Epistemic uncertainty in the location and magnitude of earthquakes in Italy from Macroseismic data

USGS Publications Warehouse

Bakun, W.H.; Gomez, Capera A.; Stucchi, M.

2011-01-01

Three independent techniques (Bakun and Wentworth, 1997; Boxer from Gasperini et al., 1999; and Macroseismic Estimation of Earthquake Parameters [MEEP; see Data and Resources section, deliverable D3] from R.M.W. Musson and M.J. Jimenez) have been proposed for estimating an earthquake location and magnitude from intensity data alone. The locations and magnitudes obtained for a given set of intensity data are almost always different, and no one technique is consistently best at matching instrumental locations and magnitudes of recent well-recorded earthquakes in Italy. Rather than attempting to select one of the three solutions as best, we use all three techniques to estimate the location and the magnitude and the epistemic uncertainties among them. The estimates are calculated using bootstrap resampled data sets with Monte Carlo sampling of a decision tree. The decision-tree branch weights are based on goodness-of-fit measures of location and magnitude for recent earthquakes. The location estimates are based on the spatial distribution of locations calculated from the bootstrap resampled data. The preferred source location is the locus of the maximum bootstrap location spatial density. The location uncertainty is obtained from contours of the bootstrap spatial density: 68% of the bootstrap locations are within the 68% confidence region, and so on. For large earthquakes, our preferred location is not associated with the epicenter but with a location on the extended rupture surface. For small earthquakes, the epicenters are generally consistent with the location uncertainties inferred from the intensity data if an epicenter inaccuracy of 2-3 km is allowed. The preferred magnitude is the median of the distribution of bootstrap magnitudes. As with location uncertainties, the uncertainties in magnitude are obtained from the distribution of bootstrap magnitudes: the bounds of the 68% uncertainty range enclose 68% of the bootstrap magnitudes, and so on. The instrumental magnitudes for large and small earthquakes are generally consistent with the confidence intervals inferred from the distribution of bootstrap resampled magnitudes.

Statistical inference based on the nonparametric maximum likelihood estimator under double-truncation.

PubMed

Emura, Takeshi; Konno, Yoshihiko; Michimae, Hirofumi

2015-07-01

Doubly truncated data consist of samples whose observed values fall between the right- and left- truncation limits. With such samples, the distribution function of interest is estimated using the nonparametric maximum likelihood estimator (NPMLE) that is obtained through a self-consistency algorithm. Owing to the complicated asymptotic distribution of the NPMLE, the bootstrap method has been suggested for statistical inference. This paper proposes a closed-form estimator for the asymptotic covariance function of the NPMLE, which is computationally attractive alternative to bootstrapping. Furthermore, we develop various statistical inference procedures, such as confidence interval, goodness-of-fit tests, and confidence bands to demonstrate the usefulness of the proposed covariance estimator. Simulations are performed to compare the proposed method with both the bootstrap and jackknife methods. The methods are illustrated using the childhood cancer dataset.

Empirical likelihood-based confidence intervals for mean medical cost with censored data.

PubMed

Jeyarajah, Jenny; Qin, Gengsheng

2017-11-10

In this paper, we propose empirical likelihood methods based on influence function and jackknife techniques for constructing confidence intervals for mean medical cost with censored data. We conduct a simulation study to compare the coverage probabilities and interval lengths of our proposed confidence intervals with that of the existing normal approximation-based confidence intervals and bootstrap confidence intervals. The proposed methods have better finite-sample performances than existing methods. Finally, we illustrate our proposed methods with a relevant example. Copyright © 2017 John Wiley & Sons, Ltd.

Confidence intervals for correlations when data are not normal.

PubMed

Bishara, Anthony J; Hittner, James B

2017-02-01

With nonnormal data, the typical confidence interval of the correlation (Fisher z') may be inaccurate. The literature has been unclear as to which of several alternative methods should be used instead, and how extreme a violation of normality is needed to justify an alternative. Through Monte Carlo simulation, 11 confidence interval methods were compared, including Fisher z', two Spearman rank-order methods, the Box-Cox transformation, rank-based inverse normal (RIN) transformation, and various bootstrap methods. Nonnormality often distorted the Fisher z' confidence interval-for example, leading to a 95 % confidence interval that had actual coverage as low as 68 %. Increasing the sample size sometimes worsened this problem. Inaccurate Fisher z' intervals could be predicted by a sample kurtosis of at least 2, an absolute sample skewness of at least 1, or significant violations of normality hypothesis tests. Only the Spearman rank-order and RIN transformation methods were universally robust to nonnormality. Among the bootstrap methods, an observed imposed bootstrap came closest to accurate coverage, though it often resulted in an overly long interval. The results suggest that sample nonnormality can justify avoidance of the Fisher z' interval in favor of a more robust alternative. R code for the relevant methods is provided in supplementary materials.

Four Bootstrap Confidence Intervals for the Binomial-Error Model.

ERIC Educational Resources Information Center

Lin, Miao-Hsiang; Hsiung, Chao A.

1992-01-01

Four bootstrap methods are identified for constructing confidence intervals for the binomial-error model. The extent to which similar results are obtained and the theoretical foundation of each method and its relevance and ranges of modeling the true score uncertainty are discussed. (SLD)

Efficient bootstrap estimates for tail statistics

NASA Astrophysics Data System (ADS)

Breivik, Øyvind; Aarnes, Ole Johan

2017-03-01

Bootstrap resamples can be used to investigate the tail of empirical distributions as well as return value estimates from the extremal behaviour of the sample. Specifically, the confidence intervals on return value estimates or bounds on in-sample tail statistics can be obtained using bootstrap techniques. However, non-parametric bootstrapping from the entire sample is expensive. It is shown here that it suffices to bootstrap from a small subset consisting of the highest entries in the sequence to make estimates that are essentially identical to bootstraps from the entire sample. Similarly, bootstrap estimates of confidence intervals of threshold return estimates are found to be well approximated by using a subset consisting of the highest entries. This has practical consequences in fields such as meteorology, oceanography and hydrology where return values are calculated from very large gridded model integrations spanning decades at high temporal resolution or from large ensembles of independent and identically distributed model fields. In such cases the computational savings are substantial.

Simplified Estimation and Testing in Unbalanced Repeated Measures Designs.

PubMed

Spiess, Martin; Jordan, Pascal; Wendt, Mike

2018-05-07

In this paper we propose a simple estimator for unbalanced repeated measures design models where each unit is observed at least once in each cell of the experimental design. The estimator does not require a model of the error covariance structure. Thus, circularity of the error covariance matrix and estimation of correlation parameters and variances are not necessary. Together with a weak assumption about the reason for the varying number of observations, the proposed estimator and its variance estimator are unbiased. As an alternative to confidence intervals based on the normality assumption, a bias-corrected and accelerated bootstrap technique is considered. We also propose the naive percentile bootstrap for Wald-type tests where the standard Wald test may break down when the number of observations is small relative to the number of parameters to be estimated. In a simulation study we illustrate the properties of the estimator and the bootstrap techniques to calculate confidence intervals and conduct hypothesis tests in small and large samples under normality and non-normality of the errors. The results imply that the simple estimator is only slightly less efficient than an estimator that correctly assumes a block structure of the error correlation matrix, a special case of which is an equi-correlation matrix. Application of the estimator and the bootstrap technique is illustrated using data from a task switch experiment based on an experimental within design with 32 cells and 33 participants.

Bootstrap confidence intervals and bias correction in the estimation of HIV incidence from surveillance data with testing for recent infection.

PubMed

Carnegie, Nicole Bohme

2011-04-15

The incidence of new infections is a key measure of the status of the HIV epidemic, but accurate measurement of incidence is often constrained by limited data. Karon et al. (Statist. Med. 2008; 27:4617–4633) developed a model to estimate the incidence of HIV infection from surveillance data with biologic testing for recent infection for newly diagnosed cases. This method has been implemented by public health departments across the United States and is behind the new national incidence estimates, which are about 40 per cent higher than previous estimates. We show that the delta method approximation given for the variance of the estimator is incomplete, leading to an inflated variance estimate. This contributes to the generation of overly conservative confidence intervals, potentially obscuring important differences between populations. We demonstrate via simulation that an innovative model-based bootstrap method using the specified model for the infection and surveillance process improves confidence interval coverage and adjusts for the bias in the point estimate. Confidence interval coverage is about 94–97 per cent after correction, compared with 96–99 per cent before. The simulated bias in the estimate of incidence ranges from −6.3 to +14.6 per cent under the original model but is consistently under 1 per cent after correction by the model-based bootstrap. In an application to data from King County, Washington in 2007 we observe correction of 7.2 per cent relative bias in the incidence estimate and a 66 per cent reduction in the width of the 95 per cent confidence interval using this method. We provide open-source software to implement the method that can also be extended for alternate models.

Accuracy assessment of percent canopy cover, cover type, and size class

Treesearch

H. T. Schreuder; S. Bain; R. C. Czaplewski

2003-01-01

Truth for vegetation cover percent and type is obtained from very large-scale photography (VLSP), stand structure as measured by size classes, and vegetation types from a combination of VLSP and ground sampling. We recommend using the Kappa statistic with bootstrap confidence intervals for overall accuracy, and similarly bootstrap confidence intervals for percent...

Calculating Confidence Intervals for Regional Economic Impacts of Recreastion by Bootstrapping Visitor Expenditures

Treesearch

Donald B.K. English

2000-01-01

In this paper I use bootstrap procedures to develop confidence intervals for estimates of total industrial output generated per thousand tourist visits. Mean expenditures from replicated visitor expenditure data included weights to correct for response bias. Impacts were estimated with IMPLAN. Ninety percent interval endpoints were 6 to 16 percent above or below the...

Small sample mediation testing: misplaced confidence in bootstrapped confidence intervals.

PubMed

Koopman, Joel; Howe, Michael; Hollenbeck, John R; Sin, Hock-Peng

2015-01-01

Bootstrapping is an analytical tool commonly used in psychology to test the statistical significance of the indirect effect in mediation models. Bootstrapping proponents have particularly advocated for its use for samples of 20-80 cases. This advocacy has been heeded, especially in the Journal of Applied Psychology, as researchers are increasingly utilizing bootstrapping to test mediation with samples in this range. We discuss reasons to be concerned with this escalation, and in a simulation study focused specifically on this range of sample sizes, we demonstrate not only that bootstrapping has insufficient statistical power to provide a rigorous hypothesis test in most conditions but also that bootstrapping has a tendency to exhibit an inflated Type I error rate. We then extend our simulations to investigate an alternative empirical resampling method as well as a Bayesian approach and demonstrate that they exhibit comparable statistical power to bootstrapping in small samples without the associated inflated Type I error. Implications for researchers testing mediation hypotheses in small samples are presented. For researchers wishing to use these methods in their own research, we have provided R syntax in the online supplemental materials. (c) 2015 APA, all rights reserved.

Q-mode versus R-mode principal component analysis for linear discriminant analysis (LDA)

NASA Astrophysics Data System (ADS)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2017-05-01

Many literature apply Principal Component Analysis (PCA) as either preliminary visualization or variable con-struction methods or both. Focus of PCA can be on the samples (R-mode PCA) or variables (Q-mode PCA). Traditionally, R-mode PCA has been the usual approach to reduce high-dimensionality data before the application of Linear Discriminant Analysis (LDA), to solve classification problems. Output from PCA composed of two new matrices known as loadings and scores matrices. Each matrix can then be used to produce a plot, i.e. loadings plot aids identification of important variables whereas scores plot presents spatial distribution of samples on new axes that are also known as Principal Components (PCs). Fundamentally, the scores matrix always be the input variables for building classification model. A recent paper uses Q-mode PCA but the focus of analysis was not on the variables but instead on the samples. As a result, the authors have exchanged the use of both loadings and scores plots in which clustering of samples was studied using loadings plot whereas scores plot has been used to identify important manifest variables. Therefore, the aim of this study is to statistically validate the proposed practice. Evaluation is based on performance of external error obtained from LDA models according to number of PCs. On top of that, bootstrapping was also conducted to evaluate the external error of each of the LDA models. Results show that LDA models produced by PCs from R-mode PCA give logical performance and the matched external error are also unbiased whereas the ones produced with Q-mode PCA show the opposites. With that, we concluded that PCs produced from Q-mode is not statistically stable and thus should not be applied to problems of classifying samples, but variables. We hope this paper will provide some insights on the disputable issues.

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

PubMed

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

2010-03-01

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

A combined approach of generalized additive model and bootstrap with small sample sets for fault diagnosis in fermentation process of glutamate.

PubMed

Liu, Chunbo; Pan, Feng; Li, Yun

2016-07-29

Glutamate is of great importance in food and pharmaceutical industries. There is still lack of effective statistical approaches for fault diagnosis in the fermentation process of glutamate. To date, the statistical approach based on generalized additive model (GAM) and bootstrap has not been used for fault diagnosis in fermentation processes, much less the fermentation process of glutamate with small samples sets. A combined approach of GAM and bootstrap was developed for the online fault diagnosis in the fermentation process of glutamate with small sample sets. GAM was first used to model the relationship between glutamate production and different fermentation parameters using online data from four normal fermentation experiments of glutamate. The fitted GAM with fermentation time, dissolved oxygen, oxygen uptake rate and carbon dioxide evolution rate captured 99.6 % variance of glutamate production during fermentation process. Bootstrap was then used to quantify the uncertainty of the estimated production of glutamate from the fitted GAM using 95 % confidence interval. The proposed approach was then used for the online fault diagnosis in the abnormal fermentation processes of glutamate, and a fault was defined as the estimated production of glutamate fell outside the 95 % confidence interval. The online fault diagnosis based on the proposed approach identified not only the start of the fault in the fermentation process, but also the end of the fault when the fermentation conditions were back to normal. The proposed approach only used a small sample sets from normal fermentations excitements to establish the approach, and then only required online recorded data on fermentation parameters for fault diagnosis in the fermentation process of glutamate. The proposed approach based on GAM and bootstrap provides a new and effective way for the fault diagnosis in the fermentation process of glutamate with small sample sets.

What Teachers Should Know About the Bootstrap: Resampling in the Undergraduate Statistics Curriculum

PubMed Central

Hesterberg, Tim C.

2015-01-01

Bootstrapping has enormous potential in statistics education and practice, but there are subtle issues and ways to go wrong. For example, the common combination of nonparametric bootstrapping and bootstrap percentile confidence intervals is less accurate than using t-intervals for small samples, though more accurate for larger samples. My goals in this article are to provide a deeper understanding of bootstrap methods—how they work, when they work or not, and which methods work better—and to highlight pedagogical issues. Supplementary materials for this article are available online. [Received December 2014. Revised August 2015] PMID:27019512

Graphing within-subjects confidence intervals using SPSS and S-Plus.

PubMed

Wright, Daniel B

2007-02-01

Within-subjects confidence intervals are often appropriate to report and to display. Loftus and Masson (1994) have reported methods to calculate these, and their use is becoming common. In the present article, procedures for calculating within-subjects confidence intervals in SPSS and S-Plus are presented (an R version is on the accompanying Web site). The procedure in S-Plus allows the user to report the bias corrected and adjusted bootstrap confidence intervals as well as the standard confidence intervals based on traditional methods. The presented code can be easily altered to fit the individual user's needs.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

PubMed

Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

Exploring the Replicability of a Study's Results: Bootstrap Statistics for the Multivariate Case.

ERIC Educational Resources Information Center

Thompson, Bruce

1995-01-01

Use of the bootstrap method in a canonical correlation analysis to evaluate the replicability of a study's results is illustrated. More confidence may be vested in research results that replicate. (SLD)

Examining Differential Item Functioning: IRT-Based Detection in the Framework of Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Dimitrov, Dimiter M.

2017-01-01

This article offers an approach to examining differential item functioning (DIF) under its item response theory (IRT) treatment in the framework of confirmatory factor analysis (CFA). The approach is based on integrating IRT- and CFA-based testing of DIF and using bias-corrected bootstrap confidence intervals with a syntax code in Mplus.

Assessing uncertainties in superficial water provision by different bootstrap-based techniques

NASA Astrophysics Data System (ADS)

Rodrigues, Dulce B. B.; Gupta, Hoshin V.; Mendiondo, Eduardo Mario

2014-05-01

An assessment of water security can incorporate several water-related concepts, characterizing the interactions between societal needs, ecosystem functioning, and hydro-climatic conditions. The superficial freshwater provision level depends on the methods chosen for 'Environmental Flow Requirement' estimations, which integrate the sources of uncertainty in the understanding of how water-related threats to aquatic ecosystem security arise. Here, we develop an uncertainty assessment of superficial freshwater provision based on different bootstrap techniques (non-parametric resampling with replacement). To illustrate this approach, we use an agricultural basin (291 km2) within the Cantareira water supply system in Brazil monitored by one daily streamflow gage (24-year period). The original streamflow time series has been randomly resampled for different times or sample sizes (N = 500; ...; 1000), then applied to the conventional bootstrap approach and variations of this method, such as: 'nearest neighbor bootstrap'; and 'moving blocks bootstrap'. We have analyzed the impact of the sampling uncertainty on five Environmental Flow Requirement methods, based on: flow duration curves or probability of exceedance (Q90%, Q75% and Q50%); 7-day 10-year low-flow statistic (Q7,10); and presumptive standard (80% of the natural monthly mean ?ow). The bootstrap technique has been also used to compare those 'Environmental Flow Requirement' (EFR) methods among themselves, considering the difference between the bootstrap estimates and the "true" EFR characteristic, which has been computed averaging the EFR values of the five methods and using the entire streamflow record at monitoring station. This study evaluates the bootstrapping strategies, the representativeness of streamflow series for EFR estimates and their confidence intervals, in addition to overview of the performance differences between the EFR methods. The uncertainties arisen during EFR methods assessment will be propagated through water security indicators referring to water scarcity and vulnerability, seeking to provide meaningful support to end-users and water managers facing the incorporation of uncertainties in the decision making process.

AXIN2 expression predicts prostate cancer recurrence and regulates invasion and tumor growth.

PubMed

Hu, Brian R; Fairey, Adrian S; Madhav, Anisha; Yang, Dongyun; Li, Meng; Groshen, Susan; Stephens, Craig; Kim, Philip H; Virk, Navneet; Wang, Lina; Martin, Sue Ellen; Erho, Nicholas; Davicioni, Elai; Jenkins, Robert B; Den, Robert B; Xu, Tong; Xu, Yucheng; Gill, Inderbir S; Quinn, David I; Goldkorn, Amir

2016-05-01

Treatment of prostate cancer (PCa) may be improved by identifying biological mechanisms of tumor growth that directly impact clinical disease progression. We investigated whether genes associated with a highly tumorigenic, drug resistant, progenitor phenotype impact PCa biology and recurrence. Radical prostatectomy (RP) specimens (±disease recurrence, N = 276) were analyzed by qRT-PCR to quantify expression of genes associated with self-renewal, drug resistance, and tumorigenicity in prior studies. Associations between gene expression and PCa recurrence were confirmed by bootstrap internal validation and by external validation in independent cohorts (total N = 675) and in silico. siRNA knockdown and lentiviral overexpression were used to determine the effect of gene expression on PCa invasion, proliferation, and tumor growth. Four candidate genes were differentially expressed in PCa recurrence. Of these, low AXIN2 expression was internally validated in the discovery cohort. Validation in external cohorts and in silico demonstrated that low AXIN2 was independently associated with more aggressive PCa, biochemical recurrence, and metastasis-free survival after RP. Functionally, siRNA-mediated depletion of AXIN2 significantly increased invasiveness, proliferation, and tumor growth. Conversely, ectopic overexpression of AXIN2 significantly reduced invasiveness, proliferation, and tumor growth. Low AXIN2 expression was associated with PCa recurrence after RP in our test population as well as in external validation cohorts, and its expression levels in PCa cells significantly impacted invasiveness, proliferation, and tumor growth. Given these novel roles, further study of AXIN2 in PCa may yield promising new predictive and therapeutic strategies. © 2016 Wiley Periodicals, Inc.

Reanalysis of cancer mortality in Japanese A-bomb survivors exposed to low doses of radiation: bootstrap and simulation methods

PubMed Central

2009-01-01

Background The International Commission on Radiological Protection (ICRP) recommended annual occupational dose limit is 20 mSv. Cancer mortality in Japanese A-bomb survivors exposed to less than 20 mSv external radiation in 1945 was analysed previously, using a latency model with non-linear dose response. Questions were raised regarding statistical inference with this model. Methods Cancers with over 100 deaths in the 0 - 20 mSv subcohort of the 1950-1990 Life Span Study are analysed with Poisson regression models incorporating latency, allowing linear and non-linear dose response. Bootstrap percentile and Bias-corrected accelerated (BCa) methods and simulation of the Likelihood Ratio Test lead to Confidence Intervals for Excess Relative Risk (ERR) and tests against the linear model. Results The linear model shows significant large, positive values of ERR for liver and urinary cancers at latencies from 37 - 43 years. Dose response below 20 mSv is strongly non-linear at the optimal latencies for the stomach (11.89 years), liver (36.9), lung (13.6), leukaemia (23.66), and pancreas (11.86) and across broad latency ranges. Confidence Intervals for ERR are comparable using Bootstrap and Likelihood Ratio Test methods and BCa 95% Confidence Intervals are strictly positive across latency ranges for all 5 cancers. Similar risk estimates for 10 mSv (lagged dose) are obtained from the 0 - 20 mSv and 5 - 500 mSv data for the stomach, liver, lung and leukaemia. Dose response for the latter 3 cancers is significantly non-linear in the 5 - 500 mSv range. Conclusion Liver and urinary cancer mortality risk is significantly raised using a latency model with linear dose response. A non-linear model is strongly superior for the stomach, liver, lung, pancreas and leukaemia. Bootstrap and Likelihood-based confidence intervals are broadly comparable and ERR is strictly positive by bootstrap methods for all 5 cancers. Except for the pancreas, similar estimates of latency and risk from 10 mSv are obtained from the 0 - 20 mSv and 5 - 500 mSv subcohorts. Large and significant cancer risks for Japanese survivors exposed to less than 20 mSv external radiation from the atomic bombs in 1945 cast doubt on the ICRP recommended annual occupational dose limit. PMID:20003238

Estimating uncertainty in respondent-driven sampling using a tree bootstrap method.

PubMed

Baraff, Aaron J; McCormick, Tyler H; Raftery, Adrian E

2016-12-20

Respondent-driven sampling (RDS) is a network-based form of chain-referral sampling used to estimate attributes of populations that are difficult to access using standard survey tools. Although it has grown quickly in popularity since its introduction, the statistical properties of RDS estimates remain elusive. In particular, the sampling variability of these estimates has been shown to be much higher than previously acknowledged, and even methods designed to account for RDS result in misleadingly narrow confidence intervals. In this paper, we introduce a tree bootstrap method for estimating uncertainty in RDS estimates based on resampling recruitment trees. We use simulations from known social networks to show that the tree bootstrap method not only outperforms existing methods but also captures the high variability of RDS, even in extreme cases with high design effects. We also apply the method to data from injecting drug users in Ukraine. Unlike other methods, the tree bootstrap depends only on the structure of the sampled recruitment trees, not on the attributes being measured on the respondents, so correlations between attributes can be estimated as well as variability. Our results suggest that it is possible to accurately assess the high level of uncertainty inherent in RDS.

Using the Bootstrap Method to Evaluate the Critical Range of Misfit for Polytomous Rasch Fit Statistics.

PubMed

Seol, Hyunsoo

2016-06-01

The purpose of this study was to apply the bootstrap procedure to evaluate how the bootstrapped confidence intervals (CIs) for polytomous Rasch fit statistics might differ according to sample sizes and test lengths in comparison with the rule-of-thumb critical value of misfit. A total of 25 simulated data sets were generated to fit the Rasch measurement and then a total of 1,000 replications were conducted to compute the bootstrapped CIs under each of 25 testing conditions. The results showed that rule-of-thumb critical values for assessing the magnitude of misfit were not applicable because the infit and outfit mean square error statistics showed different magnitudes of variability over testing conditions and the standardized fit statistics did not exactly follow the standard normal distribution. Further, they also do not share the same critical range for the item and person misfit. Based on the results of the study, the bootstrapped CIs can be used to identify misfitting items or persons as they offer a reasonable alternative solution, especially when the distributions of the infit and outfit statistics are not well known and depend on sample size. © The Author(s) 2016.

A new framework of statistical inferences based on the valid joint sampling distribution of the observed counts in an incomplete contingency table.

PubMed

Tian, Guo-Liang; Li, Hui-Qiong

2017-08-01

Some existing confidence interval methods and hypothesis testing methods in the analysis of a contingency table with incomplete observations in both margins entirely depend on an underlying assumption that the sampling distribution of the observed counts is a product of independent multinomial/binomial distributions for complete and incomplete counts. However, it can be shown that this independency assumption is incorrect and can result in unreliable conclusions because of the under-estimation of the uncertainty. Therefore, the first objective of this paper is to derive the valid joint sampling distribution of the observed counts in a contingency table with incomplete observations in both margins. The second objective is to provide a new framework for analyzing incomplete contingency tables based on the derived joint sampling distribution of the observed counts by developing a Fisher scoring algorithm to calculate maximum likelihood estimates of parameters of interest, the bootstrap confidence interval methods, and the bootstrap testing hypothesis methods. We compare the differences between the valid sampling distribution and the sampling distribution under the independency assumption. Simulation studies showed that average/expected confidence-interval widths of parameters based on the sampling distribution under the independency assumption are shorter than those based on the new sampling distribution, yielding unrealistic results. A real data set is analyzed to illustrate the application of the new sampling distribution for incomplete contingency tables and the analysis results again confirm the conclusions obtained from the simulation studies.

Asymptotic confidence intervals for the Pearson correlation via skewness and kurtosis.

PubMed

Bishara, Anthony J; Li, Jiexiang; Nash, Thomas

2018-02-01

When bivariate normality is violated, the default confidence interval of the Pearson correlation can be inaccurate. Two new methods were developed based on the asymptotic sampling distribution of Fisher's z' under the general case where bivariate normality need not be assumed. In Monte Carlo simulations, the most successful of these methods relied on the (Vale & Maurelli, 1983, Psychometrika, 48, 465) family to approximate a distribution via the marginal skewness and kurtosis of the sample data. In Simulation 1, this method provided more accurate confidence intervals of the correlation in non-normal data, at least as compared to no adjustment of the Fisher z' interval, or to adjustment via the sample joint moments. In Simulation 2, this approximate distribution method performed favourably relative to common non-parametric bootstrap methods, but its performance was mixed relative to an observed imposed bootstrap and two other robust methods (PM1 and HC4). No method was completely satisfactory. An advantage of the approximate distribution method, though, is that it can be implemented even without access to raw data if sample skewness and kurtosis are reported, making the method particularly useful for meta-analysis. Supporting information includes R code. © 2017 The British Psychological Society.

An adaptive confidence limit for periodic non-steady conditions fault detection

NASA Astrophysics Data System (ADS)

Wang, Tianzhen; Wu, Hao; Ni, Mengqi; Zhang, Milu; Dong, Jingjing; Benbouzid, Mohamed El Hachemi; Hu, Xiong

2016-05-01

System monitoring has become a major concern in batch process due to the fact that failure rate in non-steady conditions is much higher than in steady ones. A series of approaches based on PCA have already solved problems such as data dimensionality reduction, multivariable decorrelation, and processing non-changing signal. However, if the data follows non-Gaussian distribution or the variables contain some signal changes, the above approaches are not applicable. To deal with these concerns and to enhance performance in multiperiod data processing, this paper proposes a fault detection method using adaptive confidence limit (ACL) in periodic non-steady conditions. The proposed ACL method achieves four main enhancements: Longitudinal-Standardization could convert non-Gaussian sampling data to Gaussian ones; the multiperiod PCA algorithm could reduce dimensionality, remove correlation, and improve the monitoring accuracy; the adaptive confidence limit could detect faults under non-steady conditions; the fault sections determination procedure could select the appropriate parameter of the adaptive confidence limit. The achieved result analysis clearly shows that the proposed ACL method is superior to other fault detection approaches under periodic non-steady conditions.

Technical and scale efficiency in public and private Irish nursing homes - a bootstrap DEA approach.

PubMed

Ni Luasa, Shiovan; Dineen, Declan; Zieba, Marta

2016-10-27

This article provides methodological and empirical insights into the estimation of technical efficiency in the nursing home sector. Focusing on long-stay care and using primary data, we examine technical and scale efficiency in 39 public and 73 private Irish nursing homes by applying an input-oriented data envelopment analysis (DEA). We employ robust bootstrap methods to validate our nonparametric DEA scores and to integrate the effects of potential determinants in estimating the efficiencies. Both the homogenous and two-stage double bootstrap procedures are used to obtain confidence intervals for the bias-corrected DEA scores. Importantly, the application of the double bootstrap approach affords true DEA technical efficiency scores after adjusting for the effects of ownership, size, case-mix, and other determinants such as location, and quality. Based on our DEA results for variable returns to scale technology, the average technical efficiency score is 62 %, and the mean scale efficiency is 88 %, with nearly all units operating on the increasing returns to scale part of the production frontier. Moreover, based on the double bootstrap results, Irish nursing homes are less technically efficient, and more scale efficient than the conventional DEA estimates suggest. Regarding the efficiency determinants, in terms of ownership, we find that private facilities are less efficient than the public units. Furthermore, the size of the nursing home has a positive effect, and this reinforces our finding that Irish homes produce at increasing returns to scale. Also, notably, we find that a tendency towards quality improvements can lead to poorer technical efficiency performance.

A Comparison of Single Sample and Bootstrap Methods to Assess Mediation in Cluster Randomized Trials

ERIC Educational Resources Information Center

Pituch, Keenan A.; Stapleton, Laura M.; Kang, Joo Youn

2006-01-01

A Monte Carlo study examined the statistical performance of single sample and bootstrap methods that can be used to test and form confidence interval estimates of indirect effects in two cluster randomized experimental designs. The designs were similar in that they featured random assignment of clusters to one of two treatment conditions and…

An inferential study of the phenotype for the chromosome 15q24 microdeletion syndrome: a bootstrap analysis

PubMed Central

Ramírez-Prado, Dolores; Cortés, Ernesto; Aguilar-Segura, María Soledad; Gil-Guillén, Vicente Francisco

2016-01-01

In January 2012, a review of the cases of chromosome 15q24 microdeletion syndrome was published. However, this study did not include inferential statistics. The aims of the present study were to update the literature search and calculate confidence intervals for the prevalence of each phenotype using bootstrap methodology. Published case reports of patients with the syndrome that included detailed information about breakpoints and phenotype were sought and 36 were included. Deletions in megabase (Mb) pairs were determined to calculate the size of the interstitial deletion of the phenotypes studied in 2012. To determine confidence intervals for the prevalence of the phenotype and the interstitial loss, we used bootstrap methodology. Using the bootstrap percentiles method, we found wide variability in the prevalence of the different phenotypes (3–100%). The mean interstitial deletion size was 2.72 Mb (95% CI [2.35–3.10 Mb]). In comparison with our work, which expanded the literature search by 45 months, there were differences in the prevalence of 17% of the phenotypes, indicating that more studies are needed to analyze this rare disease. PMID:26925314

Development and validation of a new instrument to evaluate the ease of use of patient-controlled analgesic modalities for postoperative patients.

PubMed

Harding, Gale; Schein, Jeff R; Nelson, Winnie W; Vallow, Sue; Olson, William H; Hewitt, David J; Polomano, Rosemary C

2010-03-01

To describe the development and psychometric evaluation of a questionnaire assessing the ease of use that patients associate with patient-controlled analgesia (PCA) modalities. Qualitative interviews were conducted with patients who had experience with intravenous (IV) PCA for postoperative pain management to generate items relevant to the ease of using PCA modalities. The content validity of the resulting questionnaire was examined through follow-up patient interviews, and an expert panel reviewed the questionnaire. Cognitive debriefing interviews were conducted with patients to determine the clarity and content of the instructions, items, and response scales, and the ease of completing the instrument. Psychometric evaluation was performed with patients who had undergone surgery and received IV PCA for postoperative pain management. Item and scale quality and the internal consistency reliability of the questionnaire were assessed. Construct validity was evaluated by examining the relationship between subscales of the questionnaire with patient-reported outcome measures. Known-groups validity was determined by assessing the instrument's ability to differentiate between patients with versus without an IV PCA problem. A potential limitation of this study was the exclusive sampling of patients who had experience with IV PCA. The Patient Ease-of-Care (EOC) Questionnaire included 23 items in the following subscales: Confidence with Device, Comfort with Device, Movement, Dosing Confidence, Pain Control, Knowledge/Understanding, and Satisfaction. Coefficient alpha reliability estimates were ≥ 0.66 for Overall EOC (includes all subscales except Satisfaction) and all EOC subscales. Construct validity was supported by the moderate relationship between the Pain Control subscale and measures of pain severity and pain interference; additional evidence of construct validity was provided by correlations of the Confidence with Device subscale, the Satisfaction subscale, and Overall EOC with measures of pain severity, pain interference, and satisfaction. Significant mean score differences were reported between participants with and without IV PCA problems for Overall EOC and for the Comfort with Device, Confidence with Device, Movement, Pain Control, and Satisfaction subscales indicating known-groups validity. Results provide evidence for the reliability and validity of the Patient EOC Questionnaire as a measure of the ease of use that patients associate with PCA systems and may be useful for evaluating emerging PCA modalities.

Acculturation, Income and Vegetable Consumption Behaviors Among Latino Adults in the U.S.: A Mediation Analysis with the Bootstrapping Technique.

PubMed

López, Erick B; Yamashita, Takashi

2017-02-01

This study examined whether household income mediates the relationship between acculturation and vegetable consumption among Latino adults in the U.S. Data from the 2009 to 2010 National Health and Nutrition Examination Survey were analyzed. Vegetable consumption index was created based on the frequencies of five kinds of vegetables intake. Acculturation was measured with the degree of English language use at home. Path model with bootstrapping technique was employed for mediation analysis. A significant partial mediation relationship was identified. Greater acculturation [95 % bias corrected bootstrap confident interval (BCBCI) = (0.02, 0.33)] was associated with the higher income and in turn, greater vegetable consumption. At the same time, greater acculturation was associated with lower vegetable consumption [95 % BCBCI = (-0.88, -0.07)]. Findings regarding the income as a mediator of the acculturation-dietary behavior relationship inform unique intervention programs and policy changes to address health disparities by race/ethnicity.

Applying Bootstrap Resampling to Compute Confidence Intervals for Various Statistics with R

ERIC Educational Resources Information Center

Dogan, C. Deha

2017-01-01

Background: Most of the studies in academic journals use p values to represent statistical significance. However, this is not a good indicator of practical significance. Although confidence intervals provide information about the precision of point estimation, they are, unfortunately, rarely used. The infrequent use of confidence intervals might…

Confidence Intervals for Effect Sizes: Applying Bootstrap Resampling

ERIC Educational Resources Information Center

Banjanovic, Erin S.; Osborne, Jason W.

2016-01-01

Confidence intervals for effect sizes (CIES) provide readers with an estimate of the strength of a reported statistic as well as the relative precision of the point estimate. These statistics offer more information and context than null hypothesis statistic testing. Although confidence intervals have been recommended by scholars for many years,…

The Bootstrap, the Jackknife, and the Randomization Test: A Sampling Taxonomy.

PubMed

Rodgers, J L

1999-10-01

A simple sampling taxonomy is defined that shows the differences between and relationships among the bootstrap, the jackknife, and the randomization test. Each method has as its goal the creation of an empirical sampling distribution that can be used to test statistical hypotheses, estimate standard errors, and/or create confidence intervals. Distinctions between the methods can be made based on the sampling approach (with replacement versus without replacement) and the sample size (replacing the whole original sample versus replacing a subset of the original sample). The taxonomy is useful for teaching the goals and purposes of resampling schemes. An extension of the taxonomy implies other possible resampling approaches that have not previously been considered. Univariate and multivariate examples are presented.

Using a Nonparametric Bootstrap to Obtain a Confidence Interval for Pearson's "r" with Cluster Randomized Data: A Case Study

ERIC Educational Resources Information Center

Wagstaff, David A.; Elek, Elvira; Kulis, Stephen; Marsiglia, Flavio

2009-01-01

A nonparametric bootstrap was used to obtain an interval estimate of Pearson's "r," and test the null hypothesis that there was no association between 5th grade students' positive substance use expectancies and their intentions to not use substances. The students were participating in a substance use prevention program in which the unit of…

Statin use and risk of prostate cancer: a Danish population-based case-control study, 1997-2010.

PubMed

Jespersen, Christina G; Nørgaard, Mette; Friis, Søren; Skriver, Charlotte; Borre, Michael

2014-02-01

Conflicting evidence has suggested that statins possess chemopreventive properties against prostate cancer (PCa). Therefore, we examined the association between statin use and risk of PCa in a Denmark-based case-control study. We identified 42,480 patients diagnosed with incident PCa during 1997-2010 from a national cancer registry. Five age-matched population controls (n=212,400) were selected for each case using risk-set sampling. Statin use from 1996 to the index date was obtained from the National Prescription Registry. Odds ratios (ORs) adjusted for age, comorbidity, non-steroidal anti-inflammatory drug use, and educational level for PCa associated with statin use, were computed using conditional logistic regression. Analyses were stratified by duration of statin use (0-1, 2-4, 5-9, or ≥10 years), stage of PCa (localized or advanced), and type of statin used (lipophilic or hydrophilic). In total, 7915 patients (19%) and 39,384 controls (19%) redeemed statin prescriptions prior to the index date. Overall, statin users had a 6% lower risk of PCa compared with non-users [adjusted OR (ORa), 0.94; 95% confidence interval (CI), 0.91-0.97]. Risk estimates did not differ substantially by duration or type of statin used. Slightly larger statin use-associated risk reductions were observed for advanced PCa (ORa, 0.90; 95% CI, 0.85-0.96) and with statin use ≥10 years (ORa, 0.78; 95% CI, 0.65-0.95). Statin use was associated with a risk reduction overall (6%) and, specifically with advanced PCa (10%). Differences in diagnostic measures and residual confounding by socioeconomic parameters may have influenced our results. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mortality among men with locally advanced prostate cancer managed with noncurative intent: a nationwide study in PCBaSe Sweden.

PubMed

Akre, Olof; Garmo, Hans; Adolfsson, Jan; Lambe, Mats; Bratt, Ola; Stattin, Pär

2011-09-01

There are limited prognostic data for locally advanced prostate cancer PCa to guide in the choice of treatment. To assess mortality in different prognostic categories among men with locally advanced PCa managed with noncurative intent. We conducted a register-based nationwide cohort study within the Prostate Cancer DataBase Sweden. The entire cohort of locally advanced PCa included 14 908 men. After the exclusion of 2724 (18%) men treated with curative intent, 12 184 men with locally advanced PCa either with local clinical stage T3 or T4 or with T2 with serum levels of prostate-specific antigen (PSA) between 50 and 99 ng/ml and without signs of metastases remained for analysis. We followed up the patient cohort in the Cause of Death Register for ≤ 11 yr and assessed cumulative incidence of PCa -specific death stratified by age and clinical characteristics. The PCa -specific mortality at 8 yr of follow-up was 28% (95% confidence interval [CI], 25-32%) for Gleason score (GS) 2-6, 41% (95% CI, 38-44%) for GS 7, 52% (95% CI, 47-57%) for GS 8, and 64% (95% CI, 59-69%) for GS 9-10. Even for men aged >85 yr at diagnosis with GS 8-10, PCa was a major cause of death: 42% (95% CI, 37-47%). Men with locally advanced disease and a PSA<4 ng/ml at diagnosis were at particularly increased risk of dying from PCa. One important limitation is the lack of bone scans in 42% of the patient cohort, but results remained after exclusion of patients with unknown metastasis status. The PCa-specific mortality within 8 yr of diagnosis is high in locally advanced PCa, suggesting undertreatment, particularly among men in older age groups. Our results underscore the need for more studies of treatment with curative intent for locally advanced tumors. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Benchmark dose analysis via nonparametric regression modeling

PubMed Central

Piegorsch, Walter W.; Xiong, Hui; Bhattacharya, Rabi N.; Lin, Lizhen

2013-01-01

Estimation of benchmark doses (BMDs) in quantitative risk assessment traditionally is based upon parametric dose-response modeling. It is a well-known concern, however, that if the chosen parametric model is uncertain and/or misspecified, inaccurate and possibly unsafe low-dose inferences can result. We describe a nonparametric approach for estimating BMDs with quantal-response data based on an isotonic regression method, and also study use of corresponding, nonparametric, bootstrap-based confidence limits for the BMD. We explore the confidence limits’ small-sample properties via a simulation study, and illustrate the calculations with an example from cancer risk assessment. It is seen that this nonparametric approach can provide a useful alternative for BMD estimation when faced with the problem of parametric model uncertainty. PMID:23683057

Physical activity in relation to risk of prostate cancer: a systematic review and meta-analysis.

PubMed

Benke, I N; Leitzmann, M F; Behrens, G; Schmid, D

2018-05-01

Prostate cancer (PCa) is one of the most common cancers among men, yet little is known about its modifiable risk and protective factors. This study aims to quantitatively summarize observational studies relating physical activity (PA) to PCa incidence and mortality. Published articles pertaining to PA and PCa incidence and mortality were retrieved in July 2017 using the Medline and EMBASE databases. The literature review yielded 48 cohort studies and 24 case-control studies with a total of 151 748 PCa cases. The mean age of the study participants at baseline was 61 years. In random-effects models, comparing the highest versus the lowest level of overall PA showed a summary relative risk (RR) estimate for total PCa incidence close to the null [RR = 0.99, 95% confidence interval (CI) = 0.94-1.04]. The corresponding RRs for advanced and non-advanced PCa were 0.92 (95% CI = 0.80-1.06) and 0.95 (95% CI = 0.85-1.07), respectively. We noted a statistically significant inverse association between long-term occupational activity and total PCa (RR = 0.83, 95% CI = 0.71-0.98, n studies = 13), although that finding became statistically non-significant when individual studies were removed from the analysis. When evaluated by cancer subtype, an inverse association with long-term occupational activity was noted for non-advanced/non-aggressive PCa (RR = 0.51, 95% CI = 0.37-0.71, n studies = 2) and regular recreational activity was inversely related to advanced/aggressive PCa (RR = 0.75, 95% CI = 0.60-0.95, n studies = 2), although these observations are based on a low number of studies. Moreover, PA after diagnosis was related to reduced risk of PCa mortality among survivors of PCa (summary RR based on four studies = 0.69, 95% CI = 0.55-0.85). Whether PA protects against PCa remains elusive. Further investigation taking into account the complex clinical and pathologic nature of PCa is needed to clarify the PA and PCa incidence relation. Moreover, future studies are needed to confirm whether PA after diagnosis reduces risk of PCa mortality.

Determination of Time Dependent Virus Inactivation Rates

NASA Astrophysics Data System (ADS)

Chrysikopoulos, C. V.; Vogler, E. T.

2003-12-01

A methodology is developed for estimating temporally variable virus inactivation rate coefficients from experimental virus inactivation data. The methodology consists of a technique for slope estimation of normalized virus inactivation data in conjunction with a resampling parameter estimation procedure. The slope estimation technique is based on a relatively flexible geostatistical method known as universal kriging. Drift coefficients are obtained by nonlinear fitting of bootstrap samples and the corresponding confidence intervals are obtained by bootstrap percentiles. The proposed methodology yields more accurate time dependent virus inactivation rate coefficients than those estimated by fitting virus inactivation data to a first-order inactivation model. The methodology is successfully applied to a set of poliovirus batch inactivation data. Furthermore, the importance of accurate inactivation rate coefficient determination on virus transport in water saturated porous media is demonstrated with model simulations.

Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis.

PubMed

Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A

2015-05-01

Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using the bootstrap to establish statistical significance for relative validity comparisons among patient-reported outcome measures

PubMed Central

2013-01-01

Background Relative validity (RV), a ratio of ANOVA F-statistics, is often used to compare the validity of patient-reported outcome (PRO) measures. We used the bootstrap to establish the statistical significance of the RV and to identify key factors affecting its significance. Methods Based on responses from 453 chronic kidney disease (CKD) patients to 16 CKD-specific and generic PRO measures, RVs were computed to determine how well each measure discriminated across clinically-defined groups of patients compared to the most discriminating (reference) measure. Statistical significance of RV was quantified by the 95% bootstrap confidence interval. Simulations examined the effects of sample size, denominator F-statistic, correlation between comparator and reference measures, and number of bootstrap replicates. Results The statistical significance of the RV increased as the magnitude of denominator F-statistic increased or as the correlation between comparator and reference measures increased. A denominator F-statistic of 57 conveyed sufficient power (80%) to detect an RV of 0.6 for two measures correlated at r = 0.7. Larger denominator F-statistics or higher correlations provided greater power. Larger sample size with a fixed denominator F-statistic or more bootstrap replicates (beyond 500) had minimal impact. Conclusions The bootstrap is valuable for establishing the statistical significance of RV estimates. A reasonably large denominator F-statistic (F > 57) is required for adequate power when using the RV to compare the validity of measures with small or moderate correlations (r < 0.7). Substantially greater power can be achieved when comparing measures of a very high correlation (r > 0.9). PMID:23721463

Bootstrap investigation of the stability of a Cox regression model.

PubMed

Altman, D G; Andersen, P K

1989-07-01

We describe a bootstrap investigation of the stability of a Cox proportional hazards regression model resulting from the analysis of a clinical trial of azathioprine versus placebo in patients with primary biliary cirrhosis. We have considered stability to refer both to the choice of variables included in the model and, more importantly, to the predictive ability of the model. In stepwise Cox regression analyses of 100 bootstrap samples using 17 candidate variables, the most frequently selected variables were those selected in the original analysis, and no other important variable was identified. Thus there was no reason to doubt the model obtained in the original analysis. For each patient in the trial, bootstrap confidence intervals were constructed for the estimated probability of surviving two years. It is shown graphically that these intervals are markedly wider than those obtained from the original model.

A note on the kappa statistic for clustered dichotomous data.

PubMed

Zhou, Ming; Yang, Zhao

2014-06-30

The kappa statistic is widely used to assess the agreement between two raters. Motivated by a simulation-based cluster bootstrap method to calculate the variance of the kappa statistic for clustered physician-patients dichotomous data, we investigate its special correlation structure and develop a new simple and efficient data generation algorithm. For the clustered physician-patients dichotomous data, based on the delta method and its special covariance structure, we propose a semi-parametric variance estimator for the kappa statistic. An extensive Monte Carlo simulation study is performed to evaluate the performance of the new proposal and five existing methods with respect to the empirical coverage probability, root-mean-square error, and average width of the 95% confidence interval for the kappa statistic. The variance estimator ignoring the dependence within a cluster is generally inappropriate, and the variance estimators from the new proposal, bootstrap-based methods, and the sampling-based delta method perform reasonably well for at least a moderately large number of clusters (e.g., the number of clusters K ⩾50). The new proposal and sampling-based delta method provide convenient tools for efficient computations and non-simulation-based alternatives to the existing bootstrap-based methods. Moreover, the new proposal has acceptable performance even when the number of clusters is as small as K = 25. To illustrate the practical application of all the methods, one psychiatric research data and two simulated clustered physician-patients dichotomous data are analyzed. Copyright © 2014 John Wiley & Sons, Ltd.

Quantifying uncertainty on sediment loads using bootstrap confidence intervals

NASA Astrophysics Data System (ADS)

Slaets, Johanna I. F.; Piepho, Hans-Peter; Schmitter, Petra; Hilger, Thomas; Cadisch, Georg

2017-01-01

Load estimates are more informative than constituent concentrations alone, as they allow quantification of on- and off-site impacts of environmental processes concerning pollutants, nutrients and sediment, such as soil fertility loss, reservoir sedimentation and irrigation channel siltation. While statistical models used to predict constituent concentrations have been developed considerably over the last few years, measures of uncertainty on constituent loads are rarely reported. Loads are the product of two predictions, constituent concentration and discharge, integrated over a time period, which does not make it straightforward to produce a standard error or a confidence interval. In this paper, a linear mixed model is used to estimate sediment concentrations. A bootstrap method is then developed that accounts for the uncertainty in the concentration and discharge predictions, allowing temporal correlation in the constituent data, and can be used when data transformations are required. The method was tested for a small watershed in Northwest Vietnam for the period 2010-2011. The results showed that confidence intervals were asymmetric, with the highest uncertainty in the upper limit, and that a load of 6262 Mg year-1 had a 95 % confidence interval of (4331, 12 267) in 2010 and a load of 5543 Mg an interval of (3593, 8975) in 2011. Additionally, the approach demonstrated that direct estimates from the data were biased downwards compared to bootstrap median estimates. These results imply that constituent loads predicted from regression-type water quality models could frequently be underestimating sediment yields and their environmental impact.

Associations of tea and coffee consumption with prostate cancer risk

PubMed Central

Geybels, Milan S.; Neuhouser, Marian L.; Stanford, Janet L.

2013-01-01

Purpose: Tea and coffee contain bioactive compounds and both beverages have recently been associated with a reduced risk of prostate cancer (PCa). Methods: We studied associations of tea and coffee consumption with PCa risk in a population-based case-control study from King County, Washington, US. Prostate cancer cases were diagnosed in 2002-2005 and matched to controls by five-year age groups. Logistic regression was used to generate odds ratios (ORs) and 95% confidence intervals (CIs). Results: Among controls, 19% and 58% consumed at least one cup per day of tea and coffee, respectively. The analysis of tea included 892 cases and 863 controls and tea consumption was associated with a reduced overall PCa risk with an adjusted OR of 0.63 (95% CI: 0.45, 0.90; P for trend = 0.02) for men in the highest compared to lowest category of tea intake (≥2 cups/day versus ≤1 cup/week). Risk estimates did not vary substantially by Gleason grade or disease stage. Coffee consumption was not associated with risk of overall PCa or PCa in subgroups defined by tumor grade or stage. Conclusions: Our results contribute further evidence that tea consumption may be a modifiable exposure that reduces PCa risk. PMID:23412806

Effect of Statins and Anticoagulants on Prostate Cancer Aggressiveness

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

Alizadeh, Moein; Sylvestre, Marie-Pierre; Zilli, Thomas

2012-07-15

Purpose: Statins and anticoagulants (ACs) have both been associated with a less-aggressive prostate cancer (PCa) and a better outcome after treatment of localized PCa. The results of these studies might have been confounded because patients might often take both medications. We examined their respective influence on PCa aggressiveness at initial diagnosis. Materials and Methods: We analyzed 381 patients treated with either external beam radiotherapy or brachytherapy for low-risk (n = 152), intermediate-risk (n = 142), or high-risk (n = 87) localized PCa. Univariate and multivariate logistic regression analyses were used to investigate an association between these drug classes and prostatemore » cancer aggressiveness. We tested whether the concomitant use of statins and ACs had a different effect than that of either AC or statin use alone. Results: Of the 381 patients, 172 (45.1%) were taking statins and 141 (37.0%) ACs; 105 patients (27.6%) used both. On univariate analysis, the statin and AC users were associated with the prostate-specific antigen (PSA) level (p = .017) and National Comprehensive Cancer Network risk group (p = .0022). On multivariate analysis, statin use was associated with a PSA level <10 ng/mL (odds ratio, 2.9; 95% confidence interval, 1.3-6.8; p = .012) and a PSA level >20 ng/mL (odds ratio, 0.29; 95% confidence interval, 0.08-0.83; p = .03). The use of ACs was associated with a PSA level >20 ng/mL (odds ratio, 0.13; 95% confidence interval, 0.02-0.59, p = .02). Conclusion: Both AC and statins have an effect on PCa aggressiveness, with statins having a more stringent relationship with the PSA level, highlighting the importance of considering statin use in studies of PCa aggressiveness.« less

Researches of fruit quality prediction model based on near infrared spectrum

NASA Astrophysics Data System (ADS)

Shen, Yulin; Li, Lian

2018-04-01

With the improvement in standards for food quality and safety, people pay more attention to the internal quality of fruits, therefore the measurement of fruit internal quality is increasingly imperative. In general, nondestructive soluble solid content (SSC) and total acid content (TAC) analysis of fruits is vital and effective for quality measurement in global fresh produce markets, so in this paper, we aim at establishing a novel fruit internal quality prediction model based on SSC and TAC for Near Infrared Spectrum. Firstly, the model of fruit quality prediction based on PCA + BP neural network, PCA + GRNN network, PCA + BP adaboost strong classifier, PCA + ELM and PCA + LS_SVM classifier are designed and implemented respectively; then, in the NSCT domain, the median filter and the SavitzkyGolay filter are used to preprocess the spectral signal, Kennard-Stone algorithm is used to automatically select the training samples and test samples; thirdly, we achieve the optimal models by comparing 15 kinds of prediction model based on the theory of multi-classifier competition mechanism, specifically, the non-parametric estimation is introduced to measure the effectiveness of proposed model, the reliability and variance of nonparametric estimation evaluation of each prediction model to evaluate the prediction result, while the estimated value and confidence interval regard as a reference, the experimental results demonstrate that this model can better achieve the optimal evaluation of the internal quality of fruit; finally, we employ cat swarm optimization to optimize two optimal models above obtained from nonparametric estimation, empirical testing indicates that the proposed method can provide more accurate and effective results than other forecasting methods.

Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data.

PubMed

Salvatore, Stefania; Bramness, Jørgen G; Røislien, Jo

2016-07-12

Wastewater-based epidemiology (WBE) is a novel approach in drug use epidemiology which aims to monitor the extent of use of various drugs in a community. In this study, we investigate functional principal component analysis (FPCA) as a tool for analysing WBE data and compare it to traditional principal component analysis (PCA) and to wavelet principal component analysis (WPCA) which is more flexible temporally. We analysed temporal wastewater data from 42 European cities collected daily over one week in March 2013. The main temporal features of ecstasy (MDMA) were extracted using FPCA using both Fourier and B-spline basis functions with three different smoothing parameters, along with PCA and WPCA with different mother wavelets and shrinkage rules. The stability of FPCA was explored through bootstrapping and analysis of sensitivity to missing data. The first three principal components (PCs), functional principal components (FPCs) and wavelet principal components (WPCs) explained 87.5-99.6 % of the temporal variation between cities, depending on the choice of basis and smoothing. The extracted temporal features from PCA, FPCA and WPCA were consistent. FPCA using Fourier basis and common-optimal smoothing was the most stable and least sensitive to missing data. FPCA is a flexible and analytically tractable method for analysing temporal changes in wastewater data, and is robust to missing data. WPCA did not reveal any rapid temporal changes in the data not captured by FPCA. Overall the results suggest FPCA with Fourier basis functions and common-optimal smoothing parameter as the most accurate approach when analysing WBE data.

Calcium channel blocker use and risk of prostate cancer by TMPRSS2:ERG gene fusion status

PubMed Central

Geybels, Milan S.; McCloskey, Karen D.; Mills, Ian G.; Stanford, Janet L.

2017-01-01

Background Calcium channel blockers (CCBs) may affect prostate cancer (PCa) growth by various mechanisms including those related to androgens. The fusion of the androgen-regulated gene TMPRSS2 and the oncogene ERG (TMPRSS2:ERG or T2E) is common in PCa, and prostate tumors that harbor the gene fusion are believed to represent a distinct disease subtype. We studied the association of CCB use with the risk of PCa, and molecular subtypes of PCa defined by T2E status. Methods Participants were residents of King County, Washington, recruited for population-based case–control studies (1993–1996 or 2002–2005). Tumor T2E status was determined by fluorescence in situ hybridization using tumor tissue specimens from radical prostatectomy. Detailed information on use of CCBs and other variables was obtained through in-person interviews. Binomial and polytomous logistic regression were used to generate odds ratios (ORs) and 95% confidence intervals (CIs). Results The study includes 1,747 PCa patients and 1,635 age-matched controls. A subset of 563 patients treated with radical prostatectomy had T2E status determined, of which 295 were T2E positive (52%). Use of CCBs (ever vs. never) was not associated with overall PCa risk. However, among European-American men, users had a reduced risk of higher-grade PCa (Gleason scores ≥7: adjusted OR = 0.64; 95% CI: 0.44–0.95). Further, use of CCBs was associated with a reduced risk of T2E positive PCa (adjusted OR = 0.38; 95% CI: 0.19–0.78), but was not associated with T2E negative PCa. Conclusions This study found suggestive evidence that use of CCBs is associated with reduced relative risks for higher Gleason score and T2E positive PCa. Future studies of PCa etiology should consider etiologic heterogeneity as PCa subtypes may develop through different causal pathways. PMID:27753122

Comparison of bootstrap approaches for estimation of uncertainties of DTI parameters.

PubMed

Chung, SungWon; Lu, Ying; Henry, Roland G

2006-11-01

Bootstrap is an empirical non-parametric statistical technique based on data resampling that has been used to quantify uncertainties of diffusion tensor MRI (DTI) parameters, useful in tractography and in assessing DTI methods. The current bootstrap method (repetition bootstrap) used for DTI analysis performs resampling within the data sharing common diffusion gradients, requiring multiple acquisitions for each diffusion gradient. Recently, wild bootstrap was proposed that can be applied without multiple acquisitions. In this paper, two new approaches are introduced called residual bootstrap and repetition bootknife. We show that repetition bootknife corrects for the large bias present in the repetition bootstrap method and, therefore, better estimates the standard errors. Like wild bootstrap, residual bootstrap is applicable to single acquisition scheme, and both are based on regression residuals (called model-based resampling). Residual bootstrap is based on the assumption that non-constant variance of measured diffusion-attenuated signals can be modeled, which is actually the assumption behind the widely used weighted least squares solution of diffusion tensor. The performances of these bootstrap approaches were compared in terms of bias, variance, and overall error of bootstrap-estimated standard error by Monte Carlo simulation. We demonstrate that residual bootstrap has smaller biases and overall errors, which enables estimation of uncertainties with higher accuracy. Understanding the properties of these bootstrap procedures will help us to choose the optimal approach for estimating uncertainties that can benefit hypothesis testing based on DTI parameters, probabilistic fiber tracking, and optimizing DTI methods.

A fast Monte Carlo EM algorithm for estimation in latent class model analysis with an application to assess diagnostic accuracy for cervical neoplasia in women with AGC

PubMed Central

Kang, Le; Carter, Randy; Darcy, Kathleen; Kauderer, James; Liao, Shu-Yuan

2013-01-01

In this article we use a latent class model (LCM) with prevalence modeled as a function of covariates to assess diagnostic test accuracy in situations where the true disease status is not observed, but observations on three or more conditionally independent diagnostic tests are available. A fast Monte Carlo EM (MCEM) algorithm with binary (disease) diagnostic data is implemented to estimate parameters of interest; namely, sensitivity, specificity, and prevalence of the disease as a function of covariates. To obtain standard errors for confidence interval construction of estimated parameters, the missing information principle is applied to adjust information matrix estimates. We compare the adjusted information matrix based standard error estimates with the bootstrap standard error estimates both obtained using the fast MCEM algorithm through an extensive Monte Carlo study. Simulation demonstrates that the adjusted information matrix approach estimates the standard error similarly with the bootstrap methods under certain scenarios. The bootstrap percentile intervals have satisfactory coverage probabilities. We then apply the LCM analysis to a real data set of 122 subjects from a Gynecologic Oncology Group (GOG) study of significant cervical lesion (S-CL) diagnosis in women with atypical glandular cells of undetermined significance (AGC) to compare the diagnostic accuracy of a histology-based evaluation, a CA-IX biomarker-based test and a human papillomavirus (HPV) DNA test. PMID:24163493

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

MSMB gene variant alters the association between prostate cancer and number of sexual partners

PubMed Central

Stott-Miller, Marni; Wright, Jonathan L.; Stanford, Janet L.

2014-01-01

Background Recently, a genetic variant (rs10993994) in the MSMB gene associated with prostate cancer (PCa) risk was shown to correlate with reduced prostate secretory protein of 94 amino acids (PSP94) levels. Although the biological activity of PSP94 is unclear, one of its hypothesized functions is to protect prostatic cells from pathogens. Number of sexual partners and a history of sexually transmitted infections (STIs) have been positively associated with PCa risk, and these associations may be related to pathogen-induced chronic prostatic inflammation. Based on these observations, we investigated whether MSMB genotype modifies the PCa-sexual history association. Methods We estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between number of sexual partners and PCa by fitting logistic regression models, stratified by MSMB genotype, and adjusted for age, family history of PCa, and PCa screening history among 1,239 incident cases and 1,232 controls. Results Compared with 1–4 female sexual partners, men with ≥15 such partners who carried the variant T allele of rs10993994 were at increased risk for PCa (OR=1.32; 95% CI, 1.03–1.71); no association was observed in men with the CC genotype (OR=1.03; 95% CI, 0.73–1.46; p=0.05 for interaction). Similar estimates were observed for total sexual partners (any T allele OR=1.37; 95% CI, 1.07–1.77; CC genotype OR=1.11; 95% CI, 0.79–1.55; p=0.06 for interaction). Conclusions The rs10993994 genotype in the MSMB gene modifies the association between number of sexual partners and PCa risk. These findings support a hypothesized biological mechanism whereby prostatic infection/inflammation may enhance risk of PCa. PMID:24037734

Detection of prostate cancer with multiparametric MRI (mpMRI): effect of dedicated reader education on accuracy and confidence of index and anterior cancer diagnosis

PubMed Central

Garcia-Reyes, Kirema; Passoni, Niccolò M.; Palmeri, Mark L.; Kauffman, Christopher R.; Choudhury, Kingshuk Roy; Polascik, Thomas J.; Gupta, Rajan T.

2015-01-01

Purpose To evaluate the impact of dedicated reader education on accuracy/confidence of peripheral zone index cancer and anterior prostate cancer (PCa) diagnosis with mpMRI; secondary aim was to assess the ability of readers to differentiate low-grade cancer (Gleason 6 or below) from high-grade cancer (Gleason 7+). Materials and methods Five blinded radiology fellows evaluated 31 total prostate mpMRIs in this IRB-approved, HIPAA-compliant, retrospective study for index lesion detection, confidence in lesion diagnosis (1–5 scale), and Gleason grade (Gleason 6 or lower vs. Gleason 7+). Following a dedicated education program, readers reinterpreted cases after a memory extinction period, blinded to initial reads. Reference standard was established combining whole mount histopathology with mpMRI findings by a board-certified radiologist with 5 years of prostate mpMRI experience. Results Index cancer detection: pre-education accuracy 74.2%; post-education accuracy 87.7% (p = 0.003). Confidence in index lesion diagnosis: pre-education 4.22 ± 1.04; post-education 3.75 ± 1.41 (p = 0.0004). Anterior PCa detection: pre-education accuracy 54.3%; post-education accuracy 94.3% (p = 0.001). Confidence in anterior PCa diagnosis: pre-education 3.22 ± 1.54; post-education 4.29 ± 0.83 (p = 0.0003). Gleason score accuracy: pre-education 54.8%; post-education 73.5% (p = 0.0005). Conclusions A dedicated reader education program on PCa detection with mpMRI was associated with a statistically significant increase in diagnostic accuracy of index cancer and anterior cancer detection as well as Gleason grade identification as compared to pre-education values. This was also associated with a significant increase in reader diagnostic confidence. This suggests that substantial interobserver variability in mpMRI interpretation can potentially be reduced with a focus on education and that this can occur over a fellowship training year. PMID:25034558

Competing-risks mortality after radiotherapy vs. observation for localized prostate cancer: a population-based study.

PubMed

Abdollah, Firas; Sun, Maxine; Schmitges, Jan; Thuret, Rodolphe; Tian, Zhe; Shariat, Shahrokh F; Briganti, Alberto; Jeldres, Claudio; Perrotte, Paul; Montorsi, Francesco; Karakiewicz, Pierre I

2012-09-01

Contemporary patients with localized prostate cancer (PCa) are more frequently treated with radiotherapy. However, there are limited data on the effect of this treatment on cancer-specific mortality (CSM). Our objective was to test the relationship between radiotherapy and survival in men with localized PCa and compare it with those treated with observation. A population-based cohort identified 68,797 men with cT1-T2 PCa treated with radiotherapy or observation between the years 1992 and 2005. Propensity-score matching was used to minimize potential bias related to treatment assignment. Competing-risks analyses tested the effect of treatment type (radiotherapy vs. observation) on CSM, after accounting to other-cause mortality. All analyses were carried out within PCa risk, baseline comorbidity status, and age groups. Radiotherapy was associated with more favorable 10-year CSM rates than observation in patients with high-risk PCa (8.8 vs. 14.4%, hazard ratio [HR]: 0.59, 95% confidence interval [CI]: 0.50-0.68). Conversely, the beneficial effect of radiotherapy on CSM was not evident in patients with low-intermediate risk PCa (3.7 vs. 4.1%, HR: 0.91, 95% CI: 0.80-1.04). Radiotherapy was beneficial in elderly patients (5.6 vs. 7.3%, HR: 0.70, 95% CI: 0.59-0.80). Moreover, it was associated with improved CSM rates among patients with no comorbidities (5.7 vs. 6.5%, HR: 0.81, 95% CI: 0.67-0.98), one comorbidity (4.6 vs. 6.0%, HR: 0.87, 95% CI: 0.75-0.99), and more than two comorbidities (4.2 vs. 5.0%, HR: 0.79, 95% CI: 0.65-0.96). Radiotherapy substantially improves CSM in patients with high-risk PCa, with little or no benefit in patients with low-/intermediate-risk PCa relative to observation. These findings must be interpreted within the context of the limitations of observational data. Copyright © 2012 Elsevier Inc. All rights reserved.

BPH and prostate cancer risk.

PubMed

Miah, Saiful; Catto, James

2014-04-01

With the exclusion of non-melanomatous skin malignancy, prostate cancer (PCa) is the second most prevalent cancer in men globally. It has been reported that the majority of men will develop benign prostatic hyperplasia (BPH) by the time they reach their 60s. Together, these prostatic diseases have a significant morbidity and mortality affecting over a billion men throughout the world. The risk of developing prostate cancer of men suffering BPH is one that has resulted in a healthy debate amongst the urological community. Here, we try to address this conundrum with clinical and basic science evidence. Data from an online search and contemporary data presented at international urological congresses was reviewed. BPH and PCa can be linked together at a molecular and cellular level on genetic, hormonal, and inflammatory platforms suggesting that these prostatic diseases have common pathophysiological driving factors. Epidemiological studies are weighted towards the presence of BPH having a greater risk for a man to develop PCa in his lifetime; however, a conclusion of causality cannot be confidently stated. The future workload healthcare practitioners will face regarding BPH, and PCa will substantially increase. Further basic science and large epidemiological studies using a global cohort of men are required prior to the urological community confidently counseling their patients with BPH with regards to their PCa risk.

Nonparametric estimation of benchmark doses in environmental risk assessment

PubMed Central

Piegorsch, Walter W.; Xiong, Hui; Bhattacharya, Rabi N.; Lin, Lizhen

2013-01-01

Summary An important statistical objective in environmental risk analysis is estimation of minimum exposure levels, called benchmark doses (BMDs), that induce a pre-specified benchmark response in a dose-response experiment. In such settings, representations of the risk are traditionally based on a parametric dose-response model. It is a well-known concern, however, that if the chosen parametric form is misspecified, inaccurate and possibly unsafe low-dose inferences can result. We apply a nonparametric approach for calculating benchmark doses, based on an isotonic regression method for dose-response estimation with quantal-response data (Bhattacharya and Kong, 2007). We determine the large-sample properties of the estimator, develop bootstrap-based confidence limits on the BMDs, and explore the confidence limits’ small-sample properties via a short simulation study. An example from cancer risk assessment illustrates the calculations. PMID:23914133

Procrustean rotation in concert with principal component analysis of molecular dynamics trajectories: Quantifying global and local differences between conformational samples.

PubMed

Oblinsky, Daniel G; Vanschouwen, Bryan M B; Gordon, Heather L; Rothstein, Stuart M

2009-12-14

Given the principal component analysis (PCA) of a molecular dynamics (MD) conformational trajectory for a model protein, we perform orthogonal Procrustean rotation to "best fit" the PCA squared-loading matrix to that of a target matrix computed for a related but different molecular system. The sum of squared deviations of the elements of the rotated matrix from those of the target, known as the error of fit (EOF), provides a quantitative measure of the dissimilarity between the two conformational samples. To estimate precision of the EOF, we perform bootstrap resampling of the molecular conformations within the trajectories, generating a distribution of EOF values for the system and target. The average EOF per variable is determined and visualized to ascertain where, locally, system and target sample properties differ. We illustrate this approach by analyzing MD trajectories for the wild-type and four selected mutants of the beta1 domain of protein G.

Procrustean rotation in concert with principal component analysis of molecular dynamics trajectories: Quantifying global and local differences between conformational samples

NASA Astrophysics Data System (ADS)

Oblinsky, Daniel G.; VanSchouwen, Bryan M. B.; Gordon, Heather L.; Rothstein, Stuart M.

2009-12-01

Given the principal component analysis (PCA) of a molecular dynamics (MD) conformational trajectory for a model protein, we perform orthogonal Procrustean rotation to "best fit" the PCA squared-loading matrix to that of a target matrix computed for a related but different molecular system. The sum of squared deviations of the elements of the rotated matrix from those of the target, known as the error of fit (EOF), provides a quantitative measure of the dissimilarity between the two conformational samples. To estimate precision of the EOF, we perform bootstrap resampling of the molecular conformations within the trajectories, generating a distribution of EOF values for the system and target. The average EOF per variable is determined and visualized to ascertain where, locally, system and target sample properties differ. We illustrate this approach by analyzing MD trajectories for the wild-type and four selected mutants of the β1 domain of protein G.

Practical no-gold-standard evaluation framework for quantitative imaging methods: application to lesion segmentation in positron emission tomography

PubMed Central

Jha, Abhinav K.; Mena, Esther; Caffo, Brian; Ashrafinia, Saeed; Rahmim, Arman; Frey, Eric; Subramaniam, Rathan M.

2017-01-01

Abstract. Recently, a class of no-gold-standard (NGS) techniques have been proposed to evaluate quantitative imaging methods using patient data. These techniques provide figures of merit (FoMs) quantifying the precision of the estimated quantitative value without requiring repeated measurements and without requiring a gold standard. However, applying these techniques to patient data presents several practical difficulties including assessing the underlying assumptions, accounting for patient-sampling-related uncertainty, and assessing the reliability of the estimated FoMs. To address these issues, we propose statistical tests that provide confidence in the underlying assumptions and in the reliability of the estimated FoMs. Furthermore, the NGS technique is integrated within a bootstrap-based methodology to account for patient-sampling-related uncertainty. The developed NGS framework was applied to evaluate four methods for segmenting lesions from F-Fluoro-2-deoxyglucose positron emission tomography images of patients with head-and-neck cancer on the task of precisely measuring the metabolic tumor volume. The NGS technique consistently predicted the same segmentation method as the most precise method. The proposed framework provided confidence in these results, even when gold-standard data were not available. The bootstrap-based methodology indicated improved performance of the NGS technique with larger numbers of patient studies, as was expected, and yielded consistent results as long as data from more than 80 lesions were available for the analysis. PMID:28331883

Clinical Significance of Retinoic Acid Receptor Beta Promoter Methylation in Prostate Cancer: A Meta-Analysis.

PubMed

Dou, MengMeng; Zhou, XueLiang; Fan, ZhiRui; Ding, XianFei; Li, LiFeng; Wang, ShuLing; Xue, Wenhua; Wang, Hui; Suo, Zhenhe; Deng, XiaoMing

2018-01-01

Retinoic acid receptor beta (RAR beta) is a retinoic acid receptor gene that has been shown to play key roles during multiple cancer processes, including cell proliferation, apoptosis, migration and invasion. Numerous studies have found that methylation of the RAR beta promoter contributed to the occurrence and development of malignant tumors. However, the connection between RAR beta promoter methylation and prostate cancer (PCa) remains unknown. This meta-analysis evaluated the clinical significance of RAR beta promoter methylation in PCa. We searched all published records relevant to RAR beta and PCa in a series of databases, including PubMed, Embase, Cochrane Library, ISI Web of Science and CNKI. The rates of RAR beta promoter methylation in the PCa and control groups (including benign prostatic hyperplasia and normal prostate tissues) were summarized. In addition, we evaluated the source region of available samples and the methods used to detect methylation. To compare the incidence and variation in RAR beta promoter methylation in PCa and non-PCa tissues, the odds ratio (OR) and 95% confidence interval (CI) were calculated accordingly. All the data were analyzed with the statistical software STATA 12.0. Based on the inclusion and exclusion criteria, 15 articles assessing 1,339 samples were further analyzed. These data showed that the RAR beta promoter methylation rates in PCa tissues were significantly higher than the rates in the non-PCa group (OR=21.65, 95% CI: 9.27-50.57). Subgroup analysis according to the source region of samples showed that heterogeneity in Asia was small (I2=0.0%, P=0.430). Additional subgroup analysis based on the method used to detect RAR beta promoter methylation showed that the heterogeneity detected by MSP (methylation-specific PCR) was relatively small (I2=11.3%, P=0.343). Although studies reported different rates for RAR beta promoter methylation in PCa tissues, the total analysis demonstrated that RAR beta promoter methylation may be correlated with PCa carcinogenesis and that the RAR beta gene is particularly susceptible. Additional studies with sufficient data are essential to further evaluate the clinical features and prognostic utility of RAR beta promoter methylation in PCa. © 2018 The Author(s). Published by S. Karger AG, Basel.

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates.

PubMed

LeDell, Erin; Petersen, Maya; van der Laan, Mark

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC.

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates

PubMed Central

Petersen, Maya; van der Laan, Mark

2015-01-01

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC. PMID:26279737

Sunlight exposure during leisure activities and risk of prostate cancer in Montréal, Canada, 2005-2009.

PubMed

Yu, Jennifer; Lavoué, Jérôme; Parent, Marie-Élise

2014-07-28

Prostate cancer (PCa) is the leading cause of cancer in men in many developed countries, but no modifiable risk factors have been identified. A handful of analytical studies have suggested a possible etiological role for sunlight exposure. We report here on the association between leisure-time sunlight exposure during adulthood and PCa risk in the context of a population-based case-control study. In all, 1,904 PCa cases were ascertained across Montreal French hospitals between 2005 and 2009. Concurrently, 1,962 population controls, frequency matched to cases by age (±5 years), were selected from the electoral list for French-speakers in Greater Montreal. Interviews elicited the frequency of engagement in any leisure activity during adulthood. This was used to derive cumulative sunlight exposure indices: a cumulative number of leisure activities events entailing sunlight exposure and a cumulative duration of sunlight exposure during leisure activities. Unconditional logistic regression was conducted to yield odds ratios (OR) and 95% confidence intervals (CI) for estimating the association between sunlight exposure indices and PCa risk, adjusting for age, ancestry, family history of PCa, PCa screening, education, solar protection, body mass index and physical activity. Compared with men in the upper quartile category for the number of sunlight exposure events, men never exposed during leisure time had an OR of 1.32 (95% CI: 0.82-2.14). ORs were 1.11, 0.91 and 1.00 for the first to the third quartiles of exposure, respectively. Similar results were observed for cumulative duration of exposure to sunlight, and by PCa aggressiveness. These findings provide little evidence of an association between sunlight exposure during leisure-time and PCa risk. Men with no sunlight exposure appeared at somewhat higher risks but none of the estimates achieved statistical significance.

Impact of Prostate Cancer Treatment on the Sexual Quality of Life for Men-Who-Have-Sex-with-Men.

PubMed

Lee, Tsz Kin; Handy, Ariel Baker; Kwan, Winkle; Oliffe, John Lindsay; Brotto, Lori Anne; Wassersug, Richard Joel; Dowsett, Gary Wayne

2015-12-01

With earlier prostate cancer (PCa) diagnosis and an increased focus on survivorship, post-treatment sexual quality of life (QoL) has become increasingly important. Research and validated instruments for sexual QoL assessment based on heterosexual samples have limited applicability for men-who-have-sex-with-men (MSM). We aimed to create a validated instrument for assessing sexual needs and concerns of MSM post-PCa treatment. Here we explore post-PCa treatment sexual concerns for a sample of MSM, as the first part of this multi-phase project. Individual semi-structured interviews were conducted with 16 MSM face-to-face or via Internet-based video conferencing. Participants were asked open-ended questions about their experiences of sexual QoL following PCa. Interviews were recorded, transcribed verbatim, uploaded to NVivo 8(TM) , and analyzed using qualitative methodology. We have conducted semi-structure qualitative interviews on 16 MSM who were treated for PCa. Focus was on post-treatment sexual concerns. The following themes were inductively derived: (i) erectile, urinary, ejaculation, and orgasmic dysfunctions; (ii) challenges to intimate relationships; and (iii) lack of MSM-specific oncological and psychosocial support for PCa survivorship. Sexual practices pre-treatment ranked in order of frequency were masturbation, oral sex, and anal sex, an ordering that prevailed post-treatment. Sexual QoL decreased with erectile, urinary, and ejaculation dysfunctions. Post-treatment orgasms were compromised. Some single men and men in non-monogamous relationships reported a loss of confidence or difficulty meeting other men post-treatment. Limited access to targeted oncological and psychosocial supports posed difficulties in coping with PCa for MSM. The negative impact on sexual QoL can be severe for MSM and requires targeted attention. Penile-vaginal intercourse and erectile function have been the primary focus of sexual research and rehabilitation for men with PCa, and do not adequately reflect the sexual practices of MSM. Our findings suggest that future research dedicated to MSM with PCa is needed to incorporate their sexual practices and preferences specifically into treatment decisions, and that targeted oncological and psychosocial support services are also warranted. © 2015 International Society for Sexual Medicine.

Alternative methods to evaluate trial level surrogacy.

PubMed

Abrahantes, Josè Cortiñas; Shkedy, Ziv; Molenberghs, Geert

2008-01-01

The evaluation and validation of surrogate endpoints have been extensively studied in the last decade. Prentice [1] and Freedman, Graubard and Schatzkin [2] laid the foundations for the evaluation of surrogate endpoints in randomized clinical trials. Later, Buyse et al. [5] proposed a meta-analytic methodology, producing different methods for different settings, which was further studied by Alonso and Molenberghs [9], in their unifying approach based on information theory. In this article, we focus our attention on the trial-level surrogacy and propose alternative procedures to evaluate such surrogacy measure, which do not pre-specify the type of association. A promising correction based on cross-validation is investigated. As well as the construction of confidence intervals for this measure. In order to avoid making assumption about the type of relationship between the treatment effects and its distribution, a collection of alternative methods, based on regression trees, bagging, random forests, and support vector machines, combined with bootstrap-based confidence interval and, should one wish, in conjunction with a cross-validation based correction, will be proposed and applied. We apply the various strategies to data from three clinical studies: in opthalmology, in advanced colorectal cancer, and in schizophrenia. The results obtained for the three case studies are compared; they indicate that using random forest or bagging models produces larger estimated values for the surrogacy measure, which are in general stabler and the confidence interval narrower than linear regression and support vector regression. For the advanced colorectal cancer studies, we even found the trial-level surrogacy is considerably different from what has been reported. In general the alternative methods are more computationally demanding, and specially the calculation of the confidence intervals, require more computational time that the delta-method counterpart. First, more flexible modeling techniques can be used, allowing for other type of association. Second, when no cross-validation-based correction is applied, overly optimistic trial-level surrogacy estimates will be found, thus cross-validation is highly recommendable. Third, the use of the delta method to calculate confidence intervals is not recommendable since it makes assumptions valid only in very large samples. It may also produce range-violating limits. We therefore recommend alternatives: bootstrap methods in general. Also, the information-theoretic approach produces comparable results with the bagging and random forest approaches, when cross-validation correction is applied. It is also important to observe that, even for the case in which the linear model might be a good option too, bagging methods perform well too, and their confidence intervals were more narrow.

Accounting for Uncertainty in Decision Analytic Models Using Rank Preserving Structural Failure Time Modeling: Application to Parametric Survival Models.

PubMed

Bennett, Iain; Paracha, Noman; Abrams, Keith; Ray, Joshua

2018-01-01

Rank Preserving Structural Failure Time models are one of the most commonly used statistical methods to adjust for treatment switching in oncology clinical trials. The method is often applied in a decision analytic model without appropriately accounting for additional uncertainty when determining the allocation of health care resources. The aim of the study is to describe novel approaches to adequately account for uncertainty when using a Rank Preserving Structural Failure Time model in a decision analytic model. Using two examples, we tested and compared the performance of the novel Test-based method with the resampling bootstrap method and with the conventional approach of no adjustment. In the first example, we simulated life expectancy using a simple decision analytic model based on a hypothetical oncology trial with treatment switching. In the second example, we applied the adjustment method on published data when no individual patient data were available. Mean estimates of overall and incremental life expectancy were similar across methods. However, the bootstrapped and test-based estimates consistently produced greater estimates of uncertainty compared with the estimate without any adjustment applied. Similar results were observed when using the test based approach on a published data showing that failing to adjust for uncertainty led to smaller confidence intervals. Both the bootstrapping and test-based approaches provide a solution to appropriately incorporate uncertainty, with the benefit that the latter can implemented by researchers in the absence of individual patient data. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Tablet potency of Tianeptine in coated tablets by near infrared spectroscopy: model optimisation, calibration transfer and confidence intervals.

PubMed

Boiret, Mathieu; Meunier, Loïc; Ginot, Yves-Michel

2011-02-20

A near infrared (NIR) method was developed for determination of tablet potency of active pharmaceutical ingredient (API) in a complex coated tablet matrix. The calibration set contained samples from laboratory and production scale batches. The reference values were obtained by high performance liquid chromatography (HPLC) and partial least squares (PLS) regression was used to establish a model. The model was challenged by calculating tablet potency of two external test sets. Root mean square errors of prediction were respectively equal to 2.0% and 2.7%. To use this model with a second spectrometer from the production field, a calibration transfer method called piecewise direct standardisation (PDS) was used. After the transfer, the root mean square error of prediction of the first test set was 2.4% compared to 4.0% without transferring the spectra. A statistical technique using bootstrap of PLS residuals was used to estimate confidence intervals of tablet potency calculations. This method requires an optimised PLS model, selection of the bootstrap number and determination of the risk. In the case of a chemical analysis, the tablet potency value will be included within the confidence interval calculated by the bootstrap method. An easy to use graphical interface was developed to easily determine if the predictions, surrounded by minimum and maximum values, are within the specifications defined by the regulatory organisation. Copyright © 2010 Elsevier B.V. All rights reserved.

Prebiopsy Multiparametric Magnetic Resonance Imaging for Prostate Cancer Diagnosis in Biopsy-naive Men with Suspected Prostate Cancer Based on Elevated Prostate-specific Antigen Values: Results from a Randomized Prospective Blinded Controlled Trial.

PubMed

Tonttila, Panu P; Lantto, Juha; Pääkkö, Eija; Piippo, Ulla; Kauppila, Saila; Lammentausta, Eveliina; Ohtonen, Pasi; Vaarala, Markku H

2016-03-01

Multiparametric magnetic resonance imaging (MP-MRI) may improve the detection of clinically significant prostate cancer (PCa). To compare MP-MRI transrectal ultrasound (TRUS)-fusion targeted biopsy with routine TRUS-guided random biopsy for overall and clinically significant PCa detection among patients with suspected PCa based on prostate-specific antigen (PSA) values. This institutional review board-approved, single-center, prospective, randomized controlled trial (April 2011 to December 2014) included 130 biopsy-naive patients referred for prostate biopsy based on PSA values (PSA <20 ng/ml or free-to-total PSA ratio ≤0.15 and PSA <10 ng/ml). Patients were randomized 1:1 to the MP-MRI or control group. Patients in the MP-MRI group underwent prebiopsy MP-MRI followed by 10- to 12-core TRUS-guided random biopsy and cognitive MRI/TRUS fusion targeted biopsy. The control group underwent TRUS-guided random biopsy alone. MP-MRI 3-T phased-array surface coil. The primary outcome was the number of patients with biopsy-proven PCa in the MP-MRI and control groups. Secondary outcome measures included the number of positive prostate biopsies and the proportion of clinically significant PCa in the MP-MRI and control groups. Between-group analyses were performed. Overall, 53 and 60 patients were evaluable in the MP-MRI and control groups, respectively. The overall PCa detection rate and the clinically significant cancer detection rate were similar between the MP-MRI and control groups, respectively (64% [34 of 53] vs 57% [34 of 60]; 7.5% difference [95% confidence interval (CI), -10 to 25], p=0.5, and 55% [29 of 53] vs 45% [27 of 60]; 9.7% difference [95% CI, -8.5 to 27], p=0.8). The PCa detection rate was higher than assumed during the planning of this single-center trial. MP-MRI/TRUS-fusion targeted biopsy did not improve PCa detection rate compared with TRUS-guided biopsy alone in patients with suspected PCa based on PSA values. In this randomized clinical trial, additional prostate magnetic resonance imaging (MRI) before prostate biopsy appeared to offer similar diagnostic accuracy compared with routine transrectal ultrasound-guided random biopsy in the diagnosis of prostate cancer. Similar numbers of cancers were detected with and without MRI. ClinicalTrials.gov identifier: NCT01357512. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Prostate cancer mortality reduction by prostate-specific antigen-based screening adjusted for nonattendance and contamination in the European Randomised Study of Screening for Prostate Cancer (ERSPC).

PubMed

Roobol, Monique J; Kerkhof, Melissa; Schröder, Fritz H; Cuzick, Jack; Sasieni, Peter; Hakama, Matti; Stenman, Ulf Hakan; Ciatto, Stefano; Nelen, Vera; Kwiatkowski, Maciej; Lujan, Marcos; Lilja, Hans; Zappa, Marco; Denis, Louis; Recker, Franz; Berenguer, Antonio; Ruutu, Mirja; Kujala, Paula; Bangma, Chris H; Aus, Gunnar; Tammela, Teuvo L J; Villers, Arnauld; Rebillard, Xavier; Moss, Sue M; de Koning, Harry J; Hugosson, Jonas; Auvinen, Anssi

2009-10-01

Prostate-specific antigen (PSA) based screening for prostate cancer (PCa) has been shown to reduce prostate specific mortality by 20% in an intention to screen (ITS) analysis in a randomised trial (European Randomised Study of Screening for Prostate Cancer [ERSPC]). This effect may be diluted by nonattendance in men randomised to the screening arm and contamination in men randomised to the control arm. To assess the magnitude of the PCa-specific mortality reduction after adjustment for nonattendance and contamination. We analysed the occurrence of PCa deaths during an average follow-up of 9 yr in 162,243 men 55-69 yr of age randomised in seven participating centres of the ERSPC. Centres were also grouped according to the type of randomisation (ie, before or after informed written consent). Nonattendance was defined as nonattending the initial screening round in ERSPC. The estimate of contamination was based on PSA use in controls in ERSPC Rotterdam. Relative risks (RRs) with 95% confidence intervals (CIs) were compared between an ITS analysis and analyses adjusting for nonattendance and contamination using a statistical method developed for this purpose. In the ITS analysis, the RR of PCa death in men allocated to the intervention arm relative to the control arm was 0.80 (95% CI, 0.68-0.96). Adjustment for nonattendance resulted in a RR of 0.73 (95% CI, 0.58-0.93), and additional adjustment for contamination using two different estimates led to estimated reductions of 0.69 (95% CI, 0.51-0.92) to 0.71 (95% CI, 0.55-0.93), respectively. Contamination data were obtained through extrapolation of single-centre data. No heterogeneity was found between the groups of centres. PSA screening reduces the risk of dying of PCa by up to 31% in men actually screened. This benefit should be weighed against a degree of overdiagnosis and overtreatment inherent in PCa screening.

Anthropometric Measures at Multiple Times Throughout Life and Prostate Cancer Diagnosis, Metastasis, and Death.

PubMed

Gerdtsson, Axel; Poon, Jessica B; Thorek, Daniel L; Mucci, Lorelei A; Evans, Michael J; Scardino, Peter; Abrahamsson, Per-Anders; Nilsson, Peter; Manjer, Jonas; Bjartell, Anders; Malm, Johan; Vickers, Andrew; Freedland, Stephen J; Lilja, Hans; Ulmert, David

2015-12-01

Previous studies of prostate cancer (PCa) risk and anthropometrics (ie, body measurements) were based on single measurements or obtained over limited time spans. To study the association between anthropometrics measured at multiple time points in life and their relation to later diagnosis, metastasis, or death from PCa. This case-control study includes 27 167 Swedish men enrolled in two population-based projects from 1974 to 1996. PCa diagnosis up to December 31, 2006, disease information, gestation time, and anthropometrics at birth, military conscript testing, and adulthood were collected. A total of 1355 PCa cases were matched with 5271 controls. Univariate conditional logistic regression was used to determine whether clinical diagnosis, metastasis, or PCa death was associated with low birth weight (weight <2500 g); with small size for gestational age; or with weight, length, or body mass index (BMI) at birth, adolescence (aged 16-22 yr), or early middle age (aged 44-50 yr). Apart from weight at adolescence, which was associated with an increased risk of PCa diagnosis (odds ratio [OR] per 5 kg: 1.05; 95% confidence interval [CI], 1.01-1.09; p=0.026), preadulthood measurements were not associated with any PCa end point. Adulthood parameters were not associated with diagnosis. In contrast, weight and BMI at early middle age were significantly associated with metastasis (OR per 5 kg: 1.13; 95% CI, 1.06-1.20; p<0.0001, and OR: 1.09; 95% CI, 1.05-1.14; p<0.0001) and death (OR per 5 kg: 1.11 (95% CI, 1.03-1.19; p=0.005, and OR: 1.08; 95% CI, 1.03-1.13; p=0.003), respectively. It remains unclear whether these results apply to men of nonwhite origin, to populations with active PCa screening programs, or to countries without socialized health care. The analyses of these large data sets demonstrate that significant effects of body characteristics (with links to metabolic syndrome) measured at early middle age are associated with PCa disease severity, metastatic progression, and outcome. Conversely, measurements at birth and adolescence are not associated with PCa prevalence or outcome. Increased weight and body mass index in adults is associated with a higher risk of prostate cancer metastasis and death. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Prediction of resource volumes at untested locations using simple local prediction models

USGS Publications Warehouse

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

Phylogenomics provides strong evidence for relationships of butterflies and moths

PubMed Central

Kawahara, Akito Y.; Breinholt, Jesse W.

2014-01-01

Butterflies and moths constitute some of the most popular and charismatic insects. Lepidoptera include approximately 160 000 described species, many of which are important model organisms. Previous studies on the evolution of Lepidoptera did not confidently place butterflies, and many relationships among superfamilies in the megadiverse clade Ditrysia remain largely uncertain. We generated a molecular dataset with 46 taxa, combining 33 new transcriptomes with 13 available genomes, transcriptomes and expressed sequence tags (ESTs). Using HaMStR with a Lepidoptera-specific core-orthologue set of single copy loci, we identified 2696 genes for inclusion into the phylogenomic analysis. Nucleotides and amino acids of the all-gene, all-taxon dataset yielded nearly identical, well-supported trees. Monophyly of butterflies (Papilionoidea) was strongly supported, and the group included skippers (Hesperiidae) and the enigmatic butterfly–moths (Hedylidae). Butterflies were placed sister to the remaining obtectomeran Lepidoptera, and the latter was grouped with greater than or equal to 87% bootstrap support. Establishing confident relationships among the four most diverse macroheteroceran superfamilies was previously challenging, but we recovered 100% bootstrap support for the following relationships: ((Geometroidea, Noctuoidea), (Bombycoidea, Lasiocampoidea)). We present the first robust, transcriptome-based tree of Lepidoptera that strongly contradicts historical placement of butterflies, and provide an evolutionary framework for genomic, developmental and ecological studies on this diverse insect order. PMID:24966318

Does behavioral bootstrapping boost weight control confidence?: a pilot study.

PubMed

Rohrer, James E; Vickers-Douglas, Kristin S; Stroebel, Robert J

2008-04-01

Since confidence is an important predictor of ability to lose weight, methods for increasing weight-control confidence are important. The purpose of this study was to test the relationship between short-term behavior changes ('behavioral bootstrapping') and change in weight-control confidence in a small prospective weight-loss project. Data were available from 38 patients who received an initial motivational interview and a follow-up visit. Body mass index at baseline ranged from 25.5 kg/m to 50.4 kg/m (mean = 35.8, median = 34.4). Independent variables were change in weight (measured in kilograms in the clinic), self-reported change in minutes of physical activity, age, sex, and marital status. Minutes of physical activity were assessed at baseline and after 30 days, using the following question, "How many minutes do you exercise per week (e.g. fast walking, biking, treadmill)?" Weights were measured in the clinic. Weight change was inversely correlated with change in confidence (p = 0.01). An increase in physical activity was associated with an increase in confidence (p = 0.01). Age, sex, and marital status were not related to change in confidence. Independent effects of weight change and physical activity were estimated using multiple linear regression analysis: b = -0.44, p = 0.04 for change in weight, and b = 0.02, p = 0.03 for change in physical activity (r = 0.28). Short-term changes in behavior (losing weight and exercising more) lead to increased weight-control confidence in primary-care patients.

Uncertainty estimation of Intensity-Duration-Frequency relationships: A regional analysis

NASA Astrophysics Data System (ADS)

Mélèse, Victor; Blanchet, Juliette; Molinié, Gilles

2018-03-01

We propose in this article a regional study of uncertainties in IDF curves derived from point-rainfall maxima. We develop two generalized extreme value models based on the simple scaling assumption, first in the frequentist framework and second in the Bayesian framework. Within the frequentist framework, uncertainties are obtained i) from the Gaussian density stemming from the asymptotic normality theorem of the maximum likelihood and ii) with a bootstrap procedure. Within the Bayesian framework, uncertainties are obtained from the posterior densities. We confront these two frameworks on the same database covering a large region of 100, 000 km2 in southern France with contrasted rainfall regime, in order to be able to draw conclusion that are not specific to the data. The two frameworks are applied to 405 hourly stations with data back to the 1980's, accumulated in the range 3 h-120 h. We show that i) the Bayesian framework is more robust than the frequentist one to the starting point of the estimation procedure, ii) the posterior and the bootstrap densities are able to better adjust uncertainty estimation to the data than the Gaussian density, and iii) the bootstrap density give unreasonable confidence intervals, in particular for return levels associated to large return period. Therefore our recommendation goes towards the use of the Bayesian framework to compute uncertainty.

A Pilot Investigation of the Relationship between Climate Variability and Milk Compounds under the Bootstrap Technique

PubMed Central

Marami Milani, Mohammad Reza; Hense, Andreas; Rahmani, Elham; Ploeger, Angelika

2015-01-01

This study analyzes the linear relationship between climate variables and milk components in Iran by applying bootstrapping to include and assess the uncertainty. The climate parameters, Temperature Humidity Index (THI) and Equivalent Temperature Index (ETI) are computed from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis (2002–2010). Milk data for fat, protein (measured on fresh matter bases), and milk yield are taken from 936,227 milk records for the same period, using cows fed by natural pasture from April to September. Confidence intervals for the regression model are calculated using the bootstrap technique. This method is applied to the original times series, generating statistically equivalent surrogate samples. As a result, despite the short time data and the related uncertainties, an interesting behavior of the relationships between milk compound and the climate parameters is visible. During spring only, a weak dependency of milk yield and climate variations is obvious, while fat and protein concentrations show reasonable correlations. In summer, milk yield shows a similar level of relationship with ETI, but not with temperature and THI. We suggest this methodology for studies in the field of the impacts of climate change and agriculture, also environment and food with short-term data. PMID:28231215

Robust Inference of Risks of Large Portfolios

PubMed Central

Fan, Jianqing; Han, Fang; Liu, Han; Vickers, Byron

2016-01-01

We propose a bootstrap-based robust high-confidence level upper bound (Robust H-CLUB) for assessing the risks of large portfolios. The proposed approach exploits rank-based and quantile-based estimators, and can be viewed as a robust extension of the H-CLUB procedure (Fan et al., 2015). Such an extension allows us to handle possibly misspecified models and heavy-tailed data, which are stylized features in financial returns. Under mixing conditions, we analyze the proposed approach and demonstrate its advantage over H-CLUB. We further provide thorough numerical results to back up the developed theory, and also apply the proposed method to analyze a stock market dataset. PMID:27818569

A bootstrap based space-time surveillance model with an application to crime occurrences

NASA Astrophysics Data System (ADS)

Kim, Youngho; O'Kelly, Morton

2008-06-01

This study proposes a bootstrap-based space-time surveillance model. Designed to find emerging hotspots in near-real time, the bootstrap based model is characterized by its use of past occurrence information and bootstrap permutations. Many existing space-time surveillance methods, using population at risk data to generate expected values, have resulting hotspots bounded by administrative area units and are of limited use for near-real time applications because of the population data needed. However, this study generates expected values for local hotspots from past occurrences rather than population at risk. Also, bootstrap permutations of previous occurrences are used for significant tests. Consequently, the bootstrap-based model, without the requirement of population at risk data, (1) is free from administrative area restriction, (2) enables more frequent surveillance for continuously updated registry database, and (3) is readily applicable to criminology and epidemiology surveillance. The bootstrap-based model performs better for space-time surveillance than the space-time scan statistic. This is shown by means of simulations and an application to residential crime occurrences in Columbus, OH, year 2000.

Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI.

PubMed

Song, Yang; Zhang, Yu-Dong; Yan, Xu; Liu, Hui; Zhou, Minxiong; Hu, Bingwen; Yang, Guang

2018-04-16

Deep learning is the most promising methodology for automatic computer-aided diagnosis of prostate cancer (PCa) with multiparametric MRI (mp-MRI). To develop an automatic approach based on deep convolutional neural network (DCNN) to classify PCa and noncancerous tissues (NC) with mp-MRI. Retrospective. In all, 195 patients with localized PCa were collected from a PROSTATEx database. In total, 159/17/19 patients with 444/48/55 observations (215/23/23 PCas and 229/25/32 NCs) were randomly selected for training/validation/testing, respectively. T 2 -weighted, diffusion-weighted, and apparent diffusion coefficient images. A radiologist manually labeled the regions of interest of PCas and NCs and estimated the Prostate Imaging Reporting and Data System (PI-RADS) scores for each region. Inspired by VGG-Net, we designed a patch-based DCNN model to distinguish between PCa and NCs based on a combination of mp-MRI data. Additionally, an enhanced prediction method was used to improve the prediction accuracy. The performance of DCNN prediction was tested using a receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Moreover, the predicted result was compared with the PI-RADS score to evaluate its clinical value using decision curve analysis. Two-sided Wilcoxon signed-rank test with statistical significance set at 0.05. The DCNN produced excellent diagnostic performance in distinguishing between PCa and NC for testing datasets with an AUC of 0.944 (95% confidence interval: 0.876-0.994), sensitivity of 87.0%, specificity of 90.6%, PPV of 87.0%, and NPV of 90.6%. The decision curve analysis revealed that the joint model of PI-RADS and DCNN provided additional net benefits compared with the DCNN model and the PI-RADS scheme. The proposed DCNN-based model with enhanced prediction yielded high performance in statistical analysis, suggesting that DCNN could be used in computer-aided diagnosis (CAD) for PCa classification. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Deep learning ensemble with asymptotic techniques for oscillometric blood pressure estimation.

PubMed

Lee, Soojeong; Chang, Joon-Hyuk

2017-11-01

This paper proposes a deep learning based ensemble regression estimator with asymptotic techniques, and offers a method that can decrease uncertainty for oscillometric blood pressure (BP) measurements using the bootstrap and Monte-Carlo approach. While the former is used to estimate SBP and DBP, the latter attempts to determine confidence intervals (CIs) for SBP and DBP based on oscillometric BP measurements. This work originally employs deep belief networks (DBN)-deep neural networks (DNN) to effectively estimate BPs based on oscillometric measurements. However, there are some inherent problems with these methods. First, it is not easy to determine the best DBN-DNN estimator, and worthy information might be omitted when selecting one DBN-DNN estimator and discarding the others. Additionally, our input feature vectors, obtained from only five measurements per subject, represent a very small sample size; this is a critical weakness when using the DBN-DNN technique and can cause overfitting or underfitting, depending on the structure of the algorithm. To address these problems, an ensemble with an asymptotic approach (based on combining the bootstrap with the DBN-DNN technique) is utilized to generate the pseudo features needed to estimate the SBP and DBP. In the first stage, the bootstrap-aggregation technique is used to create ensemble parameters. Afterward, the AdaBoost approach is employed for the second-stage SBP and DBP estimation. We then use the bootstrap and Monte-Carlo techniques in order to determine the CIs based on the target BP estimated using the DBN-DNN ensemble regression estimator with the asymptotic technique in the third stage. The proposed method can mitigate the estimation uncertainty such as large the standard deviation of error (SDE) on comparing the proposed DBN-DNN ensemble regression estimator with the DBN-DNN single regression estimator, we identify that the SDEs of the SBP and DBP are reduced by 0.58 and 0.57  mmHg, respectively. These indicate that the proposed method actually enhances the performance by 9.18% and 10.88% compared with the DBN-DNN single estimator. The proposed methodology improves the accuracy of BP estimation and reduces the uncertainty for BP estimation. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of parametric and bootstrap method in bioequivalence test.

PubMed

Ahn, Byung-Jin; Yim, Dong-Seok

2009-10-01

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.

Comparison of Parametric and Bootstrap Method in Bioequivalence Test

PubMed Central

Ahn, Byung-Jin

2009-01-01

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption. PMID:19915699

One- and two-stage Arrhenius models for pharmaceutical shelf life prediction.

PubMed

Fan, Zhewen; Zhang, Lanju

2015-01-01

One of the most challenging aspects of the pharmaceutical development is the demonstration and estimation of chemical stability. It is imperative that pharmaceutical products be stable for two or more years. Long-term stability studies are required to support such shelf life claim at registration. However, during drug development to facilitate formulation and dosage form selection, an accelerated stability study with stressed storage condition is preferred to quickly obtain a good prediction of shelf life under ambient storage conditions. Such a prediction typically uses Arrhenius equation that describes relationship between degradation rate and temperature (and humidity). Existing methods usually rely on the assumption of normality of the errors. In addition, shelf life projection is usually based on confidence band of a regression line. However, the coverage probability of a method is often overlooked or under-reported. In this paper, we introduce two nonparametric bootstrap procedures for shelf life estimation based on accelerated stability testing, and compare them with a one-stage nonlinear Arrhenius prediction model. Our simulation results demonstrate that one-stage nonlinear Arrhenius method has significant lower coverage than nominal levels. Our bootstrap method gave better coverage and led to a shelf life prediction closer to that based on long-term stability data.

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications

PubMed Central

Chaibub Neto, Elias

2015-01-01

In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson’s sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling. PMID:26125965

Bootstrapping Least Squares Estimates in Biochemical Reaction Networks

PubMed Central

Linder, Daniel F.

2015-01-01

The paper proposes new computational methods of computing confidence bounds for the least squares estimates (LSEs) of rate constants in mass-action biochemical reaction network and stochastic epidemic models. Such LSEs are obtained by fitting the set of deterministic ordinary differential equations (ODEs), corresponding to the large volume limit of a reaction network, to network’s partially observed trajectory treated as a continuous-time, pure jump Markov process. In the large volume limit the LSEs are asymptotically Gaussian, but their limiting covariance structure is complicated since it is described by a set of nonlinear ODEs which are often ill-conditioned and numerically unstable. The current paper considers two bootstrap Monte-Carlo procedures, based on the diffusion and linear noise approximations for pure jump processes, which allow one to avoid solving the limiting covariance ODEs. The results are illustrated with both in-silico and real data examples from the LINE 1 gene retrotranscription model and compared with those obtained using other methods. PMID:25898769

Polymorphisms in nucleotide excision repair genes and risk of primary prostate cancer in Chinese Han populations.

PubMed

Wang, Mengyun; Li, Qiaoxin; Gu, Chengyuan; Zhu, Yao; Yang, Yajun; Wang, Jiucun; Jin, Li; He, Jing; Ye, Dingwei; Wei, Qingyi

2017-04-11

Genetic variants of nucleotide excision repair (NER) genes have been extensively investigated for their roles in the development of prostate cancer (PCa); however, the published results have been inconsistent. In a hospital-based case-control study of 1,004 PCa cases and 1,055 cancer-free controls, we genotyped eight potentially functional single nucleotide polymorphisms (SNPs) of NER genes (i.e., XPC, rs2228001 T>G and rs1870134 G>C; XPD, rs13181 T>G and rs238406 G>T; XPG, rs1047768 T>C, rs751402 C>T, and rs17655 G>C; and XPF, rs2276464 G>C) and assessed their associations with risk of PCa by using logistic regression analysis. Among these eight SNPs investigated, only XPC rs1870134 CG/CC variant genotypes were associated with a decreased risk of prostate cancer under a dominant genetic model (adjusted odds ratio [OR] = 0.77, 95% confidence interval [CI] = 0.64-1.91, P = 0.003). Phenotype-genotype analysis also suggested that the XPC rs1870134 CG/CC variant genotypes were associated with significantly decreased expression levels of XPC mRNA in a mix population of different ethnicities. These findings suggested that XPC SNPs may contribute to risk of PCa in Eastern Chinese men.

Impact of Sampling Density on the Extent of HIV Clustering

PubMed Central

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor

2014-01-01

Abstract Identifying and monitoring HIV clusters could be useful in tracking the leading edge of HIV transmission in epidemics. Currently, greater specificity in the definition of HIV clusters is needed to reduce confusion in the interpretation of HIV clustering results. We address sampling density as one of the key aspects of HIV cluster analysis. The proportion of viral sequences in clusters was estimated at sampling densities from 1.0% to 70%. A set of 1,248 HIV-1C env gp120 V1C5 sequences from a single community in Botswana was utilized in simulation studies. Matching numbers of HIV-1C V1C5 sequences from the LANL HIV Database were used as comparators. HIV clusters were identified by phylogenetic inference under bootstrapped maximum likelihood and pairwise distance cut-offs. Sampling density below 10% was associated with stochastic HIV clustering with broad confidence intervals. HIV clustering increased linearly at sampling density >10%, and was accompanied by narrowing confidence intervals. Patterns of HIV clustering were similar at bootstrap thresholds 0.7 to 1.0, but the extent of HIV clustering decreased with higher bootstrap thresholds. The origin of sampling (local concentrated vs. scattered global) had a substantial impact on HIV clustering at sampling densities ≥10%. Pairwise distances at 10% were estimated as a threshold for cluster analysis of HIV-1 V1C5 sequences. The node bootstrap support distribution provided additional evidence for 10% sampling density as the threshold for HIV cluster analysis. The detectability of HIV clusters is substantially affected by sampling density. A minimal genotyping density of 10% and sampling density of 50–70% are suggested for HIV-1 V1C5 cluster analysis. PMID:25275430

Multiparametric dynamic contrast-enhanced ultrasound imaging of prostate cancer.

PubMed

Wildeboer, Rogier R; Postema, Arnoud W; Demi, Libertario; Kuenen, Maarten P J; Wijkstra, Hessel; Mischi, Massimo

2017-08-01

The aim of this study is to improve the accuracy of dynamic contrast-enhanced ultrasound (DCE-US) for prostate cancer (PCa) localization by means of a multiparametric approach. Thirteen different parameters related to either perfusion or dispersion were extracted pixel-by-pixel from 45 DCE-US recordings in 19 patients referred for radical prostatectomy. Multiparametric maps were retrospectively produced using a Gaussian mixture model algorithm. These were subsequently evaluated on their pixel-wise performance in classifying 43 benign and 42 malignant histopathologically confirmed regions of interest, using a prostate-based leave-one-out procedure. The combination of the spatiotemporal correlation (r), mean transit time (μ), curve skewness (κ), and peak time (PT) yielded an accuracy of 81% ± 11%, which was higher than the best performing single parameters: r (73%), μ (72%), and wash-in time (72%). The negative predictive value increased to 83% ± 16% from 70%, 69% and 67%, respectively. Pixel inclusion based on the confidence level boosted these measures to 90% with half of the pixels excluded, but without disregarding any prostate or region. Our results suggest multiparametric DCE-US analysis might be a useful diagnostic tool for PCa, possibly supporting future targeting of biopsies or therapy. Application in other types of cancer can also be foreseen. • DCE-US can be used to extract both perfusion and dispersion-related parameters. • Multiparametric DCE-US performs better in detecting PCa than single-parametric DCE-US. • Multiparametric DCE-US might become a useful tool for PCa localization.

Phylogenomics provides strong evidence for relationships of butterflies and moths.

PubMed

Kawahara, Akito Y; Breinholt, Jesse W

2014-08-07

Butterflies and moths constitute some of the most popular and charismatic insects. Lepidoptera include approximately 160 000 described species, many of which are important model organisms. Previous studies on the evolution of Lepidoptera did not confidently place butterflies, and many relationships among superfamilies in the megadiverse clade Ditrysia remain largely uncertain. We generated a molecular dataset with 46 taxa, combining 33 new transcriptomes with 13 available genomes, transcriptomes and expressed sequence tags (ESTs). Using HaMStR with a Lepidoptera-specific core-orthologue set of single copy loci, we identified 2696 genes for inclusion into the phylogenomic analysis. Nucleotides and amino acids of the all-gene, all-taxon dataset yielded nearly identical, well-supported trees. Monophyly of butterflies (Papilionoidea) was strongly supported, and the group included skippers (Hesperiidae) and the enigmatic butterfly-moths (Hedylidae). Butterflies were placed sister to the remaining obtectomeran Lepidoptera, and the latter was grouped with greater than or equal to 87% bootstrap support. Establishing confident relationships among the four most diverse macroheteroceran superfamilies was previously challenging, but we recovered 100% bootstrap support for the following relationships: ((Geometroidea, Noctuoidea), (Bombycoidea, Lasiocampoidea)). We present the first robust, transcriptome-based tree of Lepidoptera that strongly contradicts historical placement of butterflies, and provide an evolutionary framework for genomic, developmental and ecological studies on this diverse insect order. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Assessing Mediational Models: Testing and Interval Estimation for Indirect Effects.

PubMed

Biesanz, Jeremy C; Falk, Carl F; Savalei, Victoria

2010-08-06

Theoretical models specifying indirect or mediated effects are common in the social sciences. An indirect effect exists when an independent variable's influence on the dependent variable is mediated through an intervening variable. Classic approaches to assessing such mediational hypotheses ( Baron & Kenny, 1986 ; Sobel, 1982 ) have in recent years been supplemented by computationally intensive methods such as bootstrapping, the distribution of the product methods, and hierarchical Bayesian Markov chain Monte Carlo (MCMC) methods. These different approaches for assessing mediation are illustrated using data from Dunn, Biesanz, Human, and Finn (2007). However, little is known about how these methods perform relative to each other, particularly in more challenging situations, such as with data that are incomplete and/or nonnormal. This article presents an extensive Monte Carlo simulation evaluating a host of approaches for assessing mediation. We examine Type I error rates, power, and coverage. We study normal and nonnormal data as well as complete and incomplete data. In addition, we adapt a method, recently proposed in statistical literature, that does not rely on confidence intervals (CIs) to test the null hypothesis of no indirect effect. The results suggest that the new inferential method-the partial posterior p value-slightly outperforms existing ones in terms of maintaining Type I error rates while maximizing power, especially with incomplete data. Among confidence interval approaches, the bias-corrected accelerated (BC a ) bootstrapping approach often has inflated Type I error rates and inconsistent coverage and is not recommended; In contrast, the bootstrapped percentile confidence interval and the hierarchical Bayesian MCMC method perform best overall, maintaining Type I error rates, exhibiting reasonable power, and producing stable and accurate coverage rates.

Estimating bias in causes of death ascertainment in the Finnish Randomized Study of Screening for Prostate Cancer.

PubMed

Kilpeläinen, Tuomas P; Mäkinen, Tuukka; Karhunen, Pekka J; Aro, Jussi; Lahtela, Jorma; Taari, Kimmo; Talala, Kirsi; Tammela, Teuvo L J; Auvinen, Anssi

2016-12-01

Precise cause of death (CoD) ascertainment is crucial in any cancer screening trial to avoid bias from misclassification due to excessive recording of diagnosed cancer as a CoD in death certificates instead of non-cancer disease that actually caused death. We estimated whether there was bias in CoD determination between screening (SA) and control arms (CA) in a population-based prostate cancer (PCa) screening trial. Our trial is the largest component of the European Randomized Study of Screening for Prostate Cancer with more than 80,000 men. Randomly selected deaths in men with PCa (N=442/2568 cases, 17.2%) were reviewed by an independent CoD committee. Median follow-up was 16.8 years in both arms. Overdiagnosis of PCa was present in the SA as the risk ratio for PCa incidence was 1.19 (95% confidence interval (CI) 1.14-1.24). The hazard ratio (HR) for PCa mortality was 0.94 (95%CI 0.82-1.08) in favor of the SA. Agreement with official CoD registry was 94.6% (κ=0.88) in the SA and 95.4% (κ=0.91) in the CA. Altogether 14 PCa deaths were estimated as false-positive in both arms and exclusion of these resulted in HR 0.92 (95% CI 0.80-1.06). A small differential misclassification bias in ascertainment of CoD was present, most likely due to attribution bias (overdiagnosis in the SA). Maximum precision in CoD ascertainment can only be achieved with independent review of all deaths in the diseased population. However, this is cumbersome and expensive and may provide little benefit compared to random sampling. Copyright © 2016 Elsevier Ltd. All rights reserved.

Detection of counterfeit electronic components through ambient mass spectrometry and chemometrics.

PubMed

Pfeuffer, Kevin P; Caldwell, Jack; Shelley, Jake T; Ray, Steven J; Hieftje, Gary M

2014-09-21

In the last several years, illicit electronic components have been discovered in the inventories of several distributors and even installed in commercial and military products. Illicit or counterfeit electronic components include a broad category of devices that can range from the correct unit with a more recent date code to lower-specification or non-working systems with altered names, manufacturers and date codes. Current methodologies for identification of counterfeit electronics rely on visual microscopy by expert users and, while effective, are very time-consuming. Here, a plasma-based ambient desorption/ionization source, the flowing atmospheric pressure afterglow (FAPA) is used to generate a mass-spectral fingerprint from the surface of a variety of discrete electronic integrated circuits (ICs). Chemometric methods, specifically principal component analysis (PCA) and the bootstrapped error-adjusted single-sample technique (BEAST), are used successfully to differentiate between genuine and counterfeit ICs. In addition, chemical and physical surface-removal techniques are explored and suggest which surface-altering techniques were utilized by counterfeiters.

Association between age-related reductions in testosterone and risk of prostate cancer-An analysis of patients' data with prostatic diseases.

PubMed

Wang, Kai; Chen, Xinguang; Bird, Victoria Y; Gerke, Travis A; Manini, Todd M; Prosperi, Mattia

2017-11-01

The relationship between serum total testosterone and prostate cancer (PCa) risk is controversial. The hypothesis that faster age-related reduction in testosterone is linked with increased PCa risk remains untested. We conducted our study at a tertiary-level hospital in southeast of the USA, and derived data from the Medical Registry Database of individuals that were diagnosed of any prostate-related disease from 2001 to 2015. Cases were those diagnosed of PCa and had one or more measurements of testosterone prior to PCa diagnosis. Controls were those without PCa and had one or more testosterone measurements. Multivariable logistic regression models for PCa risk of absolute levels (one-time measure and 5-year average) and annual change in testosterone were respectively constructed. Among a total of 1,559 patients, 217 were PCa cases, and neither one-time measure nor 5-year average of testosterone was found to be significantly associated with PCa risk. Among the 379 patients with two or more testosterone measurements, 27 were PCa cases. For every 10 ng/dL increment in annual reduction of testosterone, the risk of PCa would increase by 14% [adjusted odds ratio, 1.14; 95% confidence interval (CI), 1.03-1.25]. Compared to patients with a relatively stable testosterone, patients with an annual testosterone reduction of more than 30 ng/dL had 5.03 [95% CI: 1.53, 16.55] fold increase in PCa risk. This implies a faster age-related reduction in, but not absolute level of serum total testosterone as a risk factor for PCa. Further longitudinal studies are needed to confirm this finding. © 2017 UICC.

Coastal water optical properties from four Southeast Asian coastal environments ranging from relatively pristine to heavily impacted

NASA Astrophysics Data System (ADS)

Osburn, C. L.; Boyd, T. J.; Anastasiou, C. J.; Thao, P. T. P.; Reid, J. S.

2016-02-01

Optical measurements (absorbance, EEM fluorescence, remote sensing reflectance) and concurrently-collected sensor-based data (CDOM, chlorophyll-a, salinity, turbidity, and temperature) were used to link optical properties to water mass characteristics. Data and samples were collected during four field events in the Philippines (SEP2011, SEP2012 - transects from Manila to Palawan Island), Thailand (MAR2012 - Pattaya Beach area) and Vietnam (MAR2012 - Nha Trang and Ha Long Bay). EEM fluorescence spectra from each site were modeled using PARAFAC to identify representative fluorophores. Remote sensing reflectance was modeled using PCA, determining spectral loadings showing variation in samples from each site. These synthesized model data and sensor-based measurements were collated and ordinated using PCA to determine if optical properties could be linked to water quality and biogeochemical measures. PCA models at each site showed stations nearest to the coastline falling near or outside 95% confidence regions. Initial results indicate protein-like fluorophores were found in lower salinity waters and more heavily-impacted regions (Manila Bay - Philippines, Nha Trang River - Vietnam, Bang Pakong River - Thailand). Spectral slope and an component loading from remote sensing reflectance appeared to co-vary with sensor-derived CDOM fluorescence. Results from intra- and inter-site comparisons and linkages to biogeochemical parameters will be presented.

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

PubMed

Wang, Zuozhen

2018-01-01

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

Trichomonas vaginalis infection and risk of prostate cancer: associations by disease aggressiveness and race/ethnicity in the PLCO Trial.

PubMed

Marous, Miguelle; Huang, Wen-Yi; Rabkin, Charles S; Hayes, Richard B; Alderete, John F; Rosner, Bernard; Grubb, Robert L; Winter, Anke C; Sutcliffe, Siobhan

2017-08-01

Results from previous sero-epidemiologic studies of Trichomonas vaginalis infection and prostate cancer (PCa) support a positive association between this sexually transmitted infection and aggressive PCa. However, findings from previous studies are not entirely consistent, and only one has investigated the possible relation between T. vaginalis seropositivity and PCa in African-American men who are at highest risk of both infection and PCa. Therefore, we examined this possible relation in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, including separate analyses for aggressive PCa and African-American men. We included a sample of participants from a previous nested case-control study of PCa, as well as all additional Caucasian, aggressive, and African-American cases diagnosed since the previous study (total n = 438 Gleason 7 Caucasian cases, 487 more advanced Caucasian cases (≥Gleason 8 or stage III/IV), 201 African-American cases, and 1216 controls). We tested baseline sera for T. vaginalis antibodies. No associations were observed for risk of Gleason 7 (odds ratio (OR) = 0.87, 95% confidence interval (CI) 0.55-1.37) or more advanced (OR = 0.90, 95% CI 0.58-1.38) PCa in Caucasian men, or for risk of any PCa (OR = 1.06, 95% CI 0.67-1.68) in African-American men. Our findings do not support an association between T. vaginalis infection and PCa.

Performance of Bootstrap MCEWMA: Study case of Sukuk Musyarakah data

NASA Astrophysics Data System (ADS)

Safiih, L. Muhamad; Hila, Z. Nurul

2014-07-01

Sukuk Musyarakah is one of several instruments of Islamic bond investment in Malaysia, where the form of this sukuk is actually based on restructuring the conventional bond to become a Syariah compliant bond. The Syariah compliant is based on prohibition of any influence of usury, benefit or fixed return. Despite of prohibition, daily returns of sukuk are non-fixed return and in statistic, the data of sukuk returns are said to be a time series data which is dependent and autocorrelation distributed. This kind of data is a crucial problem whether in statistical and financing field. Returns of sukuk can be statistically viewed by its volatility, whether it has high volatility that describing the dramatically change of price and categorized it as risky bond or else. However, this crucial problem doesn't get serious attention among researcher compared to conventional bond. In this study, MCEWMA chart in Statistical Process Control (SPC) is mainly used to monitor autocorrelated data and its application on daily returns of securities investment data has gained widespread attention among statistician. However, this chart has always been influence by inaccurate estimation, whether on base model or its limit, due to produce large error and high of probability of signalling out-of-control process for false alarm study. To overcome this problem, a bootstrap approach used in this study, by hybridise it on MCEWMA base model to construct a new chart, i.e. Bootstrap MCEWMA (BMCEWMA) chart. The hybrid model, BMCEWMA, will be applied to daily returns of sukuk Musyarakah for Rantau Abang Capital Bhd. The performance of BMCEWMA base model showed that its more effective compare to real model, MCEWMA based on smaller error estimation, shorter the confidence interval and smaller false alarm. In other word, hybrid chart reduce the variability which shown by smaller error and false alarm. It concludes that the application of BMCEWMA is better than MCEWMA.

A Bootstrap Generalization of Modified Parallel Analysis for IRT Dimensionality Assessment

ERIC Educational Resources Information Center

Finch, Holmes; Monahan, Patrick

2008-01-01

This article introduces a bootstrap generalization to the Modified Parallel Analysis (MPA) method of test dimensionality assessment using factor analysis. This methodology, based on the use of Marginal Maximum Likelihood nonlinear factor analysis, provides for the calculation of a test statistic based on a parametric bootstrap using the MPA…

The impact of socioeconomic status on stage specific prostate cancer survival and mortality before and after introduction of PSA test in Finland.

PubMed

Seikkula, Heikki A; Kaipia, Antti J; Ryynänen, Heidi; Seppä, Karri; Pitkäniemi, Janne M; Malila, Nea K; Boström, Peter J

2018-03-01

Socioeconomic status (SES) has an impact on prostate cancer (PCa) outcomes. Men with high SES have higher incidence and lower mortality of PCa versus lower SES males. PCa cases diagnosed in Finland in 1985-2014 (N = 95,076) were identified from the Finnish Cancer Registry. Information on education level (EL) was obtained from Statistics Finland. EL was assessed with three-tiered scale: basic, upper secondary and higher education. PCa stage at diagnosis was defined as localized, metastatic or unknown. Years of diagnosis 1985-1994 were defined as pre-PSA period and thereafter as post-PSA period. We report PCa-specific survival (PCSS) and relative risks (RR) for PCa specific mortality (PCSM) among cancer cases in Finland, where healthcare is 100% publicly reimbursed and inequality in healthcare services low. Men with higher EL had markedly better 10-year PCSS: 68 versus 63% in 1985-1994 and 90 versus 85% in 1995-2004 compared to basic EL in localized PCa. The RR for PCSM among men with localized PCa and higher EL compared to basic EL was 0.76(95%confidence interval (CI) 0.66-0.88) in 1985-1994 and 0.61(95%CI 0.53-0.70) in 1995-2004. Variation in PCSS and PCSM between EL categories was evident in metastatic PCa, too. The difference in PCSM between EL categories was larger in the first 10-year post-PSA period than before that but decreased thereafter in localized PCa, suggesting PSA testing became earlier popular among men with high EL. In summary, higher SES/EL benefit PCa survival both in local and disseminated disease and the effect of EL was more pronounced in early post-PSA period. © 2017 UICC.

Performance of Bootstrapping Approaches To Model Test Statistics and Parameter Standard Error Estimation in Structural Equation Modeling.

ERIC Educational Resources Information Center

Nevitt, Jonathan; Hancock, Gregory R.

2001-01-01

Evaluated the bootstrap method under varying conditions of nonnormality, sample size, model specification, and number of bootstrap samples drawn from the resampling space. Results for the bootstrap suggest the resampling-based method may be conservative in its control over model rejections, thus having an impact on the statistical power associated…

A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling.

PubMed

Klein, Eric A; Cooperberg, Matthew R; Magi-Galluzzi, Cristina; Simko, Jeffry P; Falzarano, Sara M; Maddala, Tara; Chan, June M; Li, Jianbo; Cowan, Janet E; Tsiatis, Athanasios C; Cherbavaz, Diana B; Pelham, Robert J; Tenggara-Hunter, Imelda; Baehner, Frederick L; Knezevic, Dejan; Febbo, Phillip G; Shak, Steven; Kattan, Michael W; Lee, Mark; Carroll, Peter R

2014-09-01

Prostate tumor heterogeneity and biopsy undersampling pose challenges to accurate, individualized risk assessment for men with localized disease. To identify and validate a biopsy-based gene expression signature that predicts clinical recurrence, prostate cancer (PCa) death, and adverse pathology. Gene expression was quantified by reverse transcription-polymerase chain reaction for three studies-a discovery prostatectomy study (n=441), a biopsy study (n=167), and a prospectively designed, independent clinical validation study (n=395)-testing retrospectively collected needle biopsies from contemporary (1997-2011) patients with low to intermediate clinical risk who were candidates for active surveillance (AS). The main outcome measures defining aggressive PCa were clinical recurrence, PCa death, and adverse pathology at prostatectomy. Cox proportional hazards regression models were used to evaluate the association between gene expression and time to event end points. Results from the prostatectomy and biopsy studies were used to develop and lock a multigene-expression-based signature, called the Genomic Prostate Score (GPS); in the validation study, logistic regression was used to test the association between the GPS and pathologic stage and grade at prostatectomy. Decision-curve analysis and risk profiles were used together with clinical and pathologic characteristics to evaluate clinical utility. Of the 732 candidate genes analyzed, 288 (39%) were found to predict clinical recurrence despite heterogeneity and multifocality, and 198 (27%) were predictive of aggressive disease after adjustment for prostate-specific antigen, Gleason score, and clinical stage. Further analysis identified 17 genes representing multiple biological pathways that were combined into the GPS algorithm. In the validation study, GPS predicted high-grade (odds ratio [OR] per 20 GPS units: 2.3; 95% confidence interval [CI], 1.5-3.7; p<0.001) and high-stage (OR per 20 GPS units: 1.9; 95% CI, 1.3-3.0; p=0.003) at surgical pathology. GPS predicted high-grade and/or high-stage disease after controlling for established clinical factors (p<0.005) such as an OR of 2.1 (95% CI, 1.4-3.2) when adjusting for Cancer of the Prostate Risk Assessment score. A limitation of the validation study was the inclusion of men with low-volume intermediate-risk PCa (Gleason score 3+4), for whom some providers would not consider AS. Genes representing multiple biological pathways discriminate PCa aggressiveness in biopsy tissue despite tumor heterogeneity, multifocality, and limited sampling at time of biopsy. The biopsy-based 17-gene GPS improves prediction of the presence or absence of adverse pathology and may help men with PCa make more informed decisions between AS and immediate treatment. Prostate cancer (PCa) is often present in multiple locations within the prostate and has variable characteristics. We identified genes with expression associated with aggressive PCa to develop a biopsy-based, multigene signature, the Genomic Prostate Score (GPS). GPS was validated for its ability to predict men who have high-grade or high-stage PCa at diagnosis and may help men diagnosed with PCa decide between active surveillance and immediate definitive treatment. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Exploration of the factor structure of the Kirton Adaption-Innovation Inventory using bootstrapping estimation.

PubMed

Im, Subin; Min, Soonhong

2013-04-01

Exploratory factor analyses of the Kirton Adaption-Innovation Inventory (KAI), which serves to measure individual cognitive styles, generally indicate three factors: sufficiency of originality, efficiency, and rule/group conformity. In contrast, a 2005 study by Im and Hu using confirmatory factor analysis supported a four-factor structure, dividing the sufficiency of originality dimension into two subdimensions, idea generation and preference for change. This study extends Im and Hu's (2005) study of a derived version of the KAI by providing additional evidence of the four-factor structure. Specifically, the authors test the robustness of the parameter estimates to the violation of normality assumptions in the sample using bootstrap methods. A bias-corrected confidence interval bootstrapping procedure conducted among a sample of 356 participants--members of the Arkansas Household Research Panel, with middle SES and average age of 55.6 yr. (SD = 13.9)--showed that the four-factor model with two subdimensions of sufficiency of originality fits the data significantly better than the three-factor model in non-normality conditions.

The integrated model of sport confidence: a canonical correlation and mediational analysis.

PubMed

Koehn, Stefan; Pearce, Alan J; Morris, Tony

2013-12-01

The main purpose of the study was to examine crucial parts of Vealey's (2001) integrated framework hypothesizing that sport confidence is a mediating variable between sources of sport confidence (including achievement, self-regulation, and social climate) and athletes' affect in competition. The sample consisted of 386 athletes, who completed the Sources of Sport Confidence Questionnaire, Trait Sport Confidence Inventory, and Dispositional Flow Scale-2. Canonical correlation analysis revealed a confidence-achievement dimension underlying flow. Bias-corrected bootstrap confidence intervals in AMOS 20.0 were used in examining mediation effects between source domains and dispositional flow. Results showed that sport confidence partially mediated the relationship between achievement and self-regulation domains and flow, whereas no significant mediation was found for social climate. On a subscale level, full mediation models emerged for achievement and flow dimensions of challenge-skills balance, clear goals, and concentration on the task at hand.

A Comparison of Three Tests of Mediation

ERIC Educational Resources Information Center

Warbasse, Rosalia E.

2009-01-01

A simulation study was conducted to evaluate the performance of three tests of mediation: the bias-corrected and accelerated bootstrap (Efron & Tibshirani, 1993), the asymmetric confidence limits test (MacKinnon, 2008), and a multiple regression approach described by Kenny, Kashy, and Bolger (1998). The evolution of these methods is reviewed and…

Ejaculation Frequency and Risk of Prostate Cancer: Updated Results with an Additional Decade of Follow-up

PubMed Central

Rider, Jennifer R.; Wilson, Kathryn M.; Sinnott, Jennifer A.; Kelly, Rachel S.; Mucci, Lorelei A.; Giovannucci, Edward L.

2016-01-01

Background Evidence suggests that ejaculation frequency may be inversely related to the risk of prostate cancer (PCa), a disease for which few modifiable risk factors have been identified. Objective To incorporate an additional 10 yr of follow-up into an original analysis and to comprehensively evaluate the association between ejaculation frequency and PCa, accounting for screening, clinically relevant disease subgroups, and the impact of mortality from other causes. Design, setting, and participants A prospective cohort study of participants in the Health Professionals Follow-up Study utilizing self-reported data on average monthly ejaculation frequency. The study includes 31 925 men who answered questions on ejaculation frequency on a 1992 questionnaire and followed through to 2010. The average monthly ejaculation frequency was assessed at three time points: age 20–29 yr, age 40–49 yr, and the year before questionnaire distribution. Outcome measurements and statistical analysis Incidence of total PCa and clinically relevant disease subgroups. Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results and limitations During 480 831 person-years, 3839 men were diagnosed with PCa. Ejaculation frequency at age 40–49 yr was positively associated with age-standardized body mass index, physical activity, divorce, history of sexually transmitted infections, and consumption of total calories and alcohol. Prostate-specific antigen (PSA) test utilization by 2008, number of PSA tests, and frequency of prostate biopsy were similar across frequency categories. In multivariable analyses, the hazard ratio for PCa incidence for ≥21 compared to 4–7 ejaculations per month was 0.81 (95% confidence interval [CI] 0.72–0.92; p < 0.0001 for trend) for frequency at age 20–29 yr and 0.78 (95% CI 0.69–0.89; p < 0.0001 for trend) for frequency at age 40–49 yr. Associations were driven by low-risk disease, were similar when restricted to a PSA-screened cohort, and were unlikely to be explained by competing causes of death. Conclusions These findings provide additional evidence of a beneficial role of more frequent ejaculation throughout adult life in the etiology of PCa, particularly for low-risk disease. Patient summary We evaluated whether ejaculation frequency throughout adulthood is related to prostate cancer risk in a large US-based study. We found that men reporting higher compared to lower ejaculatory frequency in adulthood were less likely to be subsequently diagnosed with prostate cancer. PMID:27033442

PCA-LBG-based algorithms for VQ codebook generation

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Yang, Po-Yuan

2015-04-01

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.

Validation of copy number variants associated with prostate cancer risk and prognosis.

PubMed

Blackburn, August; Wilson, Desiree; Gelfond, Jonathan; Yao, Li; Hernandez, Javier; Thompson, Ian M; Leach, Robin J; Lehman, Donna M

2014-01-01

Two recent studies have reported novel heritable copy number variants on chromosomes 2p, 15q, and 12q to be associated with prostate cancer (PCa) risk in non-Hispanic Caucasians. The goal of this study was to determine whether these findings could be independently confirmed in the Caucasian population from the South Texas area. The study subjects consisted of participants of the San Antonio Biomarkers of Risk for PCa cohort and additional cases ascertained in the same metropolitan area. We genotyped all 7 of the reported copy number variants using real-time quantitative polymerase chain reaction in 1,536 (317 cases and 1,219 controls) non-Hispanic Caucasian men, and additionally, we genotyped 632 (191 cases and 441 controls) Hispanic Caucasian men for one of these variants, a deletion on 2p24.3. Association of the deletion on 2p24.3 with overall PCa risk did not meet our significance criteria but was consistent with previous reports (odds ratio, 1.40; 95% confidence interval 0.99-2.00; P = 0.06). Among Hispanic Caucasians, this deletion is much less prevalent (minor allele frequencies of 0.059 and 0.024 in non-Hispanic and Hispanic Caucasians, respectively) and did not show evidence of association with risk for PCa. Interestingly, among non-Hispanic Caucasians, carrying a homozygous deletion of 2p24.3 was significantly associated with high-grade PCa as defined by Gleason score sum ≥8 (odds ratio, 27.99; 95% confidence interval 1.99-392.6; P = 0.007 [the Fisher exact test]). The remaining 6 copy number variable regions either were not polymorphic in our cohort of non-Hispanic Caucasians or showed no evidence of association. Our findings are consistent with the reported observation that a heritable deletion on 2p24.3 is associated with PCa risk in non-Hispanic Caucasians. Additionally, our observations indicate that the 2p24.3 variant is associated with risk for high-grade PCa in a recessive manner. We were unable to replicate any association with PCa for the variants on chromosomes 15q and 12q, which may be explained by regional population differences in low frequency variants and disease heterogeneity. Published by Elsevier Inc.

Landslide susceptibility near highways is increased by one order of magnitude in the Andes of southern Ecuador, Loja province

NASA Astrophysics Data System (ADS)

Brenning, A.; Schwinn, M.; Ruiz-Páez, A. P.; Muenchow, J.

2014-03-01

Mountain roads in developing countries are known to increase landslide occurrence due to often inadequate drainage systems and mechanical destabilization of hillslopes by undercutting and overloading. This study empirically investigates landslide initiation frequency along two paved interurban highways in the tropical Andes of southern Ecuador across different climatic regimes. Generalized additive models (GAM) and generalized linear models (GLM) were used to analyze the relationship between mapped landslide initiation points and distance to highway while accounting for topographic, climatic and geological predictors as possible confounders. A spatial block bootstrap was used to obtain non-parametric confidence intervals for the odds ratio of landslide occurrence near the highways (25 m distance) compared to a 200 m distance. The estimated odds ratio was 18-21 with lower 95% confidence bounds > 13 in all analyses. Spatial bootstrap estimation using the GAM supports the higher odds ratio estimate of 21.2 (95% confidence interval: 15.5-25.3). The highway-related effects were observed to fade at about 150 m distance. Road effects appear to be enhanced in geological units characterized by Holocene gravels and Laramide andesite/basalt. Overall, landslide susceptibility was found to be more than one order of magnitude higher in close proximity to paved interurban highways in the Andes of southern Ecuador.

Landslide susceptibility near highways is increased by 1 order of magnitude in the Andes of southern Ecuador, Loja province

NASA Astrophysics Data System (ADS)

Brenning, A.; Schwinn, M.; Ruiz-Páez, A. P.; Muenchow, J.

2015-01-01

Mountain roads in developing countries are known to increase landslide occurrence due to often inadequate drainage systems and mechanical destabilization of hillslopes by undercutting and overloading. This study empirically investigates landslide initiation frequency along two paved interurban highways in the tropical Andes of southern Ecuador across different climatic regimes. Generalized additive models (GAM) and generalized linear models (GLM) were used to analyze the relationship between mapped landslide initiation points and distance to highway while accounting for topographic, climatic, and geological predictors as possible confounders. A spatial block bootstrap was used to obtain nonparametric confidence intervals for the odds ratio of landslide occurrence near the highways (25 m distance) compared to a 200 m distance. The estimated odds ratio was 18-21, with lower 95% confidence bounds >13 in all analyses. Spatial bootstrap estimation using the GAM supports the higher odds ratio estimate of 21.2 (95% confidence interval: 15.5-25.3). The highway-related effects were observed to fade at about 150 m distance. Road effects appear to be enhanced in geological units characterized by Holocene gravels and Laramide andesite/basalt. Overall, landslide susceptibility was found to be more than 1 order of magnitude higher in close proximity to paved interurban highways in the Andes of southern Ecuador.

Parametric methods outperformed non-parametric methods in comparisons of discrete numerical variables.

PubMed

Fagerland, Morten W; Sandvik, Leiv; Mowinckel, Petter

2011-04-13

The number of events per individual is a widely reported variable in medical research papers. Such variables are the most common representation of the general variable type called discrete numerical. There is currently no consensus on how to compare and present such variables, and recommendations are lacking. The objective of this paper is to present recommendations for analysis and presentation of results for discrete numerical variables. Two simulation studies were used to investigate the performance of hypothesis tests and confidence interval methods for variables with outcomes {0, 1, 2}, {0, 1, 2, 3}, {0, 1, 2, 3, 4}, and {0, 1, 2, 3, 4, 5}, using the difference between the means as an effect measure. The Welch U test (the T test with adjustment for unequal variances) and its associated confidence interval performed well for almost all situations considered. The Brunner-Munzel test also performed well, except for small sample sizes (10 in each group). The ordinary T test, the Wilcoxon-Mann-Whitney test, the percentile bootstrap interval, and the bootstrap-t interval did not perform satisfactorily. The difference between the means is an appropriate effect measure for comparing two independent discrete numerical variables that has both lower and upper bounds. To analyze this problem, we encourage more frequent use of parametric hypothesis tests and confidence intervals.

Causes of Death in Men With Prevalent Diabetes and Newly Diagnosed High- Versus Favorable-Risk Prostate Cancer

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

D'Amico, Anthony V., E-mail: adamico@partners.or; Braccioforte, Michelle H.; Moran, Brian J.

2010-08-01

Purpose: To determine whether prevalent diabetes mellitus (pDM) affects the presentation, extent of radiotherapy, or prostate cancer (PCa)-specific mortality (PCSM) and whether PCa aggressiveness affects the risk of non-PCSM, DM-related mortality, and all-cause mortality in men with pDM. Methods: Between October 1997 and July 2907, 5,279 men treated at the Chicago Prostate Cancer Center with radiotherapy for PCa were included in the study. Logistic and competing risk regression analyses were performed to assess whether pDM was associated with high-grade PCa, less aggressive radiotherapy, and an increased risk of PCSM. Competing risks and Cox regression analyses were performed to assess whethermore » PCa aggressiveness described by risk group in men with pDM was associated with the risk of non-PCSM, DM-related mortality, and all-cause mortality. Analyses were adjusted for predictors of high-grade PCa and factors that could affect treatment extent and mortality. Results: Men with pDM were more likely (adjusted hazard ratio [AHR], 1.9; 95% confidence interval [CI], 1.3-2.7; p = .002) to present with high-grade PCa but were not treated less aggressively (p = .33) and did not have an increased risk of PCSM (p = .58) compared to men without pDM. Among the men with pDM, high-risk PCa was associated with a greater risk of non-PCSM (AHR, 2.2; 95% CI, 1.1-4.5; p = .035), DM-related mortality (AHR, 5.2; 95% CI, 2.0-14.0; p = .001), and all-cause mortality (AHR, 2.4; 95% CI, 1.2-4.7; p = .01) compared to favorable-risk PCa. Conclusion: Aggressive management of pDM is warranted in men with high-risk PCa.« less

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.

Prostate extracellular vesicles in patient plasma as a liquid biopsy platform for prostate cancer using nanoscale flow cytometry.

PubMed

Biggs, Colleen N; Siddiqui, Khurram M; Al-Zahrani, Ali A; Pardhan, Siddika; Brett, Sabine I; Guo, Qiu Q; Yang, Jun; Wolf, Philipp; Power, Nicholas E; Durfee, Paul N; MacMillan, Connor D; Townson, Jason L; Brinker, Jeffrey C; Fleshner, Neil E; Izawa, Jonathan I; Chambers, Ann F; Chin, Joseph L; Leong, Hon S

2016-02-23

Extracellular vesicles released by prostate cancer present in seminal fluid, urine, and blood may represent a non-invasive means to identify and prioritize patients with intermediate risk and high risk of prostate cancer. We hypothesize that enumeration of circulating prostate microparticles (PMPs), a type of extracellular vesicle (EV), can identify patients with Gleason Score≥4+4 prostate cancer (PCa) in a manner independent of PSA. Plasmas from healthy volunteers, benign prostatic hyperplasia patients, and PCa patients with various Gleason score patterns were analyzed for PMPs. We used nanoscale flow cytometry to enumerate PMPs which were defined as submicron events (100-1000nm) immunoreactive to anti-PSMA mAb when compared to isotype control labeled samples. Levels of PMPs (counts/µL of plasma) were also compared to CellSearch CTC Subclasses in various PCa metastatic disease subtypes (treatment naïve, castration resistant prostate cancer) and in serially collected plasma sets from patients undergoing radical prostatectomy. PMP levels in plasma as enumerated by nanoscale flow cytometry are effective in distinguishing PCa patients with Gleason Score≥8 disease, a high-risk prognostic factor, from patients with Gleason Score≤7 PCa, which carries an intermediate risk of PCa recurrence. PMP levels were independent of PSA and significantly decreased after surgical resection of the prostate, demonstrating its prognostic potential for clinical follow-up. CTC subclasses did not decrease after prostatectomy and were not effective in distinguishing localized PCa patients from metastatic PCa patients. PMP enumeration was able to identify patients with Gleason Score ≥8 PCa but not patients with Gleason Score 4+3 PCa, but offers greater confidence than CTC counts in identifying patients with metastatic prostate cancer. CTC Subclass analysis was also not effective for post-prostatectomy follow up and for distinguishing metastatic PCa and localized PCa patients. Nanoscale flow cytometry of PMPs presents an emerging biomarker platform for various stages of prostate cancer.

Prostate extracellular vesicles in patient plasma as a liquid biopsy platform for prostate cancer using nanoscale flow cytometry

PubMed Central

Al-Zahrani, Ali A.; Pardhan, Siddika; Brett, Sabine I.; Guo, Qiu Q.; Yang, Jun; Wolf, Philipp; Power, Nicholas E.; Durfee, Paul N.; MacMillan, Connor D.; Townson, Jason L.; Brinker, Jeffrey C.; Fleshner, Neil E.; Izawa, Jonathan I.; Chambers, Ann F.; Chin, Joseph L.; Leong, Hon S.

2016-01-01

Background Extracellular vesicles released by prostate cancer present in seminal fluid, urine, and blood may represent a non-invasive means to identify and prioritize patients with intermediate risk and high risk of prostate cancer. We hypothesize that enumeration of circulating prostate microparticles (PMPs), a type of extracellular vesicle (EV), can identify patients with Gleason Score≥4+4 prostate cancer (PCa) in a manner independent of PSA. Patients and Methods Plasmas from healthy volunteers, benign prostatic hyperplasia patients, and PCa patients with various Gleason score patterns were analyzed for PMPs. We used nanoscale flow cytometry to enumerate PMPs which were defined as submicron events (100-1000nm) immunoreactive to anti-PSMA mAb when compared to isotype control labeled samples. Levels of PMPs (counts/μL of plasma) were also compared to CellSearch CTC Subclasses in various PCa metastatic disease subtypes (treatment naïve, castration resistant prostate cancer) and in serially collected plasma sets from patients undergoing radical prostatectomy. Results PMP levels in plasma as enumerated by nanoscale flow cytometry are effective in distinguishing PCa patients with Gleason Score≥8 disease, a high-risk prognostic factor, from patients with Gleason Score≤7 PCa, which carries an intermediate risk of PCa recurrence. PMP levels were independent of PSA and significantly decreased after surgical resection of the prostate, demonstrating its prognostic potential for clinical follow-up. CTC subclasses did not decrease after prostatectomy and were not effective in distinguishing localized PCa patients from metastatic PCa patients. Conclusions PMP enumeration was able to identify patients with Gleason Score ≥8 PCa but not patients with Gleason Score 4+3 PCa, but offers greater confidence than CTC counts in identifying patients with metastatic prostate cancer. CTC Subclass analysis was also not effective for post-prostatectomy follow up and for distinguishing metastatic PCa and localized PCa patients. Nanoscale flow cytometry of PMPs presents an emerging biomarker platform for various stages of prostate cancer. PMID:26814433

Semantic Drift in Espresso-style Bootstrapping: Graph-theoretic Analysis and Evaluation in Word Sense Disambiguation

NASA Astrophysics Data System (ADS)

Komachi, Mamoru; Kudo, Taku; Shimbo, Masashi; Matsumoto, Yuji

Bootstrapping has a tendency, called semantic drift, to select instances unrelated to the seed instances as the iteration proceeds. We demonstrate the semantic drift of Espresso-style bootstrapping has the same root as the topic drift of Kleinberg's HITS, using a simplified graph-based reformulation of bootstrapping. We confirm that two graph-based algorithms, the von Neumann kernels and the regularized Laplacian, can reduce the effect of semantic drift in the task of word sense disambiguation (WSD) on Senseval-3 English Lexical Sample Task. Proposed algorithms achieve superior performance to Espresso and previous graph-based WSD methods, even though the proposed algorithms have less parameters and are easy to calibrate.

Analyzing the Association of Polymorphisms in the CRYBB2 Gene with Prostate Cancer Risk in African Americans

PubMed Central

FARUQUE, MEZBAH U.; PAUL, RABINDRA; RICKS-SANTI, LUISEL; JINGWI, EMMANUEL Y.; AHAGHOTU, CHILEDUM A.; DUNSTON, GEORGIA M.

2016-01-01

Background/Aim Prostate cancer (PCa) shows disproportionately higher incidence and disease-associated mortality in African Americans. The human crystallin beta B2 (CRYBB2) gene has been reported as one tumor signature gene differentially expressed between African American and European American cancer patients. We investigated the role of CRYBB2 genetic variants in PCa in African Americans. Materials and Methods Subjects comprised of 233 PCa cases and 294 controls. Nine haplotype-tagged single nucleotide polymorphisms (SNPs) in and around the CRYBB2 gene were genotyped by pyrosequencing. Association analyses were performed for PCa with adjustment for age and prostate-specific antigen (PSA), under an additive genetic model. Results Out of the nine SNPs examined, rs9608380 was found to be nominally associated with PCa (odds ratio (OR)=2.619 (95% confidence interval (CI)=1.156–5.935), p=0.021). rs9306412 was in strong linkage disequilibrium with rs9608380 that showed an association p-value of 0.077. Using ENCODE data, we found rs9608380 mapped to a region annotated with regulatory motifs, such as DNase hypersensitive sites and histone modifications. Conclusion This is the first study to analyze the association between genetic variations in the CRYBB2 gene with PCa. rs9608380, associated with PCa, is a potentially functional variant. PMID:25964531

The Role of Simulation Approaches in Statistics

ERIC Educational Resources Information Center

Wood, Michael

2005-01-01

This article explores the uses of a simulation model (the two bucket story)--implemented by a stand-alone computer program, or an Excel workbook (both on the web)--that can be used for deriving bootstrap confidence intervals, and simulating various probability distributions. The strengths of the model are its generality, the fact that it provides…

Home-based care after a shortened hospital stay versus hospital-based care postpartum: an economic evaluation.

PubMed

Petrou, Stavros; Boulvain, Michel; Simon, Judit; Maricot, Patrice; Borst, François; Perneger, Thomas; Irion, Olivier

2004-08-01

To compare the cost effectiveness of early postnatal discharge and home midwifery support with a traditional postnatal hospital stay. Cost minimisation analysis within a pragmatic randomised controlled trial. The University Hospital of Geneva and its catchment area. Four hundred and fifty-nine deliveries of a single infant at term following an uncomplicated pregnancy. Prospective economic evaluation alongside a randomised controlled trial in which women were allocated to either early postnatal discharge combined with home midwifery support (n= 228) or a traditional postnatal hospital stay (n= 231). Costs (Swiss francs, 2000 prices) to the health service, social services, patients, carers and society accrued between delivery and 28 days postpartum. Clinical and psychosocial outcomes were similar in the two trial arms. Early postnatal discharge combined with home midwifery support resulted in a significant reduction in postnatal hospital care costs (bootstrap mean difference 1524 francs, 95% confidence interval [CI] 675 to 2403) and a significant increase in community care costs (bootstrap mean difference 295 francs, 95% CI 245 to 343). There were no significant differences in average hospital readmission, hospital outpatient care, direct non-medical and indirect costs between the two trial groups. Overall, early postnatal discharge combined with home midwifery support resulted in a significant cost saving of 1221 francs per mother-infant dyad (bootstrap mean difference 1209 francs, 95% CI 202 to 2155). This finding remained relatively robust following variations in the values of key economic parameters performed as part of a comprehensive sensitivity analysis. A policy of early postnatal discharge combined with home midwifery support exhibits weak economic dominance over traditional postnatal care, that is, it significantly reduces costs without compromising the health and wellbeing of the mother and infant.

Pearson-type goodness-of-fit test with bootstrap maximum likelihood estimation.

PubMed

Yin, Guosheng; Ma, Yanyuan

2013-01-01

The Pearson test statistic is constructed by partitioning the data into bins and computing the difference between the observed and expected counts in these bins. If the maximum likelihood estimator (MLE) of the original data is used, the statistic generally does not follow a chi-squared distribution or any explicit distribution. We propose a bootstrap-based modification of the Pearson test statistic to recover the chi-squared distribution. We compute the observed and expected counts in the partitioned bins by using the MLE obtained from a bootstrap sample. This bootstrap-sample MLE adjusts exactly the right amount of randomness to the test statistic, and recovers the chi-squared distribution. The bootstrap chi-squared test is easy to implement, as it only requires fitting exactly the same model to the bootstrap data to obtain the corresponding MLE, and then constructs the bin counts based on the original data. We examine the test size and power of the new model diagnostic procedure using simulation studies and illustrate it with a real data set.

Using Replicates in Information Retrieval Evaluation.

PubMed

Voorhees, Ellen M; Samarov, Daniel; Soboroff, Ian

2017-09-01

This article explores a method for more accurately estimating the main effect of the system in a typical test-collection-based evaluation of information retrieval systems, thus increasing the sensitivity of system comparisons. Randomly partitioning the test document collection allows for multiple tests of a given system and topic (replicates). Bootstrap ANOVA can use these replicates to extract system-topic interactions-something not possible without replicates-yielding a more precise value for the system effect and a narrower confidence interval around that value. Experiments using multiple TREC collections demonstrate that removing the topic-system interactions substantially reduces the confidence intervals around the system effect as well as increases the number of significant pairwise differences found. Further, the method is robust against small changes in the number of partitions used, against variability in the documents that constitute the partitions, and the measure of effectiveness used to quantify system effectiveness.

Using Replicates in Information Retrieval Evaluation

PubMed Central

VOORHEES, ELLEN M.; SAMAROV, DANIEL; SOBOROFF, IAN

2018-01-01

This article explores a method for more accurately estimating the main effect of the system in a typical test-collection-based evaluation of information retrieval systems, thus increasing the sensitivity of system comparisons. Randomly partitioning the test document collection allows for multiple tests of a given system and topic (replicates). Bootstrap ANOVA can use these replicates to extract system-topic interactions—something not possible without replicates—yielding a more precise value for the system effect and a narrower confidence interval around that value. Experiments using multiple TREC collections demonstrate that removing the topic-system interactions substantially reduces the confidence intervals around the system effect as well as increases the number of significant pairwise differences found. Further, the method is robust against small changes in the number of partitions used, against variability in the documents that constitute the partitions, and the measure of effectiveness used to quantify system effectiveness. PMID:29905334

Trends of prostate cancer incidence and mortality in Shanghai, China from 1973 to 2009.

PubMed

Qi, Di; Wu, Chunxiao; Liu, Fang; Gu, Kai; Shi, Zhuqing; Lin, Xiaoling; Tao, Sha; Xu, Wanghong; Brendler, Charles B; Zheng, Ying; Xu, Jianfeng

2015-10-01

The incidence and mortality of prostate cancer (PCa) were historically low in China but have increased considerably in recent years. This study aimed to describe the detailed trend of PCa incidence and mortality in Shanghai, China. Incidence and mortality data of PCa in urban Shanghai during 1973 and 2009 were collected by the Shanghai Municipal Center for Disease Control and Prevention. Age standardized rates (ASR) of incidence and mortality were calculated based on the 1966 world standard population. Join point regression analysis was used to describe the trends and to identify specific time points when significant changes in incidence and mortality occurred. The PCa incidence in Shanghai increased ~sixfold from an ASR of 2.13/100,000 in 1973 to 12.96/100,000 in 2009, and its rank ascended from the 17th to the 4th most common cancer during the period. The PCa mortality in Shanghai increased threefold from an ASR of 1.61/100,000 in 1973 to 4.97/100,000 in 2009, and its rank ascended from the 17th to the 6th most deadly cancer during this period. More specifically, the ASR of incidence increased slightly before 1991, sharply during1991-2004, and slightly after 2004, with annual percent changes (APC) of 2.2% (95% confidence interval: 0.3%-4.3%), 13.2% (11.4%-15.0%), and 3.2% (-0.3%-6.8%), respectively. The mortality trend was stable before 1985 and increased slowly but steadily after 1985, with APC of -0.6% (-4.4%-3.3%) and 5.3% (4.7%-6.0%), respectively. The increasing incidence and mortality rates were primarily observed in men ≥ 70 years. The incidence and mortality of PCa have increased significantly in Shanghai, China over the past four decades. © 2015 Wiley Periodicals, Inc.

Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal's Fail-Safe Number.

PubMed

Fragkos, Konstantinos C; Tsagris, Michail; Frangos, Christos C

2014-01-01

The purpose of the present paper is to assess the efficacy of confidence intervals for Rosenthal's fail-safe number. Although Rosenthal's estimator is highly used by researchers, its statistical properties are largely unexplored. First of all, we developed statistical theory which allowed us to produce confidence intervals for Rosenthal's fail-safe number. This was produced by discerning whether the number of studies analysed in a meta-analysis is fixed or random. Each case produces different variance estimators. For a given number of studies and a given distribution, we provided five variance estimators. Confidence intervals are examined with a normal approximation and a nonparametric bootstrap. The accuracy of the different confidence interval estimates was then tested by methods of simulation under different distributional assumptions. The half normal distribution variance estimator has the best probability coverage. Finally, we provide a table of lower confidence intervals for Rosenthal's estimator.

Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal's Fail-Safe Number

PubMed Central

Fragkos, Konstantinos C.; Tsagris, Michail; Frangos, Christos C.

2014-01-01

The purpose of the present paper is to assess the efficacy of confidence intervals for Rosenthal's fail-safe number. Although Rosenthal's estimator is highly used by researchers, its statistical properties are largely unexplored. First of all, we developed statistical theory which allowed us to produce confidence intervals for Rosenthal's fail-safe number. This was produced by discerning whether the number of studies analysed in a meta-analysis is fixed or random. Each case produces different variance estimators. For a given number of studies and a given distribution, we provided five variance estimators. Confidence intervals are examined with a normal approximation and a nonparametric bootstrap. The accuracy of the different confidence interval estimates was then tested by methods of simulation under different distributional assumptions. The half normal distribution variance estimator has the best probability coverage. Finally, we provide a table of lower confidence intervals for Rosenthal's estimator. PMID:27437470

Quantification of variability and uncertainty for air toxic emission inventories with censored emission factor data.

PubMed

Frey, H Christopher; Zhao, Yuchao

2004-11-15

Probabilistic emission inventories were developed for urban air toxic emissions of benzene, formaldehyde, chromium, and arsenic for the example of Houston. Variability and uncertainty in emission factors were quantified for 71-97% of total emissions, depending upon the pollutant and data availability. Parametric distributions for interunit variability were fit using maximum likelihood estimation (MLE), and uncertainty in mean emission factors was estimated using parametric bootstrap simulation. For data sets containing one or more nondetected values, empirical bootstrap simulation was used to randomly sample detection limits for nondetected values and observations for sample values, and parametric distributions for variability were fit using MLE estimators for censored data. The goodness-of-fit for censored data was evaluated by comparison of cumulative distributions of bootstrap confidence intervals and empirical data. The emission inventory 95% uncertainty ranges are as small as -25% to +42% for chromium to as large as -75% to +224% for arsenic with correlated surrogates. Uncertainty was dominated by only a few source categories. Recommendations are made for future improvements to the analysis.

The performance of the new prognostic grade and stage groups in conservatively treated prostate cancer.

PubMed

Chen, Cheng; Chen, Ye; Hu, Lin-Kun; Jiang, Chang-Chuan; Xu, Ren-Fang; He, Xiao-Zhou

2018-02-27

We evaluated the prognosis of the new grade groups and American Joint Committee on Cancer (AJCC) stage groups in men with prostate cancer (PCa) who were treated conservatively. A total of 13 798 eligible men were chosen from the Surveillance Epidemiology and End Results database. The new grade and AJCC stage groups were investigated on prostate biopsy specimens. Kaplan-Meier survival analysis and multivariable hazards models were applied to estimate the association of new grade and stage groups with overall survival (OS) and PCa-specific survival (CSS). Mean follow-up was 42.65 months (95% confidence interval: 42.47-42.84) in the entire cohort. The 3-year OS and CSS rates stepped down for grade groups 1-5 and AJCC stage groups I-IVB, respectively. After adjusting for clinical and pathological characteristics, all grade groups and AJCC stage groups were associated with higher all-cause and PCa-specific mortality compared to the reference group (all P ≤ 0.003). In conclusion, we evaluated the oncological outcome of the new grade and AJCC stage groups on biopsy specimens of conservatively treated PCa. These two novel clinically relevant classifications can assist physicians to determine different therapeutic strategies for PCa patients.

Correlation Attenuation Due to Measurement Error: A New Approach Using the Bootstrap Procedure

ERIC Educational Resources Information Center

Padilla, Miguel A.; Veprinsky, Anna

2012-01-01

Issues with correlation attenuation due to measurement error are well documented. More than a century ago, Spearman proposed a correction for attenuation. However, this correction has seen very little use since it can potentially inflate the true correlation beyond one. In addition, very little confidence interval (CI) research has been done for…

Comprehensive analysis and evaluation of big data for main transformer equipment based on PCA and Apriority

NASA Astrophysics Data System (ADS)

Guo, Lijuan; Yan, Haijun; Hao, Yongqi; Chen, Yun

2018-01-01

With the power supply level of urban power grid toward high reliability development, it is necessary to adopt appropriate methods for comprehensive evaluation of existing equipment. Considering the wide and multi-dimensional power system data, the method of large data mining is used to explore the potential law and value of power system equipment. Based on the monitoring data of main transformer and the records of defects and faults, this paper integrates the data of power grid equipment environment. Apriori is used as an association identification algorithm to extract the frequent correlation factors of the main transformer, and the potential dependence of the big data is analyzed by the support and confidence. Then, the integrated data is analyzed by PCA, and the integrated quantitative scoring model is constructed. It is proved to be effective by using the test set to validate the evaluation algorithm and scheme. This paper provides a new idea for data fusion of smart grid, and provides a reference for further evaluation of big data of power grid equipment.

Fruit and vegetables consumption is directly associated to survival after prostate cancer.

PubMed

Taborelli, Martina; Polesel, Jerry; Parpinel, Maria; Stocco, Carmen; Birri, Silvia; Serraino, Diego; Zucchetto, Antonella

2017-04-01

Since the evidence on the role of diet on prostate cancer (PCa) prognosis is still controversial, we evaluated the long-term effects of fruit and vegetables consumption on survival after PCa. A retrospective cohort study included 777 men with PCa diagnosed between 1995 and 2002 in north-eastern Italy and followed up to 2013. A validated food frequency questionnaire assessed the usual diet in the 2 years before PCa diagnosis, including detailed fruit and vegetables consumption. Adjusted hazard ratios (HRs) of death with 95% confidence intervals (CIs) were estimated using Fine-Gray models. PCa patients with a consumption of both fruit and vegetables above the median showed a higher 15-year overall survival probability than those with lower intakes (71% versus 58%, p = 0.04; HR = 0.66, 95% CI: 0.47-0.93). Consumption of foods rich in fiber (HR = 0.59, 95% CI: 0.41-0.86) and proanthocyanidins (HR = 0.58, 95% CI: 0.40-0.82) were inversely associated with overall mortality. Interestingly, proanthocyanidins (HR = 0.52; 95% CI: 0.27-0.98) and flavonols (HR = 0.40; 95% CI: 0.19-0.84) were inversely associated also with PCa-specific mortality. High consumption of fruit and vegetables offers an advantage in survival among the rising number of men living after a PCa diagnosis, possibly through the epigenetic effect of some nutrients. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analyzing hospitalization data: potential limitations of Poisson regression.

PubMed

Weaver, Colin G; Ravani, Pietro; Oliver, Matthew J; Austin, Peter C; Quinn, Robert R

2015-08-01

Poisson regression is commonly used to analyze hospitalization data when outcomes are expressed as counts (e.g. number of days in hospital). However, data often violate the assumptions on which Poisson regression is based. More appropriate extensions of this model, while available, are rarely used. We compared hospitalization data between 206 patients treated with hemodialysis (HD) and 107 treated with peritoneal dialysis (PD) using Poisson regression and compared results from standard Poisson regression with those obtained using three other approaches for modeling count data: negative binomial (NB) regression, zero-inflated Poisson (ZIP) regression and zero-inflated negative binomial (ZINB) regression. We examined the appropriateness of each model and compared the results obtained with each approach. During a mean 1.9 years of follow-up, 183 of 313 patients (58%) were never hospitalized (indicating an excess of 'zeros'). The data also displayed overdispersion (variance greater than mean), violating another assumption of the Poisson model. Using four criteria, we determined that the NB and ZINB models performed best. According to these two models, patients treated with HD experienced similar hospitalization rates as those receiving PD {NB rate ratio (RR): 1.04 [bootstrapped 95% confidence interval (CI): 0.49-2.20]; ZINB summary RR: 1.21 (bootstrapped 95% CI 0.60-2.46)}. Poisson and ZIP models fit the data poorly and had much larger point estimates than the NB and ZINB models [Poisson RR: 1.93 (bootstrapped 95% CI 0.88-4.23); ZIP summary RR: 1.84 (bootstrapped 95% CI 0.88-3.84)]. We found substantially different results when modeling hospitalization data, depending on the approach used. Our results argue strongly for a sound model selection process and improved reporting around statistical methods used for modeling count data. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation.

PubMed

Wahl, Simone; Boulesteix, Anne-Laure; Zierer, Astrid; Thorand, Barbara; van de Wiel, Mark A

2016-10-26

Missing values are a frequent issue in human studies. In many situations, multiple imputation (MI) is an appropriate missing data handling strategy, whereby missing values are imputed multiple times, the analysis is performed in every imputed data set, and the obtained estimates are pooled. If the aim is to estimate (added) predictive performance measures, such as (change in) the area under the receiver-operating characteristic curve (AUC), internal validation strategies become desirable in order to correct for optimism. It is not fully understood how internal validation should be combined with multiple imputation. In a comprehensive simulation study and in a real data set based on blood markers as predictors for mortality, we compare three combination strategies: Val-MI, internal validation followed by MI on the training and test parts separately, MI-Val, MI on the full data set followed by internal validation, and MI(-y)-Val, MI on the full data set omitting the outcome followed by internal validation. Different validation strategies, including bootstrap und cross-validation, different (added) performance measures, and various data characteristics are considered, and the strategies are evaluated with regard to bias and mean squared error of the obtained performance estimates. In addition, we elaborate on the number of resamples and imputations to be used, and adopt a strategy for confidence interval construction to incomplete data. Internal validation is essential in order to avoid optimism, with the bootstrap 0.632+ estimate representing a reliable method to correct for optimism. While estimates obtained by MI-Val are optimistically biased, those obtained by MI(-y)-Val tend to be pessimistic in the presence of a true underlying effect. Val-MI provides largely unbiased estimates, with a slight pessimistic bias with increasing true effect size, number of covariates and decreasing sample size. In Val-MI, accuracy of the estimate is more strongly improved by increasing the number of bootstrap draws rather than the number of imputations. With a simple integrated approach, valid confidence intervals for performance estimates can be obtained. When prognostic models are developed on incomplete data, Val-MI represents a valid strategy to obtain estimates of predictive performance measures.

Development of a Voided Urine Assay for Detecting Prostate Cancer Noninvasively: A Pilot Study

PubMed Central

Trabulsi, Edouard J.; Tripathi, Sushil K.; Gomella, Leonard; Solomides, Charalambos; Wickstrom, Eric; Thakur, Mathew L.

2017-01-01

Objective To validate a hypothesis that prostate cancer (PCa) can be detected noninvasively by a simple and reliable assay by targeting genomic VPAC receptors expressed on malignant PCa cells shed in voided urine. Materials and Methods VPAC receptors were targeted with a specific biomolecule, TP4303, developed in our laboratory. With an IRB “exempt” approval of use of de-identified discarded samples, an aliquot of urine collected as a standard of care, from patients presenting to the urology clinic, (N=207, M= 176, F= 31, 21 years or older) was cytospun. The cells were fixed and treated with TP4303 and 4, 6 Dimidino-2-phenylindole, Dihydrochloride (DAPI). The cells were then observed under a microscope and cells with TP4303 orange fluorescence around the blue (DAPI) nucleus were considered malignant and those only with blue nucleus were regarded as normal. VPAC presence was validated using receptor blocking assay and cell malignancy was confirmed by PCa gene profile examination. Results The urine specimens were labeled only with gender and presenting diagnosis, with no personal health identifiers or other clinical data. The assay detected VPAC positive cells in 98.6% of the patients having a PCa diagnosis, (N=141), and none (0%) of the males with benign prostatic hyperplasia (BPH) (N=10). Of the 56 “normal” patients, 62.5% (N=35, M=10, F=25) were negative for VPAC cells; 19.6% (N=11, M=11, F=0) had VPAC positive cells; and 17.8% (N=10, M=4, F=6) were uninterpretable due to excessive crystals in the urine. Although data are limited, the sensitivity of the assay was 99.3% with confidence interval of 96.1%–100% and the specificity was 100% with confidence interval of 69.2%–100%. Receptor blocking assay and FACS analyses demonstrated the presence of VPAC receptors and gene profiling examinations confirmed that the cells expressing VPAC receptors were malignant PCa cells. Conclusion These preliminary data are highly encouraging and warrant further evaluation of the assay to serve as a simple and reliable tool to detect PCa noninvasively. PMID:28075510

DWI-associated entire-tumor histogram analysis for the differentiation of low-grade prostate cancer from intermediate-high-grade prostate cancer.

PubMed

Wu, Chen-Jiang; Wang, Qing; Li, Hai; Wang, Xiao-Ning; Liu, Xi-Sheng; Shi, Hai-Bin; Zhang, Yu-Dong

2015-10-01

To investigate diagnostic efficiency of DWI using entire-tumor histogram analysis in differentiating the low-grade (LG) prostate cancer (PCa) from intermediate-high-grade (HG) PCa in comparison with conventional ROI-based measurement. DW images (b of 0-1400 s/mm(2)) from 126 pathology-confirmed PCa (diameter >0.5 cm) in 110 patients were retrospectively collected and processed by mono-exponential model. The measurement of tumor apparent diffusion coefficients (ADCs) was performed with using histogram-based and ROI-based approach, respectively. The diagnostic ability of ADCs from two methods for differentiating LG-PCa (Gleason score, GS ≤ 6) from HG-PCa (GS > 6) was determined by ROC regression, and compared by McNemar's test. There were 49 LG-tumor and 77 HG-tumor at pathologic findings. Histogram-based ADCs (mean, median, 10th and 90th) and ROI-based ADCs (mean) showed dominant relationships with ordinal GS of Pca (ρ = -0.225 to -0.406, p < 0.05). All above imaging indices reflected significant difference between LG-PCa and HG-PCa (all p values <0.01). Histogram 10th ADCs had dominantly high Az (0.738), Youden index (0.415), and positive likelihood ratio (LR+, 2.45) in stratifying tumor GS against mean, median and 90th ADCs, and ROI-based ADCs. Histogram mean, median, and 10th ADCs showed higher specificity (65.3%-74.1% vs. 44.9%, p < 0.01), but lower sensitivity (57.1%-71.3% vs. 84.4%, p < 0.05) than ROI-based ADCs in differentiating LG-PCa from HG-PCa. DWI-associated histogram analysis had higher specificity, Az, Youden index, and LR+ for differentiation of PCa Gleason grade than ROI-based approach.

Bootstrap Signal-to-Noise Confidence Intervals: An Objective Method for Subject Exclusion and Quality Control in ERP Studies

PubMed Central

Parks, Nathan A.; Gannon, Matthew A.; Long, Stephanie M.; Young, Madeleine E.

2016-01-01

Analysis of event-related potential (ERP) data includes several steps to ensure that ERPs meet an appropriate level of signal quality. One such step, subject exclusion, rejects subject data if ERP waveforms fail to meet an appropriate level of signal quality. Subject exclusion is an important quality control step in the ERP analysis pipeline as it ensures that statistical inference is based only upon those subjects exhibiting clear evoked brain responses. This critical quality control step is most often performed simply through visual inspection of subject-level ERPs by investigators. Such an approach is qualitative, subjective, and susceptible to investigator bias, as there are no standards as to what constitutes an ERP of sufficient signal quality. Here, we describe a standardized and objective method for quantifying waveform quality in individual subjects and establishing criteria for subject exclusion. The approach uses bootstrap resampling of ERP waveforms (from a pool of all available trials) to compute a signal-to-noise ratio confidence interval (SNR-CI) for individual subject waveforms. The lower bound of this SNR-CI (SNRLB) yields an effective and objective measure of signal quality as it ensures that ERP waveforms statistically exceed a desired signal-to-noise criterion. SNRLB provides a quantifiable metric of individual subject ERP quality and eliminates the need for subjective evaluation of waveform quality by the investigator. We detail the SNR-CI methodology, establish the efficacy of employing this approach with Monte Carlo simulations, and demonstrate its utility in practice when applied to ERP datasets. PMID:26903849

[Research on outlier detection methods for determination of oil yield in oil shales using near-infrared spectroscopy].

PubMed

Zhang, Huai-zhu; Lin, Jun; Zhang, Huai-Zhu

2014-06-01

In the present paper, the outlier detection methods for determination of oil yield in oil shale using near-infrared (NIR) diffuse reflection spectroscopy was studied. During the quantitative analysis with near-infrared spectroscopy, environmental change and operator error will both produce outliers. The presence of outliers will affect the overall distribution trend of samples and lead to the decrease in predictive capability. Thus, the detection of outliers are important for the construction of high-quality calibration models. The methods including principal component analysis-Mahalanobis distance (PCA-MD) and resampling by half-means (RHM) were applied to the discrimination and elimination of outliers in this work. The thresholds and confidences for MD and RHM were optimized using the performance of partial least squares (PLS) models constructed after the elimination of outliers, respectively. Compared with the model constructed with the data of full spectrum, the values of RMSEP of the models constructed with the application of PCA-MD with a threshold of a value equal to the sum of average and standard deviation of MD, RHM with the confidence level of 85%, and the combination of PCA-MD and RHM, were reduced by 48.3%, 27.5% and 44.8%, respectively. The predictive ability of the calibration model has been improved effectively.

Plant microRNA-Target Interaction Identification Model Based on the Integration of Prediction Tools and Support Vector Machine

PubMed Central

Meng, Jun; Shi, Lin; Luan, Yushi

2014-01-01

Background Confident identification of microRNA-target interactions is significant for studying the function of microRNA (miRNA). Although some computational miRNA target prediction methods have been proposed for plants, results of various methods tend to be inconsistent and usually lead to more false positive. To address these issues, we developed an integrated model for identifying plant miRNA–target interactions. Results Three online miRNA target prediction toolkits and machine learning algorithms were integrated to identify and analyze Arabidopsis thaliana miRNA-target interactions. Principle component analysis (PCA) feature extraction and self-training technology were introduced to improve the performance. Results showed that the proposed model outperformed the previously existing methods. The results were validated by using degradome sequencing supported Arabidopsis thaliana miRNA-target interactions. The proposed model constructed on Arabidopsis thaliana was run over Oryza sativa and Vitis vinifera to demonstrate that our model is effective for other plant species. Conclusions The integrated model of online predictors and local PCA-SVM classifier gained credible and high quality miRNA-target interactions. The supervised learning algorithm of PCA-SVM classifier was employed in plant miRNA target identification for the first time. Its performance can be substantially improved if more experimentally proved training samples are provided. PMID:25051153

Lycopene and Risk of Prostate Cancer

PubMed Central

Chen, Ping; Zhang, Wenhao; Wang, Xiao; Zhao, Keke; Negi, Devendra Singh; Zhuo, Li; Qi, Mao; Wang, Xinghuan; Zhang, Xinhua

2015-01-01

Abstract Prostate cancer (PCa) is a common illness for aging males. Lycopene has been identified as an antioxidant agent with potential anticancer properties. Studies investigating the relation between lycopene and PCa risk have produced inconsistent results. This study aims to determine dietary lycopene consumption/circulating concentration and any potential dose–response associations with the risk of PCa. Eligible studies published in English up to April 10, 2014, were searched and identified from Pubmed, Sciencedirect Online, Wiley online library databases and hand searching. The STATA (version 12.0) was applied to process the dose–response meta-analysis. Random effects models were used to calculate pooled relative risks (RRs) and 95% confidence intervals (CIs) and to incorporate variation between studies. The linear and nonlinear dose–response relations were evaluated with data from categories of lycopene consumption/circulating concentrations. Twenty-six studies were included with 17,517 cases of PCa reported from 563,299 participants. Although inverse association between lycopene consumption and PCa risk was not found in all studies, there was a trend that with higher lycopene intake, there was reduced incidence of PCa (P = 0.078). Removal of one Chinese study in sensitivity analysis, or recalculation using data from only high-quality studies for subgroup analysis, indicated that higher lycopene consumption significantly lowered PCa risk. Furthermore, our dose–response meta-analysis demonstrated that higher lycopene consumption was linearly associated with a reduced risk of PCa with a threshold between 9 and 21 mg/day. Consistently, higher circulating lycopene levels significantly reduced the risk of PCa. Interestingly, the concentration of circulating lycopene between 2.17 and 85 μg/dL was linearly inversed with PCa risk whereas there was no linear association >85 μg/dL. In addition, greater efficacy for the circulating lycopene concentration on preventing PCa was found for studies with high quality, follow-up >10 years and where results were adjusted by the age or the body mass index. In conclusion, our novel data demonstrates that higher lycopene consumption/circulating concentration is associated with a lower risk of PCa. However, further studies are required to determine the mechanism by which lycopene reduces the risk of PCa and if there are other factors in tomato products that might potentially decrease PCa risk and progression. PMID:26287411

HEXT, a software supporting tree-based screens for hybrid taxa in multilocus data sets, and an evaluation of the homoplasy excess test.

PubMed

Schneider, Kevin; Koblmüller, Stephan; Sefc, Kristina M

2015-11-11

The homoplasy excess test (HET) is a tree-based screen for hybrid taxa in multilocus nuclear phylogenies. Homoplasy between a hybrid taxon and the clades containing the parental taxa reduces bootstrap support in the tree. The HET is based on the expectation that excluding the hybrid taxon from the data set increases the bootstrap support for the parental clades, whereas excluding non-hybrid taxa has little effect on statistical node support. To carry out a HET, bootstrap trees are calculated with taxon-jackknife data sets, that is excluding one taxon (species, population) at a time. Excess increase in bootstrap support for certain nodes upon exclusion of a particular taxon indicates the hybrid (the excluded taxon) and its parents (the clades with increased support).We introduce a new software program, hext, which generates the taxon-jackknife data sets, runs the bootstrap tree calculations, and identifies excess bootstrap increases as outlier values in boxplot graphs. hext is written in r language and accepts binary data (0/1; e.g. AFLP) as well as co-dominant SNP and genotype data.We demonstrate the usefulness of hext in large SNP data sets containing putative hybrids and their parents. For instance, using published data of the genus Vitis (~6,000 SNP loci), hext output supports V. × champinii as a hybrid between V. rupestris and V. mustangensis .With simulated SNP and AFLP data sets, excess increases in bootstrap support were not always connected with the hybrid taxon (false positives), whereas the expected bootstrap signal failed to appear on several occasions (false negatives). Potential causes for both types of spurious results are discussed.With both empirical and simulated data sets, the taxon-jackknife output generated by hext provided additional signatures of hybrid taxa, including changes in tree topology across trees, consistent effects of exclusions of the hybrid and the parent taxa, and moderate (rather than excessive) increases in bootstrap support. hext significantly facilitates the taxon-jackknife approach to hybrid taxon detection, even though the simple test for excess bootstrap increase may not reliably identify hybrid taxa in all applications.

Trends and Correlation Estimation in Climate Sciences: Effects of Timescale Errors

NASA Astrophysics Data System (ADS)

Mudelsee, M.; Bermejo, M. A.; Bickert, T.; Chirila, D.; Fohlmeister, J.; Köhler, P.; Lohmann, G.; Olafsdottir, K.; Scholz, D.

2012-12-01

Trend describes time-dependence in the first moment of a stochastic process, and correlation measures the linear relation between two random variables. Accurately estimating the trend and correlation, including uncertainties, from climate time series data in the uni- and bivariate domain, respectively, allows first-order insights into the geophysical process that generated the data. Timescale errors, ubiquitious in paleoclimatology, where archives are sampled for proxy measurements and dated, poses a problem to the estimation. Statistical science and the various applied research fields, including geophysics, have almost completely ignored this problem due to its theoretical almost-intractability. However, computational adaptations or replacements of traditional error formulas have become technically feasible. This contribution gives a short overview of such an adaptation package, bootstrap resampling combined with parametric timescale simulation. We study linear regression, parametric change-point models and nonparametric smoothing for trend estimation. We introduce pairwise-moving block bootstrap resampling for correlation estimation. Both methods share robustness against autocorrelation and non-Gaussian distributional shape. We shortly touch computing-intensive calibration of bootstrap confidence intervals and consider options to parallelize the related computer code. Following examples serve not only to illustrate the methods but tell own climate stories: (1) the search for climate drivers of the Agulhas Current on recent timescales, (2) the comparison of three stalagmite-based proxy series of regional, western German climate over the later part of the Holocene, and (3) trends and transitions in benthic oxygen isotope time series from the Cenozoic. Financial support by Deutsche Forschungsgemeinschaft (FOR 668, FOR 1070, MU 1595/4-1) and the European Commission (MC ITN 238512, MC ITN 289447) is acknowledged.

Peace of Mind, Academic Motivation, and Academic Achievement in Filipino High School Students.

PubMed

Datu, Jesus Alfonso D

2017-04-09

Recent literature has recognized the advantageous role of low-arousal positive affect such as feelings of peacefulness and internal harmony in collectivist cultures. However, limited research has explored the benefits of low-arousal affective states in the educational setting. The current study examined the link of peace of mind (PoM) to academic motivation (i.e., amotivation, controlled motivation, and autonomous motivation) and academic achievement among 525 Filipino high school students. Findings revealed that PoM was positively associated with academic achievement β = .16, p < .05, autonomous motivation β = .48, p < .001, and controlled motivation β = .25, p < .01. As expected, PoM was negatively related to amotivation β = -.19, p < .05, and autonomous motivation was positively associated with academic achievement β = .52, p < .01. Furthermore, the results of bias-corrected bootstrap analyses at 95% confidence interval based on 5,000 bootstrapped resamples demonstrated that peace of mind had an indirect influence on academic achievement through the mediating effects of autonomous motivation. In terms of the effect sizes, the findings showed that PoM explained about 1% to 18% of the variance in academic achievement and motivation. The theoretical and practical implications of the results are elucidated.

A brief introduction to computer-intensive methods, with a view towards applications in spatial statistics and stereology.

PubMed

Mattfeldt, Torsten

2011-04-01

Computer-intensive methods may be defined as data analytical procedures involving a huge number of highly repetitive computations. We mention resampling methods with replacement (bootstrap methods), resampling methods without replacement (randomization tests) and simulation methods. The resampling methods are based on simple and robust principles and are largely free from distributional assumptions. Bootstrap methods may be used to compute confidence intervals for a scalar model parameter and for summary statistics from replicated planar point patterns, and for significance tests. For some simple models of planar point processes, point patterns can be simulated by elementary Monte Carlo methods. The simulation of models with more complex interaction properties usually requires more advanced computing methods. In this context, we mention simulation of Gibbs processes with Markov chain Monte Carlo methods using the Metropolis-Hastings algorithm. An alternative to simulations on the basis of a parametric model consists of stochastic reconstruction methods. The basic ideas behind the methods are briefly reviewed and illustrated by simple worked examples in order to encourage novices in the field to use computer-intensive methods. © 2010 The Authors Journal of Microscopy © 2010 Royal Microscopical Society.

Gabor-based kernel PCA with fractional power polynomial models for face recognition.

PubMed

Liu, Chengjun

2004-05-01

This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power polynomial models, the Gabor wavelet-based PCA method, and the Gabor wavelet-based kernel PCA method with polynomial kernels.

Evaluating sufficient similarity for drinking-water disinfection by-product (DBP) mixtures with bootstrap hypothesis test procedures.

PubMed

Feder, Paul I; Ma, Zhenxu J; Bull, Richard J; Teuschler, Linda K; Rice, Glenn

2009-01-01

In chemical mixtures risk assessment, the use of dose-response data developed for one mixture to estimate risk posed by a second mixture depends on whether the two mixtures are sufficiently similar. While evaluations of similarity may be made using qualitative judgments, this article uses nonparametric statistical methods based on the "bootstrap" resampling technique to address the question of similarity among mixtures of chemical disinfectant by-products (DBP) in drinking water. The bootstrap resampling technique is a general-purpose, computer-intensive approach to statistical inference that substitutes empirical sampling for theoretically based parametric mathematical modeling. Nonparametric, bootstrap-based inference involves fewer assumptions than parametric normal theory based inference. The bootstrap procedure is appropriate, at least in an asymptotic sense, whether or not the parametric, distributional assumptions hold, even approximately. The statistical analysis procedures in this article are initially illustrated with data from 5 water treatment plants (Schenck et al., 2009), and then extended using data developed from a study of 35 drinking-water utilities (U.S. EPA/AMWA, 1989), which permits inclusion of a greater number of water constituents and increased structure in the statistical models.

Learning predictive models that use pattern discovery--a bootstrap evaluative approach applied in organ functioning sequences.

PubMed

Toma, Tudor; Bosman, Robert-Jan; Siebes, Arno; Peek, Niels; Abu-Hanna, Ameen

2010-08-01

An important problem in the Intensive Care is how to predict on a given day of stay the eventual hospital mortality for a specific patient. A recent approach to solve this problem suggested the use of frequent temporal sequences (FTSs) as predictors. Methods following this approach were evaluated in the past by inducing a model from a training set and validating the prognostic performance on an independent test set. Although this evaluative approach addresses the validity of the specific models induced in an experiment, it falls short of evaluating the inductive method itself. To achieve this, one must account for the inherent sources of variation in the experimental design. The main aim of this work is to demonstrate a procedure based on bootstrapping, specifically the .632 bootstrap procedure, for evaluating inductive methods that discover patterns, such as FTSs. A second aim is to apply this approach to find out whether a recently suggested inductive method that discovers FTSs of organ functioning status is superior over a traditional method that does not use temporal sequences when compared on each successive day of stay at the Intensive Care Unit. The use of bootstrapping with logistic regression using pre-specified covariates is known in the statistical literature. Using inductive methods of prognostic models based on temporal sequence discovery within the bootstrap procedure is however novel at least in predictive models in the Intensive Care. Our results of applying the bootstrap-based evaluative procedure demonstrate the superiority of the FTS-based inductive method over the traditional method in terms of discrimination as well as accuracy. In addition we illustrate the insights gained by the analyst into the discovered FTSs from the bootstrap samples. Copyright 2010 Elsevier Inc. All rights reserved.

Standard Errors and Confidence Intervals from Bootstrapping for Ramsay-Curve Item Response Theory Model Item Parameters

ERIC Educational Resources Information Center

Gu, Fei; Skorupski, William P.; Hoyle, Larry; Kingston, Neal M.

2011-01-01

Ramsay-curve item response theory (RC-IRT) is a nonparametric procedure that estimates the latent trait using splines, and no distributional assumption about the latent trait is required. For item parameters of the two-parameter logistic (2-PL), three-parameter logistic (3-PL), and polytomous IRT models, RC-IRT can provide more accurate estimates…

Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival.

PubMed

Ishwaran, Hemant; Lu, Min

2018-06-04

Random forests are a popular nonparametric tree ensemble procedure with broad applications to data analysis. While its widespread popularity stems from its prediction performance, an equally important feature is that it provides a fully nonparametric measure of variable importance (VIMP). A current limitation of VIMP, however, is that no systematic method exists for estimating its variance. As a solution, we propose a subsampling approach that can be used to estimate the variance of VIMP and for constructing confidence intervals. The method is general enough that it can be applied to many useful settings, including regression, classification, and survival problems. Using extensive simulations, we demonstrate the effectiveness of the subsampling estimator and in particular find that the delete-d jackknife variance estimator, a close cousin, is especially effective under low subsampling rates due to its bias correction properties. These 2 estimators are highly competitive when compared with the .164 bootstrap estimator, a modified bootstrap procedure designed to deal with ties in out-of-sample data. Most importantly, subsampling is computationally fast, thus making it especially attractive for big data settings. Copyright © 2018 John Wiley & Sons, Ltd.

Peaks Over Threshold (POT): A methodology for automatic threshold estimation using goodness of fit p-value

NASA Astrophysics Data System (ADS)

Solari, Sebastián.; Egüen, Marta; Polo, María. José; Losada, Miguel A.

2017-04-01

Threshold estimation in the Peaks Over Threshold (POT) method and the impact of the estimation method on the calculation of high return period quantiles and their uncertainty (or confidence intervals) are issues that are still unresolved. In the past, methods based on goodness of fit tests and EDF-statistics have yielded satisfactory results, but their use has not yet been systematized. This paper proposes a methodology for automatic threshold estimation, based on the Anderson-Darling EDF-statistic and goodness of fit test. When combined with bootstrapping techniques, this methodology can be used to quantify both the uncertainty of threshold estimation and its impact on the uncertainty of high return period quantiles. This methodology was applied to several simulated series and to four precipitation/river flow data series. The results obtained confirmed its robustness. For the measured series, the estimated thresholds corresponded to those obtained by nonautomatic methods. Moreover, even though the uncertainty of the threshold estimation was high, this did not have a significant effect on the width of the confidence intervals of high return period quantiles.

Corrected confidence bands for functional data using principal components.

PubMed

Goldsmith, J; Greven, S; Crainiceanu, C

2013-03-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. Copyright © 2013, The International Biometric Society.

Corrected Confidence Bands for Functional Data Using Principal Components

PubMed Central

Goldsmith, J.; Greven, S.; Crainiceanu, C.

2014-01-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. PMID:23003003

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

Güver, Tolga; Özel, Feryal; Psaltis, Dimitrios

Many techniques for measuring neutron star radii rely on absolute flux measurements in the X-rays. As a result, one of the fundamental uncertainties in these spectroscopic measurements arises from the absolute flux calibrations of the detectors being used. Using the stable X-ray burster, GS 1826–238, and its simultaneous observations by Chandra HETG/ACIS-S and RXTE /PCA as well as by XMM-Newton EPIC-pn and RXTE /PCA, we quantify the degree of uncertainty in the flux calibration by assessing the differences between the measured fluxes during bursts. We find that the RXTE /PCA and the Chandra gratings measurements agree with each other withinmore » their formal uncertainties, increasing our confidence in these flux measurements. In contrast, XMM-Newton EPIC-pn measures 14.0 ± 0.3% less flux than the RXTE /PCA. This is consistent with the previously reported discrepancy with the flux measurements of EPIC-pn, compared with EPIC MOS1, MOS2, and ACIS-S detectors. We also show that any intrinsic time-dependent systematic uncertainty that may exist in the calibration of the satellites has already been implicity taken into account in the neutron star radius measurements.« less

Estimating the number of motor units using random sums with independently thinned terms.

PubMed

Müller, Samuel; Conforto, Adriana Bastos; Z'graggen, Werner J; Kaelin-Lang, Alain

2006-07-01

The problem of estimating the numbers of motor units N in a muscle is embedded in a general stochastic model using the notion of thinning from point process theory. In the paper a new moment type estimator for the numbers of motor units in a muscle is denned, which is derived using random sums with independently thinned terms. Asymptotic normality of the estimator is shown and its practical value is demonstrated with bootstrap and approximative confidence intervals for a data set from a 31-year-old healthy right-handed, female volunteer. Moreover simulation results are presented and Monte-Carlo based quantiles, means, and variances are calculated for N in{300,600,1000}.

Occupation, industry, and the risk of prostate cancer: a case-control study in Montréal, Canada.

PubMed

Sauvé, Jean-François; Lavoué, Jérôme; Parent, Marie-Élise

2016-10-21

Age, family history and ancestry are the only recognized risk factors for prostate cancer (PCa) but a role for environmental factors is suspected. Due to the lack of knowledge on the etiological factors for PCa, studies that are both hypothesis-generating and confirmatory are still needed. This study explores relationships between employment, by occupation and industry, and PCa risk. Cases were 1937 men aged ≤75 years with incident PCa diagnosed across Montreal French hospitals in 2005-2009. Controls were 1994 men recruited concurrently from electoral lists of French-speaking Montreal residents, frequency-matched to cases by age. In-person interviews elicited occupational histories. Unconditional logistic regression estimated odds ratios (OR) and 95 % confidence intervals (CI) for the association between employment across 696 occupations and 613 industries and PCa risk, adjusting for potential confounders. Multinomial logistic models assessed risks by PCa grade. Semi-Bayes (SB) adjustment accounted for the large number of associations evaluated. Consistently positive associations-and generally robust to SB adjustment-were found for occupations in forestry and logging (OR 1.9, 95 % CI: 1.2-3.0), social sciences (OR 1.6, 95 % CI: 1.1-2.2) and for police officers and detectives (OR: 1.8, 95 % CI 1.1-2.9). Occupations where elevated risk of high grade PCa was found included gasoline station attendants (OR 4.3, 95 % CI 1.8-10.4) and textile processing occupations (OR 1.8, 95 % CI 1.1-3.2). Aside from logging, industries with elevated PCa risk included provincial government and financial institutions. Occupations with reduced risk included farmers (OR 0.6, 95 % CI 0.4-1.0) and aircraft maintenance workers (OR 0.1, 95 % CI 0.0-0.7). Excess PCa risks were observed across several occupations, including predominantly white collar workers. Further analyses will focus on specific occupational exposures.

Genetic variation of genes involved in dihydrotestosterone metabolism and the risk of prostate cancer.

PubMed

Setlur, Sunita R; Chen, Chen X; Hossain, Ruhella R; Ha, Jung Sook; Van Doren, Vanessa E; Stenzel, Birgit; Steiner, Eberhard; Oldridge, Derek; Kitabayashi, Naoki; Banerjee, Samprit; Chen, Jin Yun; Schäfer, Georg; Horninger, Wolfgang; Lee, Charles; Rubin, Mark A; Klocker, Helmut; Demichelis, Francesca

2010-01-01

Dihydrotestosterone (DHT) is an important factor in prostate cancer (PCA) genesis and disease progression. Given PCA's strong genetic component, we evaluated the possibility that variation in genes involved in DHT metabolism influence PCA risk. We investigated copy number variants (CNV) and single nucleotide polymorphisms (SNP). We explored associations between CNV of uridine diphospho-glucuronosyltransferase (UGT) genes from the 2B subclass, given their prostate specificity and/or involvement in steroid metabolism and PCA risk. We also investigated associations between SNPs in genes (HSD3B1, SRD5A1/2, and AKR1C2) involved in the conversion of testosterone to DHT, and in DHT metabolism and PCA risk. The population consisted of 426 men (205 controls and 221 cases) who underwent prostate-specific antigen screening as part of a PCA early detection program in Tyrol, Austria. No association between CNV in UGT2B17 and UGT2B28 and PCA risk was identified. Men carrying the AA genotype at SNP rs6428830 (HSD3B1) had an odds ratio (OR) of 2.0 [95% confidence intervals (95% CI), 1.1-4.1] compared with men with GG, and men with AG or GG versus AA in rs1691053 (SRD5A1) had an OR of 1.8 (95% CI, 1.04-3.13). Individuals carrying both risk alleles had an OR of 3.1 (95% CI, 1.4-6.7) when compared with men carrying neither (P = 0.005). Controls with the AA genotype on rs7594951 (SRD5A2) tended toward higher serum DHT levels (P = 0.03). This is the first study to implicate the 5alpha-reductase isoform 1 (SRD5A1) and PCA risk, supporting the rationale of blocking enzymatic activity of both isoforms of 5alpha-reductase for PCA chemoprevention.

A new framework for comprehensive, robust, and efficient global sensitivity analysis: 2. Application

NASA Astrophysics Data System (ADS)

Razavi, Saman; Gupta, Hoshin V.

2016-01-01

Based on the theoretical framework for sensitivity analysis called "Variogram Analysis of Response Surfaces" (VARS), developed in the companion paper, we develop and implement a practical "star-based" sampling strategy (called STAR-VARS), for the application of VARS to real-world problems. We also develop a bootstrap approach to provide confidence level estimates for the VARS sensitivity metrics and to evaluate the reliability of inferred factor rankings. The effectiveness, efficiency, and robustness of STAR-VARS are demonstrated via two real-data hydrological case studies (a 5-parameter conceptual rainfall-runoff model and a 45-parameter land surface scheme hydrology model), and a comparison with the "derivative-based" Morris and "variance-based" Sobol approaches are provided. Our results show that STAR-VARS provides reliable and stable assessments of "global" sensitivity across the full range of scales in the factor space, while being 1-2 orders of magnitude more efficient than the Morris or Sobol approaches.

Comparison of mode estimation methods and application in molecular clock analysis

NASA Technical Reports Server (NTRS)

Hedges, S. Blair; Shah, Prachi

2003-01-01

BACKGROUND: Distributions of time estimates in molecular clock studies are sometimes skewed or contain outliers. In those cases, the mode is a better estimator of the overall time of divergence than the mean or median. However, different methods are available for estimating the mode. We compared these methods in simulations to determine their strengths and weaknesses and further assessed their performance when applied to real data sets from a molecular clock study. RESULTS: We found that the half-range mode and robust parametric mode methods have a lower bias than other mode methods under a diversity of conditions. However, the half-range mode suffers from a relatively high variance and the robust parametric mode is more susceptible to bias by outliers. We determined that bootstrapping reduces the variance of both mode estimators. Application of the different methods to real data sets yielded results that were concordant with the simulations. CONCLUSION: Because the half-range mode is a simple and fast method, and produced less bias overall in our simulations, we recommend the bootstrapped version of it as a general-purpose mode estimator and suggest a bootstrap method for obtaining the standard error and 95% confidence interval of the mode.

A Web-based nomogram predicting para-aortic nodal metastasis in incompletely staged patients with endometrial cancer: a Korean Multicenter Study.

PubMed

Kang, Sokbom; Lee, Jong-Min; Lee, Jae-Kwan; Kim, Jae-Weon; Cho, Chi-Heum; Kim, Seok-Mo; Park, Sang-Yoon; Park, Chan-Yong; Kim, Ki-Tae

2014-03-01

The purpose of this study is to develop a Web-based nomogram for predicting the individualized risk of para-aortic nodal metastasis in incompletely staged patients with endometrial cancer. From 8 institutions, the medical records of 397 patients who underwent pelvic and para-aortic lymphadenectomy as a surgical staging procedure were retrospectively reviewed. A multivariate logistic regression model was created and internally validated by rigorous bootstrap resampling methods. Finally, the model was transformed into a user-friendly Web-based nomogram (http://http://www.kgog.org/nomogram/empa001.html). The rate of para-aortic nodal metastasis was 14.4% (57/397 patients). Using a stepwise variable selection, 4 variables including deep myometrial invasion, non-endometrioid subtype, lymphovascular space invasion, and log-transformed CA-125 levels were finally adopted. After 1000 repetitions of bootstrapping, all of these 4 variables retained a significant association with para-aortic nodal metastasis in the multivariate analysis-deep myometrial invasion (P = 0.001), non-endometrioid histologic subtype (P = 0.034), lymphovascular space invasion (P = 0.003), and log-transformed serum CA-125 levels (P = 0.004). The model showed good discrimination (C statistics = 0.87; 95% confidence interval, 0.82-0.92) and accurate calibration (Hosmer-Lemeshow P = 0.74). This nomogram showed good performance in predicting para-aortic metastasis in patients with endometrial cancer. The tool may be useful in determining the extent of lymphadenectomy after incomplete surgery.

Assessing participation in community-based physical activity programs in Brazil.

PubMed

Reis, Rodrigo S; Yan, Yan; Parra, Diana C; Brownson, Ross C

2014-01-01

This study aimed to develop and validate a risk prediction model to examine the characteristics that are associated with participation in community-based physical activity programs in Brazil. We used pooled data from three surveys conducted from 2007 to 2009 in state capitals of Brazil with 6166 adults. A risk prediction model was built considering program participation as an outcome. The predictive accuracy of the model was quantified through discrimination (C statistic) and calibration (Brier score) properties. Bootstrapping methods were used to validate the predictive accuracy of the final model. The final model showed sex (women: odds ratio [OR] = 3.18, 95% confidence interval [CI] = 2.14-4.71), having less than high school degree (OR = 1.71, 95% CI = 1.16-2.53), reporting a good health (OR = 1.58, 95% CI = 1.02-2.24) or very good/excellent health (OR = 1.62, 95% CI = 1.05-2.51), having any comorbidity (OR = 1.74, 95% CI = 1.26-2.39), and perceiving the environment as safe to walk at night (OR = 1.59, 95% CI = 1.18-2.15) as predictors of participation in physical activity programs. Accuracy indices were adequate (C index = 0.778, Brier score = 0.031) and similar to those obtained from bootstrapping (C index = 0.792, Brier score = 0.030). Sociodemographic and health characteristics as well as perceptions of the environment are strong predictors of participation in community-based programs in selected cities of Brazil.

Brachytherapy Boost Utilization and Survival in Unfavorable-risk Prostate Cancer.

PubMed

Johnson, Skyler B; Lester-Coll, Nataniel H; Kelly, Jacqueline R; Kann, Benjamin H; Yu, James B; Nath, Sameer K

2017-11-01

There are limited comparative survival data for prostate cancer (PCa) patients managed with a low-dose rate brachytherapy (LDR-B) boost and dose-escalated external-beam radiotherapy (DE-EBRT) alone. To compare overall survival (OS) for men with unfavorable PCa between LDR-B and DE-EBRT groups. Using the National Cancer Data Base, we identified men with unfavorable PCa treated between 2004 and 2012 with androgen suppression (AS) and either EBRT followed by LDR-B or DE-EBRT (75.6-86.4Gy). Treatment selection was evaluated using logistic regression and annual percentage proportions. OS was analyzed using the Kaplan-Meier method, log-rank test, Cox proportional hazards, and propensity score matching. We identified 25038 men between 2004 and 2012, during which LDR-B boost utilization decreased from 29% to 14%. LDR-B was associated with better OS on univariate (7-yr OS: 82% vs 73%; p<0.001) and multivariate analyses (hazard ratio [HR] 0.70, 95% confidence interval [CI] 0.64-0.77). Propensity score matching verified an OS benefit associated with LDR-B boost (HR 0.74, 95% CI 0.66-0.89). The OS benefit of LDR-B boost persisted when limited to men aged <60 yr with no comorbidities. On subset analysis, there was no interaction between treatment and age, risk group, or radiation dose. Limitations include the retrospective design, nonrandomized selection bias, and the absence of treatment toxicity, hormone duration, and cancer-specific outcomes. Between 2004 and 2012, LDR-B boost utilization declined and was associated with better OS compared to DE-EBRT alone. LDR-B boost is probably the ideal treatment option for men with unfavorable PCa, pending long-term results of randomized trials. We compared radiotherapy utilization and survival for prostate cancer (PCa) patients using a national database. We found that low-dose rate brachytherapy (LDR-B) boost, a method being used less frequently, was associated with better overall survival when compared to dose-escalated external-beam radiotherapy alone for men with unfavorable PCa. Randomized trials are needed to confirm that LDR-B boost is the ideal treatment. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

A bootstrap lunar base: Preliminary design review 2

NASA Technical Reports Server (NTRS)

1987-01-01

A bootstrap lunar base is the gateway to manned solar system exploration and requires new ideas and new designs on the cutting edge of technology. A preliminary design for a Bootstrap Lunar Base, the second provided by this contractor, is presented. An overview of the work completed is discussed as well as the technical, management, and cost strategies to complete the program requirements. The lunar base design stresses the transforming capabilities of its lander vehicles to aid in base construction. The design also emphasizes modularity and expandability in the base configuration to support the long-term goals of scientific research and profitable lunar resource exploitation. To successfully construct, develop, and inhabit a permanent lunar base, however, several technological advancements must first be realized. Some of these technological advancements are also discussed.

Coupling of on-column trypsin digestion-peptide mapping and principal component analysis for stability and biosimilarity assessment of recombinant human growth hormone.

PubMed

Shatat, Sara M; Eltanany, Basma M; Mohamed, Abeer A; Al-Ghobashy, Medhat A; Fathalla, Faten A; Abbas, Samah S

2018-01-01

Peptide mapping (PM) is a vital technique in biopharmaceutical industry. The fingerprint obtained helps to qualitatively confirm host stability as well as verify primary structure, purity and integrity of the target protein. Yet, in-solution digestion followed by tandem mass spectrometry is not suitable as a routine quality control test. It is time consuming and requires sophisticated, expensive instruments and highly skilled operators. In an attempt to enhance the fuctionality of PM and extract multi-dimentional data about various critical quality attributes and comparability of biosimilars, coupling of PM generated using immobilized trypsin followed by HPLC-UV to principal component analysis (PCA) is proposed. Recombinant human growth hormone (rhGH); was selected as a model biopharmaceutical since it is available in the market from different manufacturers and its PM is a well-established pharmacopoeial test. Samples of different rhGH biosimilars as well as degraded samples: deamidated and oxidized were subjected to trypsin digestion followed by RP-HPLC-UV analysis. PCA of the entire chromatograms of test and reference samples was then conducted. Comparison of the scores of samples and investigation of the loadings plots clearly indicated the applicability of PM-PCA for: i) identity testing, ii) biosimilarity assessment and iii) stability evaluation. Hotelling's T 2 and Q statistics were employed at 95% confidence level to measure the variation and to test the conformance of each sample to the PCA model, respectively. Coupling of PM to PCA provided a novel tool to identify peptide fragments responsible for variation between the test and reference samples as well as evaluation of the extent and relative significance of this variability. Transformation of conventional PM that is largely based on subjective visual comparison into an objective statiscally-guided analysis framework should provide a simple and economic tool to help both manufacturers and regulatory authorities in quality and biosimilarity assessment of biopharmaceuticals. Copyright © 2017 Elsevier B.V. All rights reserved.

Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis.

PubMed

Austin, Peter C

2016-12-30

Propensity score methods are used to reduce the effects of observed confounding when using observational data to estimate the effects of treatments or exposures. A popular method of using the propensity score is inverse probability of treatment weighting (IPTW). When using this method, a weight is calculated for each subject that is equal to the inverse of the probability of receiving the treatment that was actually received. These weights are then incorporated into the analyses to minimize the effects of observed confounding. Previous research has found that these methods result in unbiased estimation when estimating the effect of treatment on survival outcomes. However, conventional methods of variance estimation were shown to result in biased estimates of standard error. In this study, we conducted an extensive set of Monte Carlo simulations to examine different methods of variance estimation when using a weighted Cox proportional hazards model to estimate the effect of treatment. We considered three variance estimation methods: (i) a naïve model-based variance estimator; (ii) a robust sandwich-type variance estimator; and (iii) a bootstrap variance estimator. We considered estimation of both the average treatment effect and the average treatment effect in the treated. We found that the use of a bootstrap estimator resulted in approximately correct estimates of standard errors and confidence intervals with the correct coverage rates. The other estimators resulted in biased estimates of standard errors and confidence intervals with incorrect coverage rates. Our simulations were informed by a case study examining the effect of statin prescribing on mortality. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

The Burden of Urinary Incontinence and Urinary Bother Among Elderly Prostate Cancer Survivors

PubMed Central

Kopp, Ryan P.; Marshall, Lynn M.; Wang, Patty Y.; Bauer, Douglas C.; Barrett-Connor, Elizabeth; Parsons, J. Kellogg

2014-01-01

Background Data describing urinary health in elderly, community-dwelling prostate cancer (PCa) survivors are limited. Objective To elucidate the prevalence of lower urinary tract symptoms, urinary bother, and incontinence in elderly PCa survivors compared with peers without PCa. Design, setting, and participants A cross-sectional analysis of 5990 participants in the Osteoporotic Fractures in Men Research Group, a cohort study of community-dwelling men ≥65 yr. Outcome measurements and statistical analysis We characterized urinary health using self-reported urinary incontinence and the American Urological Association Symptom Index (AUA-SI). We compared urinary health measures according to type of PCa treatment in men with PCa and men without PCa using multivariate log-binomial regression to generate prevalence ratios (PRs). Results and limitations At baseline, 706 men (12%) reported a history of PCa, with a median time since diagnosis of 6.3 yr. Of these men, 426 (60%) reported urinary incontinence. In adjusted analyses, observation (PR: 1.92; 95% confidence interval [CI], 1.15–3.21; p = 0.01), surgery (PR: 4.68; 95% CI, 4.11–5.32; p < 0.0001), radiation therapy (PR: 1.64; 95% CI, 1.20– 2.23; p = 0.002), and androgen-deprivation therapy (ADT) (PR: 2.01; 95% CI, 1.35–2.99; p = 0.0006) were each associated with daily incontinence. Daily incontinence risk increased with time since diagnosis independently of age. Observation (PR: 1.33; 95% CI, 1.00–1.78; p = 0.05), surgery (PR: 1.25; 95% CI, 1.10–1.42; p = 0.0008), and ADT (PR: 1.50; 95% CI, 1.26–1.79; p < 0.0001) were associated with increased AUA-SI bother scores. Cancer stage and use of adjuvant or salvage therapies were not available for analysis. Conclusions Compared with their peers without PCa, elderly PCa survivors had a two-fold to five-fold greater prevalence of urinary incontinence, which rose with increasing survivorship duration. Observation, surgery, and ADT were each associated with increased urinary bother. These data suggest a substantially greater burden of urinary health problems among elderly PCa survivors than previously recognized. PMID:23587870

The burden of urinary incontinence and urinary bother among elderly prostate cancer survivors.

PubMed

Kopp, Ryan P; Marshall, Lynn M; Wang, Patty Y; Bauer, Douglas C; Barrett-Connor, Elizabeth; Parsons, J Kellogg

2013-10-01

Data describing urinary health in elderly, community-dwelling prostate cancer (PCa) survivors are limited. To elucidate the prevalence of lower urinary tract symptoms, urinary bother, and incontinence in elderly PCa survivors compared with peers without PCa. A cross-sectional analysis of 5990 participants in the Osteoporotic Fractures in Men Research Group, a cohort study of community-dwelling men ≥ 65 yr. We characterized urinary health using self-reported urinary incontinence and the American Urological Association Symptom Index (AUA-SI). We compared urinary health measures according to type of PCa treatment in men with PCa and men without PCa using multivariate log-binomial regression to generate prevalence ratios (PRs). At baseline, 706 men (12%) reported a history of PCa, with a mean time since diagnosis of 6.3 yr. Of these men, 426 (60%) reported urinary incontinence. In adjusted analyses, observation (PR: 2.11; 95% confidence interval [CI], 1.22-3.65; p=0.007), surgery (PR: 4.41; 95% CI, 3.79-5.13; p<0.0001), radiation therapy (PR: 1.49; 95% CI, 1.06-2.08; p=0.02), and androgen-deprivation therapy (ADT) (PR: 2.02; 95% CI, 1.31-3.13; p=0.002) were each associated with daily incontinence. Daily incontinence risk increased with time since diagnosis independently of age. Observation (PR: 1.33; 95% CI, 1.00-1.78; p=0.05), surgery (PR: 1.25; 95% CI, 1.10-1.42; p=0.0008), and ADT (PR: 1.50; 95% CI, 1.26-1.79; p<0.0001) were associated with increased AUA-SI bother scores. Cancer stage and use of adjuvant or salvage therapies were not available for analysis. Compared with their peers without PCa, elderly PCa survivors had a two-fold to five-fold greater prevalence of urinary incontinence, which rose with increasing survivorship duration. Observation, surgery, and ADT were each associated with increased urinary bother. These data suggest a substantially greater burden of urinary health problems among elderly PCa survivors than previously recognized. Copyright © 2013 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Bootstrap Prediction Intervals in Non-Parametric Regression with Applications to Anomaly Detection

NASA Technical Reports Server (NTRS)

Kumar, Sricharan; Srivistava, Ashok N.

2012-01-01

Prediction intervals provide a measure of the probable interval in which the outputs of a regression model can be expected to occur. Subsequently, these prediction intervals can be used to determine if the observed output is anomalous or not, conditioned on the input. In this paper, a procedure for determining prediction intervals for outputs of nonparametric regression models using bootstrap methods is proposed. Bootstrap methods allow for a non-parametric approach to computing prediction intervals with no specific assumptions about the sampling distribution of the noise or the data. The asymptotic fidelity of the proposed prediction intervals is theoretically proved. Subsequently, the validity of the bootstrap based prediction intervals is illustrated via simulations. Finally, the bootstrap prediction intervals are applied to the problem of anomaly detection on aviation data.

Retirement and primary cardiac arrest in males.

PubMed Central

Siscovick, D S; Strogatz, D S; Weiss, N S; Rennert, G

1990-01-01

We investigated the association between retirement and primary cardiac arrest (PCA) in 126 male cases and controls, 25-75 years of age, without prior heart disease or comorbidity. After adjustment for age alone, retirement was not associated with an increased risk of PCA, (OR = 1.1; 95% confidence intervals = 0.5, 2.4). This lack of association was not uniform across age strata, however. In 10 of 19 discordant pairs 60 or more years of age, the control subject had been retired; in all seven discordant pairs under 60, the case had been retired (lower 95% CI of the relative risk = 1.9). PMID:2297069

Lack of association between NAT2 polymorphism and prostate cancer risk: a meta-analysis and trial sequential analysis

PubMed Central

Tang, Jingyuan; Xu, Lingyan; Xu, Haoxiang; Li, Ran; Han, Peng; Yang, Haiwei

2017-01-01

Previous studies have investigated the association between NAT2 polymorphism and the risk of prostate cancer (PCa). However, the findings from these studies remained inconsistent. Hence, we performed a meta-analysis to provide a more reliable conclusion about such associations. In the present meta-analysis, 13 independent case-control studies were included with a total of 14,469 PCa patients and 10,689 controls. All relevant studies published were searched in the databates PubMed, EMBASE, and Web of Science, till March 1st, 2017. We used the pooled odds ratios (ORs) with 95% confidence intervals (CIs) to evaluate the strength of the association between NAT2*4 allele and susceptibility to PCa. Subgroup analysis was carried out by ethnicity, source of controls and genotyping method. What's more, we also performed trial sequential analysis (TSA) to reduce the risk of type I error and evaluate whether the evidence of the results was firm. Firstly, our results indicated that NAT2*4 allele was not associated with PCa susceptibility (OR = 1.00, 95% CI= 0.95–1.05; P = 0.100). However, after excluding two studies for its heterogeneity and publication bias, no significant relationship was also detected between NAT2*4 allele and the increased risk of PCa, in fixed-effect model (OR = 0.99, 95% CI= 0.94–1.04; P = 0.451). Meanwhile, no significant increased risk of PCa was found in the subgroup analyses by ethnicity, source of controls and genotyping method. Moreover, TSA demonstrated that such association was confirmed in the present study. Therefore, this meta-analysis suggested that no significant association between NAT2 polymorphism and the risk of PCa was found. PMID:28915684

Ketamine added to morphine or hydromorphone patient-controlled analgesia for acute postoperative pain in adults: a systematic review and meta-analysis of randomized trials.

PubMed

Wang, Li; Johnston, Bradley; Kaushal, Alka; Cheng, Davy; Zhu, Fang; Martin, Janet

2016-03-01

To determine whether ketamine added to morphine or hydromorphone patient-controlled analgesia (PCA) provides clinically relevant reductions in postoperative pain, opioid requirements, and adverse events when compared with morphine or hydromorphone PCA in adults undergoing surgery. We systematically searched six databases up to June 2, 2015 for randomized controlled trials (RCTs) comparing ketamine plus morphine/hydromorphone PCA vs morphine/hydromorphone PCA for postoperative pain in adults. Thirty-six RCTs including 2,502 patients proved eligible, and 22 of these were at low risk of bias. The addition of ketamine to morphine/hydromorphone PCA decreased postoperative pain intensity at six to 72 hr when measured at rest (weighted mean difference [WMD] on a 10-cm visual analogue scale ranged from -0.4 to -1.3 cm) and during mobilization (WMD ranged from -0.4 to -0.5 cm). Adjunctive ketamine also significantly reduced cumulative morphine consumption at 24-72 hr by approximately 5-20 mg. Predefined subgroup analyses and meta-regression did not detect significant differences across subgroups, including a dose-response relationship. There was no significant difference in patient satisfaction scores at 24 and 48 hr. Nevertheless, the addition of ketamine to morphine/hydromorphone PCA significantly reduced postoperative nausea and vomiting (relative risk, 0.71; 95% confidence interval [CI], 0.60 to 0.85; absolute risk reduction, 8.9%; 95% CI, 4.6 to 12.2). Significant effects on other adverse events (e.g., hallucinations, vivid dreams) were not detected, though only a few studies reported on them. Adding ketamine to morphine/hydromorphone PCA provides a small improvement in postoperative analgesia while reducing opioid requirements. Adjunctive ketamine also reduces postoperative nausea and vomiting without a detected increase in other adverse effects; however, adverse events were probably underreported.

Rapid and accurate taxonomic classification of insect (class Insecta) cytochrome c oxidase subunit 1 (COI) DNA barcode sequences using a naïve Bayesian classifier

PubMed Central

Porter, Teresita M; Gibson, Joel F; Shokralla, Shadi; Baird, Donald J; Golding, G Brian; Hajibabaei, Mehrdad

2014-01-01

Current methods to identify unknown insect (class Insecta) cytochrome c oxidase (COI barcode) sequences often rely on thresholds of distances that can be difficult to define, sequence similarity cut-offs, or monophyly. Some of the most commonly used metagenomic classification methods do not provide a measure of confidence for the taxonomic assignments they provide. The aim of this study was to use a naïve Bayesian classifier (Wang et al. Applied and Environmental Microbiology, 2007; 73: 5261) to automate taxonomic assignments for large batches of insect COI sequences such as data obtained from high-throughput environmental sequencing. This method provides rank-flexible taxonomic assignments with an associated bootstrap support value, and it is faster than the blast-based methods commonly used in environmental sequence surveys. We have developed and rigorously tested the performance of three different training sets using leave-one-out cross-validation, two field data sets, and targeted testing of Lepidoptera, Diptera and Mantodea sequences obtained from the Barcode of Life Data system. We found that type I error rates, incorrect taxonomic assignments with a high bootstrap support, were already relatively low but could be lowered further by ensuring that all query taxa are actually present in the reference database. Choosing bootstrap support cut-offs according to query length and summarizing taxonomic assignments to more inclusive ranks can also help to reduce error while retaining the maximum number of assignments. Additionally, we highlight gaps in the taxonomic and geographic representation of insects in public sequence databases that will require further work by taxonomists to improve the quality of assignments generated using any method.

PCA3-based nomogram for predicting prostate cancer and high grade cancer on initial transrectal guided biopsy.

PubMed

Elshafei, Ahmed; Chevli, K Kent; Moussa, Ayman S; Kara, Onder; Chueh, Shih-Chieh; Walter, Peter; Hatem, Asmaa; Gao, Tianming; Jones, J Stephen; Duff, Michael

2015-12-01

To develop a validated prostate cancer antigen 3 (PCA3) based nomogram that predicts likelihood of overall prostate cancer (PCa) and intermediate/high grade prostate cancer (HGPCa) in men pursuing initial transrectal prostate biopsy (TRUS-PBx). Data were collected on 3,675 men with serum prostate specific antigen level (PSA) ≤ 20 ng/ml who underwent initial prostate biopsy with at least 10 cores sampling at time of the biopsy. Two logistic regression models were constructed to predict overall PCa and HGPCa incorporating age, race, family history (FH) of PCa, PSA at diagnosis, PCA3, total prostate volume (TPV), and digital rectal exam (DRE). One thousand six hundred twenty (44%) patients had biopsy confirmed PCa with 701 men (19.1%) showing HGPCa. Statistically significant predictors of overall PCa were age (P < 0.0001, OR. 1.51), PSA at diagnosis (P < 0.0001, OR.1.95), PCA3 (P < 0.0001, OR.3.06), TPV (P < 0.0001, OR.0.47), FH (P = 0.003, OR.1.32), and abnormal DRE (P = 0.001, OR. 1.32). While for HGPCa, predictors were age (P < 0.0001, OR.1.77), PSA (P < 0.0001, OR.2.73), PCA3 (P < 0.0001, OR.2.26), TPV (P < 0.0001, OR.0.4), and DRE (P < 0.0001, OR.1.53). Two nomograms were reconstructed for predicted overall PCa probability at time of initial biopsy with a concordance index of 0.742 (Fig. 1), and HGPCa with a concordance index of 0.768 (Fig. 2). Our internally validated initial biopsy PCA3 based nomogram is reconstructed based on a large dataset. The c-index indicates high predictive accuracy, especially for high grade PCa and improves the ability to predict biopsy outcomes. © 2015 Wiley Periodicals, Inc.

Topics in Statistical Calibration

DTIC Science & Technology

2014-03-27

on a parametric bootstrap where, instead of sampling directly from the residuals , samples are drawn from a normal distribution. This procedure will...addition to centering them (Davison and Hinkley, 1997). When there are outliers in the residuals , the bootstrap distribution of x̂0 can become skewed or...based and inversion methods using the linear mixed-effects model. Then, a simple parametric bootstrap algorithm is proposed that can be used to either

A bootstrap estimation scheme for chemical compositional data with nondetects

USGS Publications Warehouse

Palarea-Albaladejo, J; Martín-Fernández, J.A; Olea, Ricardo A.

2014-01-01

The bootstrap method is commonly used to estimate the distribution of estimators and their associated uncertainty when explicit analytic expressions are not available or are difficult to obtain. It has been widely applied in environmental and geochemical studies, where the data generated often represent parts of whole, typically chemical concentrations. This kind of constrained data is generically called compositional data, and they require specialised statistical methods to properly account for their particular covariance structure. On the other hand, it is not unusual in practice that those data contain labels denoting nondetects, that is, concentrations falling below detection limits. Nondetects impede the implementation of the bootstrap and represent an additional source of uncertainty that must be taken into account. In this work, a bootstrap scheme is devised that handles nondetects by adding an imputation step within the resampling process and conveniently propagates their associated uncertainly. In doing so, it considers the constrained relationships between chemical concentrations originated from their compositional nature. Bootstrap estimates using a range of imputation methods, including new stochastic proposals, are compared across scenarios of increasing difficulty. They are formulated to meet compositional principles following the log-ratio approach, and an adjustment is introduced in the multivariate case to deal with nonclosed samples. Results suggest that nondetect bootstrap based on model-based imputation is generally preferable. A robust approach based on isometric log-ratio transformations appears to be particularly suited in this context. Computer routines in the R statistical programming language are provided. 

Comparison of Bootstrapping and Markov Chain Monte Carlo for Copula Analysis of Hydrological Droughts

NASA Astrophysics Data System (ADS)

Yang, P.; Ng, T. L.; Yang, W.

2015-12-01

Effective water resources management depends on the reliable estimation of the uncertainty of drought events. Confidence intervals (CIs) are commonly applied to quantify this uncertainty. A CI seeks to be at the minimal length necessary to cover the true value of the estimated variable with the desired probability. In drought analysis where two or more variables (e.g., duration and severity) are often used to describe a drought, copulas have been found suitable for representing the joint probability behavior of these variables. However, the comprehensive assessment of the parameter uncertainties of copulas of droughts has been largely ignored, and the few studies that have recognized this issue have not explicitly compared the various methods to produce the best CIs. Thus, the objective of this study to compare the CIs generated using two widely applied uncertainty estimation methods, bootstrapping and Markov Chain Monte Carlo (MCMC). To achieve this objective, (1) the marginal distributions lognormal, Gamma, and Generalized Extreme Value, and the copula functions Clayton, Frank, and Plackett are selected to construct joint probability functions of two drought related variables. (2) The resulting joint functions are then fitted to 200 sets of simulated realizations of drought events with known distribution and extreme parameters and (3) from there, using bootstrapping and MCMC, CIs of the parameters are generated and compared. The effect of an informative prior on the CIs generated by MCMC is also evaluated. CIs are produced for different sample sizes (50, 100, and 200) of the simulated drought events for fitting the joint probability functions. Preliminary results assuming lognormal marginal distributions and the Clayton copula function suggest that for cases with small or medium sample sizes (~50-100), MCMC to be superior method if an informative prior exists. Where an informative prior is unavailable, for small sample sizes (~50), both bootstrapping and MCMC yield the same level of performance, and for medium sample sizes (~100), bootstrapping is better. For cases with a large sample size (~200), there is little difference between the CIs generated using bootstrapping and MCMC regardless of whether or not an informative prior exists.

External validation of a PCA-3-based nomogram for predicting prostate cancer and high-grade cancer on initial prostate biopsy.

PubMed

Greene, Daniel J; Elshafei, Ahmed; Nyame, Yaw A; Kara, Onder; Malkoc, Ercan; Gao, Tianming; Jones, J Stephen

2016-08-01

The aim of this study was to externally validate a previously developed PCA3-based nomogram for the prediction of prostate cancer (PCa) and high-grade (intermediate and/or high-grade) prostate cancer (HGPCa) at the time of initial prostate biopsy. A retrospective review was performed on a cohort of 336 men from a large urban academic medical center. All men had serum PSA <20 ng/ml and underwent initial transrectal ultrasound-guided prostate biopsy with at least 10 cores sampling for suspicious exam and/or elevated PSA. Covariates were collected for the nomogram and included age, ethnicity, family history (FH) of PCa, PSA at diagnosis, PCA3, total prostate volume (TPV), and abnormal finding on digital rectal exam (DRE). These variables were used to test the accuracy (concordance index) and calibration of a previously published PCA3 nomogram. Biopsy confirms PCa and HGPCa in 51.0% and 30.4% of validation patients, respectively. This differed from the original cohort in that it had significantly more PCa and HGPCA (51% vs. 44%, P = 0.019; and 30.4% vs. 19.1%, P < 0.001). Despite the differences in PCa detection the concordance index was 75% and 77% for overall PCa and HGPCa, respectively. Calibration for overall PCa was good. This represents the first external validation of a PCA3-based prostate cancer predictive nomogram in a North American population. Prostate 76:1019-1023, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Diagnostic Pathway with Multiparametric Magnetic Resonance Imaging Versus Standard Pathway: Results from a Randomized Prospective Study in Biopsy-naïve Patients with Suspected Prostate Cancer.

PubMed

Porpiglia, Francesco; Manfredi, Matteo; Mele, Fabrizio; Cossu, Marco; Bollito, Enrico; Veltri, Andrea; Cirillo, Stefano; Regge, Daniele; Faletti, Riccardo; Passera, Roberto; Fiori, Cristian; De Luca, Stefano

2017-08-01

An approach based on multiparametric magnetic resonance imaging (mpMRI) might increase the detection rate (DR) of clinically significant prostate cancer (csPCa). To compare an mpMRI-based pathway with the standard approach for the detection of prostate cancer (PCa) and csPCa. Between November 2014 and April 2016, 212 biopsy-naïve patients with suspected PCa (prostate specific antigen level ≤15 ng/ml and negative digital rectal examination results) were included in this randomized clinical trial. Patients were randomized into a prebiopsy mpMRI group (arm A, n=107) or a standard biopsy (SB) group (arm B, n=105). In arm A, patients with mpMRI evidence of lesions suspected for PCa underwent mpMRI/transrectal ultrasound fusion software-guided targeted biopsy (TB) (n=81). The remaining patients in arm A (n=26) with negative mpMRI results and patients in arm B underwent 12-core SB. The primary end point was comparison of the DR of PCa and csPCa between the two arms of the study; the secondary end point was comparison of the DR between TB and SB. The overall DRs were higher in arm A versus arm B for PCa (50.5% vs 29.5%, respectively; p=0.002) and csPCa (43.9% vs 18.1%, respectively; p<0.001). Concerning the biopsy approach, that is, TB in arm A, SB in arm A, and SB in arm B, the overall DRs were significantly different for PCa (60.5% vs 19.2% vs 29.5%, respectively; p<0.001) and for csPCa (56.8% vs 3.8% vs 18.1%, respectively; p<0.001). The reproducibility of the study could have been affected by the single-center nature. A diagnostic pathway based on mpMRI had a higher DR than the standard pathway in both PCa and csPCa. In this randomized trial, a pathway for the diagnosis of prostate cancer based on multiparametric magnetic resonance imaging (mpMRI) was compared with the standard pathway based on random biopsy. The mpMRI-based pathway had better performance than the standard pathway. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Facebook and Twitter vaccine sentiment in response to measles outbreaks.

PubMed

Deiner, Michael S; Fathy, Cherie; Kim, Jessica; Niemeyer, Katherine; Ramirez, David; Ackley, Sarah F; Liu, Fengchen; Lietman, Thomas M; Porco, Travis C

2017-11-01

Social media posts regarding measles vaccination were classified as pro-vaccination, expressing vaccine hesitancy, uncertain, or irrelevant. Spearman correlations with Centers for Disease Control and Prevention-reported measles cases and differenced smoothed cumulative case counts over this period were reported (using time series bootstrap confidence intervals). A total of 58,078 Facebook posts and 82,993 tweets were identified from 4 January 2009 to 27 August 2016. Pro-vaccination posts were correlated with the US weekly reported cases (Facebook: Spearman correlation 0.22 (95% confidence interval: 0.09 to 0.34), Twitter: 0.21 (95% confidence interval: 0.06 to 0.34)). Vaccine-hesitant posts, however, were uncorrelated with measles cases in the United States (Facebook: 0.01 (95% confidence interval: -0.13 to 0.14), Twitter: 0.0011 (95% confidence interval: -0.12 to 0.12)). These findings may result from more consistent social media engagement by individuals expressing vaccine hesitancy, contrasted with media- or event-driven episodic interest on the part of individuals favoring current policy.

Germline Mutations in ATM and BRCA1/2 Distinguish Risk for Lethal and Indolent Prostate Cancer and are Associated with Early Age at Death

PubMed Central

Na, Rong; Zheng, S. Lilly; Han, Misop; Yu, Hongjie; Jiang, Deke; Shah, Sameep; Ewing, Charles M.; Zhang, Liti; Novakovic, Kristian; Petkewicz, Jacqueline; Gulukota, Kamalakar; Helseth, Donald L.; Quinn, Margo; Humphries, Elizabeth; Wiley, Kathleen E.; Isaacs, Sarah D.; Wu, Yishuo; Liu, Xu; Zhang, Ning; Wang, Chi-Hsiung; Khandekar, Janardan; Hulick, Peter J.; Shevrin, Daniel H.; Cooney, Kathleen A.; Shen, Zhoujun; Partin, Alan W.; Carter, H. Ballentine; Carducci, Michael A.; Eisenberger, Mario A.; Denmeade, Sam R.; McGuire, Michael; Walsh, Patrick C.; Helfand, Brian T.; Brendler, Charles B.; Ding, Qiang; Xu, Jianfeng; Isaacs, William B.

2017-01-01

Background Germline mutations in BRCA1/2 and ATM have been associated with prostate cancer (PCa) risk. Objective To directly assess whether germline mutations in these three genes distinguish lethal from indolent PCa and whether they confer any effect on age at death. Design, setting, and participants A retrospective case-case study of 313 patients who died of PCa and 486 patients with low-risk localized PCa of European, African, and Chinese descent. Germline DNA of each of the 799 patients was sequenced for these three genes. Outcome measurements and statistical analysis Mutation carrier rates and their effect on lethal PCa were analyzed using the Fisher’s exact test and Cox regression analysis, respectively. Results and limitations The combined BRCA1/2 and ATM mutation carrier rate was significantly higher in lethal PCa patients (6.07%) than localized PCa patients (1.44%), p = 0.0007. The rate also differed significantly among lethal PCa patients as a function of age at death (10.00%, 9.08%, 8.33%, 4.94%, and 2.97% in patients who died ≤60 yr, 61–65 yr, 66–70 yr, 71–75 yr, and over 75 yr, respectively, p = 0.046) and time to death after diagnosis (12.26%, 4.76%, and 0.98% in patients who died ≤5 yr, 6–10 yr, and > 10 yr after a PCa diagnosis, respectively, p = 0.0006). Survival analysis in the entire cohort revealed mutation carriers remained an independent predictor of lethal PCa after adjusting for race and age, prostate-specific antigen, and Gleason score at the time of diagnosis (hazard ratio = 2.13, 95% confidence interval: 1.24–3.66, p = 0.004). A limitation of this study is that other DNA repair genes were not analyzed. Conclusions Mutation status of BRCA1/2 and ATM distinguishes risk for lethal and indolent PCa and is associated with earlier age at death and shorter survival time. Patient summary Prostate cancer patients with inherited mutations in BRCA1/2 and ATM are more likely to die of prostate cancer and do so at an earlier age. PMID:27989354

The PIT-trap-A "model-free" bootstrap procedure for inference about regression models with discrete, multivariate responses.

PubMed

Warton, David I; Thibaut, Loïc; Wang, Yi Alice

2017-01-01

Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)-common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of "model-free bootstrap", adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods.

Incorporating external evidence in trial-based cost-effectiveness analyses: the use of resampling methods

PubMed Central

2014-01-01

Background Cost-effectiveness analyses (CEAs) that use patient-specific data from a randomized controlled trial (RCT) are popular, yet such CEAs are criticized because they neglect to incorporate evidence external to the trial. A popular method for quantifying uncertainty in a RCT-based CEA is the bootstrap. The objective of the present study was to further expand the bootstrap method of RCT-based CEA for the incorporation of external evidence. Methods We utilize the Bayesian interpretation of the bootstrap and derive the distribution for the cost and effectiveness outcomes after observing the current RCT data and the external evidence. We propose simple modifications of the bootstrap for sampling from such posterior distributions. Results In a proof-of-concept case study, we use data from a clinical trial and incorporate external evidence on the effect size of treatments to illustrate the method in action. Compared to the parametric models of evidence synthesis, the proposed approach requires fewer distributional assumptions, does not require explicit modeling of the relation between external evidence and outcomes of interest, and is generally easier to implement. A drawback of this approach is potential computational inefficiency compared to the parametric Bayesian methods. Conclusions The bootstrap method of RCT-based CEA can be extended to incorporate external evidence, while preserving its appealing features such as no requirement for parametric modeling of cost and effectiveness outcomes. PMID:24888356

Incorporating external evidence in trial-based cost-effectiveness analyses: the use of resampling methods.

PubMed

Sadatsafavi, Mohsen; Marra, Carlo; Aaron, Shawn; Bryan, Stirling

2014-06-03

Cost-effectiveness analyses (CEAs) that use patient-specific data from a randomized controlled trial (RCT) are popular, yet such CEAs are criticized because they neglect to incorporate evidence external to the trial. A popular method for quantifying uncertainty in a RCT-based CEA is the bootstrap. The objective of the present study was to further expand the bootstrap method of RCT-based CEA for the incorporation of external evidence. We utilize the Bayesian interpretation of the bootstrap and derive the distribution for the cost and effectiveness outcomes after observing the current RCT data and the external evidence. We propose simple modifications of the bootstrap for sampling from such posterior distributions. In a proof-of-concept case study, we use data from a clinical trial and incorporate external evidence on the effect size of treatments to illustrate the method in action. Compared to the parametric models of evidence synthesis, the proposed approach requires fewer distributional assumptions, does not require explicit modeling of the relation between external evidence and outcomes of interest, and is generally easier to implement. A drawback of this approach is potential computational inefficiency compared to the parametric Bayesian methods. The bootstrap method of RCT-based CEA can be extended to incorporate external evidence, while preserving its appealing features such as no requirement for parametric modeling of cost and effectiveness outcomes.

Evaluation of prostate cancer antigen 3 for detecting prostate cancer: a systematic review and meta-analysis

NASA Astrophysics Data System (ADS)

Cui, Yong; Cao, Wenzhou; Li, Quan; Shen, Hua; Liu, Chao; Deng, Junpeng; Xu, Jiangfeng; Shao, Qiang

2016-05-01

Previous studies indicate that prostate cancer antigen 3 (PCA3) is highly expressed in prostatic tumors. However, its clinical value has not been characterized. The aim of this study was to investigate the clinical value of the urine PCA3 test in the diagnosis of prostate cancer by pooling the published data. Clinical trials utilizing the urine PCA3 test for diagnosing prostate cancer were retrieved from PubMed and Embase. A total of 46 clinical trials including 12,295 subjects were included in this meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio (+LR), negative likelihood ratio (-LR), diagnostic odds ratio (DOR) and area under the curve (AUC) were 0.65 (95% confidence interval [CI]: 0.63-0.66), 0.73 (95% CI: 0.72-0.74), 2.23 (95% CI: 1.91-2.62), 0.48 (95% CI: 0.44-0.52), 5.31 (95% CI: 4.19-6.73) and 0.75 (95% CI: 0.74-0.77), respectively. In conclusion, the urine PCA3 test has acceptable sensitivity and specificity for the diagnosis of prostate cancer and can be used as a non-invasive method for that purpose.

Consensus classification of posterior cortical atrophy

PubMed Central

Crutch, Sebastian J.; Schott, Jonathan M.; Rabinovici, Gil D.; Murray, Melissa; Snowden, Julie S.; van der Flier, Wiesje M.; Dickerson, Bradford C.; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H.; Boeve, Bradley F.; Butler, Christopher; Cappa, Stefano F.; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R.; Hof, Patrick R.; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F.; Nestor, Peter J.; Onyike, Chiadi U.; Pelak, Victoria S.; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N.; Ryan, Natalie S.; Scheltens, Philip; Shakespeare, Timothy J.; González, Aida Suárez; Tang-Wai, David F.; Yong, Keir X. X.; Carrillo, Maria; Fox, Nick C.

2017-01-01

Introduction A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Methods Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. Results A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. Discussion There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work. PMID:28259709

Consensus classification of posterior cortical atrophy.

PubMed

Crutch, Sebastian J; Schott, Jonathan M; Rabinovici, Gil D; Murray, Melissa; Snowden, Julie S; van der Flier, Wiesje M; Dickerson, Bradford C; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H; Boeve, Bradley F; Butler, Christopher; Cappa, Stefano F; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R; Hof, Patrick R; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F; Nestor, Peter J; Onyike, Chiadi U; Pelak, Victoria S; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N; Ryan, Natalie S; Scheltens, Philip; Shakespeare, Timothy J; Suárez González, Aida; Tang-Wai, David F; Yong, Keir X X; Carrillo, Maria; Fox, Nick C

2017-08-01

A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Power in Bayesian Mediation Analysis for Small Sample Research

PubMed Central

Miočević, Milica; MacKinnon, David P.; Levy, Roy

2018-01-01

It was suggested that Bayesian methods have potential for increasing power in mediation analysis (Koopman, Howe, Hollenbeck, & Sin, 2015; Yuan & MacKinnon, 2009). This paper compares the power of Bayesian credibility intervals for the mediated effect to the power of normal theory, distribution of the product, percentile, and bias-corrected bootstrap confidence intervals at N≤ 200. Bayesian methods with diffuse priors have power comparable to the distribution of the product and bootstrap methods, and Bayesian methods with informative priors had the most power. Varying degrees of precision of prior distributions were also examined. Increased precision led to greater power only when N≥ 100 and the effects were small, N < 60 and the effects were large, and N < 200 and the effects were medium. An empirical example from psychology illustrated a Bayesian analysis of the single mediator model from prior selection to interpreting results. PMID:29662296

Power in Bayesian Mediation Analysis for Small Sample Research.

PubMed

Miočević, Milica; MacKinnon, David P; Levy, Roy

2017-01-01

It was suggested that Bayesian methods have potential for increasing power in mediation analysis (Koopman, Howe, Hollenbeck, & Sin, 2015; Yuan & MacKinnon, 2009). This paper compares the power of Bayesian credibility intervals for the mediated effect to the power of normal theory, distribution of the product, percentile, and bias-corrected bootstrap confidence intervals at N≤ 200. Bayesian methods with diffuse priors have power comparable to the distribution of the product and bootstrap methods, and Bayesian methods with informative priors had the most power. Varying degrees of precision of prior distributions were also examined. Increased precision led to greater power only when N≥ 100 and the effects were small, N < 60 and the effects were large, and N < 200 and the effects were medium. An empirical example from psychology illustrated a Bayesian analysis of the single mediator model from prior selection to interpreting results.

Point Set Denoising Using Bootstrap-Based Radial Basis Function.

PubMed

Liew, Khang Jie; Ramli, Ahmad; Abd Majid, Ahmad

2016-01-01

This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study.

Priority of VHS Development Based in Potential Area using Principal Component Analysis

NASA Astrophysics Data System (ADS)

Meirawan, D.; Ana, A.; Saripudin, S.

2018-02-01

The current condition of VHS is still inadequate in quality, quantity and relevance. The purpose of this research is to analyse the development of VHS based on the development of regional potential by using principal component analysis (PCA) in Bandung, Indonesia. This study used descriptive qualitative data analysis using the principle of secondary data reduction component. The method used is Principal Component Analysis (PCA) analysis with Minitab Statistics Software tool. The results of this study indicate the value of the lowest requirement is a priority of the construction of development VHS with a program of majors in accordance with the development of regional potential. Based on the PCA score found that the main priority in the development of VHS in Bandung is in Saguling, which has the lowest PCA value of 416.92 in area 1, Cihampelas with the lowest PCA value in region 2 and Padalarang with the lowest PCA value.

Mortality Among Men with Advanced Prostate Cancer Excluded from the ProtecT Trial.

PubMed

Johnston, Thomas J; Shaw, Greg L; Lamb, Alastair D; Parashar, Deepak; Greenberg, David; Xiong, Tengbin; Edwards, Alison L; Gnanapragasam, Vincent; Holding, Peter; Herbert, Phillipa; Davis, Michael; Mizielinsk, Elizabeth; Lane, J Athene; Oxley, Jon; Robinson, Mary; Mason, Malcolm; Staffurth, John; Bollina, Prasad; Catto, James; Doble, Andrew; Doherty, Alan; Gillatt, David; Kockelbergh, Roger; Kynaston, Howard; Prescott, Steve; Paul, Alan; Powell, Philip; Rosario, Derek; Rowe, Edward; Donovan, Jenny L; Hamdy, Freddie C; Neal, David E

2017-03-01

Early detection and treatment of asymptomatic men with advanced and high-risk prostate cancer (PCa) may improve survival rates. To determine outcomes for men diagnosed with advanced PCa following prostate-specific antigen (PSA) testing who were excluded from the ProtecT randomised trial. Mortality was compared for 492 men followed up for a median of 7.4 yr to a contemporaneous cohort of men from the UK Anglia Cancer Network (ACN) and with a matched subset from the ACN. PCa-specific and all-cause mortality were compared using Kaplan-Meier analysis and Cox's proportional hazards regression. Of the 492 men excluded from the ProtecT cohort, 37 (8%) had metastases (N1, M0=5, M1=32) and 305 had locally advanced disease (62%). The median PSA was 17μg/l. Treatments included radical prostatectomy (RP; n=54; 11%), radiotherapy (RT; n=245; 50%), androgen deprivation therapy (ADT; n=122; 25%), other treatments (n=11; 2%), and unknown (n=60; 12%). There were 49 PCa-specific deaths (10%), of whom 14 men had received radical treatment (5%); and 129 all-cause deaths (26%). In matched ProtecT and ACN cohorts, 37 (9%) and 64 (16%), respectively, died of PCa, while 89 (22%) and 103 (26%) died of all causes. ProtecT men had a 45% lower risk of death from PCa compared to matched cases (hazard ratio 0.55, 95% confidence interval 0.38-0.83; p=0.0037), but mortality was similar in those treated radically. The nonrandomised design is a limitation. Men with PSA-detected advanced PCa excluded from ProtecT and treated radically had low rates of PCa death at 7.4-yr follow-up. Among men who underwent nonradical treatment, the ProtecT group had a lower rate of PCa death. Early detection through PSA testing, leadtime bias, and group heterogeneity are possible factors in this finding. Prostate cancer that has spread outside the prostate gland without causing symptoms can be detected via prostate-specific antigen testing and treated, leading to low rates of death from this disease. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Meta-analysis of CDKN2A methylation to find its role in prostate cancer development and progression, and also to find the effect of CDKN2A expression on disease-free survival (PRISMA).

PubMed

Cao, Zipei; Wei, Lijuan; Zhu, Weizhi; Yao, Xuping

2018-03-01

Reduction of cyclin-dependent kinase inhibitor 2A (CDKN2A) (p16 and p14) expression through DNA methylation has been reported in prostate cancer (PCa). This meta-analysis was conducted to assess the difference of p16 and p14 methylation between PCa and different histological types of nonmalignant controls and the correlation of p16 or p14 methylation with clinicopathological features of PCa. According to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement criteria, articles were searched in PubMed, Embase, EBSCO, Wanfang, and CNKI databases. The strength of correlation was calculated by the pooled odds ratios (ORs) and their corresponding 95% confidence intervals (95% CIs). Trial sequential analysis (TSA) was used to estimate the required population information for significant results. A total of 20 studies published from 1997 to 2017 were identified in this meta-analysis, including 1140 PCa patients and 530 cases without cancer. Only p16 methylation in PCa was significantly higher than in benign prostatic lesions (OR = 4.72, P = .011), but had a similar level in PCa and adjacent tissues or high-grade prostatic intraepithelial neoplasias (HGPIN). TSA revealed that this analysis on p16 methylation is a false positive result in cancer versus benign prostatic lesions (the estimated required information size of 5116 participants). p16 methylation was not correlated with PCa in the urine and blood. Besides, p16 methylation was not linked to clinical stage, prostate-specific antigen (PSA) level, and Gleason score (GS) of patients with PCa. p14 methylation was not correlated with PCa in tissue and urine samples. No correlation was observed between p14 methylation and clinical stage or GS. CDKN2A mutation and copy number alteration were not associated with prognosis of PCa in overall survival and disease-free survival. CDKN2A expression was not correlated with the prognosis of PCa in overall survival (492 cases) (P > .1), while CDKN2A expression was significantly associated with a poor disease-free survival (P < .01). CDKN2A methylation may not be significantly associated with the development, progression of PCa. Although CDKN2A expression had an unfavorable prognosis in disease-free survival. More studies are needed to confirm our results.

Facilitating text reading in posterior cortical atrophy.

PubMed

Yong, Keir X X; Rajdev, Kishan; Shakespeare, Timothy J; Leff, Alexander P; Crutch, Sebastian J

2015-07-28

We report (1) the quantitative investigation of text reading in posterior cortical atrophy (PCA), and (2) the effects of 2 novel software-based reading aids that result in dramatic improvements in the reading ability of patients with PCA. Reading performance, eye movements, and fixations were assessed in patients with PCA and typical Alzheimer disease and in healthy controls (experiment 1). Two reading aids (single- and double-word) were evaluated based on the notion that reducing the spatial and oculomotor demands of text reading might support reading in PCA (experiment 2). Mean reading accuracy in patients with PCA was significantly worse (57%) compared with both patients with typical Alzheimer disease (98%) and healthy controls (99%); spatial aspects of passages were the primary determinants of text reading ability in PCA. Both aids led to considerable gains in reading accuracy (PCA mean reading accuracy: single-word reading aid = 96%; individual patient improvement range: 6%-270%) and self-rated measures of reading. Data suggest a greater efficiency of fixations and eye movements under the single-word reading aid in patients with PCA. These findings demonstrate how neurologic characterization of a neurodegenerative syndrome (PCA) and detailed cognitive analysis of an important everyday skill (reading) can combine to yield aids capable of supporting important everyday functional abilities. This study provides Class III evidence that for patients with PCA, 2 software-based reading aids (single-word and double-word) improve reading accuracy. © 2015 American Academy of Neurology.

Facilitating text reading in posterior cortical atrophy

PubMed Central

Rajdev, Kishan; Shakespeare, Timothy J.; Leff, Alexander P.; Crutch, Sebastian J.

2015-01-01

Objective: We report (1) the quantitative investigation of text reading in posterior cortical atrophy (PCA), and (2) the effects of 2 novel software-based reading aids that result in dramatic improvements in the reading ability of patients with PCA. Methods: Reading performance, eye movements, and fixations were assessed in patients with PCA and typical Alzheimer disease and in healthy controls (experiment 1). Two reading aids (single- and double-word) were evaluated based on the notion that reducing the spatial and oculomotor demands of text reading might support reading in PCA (experiment 2). Results: Mean reading accuracy in patients with PCA was significantly worse (57%) compared with both patients with typical Alzheimer disease (98%) and healthy controls (99%); spatial aspects of passages were the primary determinants of text reading ability in PCA. Both aids led to considerable gains in reading accuracy (PCA mean reading accuracy: single-word reading aid = 96%; individual patient improvement range: 6%–270%) and self-rated measures of reading. Data suggest a greater efficiency of fixations and eye movements under the single-word reading aid in patients with PCA. Conclusions: These findings demonstrate how neurologic characterization of a neurodegenerative syndrome (PCA) and detailed cognitive analysis of an important everyday skill (reading) can combine to yield aids capable of supporting important everyday functional abilities. Classification of evidence: This study provides Class III evidence that for patients with PCA, 2 software-based reading aids (single-word and double-word) improve reading accuracy. PMID:26138948

External validation of urinary PCA3-based nomograms to individually predict prostate biopsy outcome.

PubMed

Auprich, Marco; Haese, Alexander; Walz, Jochen; Pummer, Karl; de la Taille, Alexandre; Graefen, Markus; de Reijke, Theo; Fisch, Margit; Kil, Paul; Gontero, Paolo; Irani, Jacques; Chun, Felix K-H

2010-11-01

Prior to safely adopting risk stratification tools, their performance must be tested in an external patient cohort. To assess accuracy and generalizability of previously reported, internally validated, prebiopsy prostate cancer antigen 3 (PCA3) gene-based nomograms when applied to a large, external, European cohort of men at risk of prostate cancer (PCa). Biopsy data, including urinary PCA3 score, were available for 621 men at risk of PCa who were participating in a European multi-institutional study. All patients underwent a ≥10-core prostate biopsy. Biopsy indication was based on suspicious digital rectal examination, persistently elevated prostate-specific antigen level (2.5-10 ng/ml) and/or suspicious histology (atypical small acinar proliferation of the prostate, >/= two cores affected by high-grade prostatic intraepithelial neoplasia in first set of biopsies). PCA3 scores were assessed using the Progensa assay (Gen-Probe Inc, San Diego, CA, USA). According to the previously reported nomograms, different PCA3 score codings were used. The probability of a positive biopsy was calculated using previously published logistic regression coefficients. Predicted outcomes were compared to the actual biopsy results. Accuracy was calculated using the area under the curve as a measure of discrimination; calibration was explored graphically. Biopsy-confirmed PCa was detected in 255 (41.1%) men. Median PCA3 score of biopsy-negative versus biopsy-positive men was 20 versus 48 in the total cohort, 17 versus 47 at initial biopsy, and 37 versus 53 at repeat biopsy (all p≤0.002). External validation of all four previously reported PCA3-based nomograms demonstrated equally high accuracy (0.73-0.75) and excellent calibration. The main limitations of the study reside in its early detection setting, referral scenario, and participation of only tertiary-care centers. In accordance with the original publication, previously developed PCA3-based nomograms achieved high accuracy and sufficient calibration. These novel nomograms represent robust tools and are thus generalizable to European men at risk of harboring PCa. Consequently, in presence of a PCA3 score, these nomograms may be safely used to assist clinicians when prostate biopsy is contemplated. Copyright © 2010 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Comparison of Methods for Estimating Low Flow Characteristics of Streams

USGS Publications Warehouse

Tasker, Gary D.

1987-01-01

Four methods for estimating the 7-day, 10-year and 7-day, 20-year low flows for streams are compared by the bootstrap method. The bootstrap method is a Monte Carlo technique in which random samples are drawn from an unspecified sampling distribution defined from observed data. The nonparametric nature of the bootstrap makes it suitable for comparing methods based on a flow series for which the true distribution is unknown. Results show that the two methods based on hypothetical distribution (Log-Pearson III and Weibull) had lower mean square errors than did the G. E. P. Box-D. R. Cox transformation method or the Log-W. C. Boughton method which is based on a fit of plotting positions.

Assessing Participation in Community-Based Physical Activity Programs in Brazil

PubMed Central

REIS, RODRIGO S.; YAN, YAN; PARRA, DIANA C.; BROWNSON, ROSS C.

2015-01-01

Purpose This study aimed to develop and validate a risk prediction model to examine the characteristics that are associated with participation in community-based physical activity programs in Brazil. Methods We used pooled data from three surveys conducted from 2007 to 2009 in state capitals of Brazil with 6166 adults. A risk prediction model was built considering program participation as an outcome. The predictive accuracy of the model was quantified through discrimination (C statistic) and calibration (Brier score) properties. Bootstrapping methods were used to validate the predictive accuracy of the final model. Results The final model showed sex (women: odds ratio [OR] = 3.18, 95% confidence interval [CI] = 2.14–4.71), having less than high school degree (OR = 1.71, 95% CI = 1.16–2.53), reporting a good health (OR = 1.58, 95% CI = 1.02–2.24) or very good/excellent health (OR = 1.62, 95% CI = 1.05–2.51), having any comorbidity (OR = 1.74, 95% CI = 1.26–2.39), and perceiving the environment as safe to walk at night (OR = 1.59, 95% CI = 1.18–2.15) as predictors of participation in physical activity programs. Accuracy indices were adequate (C index = 0.778, Brier score = 0.031) and similar to those obtained from bootstrapping (C index = 0.792, Brier score = 0.030). Conclusions Sociodemographic and health characteristics as well as perceptions of the environment are strong predictors of participation in community-based programs in selected cities of Brazil. PMID:23846162

Not seeing the forest for the trees: size of the minimum spanning trees (MSTs) forest and branch significance in MST-based phylogenetic analysis.

PubMed

Teixeira, Andreia Sofia; Monteiro, Pedro T; Carriço, João A; Ramirez, Mário; Francisco, Alexandre P

2015-01-01

Trees, including minimum spanning trees (MSTs), are commonly used in phylogenetic studies. But, for the research community, it may be unclear that the presented tree is just a hypothesis, chosen from among many possible alternatives. In this scenario, it is important to quantify our confidence in both the trees and the branches/edges included in such trees. In this paper, we address this problem for MSTs by introducing a new edge betweenness metric for undirected and weighted graphs. This spanning edge betweenness metric is defined as the fraction of equivalent MSTs where a given edge is present. The metric provides a per edge statistic that is similar to that of the bootstrap approach frequently used in phylogenetics to support the grouping of taxa. We provide methods for the exact computation of this metric based on the well known Kirchhoff's matrix tree theorem. Moreover, we implement and make available a module for the PHYLOViZ software and evaluate the proposed metric concerning both effectiveness and computational performance. Analysis of trees generated using multilocus sequence typing data (MLST) and the goeBURST algorithm revealed that the space of possible MSTs in real data sets is extremely large. Selection of the edge to be represented using bootstrap could lead to unreliable results since alternative edges are present in the same fraction of equivalent MSTs. The choice of the MST to be presented, results from criteria implemented in the algorithm that must be based in biologically plausible models.

Topical ketoprofen nanogel: artificial neural network optimization, clustered bootstrap validation, and in vivo activity evaluation based on longitudinal dose response modeling.

PubMed

Elkomy, Mohammed H; Elmenshawe, Shahira F; Eid, Hussein M; Ali, Ahmed M A

2016-11-01

This work aimed at investigating the potential of solid lipid nanoparticles (SLN) as carriers for topical delivery of Ketoprofen (KP); evaluating a novel technique incorporating Artificial Neural Network (ANN) and clustered bootstrap for optimization of KP-loaded SLN (KP-SLN); and demonstrating a longitudinal dose response (LDR) modeling-based approach to compare the activity of topical non-steroidal anti-inflammatory drug formulations. KP-SLN was fabricated by a modified emulsion/solvent evaporation method. Box-Behnken design was implemented to study the influence of glycerylpalmitostearate-to-KP ratio, Tween 80, and lecithin concentrations on particle size, entrapment efficiency, and amount of drug permeated through rat skin in 24 hours. Following clustered bootstrap ANN optimization, the optimized KP-SLN was incorporated into an aqueous gel and evaluated for rheology, in vitro release, permeability, skin irritation and in vivo activity using carrageenan-induced rat paw edema model and LDR mathematical model to analyze the time course of anti-inflammatory effect at various application durations. Lipid-to-drug ratio of 7.85 [bootstrap 95%CI: 7.63-8.51], Tween 80 of 1.27% [bootstrap 95%CI: 0.601-2.40%], and Lecithin of 0.263% [bootstrap 95%CI: 0.263-0.328%] were predicted to produce optimal characteristics. Compared with profenid® gel, the optimized KP-SLN gel exhibited slower release, faster permeability, better texture properties, greater efficacy, and similar potency. SLNs are safe and effective permeation enhancers. ANN coupled with clustered bootstrap is a useful method for finding optimal solutions and estimating uncertainty associated with them. LDR models allow mechanistic understanding of comparative in vivo performances of different topical formulations, and help design efficient dermatological bioequivalence assessment methods.

Bootstrapping Student Understanding of What Is Going on in Econometrics.

ERIC Educational Resources Information Center

Kennedy, Peter E.

2001-01-01

Explains that econometrics is an intellectual game played by rules based on the sampling distribution concept. Contains explanations for why many students are uncomfortable with econometrics. Encourages instructors to use explain-how-to-bootstrap exercises to promote student understanding. (RLH)

The PIT-trap—A “model-free” bootstrap procedure for inference about regression models with discrete, multivariate responses

PubMed Central

Thibaut, Loïc; Wang, Yi Alice

2017-01-01

Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)—common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of “model-free bootstrap”, adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods. PMID:28738071

Initial results of 3-dimensional 1H-magnetic resonance spectroscopic imaging in the localization of prostate cancer at 3 Tesla: should we use an endorectal coil?

PubMed

Yakar, Derya; Heijmink, Stijn W T P J; Hulsbergen-van de Kaa, Christina A; Huisman, Henkjan; Barentsz, Jelle O; Fütterer, Jurgen J; Scheenen, Tom W J

2011-05-01

The purpose of this study was to compare the diagnostic performance of 3 Tesla, 3-dimensional (3D) magnetic resonance spectroscopic imaging (MRSI) in the localization of prostate cancer (PCa) with and without the use of an endorectal coil (ERC). Our prospective study was approved by the institutional review board, and written informed consent was obtained from all patients. Between October 2004 and January 2006, 18 patients with histologically proven PCa on biopsy and scheduled for radical prostatectomy were included and underwent 3D-MRSI with and without an ERC. The prostate was divided into 14 regions of interest (ROIs). Four readers independently rated (on a 5-point scale) their confidence that cancer was present in each of these ROIs. These findings were correlated with whole-mount prostatectomy specimens. Areas under the receiver-operating characteristic curve were determined. A difference with a P < 0.05 was considered significant. A total of 504 ROIs were rated for the presence and absence of PCa. Localization of PCa with MRSI with the use of an ERC had a significantly higher areas under the receiver-operating characteristic curve (0.68) than MRSI without the use of an ERC (0.63) (P = 0.015). The use of an ERC in 3D MRSI in localizing PCa at 3 Tesla slightly but significantly increased the localization performance compared with not using an ERC.

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

Kang, Josephine, E-mail: jkang3@partners.org; Chen Minghui; Zhang Yuanye

Purpose: It has been recently shown that diabetes mellitus (DM) is significantly associated with the likelihood of presenting with high-grade prostate cancer (PCa) or Gleason score (GS) 8 to 10; however, whether this association holds for both Type 1 and 2 DM is unknown. In this study we evaluated whether DM Type 1, 2, or both are associated with high-grade PCa after adjusting for known predictors of high-grade disease. Methods and Materials: Between 1991 and 2010, a total of 15,330 men diagnosed with PCa and treated with radiation therapy were analyzed. A polychotomous logistic regression analysis was performed to evaluatemore » whether Type 1 or 2 DM was associated with odds of GS 7 or GS 8 to 10 compared with 6 or lower PCa, adjusting for African American race, age, prostate-specific antigen (PSA) level, and digital rectal examination findings. Results: Men with Type 1 DM (adjusted odds ratio [AOR], 2.05; 95% confidence interval [CI], 1.28-3.27; p = 0.003) or Type 2 DM (AOR, 1.58; 95% CI, 1.26-1.99; p < 0.001) were significantly more likely to be diagnosed with GS 8 to 10 PCa compared with nondiabetic men. However this was not true for GS 7, for which these respective results were AOR, 1.30; 95% CI, 0.93-1.82; p = 0.12 and AOR, 1.13; 95% CI, 0.98-1.32; p = 0.10. Conclusion: Type 1 and 2 DM were associated with a higher odds of being diagnosed with Gleason score 8 to 10 but not 7 PCa. Pending validation, men who are diagnosed with Type I DM with GS 7 or lower should be considered for additional workup to rule out occult high-grade disease.« less

Consumption of deep-fried foods and risk of prostate cancer.

PubMed

Stott-Miller, Marni; Neuhouser, Marian L; Stanford, Janet L

2013-06-01

Evidence suggests that high-heat cooking methods may increase the risk of prostate cancer (PCa). The addition of oil/fat, as in deep-frying, may be of particular concern, and has not specifically been investigated in relation to PCa. Potential mechanisms include the formation of potentially carcinogenic agents such as aldehydes, acrolein, heterocyclic amines, polycyclic aromatic hydrocarbons, and acrylamide. We estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between tertiles of intake of deep-fried foods from a food frequency questionnaire (French fries, fried chicken, fried fish, doughnuts and snack chips) and PCa risk, adjusted for potential confounders, among 1,549 cases and 1,492 controls. We additionally examined associations with more aggressive PCa (defined as regional/distant stage, elevated Gleason score or prostate-specific antigen level). Compared with <1/week, there was a positive association with PCa risk for intake ≥1/week of French fries (OR = 1.37; 95% CI, 1.11-1.69), fried chicken (OR = 1.30; 95% CI, 1.04-1.62), fried fish (OR = 1.32; 95% CI, 1.05-1.66), and doughnuts (OR = 1.35; 95% CI, 1.11-1.66). There was no association for snack chips (OR = 1.08; 95% CI, 0.89-1.32). Most of the estimates were slightly stronger for more aggressive disease (OR = 1.41; 95% CI, 1.04-1.92 for fried fish). Regular consumption of select deep-fried foods is associated with increased PCa risk. Whether this risk is specific to deep-fried foods, or whether it represents risk associated with regular intake of foods exposed to high heat and/or other aspects of the Western lifestyle, such as fast food consumption, remains to be determined. Copyright © 2013 Wiley Periodicals, Inc.

Consumption of deep-fried foods and risk of prostate cancera,b

PubMed Central

Stott-Miller, Marni; Neuhouser, Marian L.; Stanford, Janet L.

2013-01-01

Background Evidence suggests that high-heat cooking methods may increase the risk of prostate cancer (PCa). The addition of oil/fat, as in deep-frying, may be of particular concern, and has not specifically been investigated in relation to PCa. Potential mechanisms include the formation of potentially carcinogenic agents such as aldehydes, acrolein, heterocyclic amines, polycyclic aromatic hydrocarbons, and acrylamide. Methods We estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between tertiles of intake of deep-fried foods from a food frequency questionnaire (French fries, fried chicken, fried fish, doughnuts and snack chips) and PCa risk, adjusted for potential confounders, among 1,549 cases and 1,492 controls. We additionally examined associations with more aggressive PCa (defined as regional/distant stage, elevated Gleason score or prostate specific antigen level). Results Compared with <1/week, there was a positive association with PCa risk for intake ≥ 1/week of French fries (OR=1.37; 95% CI, 1.11–1.69), fried chicken (OR=1.30; 95% CI, 1.04–1.62), fried fish (OR=1.32; 95% CI, 1.05–1.66), and doughnuts (OR=1.35; 95% CI, 1.11–1.66). There was no association for snack chips (OR=1.08; 95% CI, 0.89–1.32). Most of the estimates were slightly stronger for more aggressive disease (OR=1.41; 95% CI, 1.04–1.92 for fried fish). Conclusion Regular consumption of select deep-fried foods is associated with increased PCa risk. Whether this risk is specific to deep-fried foods, or whether it represents risk associated with regular intake of foods exposed to high heat and/or other aspects of the Western lifestyle, such as fast food consumption, remains to be determined. PMID:23335051

Large institutional variations in use of androgen deprivation therapy with definitive radiotherapy in a population-based cohort of men with intermediate- and high-risk prostate cancer.

PubMed

Ong, Wee Loon; Foroudi, Farshad; Evans, Sue; Millar, Jeremy

2017-11-01

To evaluate the pattern of use of androgen deprivation therapy (ADT) with definitive radiotherapy (RT) in men with prostate cancer (PCa) in a population-based study in Australia. This is a prospective cohort of men with intermediate- and high-risk PCa, captured in the population-based Prostate Cancer Outcome Registry Victoria, who were treated with definitive prostate RT between January 2010 and December 2015. The primary outcome of interest was ADT utilization. Chi-squared test for trend was used to evaluate the temporal trend in the use of ADT over the study period. Multivariate logistic regressions were used to evaluate the effects of patient-, tumour- and treatment-related factors, and treatment institutions (public/ private and metropolitan/ regional) on the likelihood of ADT utilization. A total of 1806 men were included in the study, 199 of whom (11%) had favourable National Comprehensive Cancer Network (NCCN) intermediate-risk disease (i.e. only one intermediate-risk feature, primary Gleason grade 3, and <50% biopsy core involved), 687 (38%) had unfavourable NCCN intermediate-risk disease, and 920 (51%) had high-risk disease. Of the 1806 men, 1155 (64%) received ADT with RT. Men with NCCN high-risk PCa (84%) were more likely to have ADT than men with favourable NCCN intermediate-risk (32%) and unfavourable NCCN intermediate-risk (46%) PCa (P < 0.001). Men treated in public institutions (66%, vs 47% in private institutions; P < 0.001) and regional centres (78%, vs 59% in metropolitan institutions; P < 0.001) were more likely to receive ADT. There was a trend towards an increase in ADT utilization from 50% in 2010 to 64% in 2015 (P < 0.001). In multivariate analyses (adjusting for age, tumour-related factors, year of treatment and use of brachytherapy boost), treatment institution (public and regional) remained independently associated with increased likelihood of ADT utilization. Men with intermediate-risk PCa treated in regional and public institutions were 2.7 times (95% confidence interval [CI] 1.9-3.9; P < 0.001) and 2.8 times (95% CI 1.4-5.3; P = 0.002), more likely to receive ADT with RT, respectively, while men with high-risk PCa treated in regional and public institutions were 3.1 times (95% CI 1.7-5.7; P < 0.001) and 3.0 times (95% CI 1.7-5.4; P < 0.001), more likely to receive ADT with RT, respectively. This is the largest Australasian contemporary series reporting on the pattern of use of ADT with definitive prostate RT. While there was an increasing trend towards use of ADT over time, ADT still appeared to be underutilized in certain groups of patients who may benefit from ADT, with approximately one in five men with high-risk and one in two with unfavourable intermediate-risk PCa not receiving ADT with RT. There was notable variation in the use of ADT between public vs private and metropolitan vs regional institutions. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Integrating visual learning within a model-based ATR system

NASA Astrophysics Data System (ADS)

Carlotto, Mark; Nebrich, Mark

2017-05-01

Automatic target recognition (ATR) systems, like human photo-interpreters, rely on a variety of visual information for detecting, classifying, and identifying manmade objects in aerial imagery. We describe the integration of a visual learning component into the Image Data Conditioner (IDC) for target/clutter and other visual classification tasks. The component is based on an implementation of a model of the visual cortex developed by Serre, Wolf, and Poggio. Visual learning in an ATR context requires the ability to recognize objects independent of location, scale, and rotation. Our method uses IDC to extract, rotate, and scale image chips at candidate target locations. A bootstrap learning method effectively extends the operation of the classifier beyond the training set and provides a measure of confidence. We show how the classifier can be used to learn other features that are difficult to compute from imagery such as target direction, and to assess the performance of the visual learning process itself.

Quantile rank maps: a new tool for understanding individual brain development.

PubMed

Chen, Huaihou; Kelly, Clare; Castellanos, F Xavier; He, Ye; Zuo, Xi-Nian; Reiss, Philip T

2015-05-01

We propose a novel method for neurodevelopmental brain mapping that displays how an individual's values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be more robust to model misspecification than a linear regression-based test. The proposed methods are applied to brain imaging data from the Nathan Kline Institute Rockland Sample and from the Autism Brain Imaging Data Exchange (ABIDE) sample. Copyright © 2015 Elsevier Inc. All rights reserved.

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy.

PubMed

Jesse, Stephen; Kalinin, Sergei V

2009-02-25

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

Comparison of water extraction methods in Tibet based on GF-1 data

NASA Astrophysics Data System (ADS)

Jia, Lingjun; Shang, Kun; Liu, Jing; Sun, Zhongqing

2018-03-01

In this study, we compared four different water extraction methods with GF-1 data according to different water types in Tibet, including Support Vector Machine (SVM), Principal Component Analysis (PCA), Decision Tree Classifier based on False Normalized Difference Water Index (FNDWI-DTC), and PCA-SVM. The results show that all of the four methods can extract large area water body, but only SVM and PCA-SVM can obtain satisfying extraction results for small size water body. The methods were evaluated by both overall accuracy (OAA) and Kappa coefficient (KC). The OAA of PCA-SVM, SVM, FNDWI-DTC, PCA are 96.68%, 94.23%, 93.99%, 93.01%, and the KCs are 0.9308, 0.8995, 0.8962, 0.8842, respectively, in consistent with visual inspection. In summary, SVM is better for narrow rivers extraction and PCA-SVM is suitable for water extraction of various types. As for dark blue lakes, the methods using PCA can extract more quickly and accurately.

Preoperative Staging With 11C-Choline PET/CT Is Adequately Accurate in Patients With Very High-Risk Prostate Cancer.

PubMed

Schiavina, Riccardo; Bianchi, Lorenzo; Mineo Bianchi, Federico; Borghesi, Marco; Pultrone, Cristian Vincenzo; Dababneh, Hussam; Castellucci, Paolo; Ceci, Francesco; Nanni, Cristina; Gaudiano, Caterina; Fiorentino, Michelangelo; Porreca, Angelo; Chessa, Francesco; Minervini, Andrea; Fanti, Stefano; Brunocilla, Eugenio

2018-05-30

To evaluate the accuracy of 11 C-choline positron emission tomography (PET)/computed tomography (CT) for nodal staging of prostate cancer (PCa) in different populations of high-risk patients. We evaluated 262 individuals with intermediate- or high-risk PCa submitted to radical prostatectomy and extended pelvic lymph node dissection. Within men with high-risk disease, we identified a subgroup of individuals harboring very high-risk (VHR, n = 28) disease: clinical stage ≥ T2c and more than 5 cores with Gleason score 8-10; primary biopsy Gleason score of 5; 3 high-risk features; or prostate-specific antigen ≥ 30 ng/mL. The diagnostic accuracy of PET/CT and contrast-enhanced CT (CECT) was assessed after stratifying patients according to risk group classification on a patient- and anatomic region-based analysis. On patient-based analysis, considering high-risk patients (n = 155), 11 C-choline PET/CT versus CECT had sensitivity and specificity of 50% and 76% versus 21% and 92%, respectively. Considering VHR men as separate subgroups (n = 28), 11 C-choline PET/CT versus CECT had sensitivity and specificity of 71% and 93% versus 25% and 79%, respectively. Accordingly, in the VHR category, the area under the curve of 11 C-choline PET/CT versus CECT was 0.86 (95% confidence interval, 0.71-1.0) versus 0.69 (95% confidence interval, 0.52-0.86), respectively. On anatomic region-based analysis, considering the VHR group, 11 C-choline PET/CT versus CECT had sensitivity and specificity of 70.6% and 95.5% versus 35.3% and 98.5%, respectively. Patients with VHR characteristics could represent the ideal candidate to undergo disease staging with PET/CT before surgery with the highest cost efficacy. Copyright © 2018 Elsevier Inc. All rights reserved.

Prostate tumor DNA methylation is associated with cigarette smoking and adverse prostate cancer outcomes.

PubMed

Shui, Irene M; Wong, Chao-Jen; Zhao, Shanshan; Kolb, Suzanne; Ebot, Ericka M; Geybels, Milan S; Rubicz, Rohina; Wright, Jonathan L; Lin, Daniel W; Klotzle, Brandy; Bibikova, Marina; Fan, Jian-Bing; Ostrander, Elaine A; Feng, Ziding; Stanford, Janet L

2016-07-15

DNA methylation has been hypothesized as a mechanism for explaining the association between smoking and adverse prostate cancer (PCa) outcomes. This study was aimed at assessing whether smoking is associated with prostate tumor DNA methylation and whether these alterations may explain in part the association of smoking with PCa recurrence and mortality. A total of 523 men had radical prostatectomy as their primary treatment, detailed smoking history data, long-term follow-up for PCa outcomes, and tumor tissue profiled for DNA methylation. Ninety percent of the men also had matched tumor gene expression data. A methylome-wide analysis was conducted to identify differentially methylated regions (DMRs) by smoking status. To select potential functionally relevant DMRs, their correlation with the messenger RNA (mRNA) expression of corresponding genes was evaluated. Finally, a smoking-related methylation score based on the top-ranked DMRs was created to assess its association with PCa outcomes. Forty DMRs were associated with smoking status, and 10 of these were strongly correlated with mRNA expression (aldehyde oxidase 1 [AOX1], claudin 5 [CLDN5], early B-cell factor 1 [EBF1], homeobox A7 [HOXA7], lectin galactoside-binding soluble 3 [LGALS3], microtubule-associated protein τ [MAPT], protocadherin γ A [PCDHGA]/protocadherin γ B [PCDHGB], paraoxonase 3 [PON3], synaptonemal complex protein 2 like [SYCP2L], and zinc finger and SCAN domain containing 12 [ZSCAN12]). Men who were in the highest tertile for the smoking-methylation score derived from these DMRs had a higher risk of recurrence (odds ratio [OR], 2.29; 95% confidence interval [CI], 1.42-3.72) and lethal disease (OR, 4.21; 95% CI, 1.65-11.78) in comparison with men in the lower 2 tertiles. This integrative molecular epidemiology study supports the hypothesis that smoking-associated tumor DNA methylation changes may explain at least part of the association between smoking and adverse PCa outcomes. Future studies are warranted to confirm these findings and understand the implications for improving patient outcomes. Cancer 2016;122:2168-77. © 2016 American Cancer Society. © 2016 American Cancer Society.

Association between cytochrome CYP17A1, CYP3A4, and CYP3A43 polymorphisms and prostate cancer risk and aggressiveness in a Korean study population

PubMed Central

Han, Jun Hyun; Lee, Yong Seong; Kim, Hae Jong; Lee, Shin Young; Myung, Soon Chul

2015-01-01

In this study, we evaluated genetic variants of the androgen metabolism genes CYP17A1, CYP3A4, and CYP3A43 to determine whether they play a role in the development of prostate cancer (PCa) in Korean men. The study population included 240 pathologically diagnosed cases of PCa and 223 age-matched controls. Among the 789 single-nucleotide polymorphism (SNP) database variants detected, 129 were reported in two Asian groups (Han Chinese and Japanese) in the HapMap database. Only 21 polymorphisms of CYP17A1, CYP3A4, and CYP3A43 were selected based on linkage disequilibrium in Asians (r2 = 1), locations (SNPs in exons were preferred), and amino acid changes and were assessed. In addition, we performed haplotype analysis for the 21 SNPs in CYP17A1, CYP3A4, and CYP3A43 genes. To determine the association between genotype and haplotype distributions of patients and controls, logistic analyses were carried out, controlling for age. Twelve sequence variants and five major haplotypes were identified in CYP17A1. Five sequence variants and two major haplotypes were identified in CYP3A4. Four sequence variants and four major haplotypes were observed in CYP3A43. CYP17A1 haplotype-2 (Ht-2) (odds ratio [OR], 1.51; 95% confidence interval [CI], 1.04–2.18) was associated with PCa susceptibility. CYP3A4 Ht-2 (OR: 1.87; 95% CI: 1.02–3.43) was associated with PCa metastatic potential according to tumor stage. rs17115149 (OR: 1.96; 95% CI: 1.04–3.68) and CYP17A1 Ht-4 (OR: 2.01; 95% CI: 1.07–4.11) showed a significant association with histologic aggressiveness according to Gleason score. Genetic variants of CYP17A1 and CYP3A4 may play a role in the development of PCa in Korean men. PMID:25337833

Association between cytochrome CYP17A1, CYP3A4, and CYP3A43 polymorphisms and prostate cancer risk and aggressiveness in a Korean study population.

PubMed

Han, Jun Hyun; Lee, Yong Seong; Kim, Hae Jong; Lee, Shin Young; Myung, Soon Chul

2015-01-01

In this study, we evaluated genetic variants of the androgen metabolism genes CYP17A1, CYP3A4, and CYP3A43 to determine whether they play a role in the development of prostate cancer (PCa) in Korean men. The study population included 240 pathologically diagnosed cases of PCa and 223 age-matched controls. Among the 789 single-nucleotide polymorphism (SNP) database variants detected, 129 were reported in two Asian groups (Han Chinese and Japanese) in the HapMap database. Only 21 polymorphisms of CYP17A1, CYP3A4, and CYP3A43 were selected based on linkage disequilibrium in Asians (r2 = 1), locations (SNPs in exons were preferred), and amino acid changes and were assessed. In addition, we performed haplotype analysis for the 21 SNPs in CYP17A1, CYP3A4, and CYP3A43 genes. To determine the association between genotype and haplotype distributions of patients and controls, logistic analyses were carried out, controlling for age. Twelve sequence variants and five major haplotypes were identified in CYP17A1. Five sequence variants and two major haplotypes were identified in CYP3A4. Four sequence variants and four major haplotypes were observed in CYP3A43. CYP17A1 haplotype-2 (Ht-2) (odds ratio [OR], 1.51; 95% confidence interval [CI], 1.04-2.18) was associated with PCa susceptibility. CYP3A4 Ht-2 (OR: 1.87; 95% CI: 1.02-3.43) was associated with PCa metastatic potential according to tumor stage. rs17115149 (OR: 1.96; 95% CI: 1.04-3.68) and CYP17A1 Ht-4 (OR: 2.01; 95% CI: 1.07-4.11) showed a significant association with histologic aggressiveness according to Gleason score. Genetic variants of CYP17A1 and CYP3A4 may play a role in the development of PCa in Korean men.

Metformin association with lower prostate cancer recurrence in type 2 diabetes: a systematic review and meta-analysis.

PubMed

Hwang, In Cheol; Park, Sang Min; Shin, Doosup; Ahn, Hong Yup; Rieken, Malte; Shariat, Shahrokh F

2015-01-01

Accumulating evidence suggests that metformin possesses anticarcinogenic properties, and its use is associated with favorable outcomes in several cancers. However, it remains unclear whether metformin influences prognosis in prostate cancer (PCa) with concurrent type 2 diabetes (T2D). We searched PubMed, EMBASE, and the Cochrane Library from database inception to April 16, 2014 without language restrictions to identify studies investigating the effect of metformin treatment on outcomes of PCa with concurrent T2D. We conducted a meta-analysis to quantify the risk of recurrence, progression, cancer-specific mortality, and all-cause mortality. Summary relative risks (RRs) with corresponding 95% confidence intervals (CIs) were calculated. Publication bias was assessed by Begg's rank correlation test. A total of eight studies fulfilled the eligibility criteria. We found that diabetic PCa patients who did not use metformin were at increased risk of cancer recurrence (RR, 1.20; 95%CI, 1.00-1.44), compared with those who used metformin. A similar trend was observed for other outcomes, but their relationships did not reach statistical significance. Funnel plot asymmetry was not observed among studies reporting recurrence (p=0.086). Our results suggest that metformin may improve outcomes in PCa patients with concurrent T2D. Well-designed large studies and collaborative basic research are warranted.

Methods for estimating confidence intervals in interrupted time series analyses of health interventions.

PubMed

Zhang, Fang; Wagner, Anita K; Soumerai, Stephen B; Ross-Degnan, Dennis

2009-02-01

Interrupted time series (ITS) is a strong quasi-experimental research design, which is increasingly applied to estimate the effects of health services and policy interventions. We describe and illustrate two methods for estimating confidence intervals (CIs) around absolute and relative changes in outcomes calculated from segmented regression parameter estimates. We used multivariate delta and bootstrapping methods (BMs) to construct CIs around relative changes in level and trend, and around absolute changes in outcome based on segmented linear regression analyses of time series data corrected for autocorrelated errors. Using previously published time series data, we estimated CIs around the effect of prescription alerts for interacting medications with warfarin on the rate of prescriptions per 10,000 warfarin users per month. Both the multivariate delta method (MDM) and the BM produced similar results. BM is preferred for calculating CIs of relative changes in outcomes of time series studies, because it does not require large sample sizes when parameter estimates are obtained correctly from the model. Caution is needed when sample size is small.

Developing and Evaluating Creativity Gamification Rehabilitation System: The Application of PCA-ANFIS Based Emotions Model

ERIC Educational Resources Information Center

Su, Chung-Ho; Cheng, Ching-Hsue

2016-01-01

This study aims to explore the factors in a patient's rehabilitation achievement after a total knee replacement (TKR) patient exercises, using a PCA-ANFIS emotion model-based game rehabilitation system, which combines virtual reality (VR) and motion capture technology. The researchers combine a principal component analysis (PCA) and an adaptive…

Effect-site concentration of propofol target-controlled infusion at loss of consciousness in intractable epilepsy patients receiving long-term antiepileptic drug therapy.

PubMed

Choi, Eun Mi; Choi, Seung Ho; Lee, Min Huiy; Ha, Sang Hee; Min, Kyeong Tae

2011-07-01

Propofol dose requirement for loss of consciousness (LOC) in epilepsy patients would be probably affected by increasing factors [development of tolerance, up-regulated γ-aminobutyric acid (GABAA) receptors, or antiepileptic activity of propofol] and reducing factors [synergistic interaction between propofol and antiepileptic drugs (AEDs) or reduced neuronal mass in cortex] in complex and counteracting ways. Therefore, we determined the effect-site concentration (Ce) of propofol for LOC in intractable epilepsy patients receiving chronic AEDs in comparison with non-epilepsy patients. Nineteen epilepsy patients receiving long-term AEDs therapy and 20 non-epilepsy patients, with the age of 20 to 65 years, were enrolled. The epilepsy patients took their prescribed AEDs until the morning of the operation. Ce of propofol for LOC was determined with isotonic regression method with bootstrapping approach following Dixon's up-and-down allocation. The study was carried out before surgical stimulation. Isotonic regression showed that estimated Ce50 and Ce95 of propofol for LOC were lower in epilepsy group [2.88 μg/mL (83% confidence interval, 2.82-3.13 μg/mL) and [3.43 μg/mL (95% confidence interval, 3.28-3.47 μg/mL)] than in non-epilepsy group [3.38 μg/mL (83% confidence interval, 3.17-3.63 μg/mL) and 3.92 μg/mL (95% confidence interval, 3.80-3.97 μg/mL)] with bootstrapping approach. Mean Ce50 of propofol of epilepsy group was also lower than that of non-epilepsy group without statistical significance (2.8240.19 μg/mL vs 3.16±0.38 μg/mL, P=0.056). For anesthetic induction of epilepsy patients with propofol target-controlled infusion, Ce may need to be reduced by 10% to 15% compared with non-epilepsy patients.

Understanding and Targeting Epigenetic Alterations in Acquired Bone Marrow Failure

DTIC Science & Technology

2015-05-01

Cre 1 2 P95H 3 Activated allele Neo Lox P Frt Long homology arm Short homology arm Neo cassette Probe primer P95H (GGC => GTG ) Reference: 297...right) (th indicates 95% confidence interval by bootstrapping. The schematic illustrates a p left to right, the features are the upstream exon ( gray box...and intron (black line), t (black line) and exon ( gray box). Horizontal axis, genomic coordinates defined with relative frequency of the indicated

Multiparametric magnetic resonance imaging of the prostate: current concepts*

PubMed Central

Bittencourt, Leonardo Kayat; Hausmann, Daniel; Sabaneeff, Natalia; Gasparetto, Emerson Leandro; Barentsz, Jelle O.

2014-01-01

Multiparametric MR (mpMR) imaging is rapidly evolving into the mainstay in prostate cancer (PCa) imaging. Generally, the examination consists of T2-weighted sequences, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) evaluation, and less often proton MR spectroscopy imaging (MRSI). Those functional techniques are related to biological properties of the tumor, so that DWI correlates to cellularity and Gleason scores, DCE correlates to angiogenesis, and MRSI correlates to cell membrane turnover. The combined use of those techniques enhances the diagnostic confidence and allows for better characterization of PCa. The present article reviews and illustrates the technical aspects and clinical applications of each component of mpMR imaging, in a practical approach from the urological standpoint. PMID:25741104

Estimation of confidence limits for descriptive indexes derived from autoregressive analysis of time series: Methods and application to heart rate variability.

PubMed

Beda, Alessandro; Simpson, David M; Faes, Luca

2017-01-01

The growing interest in personalized medicine requires making inferences from descriptive indexes estimated from individual recordings of physiological signals, with statistical analyses focused on individual differences between/within subjects, rather than comparing supposedly homogeneous cohorts. To this end, methods to compute confidence limits of individual estimates of descriptive indexes are needed. This study introduces numerical methods to compute such confidence limits and perform statistical comparisons between indexes derived from autoregressive (AR) modeling of individual time series. Analytical approaches are generally not viable, because the indexes are usually nonlinear functions of the AR parameters. We exploit Monte Carlo (MC) and Bootstrap (BS) methods to reproduce the sampling distribution of the AR parameters and indexes computed from them. Here, these methods are implemented for spectral and information-theoretic indexes of heart-rate variability (HRV) estimated from AR models of heart-period time series. First, the MS and BC methods are tested in a wide range of synthetic HRV time series, showing good agreement with a gold-standard approach (i.e. multiple realizations of the "true" process driving the simulation). Then, real HRV time series measured from volunteers performing cognitive tasks are considered, documenting (i) the strong variability of confidence limits' width across recordings, (ii) the diversity of individual responses to the same task, and (iii) frequent disagreement between the cohort-average response and that of many individuals. We conclude that MC and BS methods are robust in estimating confidence limits of these AR-based indexes and thus recommended for short-term HRV analysis. Moreover, the strong inter-individual differences in the response to tasks shown by AR-based indexes evidence the need of individual-by-individual assessments of HRV features. Given their generality, MC and BS methods are promising for applications in biomedical signal processing and beyond, providing a powerful new tool for assessing the confidence limits of indexes estimated from individual recordings.

Estimation of confidence limits for descriptive indexes derived from autoregressive analysis of time series: Methods and application to heart rate variability

PubMed Central

2017-01-01

The growing interest in personalized medicine requires making inferences from descriptive indexes estimated from individual recordings of physiological signals, with statistical analyses focused on individual differences between/within subjects, rather than comparing supposedly homogeneous cohorts. To this end, methods to compute confidence limits of individual estimates of descriptive indexes are needed. This study introduces numerical methods to compute such confidence limits and perform statistical comparisons between indexes derived from autoregressive (AR) modeling of individual time series. Analytical approaches are generally not viable, because the indexes are usually nonlinear functions of the AR parameters. We exploit Monte Carlo (MC) and Bootstrap (BS) methods to reproduce the sampling distribution of the AR parameters and indexes computed from them. Here, these methods are implemented for spectral and information-theoretic indexes of heart-rate variability (HRV) estimated from AR models of heart-period time series. First, the MS and BC methods are tested in a wide range of synthetic HRV time series, showing good agreement with a gold-standard approach (i.e. multiple realizations of the "true" process driving the simulation). Then, real HRV time series measured from volunteers performing cognitive tasks are considered, documenting (i) the strong variability of confidence limits' width across recordings, (ii) the diversity of individual responses to the same task, and (iii) frequent disagreement between the cohort-average response and that of many individuals. We conclude that MC and BS methods are robust in estimating confidence limits of these AR-based indexes and thus recommended for short-term HRV analysis. Moreover, the strong inter-individual differences in the response to tasks shown by AR-based indexes evidence the need of individual-by-individual assessments of HRV features. Given their generality, MC and BS methods are promising for applications in biomedical signal processing and beyond, providing a powerful new tool for assessing the confidence limits of indexes estimated from individual recordings. PMID:28968394

CREATION OF A MODEL TO PREDICT SURVIVAL IN PATIENTS WITH REFRACTORY COELIAC DISEASE USING A MULTINATIONAL REGISTRY

PubMed Central

Rubio-Tapia, Alberto; Malamut, Georgia; Verbeek, Wieke H.M.; van Wanrooij, Roy L.J.; Leffler, Daniel A.; Niveloni, Sonia I.; Arguelles-Grande, Carolina; Lahr, Brian D.; Zinsmeister, Alan R.; Murray, Joseph A.; Kelly, Ciaran P.; Bai, Julio C.; Green, Peter H.; Daum, Severin; Mulder, Chris J.J.; Cellier, Christophe

2016-01-01

Background Refractory coeliac disease is a severe complication of coeliac disease with heterogeneous outcome. Aim To create a prognostic model to estimate survival of patients with refractory coeliac disease. Methods We evaluated predictors of 5-year mortality using Cox proportional hazards regression on subjects from a multinational registry. Bootstrap re-sampling was used to internally validate the individual factors and overall model performance. The mean of the estimated regression coefficients from 400 bootstrap models was used to derive a risk score for 5-year mortality. Results The multinational cohort was composed of 232 patients diagnosed with refractory coeliac disease across 7 centers (range of 11–63 cases per center). The median age was 53 years and 150 (64%) were women. A total of 51 subjects died during 5-year follow-up (cumulative 5-year all-cause mortality = 30%). From a multiple variable Cox proportional hazards model, the following variables were significantly associated with 5-year mortality: age at refractory coeliac disease diagnosis (per 20 year increase, hazard ratio = 2.21; 95% confidence interval: 1.38, 3.55), abnormal intraepithelial lymphocytes (hazard ratio = 2.85; 95% confidence interval: 1.22, 6.62), and albumin (per 0.5 unit increase, hazard ratio = 0.72; 95% confidence interval: 0.61, 0.85). A simple weighted 3-factor risk score was created to estimate 5-year survival. Conclusions Using data from a multinational registry and previously-reported risk factors, we create a prognostic model to predict 5-year mortality among patients with refractory coeliac disease. This new model may help clinicians to guide treatment and follow-up. PMID:27485029

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

Shaffer, Richard, E-mail: rickyshaffer@yahoo.co.u; Department of Clinical Oncology, Imperial College London National Health Service Trust, London; Pickles, Tom

Purpose: Prior studies have derived low values of alpha-beta ratio (a/ss) for prostate cancer of approximately 1-2 Gy. These studies used poorly matched groups, differing definitions of biochemical failure, and insufficient follow-up. Methods and Materials: National Comprehensive Cancer Network low- or low-intermediate risk prostate cancer patients, treated with external beam radiotherapy or permanent prostate brachytherapy, were matched for prostate-specific antigen, Gleason score, T-stage, percentage of positive cores, androgen deprivation therapy, and era, yielding 118 patient pairs. The Phoenix definition of biochemical failure was used. The best-fitting value for a/ss was found for up to 90-month follow-up using maximum likelihood analysis,more » and the 95% confidence interval using the profile likelihood method. Linear quadratic formalism was applied with the radiobiological parameters of relative biological effectiveness = 1.0, potential doubling time = 45 days, and repair half-time = 1 hour. Bootstrap analysis was performed to estimate uncertainties in outcomes, and hence in a/ss. Sensitivity analysis was performed by varying the values of the radiobiological parameters to extreme values. Results: The value of a/ss best fitting the outcomes data was >30 Gy, with lower 95% confidence limit of 5.2 Gy. This was confirmed on bootstrap analysis. Varying parameters to extreme values still yielded best-fit a/ss of >30 Gy, although the lower 95% confidence interval limit was reduced to 0.6 Gy. Conclusions: Using carefully matched groups, long follow-up, the Phoenix definition of biochemical failure, and well-established statistical methods, the best estimate of a/ss for low and low-tier intermediate-risk prostate cancer is likely to be higher than that of normal tissues, although a low value cannot be excluded.« less

Return on Investment of a Work-Family Intervention: Evidence From the Work, Family, and Health Network.

PubMed

Barbosa, Carolina; Bray, Jeremy W; Dowd, William N; Mills, Michael J; Moen, Phyllis; Wipfli, Brad; Olson, Ryan; Kelly, Erin L

2015-09-01

To estimate the return on investment (ROI) of a workplace initiative to reduce work-family conflict in a group-randomized 18-month field experiment in an information technology firm in the United States. Intervention resources were micro-costed; benefits included medical costs, productivity (presenteeism), and turnover. Regression models were used to estimate the ROI, and cluster-robust bootstrap was used to calculate its confidence interval. For each participant, model-adjusted costs of the intervention were $690 and company savings were $1850 (2011 prices). The ROI was 1.68 (95% confidence interval, -8.85 to 9.47) and was robust in sensitivity analyses. The positive ROI indicates that employers' investment in an intervention to reduce work-family conflict can enhance their business. Although this was the first study to present a confidence interval for the ROI, results are comparable with the literature.

PSMA Ligands for Radionuclide Imaging and Therapy of Prostate Cancer: Clinical Status

PubMed Central

Lütje, Susanne; Heskamp, Sandra; Cornelissen, Alexander S.; Poeppel, Thorsten D.; van den Broek, Sebastiaan A. M. W.; Rosenbaum-Krumme, Sandra; Bockisch, Andreas; Gotthardt, Martin; Rijpkema, Mark; Boerman, Otto C.

2015-01-01

Prostate cancer (PCa) is the most common malignancy in men worldwide, leading to substantial morbidity and mortality. At present, imaging of PCa has become increasingly important for staging, restaging, and treatment selection. Until recently, choline-based positron emission tomography/computed tomography (PET/CT) represented the state-of-the-art radionuclide imaging technique for these purposes. However, its application is limited to patients with high PSA levels and Gleason scores. Prostate-specific membrane antigen (PSMA) is a promising new target for specific imaging of PCa, because it is upregulated in the majority of PCa. Moreover, PSMA can serve as a target for therapeutic applications. Currently, several small-molecule PSMA ligands with excellent in vivo tumor targeting characteristics are being investigated for their potential in theranostic applications in PCa. Here, a review of the recent developments in PSMA-based diagnostic imaging and therapy in patients with PCa with radiolabeled PSMA ligands is provided. PMID:26681984

A stable systemic risk ranking in China's banking sector: Based on principal component analysis

NASA Astrophysics Data System (ADS)

Fang, Libing; Xiao, Binqing; Yu, Honghai; You, Qixing

2018-02-01

In this paper, we compare five popular systemic risk rankings, and apply principal component analysis (PCA) model to provide a stable systemic risk ranking for the Chinese banking sector. Our empirical results indicate that five methods suggest vastly different systemic risk rankings for the same bank, while the combined systemic risk measure based on PCA provides a reliable ranking. Furthermore, according to factor loadings of the first component, PCA combined ranking is mainly based on fundamentals instead of market price data. We clearly find that price-based rankings are not as practical a method as fundamentals-based ones. This PCA combined ranking directly shows systemic risk contributions of each bank for banking supervision purpose and reminds banks to prevent and cope with the financial crisis in advance.

Assessing Uncertainties in Surface Water Security: A Probabilistic Multi-model Resampling approach

NASA Astrophysics Data System (ADS)

Rodrigues, D. B. B.

2015-12-01

Various uncertainties are involved in the representation of processes that characterize interactions between societal needs, ecosystem functioning, and hydrological conditions. Here, we develop an empirical uncertainty assessment of water security indicators that characterize scarcity and vulnerability, based on a multi-model and resampling framework. We consider several uncertainty sources including those related to: i) observed streamflow data; ii) hydrological model structure; iii) residual analysis; iv) the definition of Environmental Flow Requirement method; v) the definition of critical conditions for water provision; and vi) the critical demand imposed by human activities. We estimate the overall uncertainty coming from the hydrological model by means of a residual bootstrap resampling approach, and by uncertainty propagation through different methodological arrangements applied to a 291 km² agricultural basin within the Cantareira water supply system in Brazil. Together, the two-component hydrograph residual analysis and the block bootstrap resampling approach result in a more accurate and precise estimate of the uncertainty (95% confidence intervals) in the simulated time series. We then compare the uncertainty estimates associated with water security indicators using a multi-model framework and provided by each model uncertainty estimation approach. The method is general and can be easily extended forming the basis for meaningful support to end-users facing water resource challenges by enabling them to incorporate a viable uncertainty analysis into a robust decision making process.

Patient-reported urinary incontinence after radiotherapy for prostate cancer: Quantifying the dose-effect.

PubMed

Cozzarini, Cesare; Rancati, Tiziana; Palorini, Federica; Avuzzi, Barbara; Garibaldi, Elisabetta; Balestrini, Damiano; Cante, Domenico; Munoz, Fernando; Franco, Pierfrancesco; Girelli, Giuseppe; Sini, Carla; Vavassori, Vittorio; Valdagni, Riccardo; Fiorino, Claudio

2017-10-01

Urinary incontinence following radiotherapy (RT) for prostate cancer (PCa) has a relevant impact on patient's quality of life. The aim of the study was to assess the unknown dose-effect relationship for late patient-reported urinary incontinence (LPRUI). Patients were enrolled within the multi-centric study DUE01. Clinical and dosimetry data including the prescribed 2Gy equivalent dose (EQD2) were prospectively collected. LPRUI was evaluated through the ICIQ-SF questionnaire filled in by the patients at RT start/end and therefore every 6months. Patients were treated with conventional (74-80Gy, 1.8-2Gy/fr) or moderately hypo-fractionated RT (65-75.2Gy, 2.2-2.7Gy/fr) in 5 fractions/week with intensity-modulated radiotherapy. Six different end-points of 3-year LPRUI, including or not patient's perception (respectively, subjective and objective end-points), were considered. Multivariable logistic models were developed for each end-point. Data of 298 patients were analyzed. The incidence of the most severe end-point (ICIQ-SF>12) was 5.1%. EQD2 calculated with alpha-beta=0.8Gy showed the best performance in fitting data: the risk of LPRUI markedly increased for EQD2>80Gy. Previous abdominal/pelvic surgery and previous TURP were the clinical factors more significantly predictive of LPRUI. Models showed excellent performances in terms of goodness-of-fit and calibration, confirmed by bootstrap-based internal validation. When included in the analyses, baseline symptoms were a major predictor for 5 out of six end-points. LPRUI after RT for PCa dramatically depends on EQD2 and few clinical factors. Results are consistent with a larger than expected impact of moderate hypo-fractionation on the risk of LPRUI. As expected, baseline symptoms, as captured by ICIQ-SF, are associated to an increased risk of LPRUI. Copyright © 2017 Elsevier B.V. All rights reserved.

Bootstrapping Methods Applied for Simulating Laboratory Works

ERIC Educational Resources Information Center

Prodan, Augustin; Campean, Remus

2005-01-01

Purpose: The aim of this work is to implement bootstrapping methods into software tools, based on Java. Design/methodology/approach: This paper presents a category of software e-tools aimed at simulating laboratory works and experiments. Findings: Both students and teaching staff use traditional statistical methods to infer the truth from sample…

Decision tree and PCA-based fault diagnosis of rotating machinery

NASA Astrophysics Data System (ADS)

Sun, Weixiang; Chen, Jin; Li, Jiaqing

2007-04-01

After analysing the flaws of conventional fault diagnosis methods, data mining technology is introduced to fault diagnosis field, and a new method based on C4.5 decision tree and principal component analysis (PCA) is proposed. In this method, PCA is used to reduce features after data collection, preprocessing and feature extraction. Then, C4.5 is trained by using the samples to generate a decision tree model with diagnosis knowledge. At last the tree model is used to make diagnosis analysis. To validate the method proposed, six kinds of running states (normal or without any defect, unbalance, rotor radial rub, oil whirl, shaft crack and a simultaneous state of unbalance and radial rub), are simulated on Bently Rotor Kit RK4 to test C4.5 and PCA-based method and back-propagation neural network (BPNN). The result shows that C4.5 and PCA-based diagnosis method has higher accuracy and needs less training time than BPNN.

Bootstrapping Development of a Cloud-Based Spoken Dialog System in the Educational Domain from Scratch Using Crowdsourced Data. Research Report. ETS RR-16-16

ERIC Educational Resources Information Center

Ramanarayanan, Vikram; Suendermann-Oeft, David; Lange, Patrick; Ivanov, Alexei V.; Evanini, Keelan; Yu, Zhou; Tsuprun, Eugene; Qian, Yao

2016-01-01

We propose a crowdsourcing-based framework to iteratively and rapidly bootstrap a dialog system from scratch for a new domain. We leverage the open-source modular HALEF dialog system to deploy dialog applications. We illustrate the usefulness of this framework using four different prototype dialog items with applications in the educational domain…

Statistical inferences with jointly type-II censored samples from two Pareto distributions

NASA Astrophysics Data System (ADS)

Abu-Zinadah, Hanaa H.

2017-08-01

In the several fields of industries the product comes from more than one production line, which is required to work the comparative life tests. This problem requires sampling of the different production lines, then the joint censoring scheme is appeared. In this article we consider the life time Pareto distribution with jointly type-II censoring scheme. The maximum likelihood estimators (MLE) and the corresponding approximate confidence intervals as well as the bootstrap confidence intervals of the model parameters are obtained. Also Bayesian point and credible intervals of the model parameters are presented. The life time data set is analyzed for illustrative purposes. Monte Carlo results from simulation studies are presented to assess the performance of our proposed method.

Maturity associated variance in physical activity and health-related quality of life in adolescent females: a mediated effects model.

PubMed

Smart, Joan E Hunter; Cumming, Sean P; Sherar, Lauren B; Standage, Martyn; Neville, Helen; Malina, Robert M

2012-01-01

This study tested a mediated effects model of psychological and behavioral adaptation to puberty within the context of physical activity (PA). Biological maturity status, physical self-concept, PA, and health-related quality of life (HRQoL) were assessed in 222 female British year 7 to 9 pupils (mean age = 12.7 years, SD = .8). Structural equation modeling using maximum likelihood estimation and bootstrapping procedures supported the hypothesized model. Maturation status was inversely related to perceptions of sport competence, body attractiveness, and physical condition; and indirectly and inversely related to physical self-worth, PA, and HRQoL. Examination of the bootstrap-generated bias-corrected confidence intervals representing the direct and indirect paths between suggested that physical self-concept partially mediated the relations between maturity status and PA, and maturity status and HRQoL. Evidence supports the contention that perceptions of the physical self partially mediate relations maturity, PA, and HRQoL in adolescent females.

A Biopsy-based 17-gene Genomic Prostate Score as a Predictor of Metastases and Prostate Cancer Death in Surgically Treated Men with Clinically Localized Disease.

PubMed

Van Den Eeden, Stephen K; Lu, Ruixiao; Zhang, Nan; Quesenberry, Charles P; Shan, Jun; Han, Jeong S; Tsiatis, Athanasios C; Leimpeter, Amethyst D; Lawrence, H Jeffrey; Febbo, Phillip G; Presti, Joseph C

2018-01-01

A 17-gene biopsy-based reverse transcription polymerase chain reaction assay, which provides a Genomic Prostate Score (GPS-scale 0-100), has been validated as an independent predictor of adverse pathology and biochemical recurrence after radical prostatectomy (RP) in men with low- and intermediate-risk prostate cancer (PCa). To evaluate GPS as a predictor of PCa metastasis and PCa-specific death (PCD) in a large cohort of men with localized PCa and long-term follow-up. A retrospective study using a stratified cohort sampling design was performed in a cohort of men treated with RP within Kaiser Permanente Northern California. RNA from archival diagnostic biopsies was assayed to generate GPS results. We assessed the association between GPS and time to metastasis and PCD in prespecified uni- and multivariable statistical analyses, based on Cox proportional hazard models accounting for sampling weights. The final study population consisted of 279 men with low-, intermediate-, and high-risk PCa between 1995 and 2010 (median follow-up 9.8 yr), and included 64 PCD and 79 metastases. Valid GPS results were obtained for 259 (93%). In univariable analysis, GPS was strongly associated with time to PCD, hazard ratio (HR)/20 GPS units=3.23 (95% confidence interval [CI] 1.84-5.65; p<0.001), and time to metastasis, HR/20 units=2.75 (95% CI 1.63-4.63; p<0.001). The association between GPS and both end points remained significant after adjusting for National Comprehensive Cancer Network, American Urological Association, and Cancer of the Prostate Risk Assessment (CAPRA) risks (p<0.001). No patient with low- or intermediate-risk disease and a GPS of<20 developed metastases or PCD (n=31). In receiver operating characteristic analysis of PCD at 10 yr, GPS improved the c-statistic from 0.78 (CAPRA alone) to 0.84 (GPS+CAPRA; p<0.001). A limitation of the study was that patients were treated during an era when definitive treatment was standard of care with little adoption of active surveillance. GPS is a strong independent predictor of long-term outcomes in clinically localized PCa in men treated with RP and may improve risk stratification for men with newly diagnosed disease. Many prostate cancers are slow growing and unlikely to spread or threaten a man's life, while others are more aggressive and require treatment. Increasingly, doctors are using new molecular tests, such as the17-gene Genomic Prostate Score (GPS), which can be performed at the time of initial diagnosis to help determine how aggressive a given patient's cancer may be. In this study, performed in a large community-based healthcare network, GPS was shown to be a strong predictor as to whether a man's prostate cancer will spread and threaten his life after surgery, providing information that may help patients and their doctors decide on the best course of management of their disease. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Toward a strategy of patient-centered access to primary care.

PubMed

Berry, Leonard L; Beckham, Dan; Dettman, Amy; Mead, Robert

2014-10-01

Patient-centered access (PCA) to primary care services is rapidly becoming an imperative for efficiently delivering high-quality health care to patients. To enhance their PCA-related efforts, some medical practices and health systems have begun to use various tactics, including team-based care, satellite clinics, same-day and group appointments, greater use of physician assistants and nurse practitioners, and remote access to health services. However, few organizations are addressing the PCA imperative comprehensively by integrating these various tactics to develop an overall PCA management strategy. Successful integration means taking into account the changing competitive and reimbursement landscape in primary care, conducting an evidence-based assessment of the barriers and benefits of PCA implementation, and attending to the particular needs of the institution engaged in this important effort. This article provides a blueprint for creating a multifaceted but coordinated PCA strategy-one aimed squarely at making patient access a centerpiece of how health care is delivered. The case of a Wisconsin-based health system is used as an illustrative example of how other institutions might begin to conceive their fledgling PCA strategies without proposing it as a one-size-fits-all model. Copyright © 2014 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

Estimation of the diagnostic threshold accounting for decision costs and sampling uncertainty.

PubMed

Skaltsa, Konstantina; Jover, Lluís; Carrasco, Josep Lluís

2010-10-01

Medical diagnostic tests are used to classify subjects as non-diseased or diseased. The classification rule usually consists of classifying subjects using the values of a continuous marker that is dichotomised by means of a threshold. Here, the optimum threshold estimate is found by minimising a cost function that accounts for both decision costs and sampling uncertainty. The cost function is optimised either analytically in a normal distribution setting or empirically in a free-distribution setting when the underlying probability distributions of diseased and non-diseased subjects are unknown. Inference of the threshold estimates is based on approximate analytically standard errors and bootstrap-based approaches. The performance of the proposed methodology is assessed by means of a simulation study, and the sample size required for a given confidence interval precision and sample size ratio is also calculated. Finally, a case example based on previously published data concerning the diagnosis of Alzheimer's patients is provided in order to illustrate the procedure.

BootGraph: probabilistic fiber tractography using bootstrap algorithms and graph theory.

PubMed

Vorburger, Robert S; Reischauer, Carolin; Boesiger, Peter

2013-02-01

Bootstrap methods have recently been introduced to diffusion-weighted magnetic resonance imaging to estimate the measurement uncertainty of ensuing diffusion parameters directly from the acquired data without the necessity to assume a noise model. These methods have been previously combined with deterministic streamline tractography algorithms to allow for the assessment of connection probabilities in the human brain. Thereby, the local noise induced disturbance in the diffusion data is accumulated additively due to the incremental progression of streamline tractography algorithms. Graph based approaches have been proposed to overcome this drawback of streamline techniques. For this reason, the bootstrap method is in the present work incorporated into a graph setup to derive a new probabilistic fiber tractography method, called BootGraph. The acquired data set is thereby converted into a weighted, undirected graph by defining a vertex in each voxel and edges between adjacent vertices. By means of the cone of uncertainty, which is derived using the wild bootstrap, a weight is thereafter assigned to each edge. Two path finding algorithms are subsequently applied to derive connection probabilities. While the first algorithm is based on the shortest path approach, the second algorithm takes all existing paths between two vertices into consideration. Tracking results are compared to an established algorithm based on the bootstrap method in combination with streamline fiber tractography and to another graph based algorithm. The BootGraph shows a very good performance in crossing situations with respect to false negatives and permits incorporating additional constraints, such as a curvature threshold. By inheriting the advantages of the bootstrap method and graph theory, the BootGraph method provides a computationally efficient and flexible probabilistic tractography setup to compute connection probability maps and virtual fiber pathways without the drawbacks of streamline tractography algorithms or the assumption of a noise distribution. Moreover, the BootGraph can be applied to common DTI data sets without further modifications and shows a high repeatability. Thus, it is very well suited for longitudinal studies and meta-studies based on DTI. Copyright © 2012 Elsevier Inc. All rights reserved.

Interval to Testosterone Recovery After Hormonal Therapy for Prostate Cancer and Risk of Death

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

D'Amico, Anthony V.; Chen, M.-H.; Renshaw, Andrew A.

Purpose: To assess whether the risk of death is associated with the time to testosterone recovery (TTR) after radiotherapy (RT) and hormonal therapy (HT) for prostate cancer (PCa). Patients and Methods: Between 1995 and 2001, 206 men with localized, unfavorable-risk PCa were randomized to receive RT or RT plus 6 months of HT. A multivariate postrandomization Cox regression analysis was used to assess whether the TTR in years was associated with the risk of death after adjusting for the known prognostic factors, age, Adult Comorbidity Evaluation-27 score, and the use of HT for recurrence. Results: Of the 102 men randomizedmore » to receive RT and HT, 57 (56%) had a TTR of >2 years, and none of these men had died of PCa after a median follow-up of 7.6 years. As the TTR increased, the risk of death decreased significantly (adjusted hazard ratio, 0.60; 95% confidence interval, 0.43-0.84; p = .003). A significant interaction was noted between the TTR and the comorbidity score (p = .002). The survival estimates were similar (p = 0.17) across the TTR values in men with moderate to severe comorbidity; however, these estimates increased significantly (p < .001) with decreasing PCa-specific mortality (p = .006) as the TTR increased in men with no or minimal comorbidity. Conclusion: The results of our study have shown that a longer TTR after RT plus 6 months of HT for unfavorable-risk PCa is associated with a lower risk of death in men with no or minimal comorbidity.« less

The impact of metformin use on survival in prostate cancer: a systematic review and meta-analysis

PubMed Central

Xiao, Yao; Zheng, Lei; Mei, Zubing; Xu, Changbao; Liu, Changwei; Chu, Xiaohan; Hao, Bin

2017-01-01

Background Metformin has been implicated to reduce the risk of prostate cancer (PCa) beyond its glucose-lowering effect. However, the influence of metformin on prognosis of PCa is often controversial. Results A total of 13 cohort studies encompassing 177,490 individuals were included in the meta-analysis. Data on overall survival (OS) and cancer-specific survival (CSS) was extracted from 8 and six studies, respectively. Comparing metformin users with non-metformin users, the pooled hazard ratios (HRs) for OS and CSS were 0.79 (95% confidence interval [CI] 0.63–0.98) and 0.76 (95% CI 0.57–1.02), respectively. Subgroup analyses stratified by baseline charcteristics indicated significant CSS benefits were noted in studies conducted in USA/Canada with prospective, large sample size, multiple-centered study design. Five studies reported the PCa prognosis for recurrence-free survival (RFS) and metformin use was significantly associated with patient RFS (HR 0.74, 95% CI, 0.58–0.95). Methods Relevant studies were searched and identified using PubMed, Embase and Cochrane databases from inception through January 2017, which investigated associations between the use of metformin and PCa prognosis. Combined HRs with 95% CI were pooled using a random-effects model. The primary outcomes of interest were OS and CSS. Conclusions Our findings provide indication that metformin therapy has a trend to improve survival for patients with PCa. Further prospective, multi-centered, large sample size cohort studies are warranted to determine the true relationship. PMID:29245991

BATEMANATER: a computer program to estimate and bootstrap mating system variables based on Bateman's principles.

PubMed

Jones, Adam G

2015-11-01

Bateman's principles continue to play a major role in the characterization of genetic mating systems in natural populations. The modern manifestations of Bateman's ideas include the opportunity for sexual selection (i.e. I(s) - the variance in relative mating success), the opportunity for selection (i.e. I - the variance in relative reproductive success) and the Bateman gradient (i.e. β(ss) - the slope of the least-squares regression of reproductive success on mating success). These variables serve as the foundation for one convenient approach for the quantification of mating systems. However, their estimation presents at least two challenges, which I address here with a new Windows-based computer software package called BATEMANATER. The first challenge is that confidence intervals for these variables are not easy to calculate. BATEMANATER solves this problem using a bootstrapping approach. The second, more serious, problem is that direct estimates of mating system variables from open populations will typically be biased if some potential progeny or adults are missing from the analysed sample. BATEMANATER addresses this problem using a maximum-likelihood approach to estimate mating system variables from incompletely sampled breeding populations. The current version of BATEMANATER addresses the problem for systems in which progeny can be collected in groups of half- or full-siblings, as would occur when eggs are laid in discrete masses or offspring occur in pregnant females. BATEMANATER has a user-friendly graphical interface and thus represents a new, convenient tool for the characterization and comparison of genetic mating systems. © 2015 John Wiley & Sons Ltd.

A comparison of PCA/ICA for data preprocessing in remote sensing imagery classification

NASA Astrophysics Data System (ADS)

He, Hui; Yu, Xianchuan

2005-10-01

In this paper a performance comparison of a variety of data preprocessing algorithms in remote sensing image classification is presented. These selected algorithms are principal component analysis (PCA) and three different independent component analyses, ICA (Fast-ICA (Aapo Hyvarinen, 1999), Kernel-ICA (KCCA and KGV (Bach & Jordan, 2002), EFFICA (Aiyou Chen & Peter Bickel, 2003). These algorithms were applied to a remote sensing imagery (1600×1197), obtained from Shunyi, Beijing. For classification, a MLC method is used for the raw and preprocessed data. The results show that classification with the preprocessed data have more confident results than that with raw data and among the preprocessing algorithms, ICA algorithms improve on PCA and EFFICA performs better than the others. The convergence of these ICA algorithms (for data points more than a million) are also studied, the result shows EFFICA converges much faster than the others. Furthermore, because EFFICA is a one-step maximum likelihood estimate (MLE) which reaches asymptotic Fisher efficiency (EFFICA), it computers quite small so that its demand of memory come down greatly, which settled the "out of memory" problem occurred in the other algorithms.

Parameter uncertainty and nonstationarity in regional extreme rainfall frequency analysis in Qu River Basin, East China

NASA Astrophysics Data System (ADS)

Zhu, Q.; Xu, Y. P.; Gu, H.

2014-12-01

Traditionally, regional frequency analysis methods were developed for stationary environmental conditions. Nevertheless, recent studies have identified significant changes in hydrological records, leading to the 'death' of stationarity. Besides, uncertainty in hydrological frequency analysis is persistent. This study aims to investigate the impact of one of the most important uncertainty sources, parameter uncertainty, together with nonstationarity, on design rainfall depth in Qu River Basin, East China. A spatial bootstrap is first proposed to analyze the uncertainty of design rainfall depth estimated by regional frequency analysis based on L-moments and estimated on at-site scale. Meanwhile, a method combining the generalized additive models with 30-year moving window is employed to analyze non-stationarity existed in the extreme rainfall regime. The results show that the uncertainties of design rainfall depth with 100-year return period under stationary conditions estimated by regional spatial bootstrap can reach 15.07% and 12.22% with GEV and PE3 respectively. On at-site scale, the uncertainties can reach 17.18% and 15.44% with GEV and PE3 respectively. In non-stationary conditions, the uncertainties of maximum rainfall depth (corresponding to design rainfall depth) with 0.01 annual exceedance probability (corresponding to 100-year return period) are 23.09% and 13.83% with GEV and PE3 respectively. Comparing the 90% confidence interval, the uncertainty of design rainfall depth resulted from parameter uncertainty is less than that from non-stationarity frequency analysis with GEV, however, slightly larger with PE3. This study indicates that the spatial bootstrap can be successfully applied to analyze the uncertainty of design rainfall depth on both regional and at-site scales. And the non-stationary analysis shows that the differences between non-stationary quantiles and their stationary equivalents are important for decision makes of water resources management and risk management.

Sevelamer is cost effective versus calcium carbonate for the first-line treatment of hyperphosphatemia in new patients to hemodialysis: a patient-level economic evaluation of the INDEPENDENT-HD study.

PubMed

Ruggeri, Matteo; Bellasi, Antonio; Cipriani, Filippo; Molony, Donald; Bell, Cynthia; Russo, Domenico; Di Iorio, Biagio

2015-10-01

The recent multicenter, randomized, open-label INDEPENDENT study demonstrated that sevelamer improves survival in new to hemodialysis (HD) patients compared with calcium carbonate. The objective of this study was to determine the cost-effectiveness of sevelamer versus calcium carbonate for patients new to HD, using patient-level data from the INDEPENDENT study. Cost-effectiveness analysis. Adult patients new to HD in Italy. A patient-level cost-effectiveness analysis was conducted from the perspective of the Servizio Sanitario Nazionale, Italy's national health service. The analysis was conducted for a 3-year time horizon. The cost of dialysis was excluded from the base case analysis. Sevelamer was compared to calcium carbonate. Total life years (LYs), total costs, and the incremental cost per LY gained were calculated. Bootstrapping was used to estimate confidence intervals around LYs, costs, and cost-effectiveness and to calculate the cost-effectiveness acceptability curve. Sevelamer was associated with a gain of 0.26 in LYs compared to calcium carbonate, over the 3-year time horizon. Total drug costs were €3,282 higher for sevelamer versus calcium carbonate, while total hospitalization costs were €2,020 lower for sevelamer versus calcium carbonate. The total incremental cost of sevelamer versus calcium carbonate was €1,262, resulting in a cost per LY gained of €4,897. The bootstrap analysis demonstrated that sevelamer was cost effective compared with calcium carbonate in 99.4 % of 10,000 bootstrap replicates, assuming a willingness-to-pay threshold of €20,000 per LY gained. Data on hospitalizations was taken from a post hoc retrospective chart review of the patients included in the INDEPENDENT study. Patient quality of life or health utility was not included in the analysis. Sevelamer is a cost-effective alternative to calcium carbonate for the first-line treatment of hyperphosphatemia in new to HD patients in Italy.

HIV-1 Transmission During Recent Infection and During Treatment Interruptions as Major Drivers of New Infections in the Swiss HIV Cohort Study.

PubMed

Marzel, Alex; Shilaih, Mohaned; Yang, Wan-Lin; Böni, Jürg; Yerly, Sabine; Klimkait, Thomas; Aubert, Vincent; Braun, Dominique L; Calmy, Alexandra; Furrer, Hansjakob; Cavassini, Matthias; Battegay, Manuel; Vernazza, Pietro L; Bernasconi, Enos; Günthard, Huldrych F; Kouyos, Roger D; Aubert, V; Battegay, M; Bernasconi, E; Böni, J; Bucher, H C; Burton-Jeangros, C; Calmy, A; Cavassini, M; Dollenmaier, G; Egger, M; Elzi, L; Fehr, J; Fellay, J; Furrer, H; Fux, C A; Gorgievski, M; Günthard, H F; Haerry, D; Hasse, B; Hirsch, H H; Hoffmann, M; Hösli, I; Kahlert, C; Kaiser, L; Keiser, O; Klimkait, T; Kouyos, R D; Kovari, H; Ledergerber, B; Martinetti, G; de Tejada, B Martinez; Metzner, K; Müller, N; Nadal, D; Nicca, D; Pantaleo, G; Rauch, A; Regenass, S; Rickenbach, M; Rudin, C; Schöni-Affolter, F; Schmid, P; Schüpbach, J; Speck, R; Tarr, P; Trkola, A; Vernazza, P L; Weber, R; Yerly, S

2016-01-01

Reducing the fraction of transmissions during recent human immunodeficiency virus (HIV) infection is essential for the population-level success of "treatment as prevention". A phylogenetic tree was constructed with 19 604 Swiss sequences and 90 994 non-Swiss background sequences. Swiss transmission pairs were identified using 104 combinations of genetic distance (1%-2.5%) and bootstrap (50%-100%) thresholds, to examine the effect of those criteria. Monophyletic pairs were classified as recent or chronic transmission based on the time interval between estimated seroconversion dates. Logistic regression with adjustment for clinical and demographic characteristics was used to identify risk factors associated with transmission during recent or chronic infection. Seroconversion dates were estimated for 4079 patients on the phylogeny, and comprised between 71 (distance, 1%; bootstrap, 100%) to 378 transmission pairs (distance, 2.5%; bootstrap, 50%). We found that 43.7% (range, 41%-56%) of the transmissions occurred during the first year of infection. Stricter phylogenetic definition of transmission pairs was associated with higher recent-phase transmission fraction. Chronic-phase viral load area under the curve (adjusted odds ratio, 3; 95% confidence interval, 1.64-5.48) and time to antiretroviral therapy (ART) start (adjusted odds ratio 1.4/y; 1.11-1.77) were associated with chronic-phase transmission as opposed to recent transmission. Importantly, at least 14% of the chronic-phase transmission events occurred after the transmitter had interrupted ART. We demonstrate a high fraction of transmission during recent HIV infection but also chronic transmissions after interruption of ART in Switzerland. Both represent key issues for treatment as prevention and underline the importance of early diagnosis and of early and continuous treatment. © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

The Whole AMS Matrix: Using the Owens Lake, Ardath Slump, and Gaviota Slide cores to explore classification of ellipsoid shapes

NASA Astrophysics Data System (ADS)

Schwehr, K.; Driscoll, N.; Tauxe, L.

2004-12-01

Categorizing sediment history using Anisotropy of Magnetic Susceptibility (AMS) has been a long standing challenge for the paleomagnetic community. The goal is to have a robust test of shape fabrics that allows workers to classify sediments in terms of being primary depositional fabric, deposition in with currents, or altered fabrics. Additionally, it is important to be able to distinguish altered fabrics into such classes as slumps, crypto-slumps, drilling deformation (such as fluidization from drilling mud and flow-in), and so forth. To try to bring a unified test scheme to AMS interpretation, we are using three example test cases. First is the Owens Lake OL92 core, which has provided previous workers with a long core example in a lacustrian environment. OL92 was classified into five zones based on visual observations of the core photographs. Using these groupings, Rosenbaum et al. (2000) was able to use the deflection of the minimum eigen vector from vertical to classify each individual AMS sample. Second is the Ardath Shale location, which provides a clear case of a lithified outcrop scale problem that showed success with the bootstrap eigen value test. Finally is the Gaviota Slide in the Santa Barbara Basin, which provides usage of 1-2 meter gravity cores. Previous work has focused on Flinn, Jelinek, and bootstrap plots of eigen values. In supporting the shape characterization we have also used a 95% confidence F-Test by means of Hext's statistical work. We have extended the F-Test into a promising new plot of the F12 and F23 confidence values, which shows good clustering in early tests. We have applied all of the available techniques to the above three test cases and will present how each technique either succeeds or fails. Since each method has its own strengths and weaknesses, it is clear that the community needs to carefully evaluate which technique should be applied to any particular problem.

Predicting prostate biopsy outcome: prostate health index (phi) and prostate cancer antigen 3 (PCA3) are useful biomarkers.

PubMed

Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Marino, Ada; Sorrentino, Alessandra; Di Carlo, Angelina; Autorino, Riccardo; Di Lorenzo, Giuseppe; Buonerba, Carlo; Altieri, Vincenzo; Mariano, Angela; Macchia, Vincenzo; Terracciano, Daniela

2012-08-16

Indication for prostate biopsy is presently mainly based on prostate-specific antigen (PSA) serum levels and digital-rectal examination (DRE). In view of the unsatisfactory accuracy of these two diagnostic exams, research has focused on novel markers to improve pre-biopsy prostate cancer detection, such as phi and PCA3. The purpose of this prospective study was to assess the diagnostic accuracy of phi and PCA3 for prostate cancer using biopsy as gold standard. Phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay) and other established biomarkers (tPSA, fPSA and %fPSA) were assessed before a 18-core prostate biopsy in a group of 251 subjects at their first biopsy. Values of %p2PSA and phi were significantly higher in patients with PCa compared with PCa-negative group (p<0.001) and also compared with high grade prostatic intraepithelial neoplasia (HGPIN) (p<0.001). PCA3 score values were significantly higher in PCa compared with PCa-negative subjects (p<0.001) and in HGPIN vs PCa-negative patients (p<0.001). ROC curve analysis showed that %p2PSA, phi and PCA3 are predictive of malignancy. In conclusion, %p2PSA, phi and PCA3 may predict a diagnosis of PCa in men undergoing their first prostate biopsy. PCA3 score is more useful in discriminating between HGPIN and non-cancer. Copyright © 2012 Elsevier B.V. All rights reserved.

Combining Nordtest method and bootstrap resampling for measurement uncertainty estimation of hematology analytes in a medical laboratory.

PubMed

Cui, Ming; Xu, Lili; Wang, Huimin; Ju, Shaoqing; Xu, Shuizhu; Jing, Rongrong

2017-12-01

Measurement uncertainty (MU) is a metrological concept, which can be used for objectively estimating the quality of test results in medical laboratories. The Nordtest guide recommends an approach that uses both internal quality control (IQC) and external quality assessment (EQA) data to evaluate the MU. Bootstrap resampling is employed to simulate the unknown distribution based on the mathematical statistics method using an existing small sample of data, where the aim is to transform the small sample into a large sample. However, there have been no reports of the utilization of this method in medical laboratories. Thus, this study applied the Nordtest guide approach based on bootstrap resampling for estimating the MU. We estimated the MU for the white blood cell (WBC) count, red blood cell (RBC) count, hemoglobin (Hb), and platelets (Plt). First, we used 6months of IQC data and 12months of EQA data to calculate the MU according to the Nordtest method. Second, we combined the Nordtest method and bootstrap resampling with the quality control data and calculated the MU using MATLAB software. We then compared the MU results obtained using the two approaches. The expanded uncertainty results determined for WBC, RBC, Hb, and Plt using the bootstrap resampling method were 4.39%, 2.43%, 3.04%, and 5.92%, respectively, and 4.38%, 2.42%, 3.02%, and 6.00% with the existing quality control data (U [k=2]). For WBC, RBC, Hb, and Plt, the differences between the results obtained using the two methods were lower than 1.33%. The expanded uncertainty values were all less than the target uncertainties. The bootstrap resampling method allows the statistical analysis of the MU. Combining the Nordtest method and bootstrap resampling is considered a suitable alternative method for estimating the MU. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Four applications of permutation methods to testing a single-mediator model.

PubMed

Taylor, Aaron B; MacKinnon, David P

2012-09-01

Four applications of permutation tests to the single-mediator model are described and evaluated in this study. Permutation tests work by rearranging data in many possible ways in order to estimate the sampling distribution for the test statistic. The four applications to mediation evaluated here are the permutation test of ab, the permutation joint significance test, and the noniterative and iterative permutation confidence intervals for ab. A Monte Carlo simulation study was used to compare these four tests with the four best available tests for mediation found in previous research: the joint significance test, the distribution of the product test, and the percentile and bias-corrected bootstrap tests. We compared the different methods on Type I error, power, and confidence interval coverage. The noniterative permutation confidence interval for ab was the best performer among the new methods. It successfully controlled Type I error, had power nearly as good as the most powerful existing methods, and had better coverage than any existing method. The iterative permutation confidence interval for ab had lower power than do some existing methods, but it performed better than any other method in terms of coverage. The permutation confidence interval methods are recommended when estimating a confidence interval is a primary concern. SPSS and SAS macros that estimate these confidence intervals are provided.

Introducing Statistical Inference to Biology Students through Bootstrapping and Randomization

ERIC Educational Resources Information Center

Lock, Robin H.; Lock, Patti Frazer

2008-01-01

Bootstrap methods and randomization tests are increasingly being used as alternatives to standard statistical procedures in biology. They also serve as an effective introduction to the key ideas of statistical inference in introductory courses for biology students. We discuss the use of such simulation based procedures in an integrated curriculum…

Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancer.

PubMed

Wang, Jing; Wu, Chen-Jiang; Bao, Mei-Ling; Zhang, Jing; Wang, Xiao-Ning; Zhang, Yu-Dong

2017-10-01

To investigate whether machine learning-based analysis of MR radiomics can help improve the performance PI-RADS v2 in clinically relevant prostate cancer (PCa). This IRB-approved study included 54 patients with PCa undergoing multi-parametric (mp) MRI before prostatectomy. Imaging analysis was performed on 54 tumours, 47 normal peripheral (PZ) and 48 normal transitional (TZ) zone based on histological-radiological correlation. Mp-MRI was scored via PI-RADS, and quantified by measuring radiomic features. Predictive model was developed using a novel support vector machine trained with: (i) radiomics, (ii) PI-RADS scores, (iii) radiomics and PI-RADS scores. Paired comparison was made via ROC analysis. For PCa versus normal TZ, the model trained with radiomics had a significantly higher area under the ROC curve (Az) (0.955 [95% CI 0.923-0.976]) than PI-RADS (Az: 0.878 [0.834-0.914], p < 0.001). The Az between them was insignificant for PCa versus PZ (0.972 [0.945-0.988] vs. 0.940 [0.905-0.965], p = 0.097). When radiomics was added, performance of PI-RADS was significantly improved for PCa versus PZ (Az: 0.983 [0.960-0.995]) and PCa versus TZ (Az: 0.968 [0.940-0.985]). Machine learning analysis of MR radiomics can help improve the performance of PI-RADS in clinically relevant PCa. • Machine-based analysis of MR radiomics outperformed in TZ cancer against PI-RADS. • Adding MR radiomics significantly improved the performance of PI-RADS. • DKI-derived Dapp and Kapp were two strong markers for the diagnosis of PCa.

Pattern of psychotropic medication use over two decades in Australian women.

PubMed

Stuart, Amanda L; Mohebbi, Mohammadreza; Pasco, Julie A; Quirk, Shae E; Brennan-Olsen, Sharon L; Berk, Michael; Williams, Lana J

2017-12-01

Few population-based studies have been used to investigate secular trends in psychotropic medication use. Therefore, the aim of this study was to examine psychotropic medication use over time using data from the Geelong Osteoporosis Study, an on-going, population-based, cohort study of Australian women. Of the 1494 women recruited at Time 1 (1993-1997), self-reported medication use from Time 2 (2004-2008) and/or Time 3 (2011-2014) was available for 889 women. Prevalence of antidepressant/antipsychotic/anxiolytic/sedative/anticonvulsant use by age and cohort strata was calculated using bootstrapping methods. Simultaneous age-cohort patterns were evaluated using logistic regression techniques. The prevalence of any psychotropic medication use increased from 8.0% (95% confidence interval = [6.3, 9.8]) at Time 1 to 26.0% (95% confidence interval = [22.4, 29.4]) at Time 3, translating to a 4.3-fold increase in the likelihood of psychotropic medication use over the study period (odds ratio = 4.3, 95% confidence interval = [3.2, 5.8], p < 0.001). This increase was driven by the use of antidepressants (odds ratio = 6.4, 95% confidence interval = [4.2, 9.5], p < 0.001) and anticonvulsants (odds ratio = 4.4, 95% confidence interval = [1.8, 11.1]) and modest increases in the use of anxiolytic agents (odds ratio = 1.9, 95% confidence interval = [1.1, 3.1]) and sedatives (odds ratio = 1.7, 95% confidence interval = [1.6, 1.9]). The prevalence of any psychotropic medication use increased with increasing age (40-59.9 years: odds ratio = 1.9, 95% confidence interval = [1.5, 2.6]; 60-79.9 years: odds ratio = 2.6, 95% confidence interval = [1.9, 3.5], compared to the 20- to 39.9-year group). Use of selective serotonin reuptake inhibitors increased dramatically over the study period (odds ratio = 15.3, 95% confidence interval = [7.0, 33.4]). Use of psychotropic medication has increased substantially over the past two decades, especially among older women. Further investigations into the correlates and outcomes of the increased use of psychotropic medications are warranted.

Bootstrapping and Maintaining Trust in the Cloud

DTIC Science & Technology

2016-03-16

of infrastructure-as-a- service (IaaS) cloud computing services such as Ama- zon Web Services, Google Compute Engine, Rackspace, et. al. means that...Implementation We implemented keylime in ∼3.2k lines of Python in four components: registrar, node, CV, and tenant. The registrar offers a REST-based web ...bootstrap key K. It provides an unencrypted REST-based web service for these two functions. As described earlier, the pro- tocols for exchanging data

A neural network based reputation bootstrapping approach for service selection

NASA Astrophysics Data System (ADS)

Wu, Quanwang; Zhu, Qingsheng; Li, Peng

2015-10-01

With the concept of service-oriented computing becoming widely accepted in enterprise application integration, more and more computing resources are encapsulated as services and published online. Reputation mechanism has been studied to establish trust on prior unknown services. One of the limitations of current reputation mechanisms is that they cannot assess the reputation of newly deployed services as no record of their previous behaviours exists. Most of the current bootstrapping approaches merely assign default reputation values to newcomers. However, by this kind of methods, either newcomers or existing services will be favoured. In this paper, we present a novel reputation bootstrapping approach, where correlations between features and performance of existing services are learned through an artificial neural network (ANN) and they are then generalised to establish a tentative reputation when evaluating new and unknown services. Reputations of services published previously by the same provider are also incorporated for reputation bootstrapping if available. The proposed reputation bootstrapping approach is seamlessly embedded into an existing reputation model and implemented in the extended service-oriented architecture. Empirical studies of the proposed approach are shown at last.

Method for exploratory cluster analysis and visualisation of single-trial ERP ensembles.

PubMed

Williams, N J; Nasuto, S J; Saddy, J D

2015-07-30

The validity of ensemble averaging on event-related potential (ERP) data has been questioned, due to its assumption that the ERP is identical across trials. Thus, there is a need for preliminary testing for cluster structure in the data. We propose a complete pipeline for the cluster analysis of ERP data. To increase the signal-to-noise (SNR) ratio of the raw single-trials, we used a denoising method based on Empirical Mode Decomposition (EMD). Next, we used a bootstrap-based method to determine the number of clusters, through a measure called the Stability Index (SI). We then used a clustering algorithm based on a Genetic Algorithm (GA) to define initial cluster centroids for subsequent k-means clustering. Finally, we visualised the clustering results through a scheme based on Principal Component Analysis (PCA). After validating the pipeline on simulated data, we tested it on data from two experiments - a P300 speller paradigm on a single subject and a language processing study on 25 subjects. Results revealed evidence for the existence of 6 clusters in one experimental condition from the language processing study. Further, a two-way chi-square test revealed an influence of subject on cluster membership. Our analysis operates on denoised single-trials, the number of clusters are determined in a principled manner and the results are presented through an intuitive visualisation. Given the cluster structure in some experimental conditions, we suggest application of cluster analysis as a preliminary step before ensemble averaging. Copyright © 2015 Elsevier B.V. All rights reserved.

EFEMP1 as a novel DNA methylation marker for prostate cancer: array-based DNA methylation and expression profiling.

PubMed

Kim, Yong-June; Yoon, Hyung-Yoon; Kim, Seon-Kyu; Kim, Young-Won; Kim, Eun-Jung; Kim, Isaac Yi; Kim, Wun-Jae

2011-07-01

Abnormal DNA methylation is associated with many human cancers. The aim of the present study was to identify novel methylation markers in prostate cancer (PCa) by microarray analysis and to test whether these markers could discriminate normal and PCa cells. Microarray-based DNA methylation and gene expression profiling was carried out using a panel of PCa cell lines and a control normal prostate cell line. The methylation status of candidate genes in prostate cell lines was confirmed by real-time reverse transcriptase-PCR, bisulfite sequencing analysis, and treatment with a demethylation agent. DNA methylation and gene expression analysis in 203 human prostate specimens, including 106 PCa and 97 benign prostate hyperplasia (BPH), were carried out. Further validation using microarray gene expression data from the Gene Expression Omnibus (GEO) was carried out. Epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1) was identified as a lead candidate methylation marker for PCa. The gene expression level of EFEMP1 was significantly higher in tissue samples from patients with BPH than in those with PCa (P < 0.001). The sensitivity and specificity of EFEMP1 methylation status in discriminating between PCa and BPH reached 95.3% (101 of 106) and 86.6% (84 of 97), respectively. From the GEO data set, we confirmed that the expression level of EFEMP1 was significantly different between PCa and BPH. Genome-wide characterization of DNA methylation profiles enabled the identification of EFEMP1 aberrant methylation patterns in PCa. EFEMP1 might be a useful indicator for the detection of PCa.

Green tea and black tea consumption and prostate cancer risk: an exploratory meta-analysis of observational studies.

PubMed

Zheng, Jusheng; Yang, Bin; Huang, Tao; Yu, Yinghua; Yang, Jing; Li, Duo

2011-01-01

Observational studies on tea consumption and prostate cancer (PCa) risk are still inconsistent. The authors conducted a meta-analysis to investigate the association between green tea and black tea consumption with PCa risk. Thirteen studies providing data on green tea or black tea consumption were identified by searching PubMed and ISI Web of Science databases and secondary referencing qualified for inclusion. A random-effects model was used to calculate the summary odds ratios (OR) and their corresponding 95% confidence intervals (CIs). For green tea, the summary OR of PCa indicated a borderline significant association in Asian populations for highest green tea consumption vs. non/lowest (OR = 0.62; 95% CI: 0.38-1.01); and the pooled estimate reached statistically significant level for case-control studies (OR = 0.43; 95% CI: 0.25-0.73), but not for prospective cohort studies (OR = 1.00; 95% CI: 0.66-1.53). For black tea, no statistically significant association was observed for the highest vs. non/lowest black tea consumption (OR = 0.99; 95% CI: 0.82-1.20). In conclusion, this meta-analysis supported that green tea but not black tea may have a protective effect on PCa, especially in Asian populations. Further research regarding green tea consumption across different regions apart from Asia is needed.

The Effect of Social Problem Solving Skills in the Relationship between Traumatic Stress and Moral Disengagement among Inner-City African American High School Students

PubMed Central

Coker, Kendell L.; Ikpe, Uduakobong N.; Brooks, Jeannie S.; Page, Brian; Sobell, Mark B.

2014-01-01

This study examined the relationship between traumatic stress, social problem solving, and moral disengagement among African American inner-city high school students. Participants consisted of 45 (25 males and 20 females) African American students enrolled in grades 10 through 12. Mediation was assessed by testing for the indirect effect using the confidence interval derived from 10,000 bootstrapped resamples. The results revealed that social problem-solving skills have an indirect effect on the relationship between traumatic stress and moral disengagement. The findings suggest that African American youth that are negatively impacted by trauma evidence deficits in their social problem solving skills and are likely to be at an increased risk to morally disengage. Implications for culturally sensitive and trauma-based intervention programs are also provided. PMID:25071874

Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

NASA Astrophysics Data System (ADS)

Wen, Lei; Yu, Jiake; Zhao, Xin

2017-10-01

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.

The role of serum neuron-specific enolase in patients with prostate cancer: a systematic review of the recent literature.

PubMed

Muoio, Barbara; Pascale, Mariarosa; Roggero, Enrico

2018-01-01

In this systematic review, we evaluated the value of serum concentrations of neuron-specific enolase (NSE) in patients with prostate cancer (PCa) in order to clarify the possible role of NSE in the diagnosis, management, treatment and monitoring of PCa. A comprehensive search of the recent literature was conducted to find relevant data on the role of NSE in PCa. Two hundred and eighty-two records were revealed, and 19 articles including 1,772 patients with PCa (either confirmed or suspected) were selected. After reviewing the articles, the major result was that elevated serum NSE appears to correlate with prognosis in advanced PCa, particularly in patients with progressive and metastatic castration-resistant PCa. Based on the existing literature, the role of serum NSE in PCa patients should be further evaluated.

Cost-effectiveness of surgical decompression for space-occupying hemispheric infarction.

PubMed

Hofmeijer, Jeannette; van der Worp, H Bart; Kappelle, L Jaap; Eshuis, Sara; Algra, Ale; Greving, Jacoba P

2013-10-01

Surgical decompression reduces mortality and increases the probability of a favorable functional outcome after space-occupying hemispheric infarction. Its cost-effectiveness is uncertain. We assessed clinical outcomes, costs, and cost-effectiveness for the first 3 years in patients who were randomized to surgical decompression or best medical treatment within 48 hours after symptom onset in the Hemicraniectomy After Middle Cerebral Artery Infarction With Life-Threatening Edema Trial (HAMLET). Data on medical consumption were derived from case record files, hospital charts, and general practitioners. We calculated costs per quality-adjusted life year (QALY). Uncertainty was assessed with bootstrapping. A Markov model was constructed to estimate costs and health outcomes after 3 years. Of 39 patients enrolled within 48 hours, 21 were randomized to surgical decompression. After 3 years, 5 surgical (24%) and 14 medical patients (78%) had died. In the first 3 years after enrollment, operated patients had more QALYs than medically treated patients (mean difference, 1.0 QALY [95% confidence interval, 0.6-1.4]), but at higher costs (mean difference, €127,000 [95% confidence interval, 73,100-181,000]), indicating incremental costs of €127,000 per QALY gained. Ninety-eight percent of incremental cost-effectiveness ratios replicated by bootstrapping were >€80,000 per QALY gained. Markov modeling suggested costs of ≈€60,000 per QALY gained for a patient's lifetime. Surgical decompression for space-occupying infarction results in an increase in QALYs, but at very high costs. http://www.controlled-trials.com. Unique identifier: ISRCTN94237756.

Analysis of the principal component algorithm in phase-shifting interferometry.

PubMed

Vargas, J; Quiroga, J Antonio; Belenguer, T

2011-06-15

We recently presented a new asynchronous demodulation method for phase-sampling interferometry. The method is based in the principal component analysis (PCA) technique. In the former work, the PCA method was derived heuristically. In this work, we present an in-depth analysis of the PCA demodulation method.

The role of CD147 expression in prostate cancer: a systematic review and meta-analysis.

PubMed

Ye, Yun; Li, Su-Liang; Wang, Yao; Yao, Yang; Wang, Juan; Ma, Yue-Yun; Hao, Xiao-Ke

2016-01-01

There are a number of studies which show that expression of CD147 is increased significantly in prostate cancer (PCa). However, conflicting conclusions have also been reported by other researchers lately. In order to arrive at a clear conclusion, a meta-analysis of eligible studies was conducted. We searched PubMed, MEDLINE, Cochrane Library, and the China National Knowledge Infrastructure databases to identify all the published case-control studies on the relationship between the expression of CD147 and PCa until February 2016. In the end, a total of 930 patients in eight studies were included in the meta-analysis. CD147 expression in the PCa patients increased significantly (odds ratio [OR], 4.65; 95% confidence interval [CI], 3.52-6.14; Z=10.79; P<0.05), but there was obvious heterogeneity between studies (I (2)=92.9%, P<0.05). Subgroup analysis showed that positive expression of CD147 was associated with PCa among the Asian population (OR, 21.01; 95% CI, 12.88-34.28; Z=12.19; P<0.05). Furthermore, it was significantly related to TNM stage (OR, 0.24; 95% CI, 0.17-0.35; Z=7.74; P<0.05), Gleason score (OR, 0.41; 95% CI, 0.31-0.56; Z=5.62; P<0.05), differentiation grade (OR, 0.27; 95% CI, 0.13-0.56; Z=3.47; P<0.05), and pretreatment serum prostate-specific antigen level (OR, 0.07; 95% CI, 0.03-0.16; Z=6.47; P<0.05). Positive expression of CD147 was related to PCa, significant heterogeneity was not found between Asian studies, and the result became more significant. The positive expression of CD147 was significantly related to the clinicopathological characteristics of PCa. This suggests that CD147 plays an essential role in poor prognosis and recurrence prediction.

The role of CD147 expression in prostate cancer: a systematic review and meta-analysis

PubMed Central

Ye, Yun; Li, Su-Liang; Wang, Yao; Yao, Yang; Wang, Juan; Ma, Yue-Yun; Hao, Xiao-Ke

2016-01-01

Background There are a number of studies which show that expression of CD147 is increased significantly in prostate cancer (PCa). However, conflicting conclusions have also been reported by other researchers lately. In order to arrive at a clear conclusion, a meta-analysis of eligible studies was conducted. Materials and methods We searched PubMed, MEDLINE, Cochrane Library, and the China National Knowledge Infrastructure databases to identify all the published case–control studies on the relationship between the expression of CD147 and PCa until February 2016. In the end, a total of 930 patients in eight studies were included in the meta-analysis. Results CD147 expression in the PCa patients increased significantly (odds ratio [OR], 4.65; 95% confidence interval [CI], 3.52–6.14; Z=10.79; P<0.05), but there was obvious heterogeneity between studies (I2=92.9%, P<0.05). Subgroup analysis showed that positive expression of CD147 was associated with PCa among the Asian population (OR, 21.01; 95% CI, 12.88–34.28; Z=12.19; P<0.05). Furthermore, it was significantly related to TNM stage (OR, 0.24; 95% CI, 0.17–0.35; Z=7.74; P<0.05), Gleason score (OR, 0.41; 95% CI, 0.31–0.56; Z=5.62; P<0.05), differentiation grade (OR, 0.27; 95% CI, 0.13–0.56; Z=3.47; P<0.05), and pretreatment serum prostate-specific antigen level (OR, 0.07; 95% CI, 0.03–0.16; Z=6.47; P<0.05). Conclusion Positive expression of CD147 was related to PCa, significant heterogeneity was not found between Asian studies, and the result became more significant. The positive expression of CD147 was significantly related to the clinicopathological characteristics of PCa. This suggests that CD147 plays an essential role in poor prognosis and recurrence prediction. PMID:27536064

Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer

PubMed Central

Roudier, Martine P; Winters, Brian R; Coleman, Ilsa; Lam, Hung-Ming; Zhang, Xiaotun; Coleman, Roger; Chéry, Lisly; True, Lawrence D.; Higano, Celestia S.; Montgomery, Bruce; Lange, Paul H.; Snyder, Linda A.; Srivistava, Shiv; Corey, Eva; Vessella, Robert L.; Nelson, Peter S.; Üren, Aykut; Morrissey, Colm

2017-01-01

Background The TMPRSS2-ERG gene fusion is detected in approximately half of primary prostate cancers (PCa) yet the prognostic significance remains unclear. We hypothesized that ERG promotes the expression of common genes in primary PCa and metastatic castration-resistant PCa (CRPC), with the objective of identifying ERG-associated pathways, which may promote the transition from primary PCa to CRPC. Methods We constructed tissue microarrays (TMA) from 127 radical prostatectomy specimens, 20 LuCaP patient-derived xenografts (PDX), and 152 CRPC metastases obtained immediately at time of death. Nuclear ERG was assessed by immunohistochemistry (IHC). To characterize the molecular features of ERG-expressing PCa, a subset of IHC confirmed ERG+ or ERG-specimens including 11 radical prostatectomies, 20 LuCaP PDXs, and 45 CRPC metastases underwent gene expression analysis. Genes were ranked based on expression in primary PCa and CRPC. Common genes of interest were targeted for IHC analysis and expression compared with biochemical recurrence (BCR) status. Results IHC revealed that 43% of primary PCa, 35% of the LuCaP PDXs, and 18% of the CRPC metastases were ERG+ (12 of 48 patients [25%] had at least 1 ERG+ metastasis). Based on gene expression data and previous literature, two proteins involved in calcium signaling (NCALD, CACNA1D), a protein involved in inflammation (HLA-DMB), CD3 positive immune cells, and a novel ERG-associated protein, DCLK1 were evaluated in primary PCa and CRPC metastases. In ERG+ primary PCa, a weak association was seen with NCALD and CACNA1D protein expression. HLA-DMB expression and the presence of CD3 positive immune cells were decreased in CRPC metastases compared to primary PCa. DCLK1 was upregulated at the protein level in unpaired ERG+ primary PCa and CRPC metastases (p=0.0013 and p<0.0001, respectively). In primary PCa, ERG status or expression of targeted proteins was not associated with BCR-free survival. However for primary PCa, ERG+DCLK1+ patients exhibited shorter time to BCR (p=0.06) compared with ERG+DCLK1- patients. Conclusions This study examined ERG expression in primary PCa and CRPC. We have identified altered levels of inflammatory mediators associated with ERG expression. We determined expression of DCLK1 correlates with ERG expression and may play a role in primary PCa progression to metastatic CPRC. PMID:26990456

Decision-making tools in prostate cancer: from risk grouping to nomograms.

PubMed

Fontanella, Paolo; Benecchi, Luigi; Grasso, Angelica; Patel, Vipul; Albala, David; Abbou, Claude; Porpiglia, Francesco; Sandri, Marco; Rocco, Bernardo; Bianchi, Giampaolo

2017-12-01

Prostate cancer (PCa) is the most common solid neoplasm and the second leading cause of cancer death in men. After the Partin tables were developed, a number of predictive and prognostic tools became available for risk stratification. These tools have allowed the urologist to better characterize this disease and lead to more confident treatment decisions for patients. The purpose of this study is to critically review the decision-making tools currently available to the urologist, from the moment when PCa is first diagnosed until patients experience metastatic progression and death. A systematic and critical analysis through Medline, EMBASE, Scopus and Web of Science databases was carried out in February 2016 as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The search was conducted using the following key words: "prostate cancer," "prediction tools," "nomograms." Seventy-two studies were identified in the literature search. We summarized the results into six sections: Tools for prediction of life expectancy (before treatment), Tools for prediction of pathological stage (before treatment), Tools for prediction of survival and cancer-specific mortality (before/after treatment), Tools for prediction of biochemical recurrence (before/after treatment), Tools for prediction of metastatic progression (after treatment) and in the last section biomarkers and genomics. The management of PCa patients requires a tailored approach to deliver a truly personalized treatment. The currently available tools are of great help in helping the urologist in the decision-making process. These tests perform very well in high-grade and low-grade disease, while for intermediate-grade disease further research is needed. Newly discovered markers, genomic tests, and advances in imaging acquisition through mpMRI will help in instilling confidence that the appropriate treatments are being offered to patients with prostate cancer.

Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

PubMed

Seibert, Tyler M; Fan, Chun Chieh; Wang, Yunpeng; Zuber, Verena; Karunamuni, Roshan; Parsons, J Kellogg; Eeles, Rosalind A; Easton, Douglas F; Kote-Jarai, ZSofia; Al Olama, Ali Amin; Garcia, Sara Benlloch; Muir, Kenneth; Grönberg, Henrik; Wiklund, Fredrik; Aly, Markus; Schleutker, Johanna; Sipeky, Csilla; Tammela, Teuvo Lj; Nordestgaard, Børge G; Nielsen, Sune F; Weischer, Maren; Bisbjerg, Rasmus; Røder, M Andreas; Iversen, Peter; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Wokolorczyk, Dominika; Kluzniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Cuk, Katarina; Saum, Kai-Uwe; Park, Jong Y; Sellers, Thomas A; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Karow, David S; Mills, Ian G; Andreassen, Ole A; Dale, Anders M

2018-01-10

To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age. Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa. Multiple institutions that were members of international PRACTICAL consortium. All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men. Prediction with hazard score of age of onset of aggressive cancer in validation set. In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10 -16 ). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score. Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa. 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.

PAin SoluTions In the Emergency Setting (PASTIES)--patient controlled analgesia versus routine care in emergency department patients with pain from traumatic injuries: randomised trial.

PubMed

Smith, Jason E; Rockett, Mark; S, Siobhan Creanor; Squire, Rosalyn; Hayward, Chris; Ewings, Paul; Barton, Andy; Pritchard, Colin; Eyre, Victoria; Cocking, Laura; Benger, Jonathan

2015-06-21

To determine whether patient controlled analgesia (PCA) is better than routine care in patients presenting to emergency departments with moderate to severe pain from traumatic injuries. Pragmatic, multicentre, parallel group, randomised controlled trial. Five English hospitals. 200 adults (71% (n = 142) male), aged 18 to 75 years, who presented to the emergency department requiring intravenous opioid analgesia for the treatment of moderate to severe pain from traumatic injuries and were expected to be admitted to hospital for at least 12 hours. PCA (n = 99) or nurse titrated analgesia (treatment as usual; n = 101). The primary outcome was total pain experienced over the 12 hour study period, derived by standardised area under the curve (scaled from 0 to 100) of each participant's hourly pain scores, captured using a visual analogue scale. Pre-specified secondary outcomes included total morphine use, percentage of study period in moderate/severe pain, percentage of study period asleep, length of hospital stay, and satisfaction with pain management. 200 participants were included in the primary analyses. Mean total pain experienced was 47.2 (SD 21.9) for the treatment as usual group and 44.0 (24.0) for the PCA group. Adjusted analyses indicated slightly (but not statistically significantly) lower total pain experienced in the PCA group than in the routine care group (mean difference 2.7, 95% confidence interval -2.4 to 7.8). Participants allocated to PCA used more morphine in total than did participants in the treatment as usual group (mean 44.3 (23.2) v 27.2 (18.2) mg; mean difference 17.0, 11.3 to 22.7). PCA participants spent, on average, less time in moderate/severe pain (36.2% (31.0) v 44.1% (31.6)), but the difference was not statistically significant. A higher proportion of PCA participants reported being perfectly or very satisfied compared with the treatment as usual group (86% (78/91) v 76% (74/98)), but this was also not statistically significant. PCA provided no statistically significant reduction in pain compared with routine care for emergency department patients with traumatic injuries. Trial registration European Clinical Trials Database EudraCT2011-000194-31; Current Controlled Trials ISRCTN25343280. © Smith et al 2015.

On the log-normality of historical magnetic-storm intensity statistics: implications for extreme-event probabilities

USGS Publications Warehouse

Love, Jeffrey J.; Rigler, E. Joshua; Pulkkinen, Antti; Riley, Pete

2015-01-01

An examination is made of the hypothesis that the statistics of magnetic-storm-maximum intensities are the realization of a log-normal stochastic process. Weighted least-squares and maximum-likelihood methods are used to fit log-normal functions to −Dst storm-time maxima for years 1957-2012; bootstrap analysis is used to established confidence limits on forecasts. Both methods provide fits that are reasonably consistent with the data; both methods also provide fits that are superior to those that can be made with a power-law function. In general, the maximum-likelihood method provides forecasts having tighter confidence intervals than those provided by weighted least-squares. From extrapolation of maximum-likelihood fits: a magnetic storm with intensity exceeding that of the 1859 Carrington event, −Dst≥850 nT, occurs about 1.13 times per century and a wide 95% confidence interval of [0.42,2.41] times per century; a 100-yr magnetic storm is identified as having a −Dst≥880 nT (greater than Carrington) but a wide 95% confidence interval of [490,1187] nT.

Variable selection under multiple imputation using the bootstrap in a prognostic study

PubMed Central

Heymans, Martijn W; van Buuren, Stef; Knol, Dirk L; van Mechelen, Willem; de Vet, Henrica CW

2007-01-01

Background Missing data is a challenging problem in many prognostic studies. Multiple imputation (MI) accounts for imputation uncertainty that allows for adequate statistical testing. We developed and tested a methodology combining MI with bootstrapping techniques for studying prognostic variable selection. Method In our prospective cohort study we merged data from three different randomized controlled trials (RCTs) to assess prognostic variables for chronicity of low back pain. Among the outcome and prognostic variables data were missing in the range of 0 and 48.1%. We used four methods to investigate the influence of respectively sampling and imputation variation: MI only, bootstrap only, and two methods that combine MI and bootstrapping. Variables were selected based on the inclusion frequency of each prognostic variable, i.e. the proportion of times that the variable appeared in the model. The discriminative and calibrative abilities of prognostic models developed by the four methods were assessed at different inclusion levels. Results We found that the effect of imputation variation on the inclusion frequency was larger than the effect of sampling variation. When MI and bootstrapping were combined at the range of 0% (full model) to 90% of variable selection, bootstrap corrected c-index values of 0.70 to 0.71 and slope values of 0.64 to 0.86 were found. Conclusion We recommend to account for both imputation and sampling variation in sets of missing data. The new procedure of combining MI with bootstrapping for variable selection, results in multivariable prognostic models with good performance and is therefore attractive to apply on data sets with missing values. PMID:17629912

Consensus statement on definition, diagnosis, and management of high-risk prostate cancer patients on behalf of the Spanish Groups of Uro-Oncology Societies URONCOR, GUO, and SOGUG.

PubMed

Henríquez, I; Rodríguez-Antolín, A; Cassinello, J; Gonzalez San Segundo, C; Unda, M; Gallardo, E; López-Torrecilla, J; Juarez, A; Arranz, J

2018-03-01

Prostate cancer (PCa) is the most prevalent malignancy in men and the second cause of mortality in industrialized countries. Based on Spanish Register of PCa, the incidence of high-risk PCa is 29%, approximately. In spite of the evidence-based beneficial effect of radiotherapy and androgen deprivation therapy in high-risk PCa, these patients (pts) are still a therapeutic challenge for all specialists involved, in part due to the absence of comparative studies to establish which of the present disposable treatments offer better results. Nowadays, high-risk PCa definition is not well consensual through the published oncology guides. Clinical stage, tumour grade, and number of risk factors are relevant to be considered on PCa prognosis. However, these factors are susceptible to change depending on when surgical or radiation therapy is considered to be the treatment of choice. Other factors, such as reference pathologist, different diagnosis biopsy schedules, surgical or radiotherapy techniques, adjuvant treatments, biochemical failures, and follow-up, make it difficult to compare the results between different therapeutic options. This article reviews important issues concerning high-risk PCa. URONCOR, GUO, and SOGUG on behalf of the Spanish Groups of Uro-Oncology Societies have reached a consensus addressing a practical recommendation on definition, diagnosis, and management of high-risk PCa.

Risk of Localized and Advanced Prostate Cancer Among Immigrants Versus Native-Born Swedish Men: A nation-wide, population-based study

PubMed Central

Loeb, Stacy; Drevin, Linda; Robinson, David; Holmberg, Erik; Carlsson, Sigrid; Lambe, Mats; Stattin, Pär

2016-01-01

Purpose Prostate cancer (PCa) incidence and prognosis vary geographically. We examined possible differences in PCa risk by clinical risk category between native-born and immigrant populations in Sweden. Our hypothesis was that lower PSA-testing uptake among foreign-born men would result in lower rates of localized disease, and similar or higher risk of metastatic disease. Methods Using the Prostate Cancer database Sweden (PCBaSe), we identified 117,328 men with PCa diagnosed from 1991–2008, of which 8,332 were foreign-born. For each case, 5 cancer-free matched controls were randomly selected from the population register. Conditional logistic regression was used to compare low-risk, intermediate-risk, high-risk, regionally metastatic, and distant metastatic PCa based upon region of origin. Results Across all risk categories, immigrants had significantly lower PCa risk than native-born Swedish men, except North Americans and Northern Europeans. The lowest PCa risk was observed in men from the Middle East, Southern Europe and Asia. Multivariable adjustment for socioeconomic factors and comorbidities did not materially change risk estimates. Older age at immigration and more recent arrival in Sweden were associated with lower PCa risk. Non-native men were less likely to be diagnosed with PCa through PSA-testing during a health check-up. Conclusions The risk for all stages of PCa was lower among first-generation immigrants to Sweden compared to native-born men. Older age at immigration and more recent immigration were associated with particularly low risks. Patterns of PSA testing appeared to only partly explain the differences in PCa risk, since immigrant men also had a lower risk of metastatic disease. PMID:23266834

Prostate-Specific Antigen (PSA) Screening and New Biomarkers for Prostate Cancer (PCa)

PubMed Central

Rittenhouse, Harry; Hu, Xinhai; Cammann, Henning; Jung, Klaus

2014-01-01

Abstract PSA screening reduces PCa-mortality but the disadvantages overdiagnosis and overtreatment require multivariable risk-prediction tools to select appropriate treatment or active surveillance. This review explains the differences between the two largest screening trials and discusses the drawbacks of screening and its meta-analysisxs. The current American and European screening strategies are described. Nonetheless, PSA is one of the most widely used tumor markers and strongly correlates with the risk of harboring PCa. However, while PSA has limitations for PCa detection with its low specificity there are several potential biomarkers presented in this review with utility for PCa currently being studied. There is an urgent need for new biomarkers especially to detect clinically significant and aggressive PCa. From all PSA-based markers, the FDA-approved prostate health index (phi) shows improved specificity over percent free and total PSA. Another kallikrein panel, 4K, which includes KLK2 has recently shown promise in clinical research studies but has not yet undergone formal validation studies. In urine, prostate cancer gene 3 (PCA3) has also been validated and approved by the FDA for its utility to detect PCa. The potential correlation of PCA3 with cancer aggressiveness requires more clinical studies. The detection of the fusion of androgen-regulated genes with genes of the regulatory transcription factors in tissue of ~50% of all PCa-patients is a milestone in PCa research. A combination of the urinary assays for TMPRSS2:ERG gene fusion and PCA3 shows an improved accuracy for PCa detection. Overall, the field of PCa biomarker discovery is very exciting and prospective. PMID:27683457

Image restoration for three-dimensional fluorescence microscopy using an orthonormal basis for efficient representation of depth-variant point-spread functions

PubMed Central

Patwary, Nurmohammed; Preza, Chrysanthe

2015-01-01

A depth-variant (DV) image restoration algorithm for wide field fluorescence microscopy, using an orthonormal basis decomposition of DV point-spread functions (PSFs), is investigated in this study. The efficient PSF representation is based on a previously developed principal component analysis (PCA), which is computationally intensive. We present an approach developed to reduce the number of DV PSFs required for the PCA computation, thereby making the PCA-based approach computationally tractable for thick samples. Restoration results from both synthetic and experimental images show consistency and that the proposed algorithm addresses efficiently depth-induced aberration using a small number of principal components. Comparison of the PCA-based algorithm with a previously-developed strata-based DV restoration algorithm demonstrates that the proposed method improves performance by 50% in terms of accuracy and simultaneously reduces the processing time by 64% using comparable computational resources. PMID:26504634

Bootstrap study of genome-enabled prediction reliabilities using haplotype blocks across Nordic Red cattle breeds.

PubMed

Cuyabano, B C D; Su, G; Rosa, G J M; Lund, M S; Gianola, D

2015-10-01

This study compared the accuracy of genome-enabled prediction models using individual single nucleotide polymorphisms (SNP) or haplotype blocks as covariates when using either a single breed or a combined population of Nordic Red cattle. The main objective was to compare predictions of breeding values of complex traits using a combined training population with haplotype blocks, with predictions using a single breed as training population and individual SNP as predictors. To compare the prediction reliabilities, bootstrap samples were taken from the test data set. With the bootstrapped samples of prediction reliabilities, we built and graphed confidence ellipses to allow comparisons. Finally, measures of statistical distances were used to calculate the gain in predictive ability. Our analyses are innovative in the context of assessment of predictive models, allowing a better understanding of prediction reliabilities and providing a statistical basis to effectively calibrate whether one prediction scenario is indeed more accurate than another. An ANOVA indicated that use of haplotype blocks produced significant gains mainly when Bayesian mixture models were used but not when Bayesian BLUP was fitted to the data. Furthermore, when haplotype blocks were used to train prediction models in a combined Nordic Red cattle population, we obtained up to a statistically significant 5.5% average gain in prediction accuracy, over predictions using individual SNP and training the model with a single breed. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Prenatal Drug Exposure and Adolescent Cortisol Reactivity: Association with Behavioral Concerns.

PubMed

Buckingham-Howes, Stacy; Mazza, Dayna; Wang, Yan; Granger, Douglas A; Black, Maureen M

2016-09-01

To examine stress reactivity in a sample of adolescents with prenatal drug exposure (PDE) by examining the consequences of PDE on stress-related adrenocortical reactivity, behavioral problems, and drug experimentation during adolescence. Participants (76 PDE, 61 non-drug exposed [NE]; 99% African-American; 50% male; mean age = 14.17 yr, SD = 1.17) provided a urine sample, completed a drug use questionnaire, and provided saliva samples (later assayed for cortisol) before and after a mild laboratory stress task. Caregivers completed the Behavior Assessment System for Children, Second Edition (BASC II) and reported their relationship to the adolescent. The NE group was more likely to exhibit task-related cortisol reactivity compared to the PDE group. Overall behavior problems and drug experimentation were comparable across groups with no differences between PDE and NE groups. In unadjusted mediation analyses, cortisol reactivity mediated the association between PDE and BASC II aggression scores (95% bootstrap confidence interval [CI], 0.04-4.28), externalizing problems scores (95% bootstrap CI, 0.03-4.50), and drug experimentation (95% bootstrap CI, 0.001-0.54). The associations remain with the inclusion of gender as a covariate but not when age is included. Findings support and expand current research in cortisol reactivity and PDE by demonstrating that cortisol reactivity attenuates the association between PDE and behavioral problems (aggression) and drug experimentation. If replicated, PDE may have long-lasting effects on stress-sensitive physiological mechanisms associated with behavioral problems (aggression) and drug experimentation in adolescence.

Study of support vector machine and serum surface-enhanced Raman spectroscopy for noninvasive esophageal cancer detection

NASA Astrophysics Data System (ADS)

Li, Shao-Xin; Zeng, Qiu-Yao; Li, Lin-Fang; Zhang, Yan-Jiao; Wan, Ming-Ming; Liu, Zhi-Ming; Xiong, Hong-Lian; Guo, Zhou-Yi; Liu, Song-Hao

2013-02-01

The ability of combining serum surface-enhanced Raman spectroscopy (SERS) with support vector machine (SVM) for improving classification esophageal cancer patients from normal volunteers is investigated. Two groups of serum SERS spectra based on silver nanoparticles (AgNPs) are obtained: one group from patients with pathologically confirmed esophageal cancer (n=30) and the other group from healthy volunteers (n=31). Principal components analysis (PCA), conventional SVM (C-SVM) and conventional SVM combination with PCA (PCA-SVM) methods are implemented to classify the same spectral dataset. Results show that a diagnostic accuracy of 77.0% is acquired for PCA technique, while diagnostic accuracies of 83.6% and 85.2% are obtained for C-SVM and PCA-SVM methods based on radial basis functions (RBF) models. The results prove that RBF SVM models are superior to PCA algorithm in classification serum SERS spectra. The study demonstrates that serum SERS in combination with SVM technique has great potential to provide an effective and accurate diagnostic schema for noninvasive detection of esophageal cancer.

Sequence polymorphism in an insect RNA virus field population: A snapshot from a single point in space and time reveals stochastic differences among and within individual hosts

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

Stenger, Drake C., E-mail: drake.stenger@ars.usda.

Population structure of Homalodisca coagulata Virus-1 (HoCV-1) among and within field-collected insects sampled from a single point in space and time was examined. Polymorphism in complete consensus sequences among single-insect isolates was dominated by synonymous substitutions. The mutant spectrum of the C2 helicase region within each single-insect isolate was unique and dominated by nonsynonymous singletons. Bootstrapping was used to correct the within-isolate nonsynonymous:synonymous arithmetic ratio (N:S) for RT-PCR error, yielding an N:S value ~one log-unit greater than that of consensus sequences. Probability of all possible single-base substitutions for the C2 region predicted N:S values within 95% confidence limits of themore » corrected within-isolate N:S when the only constraint imposed was viral polymerase error bias for transitions over transversions. These results indicate that bottlenecks coupled with strong negative/purifying selection drive consensus sequences toward neutral sequence space, and that most polymorphism within single-insect isolates is composed of newly-minted mutations sampled prior to selection. -- Highlights: •Sampling protocol minimized differential selection/history among isolates. •Polymorphism among consensus sequences dominated by negative/purifying selection. •Within-isolate N:S ratio corrected for RT-PCR error by bootstrapping. •Within-isolate mutant spectrum dominated by new mutations yet to undergo selection.« less

Assessing uncertainties in surface water security: An empirical multimodel approach

NASA Astrophysics Data System (ADS)

Rodrigues, Dulce B. B.; Gupta, Hoshin V.; Mendiondo, Eduardo M.; Oliveira, Paulo Tarso S.

2015-11-01

Various uncertainties are involved in the representation of processes that characterize interactions among societal needs, ecosystem functioning, and hydrological conditions. Here we develop an empirical uncertainty assessment of water security indicators that characterize scarcity and vulnerability, based on a multimodel and resampling framework. We consider several uncertainty sources including those related to (i) observed streamflow data; (ii) hydrological model structure; (iii) residual analysis; (iv) the method for defining Environmental Flow Requirement; (v) the definition of critical conditions for water provision; and (vi) the critical demand imposed by human activities. We estimate the overall hydrological model uncertainty by means of a residual bootstrap resampling approach, and by uncertainty propagation through different methodological arrangements applied to a 291 km2 agricultural basin within the Cantareira water supply system in Brazil. Together, the two-component hydrograph residual analysis and the block bootstrap resampling approach result in a more accurate and precise estimate of the uncertainty (95% confidence intervals) in the simulated time series. We then compare the uncertainty estimates associated with water security indicators using a multimodel framework and the uncertainty estimates provided by each model uncertainty estimation approach. The range of values obtained for the water security indicators suggests that the models/methods are robust and performs well in a range of plausible situations. The method is general and can be easily extended, thereby forming the basis for meaningful support to end-users facing water resource challenges by enabling them to incorporate a viable uncertainty analysis into a robust decision-making process.

Sample-based estimation of tree species richness in a wet tropical forest compartment

Treesearch

Steen Magnussen; Raphael Pelissier

2007-01-01

Petersen's capture-recapture ratio estimator and the well-known bootstrap estimator are compared across a range of simulated low-intensity simple random sampling with fixed-area plots of 100 m? in a rich wet tropical forest compartment with 93 tree species in the Western Ghats of India. Petersen's ratio estimator was uniformly superior to the bootstrap...

Bootstrap imputation with a disease probability model minimized bias from misclassification due to administrative database codes.

PubMed

van Walraven, Carl

2017-04-01

Diagnostic codes used in administrative databases cause bias due to misclassification of patient disease status. It is unclear which methods minimize this bias. Serum creatinine measures were used to determine severe renal failure status in 50,074 hospitalized patients. The true prevalence of severe renal failure and its association with covariates were measured. These were compared to results for which renal failure status was determined using surrogate measures including the following: (1) diagnostic codes; (2) categorization of probability estimates of renal failure determined from a previously validated model; or (3) bootstrap methods imputation of disease status using model-derived probability estimates. Bias in estimates of severe renal failure prevalence and its association with covariates were minimal when bootstrap methods were used to impute renal failure status from model-based probability estimates. In contrast, biases were extensive when renal failure status was determined using codes or methods in which model-based condition probability was categorized. Bias due to misclassification from inaccurate diagnostic codes can be minimized using bootstrap methods to impute condition status using multivariable model-derived probability estimates. Copyright © 2017 Elsevier Inc. All rights reserved.

Contact- and distance-based principal component analysis of protein dynamics.

PubMed

Ernst, Matthias; Sittel, Florian; Stock, Gerhard

2015-12-28

To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between Cα-atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

Contact- and distance-based principal component analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Ernst, Matthias; Sittel, Florian; Stock, Gerhard

2015-12-01

To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between Cα-atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

A urinary biomarker-based risk score correlates with multiparametric MRI for prostate cancer detection.

PubMed

Hendriks, Rianne J; van der Leest, Marloes M G; Dijkstra, Siebren; Barentsz, Jelle O; Van Criekinge, Wim; Hulsbergen-van de Kaa, Christina A; Schalken, Jack A; Mulders, Peter F A; van Oort, Inge M

2017-10-01

Prostate cancer (PCa) diagnostics would greatly benefit from more accurate, non-invasive techniques for the detection of clinically significant disease, leading to a reduction of over-diagnosis and over-treatment. The aim of this study was to determine the association between a novel urinary biomarker-based risk score (SelectMDx), multiparametric MRI (mpMRI) outcomes, and biopsy results for PCa detection. This retrospective observational study used data from the validation study of the SelectMDx score, in which urine was collected after digital rectal examination from men undergoing prostate biopsies. A subset of these patients also underwent a mpMRI scan of the prostate. The indications for performing mpMRI were based on persistent clinical suspicion of PCa or local staging after PCa was found upon biopsy. All mpMRI images were centrally reviewed in 2016 by an experienced radiologist blinded for the urine test results and biopsy outcome. The PI-RADS version 2 was used. In total, 172 patients were included for analysis. Hundred (58%) patients had PCa detected upon prostate biopsy, of which 52 (52%) had high-grade disease correlated with a significantly higher SelectMDx score (P < 0.01). The median SelectMDx score was significantly higher in patients with a suspicious significant lesion on mpMRI compared to no suspicion of significant PCa (P < 0.01). For the prediction of mpMRI outcome, the area-under-the-curve of SelectMDx was 0.83 compared to 0.66 for PSA and 0.65 for PCA3. There was a positive association between SelectMDx score and the final PI-RADS grade. There was a statistically significant difference in SelectMDx score between PI-RADS 3 and 4 (P < 0.01) and between PI-RADS 4 and 5 (P < 0.01). The novel urinary biomarker-based SelectMDx score is a promising tool in PCa detection. This study showed promising results regarding the correlation between the SelectMDx score and mpMRI outcomes, outperforming PCA3. Our results suggest that this risk score could guide clinicians in identifying patients at risk for significant PCa and selecting patients for further radiological diagnostics to reduce unnecessary procedures. © 2017 Wiley Periodicals, Inc.

Prostate cancer incidence and newly diagnosed patient profile in Spain in 2010.

PubMed

Cózar, José M; Miñana, Bernardino; Gómez-Veiga, Francisco; Rodríguez-Antolín, Alfredo; Villavicencio, Humberto; Cantalapiedra, Arancha; Pedrosa, Emilio

2012-12-01

What's known on the subject? and What does the study add? Prostate cancer (PCa) accounts for 12% of newly diagnosed cases of cancer in Europe. It is one of the most frequently diagnosed tumours in the developed world. Since the introduction of prostate specific antigen as a test for early detection of PCa, the rate of diagnosis has increased significantly and specific mortality has reduced in most western countries. Most of the data on the incidence of PCa are obtained from population-based cancer registries which frequently do not cover the whole population. This first national hospital-based PCa registry aims not only to estimate the incidence of the disease but to ascertain the clinical profile of newly diagnosed PCa patients, a useful tool for evaluating the impact of the disease and its socio-health management. • To estimate the 2010 incidence of prostate cancer (PCa) in Spain. • To describe the clinical profile of newly diagnosed cases using a nationwide hospital-based registry. • This was a national epidemiological observational study in 25 public hospitals with a specific reference population according to the National Health System. • Sociodemographic and clinical variables of all newly diagnosed, histopathologically confirmed PCa cases were collected in 2010, in the area of influence of each centre. Cases diagnosed in private practice were not collected (estimated nearly 10% in Spain). • Data monitoring was external to guarantee quality and homogeneity. • The age-standardized PCa incidence was determined based on the age distribution of the European standard population. • In all, 4087 new cases of PCa were diagnosed for a reference population of 4933940 men (21.8% of the Spanish male population). • The estimated age-standardized PCa incidence was 70.75 cases per 100000 men. • Mean age at diagnosis was 69 years; 11.6% of patients presented with tumour-related symptoms and 39.5% with LUTS. Median PSA was 8 ng/mL. Gleason score was ≤ 6 in 56.5%, 7 in 26.7% and >7 in 16.8% of patients. At diagnosis, 89.8% had localized, 6.4% locally advanced and 3.8% metastatic disease. • This study on PCa incidence in Spain, a western country with intensive opportunistic PSA screening, shows that PCa is a high incidence tumour, diagnosed close to 70 years, usually asymptomatic. • Almost 40% of cases have low risk disease with a risk of over-diagnosis and over-treatment. • Around 55% of patients with intermediate or high risk disease are candidates for active therapy which may result in a reduction of cancer-specific mortality. © 2012 ASOCIACIÓN ESPANOLA UROLOGÍA.

Applying robust variant of Principal Component Analysis as a damage detector in the presence of outliers

NASA Astrophysics Data System (ADS)

Gharibnezhad, Fahit; Mujica, Luis E.; Rodellar, José

2015-01-01

Using Principal Component Analysis (PCA) for Structural Health Monitoring (SHM) has received considerable attention over the past few years. PCA has been used not only as a direct method to identify, classify and localize damages but also as a significant primary step for other methods. Despite several positive specifications that PCA conveys, it is very sensitive to outliers. Outliers are anomalous observations that can affect the variance and the covariance as vital parts of PCA method. Therefore, the results based on PCA in the presence of outliers are not fully satisfactory. As a main contribution, this work suggests the use of robust variant of PCA not sensitive to outliers, as an effective way to deal with this problem in SHM field. In addition, the robust PCA is compared with the classical PCA in the sense of detecting probable damages. The comparison between the results shows that robust PCA can distinguish the damages much better than using classical one, and even in many cases allows the detection where classic PCA is not able to discern between damaged and non-damaged structures. Moreover, different types of robust PCA are compared with each other as well as with classical counterpart in the term of damage detection. All the results are obtained through experiments with an aircraft turbine blade using piezoelectric transducers as sensors and actuators and adding simulated damages.

Robust functional regression model for marginal mean and subject-specific inferences.

PubMed

Cao, Chunzheng; Shi, Jian Qing; Lee, Youngjo

2017-01-01

We introduce flexible robust functional regression models, using various heavy-tailed processes, including a Student t-process. We propose efficient algorithms in estimating parameters for the marginal mean inferences and in predicting conditional means as well as interpolation and extrapolation for the subject-specific inferences. We develop bootstrap prediction intervals (PIs) for conditional mean curves. Numerical studies show that the proposed model provides a robust approach against data contamination or distribution misspecification, and the proposed PIs maintain the nominal confidence levels. A real data application is presented as an illustrative example.

An Intelligent Architecture Based on Field Programmable Gate Arrays Designed to Detect Moving Objects by Using Principal Component Analysis

PubMed Central

Bravo, Ignacio; Mazo, Manuel; Lázaro, José L.; Gardel, Alfredo; Jiménez, Pedro; Pizarro, Daniel

2010-01-01

This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices. PMID:22163406

An intelligent architecture based on Field Programmable Gate Arrays designed to detect moving objects by using Principal Component Analysis.

PubMed

Bravo, Ignacio; Mazo, Manuel; Lázaro, José L; Gardel, Alfredo; Jiménez, Pedro; Pizarro, Daniel

2010-01-01

This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices.

Virtual reality as a human factors design analysis tool: Macro-ergonomic application validation and assessment of the Space Station Freedom payload control area

NASA Technical Reports Server (NTRS)

Hale, Joseph P.

1994-01-01

A virtual reality (VR) Applications Program has been under development at MSFC since 1989. Its objectives are to develop, assess, validate, and utilize VR in hardware development, operations development and support, missions operations training, and science training. A variety of activities are under way within many of these areas. One ongoing macro-ergonomic application of VR relates to the design of the Space Station Freedom Payload Control Area (PCA), the control room from which onboard payload operations are managed. Several preliminary conceptual PCA layouts have been developed and modeled in VR. Various managers and potential end users have virtually 'entered' these rooms and provided valuable feedback. Before VR can be used with confidence in a particular application, it must be validated, or calibrated, for that class of applications. Two associated validation studies for macro-ergonomic applications are under way to help characterize possible distortions of filtering of relevant perceptions in a virtual world. In both studies, existing control rooms and their 'virtual counterparts will be empirically compared using distance and heading estimations to objects and subjective assessments. Approaches and findings of the PCA activities and details of the studies are presented.

Using In Vitro High-Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards.

PubMed

Burgoon, Lyle D; Druwe, Ingrid L; Painter, Kyle; Yost, Erin E

2017-02-01

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high-throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline-based meta-regression can be used to integrate data across multiple assay replicates to generate a concentration-response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk-specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta-regression, may allow risk assessors to identify points of departure and risk-specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods. © 2016 Society for Risk Analysis.

Economic evaluation of a psychological intervention for high distress cancer patients and carers: costs and quality-adjusted life years.

PubMed

Chatterton, Mary Lou; Chambers, Suzanne; Occhipinti, Stefano; Girgis, Afaf; Dunn, Jeffrey; Carter, Rob; Shih, Sophy; Mihalopoulos, Cathrine

2016-07-01

This study compared the cost-effectiveness of a psychologist-led, individualised cognitive behavioural intervention (PI) to a nurse-led, minimal contact self-management condition for highly distressed cancer patients and carers. This was an economic evaluation conducted alongside a randomised trial of highly distressed adult cancer patients and carers calling cancer helplines. Services used by participants were measured using a resource use questionnaire, and quality-adjusted life years were measured using the assessment of quality of life - eight-dimension - instrument collected through a computer-assisted telephone interview. The base case analysis stratified participants based on the baseline score on the Brief Symptom Inventory. Incremental cost-effectiveness ratio confidence intervals were calculated with a nonparametric bootstrap to reflect sampling uncertainty. The results were subjected to sensitivity analysis by varying unit costs for resource use and the method for handling missing data. No significant differences were found in overall total costs or quality-adjusted life years (QALYs) between intervention groups. Bootstrapped data suggest the PI had a higher probability of lower cost and greater QALYs for both carers and patients with high distress at baseline. For patients with low levels of distress at baseline, the PI had a higher probability of greater QALYs but at additional cost. Sensitivity analysis showed the results were robust. The PI may be cost-effective compared with the nurse-led, minimal contact self-management condition for highly distressed cancer patients and carers. More intensive psychological intervention for patients with greater levels of distress appears warranted. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models.

PubMed

Degeling, Koen; IJzerman, Maarten J; Koopman, Miriam; Koffijberg, Hendrik

2017-12-15

Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Two approaches, 1) using non-parametric bootstrapping and 2) using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500), the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25), yielding infeasible modeling outcomes. Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.

The JAGUAR Score Predicts 1-Month Disability/Death in Ischemic Stroke Patient Ineligible for Recanalization Therapy.

PubMed

Widhi Nugroho, Aryandhito; Arima, Hisatomi; Takashima, Naoyuki; Fujii, Takako; Shitara, Satoshi; Miyamatsu, Naomi; Sugimoto, Yoshihisa; Nagata, Satoru; Komori, Masaru; Kita, Yoshikuni; Miura, Katsuyuki; Nozaki, Kazuhiko

2018-06-22

Most available scoring system to predict outcome after acute ischemic stroke (AIS) were established in Western countries. We aimed to develop a simple prediction score of 1-month severe disability/death after onset in AIS patients ineligible for recanalization therapy based on readily and widely obtainable on-admission clinical, laboratory and radiological examinations in Asian developing countries. Using the Shiga Stroke Registry, a large population-based registry in Japan, multivariable logistic regression analysis was conducted in 1617 AIS patients ineligible for recanalization therapy to yield ß-coefficients of significant predictors of 1-month modified Rankin Scale score of 5-6, which were then multiplied by a specific constant and rounded to nearest integer to develop 0-10 points system. Model discrimination and calibration were evaluated in the original and bootstrapped population. Japan Coma Scale score (J), age (A), random glucose (G), untimely onset-to-arrival time (U), atrial fibrillation (A), and preadmission dependency status according to the modified Rankin Scale score (R), were recognized as independent predictors of outcome. Each of their β-coefficients was multiplied by 1.3 creating the JAGUAR score. Its area under the curve (95% confidence interval) was .901 (.880- .922) and .901 (.900- .901) in the original and bootstrapped population, respectively. It was found to have good calibration in both study population (P = .27). The JAGUAR score can be an important prediction tool of severe disability/death in AIS patients ineligible for recanalization therapy that can be applied on admission with no complicated calculation and multimodal neuroimaging necessary, thus suitable for Asian developing countries. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

E-selectin ligand-1 controls circulating prostate cancer cell rolling/adhesion and metastasis

PubMed Central

Yasmin-Karim, Sayeda; King, Michael R.; Messing, Edward M.; Lee, Yi-Fen

2014-01-01

Circulating prostate cancer (PCa) cells preferentially roll and adhere on bone marrow vascular endothelial cells, where abundant E-selectin and stromal cell-derived factor 1 (SDF-1) are expressed, subsequently initiating a cascade of activation events that eventually lead to the development of metastases. To elucidate the roles of circulating PCa cells' rolling and adhesion behaviors in cancer metastases, we applied a dynamic cylindrical flow-based microchannel device that is coated with E-selectin and SDF-1, mimicking capillary endothelium. Using this device we captured a small fraction of rolling PCa cells. These rolling cells display higher static adhesion ability, more aggressive cancer phenotypes and stem-like properties. Importantly, mice received rolling PCa cells, but not floating PCa cells, developed cancer metastases. Genes coding for E-selectin ligands and genes associated with cancer stem cells and metastasis were elevated in rolling PCa cells. Knock down of E-selectin ligand 1(ESL-1), significantly impaired PCa cells' rolling capacity and reduced cancer aggressiveness. Moreover, ESL-1 activates RAS and MAP kinase signal cascade, consequently inducing the downstream targets. In summary, circulating PCa cells' rolling capacity contributes to PCa metastasis, and that is in part controlled by ESL-1. PMID:25301730

Lightweight CoAP-Based Bootstrapping Service for the Internet of Things.

PubMed

Garcia-Carrillo, Dan; Marin-Lopez, Rafael

2016-03-11

The Internet of Things (IoT) is becoming increasingly important in several fields of industrial applications and personal applications, such as medical e-health, smart cities, etc. The research into protocols and security aspects related to this area is continuously advancing in making these networks more reliable and secure, taking into account these aspects by design. Bootstrapping is a procedure by which a user obtains key material and configuration information, among other parameters, to operate as an authenticated party in a security domain. Until now solutions have focused on re-using security protocols that were not developed for IoT constraints. For this reason, in this work we propose a design and implementation of a lightweight bootstrapping service for IoT networks that leverages one of the application protocols used in IoT : Constrained Application Protocol (CoAP). Additionally, in order to provide flexibility, scalability, support for large scale deployment, accountability and identity federation, our design uses technologies such as the Extensible Authentication Protocol (EAP) and Authentication Authorization and Accounting (AAA). We have named this service CoAP-EAP. First, we review the state of the art in the field of bootstrapping and specifically for IoT. Second, we detail the bootstrapping service: the architecture with entities and interfaces and the flow operation. Third, we obtain performance measurements of CoAP-EAP (bootstrapping time, memory footprint, message processing time, message length and energy consumption) and compare them with PANATIKI. The most significant and constrained representative of the bootstrapping solutions related with CoAP-EAP. As we will show, our solution provides significant improvements, mainly due to an important reduction of the message length.

Lightweight CoAP-Based Bootstrapping Service for the Internet of Things

PubMed Central

Garcia-Carrillo, Dan; Marin-Lopez, Rafael

2016-01-01

The Internet of Things (IoT) is becoming increasingly important in several fields of industrial applications and personal applications, such as medical e-health, smart cities, etc. The research into protocols and security aspects related to this area is continuously advancing in making these networks more reliable and secure, taking into account these aspects by design. Bootstrapping is a procedure by which a user obtains key material and configuration information, among other parameters, to operate as an authenticated party in a security domain. Until now solutions have focused on re-using security protocols that were not developed for IoT constraints. For this reason, in this work we propose a design and implementation of a lightweight bootstrapping service for IoT networks that leverages one of the application protocols used in IoT : Constrained Application Protocol (CoAP). Additionally, in order to provide flexibility, scalability, support for large scale deployment, accountability and identity federation, our design uses technologies such as the Extensible Authentication Protocol (EAP) and Authentication Authorization and Accounting (AAA). We have named this service CoAP-EAP. First, we review the state of the art in the field of bootstrapping and specifically for IoT. Second, we detail the bootstrapping service: the architecture with entities and interfaces and the flow operation. Third, we obtain performance measurements of CoAP-EAP (bootstrapping time, memory footprint, message processing time, message length and energy consumption) and compare them with PANATIKI. The most significant and constrained representative of the bootstrapping solutions related with CoAP-EAP. As we will show, our solution provides significant improvements, mainly due to an important reduction of the message length. PMID:26978362

Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer.

PubMed

Roudier, Martine P; Winters, Brian R; Coleman, Ilsa; Lam, Hung-Ming; Zhang, Xiaotun; Coleman, Roger; Chéry, Lisly; True, Lawrence D; Higano, Celestia S; Montgomery, Bruce; Lange, Paul H; Snyder, Linda A; Srivastava, Shiv; Corey, Eva; Vessella, Robert L; Nelson, Peter S; Üren, Aykut; Morrissey, Colm

2016-06-01

The TMPRSS2-ERG gene fusion is detected in approximately half of primary prostate cancers (PCa) yet the prognostic significance remains unclear. We hypothesized that ERG promotes the expression of common genes in primary PCa and metastatic castration-resistant PCa (CRPC), with the objective of identifying ERG-associated pathways, which may promote the transition from primary PCa to CRPC. We constructed tissue microarrays (TMA) from 127 radical prostatectomy specimens, 20 LuCaP patient-derived xenografts (PDX), and 152 CRPC metastases obtained immediately at time of death. Nuclear ERG was assessed by immunohistochemistry (IHC). To characterize the molecular features of ERG-expressing PCa, a subset of IHC confirmed ERG+ or ERG- specimens including 11 radical prostatectomies, 20 LuCaP PDXs, and 45 CRPC metastases underwent gene expression analysis. Genes were ranked based on expression in primary PCa and CRPC. Common genes of interest were targeted for IHC analysis and expression compared with biochemical recurrence (BCR) status. IHC revealed that 43% of primary PCa, 35% of the LuCaP PDXs, and 18% of the CRPC metastases were ERG+ (12 of 48 patients [25%] had at least one ERG+ metastasis). Based on gene expression data and previous literature, two proteins involved in calcium signaling (NCALD, CACNA1D), a protein involved in inflammation (HLA-DMB), CD3 positive immune cells, and a novel ERG-associated protein, DCLK1 were evaluated in primary PCa and CRPC metastases. In ERG+ primary PCa, a weak association was seen with NCALD and CACNA1D protein expression. HLA-DMB association with ERG was decreased and CD3 cell number association with ERG was changed from positive to negative in CRPC metastases compared to primary PCa. DCLK1 was upregulated at the protein level in unpaired ERG+ primary PCa and CRPC metastases (P = 0.0013 and P < 0.0001, respectively). In primary PCa, ERG status or expression of targeted proteins was not associated with BCR-free survival. However, for primary PCa, ERG+DCLK1+ patients exhibited shorter time to BCR (P = 0.06) compared with ERG+DCLK1- patients. This study examined ERG expression in primary PCa and CRPC. We have identified altered levels of inflammatory mediators associated with ERG expression. We determined expression of DCLK1 correlates with ERG expression and may play a role in primary PCa progression to metastatic CPRC. Prostate 76:810-822, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Accuracy of the prostate health index versus the urinary prostate cancer antigen 3 score to predict overall and significant prostate cancer at initial biopsy.

PubMed

Seisen, Thomas; Rouprêt, Morgan; Brault, Didier; Léon, Priscilla; Cancel-Tassin, Géraldine; Compérat, Eva; Renard-Penna, Raphaële; Mozer, Pierre; Guechot, Jérome; Cussenot, Olivier

2015-01-01

It remains unclear whether the Prostate Health Index (PHI) or the urinary Prostate-Cancer Antigen 3 (PCA-3) score is more accurate at screening for prostate cancer (PCa). The aim of this study was to prospectively compare the accuracy of PHI and PCA-3 scores to predict overall and significant PCa in men undergoing an initial prostate biopsy. Double-blind assessments of PHI and PCA-3 were conducted by referent physicians in 138 patients who subsequently underwent trans-rectal ultrasound-guided prostate biopsy according to a 12-core scheme. Predictive accuracies of PHI and PCA-3 were assessed using AUC and compared according to the DeLong method. Diagnostic performances with usual cut-off values for positivity (i.e., PHI >40 and PCA-3 >35) were calculated, and odds ratios associated with predicting PCa overall and significant PCa as defined by pathological updated Epstein criteria (i.e., Gleason score ≥7, more than three positive cores, or >50% cancer involvement in any core) were estimated using logistic regression. Prevalences of overall and significant PCa were 44.9% and 28.3%, respectively. PCA-3 (AUC = 0.71) was the most accurate predictor of PCa overall, and significantly outperformed PHI (AUC = 0.65; P = 0.03). However, PHI (AUC = 0.80) remained the most accurate predictor when screening exclusively for significant PCa and significantly outperformed PCA-3 (AUC = 0.55; P = 0.03). Furthermore, PCA-3 >35 had the best accuracy, and positive or negative predictive values when screening for PCa overall whereas these diagnostic performances were greater for PHI >40 when exclusively screening for significant PCa. PHI > 40 combined with PCA-3 > 35 was more specific in both cases. In multivariate analyses, PCA-3 >35 (OR = 5.68; 95%CI = [2.21-14.59]; P < 0.001) was significantly correlated with the presence of PCa overall, but PHI >40 (OR = 9.60; 95%CI = [1.72-91.32]; P = 0.001) was the only independent predictor for detecting significant PCa. Although PCA-3 score is the best predictor for PCa overall at initial biopsy, our findings strongly indicate that PHI should be used for population-based screening to avoid over-diagnosis of indolent tumors that are unlikely to cause death. © 2014 Wiley Periodicals, Inc.

Estimating source parameters from deformation data, with an application to the March 1997 earthquake swarm off the Izu Peninsula, Japan

NASA Astrophysics Data System (ADS)

Cervelli, P.; Murray, M. H.; Segall, P.; Aoki, Y.; Kato, T.

2001-06-01

We have applied two Monte Carlo optimization techniques, simulated annealing and random cost, to the inversion of deformation data for fault and magma chamber geometry. These techniques involve an element of randomness that permits them to escape local minima and ultimately converge to the global minimum of misfit space. We have tested the Monte Carlo algorithms on two synthetic data sets. We have also compared them to one another in terms of their efficiency and reliability. We have applied the bootstrap method to estimate confidence intervals for the source parameters, including the correlations inherent in the data. Additionally, we present methods that use the information from the bootstrapping procedure to visualize the correlations between the different model parameters. We have applied these techniques to GPS, tilt, and leveling data from the March 1997 earthquake swarm off of the Izu Peninsula, Japan. Using the two Monte Carlo algorithms, we have inferred two sources, a dike and a fault, that fit the deformation data and the patterns of seismicity and that are consistent with the regional stress field.

Near-field photothermal microspectroscopy for adult stem-cell identification and characterization.

PubMed

Grude, Olaug; Hammiche, Azzedine; Pollock, Hubert; Bentley, Adam J; Walsh, Michael J; Martin, Francis L; Fullwood, Nigel J

2007-12-01

The identification of stem cells in adult tissue is a challenging problem in biomedicine. Currently, stem cells are identified by individual epitopes, which are generally tissue specific. The discovery of a stem-cell marker common to other adult tissue types could open avenues in the development of therapeutic stem-cell strategies. We report the use of the novel technique of Fourier transform infrared near-field photothermal microspectroscopy (FTIR-PTMS) for the characterization of stem cells, transit amplifying (TA) cells and terminally differentiated (TD) cells in the corneal epithelium. Principal component analysis (PCA) data demonstrate excellent discrimination of cell type by spectra. PCA in combination with linear discriminant analysis (PCA-LDA) shows that FTIR-PTMS very effectively discriminates between the three cell populations. Statistically significant differences above the 99% confidence level between IR spectra from stem cells and TA cells suggest that nucleic acid conformational changes are an important component of the differences between spectral data from the two cell types. FTIR-PTMS is a new addition to existing spectroscopy methods based on the concept of interfacing a conventional FTIR spectrometer with an atomic force microscope equipped with a near-field thermal sensing probe. FTIR-PTMS spectroscopy currently has spatial resolution that is similar to that of diffraction-limited optical detection FTIR spectroscopy techniques, but as a near-field probing technique has considerable potential for further improvement. Our work also suggests that FTIR-PTMS is potentially more sensitive than synchrotron radiation FTIR spectroscopy for some applications. Microspectroscopy techniques like FTIR-PTMS provide information about the entire molecular composition of cells, in contrast to epitope recognition that only considers the presence or absence of individual molecules. Our results with FTIR-PTMS on corneal stem cells are promising for the potential development of an IR spectral fingerprint for stem cells.

Carving out the end of the world or (superconformal bootstrap in six dimensions)

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

Chang, Chi-Ming; Lin, Ying-Hsuan

We bootstrap N=(1,0) superconformal field theories in six dimensions, by analyzing the four-point function of flavor current multiplets. By assuming E 8 flavor group, we present universal bounds on the central charge C T and the flavor central charge C J. Based on the numerical data, we conjecture that the rank-one E-string theory saturates the universal lower bound on C J , and numerically determine the spectrum of long multiplets in the rank-one E-string theory. We comment on the possibility of solving the higher-rank E-string theories by bootstrap and thereby probing M-theory on AdS 7×S 4/Z 2 .

Carving out the end of the world or (superconformal bootstrap in six dimensions)

DOE PAGES

Chang, Chi-Ming; Lin, Ying-Hsuan

2017-08-29

We bootstrap N=(1,0) superconformal field theories in six dimensions, by analyzing the four-point function of flavor current multiplets. By assuming E 8 flavor group, we present universal bounds on the central charge C T and the flavor central charge C J. Based on the numerical data, we conjecture that the rank-one E-string theory saturates the universal lower bound on C J , and numerically determine the spectrum of long multiplets in the rank-one E-string theory. We comment on the possibility of solving the higher-rank E-string theories by bootstrap and thereby probing M-theory on AdS 7×S 4/Z 2 .

The influence of stigma on the quality of life for prostate cancer survivors.

PubMed

Wood, Andrew W; Barden, Sejal; Terk, Mitchell; Cesaretti, Jamie

2017-01-01

The purpose of the present study was to investigate the influence of stigma on prostate cancer (PCa) survivors' quality of life. Stigma for lung cancer survivors has been the focus of considerable research (Else-Quest & Jackson, 2014); however, gaps remain in understanding the experience of PCa stigma. A cross-sectional correlational study was designed to assess the incidence of PCa stigma and its influence on the quality of life of survivors. Eighty-five PCa survivors were administered survey packets consisting of a stigma measure, a PCa-specific quality of life measure, and a demographic survey during treatment of their disease. A linear regression analysis was conducted with the data received from PCa survivors. Results indicated that PCa stigma has a significant, negative influence on the quality of life for survivors (R 2 = 0.33, F(4, 80) = 11.53, p < 0.001). There were no statistically significant differences in PCa stigma based on demographic variables (e.g., race and age). Implications for physical and mental health practitioners and researchers are discussed.

Motor features in posterior cortical atrophy and their imaging correlates☆

PubMed Central

Ryan, Natalie S.; Shakespeare, Timothy J.; Lehmann, Manja; Keihaninejad, Shiva; Nicholas, Jennifer M.; Leung, Kelvin K.; Fox, Nick C.; Crutch, Sebastian J.

2014-01-01

Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by impaired higher visual processing skills; however, motor features more commonly associated with corticobasal syndrome may also occur. We investigated the frequency and clinical characteristics of motor features in 44 PCA patients and, with 30 controls, conducted voxel-based morphometry, cortical thickness, and subcortical volumetric analyses of their magnetic resonance imaging. Prominent limb rigidity was used to define a PCA-motor subgroup. A total of 30% (13) had PCA-motor; all demonstrating asymmetrical left upper limb rigidity. Limb apraxia was more frequent and asymmetrical in PCA-motor, as was myoclonus. Tremor and alien limb phenomena only occurred in this subgroup. The subgroups did not differ in neuropsychological test performance or apolipoprotein E4 allele frequency. Greater asymmetry of atrophy occurred in PCA-motor, particularly involving right frontoparietal and peri-rolandic cortices, putamen, and thalamus. The 9 patients (including 4 PCA-motor) with pathology or cerebrospinal fluid all showed evidence of Alzheimer's disease. Our data suggest that PCA patients with motor features have greater atrophy of contralateral sensorimotor areas but are still likely to have underlying Alzheimer's disease. PMID:25086839

On the Model-Based Bootstrap with Missing Data: Obtaining a "P"-Value for a Test of Exact Fit

ERIC Educational Resources Information Center

Savalei, Victoria; Yuan, Ke-Hai

2009-01-01

Evaluating the fit of a structural equation model via bootstrap requires a transformation of the data so that the null hypothesis holds exactly in the sample. For complete data, such a transformation was proposed by Beran and Srivastava (1985) for general covariance structure models and applied to structural equation modeling by Bollen and Stine…

Review of Orbital Propellant Transfer Techniques and the Feasibility of a Thermal Bootstrap Propellant Transfer Concepts

NASA Technical Reports Server (NTRS)

Yoshikawa, H. H.; Madison, I. B.

1971-01-01

This study was performed in support of the NASA Task B-2 Study Plan for Space Basing. The nature of space-based operations implies that orbital transfer of propellant is a prime consideration. The intent of this report is (1) to report on the findings and recommendations of existing literature on space-based propellant transfer techniques, and (2) to determine possible alternatives to the recommended methods. The reviewed literature recommends, in general, the use of conventional liquid transfer techniques (i.e., pumping) in conjunction with an artificially induced gravitational field. An alternate concept that was studied, the Thermal Bootstrap Transfer Process, is based on the compression of a two-phase fluid with subsequent condensation to a liquid (vapor compression/condensation). This concept utilizes the intrinsic energy capacities of the tanks and propellant by exploiting temperature differentials and available energy differences. The results indicate the thermodynamic feasibility of the Thermal Bootstrap Transfer Process for a specific range of tank sizes, temperatures, fill-factors and receiver tank heat transfer coefficients.

Capital market based warning indicators of bank runs

NASA Astrophysics Data System (ADS)

Vakhtina, Elena; Wosnitza, Jan Henrik

2015-01-01

In this investigation, we examine the univariate as well as the multivariate capabilities of the log-periodic [super-exponential] power law (LPPL) for the prediction of bank runs. The research is built upon daily CDS spreads of 40 international banks for the period from June 2007 to March 2010, i.e. at the heart of the global financial crisis. For this time period, 20 of the financial institutions received federal bailouts and are labeled as defaults while the remaining institutions are categorized as non-defaults. The employed multivariate pattern recognition approach represents a modification of the CORA3 algorithm. The approach is found to be robust regardless of reasonable changes of its inputs. Despite the fact that distinct alarm indices for banks do not clearly demonstrate predictive capabilities of the LPPL, the synchronized alarm indices confirm the multivariate discriminative power of LPPL patterns in CDS spread developments acknowledged by bootstrap intervals with 70% confidence level.

On a PCA-based lung motion model

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Jia, Xun; Zhao, Tianyu; Liu, Weifeng; Wuenschel, Sara; Lamb, James; Yang, Deshan; Low, Daniel A.; Jiang, Steve B.

2011-09-01

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772-81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921-9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1 mm (0.7 ± 0.1 mm). When a single artificial internal marker was used to derive the lung motion, the average 3D error was found to be within 2 mm (1.8 ± 0.3 mm) through comprehensive statistical analysis. The optimal number of PCA coefficients needs to be determined on a patient-by-patient basis and two PCA coefficients seem to be sufficient for accurate modeling of the lung motion for most patients. In conclusion, we have presented thorough theoretical analysis and clinical validation of the PCA lung motion model. The feasibility of deriving the entire lung motion using a single marker has also been demonstrated on clinical data using a simulation approach.

Liposome bupivacaine for improvement in economic outcomes and opioid burden in GI surgery: IMPROVE Study pooled analysis.

PubMed

Cohen, Stephen M; Vogel, Jon D; Marcet, Jorge E; Candiotti, Keith A

2014-01-01

Postsurgical pain management remains a significant challenge. Liposome bupivacaine, as part of a multimodal analgesic regimen, has been shown to significantly reduce postsurgical opioid consumption, hospital length of stay (LOS), and hospitalization costs in gastrointestinal (GI) surgery, compared with intravenous (IV) opioid-based patient-controlled analgesia (PCA). Pooled results from open-label studies comparing a liposome bupivacaine-based multimodal analgesic regimen with IV opioid PCA were analyzed. Patients (n=191) who underwent planned surgery and received study drug (IV opioid PCA, n=105; multimodal analgesia, n=86) were included. Liposome bupivacaine-based multimodal analgesia compared with IV opioid PCA significantly reduced mean (standard deviation [SD]) postsurgical opioid consumption (38 [55] mg versus [vs] 96 [85] mg; P<0.0001), postsurgical LOS (median 2.9 vs 4.3 days; P<0.0001), and mean hospitalization costs (US$8,271 vs US$10,726; P=0.0109). The multimodal analgesia group reported significantly fewer patients with opioid-related adverse events (AEs) than the IV opioid PCA group (P=0.0027); there were no significant between-group differences in patient satisfaction scores at 30 days. A liposome bupivacaine-based multimodal analgesic regimen was associated with significantly less opioid consumption, opioid-related AEs, and better health economic outcomes compared with an IV opioid PCA-based regimen in patients undergoing GI surgery. This pooled analysis is based on data from Phase IV clinical trials registered on the US National Institutes of Health www.ClinicalTrials.gov database under study identifiers NCT01460485, NCT01507220, NCT01507233, NCT01509638, NCT01509807, NCT01509820, NCT01461122, NCT01461135, NCT01534988, and NCT01507246.

Wavelet method for CT colonography computer-aided polyp detection.

PubMed

Li, Jiang; Van Uitert, Robert; Yao, Jianhua; Petrick, Nicholas; Franaszek, Marek; Huang, Adam; Summers, Ronald M

2008-08-01

Computed tomographic colonography (CTC) computer aided detection (CAD) is a new method to detect colon polyps. Colonic polyps are abnormal growths that may become cancerous. Detection and removal of colonic polyps, particularly larger ones, has been shown to reduce the incidence of colorectal cancer. While high sensitivities and low false positive rates are consistently achieved for the detection of polyps sized 1 cm or larger, lower sensitivities and higher false positive rates occur when the goal of CAD is to identify "medium"-sized polyps, 6-9 mm in diameter. Such medium-sized polyps may be important for clinical patient management. We have developed a wavelet-based postprocessor to reduce false positives for this polyp size range. We applied the wavelet-based postprocessor to CTC CAD findings from 44 patients in whom 45 polyps with sizes of 6-9 mm were found at segmentally unblinded optical colonoscopy and visible on retrospective review of the CT colonography images. Prior to the application of the wavelet-based postprocessor, the CTC CAD system detected 33 of the polyps (sensitivity 73.33%) with 12.4 false positives per patient, a sensitivity comparable to that of expert radiologists. Fourfold cross validation with 5000 bootstraps showed that the wavelet-based postprocessor could reduce the false positives by 56.61% (p <0.001), to 5.38 per patient (95% confidence interval [4.41, 6.34]), without significant sensitivity degradation (32/45, 71.11%, 95% confidence interval [66.39%, 75.74%], p=0.1713). We conclude that this wavelet-based postprocessor can substantially reduce the false positive rate of our CTC CAD for this important polyp size range.

A revisit to contingency table and tests of independence: bootstrap is preferred to Chi-square approximations as well as Fisher's exact test.

PubMed

Lin, Jyh-Jiuan; Chang, Ching-Hui; Pal, Nabendu

2015-01-01

To test the mutual independence of two qualitative variables (or attributes), it is a common practice to follow the Chi-square tests (Pearson's as well as likelihood ratio test) based on data in the form of a contingency table. However, it should be noted that these popular Chi-square tests are asymptotic in nature and are useful when the cell frequencies are "not too small." In this article, we explore the accuracy of the Chi-square tests through an extensive simulation study and then propose their bootstrap versions that appear to work better than the asymptotic Chi-square tests. The bootstrap tests are useful even for small-cell frequencies as they maintain the nominal level quite accurately. Also, the proposed bootstrap tests are more convenient than the Fisher's exact test which is often criticized for being too conservative. Finally, all test methods are applied to a few real-life datasets for demonstration purposes.

Improvement of Prostate Cancer Diagnosis by Detecting PSA Glycosylation-Specific Changes.

PubMed

Llop, Esther; Ferrer-Batallé, Montserrat; Barrabés, Sílvia; Guerrero, Pedro Enrique; Ramírez, Manel; Saldova, Radka; Rudd, Pauline M; Aleixandre, Rosa N; Comet, Josep; de Llorens, Rafael; Peracaula, Rosa

2016-01-01

New markers based on PSA isoforms have recently been developed to improve prostate cancer (PCa) diagnosis. However, novel approaches are still required to differentiate aggressive from non-aggressive PCa to improve decision making for patients. PSA glycoforms have been shown to be differentially expressed in PCa. In particular, changes in the extent of core fucosylation and sialylation of PSA N-glycans in PCa patients compared to healthy controls or BPH patients have been reported. The objective of this study was to determine these specific glycan structures in serum PSA to analyze their potential value as markers for discriminating between BPH and PCa of different aggressiveness. In the present work, we have established two methodologies to analyze the core fucosylation and the sialic acid linkage of PSA N-glycans in serum samples from BPH (29) and PCa (44) patients with different degrees of aggressiveness. We detected a significant decrease in the core fucose and an increase in the α2,3-sialic acid percentage of PSA in high-risk PCa that differentiated BPH and low-risk PCa from high-risk PCa patients. In particular, a cut-off value of 0.86 of the PSA core fucose ratio, could distinguish high-risk PCa patients from BPH with 90% sensitivity and 95% specificity, with an AUC of 0.94. In the case of the α2,3-sialic acid percentage of PSA, the cut-off value of 30% discriminated between high-risk PCa and the group of BPH, low-, and intermediate-risk PCa with a sensitivity and specificity of 85.7% and 95.5%, respectively, with an AUC of 0.97. The latter marker exhibited high performance in differentiating between aggressive and non-aggressive PCa and has the potential for translational application in the clinic.

Improvement of Prostate Cancer Diagnosis by Detecting PSA Glycosylation-Specific Changes

PubMed Central

Llop, Esther; Ferrer-Batallé, Montserrat; Barrabés, Sílvia; Guerrero, Pedro Enrique; Ramírez, Manel; Saldova, Radka; Rudd, Pauline M.; Aleixandre, Rosa N.; Comet, Josep; de Llorens, Rafael; Peracaula, Rosa

2016-01-01

New markers based on PSA isoforms have recently been developed to improve prostate cancer (PCa) diagnosis. However, novel approaches are still required to differentiate aggressive from non-aggressive PCa to improve decision making for patients. PSA glycoforms have been shown to be differentially expressed in PCa. In particular, changes in the extent of core fucosylation and sialylation of PSA N-glycans in PCa patients compared to healthy controls or BPH patients have been reported. The objective of this study was to determine these specific glycan structures in serum PSA to analyze their potential value as markers for discriminating between BPH and PCa of different aggressiveness. In the present work, we have established two methodologies to analyze the core fucosylation and the sialic acid linkage of PSA N-glycans in serum samples from BPH (29) and PCa (44) patients with different degrees of aggressiveness. We detected a significant decrease in the core fucose and an increase in the α2,3-sialic acid percentage of PSA in high-risk PCa that differentiated BPH and low-risk PCa from high-risk PCa patients. In particular, a cut-off value of 0.86 of the PSA core fucose ratio, could distinguish high-risk PCa patients from BPH with 90% sensitivity and 95% specificity, with an AUC of 0.94. In the case of the α2,3-sialic acid percentage of PSA, the cut-off value of 30% discriminated between high-risk PCa and the group of BPH, low-, and intermediate-risk PCa with a sensitivity and specificity of 85.7% and 95.5%, respectively, with an AUC of 0.97. The latter marker exhibited high performance in differentiating between aggressive and non-aggressive PCa and has the potential for translational application in the clinic. PMID:27279911

An In Vitro Spectroscopic Analysis to Determine Whether para-Chloroaniline is Produced from Mixing Sodium Hypochlorite and Chlorhexidine

PubMed Central

Thomas, John E.; Sem, Daniel S.

2009-01-01

Introduction The purpose of this in vitro study was to determine whether para-chloroaniline (PCA) is formed through the reaction of mixing sodium hypochlorite (NaOCl) and chlorhexidine (CHX). Methods Initially commercially available samples of chlorhexidine acetate (CHXa) and PCA were analyzed with 1H NMR spectroscopy. Two solutions, NaOCl and CHXa, were warmed to 37°C and when mixed they produced a brown precipitate. This precipitate was separated in half and pure PCA was added to one of the samples for comparison before they were each analyzed with 1H NMR spectroscopy. Results The peaks in the 1H NMR spectra of CHXa and PCA were assigned to specific protons of the molecules, and the location of the aromatic peaks in the PCA spectrum defined the PCA doublet region. While the spectrum of the precipitate alone resulted in a complex combination of peaks, upon magnification there were no peaks in the PCA doublet region which were intense enough to be quantified. In the spectrum of the precipitate, to which PCA was added, two peaks do appear in the PCA doublet region. Comparing this spectrum to that of precipitate alone, the peaks in the PCA doublet region are not visible prior to the addition of PCA. Conclusions Based on this in vitro study, the reaction mixture of NaOCl and CHXa does not produce PCA at any measurable quantity and further investigation is needed to determine the chemical composition of the brown precipitate. PMID:20113799

A Late Pleistocene sea level stack

NASA Astrophysics Data System (ADS)

Spratt, Rachel M.; Lisiecki, Lorraine E.

2016-04-01

Late Pleistocene sea level has been reconstructed from ocean sediment core data using a wide variety of proxies and models. However, the accuracy of individual reconstructions is limited by measurement error, local variations in salinity and temperature, and assumptions particular to each technique. Here we present a sea level stack (average) which increases the signal-to-noise ratio of individual reconstructions. Specifically, we perform principal component analysis (PCA) on seven records from 0 to 430 ka and five records from 0 to 798 ka. The first principal component, which we use as the stack, describes ˜ 80 % of the variance in the data and is similar using either five or seven records. After scaling the stack based on Holocene and Last Glacial Maximum (LGM) sea level estimates, the stack agrees to within 5 m with isostatically adjusted coral sea level estimates for Marine Isotope Stages 5e and 11 (125 and 400 ka, respectively). Bootstrapping and random sampling yield mean uncertainty estimates of 9-12 m (1σ) for the scaled stack. Sea level change accounts for about 45 % of the total orbital-band variance in benthic δ18O, compared to a 65 % contribution during the LGM-to-Holocene transition. Additionally, the second and third principal components of our analyses reflect differences between proxy records associated with spatial variations in the δ18O of seawater.

Comparative evaluation of urinary PCA3 and TMPRSS2: ERG scores and serum PHI in predicting prostate cancer aggressiveness.

PubMed

Tallon, Lucile; Luangphakdy, Devillier; Ruffion, Alain; Colombel, Marc; Devonec, Marian; Champetier, Denis; Paparel, Philippe; Decaussin-Petrucci, Myriam; Perrin, Paul; Vlaeminck-Guillem, Virginie

2014-07-30

It has been suggested that urinary PCA3 and TMPRSS2:ERG fusion tests and serum PHI correlate to cancer aggressiveness-related pathological criteria at prostatectomy. To evaluate and compare their ability in predicting prostate cancer aggressiveness, PHI and urinary PCA3 and TMPRSS2:ERG (T2) scores were assessed in 154 patients who underwent radical prostatectomy for biopsy-proven prostate cancer. Univariate and multivariate analyses using logistic regression and decision curve analyses were performed. All three markers were predictors of a tumor volume≥0.5 mL. Only PHI predicted Gleason score≥7. T2 score and PHI were both independent predictors of extracapsular extension(≥pT3), while multifocality was only predicted by PCA3 score. Moreover, when compared to a base model (age, digital rectal examination, serum PSA, and Gleason sum at biopsy), the addition of both PCA3 score and PHI to the base model induced a significant increase (+12%) when predicting tumor volume>0.5 mL. PHI and urinary PCA3 and T2 scores can be considered as complementary predictors of cancer aggressiveness at prostatectomy.

An analytical approach based on ESI-MS, LC-MS and PCA for the quali-quantitative analysis of cycloartane derivatives in Astragalus spp.

PubMed

Napolitano, Assunta; Akay, Seref; Mari, Angela; Bedir, Erdal; Pizza, Cosimo; Piacente, Sonia

2013-11-01

Astragalus species are widely used as health foods and dietary supplements, as well as drugs in traditional medicine. To rapidly evaluate metabolite similarities and differences among the EtOH extracts of the roots of eight commercial Astragalus spp., an approach based on direct analyses by ESI-MS followed by PCA of ESI-MS data, was carried out. Successively, quali-quantitative analyses of cycloartane derivatives in the eight Astragalus spp. by LC-ESI-MS(n) and PCA of LC-ESI-MS data were performed. This approach allowed to promptly highlighting metabolite similarities and differences among the various Astragalus spp. PCA results from LC-ESI-MS data of Astragalus samples were in reasonable agreement with both PCA results of ESI-MS data and quantitative results. This study affords an analytical method for the quali-quantitative determination of cycloartane derivatives in herbal preparations used as health and food supplements. Copyright © 2013 Elsevier B.V. All rights reserved.

Molecular Imaging and Therapy of Prostate Cancer

DTIC Science & Technology

2015-10-01

arsenic-based, IGF1R-targeted radiopharmaceuticals can allow for PET imaging, IRT, and monitoring the therapeutic response of PCa. Specific Aims: Aim 1: To...models with PET imaging. Aim 3: To monitor the efficacy of 76As-based IRT of PCa with multimodality imaging.

Biparametric MRI of the prostate.

PubMed

Scialpi, Michele; D'Andrea, Alfredo; Martorana, Eugenio; Malaspina, Corrado Maria; Aisa, Maria Cristina; Napoletano, Maria; Orlandi, Emanuele; Rondoni, Valeria; Scialpi, Pietro; Pacchiarini, Diamante; Palladino, Diego; Dragone, Michele; Di Renzo, Giancarlo; Simeone, Annalisa; Bianchi, Giampaolo; Brunese, Luca

2017-12-01

Biparametric Magnetic Resonance Imaging (bpMRI) of the prostate combining both morphologic T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) is emerging as an alternative to multiparametric MRI (mpMRI) to detect, to localize and to guide prostatic targeted biopsy in patients with suspicious prostate cancer (PCa). BpMRI overcomes some limitations of mpMRI such as the costs, the time required to perform the study, the use of gadolinium-based contrast agents and the lack of a guidance for management of score 3 lesions equivocal for significant PCa. In our experience the optimal and similar clinical results of the bpMRI in comparison to mpMRI are essentially related to the DWI that we consider the dominant sequence for detection suspicious PCa both in transition and in peripheral zone. In clinical practice, the adoption of bpMRI standardized scoring system, indicating the likelihood to diagnose a clinically significant PCa and establishing the management of each suspicious category (from 1 to 4), could represent the rationale to simplify and to improve the current interpretation of mpMRI based on Prostate Imaging and Reporting Archiving Data System version 2 (PI-RADS v2). In this review article we report and describe the current knowledge about bpMRI in the detection of suspicious PCa and a simplified PI-RADS based on bpMRI for management of each suspicious PCa categories to facilitate the communication between radiologists and urologists.

Biparametric MRI of the prostate

PubMed Central

Scialpi, Michele; D’Andrea, Alfredo; Martorana, Eugenio; Malaspina, Corrado Maria; Aisa, Maria Cristina; Napoletano, Maria; Orlandi, Emanuele; Rondoni, Valeria; Scialpi, Pietro; Pacchiarini, Diamante; Palladino, Diego; Dragone, Michele; Di Renzo, Giancarlo; Simeone, Annalisa; Bianchi, Giampaolo; Brunese, Luca

2017-01-01

Biparametric Magnetic Resonance Imaging (bpMRI) of the prostate combining both morphologic T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) is emerging as an alternative to multiparametric MRI (mpMRI) to detect, to localize and to guide prostatic targeted biopsy in patients with suspicious prostate cancer (PCa). BpMRI overcomes some limitations of mpMRI such as the costs, the time required to perform the study, the use of gadolinium-based contrast agents and the lack of a guidance for management of score 3 lesions equivocal for significant PCa. In our experience the optimal and similar clinical results of the bpMRI in comparison to mpMRI are essentially related to the DWI that we consider the dominant sequence for detection suspicious PCa both in transition and in peripheral zone. In clinical practice, the adoption of bpMRI standardized scoring system, indicating the likelihood to diagnose a clinically significant PCa and establishing the management of each suspicious category (from 1 to 4), could represent the rationale to simplify and to improve the current interpretation of mpMRI based on Prostate Imaging and Reporting Archiving Data System version 2 (PI-RADS v2). In this review article we report and describe the current knowledge about bpMRI in the detection of suspicious PCa and a simplified PI-RADS based on bpMRI for management of each suspicious PCa categories to facilitate the communication between radiologists and urologists. PMID:29201499

Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model.

PubMed

Lin, Yuxin; Chen, Feifei; Shen, Li; Tang, Xiaoyu; Du, Cui; Sun, Zhandong; Ding, Huijie; Chen, Jiajia; Shen, Bairong

2018-05-21

Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to be biomarkers for disease prediction. In addition, computer-aided biomarker discovery is now becoming an attractive paradigm for precision diagnosis and prognosis of complex diseases. In this study, we identified key microRNAs as biomarkers for predicting PCa metastasis based on network vulnerability analysis. We first extracted microRNAs and mRNAs that were differentially expressed between primary PCa and metastatic PCa (MPCa) samples. Then we constructed the MPCa-specific microRNA-mRNA network and screened microRNA biomarkers by a novel bioinformatics model. The model emphasized the characterization of systems stability changes and the network vulnerability with three measurements, i.e. the structurally single-line regulation, the functional importance of microRNA targets and the percentage of transcription factor genes in microRNA unique targets. With this model, we identified five microRNAs as putative biomarkers for PCa metastasis. Among them, miR-101-3p and miR-145-5p have been previously reported as biomarkers for PCa metastasis and the remaining three, i.e. miR-204-5p, miR-198 and miR-152, were screened as novel biomarkers for PCa metastasis. The results were further confirmed by the assessment of their predictive power and biological function analysis. Five microRNAs were identified as candidate biomarkers for predicting PCa metastasis based on our network vulnerability analysis model. The prediction performance, literature exploration and functional enrichment analysis convinced our findings. This novel bioinformatics model could be applied to biomarker discovery for other complex diseases.

Differentiation of neuropsychological features between posterior cortical atrophy and early onset Alzheimer's disease.

PubMed

Li, Jieying; Wu, Liyong; Tang, Yi; Zhou, Aihong; Wang, Fen; Xing, Yi; Jia, Jianping

2018-05-10

Posterior cortical atrophy (PCA) is a group of clinical syndromes characterized by visuospatial and visuoperceptual impairment, with memory relatively preserved. Although PCA is pathologically almost identical to Alzheimer's disease (AD), they have different cognitive features. Those differences have only rarely been reported in any Chinese population. The purpose of the study is to establish neuropsychological tests that distinguish the clinical features of PCA from early onset AD (EOAD). Twenty-one PCA patients, 20 EOAD patients, and 20 healthy controls participated in this study. Patients had disease duration of ≤4 years. All participants completed a series of neuropsychological tests to evaluate their visuospatial, visuoperceptual, visuo-constructive, language, executive function, memory, calculation, writing, and reading abilities. The cognitive features of PCA and EOAD were compared. All the neuropsychological test scores showed that both the PCA and EOAD patients were significantly more impaired than people in the control group. However, PCA patients were significantly more impaired than EOAD patients in visuospatial, visuoperceptual, and visuo-constructive function, as well as in handwriting, and reading Chinese characters. The profile of neuropsychological test results highlights cognitive features that differ between PCA and EOAD. One surprising result is that the two syndromes could be distinguished by patients' ability to read and write Chinese characters. Tests based on these characteristics could therefore form a brief PCA neuropsychological examination that would improve the diagnosis of PCA.

Performance assessment of automated tissue characterization for prostate H and E stained histopathology

NASA Astrophysics Data System (ADS)

DiFranco, Matthew D.; Reynolds, Hayley M.; Mitchell, Catherine; Williams, Scott; Allan, Prue; Haworth, Annette

2015-03-01

Reliable automated prostate tumor detection and characterization in whole-mount histology images is sought in many applications, including post-resection tumor staging and as ground-truth data for multi-parametric MRI interpretation. In this study, an ensemble-based supervised classification algorithm for high-resolution histology images was trained on tile-based image features including histogram and gray-level co-occurrence statistics. The algorithm was assessed using different combinations of H and E prostate slides from two separate medical centers and at two different magnifications (400x and 200x), with the aim of applying tumor classification models to new data. Slides from both datasets were annotated by expert pathologists in order to identify homogeneous cancerous and non-cancerous tissue regions of interest, which were then categorized as (1) low-grade tumor (LG-PCa), including Gleason 3 and high-grade prostatic intraepithelial neoplasia (HG-PIN), (2) high-grade tumor (HG-PCa), including various Gleason 4 and 5 patterns, or (3) non-cancerous, including benign stroma and benign prostatic hyperplasia (BPH). Classification models for both LG-PCa and HG-PCa were separately trained using a support vector machine (SVM) approach, and per-tile tumor prediction maps were generated from the resulting ensembles. Results showed high sensitivity for predicting HG-PCa with an AUC up to 0.822 using training data from both medical centres, while LG-PCa showed a lower sensitivity of 0.763 with the same training data. Visual inspection of cancer probability heatmaps from 9 patients showed that 17/19 tumors were detected, and HG-PCa generally reported less false positives than LG-PCa.

Prostatitis, other genitourinary infections and prostate cancer: results from a population-based case-control study.

PubMed

Boehm, Katharina; Valdivieso, Roger; Meskawi, Malek; Larcher, Alessandro; Schiffmann, Jonas; Sun, Maxine; Graefen, Markus; Saad, Fred; Parent, Marie-Élise; Karakiewicz, Pierre I

2016-03-01

We relied on a population-based case-control study (PROtEuS) to examine a potential association between the presence of histologically confirmed prostate cancer (PCa) and history of genitourinary infections, e.g., prostatitis, urethritis, orchitis and epididymitis. Cases were 1933 men with incident PCa, diagnosed across Montreal hospitals between 2005 and 2009. Population controls were 1994 men from the same residential area and age distribution. In-person interviews collected information about socio-demographic characteristics, lifestyle and medical history, e.g., self-reported history of several genitourinary infections, as well as on PCa screening. Logistic regression analyses tested overall and grade-specific associations, including subgroup analyses with frequent PSA testing. After multivariable adjustment, prostatitis was associated with an increased risk of any PCa (OR 1.81 [1.44-2.27]), but not urethritis (OR 1.05 [0.84-1.30]), orchitis (OR 1.28 [0.92-1.78]) or epididymitis (OR 0.98 [0.57-1.68]). The association between prostatitis and PCa was more pronounced for low-grade PCa (Gleason ≤ 6: OR 2.11 [1.61-2.77]; Gleason ≥ 7: OR 1.59 [1.22-2.07]). Adjusting for frequency of physician visits, PSA testing frequency or restricting analyses to frequently screened subjects did not affect these results. Prostatitis was associated with an increased probability for detecting PCa even after adjustment for frequency of PSA testing and physician visits, but not urethritis, orchitis or epididymitis. These considerations may be helpful in clinical risk stratification of individuals in whom the risk of PCa is pertinent.

Posterior cortical atrophy: an investigation of scan paths generated during face matching tasks

PubMed Central

Meek, Benjamin P.; Locheed, Keri; Lawrence-Dewar, Jane M.; Shelton, Paul; Marotta, Jonathan J.

2013-01-01

When viewing a face, healthy individuals focus more on the area containing the eyes and upper nose in order to retrieve important featural and configural information. In contrast, individuals with face blindness (prosopagnosia) tend to direct fixations toward individual facial features—particularly the mouth. Presented here is an examination of face perception deficits in individuals with Posterior Cortical Atrophy (PCA). PCA is a rare progressive neurodegenerative disorder that is characterized by atrophy in occipito-parietal and occipito-temporal cortices. PCA primarily affects higher visual processing, while memory, reasoning, and insight remain relatively intact. A common symptom of PCA is a decreased effective field of vision caused by the inability to “see the whole picture.” Individuals with PCA and healthy control participants completed a same/different discrimination task in which images of faces were presented as cue-target pairs. Eye-tracking equipment and a novel computer-based perceptual task—the Viewing Window paradigm—were used to investigate scan patterns when faces were presented in open view or through a restricted-view, respectively. In contrast to previous prosopagnosia research, individuals with PCA each produced unique scan paths that focused on non-diagnostically useful locations. This focus on non-diagnostically useful locations was also present when using a restricted viewing aperture, suggesting that individuals with PCA have difficulty processing the face at either the featural or configural level. In fact, it appears that the decreased effective field of view in PCA patients is so severe that it results in an extreme dependence on local processing, such that a feature-based approach is not even possible. PMID:23825453

The Present and Future of Prostate Cancer Urine Biomarkers

PubMed Central

Rigau, Marina; Olivan, Mireia; Garcia, Marta; Sequeiros, Tamara; Montes, Melania; Colás, Eva; Llauradó, Marta; Planas, Jacques; de Torres, Inés; Morote, Juan; Cooper, Colin; Reventós, Jaume; Clark, Jeremy; Doll, Andreas

2013-01-01

In order to successfully cure patients with prostate cancer (PCa), it is important to detect the disease at an early stage. The existing clinical biomarkers for PCa are not ideal, since they cannot specifically differentiate between those patients who should be treated immediately and those who should avoid over-treatment. Current screening techniques lack specificity, and a decisive diagnosis of PCa is based on prostate biopsy. Although PCa screening is widely utilized nowadays, two thirds of the biopsies performed are still unnecessary. Thus the discovery of non-invasive PCa biomarkers remains urgent. In recent years, the utilization of urine has emerged as an attractive option for the non-invasive detection of PCa. Moreover, a great improvement in high-throughput “omic” techniques has presented considerable opportunities for the identification of new biomarkers. Herein, we will review the most significant urine biomarkers described in recent years, as well as some future prospects in that field. PMID:23774836

Genome-wide copy number analysis reveals candidate gene loci that confer susceptibility to high-grade prostate cancer.

PubMed

Poniah, Prevathe; Mohd Zain, Shamsul; Abdul Razack, Azad Hassan; Kuppusamy, Shanggar; Karuppayah, Shankar; Sian Eng, Hooi; Mohamed, Zahurin

2017-09-01

Two key issues in prostate cancer (PCa) that demand attention currently are the need for a more precise and minimally invasive screening test owing to the inaccuracy of prostate-specific antigen and differential diagnosis to distinguish advanced vs. indolent cancers. This continues to pose a tremendous challenge in diagnosis and prognosis of PCa and could potentially lead to overdiagnosis and overtreatment complications. Copy number variations (CNVs) in the human genome have been linked to various carcinomas including PCa. Detection of these variants may improve clinical treatment as well as an understanding of the pathobiology underlying this complex disease. To this end, we undertook a pilot genome-wide CNV analysis approach in 36 subjects (18 patients with high-grade PCa and 18 controls that were matched by age and ethnicity) in search of more accurate biomarkers that could potentially explain susceptibility toward high-grade PCa. We conducted this study using the array comparative genomic hybridization technique. Array results were validated in 92 independent samples (46 high-grade PCa, 23 benign prostatic hyperplasia, and 23 healthy controls) using polymerase chain reaction-based copy number counting method. A total of 314 CNV regions were found to be unique to PCa subjects in this cohort (P<0.05). A log 2 ratio-based copy number analysis revealed 5 putative rare or novel CNV loci or both associated with susceptibility to PCa. The CNV gain regions were 1q21.3, 15q15, 7p12.1, and a novel CNV in PCa 12q23.1, harboring ARNT, THBS1, SLC5A8, and DDC genes that are crucial in the p53 and cancer pathways. A CNV loss and deletion event was observed at 8p11.21, which contains the SFRP1 gene from the Wnt signaling pathway. Cross-comparison analysis with genes associated to PCa revealed significant CNVs involved in biological processes that elicit cancer pathogenesis via cytokine production and endothelial cell proliferation. In conclusion, we postulated that the CNVs identified in this study could provide an insight into the development of advanced PCa. Copyright © 2017 Elsevier Inc. All rights reserved.

Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) Significantly Improve Prostate Cancer Detection at Initial Biopsy in a Total PSA Range of 2–10 ng/ml

PubMed Central

Perdonà, Sisto; Marino, Ada; Mazzarella, Claudia; Perruolo, Giuseppe; D’Esposito, Vittoria; Cosimato, Vincenzo; Buonerba, Carlo; Di Lorenzo, Giuseppe; Musi, Gennaro; De Cobelli, Ottavio; Chun, Felix K.; Terracciano, Daniela

2013-01-01

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2–10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2–10 ng/ml at initial biopsy, outperforming currently used %fPSA. PMID:23861782

Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) significantly improve prostate cancer detection at initial biopsy in a total PSA range of 2-10 ng/ml.

PubMed

Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Marino, Ada; Mazzarella, Claudia; Perruolo, Giuseppe; D'Esposito, Vittoria; Cosimato, Vincenzo; Buonerba, Carlo; Di Lorenzo, Giuseppe; Musi, Gennaro; De Cobelli, Ottavio; Chun, Felix K; Terracciano, Daniela

2013-01-01

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2-10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2-10 ng/ml at initial biopsy, outperforming currently used %fPSA.

Isolation of candidate genes for apomictic development in buffelgrass (Pennisetum ciliare).

PubMed

Singh, Manjit; Burson, Byron L; Finlayson, Scott A

2007-08-01

Asexual reproduction through seeds, or apomixis, is a process that holds much promise for agricultural advances. However, the molecular mechanisms underlying apomixis are currently poorly understood. To identify genes related to female gametophyte development in apomictic ovaries of buffelgrass (Pennisetum ciliare (L.) Link), Suppression Subtractive Hybridization of ovary cDNA with leaf cDNA was performed. Through macroarray screening of subtracted cDNAs two genes were identified, Pca21 and Pca24, that showed differential expression between apomictic and sexual ovaries. Sequence analysis showed that both Pca21 and Pca24 are novel genes not previously characterized in plants. Pca21 shows homology to two wheat genes that are also expressed during reproductive development. Pca24 has similarity to coiled-coil-helix-coiled-coil-helix (CHCH) domain containing proteins from maize and sugarcane. Northern blot analysis revealed that both of these genes are expressed throughout female gametophyte development in apomictic ovaries. In situ hybridizations localized the transcript of these two genes to the developing embryo sacs in the apomictic ovaries. Based on the expression patterns it was concluded that Pca21 and Pca24 likely play a role during apomictic development in buffelgrass.

Motor features in posterior cortical atrophy and their imaging correlates.

PubMed

Ryan, Natalie S; Shakespeare, Timothy J; Lehmann, Manja; Keihaninejad, Shiva; Nicholas, Jennifer M; Leung, Kelvin K; Fox, Nick C; Crutch, Sebastian J

2014-12-01

Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by impaired higher visual processing skills; however, motor features more commonly associated with corticobasal syndrome may also occur. We investigated the frequency and clinical characteristics of motor features in 44 PCA patients and, with 30 controls, conducted voxel-based morphometry, cortical thickness, and subcortical volumetric analyses of their magnetic resonance imaging. Prominent limb rigidity was used to define a PCA-motor subgroup. A total of 30% (13) had PCA-motor; all demonstrating asymmetrical left upper limb rigidity. Limb apraxia was more frequent and asymmetrical in PCA-motor, as was myoclonus. Tremor and alien limb phenomena only occurred in this subgroup. The subgroups did not differ in neuropsychological test performance or apolipoprotein E4 allele frequency. Greater asymmetry of atrophy occurred in PCA-motor, particularly involving right frontoparietal and peri-rolandic cortices, putamen, and thalamus. The 9 patients (including 4 PCA-motor) with pathology or cerebrospinal fluid all showed evidence of Alzheimer's disease. Our data suggest that PCA patients with motor features have greater atrophy of contralateral sensorimotor areas but are still likely to have underlying Alzheimer's disease. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States

USGS Publications Warehouse

Mousavi, S. Mostafa; Beroza, Gregory C.; Hoover, Susan M.

2018-01-01

Probabilistic seismic hazard analysis (PSHA) characterizes ground-motion hazard from earthquakes. Typically, the time horizon of a PSHA forecast is long, but in response to induced seismicity related to hydrocarbon development, the USGS developed one-year PSHA models. In this paper, we present a display of the variability in USGS hazard curves due to epistemic uncertainty in its informed submodel using a simple bootstrapping approach. We find that variability is highest in low-seismicity areas. On the other hand, areas of high seismic hazard, such as the New Madrid seismic zone or Oklahoma, exhibit relatively lower variability simply because of more available data and a better understanding of the seismicity. Comparing areas of high hazard, New Madrid, which has a history of large naturally occurring earthquakes, has lower forecast variability than Oklahoma, where the hazard is driven mainly by suspected induced earthquakes since 2009. Overall, the mean hazard obtained from bootstrapping is close to the published model, and variability increased in the 2017 one-year model relative to the 2016 model. Comparing the relative variations caused by individual logic-tree branches, we find that the highest hazard variation (as measured by the 95% confidence interval of bootstrapping samples) in the final model is associated with different ground-motion models and maximum magnitudes used in the logic tree, while the variability due to the smoothing distance is minimal. It should be pointed out that this study is not looking at the uncertainty in the hazard in general, but only as it is represented in the USGS one-year models.

A Positive Family History as risk factor for Prostate Cancer in a Population-based Study with organized PSA-Screening: Results of the Swiss ERSPC (Aarau)

PubMed Central

Randazzo, Marco; Müller, Alexander; Carlsson, Sigrid; Eberli, Daniel; Huber, Andreas; Grobholz, Rainer; Manka, Lukas; Mortezavi, Ashkan; Sulser, Tullio; Recker, Franz; Kwiatkowski, Maciej

2016-01-01

Objective To assess the value of positive family history (FH) as a risk factor for prostate cancer (PCa) incidence and grade among men undergoing organized PSA-screening in a population-based study. Patients and Methods The study cohort comprised all attendees of the Swiss arm of the European Randomized Study of Screening for Prostate Cancer (ERSPC) with systematic PSA-tests every 4 years. Men reporting first-degree relative(s) diagnosed with PCa were considered to have a positive FH. Biopsy was exclusively PSA-triggered with a threshold of 3 ng/ml. Primary endpoint was PCa diagnosis. Kaplan-Meier and Cox regression analyses were used. Results Of 4,932 attendees with a median age of 60.9 (IQR 57.6–65.1) years, 334 (6.8%) reported a positive FH. Median follow-up duration was 11.6 years (IQR 10.3–13.3). Cumulative PCa incidence was 60/334 (18%, positive FH) and 550/4,598 (12%, negative FH) (OR 1.6, 95% CI 1.2–2.2, p=0.001), respectively. In both groups, most PCa diagnosed had a low grade. There were no significant differences in PSA at diagnosis, biopsy Gleason score or Gleason score on pathologic specimen among men who underwent radical prostatectomy between both groups, respectively. On multivariable analysis, age (HR 1.04, 95% CI 1.02–1.06), baseline PSA (HR 1.13 95% CI 1.12–1.14), and FH (HR 1.6, CI 1.24–2.14) were independent predictors for overall PCa incidence (p<0.0001 each). Only baseline PSA (HR 1.14, 95% CI 1.12–1.16, p<0.0001) was an independent predictor of Gleason score ≥7 PCa on prostate biopsy. The proportion of interval PCa diagnosed in between the screening rounds was non-significantly different. Conclusion Irrespective of the FH status, the current PSA-based screening setting detects the majority of aggressive PCa and missed only a minority of interval cancers with a 4-year screening algorithm. Our results suggest that men with a positive FH are at increased risk for low grade but not aggressive PCa. PMID:26332304

European Randomized Study of Screening for Prostate Cancer Risk Calculator: External Validation, Variability, and Clinical Significance.

PubMed

Gómez-Gómez, Enrique; Carrasco-Valiente, Julia; Blanca-Pedregosa, Ana; Barco-Sánchez, Beatriz; Fernandez-Rueda, Jose Luis; Molina-Abril, Helena; Valero-Rosa, Jose; Font-Ugalde, Pilar; Requena-Tapia, Maria José

2017-04-01

To externally validate the European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator (RC) and to evaluate its variability between 2 consecutive prostate-specific antigen (PSA) values. We prospectively catalogued 1021 consecutive patients before prostate biopsy for suspicion of prostate cancer (PCa). The risk of PCa and significant PCa (Gleason score ≥7) from 749 patients was calculated according to ERSPC-RC (digital rectal examination-based version 3 of 4) for 2 consecutive PSA tests per patient. The calculators' predictions were analyzed using calibration plots and the area under the receiver operating characteristic curve (area under the curve). Cohen kappa coefficient was used to compare the ability and variability. Of 749 patients, PCa was detected in 251 (33.5%) and significant PCa was detected in 133 (17.8%). Calibration plots showed an acceptable parallelism and similar discrimination ability for both PSA levels with an area under the curve of 0.69 for PCa and 0.74 for significant PCa. The ERSPC showed 226 (30.2%) unnecessary biopsies with the loss of 10 significant PCa. The variability of the RC was 16% for PCa and 20% for significant PCa, and a higher variability was associated with a reduced risk of significant PCa. We can conclude that the performance of the ERSPC-RC in the present cohort shows a high similitude between the 2 PSA levels; however, the RC variability value is associated with a decreased risk of significant PCa. The use of the ERSPC in our cohort detects a high number of unnecessary biopsies. Thus, the incorporation of ERSPC-RC could help the clinical decision to carry out a prostate biopsy. Copyright © 2016 Elsevier Inc. All rights reserved.

Using Stochastic Approximation Techniques to Efficiently Construct Confidence Intervals for Heritability.

PubMed

Schweiger, Regev; Fisher, Eyal; Rahmani, Elior; Shenhav, Liat; Rosset, Saharon; Halperin, Eran

2018-06-22

Estimation of heritability is an important task in genetics. The use of linear mixed models (LMMs) to determine narrow-sense single-nucleotide polymorphism (SNP)-heritability and related quantities has received much recent attention, due of its ability to account for variants with small effect sizes. Typically, heritability estimation under LMMs uses the restricted maximum likelihood (REML) approach. The common way to report the uncertainty in REML estimation uses standard errors (SEs), which rely on asymptotic properties. However, these assumptions are often violated because of the bounded parameter space, statistical dependencies, and limited sample size, leading to biased estimates and inflated or deflated confidence intervals (CIs). In addition, for larger data sets (e.g., tens of thousands of individuals), the construction of SEs itself may require considerable time, as it requires expensive matrix inversions and multiplications. Here, we present FIESTA (Fast confidence IntErvals using STochastic Approximation), a method for constructing accurate CIs. FIESTA is based on parametric bootstrap sampling, and, therefore, avoids unjustified assumptions on the distribution of the heritability estimator. FIESTA uses stochastic approximation techniques, which accelerate the construction of CIs by several orders of magnitude, compared with previous approaches as well as to the analytical approximation used by SEs. FIESTA builds accurate CIs rapidly, for example, requiring only several seconds for data sets of tens of thousands of individuals, making FIESTA a very fast solution to the problem of building accurate CIs for heritability for all data set sizes.

Evaluation of urinary prostate cancer antigen-3 (PCA3) and TMPRSS2-ERG score changes when starting androgen-deprivation therapy with triptorelin 6-month formulation in patients with locally advanced and metastatic prostate cancer.

PubMed

Martínez-Piñeiro, Luis; Schalken, Jack A; Cabri, Patrick; Maisonobe, Pascal; de la Taille, Alexandre

2014-10-01

To assess prostate cancer antigen-3 (PCA3) and TMPRSS2-ERG scores in patients with advanced and metastatic prostate cancer at baseline and after 6 months of treatment with triptorelin 22.5 mg, and analyse these scores in patient-groups defined by different disease characteristics. The Triptocare study was a prospective, open-label, multicentre, single-arm, Phase III study of triptorelin 22.5 mg in men with locally advanced or metastatic prostate cancer, who were naïve to androgen-deprivation therapy (ADT). The primary objective was to model the urinary PCA3 change at 6 months, according to baseline variables. Other outcome measures included urinary PCA3 and TMPRSS2-ERG scores and statuses, and serum testosterone and prostate-specific antigen (PSA) levels at baseline and at 1, 3 and 6 months after initiation of ADT. Safety was assessed by recording adverse events and changes in laboratory parameters. The intent-to-treat population comprised 322 patients; 39 (12.1%) had non-assessable PCA3 scores at baseline, and 109/322 (33.9%), 215/313 (68.7%) and 232/298 (77.9%) had non-assessable PCA3 scores at 1, 3 and 6 months, respectively. Baseline Gleason score was the only variable associated with non-assessability of PCA3 score at 6 months (P = 0.017) - the hazard of having a non-assessable PCA3 score at 6 months was 1.824-fold higher (95% confidence interval 1.186-2.805) in patients with a Gleason score ≥8 vs those with a Gleason score ≤6. The median PCA3 scores at baseline were significantly higher in patients aged ≥65 years vs those aged <65 years and in patients with a serum PSA level <100 ng/mL vs those with serum PSA level of >200 ng/mL. The median PCA3 score was significantly lower in patients with metastasis than in patients with no metastasis or unknown metastasis status. TMPRSS2-ERG scores ≥35 were considered positive (n = 149 [51.6%]). Age, presence of metastasis, PSA level and Gleason score at baseline were not associated with a significant difference in the proportion of TMPRSS2-ERG-positive scores. The median serum PSA levels decreased from 45.5 ng/mL at baseline to 1.2 ng/mL after 6 months, and as expected, >90% of patients achieved castrate levels of testosterone (<50 ng/dL) at 1, 3, and 6 months during triptorelin treatment. The safety profile reported from this study is consistent with the known safety profile of triptorelin. These data from the Triptocare study suggest that urinary PCA3 or TMPRSS2-ERG score are not reliable markers of cancer stage in advanced prostate cancer. Urinary PCA3 and TMPRSS2-ERG scores do not appear to be useful in assessing response to ADT in advanced prostate cancer, with most patients having non-assessable scores after 6 months of treatment. © 2013 The Authors. BJU International © 2013 BJU International.

The Association Between Calcium Channel Blocker Use and Prostate Cancer Outcome

PubMed Central

Poch, Michael A.; Mehedint, Diana; Green, Dawn J.; Payne-Ondracek, Rochelle; Fontham, Elizabeth T.H.; Bensen, Jeannette T.; Attwood, Kristopher; Wilding, Gregory E.; Guru, Khurshid A.; Underwood, Willie; Mohler, James L.; Heemers, Hannelore V.

2018-01-01

BACKGROUND Epidemiological studies indicate that calcium channel blocker (CCB) use is inversely related to prostate cancer (PCa) incidence. The association between CCB use and PCa aggressiveness at the time of radical prostatectomy (RP) and outcome after RP was examined. METHODS Medication use, PCa aggressiveness and post-RP outcome were retrieved from a prospectively populated database that contains clinical and outcome for RP patients at Roswell Park Cancer Institute (RPCI) from 1993 to 2010. The database was queried for anti-hypertensive medication use at diagnosis for patients with ≥1 year follow-up. Recurrence was defined using NCCN guidelines. Chi-Square tests assessed the relationship between CCB use and PCa aggressiveness. Cox regression models compared the distribution of progression-free survival (PFS) and overall survival (OS) with adjustment for covariates. Results for association between CCB usage and PCa aggressiveness were validated using data from the population-based North Carolina-Louisiana Prostate Cancer Project (PCaP). RESULTS 48%, 37%, and 15% of RPCI’s RP patients (n = 875) had low, intermediate, and high aggressive PCa, respectively. 104 (11%) had a history of CCB use. Patients taking CCBs were more likely to be older, have a higher BMI and use additional anti-hypertensive medications. Diagnostic PSA levels, PCa aggressiveness, and margin status were similar for CCB users and non-users. PFS and OS did not differ between the two groups. Tumor aggressiveness was associated with PFS. CCB use in the PCaP study population was not associated with PCa aggressiveness. CONCLUSIONS CCB use is not associated with PCa aggressiveness at diagnosis, PFS or OS. PMID:23280547

Epithelial-to-mesenchymal transition leads to disease-stage differences in circulating tumor cell detection and metastasis in pre-clinical models of prostate cancer.

PubMed

Lowes, Lori E; Goodale, David; Xia, Ying; Postenka, Carl; Piaseczny, Matthew M; Paczkowski, Freeman; Allan, Alison L

2016-11-15

Metastasis is the cause of most prostate cancer (PCa) deaths and has been associated with circulating tumor cells (CTCs). The presence of ≥5 CTCs/7.5mL of blood is a poor prognosis indicator in metastatic PCa when assessed by the CellSearch® system, the "gold standard" clinical platform. However, ~35% of metastatic PCa patients assessed by CellSearch® have undetectable CTCs. We hypothesize that this is due to epithelial-to-mesenchymal transition (EMT) and subsequent loss of necessary CTC detection markers, with important implications for PCa metastasis. Two pre-clinical assays were developed to assess human CTCs in xenograft models; one comparable to CellSearch® (EpCAM-based) and one detecting CTCs semi-independent of EMT status via combined staining with EpCAM/HLA (human leukocyte antigen). In vivo differences in CTC generation, kinetics, metastasis and EMT status were determined using 4 PCa models with progressive epithelial (LNCaP, LNCaP-C42B) to mesenchymal (PC-3, PC-3M) phenotypes. Assay validation demonstrated that the CellSearch®-based assay failed to detect a significant number (~40-50%) of mesenchymal CTCs. In vivo, PCa with an increasingly mesenchymal phenotype shed greater numbers of CTCs more quickly and with greater metastatic capacity than PCa with an epithelial phenotype. Notably, the CellSearch®-based assay captured the majority of CTCs shed during early-stage disease in vivo, and only after establishment of metastases were a significant number of undetectable CTCs present. This study provides important insight into the influence of EMT on CTC generation and subsequent metastasis, and highlights that novel technologies aimed at capturing mesenchymal CTCs may only be useful in the setting of advanced metastatic disease.

On a PCA-based lung motion model

PubMed Central

Li, Ruijiang; Lewis, John H; Jia, Xun; Zhao, Tianyu; Liu, Weifeng; Wuenschel, Sara; Lamb, James; Yang, Deshan; Low, Daniel A; Jiang, Steve B

2014-01-01

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772–81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921–9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1 mm (0.7 ± 0.1 mm). When a single artificial internal marker was used to derive the lung motion, the average 3D error was found to be within 2 mm (1.8 ± 0.3 mm) through comprehensive statistical analysis. The optimal number of PCA coefficients needs to be determined on a patient-by-patient basis and two PCA coefficients seem to be sufficient for accurate modeling of the lung motion for most patients. In conclusion, we have presented thorough theoretical analysis and clinical validation of the PCA lung motion model. The feasibility of deriving the entire lung motion using a single marker has also been demonstrated on clinical data using a simulation approach. PMID:21865624

Copula based prediction models: an application to an aortic regurgitation study

PubMed Central

Kumar, Pranesh; Shoukri, Mohamed M

2007-01-01

Background: An important issue in prediction modeling of multivariate data is the measure of dependence structure. The use of Pearson's correlation as a dependence measure has several pitfalls and hence application of regression prediction models based on this correlation may not be an appropriate methodology. As an alternative, a copula based methodology for prediction modeling and an algorithm to simulate data are proposed. Methods: The method consists of introducing copulas as an alternative to the correlation coefficient commonly used as a measure of dependence. An algorithm based on the marginal distributions of random variables is applied to construct the Archimedean copulas. Monte Carlo simulations are carried out to replicate datasets, estimate prediction model parameters and validate them using Lin's concordance measure. Results: We have carried out a correlation-based regression analysis on data from 20 patients aged 17–82 years on pre-operative and post-operative ejection fractions after surgery and estimated the prediction model: Post-operative ejection fraction = - 0.0658 + 0.8403 (Pre-operative ejection fraction); p = 0.0008; 95% confidence interval of the slope coefficient (0.3998, 1.2808). From the exploratory data analysis, it is noted that both the pre-operative and post-operative ejection fractions measurements have slight departures from symmetry and are skewed to the left. It is also noted that the measurements tend to be widely spread and have shorter tails compared to normal distribution. Therefore predictions made from the correlation-based model corresponding to the pre-operative ejection fraction measurements in the lower range may not be accurate. Further it is found that the best approximated marginal distributions of pre-operative and post-operative ejection fractions (using q-q plots) are gamma distributions. The copula based prediction model is estimated as: Post -operative ejection fraction = - 0.0933 + 0.8907 × (Pre-operative ejection fraction); p = 0.00008 ; 95% confidence interval for slope coefficient (0.4810, 1.3003). For both models differences in the predicted post-operative ejection fractions in the lower range of pre-operative ejection measurements are considerably different and prediction errors due to copula model are smaller. To validate the copula methodology we have re-sampled with replacement fifty independent bootstrap samples and have estimated concordance statistics 0.7722 (p = 0.0224) for the copula model and 0.7237 (p = 0.0604) for the correlation model. The predicted and observed measurements are concordant for both models. The estimates of accuracy components are 0.9233 and 0.8654 for copula and correlation models respectively. Conclusion: Copula-based prediction modeling is demonstrated to be an appropriate alternative to the conventional correlation-based prediction modeling since the correlation-based prediction models are not appropriate to model the dependence in populations with asymmetrical tails. Proposed copula-based prediction model has been validated using the independent bootstrap samples. PMID:17573974

A comparison of bootstrap methods and an adjusted bootstrap approach for estimating the prediction error in microarray classification.

PubMed

Jiang, Wenyu; Simon, Richard

2007-12-20

This paper first provides a critical review on some existing methods for estimating the prediction error in classifying microarray data where the number of genes greatly exceeds the number of specimens. Special attention is given to the bootstrap-related methods. When the sample size n is small, we find that all the reviewed methods suffer from either substantial bias or variability. We introduce a repeated leave-one-out bootstrap (RLOOB) method that predicts for each specimen in the sample using bootstrap learning sets of size ln. We then propose an adjusted bootstrap (ABS) method that fits a learning curve to the RLOOB estimates calculated with different bootstrap learning set sizes. The ABS method is robust across the situations we investigate and provides a slightly conservative estimate for the prediction error. Even with small samples, it does not suffer from large upward bias as the leave-one-out bootstrap and the 0.632+ bootstrap, and it does not suffer from large variability as the leave-one-out cross-validation in microarray applications. Copyright (c) 2007 John Wiley & Sons, Ltd.

The monoamine oxidase A gene promoter repeat and prostate cancer risk.

PubMed

White, Thomas A; Kwon, Erika M; Fu, Rong; Lucas, Jared M; Ostrander, Elaine A; Stanford, Janet L; Nelson, Peter S

2012-11-01

Amine catabolism by monoamine oxidase A (MAOA) contributes to oxidative stress, which plays a role in prostate cancer (PCa) development and progression. An upstream variable-number tandem repeat (uVNTR) in the MAOA promoter influences gene expression and activity, and may thereby affect PCa susceptibility. Caucasian (n = 2,572) men from two population-based case-control studies of PCa were genotyped for the MAOA-VNTR. Logistic regression was used to assess PCa risk in relation to genotype. Common alleles of the MAOA-VNTR were not associated with the relative risk of PCa, nor did the relationship differ by clinical features of the disease. The rare 5-copy variant (frequency: 0.5% in cases; 1.8% in controls), however, was associated with a reduced PCa risk (odds ratio, OR = 0.30, 95% CI 0.13-0.71). A rare polymorphism of the MAOA promoter previously shown to confer low expression was associated with a reduced risk of developing PCa. This novel finding awaits confirmation in other study populations. Copyright © 2012 Wiley Periodicals, Inc.

Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy.

PubMed

Rubio-Briones, Jose; Borque, Angel; Esteban, Luis M; Casanova, Juan; Fernandez-Serra, Antonio; Rubio, Luis; Casanova-Salas, Irene; Sanz, Gerardo; Domínguez-Escrig, Jose; Collado, Argimiro; Gómez-Ferrer, Alvaro; Iborra, Inmaculada; Ramírez-Backhaus, Miguel; Martínez, Francisco; Calatrava, Ana; Lopez-Guerrero, Jose A

2015-09-11

PCA3 has been included in a nomogram outperforming previous clinical models for the prediction of any prostate cancer (PCa) and high grade PCa (HGPCa) at the initial prostate biopsy (IBx). Our objective is to validate such IBx-specific PCA3-based nomogram. We also aim to optimize the use of this nomogram in clinical practice through the definition of risk groups. Independent external validation. Clinical and biopsy data from a contemporary cohort of 401 men with the same inclusion criteria to those used to build up the reference's nomogram in IBx. The predictive value of the nomogram was assessed by means of calibration curves and discrimination ability through the area under the curve (AUC). Clinical utility of the nomogram was analyzed by choosing thresholds points that minimize the overlapping between probability density functions (PDF) in PCa and no PCa and HGPCa and no HGPCa groups, and net benefit was assessed by decision curves. We detect 28% of PCa and 11 % of HGPCa in IBx, contrasting to the 46 and 20% at the reference series. Due to this, there is an overestimation of the nomogram probabilities shown in the calibration curve for PCa. The AUC values are 0.736 for PCa (C.I.95%:0.68-0.79) and 0.786 for HGPCa (C.I.95%:0.71-0.87) showing an adequate discrimination ability. PDF show differences in the distributions of nomogram probabilities in PCa and not PCa patient groups. A minimization of the overlapping between these curves confirms the threshold probability of harboring PCa >30 % proposed by Hansen is useful to indicate a IBx, but a cut-off > 40% could be better in series of opportunistic screening like ours. Similar results appear in HGPCa analysis. The decision curve also shows a net benefit of 6.31% for the threshold probability of 40%. PCA3 is an useful tool to select patients for IBx. Patients with a calculated probability of having PCa over 40% should be counseled to undergo an IBx if opportunistic screening is required.

A Neighborhood-Based Intervention to Reduce Prostate Cancer Disparities

DTIC Science & Technology

2017-10-01

for men from the neighborhoods. We also began recruitment and sessions to test the PCa educational intervention. Results: Focus group participants had...making about PCa screening Sub-aim 4: To observe the rates of PCa screening in the intervention and control groups 2. Keywords Prostate Cancer...mobilization of community health workers from high risk neighborhoods. Recruitment and conduct of “ control ” group educational sessions. Establishment of

Comparative Study of Blood-Based Biomarkers, α2,3-Sialic Acid PSA and PHI, for High-Risk Prostate Cancer Detection.

PubMed

Ferrer-Batallé, Montserrat; Llop, Esther; Ramírez, Manel; Aleixandre, Rosa Núria; Saez, Marc; Comet, Josep; de Llorens, Rafael; Peracaula, Rosa

2017-04-17

Prostate Specific Antigen (PSA) is the most commonly used serum marker for prostate cancer (PCa), although it is not specific and sensitive enough to allow the differential diagnosis of the more aggressive tumors. For that, new diagnostic methods are being developed, such as PCA-3, PSA isoforms that have resulted in the 4K score or the Prostate Health Index (PHI), and PSA glycoforms. In the present study, we have compared the PHI with our recently developed PSA glycoform assay, based on the determination of the α2,3-sialic acid percentage of serum PSA (% α2,3-SA), in a cohort of 79 patients, which include 50 PCa of different grades and 29 benign prostate hyperplasia (BPH) patients. The % α2,3-SA could distinguish high-risk PCa patients from the rest of patients better than the PHI (area under the curve (AUC) of 0.971 vs. 0.840), although the PHI correlated better with the Gleason score than the % α2,3-SA. The combination of both markers increased the AUC up to 0.985 resulting in 100% sensitivity and 94.7% specificity to differentiate high-risk PCa from the other low and intermediate-risk PCa and BPH patients. These results suggest that both serum markers complement each other and offer an improved diagnostic tool to identify high-risk PCa, which is an important requirement for guiding treatment decisions.

IMPROVED SEARCH OF PRINCIPAL COMPONENT ANALYSIS DATABASES FOR SPECTRO-POLARIMETRIC INVERSION

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

Casini, R.; Lites, B. W.; Ramos, A. Asensio

2013-08-20

We describe a simple technique for the acceleration of spectro-polarimetric inversions based on principal component analysis (PCA) of Stokes profiles. This technique involves the indexing of the database models based on the sign of the projections (PCA coefficients) of the first few relevant orders of principal components of the four Stokes parameters. In this way, each model in the database can be attributed a distinctive binary number of 2{sup 4n} bits, where n is the number of PCA orders used for the indexing. Each of these binary numbers (indices) identifies a group of ''compatible'' models for the inversion of amore » given set of observed Stokes profiles sharing the same index. The complete set of the binary numbers so constructed evidently determines a partition of the database. The search of the database for the PCA inversion of spectro-polarimetric data can profit greatly from this indexing. In practical cases it becomes possible to approach the ideal acceleration factor of 2{sup 4n} as compared to the systematic search of a non-indexed database for a traditional PCA inversion. This indexing method relies on the existence of a physical meaning in the sign of the PCA coefficients of a model. For this reason, the presence of model ambiguities and of spectro-polarimetric noise in the observations limits in practice the number n of relevant PCA orders that can be used for the indexing.« less

Biological Evaluation and Molecular Docking of Protocatechuic Acid from Hibiscus sabdariffa L. as a Potent Urease Inhibitor by an ESI-MS Based Method.

PubMed

Hassan, Sherif T S; Švajdlenka, Emil

2017-10-11

Studies on enzyme inhibition remain a crucial area in drug discovery since these studies have led to the discoveries of new lead compounds useful in the treatment of several diseases. In this study, protocatechuic acid (PCA), an active compound from Hibiscus sabdariffa L. has been evaluated for its inhibitory properties against jack bean urease (JBU) as well as its possible toxic effect on human gastric epithelial cells (GES-1). Anti-urease activity was evaluated by an Electrospray Ionization-Mass Spectrometry (ESI-MS) based method, while cytotoxicity was assayed by the MTT method. PCA exerted notable anti-JBU activity compared with that of acetohydroxamic acid (AHA), with IC 50 values of 1.7 and 3.2 µM, respectively. PCA did not show any significant cytotoxic effect on (GES-1) cells at concentrations ranging from 1.12 to 3.12 µM. Molecular docking study revealed high spontaneous binding ability of PCA to the active site of urease. Additionally, the anti-urease activity was found to be related to the presence of hydroxyl moieties of PCA. This study presents PCA as a natural urease inhibitor, which could be used safely in the treatment of diseases caused by urease-producing bacteria.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap.

PubMed

Zhou, Hanzhi; Elliott, Michael R; Raghunathan, Trivellore E

2016-06-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in "Delta-V," a key crash severity measure.

Risk of cutaneous adverse events with febuxostat treatment in patients with skin reaction to allopurinol. A retrospective, hospital-based study of 101 patients with consecutive allopurinol and febuxostat treatment.

PubMed

Bardin, Thomas; Chalès, Gérard; Pascart, Tristan; Flipo, René-Marc; Korng Ea, Hang; Roujeau, Jean-Claude; Delayen, Aurélie; Clerson, Pierre

2016-05-01

To investigate the cutaneous tolerance of febuxostat in gouty patients with skin intolerance to allopurinol. We identified all gouty patients who had sequentially received allopurinol and febuxostat in the rheumatology departments of 4 university hospitals in France and collected data from hospital files using a predefined protocol. Patients who had not visited the prescribing physician during at least 2 months after febuxostat prescription were excluded. The odds ratio (OR) for skin reaction to febuxostat in patients with a cutaneous reaction to allopurinol versus no reaction was calculated. For estimating the 95% confidence interval (95% CI), we used the usual Wald method and a bootstrap method. In total, 113 gouty patients had sequentially received allopurinol and febuxostat; 12 did not visit the prescribing physician after febuxostat prescription and were excluded. Among 101 patients (86 males, mean age 61±13.9 years), 2/22 (9.1%) with a history of cutaneous reactions to allopurinol showed skin reactions to febuxostat. Two of 79 patients (2.5%) without a skin reaction to allopurinol showed skin intolerance to febuxostat. The ORs were not statistically significant with the usual Wald method (3.85 [95% CI 0.51-29.04]) or bootstrap method (3.86 [95% CI 0.80-18.74]). The risk of skin reaction with febuxostat seems moderately increased in patients with a history of cutaneous adverse events with allopurinol. This moderate increase does not support the cross-reactivity of the two drugs. Copyright © 2015. Published by Elsevier SAS.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap

PubMed Central

Zhou, Hanzhi; Elliott, Michael R.; Raghunathan, Trivellore E.

2017-01-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in “Delta-V,” a key crash severity measure. PMID:29226161

Efficiency determinants and capacity issues in Brazilian for-profit hospitals.

PubMed

Araújo, Cláudia; Barros, Carlos P; Wanke, Peter

2014-06-01

This paper reports on the use of different approaches for assessing efficiency of a sample of major Brazilian for-profit hospitals. Starting out with the bootstrapping technique, several DEA estimates were generated, allowing the use of confidence intervals and bias correction in central estimates to test for significant differences in efficiency levels and input-decreasing/output-increasing potentials. The findings indicate that efficiency is mixed in Brazilian for-profit hospitals. Opportunities for accommodating future demand appear to be scarce and strongly dependent on particular conditions related to the accreditation and specialization of a given hospital.

Novel antiproliferative flavonoids induce cell cycle arrest in human prostate cancer cell lines.

PubMed

Haddad, A Q; Venkateswaran, V; Viswanathan, L; Teahan, S J; Fleshner, N E; Klotz, L H

2006-01-01

Epidemiologic studies have demonstrated an inverse association between flavonoid intake and prostate cancer (PCa) risk. The East Asian diet is very high in flavonoids and, correspondingly, men in China and Japan have the lowest incidence of PCa worldwide. There are thousands of different naturally occurring and synthetic flavonoids. However, only a few have been studied in PCa. Our aim was to identify novel flavonoids with antiproliferative effect in PCa cell lines, as well as determine their effects on cell cycle. We have screened a representative subgroup of 26 flavonoids for antiproliferative effect on the human PCa (LNCaP and PC3), breast cancer (MCF-7), and normal prostate stromal cell lines (PrSC). Using a fluorescence-based cell proliferation assay (Cyquant), we have identified five flavonoids, including the novel compounds 2,2'-dihydroxychalcone and fisetin, with antiproliferative and cell cycle arresting properties in human PCa in vitro. Most of the flavonoids tested exerted antiproliferative effect at lower doses in the PCa cell lines compared to the non-PCa cells. Flow cytometry was used as a means to determine the effects on cell cycle. PC3 cells were arrested in G2/M phase by flavonoids. LNCaP cells demonstrated different cell cycle profiles. Further studies are warranted to determine the molecular mechanism of action of 2,2'-DHC and fisetin in PCa, and to establish their effectiveness in vivo.

Small molecule screening reveals a transcription-independent pro-survival function of androgen receptor in castration-resistant prostate cancer

PubMed Central

Narizhneva, Natalia V.; Tararova, Natalia D.; Ryabokon, Petro; Shyshynova, Inna; Prokvolit, Anatoly; Komarov, Pavel G.; Purmal, Andrei A.; Gudkov, Andrei V.; Gurova, Katerina V.

2010-01-01

In prostate cancer (PCa) patients, initial responsiveness to androgen deprivation therapy is frequently followed by relapse due to development of treatment-resistant androgen-independent PCa. This is typically associated with acquisition of mutations in AR that allow activity as a transcription factor in the absence of ligand, indicating that androgen-independent PCa remains dependent on AR function. Our strategy to effectively target AR in androgen-independent PCa involved using a cell-based readout to isolate small molecules that inhibit AR transactivation function through mechanisms other than modulation of ligand binding. A number of the identified inhibitors were toxic to AR-expressing PCa cells regardless of their androgen dependence. Among these, some only suppressed PCa cell growth (ARTIS), while others induced cell death (ARTIK). ARTIK, but not ARTIS, compounds caused disappearance of AR protein from treated cells. siRNA against AR behaved like ARTIK compounds, while a dominant negative AR mutant that prevents AR-mediated transactivation but does not eliminate the protein showed only a growth suppressive effect. These observations reveal a transcription-independent function of AR that is essential for PCa cell viability and, therefore, is an ideal target for anti-PCa treatment. Indeed, several of the identified AR inhibitors demonstrated in vivo efficacy in mouse models of PCa and are candidates for pharmacologic optimization. PMID:19946220

Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution.

PubMed

Mukhopadhyay, Nitai D; Sampson, Andrew J; Deniz, Daniel; Alm Carlsson, Gudrun; Williamson, Jeffrey; Malusek, Alexandr

2012-01-01

Correlated sampling Monte Carlo methods can shorten computing times in brachytherapy treatment planning. Monte Carlo efficiency is typically estimated via efficiency gain, defined as the reduction in computing time by correlated sampling relative to conventional Monte Carlo methods when equal statistical uncertainties have been achieved. The determination of the efficiency gain uncertainty arising from random effects, however, is not a straightforward task specially when the error distribution is non-normal. The purpose of this study is to evaluate the applicability of the F distribution and standardized uncertainty propagation methods (widely used in metrology to estimate uncertainty of physical measurements) for predicting confidence intervals about efficiency gain estimates derived from single Monte Carlo runs using fixed-collision correlated sampling in a simplified brachytherapy geometry. A bootstrap based algorithm was used to simulate the probability distribution of the efficiency gain estimates and the shortest 95% confidence interval was estimated from this distribution. It was found that the corresponding relative uncertainty was as large as 37% for this particular problem. The uncertainty propagation framework predicted confidence intervals reasonably well; however its main disadvantage was that uncertainties of input quantities had to be calculated in a separate run via a Monte Carlo method. The F distribution noticeably underestimated the confidence interval. These discrepancies were influenced by several photons with large statistical weights which made extremely large contributions to the scored absorbed dose difference. The mechanism of acquiring high statistical weights in the fixed-collision correlated sampling method was explained and a mitigation strategy was proposed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Real World Evidence: A Quantitative and Qualitative Glance at Participant Feedback from a Free-Response Survey Investigating Experiences of a Structured Exercise Intervention for Men with Prostate Cancer.

PubMed

Fox, L; Cahill, F; Burgess, C; Peat, N; Rudman, S; Kinsella, J; Cahill, D; George, G; Santaolalla, A; Van Hemelrijck, M

2017-01-01

To explore patient experiences of a structured exercise intervention for men with prostate cancer (PCa). 41 men with either localised or advanced PCa who had been referred for a structured exercise programme by their physician and then subsequently consented to a telephone survey. Participants underwent a 10-week supervised exercise programme within a large cancer centre hospital consisting of 8 sessions. They then completed a short multiple choice telephone survey, elaborating on their responses where appropriate. Views expressed by participants were analysed using an affinity diagram and common themes were identified. Feedback from our telephone surveys was consistently positive and suggests that the structured exercise intervention provides exercise confidence, motivation to exercise, and social support and promotes positive health behaviour change in the context of exercise. Individual differences arose amongst participants in their perceived utility of the intervention, with 73.3% expressing a preference for structured exercise classes and 19.5% expressing a preference for exercising independently. Design of a structured exercise intervention for patients with PCa should embrace the positive aspects outlined here but consider patients' individual differences. Ongoing feedback from patients should be utilised alongside traditional study designs to inform intervention design in this area.

A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

PubMed

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network

PubMed Central

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J.

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483

Expression of SLCO transport genes in castration resistant prostate cancer and impact of genetic variation in SCLO1B3 and SLCO2B1 on prostate cancer outcomes

PubMed Central

Wright, Jonathan L; Kwon, Erika M; Ostrander, Elaine A; Montgomery, R Bruce; Lin, Daniel W; Vessella, Robert; Stanford, Janet L; Mostaghel, Elahe A

2011-01-01

Background Metastases from men with castration resistant prostate cancer (CRPC) harbor increased tumoral androgens vs. untreated prostate cancers (PCa). This may reflect steroid uptake by OATP/SLCO transporters. We evaluated SLCO gene expression in CRPC metastases and determined whether PCa outcomes are associated with single nucleotide polymorphisms (SNPs) in SLCO2B1 and SLCO1B3, transporters previously demonstrated to mediate androgen uptake. Methods Transcripts encoding 11 SLCO genes were analyzed in untreated PCa, and in metastatic CRPC tumors obtained by rapid autopsy. SNPs in SLCO2B1 and SLCO1B3 were genotyped in a population-based cohort of 1,309 Caucasian PCa patients. Median survival follow-up was 7.0 years (0.77–16.4). The risk of PCa recurrence/progression and PCa-specific mortality (PCSM) was estimated with Cox proportional hazards analysis. Results Six SLCO genes were highly expressed in CRPC metastases vs. untreated PCa, including SLCO1B3 (3.6 fold, p=0.0517) and SLCO2B1 (5.5 fold, p=0.0034). Carriers of the variant alleles SLCO2B1 SNP rs12422149 (HR 1.99, 95% CI 1.11 – 3.55) or SLCO1B3 SNP rs4149117 (HR 1.76, 95% CI 1.00 – 3.08) had an increased risk of PCSM. Conclusions CRPC metastases demonstrate increased expression of SLCO genes vs. primary PCa. Genetic variants of SLCO1B3 and SLCO2B1 are associated with PCSM. Expression and genetic variation of SLCO genes which alter androgen uptake may be important in PCa outcomes. Impact OATP/SLCO genes may be potential biomarkers for assessing risk of prostate cancer-specific mortality. Expression and genetic variation in these genes may allow stratification of patients to more aggressive hormonal therapy or earlier incorporation of non-hormonal based treatment strategies. PMID:21266523

Estimation of αL, velocity, Kd and confidence limits from tracer injection test data

USGS Publications Warehouse

Broermann, James; Bassett, R.L.; Weeks, Edwin P.; Borgstrom, Mark

1997-01-01

Bromide and boron were used as tracers during an injection experiment conducted at an artificial recharge facility near Stanton, Texas. The Ogallala aquifer at the Stanton site represents a heterogeneous alluvial environment and provides the opportunity to report scale dependent dispersivities at observation distances of 2 to 15 m in this setting. Values of longitudinal dispersivities are compared with other published values. Water samples were collected at selected depths both from piezometers and from fully screened observation wells at radii of 2, 5, 10 and 15 m. An exact analytical solution is used to simulate the concentration breakthrough curves and estimate longitudinal dispersivities and velocity parameters. Greater confidence can be placed on these data because the estimated parameters are error bounded using the bootstrap method. The non-conservative behavior of boron transport in clay rich sections of the aquifer were quantified with distribution coefficients by using bromide as a conservative reference tracer.

Estimation of αL, velocity, Kd, and confidence limits from tracer injection data

USGS Publications Warehouse

Broermann, James; Bassett, R.L.; Weeks, Edwin P.; Borgstrom, Mark

1997-01-01

Bromide and boron were used as tracers during an injection experiment conducted at an artificial recharge facility near Stanton, Texas. The Ogallala aquifer at the Stanton site represents a heterogeneous alluvial environment and provides the opportunity to report scale dependent dispersivities at observation distances of 2 to 15 m in this setting. Values of longitudinal dispersivities are compared with other published values. Water samples were collected at selected depths both from piezometers and from fully screened observation wells at radii of 2, 5, 10 and 15 m. An exact analytical solution is used to simulate the concentration breakthrough curves and estimate longitudinal dispersivities and velocity parameters. Greater confidence can be placed on these data because the estimated parameters are error bounded using the bootstrap method. The non-conservative behavior of boron transport in clay rich sections of the aquifer were quantified with distribution coefficients by using bromide as a conservative reference tracer.

Polymorphisms in carcinogen metabolism enzymes, fish intake, and risk of prostate cancer

PubMed Central

Stern, Mariana C.

2012-01-01

Cooking fish at high temperature can produce potent carcinogens such as heterocyclic amines and polycyclic aromatic hydrocarbons. The effects of these carcinogens may undergo modification by the enzymes responsible for their detoxification and/or activation. In this study, we investigated genetic polymorphisms in nine carcinogen metabolism enzymes and their modifying effects on the association between white or dark fish consumption and prostate cancer (PCA) risk. We genotyped 497 localized and 936 advanced PCA cases and 760 controls from the California Collaborative Case–Control Study of Prostate Cancer. Three polymorphisms, EPHX1 Tyr113His, CYP1B1 Leu432Val and GSTT1 null/present, were associated with localized PCA risk. The PTGS2 765 G/C polymorphism modified the association between white fish consumption and advanced PCA risk (interaction P 5 0.002), with high white fish consumption being positively associated with risk only among carriers of the C allele. This effect modification by PTGS2 genotype was stronger when restricted to consumption of well-done white fish (interaction P 5 0.021). These findings support the hypotheses that changes in white fish brought upon by high-temperature cooking methods, such as carcinogen accumulation and/or fatty acid composition changes, may contribute to prostate carcinogenesis. However, the gene–diet interactions should be interpreted with caution given the limited sample size. Thus, our findings require further validation with additional studies. Abbreviations: AA African American; BMI body mass index; CI confidence interval; CNV copy number variant; EPIC European Prospective Investigation into Cancer and Nutrition; HCA heterocyclic amine; HCFA Health Care Financing Administration; LAC Los Angeles county; MAF minor allele frequency; NHW non-Hispanic White; OR odds ratio; PAH polycyclic aromatic hydrocarbon; PCA prostate cancer; PTGS2 prostaglandin- endoperoxide synthase 2; PUFA polyunsaturated fatty acids; RDD random-digit dialing; SEER Surveillance, Epidemiology, and End Result; SES socio-economic status; SFBA San Francisco Bay Area; SNP single-nucleotide polymorphism PMID:22610071

Why and Where do We Miss Significant Prostate Cancer with Multi-parametric Magnetic Resonance Imaging followed by Magnetic Resonance-guided and Transrectal Ultrasound-guided Biopsy in Biopsy-naïve Men?

PubMed

Schouten, Martijn G; van der Leest, Marloes; Pokorny, Morgan; Hoogenboom, Martijn; Barentsz, Jelle O; Thompson, Les C; Fütterer, Jurgen J

2017-06-01

Knowledge of significant prostate (sPCa) locations being missed with magnetic resonance (MR)- and transrectal ultrasound (TRUS)-guided biopsy (Bx) may help to improve these techniques. To identify the location of sPCa lesions being missed with MR- and TRUS-Bx. In a referral center, 223 consecutive Bx-naive men with elevated prostate specific antigen level and/or abnormal digital rectal examination were included. Histopathologically-proven cancer locations, Gleason score, and tumor length were determined. All patients underwent multi-parametric MRI and 12-core systematic TRUS-Bx. MR-Bx was performed in all patients with suspicion of PCa on multi-parametric MRI (n=142). Cancer locations were compared between MR- and TRUS-Bx. Proportions were expressed as percentages, and the corresponding 95% confidence intervals were calculated. In total, 191 lesions were found in 108 patients with sPCa. From these lesion 74% (141/191) were defined as sPCa on either MR- or TRUS-Bx. MR-Bx detected 74% (105/141) of these lesions and 61% (86/141) with TRUS-Bx. TRUS-Bx detected more lesions compared with MR-Bx (140 vs 109). However, these lesions were often low risk (39%). Significant lesions missed with MR-Bx most often had involvement of dorsolateral (58%) and apical (37%) segments and missed segments with TRUS-Bx were located anteriorly (79%), anterior midprostate (50%), and anterior apex (23%). Both techniques have difficulties in detecting apical lesions. MR-Bx most often missed cancer with involvement of the dorsolateral part (58%) and TRUS-Bx with involvement of the anterior part (79%). Both biopsy techniques miss cancer in specific locations within the prostate. Identification of these lesions may help to improve these techniques. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Increased resource use in men with metastatic prostate cancer does not result in improved survival or quality of care at the end of life.

PubMed

Golan, Ron; Bernstein, Adrien N; Gu, Xiangmei; Dinerman, Brian F; Sedrakyan, Art; Hu, Jim C

2018-05-15

Cancer care and end-of-life (EOL) care contribute substantially to health care expenditures. Outside of clinical trials, to our knowledge there exists no standardized protocol to monitor disease progression in men with metastatic prostate cancer (mPCa). The objective of the current study was to evaluate the factors and outcomes associated with increased imaging and serum prostate-specific antigen use in men with mPCa. Using Surveillance, Epidemiology, and End Results-Medicare data from 2004 to 2012, the authors identified men diagnosed with mPCa with at least 6 months of follow-up. Extreme users were classified as those who had either received prostate-specific antigen testing greater than once per month, or who underwent cross-sectional imaging or bone scan more frequently than every 2 months over a 6-month period. Associations between extreme use and survival outcomes, costs, and quality of care at EOL, as measured by timing of hospice referral, frequency of emergency department visits, length of stay, and intensive care unit or hospital admissions, were examined. Overall, a total of 3026 men with mPCa were identified, 791 of whom (26%) were defined as extreme users. Extreme users were more commonly young, white/non-Hispanic, married, higher earning, and more educated (P<.001, respectively). Extreme use was not associated with improved quality of care at EOL. Yearly health care costs after diagnosis were 36.4% higher among extreme users (95% confidence interval, 27.4%-45.3%; P<.001). Increased monitoring among men with mPCa significantly increases health care costs, without a definitive improvement in survival nor quality of care at EOL noted. Monitoring for disease progression outside of clinical trials should be reserved for those in whom findings will change management. Cancer 2018;124:2212-9. © 2018 American Cancer Society. © 2018 American Cancer Society.

AMACR polymorphisms, dietary intake of red meat and dairy and prostate cancer risk.

PubMed

Wright, Jonathan L; Neuhouser, Marian L; Lin, Daniel W; Kwon, Erika M; Feng, Ziding; Ostrander, Elaine A; Stanford, Janet L

2011-04-01

Alpha-methylacyl CoA racemase (AMACR) is an enzyme involved in fatty acids metabolism. One of AMACRs primary substrates, phytanic acid, is principally obtained from dietary red meat/dairy, which are associated with prostate cancer (PCa) risk. AMACR is also a tumor tissue biomarker over-expressed in PCa. In this study, we explored the potential relationship between AMACR polymorphisms, red meat/dairy intake, and PCa risk. Caucasian participants from two population-based PCa case-control studies were included. AMACR single nucleotide polymorphisms (SNPs) were selected to capture variation across the gene and regulatory regions. Red meat and dairy intake was determined from food frequency questionnaires. The odds ratio (OR) of PCa (overall and by disease aggressiveness) was estimated by logistic and polytomous regression. Potential interactions between genotypes and dietary exposures were evaluated. Data from 1,309 cases and 1,267 controls were analyzed. Carriers of the variant T allele (rs2287939) had an OR of 0.81 (95% CI 0.68-0.97) for less aggressive PCa, but no alteration in risk for more aggressive PCa. Red meat consumption was positively associated with PCa risk, and the association was stronger for more aggressive disease (lowest vs. highest tertile OR=1.55, 95% CI 1.10-2.20). No effect modification of AMACR polymorphisms by either dietary red meat or dairy intake on PCa risk was observed. PCa risk varied by level of red meat intake and by one AMACR SNP, but there was no evidence for gene-environment interaction. These findings suggest that the effects of AMACR polymorphisms and red meat and dairy on PCa risk are independent. Copyright © 2010 Wiley-Liss, Inc.

Optimal prophylactic and definitive therapy for bicalutamide-induced gynecomastia: results of a meta-analysis

PubMed Central

Tunio, M.A.; Al-Asiri, M.; Al-Amro, A.; Bayoumi, Y.; Fareed, M.

2012-01-01

Objective Bicalutamide is approved as an adjuvant to primary treatments (radical prostatectomy or radiotherapy) or as monotherapy in men with locally advanced, nonmetastatic prostate cancer (pca). However, this treatment induces gynecomastia in most patients, which often results in treatment discontinuation. Optimal therapy for these breast events is not known so far. We undertook a meta-analysis to assess the efficacy of various treatment options for bicalutamide-induced gynecomastia. Methods The medline, cancerlit, and Cochrane library databases were searched and the Google search engine was used to identify prospective and retrospective controlled studies published in English from January 2000 to December 2010 comparing prophylactic or curative treatment options with a control group (no treatment) for pca patients who developed bicalutamide-induced gynecomastia. Radiotherapy-induced cardiotoxicity was also evaluated. Results The search identified nine controlled trials with a total patient population of 1573. Pooled results from prophylactic trials showed a significant reduction of gynecomastia in pca patients treated with prophylactic tamoxifen 20 mg daily (odds ratio: 0.06; 95% confidence interval: 0.05 to 0.09; p = 0.09), and pooled results from treatment trials showed a significant response of gynecomastia to definitive radiotherapy (odds ratio: 0.06; 95% confidence interval: 0.01 to 0.24; p < 0.0001). Aromatase inhibitors and weekly tamoxifen were not found to be effective as prophylactic and curative options. For the radiotherapy, skin-to-heart distance was found to be an important risk factor for cardiotoxicity (p = 0.006). A funnel plot of the meta-analysis showed significant heterogeneity (Egger test p < 0.00001) because of low sample size. Conclusions Our meta-analysis suggests using prophylactic tamoxifen 20 mg daily as the first-line preventive measure and radiotherapy as the first-line treatment option for bicalutamide-induced gynecomastia. Aromatase inhibitors and weekly tamoxifen are not recommended. PMID:22876157

MiR-145 detection in urinary extracellular vesicles increase diagnostic efficiency of prostate cancer based on hydrostatic filtration dialysis method.

PubMed

Xu, Yong; Qin, Sihua; An, Taixue; Tang, Yueting; Huang, Yiyao; Zheng, Lei

2017-07-01

Extracellular vesicles (EVs) can be detected in body fluids and may serve as disease biomarkers. Increasing evidence suggests that circulating miRNAs in serum and urine may be potential non-invasive biomarkers for prostate cancer (PCa). In the present study, we aimed to investigate whether hydrostatic filtration dialysis (HFD) is suitable for urinary EVs (UEVs) isolation and whether such reported PCa-related miRNAs can be detected in UEVs as PCa biomarkers. To analyze EVs miRNAs, we searched for an easy and economic method to enrich EVs from urine samples. We compared the efficiency of HFD method and conventional ultracentrifugation (UC) in isolating UEVs. Subsequently, UEVs were isolated from patients with PCa, patients with benign prostate hyperplasia (BPH) and healthy individuals. Differential expression of four PCa-related miRNAs (miR-572, miR-1290, miR-141, and miR-145) were measured in UEVs and paired serum EVs using SYBR Green-based quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The overall performance of HFD was similar to UC. In miRNA yield, both HFD and UC can meet the needs of further analysis. The level of miR-145 in UEVs was significantly increased in patients with PCa compared with the patients with BPH (P = 0.018). In addition, significant increase was observed in miR-145 levels when patients with Gleason score ≥8 tumors compared with Gleason score ≤7 (P = 0.020). Receiver-operating characteristic curve (ROC) revealed that miR-145 in UEVs combined with serum PSA could differentiate PCa from BPH better than PSA alone (AUC 0.863 and AUC 0.805, respectively). In serum EVs, four miRNAs were significantly higher in patients with PCa than with BPH. HFD is appropriate for UEVs isolation and miRNA analysis when compared with conventional UC. miR-145 in UEVs is upregulated from PCa patients compared BPH patients and healthy controls. We suggest the potential use of UEVs miR-145 as a biomarker of PCa. © 2017 Wiley Periodicals, Inc.

Prostate Cancer Detection and Prognosis: From Prostate Specific Antigen (PSA) to Exosomal Biomarkers

PubMed Central

Filella, Xavier; Foj, Laura

2016-01-01

Prostate specific antigen (PSA) remains the most used biomarker in the management of early prostate cancer (PCa), in spite of the problems related to false positive results and overdiagnosis. New biomarkers have been proposed in recent years with the aim of increasing specificity and distinguishing aggressive from non-aggressive PCa. The emerging role of the prostate health index and the 4Kscore is reviewed in this article. Both are blood-based tests related to the aggressiveness of the tumor, which provide the risk of suffering PCa and avoiding negative biopsies. Furthermore, the use of urine has emerged as a non-invasive way to identify new biomarkers in recent years, including the PCA3 and TMPRSS2:ERG fusion gene. Available results about the PCA3 score showed its usefulness to decide the repetition of biopsy in patients with a previous negative result, although its relationship with the aggressiveness of the tumor is controversial. More recently, aberrant microRNA expression in PCa has been reported by different authors. Preliminary results suggest the utility of circulating and urinary microRNAs in the detection and prognosis of PCa. Although several of these new biomarkers have been recommended by different guidelines, large prospective and comparative studies are necessary to establish their value in PCa detection and prognosis. PMID:27792187

Prostate Cancer Detection and Prognosis: From Prostate Specific Antigen (PSA) to Exosomal Biomarkers.

PubMed

Filella, Xavier; Foj, Laura

2016-10-26

Prostate specific antigen (PSA) remains the most used biomarker in the management of early prostate cancer (PCa), in spite of the problems related to false positive results and overdiagnosis. New biomarkers have been proposed in recent years with the aim of increasing specificity and distinguishing aggressive from non-aggressive PCa. The emerging role of the prostate health index and the 4Kscore is reviewed in this article. Both are blood-based tests related to the aggressiveness of the tumor, which provide the risk of suffering PCa and avoiding negative biopsies. Furthermore, the use of urine has emerged as a non-invasive way to identify new biomarkers in recent years, including the PCA3 and TMPRSS2:ERG fusion gene. Available results about the PCA3 score showed its usefulness to decide the repetition of biopsy in patients with a previous negative result, although its relationship with the aggressiveness of the tumor is controversial. More recently, aberrant microRNA expression in PCa has been reported by different authors. Preliminary results suggest the utility of circulating and urinary microRNAs in the detection and prognosis of PCa. Although several of these new biomarkers have been recommended by different guidelines, large prospective and comparative studies are necessary to establish their value in PCa detection and prognosis.

Application of EOF/PCA-based methods in the post-processing of GRACE derived water variations

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen

2010-05-01

Two problems that users of monthly GRACE gravity field solutions face are 1) the presence of correlated noise in the Stokes coefficients that increases with harmonic degree and causes ‘striping', and 2) the fact that different physical signals are overlaid and difficult to separate from each other in the data. These problems are termed the signal-noise separation problem and the signal-signal separation problem. Methods that are based on principal component analysis and empirical orthogonal functions (PCA/EOF) have been frequently proposed to deal with these problems for GRACE. However, different strategies have been applied to different (spatial: global/regional, spectral: global/order-wise, geoid/equivalent water height) representations of the GRACE level 2 data products, leading to differing results and a general feeling that PCA/EOF-based methods are to be applied ‘with care'. In addition, it is known that conventional EOF/PCA methods force separated modes to be orthogonal, and that, on the other hand, to either EOFs or PCs an arbitrary orthogonal rotation can be applied. The aim of this paper is to provide a common theoretical framework and to study the application of PCA/EOF-based methods as a signal separation tool due to post-process GRACE data products. In order to investigate and illustrate the applicability of PCA/EOF-based methods, we have employed them on GRACE level 2 monthly solutions based on the Center for Space Research, University of Texas (CSR/UT) RL04 products and on the ITG-GRACE03 solutions from the University of Bonn, and on various representations of them. Our results show that EOF modes do reveal the dominating annual, semiannual and also long-periodic signals in the global water storage variations, but they also show how choosing different strategies changes the outcome and may lead to unexpected results.

2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.

PubMed

Du, Qi-Shi; Wang, Shu-Qing; Xie, Neng-Zhong; Wang, Qing-Yan; Huang, Ri-Bo; Chou, Kuo-Chen

2017-09-19

A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development.

Identification and classification of upper limb motions using PCA.

PubMed

Veer, Karan; Vig, Renu

2018-03-28

This paper describes the utility of principal component analysis (PCA) in classifying upper limb signals. PCA is a powerful tool for analyzing data of high dimension. Here, two different input strategies were explored. The first method uses upper arm dual-position-based myoelectric signal acquisition and the other solely uses PCA for classifying surface electromyogram (SEMG) signals. SEMG data from the biceps and the triceps brachii muscles and four independent muscle activities of the upper arm were measured in seven subjects (total dataset=56). The datasets used for the analysis are rotated by class-specific principal component matrices to decorrelate the measured data prior to feature extraction.

Building hospital pharmacy practice research capacity in Qatar: a cross-sectional survey of hospital pharmacists.

PubMed

Stewart, Derek; Al Hail, Moza; Abdul Rouf, P V; El Kassem, Wessam; Diack, Lesley; Thomas, Binny; Awaisu, Ahmed

2015-06-01

There is a need to systematically develop research capacity within pharmacy practice. Hamad Medical Corporation (HMC) is the principal non-profit health care provider in Qatar. Traditionally, pharmacists in Qatar have limited training related to research and lack direct experience of research processes. To determine the interests, experience and confidence of hospital pharmacists employed by HMC, Qatar in relation to research, attitudes towards research, and facilitators and barriers. Hospital pharmacy, Qatar. A cross-sectional survey of all pharmacists (n = 401). Responses were analysed using descriptive and inferential statistics, and principal component analysis (PCA). Interests, experience and confidence in research; attitudes towards research; and facilitators and barriers to participation in research. The response rate was 53.1 % (n = 213). High levels of interest were expressed for all aspects of research, with respondents less experienced and less confident. Summary scores for items of interest were significantly higher than experience and confidence (p < 0.001). PCA identified four components: general attitudes towards research; confidence, motivation and resources; research culture; and support. While respondents were generally positive in response to all items, they were less sure of resources to conduct research, access to training and statistical support. They were also generally unsure of many aspects relating to research culture. Half (50.7 %, n = 108) had either never thought about being involved in research or taken no action. In multivariate binary logistic regression analysis, the significant factors were possessing postgraduate qualifications [odds ratio (OR) 3.48 (95 % CI 1.73-6.99), p < 0.001] and having more positive general attitudes to research [OR 3.24 (95 % CI 1.62-4.67), p = 0.001]. Almost all (89.7 %, n = 172) expressed interest in being involved in research training. HMC pharmacists expressed significantly higher levels of interest in research compared to experience and confidence. While general attitudes towards research were positive, there were some barriers relating to support (e.g. administration) and research culture. Positive attitudes towards research and possessing postgraduate qualifications were significant in relation to readiness to participate in research and research training. Findings are of key relevance when considering the aims of research capacity building of encouraging research, improving skills and identifying skills gaps.

Evaluation of different approaches for identifying optimal sites to predict mean hillslope soil moisture content

NASA Astrophysics Data System (ADS)

Liao, Kaihua; Zhou, Zhiwen; Lai, Xiaoming; Zhu, Qing; Feng, Huihui

2017-04-01

The identification of representative soil moisture sampling sites is important for the validation of remotely sensed mean soil moisture in a certain area and ground-based soil moisture measurements in catchment or hillslope hydrological studies. Numerous approaches have been developed to identify optimal sites for predicting mean soil moisture. Each method has certain advantages and disadvantages, but they have rarely been evaluated and compared. In our study, surface (0-20 cm) soil moisture data from January 2013 to March 2016 (a total of 43 sampling days) were collected at 77 sampling sites on a mixed land-use (tea and bamboo) hillslope in the hilly area of Taihu Lake Basin, China. A total of 10 methods (temporal stability (TS) analyses based on 2 indices, K-means clustering based on 6 kinds of inputs and 2 random sampling strategies) were evaluated for determining optimal sampling sites for mean soil moisture estimation. They were TS analyses based on the smallest index of temporal stability (ITS, a combination of the mean relative difference and standard deviation of relative difference (SDRD)) and based on the smallest SDRD, K-means clustering based on soil properties and terrain indices (EFs), repeated soil moisture measurements (Theta), EFs plus one-time soil moisture data (EFsTheta), and the principal components derived from EFs (EFs-PCA), Theta (Theta-PCA), and EFsTheta (EFsTheta-PCA), and global and stratified random sampling strategies. Results showed that the TS based on the smallest ITS was better (RMSE = 0.023 m3 m-3) than that based on the smallest SDRD (RMSE = 0.034 m3 m-3). The K-means clustering based on EFsTheta (-PCA) was better (RMSE <0.020 m3 m-3) than these based on EFs (-PCA) and Theta (-PCA). The sampling design stratified by the land use was more efficient than the global random method. Forty and 60 sampling sites are needed for stratified sampling and global sampling respectively to make their performances comparable to the best K-means method (EFsTheta-PCA). Overall, TS required only one site, but its accuracy was limited. The best K-means method required <8 sites and yielded high accuracy, but extra soil and terrain information is necessary when using this method. The stratified sampling strategy can only be used if no pre-knowledge about soil moisture variation is available. This information will help in selecting the optimal methods for estimation the area mean soil moisture.

Feature Extraction of Event-Related Potentials Using Wavelets: An Application to Human Performance Monitoring

NASA Technical Reports Server (NTRS)

Trejo, Leonard J.; Shensa, Mark J.; Remington, Roger W. (Technical Monitor)

1998-01-01

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many f ree parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation,-, algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance.

Feature extraction of event-related potentials using wavelets: an application to human performance monitoring

NASA Technical Reports Server (NTRS)

Trejo, L. J.; Shensa, M. J.

1999-01-01

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many free parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance. Copyright 1999 Academic Press.

Investigation of probabilistic principal component analysis compared to proper orthogonal decomposition methods for basis extraction and missing data estimation

NASA Astrophysics Data System (ADS)

Lee, Kyunghoon

To evaluate the maximum likelihood estimates (MLEs) of probabilistic principal component analysis (PPCA) parameters such as a factor-loading, PPCA can invoke an expectation-maximization (EM) algorithm, yielding an EM algorithm for PPCA (EM-PCA). In order to examine the benefits of the EM-PCA for aerospace engineering applications, this thesis attempts to qualitatively and quantitatively scrutinize the EM-PCA alongside both POD and gappy POD using high-dimensional simulation data. In pursuing qualitative investigations, the theoretical relationship between POD and PPCA is transparent such that the factor-loading MLE of PPCA, evaluated by the EM-PCA, pertains to an orthogonal basis obtained by POD. By contrast, the analytical connection between gappy POD and the EM-PCA is nebulous because they distinctively approximate missing data due to their antithetical formulation perspectives: gappy POD solves a least-squares problem whereas the EM-PCA relies on the expectation of the observation probability model. To juxtapose both gappy POD and the EM-PCA, this research proposes a unifying least-squares perspective that embraces the two disparate algorithms within a generalized least-squares framework. As a result, the unifying perspective reveals that both methods address similar least-squares problems; however, their formulations contain dissimilar bases and norms. Furthermore, this research delves into the ramifications of the different bases and norms that will eventually characterize the traits of both methods. To this end, two hybrid algorithms of gappy POD and the EM-PCA are devised and compared to the original algorithms for a qualitative illustration of the different basis and norm effects. After all, a norm reflecting a curve-fitting method is found to more significantly affect estimation error reduction than a basis for two example test data sets: one is absent of data only at a single snapshot and the other misses data across all the snapshots. From a numerical performance aspect, the EM-PCA is computationally less efficient than POD for intact data since it suffers from slow convergence inherited from the EM algorithm. For incomplete data, this thesis quantitatively found that the number of data missing snapshots predetermines whether the EM-PCA or gappy POD outperforms the other because of the computational cost of a coefficient evaluation, resulting from a norm selection. For instance, gappy POD demands laborious computational effort in proportion to the number of data-missing snapshots as a consequence of the gappy norm. In contrast, the computational cost of the EM-PCA is invariant to the number of data-missing snapshots thanks to the L2 norm. In general, the higher the number of data-missing snapshots, the wider the gap between the computational cost of gappy POD and the EM-PCA. Based on the numerical experiments reported in this thesis, the following criterion is recommended regarding the selection between gappy POD and the EM-PCA for computational efficiency: gappy POD for an incomplete data set containing a few data-missing snapshots and the EM-PCA for an incomplete data set involving multiple data-missing snapshots. Last, the EM-PCA is applied to two aerospace applications in comparison to gappy POD as a proof of concept: one with an emphasis on basis extraction and the other with a focus on missing data reconstruction for a given incomplete data set with scattered missing data. The first application exploits the EM-PCA to efficiently construct reduced-order models of engine deck responses obtained by the numerical propulsion system simulation (NPSS), some of whose results are absent due to failed analyses caused by numerical instability. Model-prediction tests validate that engine performance metrics estimated by the reduced-order NPSS model exhibit considerably good agreement with those directly obtained by NPSS. Similarly, the second application illustrates that the EM-PCA is significantly more cost effective than gappy POD at repairing spurious PIV measurements obtained from acoustically-excited, bluff-body jet flow experiments. The EM-PCA reduces computational cost on factors 8 ˜ 19 compared to gappy POD while generating the same restoration results as those evaluated by gappy POD. All in all, through comprehensive theoretical and numerical investigation, this research establishes that the EM-PCA is an efficient alternative to gappy POD for an incomplete data set containing missing data over an entire data set. (Abstract shortened by UMI.)

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

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

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

Tests of Independence for Ordinal Data Using Bootstrap.

ERIC Educational Resources Information Center

Chan, Wai; Yung, Yiu-Fai; Bentler, Peter M.; Tang, Man-Lai

1998-01-01

Two bootstrap tests are proposed to test the independence hypothesis in a two-way cross table. Monte Carlo studies are used to compare the traditional asymptotic test with these bootstrap methods, and the bootstrap methods are found superior in two ways: control of Type I error and statistical power. (SLD)

Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI.

PubMed

Yang, Xin; Liu, Chaoyue; Wang, Zhiwei; Yang, Jun; Min, Hung Le; Wang, Liang; Cheng, Kwang-Ting Tim

2017-12-01

Multi-parameter magnetic resonance imaging (mp-MRI) is increasingly popular for prostate cancer (PCa) detection and diagnosis. However, interpreting mp-MRI data which typically contains multiple unregistered 3D sequences, e.g. apparent diffusion coefficient (ADC) and T2-weighted (T2w) images, is time-consuming and demands special expertise, limiting its usage for large-scale PCa screening. Therefore, solutions to computer-aided detection of PCa in mp-MRI images are highly desirable. Most recent advances in automated methods for PCa detection employ a handcrafted feature based two-stage classification flow, i.e. voxel-level classification followed by a region-level classification. This work presents an automated PCa detection system which can concurrently identify the presence of PCa in an image and localize lesions based on deep convolutional neural network (CNN) features and a single-stage SVM classifier. Specifically, the developed co-trained CNNs consist of two parallel convolutional networks for ADC and T2w images respectively. Each network is trained using images of a single modality in a weakly-supervised manner by providing a set of prostate images with image-level labels indicating only the presence of PCa without priors of lesions' locations. Discriminative visual patterns of lesions can be learned effectively from clutters of prostate and surrounding tissues. A cancer response map with each pixel indicating the likelihood to be cancerous is explicitly generated at the last convolutional layer of the network for each modality. A new back-propagated error E is defined to enforce both optimized classification results and consistent cancer response maps for different modalities, which help capture highly representative PCa-relevant features during the CNN feature learning process. The CNN features of each modality are concatenated and fed into a SVM classifier. For images which are classified to contain cancers, non-maximum suppression and adaptive thresholding are applied to the corresponding cancer response maps for PCa foci localization. Evaluation based on 160 patient data with 12-core systematic TRUS-guided prostate biopsy as the reference standard demonstrates that our system achieves a sensitivity of 0.46, 0.92 and 0.97 at 0.1, 1 and 10 false positives per normal/benign patient which is significantly superior to two state-of-the-art CNN-based methods (Oquab et al., 2015; Zhou et al., 2015) and 6-core systematic prostate biopsies. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting Postsurgical Satisfaction in Adolescents With Idiopathic Scoliosis: The Role of Presurgical Functioning and Expectations.

PubMed

Sieberg, Christine B; Manganella, Juliana; Manalo, Gem; Simons, Laura E; Hresko, M Timothy

2017-12-01

There is a need to better assess patient satisfaction and surgical outcomes. The purpose of the current study is to identify how preoperative expectations can impact postsurgical satisfaction among youth with adolescent idiopathic scoliosis undergoing spinal fusion surgery. The present study includes patients with adolescent idiopathic scoliosis undergoing spinal fusion surgery enrolled in a prospective, multicentered registry examining postsurgical outcomes. The Scoliosis Research Society Questionnaire-Version 30, which assesses pain, self-image, mental health, and satisfaction with management, along with the Spinal Appearance Questionnaire, which measures surgical expectations was administered to 190 patients before surgery and 1 and 2 years postoperatively. Regression analyses with bootstrapping (with n=5000 bootstrap samples) were conducted with 99% bias-corrected confidence intervals to examine the extent to which preoperative expectations for spinal appearance mediated the relationship between presurgical mental health and pain and 2-year postsurgical satisfaction. Results indicate that preoperative mental health, pain, and expectations are predictive of postsurgical satisfaction. With the shifting health care system, physicians may want to consider patient mental health, pain, and expectations before surgery to optimize satisfaction and ultimately improve clinical care and patient outcomes. Level I-prognostic study.

Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy

NASA Astrophysics Data System (ADS)

Traversaro, Francisco; O. Redelico, Francisco

2018-04-01

In nonlinear dynamics, and to a lesser extent in other fields, a widely used measure of complexity is the Permutation Entropy. But there is still no known method to determine the accuracy of this measure. There has been little research on the statistical properties of this quantity that characterize time series. The literature describes some resampling methods of quantities used in nonlinear dynamics - as the largest Lyapunov exponent - but these seems to fail. In this contribution, we propose a parametric bootstrap methodology using a symbolic representation of the time series to obtain the distribution of the Permutation Entropy estimator. We perform several time series simulations given by well-known stochastic processes: the 1/fα noise family, and show in each case that the proposed accuracy measure is as efficient as the one obtained by the frequentist approach of repeating the experiment. The complexity of brain electrical activity, measured by the Permutation Entropy, has been extensively used in epilepsy research for detection in dynamical changes in electroencephalogram (EEG) signal with no consideration of the variability of this complexity measure. An application of the parametric bootstrap methodology is used to compare normal and pre-ictal EEG signals.

What Is the Negative Predictive Value of Multiparametric Magnetic Resonance Imaging in Excluding Prostate Cancer at Biopsy? A Systematic Review and Meta-analysis from the European Association of Urology Prostate Cancer Guidelines Panel.

PubMed

Moldovan, Paul C; Van den Broeck, Thomas; Sylvester, Richard; Marconi, Lorenzo; Bellmunt, Joaquim; van den Bergh, Roderick C N; Bolla, Michel; Briers, Erik; Cumberbatch, Marcus G; Fossati, Nicola; Gross, Tobias; Henry, Ann M; Joniau, Steven; van der Kwast, Theo H; Matveev, Vsevolod B; van der Poel, Henk G; De Santis, Maria; Schoots, Ivo G; Wiegel, Thomas; Yuan, Cathy Yuhong; Cornford, Philip; Mottet, Nicolas; Lam, Thomas B; Rouvière, Olivier

2017-08-01

It remains unclear whether patients with a suspicion of prostate cancer (PCa) and negative multiparametric magnetic resonance imaging (mpMRI) can safely obviate prostate biopsy. To systematically review the literature assessing the negative predictive value (NPV) of mpMRI in patients with a suspicion of PCa. The Embase, Medline, and Cochrane databases were searched up to February 2016. Studies reporting prebiopsy mpMRI results using transrectal or transperineal biopsy as a reference standard were included. We further selected for meta-analysis studies with at least 10-core biopsies as the reference standard, mpMRI comprising at least T2-weighted and diffusion-weighted imaging, positive mpMRI defined as a Prostate Imaging Reporting Data System/Likert score of ≥3/5 or ≥4/5, and results reported at patient level for the detection of overall PCa or clinically significant PCa (csPCa) defined as Gleason ≥7 cancer. A total of 48 studies (9613 patients) were eligible for inclusion. At patient level, the median prevalence was 50.4% (interquartile range [IQR], 36.4-57.7%) for overall cancer and 32.9% (IQR, 28.1-37.2%) for csPCa. The median mpMRI NPV was 82.4% (IQR, 69.0-92.4%) for overall cancer and 88.1% (IQR, 85.7-92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, for overall cancer (r=-0.64, p<0.0001) and csPCa (r=-0.75, p=0.032). Eight studies fulfilled the inclusion criteria for meta-analysis. Seven reported results for overall PCa. When the overall PCa prevalence increased from 30% to 60%, the combined NPV estimates decreased from 88% (95% confidence interval [95% CI], 77-99%) to 67% (95% CI, 56-79%) for a cut-off score of 3/5. Only one study selected for meta-analysis reported results for Gleason ≥7 cancers, with a positive biopsy rate of 29.3%. The corresponding NPV for a cut-off score of ≥3/5 was 87.9%. The NPV of mpMRI varied greatly depending on study design, cancer prevalence, and definitions of positive mpMRI and csPCa. As cancer prevalence was highly variable among series, risk stratification of patients should be the initial step before considering prebiopsy mpMRI and defining those in whom biopsy may be omitted when the mpMRI is negative. This systematic review examined if multiparametric magnetic resonance imaging (MRI) scan can be used to reliably predict the absence of prostate cancer in patients suspected of having prostate cancer, thereby avoiding a prostate biopsy. The results suggest that whilst it is a promising tool, it is not accurate enough to replace prostate biopsy in such patients, mainly because its accuracy is variable and influenced by the prostate cancer risk. However, its performance can be enhanced if there were more accurate ways of determining the risk of having prostate cancer. When such tools are available, it should be possible to use an MRI scan to avoid biopsy in patients at a low risk of prostate cancer. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Prostate cancer outcomes in France: treatments, adverse effects and two-year mortality

PubMed Central

2014-01-01

Background This very large population-based study investigated outcomes after a diagnosis of prostate cancer (PCa) in terms of mortality rates, treatments and adverse effects. Methods Among the 11 million men aged 40 years and over covered by the general national health insurance scheme, those with newly managed PCa in 2009 were followed for two years based on data from the national health insurance information system (SNIIRAM). Patients were identified using hospitalisation diagnoses and specific refunds related to PCa and PCa treatments. Adverse effects of PCa treatments were identified by using hospital diagnoses, specific procedures and drug refunds. Results The age-standardised two-year all-cause mortality rate among the 43,460 men included in the study was 8.4%, twice that of all men aged 40 years and over. Among the 36,734 two-year survivors, 38% had undergone prostatectomy, 36% had been treated by hormone therapy, 29% by radiotherapy, 3% by brachytherapy and 20% were not treated. The frequency of treatment-related adverse effects varied according to age and type of treatment. Among men between 50 and 69 years of age treated by prostatectomy alone, 61% were treated for erectile dysfunction and 24% were treated for urinary disorders. The frequency of treatment for these disorders decreased during the second year compared to the first year (erectile dysfunction: 41% vs 53%, urinary disorders: 9% vs 20%). The frequencies of these treatments among men treated by external beam radiotherapy alone were 7% and 14%, respectively. Among men between 50 and 69 years with treated PCa, 46% received treatments for erectile dysfunction and 22% for urinary disorders. For controls without PCa but treated surgically for benign prostatic hyperplasia, these frequencies were 1.5% and 6.0%, respectively. Conclusions We report high survival rates two years after a diagnosis of PCa, but a high frequency of PCa treatment-related adverse effects. These frequencies remain underestimated, as they are based on treatments for erectile dysfunction and urinary disorders and do not reflect all functional outcomes. These results should help urologists and general practitioners to inform their patients about outcomes at the time of screening and diagnosis, and especially about potential treatment-related adverse effects. PMID:24927850

Statistical aspects of genetic association testing in small samples, based on selective DNA pooling data in the arctic fox.

PubMed

Szyda, Joanna; Liu, Zengting; Zatoń-Dobrowolska, Magdalena; Wierzbicki, Heliodor; Rzasa, Anna

2008-01-01

We analysed data from a selective DNA pooling experiment with 130 individuals of the arctic fox (Alopex lagopus), which originated from 2 different types regarding body size. The association between alleles of 6 selected unlinked molecular markers and body size was tested by using univariate and multinomial logistic regression models, applying odds ratio and test statistics from the power divergence family. Due to the small sample size and the resulting sparseness of the data table, in hypothesis testing we could not rely on the asymptotic distributions of the tests. Instead, we tried to account for data sparseness by (i) modifying confidence intervals of odds ratio; (ii) using a normal approximation of the asymptotic distribution of the power divergence tests with different approaches for calculating moments of the statistics; and (iii) assessing P values empirically, based on bootstrap samples. As a result, a significant association was observed for 3 markers. Furthermore, we used simulations to assess the validity of the normal approximation of the asymptotic distribution of the test statistics under the conditions of small and sparse samples.

Small Vocabulary Recognition Using Surface Electromyography in an Acoustically Harsh Environment

NASA Technical Reports Server (NTRS)

Betts, Bradley J.; Jorgensen, Charles

2005-01-01

This paper presents results of electromyographic-based (EMG-based) speech recognition on a small vocabulary of 15 English words. The work was motivated in part by a desire to mitigate the effects of high acoustic noise on speech intelligibility in communication systems used by first responders. Both an off-line and a real-time system were constructed. Data were collected from a single male subject wearing a fireghter's self-contained breathing apparatus. A single channel of EMG data was used, collected via surface sensors at a rate of 104 samples/s. The signal processing core consisted of an activity detector, a feature extractor, and a neural network classifier. In the off-line phase, 150 examples of each word were collected from the subject. Generalization testing, conducted using bootstrapping, produced an overall average correct classification rate on the 15 words of 74%, with a 95% confidence interval of [71%, 77%]. Once the classifier was trained, the subject used the real-time system to communicate and to control a robotic device. The real-time system was tested with the subject exposed to an ambient noise level of approximately 95 decibels.

Mutational Landscape of Candidate Genes in Familial Prostate Cancer

PubMed Central

Johnson, Anna M.; Zuhlke, Kimberly A.; Plotts, Chris; McDonnell, Shannon K.; Middha, Sumit; Riska, Shaun M.; Thibodeau, Stephen N.; Douglas, Julie A.; Cooney, Kathleen A.

2014-01-01

Background Family history is a major risk factor for prostate cancer (PCa), suggesting a genetic component to the disease. However, traditional linkage and association studies have failed to fully elucidate the underlying genetic basis of familial PCa. Methods Here we use a candidate gene approach to identify potential PCa susceptibility variants in whole exome sequencing data from familial PCa cases. Six hundred ninety-seven candidate genes were identified based on function, location near a known chromosome 17 linkage signal, and/or previous association with prostate or other cancers. Single nucleotide variants (SNVs) in these candidate genes were identified in whole exome sequence data from 33 PCa cases from 11 multiplex PCa families (3 cases/family). Results Overall, 4856 candidate gene SNVs were identified, including 1052 missense and 10 nonsense variants. Twenty missense variants were shared by all 3 family members in each family in which they were observed. Additionally, 15 missense variants were shared by 2 of 3 family members and predicted to be deleterious by 5 different algorithms. Four missense variants, BLM Gln123Arg, PARP2 Arg283Gln, LRCC46 Ala295Thr and KIF2B Pro91Leu, and 1 nonsense variant, CYP3A43 Arg441Ter, showed complete co-segregation with PCa status. Twelve additional variants displayed partial co-segregation with PCa. Conclusions Forty-three nonsense and shared, missense variants were identified in our candidate genes. Further research is needed to determine the contribution of these variants to PCa susceptibility. PMID:25111073

Stream-based Hebbian eigenfilter for real-time neuronal spike discrimination

PubMed Central

2012-01-01

Background Principal component analysis (PCA) has been widely employed for automatic neuronal spike sorting. Calculating principal components (PCs) is computationally expensive, and requires complex numerical operations and large memory resources. Substantial hardware resources are therefore needed for hardware implementations of PCA. General Hebbian algorithm (GHA) has been proposed for calculating PCs of neuronal spikes in our previous work, which eliminates the needs of computationally expensive covariance analysis and eigenvalue decomposition in conventional PCA algorithms. However, large memory resources are still inherently required for storing a large volume of aligned spikes for training PCs. The large size memory will consume large hardware resources and contribute significant power dissipation, which make GHA difficult to be implemented in portable or implantable multi-channel recording micro-systems. Method In this paper, we present a new algorithm for PCA-based spike sorting based on GHA, namely stream-based Hebbian eigenfilter, which eliminates the inherent memory requirements of GHA while keeping the accuracy of spike sorting by utilizing the pseudo-stationarity of neuronal spikes. Because of the reduction of large hardware storage requirements, the proposed algorithm can lead to ultra-low hardware resources and power consumption of hardware implementations, which is critical for the future multi-channel micro-systems. Both clinical and synthetic neural recording data sets were employed for evaluating the accuracy of the stream-based Hebbian eigenfilter. The performance of spike sorting using stream-based eigenfilter and the computational complexity of the eigenfilter were rigorously evaluated and compared with conventional PCA algorithms. Field programmable logic arrays (FPGAs) were employed to implement the proposed algorithm, evaluate the hardware implementations and demonstrate the reduction in both power consumption and hardware memories achieved by the streaming computing Results and discussion Results demonstrate that the stream-based eigenfilter can achieve the same accuracy and is 10 times more computationally efficient when compared with conventional PCA algorithms. Hardware evaluations show that 90.3% logic resources, 95.1% power consumption and 86.8% computing latency can be reduced by the stream-based eigenfilter when compared with PCA hardware. By utilizing the streaming method, 92% memory resources and 67% power consumption can be saved when compared with the direct implementation of GHA. Conclusion Stream-based Hebbian eigenfilter presents a novel approach to enable real-time spike sorting with reduced computational complexity and hardware costs. This new design can be further utilized for multi-channel neuro-physiological experiments or chronic implants. PMID:22490725

Effect of non-normality on test statistics for one-way independent groups designs.

PubMed

Cribbie, Robert A; Fiksenbaum, Lisa; Keselman, H J; Wilcox, Rand R

2012-02-01

The data obtained from one-way independent groups designs is typically non-normal in form and rarely equally variable across treatment populations (i.e., population variances are heterogeneous). Consequently, the classical test statistic that is used to assess statistical significance (i.e., the analysis of variance F test) typically provides invalid results (e.g., too many Type I errors, reduced power). For this reason, there has been considerable interest in finding a test statistic that is appropriate under conditions of non-normality and variance heterogeneity. Previously recommended procedures for analysing such data include the James test, the Welch test applied either to the usual least squares estimators of central tendency and variability, or the Welch test with robust estimators (i.e., trimmed means and Winsorized variances). A new statistic proposed by Krishnamoorthy, Lu, and Mathew, intended to deal with heterogeneous variances, though not non-normality, uses a parametric bootstrap procedure. In their investigation of the parametric bootstrap test, the authors examined its operating characteristics under limited conditions and did not compare it to the Welch test based on robust estimators. Thus, we investigated how the parametric bootstrap procedure and a modified parametric bootstrap procedure based on trimmed means perform relative to previously recommended procedures when data are non-normal and heterogeneous. The results indicated that the tests based on trimmed means offer the best Type I error control and power when variances are unequal and at least some of the distribution shapes are non-normal. © 2011 The British Psychological Society.

Does Bootstrap Procedure Provide Biased Estimates? An Empirical Examination for a Case of Multiple Regression.

ERIC Educational Resources Information Center

Fan, Xitao

This paper empirically and systematically assessed the performance of bootstrap resampling procedure as it was applied to a regression model. Parameter estimates from Monte Carlo experiments (repeated sampling from population) and bootstrap experiments (repeated resampling from one original bootstrap sample) were generated and compared. Sample…

Using the Descriptive Bootstrap to Evaluate Result Replicability (Because Statistical Significance Doesn't)

ERIC Educational Resources Information Center

Spinella, Sarah

2011-01-01

As result replicability is essential to science and difficult to achieve through external replicability, the present paper notes the insufficiency of null hypothesis statistical significance testing (NHSST) and explains the bootstrap as a plausible alternative, with a heuristic example to illustrate the bootstrap method. The bootstrap relies on…

Prostate health index (PHI) and prostate-specific antigen (PSA) predictive models for prostate cancer in the Chinese population and the role of digital rectal examination-estimated prostate volume.

PubMed

Chiu, Peter K F; Roobol, Monique J; Teoh, Jeremy Y; Lee, Wai-Man; Yip, Siu-Ying; Hou, See-Ming; Bangma, Chris H; Ng, Chi-Fai

2016-10-01

To investigate PSA- and PHI (prostate health index)-based models for prediction of prostate cancer (PCa) and the feasibility of using DRE-estimated prostate volume (DRE-PV) in the models. This study included 569 Chinese men with PSA 4-10 ng/mL and non-suspicious DRE with transrectal ultrasound (TRUS) 10-core prostate biopsies performed between April 2008 and July 2015. DRE-PV was estimated using 3 pre-defined classes: 25, 40, or 60 ml. The performance of PSA-based and PHI-based predictive models including age, DRE-PV, and TRUS prostate volume (TRUS-PV) was analyzed using logistic regression and area under the receiver operating curves (AUC), in both the whole cohort and the screening age group of 55-75. PCa and high-grade PCa (HGPCa) was diagnosed in 10.9 % (62/569) and 2.8 % (16/569) men, respectively. The performance of DRE-PV-based models was similar to TRUS-PV-based models. In the age group 55-75, the AUCs for PCa of PSA alone, PSA with DRE-PV and age, PHI alone, PHI with DRE-PV and age, and PHI with TRUS-PV and age were 0.54, 0.71, 0.76, 0.78, and 0.78, respectively. The corresponding AUCs for HGPCa were higher (0.60, 0.70, 0.85, 0.83, and 0.83). At 10 and 20 % risk threshold for PCa, 38.4 and 55.4 % biopsies could be avoided in the PHI-based model, respectively. PHI had better performance over PSA-based models and could reduce unnecessary biopsies. A DRE-assessed PV can replace TRUS-assessed PV in multivariate prediction models to facilitate clinical use.

Neural network ensemble based CAD system for focal liver lesions from B-mode ultrasound.

PubMed

Virmani, Jitendra; Kumar, Vinod; Kalra, Naveen; Khandelwal, Niranjan

2014-08-01

A neural network ensemble (NNE) based computer-aided diagnostic (CAD) system to assist radiologists in differential diagnosis between focal liver lesions (FLLs), including (1) typical and atypical cases of Cyst, hemangioma (HEM) and metastatic carcinoma (MET) lesions, (2) small and large hepatocellular carcinoma (HCC) lesions, along with (3) normal (NOR) liver tissue is proposed in the present work. Expert radiologists, visualize the textural characteristics of regions inside and outside the lesions to differentiate between different FLLs, accordingly texture features computed from inside lesion regions of interest (IROIs) and texture ratio features computed from IROIs and surrounding lesion regions of interests (SROIs) are taken as input. Principal component analysis (PCA) is used for reducing the dimensionality of the feature space before classifier design. The first step of classification module consists of a five class PCA-NN based primary classifier which yields probability outputs for five liver image classes. The second step of classification module consists of ten binary PCA-NN based secondary classifiers for NOR/Cyst, NOR/HEM, NOR/HCC, NOR/MET, Cyst/HEM, Cyst/HCC, Cyst/MET, HEM/HCC, HEM/MET and HCC/MET classes. The probability outputs of five class PCA-NN based primary classifier is used to determine the first two most probable classes for a test instance, based on which it is directed to the corresponding binary PCA-NN based secondary classifier for crisp classification between two classes. By including the second step of the classification module, classification accuracy increases from 88.7 % to 95 %. The promising results obtained by the proposed system indicate its usefulness to assist radiologists in differential diagnosis of FLLs.

Sevelamer is cost-saving vs. calcium carbonate in non-dialysis-dependent CKD patients in italy: a patient-level cost-effectiveness analysis of the INDEPENDENT study.

PubMed

Ruggeri, Matteo; Cipriani, Filippo; Bellasi, Antonio; Russo, Domenico; Di Iorio, Biagio

2014-01-01

To conduct a cost-effectiveness analysis of sevelamer versus calcium carbonate in patients with non-dialysis-dependent CKD (NDD-CKD) from the Italian NHS perspective using patient-level data from the INDEPENDENT-CKD study. Patient-level data on all-cause mortality, dialysis inception and phosphate binder dose were obtained for all 107 sevelamer and 105 calcium carbonate patients from the INDEPENDENT-CKD study. Hospitalization and frequency of dialysis data were collected post hoc for all patients via a retrospective chart review. Phosphate binder, hospitalization, and dialysis costs were expressed in 2012 euros using hospital pharmacy, Italian diagnosis-related group and ambulatory tariffs, respectively. Total life years (LYs) and costs per treatment group were calculated for the 3-year period of the study. Bootstrapping was used to estimate confidence intervals around outcomes, costs, and cost-effectiveness and to calculate the cost-effectiveness acceptability curve. A subgroup analysis of patients who did not initiate dialysis during the INDEPENDENT-CKD study was also conducted. Sevelamer was associated with 0.06 additional LYs (95% CI -0.04 to 0.16) and cost savings of EUR -5,615 (95% CI -10,066 to -1,164) per patient compared with calcium carbonate. On the basis of the bootstrap analysis, sevelamer was dominant compared to calcium carbonate in 87.1% of 10,000 bootstrap replicates. Similar results were observed in the subgroup analysis. RESULTS were driven by a significant reduction in all-cause mortality and significantly fewer hospitalizations in the sevelamer group, which offset the higher acquisition cost for sevelamer. Sevelamer provides more LYs and is less costly than calcium carbonate in patients with NDD-CKD in Italy.

From genus to phylum: large-subunit and internal transcribed spacer rRNA operon regions show similar classification accuracies influenced by database composition.

PubMed

Porras-Alfaro, Andrea; Liu, Kuan-Liang; Kuske, Cheryl R; Xie, Gary

2014-02-01

We compared the classification accuracy of two sections of the fungal internal transcribed spacer (ITS) region, individually and combined, and the 5' section (about 600 bp) of the large-subunit rRNA (LSU), using a naive Bayesian classifier and BLASTN. A hand-curated ITS-LSU training set of 1,091 sequences and a larger training set of 8,967 ITS region sequences were used. Of the factors evaluated, database composition and quality had the largest effect on classification accuracy, followed by fragment size and use of a bootstrap cutoff to improve classification confidence. The naive Bayesian classifier and BLASTN gave similar results at higher taxonomic levels, but the classifier was faster and more accurate at the genus level when a bootstrap cutoff was used. All of the ITS and LSU sections performed well (>97.7% accuracy) at higher taxonomic ranks from kingdom to family, and differences between them were small at the genus level (within 0.66 to 1.23%). When full-length sequence sections were used, the LSU outperformed the ITS1 and ITS2 fragments at the genus level, but the ITS1 and ITS2 showed higher accuracy when smaller fragment sizes of the same length and a 50% bootstrap cutoff were used. In a comparison using the larger ITS training set, ITS1 and ITS2 had very similar accuracy classification for fragments between 100 and 200 bp. Collectively, the results show that any of the ITS or LSU sections we tested provided comparable classification accuracy to the genus level and underscore the need for larger and more diverse classification training sets.

From Genus to Phylum: Large-Subunit and Internal Transcribed Spacer rRNA Operon Regions Show Similar Classification Accuracies Influenced by Database Composition

PubMed Central

Liu, Kuan-Liang; Kuske, Cheryl R.

2014-01-01

We compared the classification accuracy of two sections of the fungal internal transcribed spacer (ITS) region, individually and combined, and the 5′ section (about 600 bp) of the large-subunit rRNA (LSU), using a naive Bayesian classifier and BLASTN. A hand-curated ITS-LSU training set of 1,091 sequences and a larger training set of 8,967 ITS region sequences were used. Of the factors evaluated, database composition and quality had the largest effect on classification accuracy, followed by fragment size and use of a bootstrap cutoff to improve classification confidence. The naive Bayesian classifier and BLASTN gave similar results at higher taxonomic levels, but the classifier was faster and more accurate at the genus level when a bootstrap cutoff was used. All of the ITS and LSU sections performed well (>97.7% accuracy) at higher taxonomic ranks from kingdom to family, and differences between them were small at the genus level (within 0.66 to 1.23%). When full-length sequence sections were used, the LSU outperformed the ITS1 and ITS2 fragments at the genus level, but the ITS1 and ITS2 showed higher accuracy when smaller fragment sizes of the same length and a 50% bootstrap cutoff were used. In a comparison using the larger ITS training set, ITS1 and ITS2 had very similar accuracy classification for fragments between 100 and 200 bp. Collectively, the results show that any of the ITS or LSU sections we tested provided comparable classification accuracy to the genus level and underscore the need for larger and more diverse classification training sets. PMID:24242255

Measurement Error Correction for Predicted Spatiotemporal Air Pollution Exposures.

PubMed

Keller, Joshua P; Chang, Howard H; Strickland, Matthew J; Szpiro, Adam A

2017-05-01

Air pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data. We analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated date of conception during 2002-2005 (n = 403,881). We predicted trimester-specific PM2.5 exposure using a complex spatiotemporal exposure model. To improve spatial compatibility, we restricted to mothers residing in counties with a PM2.5 monitor (n = 180,440). We accounted for additional measurement error via a nonparametric bootstrap. Third trimester PM2.5 exposure was associated with lower birth weight in the uncorrected (-2.4 g per 1 μg/m difference in exposure; 95% confidence interval [CI]: -3.9, -0.8) and bootstrap-corrected (-2.5 g, 95% CI: -4.2, -0.8) analyses. Results for the unrestricted analysis were attenuated (-0.66 g, 95% CI: -1.7, 0.35). This study presents a novel application of measurement error correction for spatiotemporal air pollution exposures. Our results demonstrate the importance of spatial compatibility between monitor and subject locations and provide evidence of the association between air pollution exposure and birth weight.

Distinguishing dissolved organic matter at its origin: size and optical properties of leaf-litter leachates.

PubMed

Cuss, C W; Guéguen, C

2013-09-01

Dissolved organic matter (DOM) was leached from eight distinct samples of leaves taken from six distinct trees (red maple, bur oak at three times of the year, two sugar maple and two white spruce trees from disparate soil types). Multiple samples were taken over 72-96h of leaching. The size and optical properties of leachates were assessed using asymmetrical flow field-flow fractionation (AF4) coupled to diode-array ultraviolet/visible absorbance and excitation-emission matrix fluorescence detectors (EEM). The fluorescence of unfractionated samples was also analyzed. EEMs were analyzed using parallel factor analysis (PARAFAC) and principal component analysis (PCA) of proportional component loadings. Both the unfractionated and AF4-fractionated leachates had distinct size and optical properties. The 95% confidence ranges for molecular weight distributions were determined as: 210-440Da for spruce, 540-920Da for sugar maple, 630-800Da for spring oak leaves, 930-950Da for senescent oak, 1490-1670 for senescent red maple, and 3430-4270Da for oak leaves that were collected from the ground after spring thaw. In most cases the fluorescence properties of leachates were different for individuals from different soil types and across seasons; however, PCA of PARAFAC loadings revealed that the observed distinctiveness was chiefly species-based. Strong correlations were found between the molecular weight distribution of both unfractionated and fractionated leachates and their principal component loadings (R(2)=0.85 and 0.95, respectively). It is concluded that results support a species-based origin for differences in optical properties. Copyright © 2013 Elsevier Ltd. All rights reserved.

Model specification and bootstrapping for multiply imputed data: An application to count models for the frequency of alcohol use

PubMed Central

Comulada, W. Scott

2015-01-01

Stata’s mi commands provide powerful tools to conduct multiple imputation in the presence of ignorable missing data. In this article, I present Stata code to extend the capabilities of the mi commands to address two areas of statistical inference where results are not easily aggregated across imputed datasets. First, mi commands are restricted to covariate selection. I show how to address model fit to correctly specify a model. Second, the mi commands readily aggregate model-based standard errors. I show how standard errors can be bootstrapped for situations where model assumptions may not be met. I illustrate model specification and bootstrapping on frequency counts for the number of times that alcohol was consumed in data with missing observations from a behavioral intervention. PMID:26973439

Cohort Profile: the National Prostate Cancer Register of Sweden and Prostate Cancer data Base Sweden 2.0.

PubMed

Van Hemelrijck, Mieke; Wigertz, Annette; Sandin, Fredrik; Garmo, Hans; Hellström, Karin; Fransson, Per; Widmark, Anders; Lambe, Mats; Adolfsson, Jan; Varenhorst, Eberhard; Johansson, Jan-Erik; Stattin, Pär

2013-08-01

In 1987, the first Regional Prostate Cancer Register was set up in the South-East health-care region of Sweden. Other health-care regions joined and since 1998 virtually all prostate cancer (PCa) cases are registered in the National Prostate Cancer Register (NPCR) of Sweden to provide data for quality assurance, bench marking and clinical research. NPCR includes data on tumour stage, Gleason score, serum level of prostate-specific antigen (PSA) and primary treatment. In 2008, the NPCR was linked to a number of other population-based registers by use of the personal identity number. This database named Prostate Cancer data Base Sweden (PCBaSe) has now been extended with more cases, longer follow-up and a selection of two control series of men free of PCa at the time of sampling, as well as information on brothers of men diagnosed with PCa, resulting in PCBaSe 2.0. This extension allows for studies with case-control, cohort or longitudinal case-only design on aetiological factors, pharmaceutical prescriptions and assessment of long-term outcomes. The NPCR covers >96% of all incident PCa cases registered by the Swedish Cancer Register, which has an underreporting of <3.7%. The NPCR is used to assess trends in incidence, treatment and outcome of men with PCa. Since the national registers linked to PCBaSe are complete, studies from PCBaSe 2.0 are truly population based.

Prospective randomized trial comparing magnetic resonance imaging (MRI)-guided in-bore biopsy to MRI-ultrasound fusion and transrectal ultrasound-guided prostate biopsy in patients with prior negative biopsies.

PubMed

Arsov, Christian; Rabenalt, Robert; Blondin, Dirk; Quentin, Michael; Hiester, Andreas; Godehardt, Erhard; Gabbert, Helmut E; Becker, Nikolaus; Antoch, Gerald; Albers, Peter; Schimmöller, Lars

2015-10-01

A significant proportion of prostate cancers (PCas) are missed by conventional transrectal ultrasound-guided biopsy (TRUS-GB). It remains unclear whether the combined approach using targeted magnetic resonance imaging (MRI)-ultrasound fusion-guided biopsy (FUS-GB) and systematic TRUS-GB is superior to targeted MRI-guided in-bore biopsy (IB-GB) for PCa detection. To compare PCa detection between IB-GB alone and FUS-GB + TRUS-GB in patients with at least one negative TRUS-GB and prostate-specific antigen ≥4 ng/ml. Patients were prospectively randomized after multiparametric prostate MRI to IB-GB (arm A) or FUS-GB + TRUS-GB (arm B) from November 2011 to July 2014. The study was powered at 80% to demonstrate an overall PCa detection rate of ≥60% in arm B compared to 40% in arm A. Secondary endpoints were the distribution of highest Gleason scores, the rate of detection of significant PCa (Gleason ≥7), the number of biopsy cores to detect one (significant) PCa, the positivity rate for biopsy cores, and tumor involvement per biopsy core. The study was halted after interim analysis because the primary endpoint was not met. The trial enrolled 267 patients, of whom 210 were analyzed (106 randomized to arm A and 104 to arm B). PCa detection was 37% in arm A and 39% in arm B (95% confidence interval for difference, -16% to 11%; p=0.7). Detection rates for significant PCa (29% vs 32%; p=0.7) and the highest percentage tumor involvement per biopsy core (48% vs 42%; p=0.4) were similar between the arms. The mean number of cores was 5.6 versus 17 (p<0.001). A limitation is the limited number of patients because of early cessation of accrual. This trial failed to identify an important improvement in detection rate for the combined biopsy approach over MRI-targeted biopsy alone. A prospective comparison between MRI-targeted biopsy alone and systematic TRUS-GB is justified. Our randomized study showed similar prostate cancer detection rates between targeted prostate biopsy guided by magnetic resonance imaging and the combination of targeted biopsy and systematic transrectal ultrasound-guided prostate biopsy. An important improvement in detection rates using the combined biopsy approach can be excluded. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

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

Benadjaoud, Mohamed Amine, E-mail: mohamedamine.benadjaoud@gustaveroussy.fr; Université Paris sud, Le Kremlin-Bicêtre; Institut Gustave Roussy, Villejuif

2014-11-01

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principalmore » components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion: Functional data analysis provides an attractive method for flexibly estimating the dose-volume effect for normal tissues in external radiation therapy.« less

Construction of prediction intervals for Palmer Drought Severity Index using bootstrap

NASA Astrophysics Data System (ADS)

Beyaztas, Ufuk; Bickici Arikan, Bugrayhan; Beyaztas, Beste Hamiye; Kahya, Ercan

2018-04-01

In this study, we propose an approach based on the residual-based bootstrap method to obtain valid prediction intervals using monthly, short-term (three-months) and mid-term (six-months) drought observations. The effects of North Atlantic and Arctic Oscillation indexes on the constructed prediction intervals are also examined. Performance of the proposed approach is evaluated for the Palmer Drought Severity Index (PDSI) obtained from Konya closed basin located in Central Anatolia, Turkey. The finite sample properties of the proposed method are further illustrated by an extensive simulation study. Our results revealed that the proposed approach is capable of producing valid prediction intervals for future PDSI values.

Patient Preferences and Urologist Judgments on Prostate Cancer Therapy in Japan.

PubMed

Nakayama, Masahiko; Kobayashi, Hisanori; Okazaki, Masateru; Imanaka, Keiichiro; Yoshizawa, Kazutake; Mahlich, Jörg

2018-05-01

The purpose of the present study is to investigate the concordance of treatment preferences between patients and physicians in prostate cancer (PCa) in Japan. An internet-based discrete choice experiment was conducted. Patients and physicians were asked to select their preferred treatment from a pair of hypothetical treatments consisting of four attributes: quality of life (QOL), treatment effectiveness, side effects, and accessibility of treatment. The data were analyzed using a conditional logistic regression model to calculate coefficients and the relative importance (RI) of each attribute. A total of 103 PCa patients and 127 physicians responded. The study looked at 37 patients considered as advanced PCa and 66 who were non-advanced PCa. All of the physicians were urologists. Advanced PCa patients ranked the attributes as follows: treatment effectiveness (RI: 32%), accessibility of treatment (RI: 26%), QOL (RI: 23%), and side effects (RI: 19%). For physicians, the RI ranking was the same as for advanced PCa patients; treatment effectiveness (RI: 29%), accessibility of treatment (RI: 27%), QOL (RI: 26%), and side effects (RI: 18%). For non-advanced PCa patients, accessibility of treatment ranked the highest RI (27%) and treatment effectiveness ranked as the lowest RI (14%). Our study suggests that the ranking of the attributes was consistent between advanced PCa patients and physicians. The most influential attribute was treatment effectiveness. Treatment preferences also vary by disease stage.

Waist-hip Ratio (WHR), a Better Predictor for Prostate Cancer than Body Mass Index (BMI): Results from a Chinese Hospital-based Biopsy Cohort.

PubMed

Tang, Bo; Han, Cheng-Tao; Zhang, Gui-Ming; Zhang, Cui-Zhu; Yang, Wei-Yi; Shen, Ying; Vidal, Adriana C; Freedland, Stephen J; Zhu, Yao; Ye, Ding-Wei

2017-03-08

To investigate whether waist-hip ratio (WHR) is a better predictor of prostate cancer (PCa) incidence than body mass index (BMI) in Chinese men. Of consecutive patients who underwent prostate biopsies in one tertiary center between 2013 and 2015, we examined data on 1018 with PSA ≤20 ng/ml. Clinical data and biopsy outcomes were collected. Logistic regression was used to evaluate the associations between BMI, WHR and PCa incidence. Area under the ROC (AUC) was used to evaluate the accuracy of different prognostic models. A total of 255 men and 103 men were diagnosed with PCa and high grade PCa (HGPCa, Gleason score ≥8). WHR was an independent risk factor for both PCa (OR = 1.07 95%Cl 1.03-1.11) and HGPCa (OR = 1.14 95%Cl 1.09-1.19) detection, while BMI had no relationship with either PCa or HGPCa detection. Adding WHR to a multivariable model increased the AUC for detecting HGPCa from 0.66 (95%Cl 0.60-0.72) to 0.71 (95%Cl 0.65-0.76). In this Chinese cohort, WHR was significantly predictive of PCa and HGPCa. Adding WHR to a multivariable model increased the diagnostic accuracy for detecting HGPCa. If confirmed, including WHR measurement may improve PCa and HGPCa detection.

Waist-hip Ratio (WHR), a Better Predictor for Prostate Cancer than Body Mass Index (BMI): Results from a Chinese Hospital-based Biopsy Cohort

PubMed Central

Tang, Bo; Han, Cheng-Tao; Zhang, Gui-Ming; Zhang, Cui-Zhu; Yang, Wei-Yi; Shen, Ying; Vidal, Adriana C.; Freedland, Stephen J.; Zhu, Yao; Ye, Ding-Wei

2017-01-01

To investigate whether waist-hip ratio (WHR) is a better predictor of prostate cancer (PCa) incidence than body mass index (BMI) in Chinese men. Of consecutive patients who underwent prostate biopsies in one tertiary center between 2013 and 2015, we examined data on 1018 with PSA ≤20 ng/ml. Clinical data and biopsy outcomes were collected. Logistic regression was used to evaluate the associations between BMI, WHR and PCa incidence. Area under the ROC (AUC) was used to evaluate the accuracy of different prognostic models. A total of 255 men and 103 men were diagnosed with PCa and high grade PCa (HGPCa, Gleason score ≥8). WHR was an independent risk factor for both PCa (OR = 1.07 95%Cl 1.03–1.11) and HGPCa (OR = 1.14 95%Cl 1.09–1.19) detection, while BMI had no relationship with either PCa or HGPCa detection. Adding WHR to a multivariable model increased the AUC for detecting HGPCa from 0.66 (95%Cl 0.60–0.72) to 0.71 (95%Cl 0.65–0.76). In this Chinese cohort, WHR was significantly predictive of PCa and HGPCa. Adding WHR to a multivariable model increased the diagnostic accuracy for detecting HGPCa. If confirmed, including WHR measurement may improve PCa and HGPCa detection. PMID:28272469

The fractal characteristic of facial anthropometric data for developing PCA fit test panels for youth born in central China.

PubMed

Yang, Lei; Wei, Ran; Shen, Henggen

2017-01-01

New principal component analysis (PCA) respirator fit test panels had been developed for current American and Chinese civilian workers based on anthropometric surveys. The PCA panels used the first two principal components (PCs) obtained from a set of 10 facial dimensions. Although the PCA panels for American and Chinese subjects adopted the bivairate framework with two PCs, the number of the PCs retained in the PCA analysis was different between Chinese subjects and Americans. For the Chinese youth group, the third PC should be retained in the PCA analysis for developing new fit test panels. In this article, an additional number label (ANL) is used to explain the third PC in PCA analysis when the first two PCs are used to construct the PCA half-facepiece respirator fit test panel for Chinese group. The three-dimensional box-counting method is proposed to estimate the ANLs by calculating fractal dimensions of the facial anthropometric data of the Chinese youth. The linear regression coefficients of scale-free range R 2 are all over 0.960, which demonstrates that the facial anthropometric data of the Chinese youth has fractal characteristic. The youth subjects born in Henan province has an ANL of 2.002, which is lower than the composite facial anthropometric data of Chinese subjects born in many provinces. Hence, Henan youth subjects have the self-similar facial anthropometric characteristic and should use the particular ANL (2.002) as the important tool along with using the PCA panel. The ANL method proposed in this article not only provides a new methodology in quantifying the characteristics of facial anthropometric dimensions for any ethnic/racial group, but also extends the scope of PCA panel studies to higher dimensions.

Expression of spermidine/spermine N(1) -acetyl transferase (SSAT) in human prostate tissues is related to prostate cancer progression and metastasis.

PubMed

Huang, Wei; Eickhoff, Jens C; Mehraein-Ghomi, Farideh; Church, Dawn R; Wilding, George; Basu, Hirak S

2015-08-01

Prostate cancer (PCa) in many patients remains indolent for the rest of their lives, but in some patients, it progresses to lethal metastatic disease. Gleason score is the current clinical method for PCa prognosis. It cannot reliably identify aggressive PCa, when GS is ≤ 7. It is shown that oxidative stress plays a key role in PCa progression. We have shown that in cultured human PCa cells, an activation of spermidine/spermine N(1) -acetyl transferase (SSAT; EC 2.3.1.57) enzyme initiates a polyamine oxidation pathway and generates copious amounts of reactive oxygen species in polyamine-rich PCa cells. We used RNA in situ hybridization and immunohistochemistry methods to detect SSAT mRNA and protein expression in two tissue microarrays (TMA) created from patient's prostate tissues. We analyzed 423 patient's prostate tissues in the two TMAs. Our data show that there is a significant increase in both SSAT mRNA and the enzyme protein in the PCa cells as compared to their benign counterpart. This increase is even more pronounced in metastatic PCa tissues as compared to the PCa localized in the prostate. In the prostatectomy tissues from early-stage patients, the SSAT protein level is also high in the tissues obtained from the patients who ultimately progress to advanced metastatic disease. Based on these results combined with published data from our and other laboratories, we propose an activation of an autocrine feed-forward loop of PCa cell proliferation in the absence of androgen as a possible mechanism of castrate-resistant prostate cancer growth. © 2015 Wiley Periodicals, Inc.

Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm.

PubMed

Saba, Luca; Jain, Pankaj K; Suri, Harman S; Ikeda, Nobutaka; Araki, Tadashi; Singh, Bikesh K; Nicolaides, Andrew; Shafique, Shoaib; Gupta, Ajay; Laird, John R; Suri, Jasjit S

2017-06-01

Severe atherosclerosis disease in carotid arteries causes stenosis which in turn leads to stroke. Machine learning systems have been previously developed for plaque wall risk assessment using morphology-based characterization. The fundamental assumption in such systems is the extraction of the grayscale features of the plaque region. Even though these systems have the ability to perform risk stratification, they lack the ability to achieve higher performance due their inability to select and retain dominant features. This paper introduces a polling-based principal component analysis (PCA) strategy embedded in the machine learning framework to select and retain dominant features, resulting in superior performance. This leads to more stability and reliability. The automated system uses offline image data along with the ground truth labels to generate the parameters, which are then used to transform the online grayscale features to predict the risk of stroke. A set of sixteen grayscale plaque features is computed. Utilizing the cross-validation protocol (K = 10), and the PCA cutoff of 0.995, the machine learning system is able to achieve an accuracy of 98.55 and 98.83%corresponding to the carotidfar wall and near wall plaques, respectively. The corresponding reliability of the system was 94.56 and 95.63%, respectively. The automated system was validated against the manual risk assessment system and the precision of merit for same cross-validation settings and PCA cutoffs are 98.28 and 93.92%for the far and the near wall, respectively.PCA-embedded morphology-based plaque characterization shows a powerful strategy for risk assessment and can be adapted in clinical settings.

Combining test statistics and models in bootstrapped model rejection: it is a balancing act

PubMed Central

2014-01-01

Background Model rejections lie at the heart of systems biology, since they provide conclusive statements: that the corresponding mechanistic assumptions do not serve as valid explanations for the experimental data. Rejections are usually done using e.g. the chi-square test (χ2) or the Durbin-Watson test (DW). Analytical formulas for the corresponding distributions rely on assumptions that typically are not fulfilled. This problem is partly alleviated by the usage of bootstrapping, a computationally heavy approach to calculate an empirical distribution. Bootstrapping also allows for a natural extension to estimation of joint distributions, but this feature has so far been little exploited. Results We herein show that simplistic combinations of bootstrapped tests, like the max or min of the individual p-values, give inconsistent, i.e. overly conservative or liberal, results. A new two-dimensional (2D) approach based on parametric bootstrapping, on the other hand, is found both consistent and with a higher power than the individual tests, when tested on static and dynamic examples where the truth is known. In the same examples, the most superior test is a 2D χ2vsχ2, where the second χ2-value comes from an additional help model, and its ability to describe bootstraps from the tested model. This superiority is lost if the help model is too simple, or too flexible. If a useful help model is found, the most powerful approach is the bootstrapped log-likelihood ratio (LHR). We show that this is because the LHR is one-dimensional, because the second dimension comes at a cost, and because LHR has retained most of the crucial information in the 2D distribution. These approaches statistically resolve a previously published rejection example for the first time. Conclusions We have shown how to, and how not to, combine tests in a bootstrap setting, when the combination is advantageous, and when it is advantageous to include a second model. These results also provide a deeper insight into the original motivation for formulating the LHR, for the more general setting of nonlinear and non-nested models. These insights are valuable in cases when accuracy and power, rather than computational speed, are prioritized. PMID:24742065

Nonparametric bootstrap analysis with applications to demographic effects in demand functions.

PubMed

Gozalo, P L

1997-12-01

"A new bootstrap proposal, labeled smooth conditional moment (SCM) bootstrap, is introduced for independent but not necessarily identically distributed data, where the classical bootstrap procedure fails.... A good example of the benefits of using nonparametric and bootstrap methods is the area of empirical demand analysis. In particular, we will be concerned with their application to the study of two important topics: what are the most relevant effects of household demographic variables on demand behavior, and to what extent present parametric specifications capture these effects." excerpt

Effects of magnetic islands on bootstrap current in toroidal plasmas

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

Dong, G.; Lin, Z.

The effects of magnetic islands on electron bootstrap current in toroidal plasmas are studied using gyrokinetic simulations. The magnetic islands cause little changes of the bootstrap current level in the banana regime because of trapped electron effects. In the plateau regime, the bootstrap current is completely suppressed at the island centers due to the destruction of trapped electron orbits by collisions and the flattening of pressure profiles by the islands. In the collisional regime, small but finite bootstrap current can exist inside the islands because of the pressure gradients created by large collisional transport across the islands. Lastly, simulation resultsmore » show that the bootstrap current level increases near the island separatrix due to steeper local density gradients.« less

Effects of magnetic islands on bootstrap current in toroidal plasmas

DOE PAGES

Dong, G.; Lin, Z.

2016-12-19

The effects of magnetic islands on electron bootstrap current in toroidal plasmas are studied using gyrokinetic simulations. The magnetic islands cause little changes of the bootstrap current level in the banana regime because of trapped electron effects. In the plateau regime, the bootstrap current is completely suppressed at the island centers due to the destruction of trapped electron orbits by collisions and the flattening of pressure profiles by the islands. In the collisional regime, small but finite bootstrap current can exist inside the islands because of the pressure gradients created by large collisional transport across the islands. Lastly, simulation resultsmore » show that the bootstrap current level increases near the island separatrix due to steeper local density gradients.« less

On the Log-Normality of Historical Magnetic-Storm Intensity Statistics: Implications for Extreme-Event Probabilities

NASA Astrophysics Data System (ADS)

Love, J. J.; Rigler, E. J.; Pulkkinen, A. A.; Riley, P.

2015-12-01

An examination is made of the hypothesis that the statistics of magnetic-storm-maximum intensities are the realization of a log-normal stochastic process. Weighted least-squares and maximum-likelihood methods are used to fit log-normal functions to -Dst storm-time maxima for years 1957-2012; bootstrap analysis is used to established confidence limits on forecasts. Both methods provide fits that are reasonably consistent with the data; both methods also provide fits that are superior to those that can be made with a power-law function. In general, the maximum-likelihood method provides forecasts having tighter confidence intervals than those provided by weighted least-squares. From extrapolation of maximum-likelihood fits: a magnetic storm with intensity exceeding that of the 1859 Carrington event, -Dst > 850 nT, occurs about 1.13 times per century and a wide 95% confidence interval of [0.42, 2.41] times per century; a 100-yr magnetic storm is identified as having a -Dst > 880 nT (greater than Carrington) but a wide 95% confidence interval of [490, 1187] nT. This work is partially motivated by United States National Science and Technology Council and Committee on Space Research and International Living with a Star priorities and strategic plans for the assessment and mitigation of space-weather hazards.

Bootstrap-based procedures for inference in nonparametric receiver-operating characteristic curve regression analysis.

PubMed

Rodríguez-Álvarez, María Xosé; Roca-Pardiñas, Javier; Cadarso-Suárez, Carmen; Tahoces, Pablo G

2018-03-01

Prior to using a diagnostic test in a routine clinical setting, the rigorous evaluation of its diagnostic accuracy is essential. The receiver-operating characteristic curve is the measure of accuracy most widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy also needs to be assessed. In this paper, we focus on an estimator for the covariate-specific receiver-operating characteristic curve based on direct regression modelling and nonparametric smoothing techniques. This approach defines the class of generalised additive models for the receiver-operating characteristic curve. The main aim of the paper is to offer new inferential procedures for testing the effect of covariates on the conditional receiver-operating characteristic curve within the above-mentioned class. Specifically, two different bootstrap-based tests are suggested to check (a) the possible effect of continuous covariates on the receiver-operating characteristic curve and (b) the presence of factor-by-curve interaction terms. The validity of the proposed bootstrap-based procedures is supported by simulations. To facilitate the application of these new procedures in practice, an R-package, known as npROCRegression, is provided and briefly described. Finally, data derived from a computer-aided diagnostic system for the automatic detection of tumour masses in breast cancer is analysed.

From measurements to metrics: PCA-based indicators of cyber anomaly

NASA Astrophysics Data System (ADS)

Ahmed, Farid; Johnson, Tommy; Tsui, Sonia

2012-06-01

We present a framework of the application of Principal Component Analysis (PCA) to automatically obtain meaningful metrics from intrusion detection measurements. In particular, we report the progress made in applying PCA to analyze the behavioral measurements of malware and provide some preliminary results in selecting dominant attributes from an arbitrary number of malware attributes. The results will be useful in formulating an optimal detection threshold in the principal component space, which can both validate and augment existing malware classifiers.

Morphological and molecular differentiation of Parastrigea (Trematoda: Strigeidae) from Mexico, with the description of a new species.

PubMed

Hernández-Mena, David Iván; García-Prieto, Luís; García-Varela, Martín

2014-04-01

Parastrigea plataleae n. sp. (Digenea: Strigeidae) is described from the intestine of the roseate spoonbill Platalea ajaja (Threskiornithidae) from four localities on the Pacific coast of Mexico. The new species is mainly distinguished from the other 18 described species of Parastrigea based on the ratio of its hindbody length to forebody length. A principal component analysis (PCA) of 16 morphometric traits for 15 specimens of P. plataleae n. sp., five of Parastrigea cincta and 11 of Parastrigea diovadena previously recorded in Mexico, clearly shows three clusters, which correspond to the three species. DNA sequences of the internal transcribed spacers (ITSs) of ribosomal DNA and the mitochondrial gene cytochrome c oxidase subunit I (cox 1) were used to corroborate this morphological distinction. The genetic divergence estimated among P. plataleae n. sp., P. cincta and P. diovadena ranged from 0.5 to 1.48% for ITSs and from 9.31 to 11.47% for cox 1. Maximum parsimony (MP) and maximum likelihood (ML) analyses were performed on the combined datasets (ITSs+cox 1) and on each dataset alone. All of the phylogenetic analyses indicated that the specimens from the roseate spoonbill represent a clade with strong bootstrap support. The morphological evidence and the genetic divergence in combination with the reciprocal monophyly in all of the phylogenetic trees support the hypothesis that the digeneans found in the intestines of roseate spoonbills represent a new species. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Collaborative Review: Risk-Based Prostate Cancer Screening

PubMed Central

Zhu, Xiaoye; Albertsen, Peter C.; Andriole, Gerald L.; Roobol, Monique J.; Schröder, Fritz H.; Vickers, Andrew J.

2016-01-01

Context Widespread mass screening of prostate cancer (PCa) is not recommended because the balance between benefits and harms is still not well established. The achieved mortality reduction comes with considerable harm such as unnecessary biopsies, overdiagnoses, and overtreatment. Therefore, patient stratification with regard to PCa risk and aggressiveness is necessary to identify those men who are at risk and may actually benefit from early detection. Objective This review critically examines the current evidence regarding risk-based PCa screening. Evidence acquisition A search of the literature was performed using the Medline database. Further studies were selected based on manual searches of reference lists and review articles. Evidence synthesis Prostate-specific antigen (PSA) has been shown to be the single most significant predictive factor for identifying men at increased risk of developing PCa. Especially in men with no additional risk factors, PSA alone provides an appropriate marker up to 30 yr into the future. After assessment of an early PSA test, the screening frequency may be determined based on individualized risk. A limited list of additional factors such as age, comorbidity, prostate volume, family history, ethnicity, and previous biopsy status have been identified to modify risk and are important for consideration in routine practice. In men with a known PSA, risk calculators may hold the promise of identifying those who are at increased risk of having PCa and are therefore candidates for biopsy. Conclusions PSA testing may serve as the foundation for a more risk-based assessment. However, the decision to undergo early PSA testing should be a shared one between the patient and his physician based on information balancing its advantages and disadvantages. PMID:22134009

Effect of age at onset on cortical thickness and cognition in posterior cortical atrophy

PubMed Central

Suárez-González, Aida; Lehmann, Manja; Shakespeare, Timothy J.; Yong, Keir X.X.; Paterson, Ross W.; Slattery, Catherine F.; Foulkes, Alexander J.M.; Rabinovici, Gil D.; Gil-Néciga, Eulogio; Roldán-Lora, Florinda; Schott, Jonathan M.; Fox, Nick C.; Crutch, Sebastian J.

2016-01-01

Age at onset (AAO) has been shown to influence the phenotype of Alzheimer’s disease (AD), but how it affects atypical presentations of AD remains unknown. Posterior cortical atrophy (PCA) is the most common form of atypical AD. In this study, we aimed to investigate the effect of AAO on cortical thickness and cognitive function in 98 PCA patients. We used Freesurfer (v5.3.0) to compare cortical thickness with AAO both as a continuous variable, and by dichotomizing the groups based on median age (58 years). In both the continuous and dichotomized analyses, we found a pattern suggestive of thinner cortex in precuneus and parietal areas in earlier-onset PCA, and lower cortical thickness in anterior cingulate and prefrontal cortex in later-onset PCA. These cortical thickness differences between PCA subgroups were consistent with earlier-onset PCA patients performing worse on cognitive tests involving parietal functions. Our results provide a suggestion that AAO may not only affect the clinico-anatomical characteristics in AD but may also affect atrophy patterns and cognition within atypical AD phenotypes. PMID:27318138

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

Performance of serum prostate-specific antigen isoform [-2]proPSA (p2PSA) and the prostate health index (PHI) in a Chinese hospital-based biopsy population.

PubMed

Na, Rong; Ye, Dingwei; Liu, Fang; Chen, Haitao; Qi, Jun; Wu, Yishuo; Zhang, Guiming; Wang, Meilin; Wang, Wenying; Sun, Jielin; Yu, Guopeng; Zhu, Yao; Ren, Shancheng; Zheng, S Lilly; Jiang, Haowen; Sun, Yinghao; Ding, Qiang; Xu, Jianfeng

2014-11-01

The use of serum [-2]proPSA (p2PSA) and its derivative, the prostate health index (PHI), in detecting prostate cancer (PCa) have been consistently shown to have better performance than total prostate-specific antigen (tPSA) in discriminating biopsy outcomes in western countries. However, little is known about their performance in Chinese men. Our objective is to test the performance of p2PSA and PHI and their added value to tPSA in discriminating biopsy outcomes in Chinese men. Consecutive patients who underwent prostate biopsy in three tertiary hospitals in Shanghai, China during 2012-2013 were recruited. Serum tPSA, free PSA (fPSA), and p2PSA were measured centrally using Beckman Coulter's DxI 800 Immunoassay System. The primary outcome is PCa and the secondary outcome is high-grade PCa (Gleason Score of 4 + 3 or worse). Discriminative performance was assessed using the area under the receiver operating characteristic curve (AUC), detection rate and Decision Curve Analysis (DCA). Among 636 patients who underwent prostate biopsy, PHI was a significant predictor of biopsy outcomes, independent of other clinical variables. The AUC in discriminating PCa from non-PCa was consistently higher for PHI than tPSA in the entire cohort (0.88 vs. 0.81) as well as in patients with tPSA at 2-10 ng/ml (0.73 vs. 0.53), at 10.1-20 ng/ml (0.81 vs. 0.58), and at tPSA >20 ng/ml (0.90 vs. 0.80). The differences were statistically significant in all comparisons, P < 0.01. To detect 90% of all PCa in the cohort, 362 and 457 patients would need to be biopsied based on PHI and tPSA cutoff, respectively, a 21% reduction for PHI. Similar results were found for discriminating high-grade PCa. PHI provides added value over tPSA in discriminating PCa and high-grade PCa in patients who underwent prostate biopsy in China. © 2014 Wiley Periodicals, Inc.

Epigenetics in prostate cancer: biologic and clinical relevance.

PubMed

Jerónimo, Carmen; Bastian, Patrick J; Bjartell, Anders; Carbone, Giuseppina M; Catto, James W F; Clark, Susan J; Henrique, Rui; Nelson, William G; Shariat, Shahrokh F

2011-10-01

Prostate cancer (PCa) is one of the most common human malignancies and arises through genetic and epigenetic alterations. Epigenetic modifications include DNA methylation, histone modifications, and microRNAs (miRNA) and produce heritable changes in gene expression without altering the DNA coding sequence. To review progress in the understanding of PCa epigenetics and to focus upon translational applications of this knowledge. PubMed was searched for publications regarding PCa and DNA methylation, histone modifications, and miRNAs. Reports were selected based on the detail of analysis, mechanistic support of data, novelty, and potential clinical applications. Aberrant DNA methylation (hypo- and hypermethylation) is the best-characterized alteration in PCa and leads to genomic instability and inappropriate gene expression. Global and locus-specific changes in chromatin remodeling are implicated in PCa, with evidence suggesting a causative dysfunction of histone-modifying enzymes. MicroRNA deregulation also contributes to prostate carcinogenesis, including interference with androgen receptor signaling and apoptosis. There are important connections between common genetic alterations (eg, E twenty-six fusion genes) and the altered epigenetic landscape. Owing to the ubiquitous nature of epigenetic alterations, they provide potential biomarkers for PCa detection, diagnosis, assessment of prognosis, and post-treatment surveillance. Altered epigenetic gene regulation is involved in the genesis and progression of PCa. Epigenetic alterations may provide valuable tools for the management of PCa patients and be targeted by pharmacologic compounds that reverse their nature. The potential for epigenetic changes in PCa requires further exploration and validation to enable translation to the clinic. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

PCA based clustering for brain tumor segmentation of T1w MRI images.

PubMed

Kaya, Irem Ersöz; Pehlivanlı, Ayça Çakmak; Sekizkardeş, Emine Gezmez; Ibrikci, Turgay

2017-03-01

Medical images are huge collections of information that are difficult to store and process consuming extensive computing time. Therefore, the reduction techniques are commonly used as a data pre-processing step to make the image data less complex so that a high-dimensional data can be identified by an appropriate low-dimensional representation. PCA is one of the most popular multivariate methods for data reduction. This paper is focused on T1-weighted MRI images clustering for brain tumor segmentation with dimension reduction by different common Principle Component Analysis (PCA) algorithms. Our primary aim is to present a comparison between different variations of PCA algorithms on MRIs for two cluster methods. Five most common PCA algorithms; namely the conventional PCA, Probabilistic Principal Component Analysis (PPCA), Expectation Maximization Based Principal Component Analysis (EM-PCA), Generalize Hebbian Algorithm (GHA), and Adaptive Principal Component Extraction (APEX) were applied to reduce dimensionality in advance of two clustering algorithms, K-Means and Fuzzy C-Means. In the study, the T1-weighted MRI images of the human brain with brain tumor were used for clustering. In addition to the original size of 512 lines and 512 pixels per line, three more different sizes, 256 × 256, 128 × 128 and 64 × 64, were included in the study to examine their effect on the methods. The obtained results were compared in terms of both the reconstruction errors and the Euclidean distance errors among the clustered images containing the same number of principle components. According to the findings, the PPCA obtained the best results among all others. Furthermore, the EM-PCA and the PPCA assisted K-Means algorithm to accomplish the best clustering performance in the majority as well as achieving significant results with both clustering algorithms for all size of T1w MRI images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Analyzing and modeling methods of near infrared spectroscopy for in-situ prediction of oil yield from oil shale].

PubMed

Liu, Jie; Zhang, Fu-Dong; Teng, Fei; Li, Jun; Wang, Zhi-Hong

2014-10-01

In order to in-situ detect the oil yield of oil shale, based on portable near infrared spectroscopy analytical technology, with 66 rock core samples from No. 2 well drilling of Fuyu oil shale base in Jilin, the modeling and analyzing methods for in-situ detection were researched. By the developed portable spectrometer, 3 data formats (reflectance, absorbance and K-M function) spectra were acquired. With 4 different modeling data optimization methods: principal component-mahalanobis distance (PCA-MD) for eliminating abnormal samples, uninformative variables elimination (UVE) for wavelength selection and their combina- tions: PCA-MD + UVE and UVE + PCA-MD, 2 modeling methods: partial least square (PLS) and back propagation artificial neural network (BPANN), and the same data pre-processing, the modeling and analyzing experiment were performed to determine the optimum analysis model and method. The results show that the data format, modeling data optimization method and modeling method all affect the analysis precision of model. Results show that whether or not using the optimization method, reflectance or K-M function is the proper spectrum format of the modeling database for two modeling methods. Using two different modeling methods and four different data optimization methods, the model precisions of the same modeling database are different. For PLS modeling method, the PCA-MD and UVE + PCA-MD data optimization methods can improve the modeling precision of database using K-M function spectrum data format. For BPANN modeling method, UVE, UVE + PCA-MD and PCA- MD + UVE data optimization methods can improve the modeling precision of database using any of the 3 spectrum data formats. In addition to using the reflectance spectra and PCA-MD data optimization method, modeling precision by BPANN method is better than that by PLS method. And modeling with reflectance spectra, UVE optimization method and BPANN modeling method, the model gets the highest analysis precision, its correlation coefficient (Rp) is 0.92, and its standard error of prediction (SEP) is 0.69%.

Kernel Principal Component Analysis for dimensionality reduction in fMRI-based diagnosis of ADHD.

PubMed

Sidhu, Gagan S; Asgarian, Nasimeh; Greiner, Russell; Brown, Matthew R G

2012-01-01

This study explored various feature extraction methods for use in automated diagnosis of Attention-Deficit Hyperactivity Disorder (ADHD) from functional Magnetic Resonance Image (fMRI) data. Each participant's data consisted of a resting state fMRI scan as well as phenotypic data (age, gender, handedness, IQ, and site of scanning) from the ADHD-200 dataset. We used machine learning techniques to produce support vector machine (SVM) classifiers that attempted to differentiate between (1) all ADHD patients vs. healthy controls and (2) ADHD combined (ADHD-c) type vs. ADHD inattentive (ADHD-i) type vs. controls. In different tests, we used only the phenotypic data, only the imaging data, or else both the phenotypic and imaging data. For feature extraction on fMRI data, we tested the Fast Fourier Transform (FFT), different variants of Principal Component Analysis (PCA), and combinations of FFT and PCA. PCA variants included PCA over time (PCA-t), PCA over space and time (PCA-st), and kernelized PCA (kPCA-st). Baseline chance accuracy was 64.2% produced by guessing healthy control (the majority class) for all participants. Using only phenotypic data produced 72.9% accuracy on two class diagnosis and 66.8% on three class diagnosis. Diagnosis using only imaging data did not perform as well as phenotypic-only approaches. Using both phenotypic and imaging data with combined FFT and kPCA-st feature extraction yielded accuracies of 76.0% on two class diagnosis and 68.6% on three class diagnosis-better than phenotypic-only approaches. Our results demonstrate the potential of using FFT and kPCA-st with resting-state fMRI data as well as phenotypic data for automated diagnosis of ADHD. These results are encouraging given known challenges of learning ADHD diagnostic classifiers using the ADHD-200 dataset (see Brown et al., 2012).

Monitoring of the posterior cricoarytenoid muscle represents another option for neural monitoring during thyroid surgery: Normative vagal and recurrent laryngeal nerve posterior cricoarytenoid muscle electromyographic data.

PubMed

Liddy, Whitney; Barber, Samuel R; Lin, Brian M; Kamani, Dipti; Kyriazidis, Natalia; Lawson, Bradley; Randolph, Gregory W

2018-01-01

Intraoperative neural monitoring (IONM) of laryngeal nerves using electromyography (EMG) is routinely performed using endotracheal tube surface electrodes adjacent to the vocalis muscles. Other laryngeal muscles such as the posterior cricoarytenoid muscle (PCA) are indirectly monitored. The PCA may be directly and reliably monitored through an electrode placed in the postcricoid region. Herein, we describe the method and normative data for IONM using PCA EMG. Retrospective review. Data were reviewed retrospectively for thyroid and parathyroid surgery patients with IONM of laryngeal nerves from January to August 2016. Recordings of vocalis and PCA EMG amplitudes and latencies with stimulation of laryngeal nerves were obtained using endotracheal (ET) tube-based and postcricoid surface electrodes. Data comprised EMG responses in vocalis and PCA recording channels with stimulation of the vagus, recurrent laryngeal nerve (RLN), and external branch of the superior laryngeal nerve from 20 subjects (11 left, 9 right), as well as PCA EMG threshold data with RLN stimulation from 17 subjects. Mean EMG amplitude was 725.69 ± 108.58 microvolts (µV) for the ipsilateral vocalis and 329.44 ± 34.12 µV for the PCA with vagal stimulation, and 1,059.75 ± 140.40 µV for the ipsilateral vocalis and 563.88 ± 116.08 µV for the PCA with RLN stimulation. There were no statistically significant differences in mean latency. For threshold cutoffs of the PCA with RLN stimulation, mean minimum and maximum threshold intensities were 0.37 milliamperes (mA) and 0.84 mA, respectively. This study shows robust and reliable PCA EMG waveforms with direct nerve stimulation. Further studies will evaluate feasibility and application of the PCA electrode as a complementary quantitative tool in IONM. 4. Laryngoscope, 128:283-289, 2018. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Epigenetics-related genes in prostate cancer: expression profile in prostate cancer tissues, androgen-sensitive and -insensitive cell lines.

PubMed

Shaikhibrahim, Zaki; Lindstrot, Andreas; Ochsenfahrt, Jacqueline; Fuchs, Kerstin; Wernert, Nicolas

2013-01-01

Epigenetic changes have been suggested to drive prostate cancer (PCa) development and progression. Therefore, in this study, we aimed to identify novel epigenetics-related genes in PCa tissues, and to examine their expression in metastatic PCa cell lines. We analyzed the expression of epigenetics-related genes via a clustering analysis based on gene function in moderately and poorly differentiated PCa glands compared to normal glands of the peripheral zone (prostate proper) from PCa patients using Whole Human Genome Oligo Microarrays. Our analysis identified 12 epigenetics-related genes with a more than 2-fold increase or decrease in expression and a p-value <0.01. In modera-tely differentiated tumors compared to normal glands of the peripheral zone, we found the genes, TDRD1, IGF2, DICER1, ADARB1, HILS1, GLMN and TRIM27, to be upregulated, whereas TNRC6A and DGCR8 were found to be downregulated. In poorly differentiated tumors, we found TDRD1, ADARB and RBM3 to be upregulated, whereas DGCR8, PIWIL2 and BC069781 were downregulated. Our analysis of the expression level for each gene in the metastatic androgen-sensitive VCaP and LNCaP, and -insensitive PC3 and DU-145 PCa cell lines revealed differences in expression among the cell lines which may reflect the different biological properties of each cell line, and the potential role of each gene at different metastatic sites. The novel epigenetics-related genes that we identified in primary PCa tissues may provide further insight into the role that epigenetic changes play in PCa. Moreover, some of the genes that we identified may play important roles in primary PCa and metastasis, in primary PCa only, or in metastasis only. Follow-up studies are required to investigate the functional role and the role that the expression of these genes play in the outcome and progression of PCa using tissue microarrays.

PBOV1 as a potential biomarker for more advanced prostate cancer based on protein and digital histomorphometric analysis.

PubMed

Carleton, Neil M; Zhu, Guangjing; Gorbounov, Mikhail; Miller, M Craig; Pienta, Kenneth J; Resar, Linda M S; Veltri, Robert W

2018-05-01

There are few tissue-based biomarkers that can accurately predict prostate cancer (PCa) progression and aggressiveness. We sought to evaluate the clinical utility of prostate and breast overexpressed 1 (PBOV1) as a potential PCa biomarker. Patient tumor samples were designated by Grade Groups using the 2014 Gleason grading system. Primary radical prostatectomy tumors were obtained from 48 patients and evaluated for PBOV1 levels using Western blot analysis in matched cancer and benign cancer-adjacent regions. Immunohistochemical evaluation of PBOV1 was subsequently performed in 80 cancer and 80 benign cancer-adjacent patient samples across two tissue microarrays (TMAs) to verify protein levels in epithelial tissue and to assess correlation between PBOV1 proteins and nuclear architectural changes in PCa cells. Digital histomorphometric analysis was used to track 22 parameters that characterized nuclear changes in PBOV1-stained cells. Using a training and test set for validation, multivariate logistic regression (MLR) models were used to identify significant nuclear parameters that distinguish Grade Group 3 and above PCa from Grade Group 1 and 2 PCa regions. PBOV1 protein levels were increased in tumors from Grade Group 3 and above (GS 4 + 3 and ≥ 8) regions versus Grade Groups 1 and 2 (GS 3 + 3 and 3 + 4) regions (P = 0.005) as assessed by densitometry of immunoblots. Additionally, by immunoblotting, PBOV1 protein levels differed significantly between Grade Group 2 (GS 3 + 4) and Grade Group 3 (GS 4 + 3) PCa samples (P = 0.028). In the immunohistochemical analysis, measures of PBOV1 staining intensity strongly correlated with nuclear alterations in cancer cells. An MLR model retaining eight parameters describing PBOV1 staining intensity and nuclear architecture discriminated Grade Group 3 and above PCa from Grade Group 1 and 2 PCa and benign cancer-adjacent regions with a ROC-AUC of 0.90 and 0.80, respectively, in training and test sets. Our study demonstrates that the PBOV1 protein could be used to discriminate Grade Group 3 and above PCa. Additionally, the PBOV1 protein could be involved in modulating changes to the nuclear architecture of PCa cells. Confirmatory studies are warranted in an independent population for further validation. © 2018 Wiley Periodicals, Inc.

Satisfaction with Life Scale (SWLS) in Caregivers of Clinically-Referred Youth: Psychometric Properties and Mediation Analysis

PubMed Central

Athay, M. Michele

2012-01-01

This paper presents the psychometric evaluation of the Satisfaction with Life Scale (SWLS; Diener, Emmons, Larson & Griffen, 1985) used with a large sample (N = 610) of caregivers for youth receiving mental health services. Methods from classical test theory, factor analysis and item response theory are utilized. Additionally, this paper investigates whether caregiver strain mediates the effect of youth symptom severity on caregiver life satisfaction (N = 356). Bootstrapped confidence intervals are used to determine the significance of the mediated effects. Results indicate that the SWLS is a psychometrically sound instrument to be used with caregivers of clinically-referred youth. Mediation analyses found that the effect of youth symptom severity on caregiver life satisfaction is mediated by caregiver strain but that the mediation effect differs based on the type of youth symptoms. Caregiver strain is a partial mediator when externalizing symptoms are measured and a full mediator when internalizing symptoms are measured. Implications for future research and clinical practice are discussed. PMID:22407554

Inadequacy of Conventional Grab Sampling for Remediation Decision-Making for Metal Contamination at Small-Arms Ranges.

PubMed

Clausen, J L; Georgian, T; Gardner, K H; Douglas, T A

2018-01-01

Research shows grab sampling is inadequate for evaluating military ranges contaminated with energetics because of their highly heterogeneous distribution. Similar studies assessing the heterogeneous distribution of metals at small-arms ranges (SAR) are lacking. To address this we evaluated whether grab sampling provides appropriate data for performing risk analysis at metal-contaminated SARs characterized with 30-48 grab samples. We evaluated the extractable metal content of Cu, Pb, Sb, and Zn of the field data using a Monte Carlo random resampling with replacement (bootstrapping) simulation approach. Results indicate the 95% confidence interval of the mean for Pb (432 mg/kg) at one site was 200-700 mg/kg with a data range of 5-4500 mg/kg. Considering the U.S. Environmental Protection Agency screening level for lead is 400 mg/kg, the necessity of cleanup at this site is unclear. Resampling based on populations of 7 and 15 samples, a sample size more realistic for the area yielded high false negative rates.

An index of effluent aquatic toxicity designed by partial least squares regression, using acute and chronic tests and expert judgements.

PubMed

Vindimian, Éric; Garric, Jeanne; Flammarion, Patrick; Thybaud, Éric; Babut, Marc

1999-10-01

The evaluation of the ecotoxicity of effluents requires a battery of biological tests on several species. In order to derive a summary parameter from such a battery, a single endpoint was calculated for all the tests: the EC10, obtained by nonlinear regression, with bootstrap evaluation of the confidence intervals. Principal component analysis was used to characterize and visualize the correlation between the tests. The table of the toxicity of the effluents was then submitted to a panel of experts, who classified the effluents according to the test results. Partial least squares (PLS) regression was used to fit the average value of the experts' judgements to the toxicity data, using a simple equation. Furthermore, PLS regression on partial data sets and other considerations resulted in an optimum battery, with two chronic tests and one acute test. The index is intended to be used for the classification of effluents based on their toxicity to aquatic species. Copyright © 1999 SETAC.

An index of effluent aquatic toxicity designed by partial least squares regression, using acute and chronic tests and expert judgments

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

Vindimian, E.; Garric, J.; Flammarion, P.

1999-10-01

The evaluation of the ecotoxicity of effluents requires a battery of biological tests on several species. In order to derive a summary parameter from such a battery, a single endpoint was calculated for all the tests: the EC10, obtained by nonlinear regression, with bootstrap evaluation of the confidence intervals. Principal component analysis was used to characterize and visualize the correlation between the tests. The table of the toxicity of the effluents was then submitted to a panel of experts, who classified the effluents according to the test results. Partial least squares (PLS) regression was used to fit the average valuemore » of the experts' judgments to the toxicity data, using a simple equation. Furthermore, PLS regression on partial data sets and other considerations resulted in an optimum battery, with two chronic tests and one acute test. The index is intended to be used for the classification of effluents based on their toxicity to aquatic species.« less

Study of recognizing multiple persons' complicated hand gestures from the video sequence acquired by a moving camera

NASA Astrophysics Data System (ADS)

Dan, Luo; Ohya, Jun

2010-02-01

Recognizing hand gestures from the video sequence acquired by a dynamic camera could be a useful interface between humans and mobile robots. We develop a state based approach to extract and recognize hand gestures from moving camera images. We improved Human-Following Local Coordinate (HFLC) System, a very simple and stable method for extracting hand motion trajectories, which is obtained from the located human face, body part and hand blob changing factor. Condensation algorithm and PCA-based algorithm was performed to recognize extracted hand trajectories. In last research, this Condensation Algorithm based method only applied for one person's hand gestures. In this paper, we propose a principal component analysis (PCA) based approach to improve the recognition accuracy. For further improvement, temporal changes in the observed hand area changing factor are utilized as new image features to be stored in the database after being analyzed by PCA. Every hand gesture trajectory in the database is classified into either one hand gesture categories, two hand gesture categories, or temporal changes in hand blob changes. We demonstrate the effectiveness of the proposed method by conducting experiments on 45 kinds of sign language based Japanese and American Sign Language gestures obtained from 5 people. Our experimental recognition results show better performance is obtained by PCA based approach than the Condensation algorithm based method.

Automated Detection of Clinically Significant Prostate Cancer in mp-MRI Images Based on an End-to-End Deep Neural Network.

PubMed

Wang, Zhiwei; Liu, Chaoyue; Cheng, Danpeng; Wang, Liang; Yang, Xin; Cheng, Kwang-Ting

2018-05-01

Automated methods for detecting clinically significant (CS) prostate cancer (PCa) in multi-parameter magnetic resonance images (mp-MRI) are of high demand. Existing methods typically employ several separate steps, each of which is optimized individually without considering the error tolerance of other steps. As a result, they could either involve unnecessary computational cost or suffer from errors accumulated over steps. In this paper, we present an automated CS PCa detection system, where all steps are optimized jointly in an end-to-end trainable deep neural network. The proposed neural network consists of concatenated subnets: 1) a novel tissue deformation network (TDN) for automated prostate detection and multimodal registration and 2) a dual-path convolutional neural network (CNN) for CS PCa detection. Three types of loss functions, i.e., classification loss, inconsistency loss, and overlap loss, are employed for optimizing all parameters of the proposed TDN and CNN. In the training phase, the two nets mutually affect each other and effectively guide registration and extraction of representative CS PCa-relevant features to achieve results with sufficient accuracy. The entire network is trained in a weakly supervised manner by providing only image-level annotations (i.e., presence/absence of PCa) without exact priors of lesions' locations. Compared with most existing systems which require supervised labels, e.g., manual delineation of PCa lesions, it is much more convenient for clinical usage. Comprehensive evaluation based on fivefold cross validation using 360 patient data demonstrates that our system achieves a high accuracy for CS PCa detection, i.e., a sensitivity of 0.6374 and 0.8978 at 0.1 and 1 false positives per normal/benign patient.

Statistical inference for tumor growth inhibition T/C ratio.

PubMed

Wu, Jianrong

2010-09-01

The tumor growth inhibition T/C ratio is commonly used to quantify treatment effects in drug screening tumor xenograft experiments. The T/C ratio is converted to an antitumor activity rating using an arbitrary cutoff point and often without any formal statistical inference. Here, we applied a nonparametric bootstrap method and a small sample likelihood ratio statistic to make a statistical inference of the T/C ratio, including both hypothesis testing and a confidence interval estimate. Furthermore, sample size and power are also discussed for statistical design of tumor xenograft experiments. Tumor xenograft data from an actual experiment were analyzed to illustrate the application.

Bedside ROP screening and telemedicine interpretation integrated to a neonatal transport system: Economic aspects and return on investment analysis.

PubMed

Kovács, Gábor; Somogyvári, Zsolt; Maka, Erika; Nagyjánosi, László

Peter Cerny Ambulance Service - Premature Eye Rescue Program (PCA-PERP) uses digital retinal imaging (DRI) with remote interpretation in bedside ROP screening, which has advantages over binocular indirect ophthalmoscopy (BIO) in screening of premature newborns. We aimed to demonstrate that PCA-PERP provides good value for the money and to model the cost ramifications of a similar newly launched system. As DRI was demonstrated to have high diagnostic performance, only the costs of bedside DRI-based screening were compared to those of traditional transport and BIO-based screening (cost-minimization analysis). The total costs of investment and maintenance were analyzed with micro-costing method. A ten-year analysis time-horizon and service provider's perspective were applied. From the launch of PCA-PERP up to the end of 2014, 3722 bedside examinations were performed in the PCA covered central region of Hungary. From 2009 to 2014, PCA-PERP saved 92,248km and 3633 staff working hours, with an annual nominal cost-savings ranging from 17,435 to 35,140 Euro. The net present value was 127,847 Euro at the end of 2014, with a payback period of 4.1years and an internal rate of return of 20.8%. Our model presented the NPVs of different scenarios with different initial investments, annual number of transports and average transport distances. PCA-PERP as bedside screening with remote interpretation, when compared to a transport-based screening with BIO, produced better cost-savings from the perspective of the service provider and provided a return on initial investment within five years after the project initiation. Copyright © 2017 Elsevier B.V. All rights reserved.

Germline Missense Variants in the BTNL2 Gene Are Associated with Prostate Cancer Susceptibility

PubMed Central

FitzGerald, Liesel M.; Kumar, Akash; Boyle, Evan A.; Zhang, Yuzheng; McIntosh, Laura M.; Kolb, Suzanne; Stott-Miller, Marni; Smith, Tiffany; Karyadi, Danielle M.; Ostrander, Elaine A.; Hsu, Li; Shendure, Jay; Stanford, Janet L.

2013-01-01

Background Rare, inherited mutations account for 5%–10% of all prostate cancer (PCa) cases. However, to date, few causative mutations have been identified. Methods To identify rare mutations for PCa, we performed whole-exome sequencing (WES) in multiple kindreds (n = 91) from 19 hereditary prostate cancer (HPC) families characterized by aggressive or early onset phenotypes. Candidate variants (n = 130) identified through family- and bioinformatics-based filtering of WES data were then genotyped in an independent set of 270 HPC families (n = 819 PCa cases; n = 496 unaffected relatives) for replication. Two variants with supportive evidence were subsequently genotyped in a population-based case-control study (n = 1,155 incident PCa cases; n = 1,060 age-matched controls) for further confirmation. All participants were men of European ancestry. Results The strongest evidence was for two germline missense variants in the butyrophilin-like 2 (BTNL2) gene (rs41441651, p.Asp336Asn and rs28362675, p.Gly454Cys) that segregated with affection status in two of the WES families. In the independent set of 270 HPC families, 1.5% (rs41441651; P = 0.0032) and 1.2% (rs28362675; P = 0.0070) of affected men, but no unaffected men, carried a variant. Both variants were associated with elevated PCa risk in the population-based study (rs41441651: OR = 2.7; 95% CI, 1.27–5.87; P = 0.010; rs28362675: OR = 2.5; 95% CI, 1.16–5.46; P = 0.019). Conclusions Results indicate that rare BTNL2 variants play a role in susceptibility to both familial and sporadic prostate cancer. Impact Results implicate BTNL2 as a novel PCa susceptibility gene. PMID:23833122

Prevalence of the HOXB13 G84E mutation in Danish men undergoing radical prostatectomy and its correlations with prostate cancer risk and aggressiveness.

PubMed

Storebjerg, Tine M; Høyer, Søren; Kirkegaard, Pia; Bro, Flemming; Ørntoft, Torben F; Borre, Michael; Sørensen, Karina D

2016-10-01

To determine the prevalence of the HOXB13 G84E mutation (rs138213197) in Danish men with or without prostate cancer (PCa) and to investigate possible correlations between HOXB13 mutation status and clinicopathological characteristics associated with tumour aggressiveness. We conducted a case-control study including 995 men with PCa (cases) who underwent radical prostatectomy (RP) between 1997 and 2011 at the Department of Urology, Aarhus University Hospital, Denmark. As controls, we used 1622 healthy men with a normal prostate specific antigen (PSA) level. The HOXB13 G84E mutation was identified in 0.49% of controls and in 2.51% of PCa cases. The mutation was associated with a 5.12-fold increased relative risk (RR) of PCa (95% confidence interval [CI] 2.26-13.38; P = 13 × 10(-6) ). Furthermore, carriers of the risk allele were significantly more likely to have a higher PSA level at diagnosis (mean PSA 19.9 vs 13.6 ng/mL; P = 0.032), a pathological Gleason score ≥7 (83.3 vs 60.9%; P = 0.032), and positive surgical margins (56.0 vs 28.5%; P = 0.006) than non-carriers. Risk allele carriers were also more likely to have aggressive disease (54.2 vs 28.6%; P = 0.011), as defined by a preoperative PSA ≥20 ng/mL, pathological Gleason score ≥ (4+3) and/or presence of regional/distant disease. At a mean follow-up of 7 months, we found no significant association between HOXB13 mutation status and biochemical recurrence in this cohort of men who underwent RP. This is the first study to investigate the HOXB13 G84E mutation in Danish men. The mutation was detected in 0.49% of controls and in 2.51% of cases, and was associated with 5.12-fold increased RR of being diagnosed with PCa. In our RP cohort, HOXB13 mutation carriers were more likely to develop aggressive PCa. Further studies are needed to assess the potential of HOXB13 for future targeted screening approaches. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.

Comorbidity structure of psychological disorders in the online e-PASS data as predictors of psychosocial adjustment measures: psychological distress, adequate social support, self-confidence, quality of life, and suicidal ideation.

PubMed

Al-Asadi, Ali M; Klein, Britt; Meyer, Denny

2014-10-28

A relative newcomer to the field of psychology, e-mental health has been gaining momentum and has been given considerable research attention. Although several aspects of e-mental health have been studied, 1 aspect has yet to receive attention: the structure of comorbidity of psychological disorders and their relationships with measures of psychosocial adjustment including suicidal ideation in online samples. This exploratory study attempted to identify the structure of comorbidity of 21 psychological disorders assessed by an automated online electronic psychological assessment screening system (e-PASS). The resulting comorbidity factor scores were then used to assess the association between comorbidity factor scores and measures of psychosocial adjustments (ie, psychological distress, suicidal ideation, adequate social support, self-confidence in dealing with mental health issues, and quality of life). A total of 13,414 participants were assessed using a complex online algorithm that resulted in primary and secondary Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) diagnoses for 21 psychological disorders on dimensional severity scales. The scores on these severity scales were used in a principal component analysis (PCA) and the resulting comorbidity factor scores were related to 4 measures of psychosocial adjustments. A PCA based on 17 of the 21 psychological disorders resulted in a 4-factor model of comorbidity: anxiety-depression consisting of all anxiety disorders, major depressive episode (MDE), and insomnia; substance abuse consisting of alcohol and drug abuse and dependency; body image-eating consisting of eating disorders, body dysmorphic disorder, and obsessive-compulsive disorders; depression-sleep problems consisting of MDE, insomnia, and hypersomnia. All comorbidity factor scores were significantly associated with psychosocial measures of adjustment (P<.001). They were positively related to psychological distress and suicidal ideation, but negatively related to adequate social support, self-confidence, and quality of life. This exploratory study identified 4 comorbidity factors in the e-PASS data and these factor scores significantly predicted 5 psychosocial adjustment measures. Australian and New Zealand Clinical Trials Registry ACTRN121611000704998; http://www.anzctr.org.au/trial_view.aspx?ID=336143 (Archived by WebCite at http://www.webcitation.org/618r3wvOG).

Comorbidity Structure of Psychological Disorders in the Online e-PASS Data as Predictors of Psychosocial Adjustment Measures: Psychological Distress, Adequate Social Support, Self-Confidence, Quality of Life, and Suicidal Ideation

PubMed Central

Klein, Britt; Meyer, Denny

2014-01-01

Background A relative newcomer to the field of psychology, e-mental health has been gaining momentum and has been given considerable research attention. Although several aspects of e-mental health have been studied, 1 aspect has yet to receive attention: the structure of comorbidity of psychological disorders and their relationships with measures of psychosocial adjustment including suicidal ideation in online samples. Objective This exploratory study attempted to identify the structure of comorbidity of 21 psychological disorders assessed by an automated online electronic psychological assessment screening system (e-PASS). The resulting comorbidity factor scores were then used to assess the association between comorbidity factor scores and measures of psychosocial adjustments (ie, psychological distress, suicidal ideation, adequate social support, self-confidence in dealing with mental health issues, and quality of life). Methods A total of 13,414 participants were assessed using a complex online algorithm that resulted in primary and secondary Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) diagnoses for 21 psychological disorders on dimensional severity scales. The scores on these severity scales were used in a principal component analysis (PCA) and the resulting comorbidity factor scores were related to 4 measures of psychosocial adjustments. Results A PCA based on 17 of the 21 psychological disorders resulted in a 4-factor model of comorbidity: anxiety-depression consisting of all anxiety disorders, major depressive episode (MDE), and insomnia; substance abuse consisting of alcohol and drug abuse and dependency; body image–eating consisting of eating disorders, body dysmorphic disorder, and obsessive-compulsive disorders; depression–sleep problems consisting of MDE, insomnia, and hypersomnia. All comorbidity factor scores were significantly associated with psychosocial measures of adjustment (P<.001). They were positively related to psychological distress and suicidal ideation, but negatively related to adequate social support, self-confidence, and quality of life. Conclusions This exploratory study identified 4 comorbidity factors in the e-PASS data and these factor scores significantly predicted 5 psychosocial adjustment measures. Trial Registration Australian and New Zealand Clinical Trials Registry ACTRN121611000704998; http://www.anzctr.org.au/trial_view.aspx?ID=336143 (Archived by WebCite at http://www.webcitation.org/618r3wvOG). PMID:25351885

The Role of Proteomics in Biomarker Development for Improved Patient Diagnosis and Clinical Decision Making in Prostate Cancer

PubMed Central

Tonry, Claire L.; Leacy, Emma; Raso, Cinzia; Finn, Stephen P.; Armstrong, John; Pennington, Stephen R.

2016-01-01

Prostate Cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA) is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i) might best receive no treatment (active surveillance of the disease); (ii) would benefit from existing treatments; or (iii) those who are likely to succumb to disease recurrence and/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i) provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii) address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii) make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making. PMID:27438858

Real World Evidence: A Quantitative and Qualitative Glance at Participant Feedback from a Free-Response Survey Investigating Experiences of a Structured Exercise Intervention for Men with Prostate Cancer

PubMed Central

Cahill, F.; Burgess, C.; Peat, N.; Rudman, S.; Kinsella, J.; Cahill, D.; George, G.; Santaolalla, A.; Van Hemelrijck, M.

2017-01-01

Aim To explore patient experiences of a structured exercise intervention for men with prostate cancer (PCa). Sample 41 men with either localised or advanced PCa who had been referred for a structured exercise programme by their physician and then subsequently consented to a telephone survey. Method Participants underwent a 10-week supervised exercise programme within a large cancer centre hospital consisting of 8 sessions. They then completed a short multiple choice telephone survey, elaborating on their responses where appropriate. Views expressed by participants were analysed using an affinity diagram and common themes were identified. Results Feedback from our telephone surveys was consistently positive and suggests that the structured exercise intervention provides exercise confidence, motivation to exercise, and social support and promotes positive health behaviour change in the context of exercise. Individual differences arose amongst participants in their perceived utility of the intervention, with 73.3% expressing a preference for structured exercise classes and 19.5% expressing a preference for exercising independently. Conclusion Design of a structured exercise intervention for patients with PCa should embrace the positive aspects outlined here but consider patients' individual differences. Ongoing feedback from patients should be utilised alongside traditional study designs to inform intervention design in this area. PMID:28758113

Serum markers for prostate cancer: a rational approach to the literature.

PubMed

Steuber, Thomas; O'Brien, Matthew Frank; Lilja, Hans

2008-07-01

Due to its universal applicability for early detection and prediction of cancer stage and disease recurrence, widespread implementation of serum-based prostate-specific antigen (PSA) measurements has a significant influence on current treatment strategies for men with prostate cancer (PCa). However, over-detection and the resultant over-treatment of indolent cancers have been strongly implicated to occur. Using current recommended guidelines, the PSA test suffers from both limited sensitivity and specificity to enable efficacious population-based cancer detection. Therefore, novel biomarkers are much needed to complement PSA by enhancing its diagnostic and prognostic performance. The present literature on serum markers for PCa was reviewed. PSA derivatives, molecular PSA isoforms, and novel molecular targets in blood were summarized and weighted against their potential to improve decision-making of men with PCa. Current evidence suggests that no single analyte is likely to achieve the desired level of diagnostic and prognostic accuracy for PCa. However, the combination of biomarkers with clinical and demographic data, for example, using established standard nomograms, has produced progress toward the goal of both optimal screening and risk assessment. Furthermore, potential candidate molecular markers for PCa can be derived from high-throughput technologies. Current studies demonstrate that understanding dynamic PSA changes over time may offer diagnostic and prognostic information. Bridging the gap between basic science and clinical practice represents the main goal in the near future to enable physicians to tailor risk-adjusted screening and treatment strategies for current patients with PCa.

Identifying natural and anthropogenic sources of metals in urban and rural soils using GIS-based data, PCA, and spatial interpolation

PubMed Central

Davis, Harley T.; Aelion, C. Marjorie; McDermott, Suzanne; Lawson, Andrew B.

2009-01-01

Determining sources of neurotoxic metals in rural and urban soils is important for mitigating human exposure. Surface soil from four areas with significant clusters of mental retardation and developmental delay (MR/DD) in children, and one control site were analyzed for nine metals and characterized by soil type, climate, ecological region, land use and industrial facilities using readily-available GIS-based data. Kriging, principal component analysis (PCA) and cluster analysis (CA) were used to identify commonalities of metal distribution. Three MR/DD areas (one rural and two urban) had similar soil types and significantly higher soil metal concentrations. PCA and CA results suggested that Ba, Be and Mn were consistently from natural sources; Pb and Hg from anthropogenic sources; and As, Cr, Cu, and Ni from both sources. Arsenic had low commonality estimates, was highly associated with a third PCA factor, and had a complex distribution, complicating mitigation strategies to minimize concentrations and exposures. PMID:19361902

Emory University: Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

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

Tucker, Susan L.; Liu, H. Helen; Wang, Shulian

Purpose: The aim of this study was to investigate the effect of radiation dose distribution in the lung on the risk of postoperative pulmonary complications among esophageal cancer patients. Methods and Materials: We analyzed data from 110 patients with esophageal cancer treated with concurrent chemoradiotherapy followed by surgery at our institution from 1998 to 2003. The endpoint for analysis was postsurgical pneumonia or acute respiratory distress syndrome. Dose-volume histograms (DVHs) and dose-mass histograms (DMHs) for the whole lung were used to fit normal-tissue complication probability (NTCP) models, and the quality of fits were compared using bootstrap analysis. Results: Normal-tissue complicationmore » probability modeling identified that the risk of postoperative pulmonary complications was most significantly associated with small absolute volumes of lung spared from doses {>=}5 Gy (VS5), that is, exposed to doses <5 Gy. However, bootstrap analysis found no significant difference between the quality of this model and fits based on other dosimetric parameters, including mean lung dose, effective dose, and relative volume of lung receiving {>=}5 Gy, probably because of correlations among these factors. The choice of DVH vs. DMH or the use of fractionation correction did not significantly affect the results of the NTCP modeling. The parameter values estimated for the Lyman NTCP model were as follows (with 95% confidence intervals in parentheses): n = 1.85 (0.04, {infinity}), m = 0.55 (0.22, 1.02), and D {sub 5} = 17.5 Gy (9.4 Gy, 102 Gy). Conclusions: In this cohort of esophageal cancer patients, several dosimetric parameters including mean lung dose, effective dose, and absolute volume of lung receiving <5 Gy provided similar descriptions of the risk of postoperative pulmonary complications as a function of Radiation dose distribution in the lung.« less

Development of a prognostic nomogram for cirrhotic patients with upper gastrointestinal bleeding.

PubMed

Zhou, Yu-Jie; Zheng, Ji-Na; Zhou, Yi-Fan; Han, Yi-Jing; Zou, Tian-Tian; Liu, Wen-Yue; Braddock, Martin; Shi, Ke-Qing; Wang, Xiao-Dong; Zheng, Ming-Hua

2017-10-01

Upper gastrointestinal bleeding (UGIB) is a complication with a high mortality rate in critically ill patients presenting with cirrhosis. Today, there exist few accurate scoring models specifically designed for mortality risk assessment in critically ill cirrhotic patients with upper gastrointestinal bleeding (CICGIB). Our aim was to develop and evaluate a novel nomogram-based model specific for CICGIB. Overall, 540 consecutive CICGIB patients were enrolled. On the basis of Cox regression analyses, the nomogram was constructed to estimate the probability of 30-day, 90-day, 270-day, and 1-year survival. An upper gastrointestinal bleeding-chronic liver failure-sequential organ failure assessment (UGIB-CLIF-SOFA) score was derived from the nomogram. Performance assessment and internal validation of the model were performed using Harrell's concordance index (C-index), calibration plot, and bootstrap sample procedures. UGIB-CLIF-SOFA was also compared with other prognostic models, such as CLIF-SOFA and model for end-stage liver disease, using C-indices. Eight independent factors derived from Cox analysis (including bilirubin, creatinine, international normalized ratio, sodium, albumin, mean artery pressure, vasopressin used, and hematocrit decrease>10%) were assembled into the nomogram and the UGIB-CLIF-SOFA score. The calibration plots showed optimal agreement between nomogram prediction and actual observation. The C-index of the nomogram using bootstrap (0.729; 95% confidence interval: 0.689-0.766) was higher than that of the other models for predicting survival of CICGIB. We have developed and internally validated a novel nomogram and an easy-to-use scoring system that accurately predicts the mortality probability of CICGIB on the basis of eight easy-to-obtain parameters. External validation is now warranted in future clinical studies.

Identifying Emergency Department Patients at Low Risk for a Variceal Source of Upper Gastrointestinal Hemorrhage.

PubMed

Klein, Lauren R; Money, Joel; Maharaj, Kaveesh; Robinson, Aaron; Lai, Tarissa; Driver, Brian E

2017-11-01

Assessing the likelihood of a variceal versus nonvariceal source of upper gastrointestinal bleeding (UGIB) guides therapy, but can be difficult to determine on clinical grounds. The objective of this study was to determine if there are easily ascertainable clinical and laboratory findings that can identify a patient as low risk for a variceal source of hemorrhage. This was a retrospective cohort study of adult ED patients with UGIB between January 2008 and December 2014 who had upper endoscopy performed during hospitalization. Clinical and laboratory data were abstracted from the medical record. The source of the UGIB was defined as variceal or nonvariceal based on endoscopic reports. Binary recursive partitioning was utilized to create a clinical decision rule. The rule was internally validated and test characteristics were calculated with 1,000 bootstrap replications. A total of 719 patients were identified; mean age was 55 years and 61% were male. There were 71 (10%) patients with a variceal UGIB identified on endoscopy. Binary recursive partitioning yielded a two-step decision rule (platelet count > 200 × 10 9 /L and an international normalized ratio [INR] < 1.3), which identified patients who were low risk for a variceal source of hemorrhage. For the bootstrapped samples, the rule performed with 97% sensitivity (95% confidence interval [CI] = 91%-100%) and 49% specificity (95% CI = 44%-53%). Although this derivation study must be externally validated before widespread use, patients presenting to the ED with an acute UGIB with platelet count of >200 × 10 9 /L and an INR of <1.3 may be at very low risk for a variceal source of their upper gastrointestinal hemorrhage. © 2017 by the Society for Academic Emergency Medicine.

Novel CPR system that predicts return of spontaneous circulation from amplitude spectral area before electric shock in ventricular fibrillation.

PubMed

Nakagawa, Yoshihide; Amino, Mari; Inokuchi, Sadaki; Hayashi, Satoshi; Wakabayashi, Tsutomu; Noda, Tatsuya

2017-04-01

Amplitude spectral area (AMSA), an index for analysing ventricular fibrillation (VF) waveforms, is thought to predict the return of spontaneous circulation (ROSC) after electric shocks, but its validity is unconfirmed. We developed an equation to predict ROSC, where the change in AMSA (ΔAMSA) is added to AMSA measured immediately before the first shock (AMSA1). We examine the validity of this equation by comparing it with the conventional AMSA1-only equation. We retrospectively investigated 285 VF patients given prehospital electric shocks by emergency medical services. ΔAMSA was calculated by subtracting AMSA1 from last AMSA immediately before the last prehospital electric shock. Multivariate logistic regression analysis was performed using post-shock ROSC as a dependent variable. Analysis data were subjected to receiver operating characteristic curve analysis, goodness-of-fit testing using a likelihood ratio test, and the bootstrap method. AMSA1 (odds ratio (OR) 1.151, 95% confidence interval (CI) 1.086-1.220) and ΔAMSA (OR 1.289, 95% CI 1.156-1.438) were independent factors influencing ROSC induction by electric shock. Area under the curve (AUC) for predicting ROSC was 0.851 for AMSA1-only and 0.891 for AMSA1+ΔAMSA. Compared with the AMSA1-only equation, the AMSA1+ΔAMSA equation had significantly better goodness-of-fit (likelihood ratio test P<0.001) and showed good fit in the bootstrap method. Post-shock ROSC was accurately predicted by adding ΔAMSA to AMSA1. AMSA-based ROSC prediction enables application of electric shock to only those patients with high probability of ROSC, instead of interrupting chest compressions and delivering unnecessary shocks to patients with low probability of ROSC. Copyright © 2017 Elsevier B.V. All rights reserved.

Clinical Risk Index for Babies score for the prediction of neurodevelopmental outcomes at 3 years of age in infants of very low birthweight.

PubMed

Lodha, Abhay; Sauvé, Reg; Chen, Sophie; Tang, Selphee; Christianson, Heather

2009-11-01

In this study, we evaluated the Clinical Risk Index for Babies - revised (CRIB-II) score as a predictor of long-term neurodevelopmental outcomes in preterm infants at 36 months' corrected age. CRIB-II scores, which include birthweight, gestational age, sex, admission temperature, and base excess, were recorded prospectively on all infants weighing 1250g or less admitted to the neonatal intensive care unit (NICU). The sensitivity and specificity of CRIB-II scores to predict poor outcomes were examined using receiver operating characteristic curves, and predictive accuracy was assessed using the area under the curve (AUC), based on the observed values entered on a continuous scale. Poor outcomes were defined as death or major neurodevelopmental disability (cerebral palsy, neurosensory hearing loss requiring amplification, legal blindness, severe seizure disorder, or cognitive score >2SD below the mean for adjusted age determined by clinical neurological examination and on the Wechsler Preschool and Primary Scale of Intelligence, Bayley Scales of Infant Development, or revised Leiter International Performance Scale). Of the 180 infants admitted to the NICU, 155 survived. Complete follow-up data were available for 107 children. The male:female ratio was 50:57 (47-53%), median birthweight was 930g (range 511-1250g), and median gestational age was 27 weeks (range 23-32wks). Major neurodevelopmental impairment was observed in 11.2% of participants. In a regression model, the CRIB-II score was significantly correlated with long-term neurodevelopmental outcomes. It predicted major neurodevelopmental impairment (odds ratio [OR] 1.57, bootstrap 95% confidence interval [CI] 1.26-3.01; AUC 0.84) and poor outcome (OR 1.46; bootstrap 95% CI 1.31-1.71, AUC 0.82) at 36 months' corrected age. CRIB-II scores of 13 or more in the first hour of life can reliably predict major neurodevelopmental impairment at 36 months' corrected age (sensitivity 83%; specificity 84%).

A Bayesian taxonomic classification method for 16S rRNA gene sequences with improved species-level accuracy.

PubMed

Gao, Xiang; Lin, Huaiying; Revanna, Kashi; Dong, Qunfeng

2017-05-10

Species-level classification for 16S rRNA gene sequences remains a serious challenge for microbiome researchers, because existing taxonomic classification tools for 16S rRNA gene sequences either do not provide species-level classification, or their classification results are unreliable. The unreliable results are due to the limitations in the existing methods which either lack solid probabilistic-based criteria to evaluate the confidence of their taxonomic assignments, or use nucleotide k-mer frequency as the proxy for sequence similarity measurement. We have developed a method that shows significantly improved species-level classification results over existing methods. Our method calculates true sequence similarity between query sequences and database hits using pairwise sequence alignment. Taxonomic classifications are assigned from the species to the phylum levels based on the lowest common ancestors of multiple database hits for each query sequence, and further classification reliabilities are evaluated by bootstrap confidence scores. The novelty of our method is that the contribution of each database hit to the taxonomic assignment of the query sequence is weighted by a Bayesian posterior probability based upon the degree of sequence similarity of the database hit to the query sequence. Our method does not need any training datasets specific for different taxonomic groups. Instead only a reference database is required for aligning to the query sequences, making our method easily applicable for different regions of the 16S rRNA gene or other phylogenetic marker genes. Reliable species-level classification for 16S rRNA or other phylogenetic marker genes is critical for microbiome research. Our software shows significantly higher classification accuracy than the existing tools and we provide probabilistic-based confidence scores to evaluate the reliability of our taxonomic classification assignments based on multiple database matches to query sequences. Despite its higher computational costs, our method is still suitable for analyzing large-scale microbiome datasets for practical purposes. Furthermore, our method can be applied for taxonomic classification of any phylogenetic marker gene sequences. Our software, called BLCA, is freely available at https://github.com/qunfengdong/BLCA .

DNA vaccination for prostate cancer, from preclinical to clinical trials - where we stand?

PubMed Central

2012-01-01

Development of various vaccines for prostate cancer (PCa) is becoming an active research area. PCa vaccines are perceived to have less toxicity compared with the available cytotoxic agents. While various immune-based strategies can elicit anti-tumour responses, DNA vaccines present increased efficacy, inducing both humoural and cellular immunity. This immune activation has been proven effective in animal models and initial clinical trials are encouraging. However, to validate the role of DNA vaccination in currently available PCa management paradigms, strong clinical evidence is still lacking. This article provides an overview of the basic principles of DNA vaccines and aims to provide a summary of preclinical and clinical trials outlining the benefits of this immunotherapy in the management of PCa. PMID:23046944

Probabilistic sensitivity analysis incorporating the bootstrap: an example comparing treatments for the eradication of Helicobacter pylori.

PubMed

Pasta, D J; Taylor, J L; Henning, J M

1999-01-01

Decision-analytic models are frequently used to evaluate the relative costs and benefits of alternative therapeutic strategies for health care. Various types of sensitivity analysis are used to evaluate the uncertainty inherent in the models. Although probabilistic sensitivity analysis is more difficult theoretically and computationally, the results can be much more powerful and useful than deterministic sensitivity analysis. The authors show how a Monte Carlo simulation can be implemented using standard software to perform a probabilistic sensitivity analysis incorporating the bootstrap. The method is applied to a decision-analytic model evaluating the cost-effectiveness of Helicobacter pylori eradication. The necessary steps are straightforward and are described in detail. The use of the bootstrap avoids certain difficulties encountered with theoretical distributions. The probabilistic sensitivity analysis provided insights into the decision-analytic model beyond the traditional base-case and deterministic sensitivity analyses and should become the standard method for assessing sensitivity.

Bootstrapping the energy flow in the beginning of life.

PubMed

Hengeveld, R; Fedonkin, M A

2007-01-01

This paper suggests that the energy flow on which all living structures depend only started up slowly, the low-energy, initial phase starting up a second, slightly more energetic phase, and so on. In this way, the build up of the energy flow follows a bootstrapping process similar to that found in the development of computers, the first generation making possible the calculations necessary for constructing the second one, etc. In the biogenetic upstart of an energy flow, non-metals in the lower periods of the Periodic Table of Elements would have constituted the most primitive systems, their operation being enhanced and later supplanted by elements in the higher periods that demand more energy. This bootstrapping process would put the development of the metabolisms based on the second period elements carbon, nitrogen and oxygen at the end of the evolutionary process rather than at, or even before, the biogenetic event.

Treatment of a patient with posterior cortical atrophy (PCA) with chiropractic manipulation and Dynamic Neuromuscular Stabilization (DNS): A case report.

PubMed

Francio, Vinicius T; Boesch, Ron; Tunning, Michael

2015-03-01

Posterior cortical atrophy (PCA) is a rare progressive neurodegenerative syndrome which unusual symptoms include deficits of balance, bodily orientation, chronic pain syndrome and dysfunctional motor patterns. Current research provides minimal guidance on support, education and recommended evidence-based patient care. This case reports the utilization of chiropractic spinal manipulation, dynamic neuromuscular stabilization (DNS), and other adjunctive procedures along with medical treatment of PCA. A 54-year-old male presented to a chiropractic clinic with non-specific back pain associated with visual disturbances, slight memory loss, and inappropriate cognitive motor control. After physical examination, brain MRI and PET scan, the diagnosis of PCA was recognized. Chiropractic spinal manipulation and dynamic neuromuscular stabilization were utilized as adjunctive care to conservative pharmacological treatment of PCA. Outcome measurements showed a 60% improvement in the patient's perception of health with restored functional neuromuscular pattern, improvements in locomotion, posture, pain control, mood, tolerance to activities of daily living (ADLs) and overall satisfactory progress in quality of life. Yet, no changes on memory loss progression, visual space orientation, and speech were observed. PCA is a progressive and debilitating condition. Because of poor awareness of PCA by physicians, patients usually receive incomplete care. Additional efforts must be centered on the musculoskeletal features of PCA, aiming enhancement in quality of life and functional improvements (FI). Adjunctive rehabilitative treatment is considered essential for individuals with cognitive and motor disturbances, and manual medicine procedures may be consider a viable option.

Digital map of posterior cerebral artery infarcts associated with posterior cerebral artery trunk and branch occlusion.

PubMed

Phan, Thanh G; Fong, Ashley C; Donnan, Geoffrey; Reutens, David C

2007-06-01

Knowledge of the extent and distribution of infarcts of the posterior cerebral artery (PCA) may give insight into the limits of the arterial territory and infarct mechanism. We describe the creation of a digital atlas of PCA infarcts associated with PCA branch and trunk occlusion by magnetic resonance imaging techniques. Infarcts were manually segmented on T(2)-weighted magnetic resonance images obtained >24 hours after stroke onset. The images were linearly registered into a common stereotaxic coordinate space. The segmented images were averaged to yield the probability of involvement by infarction at each voxel. Comparisons were made with existing maps of the PCA territory. Thirty patients with a median age of 61 years (range, 22 to 86 years) were studied. In the digital atlas of the PCA, the highest frequency of infarction was within the medial temporal lobe and lingual gyrus (probability=0.60 to 0.70). The mean and maximal PCA infarct volumes were 55.1 and 128.9 cm(3), respectively. Comparison with published maps showed greater agreement in the anterior and medial boundaries of the PCA territory compared with its posterior and lateral boundaries. We have created a probabilistic digital atlas of the PCA based on subacute magnetic resonance scans. This approach is useful for establishing the spatial distribution of strokes in a given cerebral arterial territory and determining the regions within the arterial territory that are at greatest risk of infarction.

Examination of the reliability of the crash modification factors using empirical Bayes method with resampling technique.

PubMed

Wang, Jung-Han; Abdel-Aty, Mohamed; Wang, Ling

2017-07-01

There have been plenty of studies intended to use different methods, for example, empirical Bayes before-after methods, to get accurate estimation of CMFs. All of them have different assumptions toward crash count if there was no treatment. Additionally, another major assumption is that multiple sites share the same true CMF. Under this assumption, the CMF at an individual intersection is randomly drawn from a normally distributed population of CMFs at all intersections. Since CMFs are non-zero values, the population of all CMFs might not follow normal distributions, and even if it does, the true mean of CMFs at some intersections may be different from that at others. Therefore, a bootstrap method based on before-after empirical Bayes theory was proposed to estimate CMFs, but it did not make distributional assumptions. This bootstrap procedure has the added benefit of producing a measure of CMF stability. Furthermore, based on the bootstrapped CMF, a new CMF precision rating method was proposed to evaluate the reliability of CMFs. This study chose 29 urban four-legged intersections as treated sites, and their controls were changed from stop-controlled to signal-controlled. Meanwhile, 124 urban four-legged stop-controlled intersections were selected as reference sites. At first, different safety performance functions (SPFs) were applied to five crash categories, and it was found that each crash category had different optimal SPF form. Then, the CMFs of these five crash categories were estimated using the bootstrap empirical Bayes method. The results of the bootstrapped method showed that signalization significantly decreased Angle+Left-Turn crashes, and its CMF had the highest precision. While, the CMF for Rear-End crashes was unreliable. For KABCO, KABC, and KAB crashes, their CMFs were proved to be reliable for the majority of intersections, but the estimated effect of signalization may be not accurate at some sites. Copyright © 2017 Elsevier Ltd. All rights reserved.

Performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches in VQ codebook generation for image compression

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Chou, Ping-Yi; Chou, Jyh-Horng

2015-11-01

The aim of this study is to generate vector quantisation (VQ) codebooks by integrating principle component analysis (PCA) algorithm, Linde-Buzo-Gray (LBG) algorithm, and evolutionary algorithms (EAs). The EAs include genetic algorithm (GA), particle swarm optimisation (PSO), honey bee mating optimisation (HBMO), and firefly algorithm (FF). The study is to provide performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches. The PCA-EA-LBG approaches contain PCA-GA-LBG, PCA-PSO-LBG, PCA-HBMO-LBG, and PCA-FF-LBG, while the PCA-LBG-EA approaches contain PCA-LBG, PCA-LBG-GA, PCA-LBG-PSO, PCA-LBG-HBMO, and PCA-LBG-FF. All training vectors of test images are grouped according to PCA. The PCA-EA-LBG used the vectors grouped by PCA as initial individuals, and the best solution gained by the EAs was given for LBG to discover a codebook. The PCA-LBG approach is to use the PCA to select vectors as initial individuals for LBG to find a codebook. The PCA-LBG-EA used the final result of PCA-LBG as an initial individual for EAs to find a codebook. The search schemes in PCA-EA-LBG first used global search and then applied local search skill, while in PCA-LBG-EA first used local search and then employed global search skill. The results verify that the PCA-EA-LBG indeed gain superior results compared to the PCA-LBG-EA, because the PCA-EA-LBG explores a global area to find a solution, and then exploits a better one from the local area of the solution. Furthermore the proposed PCA-EA-LBG approaches in designing VQ codebooks outperform existing approaches shown in the literature.

Clinical performance of serum prostate-specific antigen isoform [-2]proPSA (p2PSA) and its derivatives, %p2PSA and the prostate health index (PHI), in men with a family history of prostate cancer: results from a multicentre European study, the PROMEtheuS project.

PubMed

Lazzeri, Massimo; Haese, Alexander; Abrate, Alberto; de la Taille, Alexandre; Redorta, Joan Palou; McNicholas, Thomas; Lughezzani, Giovanni; Lista, Giuliana; Larcher, Alessandro; Bini, Vittorio; Cestari, Andrea; Buffi, Nicolòmaria; Graefen, Markus; Bosset, Olivier; Le Corvoisier, Philippe; Breda, Alberto; de la Torre, Pablo; Fowler, Linda; Roux, Jacques; Guazzoni, Giorgio

2013-08-01

To test the sensitivity, specificity and accuracy of serum prostate-specific antigen isoform [-2]proPSA (p2PSA), %p2PSA and the prostate health index (PHI), in men with a family history of prostate cancer (PCa) undergoing prostate biopsy for suspected PCa. To evaluate the potential reduction in unnecessary biopsies and the characteristics of potentially missed cases of PCa that would result from using serum p2PSA, %p2PSA and PHI. The analysis consisted of a nested case-control study from the PRO-PSA Multicentric European Study, the PROMEtheuS project. All patients had a first-degree relative (father, brother, son) with PCa. Multivariable logistic regression models were complemented by predictive accuracy analysis and decision-curve analysis. Of the 1026 patients included in the PROMEtheuS cohort, 158 (15.4%) had a first-degree relative with PCa. p2PSA, %p2PSA and PHI values were significantly higher (P < 0.001), and free/total PSA (%fPSA) values significantly lower (P < 0.001) in the 71 patients with PCa (44.9%) than in patients without PCa. Univariable accuracy analysis showed %p2PSA (area under the receiver-operating characteristic curve [AUC]: 0.733) and PHI (AUC: 0.733) to be the most accurate predictors of PCa at biopsy, significantly outperforming total PSA ([tPSA] AUC: 0.549), free PSA ([fPSA] AUC: 0.489) and %fPSA (AUC: 0.600) (P ≤ 0.001). For %p2PSA a threshold of 1.66 was found to have the best balance between sensitivity and specificity (70.4 and 70.1%; 95% confidence interval [CI]: 58.4-80.7 and 59.4-79.5 respectively). A PHI threshold of 40 was found to have the best balance between sensitivity and specificity (64.8 and 71.3%, respectively; 95% CI 52.5-75.8 and 60.6-80.5). At 90% sensitivity, the thresholds for %p2PSA and PHI were 1.20 and 25.5, with a specificity of 37.9 and 25.5%, respectively. At a %p2PSA threshold of 1.20, a total of 39 (24.8%) biopsies could have been avoided, but two cancers with a Gleason score (GS) of 7 would have been missed. At a PHI threshold of 25.5 a total of 27 (17.2%) biopsies could have been avoided and two (3.8%) cancers with a GS of 7 would have been missed. In multivariable logistic regression models, %p2PSA and PHI achieved independent predictor status and significantly increased the accuracy of multivariable models including PSA and prostate volume by 8.7 and 10%, respectively (P ≤ 0.001). p2PSA, %p2PSA and PHI were directly correlated with Gleason score (ρ: 0.247, P = 0.038; ρ: 0.366, P = 0.002; ρ: 0.464, P < 0.001, respectively). %p2PSA and PHI are more accurate than tPSA, fPSA and %fPSA in predicting PCa in men with a family history of PCa. Consideration of %p2PSA and PHI results in the avoidance of several unnecessary biopsies. p2PSA, %p2PSA and PHI correlate with cancer aggressiveness. © 2013 BJU International.

Damage detection of engine bladed-disks using multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Fang, X.; Tang, J.

2006-03-01

The timely detection of damage in aero-engine bladed-disks is an extremely important and challenging research topic. Bladed-disks have high modal density and, particularly, their vibration responses are subject to significant uncertainties due to manufacturing tolerance (blade-to-blade difference or mistuning), operating condition change and sensor noise. In this study, we present a new methodology for the on-line damage detection of engine bladed-disks using their vibratory responses during spin-up or spin-down operations which can be measured by blade-tip-timing sensing technique. We apply a principle component analysis (PCA)-based approach for data compression, feature extraction, and denoising. The non-model based damage detection is achieved by analyzing the change between response features of the healthy structure and of the damaged one. We facilitate such comparison by incorporating the Hotelling's statistic T2 analysis, which yields damage declaration with a given confidence level. The effectiveness of the method is demonstrated by case studies.

Reduced ion bootstrap current drive on NTM instability

NASA Astrophysics Data System (ADS)

Qu, Hongpeng; Wang, Feng; Wang, Aike; Peng, Xiaodong; Li, Jiquan

2018-05-01

The loss of bootstrap current inside magnetic island plays a dominant role in driving the neoclassical tearing mode (NTM) instability in tokamak plasmas. In this work, we investigate the finite-banana-width (FBW) effect on the profile of ion bootstrap current in the island vicinity via an analytical approach. The results show that even if the pressure gradient vanishes inside the island, the ion bootstrap current can partly survive due to the FBW effect. The efficiency of the FBW effect is higher when the island width becomes smaller. Nevertheless, even when the island width is comparable to the ion FBW, the unperturbed ion bootstrap current inside the island cannot be largely recovered by the FBW effect, and thus the current loss still exists. This suggests that FBW effect alone cannot dramatically reduce the ion bootstrap current drive on NTMs.

Bootstrap Percolation on Homogeneous Trees Has 2 Phase Transitions

NASA Astrophysics Data System (ADS)

Fontes, L. R. G.; Schonmann, R. H.

2008-09-01

We study the threshold θ bootstrap percolation model on the homogeneous tree with degree b+1, 2≤ θ≤ b, and initial density p. It is known that there exists a nontrivial critical value for p, which we call p f , such that a) for p> p f , the final bootstrapped configuration is fully occupied for almost every initial configuration, and b) if p< p f , then for almost every initial configuration, the final bootstrapped configuration has density of occupied vertices less than 1. In this paper, we establish the existence of a distinct critical value for p, p c , such that 0< p c < p f , with the following properties: 1) if p≤ p c , then for almost every initial configuration there is no infinite cluster of occupied vertices in the final bootstrapped configuration; 2) if p> p c , then for almost every initial configuration there are infinite clusters of occupied vertices in the final bootstrapped configuration. Moreover, we show that 3) for p< p c , the distribution of the occupied cluster size in the final bootstrapped configuration has an exponential tail; 4) at p= p c , the expected occupied cluster size in the final bootstrapped configuration is infinite; 5) the probability of percolation of occupied vertices in the final bootstrapped configuration is continuous on [0, p f ] and analytic on ( p c , p f ), admitting an analytic continuation from the right at p c and, only in the case θ= b, also from the left at p f .

A Novel Weighted Kernel PCA-Based Method for Optimization and Uncertainty Quantification

NASA Astrophysics Data System (ADS)

Thimmisetty, C.; Talbot, C.; Chen, X.; Tong, C. H.

2016-12-01

It has been demonstrated that machine learning methods can be successfully applied to uncertainty quantification for geophysical systems through the use of the adjoint method coupled with kernel PCA-based optimization. In addition, it has been shown through weighted linear PCA how optimization with respect to both observation weights and feature space control variables can accelerate convergence of such methods. Linear machine learning methods, however, are inherently limited in their ability to represent features of non-Gaussian stochastic random fields, as they are based on only the first two statistical moments of the original data. Nonlinear spatial relationships and multipoint statistics leading to the tortuosity characteristic of channelized media, for example, are captured only to a limited extent by linear PCA. With the aim of coupling the kernel-based and weighted methods discussed, we present a novel mathematical formulation of kernel PCA, Weighted Kernel Principal Component Analysis (WKPCA), that both captures nonlinear relationships and incorporates the attribution of significance levels to different realizations of the stochastic random field of interest. We also demonstrate how new instantiations retaining defining characteristics of the random field can be generated using Bayesian methods. In particular, we present a novel WKPCA-based optimization method that minimizes a given objective function with respect to both feature space random variables and observation weights through which optimal snapshot significance levels and optimal features are learned. We showcase how WKPCA can be applied to nonlinear optimal control problems involving channelized media, and in particular demonstrate an application of the method to learning the spatial distribution of material parameter values in the context of linear elasticity, and discuss further extensions of the method to stochastic inversion.

Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

PubMed

Reena Benjamin, J; Jayasree, T

2018-02-01

In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

Monte Carlo based statistical power analysis for mediation models: methods and software.

PubMed

Zhang, Zhiyong

2014-12-01

The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.

Extraction of prostatic lumina and automated recognition for prostatic calculus image using PCA-SVM.

PubMed

Wang, Zhuocai; Xu, Xiangmin; Ding, Xiaojun; Xiao, Hui; Huang, Yusheng; Liu, Jian; Xing, Xiaofen; Wang, Hua; Liao, D Joshua

2011-01-01

Identification of prostatic calculi is an important basis for determining the tissue origin. Computation-assistant diagnosis of prostatic calculi may have promising potential but is currently still less studied. We studied the extraction of prostatic lumina and automated recognition for calculus images. Extraction of lumina from prostate histology images was based on local entropy and Otsu threshold recognition using PCA-SVM and based on the texture features of prostatic calculus. The SVM classifier showed an average time 0.1432 second, an average training accuracy of 100%, an average test accuracy of 93.12%, a sensitivity of 87.74%, and a specificity of 94.82%. We concluded that the algorithm, based on texture features and PCA-SVM, can recognize the concentric structure and visualized features easily. Therefore, this method is effective for the automated recognition of prostatic calculi.

An incidence model of the cost of advanced prostate cancer in Spain.

PubMed

Hart, W M; Nazir, J; Baskin-Bey, E

2014-02-01

Prostate cancer (PCa) is the second leading cancer diagnosed among men. In Spain the incidence of PCa was 70.75 cases per 100,000 males. Advanced PCa has spread outside of the prostate capsule and may involve other parts of the body. The aim of this study was to estimate the lifetime costs of a cohort of advanced PCa patients diagnosed in Spain in 2012. A partitioned economic model was developed in EXCEL incorporating Spanish incidence, mortality, and cost data supplemented with data from the international literature. Progression from Stage III to Stage IV was permitted. Costs were discounted at the standard rate of 3%. Lifetime costs were presented on an individual basis and for the entire cohort of newly diagnosed Stage III and Stage IV PCa patients. Lifetime costs for advanced PCa were ∼€19,961 per patient (mean survival of 8.4 years). Using the projected incident cases for 2012 (3047), the total cost for the incident cohort of patients in 2012 would amount to €61 million. These results were more sensitive to changes in the ongoing costs (post-initial 12 months) of Stage III PCa, the rate of progression from Stage III to Stage IV, and the discount rate applied to costs. This study provides an estimate of the lifetime costs of advanced PCa in Spain and a framework for further research. The study is limited by the availability of long-term Spanish data and the need to make inferences from international studies. However, until long-term prospective or observational data do become available in Spain, based on the assumptions, the current results indicate that the burden of advanced PCa in Spain is substantial. Any treatments that could potentially reduce the economic burden of the disease should be of interest to healthcare decision makers.

Prostate cancer gene 3 and multiparametric magnetic resonance can reduce unnecessary biopsies: decision curve analysis to evaluate predictive models.

PubMed

Busetto, Gian Maria; De Berardinis, Ettore; Sciarra, Alessandro; Panebianco, Valeria; Giovannone, Riccardo; Rosato, Stefano; D'Errigo, Paola; Di Silverio, Franco; Gentile, Vincenzo; Salciccia, Stefano

2013-12-01

To overcome the well-known prostate-specific antigen limits, several new biomarkers have been proposed. Since its introduction in clinical practice, the urinary prostate cancer gene 3 (PCA3) assay has shown promising results for prostate cancer (PC) detection. Furthermore, multiparametric magnetic resonance imaging (mMRI) has the ability to better describe several aspects of PC. A prospective study of 171 patients with negative prostate biopsy findings and a persistent high prostate-specific antigen level was conducted to assess the role of mMRI and PCA3 in identifying PC. All patients underwent the PCA3 test and mMRI before a second transrectal ultrasound-guided prostate biopsy. The accuracy and reliability of PCA3 (3 different cutoff points) and mMRI were evaluated. Four multivariate logistic regression models were analyzed, in terms of discrimination and the cost benefit, to assess the clinical role of PCA3 and mMRI in predicting the biopsy outcome. A decision curve analysis was also plotted. Repeated transrectal ultrasound-guided biopsy identified 68 new cases (41.7%) of PC. The sensitivity and specificity of the PCA3 test and mMRI was 68% and 49% and 74% and 90%, respectively. Evaluating the regression models, the best discrimination (area under the curve 0.808) was obtained using the full model (base clinical model plus mMRI and PCA3). The decision curve analysis, to evaluate the cost/benefit ratio, showed good performance in predicting PC with the model that included mMRI and PCA3. mMRI increased the accuracy and sensitivity of the PCA3 test, and the use of the full model significantly improved the cost/benefit ratio, avoiding unnecessary biopsies. Copyright © 2013 Elsevier Inc. All rights reserved.

[Evaluation of the effectiveness of patient-controlled analgesia in children with sickle cell anemia from the perspective of healthcare professionals and parents].

PubMed

Turaç, Ayşegül; Rumeli Atıcı, Şebnem

2016-07-01

This study evaluated the efficacy of patient-controlled analgesia (PCA) used by children with sickle cell anemia (SCA) based on the attitudes of parents and healthcare professionals. A total of 86 individuals were involved in the study: 54 parents of children with SCA who were receiving treatment and 32 healthcare providers (doctors, nurses). To evaluate the effectiveness of the PCA method, a questionnaire was prepared to determine the level of knowledge of the participants about the PCA method and their perception of its advantages and disadvantages. According to 65.6% (n=21) of the healthcare providers, PCA should be used during acute phase of pain. The great majority of the participants (93%; n=80) thought that pain was effectively controlled both during the day and at night. PCA reduced the fear of unavailability of analgesic drugs in 83.3% (n=45) of parents and in 87.5% (n=28) of healthcare providers. More parents (37%) reported a reduction in the fear of return of pain than healthcare providers (9.4%) (p<0.05). Most parents (87%; n=47) reported that they preferred to wait until their child complained of severe pain to use on-demand doses of analgesic due to concerns about overdose and addiction. Resolving machine alarms (48%; n=26) and the length of time required to refill the machine (48%; n=26) were reported as disadvantages of PCA method. In this study, parents and healthcare professionals found PCA to be effective in relieving pain in children with SCA; however, fears and biased knowledge of users about the analgesic drug are thought to inhibit reaching sufficient dosage. Educational courses for users about PCA and the drugs used may increase the effectiveness of PCA method.

The effect of start and stop age at screening on the risk of being diagnosed with prostate cancer

PubMed Central

Arnsrud Godtman, Rebecka; Carlsson, Sigrid; Holmberg, Erik; Stranne, Johan; Hugosson, Jonas

2016-01-01

Purpose The aim of this study was to investigate the effect of age and number of screens on the risk of prostate cancer (PCa) diagnosis. Materials and Methods The Göteborg randomized population-based PCa screening trial has, since 1995, invited men biennially for prostate-specific antigen (PSA)-testing, until the upper age limit 70 years. Men with a PSA-level above the threshold ≥2.5 ng/ml were recommended further work-up including 10-core biopsy (sextant before 2009). The present study comprises 9,065 men born 1930–43 (1944 excluded due to different screening algorithm). Complete attendees were defined as men who accepted all screening invitations (maximum 3–9 invitations). Cumulative incidence of PCa was calculated using standard methods. Results Of the 3,488 (38%) complete attendees, 667 were diagnosed with PCa (follow-up 1995–30 Jun 2014). At the age 70, there was no significant difference in PCa risk between those who started screening at the age of 52 (9 screens), 55 (7 screens) or 60 (5 screens) years. However, the cumulative risk of PCa diagnosis increased dramatically with age and was 7.9% at age 60, 15% at age 65 and 21% at age 70, for men who had been screened ≥4 times. Conclusion There was no clear association between risk of PCa and the number of screens. Starting screening at an early age appears to advance the time of PCa diagnosis but does not seem to increase the risk of being diagnosed with the disease. Age at termination of screening is strongly associated with the risk of being diagnosed with PCa. PMID:26678954

A three-gene panel on urine increases PSA specificity in the detection of prostate cancer.

PubMed

Rigau, Marina; Ortega, Israel; Mir, Maria Carmen; Ballesteros, Carlos; Garcia, Marta; Llauradó, Marta; Colás, Eva; Pedrola, Núria; Montes, Melania; Sequeiros, Tamara; Ertekin, Tugce; Majem, Blanca; Planas, Jacques; Ruiz, Anna; Abal, Miguel; Sánchez, Alex; Morote, Juan; Reventós, Jaume; Doll, Andreas

2011-12-01

Several studies have demonstrated the usefulness of monitoring an RNA transcript, such as PCA3, in post-prostate massage (PM) urine for increasing the specificity of prostate-specific antigen (PSA) in the detection of prostate cancer (PCa). However, a single marker may not necessarily reflect the multifactorial nature of PCa. We analyzed post-PM urine samples from 154 consecutive patients, who presented for prostate biopsies because of elevated serum PSA (>4 ng/ml) and/or abnormal digital rectal exam. We tested whether the putative PCa biomarkers PSMA, PSGR, and PCA3 could be detected by quantitative real-time PCR in post-PM urine sediment. We combined these findings to test if a combination of these biomarkers could improve the specificity of actual diagnosis. Afterwards, we specifically tested our model for clinical usefulness in the PSA diagnostic "gray zone" (4-10 ng/ml) on a target subset of 82 men with no prior biopsy. By univariate analysis, we found that the PSMA, PSGR, and PCA3 scores were significant predictors of PCa. Using a multiplex model, the area under the multi receiver-operating characteristic curve was 0.74 versus 0.82 in the diagnostic "gray zone." Fixing the sensitivity at 96%, we obtained a specificity of 34% and 50% in the gray zone. Taken together, these results provide a strategy for the development of a more accurate model for PCa diagnosis. In the future, a multiplexed, urine-based diagnostic test for PCa with a higher specificity, but the same sensitivity as the serum-PSA test, could be used to determine better which patients should undergo biopsy. Copyright © 2011 Wiley Periodicals, Inc.

An Estimate of the Incidence of Prostate Cancer in Africa: A Systematic Review and Meta-Analysis

PubMed Central

Aderemi, Adewale Victor; Iseolorunkanmi, Alexander; Oyedokun, Ayo; Ayo, Charles K.

2016-01-01

Background Prostate cancer (PCa) is rated the second most common cancer and sixth leading cause of cancer deaths among men globally. Reports show that African men suffer disproportionately from PCa compared to men from other parts of the world. It is still quite difficult to accurately describe the burden of PCa in Africa due to poor cancer registration systems. We systematically reviewed the literature on prostate cancer in Africa and provided a continent-wide incidence rate of PCa based on available data in the region. Methods A systematic literature search of Medline, EMBASE and Global Health from January 1980 to June 2015 was conducted, with additional search of Google Scholar, International Association of Cancer Registries (IACR), International Agency for Research on Cancer (IARC), and WHO African region websites, for studies that estimated incidence rate of PCa in any African location. Having assessed quality and consistency across selected studies, we extracted incidence rates of PCa and conducted a random effects meta-analysis. Results Our search returned 9766 records, with 40 studies spreading across 16 African countries meeting our selection criteria. We estimated a pooled PCa incidence rate of 22.0 (95% CI: 19.93–23.97) per 100,000 population, and also reported a median incidence rate of 19.5 per 100,000 population. We observed an increasing trend in PCa incidence with advancing age, and over the main years covered. Conclusion Effective cancer registration and extensive research are vital to appropriately quantifying PCa burden in Africa. We hope our findings may further assist at identifying relevant gaps, and contribute to improving knowledge, research, and interventions targeted at prostate cancer in Africa. PMID:27073921

[Development of a diagnostic test system for early non-invasive detection of prostate cancer based on PCA3 mRNA levels in urine sediment using quantitative reverse tanscription polymerase chain reaction (qRT-PCR)].

PubMed

Pavlov, K A; Shkoporov, A N; Khokhlova, E V; Korchagina, A A; Sidorenkov, A V; Grigor'ev, M É; Pushkar', D Iu; Chekhonin, V P

2013-01-01

The wide introduction of prostatic specific antigen (PSA) determination into clinical practice has resulted in a larger number of prostate biopsies, while the lower age threshold for PSA has led to a larger number of unnecessary prostate biopsies. Hence, there is a need for new biomarkers that can detect prostate cancer. PCA3 is a noncoding messenger ribonucleic acid (mRNA) that is expressed exclusively in prostate cells. The aim of the study has been to develop a diagnostic test system for early non-invasive detection of prostate cancer based on PCA3 mRNA levels in urine sediment using quantitative reverse transcription polymerase chain reaction (qRT-PCR). As part of the study, a laboratory diagnostic test system prototype has been designed, an application methodology has been developed and specificity and sensitivity data of the method has been assessed. The diagnostic system has demonstrated its ability to detect significantly elevated levels of PCA 3/KLK 3 in samples from prostate cancer (PCa) patients compared with those from healthy men. The findings have shown relatively high diagnostic sensitivity, specificity and negative-predictive values for an early non-invasive screening of prostate cancer

A measure for objects clustering in principal component analysis biplot: A case study in inter-city buses maintenance cost data

NASA Astrophysics Data System (ADS)

Ginanjar, Irlandia; Pasaribu, Udjianna S.; Indratno, Sapto W.

2017-03-01

This article presents the application of the principal component analysis (PCA) biplot for the needs of data mining. This article aims to simplify and objectify the methods for objects clustering in PCA biplot. The novelty of this paper is to get a measure that can be used to objectify the objects clustering in PCA biplot. Orthonormal eigenvectors, which are the coefficients of a principal component model representing an association between principal components and initial variables. The existence of the association is a valid ground to objects clustering based on principal axes value, thus if m principal axes used in the PCA, then the objects can be classified into 2m clusters. The inter-city buses are clustered based on maintenance costs data by using two principal axes PCA biplot. The buses are clustered into four groups. The first group is the buses with high maintenance costs, especially for lube, and brake canvass. The second group is the buses with high maintenance costs, especially for tire, and filter. The third group is the buses with low maintenance costs, especially for lube, and brake canvass. The fourth group is buses with low maintenance costs, especially for tire, and filter.

A new statistical PCA-ICA algorithm for location of R-peaks in ECG.

PubMed

Chawla, M P S; Verma, H K; Kumar, Vinod

2008-09-16

The success of ICA to separate the independent components from the mixture depends on the properties of the electrocardiogram (ECG) recordings. This paper discusses some of the conditions of independent component analysis (ICA) that could affect the reliability of the separation and evaluation of issues related to the properties of the signals and number of sources. Principal component analysis (PCA) scatter plots are plotted to indicate the diagnostic features in the presence and absence of base-line wander in interpreting the ECG signals. In this analysis, a newly developed statistical algorithm by authors, based on the use of combined PCA-ICA for two correlated channels of 12-channel ECG data is proposed. ICA technique has been successfully implemented in identifying and removal of noise and artifacts from ECG signals. Cleaned ECG signals are obtained using statistical measures like kurtosis and variance of variance after ICA processing. This analysis also paper deals with the detection of QRS complexes in electrocardiograms using combined PCA-ICA algorithm. The efficacy of the combined PCA-ICA algorithm lies in the fact that the location of the R-peaks is bounded from above and below by the location of the cross-over points, hence none of the peaks are ignored or missed.

Visuospatial bootstrapping: implicit binding of verbal working memory to visuospatial representations in children and adults.

PubMed

Darling, Stephen; Parker, Mary-Jane; Goodall, Karen E; Havelka, Jelena; Allen, Richard J

2014-03-01

When participants carry out visually presented digit serial recall, their performance is better if they are given the opportunity to encode extra visuospatial information at encoding-a phenomenon that has been termed visuospatial bootstrapping. This bootstrapping is the result of integration of information from different modality-specific short-term memory systems and visuospatial knowledge in long term memory, and it can be understood in the context of recent models of working memory that address multimodal binding (e.g., models incorporating an episodic buffer). Here we report a cross-sectional developmental study that demonstrated visuospatial bootstrapping in adults (n=18) and 9-year-old children (n=15) but not in 6-year-old children (n=18). This is the first developmental study addressing visuospatial bootstrapping, and results demonstrate that the developmental trajectory of bootstrapping is different from that of basic verbal and visuospatial working memory. This pattern suggests that bootstrapping (and hence integrative functions such as those associated with the episodic buffer) emerge independent of the development of basic working memory slave systems during childhood. Copyright © 2013 Elsevier Inc. All rights reserved.

Relative Linkages of Stream Dissolved Oxygen with the Hydroclimatic and Biogeochemical Drivers across the Gulf Coast of U.S.A.

NASA Astrophysics Data System (ADS)

Gebreslase, A. K.; Abdul-Aziz, O. I.

2017-12-01

Dynamics of coastal stream water quality is influenced by a multitude of interacting environmental drivers. A systematic data analytics approach was employed to determine the relative linkages of stream dissolved oxygen (DO) with the hydroclimatic and biogeochemical variables across the Gulf Coast of U.S.A. Multivariate pattern recognition techniques of PCA and FA, alongside Pearson's correlation matrix, were utilized to examine the interrelation of variables at 36 water quality monitoring stations from USGS NWIS and EPA STORET databases. Power-law based partial least square regression models with a bootstrap Monte Carlo procedure (1000 iterations) were developed to estimate the relative linkages of dissolved oxygen with the hydroclimatic and biogeochemical variables by appropriately resolving multicollinearity (Nash-Sutcliffe efficiency = 0.58-0.94). Based on the dominant drivers, stations were divided into four environmental regimes. Water temperature was the dominant driver of DO in the majority of streams, representing most the northern part of Gulf Coast states. However, streams in the southern part of Texas and Florida showed a dominant pH control on stream DO. Further, streams representing the transition zone of the two environmental regimes showed notable controls of multiple drivers (i.e., water temperature, stream flow, and specific conductance) on the stream DO. The data analytics research provided profound insight to understand the dynamics of stream DO with the hydroclimatic and biogeochemical variables. The knowledge can help water quality managers in formulating plans for effective stream water quality and watershed management in the U.S. Gulf Coast. Keywords Data analytics, coastal streams, relative linkages, dissolved oxygen, environmental regimes, Gulf Coast, United States.

A Study of Wind Turbine Comprehensive Operational Assessment Model Based on EM-PCA Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Minqiang; Xu, Bin; Zhan, Yangyan; Ren, Danyuan; Liu, Dexing

2018-01-01

To assess wind turbine performance accurately and provide theoretical basis for wind farm management, a hybrid assessment model based on Entropy Method and Principle Component Analysis (EM-PCA) was established, which took most factors of operational performance into consideration and reach to a comprehensive result. To verify the model, six wind turbines were chosen as the research objects, the ranking obtained by the method proposed in the paper were 4#>6#>1#>5#>2#>3#, which are completely in conformity with the theoretical ranking, which indicates that the reliability and effectiveness of the EM-PCA method are high. The method could give guidance for processing unit state comparison among different units and launching wind farm operational assessment.

Power line identification of millimeter wave radar based on PCA-GS-SVM

NASA Astrophysics Data System (ADS)

Fang, Fang; Zhang, Guifeng; Cheng, Yansheng

2017-12-01

Aiming at the problem that the existing detection method can not effectively solve the security of UAV's ultra low altitude flight caused by power line, a power line recognition method based on grid search (GS) and the principal component analysis and support vector machine (PCA-SVM) is proposed. Firstly, the candidate line of Hough transform is reduced by PCA, and the main feature of candidate line is extracted. Then, upport vector machine (SVM is) optimized by grid search method (GS). Finally, using support vector machine classifier optimized parameters to classify the candidate line. MATLAB simulation results show that this method can effectively identify the power line and noise, and has high recognition accuracy and algorithm efficiency.

Interspecies Interactions Reverse the Hazard of Antibiotics Exposure: A Plankton Community Study on Responses to Ciprofloxacin hydrochloride.

PubMed

Wang, Changyou; Wang, Ziyang; Zhang, Yong; Su, Rongguo

2017-05-24

The ecotoxicological effects of Ciprofloxacin hydrochloride (CIP) were tested on population densities of plankton assemblages consisting of two algae (Isochrysis galbana and Platymonas subcordiformis) and a rotifer (Brachionus plicatilis). The I. galbana showed a significant decrease in densities when concentrations of CIP were above 2.0 mg L -1 in single-species tests, while P. subcordiformis and B. plicatilis were stable in densities when CIP were less than10.0 mg L -1 . The equilibrium densities of I. galbana in community test increased with CIP concentrations after falling to a trough at 5.0 mg L -1 , showed a completely different pattern of P. subcordiformis which decreased with CIP concentrations after reaching a peak at 30.0 mg L -1 . The observed beneficial effect was a result of interspecies interactions of trophic cascade that buffered for more severe direct effects of toxicants. The community test-based NOEC of CIP (2.0 mg L -1 ), embodying the indirect effects, was different from the extrapolated one derived by single-species tests (0.5 mg L -1 ), but all lacked confidence interval. A CIP threshold concentration of obvious relevance to ecological interaction was calculated with a simplified plankton ecological model, achieving a value of 1.26 mg L -1 with a 95% bootstrapping confidence interval from 1.18 to 1.31 mg L -1 .