在多变量回归的第三阶段瘤学试验中增加功率:对535个初级终点分析的实证评估
Alexander D Sherry1, Adina H Passy1, Zachary R McCaw2,3
1Department of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
JCO clinical cancer informatics
|August 30, 2024
概括
在III期瘤学试验中的多变量分析显著增加了对主要终点 (PEP) 证明优越性的可能性. 然而,像共变量分类这样的障碍限制了功率的增长,阻碍了获得新疗法的机会.
科学领域:
- 瘤学 临床试验 临床试验
- 生物统计学 生物统计学
- 基于证据的医学基于证据的医学.
背景情况:
- 第三阶段瘤学试验通常具有较低的统计能力,增加了假阴性结果的风险.
- 结合预后共变量的多变量模型是增强统计能力的潜在策略.
研究的目的:
- 研究多变量初级终点 (PEP) 分析在III期瘤学试验中的利用和影响.
- 测试假设,使用多变量PEP分析的试验比使用单变量分析的试验更有可能证明优越性.
主要方法:
- 在clinicaltrials.gov上注册的试验中对PEP分析进行了审查.
- 后勤回归模型被用来计算调整的赔率比率 (aORs),以比较优势结果.
主要成果:
- 在535项试验中,69%使用了多变量PEP分析.
- 使用多变量PEP分析的试验更有可能证明优越性 (57%对42%;aOR,1.78;P = .007).
- 在多变量模型中常见的分层分析通常会导致因共变量分类而导致功率损失,特别是在免疫治疗试验中.
结论:
- 在III期试验中使用多变量模型增加了证明PEP优势的可能性.
- 功率增长的障碍包括条件模型的不足利用和分层分析中的共变量分类造成的功率损失.
- 优化传统方法可以增强试验能力,改善患者获得有效的新型癌症疗法.
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