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Updated: Jun 17, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Proportional Hazards Violations in Phase III Cancer Clinical Trials: A Potential Source of Trial Misinterpretation
Timothy A Lin1,2, Zachary R McCaw3,4, Alex Koong1
1Division of Radiation Oncology, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Purpose:
Survival analyses of novel agents with long-term responders often exhibit differential hazard rates over time. Such proportional hazards violations (PHV) may reduce the power of the log-rank test and lead to misinterpretation of trial results. We aimed to characterize the incidence and study attributes associated with PHVs in phase III oncology trials and assess the utility of restricted mean survival time and maximum combination test as additional analyses.
Experimental Design:
Clinicaltrials.gov and PubMed were searched to identify two-arm, randomized, phase III superiority-design cancer trials with time-to-event primary endpoints and published results through 2020. Patient-level data were reconstructed from published Kaplan-Meier curves. PHVs were assessed using Schoenfeld residuals.
Results:
Three hundred fifty-seven Kaplan-Meier comparisons across 341 trials were analyzed, encompassing 292,831 enrolled patients. PHVs were identified in 85/357 [23.8%; 95% confidence interval (CI), 19.7%, 28.5%] comparisons. In multivariable analysis, non-overall survival endpoints [OR, 2.16 (95% CI, 1.21, 3.87); P = 0.009] were associated with higher odds of PHVs, and immunotherapy comparisons [OR 1.94 (95% CI, 0.98, 3.86); P = 0.058] were weakly suggestive of higher odds of PHVs. Few trials with PHVs (25/85, 29.4%) prespecified a statistical plan to account for PHVs. Fourteen trials with PHVs exhibited discordant statistical signals with restricted mean survival time or maximum combination test, of which 10 (71%) reported negative results.
Conclusions:
PHVs are common across therapy types, and attempts to account for PHVs in statistical design are lacking despite the potential for results exhibiting nonproportional hazards to be misinterpreted.
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