title: Simulating effects of biomarker enrichment on Alzheimer's disease prevention trials: conceptual framework and example.
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.
  
  
  CONCLUSIONS
  Biomarker enrichment can increase statistical power, but estimates of the expected increase are sensitive to a variety of assumptions outlined in the framework.
authors: Department of Psychiatry, Division of Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: jeannie-marie@jhu.edu.
authors: Jeannie-Marie S
authors: JM
authors: Leoutsakos
authors: STEM Magnet Program, South River High School, Edgewater, MD, USA.
authors: Alexandra L
authors: AL
authors: Bartlett
authors: Department of Psychiatry, Division of Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors: Sarah N
authors: SN
authors: Forrester
authors: Department of Psychiatry, Division of Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors: Constantine G
authors: CG
authors: Lyketsos
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000517:prevention & control*; D000893:Anti-Inflammatory Agents / Q000627:therapeutic use*; D015415:Biomarkers / Q000378:metabolism*; D000068579:Celecoxib; D003198:Computer Simulation; D052246:Cyclooxygenase 2 Inhibitors / Q000627:therapeutic use; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D015233:Models, Statistical; D009288:Naproxen / Q000627:therapeutic use; D011720:Pyrazoles / Q000627:therapeutic use; D013449:Sulfonamides / Q000627:therapeutic use
chemical_list: D000893:Anti-Inflammatory Agents; D015415:Biomarkers; D052246:Cyclooxygenase 2 Inhibitors; D011720:Pyrazoles; D013449:Sulfonamides; D009288:Naproxen; D000068579:Celecoxib
keywords: Alzheimer's disease; Biomarker enrichment; Dementia; Random effects; Simulation; Statistical power; Trajectory
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