| アブストラクト | Cardiovascular disease (CVD) risk-prediction models are used to identify high-risk individuals and guide statin initiation. However, these models are usually derived from individuals who might initiate statins during follow-up. We present a simple approach to address statin initiation to predict "statin-naive" CVD risk. We analyzed primary care data (2004-2017) from the UK Clinical Practice Research Datalink for 1,678,727 individuals (aged 40-85 years) without CVD or statin treatment history at study entry. We derived age- and sex-specific prediction models including conventional risk factors and a time-dependent effect of statin initiation constrained to 25% risk reduction (from trial results). We compared predictive performance and measures of public-health impact (e.g., number needed to screen to prevent 1 event) against models ignoring statin initiation. During a median follow-up of 8.9 years, 103,163 individuals developed CVD. In models accounting for (versus ignoring) statin initiation, 10-year CVD risk predictions were slightly higher; predictive performance was moderately improved. However, few individuals were reclassified to a high-risk threshold, resulting in negligible improvements in number needed to screen to prevent 1 event. In conclusion, incorporating statin effects from trial results into risk-prediction models enables statin-naive CVD risk estimation and provides moderate gains in predictive ability but had a limited impact on treatment decision-making under current guidelines in this population. |
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| ジャーナル名 | American journal of epidemiology |
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| 投稿日 | 2021/2/18 |
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| 投稿者 | Xu, Zhe; Arnold, Matthew; Stevens, David; Kaptoge, Stephen; Pennells, Lisa; Sweeting, Michael J; Barrett, Jessica; Di Angelantonio, Emanuele; Wood, Angela M |
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| 組織名 | |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/33595074/ |
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