Informative event rate in study determination, study design, and interim analysis monitoring with non-proportional hazards

Fri, May 8, 2026, 08:00 – 09:00AM (PDT), 11:00 – 12:00 noon (EST)

Title: Informative event rate in study determination, study design, and interim analysis monitoring with non-proportional hazards

Abstract:

A cancer trial with an immunotherapy or antibody drug conjugate often has a certain delay/crossing time before the drug to take effect. In this paper, we propose to call the events that occur during and after the delay/crossing time as non-informative events and informative events, respectively. We propose to call the rate of number of informative events divided by total number of events as informative event rate, though this rate has been used in the literature. We show three innovative usages of  under non-proportional hazards (NPH) setting: (1) based on informative event rate, the minimum average hazard ratio (aHRmin) can be calculated analytically and used to determine whether trials are worth being conducted for a test drug to get a meaningful average hazard ratio (aHR) at the planning stage; (2) based on a series of informative event rate, aHR and power can be calculated and a proper design can be selected for a trial with a targeted aHR at the design stage; (3) based on informative event rate, a better interim analysis timing to ensure a certain probability for early efficacy/futility stopping can be determined during the course of a study. aHR and the probability for early efficacy/futility stopping under different enrollment scenarios in a simulation were verified by calculation. We propose the concepts of the informative event rate, aHRmin, and a targeted aHR and use them in study determination, study design, and interim analysis monitoring under an NPH setting with a delay/crossing time.

Speaker: Dr. Shufang Liu

Shufang Liu is a senior director of statistics at Vir Bio with 19 years of experience in industry. She worked at Gilead, Astellas, AbbVie, and PRA before joining Vir Bio. Her expertise spans early-to-late phase clinical trials. She is interested in advanced study design, Bayesian study design and analysis, seamless study design, utilization of real-world data, etc. She has co-authored over 10 peer-reviewed statistical papers.  She holds a Ph.D. in Statistics from North Caroline State University.