Back to Search Start Over

Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets

Authors :
Kunihiro Matsushita
Simerjot K Jassal
Yingying Sang
Shoshana H Ballew
Morgan E Grams
Aditya Surapaneni
Johan Arnlov
Nisha Bansal
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 Gutierrez
Farzad Hadaegh
Jiang He
Shih-Jen Hwang
Tazeen H Jafar
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
David MJ Naimark
Christoph Nowak
Takayoshi Ohkubo
Michelle J Pena
Kevan R Polkinghorne
Charumathi Sabanayagam
Toshimi Sairenchi
Markus P Schneider
Varda Shalev
Michael 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
Elke Schaeffner
Josef Coresh
Source :
EClinicalMedicine, Vol 27, Iss , Pp 100552- (2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

Background: Chronic kidney disease (CKD) measures (estimated glomerular filtration rate [eGFR] and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. “CKD Patch” is a validated method to calibrate and improve the predicted risk from established equations according to CKD measures. Methods: Utilizing data from 4,143,535 adults from 35 datasets, we developed several “CKD Patches” incorporating eGFR and albuminuria, to enhance prediction of risk of atherosclerotic CVD (ASCVD) by the Pooled Cohort Equation (PCE) and CVD mortality by Systematic COronary Risk Evaluation (SCORE). The risk enhancement by CKD Patch was determined by the deviation between individual CKD measures and the values expected from their traditional CVD risk factors and the hazard ratios for eGFR and albuminuria. We then validated this approach among 4,932,824 adults from 37 independent datasets, comparing the original PCE and SCORE equations (recalibrated in each dataset) to those with addition of CKD Patch. Findings: We confirmed the prediction improvement with the CKD Patch for CVD mortality beyond SCORE and ASCVD beyond PCE in validation datasets (Δc-statistic 0.027 [95% CI 0.018–0.036] and 0.010 [0.007–0.013] and categorical net reclassification improvement 0.080 [0.032–0.127] and 0.056 [0.044–0.067], respectively). The median (IQI) of the ratio of predicted risk for CVD mortality with CKD Patch vs. the original prediction with SCORE was 2.64 (1.89–3.40) in very high-risk CKD (e.g., eGFR 30–44 ml/min/1.73m2 with albuminuria ≥30 mg/g), 1.86 (1.48–2.44) in high-risk CKD (e.g., eGFR 45–59 ml/min/1.73m2 with albuminuria 30–299 mg/g), and 1.37 (1.14–1.69) in moderate risk CKD (e.g., eGFR 60–89 ml/min/1.73m2 with albuminuria 30–299 mg/g), indicating considerable risk underestimation in CKD with SCORE. The corresponding estimates for ASCVD with PCE were 1.55 (1.37–1.81), 1.24 (1.10–1.54), and 1.21 (0.98–1.46). Interpretation: The “CKD Patch” can be used to quantitatively enhance ASCVD and CVD mortality risk prediction equations recommended in major US and European guidelines according to CKD measures, when available. Funding: US National Kidney Foundation and the NIDDK.

Details

Language :
English
ISSN :
25895370
Volume :
27
Issue :
100552-
Database :
Directory of Open Access Journals
Journal :
EClinicalMedicine
Publication Type :
Academic Journal
Accession number :
edsdoj.998af47783114dca839d455850f5705b
Document Type :
article
Full Text :
https://doi.org/10.1016/j.eclinm.2020.100552