Scholarlink

<p>It is often not feasible to conduct randomized clinical trials (RCTs) with a sufficiently large sample size in a pediatric study. A common strategy to improve feasibility is to borrow information from a comparable external adult study. However, adult trial subjects may not be directly comparable to pediatric patients due to differences in baseline characteristics, prognostic factors, comorbidities, and previous treatments. In this article, we propose a propensity score integrated borrowing-by-parts power prior to estimate the effect of treatment in a pediatric study using a Bayesian approach. Specifically, we first estimate the propensity scores to assess the comparability between the pediatric and adult study. We then form strata based on these propensity scores and apply a stratum-specific borrowing-by-parts power prior, allowing for greater flexibility in borrowing information from different components of the data. In addition, we introduce data-driven discounting parameters to determine the level of borrowing. An extensive simulation study is carried out to demonstrate the proposed approach. To illustrate the practical implementation of our approach, we apply it to a case study of systemic lupus erythematosus (SLE) disease.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Propensity Score-Based Borrowing-By-Parts Power Prior for Augmenting Control Arm in Clinical Trials: A Two-Stage Approach

  • 期刊论文

  • 发表日期：

    2026年1月22日

查看全文
  • Apu Chandra Das,
  • Yeongjin Gwon,
  • Pablo Bonangelino

摘要

It is often not feasible to conduct randomized clinical trials (RCTs) with a sufficiently large sample size in a pediatric study. A common strategy to improve feasibility is to borrow information from a comparable external adult study. However, adult trial subjects may not be directly comparable to pediatric patients due to differences in baseline characteristics, prognostic factors, comorbidities, and previous treatments. In this article, we propose a propensity score integrated borrowing-by-parts power prior to estimate the effect of treatment in a pediatric study using a Bayesian approach. Specifically, we first estimate the propensity scores to assess the comparability between the pediatric and adult study. We then form strata based on these propensity scores and apply a stratum-specific borrowing-by-parts power prior, allowing for greater flexibility in borrowing information from different components of the data. In addition, we introduce data-driven discounting parameters to determine the level of borrowing. An extensive simulation study is carried out to demonstrate the proposed approach. To illustrate the practical implementation of our approach, we apply it to a case study of systemic lupus erythematosus (SLE) disease.