2017
DOI: 10.1016/j.jacc.2016.10.060
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Comparison of Propensity Score Methods and Covariate Adjustment

Abstract: Abstract:Propensity scores (PS) are an increasingly popular method to adjust for confounding in observational studies. PS methods have theoretical advantages over traditional covariate adjustment, but their relative performance in real-word scenarios is poorly characterized. We used datasets from four large-scale cardiovascular observational studies (PROMETHEUS, ADAPT-DES, THIN, and CHARM) to compare the performance of traditional covariate adjustment and four commonly used PS methods: matching, stratification… Show more

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Cited by 541 publications
(426 citation statements)
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“…Fourth, after 2015, most of the cases were treated with the Turbo‐Power device which may have further improved the outcomes compared to the initial laser devices. Fifth, the two groups had differences in their baseline characteristics, but propensity score matching analysis was not used because of the small sample . Sixth, two different DCB devices were used, Lutonix and In.PACT.…”
Section: Discussionmentioning
confidence: 99%
“…Fourth, after 2015, most of the cases were treated with the Turbo‐Power device which may have further improved the outcomes compared to the initial laser devices. Fifth, the two groups had differences in their baseline characteristics, but propensity score matching analysis was not used because of the small sample . Sixth, two different DCB devices were used, Lutonix and In.PACT.…”
Section: Discussionmentioning
confidence: 99%
“…A propensity score is defined as the probability of a patient being assigned to an intervention, given a set of covariates and all patient characteristics being summarized into a single covariate, thus reducing (although not eliminating) the potential for overfitting and correcting for selection biases and potential confounding. While this technique provides an excellent balance of covariates in most circumstances, it is less precise, and some patients may remain unmatched and hence excluded from the analysis 33. Moreover, it balances the distribution of characteristics between the compared exposure groups on average, thus there may be pairs that are discordant on special characteristics; finally, there is no clear understanding of the relative performance of matching strategies in subgroup analyses 34…”
Section: A Critical Appraisal Of Methodological Issuesmentioning
confidence: 99%
“…A propensity score approach was also considered with ICP (Yes vs. No) as the outcome. However, there was still an imbalance of covariates after stratification adjustment, indicating that this approach was not optimal [20, 21]. A two-sided p value < 0.05 was considered statistically significant.…”
Section: Methodsmentioning
confidence: 99%