论文标题
了解和调整从概念验证研究到更确认的研究的选择偏见
Understanding and adjusting the selection bias from a proof-of-concept study to a more confirmatory study
论文作者
论文摘要
长期以来，人们一直注意到，在小型早期研究中观察到的功效通常比以后的大型研究要好。从历史上看，早期概念证明研究的疗效膨胀要么被忽略，要么使用常见主义者或贝叶斯方法进行经验调整。在本文中，我们系统地解释了从测量误差模型和选择偏见的角度，在小型早期研究中导致疗效通胀的根本原因。建立了一种系统的方法来调整早期研究的结果，从频繁主义者和贝叶斯的角度来看。提出了一个分层模型，以估计化合物投资组合的功效的分布，这可以作为贝叶斯方法的先前分布。我们通过理论表明，系统调整为化合物组合的真实平均功效提供了无偏估计量。在早期的小型和更大的研究中，将调整应用于配对数据，以供糖尿病和免疫学中的一组化合物。调整后，早期小型研究中的偏见似乎减少了。
It has long been noticed that the efficacy observed in small early phase studies is generally better than that observed in later larger studies. Historically, the inflation of the efficacy results from early proof-of-concept studies is either ignored, or adjusted empirically using a frequentist or Bayesian approach. In this article, we systematically explained the underlying reason for the inflation of efficacy results in small early phase studies from the perspectives of measurement error models and selection bias. A systematic method was built to adjust the early phase study results from both frequentist and Bayesian perspectives. A hierarchical model was proposed to estimate the distribution of the efficacy for a portfolio of compounds, which can serve as the prior distribution for the Bayesian approach. We showed through theory that the systematic adjustment provides an unbiased estimator for the true mean efficacy for a portfolio of compounds. The adjustment was applied to paired data for the efficacy in early small and later larger studies for a set of compounds in diabetes and immunology. After the adjustment, the bias in the early phase small studies seems to be diminished.
