Biostatistics Commons^™

Genetic Modulation Of Lipid Profiles Following Lifestyle Modification Or Metformin Treatment: The Diabetes Prevention Program, Toni I. Pollin, Tamara Isakova, Kathleen A. Jablonski, Paul I.W. De Bakker, Andrew Taylor, Jarred B. Mcateer, Qing Pan, Edward Horton, Linda M. Delahanty, David Altshuler, Alan R. Shuldiner, Ronald Goldberg, Jose C. Florez, George A. Bray

Epidemiology Faculty Publications

Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04–1×10−17). Except for total HDL particles (r = −0.03, …

Targeted Learning For Causality And Statistical Analysis In Medical Research, Sherri Rose, Richard J.C.M. Starmans, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

The authors present the use of targeted learning methods for medical research, prepared as a chapter for the upcoming book "Statistics: Discovering Your Future Power." The targeted learning framework involves the explicit specification of the data, model, and parameter. The estimators are double robust and efficient, and can incorporate machine learning procedures such as the super learner.

Modeling Sleep Fragmentation In Populations Of Sleep Hypnograms, Bruce J. Swihart, Naresh M. Punjabi, Ciprian M. Crainiceanu

Johns Hopkins University, Dept. of Biostatistics Working Papers

We introduce methods for the analysis of large populations of sleep architectures (hypnograms) that respect the 5-state 20-transition-type structure defined by the American Academy of Sleep Medicine. By applying these methods to the hypnograms of 5598 subjects from the Sleep Heart Health Study we: 1) provide the firrst analysis of sleep hypnogram data of such size and complexity in a community cohort with a 4-level comorbidity; 2) compare 5-state 20-transition-type sleep to 3-state 6-transition-type sleep for a check of feasibility and information-loss; 3) extend current approaches to multivariate survival data analysis to populations of time-to-transition processes; and 4) provide scalable …

A Phase I Bayesian Adaptive Design To Simultaneously Optimize Dose And Schedule Assignments Both Among And Within Patients, Thomas M. Braun, Jin Zhang

The University of Michigan Department of Biostatistics Working Paper Series

In traditional schedule or dose-schedule finding designs, patients are assumed to receive their assigned dose-schedule combination throughout the trial even though the combination may be found to have an undesirable toxicity profile, which contradicts actual clinical practice. Since no systematic approach exists to optimize intra-patient dose-schedule as- signment, we propose a Phase I clinical trial design that extends existing approaches that optimize dose and schedule solely among patients by incorporating adaptive variations to dose-schedule assignments within patients as the study proceeds. Our design is based on a Bayesian non-mixture cure rate model that incorporates multiple administrations each patient receives with …

Fitting And Interpreting Continuous-Time Latent Markov Models For Panel Data, Jane M. Lange, Vladimir N. Minin

UW Biostatistics Working Paper Series

Multistate models are used to characterize disease processes within an individual. Clinical studies often observe the disease status of individuals at discrete time points, making exact times of transitions between disease states unknown. Such panel data pose considerable modeling challenges. Assuming the disease process progresses according a standard continuous-time Markov chain (CTMC) yields tractable likelihoods, but the assumption of exponential sojourn time distributions is typically unrealistic. More flexible semi-Markov models permit generic sojourn distributions yet yield intractable likelihoods for panel data in the presence of reversible transitions. One attractive alternative is to assume that the disease process is characterized by …

Transitions Among Health States Using 12 Measures Of Successful Aging: Results From The Cardiovascular Health Study, Stephen Thielke, Paula Diehr

UW Biostatistics Working Paper Series

Introduction

Successful aging has many dimensions, which may manifest differently in men and women and at different ages. We sought to characterize one-year transitions in 12 measures of successful aging among a large cohort of older adults.

Methods

We analyzed twelve different measures of health in the Cardiovascular Health Study: self-rated health, ADLs, IADLs, depression, cognition, timed walk, number of days spent in bed, number of blocks walked, extremity strength, recent hospitalizations, feelings about life as a whole, and life satisfaction. We dichotomized responses for each variable into “healthy” or “sick”, and estimated the prevalence of the healthy state and …

Flexible Covariate-Adjusted Exact Tests For Randomized Studies, Alisa J. Stephens, Eric J. Tchetgen Tchetgen, Victor De Gruttola

Harvard University Biostatistics Working Paper Series

No abstract provided.

Locally Efficient Estimation Of Marginal Treatment Effects When Outcomes Are Correlated: Is The Prize Worth The Chase?, Alisa J. Stephens, Eric J. Tchetgen Tchetgen, Victor De Gruttola

Harvard University Biostatistics Working Paper Series

No abstract provided.

Fall In C-Peptide During First 2 Years From Diagnosis: Evidence Of At Least Two Distinct Phases From Composite Type 1 Diabetes Trialnet Data., Carla J. Greenbaum, Craig A. Beam, David Boulware, Stephen E. Gitelman, Peter A. Gottlieb, Kevan C. Herold, John M. Lachin, Paula L. Mcgee, Jerry P. Palmer, Mark D. Pescovitz, Heidi Krause-Steinrauf, Jay S. Skyler, Jay M. Sosenko

Epidemiology Faculty Publications

Interpretation of clinical trials to alter the decline in β-cell function after diagnosis of type 1 diabetes depends on a robust understanding of the natural history of disease. Combining data from the Type 1 Diabetes TrialNet studies, we describe the natural history of β-cell function from shortly after diagnosis through 2 years post study randomization, assess the degree of variability between patients, and investigate factors that may be related to C-peptide preservation or loss. We found that 93% of individuals have detectable C-peptide 2 years from diagnosis. In 11% of subjects, there was no significant fall from baseline by 2 …

Genetic Susceptibility To Type 2 Diabetes: A Global Meta-Analysis Studying The Genetic Differences In Tunisian Populations, Rym Berhouma, S. Kouidhi, M. Ammar, H. Abid, T. Baroudi, H. Ennafaa, A. Benammar-Elgaaied

Human Biology Open Access Pre-Prints

The present study is the first meta-analysis to evaluate type 2 diabetes (T2D) - associated polymorphisms in cohorts originated from several Tunisian regions. In fact, we evaluated the effect of seven polymorphisms in the following genes; PPARg ( Pro12Ala), TNFα (-308A/G), ENPP1(K121Q), TCF7L2(rs7903146 C/T), MTHFR( C677T), ACE(I/D), CAPN10(3R/2R) on T2D risk, through a meta-analysis combining data of previous studies performed on Tunisian populations originating from the north, centre or south of the country. R statistics version 2.12.1 software was used to estimate the heterogeneity between studies. Pooled ORs were computed by the fixed-effects method of Mantel-Haenszel if no heterogeneity between …

Bayesian Adaptive Designs For Early Phase Clinical Trials, Chunyan Cai

Dissertations and Theses (Open Access)

My dissertation focuses mainly on Bayesian adaptive designs for phase I and phase II clinical trials. It includes three specific topics: (1) proposing a novel two-dimensional dose-finding algorithm for biological agents, (2) developing Bayesian adaptive screening designs to provide more efficient and ethical clinical trials, and (3) incorporating missing late-onset responses to make an early stopping decision.

Treating patients with novel biological agents is becoming a leading trend in oncology. Unlike cytotoxic agents, for which toxicity and efficacy monotonically increase with dose, biological agents may exhibit non-monotonic patterns in their dose-response relationships. Using a trial with two biological agents as …

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

U.C. Berkeley Division of Biostatistics Working Paper Series

In many randomized and observational studies the allocation of treatment among a sample of n independent and identically distributed units is a function of the covariates of all sampled units. As a result, the treatment labels among the units are possibly dependent, complicating estimation and posing challenges for statistical inference. For example, cluster randomized trials frequently sample communities from some target population, construct matched pairs of communities from those included in the sample based on some metric of similarity in baseline community characteristics, and then randomly allocate a treatment and a control intervention within each matched pair. In this case, …

A Comparison Of Methods Of Analysis To Control For Confounding In A Cohort Study Of A Dietary Intervention, Esinhart Hali

Theses and Dissertations

Comparing samples from different populations can be biased by confounding. There are several statistical methods that can be used to control for confounding. These include; multiple linear regression, propensity score matching, propensity score/logit of propensity score as a single covariate in a linear regression model, stratified analysis using propensity score quintiles, weighted analysis using propensity scores or trimmed scores. The data were from two studies of a dietary intervention (FIBERR and RNP). The outcome variable was change from baseline to one month for eight outcome measures; fat, fiber, and fruits/ vegetables behavior, fat, fiber, and fruits/vegetables intentions, fat and fruits/vegetables …

The Effect Of Baseline Cluster Stratification On The Power Of Pre-Post Analysis, Fengjiao Hu

Theses and Dissertations

The purpose of study is to check whether the power of detecting the effect of intervention versus control in a pre- and post-study can be increased by using a stratified randomized controlled design. A stratified randomized controlled design with two study arms and two time points, where strata are determined by clustering on baseline outcomes of the primary measure, is considered. A modified hierarchical clustering algorithm is developed which guarantees optimality as well as requiring each cluster to have at least one subject per study arm. The power is calculated based on simulated bivariate normal distributed primary measures with mixture …

Does Pair-Matching On Ordered Baseline Measures Increase Power: A Simulation Study, Yan Jin

Theses and Dissertations

It has been shown that pair-matching on an ordered baseline with normally distributed measures reduces the variance of the estimated treatment effect (Park and Johnson, 2006). The main objective of this study is to examine if pair-matching improves the power when the distribution is a mixture of two normal distributions. Multiple scenarios with a combination of different sample sizes and parameters are simulated. The power curves are provided for three cases, with and without matching, as follows: analysis of post-intervention data only, adding baseline as a covariate, and classic pre-post comparison. The study shows that the additional variance reduction provided …

Analytic Programming With Fmri Data: A Quick-Start Guide For Statisticians Using R, Ani Eloyan, Shanshan Li, John Muschelli, Jim Pekar, Stewart Mostofsky, Brian S. Caffo

Johns Hopkins University, Dept. of Biostatistics Working Papers

Functional magnetic resonance imaging (fMRI) is a thriving field that plays an important role in medical imaging analysis, biological and neuroscience research and practice. This manuscript gives a didactic introduction to the statistical analysis of fMRI data using the R project along with the relevant R code. The goal is to give tatisticians who would like to pursue research in this area a quick start for programming with fMRI data along with the available data visualization tools.

Assessing Movement Of Fish Through Spectral Analysis Of Otolith Life History Scans, Renee Reilly Hoover

OES Theses and Dissertations

The ability to accurately measure movement timing across environmental gradients is fundamental for testing hypotheses in marine ecology that deal with ingress, egress, and migration of fish. Timing and patterns of movement have been estimated using life-history scans of the chemical signatures encoded in fish otoliths (ear stones). I provide a quantitative approach to examining life history scan data using spectral analysis, which retrospectively measures the movement timing for individual fish. Sagittal otoliths from juvenile Atlantic croaker (Micropogonias undulates) and adult black sea bass (Centropristis striata) were sampled using laser ablation inductively coupled plasma mass spectrometry …

Causal Mediation In A Survival Setting With Time-Dependent Mediators, Wenjing Zheng, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

The effect of an expsore on an outcome of interest is often mediated by intermediate variables. The goal of causal mediation analysis is to evaluate the role of these intermediate variables (mediators) in the causal effect of the exposure on the outcome. In this paper, we consider causal mediation of a baseline exposure on a survival (or time-to-event) outcome, when the mediator is time-dependent. The challenge in this setting lies in that the event process takes places jointly with the mediator process; in particular, the length of the mediator history depends on the survival time. As a result, we argue …

On Identification Of Natural Direct Effects When A Confounder Of The Mediator Is Directly Affected By Exposure, Eric J. Tchetgen Tchetgen, Tyler J. Vanderweele

COBRA Preprint Series

Natural direct and indirect effects formalize traditional notions of mediation analysis into a rigorous causal framework and have recently received considerable attention in epidemiology and in the social sciences. Sufficient conditions for identification of natural direct effects were formulated by Judea Pearl under a nonparametric structural equations model, which assumes certain independencies between potential outcomes. A common situation in epidemiology is that a confounder of the mediator is affected by the exposure, in which case, natural direct effects fail to be nonparametrically identified without additional assumptions, even under Pearl's nonparametric structural equations model. In this paper, the authors show that …

Selective Impact Of Hiv Disease Progression On The Innate Immune System In The Human Female Reproductive Tract., Timothy Lahey, Mimi Ghosh, John V. Fahey, Zheng Sheng, Lucy R. Mukura, Yan Song, Susan Cu-Uvin, Kenneth H. Mayer, Peter F. Wright, John C. Kappes, Christina Ochsenbauer, Charles R. Wira

Epidemiology Faculty Publications

Background

We have previously demonstrated intrinsic anti-HIV activity in cervicovaginal lavage (CVL) from HIV-infected women with high CD4 counts and not on antiretroviral therapy. However, the impact of HIV disease progression on CVL innate immune responses has not been delineated.

Methods

CVL from 57 HIV-infected women not on antiretroviral therapy were collected by washing the cervicovaginal area with 10 ml of sterile normal saline. We characterized subject HIV disease progression by CD4 count strata: >500 cells/µl, 200–500 cells/µl, or <200 cells/µl of blood. To assess CVL anti-HIV activity, we incubated TZM-bl cells with HIV plus or minus CVL. Antimicrobials, cytokines, chemokines and anti-gp160 HIV IgG antibodies were measured by ELISA and Luminex.

Results

CVL exhibited broad anti-HIV activity against multiple laboratory-adapted and transmitted/founder (T/F) viruses, with anti-HIV activity ranging from 0 to 100% …

Adaptive Randomization Designs, Jenna Colavincenzo

Statistics

Adaptive design methodologies use prior information to develop a clinical trial design. The goal of an adaptive design is to maintain the integrity and validity of the study while giving the researcher flexibility in identifying the optimal treatment. An example of an adaptive design can be seen in a basic pharmaceutical trial. There are three phases of the overall trial to compare treatments and experimenters use the information from the previous phase to make changes to the subsequent phase before it begins.

Adaptive design methods have been in practice since the 1970s, but have become increasingly complex ever since. One …

Predictors Of Hypertension And Prehypertension In Cal Poly Students, Toria Mock

Statistics

This study analyzed predictors of hypertension and prehypertension in Cal Poly students. Hypertension and prehypertension are known to increase the risk of blood clots, plaque buildup, and tissue/organ damage from blocked arteries. Researching predictors of hypertension and prehypertension can help to determine methods of minimizing the probability of hypertension and prehypertension in a patient. Data from the FLASH study was used to analyze associations between possible predictor variables, such as stress and physical activity, and hypertension/prehypertension. BMI, bodyfat, and the interaction between videogames per weekend day and gender were found to be significantly associated with hypertension and prehypertension in Cal …

Change-Point Analysis Of Paired Allele-Specific Copy Number Variation Data, Yinglei Lai

GW Biostatistics Center

The recent genome-wide allele-specific copy number variation data enable us to explore two types of genomic information including chromosomal genotype variations as well as DNA copy number variations. For a cancer study, it is common to collect data for paired normal and tumor samples. Then, two types of paired data can be obtained to study a disease subject. However, there is a lack of methods for a simultaneous analysis of these four sequences of data. In this study, we propose a statistical framework based on the change-point analysis approach. The validity and usefulness of our proposed statistical framework are demonstrated …

Characteristics Of Children With Type 1 Diabetes And Persistent Suboptimal Glycemic Control., Hyuntae Kim, Angelo Elmi, Celia L. Henderson, Fran R. Cogen, Paul B. Kaplowitz

Epidemiology Faculty Publications

Objective: This study aims to determine the relationship between the duration of persistent poor glycemic control in type 1 diabetes mellitus (T1DM) children and the likelihood of subsequent improvement.

Methods: A retrospective cohort study was conducted on T1DM patients aged 6-18 years, followed for at least six visits at Children’s National Medical Center (Washington, DC) with at least one hemoglobin A1c (HbA1c) ≥10% after the first year since the initial visit (n=151). Medical records of patients with subsequently improved glycemic control were reviewed (n=39).

Results: Patients aged 12-18 years, females, and Medicaid patients were twice as likely to be in …

Unbiased Estimation For The Contextual Effect Of Duration Of Adolescent Height Growth On Adulthood Obesity And Health Outcomes Via Hierarchical Linear And Nonlinear Models, Robert Carrico

Theses and Dissertations

This dissertation has multiple aims in studying hierarchical linear models in biomedical data analysis. In Chapter 1, the novel idea of studying the durations of adolescent growth spurts as a predictor of adulthood obesity is defined, established, and illustrated. The concept of contextual effects modeling is introduced in this first section as we study secular trend of adulthood obesity and how this trend is mitigated by the durations of individual adolescent growth spurts and the secular average length of adolescent growth spurts. It is found that individuals with longer periods of fast height growth in adolescence are more prone to …

Families Or Unrelated: The Evolving Debate In Genetic Association Studies, David W. Fardo, Richard Charnigo, Michael P. Epstein

Biostatistics Faculty Publications

To help uncover the genetic determinants of complex disease, a scientist often designs an association study using either unrelated subjects or family members within pedigrees. But which of these two subject recruitment paradigms is preferable? This editorial addresses the debate over the relative merits of family- and population-based genetic association studies. We begin by briefly recounting the evolution of genetic epidemiology and the rich crossroads of statistics and genetics. We then detail the arguments for the two aforementioned paradigms in recent and current applications. Finally, we speculate on how the debate may progress with the emergence of next-generation sequencing technologies.

Dna Methylation Arrays As Surrogate Measures Of Cell Mixture Distribution, Eugene Houseman, William P. Accomando, Devin C. Koestler, Brock C. Christensen, Carmen J. Marsit

Dartmouth Scholarship

There has been a long-standing need in biomedical research for a method that quantifies the normally mixed composition of leukocytes beyond what is possible by simple histological or flow cytometric assessments. The latter is restricted by the labile nature of protein epitopes, requirements for cell processing, and timely cell analysis. In a diverse array of diseases and following numerous immune-toxic exposures, leukocyte composition will critically inform the underlying immuno-biology to most chronic medical conditions. Emerging research demonstrates that DNA methylation is responsible for cellular differentiation, and when measured in whole peripheral blood, serves to distinguish cancer cases from controls.

Why Odds Ratio Estimates Of Gwas Are Almost Always Close To 1.0, Yutaka Yasui

COBRA Preprint Series

“Missing heritability” in genome-wide association studies (GWAS) refers to the seeming inability for GWAS data to capture the great majority of genetic causes of a disease in comparison to the known degree of heritability for the disease, in spite of GWAS’ genome-wide measures of genetic variations. This paper presents a simple mathematical explanation for this phenomenon, assuming that the heritability information exists in GWAS data. Specifically, it focuses on the fact that the great majority of association measures (in the form of odds ratios) from GWAS are consistently close to the value that indicates no association, explains why this occurs, …

Analyzing Multiple Independent Spatial Point Processes, Neal Grantham

Statistics

No abstract provided.

Differential Patterns Of Interaction And Gaussian Graphical Models, Masanao Yajima, Donatello Telesca, Yuan Ji, Peter Muller

COBRA Preprint Series

We propose a methodological framework to assess heterogeneous patterns of association amongst components of a random vector expressed as a Gaussian directed acyclic graph. The proposed framework is likely to be useful when primary interest focuses on potential contrasts characterizing the association structure between known subgroups of a given sample. We provide inferential frameworks as well as an efficient computational algorithm to fit such a model and illustrate its validity through a simulation. We apply the model to Reverse Phase Protein Array data on Acute Myeloid Leukemia patients to show the contrast of association structure between refractory patients and relapsed …