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Design and Analysis of Clinical Trials with Non-proportional Hazards

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Robust Design and Analysis of Clinical Trials with Non-proportional Hazards: Methodology and Implementation in R

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Instructors: Satrajit Roychoudhury (Pfizer Inc) and Keaven M Anderson (Merck & Co., Inc)

Short course if free for ASA San Diego Chapter members. For non San Diego Chapter members, it would be $10 (one year San Diego Chapter membership included).

Overview:

Targeting the immune system has emerged as a promising treatment for cancer patients in recent years. Immunotherapy boosts the body's natural defenses to fight cancer. However, this novel treatment poses new challenges in the study design and statistical analysis of clinical trials. A major challenge is the delayed onset of treatment effects due to the mechanism of immunotherapy which violates the proportional hazard (PH) assumption. The conventional log-rank test may suffer a significant power loss in such scenarios.

This course will focus on different alternative design and analysis approaches for immune-oncology trials with potential non-proportional data. These include piecewise log-rank test and average hazard ratio, weighted log-rank test, combination tests and Kaplan-Meier based methods. The short course will also introduce a new approach based on a combination of multiple Fleming-Harrington WLR tests and is referred as the MaxCombo test which adaptively chooses best test depending on the underlying data. Finally, a stepwise approach for estimating treatment effect.

The short course will provide the analysis methodology, general design strategies, sample size calculation, evaluation of operating characteristics and necessary steps for protocol implementation in real life. The course with use real life examples and practical implementation with the new R package simtrial, gsDesign2 and gsdmvn.

PRESENTER(S):

Dr. Satrajit Roychoudhury is a Senior Director and a member of Statistical Research and Innovation group in Pfizer Inc. Prior to joining, he was a member of Statistical Methodology and Consulting group at Novartis. He started his career as a research statistician in Schering-Plough Research Institute (now Merck Co.). He has 12+ years of extensive experience in working in different phases of clinical trials. His primary expertise includes implementation of innovative statistical methodology in clinical trials. He has co-authored several publications/book chapters in this area and provided statistical training at major conferences. His areas of research include the use of survival analysis, model-informed drug development and Bayesian methods in clinical trials.

Dr. Keaven M Anderson is a Associate Scientific VP heading the Methodology Research biostatistics group at Merck where he has worked since 2003. He is a fellow of the ASA. Since completing his PhD in mathematical statistics at Stanford University and a post doc at the Harvard School of Public Health, Keaven has also worked at the Framingham Heart Study for the NIH prior to taking a pharmaceutical position at Centocor/J&J. He has long-standing interests in group sequential design and survival analysis. More recently, he has been interested in applications of multiplicity control using graphical methods and in trial design for immuno-oncology trials.

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