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

TitleMultinational Assessment of Accuracy of Equations for Predicting Risk of Kidney Failure: A Meta-analysis.
Publication TypeJournal Article
Year of Publication2016
AuthorsTangri, N, Grams, ME, Levey, AS, Coresh, J, Appel, LJ, Astor, BC, Chodick, G, Collins, AJ, Djurdjev, O, C Elley, R, Evans, M, Garg, AX, Hallan, SI, Inker, LA, Ito, S, Jee, SHa, Kovesdy, CP, Kronenberg, F, Heerspink, HJLambers, Marks, A, Nadkarni, GN, Navaneethan, SD, Nelson, RG, Titze, S, Sarnak, MJ, Stengel, B, Woodward, M, Iseki, K
Corporate AuthorsCKD Prognosis Consortium
JournalJAMA
Volume315
Issue2
Pagination164-74
Date Published2016 Jan 12
ISSN1538-3598
KeywordsCohort Studies, Disease Progression, Humans, Prognosis, Proportional Hazards Models, Renal Insufficiency, Renal Insufficiency, Chronic, Risk Assessment
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 (Pā€‰=ā€‰.04 and Pā€‰=ā€‰.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.

DOI10.1001/jama.2015.18202
Alternate JournalJAMA
PubMed ID26757465
PubMed Central IDPMC4752167
Grant ListU01 DK061028 / DK / NIDDK NIH HHS / United States
HHSN268201100012C / HL / NHLBI NIH HHS / United States
R01 CA165001 / CA / NCI NIH HHS / United States
K23 DK067303 / DK / NIDDK NIH HHS / United States
U01 DK035073 / DK / NIDDK NIH HHS / United States
HHSN268201100010C / HL / NHLBI NIH HHS / United States
HHSN268201100008C / HL / NHLBI NIH HHS / United States
U01 DK060984 / DK / NIDDK NIH HHS / United States
UL1 TR001079 / TR / NCATS NIH HHS / United States
K23 DK002904 / DK / NIDDK NIH HHS / United States
HHSN268201100007C / HL / NHLBI NIH HHS / United States
U01 DK060980 / DK / NIDDK NIH HHS / United States
U01 DK060963 / DK / NIDDK NIH HHS / United States
HHSN268201100011C / HL / NHLBI NIH HHS / United States
K08DK092287 / DK / NIDDK NIH HHS / United States
U01 DK061022 / DK / NIDDK NIH HHS / United States
HHSN268201100006C / HL / NHLBI NIH HHS / United States
UL1 TR000003 / TR / NCATS NIH HHS / United States
U01 NS041588 / NS / NINDS NIH HHS / United States
R01DK100446-01 / DK / NIDDK NIH HHS / United States
UL1 TR000424 / TR / NCATS NIH HHS / United States
U01 DK060902 / DK / NIDDK NIH HHS / United States
U01 DK060990 / DK / NIDDK NIH HHS / United States
HHSN268201100009C / HL / NHLBI NIH HHS / United States
HHSN268201100005C / HL / NHLBI NIH HHS / United States
K08 DK092287 / DK / NIDDK NIH HHS / United States
R01 DK100446 / DK / NIDDK NIH HHS / United States