title: Propensity scores for confounder adjustment when assessing the effects of medical interventions using nonexperimental study designs.
abstract: Treatment effects, especially when comparing two or more therapeutic alternatives as in comparative effectiveness research, are likely to be heterogeneous across age, gender, co-morbidities and co-medications. Propensity scores (PSs), an alternative to multivariable outcome models to control for measured confounding, have specific advantages in the presence of heterogeneous treatment effects. Implementing PSs using matching or weighting allows us to estimate different overall treatment effects in differently defined populations. Heterogeneous treatment effects can also be due to unmeasured confounding concentrated in those treated contrary to prediction. Sensitivity analyses based on PSs can help to assess such unmeasured confounding. PSs should be considered a primary or secondary analytic strategy in nonexperimental medical research, including pharmacoepidemiology and nonexperimental comparative effectiveness research.
authors: Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors: T
authors: T
authors: Stürmer
authors: R
authors: R
authors: Wyss
authors: R J
authors: RJ
authors: Glynn
authors: M A
authors: MA
authors: Brookhart
mesh_terms: D000367:Age Factors; D015897:Comorbidity; D057186:Comparative Effectiveness Research / Q000379:methods / Q000592:standards; D015986:Confounding Factors, Epidemiologic; D004359:Drug Therapy, Combination; D015340:Epidemiologic Research Design; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data; D017891:Pharmacoepidemiology / Q000379:methods; D057216:Propensity Score; D012737:Sex Factors
keywords: comparative effectiveness research; confounding; epidemiologic methods; heterogeneity; pharmacoepidemiology; propensity scores