Propensity scores for confounder adjustment when assessing the effects of medical interventions using nonexperimental study designs

J Intern Med. 2014 Jun;275(6):570-80. doi: 10.1111/joim.12197. Epub 2014 Feb 13.


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.

Keywords: comparative effectiveness research; confounding; epidemiologic methods; heterogeneity; pharmacoepidemiology; propensity scores.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Age Factors
  • Comorbidity
  • Comparative Effectiveness Research* / methods
  • Comparative Effectiveness Research* / standards
  • Confounding Factors, Epidemiologic*
  • Drug Therapy, Combination
  • Epidemiologic Research Design
  • Humans
  • Outcome Assessment, Health Care / methods
  • Outcome Assessment, Health Care / standards
  • Outcome Assessment, Health Care / statistics & numerical data
  • Pharmacoepidemiology / methods
  • Propensity Score*
  • Sex Factors