University of Connecticut
Department of Statistics
Storrs, Connecticut
Presents the
Robert W. Makuch Distinguished Lecture
in Biostatistics
featuring
Martin Kulldorff, Ph.D.
Professor of Population Medicine
Harvard Medical School
Sequential Statistical Analysis for Post-Market Vaccine
and Drug Safety Surveillance
ABSTRACT
Post-market drug and vaccine safety surveillance is important in order to detect rare but serious adverse events not found during phase 2 or 3 clinical trials. Safety problems may go undetected either because the event is too rare to occur in sufficient numbers among the limited sample size of a phase three clinical trial, or because the adverse events only occur in a certain sub population that was excluded from the trial, such as children or people with heart problems. In order to detect a safety problem as soon as possible, frequent repeated analyses of cumulative post-market observational data are required, using sequential statistical analysis. The maximized sequential probability ratio test is an exact sequential method that has been used for both vaccine and drug safety surveillance. In this talk, those efforts are reviewed from both a methodological and public health perspective. We discuss and illustrate how statistical power and the expected time to signal are affected by study design issues such as whether to use continuous versus group sequential analysis. We give multiple examples from vaccine safety surveillance that uses weekly data feeds of observational data extracted from electronic medical records.
DATE: Wednesday, March 5, 2014
TIME: 4:00 p.m.
PLACE: Philip E. Austin Building – Room 105
Coffee will be served at 3:30 in AUST 326
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.
Martin Kulldorff, is a Professor and biostatistician in the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute. His main research interest is the development of statistical methods for disease surveillance, and the application of biostatistics in a wide range of medical studies.
Dr. Kulldorff has developed spatial and space-time scan statistics for geographical disease surveillance, including methods for the early detection of disease outbreaks. He is also very interested in vaccine and drug safety surveillance using different sequential analysis and data mining methods.
For more information, contact: Tracy Burke at tracy.burke@uconn.edu