Background: Studies report mixed findings regarding antidepressant agents and suicide risks, and few examine suicide deaths. Studies using observational data can accrue the large sample sizes needed to examine suicide death, but selection biases must be addressed. We assessed associations between suicide death and treatment with the 7 most commonly used antidepressants in a national sample of Department of Veterans Affairs patients in depression treatment. Multiple analytic strategies were used to address potential selection biases.
Methods: We identified Department of Veterans Affairs patients with depression diagnoses and new antidepressant starts between April 1, 1999, and September 30, 2004 (N = 502,179). Conventional Cox regression models, Cox models with inverse probability of treatment weighting, propensity-stratified Cox models, marginal structural models (MSM), and instrumental variable analyses were used to examine relationships between suicide and exposure to bupropion, citalopram, fluoxetine, mirtazapine, paroxetine, sertraline, and venlafaxine.
Results: Crude suicide rates varied from 88 to 247 per 100,000 person-years across antidepressant agents. In multiple Cox models and MSMs, sertraline and fluoxetine had lower risks for suicide death than paroxetine. Bupropion had lower risks than several antidepressants in Cox models but not MSMs. Instrumental variable analyses did not find significant differences across antidepressants.
Discussion: Most antidepressants did not differ in their risk for suicide death. However, across several analytic approaches, although not instrumental variable analyses, fluoxetine and sertraline had lower risks of suicide death than paroxetine. These findings are congruent with the Food and Drug Administration meta-analysis of randomized controlled trials reporting lower risks for “suicidality” for sertraline and a trend toward lower risks with fluoxetine than for other antidepressants. Nevertheless, divergence in findings by analytic approach suggests caution when interpreting results.
From the *Department of Veterans Affairs, Ann Arbor Center of Excellence (COE), Serious Mental Illness Treatment Resource and Evaluation Center (SMITREC); †Department of Psychiatry, University of Michigan Medical School; and ‡Center for Statistical Consultation and Research, §Michigan Department of Health Management and Policy, School of Public Health, and ∥Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI.
Received February 11, 2011; accepted after revision November 29, 2011.
Reprints: Marcia Valenstein, MD, MS, University of Michigan, North Campus Research Complex 2800 Plymouth Rd, Bldg 14, Rm D035, Ann Arbor, MI (e-mail: firstname.lastname@example.org).
The funding sources for this work were the Department of Veterans Affairs, Health Services Research and Development Service, IIR 04-211-1, MRP 03-320, CD2 07-206-1, and CDA 10-036-1, and the National Institute of Mental Health, R01-MH078698-01. Resources were also contributed by SMITREC, Ann Arbor, MI.