Patient-centered clinical trials

Drug Discov Today. 2018 Feb;23(2):395-401. doi: 10.1016/j.drudis.2017.09.016. Epub 2017 Oct 4.


We apply Bayesian decision analysis (BDA) to incorporate patient preferences in the regulatory approval process for new therapies. By assigning weights to type I and type II errors based on patient preferences, the significance level (α) and power (1-β) of a randomized clinical trial (RCT) for a new therapy can be optimized to maximize the value to current and future patients and, consequently, to public health. We find that for weight-loss devices, potentially effective low-risk treatments have optimal αs larger than the traditional one-sided significance level of 5%, whereas potentially less effective and riskier treatments have optimal αs below 5%. Moreover, the optimal RCT design, including trial size, varies with the risk aversion and time-to-access preferences and the medical need of the target population.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Bayes Theorem
  • Clinical Trials as Topic / methods*
  • Decision Making
  • Humans
  • Patient-Centered Care / methods*
  • Randomized Controlled Trials as Topic / methods
  • Research Design