Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/36056
DC FieldValueLanguage
dc.contributor.authorNegrin, Miguel A.en_US
dc.contributor.authorNam, Julianen_US
dc.contributor.authorBriggs, Andrew H.en_US
dc.contributor.otherNegrin, Miguel
dc.date.accessioned2018-05-14T10:07:16Z-
dc.date.available2018-05-14T10:07:16Z-
dc.date.issued2017en_US
dc.identifier.issn0272-989Xen_US
dc.identifier.urihttp://hdl.handle.net/10553/36056-
dc.description.abstractObjective. Survival extrapolation using a single, best-fit model ignores 2 sources of model uncertainty: uncertainty in the true underlying distribution and uncertainty about the stability of the model parameters over time. Bayesian model averaging (BMA) has been used to account for the former, but it can also account for the latter. We investigated BMA using a published comparison of the Charnley and Spectron hip prostheses using the original 8-year follow-up registry data. Methods. A wide variety of alternative distributions were fitted. Two additional distributions were used to address uncertainty about parameter stability: optimistic and skeptical. The optimistic (skeptical) model represented the model distribution with the highest (lowest) estimated probabilities of survival but reestimated using, as prior information, the most optimistic (skeptical) parameter estimated for intermediate follow-up periods. Distributions were then averaged assuming the same posterior probabilities for the optimistic, skeptical, and noninformative models. Cost-effectiveness was compared using both the original 8-year and extended 16-year follow-up data. Results. We found that all models obtained similar revision-free years during the observed period. In contrast, there was variability over the decision time horizon. Over the observed period, we detected considerable uncertainty in the shape parameter for Spectron. After BMA, Spectron was cost-effective at a threshold of 20,000 pound with 93% probability, whereas the best-fit model was 100%; by contrast, with a 16-year follow-up, it was 0%. Conclusions. This case study casts doubt on the ability of the single best-fit model selected by information criteria statistics to adequately capture model uncertainty. Under this scenario, BMA weighted by posterior probabilities better addressed model uncertainty. However, there is still value in regularly updating health economic models, even where decision uncertainty is low.en_US
dc.languageengen_US
dc.relation.ispartofMedical Decision Makingen_US
dc.sourceMedical Decision Making[ISSN 0272-989X],v. 37 (4), p. 367-376en_US
dc.subject530202 Modelos econométricosen_US
dc.subject.otherProvider decision makingen_US
dc.subject.otherAcceptability curvesen_US
dc.subject.otherCost-effectiveness analysisen_US
dc.subject.otherEconometric methodsen_US
dc.subject.otherDecision analysisen_US
dc.subject.otherMarkov modelsen_US
dc.subject.otherBayesian statistical methodsen_US
dc.subject.otherSurvival analysisen_US
dc.titleBayesian solutions for handling uncertainty in survival extrapolationen_US
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticlees
dc.identifier.doi10.1177/0272989X16650669
dc.identifier.scopus85019089156
dc.identifier.isi000403059700007
dcterms.isPartOfMedical Decision Making
dcterms.sourceMedical Decision Making[ISSN 0272-989X],v. 37 (4), p. 367-376
dc.contributor.authorscopusid9249657200
dc.contributor.authorscopusid55965465500
dc.contributor.authorscopusid7102129603
dc.identifier.eissn1552-681X-
dc.description.lastpage376-
dc.identifier.issue4-
dc.description.firstpage367-
dc.relation.volume37-
dc.investigacionCiencias Sociales y Jurídicasen_US
dc.type2Artículoen_US
dc.identifier.wosWOS:000403059700007-
dc.contributor.daisngid1285254
dc.contributor.daisngid3849343
dc.contributor.daisngid4600
dc.identifier.investigatorRIDK-8293-2017
dc.contributor.wosstandardWOS:Negrin, MA
dc.contributor.wosstandardWOS:Nam, J
dc.contributor.wosstandardWOS:Briggs, AH
dc.date.coverdateEnero 2017
dc.identifier.ulpgces
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptTécnicas estadísticas bayesianas y de decisión en la economía y empresa-
crisitem.author.deptIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.orcid0000-0002-7074-6268-
crisitem.author.parentorgIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.fullNameNegrín Hernández, Miguel Ángel-
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