Immune checkpoint inhibitor--based therapies often produce heterogeneous survival responses, including early risk, delayed treatment benefit, and durable long-term survival in a subset of patients. In these settings, conventional summary measures such as the hazard ratio may not adequately describe how treatment effects evolve over follow-up. We propose a milestone-based framework that separates long-term survival beyond a clinically meaningful time point from earlier outcomes and provides a practical way to characterize patient heterogeneity in treatment response. The framework summarizes treatment differences through milestone survival probabilities and, among patients who do not reach the milestone, characterizes short-term treatment ordering over time using a tau-based summary that helps identify hazard reversal. We illustrate the approach using reconstructed individual-level data from three landmark phase III trials: CheckMate~067, CheckMate~227, and CLEAR. Across these examples, the framework captures patterns that are difficult to summarize with conventional measures, including settings in which early disadvantage coexists with later durable benefit. It also helps clarify when treatment benefit begins to emerge and how short-term and long-term effects differ within the same trial. This approach provides a clinically interpretable and statistically principled way to evaluate heterogeneous and time-varying treatment effects in oncology trials with nonproportional hazards.

翻译：基于免疫检查点抑制剂的疗法常产生异质性生存反应，包括早期风险、延迟的治疗获益以及部分患者的持久长期生存。在此类情形下，传统的汇总指标（如风险比）可能不足以描述治疗效果在随访过程中的演变规律。我们提出了一种基于里程碑的分析框架，该框架将超过临床上有意义时间点的长期生存与早期结局分离，并提供了一种实用方法来表征患者对治疗反应的异质性。该框架通过里程碑生存概率总结治疗效果差异，并针对未达到里程碑的患者，采用基于tau的汇总指标刻画其短期治疗排序随时间的变化，从而有助于识别风险逆转现象。我们利用三项里程碑式III期试验（CheckMate~067、CheckMate~227和CLEAR）的个体水平重建数据对该方法进行了验证。在实例分析中，该框架捕捉到了传统指标难以概括的模式，包括早期劣势与后期持久获益并存的情形。同时，该方法有助于厘清治疗获益的开始时间点，以及同一试验中短期效应与长期效应的差异。该框架为评估非比例风险条件下肿瘤学试验中异质性和时变治疗效果提供了具有临床可解释性和统计严整性的分析途径。