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Articles 1 - 30 of 30
Full-Text Articles in Physical Sciences and Mathematics
A Novel Totivirus And Piscine Reovirus (Prv) In Atlantic Salmon (Salmo Salar) With Cardiomyopathy Syndrome (Cms), Torstein Tengs
A Novel Totivirus And Piscine Reovirus (Prv) In Atlantic Salmon (Salmo Salar) With Cardiomyopathy Syndrome (Cms), Torstein Tengs
Dr. Torstein Tengs
BACKGROUNDCardiomyopathy syndrome (CMS) is a severe disease affecting large farmed Atlantic salmon. Mortality often appears without prior clinical signs, typically shortly prior to slaughter. We recently reported the finding and the complete genomic sequence of a novel piscine reovirus (PRV), which is associated with another cardiac disease in Atlantic salmon; heart and skeletal muscle inflammation (HSMI). In the present work we have studied whether PRV or other infectious agents may be involved in the etiology of CMS.RESULTSUsing high throughput sequencing on heart samples from natural outbreaks of CMS and from fish experimentally challenged with material from fish diagnosed with CMS …
On Nonparametric Comparison Of Images And Regression Surfaces, Xiao-Feng Wang, Deping Ye
On Nonparametric Comparison Of Images And Regression Surfaces, Xiao-Feng Wang, Deping Ye
Xiaofeng Wang
Multivariate local regression is an important tool for image processing and analysis. In many practical biomedical problems, one is often interested in comparing a group of images or regression surfaces. In this paper, we extend the existing method of testing the equality of nonparametric curves by Dette and Neumeyer (2001) and consider a test statistic by means of an L2-distance in the multi-dimensional case under a completely heteroscedastic nonparametric model. The test statistic is also extended to be used in the case of spatial correlated errors. Two bootstrap procedures are described in order to approximate the critical values of the …
Health Benefits Of Increased Walking For Sedentary, Generally Healthy Older Adults: Using Longitudinal Data To Approximate An Intervention Trial, Paula Diehr
Paula Diehr
BACKGROUND: Older adults are often advised to walk more, but randomized trials have not conclusively established the benefits of walking in this age group. Typical analyses based on observational data may have biased results. Here, we propose a "limited-bias," more interpretable estimate of the health benefits to sedentary healthy older adults of walking more, using longitudinal data from the Cardiovascular Health Study. METHODS: The number of city blocks walked per week, collected annually, was classified as sedentary (<7 blocks per>week), somewhat active, or active (>or=28). Analysis was restricted to persons sedentary and healthy in the first 2 years. In Year …
Heart And Skeletal Muscle Inflammation Of Farmed Salmon Is Associated With Infection With A Novel Reovirus, Torstein Tengs
Heart And Skeletal Muscle Inflammation Of Farmed Salmon Is Associated With Infection With A Novel Reovirus, Torstein Tengs
Dr. Torstein Tengs
Atlantic salmon (Salmo salar L.) mariculture has been associated with epidemics of infectious diseases that threaten not only local production, but also wild fish coming into close proximity to marine pens and fish escaping from them. Heart and skeletal muscle inflammation (HSMI) is a frequently fatal disease of farmed Atlantic salmon. First recognized in one farm in Norway in 1999, HSMI was subsequently implicated in outbreaks in other farms in Norway and the United Kingdom. Although pathology and disease transmission studies indicated an infectious basis, efforts to identify an agent were unsuccessful. Here we provide evidence that HSMI is associated …
Non-Prejudiced Detection And Characterization Of Genetic Modifications, Torstein Tengs
Non-Prejudiced Detection And Characterization Of Genetic Modifications, Torstein Tengs
Dr. Torstein Tengs
The application of gene technology is becoming widespread much thanks to the rapid increase in technology, resource, and knowledge availability. Consequently, the diversity and number of genetically modified organisms (GMOs) that may find their way into the food chain or the environment, intended or unintended, is rapidly growing. From a safety point of view the ability to detect and characterize in detail any GMO, independent of publicly available information, is fundamental. Pre-release risk assessments of GMOs are required in most jurisdictions and are usually based on application of technologies with limited ability to detect unexpected rearrangements and insertions. We present …
Comparison Of Nine Different Real-Time Pcr Chemistries For Qualitative And Quantitative Applications In Gmo Detection, Torstein Tengs
Comparison Of Nine Different Real-Time Pcr Chemistries For Qualitative And Quantitative Applications In Gmo Detection, Torstein Tengs
Dr. Torstein Tengs
Several techniques have been developed for detection and quantification of genetically modified organisms, but quantitative real-time PCR is by far the most popular approach. Among the most commonly used realtime PCR chemistries are TaqMan probes and SYBR green, but many other detection chemistries have also been developed. Because their performance has never been compared systematically, here we present an extensive evaluation of some promising chemistries: sequenceunspecific DNA labeling dyes (SYBR green), primer-based technologies (AmpliFluor, Plexor, Lux primers), and techniques involving double-labeled probes, comprising hybridization (molecular beacon) and hydrolysis (TaqMan, CPT, LNA, and MGB) probes, based on recently published experimental data. …
Prevalence, Incidence, And Persistence Of Major Depressive Symptoms In The Cardiovascular Health Study, Stephen M. Thielke Md, Ms, Paula Diehr Phd
Prevalence, Incidence, And Persistence Of Major Depressive Symptoms In The Cardiovascular Health Study, Stephen M. Thielke Md, Ms, Paula Diehr Phd
Paula Diehr
PURPOSE: To explore the association of major depressive symptoms with advancing age, sex, and self-rated health among older adults. DESIGN AND METHODS: We analyzed 10 years of annual assessments in a longitudinal cohort of 5888 Medicare recipients in the Cardiovascular Health Study. Self-rated health was assessed with a single question, and subjects categorized as healthy or sick. Major depressive symptoms were assessed using the Center for Epidemiologic Studies Short Depression Scale, with subjects categorized as nondepressed (score < 10) or depressed (> or =10). Age-, sex-, and health-specific prevalence of depression and the probabilities of transition between depressed and nondepressed states were estimated. RESULTS: The …
A Mixture Model Based Approach For Estimating The Fdr In Replicated Microarray Data, Shuo Jiao, Shunpu Zhang
A Mixture Model Based Approach For Estimating The Fdr In Replicated Microarray Data, Shuo Jiao, Shunpu Zhang
Shuo Jiao
One of the mostly used methods for estimating the false discovery rate (FDR) is the permutation based method. The permutation based method has the well-known granularity problem due to the discrete nature of the permuted null scores. The granularity problem may produce very unstable FDR estimates. Such instability may cause scientists to over- or under-estimate the number of false positives among the genes declared as significant, and hence result in inaccurate interpretation of biological data. In this paper, we propose a new model based method as an improvement of the permutation based FDR estimation method of SAM [1] The new …
Event Adjudication Changes Key Results In Open-Label Trials: The Affirm Experience, Elaine M. Nasco, April Slee, Kent M. Koprowicz, Robert G. Hart
Event Adjudication Changes Key Results In Open-Label Trials: The Affirm Experience, Elaine M. Nasco, April Slee, Kent M. Koprowicz, Robert G. Hart
Kent M Koprowicz
Event Adjudication Changes Key Results in Open-Label Trials: The AFFIRM Experience Author Block: Elaine M. Nasco, April Slee, Kent Koprowicz, Robert G. Hart, Axio Research, LLC, Seattle, WA Abstract: Background: The value of central event adjudication of endpoints in multi-center randomized trials has recently been questioned. Methods: The NIH-sponsored Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) trial randomized 4,060 atrial fibrillation patients to antiarrhythmic drugs (rhythm control) vs. rate-controlling drugs, given open-label, at 213 clinical sites. While the primary outcome was mortality, a key secondary endpoint was ischemic stroke (IS), centrally adjudicated by those reviewing source documents from which …
Estimating The Proportion Of Equivalently Expressed Genes In Microarray Data Based On Transformed Test Statistics, Shuo Jiao, Shunpu Zhang
Estimating The Proportion Of Equivalently Expressed Genes In Microarray Data Based On Transformed Test Statistics, Shuo Jiao, Shunpu Zhang
Shuo Jiao
In microarray data analysis, false discovery rate (FDR) is now widely accepted as the control criterion to account for multiple hypothesis testing. The proportion of equivalently expressed genes (π0) is a key component to be estimated in the estimation of FDR. Some commonly used π0 estimators (BUM, SPLOSH, QVALUE, and LBE ) are all based on p-values, and they are essentially upper bounds of π0. The simulations we carried out show that these four methods significantly overestimate the true π0 when differentially expressed genes and equivalently expressed genes are not well separated. To solve this problem, we first introduce a …
Wavelet-Based Functional Linear Mixed Models: An Application To Measurement Error–Corrected Distributed Lag Models, Elizabeth J. Malloy, Jeffrey S. Morris, Sara D. Adar, Helen Suh, Diane R. Gold, Brent A. Coull
Wavelet-Based Functional Linear Mixed Models: An Application To Measurement Error–Corrected Distributed Lag Models, Elizabeth J. Malloy, Jeffrey S. Morris, Sara D. Adar, Helen Suh, Diane R. Gold, Brent A. Coull
Jeffrey S. Morris
Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient …
Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris
Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris
Jeffrey S. Morris
A recent article published in The Annals of Applied Statistics (AOAS) by two MD Anderson researchers—Keith Baggerly and Kevin Coombes—dissects results from a highly-influential series of medical papers involving genomics-driven personalized cancer therapy, and outlines a series of simple yet fatal flaws that raises serious questions about the veracity of the original results. Having immediate and strong impact, this paper, along with related work, is providing the impetus for new standards of reproducibility in scientific research.
Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes
Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes
Jeffrey S. Morris
Proteomic profiling has the potential to impact the diagnosis, prognosis, and treatment of various diseases. A number of different proteomic technologies are available that allow us to look at many proteins at once, and all of them yield complex data that raise significant quantitative challenges. Inadequate attention to these quantitative issues can prevent these studies from achieving their desired goals, and can even lead to invalid results. In this chapter, we describe various ways the involvement of statisticians or other quantitative scientists in the study team can contribute to the success of proteomic research, and we outline some of the …
Informatics And Statistics For Analyzing 2-D Gel Electrophoresis Images, Andrew W. Dowsey, Jeffrey S. Morris, Howard G. Gutstein, Guang Z. Yang
Informatics And Statistics For Analyzing 2-D Gel Electrophoresis Images, Andrew W. Dowsey, Jeffrey S. Morris, Howard G. Gutstein, Guang Z. Yang
Jeffrey S. Morris
Whilst recent progress in ‘shotgun’ peptide separation by integrated liquid chromatography and mass spectrometry (LC/MS) has enabled its use as a sensitive analytical technique, proteome coverage and reproducibility is still limited and obtaining enough replicate runs for biomarker discovery is a challenge. For these reasons, recent research demonstrates the continuing need for protein separation by two-dimensional gel electrophoresis (2-DE). However, with traditional 2-DE informatics, the digitized images are reduced to symbolic data though spot detection and quantification before proteins are compared for differential expression by spot matching. Recently, a more robust and automated paradigm has emerged where gels are directly …
Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris
Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris
Jeffrey S. Morris
Array-based comparative genomic hybridization (aCGH) is a high-resolution high-throughput technique for studying the genetic basis of cancer. The resulting data consists of log fluorescence ratios as a function of the genomic DNA location and provides a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimation of the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most current methods proceed by modeling a single sample/array at a time, and thus fail to borrow strength across multiple samples to infer shared regions of copy number aberrations. …
Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veera Baladandayuthapani
Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veera Baladandayuthapani
Veera Baladandayuthapani
No abstract provided.
Estimating Smooth Distribution Function In The Presence Of Heteroscedastic Measurement Errors, Xiao-Feng Wang, Zhaozhi Fan, Bin Wang
Estimating Smooth Distribution Function In The Presence Of Heteroscedastic Measurement Errors, Xiao-Feng Wang, Zhaozhi Fan, Bin Wang
Xiaofeng Wang
Measurement error occurs in many biomedical fields. The challenges arise when errors are heteroscedastic since we literally have only one observation for each error distribution. This paper concerns the estimation of smooth distribution function when data are contaminated with heteroscedastic errors. We study two types of methods to recover the unknown distribution function: a Fourier-type deconvolution method and a simulation extrapolation (SIMEX) method. The asymptotics of the two estimators are explored and the asymptotic pointwise confidence bands of the SIMEX estimator are obtained. The finite sample performances of the two estimators are evaluated through a simulation study. Finally, we illustrate …
Identification Of Ovarian Cancer Symptoms In Health Insurance Claims Data., Paula Diehr, Sean Devlin
Identification Of Ovarian Cancer Symptoms In Health Insurance Claims Data., Paula Diehr, Sean Devlin
Paula Diehr
Background: Women with ovarian cancer have reported abdominal=pelvic pain, bloating, difficulty eating or feeling full quickly, and urinary frequency=urgency prior to diagnosis. We explored these findings in a general population using a dataset of insured women aged 40–64 and investigated the potential effectiveness of a routine review of claims data as a prescreen to identify women at high risk for ovarian cancer. Methods: Data from a large Washington State health insurer were merged with the Seattle-Puget Sound Surveillance, Epidemiology and End Results (SEER) cancer registry for 2000–2004. We estimated the prevalence of symptoms in the 36 months prior to diagnosis …
Targeted Maximum Likelihood Estimation Of The Parameter Of A Marginal Structural Model, Michael Rosenblum, Mark J. Van Der Laan
Targeted Maximum Likelihood Estimation Of The Parameter Of A Marginal Structural Model, Michael Rosenblum, Mark J. Van Der Laan
Michael Rosenblum
Targeted maximum likelihood estimation is a versatile tool for estimating parameters in semiparametric and nonparametric models. We work through an example applying targeted maximum likelihood methodology to estimate the parameter of a marginal structural model. In the case we consider, we show how this can be easily done by clever use of standard statistical software. We point out differences between targeted maximum likelihood estimation and other approaches (including estimating function based methods). The application we consider is to estimate the effect of adherence to antiretroviral medications on virologic failure in HIV positive individuals.
Application Of Causal Inference Methods To Improve The Treatment Of Hiv In Resource-Limited Settings., Maya Petersen
Application Of Causal Inference Methods To Improve The Treatment Of Hiv In Resource-Limited Settings., Maya Petersen
Maya Petersen
No abstract provided.
Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh
Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh
Debashis Ghosh
In high-throughput studies involving genetic data such as from gene expression mi- croarrays, dierential expression analysis between two or more experimental conditions has been a very common analytical task. Much of the resulting literature on multiple comparisons has paid relatively little attention to the choice of test statistic. In this article, we focus on the issue of choice of test statistic based on a special pattern of dierential expression. The approach here is based on recasting multiple comparisons procedures for assessing outlying expression values. A major complication is that the resulting p-values are discrete; some theoretical properties of sequential testing …
Detecting Outlier Genes From High-Dimensional Data: A Fuzzy Approach, Debashis Ghosh
Detecting Outlier Genes From High-Dimensional Data: A Fuzzy Approach, Debashis Ghosh
Debashis Ghosh
A recent nding in cancer research has been the characterization of previously undis- covered chromosomal abnormalities in several types of solid tumors. This was found based on analyses of high-throughput data from gene expression microarrays and motivated the development of so-called `outlier' tests for dierential expression. One statistical issue was the potential discreteness of the test statistics. Using ideas from fuzzy set theory, we develop fuzzy outlier detection algorithms that have links to ideas in multiple comparisons. Two- and K-sample extensions are considered. The methodology is illustrated by application to two microarray studies.
Links Between Analysis Of Surrogate Endpoints And Endogeneity, Debashis Ghosh, Jeremy M. Taylor, Michael R. Elliott
Links Between Analysis Of Surrogate Endpoints And Endogeneity, Debashis Ghosh, Jeremy M. Taylor, Michael R. Elliott
Debashis Ghosh
There has been substantive interest in the assessment of surrogate endpoints in medical research. These are measures which could potentially replace \true" endpoints in clinical trials and lead to studies that require less follow-up. Recent research in the area has focused on assessments using causal inference frameworks. Beginning with a simple model for associating the surrogate and true endpoints in the population, we approach the problem as one of endogenous covariates. An instrumental variables estimator and general two-stage algorithm is proposed. Existing surrogacy frameworks are then evaluated in the context of the model. A numerical example is used to illustrate …
Meta-Analysis For Surrogacy: Accelerated Failure Time Models And Semicompeting Risks Modelling, Debashis Ghosh, Jeremy M. Taylor, Daniel J. Sargent
Meta-Analysis For Surrogacy: Accelerated Failure Time Models And Semicompeting Risks Modelling, Debashis Ghosh, Jeremy M. Taylor, Daniel J. Sargent
Debashis Ghosh
There has been great recent interest in the medical and statistical literature in the assessment and validation of surrogate endpoints as proxies for clinical endpoints in medical studies. More recently, authors have focused on using meta-analytical methods for quanti cation of surrogacy. In this article, we extend existing procedures for analysis based on the accelerated failure time model to this setting. An advantage of this approach relative to proportional hazards model is that it allows for analysis in the semi-competing risks setting, where we constrain the surrogate endpoint to occur before the true endpoint. A novel principal components procedure is …
Spline-Based Models For Predictiveness Curves, Debashis Ghosh, Michael Sabel
Spline-Based Models For Predictiveness Curves, Debashis Ghosh, Michael Sabel
Debashis Ghosh
A biomarker is dened to be a biological characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. The use of biomarkers in cancer has been advocated for a variety of purposes, which include use as surrogate endpoints, early detection of disease, proxies for environmental exposure and risk prediction. We deal with the latter issue in this paper. Several authors have proposed use of the predictiveness curve for assessing the capacity of a biomarker for risk prediction. For most situations, it is reasonable to assume monotonicity of …
Combining Multiple Models With Survival Data: The Phase Algorithm, Debashis Ghosh, Zheng Yuan
Combining Multiple Models With Survival Data: The Phase Algorithm, Debashis Ghosh, Zheng Yuan
Debashis Ghosh
In many scientic studies, one common goal is to develop good prediction rules based on a set of available measurements. This paper proposes a model averaging methodology using proportional hazards regression models to construct new estimators of predicted survival probabilities. A screening step based on an adaptive searching algorithm is used to handle large numbers of covariates. The nite-sample properties of the proposed methodology is assessed using simulation studies. Application of the method to a cancer biomarker study is also given.
Accounting For Response Misclassification And Covariate Measurement Error Improves Powers And Reduces Bias In Epidemiologic Studies, Dunlei Cheng, Adam J. Branscum, James D. Stamey
Accounting For Response Misclassification And Covariate Measurement Error Improves Powers And Reduces Bias In Epidemiologic Studies, Dunlei Cheng, Adam J. Branscum, James D. Stamey
Dunlei Cheng
Purpose: To quantify the impact of ignoring misclassification of a response variable and measurement error in a covariate on statistical power, and to develop software for sample size and power analysis that accounts for these flaws in epidemiologic data. Methods: A Monte Carlo simulation-based procedure is developed to illustrate the differences in design requirements and inferences between analytic methods that properly account for misclassification and measurement error to those that do not in regression models for cross-sectional and cohort data. Results: We found that failure to account for these flaws in epidemiologic data can lead to a substantial reduction in …
A Bayesian Approach To Sample Size Determination For Studies Designed To Evaluate Continuous Medical Tests, Dunlei Cheng, Adam J. Branscum, James D. Stamey
A Bayesian Approach To Sample Size Determination For Studies Designed To Evaluate Continuous Medical Tests, Dunlei Cheng, Adam J. Branscum, James D. Stamey
Dunlei Cheng
We develop a Bayesian approach to sample size and power calculations for cross-sectional studies that are designed to evaluate and compare continuous medical tests. For studies that involve one test or two conditionally independent or dependent tests, we present methods that are applicable when the true disease status of sampled individuals will be available and when it will not. Within a hypothesis testing framework, we consider the goal of demonstrating that a medical test has area under the receiver operating characteristic (ROC) curve that exceeds a minimum acceptable level or another relevant threshold, and the goals of establishing the superiority …
Statistical Criteria For Selecting The Optimal Number Of Untreated Subjects Matched To Each Treated Subject When Using Many-To-One Matching On The Propensity Score, Peter C. Austin
Peter Austin
Propensity-score matching is increasingly being used to estimate the effects of treatments using observational data. In many-to-one (M:1) matching on the propensity score, M untreated subjects are matched to each treated subject using the propensity score. The authors used Monte Carlo simulations to examine the effect of the choice of M on the statistical performance of matched estimators. They considered matching 1–5 untreated subjects to each treated subject using both nearest-neighbor matching and caliper matching in 96 different scenarios. Increasing the number of untreated subjects matched to each treated subject tended to increase the bias in the estimated treatment effect; …
The Performance Of Different Propensity-Score Methods For Estimating Differences In Proportions (Risk Differences Or Absolute Risk Reductions) In Observational Studies, Peter C. Austin
Peter Austin
Propensity score methods are increasingly being used to estimate the effects of treatments on health outcomes using observational data. There are four methods for using the propensity score to estimate treatment effects: covariate adjustment using the propensity score, stratification on the propensity score, propensity-score matching, and inverse probability of treatment weighting (IPTW) using the propensity score. When outcomes are binary, the effect of treatment on the outcome can be described using odds ratios, relative risks, risk differences, or the number needed to treat. Several clinical commentators suggested that risk differences and numbers needed to treat are more meaningful for clinical …