More data, more answers: picking the optimal antidepressant

In an era of increasingly large datasets for health and emphasis on so-called big data analyses, key clinical questions remain unpretentiously simple. For example, do some antidepressants work better than others for depression? And are some more tolerable than others, at least as measured in dropout rates? A quick PubMed search of antidepressant meta-analyses yields more than 2000 hits, but the complexity of understanding which antidepressants are better or more tolerable than others is made particularly daunting by the fact that more than 40 antidepressants are available. Andrea Cipriani and colleagues provided a novel answer to these questions originally in a paper published in The Lancet in 2009, introducing the new method of network meta-analysis to psychiatry and showing that four of the 12 then newer antidepressants were more efficacious than the rest. In that landmark study, the authors examined 117 trials with nearly 26 000 participants. 9 years later in The Lancet, Cipriani and colleagues report their work applying a similar method to address the same question; this time they evaluated 21 antidepressants and placebo in 522 double-blind trials with 116 477 participants. Chief among the findings are detailed new results on efficacy (8-week outcomes) and acceptability (8-week dropout rates due to all causes). The study found that all antidepressants were more efficacious than placebo, with odds ratios (ORs) ranging from 2·13 (95% credible interval [CrI] 1·89–2·41) for amitriptyline to 1·37 (1·16–1·63) for reboxetine. Additionally, the study found reduced differences between antidepressants compared with the 2009 study, with ORs (usually with broad CrIs) from 1·15 to 1·55 for efficacy and from 0·64 to 0·83 for acceptability (tolerability). More specifically, head-to-head efficacy comparisons of antidepressants dis closed seven agents (agomelatine, amitriptyline, escitalopram, mirtazapine, paroxetine, venlafaxine, and vortioxetine) as distinctly more effective and four agents (fluoxetine, fluvoxamine, reboxetine, and trazodone) to be somewhat less effective than the other antidepressants. As a method, network meta-analysis has emerged as a legitimate approach, as shown (via a simple MEDLINE search) by more than 900 network meta-analysis publications in the area of cancer based on this method, and more than 200 publications related to depression, although few are full network meta-analysis studies. In this latest paper, Cipriani and colleagues carefully follow recommended procedures to optimise methodological rigour and identify potential sources of bias and error. They also sought to maximise clinical relevance by focusing not only on modern antidepressants but also including the two WHO recommended essential antidepressants, amitriptyline and clomipramine. Special effort to minimise bias was achieved by obtaining additional unpublished data for more than half of the studies, and also by separate analyses to look for various potential contributors to bias including pharmaceutical sponsorship. Finally, for clinical relevance and face validity, although network meta-analysis was used to generate overall findings, results from head-to-head clinical studies were emphasised. The current study used efficacy outcomes at 8 weeks, while dropout rates at 8 weeks served as a proxy for overall side-effect burden, termed acceptability. Although seven antidepressants had higher efficacy than the other antidepressants, after factoring in acceptability, three emerged as preferable: agomelatine, escitalopram, and vortioxetine. Three antidepressants had a poor profile of efficacy and acceptability: fluvoxamine, reboxetine, and trazodone. A direct clinical implication is that the three net efficacious antidepressants might be considered first choice, whereas the three less efficacious antidepressants might be avoided initially. Depression severity or other patient characteristics might also argue for first-line consideration of the remaining so-called superior agents in terms of efficacy—namely, amitriptyline and venlafaxine. Published Online February 21, 2018 http://dx.doi.org/10.1016/ S0140-6736(18)30421-5