Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP
Matsushita, Kunihiro; Kaptoge, Stephen; Hageman, Steven H.J.; Sang, Yingying; Ballew, Shoshana H.; Grams, Morgan E.; Surapaneni, Aditya; Sun, Luanluan; Arnlov, Johan; Bozic, Milica; Brenner, Hermann; Brunskill, Nigel J.; Chang, Alex R.; Chinnadurai, Rajkumar; Cirillo, Massimo; Correa, Adolfo; Ebert, Natalie; Eckardt, Kai Uwe; Gansevoort, Ron T.; Gutierrez, Orlando; Hadaegh, Farzad; He, Jiang; Hwang, Shih Jen; Jafar, Tazeen H.; Jassal, Simerjot K.; Kayama, Takamasa; Kovesdy, Csaba P.; Landman, Gijs W.; Levey, Andrew S.; Lloyd-Jones, Donald M.; Major, Rupert W.; Miura, Katsuyuki; Muntner, Paul; Nadkarni, Girish N.; Nowak, Christoph; Ohkubo, Takayoshi; Pena, Michelle J.; Polkinghorne, Kevan R.; Sairenchi, Toshimi; Schaeffner, Elke; Schneider, Markus P.; Shalev, Varda; Shlipak, Michael G.; Solbu, Marit D.; Stempniewicz, Nikita; Tollitt, James; Valdivielso, José M.; Van Der Leeuw, Joep; Dorresteijn, Jannick A.N.; Visseren, Frank L.J.
(2023) European Journal of Preventive Cardiology, volume 30, issue 1, pp. 8 - 16
(Article)
Abstract
Aims: The 2021 European Society of Cardiology (ESC) guideline on cardiovascular disease (CVD) prevention categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, systemic
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coronary risk estimation 2 (SCORE2) and systemic coronary risk estimation 2 in older persons (SCORE2-OP), to predict CVD risk. We developed and validated an 'Add-on' to incorporate CKD measures into these algorithms, using a validated approach. Methods: In 3,054 840 participants from 34 datasets, we developed three Add-ons [eGFR only, eGFR + urinary albumin-to-creatinine ratio (ACR) (the primary Add-on), and eGFR + dipstick proteinuria] for SCORE2 and SCORE2-OP. We validated C-statistics and net reclassification improvement (NRI), accounting for competing risk of non-CVD death, in 5,997 719 participants from 34 different datasets. Results: In the target population of SCORE2 and SCORE2-OP without diabetes, the CKD Add-on (eGFR only) and CKD Add-on (eGFR + ACR) improved C-statistic by 0.006 (95%CI 0.004-0.008) and 0.016 (0.010-0.023), respectively, for SCORE2 and 0.012 (0.009-0.015) and 0.024 (0.014-0.035), respectively, for SCORE2-OP. Similar results were seen when we included individuals with diabetes and tested the CKD Add-on (eGFR + dipstick). In 57 485 European participants with CKD, SCORE2 or SCORE2-OP with a CKD Add-on showed a significant NRI [e.g. 0.100 (0.062-0.138) for SCORE2] compared to the qualitative approach in the ESC guideline. Conclusion: Our Add-ons with CKD measures improved CVD risk prediction beyond SCORE2 and SCORE2-OP. This approach will help clinicians and patients with CKD refine risk prediction and further personalize preventive therapies for CVD.
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Keywords: Aged, Aged, 80 and over, Albuminuria/diagnosis, Cardiovascular Diseases/diagnosis, Creatinine, Glomerular Filtration Rate, Heart Disease Risk Factors, Humans, Renal Insufficiency, Chronic/diagnosis, Risk Factors, Cardiovascular disease, Risk prediction, Chronic kidney disease, Meta-analysis, Epidemiology, Cardiology and Cardiovascular Medicine, Journal Article
ISSN: 2047-4873
Publisher: Oxford University Press
Note: Publisher Copyright: © 2022 The Author(s).
(Peer reviewed)