title: Role of disease risk scores in comparative effectiveness research with emerging therapies.
abstract: BACKGROUND
  Usefulness of propensity scores and regression models to balance potential confounders at treatment initiation may be limited for newly introduced therapies with evolving use patterns.
  
  
  OBJECTIVE
  To consider settings in which the disease risk score has theoretical advantages as a balancing score in comparative effectiveness research because of stability of disease risk and the availability of ample historical data on outcomes in people treated before introduction of the new therapy.
  
  
  METHODS
  We review the indications for and balancing properties of disease risk scores in the setting of evolving therapies and discuss alternative approaches for estimation. We illustrate development of a disease risk score in the context of the introduction of atorvastatin and the use of high-dose statin therapy beginning in 1997, based on data from 5668 older survivors of myocardial infarction who filled a statin prescription within 30 days after discharge from 1995 until 2004. Theoretical considerations suggested development of a disease risk score among nonusers of atorvastatin and high-dose statins during the period 1995-1997.
  
  
  RESULTS
  Observed risk of events increased from 11% to 35% across quintiles of the disease risk score, which had a C-statistic of 0.71. The score allowed control of many potential confounders even during early follow-up with few study endpoints.
  
  
  CONCLUSIONS
  Balancing on a disease risk score offers an attractive alternative to a propensity score in some settings such as newly marketed drugs and provides an important axis for evaluation of potential effect modification. Joint consideration of propensity and disease risk scores may be valuable.
authors.affiliation: Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 1620 Tremont Street, Boston, MA 02120, USA. rglynn@rics.bwh.harvard.edu
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Glynn
authors.forename: Joshua J
authors.initials: JJ
authors.lastname: Gagne
authors.forename: Sebastian
authors.initials: S
authors.lastname: Schneeweiss
mesh_terms: D057186:Comparative Effectiveness Research; D015986:Confounding Factors, Epidemiologic; D004305:Dose-Response Relationship, Drug; D015340:Epidemiologic Research Design; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000008:administration & dosage / Q000627:therapeutic use; D015233:Models, Statistical; D009203:Myocardial Infarction / Q000453:epidemiology* / Q000517:prevention & control; D010043:Outcome and Process Assessment, Health Care; D057216:Propensity Score; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012307:Risk Factors
chemical_list: D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors