Physical Sciences and Mathematics Commons^™

Piscine Myocarditis Virus (Pmcv) In Wild Atlantic Salmon Salmo Salar, Torstein Tengs Dr.

Dr. Torstein Tengs

Cardiomyopathy syndrome (CMS) is a severe cardiac disease of sea-farmed Atlantic salmon Salmo salar L., but CMS-like lesions have also been found in wild Atlantic salmon. In 2010 a double-stranded RNA virus of the Totiviridae family, provisionally named piscine myocarditis virus (PMCV), was described as the causative agent of CMS. In the present paper we report the first detection of PMCV in wild Atlantic salmon. The study is based on screening of 797 wild Atlantic salmon by real-time RT-PCR. The samples were collected from 35 different rivers along the coast of Norway, and all individuals included in the study were …

Generalized Estimating Equations, Second Edition.Pdf, James W. Hardin, Joseph M.. Hilbe

Joseph M Hilbe

Generalized Estimating Equations, Second edition, updates the best-selling previous edition, which has been the standard text on the subject since it was published a decade ago. Combining theory and application, the text provides readers with a comprehensive discussion of GEE and related models. Numerous examples are employed throughout the text, along with the software code used to create, run, and evaluate the models being examined. Stata is used as the primary software for running and displaying modeling output; associated R code is also given to allow R users to replicate Stata examples. Specific examples of SAS usage are provided in …

A Pooled Analysis Of Smoking And Colorectal Cancer: Timing Of Exposure And Interactions With Environmental Factors

Shuo Jiao

Background:Considerable evidence suggests that cigarette smoking is associated with a higher risk of colorectal cancer. What is unclear, however, is the impact of quitting smoking on risk attenuation and whether other risk factors for colorectal cancer modify this association. Methods:We performed a pooled analysis of 8 studies, including 6,796 colorectal cancer cases and 7,770 controls to evaluate the association between cigarette smoking history and colorectal cancer risk, and to investigate potential effect modification by other risk factors. Results:Current smokers (OR=1.26, 95% CI=1.11-1.43) and former smokers (OR=1.18, 95% CI=1.09-1.27), relative to never smokers, showed higher risks of colorectal cancer. Former smokers …

Prevalence Of Tick Borne Encephalitis Virus In Tick Nymphs In Relation To Climatic Factors On The Southern Coast Of Norway, Torstein Tengs Dr.

Dr. Torstein Tengs

BACKGROUND

Tick-borne encephalitis (TBE) is among the most important vector borne diseases of humans in Europe and is currently identified as a major health problem in many countries. TBE endemic zones have expanded over the past two decades, as well as the number of reported cases within endemic areas. Multiple factors are ascribed for the increased incidence of TBE, including climatic change. The number of TBE cases has also increased in Norway over the past decade, and the human cases cluster along the southern coast of Norway. In Norway the distribution and prevalence of TBE virus (TBEV) in tick populations …

A Strain Of Piscine Myocarditis Virus (Pmcv) Infecting Argentina Silus (Ascanius), Torstein Tengs Dr.

Dr. Torstein Tengs

No abstract.

Targeted Maximum Likelihood Estimation For Dynamic Treatment Regimes In Sequential Randomized Controlled Trials, Paul Chaffee, Mark J. Van Der Laan

Paul H. Chaffee

Sequential Randomized Controlled Trials (SRCTs) are rapidly becoming essential tools in the search for optimized treatment regimes in ongoing treatment settings. Analyzing data for multiple time-point treatments with a view toward optimal treatment regimes is of interest in many types of afflictions: HIV infection, Attention Deficit Hyperactivity Disorder in children, leukemia, prostate cancer, renal failure, and many others. Methods for analyzing data from SRCTs exist but they are either inefficient or suffer from the drawbacks of estimating equation methodology. We describe an estimation procedure, targeted maximum likelihood estimation (TMLE), which has been fully developed and implemented in point treatment settings, …

Comparing Years Of Healthy Life, Measured In 16 Ways, For Normal Weight And Overweight Older Adults, Paula Diehr

Paula Diehr

Introduction. The traditional definitions of overweight and obesity are not age specific, even though the relationship of weight to mortality is different for older adults. Effects of adiposity on aspects of health beside mortality have not been well investigated. Methods. We calculated the number of years of healthy life (YHL) in the 10 years after baseline, for 5,747 older adults. YHL was defined in 16 different ways. We compared Normal and Overweight persons, classified either by bodymass index (BMI) or by waist circumference (WC). Findings. YHL for Normal and Overweight persons differed significantly in 25% of the comparisons, of which …

Quantification Of Piscine Reovirus (Prv) At Different Stages Of Atlantic Salmon Salmo Salar Production, Torstein Tengs Dr.

Dr. Torstein Tengs

The newly described piscine reovirus (PRV) appears to be associated with the development of heart and skeletal muscle inflammation (HSMI) in farmed Atlantic salmon Salmo salar L. PRV seems to be ubiquitous among fish in Norwegian salmon farms, but high viral loads and tissue distribution support a causal relationship between virus and disease. In order to improve understanding of the distribution of PRV in the salmon production line, we quantified PRV by using real-time PCR on heart samples collected at different points in the life cycle from pre-smolts to fish ready for slaughter. PRV positive pre-smolts were found in about …

Joint Generalized Models For Multi-Dimensional Outcomes: A Case Study Of Neuroscience Data From Multi-Modalities, Xiao-Feng Wang

Xiaofeng Wang

This paper is motivated from the analysis of neuroscience data in a study of neural and muscular mechanisms of muscle fatigue. Multidimensional outcomes of different natures were obtained simultaneously from multiple modalities, including handgrip force, electromyography (EMG), and functional magnetic resonance imaging (fMRI). We first study individual modeling of the univariate response depending on its nature. A mixed-effects beta model and a mixed-effects simplex model are compared for modeling the force/EMG percentages. A mixed-effects negative-binomial model is proposed for modeling the fMRI counts. Then, I present a joint modeling approach to model the multidimensional outcomes together, which allows us to …

Characterization Of Gene–Environment Interactions For Colorectal Cancer Susceptibility Loci

Shuo Jiao

Genome-wide association studies (GWAS) have identified more than a dozen loci associated with colorectal cancer (CRC) risk. Here, we examined potential effect-modification between single-nucleotide polymorphisms (SNP) at 10 of these loci and probable or established environmental risk factors for CRC in 7,016 CRC cases and 9,723 controls from nine cohort and case–control studies. We used meta-analysis of an efficient empirical-Bayes estimator to detect potential multiplicative interactions between each of the SNPs [rs16892766 at 8q23.3 (EIF3H/UTP23), rs6983267 at 8q24 (MYC), rs10795668 at 10p14 (FLJ3802842), rs3802842 at 11q23 (LOC120376), rs4444235 at 14q22.2 (BMP4), rs4779584 at 15q13 (GREM1), rs9929218 at 16q22.1 (CDH1), rs4939827 …

Powerful Cocktail Methods For Detecting Genome-Wide Gene-Environment Interaction, Li Hsu, Shuo Jiao, James Y. Dai, Carolyn M. Hutter, Ulrike Peters, Charles Kooperberg

Shuo Jiao

Identifying gene and environment interaction (G × E) can provide insights into biological networks of complex diseases, identify novel genes that act synergistically with environmental factors, and inform risk prediction. However, despite the fact that hundreds of novel disease-associated loci have been identified from genome-wide association studies (GWAS), few G×Es have been discovered. One reason is thatmost studies are underpowered for detecting these interactions. Several new methods have been proposed to improve power for G × E analysis, but performance varies with scenario. In this article, we present a module-based approach to integrating various methods that exploits each method’s most …

The Effects Of Error Magnitude And Bandwidth Selection For Deconvolution With Unknown Error Distribution, Xiao-Feng Wang, Deping Ye

Xiaofeng Wang

The error distribution is generally unknown in deconvolution problems with real applications. A separate independent experiment is thus often conducted to collect the additional noise data in those studies. In this paper, we study the nonparametric deconvolution estimation from a contaminated sample coupled with an additional noise sample. A ridge-based kernel deconvolution estimator is proposed and its asymptotic properties are investigated depending on the error magnitude. We then present a data-driven bandwidth selection algorithm with combining the bootstrap method and the idea of simulation extrapolation. The finite sample performance of the proposed methods and the effects of error magnitude are …

Sample Size Calculations For Roc Studies: Parametric Robustness And Bayesian Nonparametrics, Dunlei Cheng, Adam J. Branscum, Wesley O. Johnson

Dunlei Cheng

Methods for sample size calculations in ROC studies often assume independent normal distributions for test scores among the diseased and non-diseased populations. We consider sample size requirements under the default two-group normal model when the data distribution for the diseased population is either skewed or multimodal. For these two common scenarios we investigate the potential for robustness of calculated sample sizes under the mis-specified normal model and we compare to sample sizes calculated under a more flexible nonparametric Dirichlet process mixture model. We also highlight the utility of flexible models for ROC data analysis and their importance to study design. …

Statistical Methods For Proteomic Biomarker Discovery Based On Feature Extraction Or Functional Modeling Approaches, Jeffrey S. Morris

Jeffrey S. Morris

In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational …

Integrative Bayesian Analysis Of High-Dimensional Multi-Platform Genomics Data, Wenting Wang, Veerabhadran Baladandayuthapani, Jeffrey S. Morris, Bradley M. Broom, Ganiraju C. Manyam, Kim-Anh Do

Jeffrey S. Morris

Motivation: Analyzing data from multi-platform genomics experiments combined with patients’ clinical outcomes helps us understand the complex biological processes that characterize a disease, as well as how these processes relate to the development of the disease. Current integration approaches that treat the data are limited in that they do not consider the fundamental biological relationships that exist among the data from platforms.

Statistical Model: We propose an integrative Bayesian analysis of genomics data (iBAG) framework for identifying important genes/biomarkers that are associated with clinical outcome. This framework uses a hierarchical modeling technique to combine the data obtained from multiple platforms …

The Problem Of Partial Ordering In Phase I Clinical Trials, Nolan A. Wages

Nolan A. Wages

No abstract provided.

A Generalized Regression Model For Region Of Interest Analysis Of Fmri Data, Xiao-Feng Wang, Zhiguo Jiang, Janis J. Daly, Guang H. Yue

Xiaofeng Wang

In this study functional Magnetic Resonance Imaging (fMRI) was used to evaluate cortical motor network adaptation after a rehabilitation program for upper extremity motor function in chronic stroke patients. Patients and healthy controls were imaged when they attempted to perform shoulder–elbow and wrist–hand movements in a 1.5 T Siemens scanner. We perform fMRI analysis at both single- and group-subject levels. Activated voxel counts are calculated to quantify brain activation in regions of interest. We discuss several candidate regression models for making inference on the count data, and propose an application of a generalized negative-binomial model (GNBM) with structured dispersion in …

A Systematic Mapping Approach Of 16q12.2/Fto And Bmi In More Than 20,000 African Americans Narrows In On The Underlying Functional Variation: Results From The Population Architecture Using Genomics And Epidemiology (Page) Study

Shuo Jiao

Genetic variants in intron 1 of the fat mass– and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI–associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped …

Genome-Wide Search For Gene-Gene Interactions In Colorectal Cancer

Shuo Jiao

Genome-wide association studies (GWAS) have successfully identified a number of single-nucleotide polymorphisms (SNPs) associated with colorectal cancer (CRC) risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG) is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to …

Super Learning, Maya Petersen, M J. Van Der Laan

Maya Petersen

No abstract provided.

Diagnosing And Responding To Violations In The Positivity Assumption., Maya Petersen, K E. Porter, S Gruber, Y Wang, M J. Van Der Laan

Maya Petersen

No abstract provided.

Adaptive Matching In Randomized Trials And Observational Studies., M J. Van Der Laan, L Balzer, Maya Petersen

Maya Petersen

No abstract provided.

Pre-Specified Analysis Plans And Learning From Data. Where Are We And Where Are We Going?”, Maya Petersen

Maya Petersen

No abstract provided.

“'Loss-To-Follow-Up' In Observational Clinical Cohorts: Longitudinal Effect Estimation In The Presence Of Informative Monitoring.”, Maya Petersen

Maya Petersen

No abstract provided.

James-Stein Estimation And The Benjamini-Hochberg Procedure, Debashis Ghosh

Debashis Ghosh

For the problem of multiple testing, the Benjamini-Hochberg (B-H) procedure has become a very popular method in applications. Based on a spacings theory representation of the B-H procedure, we are able to motivate the use of shrinkage estimators for modifying the B-H procedure. Several generalizations in the paper are discussed, and the methodology is applied to real and simulated datasets.

Shrinkage In Adaptive Procedures For False Discovery Rate Estimation In Multiple Testing: Structure And Synthesis, Debashis Ghosh

Debashis Ghosh

There has been much interest in the study of adaptive estimation procedures for controlling the false discovery rate (FDR). In this article, we take the direct approach to estimation of FDR of Storey (2002) and show how it can reexpressed as a particular type of shrinkage estimator. This representation leads to natural conditions on finite-sample FDR control for a general class of shrinkage estimators. In addition, many previous proposals from the literature can be unified under this framework for which finite-sample FDR results can be developed. Some asymptotic results are also provided.

Proportional Mean Residual Life Model For Right-Censored Length-Biased Data, Gary Kwun Chuen Chan, Ying Qing Chen, Chongzhi Di

Chongzhi Di

To study disease association with risk factors in epidemiologic studies, cross-sectional sampling is often more focused and less costly for recruiting study subjects who have already experienced initiating events. For time-to-event outcome, however, such a sampling strategy may be length-biased. Coupled with censoring, analysis of length-biased data can be quite challenging, due to the so-called “induced informative censoring” in which the survival time and censoring time are correlated through a common backward recurrence time. We propose to use the proportional mean residual life model of Oakes and Dasu (1990) for analysis of censored length-biased survival data. Several nonstandard data structures, …

Comparing The Cohort Design And The Nested Case-Control Design In The Presence Of Both Time-Invariant And Time-Dependent Treatment And Competing Risks: Bias And Precision, Peter C. Austin

Peter Austin

Purpose: Observational studies using electronic administrative health care databases are often used to estimate the effects of treatments and exposures. Traditionally, a cohort design has been used to estimate these effects, but increasingly studies are using a nested case-control (NCC) design. The relative statistical efficiency of these two designs has not been examined in detail.

Methods: We used Monte Carlo simulations to compare these two designs in terms of the bias and precision of effect estimates. We examined three different settings: (A): treatment occurred at baseline and there was a single outcome of interest; (B): treatment was time-varying and there …

Using Ensemble-Based Methods For Directly Estimating Causal Effects: An Investigation Of Tree-Based G-Computation, Peter C. Austin

Peter Austin

Researchers are increasingly using observational or nonrandomized data to estimate causal treatment effects. Essential to the production of high-quality evidence is the ability to reduce or minimize the confounding that frequently occurs in observational studies. When using the potential outcome framework to define causal treatment effects, one requires the potential outcome under each possible treatment. However, only the outcome under the actual treatment received is observed, whereas the potential outcomes under the other treatments are considered missing data. Some authors have proposed that parametric regression models be used to estimate potential outcomes. In this study, we examined the use of …

Regression Trees For Predicting Mortality In Patients With Cardiovascular Disease: What Improvement Is Achieved By Using Ensemble-Based Methods?, Peter C. Austin

Peter Austin

In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1991-2001 and …