Department of Clinical Medicine (Biostatistics), Kitasato University School of Pharmacy, 5-9-1 Shirokane, Minato-ku, Tokyo 108-0072, Japan
Division of Population Sciences, Department of Medical Oncology, Dana Farber Cancer Institute, Boston, Massachusetts
JAMA Oncol. 2017 Dec 1;3(12):1692-1696. doi: 10.1001/jamaoncol.2017.2797.
In a comparative clinical study with progression-free survival (PFS) or overall survival (OS) as the end point, the hazard ratio (HR) is routinely used to design the study and to estimate the treatment effect at the end of the study. The clinical interpretation of the HR may not be straightforward, especially when the underlying model assumption is not valid. A robust procedure for study design and analysis that enables clinically meaningful interpretation of trial results is warranted.
To discuss issues of conventional trial design and analysis and to present alternatives to the HR using a recent immunotherapy study as an illustrative example.
DESIGN, SETTING, AND PARTICIPANTS: By comparing 2 groups in a survival analysis, we discuss issues of using the HR and present the restricted mean survival time (RMST) as a summary measure of patients’ survival profile over time. We show how to use the difference or ratio in RMST between 2 groups as an alternative for designing and analyzing a clinical study with an immunotherapy study as an illustrative example.
Overall survival or PFS. Group contrast measures included HR, RMST difference or ratio, and the event rate difference.
For the illustrative example, the HR procedure indicates that nivolumab significantly prolonged patient OS and was numerically better than docetaxel for PFS. However, the median PFS time of docetaxel was significantly better than that of nivolumab. Therefore, it may be difficult to use median OS and/or PFS to interpret of the HR value clinically. On the other hand, using RMST difference, nivolumab was significantly better than docetaxel for both OS and PFS. We also provide details regarding design of a future study with RMST-based measures.
The design and analysis of a conventional cancer clinical trial can be improved by adopting a robust statistical procedure that enables clinically meaningful interpretations of the treatment effect. The RMST-based quantitative method may be used as a primary tool for future cancer trials or to help us to better understand the clinical interpretation of the HR even when its model assumption is plausible.
在以无进展生存期 (PFS) 或总生存期 (OS) 为终点的对照临床研究中，风险比 (HR) 通常用于设计研究并在研究结束时估计治疗效果。HR 的临床解释可能并不直观，特别是当基础模型假设不成立时。需要一种稳健的研究设计和分析程序，以便对试验结果进行有意义的临床解释。
讨论传统试验设计和分析中的问题，并以最近的免疫治疗研究为例，介绍替代 HR 的方法。
设计、设置和参与者：通过对生存分析中的 2 组进行比较，我们讨论了使用 HR 的问题，并提出了受限平均生存时间 (RMST) 作为患者随时间生存状况的总结衡量标准。我们展示了如何使用 2 组之间的 RMST 差异或比值作为设计和分析临床试验的替代方法，以免疫治疗研究为例。
总生存或 PFS。组间对比指标包括 HR、RMST 差异或比值以及事件率差异。
对于该示例，HR 程序表明纳武单抗显著延长了患者的 OS，在 PFS 方面优于多西他赛，且数值上更好。然而，多西他赛的中位 PFS 时间明显优于纳武单抗。因此，使用中位 OS 和/或 PFS 来解释 HR 值可能具有一定难度。另一方面，使用 RMST 差异，纳武单抗在 OS 和 PFS 方面均明显优于多西他赛。我们还提供了有关基于 RMST 指标设计未来研究的详细信息。
通过采用稳健的统计程序，可以改善常规癌症临床试验的设计和分析，从而能够对治疗效果进行有意义的临床解释。RMST 为基础的定量方法可作为未来癌症试验的主要工具，或有助于我们更好地理解 HR 的临床解释，即使其模型假设合理。
