to the "School…

Meta-analysis and psychophysiology: A tutorial using depression and action-monitoring event-related potentials.

PubMed

Moran, Tim P; Schroder, Hans S; Kneip, Chelsea; Moser, Jason S

2017-01-01

Meta-analyses are regularly used to quantitatively integrate the findings of a field, assess the consistency of an effect and make decisions based on extant research. The current article presents an overview and step-by-step tutorial of meta-analysis aimed at psychophysiological researchers. We also describe best-practices and steps that researchers can take to facilitate future meta-analysis in their sub-discipline. Lastly, we illustrate each of the steps by presenting a novel meta-analysis on the relationship between depression and action-monitoring event-related potentials - the error-related negativity (ERN) and the feedback negativity (FN). This meta-analysis found that the literature on depression and the ERN is contaminated by publication bias. With respect to the FN, the meta-analysis found that depression does predict the magnitude of the FN; however, this effect was dependent on the type of task used by the study. Copyright © 2016 Elsevier B.V. All rights reserved.

A Network Meta-Analysis Comparing Effects of Various Antidepressant Classes on the Digit Symbol Substitution Test (DSST) as a Measure of Cognitive Dysfunction in Patients with Major Depressive Disorder.

PubMed

Baune, Bernhard T; Brignone, Mélanie; Larsen, Klaus Groes

2018-02-01

Major depressive disorder is a common condition that often includes cognitive dysfunction. A systematic literature review of studies and a network meta-analysis were carried out to assess the relative effect of antidepressants on cognitive dysfunction in major depressive disorder. MEDLINE, Embase, Cochrane, CDSR, and PsychINFO databases; clinical trial registries; and relevant conference abstracts were searched for randomized controlled trials assessing the effects of antidepressants/placebo on cognition. A network meta-analysis comparing antidepressants was conducted using a random effects model. The database search retrieved 11337 citations, of which 72 randomized controlled trials from 103 publications met the inclusion criteria. The review identified 86 cognitive tests assessing the effect of antidepressants on cognitive functioning. However, the Digit Symbol Substitution Test, which targets multiple domains of cognition and is recognized as being sensitive to change, was the only test that was used across 12 of the included randomized controlled trials and that allowed the construction of a stable network suitable for the network meta-analysis. The interventions assessed included selective serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors, and other non-selective serotonin reuptake inhibitors/serotonin-norepinephrine reuptake inhibitors. The network meta-analysis using the Digit Symbol Substitution Test showed that vortioxetine was the only antidepressant that improved cognitive dysfunction on the Digit Symbol Substitution Test vs placebo {standardized mean difference: 0.325 (95% CI = 0.120; 0.529, P=.009}. Compared with other antidepressants, vortioxetine was statistically more efficacious on the Digit Symbol Substitution Test vs escitalopram, nortriptyline, and the selective serotonin reuptake inhibitor and tricyclic antidepressant classes. This study highlighted the large variability in measures used to assess cognitive functioning. The findings on the Digit Symbol Substitution Test indicate differential effects of various antidepressants on improving cognitive function in patients with major depressive disorder. © The Author 2017. Published by Oxford University Press on behalf of CINP.

Meta-analysis of high-latitude nitrogen-addition and warming studies implies ecological mechanisms overlooked by land models

DOE PAGES

Bouskill, N. J.; Riley, W. J.; Tang, J. Y.

2014-12-11

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the climate. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the aboveground and belowground responses to warming and nitrogen addition in high-latitude ecosystems, and identified absent or poorly parameterized mechanisms in CLM4.5. While the two model versions predicted similar soil carbon stock trajectories following both warming and nitrogen addition, other predicted variables (e.g., belowgroundmore » respiration) differed from observations in both magnitude and direction, indicating that CLM4.5 has inadequate underlying mechanisms for representing high-latitude ecosystems. On the basis of observational synthesis, we attribute the model–observation differences to missing representations of microbial dynamics, aboveground and belowground coupling, and nutrient cycling, and we use the observational meta-analysis to discuss potential approaches to improving the current models. However, we also urge caution concerning the selection of data sets and experiments for meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average = 72 kg ha -1 yr -1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which precludes a rigorous evaluation of the model responses to likely nitrogen perturbations. Overall, we demonstrate that elucidating ecological mechanisms via meta-analysis can identify deficiencies in ecosystem models and empirical experiments.« less

Effectiveness of massage therapy for shoulder pain: a systematic review and meta-analysis.

PubMed

Yeun, Young-Ran

2017-05-01

[Purpose] This study performed an effect-size analysis of massage therapy for shoulder pain. [Subjects and Methods] The database search was conducted using PubMed, CINAHL, Embase, PsycINFO, RISS, NDSL, NANET, DBpia, and KoreaMed. The meta-analysis was based on 15 studies, covering a total of 635 participants, and used a random effects model. [Results] The effect size estimate showed that massage therapy had a significant effect on reducing shoulder pain for short-term efficacy (SMD: -1.08, 95% CI: -1.51 to -0.65) and for long-term efficacy (SMD: -0.47, 95% CI: -0.71 to -0.23). [Conclusion] The findings from this review suggest that massage therapy is effective at improving shoulder pain. However, further research is needed, especially a randomized controlled trial design or a large sample size, to provide evidence-based recommendations.

Occupational exposure to hexavalent chromium and cancers of the gastrointestinal tract: a meta-analysis.

PubMed

Gatto, Nicole M; Kelsh, Michael A; Mai, Diem Ha; Suh, Mina; Proctor, Deborah M

2010-08-01

We conducted a systematic literature review and meta-analysis of oral cavity, esophageal, stomach, small intestine, colon, and rectal cancers among workers occupationally exposed to Cr(VI). Using PubMed, studies published from 1950 to 2009 evaluating the relationship between Cr(VI) exposure and GI cancers were identified. Measures of effect and variability were extracted from 32 studies meeting specific inclusion criteria, and meta-analysis summary relative risk measures were calculated using random effects models and inverse variance weighting methods. Meta-standardized mortality ratios (SMRs) were, for cancer of the: oral cavity [1.02 (95% CI=0.77-1.34)]; esophagus [1.17 (95% CI=0.90-1.51)]; stomach [1.09 (95% CI=0.93-1.28)]; colon [0.89 (95% CI=0.70-1.12)]; and rectum [1.17 (95% CI=0.98-1.39)]. Analyses of more highly exposed subgroups included in the studies or subgroups based on geographic region or by industry with recognized Cr(VI) exposures (welding, chrome plating, chromate production, and pigment production) did not result in elevated meta-SMRs except for esophageal cancer among US cohorts [meta-SMR=1.49 (95% CI=1.06-2.09)]. However, that finding was based on a subgroup of only four studies, one of which was a PMR study. Potential confounding by socioeconomic status (SES), diet and/or smoking, or limitations due to the healthy-worker effect (HWE) were evaluated, and while smoking, diet and SES may be important factors that may have upwardly biased the meta-SMRs, HWE is not likely to have significantly affected the summary results. None of three studies reporting small intestine cancers observed a statistically significant increased risk. These meta-analyses and literature review indicate that Cr(VI)-exposed workers are not at a greater risk of GI cancers than the general population.

A Systematic Review and Meta-Analysis of Predictors of Expressive-Language Outcomes Among Late Talkers.

PubMed

Fisher, Evelyn L

2017-10-17

The purpose of this study was to explore the literature on predictors of outcomes among late talkers using systematic review and meta-analysis methods. We sought to answer the question: What factors predict preschool-age expressive-language outcomes among late-talking toddlers? We entered carefully selected search terms into the following electronic databases: Communication & Mass Media Complete, ERIC, Medline, PsycEXTRA, Psychological and Behavioral Sciences, and PsycINFO. We conducted a separate, random-effects model meta-analysis for each individual predictor that was used in a minimum of 5 studies. We also tested potential moderators of the relationship between predictors and outcomes using metaregression and subgroup analysis. Last, we conducted publication-bias and sensitivity analyses. We identified 20 samples, comprising 2,134 children, in a systematic review. According to the results of the meta-analyses, significant predictors of expressive-language outcomes included toddlerhood expressive-vocabulary size, receptive language, and socioeconomic status. Nonsignificant predictors included phrase speech, gender, and family history. To our knowledge this is the first synthesis of the literature on predictors of outcomes among late talkers using meta-analysis. Our findings clarify the contributions of several constructs to outcomes and highlight the importance of early receptive language to expressive-language development. https://doi.org/10.23641/asha.5313454.

Coffee Consumption and Risk of Biliary Tract Cancers and Liver Cancer: A Dose-Response Meta-Analysis of Prospective Cohort Studies.

PubMed

Godos, Justyna; Micek, Agnieszka; Marranzano, Marina; Salomone, Federico; Rio, Daniele Del; Ray, Sumantra

2017-08-28

A meta-analysis was conducted to summarize the evidence from prospective cohort and case-control studies regarding the association between coffee intake and biliary tract cancer (BTC) and liver cancer risk. Eligible studies were identified by searches of PubMed and EMBASE databases from the earliest available online indexing year to March 2017. The dose-response relationship was assessed by a restricted cubic spline model and multivariate random-effect meta-regression. A stratified and subgroup analysis by smoking status and hepatitis was performed to identify potential confounding factors. We identified five studies on BTC risk and 13 on liver cancer risk eligible for meta-analysis. A linear dose-response meta-analysis did not show a significant association between coffee consumption and BTC risk. However, there was evidence of inverse correlation between coffee consumption and liver cancer risk. The association was consistent throughout the various potential confounding factors explored including smoking status, hepatitis, etc. Increasing coffee consumption by one cup per day was associated with a 15% reduction in liver cancer risk (RR 0.85; 95% CI 0.82 to 0.88). The findings suggest that increased coffee consumption is associated with decreased risk of liver cancer, but not BTC.

Coffee Consumption and Risk of Biliary Tract Cancers and Liver Cancer: A Dose–Response Meta-Analysis of Prospective Cohort Studies

PubMed Central

Micek, Agnieszka; Marranzano, Marina; Ray, Sumantra

2017-01-01

Background: A meta-analysis was conducted to summarize the evidence from prospective cohort and case-control studies regarding the association between coffee intake and biliary tract cancer (BTC) and liver cancer risk. Methods: Eligible studies were identified by searches of PubMed and EMBASE databases from the earliest available online indexing year to March 2017. The dose–response relationship was assessed by a restricted cubic spline model and multivariate random-effect meta-regression. A stratified and subgroup analysis by smoking status and hepatitis was performed to identify potential confounding factors. Results: We identified five studies on BTC risk and 13 on liver cancer risk eligible for meta-analysis. A linear dose–response meta-analysis did not show a significant association between coffee consumption and BTC risk. However, there was evidence of inverse correlation between coffee consumption and liver cancer risk. The association was consistent throughout the various potential confounding factors explored including smoking status, hepatitis, etc. Increasing coffee consumption by one cup per day was associated with a 15% reduction in liver cancer risk (RR 0.85; 95% CI 0.82 to 0.88). Conclusions: The findings suggest that increased coffee consumption is associated with decreased risk of liver cancer, but not BTC. PMID:28846640

The transcription factor p53: Not a repressor, solely an activator

PubMed Central

Fischer, Martin; Steiner, Lydia; Engeland, Kurt

2014-01-01

The predominant function of the tumor suppressor p53 is transcriptional regulation. It is generally accepted that p53-dependent transcriptional activation occurs by binding to a specific recognition site in promoters of target genes. Additionally, several models for p53-dependent transcriptional repression have been postulated. Here, we evaluate these models based on a computational meta-analysis of genome-wide data. Surprisingly, several major models of p53-dependent gene regulation are implausible. Meta-analysis of large-scale data is unable to confirm reports on directly repressed p53 target genes and falsifies models of direct repression. This notion is supported by experimental re-analysis of representative genes reported as directly repressed by p53. Therefore, p53 is not a direct repressor of transcription, but solely activates its target genes. Moreover, models based on interference of p53 with activating transcription factors as well as models based on the function of ncRNAs are also not supported by the meta-analysis. As an alternative to models of direct repression, the meta-analysis leads to the conclusion that p53 represses transcription indirectly by activation of the p53-p21-DREAM/RB pathway. PMID:25486564

A meta-analysis of the association of serum ischaemia-modified albumin levels with human hypothyroidism and hyperthyroidism.

PubMed

Reddy, Varikasuvu Seshadri; Bukke, Suman; Mahato, Khageshwar; Kumar, Vinod; Reddy, Netala Vasudeva; Munikumar, Manne; Vodelu, Bramahanapally

2017-02-28

Serum levels of ischaemia-modified albumin (IMA) have been studied as a novel and simple measure of oxidative stress (OXS) in different thyroid pathologies. However, results of available studies in the literature were not consistent. This meta-analysis was attempted to quantify the overall effect size for serum IMA levels in human hypothyroidism (HT) and hyperthyroidism (HYT) and to study its associations with the thyroid profile. Databases of PubMed/Medline, EMBASE, Google Scholar, Web of Science and Science Direct were searched for articles. Data on serum IMA levels in HT, HYT patients and euthyroid controls were extracted to compute standardized mean differences (SMD) by the random-effects model. The associations between IMA and thyroid profile were computed by the meta-analysis of correlation coefficients. IMA levels in HT patients (SMD=1.12; Z=2.76; P=0.006) and HYT patients (SMD=1.64; Z=2.57; P=0.01) were significantly higher than in euthyroid controls and the thyroid treatment showed a favourble effect on serum IMA levels. There were strong and significant correlations between IMA and hormonal status in HT and HYT groups. This meta-analysis showing increased IMA level in both HT and HYT patients and its association with thyroid profile suggests that serum IMA could be used as a simple measure of increased OXS in thyroid dysfunction. © 2017 The Author(s).

Estimating the price elasticity of beer: meta-analysis of data with heterogeneity, dependence, and publication bias.

PubMed

Nelson, Jon P

2014-01-01

Precise estimates of price elasticities are important for alcohol tax policy. Using meta-analysis, this paper corrects average beer elasticities for heterogeneity, dependence, and publication selection bias. A sample of 191 estimates is obtained from 114 primary studies. Simple and weighted means are reported. Dependence is addressed by restricting number of estimates per study, author-restricted samples, and author-specific variables. Publication bias is addressed using funnel graph, trim-and-fill, and Egger's intercept model. Heterogeneity and selection bias are examined jointly in meta-regressions containing moderator variables for econometric methodology, primary data, and precision of estimates. Results for fixed- and random-effects regressions are reported. Country-specific effects and sample time periods are unimportant, but several methodology variables help explain the dispersion of estimates. In models that correct for selection bias and heterogeneity, the average beer price elasticity is about -0.20, which is less elastic by 50% compared to values commonly used in alcohol tax policy simulations. Copyright © 2013 Elsevier B.V. All rights reserved.

Cost-Effectiveness of Four Educational Interventions.

ERIC Educational Resources Information Center

Levin, Henry M.; And Others

This study employs meta-analysis and cost-effectiveness instruments to evaluate and compare cross-age tutoring, computer assistance, class size reductions, and instructional time increases for their utility in improving elementary school reading and math scores. Using intervention effect studies as replication models, researchers first estimate…

Dealing with feeling: a meta-analysis of the effectiveness of strategies derived from the process model of emotion regulation.

PubMed

Webb, Thomas L; Miles, Eleanor; Sheeran, Paschal

2012-07-01

The present meta-analysis investigated the effectiveness of strategies derived from the process model of emotion regulation in modifying emotional outcomes as indexed by experiential, behavioral, and physiological measures. A systematic search of the literature identified 306 experimental comparisons of different emotion regulation (ER) strategies. ER instructions were coded according to a new taxonomy, and meta-analysis was used to evaluate the effectiveness of each strategy across studies. The findings revealed differences in effectiveness between ER processes: Attentional deployment had no effect on emotional outcomes (d(+) = 0.00), response modulation had a small effect (d(+) = 0.16), and cognitive change had a small-to-medium effect (d(+) = 0.36). There were also important within-process differences. We identified 7 types of attentional deployment, 4 types of cognitive change, and 4 types of response modulation, and these distinctions had a substantial influence on effectiveness. Whereas distraction was an effective way to regulate emotions (d(+) = 0.27), concentration was not (d(+) = -0.26). Similarly, suppressing the expression of emotion proved effective (d(+) = 0.32), but suppressing the experience of emotion or suppressing thoughts of the emotion-eliciting event did not (d(+) = -0.04 and -0.12, respectively). Finally, reappraising the emotional response proved less effective (d(+) = 0.23) than reappraising the emotional stimulus (d(+) = 0.36) or using perspective taking (d(+) = 0.45). The review also identified several moderators of strategy effectiveness including factors related to the (a) to-be-regulated emotion, (b) frequency of use and intended purpose of the ER strategy, (c) study design, and (d) study characteristics.

Multidimensional Perfectionism and Burnout: A Meta-Analysis.

PubMed

Hill, Andrew P; Curran, Thomas

2016-08-01

A meta-analysis of research examining the relationships between multidimensional perfectionism and burnout is provided. In doing so, relationships before and after controlling for the relationship between dimensions of perfectionism were examined along with whether relationships were moderated by domain (work, sport, or education). A literature search yielded 43 studies (N = 9,838) and 663 effect sizes. Meta-analysis using random-effects models revealed that perfectionistic strivings had small negative or non-significant relationships with overall burnout and symptoms of burnout. By contrast, perfectionistic concerns displayed medium-to-large and medium positive relationships with overall burnout and symptoms of burnout. After controlling for the relationship between dimensions of perfectionism, "pure" perfectionistic strivings displayed notably larger negative relationships. In terms of moderation, in some cases, perfectionistic strivings were less adaptive and perfectionistic concerns more maladaptive in the work domain. Future research should examine explanatory mechanisms, adopt longitudinal designs, and develop interventions to reduce perfectionistic concerns fueled burnout. © 2015 by the Society for Personality and Social Psychology, Inc.

Does albendazole affect seizure remission and computed tomography response in children with neurocysticercosis? A Systematic review and meta-analysis.

PubMed

Mazumdar, Maitreyi; Pandharipande, Pari; Poduri, Annapurna

2007-02-01

A recent trial suggested that albendazole reduces seizures in adults with neurocysticercosis. There is still no consensus regarding optimal management of neurocysticercosis in children. The authors conducted a systematic review and meta-analysis to assess the efficacy of albendazole in children with neurocysticercosis, by searching the Cochrane Databases, MEDLINE, EMBASE, and LILACS. Three reviewers extracted data using an intent-to-treat analysis. Random effects models were used to estimate relative risks. Four randomized trials were selected for meta-analysis, and 10 observational studies were selected for qualitative review. The relative risk of seizure remission in treatment versus control was 1.26 (1.09, 1.46). The relative risk of improvement in computed tomography in these trials was 1.15 (0.97, 1.36). Review of observational studies showed conflicting results, likely owing to preferential administration of albendazole to sicker children.

Accuracy of magnetic resonance venography in diagnosing cerebral venous sinus thrombosis.

PubMed

Gao, Liansheng; Xu, Weilin; Li, Tao; Yu, Xiaobo; Cao, Shenglong; Xu, Hangzhe; Yan, Feng; Chen, Gao

2018-05-17

The non-specific clinical manifestations and lack of effective diagnostic techniques have made cerebral venous sinus thrombosis (CVST) difficult to recognize and easy to misdiagnose. Several studies have suggested that different types of magnetic resonance venography (MRV) have advantages in diagnosing CVST. We conducted this meta-analysis to assess the accuracy of MRV in identifying CVST. We searched the Embase, PubMed, and Chinese Biomedical (CBM) databases comprehensively to retrieve eligible articles up to Mar 31, 2018. The methodological quality of each article was evaluated individually. The summary diagnostic accuracy of MRV for CVST was obtained from pooled analysis with random-effects models. Sensitivity analysis, subgroup analysis, and meta-regression were used to explore the sources of heterogeneity. A trim and fill analysis was conducted to correct the funnel plot asymmetry. The meta-analysis synthesized 12 articles containing 27 cohorts with a total of 1933 cases. The pooled sensitivity and specificity were 0.86 (95% CI: 0.83, 0.89) and 0.94 (95% CI: 0.93, 0.95), respectively. The pooled diagnostic odds ratio (DOR) was 75.24 (95% CI: 38.33, 147.72). The area under the curve (AUC) was 0.9472 (95% CI: 0.9229, 0.9715). Subgroup analysis and meta-regression analysis revealed the technical types of MRV and the methods of counting cases contributing to the heterogeneity. The trim and fill method confirmed that publication bias has little effect on our results. MRV has excellent diagnostic performance and is accurate in confirming CVST. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative effect and safety of verapamil in keloid and hypertrophic scar treatment: a meta-analysis.

PubMed

Li, Zhouna; Jin, Zhehu

2016-01-01

Keloids and hypertrophic scars are the most common types of pathological scarring. Traditionally, keloids have been considered as a result of aberrant wound healing, involving excessive fibroblast participation that is characterized by hyalinized collagen bundles. However, the usefulness of this characterization has been questioned. In recent years, studies have reported the appropriate use of verapamil for keloids and hypertrophic scars. Searches were conducted on the databases Medline, Embase, Cochrane, PubMed, and China National Knowledge Infrastructure from 2006 to July 2016. State12.0 was used for literature review, data extraction, and meta-analysis. Treatment groups were divided into verapamil and nonverapamil group. Nonverapamil group includes steroids and intense pulsed light (IPL) therapy. Total effective rates include cure rate and effective rate. Cure: skin lesions were completely flattened, became soft and symptoms disappeared. Efficacy: skin lesions subsided, patient significantly reduced symptoms. Inefficient definition of skin was progression free or became worse. Random-effects model was used for the meta-analysis. Six studies that included 331 patients with keloids and hypertrophic scars were analyzed. Analysis of the total effective rate of skin healing was performed. The total effective rates in the two groups were 54.07% (verapamil) and 53.18% (nonverapamil), respectively. The meta-analysis showed that there was no difference between the two groups. We also compared the adverse reactions between the verapamil treatment group and the steroids treatment group in two studies, and the result indicated that the verapamil group showed less adverse reactions. There were no differences between the application of verapamil and nonverapamil group in keloids and hypertrophic scars treatment. Verapamil could act as an effective alternative modality in the prevention and treatment of keloid and hypertrophic scars. A larger number of studies are required to confirm our conclusion.

Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis123

PubMed Central

Pan, An; Willett, Walter C; Hu, Frank B

2013-01-01

Background: The relation between sugar-sweetened beverages (SSBs) and body weight remains controversial. Objective: We conducted a systematic review and meta-analysis to summarize the evidence in children and adults. Design: We searched PubMed, EMBASE, and Cochrane databases through March 2013 for prospective cohort studies and randomized controlled trials (RCTs) that evaluated the SSB-weight relation. Separate meta-analyses were conducted in children and adults and for cohorts and RCTs by using random- and fixed-effects models. Results: Thirty-two original articles were included in our meta-analyses: 20 in children (15 cohort studies, n = 25,745; 5 trials, n = 2772) and 12 in adults (7 cohort studies, n = 174,252; 5 trials, n = 292). In cohort studies, one daily serving increment of SSBs was associated with a 0.06 (95% CI: 0.02, 0.10) and 0.05 (95% CI: 0.03, 0.07)-unit increase in BMI in children and 0.22 kg (95% CI: 0.09, 0.34 kg) and 0.12 kg (95% CI: 0.10, 0.14 kg) weight gain in adults over 1 y in random- and fixed-effects models, respectively. RCTs in children showed reductions in BMI gain when SSBs were reduced [random and fixed effects: −0.17 (95% CI: −0.39, 0.05) and −0.12 (95% CI: −0.22, −0.2)], whereas RCTs in adults showed increases in body weight when SSBs were added (random and fixed effects: 0.85 kg; 95% CI: 0.50, 1.20 kg). Sensitivity analyses of RCTs in children showed more pronounced benefits in preventing weight gain in SSB substitution trials (compared with school-based educational programs) and among overweight children (compared with normal-weight children). Conclusion: Our systematic review and meta-analysis of prospective cohort studies and RCTs provides evidence that SSB consumption promotes weight gain in children and adults. PMID:23966427

Systematic Review and Meta-Analysis: Dose-Response Relationship of Selective Serotonin Reuptake Inhibitors in Major Depressive Disorder.

PubMed

Jakubovski, Ewgeni; Varigonda, Anjali L; Freemantle, Nicholas; Taylor, Matthew J; Bloch, Michael H

2016-02-01

Previous studies suggested that the treatment response to selective serotonin reuptake inhibitors (SSRIs) in major depressive disorder follows a flat response curve within the therapeutic dose range. The present study was designed to clarify the relationship between dosage and treatment response in major depressive disorder. The authors searched PubMed for randomized placebo-controlled trials examining the efficacy of SSRIs for treating adults with major depressive disorder. Trials were also required to assess improvement in depression severity at multiple time points. Additional data were collected on treatment response and all-cause and side effect-related discontinuation. All medication doses were transformed into imipramine-equivalent doses. The longitudinal data were analyzed with a mixed-regression model. Endpoint and tolerability analyses were analyzed using meta-regression and stratified subgroup analysis by predefined SSRI dose categories in order to assess the effect of SSRI dosing on the efficacy and tolerability of SSRIs for major depressive disorder. Forty studies involving 10,039 participants were included. Longitudinal modeling (dose-by-time interaction=0.0007, 95% CI=0.0001-0.0013) and endpoint analysis (meta-regression: β=0.00053, 95% CI=0.00018-0.00088, z=2.98) demonstrated a small but statistically significant positive association between SSRI dose and efficacy. Higher doses of SSRIs were associated with an increased likelihood of dropouts due to side effects (meta-regression: β=0.00207, 95% CI=0.00071-0.00342, z=2.98) and decreased likelihood of all-cause dropout (meta-regression: β=-0.00093, 95% CI=-0.00165 to -0.00021, z=-2.54). Higher doses of SSRIs appear slightly more effective in major depressive disorder. This benefit appears to plateau at around 250 mg of imipramine equivalents (50 mg of fluoxetine). The slightly increased benefits of SSRIs at higher doses are somewhat offset by decreased tolerability at high doses.

Efficacy of Virtual Patients in Medical Education: A Meta-Analysis of Randomized Studies

ERIC Educational Resources Information Center

Consorti, Fabrizio; Mancuso, Rosaria; Nocioni, Martina; Piccolo, Annalisa

2012-01-01

A meta-analysis was performed to assess the Effect Size (ES) from randomized studies comparing the effect of educational interventions in which Virtual patients (VPs) were used either as an alternative method or additive to usual curriculum versus interventions based on more traditional methods. Meta-analysis was designed, conducted and reported…