Affiliations 

  • 1 Faculty of Pharmaceutical Sciences, Department of Pharmacy Practice, Center of Pharmaceutical Outcomes Research, Naresuan University, Phitsanulok, Thailand; Department of Pharmacy Systems, Outcomes and Policy, Center for Pharmacoepidemiology and Pharmacoeconomic Research, College of Pharmacy, University of Illinois at Chicago, Chicago, IL, USA
  • 2 Faculty of Pharmaceutical Sciences, Department of Pharmacy Practice, Center of Pharmaceutical Outcomes Research, Naresuan University, Phitsanulok, Thailand; School of Pharmacy, Monash University Malaysia, Selangor, Malaysia; School of Population Health, University of Queensland, Brisbane, Australia; School of Pharmacy, University of Wisconsin-Madison, Madison, WI, USA
  • 3 Department of Pharmacy, Buddhachinaraj Hospital, Muang, Phitsanulok, Thailand
  • 4 Department of Pharmacy Systems, Outcomes and Policy, Center for Pharmacoepidemiology and Pharmacoeconomic Research, College of Pharmacy, University of Illinois at Chicago, Chicago, IL, USA. Electronic address: toddlee@uic.edu
Value Health Reg Issues, 2014 May;3:222-228.
PMID: 29702931 DOI: 10.1016/j.vhri.2014.04.013

Abstract

OBJECTIVES: To evaluate whether there are differences in propensity score (PS) and treatment effects estimated using conventional and calendar time-specific PS (CTS-PS) approaches.

METHODS: A retrospective database analysis at a university-affiliated hospital in Thailand was used. Diabetic patients receiving glucose-lowering medications from July 2008 to June 2011 were included. Patients were categorized into those exposed and not exposed to thiazolidinediones (TZDs). PSs were estimated by using conventional PS and CTS-PS. In the CTS-PS, PS was separately estimated for three specific calendar time periods. Patients were matched 1:1 using caliper matching. The outcomes were cardiovascular and all-cause hospitalizations. The TZD and non-TZD groups were compared with Cox proportional hazard models.

RESULTS: A total of 2165 patients were included. The average conventional PS was 0.198 (95% confidence interval [CI] 0.195-0.202), while the average PS in the CTS-PS approach was 0.212 (0.206-0.218), 0.180 (0.173-0.188), and 0.205 (0.197-0.213) for July 2008 to June 2009, July 2009 to June 2010, and July 2010 to June 2011, respectively. The average difference in PS was 0.012 (P < 0.001), -0.009 (P ≤ 0.002), and 0.000 (P = 0.950) in the three calendar time periods. The adjusted hazard ratios of the conventional PS-matched cohort were 0.97 (95% CI 0.39-2.45) and 0.97 (95% CI 0.78-1.20) for CVD-related and all-cause hospitalizations, while the adjusted hazard ratios of the CTS-PS-matched cohort were 1.11 (95% CI 0.43-2.88) and 1.12 (95% CI 0.91-1.39), respectively.

CONCLUSION: CTS-PS is different from PS estimated by using the conventional approach. CTS-PS should be considered when a pattern of medication use has changed over the study period.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.