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Title: Survival and quality of life impact of a risk-based allocation algorithm for deceased donor kidney transplantation.
Austin Authors: Calisa, Vaishnavi;Craig, Jonathan C;Howard, Kirsten;Howell, Martin;Alexander, Stephen;Chadban, Steven J;Clayton, Philip;Lim, Wai H;Kanellis, John;Wyburn, Kate;Johnson, David W;McDonald, Stephen P;Opdam, Helen I ;Chapman, Jeremy R;Yang, Jean;Wong, Germaine
Affiliation: Sydney School of Public Heath, The University of Sydney
Centre for Kidney Research, Kid's Research Institute, The Children's Hospital at Westmead
ANZDATA Registry, SA Health and Medical Research Institute, Adelaide, Australia
Renal Medicine, Royal Prince Alfred Hospital, Sydney, Australia
Kidney Node, Charles Perkins Centre, University of Sydney, Australia
School of Medicine, University of Adelaide, Adelaide, Australia
Central Northern Adelaide Renal and Transplantation Service, Royal Adelaide Hospital, Adelaide, Australia
Department of Renal Medicine, Sir Charles Gairdner Hospital, Perth, Australia
School of Medicine and Pharmacology, University of Western Australia, Perth, Australia
Department of Nephrology, Monash Health and Centre for Inflammatory Diseases, Department of Medicine, Monash University, Clayton, Victoria, Australia
Department of Nephrology, Princess Alexandra Hospital, Brisbane, Australia
Centre for Kidney Disease Research, University of Queensland, Brisbane, Australia
Translational Research Institute, Brisbane, Australia
Austin Health, Heidelberg, Victoria, Australia
Centre for Transplant and Renal Research, Westmead Hospital
School of Mathematics and Statistics, University of Sydney, Australia
Issue Date: 2018
Date: 2018
Publication information: Transplantation 2018; 102(9): 1530-1537
Abstract: To determine the incremental gains in graft and patient survival under a risk-based, deceased donor kidney allocation compared to the current Australian algorithm. Risk-based matching algorithms were applied to first graft, kidney only recipients (n=7513) transplanted in Australia between 1994 and 2013. Probabilistic models were used to compare the waiting time, life and quality-adjusted life years and graft years between the 8 risk-based allocation strategies against current practice. Compared to current practice, KDRI-EPTS matching of the lowest 20% of scores reduced median waiting time by 0.64 years (95% CI: 0.52-0.73) for recipients aged ≤ 30 years, but increased waiting time by 0.94 years (95% CI: 0.79 - 1.09) for recipients aged > 60 years. Among all age groups, the greatest gains occurred if KDRI-EPTS matching of the lowest 30% of scores was used, incurring a median overall gain of 0.63 (95% CI: 0.03-1.25) life years and 0.78 (95% CI: 0.30 - 1.26) graft years compared to current practice. A median gain in survival of 1.91 years for younger recipients (aged 30-45 years) was offset by a median reduction in survival (by 0.95 life years) among the older recipients. Prioritisation of lower quality donor kidneys for older candidates reduced the waiting time for recipients aged > 45 years, but no changes in graft and patient survivals were observed. Risk-based matching engendered a moderate, overall increase in graft and patient survival, accrued through benefits for recipients aged ≤ 45 years but disadvantage to recipients aged > 60 years.
DOI: 10.1097/TP.0000000000002144
Journal: Transplantation
PubMed URL: 29485512
PubMed URL:
Type: Journal Article
Appears in Collections:Journal articles

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