Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP

Matsushita K, Kaptoge S, Hageman SHJ, Sang Y, Ballew SH, Grams ME, Surapaneni A, Sun L, Arnlov J, Bozic M, Brenner H, Brunskill NJ, Chang AR, Chinnadurai R, Cirillo M, Correa A, Ebert N, Eckardt KU, Gansevoort RT, Gutierrez O, Hadaegh F, He J, Hwang SJ, Jafar TH, Jassal SK, Kayama T, Kovesdy CP, Landman GW, Levey AS, Lloyd-Jones DM, Major RW, Miura K, Muntner P, Nadkarni GN, Nowak C, Ohkubo T, Pena MJ, Polkinghorne KR, Sairenchi T, Schaeffner E, Schneider M, Shalev V, Shlipak MG, Solbu MD, Stempniewicz N, Tollitt J, Valdivielso JM, Van Der Leeuw J, Wang AYM, Wen CP, Woodward M, Yamagishi K, Yatsuya H, Zhang L, Dorresteijn JAN, Di Angelantonio E, Visseren FLJ, Pennells L, Coresh J (2023)

Publication Language: English

Publication Type: Journal article

Publication year: 2023

Journal

Book Volume: 30

Pages Range: 8-16

Journal Issue: 1

DOI: 10.1093/eurjpc/zwac176

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 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.

Authors with CRIS profile

Involved external institutions

Icahn School of Medicine at Mount Sinai United States (USA) (US) Karolinska Institute Sweden (SE) Teikyo University Japan (JP) University of Groningen / Rijksuniversiteit Groningen Netherlands (NL) Monash University Australia (AU) Dokkyo Medical University Japan (JP) Maccabi Healthcare Israel (IL) Johns Hopkins University (JHU) United States (USA) (US) University of Cambridge United Kingdom (GB) University Medical Centre Utrecht (UMC Utrecht) Netherlands (NL) Institut de Recerca Biomèdica de Lleida (IRBLleida) Spain (ES) Ruprecht-Karls-Universität Heidelberg Germany (DE) University of Leicester United Kingdom (GB) Geisinger Medical Center United States (USA) (US) Northern Care Alliance NHS Trust United Kingdom (GB) University of Mississippi Medical Center United States (USA) (US) University of Alabama at Birmingham (UAB) United States (USA) (US) Shahid Beheshti University of Medical Sciences Iran, Islamic Republic of (IR) Framingham Heart Study United States (USA) (US) Duke-NUS Medical School / 杜克—国大医学研究生院 Singapore (SG) University of California, San Diego (UC San Diego, UCSD) United States (USA) (US) Yamagata University (YU) Japan (JP) Memphis VA Medical Center United States (USA) (US) Tufts University United States (USA) (US) University of California San Francisco (UCSF) United States (USA) (US) University Hospital of North Norway / Universitetssykehuset Nord-Norge (UNN) Norway (NO) American Medical Group Association (AMGA) United States (USA) (US) University of Hong Kong (HKU) / 香港大學 Hong Kong (HK) China Medical University (CMU) / 中国医科大学 China (CN) University of Tsukuba / 筑波大学 Japan (JP) Fujita Health University Japan (JP) Peking University First Hospital / 北大国际医院 China (CN) Università degli Studi di Napoli Federico II Italy (IT) Gelre ziekenhuizen Apeldoorn Netherlands (NL) Tulane University United States (USA) (US) Charité - Universitätsmedizin Berlin Germany (DE) Northwestern University United States (USA) (US) Shiga University of Medical Science Japan (JP)

How to cite

APA:

Matsushita, K., Kaptoge, S., Hageman, S.H.J., Sang, Y., Ballew, S.H., Grams, M.E.,... Coresh, J. (2023). Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP. European Journal of Preventive Cardiology, 30(1), 8-16. https://doi.org/10.1093/eurjpc/zwac176

MLA:

Matsushita, Kunihiro, et al. "Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP." European Journal of Preventive Cardiology 30.1 (2023): 8-16.

BibTeX: Download