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III期肿瘤试验中具有统计学意义的生存推断脆弱性

Survival-inferred fragility of statistical significance in phase III oncology trials.

作者信息

Sherry Alexander D, Liu Yufei, Msaouel Pavlos, Lin Timothy A, Koong Alex, Lin Christine, Abi Jaoude Joseph, Patel Roshal R, Kouzy Ramez, El-Alam Molly B, Miller Avital M, Owiwi Mohannad, Ofer Jonathan, Bomze David, McCaw Zachary R, Meirson Tomer, Ludmir Ethan B

机构信息

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

Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA.

出版信息

NPJ Precis Oncol. 2025 Jul 24;9(1):256. doi: 10.1038/s41698-025-01024-2.

DOI:10.1038/s41698-025-01024-2
PMID:40707724
Abstract

In phase III oncology trials, superiority is defined by statistical significance using P thresholds. However, this approach has been criticized because P is continuous. Here, we reconstruct patient-level data for 230 phase III oncology trials to model the robustness of statistical significance by estimating the survival-inferred fragility index (SIFI), defined as the smallest number of patients changing arms that alters the statistical significance interpretation. The median SIFI was 8 patients (IQR 4-19), representing 1.4% of enrollments (IQR 0.7%-3%). As a continuous statistic, P-but not the significance interpretation-was correlated with SIFI. Moreover, overall survival endpoints were more fragile than surrogate endpoints. Taken together, while phase III oncology trials are intended to robustly inform patient care, shifting the assignment of a few patients is often sufficient to upend the statistical significance interpretation. This vulnerability underscores the need for more robust strategies to identify superiority in oncology.

摘要

在III期肿瘤学试验中,优越性是通过使用P值阈值的统计学显著性来定义的。然而,这种方法受到了批评,因为P值是连续的。在这里,我们重建了230项III期肿瘤学试验的患者水平数据,通过估计生存推断脆弱性指数(SIFI)来模拟统计学显著性的稳健性,SIFI定义为改变治疗组会改变统计学显著性解释的最少患者数量。SIFI的中位数为8名患者(四分位间距4-19),占入组人数的1.4%(四分位间距0.7%-3%)。作为一个连续统计量,P值(而非显著性解释)与SIFI相关。此外,总生存终点比替代终点更脆弱。综上所述,虽然III期肿瘤学试验旨在为患者护理提供有力依据,但改变少数患者的治疗分配往往足以颠覆统计学显著性解释。这种脆弱性凸显了在肿瘤学中需要更稳健的策略来确定优越性。

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本文引用的文献

1
Statistical Fragility of Findings From Randomized Phase 3 Trials in Pediatric Oncology.儿科肿瘤学随机3期试验结果的统计脆弱性
Cancer Med. 2024 Dec;13(24):e70356. doi: 10.1002/cam4.70356.
2
Evidenced-Based Prior for Estimating the Treatment Effect of Phase III Randomized Trials in Oncology.基于证据的 III 期随机临床试验治疗效果估计先验。
JCO Precis Oncol. 2024 Oct;8:e2400363. doi: 10.1200/PO.24.00363. Epub 2024 Oct 2.
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Increasing Power in Phase III Oncology Trials With Multivariable Regression: An Empirical Assessment of 535 Primary End Point Analyses.
在 III 期肿瘤学试验中使用多变量回归提高效能:对 535 项主要终点分析的实证评估。
JCO Clin Cancer Inform. 2024 Sep;8:e2400102. doi: 10.1200/CCI.24.00102.
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Proportional Hazards Violations in Phase III Cancer Clinical Trials: A Potential Source of Trial Misinterpretation.三期癌症临床试验中比例风险违反:潜在的试验误解来源。
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NEJM Evid. 2024 Jan;3(1):EVIDoa2300003. doi: 10.1056/EVIDoa2300003. Epub 2023 Dec 22.
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Semin Radiat Oncol. 2023 Oct;33(4):429-437. doi: 10.1016/j.semradonc.2023.06.007.
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A Causal Framework for Making Individualized Treatment Decisions in Oncology.肿瘤学中做出个体化治疗决策的因果框架。
Cancers (Basel). 2022 Aug 14;14(16):3923. doi: 10.3390/cancers14163923.
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