发表机构
Health Services Research Centre, Akershus University Hospital; Maths in Health B.V.（阿克什胡斯大学医院健康服务研究中心; Maths in Health 有限公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对随机撤药试验中应答者基线特征缺失导致的人群调整间接比较受限问题，提出再随机化概率加权方法，经合成试验及模拟验证可降低持久应答偏差，实现跨试验设计的人群调整比较。
AI 中文摘要
随机撤药试验会将诱导期应答者再随机分配至继续治疗或撤药组。基线特征通常针对诱导期人群报告，但应答者的基线特征不可得，这限制了维护结局的人群调整间接比较。本文提出再随机化概率加权方法，该方法结合诱导期人群校准与基于已知维护分配概率的逆加权。将诱导期无应答编码为失败，定义持久应答为诱导期和维护期均应答。该设计权重在随机化期望中重现诱导期人群协变量总和，可利用已报告的诱导期基线进行人群调整。尽管不同诱导治疗会产生不同的应答者人群，仍可估计条件维护概率。一项包含三项试验的合成演示显示，在两项比较中，持久应答的偏差分别从0.106降至0.001、从0.055降至0.001；全程序模拟显示区间覆盖率为91.5%-94.3%；压力情景阐明了遗漏协变量和错误分配权重带来的偏差。该方法将成熟的设计加权与汇总稀释方法相结合，用于跨随机撤药试验和持续治疗试验设计的人群调整比较，要求具备兼容的持久应答终点及可信的迁移和建模假设。不同诱导方案后的撤药并非自动成为共同对照，在无有效锚定时，仅当严格的调整假设可证实时，无锚定比较才适用。
英文摘要
Randomized-withdrawal trials re-randomize induction responders to continued treatment or withdrawal. Baseline characteristics are often reported for the induction population but unavailable for responders, limiting population-adjusted indirect comparisons of maintenance outcomes. We describe re-randomization-probability weighting, which combines induction-population calibration with inverse weighting by known maintenance assignment probabilities. Coding induction non-response as failure defines durable response: response at both induction and maintenance. The design weights reproduce induction-population covariate totals in randomization expectation, allowing population adjustment using reported induction baselines. Conditional maintenance probabilities can also be estimated, although different induction treatments generate different responder populations. A synthetic three-trial demonstration reduced durable-response bias from 0.106 to 0.001 and from 0.055 to 0.001 in two comparisons. Full-procedure simulations showed interval coverage of 91.5% - 94.3%; stress scenarios illustrated bias from omitted covariates and incorrect assignment weights. The method connects established design weighting and aggregate dilution approaches to population-adjusted comparison across randomized-withdrawal and treat-through designs. It requires compatible durable-response endpoints and credible transport and modeling assumptions. Withdrawal after different induction regimens is not automatically a common comparator. Where no valid anchor exists, unanchored comparison is appropriate only if its demanding adjustment assumptions are defensible.
Comments30 pages, 5 tables, 4 figures
