Pharmacometrics-Enhanced Bayesian Borrowing for Pediatric Extrapolation - A Case Study of the DINAMO Trial.

IF 2 4区 医学 Q4 MEDICAL INFORMATICS
Martin Oliver Sailer, Dietmar Neubacher, Curtis Johnston, James Rogers, Matthew Wiens, Alejandro Pérez-Pitarch, Igor Tartakovsky, Jan Marquard, Lori M Laffel
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Abstract

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.

用于儿科外推的药物计量学增强贝叶斯借法--DINAMO 试验案例研究。
贝叶斯借鉴分析在儿科试验的设计和分析中发挥着重要作用。本文介绍了预先指定的药物计量学增强贝叶斯借用(PEBB)分析的使用情况,该分析是为了克服儿科DINAMO试验中因主要终点的变异性大于预期而导致的统计能力下降的预期而进行的。DINAMO试验评估了恩格列净给药方案相对于安慰剂和利拉利汀相对于安慰剂对2型糖尿病(T2D)年轻人血糖控制(26周内HbA1c的变化)的有效性和安全性。根据现有的成人和儿童 T2D 患者的历史数据,利用先前拟合的安格列净和利拉利汀的药代动力学和暴露-反应模型模拟受试者数据,并得出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和药物管理局的代表提供了建议,以确定先验的有效样本大小和信息先验成分的权重。对恩格列净和利拉利汀分别进行了基于暴露反应的贝叶斯借方分析,结果显示后验均值和95%可信区间与试验结果一致。此外,还使用各种备选权重进行了敏感性分析。在这项分析中使用 PEBB,既结合了对成人和年轻 T2D 患者的药效学差异进行机理建模的优势,又结合了通过贝叶斯动态借法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率的一种有前途的选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Therapeutic innovation & regulatory science
Therapeutic innovation & regulatory science MEDICAL INFORMATICS-PHARMACOLOGY & PHARMACY
CiteScore
3.40
自引率
13.30%
发文量
127
期刊介绍: Therapeutic Innovation & Regulatory Science (TIRS) is the official scientific journal of DIA that strives to advance medical product discovery, development, regulation, and use through the publication of peer-reviewed original and review articles, commentaries, and letters to the editor across the spectrum of converting biomedical science into practical solutions to advance human health. The focus areas of the journal are as follows: Biostatistics Clinical Trials Product Development and Innovation Global Perspectives Policy Regulatory Science Product Safety Special Populations
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