The Heterogeneity Effect of Surveillance Intervals on Progression-Free Survival

• Activity Number: 470 - Lifetime Risk, Competing Risk, and Recurrent Events
• Type: Contributed
• Date/Time: Thursday, August 6, 2020 : 10:00 AM to 2:00 PM
• Sponsor: Lifetime Data Science Section
• Author(s): Jingwei Wu* and Zihang Zhong and Jianling Bai and Hao Yu
• Companies: College pf Public Health, Temple University and Department of Biostatistics, School of Public Health, Nanjing Medical University and School of Public Health, Nanjing Medical University and School of Public Health, Nanjing Medical University
• Keywords: progression-free survival; surveillance interval; cancer clinical trial; false positive rate; power

Abstract

Progression-free survival (PFS) is an increasingly important surrogate endpoint in cancer clinical trial. However, the true time of progression is typically unknown if evaluation of progression status is only scheduled at given surveillance intervals. In addition, comparisons between treatment arms under different surveillance schema is not uncommon. Thus, any analysis that ignores uncertainty of progression time and heterogeneity effect of surveillance intervals may lead to unexpected bias on the conclusion of efficacy. In this research, we explore whether the heterogeneity of the surveillance intervals may interfere with the validity of the conclusion of efficacy based on PFS, and the extent to which the variation would bias the results. Herein, simulation data of the true progression times is generated from a Weibull distribution with uniform censoring. We calculate the hazard ratios and examine false positive rate, power and bias under different surveillance intervals, given different median PFS and censoring rate setting. We show that heterogeneous surveillance intervals need to be accommodated appropriately in the PFS analysis of efficacy between different treatments.