In most clinical oncology trials, time-to-first-event analyses are used for efficacy assessment, which often do not capture the entire disease process. Instead, the focus may be on more complex time-to-event endpoints, such as the course of disease after the first event or endpoints occurring after randomization. We propose "relapse- and immunosuppression-free survival" (RIFS) as an innovative and clinically relevant outcome measure for assessing treatment success after hematopoietic stem cell transplant (SCT). To capture the time-dynamic relationship of multiple episodes of immunosuppressive therapy during follow-up, relapse, and nonrelapse mortality, a multistate model was developed. The statistical complexity is that the probability of RIFS is nonmonotonic over time; thus, standard time-to-first-event methodology is inappropriate for formal treatment comparisons. Instead, a generalization of the Kaplan-Meier method was used for probability estimation, and simulation-based resampling was suggested as a strategy for statistical inference. We reanalyzed data from a recently published phase III trial in 201 leukemia patients after SCT. The study evaluated long-term treatment success of standard graft-versus-host disease prophylaxis plus a pretransplant antihuman T-lymphocyte immunoglobulin compared with standard prophylaxis alone. Results suggested that treatment increased the long-term probability of RIFS by approximately 30% during the entire follow-up period, which complements the original findings. This article highlights the importance of complex endpoints in oncology, which provide deeper insight into the treatment and disease process over time. Multistate models combined with resampling are highlighted as a promising tool to evaluate treatment success beyond standard endpoints. An example code is provided in the Supplementary Materials.

中文翻译：

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造血干细胞移植后无复发和无免疫抑制的存活：我们如何评估复杂的事件发生终点的治疗成功率？

在大多数临床肿瘤学试验中，使用首次发病时间分析进行疗效评估，但往往无法捕获整个疾病过程。取而代之的是，重点可能放在更复杂的事件发生时间终点上，例如第一次事件后的病程或随机化之后发生的终点。我们提出“无复发和无免疫抑制生存”（RIFS）作为评估造血干细胞移植（SCT）后治疗成功的创新和临床相关结果指标。为了捕获随访，复发和非复发死亡率期间免疫抑制治疗多次发作的时间动态关系，开发了一种多状态模型。统计上的复杂性是RIFS的概率随时间变化是非单调的。从而，标准的首次发病时间方法不适用于正式治疗比较。取而代之的是，将Kaplan-Meier方法的一般化用于概率估计，并建议将基于仿真的重采样作为统计推断的策略。我们重新分析了最近发表的SCT后201例白血病患者的III期试验数据。这项研究评估了标准的移植物抗宿主疾病预防措施加上移植前抗人T淋巴细胞免疫球蛋白与单独的标准预防措施相比的长期治疗效果。结果表明，在整个随访期间，治疗可使RIFS的长期可能性增加约30％，这与最初的发现相辅相成。本文强调了肿瘤学中复杂终点的重要性，随着时间的流逝，可以提供对治疗和疾病过程的更深入了解。多状态模型与重采样相结合被强调为评估超出标准终点的治疗成功与否的有前途的工具。补充材料中提供了示例代码。