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Individual response to antidepressants for depression in adults-a meta-analysis and simulation study

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  • Klaus Munkholm
  • Stephanie Winkelbeiner
  • Philipp Homan

Abstract

Background: The observation that some patients appear to respond better to antidepressants for depression than others encourages the assumption that the effect of antidepressants differs between individuals and that treatment can be personalized. Objective: To compare the outcome variance in patients receiving antidepressants with the outcome variance in patients receiving placebo in randomized controlled trials (RCTs) of adults with major depressive disorder (MDD) and to illustrate, using simulated data, components of variation of RCTs. Methods: From a dataset comprising 522 RCTs of antidepressants for adult MDD, we selected the placebo-controlled RCTs reporting outcomes on the 17 or 21 item Hamilton Depression Rating Scale or the Montgomery-Asberg Depression Rating Scale and extracted the means and SDs of raw endpoint scores or baseline to endpoint changes scores on eligible depression symptom rating scales. We conducted inverse variance random-effects meta-analysis with the variability ratio (VR), the ratio between the outcome variance in the group of patients receiving antidepressants and the outcome variance in the group receiving placebo, as the primary outcome. An increased variance in the antidepressant group would indicate individual differences in response to antidepressants. Results: We analysed 222 RCTs that investigated 19 different antidepressants compared with placebo in 345 comparisons, comprising a total of 61144 adults with an MDD diagnosis. Across all comparisons, the VR for raw endpoint scores was 0.98 (95% CI 0.96 to 1.00, I2 = 0%) and 1.00 (95% CI 0.99 to 1.02, I2 = 0%) for baseline-to-endpoint change scores. Conclusion: Based on these data, we cannot reject the null hypothesis of equal variances in the antidepressant group and the placebo group. Given that RCTs cannot provide direct evidence for individual treatment effects, it may be most reasonable to assume that the average effect of antidepressants applies also to the individual patient.

Suggested Citation

  • Klaus Munkholm & Stephanie Winkelbeiner & Philipp Homan, 2020. "Individual response to antidepressants for depression in adults-a meta-analysis and simulation study," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-16, August.
    • Handle: RePEc:plo:pone00:0237950
    DOI: 10.1371/journal.pone.0237950
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    References listed on IDEAS

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    1. Irving Kirsch & Brett J Deacon & Tania B Huedo-Medina & Alan Scoboria & Thomas J Moore & Blair T Johnson, 2008. "Initial Severity and Antidepressant Benefits: A Meta-Analysis of Data Submitted to the Food and Drug Administration," PLOS Medicine, Public Library of Science, vol. 5(2), pages 1-9, February.
    2. Stephen Senn, 2018. "Statistical pitfalls of personalized medicine," Nature, Nature, vol. 563(7733), pages 619-621, November.
    3. Viechtbauer, Wolfgang, 2010. "Conducting Meta-Analyses in R with the metafor Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i03).
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    1. Constantin Volkmann & Alexander Volkmann & Christian A Müller, 2020. "On the treatment effect heterogeneity of antidepressants in major depression: A Bayesian meta-analysis and simulation study," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-22, November.

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