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Excess cumulative incidence estimation for matched cohort survival studies

dc.rights.licenseopenen_US
dc.contributor.authorBOSCHINI, C.
dc.contributor.authorANDERSEN, K. K.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorJACQMIN-GADDA, Helene
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorJOLY, Pierre
dc.contributor.authorSCHEIKE, T. H.
dc.date.accessioned2021-01-18T10:36:48Z
dc.date.available2021-01-18T10:36:48Z
dc.date.issued2020
dc.identifier.issn1097-0258 (Electronic) 0277-6715 (Linking)en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/25810
dc.description.abstractEnWe suggest a regression approach to estimate the excess cumulative incidence function (CIF) when matched data are available. In a competing risk setting, we define the excess risk as the difference between the CIF in the exposed group and the background CIF observed in the unexposed group. We show that the excess risk can be estimated through an extended binomial regression model that actively uses the matched structure of the data, avoiding further estimation of both the exposed and the unexposed CIFs. The method naturally deals with two time scales, age and time since exposure and simplifies how to deal with the left truncation on the age time‐scale. The model makes it easy to predict individual excess risk scenarios and allows for a direct interpretation of the covariate effects on the cumulative incidence scale. After introducing the model and some theory to justify the approach, we show via simulations that our model works well in practice. We conclude by applying the excess risk model to data from the ALiCCS study to investigate the excess risk of late events in childhood cancer survivors.
dc.language.isoENen_US
dc.subjectBiostatistics
dc.title.enExcess cumulative incidence estimation for matched cohort survival studies
dc.title.alternativeStat Meden_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1002/sim.8561en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed32501587en_US
bordeaux.journalStatistics in Medicineen_US
bordeaux.page2606-2620en_US
bordeaux.volume39en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.issue20en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.teamBIOSTAT_BPHen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-03166159
hal.version1
hal.date.transferred2021-03-11T09:23:48Z
hal.exporttrue
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Statistics%20in%20Medicine&rft.date=2020&rft.volume=39&rft.issue=20&rft.spage=2606-2620&rft.epage=2606-2620&rft.eissn=1097-0258%20(Electronic)%200277-6715%20(Linking)&rft.issn=1097-0258%20(Electronic)%200277-6715%20(Linking)&rft.au=BOSCHINI,%20C.&ANDERSEN,%20K.%20K.&JACQMIN-GADDA,%20Helene&JOLY,%20Pierre&SCHEIKE,%20T.%20H.&rft.genre=article


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