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A Systematic Review and Individual Patient Data Network Analysis of the Residual Symptom Structure Following Cognitive-Behavioral Therapy and Escitalopram, Mirtazapine and Venlafaxine for Depression

OBJECTIVE: Consistent evidence suggests residual depressive symptomology are the strongest predictors of depression relapse following cognitive-behavioral therapy (CBT) and antidepressant medications (ADM's). Psychometric network models help detecting and understanding central symptoms that rem...

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Autores principales: Whiston, Aoife, Lennon, Amy, Brown, Catherine, Looney, Chloe, Larkin, Eve, O'Sullivan, Laurie, Sik, Nurcan, Semkovska, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8843824/
https://www.ncbi.nlm.nih.gov/pubmed/35178002
http://dx.doi.org/10.3389/fpsyt.2022.746678
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author Whiston, Aoife
Lennon, Amy
Brown, Catherine
Looney, Chloe
Larkin, Eve
O'Sullivan, Laurie
Sik, Nurcan
Semkovska, Maria
author_facet Whiston, Aoife
Lennon, Amy
Brown, Catherine
Looney, Chloe
Larkin, Eve
O'Sullivan, Laurie
Sik, Nurcan
Semkovska, Maria
author_sort Whiston, Aoife
collection PubMed
description OBJECTIVE: Consistent evidence suggests residual depressive symptomology are the strongest predictors of depression relapse following cognitive-behavioral therapy (CBT) and antidepressant medications (ADM's). Psychometric network models help detecting and understanding central symptoms that remain post-treatment, along with their complex co-occurrences. However, individual psychometric network studies show inconsistent findings. This systematic review and IPD network analysis aimed to estimate and compare the symptom network structures of residual depressive symptoms following CBT, ADM's, and their combination. METHODS: PsycINFO, PsycArticles, and PubMed were systematically searched through October 2020 for studies that have assessed individuals with major depression at post-treatment receiving either CBT and/or ADM's (venlafaxine, escitalopram, mirtazapine). IPD was requested from eligible samples to estimate and compare residual symptom psychometric network models post-CBT and post-ADM's. RESULTS: In total, 25 from 663 eligible samples, including 1,389 patients qualified for the IPD. Depressed mood and anhedonia were consistently central residual symptoms post-CBT and post-ADM's. For CBT, fatigue-related and anxiety symptoms were also central post-treatment. A significant difference in network structure across treatments (CBT vs. ADM) was observed for samples measuring depression severity using the MADRS. Specifically, stronger symptom occurrences were present amongst lassitude-suicide post-CBT (vs. ADM's) and amongst lassitude-inability to feel post-ADM's (vs. CBT). No significant difference in global strength was observed across treatments. CONCLUSIONS: Core major depression symptoms remain central across treatments, strategies to target these symptoms should be considered. Anxiety and fatigue related complaints also remain central post-CBT. Efforts must be made amongst researchers, institutions, and journals to permit sharing of IPD. Systematic Review Registration: A protocol was prospectively registered on PROSPERO (CRD42020141663; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=141663).
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spelling pubmed-88438242022-02-16 A Systematic Review and Individual Patient Data Network Analysis of the Residual Symptom Structure Following Cognitive-Behavioral Therapy and Escitalopram, Mirtazapine and Venlafaxine for Depression Whiston, Aoife Lennon, Amy Brown, Catherine Looney, Chloe Larkin, Eve O'Sullivan, Laurie Sik, Nurcan Semkovska, Maria Front Psychiatry Psychiatry OBJECTIVE: Consistent evidence suggests residual depressive symptomology are the strongest predictors of depression relapse following cognitive-behavioral therapy (CBT) and antidepressant medications (ADM's). Psychometric network models help detecting and understanding central symptoms that remain post-treatment, along with their complex co-occurrences. However, individual psychometric network studies show inconsistent findings. This systematic review and IPD network analysis aimed to estimate and compare the symptom network structures of residual depressive symptoms following CBT, ADM's, and their combination. METHODS: PsycINFO, PsycArticles, and PubMed were systematically searched through October 2020 for studies that have assessed individuals with major depression at post-treatment receiving either CBT and/or ADM's (venlafaxine, escitalopram, mirtazapine). IPD was requested from eligible samples to estimate and compare residual symptom psychometric network models post-CBT and post-ADM's. RESULTS: In total, 25 from 663 eligible samples, including 1,389 patients qualified for the IPD. Depressed mood and anhedonia were consistently central residual symptoms post-CBT and post-ADM's. For CBT, fatigue-related and anxiety symptoms were also central post-treatment. A significant difference in network structure across treatments (CBT vs. ADM) was observed for samples measuring depression severity using the MADRS. Specifically, stronger symptom occurrences were present amongst lassitude-suicide post-CBT (vs. ADM's) and amongst lassitude-inability to feel post-ADM's (vs. CBT). No significant difference in global strength was observed across treatments. CONCLUSIONS: Core major depression symptoms remain central across treatments, strategies to target these symptoms should be considered. Anxiety and fatigue related complaints also remain central post-CBT. Efforts must be made amongst researchers, institutions, and journals to permit sharing of IPD. Systematic Review Registration: A protocol was prospectively registered on PROSPERO (CRD42020141663; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=141663). Frontiers Media S.A. 2022-02-01 /pmc/articles/PMC8843824/ /pubmed/35178002 http://dx.doi.org/10.3389/fpsyt.2022.746678 Text en Copyright © 2022 Whiston, Lennon, Brown, Looney, Larkin, O'Sullivan, Sik and Semkovska. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychiatry
Whiston, Aoife
Lennon, Amy
Brown, Catherine
Looney, Chloe
Larkin, Eve
O'Sullivan, Laurie
Sik, Nurcan
Semkovska, Maria
A Systematic Review and Individual Patient Data Network Analysis of the Residual Symptom Structure Following Cognitive-Behavioral Therapy and Escitalopram, Mirtazapine and Venlafaxine for Depression
title A Systematic Review and Individual Patient Data Network Analysis of the Residual Symptom Structure Following Cognitive-Behavioral Therapy and Escitalopram, Mirtazapine and Venlafaxine for Depression
title_full A Systematic Review and Individual Patient Data Network Analysis of the Residual Symptom Structure Following Cognitive-Behavioral Therapy and Escitalopram, Mirtazapine and Venlafaxine for Depression
title_fullStr A Systematic Review and Individual Patient Data Network Analysis of the Residual Symptom Structure Following Cognitive-Behavioral Therapy and Escitalopram, Mirtazapine and Venlafaxine for Depression
title_full_unstemmed A Systematic Review and Individual Patient Data Network Analysis of the Residual Symptom Structure Following Cognitive-Behavioral Therapy and Escitalopram, Mirtazapine and Venlafaxine for Depression
title_short A Systematic Review and Individual Patient Data Network Analysis of the Residual Symptom Structure Following Cognitive-Behavioral Therapy and Escitalopram, Mirtazapine and Venlafaxine for Depression
title_sort systematic review and individual patient data network analysis of the residual symptom structure following cognitive-behavioral therapy and escitalopram, mirtazapine and venlafaxine for depression
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8843824/
https://www.ncbi.nlm.nih.gov/pubmed/35178002
http://dx.doi.org/10.3389/fpsyt.2022.746678
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