A Machine Learning Approach to Identifying Placebo Responders in Late-Life Depression Trials.

Journal: The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry
PMID:

Abstract

OBJECTIVE: Despite efforts to identify characteristics associated with medication-placebo differences in antidepressant trials, few consistent findings have emerged to guide participant selection in drug development settings and differential therapeutics in clinical practice. Limitations in the methodologies used, particularly searching for a single moderator while treating all other variables as noise, may partially explain the failure to generate consistent results. The present study tested whether interactions between pretreatment patient characteristics, rather than a single-variable solution, may better predict who is most likely to benefit from placebo versus medication.

Authors

  • Sigal Zilcha-Mano
    Department of Psychology, University of Haifa, Haifa, Israel.
  • Steven P Roose
    Columbia University College of Physicians and Surgeons, New York State Psychiatric Institute, New York, NY.
  • Patrick J Brown
    Columbia University College of Physicians and Surgeons, New York State Psychiatric Institute, New York, NY.
  • Bret R Rutherford
    Columbia University College of Physicians and Surgeons, New York State Psychiatric Institute, New York, NY.