Temporal validation of the Australian estimated post-transplant survival score.


Journal

Nephrology (Carlton, Vic.)
ISSN: 1440-1797
Titre abrégé: Nephrology (Carlton)
Pays: Australia
ID NLM: 9615568

Informations de publication

Date de publication:
May 2023
Historique:
revised: 13 03 2023
received: 23 10 2022
accepted: 15 03 2023
medline: 17 4 2023
pubmed: 21 3 2023
entrez: 20 3 2023
Statut: ppublish

Résumé

The Australian estimated post-transplant survival (EPTS-AU) prediction score was developed by re-fitting the United States of America EPTS, without diabetes, to the Australian and New Zealand kidney transplant population over 2002-2013. The EPTS-AU score incorporates age, previous transplantation and time on dialysis. Diabetes was excluded from the score, as this was not previously recorded in the Australian allocation system. In May 2021, the EPTS-AU prediction score was incorporated into the Australian kidney allocation algorithm to optimize utility for recipients (maximized benefit). We aimed to temporally validate the EPTS-AU prediction score to ensure it can be used for this purpose. Using the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry, we included adult recipients of deceased donor kidney-only transplants between 2014 and 2021. We constructed Cox models for patient survival. We assessed validation using measures of model fit (Akaike information criterion and misspecification), discrimination (Harrell's C statistic and Kaplan-Meier curves), and calibration (observed vs. predicted survival). Six thousand four hundred and two recipients were included in the analysis. The EPTS-AU had moderate discrimination with a C statistic of 0.69 (95% CI 0.67, 0.71), and clear delineation between Kaplan-Meier's survival curves of EPTS-AU. The EPTS was well calibrated with the predicted survivals equating with the observed survival outcomes for all prognostic groups. The EPTS-AU performs reasonably well in choosing between recipients (discrimination) and to predict a recipient's survival (calibration). Reassuringly, the score is functioning as intended to predict post-transplant survival for recipients as part of the national allocation algorithm.

Identifiants

pubmed: 36941195
doi: 10.1111/nep.14158
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

292-298

Subventions

Organisme : National Health and Medical Research Council (Postgraduate Research Scholarship)

Informations de copyright

© 2023 Asian Pacific Society of Nephrology.

Références

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Auteurs

G L Irish (GL)

Transplant Epidemiology Group (TrEG), Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, Australia.
Central and Northern Adelaide Renal and Transplantation Service, Royal Adelaide Hospital, Adelaide, Australia.
Department of Medicine, The University of Adelaide, Adelaide, Australia.

S Campbell (S)

Department of Nephrology, Princess Alexandra Hospital, Brisbane, Queensland, Australia.
School of Medicine, The University of Queensland, Brisbane, Queensland, Australia.

J Kanellis (J)

Department of Nephrology, Monash Health, Melbourne, Australia.
Centre for Inflammatory Diseases, Department of Medicine, Monash University, Melbourne, Australia.

Kate Wyburn (K)

Faculty of Medicine and Health, Central Clinical School, The University of Sydney, Sydney, New South Wales, Australia.
Department of Renal Medicine, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia.

Philip A Clayton (PA)

Transplant Epidemiology Group (TrEG), Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, Australia.
Central and Northern Adelaide Renal and Transplantation Service, Royal Adelaide Hospital, Adelaide, Australia.
Department of Medicine, The University of Adelaide, Adelaide, Australia.

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