Multinational Assessment of Accuracy of Equations for Predicting Risk of Kidney Failure: A Meta-analysis

Tangri N, Grams ME, Levey AS, Coresh J, Appel LJ, Astor BC, Chodick G, Collins AJ, Djurdjev O, Elley R, Evans M, Garg AX, Hallan SI, Nicer LA, Ito S, Jee SH, Kovesdy CP, Kronenberg F, Heerspink HJL, Marks A, Nadkarni GN, Navaneethan SD, Nelson RG, Titze S, Sarnak MJ, Stengel B, Woodward M, Iseki K (2016)

Publication Type: Journal article

Publication year: 2016

Journal

Book Volume: 315

Pages Range: 164-74

Journal Issue: 2

DOI: 10.1001/jama.2015.18202

Abstract

Identifying patients at risk of chronic kidney disease (CKD) progression may facilitate more optimal nephrology care. Kidney failure risk equations, including such factors as age, sex, estimated glomerular filtration rate, and calcium and phosphate concentrations, were previously developed and validated in 2 Canadian cohorts. Validation in other regions and in CKD populations not under the care of a nephrologist is needed.To evaluate the accuracy of the risk equations across different geographic regions and patient populations through individual participant data meta-analysis.Thirty-one cohorts, including 721,357 participants with CKD stages 3 to 5 in more than 30 countries spanning 4 continents, were studied. These cohorts collected data from 1982 through 2014.Cohorts participating in the CKD Prognosis Consortium with data on end-stage renal disease.Data were obtained and statistical analyses were performed between July 2012 and June 2015. Using the risk factors from the original risk equations, cohort-specific hazard ratios were estimated and combined using random-effects meta-analysis to form new pooled kidney failure risk equations. Original and pooled kidney failure risk equation performance was compared, and the need for regional calibration factors was assessed.Kidney failure (treatment by dialysis or kidney transplant).During a median follow-up of 4 years of 721,357 participants with CKD, 23,829 cases kidney failure were observed. The original risk equations achieved excellent discrimination (ability to differentiate those who developed kidney failure from those who did not) across all cohorts (overall C statistic, 0.90; 95% CI, 0.89-0.92 at 2 years; C statistic at 5 years, 0.88; 95% CI, 0.86-0.90); discrimination in subgroups by age, race, and diabetes status was similar. There was no improvement with the pooled equations. Calibration (the difference between observed and predicted risk) was adequate in North American cohorts, but the original risk equations overestimated risk in some non-North American cohorts. Addition of a calibration factor that lowered the baseline risk by 32.9% at 2 years and 16.5% at 5 years improved the calibration in 12 of 15 and 10 of 13 non-North American cohorts at 2 and 5 years, respectively (P = .04 and P = .02).Kidney failure risk equations developed in a Canadian population showed high discrimination and adequate calibration when validated in 31 multinational cohorts. However, in some regions the addition of a calibration factor may be necessary.

Involved external institutions

University of Manitoba Canada (CA) Johns Hopkins Hospital United States (USA) (US) Tufts University United States (USA) (US) Johns Hopkins University (JHU) United States (USA) (US) University of Wisconsin - Madison United States (USA) (US) Tel Aviv University Israel (IL) Minneapolis Medical Research Foundation United States (USA) (US) Provincial Health Services Authority Canada (CA) University of Auckland New Zealand (NZ) Karolinska Institute Sweden (SE) Western University Canada (CA) NTNU Trondheim - Norwegian University of Science and Technology Norway (NO) Tohoku University Japan (JP) Yonsei University Korea, Republic of (KR) Memphis VA Medical Center United States (USA) (US) Medizinische Universität Innsbruck Austria (AT) University of Groningen / Rijksuniversiteit Groningen Netherlands (NL) University of Aberdeen United Kingdom (GB) Icahn School of Medicine at Mount Sinai United States (USA) (US) Cleveland Clinic United States (USA) (US) National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK / NIDDKD) United States (USA) (US) National Institute for Health and Medical Research / Institut national de la santé et de la recherche médicale (INSERM) France (FR) University of the Ryukyus / 琉球大学 Japan (JP)

How to cite

APA:

Tangri, N., Grams, M.E., Levey, A.S., Coresh, J., Appel, L.J., Astor, B.C.,... Iseki, K. (2016). Multinational Assessment of Accuracy of Equations for Predicting Risk of Kidney Failure: A Meta-analysis. Journal of the American Medical Association, 315(2), 164-74. https://doi.org/10.1001/jama.2015.18202

MLA:

Tangri, Navdeep, et al. "Multinational Assessment of Accuracy of Equations for Predicting Risk of Kidney Failure: A Meta-analysis." Journal of the American Medical Association 315.2 (2016): 164-74.

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