On information fraction for Fleming‐Harrington type weighted log‐rank tests in a group‐sequential clinical trial design. (24th February 2021)

• Record Type: Journal Article
• Authors: Kundu, Madan G.; Sarkar, Jyotirmoy
• Is Part Of: Statistics in medicine. Volume 40:Number 10(2021)
• Page Start: 2321
• Page End: 2338
• Publication Date: 2021-02-24
• Subjects: censoring distribution against events -- delayed effects -- early separation -- Fleming‐Harrington test -- information fraction -- interim analyses -- late separation -- nonproportional hazards -- time‐to‐event endpoint -- type I error; Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.8905
• Languages: English
• ISSNs: 0277-6715

Abstract

Abstract : When comparing survival times of treatment and control groups under a more realistic nonproportional hazards scenario, the standard log‐rank (SLR) test may be replaced by a more efficient weighted log‐rank (WLR) test, such as the Fleming‐Harrington (FH) test. Designing a group‐sequential clinical trial with one or more interim looks during which a FH test will be performed, necessitates correctly quantifying the information fraction (IF). For SLR test, IF is defined simply as the ratio of interim to final numbers of events; but for FH test, it can deviate substantially from this ratio. In this article, we separate the effect of weight function (of FH test) alone on IF from the effect of censoring. We have shown that, without considering the effect of censoring, IF can be derived analytically for FH test using information available at the design stage and the additional effect due to censoring is relatively smaller. This article intends to serve two major purposes: first, to emphasize and rationalize the deviation of IF in weighted log‐rank test from that of SLR test which is often overlooked (Jiménez, Stalbovskaya, and Jones); second, although it is impossible to predict IF for a weighted log‐rank test at the design stage, our decomposition of effects on IF provides a reasonable and practically feasible range of IF to work with. We illustrate our approach with an example and provide simulation results to evaluate operating characteristics.