Sailer Martin Oliver, Neubacher Dietmar, Johnston Curtis, Rogers James, Wiens Matthew, Pérez-Pitarch Alejandro, Tartakovsky Igor, Marquard Jan, Laffel Lori M
Global Biostatistics & Data Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Strasse 65, 88397, Biberach, Germany.
Metrum Research Group, Tariffville, CT, 06081, USA.
Ther Innov Regul Sci. 2025 Jan;59(1):112-123. doi: 10.1007/s43441-024-00707-5. Epub 2024 Oct 7.
Bayesian borrowing analyses have an important role in the design and analysis of pediatric trials. This paper describes use of a prespecified Pharmacometrics Enhanced Bayesian Borrowing (PEBB) analysis that was conducted to overcome an expectation for reduced statistical power in the pediatric DINAMO trial due to a greater than expected variability in the primary endpoint. The DINAMO trial assessed the efficacy and safety of an empagliflozin dosing regimen versus placebo and linagliptin versus placebo on glycemic control (change in HbA1c over 26 weeks) in young people with type 2 diabetes (T2D). Previously fitted pharmacokinetic and exposure-response models for empagliflozin and linagliptin based on available historical data in adult and pediatric patients with T2D were used to simulate participant data and derive the informative component of a Bayesian robust mixture prior distribution. External experts and representatives from the U.S. Food and Drug Administration provided recommendations to determine the effective sample size of the prior and the weight of the informative prior component. Separate exposure response-based Bayesian borrowing analyses for empagliflozin and linagliptin showed posterior mean and 95% credible intervals that were consistent with the trial results. Sensitivity analyses with a full range of alternative weights were also performed. The use of PEBB in this analysis combined advantages of mechanistic modeling of pharmacometric differences between adults and young people with T2D, with advantages of partial extrapolation through Bayesian dynamic borrowing. Our findings suggest that the described PEBB approach is a promising option to optimize the power for future pediatric trials.
贝叶斯借用分析在儿科试验的设计和分析中具有重要作用。本文描述了一种预先指定的药代动力学增强贝叶斯借用（PEBB）分析的应用，该分析旨在克服儿科糖尿病干预和管理结果评估（DINAMO）试验中由于主要终点的变异性大于预期而导致的统计功效降低的预期。DINAMO试验评估了恩格列净给药方案与安慰剂以及利格列汀与安慰剂对2型糖尿病（T2D）青少年血糖控制（26周内糖化血红蛋白[HbA1c]的变化）的疗效和安全性。基于T2D成年和儿科患者的现有历史数据，先前拟合的恩格列净和利格列汀的药代动力学和暴露-反应模型用于模拟参与者数据，并推导贝叶斯稳健混合先验分布的信息成分。外部专家和美国食品药品监督管理局的代表提供了建议，以确定先验的有效样本量和信息先验成分的权重。对恩格列净和利格列汀分别进行基于暴露反应的贝叶斯借用分析，结果显示后验均值和95%可信区间与试验结果一致。还进行了一系列替代权重的敏感性分析。在该分析中使用PEBB结合了T2D成人和青少年之间药代动力学差异的机制建模优势，以及通过贝叶斯动态借用进行部分外推的优势。我们的研究结果表明，所描述的PEBB方法是优化未来儿科试验功效的一个有前景的选择。
