Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/45336
Title: A competing risks model to estimate the risk of graft failure and patient death after kidney transplantation using continuous donor-recipient age combinations
Authors: Coemans, Maarten
Tran , Thuong Hien
Doeurohler, Bernd
Massie, Allan B.
VERBEKE, Geert 
Segev, Dorry L.
Gentry, Sommer E.
Naesens, Maarten
Issue Date: 2025
Publisher: ELSEVIER SCIENCE INC
Source: American journal of transplantation, 25 (2) , p. 355 -367
Abstract: Graft failure and recipient death with functioning graft are important competing outcomes after kidney transplantation. Risk prediction models typically censor for the competing outcome thereby overestimating the cumulative incidence. The magnitude of this overestimation is not well described in real-world transplant data. This retrospective cohort study analyzed data from the European Collaborative Transplant Study (n = 125 250) and from the American Scientific Registry of Transplant Recipients (n = 190 258). Separate cause-specific hazard models using donor and recipient age as continuous predictors were developed for graft failure and recipient death. The hazard of graft failure increased quadratically with increasing donor age and decreased decaying with increasing recipient age. The hazard of recipient death increased linearly with increasing donor and recipient age. The cumulative incidence overestimation due to competing risk-censoring was largest in high-risk populations for both outcomes (old donors/recipients), sometimes amounting to 8.4 and 18.8 percentage points for graft failure and recipient death, respectively. In our illustrative model for posttransplant risk prediction, the absolute risk of graft failure and death is overestimated when censoring for the competing event, mainly in older donors and recipients. Prediction models for absolute risks should treat graft failure and death as events.
Notes: Naesens, M (corresponding author), Herestr 49, B-3000 Leuven, Belgium.
maarten.naesens@uzleuven.be
Keywords: censoring;graft loss;prediction model;time-to-event analysis;competing risks
Document URI: http://hdl.handle.net/1942/45336
ISSN: 1600-6135
e-ISSN: 1600-6143
DOI: 10.1016/j.ajt.2024.07.029
ISI #: 001412521700001
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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