Simulating effects of biomarker enrichment on Alzheimer's disease prevention trials: Conceptual framework and example

Jeannie Marie S. Leoutsakos, Alexandra L. Bartlett, Sarah N. Forrester, Constantine G. Lyketsos

Research output: Contribution to journalArticle

Abstract

Background We present a conceptual framework for simulations to determine the utility of biomarker enrichment to increase statistical power to detect a treatment effect in future Alzheimer's disease prevention trials. We include a limited set of simulation results to illustrate aspects of this framework. Methods We simulated data based on the Alzheimer's Disease Anti-Inflammatory Prevention Trial, and a range of sample sizes, biomarker positive predictive values, and treatment effects. We also investigated the consequences of assuming homogeneity of parameter estimates as a function of dementia outcome. Results Use of biomarkers to increase the sample fraction that would develop Alzheimer's disease in the absence of intervention from 0.5 to 0.8 would increase power from 0.35 to 0.69 with n = 200. Ignoring sample heterogeneity resulted in overestimation of power. Conclusion Biomarker enrichment can increase statistical power, but estimates of the expected increase are sensitive to a variety of assumptions outlined in the framework.

Original languageEnglish (US)
Pages (from-to)152-161
Number of pages10
JournalAlzheimer's and Dementia
Volume10
Issue number2
DOIs
StatePublished - Mar 2014

Keywords

  • Alzheimer's disease
  • Biomarker enrichment
  • Dementia
  • Random effects
  • Simulation
  • Statistical power
  • Trajectory

ASJC Scopus subject areas

  • Epidemiology
  • Health Policy
  • Developmental Neuroscience
  • Clinical Neurology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience

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