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Statistical power for MACE and individual secondary endpoints in cardiovascular outcomes trials for type 2 diabetes:

Sebastian Birker1, Juris J Meier1,2, Michael A Nauck3

  • 1Diabetes, Endocrinology, Metabolism Section, Medical Department I, Katholisches Klinikum Bochum gGmbH, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791, Bochum, Germany.

Scientific Reports
|December 6, 2022
PubMed

Insights

Cardiovascular outcomes trials (CVOTs) for type 2 diabetes drugs have sufficient power for their primary composite endpoint (major adverse cardiovascular events), but not for individual outcomes. This is especially true for smaller trials, cautioning against comparing individual endpoint results between studies.

Area of Science:

  • Endocrinology
  • Cardiology
  • Clinical Trials

Background:

  • Cardiovascular outcomes trials (CVOTs) for type 2 diabetes treatments commonly use a composite endpoint of major adverse cardiovascular events (MACE).
  • Individual cardiovascular event data (myocardial infarction, stroke, cardiovascular death, etc.) are also reported but may lack sufficient statistical power.

Approach:

  • This study post hoc estimated the statistical power of published CVOTs to detect significant differences (10-25%) in individual versus composite endpoints.
  • Power was assessed using two-sided log-rank tests comparing event proportions in patients.

Key Points:

  • Larger CVOTs demonstrated high power (82.3-100.0%) for detecting a 15% difference in MACE.
  • Smaller, preliminary trials showed lower power for MACE (e.g., 69.1% and 50.5%).
  • Statistical power for individual cardiovascular outcomes was consistently lower than for the composite MACE endpoint across trials.

Conclusions:

  • CVOTs generally possess adequate power for their primary composite MACE endpoint.
  • However, power to detect significant differences in individual cardiovascular outcomes is often insufficient, particularly in smaller studies.
  • Caution is advised when comparing individual endpoint results across different CVOTs to assess heterogeneity within or between drug classes.

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