TY - JOUR
T1 - Risk Prediction Models for Atherosclerotic Cardiovascular Disease in Patients with Chronic Kidney Disease
T2 - The CRIC Study
AU - Bundy, Joshua D.
AU - Rahman, Mahboob
AU - Matsushita, Kunihiro
AU - Jaeger, Byron C.
AU - Cohen, Jordana B.
AU - Chen, Jing
AU - Deo, Rajat
AU - Dobre, Mirela A.
AU - Feldman, Harold I.
AU - Flack, John
AU - Kallem, Radhakrishna R.
AU - Lash, James P.
AU - Seliger, Stephen
AU - Shafi, Tariq
AU - Weiner, Shoshana J.
AU - Wolf, Myles
AU - Yang, Wei
AU - Allen, Norrina B.
AU - Bansal, Nisha
AU - He, Jiang
N1 - Funding Information:
Funding for the CRIC study was obtained under a cooperative agreement from the National Institute of Diabetes and Digestive and Kidney Diseases (U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028, U01DK060980, U01DK060963, U01DK060902, and U24DK060990). In addition, this work was supported in part by the Perelman School of Medicine at the University of Pennsylvania Clinical and Translational Science Award, National Center for Advancing Translational Sciences (UL1TR000003), Johns Hopkins University (UL1TR000424), University of Maryland General Clinical Research Center (M01 RR-16500), Clinical and Translational Science Collaborative of Cleveland, the National Center for Advancing Translational Sciences component of the NIH roadmap for Medical Research (UL1TR000439), Michigan Institute for Clinical and Health Research (UL1TR000433), University of Illinois at Chicago Clinical and Translational Science Award (UL1RR029879), Tulane COBRE for Clinical and Translational Research in Cardiometabolic Diseases (P20 GM109036), Kaiser Permanente, National Center for Research Resources (UCSF-CTSI UL1 RR-024131), and Department of Internal Medicine, University of New Mexico School of Medicine Albuquerque, New Mexico (R01DK119199). J.D. Bundy was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development career development grant (K12HD043451). The ARIC study is supported by the National Heart, Lung, and Blood Institute (HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, and HHSN268201700005I). MESA is supported by the National Heart, Lung, and Blood Institute (75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, and N01-HC-95169), and by the National Center for Advancing Translational Sciences (UL1TR000040, UL1TR001079, and UL1TR001420).
Funding Information:
N.B. Allen reports research funding with AHA and National Institutes of Health (NIH)/National Heart, Lung, and Blood Institute (NHLBI). N. Bansal reports associate editor for Kidney360. J.B. Cohen reports honoraria from UpToDate; and research funding with AHA and NIH/NHLBI and NIH/ National Center for Advancing Translational Sciences. R. Deo reports consultancy agreements with Biotronik, Boehringer Ingelheim, Janssen Pharmaceuticals, and Pfizer; research funding with iRhythm Technologies; editorial boards for Circulation and Heart Rhythm O2; and steering committee for Kidney Disease: Improving Global Outcomes. M.A. Dobre reports honoraria from Relypsa Inc. and Tricida; and scientific advisor or membership with Tricida (Metabolic Acidosis Working Group) and Relypsa (Resistant Hypertension Working Group). H.I. Feldman reports consultancy with InMed, Inc., Kyowa Hakko Kirin, National Kidney Foundation, and University of California, Los Angeles; steering committee for the CRIC study; member of advisory board of the National Kidney Foundation; editor-in-chief of American Journal of Kidney Disease. J.P. Lash reports scientific advisor or membership with Kidney360. K. Matsushita reports consultancy agreements with Akebia, Kyowa Hakko Kirin, and Mitsubishi Tanabe; research funding from Kyowa Hakko Kirin; honoraria from Fukuda Denshi; and scientific advisor or membership with American Journal of Kidney Disease, Circulation Reports, and Kidney International.
Publisher Copyright:
© 2022 by the American Society of Nephrology.
PY - 2022/3
Y1 - 2022/3
N2 - Background Individuals with CKD may be at high risk for atherosclerotic cardiovascular disease (ASCVD). However, there are no ASCVD risk prediction models developed in CKD populations to inform clinical care and prevention. Methods We developed and validated 10-year ASCVD risk prediction models in patients with CKD that included participants without self-reported cardiovascular disease from the Chronic Renal Insufficiency Cohort (CRIC) study. ASCVD was defined as the first occurrence of adjudicated fatal and nonfatal stroke or myocardial infarction. Our models used clinically available variables and novel biomarkers. Model performance was evaluated based on discrimination, calibration, and net reclassification improvement. Results Of 2604 participants (mean age 55.8 years; 52.0% male) included in the analyses, 252 had incident ASCVD within 10 years of baseline. Compared with the American College of Cardiology/American Heart Association pooled cohort equations (area under the receiver operating characteristic curve [AUC]50.730), a model with coefficients estimated within the CRIC sample had higher discrimination (P50.03), achieving an AUC of 0.736 (95% confidence interval [CI], 0.649 to 0.826). The CRIC model developed using clinically available variables had an AUC of 0.760 (95% CI, 0.678 to 0.851). The CRIC biomarker-enriched model had an AUC of 0.771 (95% CI, 0.674 to 0.853), which was significantly higher than the clinical model (P50.001). Both the clinical and biomarker-enriched models were well-calibrated and improved reclassification of nonevents compared with the pooled cohort equations (6.6%; 95% CI, 3.7% to 9.6% and 10.0%; 95% CI, 6.8% to 13.3%, respectively). Conclusions The 10-year ASCVD risk prediction models developed in patients with CKD, including novel kidney and cardiac biomarkers, performed better than equations developed for the general population using only traditional risk factors.
AB - Background Individuals with CKD may be at high risk for atherosclerotic cardiovascular disease (ASCVD). However, there are no ASCVD risk prediction models developed in CKD populations to inform clinical care and prevention. Methods We developed and validated 10-year ASCVD risk prediction models in patients with CKD that included participants without self-reported cardiovascular disease from the Chronic Renal Insufficiency Cohort (CRIC) study. ASCVD was defined as the first occurrence of adjudicated fatal and nonfatal stroke or myocardial infarction. Our models used clinically available variables and novel biomarkers. Model performance was evaluated based on discrimination, calibration, and net reclassification improvement. Results Of 2604 participants (mean age 55.8 years; 52.0% male) included in the analyses, 252 had incident ASCVD within 10 years of baseline. Compared with the American College of Cardiology/American Heart Association pooled cohort equations (area under the receiver operating characteristic curve [AUC]50.730), a model with coefficients estimated within the CRIC sample had higher discrimination (P50.03), achieving an AUC of 0.736 (95% confidence interval [CI], 0.649 to 0.826). The CRIC model developed using clinically available variables had an AUC of 0.760 (95% CI, 0.678 to 0.851). The CRIC biomarker-enriched model had an AUC of 0.771 (95% CI, 0.674 to 0.853), which was significantly higher than the clinical model (P50.001). Both the clinical and biomarker-enriched models were well-calibrated and improved reclassification of nonevents compared with the pooled cohort equations (6.6%; 95% CI, 3.7% to 9.6% and 10.0%; 95% CI, 6.8% to 13.3%, respectively). Conclusions The 10-year ASCVD risk prediction models developed in patients with CKD, including novel kidney and cardiac biomarkers, performed better than equations developed for the general population using only traditional risk factors.
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UR - http://www.scopus.com/inward/citedby.url?scp=85125254341&partnerID=8YFLogxK
U2 - 10.1681/ASN.2021060747
DO - 10.1681/ASN.2021060747
M3 - Article
C2 - 35145041
AN - SCOPUS:85125254341
VL - 33
SP - 601
EP - 611
JO - Journal of the American Society of Nephrology
JF - Journal of the American Society of Nephrology
SN - 1046-6673
IS - 3
ER -