Biostatistics Commons^™

Multi-Tgdr, A Multi-Class Regularization Method, Identifies The Metabolic Profiles Of Hepatocellular Carcinoma And Cirrhosis Infected With Hepatitis B Or Hepatitis C Virus, Suyan Tian, Howard H. Chang, Chi Wang, Jing Jiang, Xiaomei Wang, Junqi Niu

Biostatistics Faculty Publications

BACKGROUND: Over the last decade, metabolomics has evolved into a mainstream enterprise utilized by many laboratories globally. Like other "omics" data, metabolomics data has the characteristics of a smaller sample size compared to the number of features evaluated. Thus the selection of an optimal subset of features with a supervised classifier is imperative. We extended an existing feature selection algorithm, threshold gradient descent regularization (TGDR), to handle multi-class classification of "omics" data, and proposed two such extensions referred to as multi-TGDR. Both multi-TGDR frameworks were used to analyze a metabolomics dataset that compares the metabolic profiles of hepatocellular carcinoma (HCC) …

A Bayesian Analysis Of The Spatial Concentration Of Individual Wealth In The Us North During The Nineteenth Century, Alice Kasakoff, Andrew Lawson, Emily Van Meter

Biostatistics Faculty Publications

Background: Kin effects can be difficult to distinguish from those of spatial proximity, since kin tend to live close to each other. Thus, past research showing correlations between the wealth of relatives may be showing the effects of proximity and shared locations, not the effects of kin.

Objective: What are the effects of kin and of spatial proximity upon wealth? This is studied both for fathers and sons and for brothers.

Methods: Data comes from a genealogical sample that has been linked to the US census of 1860. The genealogies allow us to identify fathers, sons, and …

Venue-Based Recruitment Of Women At Elevated Risk For Hiv: An Hiv Prevention Trials Network Study, Danielle F. Haley, Carol E. Golin, Wafaa M. El-Sadr, James P. Hughes, Jing Wang, Irene Kuo, +13 Additional Authors

Epidemiology Faculty Publications

Background: The challenge of identifying and recruiting U.S. women at elevated risk for HIV acquisition impedes prevention studies and services. HIV Prevention Trials Network (HPTN) 064 was a U.S. multisite, longitudinal cohort study designed to estimate HIV incidence among women living in communities with prevalent HIV and poverty. Venue-based sampling (VBS) methodologies and participant and venue characteristics are described.

Methods: Eligible women were recruited from 10 U.S. communities with prevalent HIV and poverty using VBS. Participant eligibility criteria included age 18–44 years, residing in a designated census tract/zip code, and self-report of at least one high-risk personal and/or male sexual …

The Impact Of Salsalate Treatment On Serum Levels Of Advanced Glycation End Products In Type 2 Diabetes., Joshua I Barzilay, Kathleen A. Jablonski, Vivian Fonseca, Steven E Shoelson, Allison B Goldfine, Christopher Strauch, Vincent M Monnier, Tinsal-T2d Research Consortium.

GW Biostatistics Center

OBJECTIVE Salsalate is a nonacetylated salicylate that lowers glucose levels in people with type 2 diabetes (T2D). Here we examined whether salsalate also lowered serum-protein-bound levels of early and advanced glycation end products (AGEs) that have been implicated in diabetic vascular complications. RESEARCH DESIGN AND METHODS Participants were from the Targeting Inflammation Using Salsalate for Type 2 Diabetes (TINSAL-T2D) study, which examined the impact of salsalate treatment on hemoglobin A1c (HbA1c) and a wide variety of other parameters. One hundred eighteen participants received salsalate, 3.5 g/day for 48 weeks, and 109 received placebo. Early glycation product levels (HbA1c and fructoselysine …

Genetic Risk Of Progression To Type 2 Diabetes And Response To Intensive Lifestyle Or Metformin In Prediabetic Women With And Without A History Of Gestational Diabetes Mellitus., Shannon D Sullivan, Kathleen A. Jablonski, Jose C Florez, Dana Dabelea, Paul W Franks, Sam Dagogo-Jack, Catherine Kim, William C Knowler, Costas A Christophi, Robert Ratner, Diabetes Prevention Program Research Group.

GW Biostatistics Center

OBJECTIVE The Diabetes Prevention Program (DPP) trial investigated rates of progression to diabetes among adults with prediabetes randomized to treatment with placebo, metformin, or intensive lifestyle intervention. Among women in the DPP, diabetes risk reduction with metformin was greater in women with prior gestational diabetes mellitus (GDM) compared with women without GDM but with one or more previous live births.

RESEARCH DESIGN AND METHODS We asked if genetic variability could account for these differences by comparing β-cell function and genetic risk scores (GRS), calculated from 34 diabetes-associated loci, between women with and without histories of GDM.

RESULTS β-Cell function was …

Metabolic Syndrome Components And Their Response To Lifestyle And Metformin Interventions Are Associated With Differences In Diabetes Risk In Persons With Impaired Glucose Tolerance, H. Florez, M. Temprosa, Trevor J. Orchard, Kieren J. Mather, Santica M. Marcovina, Elizabeth Barrett-Connor, Edward Horton, C. D. Saudek, F. X. Pi-Sunyer, R. E. Ratner, R. B. Goldberg

GW Biostatistics Center

Aims

To determine the association of metabolic syndrome (MetS) and its components with diabetes risk in participants with impaired glucose tolerance (IGT), and whether intervention-related changes in MetS lead to differences in diabetes incidence.

Methods

We used the National Cholesterol Education Program/Adult Treatment Panel III (NCEP/ATP III) revised MetS definition at baseline and intervention-related changes of its components to predict incident diabetes using Cox models in 3234 Diabetes Prevention Program (DPP) participants with IGT over an average follow-up of 3.2 years.

Results

In an intention-to-treat analysis, the demographic-adjusted hazard ratios (95% confidence interval) for diabetes in those with MetS (vs. …

Pre-Maceration, Saignée And Temperature Affect Daily Evolution Of Pigment Extraction During Vinification, Ottorino L. Pantani, Federico M. Stefanini, Irene Lozzi, Luca Calamai, Alessandra Biondi Bartolini, Stefano Di Blasi

COBRA Preprint Series

Consumer demand for intensely coloured wines necessitates the systematic testing of pigment extraction in Sangiovese, a cultivar poor in easily extractable anthocyanins. Pre-fermentation (absent, cold soak pre-fermentation at 5 °C, cryomaceration by liquid N₂ addition), temperature (20 or 30 °C), and saignée were compared during vinification (800 kg). Concentrations of anthocyanins, non-anthocyanic flavonoids and SO₂-resistant pigments were recorded daily. A semiparametric Bayesian model permitted the kinetic description and the comparison of sigmoidal- and exponential-like curves. In total anthocyanins, saignée at 30 °C yielded a significant gain, later lost at drawing off; cryomaceration had little effect and cold …

Bounds To Evaluate The Pure/Natural Direct Effect Without Cross-World Counterfactual Independence, Eric Tchetgen Tchetgen, Kelesitse Phiri

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Global Partial Likelihood Estimator Of The Time-Varying Effects For Time-Dependent Treatment, Huazhen Lin, Zhe Fei, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

The timing of time-dependent treatment - e.g., when to perform kidney transplantation - is an important factor for evaluating treatment efficacy. A naive comparison between the treatment and nontreatment groups, while ignoring the timing of treatment, typically yields results that might biasedly favor the treatment group, as only patients who survive long enough will get treated. On the other hand, studying the effect of time-dependent treatment is often complex, as it involves modeling treatment history and accounting for the possible time-varying nature of the treatment effect. We propose a varying-coefficient Cox model that investigates the efficacy of time-dependent treatment by …

A Unification Of Mediation And Interaction: A Four-Way Decomposition, Tyler J. Vanderweele

Harvard University Biostatistics Working Paper Series

It is shown that the overall effect of an exposure on an outcome, in the presence of a mediator with which the exposure may interact, can be decomposed into four components: (i) the effect of the exposure in the absence of the mediator, (ii) the interactive effect when the mediator is left to what it would be in the absence of exposure, (iii) a mediated interaction, and (iv) a pure mediated effect. These four components, respectively, correspond to the portion of the effect that is due to neither mediation nor interaction, to just interaction (but not mediation), to both mediation …

Five Fundamental Gaps In Nature-Nurture Science, Peter J. Taylor

Working Papers on Science in a Changing World

Difficulties identifying causally relevant genetic variants underlying patterns of human variation have been given competing interpretations. The debate is illuminated in this article by drawing attention to the issue of underlying heterogeneity—the possibility that genetic and environmental factors or entities underlying a trait are heterogeneous—as well as four other fundamental gaps in the methods and interpretation of classical quantitative genetics: "Genetic" and "environmental" fractions of variation in traits are distinct from measurable genetic and environmental factors underlying the traits’ development; Standard formulas for partitioning variation in human traits are unreliable; Methods for translation from fractions of variation to measurable …

New Malignancies After Squamous Cell Carcinoma And Melanomas: A Population-Based Study From Norway, Trude E. Robsahm, Margaret R. Karagas, Judy R. Rees, Astri Syse

Dartmouth Scholarship

Skin cancer survivors experience an increased risk for subsequent malignancies but the associated risk factors are poorly understood. This study examined the risk of a new primary cancer following an initial skin cancer and assessed risk factors associated with second primary cancers.

Efficiently Identifying Failures Using Quantitative Tests, Matrix-Pooling And The Em-Algorithm, Brett Hanscom, Susanne May, Jim Hughes

UW Biostatistics Working Paper Series

Pooled-testing methods can greatly reduce the number of tests needed to identify failures in a collection of samples. Existing methodology has focused primarily on binary tests, but there is a clear need for improved efficiency when using expensive quantitative tests, such as tests for HIV viral load in resource-limited settings. We propose a matrix-pooling method which, based on pooled-test results, uses the EM algorithm to identify individual samples most likely to be failures. Two hundred datasets for each of a wide range of failure prevalence were simulated to test the method. When the measurement of interest was normally distributed, at …

A Predictive Enrichment Procedure To Identify Potential Responders To A New Therapy For Randomized, Comparative, Controlled Clinical Studies, Junlong Li, Lihui Zhao, Lu Tian, Tianxi Cai, Brian Claggett, Andrea Callegaro, Benjamin Dizier, Bart Spiessens, Fernando Ulloa-Montoya, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

The Association Of Calcium Intake And Other Risk Factors With Cardiovascular Disease Among Obese Adults In Usa, Yang Chen, Sheryl Strasser, Katie Callahan, David Blackley, Yan Cao, Liang Wang, Shimin Zheng

ETSU Faculty Works

In this study, we used a cross-sectional study design to examine the relationship between the calcium intake and risk factors for CVD among obese adults by using continuous waves of National Health and Nutrition Examination Survey (NHANES) data 1999-2010. The association between calcium intake and risk factors of CVD (hypertension, total cholesterol, HDL, glycohemoglobin), CRP, albuminuria) is assessed among obese adults in USA. The incidence of Cardiovascular Disease (CVD) is high among obese people. The potential effects of inadequate calcium intake on CVD are receiving increased epidemiologic attention. Understanding the association between risk factors for CVD and calcium intake among …

A Novel Three Serum Phospholipid Panel Differentiates Normal Individuals From Those With Prostate Cancer, Nima Patel, Robert L. Vogel, Kumar Chandra-Kuntal, Wayne Glasgow, Uddhav Kelavkar

Biostatistics: Faculty Publications

Background: The results of prostate specific antigen (PSA) and digital rectal examination (DRE) screenings lead to both under and over treatment of prostate cancer (PCa). As such, there is an urgent need for the identification and evaluation of new markers for early diagnosis and disease prognosis. Studies have shown a link between PCa, lipids and lipid metabolism. Therefore, the aim of this study was to examine the concentrations and distribution of serum lipids in patients with PCa as compared with serum from controls.

Method: Using Electrospray ionization mass spectrometry (ESI-MS/MS) lipid profiling, we analyzed serum phospholipids from age-matched subjects who …

Clustering Survival Outcomes Using Dirichlet Process Mixture, Lili Zhao, Jingchunzi Shi, Tempie H. Shearon, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

Motivated by the national evaluation of mortality rates at kidney transplant centers in the United States, we sought to assess transplant center long- term survival outcomes by applying a methodology developed in Bayesian non-parametrics literature. We described a Dirichlet process model and a Dirichlet process mixture model with a Half-Cauchy for the estimation of the risk- adjusted effects of the transplant centers. To improve the model performance and interpretability, we centered the Dirichlet process. We also proposed strategies to increase model's classification ability. Finally we derived statistical measures and created graphical tools to rate transplant centers and identify outlying centers …

Mediation Analysis With Time-Varying Exposures And Mediators, Tyler J. Vanderweele, Eric Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

In this paper we consider mediation analysis when exposures and mediators vary over time. We give non-parametric identification results, discuss parametric implementation, and also provide a weighting approach to direct and indirect effects based on combining the results of two marginal structural models. We also discuss how our results give rise to a causal interpretation of the effect estimates produced from longitudinal structural equation models. When there are no time-varying confounders affected by prior exposure and mediator values, identification of direct and indirect effects is achieved by a longitudinal version of Pearl's mediation formula. When there are time-varying confounders affected …

A Phylogenetic Model For Understanding The Effect Of Gene Duplication On Cancer Progression, Qin Ma, Jaxk H. Reeves, David A. Liberles, Lili Yu, Zheng Chang, Jing Zhao, Juan Cui, Ying Xu, Liang Liu

Biostatistics: Faculty Publications

As biotechnology advances rapidly, a tremendous amount of cancer genetic data has become available, providing an unprecedented opportunity for understanding the genetic mechanisms of cancer. To understand the effects of duplications and deletions on cancer progression, two genomes (normal and tumor) were sequenced from each of five stomach cancer patients in different stages (I, II, III and IV). We developed a phylogenetic model for analyzing stomach cancer data. The model assumes that duplication and deletion occur in accordance with a continuous time Markov Chain along the branches of a phylogenetic tree attached with five extended branches leading to the tumor …

Regression Modeling Of Longitudinal Binary Outcomes With Outcome-Dependent Observation Times, Kay See Tan, Andrea B. Troxel, Stephen E. Kimmel, Kevin G. Volpp, Benjamin French

UPenn Biostatistics Working Papers

Conventional longitudinal data analysis methods assume that outcomes are independent of the data-collection schedule. However, the independence assumption may be violated, for example, when adverse events trigger additional physician visits in between prescheduled follow-ups. Observation times may therefore be associated with outcome values, which may introduce bias when estimating the eect of covariates on outcomes using standard longitudinal regression methods. Existing semi-parametric methods that accommodate outcome-dependent observation times are limited to the analysis of continuous outcomes. We develop new methods for the analysis of binary outcomes, while retaining the exibility of semi-parametric models. Our methods are based on counting process …