アブストラクト | BACKGROUND AND AIMS: The SAFEHEART tool has shown good discrimination in predicting cardiovascular events in a bespoke genotyped cohort with familial hypercholesterolaemia (FH). We assessed whether the tool could aid clinical decision making in an English routine care cohort with FH. METHODS: A historical (2000-2017) open cohort of 3643 participants aged 18-79 years and >/=6-months since FH diagnosis was derived from the Clinical Practice Research Datalink. Individual 10-year cardiovascular risks were predicted using the SAFEHEART model, with multiple imputation used to manage missing data. Outcomes were the first occurrence of myocardial infarction, coronary revascularisation, ischaemic stroke, carotid revascularisation, peripheral arterial revascularisation, non-traumatic lower limb amputation, or cardiovascular death. Model performance was assessed using standard measures of calibration and discrimination, and decision curve analysis. RESULTS: 147 outcome events were observed over a median 3.73 (IQR 1.59-6.48) years follow-up. While the model had some discriminatory value (Harrell's c-statistic 0.67 (95% CI 0.61-0.72)), observed outcome risks departed substantially from predicted risks. Calibration slopes for men and women by age decile were 10.09 (95% CI 7.40-12.77) and 2.85 (1.25-4.45), respectively. Recalibration-in-the-large led to closer alignment of observed and predicted risks (recalibration slopes 3.48 (2.55-4.41) and 1.14 (0.50-1.79), respectively). Decision curve analysis suggested the recalibrated model had net benefit at predicted risks of 10-30%. CONCLUSIONS: The original SAFEHEART model has limited generalisability to the routinely identifiable English primary care FH population. With recalibration it appears to have moderate utility at 10-30% predicted risk. It may have greater validity in more bespoke genetically defined FH populations. |
ジャーナル名 | Atherosclerosis |
Pubmed追加日 | 2022/8/12 |
投稿者 | McKay, Ailsa J; Gunn, Laura H; Ray, Kausik K |
組織名 | Imperial Centre for Cardiovascular Disease Prevention, Department of Primary Care;and Public Health, Imperial College London, St Dunstan's Road, London, UK.;Electronic address: ailsa.mckay08@imperial.ac.uk.;Department of Public Health Sciences and School of Data Science, University of;North Carolina at Charlotte, Charlotte, NC, USA; Department of Primary Care and;Public Health, School of Public Health, Imperial College London, UK. |
Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/35953355/ |