Optimal doses of antidepressants in dependence on age: Combined covariate actions in Bayesian network meta-analysis

Abstract

Background: The meta-analysis by Furukawa et al. (The Lancet Psychiatry 2019, 6(7)) reported optimal doses for antidepressants in adult major depressive disorder (MDD). The present reanalysis aimed to adjust optimal doses in dependence on age. Methods: Analysis was based on the same dataset by Cipriani et al. (The Lancet 2018, 391(10128)) comparing 21 antidepressants in MDD. Random-effects Bayesian network meta-analysis was implemented to estimate the combined covariate action using restricted cubic splines (RCS). Balanced treatment recommendations were derived for the outcomes efficacy (response), acceptability (dropouts for any reason), and tolerability (dropouts due to adverse events). Findings: The combined covariate action of dose and age suggested agomelatine and escitalopram as the best-balanced antidepressants in terms of efficacy and tolerability that may be escalated until 40 and 60 mg/day fluoxetine equivalents (mg/dayFE), respectively, for ages 30–65 years. Desvenlafaxine, duloxetine, fluoxetine, milnacipran, and vortioxetine may be escalated until 20–40 mg/dayFE, whereas bupropion, citalopram, mirtazapine, paroxetine, and venlafaxine may not be given in doses > 20 mg/dayFE. Amitriptyline, clomipramine, fluvoxamine, levomilnacipran, reboxetine, sertraline, and trazodone revealed no relevant balanced benefits and may therefore not be recommended for antidepressant treatment. None of the antidepressants was observed to provide balanced benefits in patients >70 years because of adverse events exceeding efficacy. Interpretation: Findings suggest that the combined covariate action of dose and age provides a better basis for judging antidepressant clinical benefits than considering dose or age separately, and may thus inform decision makers to accurately guide antidepressant dosing recommendations in MDD. Funding: No funding. Keywords: Meta-analysis, antidepressants, dose, age