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著名的HER2陽性早期乳腺癌術后拉帕替尼與曲妥珠單抗輔助治療優(yōu)化（ALLTO）隨機對照研究方案設計極其復雜,，入組患者將近萬例,，化費將近十億美元,，結果以拉帕替尼完敗而告終,。 ALTTO (Adjuvant Lapatinib And/Or Trastuzumab Treatment Optimisation) Study: A Randomised, Multi-centre, Open-label, Phase III Study of Adjuvant Lapatinib, Trastuzumab, Their Sequence and Their Combination in Patients With HER2/ErbB2 Positive Primary Breast Cancer; BIG 2-06/N063D; EGF106708 (NCT00490139) 2019年6月26日,，歐洲腫瘤內科學會《腫瘤學報》在線發(fā)表蘇格蘭前沿科學,、英國諾華,、美國國家癌癥研究所,、梅奧醫(yī)學中心、美國腫瘤臨床研究聯(lián)盟,、美國阿斯利康,、哈佛大學醫(yī)學院、哈佛大學陳曾熙公共衛(wèi)生學院,、達納法伯癌癥研究所,、波士頓前沿科學技術研究基金會、比利時布魯塞爾自由大學朱爾博爾代研究院,、國際乳腺癌協(xié)作組的報告,，分析了ALLTO研究統(tǒng)計學假設的教訓。 雖然隨機對照研究的設計,、實施和分析已經(jīng)具備標準,，但是取決于終點事件發(fā)生率（風險率）、治療效果比例（風險比）以及不同時間和不同亞組之間事件強度和類型差異的各種常用統(tǒng)計學假設可能受到質疑,，將來設計,、實施和分析隨機對照研究時必須審慎考慮。ALTTO研究于2007年6月～2011年7月入組HER2陽性早期乳腺癌患者8381例,，本文作者分析了常用統(tǒng)計學假設如何影響隨機對照研究結果報告,。 結果,，作者認為：
Ann Oncol. 2019 Jun 26. [Epub ahead of print] Are we assuming too much with our statistical assumptions? Lessons learned from the ALTTO Trial. Holmes EM, Bradbury I, Williams LS, Korde L, deAzambuja E, Fumagalli D, Moreno-Aspitia A, Baselga J, Piccart-Gebhart M, Dueck AC, Gelber RD. Frontier Science (Scotland), Kincraig, Kingussie, UK; Novartis Pharmaceuticals UK Limited, Frimley, UK; National Cancer Institute, Bethesda, MD, USA; Institut Jules Bordet, Université Libre de Bruxelles (U.L.B), Brussels, Belgium; Breast International Group (BIG), Brussels, Belgium; Alliance for Clinical Trials in Oncology, Mayo Clinic, Jacksonville, FL, USA; AstraZeneca, Gaithersburg, MD, USA; Alliance Statistics and Data Center, Mayo Clinic, Scottsdale, AZ, USA; Dana-Farber Cancer Institute, Harvard Medical School, Harvard T.H. Chan School of Public Health, Frontier Science and Technology Research Foundation, Boston, MA, USA. BACKGROUND: Design, conduct, and analysis of randomized clinical trials (RCTs) with time to event endpoints rely on a variety of assumptions regarding event rates (hazard rates), proportionality of treatment effects (proportional hazards), and differences in intensity and type of events over time and between subgroups. DESIGN AND METHODS: In this paper, we use the experience of the recently reported Adjuvant Lapatinib and/or Trastuzumab Treatment Optimization (ALTTO) RCT, which enrolled 8381 patients with HER2-positive early breast cancer between June 2007 and July 2011, to highlight how routinely applied statistical assumptions can impact RCT result reporting. RESULTS AND CONCLUSIONS: Futility stopping rules are important to protect patient safety, but stopping early for efficacy can be misleading as short-term results may not imply long-term efficacy. Biologically important differences between subgroups may drive clinically different treatment effects, and should be taken into account, e.g. by pre-specifying primary subgroup analyses and restricting endpoints to events which are known to be affected by the targeted-therapies. The usual focus on the Cox model may be misleading if we do not carefully consider non-proportionality of the hazards. The results of the accelerated failure time (AFT) model illustrate that giving more weight to later events (as in the log rank test) can affect conclusions. The assumption that accruing additional events will always ensure gain in power needs to be challenged. Changes in hazard rates and hazard ratios over time should be considered. Required family-wise control of type 1 error ≤ 5% in clinical trials with multiple experimental arms discourages investigations designed to answer more than one question. TRIAL REGISTRATION: clinicaltrials.gov Identifier NCT00490139 KEYWORDS: proportional hazards, stopping boundaries, accelerated failure time models, power, family-wise type 1 error, early breast cancer DOI: 10.1093/annonc/mdz195
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