五种不同风险模型在一级预防指南中的意义。

Implications of Five Different Risk Models In Primary Prevention Guidelines.

作者信息

Sud Maneesh, Sivaswamy Atul, Austin Peter C, Abdel-Qadir Husam, Anderson Todd J, Naimark David M J, Lee Douglas S, Roifman Idan, Thanassoulis George, Tu Karen, Wijeysundera Harindra C, Ko Dennis T

机构信息

Schulich Heart Program, Sunnybrook Health Sciences Centre, University of Toronto, Canada.

Institute of Health Policy Management, and Evaluation,University of Toronto, Canada.

出版信息

Eur Heart J Qual Care Clin Outcomes. 2024 May 11. doi: 10.1093/ehjqcco/qcae034.

DOI:10.1093/ehjqcco/qcae034

PMID:38734893

Abstract

BACKGROUND

A lack of consensus exists across guidelines as to which risk model should be used for the primary prevention of cardiovascular disease (CVD). Our objective was to determine potential improvements in the number needed to treat (NNT) and number of events prevented (NEP) using different risk models in patients eligible for risk stratification.

METHODS

A retrospective observational cohort was assembled from primary care patients in Ontario, Canada between January 1st, 2010, to December 31st, 2014 and followed for up to 5 years. Risk estimation was undertaken in patients 40-75 years of age, without CVD, diabetes, or chronic kidney disease using the Framingham Risk Score (FRS), Pooled Cohort Equations (PCEs), a recalibrated FRS (R-FRS), Systematic Coronary Risk Evaluation 2 (SCORE2), and the low-risk region recalibrated SCORE2 (LR-SCORE2).

RESULTS

The cohort consisted of 47,399 patients (59% women, mean age 54). The NNT with statins was lowest for SCORE2 at 40, followed by LR-SCORE2 at 41, R-FRS at 43, PCEs at 55, and FRS at 65. Models that selected for individuals with a lower NNT recommended statins to fewer, but higher risk patients. For instance, SCORE2 recommended statins to 7.9% of patients (5-year CVD incidence 5.92%). The FRS, however, recommended statins to 34.6% of patients (5-year CVD incidence 4.01%). Accordingly, the NEP was highest for the FRS at 406 and lowest for SCORE2 at 156.

CONCLUSIONS

Newer models such as SCORE2 may improve statin allocation to higher risk groups with a lower NNT but prevent fewer events at the population level.

摘要

背景

关于应使用哪种风险模型进行心血管疾病（CVD）的一级预防，各指南之间缺乏共识。我们的目标是确定在符合风险分层条件的患者中，使用不同风险模型时所需治疗人数（NNT）和预防事件数（NEP）的潜在改善情况。

方法

从2010年1月1日至2014年12月31日期间加拿大安大略省的初级保健患者中组建了一个回顾性观察队列，并随访长达5年。使用弗雷明汉风险评分（FRS）、合并队列方程（PCEs）、重新校准的FRS（R-FRS）、系统性冠状动脉风险评估2（SCORE2）以及低风险区域重新校准的SCORE2（LR-SCORE2），对年龄在40 - 75岁、无CVD、糖尿病或慢性肾病的患者进行风险评估。

结果

该队列由47,399名患者组成（59%为女性，平均年龄54岁）。使用他汀类药物时，SCORE2的NNT最低，为40，其次是LR-SCORE2，为41，R-FRS为43，PCEs为55，FRS为65。选择NNT较低个体的模型推荐使用他汀类药物的患者较少，但风险较高。例如，SCORE2推荐7.9%的患者使用他汀类药物（5年CVD发病率5.92%）。然而，FRS推荐34.6%的患者使用他汀类药物（5年CVD发病率4.01%）。因此，FRS的NEP最高，为406，SCORE2的NEP最低，为156。