Model-Informed Approach to Assess the Treatment Effect Conditional to the Level of Placebo Response

Clin Pharmacol Ther. 2019 Dec;106(6):1253-1260. doi: 10.1002/cpt.1584. Epub 2019 Aug 30.

Abstract

One of the most important reasons for failure of placebo-controlled randomized controlled clinical trials (RCTs) is the lack of appropriate methodologies for detecting treatment effect (TE; difference between placebo and active treatment response) in the presence of excessively low/high levels of placebo response. Although, the higher the level of placebo response in a trial, the lower the apparent detectable TE. TE is usually estimated in a conventional analysis of an RCT as an "apparent" TE value conditional to the level of placebo response in that RCT. A model-informed methodology is proposed to establish a relationship between level of placebo response and TE. This relationship is used to estimate the "typical" TE associated with a "typical" level of placebo response, irrespective of the level of placebo response observed. The approach can be valuable for providing a reliable estimate of TE, for conducting risk/benefit analysis, and for determining dosage recommendations.

MeSH terms

  • Antidepressive Agents / therapeutic use
  • Depressive Disorder / drug therapy
  • Humans
  • Models, Statistical*
  • Paroxetine / therapeutic use
  • Placebo Effect*
  • Randomized Controlled Trials as Topic
  • Treatment Outcome*

Substances

  • Antidepressive Agents
  • Paroxetine