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Three handy tips and a practical guide to improve your propensity score models

2019-04-01Recensão Acesso aberto
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dc.contributor.authorBergstra, Sytske Anne
dc.contributor.authorSepriano, Alexandre
dc.contributor.authorSepriano, Alexandre
dc.contributor.authorRamiro, Sofia
dc.contributor.authorRamiro, Sofia
dc.contributor.authorLandewé, Robert
dc.contributor.institutionNOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
dc.contributor.pblBMJ Publishing Group
dc.date.accessioned2019-05-21T22:17:35Z
dc.date.available2019-05-21T22:17:35Z
dc.date.issued2019-04-01
dc.description.abstractReal-world data are increasingly available to investigate real-world' safety and efficacy. However, since treatment in observational studies is not randomly allocated, confounding by indication may occur, in which differences in patient characteristics may influence both treatment choices and treatment responses. A popular method to adjust for this type of bias is the use of propensity scores (PS). The PS is a score between 0 and 1 that reflects the likelihood per patient of receiving one of the treatment categories of interest conditional on a set of variables. At least in theory, in patients with similar PS, the treatment prescribed will be independent of these variables (pseudorandomisation). But researchers using PS sometimes fail to recognise important methodological flaws which can lead to spurious conclusions. These include perfect prediction of treatment allocation, untied observations and lack of generalisability due to oversimplification of complex clinical scenarios. In this viewpoint we will discuss the most commonly encountered flaws and provide a stepwise description on the estimation and use of PS, such that in future publications these flaws can be avoided.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent320613
dc.identifier.doi10.1136/rmdopen-2019-000953
dc.identifier.issn2044-6055
dc.identifier.otherPURE: 13256622
dc.identifier.otherPURE UUID: 52578128-51bc-4cab-b30e-75d63140b91b
dc.identifier.otherScopus: 85065299275
dc.identifier.otherPubMed: 31168417
dc.identifier.otherWOS: 000467325800007
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=85065299275&partnerID=8YFLogxK
dc.identifier.urlhttps://www.scopus.com/pages/publications/85065299275
dc.language.isoeng
dc.peerreviewedyes
dc.subjectbias
dc.subjectobservational studies
dc.subjectpropensity scores
dc.subjecttreatment effects
dc.subjectRheumatology
dc.subjectImmunology and Allergy
dc.subjectImmunology
dc.titleThree handy tips and a practical guide to improve your propensity score modelsen
dc.typereview
degois.publication.issue1
degois.publication.titleRMD Open
degois.publication.volume5
dspace.entity.typePublication
person.familyNameSepriano
person.familyNameRamiro
person.givenNameAlexandre
person.givenNameSofia
person.identifier397398
person.identifier.ciencia-id5E1B-9976-5CE4
person.identifier.ciencia-idC513-D4F1-EEC3
person.identifier.orcid0000-0003-1954-0229
person.identifier.orcid0000-0002-8899-9087
person.identifier.scopus-author-id55266526300
rcaap.rightsopenAccess
relation.isAuthorOfPublicationd87df0c7-841b-4648-a99e-296348e2e286
relation.isAuthorOfPublication9853406a-2641-440d-a8b1-a516bdb6f32f
relation.isAuthorOfPublication.latestForDiscoveryd87df0c7-841b-4648-a99e-296348e2e286

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