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Specificity profile of paroxetine in major depressive disorder: meta-regression of double-blind, randomized clinical trials.

Author(s): Serretti A, Gibiino S, Drago A.

Affiliation(s): Institute of Psychiatry, University of Bologna, Italy. alessandro.serretti@unibo.it

Publication date & source: 2011, J Affect Disord. , 132(1-2):14-25

BACKGROUND: Meta-analyses and reviews are powerful tools to inform clinicians on overall effects of their therapeutic choices, but do not provide practically useful clinical profiles for each drug optimal efficacy. Therefore clinicians in everyday practice have to rely mainly on personal or anecdotic experience. The aim of present study was to define the most suitable sociodemographic and disease-related profile for the use of paroxetine as an antidepressant treatment. METHODS: MEDLINE, EMBASE, CINAHL, and PsycINFO were searched for randomized controlled trials (RCT) in English focused on "paroxetine" and "depressive disorder" or "major depression". We also considered reviews and meta-analyses focusing on paroxetine. Fifty-five total unique RCTs were included and sociodemographic and clinical data as moderator of efficacy measures (standardized mean difference based on Hamilton Depressive Rating Scale and Montgomery-Asberg Depression Rating Scale) were investigated via meta-regression analysis. RESULTS: Paroxetine was significantly characterized by better response in females and in Caucasians, whilst for patients who have been ill for a longer time before treatment, the smaller was the antidepressant effect. Other disease-related variables were not found to be significant moderators in clinical outcome. LIMITATIONS: Meta-regression may lack sufficient sensibility to detect specific subtle features, so a failure to find significant effect is not definitive evidence of a lack of effect. CONCLUSIONS: Our results, though significant, were generally observed with small estimate values, their clinical relevance is subtle since each feature is expected to influence marginally the whole outcome, and probably a more pronounced effect could result only by analyzing very large samples.

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