BUILDING A DOSE TOXO-EQUIVALENCE MODEL FROM A BAYESIAN META-ANALYSIS OF PUBLISHED CLINICAL TRIALS

• 成果类型: Article
• 署名作者: Sigworth, Elizabeth A.; Rubinstein, Samuel M.; Warner, Jeremy L.; Chen, Yong; Chen, Qingxia
• 署名单位: Vanderbilt University; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Vanderbilt University; University of Pennsylvania
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• 发表日期: 2023
• 页码: 3012-3012
• 关键词: individual patient data; level data; EFFICIENCY; variance

摘要

In clinical practice medications are often interchanged in treatment pro-tocols when a patient negatively reacts to their first line of therapy. Although switching between medications is common, clinicians often lack structured guidance when choosing the initial dose and frequency of a new medica-tion, given the former with respect to risk of adverse events. In this paper we propose to establish this dose toxo-equivalence relationship using published clinical trial results with one or both drugs of interest via a Bayesian meta -analysis model that accounts for both within-and between-study variances. With the posterior parameter samples from this model, we compute median and 95% credible intervals for equivalent dose pairs of the two drugs that are predicted to produce equal rates of an adverse outcome, relying solely on study-level information. Via extensive simulations, we show that this ap-proach approximates well the true dose toxo-equivalence relationship, con-sidering different study designs, levels of between-study variance, and the inclusion/exclusion of nonconfounder/nonmodifier subject-level covariates in addition to study-level covariates. We compare the performance of this study -level meta-analysis estimate to the equivalent individual patient data meta -analysis model and find comparable bias and minimal efficiency loss in the study-level coefficients used in the dose toxo-equivalence relationship. Fi-nally, we present the findings of our dose toxo-equivalence model applied to two chemotherapy drugs, based on data from 169 published clinical trials.