Propensity score-based approaches to confounding by indication in individual patient data meta-analysis: non-standardized treatment for multidrug resistant tuberculosis

dc.contributor.authorFox, Gregory J.en_ZA
dc.contributor.authorBenedetti, Andreaen_ZA
dc.contributor.authorMitnick, Carole D.en_ZA
dc.contributor.authorPai, Madhukaren_ZA
dc.contributor.authorMenzies, Dicken_ZA
dc.contributor.authorThe Collaborative Group for Meta-Analysis of Individual Patient Data in MDR-TBen_ZA
dc.date.accessioned2017-09-20T12:25:38Z
dc.date.available2017-09-20T12:25:38Z
dc.date.issued2016
dc.descriptionCITATION: Fox, G. J., et al. 2016. Propensity score-based approaches to confounding by indication in individual patient data meta-analysis: non-standardized treatment for multidrug resistant tuberculosis. PLoS ONE, 11(3):e0151724, doi:10.1371/journal.pone.0151724.
dc.descriptionThe original publication is available at http://journals.plos.org/plosone
dc.description.abstractBackground: In the absence of randomized clinical trials, meta-analysis of individual patient data (IPD) from observational studies may provide the most accurate effect estimates for an intervention. However, confounding by indication remains an important concern that can be addressed by incorporating individual patient covariates in different ways. We compared different analytic approaches to account for confounding in IPD from patients treated for multi-drug resistant tuberculosis (MDR-TB). Methods: Two antibiotic classes were evaluated, fluoroquinolones—considered the cornerstone of effective MDR-TB treatment—and macrolides, which are known to be safe, yet are ineffective in vitro. The primary outcome was treatment success against treatment failure, relapse or death. Effect estimates were obtained using multivariable and propensity-score based approaches. Results: Fluoroquinolone antibiotics were used in 28 included studies, within which 6,612 patients received a fluoroquinolone and 723 patients did not. Macrolides were used in 15 included studies, within which 459 patients received this class of antibiotics and 3,670 did not. Both standard multivariable regression and propensity score-based methods resulted in similar effect estimates for early and late generation fluoroquinolones, while macrolide antibiotics use was associated with reduced treatment success. Conclusions: In this individual patient data meta-analysis, standard multivariable and propensity-score based methods of adjusting for individual patient covariates for observational studies yielded produced similar effect estimates. Even when adjustment is made for potential confounding, interpretation of adjusted estimates must still consider the potential for residual bias.en_ZA
dc.description.urihttp://journals.plos.org/plosone/article?id=10.1371/journal.pone.0151724
dc.description.versionPublisher's version
dc.format.extent19 pages
dc.identifier.citationFox, G. J., et al. 2016. Propensity score-based approaches to confounding by indication in individual patient data meta-analysis: non-standardized treatment for multidrug resistant tuberculosis. PLoS ONE, 11(3):e0151724, doi:10.1371/journal.pone.0151724
dc.identifier.issn1932-6203 (online)
dc.identifier.otherdoi:10.1371/journal.pone.0151724
dc.identifier.urihttp://hdl.handle.net/10019.1/102265
dc.language.isoen_ZAen_ZA
dc.publisherPublic Library of Science
dc.rights.holderAuthors retain copyright
dc.subjectMultidrug-resistant tuberculosisen_ZA
dc.subjectTuberculosis -- Patients -- Treatmenten_ZA
dc.subjectClinical indicationsen_ZA
dc.subjectMeta-analysisen_ZA
dc.titlePropensity score-based approaches to confounding by indication in individual patient data meta-analysis: non-standardized treatment for multidrug resistant tuberculosisen_ZA
dc.typeArticleen_ZA
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