Biostatistics Commons^™

Targeted Learning Of The Probability Of Success Of An In Vitro Fertilization Program Controlling For Time-Dependent Confounders, Antoine Chambaz, Sherri Rose, Jean Bouyer, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Infertility is a global public health issue and various treatments are available. In vitro fertilization (IVF) is an increasingly common treatment method, but accurately assessing the success of IVF programs has proven challenging since they consist of multiple cycles. We present a double robust semiparametric method that incorporates machine learning to estimate the probability of success (i.e., delivery resulting from embryo transfer) of a program of at most four IVF cycles in the French Devenir Apr`es Interruption de la FIV (DAIFI) study and several simulation studies, controlling for time-dependent confounders. We find that the probability of success in the DAIFI …

Assessing The Causal Effect Of Policies: An Approach Based On Stochastic Interventions, Iván Díaz, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Stochastic interventions are a powerful tool to define parameters that measure the causal effect of a realistic intervention that intends to alter the population distribution of an exposure. In this paper we follow the approach described in D\'iaz and van der Laan (2011) to define and estimate the effect of an intervention that is expected to cause a truncation in the population distribution of the exposure. The observed data parameter that identifies the causal parameter of interest is established, as well as its efficient influence function under the non parametric model. Inverse probability of treatment weighted (IPTW), augmented IPTW and …

A Study Of Cellular Calcium Dynamics In Culture Using Fluorescence Microscopy – A Statistical And Mathematical Approach, Richard Adekola Idowu

Doctoral Dissertations

Calcium in its ionic form is very dynamic, especially in excitable cells such as muscle and brain cells, moving from the high concentration exterior of the cell to much lower concentrations inside the cell, where calcium is used as a second messenger. In brain cells, and neurons especially, calcium is a key signaling ion involved in memory and learning with excitatory neurotransmitters such as glutamate turning neurons "on." Glutamate excites the neurons in part by causing large and dynamic changes in the intracellular calcium concentration. While these dynamics are essential for normal signaling in the brain, excessive and sustained elevations …

Quantifying Alternative Splicing From Paired-End Rna-Sequencing Data, David Rossell, Camille Stephan-Otto Attolini, Manuel Kroiss, Almond Stöcker

COBRA Preprint Series

RNA-sequencing has revolutionized biomedical research and, in particular, our ability to study gene alternative splicing. The problem has important implications for human health, as alternative splicing is involved in malfunctions at the cellular level and multiple diseases. However, the high-dimensional nature of the data and the existence of experimental biases pose serious data analysis challenges. We find that the standard data summaries used to study alternative splicing are severely limited, as they ignore a substantial amount of valuable information. Current data analysis methods are based on such summaries and are hence sub-optimal. Further, they have limited flexibility in accounting for …

Effects Of Genetic Variants Previously Associated With Fasting Glucose And Insulin In The Diabetes Prevention Program, Jose C. Florez, Kathleen A. Jablonski, Jarred B. Mcateer, Paul W. Franks, Clinton C. Mason, Kieren J. Mather, Edward Horton, Ronald Goldberg, Dana Dabelea, Steven E. Kahn, Richard F. Arakaki, Alan R. Shuldiner, William C. Knowler

Epidemiology Faculty Publications

Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies) in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A,FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes …

Robust Estimation Of Pure/Natural Direct Effects With Mediator Measurement Error, Eric J. Tchetgen Tchetgen, Sheng Hsuan Lin

COBRA Preprint Series

Recent developments in causal mediation analysis have offered new notions of direct and indirect effects, that formalize more traditional and informal notions of mediation analysis emanating primarily from the social sciences. The pure or natural direct effect of Robins-Greenland-Pearl quantifies the causal effect of an exposure that is not mediated by a variable on the causal pathway to the outcome, and combines with the natural indirect effect to produce the total causal effect of the exposure. Sufficient conditions for identification of natural direct effects were previously given, that assume certain independencies about potential outcomes, and a rich literature on estimation …

Robust Estimation Of Pure/Natural Direct Effects With Mediator Measurement Error, Eric J. Tchetgen Tchetgen, Sheng Hsuan Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.

Measuring Infertility In Populations: Constructing A Standard Definition For Use With Demographic And Reproductive Health Surveys, Maya N. Mascarenhas, Hoiwan Cheung, Colin D. Mathers, Gretchen A. Stevens

Dartmouth Scholarship

Background: Infertility is a significant disability, yet there are no reliable estimates of its global prevalence. Studies on infertility prevalence define the condition inconsistently, rendering the comparison of studies or quantitative summaries of the literature difficult. This study analyzed key components of infertility to develop a definition that can be consistently applied to globally available household survey data.

Methods: We proposed a standard definition of infertility and used it to generate prevalence estimates using 53 Demographic and Health Surveys (DHS). The analysis was restricted to the subset of DHS that contained detailed fertility information collected through the reproductive health calendar. …

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, …