Optimal management of cancer patients relies heavily on late-phase oncology randomized controlled trials. A comprehensive understanding of the key considerations in designing and interpreting late-phase trials is crucial for improving subsequent trial design, execution, and clinical decision-making. In this review, we explore important aspects of late-phase oncology trial design. We begin by examining the selection of primary endpoints, including the advantages and disadvantages of using surrogate endpoints. We address the challenges involved in assessing tumor progression and discuss strategies to mitigate bias. We define informative censoring bias and its impact on trial results, including illustrative examples of scenarios that may lead to informative censoring. We highlight the traditional roles of the log-rank test and hazard ratio in survival analyses, along with their limitations in the presence of nonproportional hazards as well as an introduction to alternative survival estimands, such as restricted mean survival time or MaxCombo. We emphasize the distinctions between the design and interpretation of superiority and noninferiority trials, and compare Bayesian and frequentist statistical approaches. Finally, we discuss appropriate utilization of phase II and phase III trial results in shaping clinical management recommendations and evaluate the inherent risks and benefits associated with relying on phase II data for treatment decisions.

癌症患者的最佳治疗在很大程度上依赖于晚期肿瘤学随机对照试验。全面了解设计和解释后期试验的关键考虑因素对于改进后续试验设计、执行和临床决策至关重要。在这篇综述中，我们探讨了后期肿瘤学试验设计的重要方面。我们首先检查主要终点的选择，包括使用替代终点的优点和缺点。我们解决了评估肿瘤进展所涉及的挑战，并讨论了减轻偏差的策略。我们定义了信息审查偏差及其对试验结果的影响，包括可能导致信息审查的场景的说明性示例。我们强调了对数秩检验和风险比在生存分析中的传统作用，以及它们在存在非比例风险时的局限性，并介绍了替代生存估计值，例如限制平均生存时间或 MaxCombo。我们强调优效性和非劣效性试验的设计和解释之间的区别，并比较贝叶斯统计方法和频率统计方法。最后，我们讨论了在制定临床管理建议时如何适当利用 II 期和 III 期试验结果，并评估依赖 II 期数据做出治疗决策相关的固有风险和益处。