Literature DB >> 30083367

Is the Kidney Donor Risk Index a Useful Tool in Non-US Patients?

Ann Young1, Greg A Knoll2,3, Eric McArthur2, Stephanie N Dixon2,4, Amit X Garg2,5, Charmaine E Lok1,2,6, Ngan N Lam7, S Joseph Kim1,2,6,8.   

Abstract

BACKGROUND: Deceased donor kidney allocation in the United States is guided by the Kidney Donor Risk Index (KDRI). The generalizability of the KDRI beyond the United States has not been widely studied.
OBJECTIVE: To assess the generalizability of the KDRI in a cohort of non-US (Canadian) deceased donor kidney transplant recipients.
DESIGN: Population-based retrospective cohort study.
SETTING: Ontario, Canada. PATIENTS: Recipients of deceased donor kidneys from January 1, 2005, to March 31, 2011.
METHODS: Using administrative data, we analyzed a cohort of deceased donor kidney recipients in Ontario, Canada. The Kaplan-Meier method and Cox proportional hazards models were used to assess the relationship between KDRI and the outcomes of graft loss and death. KDRI was modeled continuously and categorically. The ability of models with KDRI to predict recipient outcomes beyond donor age was also explored. Model discrimination was assessed using c-statistics, evaluated at 5 years of follow-up.
RESULTS: A total of 1299 consecutive deceased donor kidney transplant recipients were included. The median follow-up was 5.5 years. Mean donor age increased from 27 to 64 years across ascending KDRI quintiles. The adjusted relative hazards (95% confidence interval) for total graft loss from Q2 to Q5 (referent = Q1) were 1.27 (0.89-1.80), 1.58 (1.13-2.22), 1.43 (1.01-2.02), and 2.15 (1.54-2.99), respectively. Increased relative hazards across KDRI quintiles were also observed for death-censored graft loss, but not death with graft function. All-cause mortality was increased for the highest KDRI quintile only. In this cohort, a model with KDRI performed better than a model with donor age alone (P = .009). LIMITATIONS: Large health care databases may have precluded the complete capture of covariate data.
CONCLUSIONS: In conclusion, the KDRI is generalizable to Canadian patients in Ontario and may help inform risk assessment beyond donor age. The performance of KDRI in other non-US settings, and the need for additional model refinement, warrants further study.

Entities:  

Keywords:  Kidney Donor Risk Index; generalizability; risk assessment

Year:  2018        PMID: 30083367      PMCID: PMC6073818          DOI: 10.1177/2054358118791148

Source DB:  PubMed          Journal:  Can J Kidney Health Dis        ISSN: 2054-3581


  17 in total

1.  Coding accuracy of administrative drug claims in the Ontario Drug Benefit database.

Authors:  Adrian R Levy; Bernie J O'Brien; Connie Sellors; Paul Grootendorst; Donald Willison
Journal:  Can J Clin Pharmacol       Date:  2003

2.  Kidney donor risk index is a good prognostic tool for graft outcomes in deceased donor kidney transplantation with short, cold ischemic time.

Authors:  Miyeun Han; Jong Cheol Jeong; Tai Yeon Koo; Hee Jung Jeon; Hyuk Yong Kwon; Yoon Jung Kim; Hyun Jin Ryu; Curie Ahn; Jaeseok Yang
Journal:  Clin Transplant       Date:  2014-02-08       Impact factor: 2.863

3.  Donor characteristics associated with reduced graft survival: an approach to expanding the pool of kidney donors.

Authors:  Friedrich K Port; Jennifer L Bragg-Gresham; Robert A Metzger; Dawn M Dykstra; Brenda W Gillespie; Eric W Young; Francis L Delmonico; James J Wynn; Robert M Merion; Robert A Wolfe; Philip J Held
Journal:  Transplantation       Date:  2002-11-15       Impact factor: 4.939

4.  A simplified donor risk index for predicting outcome after deceased donor kidney transplantation.

Authors:  Christopher J E Watson; Rachel J Johnson; Rhiannon Birch; Dave Collett; J Andrew Bradley
Journal:  Transplantation       Date:  2012-02-15       Impact factor: 4.939

5.  A comprehensive risk quantification score for deceased donor kidneys: the kidney donor risk index.

Authors:  Panduranga S Rao; Douglas E Schaubel; Mary K Guidinger; Kenneth A Andreoni; Robert A Wolfe; Robert M Merion; Friedrich K Port; Randall S Sung
Journal:  Transplantation       Date:  2009-07-27       Impact factor: 4.939

6.  The impact of deceased donor kidney risk significantly varies by recipient characteristics.

Authors:  E L G Heaphy; D A Goldfarb; E D Poggio; L D Buccini; S M Flechner; J D Schold
Journal:  Am J Transplant       Date:  2013-02-13       Impact factor: 8.086

7.  Changes in Discard Rate After the Introduction of the Kidney Donor Profile Index (KDPI).

Authors:  S Bae; A B Massie; X Luo; S Anjum; N M Desai; D L Segev
Journal:  Am J Transplant       Date:  2016-03-22       Impact factor: 8.086

8.  The combined risk of donor quality and recipient age: higher-quality kidneys may not always improve patient and graft survival.

Authors:  Roland A Hernandez; Sayeed K Malek; Edgar L Milford; Samuel R G Finlayson; Stefan G Tullius
Journal:  Transplantation       Date:  2014-11-27       Impact factor: 4.939

Review 9.  A systematic review of kidney transplantation from expanded criteria donors.

Authors:  Julio Pascual; Javier Zamora; John D Pirsch
Journal:  Am J Kidney Dis       Date:  2008-09       Impact factor: 8.860

10.  The Canadian experience using the expanded criteria donor classification for allocating deceased donor kidneys for transplantation.

Authors:  Ann Young; Stephanie N Dixon; Greg A Knoll; Amit X Garg; Charmaine E Lok; Ngan N Lam; S Joseph Kim
Journal:  Can J Kidney Health Dis       Date:  2016-03-24
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  3 in total

1.  Predicting Clinical Outcome in Expanded Criteria Donor Kidney Transplantation: A Retrospective Cohort Study.

Authors:  Paramita Saha-Chaudhuri; Carly Rabin; Jean Tchervenkov; Dana Baran; Justin Morein; Ruth Sapir-Pichhadze
Journal:  Can J Kidney Health Dis       Date:  2020-06-24

2.  Kidney Transplantation in Times of Covid-19: Decision Analysis in the Canadian Context.

Authors:  Ivan Yanev; Michael Gagnon; Matthew P Cheng; Steven Paraskevas; Deepali Kumar; Alice Dragomir; Ruth Sapir-Pichhadze
Journal:  Can J Kidney Health Dis       Date:  2021-09-14

Review 3.  Using Information Available at the Time of Donor Offer to Predict Kidney Transplant Survival Outcomes: A Systematic Review of Prediction Models.

Authors:  Stephanie Riley; Qing Zhang; Wai-Yee Tse; Andrew Connor; Yinghui Wei
Journal:  Transpl Int       Date:  2022-06-23       Impact factor: 3.842

  3 in total

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