Division of Radiation Oncology, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Clin Cancer Res. 2024 Oct 15;30(20):4791-4799. doi: 10.1158/1078-0432.CCR-24-0566.
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.
目的:对具有长期应答者的新型药物进行生存分析时,通常会发现随时间变化的风险率存在差异。这种比例风险违反(PHV)可能会降低对数秩检验的功效,并导致对试验结果的错误解释。我们旨在描述在三期肿瘤学试验中 PHV 的发生率和相关研究特征,并评估受限平均生存时间和最大组合检验作为附加分析的效用。 实验设计:通过检索 Clinicaltrials.gov 和 PubMed,我们识别了两项双臂、随机、三期优效设计的癌症试验,这些试验均具有时间事件主要终点和 2020 年前发表的结果。通过已发表的 Kaplan-Meier 曲线重建患者水平数据。使用 Schoenfeld 残差评估 PHV。 结果:对 341 项试验中的 357 个 Kaplan-Meier 比较进行了分析,共纳入 292831 名入组患者。在 357 个 Kaplan-Meier 比较中有 85 个(23.8%;95%置信区间,19.7%,28.5%)被识别为 PHV。在多变量分析中,非总生存终点(OR,2.16;95%置信区间,1.21,3.87;P=0.009)与 PHV 发生的可能性更高相关,免疫治疗比较(OR,1.94;95%置信区间,0.98,3.86;P=0.058)则表明 PHV 的可能性略高。仅有少数(25/85,29.4%)发生 PHV 的试验事先制定了用于处理 PHV 的统计计划。在发生 PHV 的 14 项试验中,有 10 项(71%)采用受限平均生存时间或最大组合检验得到的统计信号不一致,且均报告了阴性结果。 结论:PHV 在各种治疗类型中都很常见,尽管存在对非比例风险结果解释错误的可能性,但在统计设计中尝试考虑 PHV 的情况却很少。
Cochrane Database Syst Rev. 2022-2-1
Clin Trials. 2020-10
BMC Med Res Methodol. 2022-1-30
NPJ Precis Oncol. 2025-7-24
ESMO Open. 2025-4
JAMA Netw Open. 2023-4-3
JAMA Oncol. 2023-4-1
Pharm Stat. 2023-1
Eur J Cancer. 2022-1