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Conditional power of antidepressant network meta-analysis.

Lisa Holper1

  • 1University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland. lisa.holper@bli.uzh.ch.

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Summary

Conditional power for antidepressant trials is low, requiring large sample sizes for conclusive evidence. This suggests careful consideration for future research in major depressive disorder (MDD).

Keywords:
AntidepressantsConclusive evidenceConditional powerNetwork meta-analysisSample size

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Area of Science:

  • Psychiatry and Mental Health
  • Clinical Trials Methodology
  • Biostatistics

Background:

  • Network meta-analysis (NMA) aids in planning randomized controlled trials (RCTs) for medical interventions.
  • Conditional power estimates the likelihood of achieving conclusive evidence by updating existing NMA data with new trials.
  • This study focuses on antidepressant treatments for major depressive disorder (MDD).

Purpose of the Study:

  • To estimate the conditional power for future trials on antidepressant treatments.
  • To determine sample sizes needed to achieve conclusive evidence in MDD treatment trials.
  • To identify antidepressants with the greatest conditional power and smallest required sample sizes.

Main Methods:

  • Utilized a network of 502 RCTs (1979-2018) for acute antidepressant treatment in MDD.
  • Assessed efficacy via Hamilton Depression Scale (HAMD) change and tolerability via dropout rates.
  • Analyzed 21 antidepressants across 231 treatment comparisons, focusing on those with inconclusive evidence.

Main Results:

  • Required sample sizes for 80% conditional power range from N=894-4190 (efficacy) and N=521-1246 (tolerability).
  • Sample sizes of N=49-485 (efficacy) and N=40-320 (tolerability) may necessitate stopping for futility (20% conditional power).
  • Clomipramine, levomilnacipran, milnacipran, nefazodone, and vilazodone showed the greatest conditional power with the smallest required sample sizes.

Conclusions:

  • Conditional power for achieving new conclusive evidence in antidepressant trials is generally low.
  • Large required sample sizes and small effect sizes limit the feasibility of future antidepressant RCTs in MDD.
  • Findings can inform researchers and decision-makers on the justification and clinical relevance of ongoing/future MDD research.