Propensity score methods to control for confounding in observational cohort studies: a statistical primer and application to endoscopy research - 19/08/19
Abstract |
Background and Aims |
Confounding is a major concern in nonexperimental studies of endoscopic interventions and can lead to biased estimates of the effects of treatment. Propensity score methods, which are commonly used in the pharmacoepidemiology literature, can effectively control for baseline confounding by balancing measured baseline confounders and risk factors and creating comparable populations of treated and untreated patients.
Methods |
We propose the following 5-step checklist to guide the use and evaluation of propensity score methods: (1) select covariates, (2) assess “Table 1” balance in risk factors before propensity score implementation, (3) estimate and implement the propensity score in the study cohort, (4) reassess “Table 1” balance in risk factors after propensity score implementation, and (5) critically evaluate differences between matched and unmatched patients after propensity score implementation. We then applied this checklist to an endoscopy example using a study cohort of 411 adults with newly diagnosed eosinophilic esophagitis (EoE), some of whom were treated with esophageal dilation.
Results |
We identified 156 patients, aged 18 and older, who were treated with esophageal dilation, and 255 patients who were nondilated. We successfully matched 148 (95%) dilated patients to nondilated patients who had a propensity score within 0.1, based on patient age, sex, race, self-reported food allergy, and presence of narrowing at baseline endoscopy. Crude imbalances were observed before propensity score matching in several baseline covariates, including age, sex, and narrowing; however, propensity score matching was successful in achieving balance across all measured covariates.
Conclusions |
We provide an introduction to propensity score methods, including a straightforward checklist for implementing propensity score methods in nonexperimental studies of treatment effectiveness. Moreover, we demonstrate the advantage of using “Table 1” as a simple but effective diagnostic tool for evaluating the success of propensity score methods in an applied example of esophageal dilation in EoE.
Il testo completo di questo articolo è disponibile in PDF.Abbreviations : EoE, SMD
Mappa
| DISCLOSURE: The following authors received research support for this study from the National Institutes of Health (grant nos. R01 AG056479 and T32 DK 007634): J. Y. Yang, J. L. Lund, and T. Stürmer. In addition, the following author disclosed financial relationships relevant to this publication: T. Stürmer: Salary support recipient as Director of Comparative Effectiveness Research, NC TraCS Institute, UNC Clinical and Translational Science Award (UL1TR002489), the Center for Pharmacoepidemiology (current members: GlaxoSmithKline, UCB BioSciences, Merck, Shire), from pharmaceutical companies (GSK, Amgen, AstraZeneca, Novo Nordisk), and from a generous contribution from Dr. Nancy A. Dreyer to the Department of Epidemiology, University of North Carolina at Chapel Hill; stock owner in Novartis, Roche, BASF, AstraZeneca, and Novo Nordisk. All other authors disclosed no financial relationships relevant to this publication. |
Vol 90 - N° 3
P. 360-369 - settembre 2019 Ritorno al numeroBenvenuto su EM|consulte, il riferimento dei professionisti della salute.
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