Improving 10-year cardiovascular risk prediction in apparently healthy people: flexible addition of risk modifiers on top of SCORE2.
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アブストラクト AIMS:In clinical practice, factors associated with cardiovascular disease (CVD) like albuminuria, education level, or coronary artery calcium (CAC) are often known, but not incorporated in cardiovascular risk prediction models. The aims of the current study were to evaluate a methodology for the flexible addition of risk modifying characteristics on top of SCORE2 and to quantify the added value of several clinically relevant risk modifying characteristics.METHODS AND RESULTS:Individuals without previous CVD or DM were included from the UK Biobank; Atherosclerosis Risk in Communities (ARIC); Multi-Ethnic Study of Atherosclerosis (MESA); European Prospective Investigation into Cancer, The Netherlands (EPIC-NL); and Heinz Nixdorf Recall (HNR) studies (n = 409 757) in whom 16 166 CVD events and 19 149 non-cardiovascular deaths were observed over exactly 10.0 years of follow-up. The effect of each possible risk modifying characteristic was derived using competing risk-adjusted Fine and Gray models. The risk modifying characteristics were applied to individual predictions with a flexible method using the population prevalence and the subdistribution hazard ratio (SHR) of the relevant predictor. Risk modifying characteristics that increased discrimination most were CAC percentile with 0.0198 [95% confidence interval (CI) 0.0115; 0.0281] and hs-Troponin-T with 0.0100 (95% CI 0.0063; 0.0137). External validation was performed in the Clinical Practice Research Datalink (CPRD) cohort (UK, n = 518 015, 12 675 CVD events). Adjustment of SCORE2-predicted risks with both single and multiple risk modifiers did not negatively affect calibration and led to a modest increase in discrimination [0.740 (95% CI 0.736-0.745) vs. unimproved SCORE2 risk C-index 0.737 (95% CI 0.732-0.741)].CONCLUSION:The current paper presents a method on how to integrate possible risk modifying characteristics that are not included in existing CVD risk models for the prediction of CVD event risk in apparently healthy people. This flexible methodology improves the accuracy of predicted risks and increases applicability of prediction models for individuals with additional risk known modifiers.ジャーナル名 European journal of preventive cardiology 投稿日 2023/6/2 投稿者 Hageman, Steven H J; Petitjaen, Carmen; Pennells, Lisa; Kaptoge, Stephen; Pajouheshnia, Romin; Tillmann, Taavi; Blaha, Michael J; McClelland, Robyn L; Matsushita, Kunihiro; Nambi, Vijay; Klungel, Olaf H; Souverein, Patrick C; van der Schouw, Yvonne T; Verschuren, W M Monique; Lehmann, Nils; Erbel, Raimund; Jockel, Karl-Heinz; Di Angelantonio, Emanuele; Visseren, Frank L J; Dorresteijn, Jannick A N 組織名 Department of Vascular Medicine, University Medical Center Utrecht, PO Box 85500,;3508 GA, Utrecht, The Netherlands.;British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public;Health and Primary Care, University of Cambridge, Cambridge, UK.;Victor Phillip Dahdaleh Heart and Lung Research Institute, University of;Cambridge, Cambridge, UK.;Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for;Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands.;Institute of Family Medicine and Public Health, University of Tartu, Tartu,;Estonia.;Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins;Hospital, Baltimore, USA.;Department of Biostatistics, University of Washington, Seattle, WA, USA.;Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health,;Baltimore, USA.;Center for Cardiovascular Disease Prevention, Michael E DeBakey Veterans Affairs;Hospital, Houston, USA.;Department of Medicine, Baylor College of Medicine, Houston, USA.;Julius Center for Health Sciences and Primary Care, University Medical Center;Utrecht, Utrecht University, Utrecht, The Netherlands.;Centre for Nutrition, Prevention and Health Services, National Institute for;Public Health and the Environment, Bilthoven, The Netherlands.;Institute for Medical Informatics, Biometry and Epidemiology, University Hospital;Essen, University Duisburg-Essen, Essen, Germany.;British Heart Foundation Centre of Research Excellence, University of Cambridge,;Cambridge, UK.;National Institute for Health and Care Research Blood and Transplant Research;Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK.;Health Data Research UK Cambridge, Wellcome Genome Campus and University of;Health Data Science Research Centre, Human Technopole, Milan, Italy. Pubmed リンク https://www.ncbi.nlm.nih.gov/pubmed/37264679/ -
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