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Predicting potential survival benefit of renal transplantation in patients with chronic kidney disease.

Abstract

BACKGROUND

To facilitate decision-making about treatment options for patients with end-stage renal disease considering kidney transplantation, we sought to develop an index for clinical prediction of risk for death.

METHODS

We derived and validated a multivariable survival model predicting time to death in 169,393 patients with end-stage renal disease who were eligible for transplantation. We modified the model into a simple point-system index.

RESULTS

Deaths occurred in 23.5% of the cohort. Twelve variables independently predicted death: age, race, cause of kidney failure, body mass index, comorbid disease, smoking, employment status, serum albumin level, year of first renal replacement therapy, kidney transplantation, time to transplant wait-listing and time on the wait list. The index separated patients into 26 groups having significantly unique five-year survival, ranging from 97.8% in the lowest-risk group to 24.7% in the highest-risk group. The index score was discriminative, with a concordance probability of 0.746 (95% CI 0.741-0.751). Observed survival in the derivation and validation cohorts was similar for each level of index score in 93.9% of patients.

INTERPRETATION

Our prognostic index uses commonly available information to predict mortality accurately in patients with end-stage renal disease. This index could provide valuable quantitative data on survival for clinicians and patients to use when deciding whether to pursue transplantation or remain on dialysis.

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  • Authors+Show Affiliations

    ,

    Faculty of Medicine, University of Ottawa, Ont. carlv@ohri.ca

    ,

    Source

    MeSH

    Age Factors
    Body Mass Index
    Comorbidity
    Continental Population Groups
    Data Interpretation, Statistical
    Employment
    Female
    Humans
    Kidney Failure, Chronic
    Kidney Transplantation
    Male
    Middle Aged
    Models, Biological
    Monte Carlo Method
    Prognosis
    Regression Analysis
    Renal Replacement Therapy
    Risk Assessment
    Serum Albumin
    Smoking
    Survival Analysis
    Time Factors
    United States
    Waiting Lists

    Pub Type(s)

    Journal Article

    Language

    eng

    PubMed ID

    20351122

    Citation

    van Walraven, Carl, et al. "Predicting Potential Survival Benefit of Renal Transplantation in Patients With Chronic Kidney Disease." CMAJ : Canadian Medical Association Journal = Journal De l'Association Medicale Canadienne, vol. 182, no. 7, 2010, pp. 666-72.
    van Walraven C, Austin PC, Knoll G. Predicting potential survival benefit of renal transplantation in patients with chronic kidney disease. CMAJ. 2010;182(7):666-72.
    van Walraven, C., Austin, P. C., & Knoll, G. (2010). Predicting potential survival benefit of renal transplantation in patients with chronic kidney disease. CMAJ : Canadian Medical Association Journal = Journal De l'Association Medicale Canadienne, 182(7), pp. 666-72. doi:10.1503/cmaj.091661.
    van Walraven C, Austin PC, Knoll G. Predicting Potential Survival Benefit of Renal Transplantation in Patients With Chronic Kidney Disease. CMAJ. 2010 Apr 20;182(7):666-72. PubMed PMID: 20351122.
    * Article titles in AMA citation format should be in sentence-case
    TY - JOUR T1 - Predicting potential survival benefit of renal transplantation in patients with chronic kidney disease. AU - van Walraven,Carl, AU - Austin,Peter C, AU - Knoll,Greg, Y1 - 2010/03/29/ PY - 2010/3/31/entrez PY - 2010/3/31/pubmed PY - 2010/9/18/medline SP - 666 EP - 72 JF - CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne JO - CMAJ VL - 182 IS - 7 N2 - BACKGROUND: To facilitate decision-making about treatment options for patients with end-stage renal disease considering kidney transplantation, we sought to develop an index for clinical prediction of risk for death. METHODS: We derived and validated a multivariable survival model predicting time to death in 169,393 patients with end-stage renal disease who were eligible for transplantation. We modified the model into a simple point-system index. RESULTS: Deaths occurred in 23.5% of the cohort. Twelve variables independently predicted death: age, race, cause of kidney failure, body mass index, comorbid disease, smoking, employment status, serum albumin level, year of first renal replacement therapy, kidney transplantation, time to transplant wait-listing and time on the wait list. The index separated patients into 26 groups having significantly unique five-year survival, ranging from 97.8% in the lowest-risk group to 24.7% in the highest-risk group. The index score was discriminative, with a concordance probability of 0.746 (95% CI 0.741-0.751). Observed survival in the derivation and validation cohorts was similar for each level of index score in 93.9% of patients. INTERPRETATION: Our prognostic index uses commonly available information to predict mortality accurately in patients with end-stage renal disease. This index could provide valuable quantitative data on survival for clinicians and patients to use when deciding whether to pursue transplantation or remain on dialysis. SN - 1488-2329 UR - https://www.unboundmedicine.com/medline/citation/20351122/full_citation L2 - http://www.cmaj.ca/cgi/pmidlookup?view=long&pmid=20351122 DB - PRIME DP - Unbound Medicine ER -