Informative censoring of surrogate end-point data in phase 3 oncology trials

Abstract

Background: Kaplan-Meier (K-M) analysis, the cornerstone of cancer clinical trial interpretation, assumes that censored patients are no more or less likely to experience an event than those followed. We sought to investigate the patterns of censoring in surrogate end-points of oncology randomised controlled trials (RCTs) and examine the relationship between censoring in practice-changing treatments that failed to demonstrate survival gain.

Methods: In this cross-sectional study of phase III RCTs published in the New England Journal of Medicine, Lancet, and JAMA, between 2010 and 2020, K-M curves of surrogate end-points with statistical significance were extracted. The reverse K-M method (i.e., events and censoring are flipped) was used to examine differential censoring using the analogous reverse hazard ratio and restricted mean survival time. Sensitivity analysis was performed by partially restoring the balance in censoring between study arms.

Results: Of the 73 eligible studies with significant surrogates, 33 (45%) reported significant overall survival benefit (concordant trials), and 40 (55%) did not (discordant trials). The proportion of studies with significant differential censoring in surrogates was 43% (17/40) and 51% (17/33) in discordant and concordant trials, respectively. Trials with a significant censoring imbalance in the experimental arm occurred only in discordant trials (15% vs 0%, odds ratio [OR] = 12.62, P = 0.033), compared to excessive censoring in the control arm which occurred more in concordant trials (28% vs 52%; OR = 0.36, P = 0.036). Although censoring imbalance occurred in both groups, after sensitivity analysis, 50% of the discordant trials lost their statistical significance, compared to 15% of concordant trials (OR = 5.6, P = 0.0018).

Conclusion: Censoring imbalance between study arms of RCTs suggests a potential systemic bias and raises uncertainty regarding the validity of the results. Informative censoring may explain the inconsistency between therapies that seem to improve disease outcomes without concomitant survival benefit and should trigger further investigation.

Keywords: Bias inclinical trials; Informative censoring; Kaplan–Meier curve; Randomized oncology trials; Survival analysis.