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

Kunihiro Matsushita, Stephen Kaptoge, Steven H.J. Hageman, Yingying Sang, Shoshana H. Ballew, Morgan E. Grams, Aditya Surapaneni, Luanluan Sun, Johan Arnlov, Milica Bozic, Hermann Brenner, Nigel J. Brunskill, Alex R. Chang, Rajkumar Chinnadurai, Massimo Cirillo, Adolfo Correa, Natalie Ebert, Kai Uwe Eckardt, Ron T. Gansevoort, Orlando GutierrezFarzad Hadaegh, Jiang He, Shih Jen Hwang, Tazeen H. Jafar, Simerjot K. Jassal, Takamasa Kayama, Csaba P. Kovesdy, Gijs W. Landman, Andrew S. Levey, Donald M. Lloyd-Jones, Rupert W. Major, Katsuyuki Miura, Paul Muntner, Girish N. Nadkarni, Christoph Nowak, Takayoshi Ohkubo, Michelle J. Pena, Kevan R. Polkinghorne, Toshimi Sairenchi, Elke Schaeffner, Markus P. Schneider, Varda Shalev, Michael G. Shlipak, Marit D. Solbu, Nikita Stempniewicz, James Tollitt, José M. Valdivielso, Joep Van Der Leeuw, Angela Yee Moon Wang, Chi Pang Wen, Mark Woodward, Kazumasa Yamagishi, Hiroshi Yatsuya, Luxia Zhang, Jannick A.N. Dorresteijn, Emanuele Di Angelantonio, Frank L.J. Visseren, Lisa Pennells, Josef Coresh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)8-16
Number of pages9
JournalEuropean journal of preventive cardiology
Issue number1
StatePublished - Jan 1 2023


  • Cardiovascular disease
  • Chronic kidney disease
  • Meta-analysis
  • Risk prediction

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Epidemiology


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