• Saswata Deb, Peter C Austin, Jack V Tu, Dennis T Ko, C David Mazer, Alex Kiss, and Stephen E Fremes.
• Schulich Heart Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada; Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.
• Can J Cardiol. 2016 Feb 1; 32 (2): 259-65.

AbstractObservational studies using propensity-score methods have been increasing in the cardiovascular literature because randomized controlled trials are not always feasible or ethical. However, propensity-score methods can be confusing, and the general audience may not fully understand the importance of this technique. The objectives of this review are to describe (1) the fundamentals of propensity score methods, (2) the techniques to assess for propensity-score model adequacy, (3) the 4 major methods for using the propensity score (matching, stratification, covariate adjustment, and inverse probability of treatment weighting [IPTW]) using examples from previously published cardiovascular studies, and (4) the strengths and weaknesses of these 4 techniques. Our review suggests that matching or IPTW using the propensity score have shown to be most effective in reducing bias of the treatment effect.Copyright © 2016 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.

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