Literature DB >> 33012870

Patient Response Trajectories in Major Depressive Disorder.

Klaus G Larsen1, Sidney H Kennedy1, Elin Heldbo Reines1, Michael E Thase1.   

Abstract

Objective: To investigate whether the efficacy of antidepressants can be understood in terms of patient response-trajectory classes. Experimental Design: Patient-level data were analysed from 1357 adults with MDD randomised to either escitalopram 20 mg/day (n = 676) or placebo (n = 681) in five 8-week randomised placebo-controlled trials. Growth mixture models (GMMs) were used to identify the response trajectories; longitudinal latent class analysis (LLCA) was used to corroborate the findings. Principal Observations: Three classes of response were identified for escitalopram and placebo based on the trajectory of the patients' Montgomery-Åsberg Depression Rating Scale (MADRS) total scores during treatment. All three classes had similar mean baseline MADRS scores, but the change from baseline after 8 weeks differed: -4.2 MADRS points for non-responders, -18.4 MADRS points for slow responders, and -26.7 points for fast responders. The proportions of non-responders, slow responders and fast responders were 53%, 38% and 9%, respectively, with placebo and 27%, 58% and 14%, respectively, with escitalopram. Receiver operating curve analysis showed that a cut-off of ≥43% improvement from baseline to week 2 predicted fast responders, and a cut-off of ≥28% improvement from baseline to week 4 predicted responders (fast or slow). There were no clinically useful differences at baseline that predicted the trajectory class to which a patient would belong. Conclusions: The presence of fast-, slow- and non-responder classes has a clear clinical relevance for guiding treatment decisions; individual patients can be classified by the change in their MADRS score from baseline at 2 or 4 weeks.
Copyright © 1964–2019 by MedWorks Media Inc, Los Angeles, CA All rights reserved. Printed in the United States.

Entities:  

Keywords:  antidepressant; depression; escitalopram; growth mixture models; longitudinal latent class analysis; receiver operating curve

Mesh:

Substances:

Year:  2020        PMID: 33012870      PMCID: PMC7511149     

Source DB:  PubMed          Journal:  Psychopharmacol Bull        ISSN: 0048-5764


  16 in total

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Authors:  Raye Z Litten; Joanne B Fertig; Daniel E Falk; Megan L Ryan; Margaret E Mattson; Joseph F Collins; Cristin Murtaugh; Domenic Ciraulo; Alan I Green; Bankole Johnson; Helen Pettinati; Robert Swift; Maryam Afshar; Mary F Brunette; Nassima A-D Tiouririne; Kyle Kampman; Robert Stout
Journal:  Alcohol Clin Exp Res       Date:  2011-09-26       Impact factor: 3.455

2.  Trajectories and antecedents of treatment response over time in early-episode psychosis.

Authors:  Stephen Z Levine; J Rabinowitz
Journal:  Schizophr Bull       Date:  2008-10-09       Impact factor: 9.306

3.  Onset of action under antidepressant treatment.

Authors:  H H Stassen; J Angst; A Delini-Stula
Journal:  Eur Psychiatry       Date:  1997       Impact factor: 5.361

4.  Delayed onset of action of antidepressant drugs? Survey of results of Zurich meta-analyses.

Authors:  H H Stassen; J Angst; A Delini-Stula
Journal:  Pharmacopsychiatry       Date:  1996-05       Impact factor: 5.788

5.  Symptomatic and Functional Outcomes and Early Prediction of Response to Escitalopram Monotherapy and Sequential Adjunctive Aripiprazole Therapy in Patients With Major Depressive Disorder: A CAN-BIND-1 Report.

Authors:  Sidney H Kennedy; Raymond W Lam; Susan Rotzinger; Roumen V Milev; Pierre Blier; Jonathan Downar; Kenneth R Evans; Faranak Farzan; Jane A Foster; Benicio N Frey; Peter Giacobbe; Geoffrey B Hall; Kate L Harkness; Stefanie Hassel; Zahinoor Ismail; Francesco Leri; Shane McInerney; Glenda M MacQueen; Luciano Minuzzi; Daniel J Müller; Sagar V Parikh; Franca M Placenza; Lena C Quilty; Arun V Ravindran; Roberto B Sassi; Claudio N Soares; Stephen C Strother; Gustavo Turecki; Anthony L Vaccarino; Fidel Vila-Rodriguez; Joanna Yu; Rudolf Uher
Journal:  J Clin Psychiatry       Date:  2019-02-05       Impact factor: 4.384

6.  Assessing the 'true' effect of active antidepressant therapy v. placebo in major depressive disorder: use of a mixture model.

Authors:  Michael E Thase; Klaus G Larsen; Sidney H Kennedy
Journal:  Br J Psychiatry       Date:  2011-12       Impact factor: 9.319

7.  The early improvement of depressive symptoms as a potential predictor of response to antidepressants in depressive patients who failed to respond to previous antidepressant treatments. Analysis of naturalistic data.

Authors:  M Bares; T Novak; M Kopecek; P Stopkova; J Kozeny; C Höschl
Journal:  Eur Psychiatry       Date:  2011-11-29       Impact factor: 5.361

8.  Predicting antidepressant response through early improvement of individual symptoms of depression incorporating baseline characteristics of patients: An individual patient data meta-analysis.

Authors:  Norio Watanabe; Kazushi Maruo; Hissei Imai; Kazutaka Ikeda; Shigeto Yamawaki; Toshi A Furukawa
Journal:  J Psychiatr Res       Date:  2020-03-18       Impact factor: 4.791

9.  Antidepressant Response Trajectories and Associated Clinical Prognostic Factors Among Older Adults.

Authors:  Stephen F Smagula; Meryl A Butters; Stewart J Anderson; Eric J Lenze; Mary Amanda Dew; Benoit H Mulsant; Francis E Lotrich; Howard Aizenstein; Charles F Reynolds
Journal:  JAMA Psychiatry       Date:  2015-10       Impact factor: 21.596

10.  Early improvement in the first 2 weeks as a predictor of treatment outcome in patients with major depressive disorder: a meta-analysis including 6562 patients.

Authors:  Armin Szegedi; Wim T Jansen; Arjen P P van Willigenburg; Egbert van der Meulen; Hans H Stassen; Michael E Thase
Journal:  J Clin Psychiatry       Date:  2009-02-24       Impact factor: 4.384

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  1 in total

1.  Trajectories of Function and Symptom Change in Desvenlafaxine Clinical Trials: Toward Personalized Treatment for Depression.

Authors:  Sigal Zilcha-Mano; Xuemei Wang; Dalia B Wajsbrot; Matthieu Boucher; Stuart A Fine; Bret R Rutherford
Journal:  J Clin Psychopharmacol       Date:  2021 Sep-Oct 01       Impact factor: 3.118

  1 in total

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