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dc.rights.licenseopenen_US
dc.contributor.authorKARADKHELE, Geeta
dc.contributor.authorMANCA, Florian
hal.structure.identifierBordeaux population health [BPH]
hal.structure.identifierGlobal Health in the Global South [GHiGS]
dc.contributor.authorKABORE, Remi
dc.contributor.authorPATZER, Rachel
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorHARAMBAT, Jerome
IDREF: 110567358
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorLEFFONDRE, Karen
IDREF: 183599128
dc.contributor.authorHOGAN, Julien
dc.contributor.editorESQUIVEL, Carlos O.
dc.date.accessioned2023-11-06T16:20:58Z
dc.date.available2023-11-06T16:20:58Z
dc.date.issued2023-03-22
dc.date.conference2023-03-25
dc.identifier.issn1399-3046en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/184633
dc.description.abstractEnIntroduction: Accurate prediction models of kidney allograft loss are lacking in children. Dynamic models allow the integration of new data throughout a patient’s follow-up making them better fitted from clinical use than traditional predictive models. In this study, we aim at externally validating a dynamic score of kidney allograft loss, developed in a derivation cohort of 793 French pediatric kidney transplant recipients, in a large cohort from the United States. Methods: All patients aged < 21 years old, transplanted in the US between January 1st 2002 and December 31st 2015 recorded in the SRTR registry were included in the validation cohort. Two predictive models were previously developed using joint models on the French National Registry data (REIN) and included recipient, donor and transplant characteristics and follow-up data (eGFR, eGFR slope). Individual predictions of allograft loss at 3 and 5 years were made by applying these two models on the validation cohort. Model accuracy was evaluated based on its discrimination (AUC) and calibration (R2). Results: 10,613 patients were included. Among them, 94% were younger than 18 years old at the time of transplantation, 59% were male, 28% received a preemptive transplant and 43% a living donor transplant. Over a median follow-up time of 6.6 [4.0;9.7] years, 2420 patients (23%) lost their graft and 316 (6%) died. The performances of the models were good with excellent discrimination (AUCs between 0.8 and 0.9) and good calibration (Figure 1). The performance of the reduced model were similar to those of the full model. Conclusion: This predictive model demonstrated high accuracy in predicting kidney allograft loss in children and support the benefit of incorporating longitudinal information to improve prediction performance. This model can be used prospectively to assess patients’ risk of graft loss and further study evaluating the impact of using this model in clinical practice are needed.
dc.language.isoENen_US
dc.title.enValidation of a dynamic prediction model of kidney allograft survival in pediatric kidney transplant recipients
dc.typeCommunication dans un congrèsen_US
dc.identifier.doi10.1111/petr.14477en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
bordeaux.pagee14477en_US
bordeaux.volume27en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.issueS2en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.conference.title12th Congress of the International Pediatric Transplant Associationen_US
bordeaux.countryusen_US
bordeaux.teamGHIGSen_US
bordeaux.teamLEHAen_US
bordeaux.teamBIOSTATen_US
bordeaux.conference.cityAustinen_US
hal.identifierhal-04272616
hal.version1
hal.date.transferred2023-11-06T16:21:00Z
hal.invitedouien_US
hal.proceedingsouien_US
hal.conference.end2023-03-28
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
workflow.import.sourcepubmed
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&amp;rft_val_fmt=info:ofi/fmt:kev:mtx:journal&amp;rft.date=2023-03-22&amp;rft.volume=27&amp;rft.issue=S2&amp;rft.spage=e14477&amp;rft.epage=e14477&amp;rft.eissn=1399-3046&amp;rft.issn=1399-3046&amp;rft.au=KARADKHELE,%20Geeta&amp;MANCA,%20Florian&amp;KABORE,%20Remi&amp;PATZER,%20Rachel&amp;HARAMBAT,%20Jerome&amp;rft.genre=unknown


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