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Original Research

Predicting Remission in Late-Life Major Depression: A Clinical Algorithm Based Upon Past Treatment History

Erica L. F. Buchalter, MDa,‡; Hanadi Ajam Oughli, MDa,‡; Eric J. Lenze, MDa; David Dixon, PhDa; J. Philip Millera; Daniel M. Blumberger, MD, MScb; Jordan F. Karp, MDc; Charles F. Reynolds III, MDc; and Benoit H. Mulsant, MD, MSb,*

Published: December 10, 2019

Article Abstract

Objective: To determine the likelihood of antidepressant response in older adults with major depression as a function of their prior antidepressant trials.

Methods: 500 older adults with major depression as diagnosed by DSM-IV criteria for major depressive episode were treated with venlafaxine extended release for 12 weeks. Participants were recruited from July 2009 to January 2014. For each participant, we collected detailed data on prior antidepressant trials for the current episode of depression. We examined the prospective remission rates as a function of number and class of prior antidepressant trials in a post hoc analysis of pooled data from 2 prior trials.

Results: Remission rates with venlafaxine were inversely correlated with the number of prior adequate medication trials (66% for no prior adequate trials, 45% for 1 prior adequate trial, 23% for 2 or more prior adequate trials; P < .0001). Additionally, if prior treatment trials included a serotonin-norepinephrine reuptake inhibitor, participants were even less likely to achieve remission with venlafaxine (32% for 1 prior adequate trial, 18% for 2 or more prior adequate trials; P < .0001). Those with prior adequate trials were also more likely to require a higher dosage of venlafaxine to achieve remission.

Conclusions: Information on an individual patient’s number and class of prior adequate antidepressant trials can be used to predict the likelihood of a successful treatment outcome with a given antidepressant in older adults with major depression. Further work is needed to refine this approach to provide personalized antidepressant treatment.

Trial Registration: identifiers: NCT00892047 and NCT02263248‘ ‹

Volume: 80

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