Department of Epidemiology and Global Health, Umeå University, 901 87, Umeå, Sweden.
Biobank Research Unit, Umeå University, 901 87, Umeå, Sweden; Department of Surgical Sciences, Uppsala University, 751 05, Uppsala, Sweden.
Atherosclerosis. 2020 Nov;312:90-98. doi: 10.1016/j.atherosclerosis.2020.08.014. Epub 2020 Aug 29.
There are guideline discussions on a lifetime approach to cardiovascular risk. Many of the available risk models estimate the short-term, usually 10-year risk of non-fatal and fatal cardiovascular diseases (CVD) grouped together. We aimed to develop lifetime risk models for non-fatal coronary heart disease, stroke, heart failure and death from CVD and non-CVD.
We included 92,915 individuals who had participated in a community-based lifestyle intervention programme at 40, 50 and/or 60 years of age. Their collected data on selected risk factors were linked to register data on hospitalizations and death. Parametric multivariable survival regression with a competing risks approach was employed to model cause-specific hazards, which were translated into cumulative incidence functions to provide the risk of experiencing each event separately. All analyses were performed gender-age wise. For illustrative purposes, "better" and "worse" risk profiles were created by setting three modifiable risk factors to the best and worst levels, respectively.
Most of the risk factors qualified for inclusion in the regressions. Men had a higher risk of cardiovascular events and the events occurred at a younger age than women. In the created risk profiles, where serum total cholesterol, smoking status and blood pressure were modified, an excessive number of CVD events were observed in the worse profiles.
Using these models, the lifetime risk of each of the first CVD events can be estimated for different risk factor profiles. Since the predictions are diagnosis specific, the estimates are more accurate.
关于心血管风险的终身方法存在指南讨论。许多可用的风险模型估计非致命和致命心血管疾病(CVD)的短期风险,通常为 10 年。我们旨在为非致命性冠心病、中风、心力衰竭和 CVD 和非 CVD 死亡开发终身风险模型。
我们纳入了 92915 名曾在 40、50 和/或 60 岁时参加过基于社区的生活方式干预计划的个体。他们收集的关于选定风险因素的数据与医院就诊和死亡登记数据相关联。采用具有竞争风险方法的参数多变量生存回归来对特定病因的风险进行建模,这些风险被转化为累积发生率函数,以分别提供每种事件发生的风险。所有分析均按性别-年龄进行。为了说明问题,通过将三个可改变的风险因素分别设置为最佳和最差水平,创建了“更好”和“更差”风险概况。
大多数风险因素符合回归要求。男性的心血管事件风险较高,且事件发生年龄比女性更早。在创建的风险概况中,当改变血清总胆固醇、吸烟状况和血压时,观察到更差的概况中存在过多的 CVD 事件。
使用这些模型,可以为不同的风险因素概况估计每种首次 CVD 事件的终身风险。由于预测是针对特定诊断的,因此估计更为准确。