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Multimodal Biomarkers Predict Who Responds to Common Antidepressants but Not Which Drug Works Best

The SMART Trial found much higher response rates for patients with one or two positive biomarkers, suggesting validated biomarker stratification could improve clinical outcomes.

Overview

  • The SMART Trial tested whether a prespecified multimodal algorithm could guide choice between sertraline and bupropion and found no significant difference on the trial’s primary endpoint for biomarker-concordant drug assignment.
  • Participants with two positive biomarkers had a 71.4% response rate, those with one positive biomarker had a 65.4% response rate, and participants with two negative biomarkers had a 42.9% response rate.
  • The biomarker set combined a functional MRI marker, measures of reward learning and sensitivity, cognitive control tests, clinical variables (depression severity and neuroticism), and employment status to generate drug-specific indications.
  • Predictive performance varied by drug with cross-validated AUCs of 0.86 for bupropion and 0.66 for sertraline, and authors say limited sample size reduced power to detect moderate effects on the primary outcome.
  • If replicated in larger and more diverse samples and adapted for real-world use without routine MRI, biomarker stratification could shorten the trial-and-error period for patients and help clinicians identify people unlikely to respond to standard antidepressants so they can try alternatives sooner.