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Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate.

TitleComparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate.
Publication TypeJournal Article
Year of Publication2012
AuthorsMatsushita, K, Mahmoodi, BK, Woodward, M, Emberson, JR, Jafar, TH, Jee, SHa, Polkinghorne, KR, Shankar, A, Smith, DH, Tonelli, M, Warnock, DG, Wen, C-P, Coresh, J, Gansevoort, RT, Hemmelgarn, BR, Levey, AS
Corporate/Institutional AuthorsChronic Kidney Disease Prognosis Consortium,
JournalJAMA
Volume307
Issue18
Pagination1941-51
Date Published2012 May 09
ISSN1538-3598
KeywordsAfrican Continental Ancestry Group, Aged, Algorithms, Asian Continental Ancestry Group, Cardiovascular Diseases, Cohort Studies, Decision Support Techniques, European Continental Ancestry Group, Female, Glomerular Filtration Rate, Humans, Kidney Failure, Chronic, Male, Middle Aged, Models, Theoretical, Risk Assessment, Sex Factors
Abstract<p><b>CONTEXT: </b>The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking.</p><p><b>OBJECTIVE: </b>To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics.</p><p><b>DESIGN, SETTING, AND PARTICIPANTS: </b>A meta-analysis of data from 1.1 million adults (aged ≥ 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012.</p><p><b>MAIN OUTCOME MEASURES: </b>All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years).</p><p><b>RESULTS: </b>Estimated GFR was classified into 6 categories (≥90, 60-89, 45-59, 30-44, 15-29, and <15 mL/min/1.73 m(2)) by both equations. Compared with the MDRD Study equation, 24.4% and 0.6% of participants from general population cohorts were reclassified to a higher and lower estimated GFR category, respectively, by the CKD-EPI equation, and the prevalence of CKD stages 3 to 5 (estimated GFR <60 mL/min/1.73 m(2)) was reduced from 8.7% to 6.3%. In estimated GFR of 45 to 59 mL/min/1.73 m(2) by the MDRD Study equation, 34.7% of participants were reclassified to estimated GFR of 60 to 89 mL/min/1.73 m(2) by the CKD-EPI equation and had lower incidence rates (per 1000 person-years) for the outcomes of interest (9.9 vs 34.5 for all-cause mortality, 2.7 vs 13.0 for cardiovascular mortality, and 0.5 vs 0.8 for ESRD) compared with those not reclassified. The corresponding adjusted hazard ratios were 0.80 (95% CI, 0.74-0.86) for all-cause mortality, 0.73 (95% CI, 0.65-0.82) for cardiovascular mortality, and 0.49 (95% CI, 0.27-0.88) for ESRD. Similar findings were observed in other estimated GFR categories by the MDRD Study equation. Net reclassification improvement based on estimated GFR categories was significantly positive for all outcomes (range, 0.06-0.13; all P < .001). Net reclassification improvement was similarly positive in most subgroups defined by age (<65 years and ≥65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts.</p><p><b>CONCLUSION: </b>The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.</p>
DOI10.1001/jama.2012.3954
Alternate JournalJAMA
PubMed ID22570462
PubMed Central IDPMC3837430
Grant ListHHSN268201100012C / HL / NHLBI NIH HHS / United States
K23 DK067303 / DK / NIDDK NIH HHS / United States
N01 HC085086 / HC / NHLBI NIH HHS / United States
U01 DK035073 / DK / NIDDK NIH HHS / United States
HHSN268201100010C / HL / NHLBI NIH HHS / United States
R01 AG015928 / AG / NIA NIH HHS / United States
HHSN268201100008C / HL / NHLBI NIH HHS / United States
N01 HC075150 / HC / NHLBI NIH HHS / United States
K23 DK002904 / DK / NIDDK NIH HHS / United States
U10 EY006594 / EY / NEI NIH HHS / United States
HHSN268201100007C / HL / NHLBI NIH HHS / United States
N01 HC015103 / HC / NHLBI NIH HHS / United States
N01 HC025195 / HC / NHLBI NIH HHS / United States
HHSN268201100011C / HL / NHLBI NIH HHS / United States
N01HC55222 / HL / NHLBI NIH HHS / United States
R01 AG007181 / AG / NIA NIH HHS / United States
R01 DK073217 / DK / NIDDK NIH HHS / United States
HHSN268201100006C / HL / NHLBI NIH HHS / United States
R01 DK031801 / DK / NIDDK NIH HHS / United States
U01 NS041588 / NS / NINDS NIH HHS / United States
N01 HC095169 / HC / NHLBI NIH HHS / United States
R01 HL080295 / HL / NHLBI NIH HHS / United States
R01 AG020098 / AG / NIA NIH HHS / United States
N01HC75150 / HL / NHLBI NIH HHS / United States
HHSN268201100009C / HL / NHLBI NIH HHS / United States
HHSN268201100005C / HL / NHLBI NIH HHS / United States
N01 HC085079 / HC / NHLBI NIH HHS / United States
R01 HL068140 / HL / NHLBI NIH HHS / United States
R01 AG023629 / AG / NIA NIH HHS / United States
R01 AG028507 / AG / NIA NIH HHS / United States
R01 AG027058 / AG / NIA NIH HHS / United States
N01 HC045133 / HC / NHLBI NIH HHS / United States
N01 HC035129 / HC / NHLBI NIH HHS / United States
CZH/4/656 / / Chief Scientist Office / United Kingdom
R01 HL043232-03 / HL / NHLBI NIH HHS / United States
N01 HC095159 / HC / NHLBI NIH HHS / United States