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JAMA Netw Open. 2023 Apr 3;6(4):e236498. doi: 10.1001/jamanetworkopen.2023.6498.
2
Using and Understanding Survival Statistics - or How We Learned to Stop Worrying and Love the Kaplan-Meier Estimate.使用与理解生存统计数据——或者说我们是如何学会不再担忧并爱上卡普兰-迈耶估计法的。
Int J Radiat Oncol Biol Phys. 2023 Mar 15;115(4):839-846. doi: 10.1016/j.ijrobp.2022.11.035.
3
The MaxCombo Test Severely Violates the Type I Error Rate.MaxCombo测试严重违反了I型错误率。
JAMA Oncol. 2023 Apr 1;9(4):571-572. doi: 10.1001/jamaoncol.2022.7747.
4
High-Dose Once-Daily Thoracic Radiotherapy in Limited-Stage Small-Cell Lung Cancer: CALGB 30610 (Alliance)/RTOG 0538.局限期小细胞肺癌高剂量每日一次胸部放疗:CALGB 30610(Alliance)/RTOG 0538。
J Clin Oncol. 2023 May 1;41(13):2394-2402. doi: 10.1200/JCO.22.01359. Epub 2023 Jan 9.
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Interpreting the results of noninferiority trials-a review.非劣效性试验结果解读——综述
Br J Cancer. 2022 Nov;127(10):1755-1759. doi: 10.1038/s41416-022-01937-w. Epub 2022 Sep 15.
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Handling Informative Premature Treatment or Study Discontinuation for Assessing Between-Group Differences in a Comparative Oncology Trial.在比较肿瘤学试验中处理用于评估组间差异的信息性提前治疗或研究中止情况。
JAMA Oncol. 2022 Oct 1;8(10):1502-1503. doi: 10.1001/jamaoncol.2022.2394.
7
Log-Rank Test vs MaxCombo and Difference in Restricted Mean Survival Time Tests for Comparing Survival Under Nonproportional Hazards in Immuno-oncology Trials: A Systematic Review and Meta-analysis.对数秩检验与最大连续检验和受限平均生存时间检验在免疫肿瘤学试验中非比例风险下生存比较的比较:系统评价和荟萃分析。
JAMA Oncol. 2022 Sep 1;8(9):1294-1300. doi: 10.1001/jamaoncol.2022.2666.
8
Testing for Differences in Survival When Treatment Effects Are Persistent, Decaying, or Delayed.当治疗效果持续、衰减或延迟时,对生存差异进行检验。
J Clin Oncol. 2022 Oct 20;40(30):3537-3545. doi: 10.1200/JCO.21.01811. Epub 2022 Jun 29.
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Understanding the Differences Between Bayesian and Frequentist Statistics.理解贝叶斯统计与频率论统计之间的差异。
Int J Radiat Oncol Biol Phys. 2022 Apr 1;112(5):1076-1082. doi: 10.1016/j.ijrobp.2021.12.011.
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晚期肿瘤学试验设计和解读中的挑战、复杂性和注意事项。

Challenges, Complexities, and Considerations in the Design and Interpretation of Late-Phase Oncology Trials.

机构信息

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD.

Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX.

出版信息

Semin Radiat Oncol. 2023 Oct;33(4):429-437. doi: 10.1016/j.semradonc.2023.06.007.

DOI:10.1016/j.semradonc.2023.06.007
PMID:37684072
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10917127/
Abstract

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.

摘要

癌症患者的最佳管理在很大程度上依赖于晚期肿瘤随机对照试验。全面了解设计和解释晚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,我们探讨了晚期肿瘤试验设计的重要方面。我们首先研究了主要终点的选择,包括使用替代终点的优缺点。我们讨论了评估肿瘤进展所涉及的挑战,并探讨了减轻偏差的策略。我们定义了信息性删失偏差及其对试验结果的影响,包括可能导致信息性删失的情况的示例。我们强调了传统的对数秩检验和风险比在生存分析中的作用,以及它们在存在非比例风险时的局限性,以及对替代生存估计量的介绍,如受限平均生存时间或 MaxCombo。我们强调了优越性和非劣效性试验设计和解释之间的区别,并比较了贝叶斯和频率主义统计学方法。最后,我们讨论了在制定临床管理建议时如何合理利用 II 期和 III 期试验结果,并评估了依赖 II 期数据进行治疗决策的固有风险和益处。