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

Roberto Gomeni, Jonathan Rabinowitz, Navin Goyal, Françoise Marie Madeleine Bressolle-Gomeni, Maurizio Fava

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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.

Original languageEnglish
Pages (from-to)1253-1260
Number of pages8
JournalClinical Pharmacology and Therapeutics
Volume106
Issue number6
DOIs
StatePublished - 1 Dec 2019

Bibliographical note

Publisher Copyright:
© 2019 The Authors Clinical Pharmacology & Therapeutics © 2019 American Society for Clinical Pharmacology and Therapeutics

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