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JAMA. 2016 Jan 12;315(2):164-74. doi: 10.1001/jama.2015.18202.

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

Author information

1
Department of Medicine, Seven Oaks General Hospital, University of Manitoba, Winnipeg, Canada2Department of Community Health Sciences, Seven Oaks General Hospital, University of Manitoba, Winnipeg, Canada.
2
Johns Hopkins Medical Institutions, Baltimore, Maryland.
3
Division of Nephrology at Tufts Medical Center, Boston, Massachusetts.
4
Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
5
Johns Hopkins Medical Institutions, Baltimore, Maryland5Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
6
Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison7Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison.
7
Medical Division, Maccabi Healthcare Services, and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
8
Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, Minnesota10Department of Medicine, University of Minnesota, Minneapolis.
9
Department of Measurement & Reporting, Provincial Health Service Authority, Vancouver, British Columbia, Canada.
10
Department of General Practice and Primary Health Care, School of Population Health, University of Auckland, Auckland, New Zealand.
11
Division of Renal Medicine, CLINTEC, Karolinska Institutet, Stockholm, Sweden.
12
Departments of Medicine and Epidemiology and Biostatistics, Western University, and Institute for Clinical Evaluative Sciences, Ontario, Canada.
13
Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science Technology, Trondheim16Division of Nephrology, Department of Medicine, St Olav University Hospital, Trondheim, Norway.
14
Division of Nephrology, Endocrinology and Vascular Medicine, Department of Medicine, Tohoku University School of Medicine, Sendai, Japan.
15
Department of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Korea.
16
Memphis Veterans Affairs Medical Center, Memphis, Tennessee20University of Tennessee Health Science Center, Memphis, Tennessee.
17
Department of Medical Genetics, Molecular and Clinical Pharmacology, Division of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
18
Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, the Netherlands.
19
Division of Applied Health Sciences, University of Aberdeen, and NHS Grampian, Foresterhill, Aberdeen, Scotland.
20
Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.
21
Division of Nephrology and Hypertension, Cleveland Clinic, Cleveland, Ohio.
22
National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona.
23
Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany.
24
CESP, INSERM, Villejuif, France29Université Paris-Saclay, Université Paris-Sud, UVSQ, Villejuif, France.
25
Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland30The George Institute for Global Health, Nuffield Department of Population Health, University of Oxford, Oxford, England31The George Institute for Global Health, University of Sydney, Sy.
26
Dialysis Unit, University Hospital of the Ryukyus, Nishihara, Okinawa, Japan.

Erratum in

Abstract

IMPORTANCE:

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.

OBJECTIVE:

To evaluate the accuracy of the risk equations across different geographic regions and patient populations through individual participant data meta-analysis.

DATA SOURCES:

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.

STUDY SELECTION:

Cohorts participating in the CKD Prognosis Consortium with data on end-stage renal disease.

DATA EXTRACTION AND SYNTHESIS:

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.

MAIN OUTCOMES AND MEASURES:

Kidney failure (treatment by dialysis or kidney transplant).

RESULTS:

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).

CONCLUSIONS AND RELEVANCE:

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.

PMID:
26757465
PMCID:
PMC4752167
DOI:
10.1001/jama.2015.18202
[Indexed for MEDLINE]
Free PMC Article

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