University of Connecticut
Department of Statistics
Storrs, Connecticut
Presents the
Robert W. Makuch Distinguished Lecture
in Biostatistics
featuring
Jeremy M G Taylor, Ph.D.
Pharmacia Research Professor, Department of Biostatistics
Professor, Radiation Oncology
Associate Director for Biostatistics, Comprehensive Cancer Center
University of Michigan
Surrogacy assessment in clinical trials using principal stratification
ABSTRACT
In clinical trials, a surrogate outcome variable (S) can be measured before the true outcome of interest (T) and may provide early information regarding the treatment (Z) effect on T. Most previous methods for surrogate validation rely on models for the conditional distribution of T given Z and S. However, S is a post-randomization variable, and unobserved, simultaneous predictors of S and T may exist. When such confounders exist, these methods do not have a causal interpretation. Using the principal surrogacy framework introduced by Frangakis and Rubin (2002), we propose a Bayesian estimation strategy for surrogate validation when the joint distribution of potential surrogate and outcome measures is multivariate normal, and extend it using copulas to the case of an ordered categorical surrogate and a censored event time true endpoint. We model the joint conditional distribution of the potential outcomes of T, given the potential outcomes of S and propose surrogacy validation measures from this model. By conditioning on principal strata of S, the resulting estimates are causal. As the model is not fully identifiable from the data, we propose some reasonable prior distributions and assumptions that can be placed on weakly identified parameters to aid in estimation. The method is applied to data from a macular degeneration study and data from an advanced colorectal cancer clinical trial.
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Jeremy M G Taylor PhD is the Pharmacia Professor of Biostatistics at the University of Michigan. He obtained a Bachelor’s degree in Mathematics and a Diploma in Statistics from Cambridge University and a PhD in Statistics from University of California Berkeley. He was a faculty member in the Department of Biostatistics and the Department of Radiation Oncology at UCLA from 1983 to 1998. He is currently a faculty member in the Department of Biostatistics, the Department of Radiation Oncology and the Department of Computational Medicine and Bioinformatics and the Director of the Center for Cancer Biostatistics at the University of Michigan. He is the winner of the Michael Fry award from the Radiation Research Society and the Mortimer Spiegelman award from the American Public Health Association. He is a former Chair of the Biometrics section of the American Statistical Association and a Fellow of the ASA. He is the former chair of the Biostatistical Methods and Research Design grant review committee for the National Institutes of Health. He is currently one of the coordinating editors of Biometrics. He has 300 publications and research interests in longitudinal and survival data, cure models, methods for missing data, biomarkers, surrogate and auxiliary variables. He has worked extensively in AIDS research but currently mainly focusses on cancer research.
Robert Makuch is a professor in the Department of Biostatistics at the Yale School of Public Health and Director of the Regulatory Affairs Track. A graduate of the University of Connecticut (BA), University of Washington (MA – mathematics), and Yale University (MPhil, PhD), Professor Makuch worked at the National Cancer Institute (NCI) and the World Health Organization’s International Agency for Research on Cancer early in his career. He also was heavily involved in HIV research from the mid 80's through the early-mid 90's. He participated on the data monitoring committee for the original AZT vs. placebo randomized clinical trial in AIDS patients, and served on numerous committees for the NCI and the National Institute of Allergy and Infectious Diseases. He returned to Yale in 1986, and has worked extensively on methodologic issues in clinical trials and large population-based studies since. Another area of interest involves detection of rare adverse drug events, especially in the post-marketing environment. These area of methodologic research evolved as a result of his continued interest (since the mid 80s) in regulatory affairs science. In addition, Makuch developed a regulatory affairs track at YSPH for its students, and over the past 4 years has been the leader of numerous training programs for senior delegations of the Chinese Food and Drug Agency. His areas of medical application include cancer, HIV, arthritis, and cardiovascular disease.
In 2003, Makuch received the American Statistical Association Fellow Award for his numerous contributions to the field. In 2008, Makuch was received a Distinguished Alumni Award from the University of Connecticut. In 2012, Makuch was nominated to serve on the University of Connecticut' Dean's Advisory Board for the College of Liberal Arts and Sciences. He also developed a 5-year biostatistics training program in Japan, in collaboration with the Japanese government. His primary research interests continue to be methodologic issues in the design, conduct, and analysis of clinical and large-population/epidemiologic studies. Design and sample size considerations for Phase IV studies is another active research area, in which a new class of hybrid designs has been proposed for scientific and regulatory purposes to detect rare adverse events.
DATE: Wednesday, March 25, 2015
TIME: 4:00 p.m.
PLACE: Philip E. Austin Building – Room 105
Coffee will be served at 3:30 in AUST 326
For more information, contact: Tracy Burke at tracy.burke@uconn.edu