Clinical Trials Commons^™

Stratifying Subjects For Treatment Selection With Censored Event Time Data From A Comparative Study, Lihui Zhao, Tianxi Cai, Lu Tian, Hajime Uno, Scott D. Solomon, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Improving Statistical Analysis Of Prospective Clinical Trials In Stem Cell Transplantation. An Inventory Of New Approaches In Survival Analysis, Aurelien Latouche

COBRA Preprint Series

The CLINT project is an European Union funded project, run as a specific support action, under the sixth framework programme. It is a 2 year project aimed at supporting the European Group for Blood and Marrow Transplantation (EBMT) to develop its infrastructure for the conduct of trans-European clinical trials in accordance with the EU Clinical Trials Directive, and to facilitate International prospective clinical trials in stem cell transplantation. The initial task is to create an inventory of the existing biostatistical literature on new approaches to survival analyses that are not currently widely utilised. The estimation of survival endpoints is introduced, …

The Use Of Propensity Scores To Assess The Generalizability Of Results From Randomized Trials, Elizabeth A. Stuart, Stephen R. Cole, Catherine P. Bradshaw, Philip J. Leaf

Johns Hopkins University, Dept. of Biostatistics Working Papers

Randomized trials remain the most accepted design for estimating the effects of interventions, but they do not necessarily answer a question of primary interest: Will the program be effective in a target population in which it may be implemented? In other words,are the results generalizable? There has been very little statistical research on how to assess the generalizability, or "external validity," of randomized trials. We propose the use of propensity-score-based metrics to quantify the similarity of the participants in a randomized trial and a target population. In this setting the propensity score model predicts participation in the randomized trial, given …

Estimating Causal Effects In Trials Involving Multi-Treatment Arms Subject To Non-Compliance: A Bayesian Frame-Work, Qi Long, Roderick J. Little, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.

Assessing Noninferiority In A Three-Arm Trial Using The Bayesian Approach, Pulak Ghosh, Farouk S. Nathoo, Mithat Gonen, Ram C. Tiwari

Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series

Non-inferiority trials, which aim to demonstrate that a test product is not worse than a competitor by more than a pre-specified small amount, are of great importance to the pharmaceutical community. As a result, methodology for designing and analyzing such trials is required, and developing new methods for such analysis is an important area of statistical research. The three-arm clinical trial is usually recommended for non-inferiority trials by the Food and Drug Administration (FDA). The three-arm trial consists of a placebo, a reference, and an experimental treatment, and simultaneously tests the superiority of the reference over the placebo along with …

Nonparametric Regression With Missing Outcomes Using Weighted Kernel Estimating Equations, Lu Wang, Andrea Rotnitzky, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.

Utilizing The Integrated Difference Of Two Survival Functions To Quantify The Treatment Contrast For Designing, Monitoring And Analyzing A Comparative Clinical Study, Lihui Zhao, Lu Tian, Hajime Uno, Scott D. Solomon, Marc A. Pfeffer, J. S. Schindler, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Efficient Design And Inference For Multi-Stage Randomized Trials Of Individualized Treatment Policies, Ree Dawson, Philip W. Lavori

COBRA Preprint Series

Increased clinical interest in individualized ‘adaptive’ treatment policies has shifted the methodological focus for their development from the analysis of naturalistically observed strategies to experimental evaluation of a pre-selected set of strategies via multi-stage designs. Because multi-stage studies often avoid the ‘curse of dimensionality’ inherent in uncontrolled studies, and hence the need to parametrically smooth trial data, it is not surprising in this context to find direct connections among different methodological approaches. We show by asymptotic and algebraic proof that the maximum likelihood (ML) and optimal semi-parametric estimators of the mean of a treatment policy and its standard error are …

Graphical Procedures For Evaluating Overall And Subject-Specific Incremental Values From New Predictors With Censored Event Time Data, Hajime Uno, Tianxi Cai, Lu Tian, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Software Internationalization: A Framework Validated Against Industry Requirements For Computer Science And Software Engineering Programs, John Huân Vũ

Master's Theses

View John Huân Vũ's thesis presentation at http://youtu.be/y3bzNmkTr-c.

In 2001, the ACM and IEEE Computing Curriculum stated that it was necessary to address "the need to develop implementation models that are international in scope and could be practiced in universities around the world." With increasing connectivity through the internet, the move towards a global economy and growing use of technology places software internationalization as a more important concern for developers. However, there has been a "clear shortage in terms of numbers of trained persons applying for entry-level positions" in this area. Eric Brechner, Director of Microsoft Development Training, suggested …

Exploring The Benefits Of Adaptive Sequential Designs In Time-To-Event Endpoint Settings, Sarah C. Emerson, Kyle Rudser, Scott S. Emerson

UW Biostatistics Working Paper Series

Sequential analysis is frequently employed to address ethical and financial issues in clinical trials. Sequential analysis may be performed using standard group sequential designs, or, more recently, with adaptive designs that use estimates of treatment effect to modify the maximal statistical information to be collected. In the general setting in which statistical information and clinical trial costs are functions of the number of subjects used, it has yet to be established whether there is any major efficiency advantage to adaptive designs over traditional group sequential designs. In survival analysis, however, statistical information (and hence efficiency) is most closely related to …

Neurodevelopmental Outcome & Mr Spectroscopy Of Therapeutic Hypothermia After Pediatric Drowning, Sharon Mieras Perugini

Loma Linda University Electronic Theses, Dissertations & Projects

Despite advances in medical treatment and technology, outcome following pediatric drowning can vary widely from mild to severe impairments and death. Prognosis is often difficult to predict given a number of contributing factors. As such, this study examined the relationship between clinical indicators including submersion duration, initial GCS and PRISM scores, and waking time with outcome as well as metabolite ratios based on magnetic resonance spectroscopy. Research stemming from the area of cardiac arrest as well as anecdotal case study reports of cold water drownings suggests that lowering the body temperature may be helpful and protective. As such, the use …

The Effects Of Physical Activity And Nutrient Intake On The Risk Of Hip Fracture : Results From The Adventist Health Study-2, Wen-Ling Liao

Loma Linda University Electronic Theses, Dissertations & Projects

This is a two year of follow up study of Adventist Health Study-2 (AHS-2). We assessed the association between physical activity, nutrient intake and risk of hip fracture among peri- and post menopausal Caucasian women using unconditional logistic regression models. All subjects completed a lifestyle questionnaire which including information of physical activity and frequency and portion size of food intake at enrollment into the study (2002-2007). The “Bi-Annual Hospitalization History” questionnaire which included a question about hip fractures due to minor trauma/falls was sent to subjects approximately two years after enrollment, with a response rat of 82.84%. In this cohort, …

A Bayesian Shrinkage Model For Incomplete Longitudinal Binary Data With Application To The Breast Cancer Prevention Trial, C. Wang, M.J. Daniels, Daniel O. Scharfstein, S. Land

Johns Hopkins University, Dept. of Biostatistics Working Papers

We consider inference in randomized studies, in which repeatedly measured outcomes may be informatively missing due to drop out. In this setting, it is well known that full data estimands are not identified unless unverified assumptions are imposed. We assume a non-future dependence model for the drop-out mechanism and posit an exponential tilt model that links non-identifiable and identifiable distributions. This model is indexed by non-identified parameters, which are assumed to have an informative prior distribution, elicited from subject-matter experts. Under this model, full data estimands are shown to be expressed as functionals of the distribution of the observed data. …

Application Of Time-To-Event Methods In The Assessment Of Safety In Clinical Trials, Kelly L. Moore, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Since randomized controlled trials (RCT) are typically designed and powered for efficacy rather than safety, power is an important concern in the analysis of the effect of treatment on the occurrence of adverse events (AE). These outcomes are often time-to-event outcomes which will naturally be subject to right-censoring due to early patient withdrawals. In the analysis of the treatment effect on such an outcome, gains in efficiency, and thus power, can be achieved by exploiting covariate information. We apply the targeted maximum likelihood methodology to the estimation of treatment specific survival at a fixed end point for right-censored survival outcomes. …

Relaxing Latent Ignorability In The Itt Analysis Of Randomized Studies With Missing Data And Noncompliance, L Taylor, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Abstract: In this paper we consider the problem in causal inference of estimating the local complier average causal effect (CACE) parameter in the setting of a randomized clinical trial with a binary outcome, cross-over noncompliance, and unintentional missing data on the responses. We focus on the development of a moment estimator that relaxes the assumption of latent ignorability and incorporates sensitivity parameters that represent the relationship between potential outcomes and associated potential response indicators. If conclusions are insensitive over a range of logically possible values of the sensitivity parameters, then the number of interpretations of the data is reduced, and …

Multiple Imputation Methods For Treatment Noncompliance And Nonresponse In Randomized Clinical Trials, Leslie Taylor, Xiao-Hua (Andrew) Zhou

UW Biostatistics Working Paper Series

Summary: Randomized clinical trials are a powerful tool for investigating causal treatment effects, but in human trials there are oftentimes problems of noncompliance which standard analyses, such as the intention-to-treat or as-treated analysis, either ignore or incorporate in such a way that the resulting estimand is no longer a causal effect. One alternative to these analyses is the complier average causal effect (CACE) which estimates the average causal treatment effect among a subpopulation that would comply under any treatment assigned. We focus on the setting of a randomized clinical trial with crossover treatment noncompliance (e.g., control subjects could receive the …

Selecting Optimal Treatments Based On Predictive Factors, Eric C. Polley, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

No abstract provided.

In Step With Hiv Vaccines? A Content Analysis Of Local Recruitment Campaigns For An International Hiv Vaccine Study, Paula M. Frew, Wendy Macias, Kayshin Chan, Ashley Harding

Environmental & Global Health Faculty Research

During the past two decades of the HIV/AIDS pandemic, several recruitment campaigns were designed to generate community involvement in preventive HIV vaccine clinical trials. These efforts utilized a blend of advertising and marketing strategies mixed with public relations and community education approaches to attract potential study participants to clinical trials (integrated marketing communications). Although more than 30,000 persons worldwide have participated in preventive HIV vaccine studies, no systematic analysis of recruitment campaigns exists. This content analysis study was conducted to examine several United States and Canadian recruitment campaigns for one of the largest-scale HIV vaccine trials to date (the “Step …

Volunteer Studies In Pain Research — Opportunities And Challenges To Replace Animal Experiments: The Report And Recommendations Of A Focus On Alternatives Workshop, C. K. Langley, Q. Aziz, C. Bountra, N. Gordon, P. Hawkins, A. Jones, G. Langley, T. Nurmikko, I. Tracey

Experimentation Collection

Despite considerable research, effective and safe treatments for human pain disorders remain elusive. Understanding the biology of different human pain conditions and researching effective treatments continue to be dominated by animal models, some of which are of limited value. British and European legislation demands that non-animal approaches should be considered before embarking on research using experimental animals. Recent scientific and technical developments, particularly in human neuroimaging, offer the potential to replace some animal procedures in the study of human pain. A group of pain research experts from academia and industry met with the aim of exploring creatively the tools, strategies …

The Calculation Of The 97.5% Upper Confidence Bound: Application To Clustered Binary Data In A Binomial Non-Inferiority Two-Sample Trial., William F. Mccarthy

COBRA Preprint Series

This paper will discuss the analysis of a cluster randomized binomial non-inferiority two-sample trial. The determination of the intra-cluster correlation coefficient (ICC) and its use in the calculation of the 97.5% upper confidence bound for delta, the true difference in binomial proportions between the active control and the experimental treatment groups, will be outlined.

The Design And Sample Size Requirement For A Cluster Randomized Non-Inferiority Trial With Two Binary Co-Primary Outcomes., William F. Mccarthy

COBRA Preprint Series

This paper will discuss the design and sample size requirement for a cluster randomized non-inferiority trial with two binary co-primary outcomes. A hypothetical study (the EXAMPLE Trial) will be considered.

Lets assume the EXAMPLE Trial will consist of two separate binomial non-inferiority two-sample trials. Trial 1: the Coronary Artery Disease known population (co-primary 1) and Trial 2: the Coronary Artery Disease unknown population (co-primary 2). A physician-month cluster randomization scheme will be used. That is, for each trial (trial 1 and trial 2) every month for a 12-month period, each physician participating in the EXAMPLE Trial will be allocated a …

A Comparison Of Methods For Estimating The Causal Effect Of A Treatment In Randomized Clinical Trials Subject To Noncompliance, Rod Little, Qi Long, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.

Analysis Of Subgroup Effects In Randomized Trials When Subgroup Membership Is Informatively Missing: Application To The Madit Ii Study, Daniel O. Scharfstein, Georgiana Onicescu, Steven Goodman

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this paper, we develop and implement a general sensitivity analysis methodology for drawing inference about subgroup effects in a two-arm randomized trial when subgroup status is only known for a non-random sample in one of the trial arms. The methodology is developed in the context of the MADIT II study, a randomized trial designed to evaluate the effectiveness of implantable defibrillators on survival.

Causal Inference In Observational Studies With Outcome-Dependent Sampling, Weiwei Wang, Daniel Scharfstein, Zhiqiang Tan, Ellen J. Mackenzie

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this paper, we consider estimation of the causal effect of a treatment on an outcome from observational data collected in two phases. In the first phase, a simple random sample of individuals are drawn from a population. On these individuals, information is obtained on treatment, outcome, and a few low-dimensional confounders. These individuals are then stratified according to these factors. In the second phase, a random sub-sample of individuals are drawn from each stratum, with known, stratum-specific selection probabilities. On these individuals, a rich set of confounding factors are collected. In this setting, we introduce four estimators: (1) simple …

Nonparametric Inference Procedure For Percentiles Of The Random Effect Distribution In Meta Analysis, Rui Wang, Lu Tian, Tianxi Cai, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Parametric Non-Mixture Cure Models For Schedule-Finding Of Therapeutic Agents, Thomas M. Braun, Changying A. Liu

The University of Michigan Department of Biostatistics Working Paper Series

We propose a Phase I clinical trial design that seeks to determine the cumulative safety of a series of administrations of a fixed dose of an investigational agent. In contrast to traditional Phase I trials that are designed to solely find the maximum tolerated dose (MTD) of the agent, our design instead identifies a maximum tolerated schedule (MTS) that includes an MTD as well as a vector of recommended administration times. Our model is based upon a non-mixture cure model that constrains the probability of toxicity for all subjects to monotonically increase with both dose and the number of administrations …

Abstracts In High Profile Journals Often Fail To Report Harm, Enrique Bernal-Delgado, Elliot S. Fisher

Dartmouth Scholarship

To describe how frequently harm is reported in the abstract of high impact factor medical journals. We carried out a blinded structured review of a random sample of 363 Randomised Controlled Trials (RCTs) carried out on human beings, and published in high impact factor medical journals in 2003. Main endpoint: 1) Proportion of articles reporting harm in the abstract; and 2) Proportion of articles that reported harm in the abstract when harm was reported in the main body of the article. Analysis: Corrected Prevalence Ratio (cPR) and its exact confidence interval were calculated. Non-conditional logistic regression was used.

Targeted Methods For Biomarker Discovery, The Search For A Standard, Catherine Tuglus, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

More often than not biomarker studies analyze large quantities of variables with complicated and generally unknown correlation structure. There are numerous statistical methods which attempt to unravel these variables and determine the underlying mechanism through identification of causally related biomarkers. Results from these methods are generally difficult to interpret and nearly impossible to compare across studies. The FDA has currently called for a standardization of methods and protocol for biomarker detection. In response, we propose targeted variable importance (tVIM) as a standardized method for biomarker discovery. Through the use of targeted Maximum Likelihood, tVIM provides double robust estimates of variable …

Covariate Adjustment For The Intention-To-Treat Parameter With Empirical Efficiency Maximization, Daniel B. Rubin, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In randomized experiments, the intention-to-treat parameter is defined as the difference in expected outcomes between groups assigned to treatment and control arms. There is a large literature focusing on how (possibly misspecified) working models can sometimes exploit baseline covariate measurements to gain precision, although covariate adjustment is not strictly necessary. In Rubin and van der Laan (2008), we proposed the technique of empirical efficiency maximization for improving estimation by forming nonstandard fits of such working models. Considering a more realistic randomization scheme than in our original article, we suggest a new class of working models for utilizing covariate information, show …