Literature DB >> 27438687

Combining moderators to identify clinical profiles of patients who will, and will not, benefit from aripiprazole augmentation for treatment resistant late-life major depressive disorder.

Stephen F Smagula1, Meredith L Wallace2, Stewart J Anderson3, Jordan F Karp4, Eric J Lenze5, Benoit H Mulsant6, Meryl A Butters2, Daniel M Blumberger6, Breno S Diniz7, Francis E Lotrich2, Mary Amanda Dew8, Charles F Reynolds9.   

Abstract

Personalizing treatment for late-life depression requires identifying and integrating information from multiple factors that influence treatment efficacy (moderators). We performed exploratory moderator analyses using data from a multi-site, randomized, placebo-controlled, double-blind trial of aripiprazole augmentation. Patients (n = 159) aged ≥60 years had major depressive disorder that failed to remit with venlafaxine monotherapy. We examined effect sizes of 39 potential moderators of aripiprazole (vs. placebo) augmentation efficacy using the outcome of percentage reduction in depressive symptom after 12 weeks. We then incorporated information from the individually relevant variables in combined moderators. A larger aripiprazole treatment effect was related to: white race, better physical function, better performance on Trail-Making, attention, immediate, and delayed memory tests, greater psychomotor agitation and suicidality symptoms, and a history of adequate antidepressant pharmacotherapy. A smaller aripiprazole treatment effect was observed in patients with: more pain and more work/activity impairment and libido symptoms. Combining information from race and Trail-Making test performance (base combined moderator (Mb*)) produced a larger effect size (Spearman effect size = 0.29 (95% confidence interval (CI): 0.15, 0.42)) than any individual moderator. Adding other individually relevant moderators in the full combined moderator (Mf*) further improved effect size (Spearman effect size = 0.39 (95% CI: 0.25, 0.52)) and identified a sub-group benefiting more from placebo plus continuation venlafaxine monotherapy than adjunctive aripiprazole. Combining moderators can help clinicians personalize depression treatment. We found the majority of our patients benefited from adjunctive aripiprazole, but a smaller subgroup that is identifiable using clinical measures appeared to benefit more from continuation venlafaxine plus placebo.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Aripiprazole; Combined moderators; Late-life depression; Moderators; Personalized medicine

Mesh:

Substances:

Year:  2016        PMID: 27438687      PMCID: PMC5021594          DOI: 10.1016/j.jpsychires.2016.07.005

Source DB:  PubMed          Journal:  J Psychiatr Res        ISSN: 0022-3956            Impact factor:   4.791


  20 in total

1.  Efficacy, safety, and tolerability of augmentation pharmacotherapy with aripiprazole for treatment-resistant depression in late life: a randomised, double-blind, placebo-controlled trial.

Authors:  Eric J Lenze; Benoit H Mulsant; Daniel M Blumberger; Jordan F Karp; John W Newcomer; Stewart J Anderson; Mary Amanda Dew; Meryl A Butters; Jacqueline A Stack; Amy E Begley; Charles F Reynolds
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6.  Predictors of remission with placebo using an integrated study database from patients with major depressive disorder.

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7.  Impact of Prior Treatment on Remission of Late-Life Depression with Venlafaxine and Subsequent Aripiprazole or Placebo Augmentation.

Authors:  Jonathan H Hsu; Benoit H Mulsant; Eric J Lenze; Jordan F Karp; Helen Lavretsky; Steven P Roose; Charles F Reynolds; Daniel M Blumberger
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8.  Predictors and Moderators of Remission With Aripiprazole Augmentation in Treatment-Resistant Late-Life Depression: An Analysis of the IRL-GRey Randomized Clinical Trial.

Authors:  Shriya H Kaneriya; Gregg A Robbins-Welty; Stephen F Smagula; Jordan F Karp; Meryl A Butters; Eric J Lenze; Benoit H Mulsant; Daniel Blumberger; Stewart J Anderson; Mary Amanda Dew; Francis Lotrich; Howard J Aizenstein; Breno S Diniz; Charles F Reynolds
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10.  Dynamic prediction of treatment response in late-life depression.

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  13 in total

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2.  Getting to precision psychopharmacology: Combining clinical and genetic information to predict fat gain from aripiprazole.

Authors:  H Oughli; E J Lenze; A E Locke; M D Yingling; Y Zhong; J P Miller; C F Reynolds; B H Mulsant; J W Newcomer; T R Peterson; D J Müller; G E Nicol
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7.  A Machine Learning Approach to Identifying Placebo Responders in Late-Life Depression Trials.

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8.  Promise and Challenges of Using Combined Moderator Methods to Personalize Mental Health Treatment.

Authors:  Meredith L Wallace; Stephen F Smagula
Journal:  Am J Geriatr Psychiatry       Date:  2018-04-24       Impact factor: 4.105

9.  Specific depressive symptoms predict remission to aripiprazole augmentation in late-life treatment resistant depression.

Authors:  Marie Anne Gebara; Elizabeth A DiNapoli; John Kasckow; Jordan F Karp; Daniel M Blumberger; Eric J Lenze; Benoit H Mulsant; Charles F Reynolds
Journal:  Int J Geriatr Psychiatry       Date:  2017-10-03       Impact factor: 3.485

10.  Pharmacological interventions for treatment-resistant depression in adults.

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