Objective: Evaluate the clinical utility of combinatorial pharmacogenomic testing for informing medication selection among older adults who have experienced antidepressant medication failure for major depressive disorder (MDD).
Design: Post hoc analysis of data from a blinded, randomized controlled trial comparing two active treatment arms.
Setting: Psychiatry specialty and primary care clinics across 60 U.S. community and academic sites.
Participants: Adults age 65 years or older at baseline (n = 206), diagnosed with MDD and inadequate response to at least one medication on the combinatorial pharmacogenomic test report during the current depressive episode.
Intervention: Combinatorial pharmacogenomic testing to inform medication selection (guided-care), compared with treatment as usual (TAU).
Outcomes: Mean percent symptom improvement, response rate, and remission rateat week 8, measured using the 17-item Hamilton Depression Rating Scale; medication switching; and comorbidity moderator analysis.
Results: At week 8, symptom improvement was not significantly different for guided-care than for TAU (∆ = 8.1%, t = 1.64, df = 187; p = 0.102); however, guided-care showed significantly improved response (∆ = 13.6%, t = 2.16, df = 187; p = 0.032) and remission (∆ = 12.7%, t = 2.49, df = 189; p = 0.014) relative to TAU. By week 8, more than twice as many patients in guided-care than in TAU were on medications predicted to have no gene-drug interactions (χ2 = 19.3, df = 2; p <0.001). Outcomes in the guided-care arm showed consistent improvement through the end of the open-design 24-week trial, indicating durability of the effect. Differences in outcomes between arms were not significantly impacted by comorbidities.
Conclusions: Combinatorial pharmacogenomic test-informed medication selection improved outcomes over TAU among older adults with depression.
Keywords: Late-life depression; antidepressant; clinical trial; geriatric depression; major depressive disorder; medication selection; pharmacogenomics.
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.