Suicide risk with selective serotonin reuptake inhibitors and other new-generation antidepressants in adults: a systematic review and meta-analysis of observational studies

Abstract

Background There is ongoing controversy whether antidepressant use alters suicide risk in adults with depression and other treatment indications. Methods Systematic review of observational studies, searching MEDLINE, PsycINFO, Web of Science, PsycARTICLES and SCOPUS for case–control and cohort studies. We included studies on depression and various indications unspecified (including off-label use) reporting risk of suicide and/or suicide attempt for adult patients using selective serotonin reuptake inhibitors (SSRI) and other new-generation antidepressants relative to non-users. Effects were meta-analytically aggregated with random-effects models, reporting relative risk (RR) estimates with 95% CIs. Publication bias was assessed via funnel-plot asymmetry and trim-and-fill method. Financial conflict of interest (fCOI) was defined present when lead authors’ professorship was industry-sponsored, they received industry-payments, or when the study was industry-sponsored. Results We included 27 studies, 19 on depression and 8 on various indications unspecified (n=1.45 million subjects). SSRI were not definitely related to suicide risk (suicide and suicide attempt combined) in depression (RR=1.03, 0.70–1.51) and all indications (RR=1.19, 0.88–1.60). Any new-generation antidepressant was associated with higher suicide risk in depression (RR=1.29, 1.06–1.57) and all indications (RR=1.45, 1.23–1.70). Studies with fCOI reported significantly lower risk estimates than studies without fCOI. Funnel-plots were asymmetrical and imputation of missing studies with trim-and-fill method produced considerably higher risk estimates. Conclusions Exposure to new-generation antidepressants is associated with higher suicide risk in adult routine-care patients with depression and other treatment indications. Publication bias and fCOI likely contribute to systematic underestimation of risk in the published literature. Registration Open Science Framework, https://osf.io/eaqwn/