Sigworth Elizabeth A, Rubinstein Samuel M, Warner Jeremy L, Chen Yong, Chen Qingxia
Department of Biostatistics, Vanderbilt University.
Division of Hematology, University of North Carolina School of Medicine.
Ann Appl Stat. 2023 Dec;17(4):2993-3012. doi: 10.1214/23-aoas1748. Epub 2023 Oct 30.
In clinical practice medications are often interchanged in treatment protocols 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 medication, 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 approach approximates well the true dose toxo-equivalence relationship, considering 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. Finally, we present the findings of our dose toxo-equivalence model applied to two chemotherapy drugs, based on data from 169 published clinical trials.
在临床实践中，当患者对一线治疗产生负面反应时，治疗方案中经常会更换药物。虽然药物之间的切换很常见，但临床医生在选择新药的初始剂量和给药频率时，往往缺乏结构化的指导，尤其是考虑到前者可能带来的不良事件风险。在本文中，我们建议通过贝叶斯荟萃分析模型，利用已发表的关于一种或两种感兴趣药物的临床试验结果，建立这种剂量毒性等效关系，该模型同时考虑了研究内和研究间的方差。利用该模型的后验参数样本，我们仅依靠研究层面的信息，计算两种药物等效剂量对的中位数和95%可信区间，这些等效剂量对预计会产生相同的不良结局发生率。通过广泛的模拟，我们表明，考虑到不同的研究设计、研究间方差水平，以及除研究层面协变量外是否纳入非混杂/非修饰个体层面协变量，这种方法能很好地近似真实的剂量毒性等效关系。我们将这种研究层面荟萃分析估计的性能与等效的个体患者数据荟萃分析模型进行比较，发现在剂量毒性等效关系中使用的研究层面系数存在可比的偏差和最小的效率损失。最后，我们根据169项已发表临床试验的数据，展示了我们的剂量毒性等效模型应用于两种化疗药物的结果。
