title: Propensity score methods gave similar results to traditional regression modeling in observational studies: a systematic review.
abstract: OBJECTIVE
  To determine whether adjusting for confounder bias in observational studies using propensity scores gives different results than using traditional regression modeling.
  
  
  METHODS
  Medline and Embase were used to identify studies that described at least one association between an exposure and an outcome using both traditional regression and propensity score methods to control for confounding. From 43 studies, 78 exposure-outcome associations were found. Measures of the quality of propensity score implementation were determined. The statistical significance of each association using both analytical methods was compared. The odds or hazard ratios derived using both methods were compared quantitatively.
  
  
  RESULTS
  Statistical significance differed between regression and propensity score methods for only 8 of the associations (10%), kappa = 0.79 (95% CI = 0.65-0.92). In all cases, the regression method gave a statistically significant association not observed with the propensity score method. The odds or hazard ratio derived using propensity scores was, on average, 6.4% closer to unity than that derived using traditional regression.
  
  
  CONCLUSIONS
  Observational studies had similar results whether using traditional regression or propensity scores to adjust for confounding. Propensity scores gave slightly weaker associations; however, many of the reviewed studies did not implement propensity scores well.
authors.affiliation: Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada. baiju.shah@ices.on.ca
authors.forename: Baiju R
authors.initials: BR
authors.lastname: Shah
authors.forename: Andreas
authors.initials: A
authors.lastname: Laupacis
authors.forename: Janet E
authors.initials: JE
authors.lastname: Hux
authors.forename: Peter C
authors.initials: PC
authors.lastname: Austin
mesh_terms: D015982:Bias; D015986:Confounding Factors, Epidemiologic; D003627:Data Interpretation, Statistical; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000379:methods*; D012044:Regression Analysis; D012107:Research Design