title: Head to head comparison of the propensity score and the high-dimensional propensity score matching methods.
abstract: BACKGROUND
  Comparative performance of the traditional propensity score (PS) and high-dimensional propensity score (hdPS) methods in the adjustment for confounding by indication remains unclear. We aimed to identify which method provided the best adjustment for confounding by indication within the context of the risk of diabetes among patients exposed to moderate versus high potency statins.
  
  
  METHODS
  A cohort of diabetes-free incident statins users was identified from the Quebec's publicly funded medico-administrative database (Full Cohort). We created two matched sub-cohorts by matching one patient initiated on a lower potency to one patient initiated on a high potency either on patients' PS or hdPS. Both methods' performance were compared by means of the absolute standardized differences (ASDD) regarding relevant characteristics and by means of the obtained measures of association.
  
  
  RESULTS
  Eight out of the 18 examined characteristics were shown to be unbalanced within the Full Cohort. Although matching on either method achieved balance within all examined characteristic, matching on patients' hdPS created the most balanced sub-cohort. Measures of associations and confidence intervals obtained within the two matched sub-cohorts overlapped.
  
  
  CONCLUSIONS
  Although ASDD suggest better matching with hdPS than with PS, measures of association were almost identical when adjusted for either method. Use of the hdPS method in adjusting for confounding by indication within future studies should be recommended due to its ability to identify confounding variables which may be unknown to the investigators.
authors.affiliation: Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada. guertinj@mcmaster.ca.|Programs for Assessment of Technology in Health, St. Joseph's Healthcare Hamilton, Hamilton, QC, Canada. guertinj@mcmaster.ca.
authors.forename: Jason R
authors.initials: JR
authors.lastname: Guertin
authors.affiliation: Research Institute of the McGill University Health Centre, Montreal, QC, Canada. elham.rahme@mcgill.ca.|Department of Medicine, McGill University, Montreal, QC, Canada. elham.rahme@mcgill.ca.
authors.forename: Elham
authors.initials: E
authors.lastname: Rahme
authors.affiliation: Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC, Canada. colin.dormuth@ti.ubc.ca.
authors.forename: Colin R
authors.initials: CR
authors.lastname: Dormuth
authors.affiliation: Pharmacoeconomic and Pharmacoepidemiology unit, Research Center of the Centre hospitalier de l'Université de Montréal, Pavillon S, 850 St-Denis, 3e étage, Montreal, QC, Canada. jacques.le.lorier@sympatico.ca.
authors.forename: Jacques
authors.initials: J
authors.lastname: LeLorier
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D016022:Case-Control Studies; D057186:Comparative Effectiveness Research / Q000379:methods*; D016001:Confidence Intervals; D015986:Confounding Factors, Epidemiologic; D016208:Databases, Factual; D005260:Female; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000008:administration & dosage*; D006949:Hyperlipidemias / Q000175:diagnosis / Q000188:drug therapy* / Q000453:epidemiology*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D057216:Propensity Score; D011792:Quebec; D012016:Reference Values; D012737:Sex Factors
chemical_list: D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors