Rei Monden1, Annelieke M Roest2, Don van Ravenzwaaij3, Eric-Jan Wagenmakers4, Richard Morey5, Klaas J Wardenaar6, Peter de Jonge3. 1. University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, The Netherlands. Electronic address: r.tendeiro-monden@umcg.nl. 2. University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, The Netherlands; University of Groningen, Faculty of Behavioural and Social Sciences, Groningen, The Netherlands. 3. University of Groningen, Faculty of Behavioural and Social Sciences, Groningen, The Netherlands. 4. University of Amsterdam, Department of Psychology, Amsterdam, The Netherlands. 5. Cardiff University, School of Psychology, Cognitive Science, Wales, United Kingdom. 6. University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, The Netherlands.
Abstract
BACKGROUND: Studies have shown similar efficacy of different antidepressants in the treatment of depression. METHOD: Data of phase-2 and -3 clinical-trials for 16 antidepressants (levomilnacipran, desvenlafaxine, duloxetine, venlafaxine, paroxetine, escitalopram, vortioxetine, mirtazapine, venlafaxine XR, sertraline, fluoxetine, citalopram, paroxetine CR, nefazodone, bupropion, vilazodone), approved by the FDA for the treatment of depression between 1987 and 2016, were extracted from the FDA reviews that were used to evaluate efficacy prior to marketing approval, which are less liable to reporting biases. Meta-analytic Bayes factors, which quantify the strength of evidence for efficacy, were calculated. In addition, posterior pooled effect-sizes were calculated and compared with classical estimations. RESULTS: The resulted Bayes factors showed that the evidence load for efficacy varied strongly across antidepressants. However, all tested drugs except for bupropion and vilazodone showed strong evidence for their efficacy. The posterior effect-size distributions showed variation across antidepressants, with the highest pooled estimated effect size for venlafaxine followed by paroxetine, and the lowest for bupropion and vilazodone. LIMITATIONS: Not all published trials were included in the study. CONCLUSIONS: The results illustrate the importance of considering both the effect size and the evidence-load when judging the efficacy of a treatment. In doing so, the currently employed Bayesian approach provided clear insights on top of those gained with traditional approaches.
BACKGROUND: Studies have shown similar efficacy of different antidepressants in the treatment of depression. METHOD: Data of phase-2 and -3 clinical-trials for 16 antidepressants (levomilnacipran, desvenlafaxine, duloxetine, venlafaxine, paroxetine, escitalopram, vortioxetine, mirtazapine, venlafaxine XR, sertraline, fluoxetine, citalopram, paroxetine CR, nefazodone, bupropion, vilazodone), approved by the FDA for the treatment of depression between 1987 and 2016, were extracted from the FDA reviews that were used to evaluate efficacy prior to marketing approval, which are less liable to reporting biases. Meta-analytic Bayes factors, which quantify the strength of evidence for efficacy, were calculated. In addition, posterior pooled effect-sizes were calculated and compared with classical estimations. RESULTS: The resulted Bayes factors showed that the evidence load for efficacy varied strongly across antidepressants. However, all tested drugs except for bupropion and vilazodone showed strong evidence for their efficacy. The posterior effect-size distributions showed variation across antidepressants, with the highest pooled estimated effect size for venlafaxine followed by paroxetine, and the lowest for bupropion and vilazodone. LIMITATIONS: Not all published trials were included in the study. CONCLUSIONS: The results illustrate the importance of considering both the effect size and the evidence-load when judging the efficacy of a treatment. In doing so, the currently employed Bayesian approach provided clear insights on top of those gained with traditional approaches.
Authors: Barbara Nussbaumer-Streit; Kylie Thaler; Andrea Chapman; Thomas Probst; Dietmar Winkler; Andreas Sönnichsen; Bradley N Gaynes; Gerald Gartlehner Journal: Cochrane Database Syst Rev Date: 2021-03-04
Authors: Merle-Marie Pittelkow; Ymkje Anna de Vries; Rei Monden; Jojanneke A Bastiaansen; Don van Ravenzwaaij Journal: Psychol Med Date: 2021-10-08 Impact factor: 7.723