title: Population Impact & Efficiency of Benefit-Targeted Versus Risk-Targeted Statin Prescribing for Primary Prevention of Cardiovascular Disease.
abstract: Benefit-targeted statin prescribing may be superior to risk-targeted statin prescribing (the current standard), but the impact and efficiency of this approach are unclear.
  
  
  
  We analyzed the National Health and Nutrition Examination Survey (NHANES) using an open-source model (the Prevention Impact and Efficiency Model) to compare targeting of statin therapy according to expected benefit (benefit-targeted) versus baseline risk (risk-targeted) in terms of projected population-level impact and efficiency. Impact was defined as relative % reduction in atherosclerotic cardiovascular disease in the US population for the given strategy compared to current statin treatment patterns; and efficiency as the number needed to treat over 10 years (NNT10, average and maximum) to prevent each atherosclerotic cardiovascular disease event. Benefit-targeted moderate-intensity statin therapy at a treatment threshold of 2.3% expected 10-year absolute risk reduction could produce a 5.7% impact (95% confidence interval, 4.8-6.7). This is approximately equivalent to the potential impact of risk-targeted therapy at a treatment threshold of 5% 10-year atherosclerotic cardiovascular disease risk (5.6% impact [4.7-6.6]). Whereas the estimated maximum NNT10is much improved for benefit-targeted versus risk-targeted therapy at these equivalent-impact thresholds (43.5 vs 180), the average NNT10is nearly equivalent (24.2 vs 24.6). Reaching 10% impact (half the Healthy People 2020 impact objective, loosely defined) is theoretically possible with benefit-targeted moderate-intensity statins of persons with expected absolute risk reduction >2.3% if we expand age eligibility and account for treatment of all persons with diabetes mellitus or with low-density lipoprotein >190 mg/dL (impact=12.4%; average NNT10=23.0).
  
  
  
  Benefit-based targeting of statin therapy provides modest gains in efficiency over risk-based prescribing and could theoretically help attain approximately half of the Healthy People 2020 impact goal with reasonable efficiency.
authors.affiliation: Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA mpletcher@epi.ucsf.edu.|Department of Medicicine, University of California, San Francisco, San Francisco, CA.
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Pletcher
authors.affiliation: Dell Medical School, University of Texas at Austin, TX.
authors.forename: Michael
authors.initials: M
authors.lastname: Pignone
authors.affiliation: Department of Health Policy and Management, Gillings School of Public Health, Chapel Hill, NC.|School of Medicine, University of North Carolina, Chapel Hill, NC.
authors.forename: Jamie A
authors.initials: JA
authors.lastname: Jarmul
authors.affiliation: Division of General Medicine, Columbia University Medical Center, New York, NY.
authors.forename: Andrew E
authors.initials: AE
authors.lastname: Moran
authors.affiliation: Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA.
authors.forename: Eric
authors.initials: E
authors.lastname: Vittinghoff
authors.affiliation: Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA.|Department of Pediatrics, University of California, San Francisco, San Francisco, CA.
authors.forename: Thomas
authors.initials: T
authors.lastname: Newman
mesh_terms: D000328:Adult; D000368:Aged; D002318:Cardiovascular Diseases / Q000453:epidemiology / Q000517:prevention & control*; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000627:therapeutic use*; D008297:Male; D008875:Middle Aged; D009749:Nutrition Surveys; D057285:Precision Medicine / Q000379:methods*; D011322:Primary Prevention / Q000379:methods*; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D014481:United States / Q000453:epidemiology; D055815:Young Adult
chemical_list: D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors
keywords: cholesterol; population; risk assessment; statin