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Evaluating Cost-Effectiveness in Using High-Kidney Donor Profile Index Organs.
Ellison, Trevor A; Bae, Sunjae; Chow, Eric K H; Massie, Allan B; Kucirka, Lauren M; Van Arendonk, Kyle J; Segev, Dorry L.
Afiliação
  • Ellison TA; Department of Cardiothoracic Surgery, Genesis Healthcare, Zanesville, OH. Electronic address: trevorellison@gmail.com.
  • Bae S; Department of Surgery, NYU Grossman School of Medicine, NY; Department of Population Health, NYU Grossman School of Medicine, NY.
  • Chow EKH; Rosalind Franklin University of Medicine and Science, North Chicago, IL.
  • Massie AB; Department of Surgery, NYU Grossman School of Medicine, NY; Department of Population Health, NYU Grossman School of Medicine, NY.
  • Kucirka LM; Department of Obstetrics and Gynecology, University of North Carolina, NC.
  • Van Arendonk KJ; Department of Surgery, Division of Pediatric Surgery, Medical College of Wisconsin, WI.
  • Segev DL; Department of Surgery, NYU Grossman School of Medicine, NY; Department of Population Health, NYU Grossman School of Medicine, NY.
Transplant Proc ; 55(10): 2333-2344, 2023 Dec.
Article em En | MEDLINE | ID: mdl-37925233
ABSTRACT
A more granular donor kidney grading scale, the kidney donor profile index (KDPI), has recently emerged in contradistinction to the standard criteria donor/expanded criteria donor framework. In this paper, we built a Markov decision process model to evaluate the survival, quality-adjusted life years (QALY), and cost advantages of using high-KDPI kidneys based on multiple KDPI strata over a 60-month time horizon as opposed to remaining on the waiting list waiting for a lower-KDPI kidney. Data for the model were gathered from the Scientific Registry of Transplant Recipients and the United States Renal Data System Medicare parts A, B, and D databases. Of the 129,024 phenotypes delineated in this model, 65% of them would experience a survival benefit, 81% would experience an increase in QALYs, 87% would see cost-savings, and 76% would experience cost-savings per QALY from accepting a high-KDPI kidney rather than remaining on the waiting list waiting for a kidney of lower-KDPI. Classification and regression tree analysis (CART) revealed the main drivers of increased survival in accepting high-KDPI kidneys were wait time ≥30 months, panel reactive antibody (PRA) <90, age ≥45 to 65, diagnosis leading to renal failure, and prior transplantation. The CART analysis showed the main drivers of increased QALYs in accepting high-kidneys were wait time ≥30 months, PRA <90, and age ≥55 to 65.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transplante de Rim Limite: Aged / Humans País como assunto: America do norte Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transplante de Rim Limite: Aged / Humans País como assunto: America do norte Idioma: En Ano de publicação: 2023 Tipo de documento: Article