Literature DB >> 21349620

Development and evaluation of a composite risk score to predict kidney transplant failure.

Jason Moore1, Xiang He, Shazia Shabir, Rajesh Hanvesakul, David Benavente, Paul Cockwell, Mark A Little, Simon Ball, Nicholas Inston, Atholl Johnston, Richard Borrows.   

Abstract

BACKGROUND: Although risk factors for kidney transplant failure are well described, prognostic risk scores to estimate risk in prevalent transplant recipients are limited. STUDY
DESIGN: Development and validation of risk-prediction instruments. SETTING & PARTICIPANTS: The development data set included 2,763 prevalent patients more than 12 months posttransplant enrolled into the LOTESS (Long Term Efficacy and Safety Surveillance) Study. The validation data set included 731 patients who underwent transplant at a single UK center. PREDICTOR: Estimated glomerular filtration rate (eGFR) and other risk factors were evaluated using Cox regression. OUTCOME: Scores for death-censored and overall transplant failure were based on the summed hazard ratios for baseline predictor variables. Predictive performance was assessed using calibration (Hosmer-Lemeshow statistic), discrimination (C statistic), and clinical reclassification (net reclassification improvement) compared with eGFR alone.
RESULTS: In the development data set, 196 patients died and another 225 experienced transplant failure. eGFR, recipient age, race, serum urea and albumin levels, declining eGFR, and prior acute rejection predicted death-censored transplant failure. eGFR, recipient age, sex, serum urea and albumin levels, and declining eGFR predicted overall transplant failure. In the validation data set, 44 patients died and another 101 experienced transplant failure. The weighted scores comprising these variables showed adequate discrimination and calibration for death-censored (C statistic, 0.83; 95% CI, 0.75-0.91; Hosmer-Lemeshow χ(2)P = 0.8) and overall (C statistic, 0.70; 95% CI, 0.64-0.77; Hosmer-Lemeshow χ(2)P = 0.5) transplant failure. However, the scores failed to reclassify risk compared with eGFR alone (net reclassification improvements of 7.6% [95% CI, -0.2 to 13.4; P = 0.09] and 4.3% [95% CI, -2.7 to 11.8; P = 0.3] for death-censored and overall transplant failure, respectively). LIMITATIONS: Retrospective analysis of predominantly cyclosporine-treated patients; limited study size and categorization of variables may limit power to detect effect.
CONCLUSIONS: Although the scores performed well regarding discrimination and calibration, clinically relevant risk reclassification over eGFR alone was not evident, emphasizing the stringent requirements for such scores. Further studies are required to develop and refine this process.
Copyright © 2011 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

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Mesh:

Year:  2011        PMID: 21349620     DOI: 10.1053/j.ajkd.2010.12.017

Source DB:  PubMed          Journal:  Am J Kidney Dis        ISSN: 0272-6386            Impact factor:   8.860


  15 in total

1.  Predictive Score for Posttransplantation Outcomes.

Authors:  Miklos Z Molnar; Danh V Nguyen; Yanjun Chen; Vanessa Ravel; Elani Streja; Mahesh Krishnan; Csaba P Kovesdy; Rajnish Mehrotra; Kamyar Kalantar-Zadeh
Journal:  Transplantation       Date:  2017-06       Impact factor: 4.939

2.  A new clinical prediction tool for 5-year kidney transplant outcome.

Authors:  Colin R Lenihan; Joseph B Lockridge; Jane C Tan
Journal:  Am J Kidney Dis       Date:  2014-04       Impact factor: 8.860

3.  Access to kidney transplantation among pediatric candidates with prior solid organ transplants in the United States.

Authors:  Syed Ali Husain; Kristen L King; Nina L Owen-Simon; Hilda E Fernandez; Lloyd E Ratner; Sumit Mohan
Journal:  Pediatr Transplant       Date:  2022-05-26

4.  Surrogate Endpoints for Late Kidney Transplantation Failure.

Authors:  Maarten Naesens; Klemens Budde; Luuk Hilbrands; Rainer Oberbauer; Maria Irene Bellini; Denis Glotz; Josep Grinyó; Uwe Heemann; Ina Jochmans; Liset Pengel; Marlies Reinders; Stefan Schneeberger; Alexandre Loupy
Journal:  Transpl Int       Date:  2022-05-20       Impact factor: 3.842

5.  Derivation of a Predictive Model for Graft Loss Following Acute Kidney Injury in Kidney Transplant Recipients.

Authors:  Amber O Molnar; Carl van Walraven; Dean Fergusson; Amit X Garg; Greg Knoll
Journal:  Can J Kidney Health Dis       Date:  2017-01-30

6.  Preoperative hypoalbuminemia was associated with acute kidney injury in high-risk patients following non-cardiac surgery: a retrospective cohort study.

Authors:  Nan Li; Hong Qiao; Jing-Fei Guo; Hong-Yun Yang; Xue-Ying Li; Shuang-Ling Li; Dong-Xin Wang; Li Yang
Journal:  BMC Anesthesiol       Date:  2019-09-02       Impact factor: 2.217

7.  Development and validation of a risk index to predict kidney graft survival: the kidney transplant risk index.

Authors:  Sameera Senanayake; Sanjeewa Kularatna; Helen Healy; Nicholas Graves; Keshwar Baboolal; Matthew P Sypek; Adrian Barnett
Journal:  BMC Med Res Methodol       Date:  2021-06-21       Impact factor: 4.615

Review 8.  Causal relationship between hypoalbuminemia and acute kidney injury.

Authors:  Christian J Wiedermann; Wolfgang Wiedermann; Michael Joannidis
Journal:  World J Nephrol       Date:  2017-07-06

9.  An adjustable predictive score of graft survival in kidney transplant patients and the levels of risk linked to de novo donor-specific anti-HLA antibodies.

Authors:  Aurélie Prémaud; Matthieu Filloux; Philippe Gatault; Antoine Thierry; Matthias Büchler; Eliza Munteanu; Pierre Marquet; Marie Essig; Annick Rousseau
Journal:  PLoS One       Date:  2017-07-03       Impact factor: 3.240

10.  Identification of a urine metabolite constellation characteristic for kidney allograft rejection.

Authors:  Miriam Banas; Sindy Neumann; Johannes Eiglsperger; Eric Schiffer; Franz Josef Putz; Simone Reichelt-Wurm; Bernhard Karl Krämer; Philipp Pagel; Bernhard Banas
Journal:  Metabolomics       Date:  2018-08-30       Impact factor: 4.290

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