2000
DOI: 10.1002/(sici)1099-1557(200003/04)9:2<93::aid-pds474>3.3.co;2-9
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The use of propensity scores in pharmacoepidemiologic research
Abstract: Purpose Ð To describe the application of propensity score analysis in pharmacoepidemiologic research using a study comparing the renal eects of two commonly prescribed non-steroidal anti-in¯ammatory drugs (NSAIDs).Method Ð Observational data were collected on the change in renal function, as measured by serum creatinine concentration, before and after use of two NSAIDs, Ibuprofen and Sulindac. To estimate the treatment eect of the dierent NSAIDs, we used the propensity score methodology to reduce the potential…
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Cited by 39 publications
(34 citation statements)
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Abstract
Smart CitationsHow this paper cites the one you are viewing
“…30,31 Fourth, we controlled for the likelihood of administration of moreintense acid suppression therapy using techniques commonly recommended in pharmacoepidemiology. 32 Finally, our results were resilient to the specific analytic technique applied, with remarkably similar estimates of the dose-response relationship.…”
Section: Comment
supporting
confidence: 58%
Abstract
Smart CitationsHow this paper cites the one you are viewing
“…30,31 Fourth, we controlled for the likelihood of administration of moreintense acid suppression therapy using techniques commonly recommended in pharmacoepidemiology. 32 Finally, our results were resilient to the specific analytic technique applied, with remarkably similar estimates of the dose-response relationship.…”
Section: Comment
supporting
confidence: 58%
Smart CitationsHow this paper cites the one you are viewing
“…To reduce the potential for selection bias in examining rates of ALI events between PIbased DAA therapy (glecaprevir/pibrentasvir, elbasvir/grazoprevir, or PRO/PROD) and non-PIbased regimens (sofosbuvir/ledipasvir or sofosbuvir/velpatasvir), we developed propensity scores, which determine each patient's probability of being assigned to a particular treatment given their observed set of baselined covariates. 24 Propensity score methods allow for the reduction of bias when estimating treatment effects by accounting for the differential probability of receiving PI-based or non-PI-based DAA therapy. The propensity score model was developed using logistic regression, with potential determinants of PI-based DAA therapy as independent variables and PI-based DAA treatment exposure as the dependent variable.…”
Section: Discussion
mentioning
confidence: 99%
Abstract
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“…Because this was a retrospective cohort study, patients were not randomized before the interventions. Therefore, we used a propensity score matching method to reduce the bias due to confounding [17]. A logistic regression model was created to calculate the propensity score.…”
Section: Discussion
mentioning
confidence: 99%
