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在使用最小化方法的随机对照试验中,在非成比例的危险下进行非对象和重新随机化试验之间的比较
Ryusei Kimura1,2, Shogo Nomura3, Kengo Nagashima4
1Biostatistics Unit, Clinical and Translational Research Center, Keio University Hospital, Tokyo, 160-8582, Japan. kimura.ryusei@keio.jp.
BMC medical research methodology
|July 30, 2024
概括
重新随机化试验,特别是分层的MaxCombo试验,为分析随机对照试验中的生存数据提供了强大的力量,特别是当存在不成比例的危险时,随机化对照试验的最小化.
科学领域:
- 生物统计学 生物统计学
- 临床试验 临床试验
- 生存分析的分析.
背景情况:
- 波克-西蒙最小化是随机对照试验 (RCT) 中平衡治疗分配的常用方法.
- 传统的对生存结果的非对称测试可能是保守的,或者有膨胀的I型错误率,特别是在小样本或与不成比例的危险 (非PH).
- 现有的重新随机化测试在非PH的场景中是有限的,可能会降低统计能力.
研究的目的:
- 建议和评估使用最小化进行RCT的新型重新随机化试验,特别针对非PH场景.
- 将这些新测试的性能与现有的非对称和重新随机化方法进行比较.
- 在各种非PH条件下评估统计能力和I型错误率.
主要方法:
- 开发了两个重新随机化测试:加权日志等级测试的最大组合 (MaxCombo) 和受限平均存活时间 (dRMST) 的差异.
- 将这些测试与使用模拟数据与非PH (延迟,交叉,减小效应) 的日志级和Cox PH模型进行比较.
- 在不同的样本大小 (50,100,500) 和分配比率 (1:1) 中评估了性能.
主要成果:
- 重新随机化测试在零场景中保持了标称I型错误率.
- 未调整的非对应性测试过于保守;调整的非对应性测试 (Cox PH,dRMST) 在小样本大小 (n=50) 中显示出膨胀的I型错误率.
- 基于MaxCombo的分层重新随机化测试在所有测试的场景中始终表现出强大的统计能力.
结论:
- 重新随机化试验是利用最小化进行的RCT的一个有价值的替代方案,特别是在非PH的存在时.
- 分层的MaxCombo测试在各种非PH情况下提供了优越和强大的功率.
- 这些发现支持在复杂的试验设计中使用先进的重新随机化技术进行更可靠的生存分析.
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