TY - JOUR
T1 - Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP
AU - Matsushita, Kunihiro
AU - Kaptoge, Stephen
AU - Hageman, Steven H.J.
AU - Sang, Yingying
AU - Ballew, Shoshana H.
AU - Grams, Morgan E.
AU - Surapaneni, Aditya
AU - Sun, Luanluan
AU - Arnlov, Johan
AU - Bozic, Milica
AU - Brenner, Hermann
AU - Brunskill, Nigel J.
AU - Chang, Alex R.
AU - Chinnadurai, Rajkumar
AU - Cirillo, Massimo
AU - Correa, Adolfo
AU - Ebert, Natalie
AU - Eckardt, Kai Uwe
AU - Gansevoort, Ron T.
AU - Gutierrez, Orlando
AU - Hadaegh, Farzad
AU - He, Jiang
AU - Hwang, Shih Jen
AU - Jafar, Tazeen H.
AU - Jassal, Simerjot K.
AU - Kayama, Takamasa
AU - Kovesdy, Csaba P.
AU - Landman, Gijs W.
AU - Levey, Andrew S.
AU - Lloyd-Jones, Donald M.
AU - Major, Rupert W.
AU - Miura, Katsuyuki
AU - Muntner, Paul
AU - Nadkarni, Girish N.
AU - Nowak, Christoph
AU - Ohkubo, Takayoshi
AU - Pena, Michelle J.
AU - Polkinghorne, Kevan R.
AU - Sairenchi, Toshimi
AU - Schaeffner, Elke
AU - Schneider, Markus P.
AU - Shalev, Varda
AU - Shlipak, Michael G.
AU - Solbu, Marit D.
AU - Stempniewicz, Nikita
AU - Tollitt, James
AU - Valdivielso, José M.
AU - Van Der Leeuw, Joep
AU - Dorresteijn, Jannick A.N.
AU - Visseren, Frank L.J.
N1 - Publisher Copyright:
© 2022 The Author(s).
PY - 2023/1/1
Y1 - 2023/1/1
N2 - 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.
AB - 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.
KW - Aged
KW - Aged, 80 and over
KW - Albuminuria/diagnosis
KW - Cardiovascular Diseases/diagnosis
KW - Creatinine
KW - Glomerular Filtration Rate
KW - Heart Disease Risk Factors
KW - Humans
KW - Renal Insufficiency, Chronic/diagnosis
KW - Risk Factors
KW - Cardiovascular disease
KW - Risk prediction
KW - Chronic kidney disease
KW - Meta-analysis
UR - http://www.scopus.com/inward/record.url?scp=85146193294&partnerID=8YFLogxK
U2 - 10.1093/eurjpc/zwac176
DO - 10.1093/eurjpc/zwac176
M3 - Article
C2 - 35972749
SN - 2047-4873
VL - 30
SP - 8
EP - 16
JO - European Journal of Preventive Cardiology
JF - European Journal of Preventive Cardiology
IS - 1
ER -