Literature DB >> 31303567

Influence of baseline severity on the effects of SSRIs in depression: an item-based, patient-level post-hoc analysis.

Fredrik Hieronymus1, Alexander Lisinski1, Staffan Nilsson2, Elias Eriksson3.   

Abstract

BACKGROUND: Reports claiming that antidepressants are effective only in patients with severe depression have affected treatment guidelines but these reports usually use a disputed measure of improvement, a decrease in the sum-score of the 17-item Hamilton Depression Rating Scale (HDRS-17), and are based on group-level rather than patient-level data.
METHOD: In this item-based, patient-level, post-hoc analysis, we pooled data from all completed, acute-phase, placebo-controlled, industry-sponsored, HDRS-based trials of the SSRIs citalopram, paroxetine, or sertraline in adult major depression. Patient-level data were pooled and subjected to item-based post-hoc analyses to assess the effect of baseline severity of depression on the response to treatment as assessed with HDRS-17 sum score, the depressed mood item of the HDRS, a six-item HDRS subscale (HDRS-6), and the remaining 11 HDRS items not included in this subscale (non-HDRS-6). Patients were defined as having non-severe depression if they had a baseline HDRS-17 sum score of 18 points or less and as having severe depression if they had a score of 27 points or more.
FINDINGS: Our study population consisted of 8262 patients from 28 placebo-controlled SSRI trials. Participants were treated with either citalopram (n=744), paroxetine (n=2981), sertraline (n=1202), fluoxetine (active-control group; n=754), or placebo (n=2581). 654 patients were defined as having non-severe depression and 1377 as having severe depression. Patients with non-severe and severe depression did not differ with respect to SSRI-induced decrease in depressed mood and other HDRS symptoms belonging to the HDRS-6 subscale. However, after exclusion of patients with rare extreme baseline values, a positive association was seen between severity and efficacy when using HDRS-17 sum score as the effect parameter. This result was largely due to a more pronounced response to treatment with respect to non-HDRS-6 items in patients with severe depression than in those with non-severe depression. This outcome could be explained by non-HDRS-6 items, more so than HDRS-6 items, being more severe and prevalent at baseline in severe than in non-severe cases; hence, less room was left for improvement in these areas in patients with non-severe depression.
INTERPRETATION: The use of an outcome measure that includes symptoms that rate low at baseline in patients with non-severe depression might result in the interpretation that SSRIs are ineffective in these patients. With respect to alleviation of HDRS-6 items, SSRIs appear to be as effective in patients with non-severe depression as in those with severe depression. FUNDING: Swedish Medical Research Council, AFA Insurance, Swedish Brain Foundation, Sahlgrenska University Hospital (Avtal om Läkarutbildning och Forskning), Bertil Hållsten's Foundation, and Söderberg's Foundation.
Copyright © 2019 Elsevier Ltd. All rights reserved.

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Year:  2019        PMID: 31303567     DOI: 10.1016/S2215-0366(19)30216-0

Source DB:  PubMed          Journal:  Lancet Psychiatry        ISSN: 2215-0366            Impact factor:   27.083


  12 in total

1.  Beneficial Effects of Crocin against Depression via Pituitary Adenylate Cyclase-Activating Polypeptide.

Authors:  Linyu Lu; Die Wu; Kai Wang; Juanjuan Tang; Gang Chen
Journal:  Biomed Res Int       Date:  2020-06-24       Impact factor: 3.411

2.  The clinical effectiveness of sertraline in primary care and the role of depression severity and duration (PANDA): a pragmatic, double-blind, placebo-controlled randomised trial.

Authors:  Gemma Lewis; Larisa Duffy; Anthony Ades; Rebekah Amos; Ricardo Araya; Sally Brabyn; Katherine S Button; Rachel Churchill; Catherine Derrick; Christopher Dowrick; Simon Gilbody; Christopher Fawsitt; William Hollingworth; Vivien Jones; Tony Kendrick; David Kessler; Daphne Kounali; Naila Khan; Paul Lanham; Jodi Pervin; Tim J Peters; Derek Riozzie; George Salaminios; Laura Thomas; Nicky J Welton; Nicola Wiles; Rebecca Woodhouse; Glyn Lewis
Journal:  Lancet Psychiatry       Date:  2019-09-19       Impact factor: 27.083

3.  What are the chances for personalised treatment with antidepressants? Detection of patient-by-treatment interaction with a variance ratio meta-analysis.

Authors:  Martin Plöderl; Michael Pascal Hengartner
Journal:  BMJ Open       Date:  2019-12-23       Impact factor: 2.692

4.  One (effect) size does not fit at all: Interpreting clinical significance and effect sizes in depression treatment trials.

Authors:  Fredrik Hieronymus; Sameer Jauhar; Søren Dinesen Østergaard; Allan H Young
Journal:  J Psychopharmacol       Date:  2020-05-25       Impact factor: 4.153

5.  The sociodemographic and clinical profile of patients with major depressive disorder receiving SSRIs as first-line antidepressant treatment in European countries.

Authors:  Gernot Fugger; Lucie Bartova; Chiara Fabbri; Giuseppe Fanelli; Markus Dold; Marleen Margret Mignon Swoboda; Alexander Kautzky; Joseph Zohar; Daniel Souery; Julien Mendlewicz; Stuart Montgomery; Dan Rujescu; Alessandro Serretti; Siegfried Kasper
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2022-01-06       Impact factor: 5.760

6.  Impact of chosen cutoff on response rate differences between selective serotonin reuptake inhibitors and placebo.

Authors:  Alexander Lisinski; Fredrik Hieronymus; Staffan Nilsson; Elias Eriksson
Journal:  Transl Psychiatry       Date:  2022-04-14       Impact factor: 7.989

7.  Concordance between clinician-rated and patient reported outcome measures of depressive symptoms in treatment resistant depression.

Authors:  Rachel Hershenberg; William M McDonald; Andrea Crowell; Patricio Riva-Posse; W Edward Craighead; Helen S Mayberg; Boadie W Dunlop
Journal:  J Affect Disord       Date:  2020-01-22       Impact factor: 4.839

8.  Item-based analysis of the effects of duloxetine in depression: a patient-level post hoc study.

Authors:  Alexander Lisinski; Fredrik Hieronymus; Jakob Näslund; Staffan Nilsson; Elias Eriksson
Journal:  Neuropsychopharmacology       Date:  2019-09-14       Impact factor: 7.853

9.  Combining machine learning algorithms for prediction of antidepressant treatment response.

Authors:  Alexander Kautzky; Hans-Juergen Möller; Markus Dold; Lucie Bartova; Florian Seemüller; Gerd Laux; Michael Riedel; Wolfgang Gaebel; Siegfried Kasper
Journal:  Acta Psychiatr Scand       Date:  2020-11-27       Impact factor: 6.392

10.  NLRP3/caspase-1/GSDMD-mediated pyroptosis exerts a crucial role in astrocyte pathological injury in mouse model of depression.

Authors:  Shanshan Li; Yiming Sun; Mengmeng Song; Yuting Song; Yinquan Fang; Qingyu Zhang; Xueting Li; Nanshan Song; Jianhua Ding; Ming Lu; Gang Hu
Journal:  JCI Insight       Date:  2021-12-08
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