Health Economics and Policy Evaluation Research (HEPER) Group, Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia; Baker Heart and Diabetes Institute, Melbourne, Australia.
Adelaide Medical School, University of Adelaide, Australia.
Value Health. 2024 Dec;27(12):1743-1752. doi: 10.1016/j.jval.2024.07.010. Epub 2024 Jul 31.
Our objective was to design and develop an open-source model capable of simulating interventions for primary prevention of cardiovascular disease (CVD) that incorporated the cumulative effects of risk factors (eg, cholesterol years or blood-pressure years) to enhance health economic modeling in settings which clinical trials are not possible.
We reviewed the literature to design the model structure by selecting the most important causal risk factors for CVD-low-density lipoprotein-cholesterol (LDL-C), systolic blood pressure (SBP), smoking, diabetes, and lipoprotein (a) (Lp(a))-and most common CVDs-myocardial infarction and stroke. The epidemiological basis of the model involves the simulation of risk factor trajectories, which are used to modify CVD risk via causal effect estimates derived from Mendelian randomization. LDL-C, SBP, Lp(a), and smoking all have cumulative impacts on CVD risk, which were incorporated into the health economic model. The data for the model were primarily sourced from the UK Biobank study. We calibrated the model using clinical trial data and validated the model against the observed UK Biobank data. Finally, we performed an example health economic analysis to demonstrate the utility of the model. The model is open source.
The model performed well in all validation tests. It was able to produce interpretable and plausible (consistent with expectations of the existing literature) results from an example health economic analysis.
We have constructed an open-source health economic model capable of incorporating the cumulative effect of LDL-C (ie, cholesterol years), SBP (SBP-years), Lp(a), and smoking on lifetime CVD risk.
我们旨在设计和开发一种开源模型，该模型能够模拟用于心血管疾病（CVD）一级预防的干预措施，纳入风险因素的累积效应（例如，胆固醇年或血压年），以增强在临床试验不可行的情况下进行健康经济建模的能力。
我们通过选择 LDL-C、SBP、吸烟、糖尿病和脂蛋白（a）（Lp（a））等最重要的因果风险因素以及最常见的 CVD 事件——心肌梗死和中风，来设计模型结构，综述文献。模型的流行病学基础涉及风险因素轨迹的模拟，这些轨迹通过来自孟德尔随机化的因果效应估计来改变 CVD 风险。LDL-C、SBP、Lp（a）和吸烟对 CVD 风险均具有累积影响，这些影响已纳入健康经济模型中。模型数据主要来自英国生物库研究。我们使用临床试验数据对模型进行校准，并使用英国生物库观察数据对模型进行验证。最后，我们进行了一个健康经济分析示例，以展示模型的实用性。该模型是开源的。
模型在所有验证测试中表现良好。它能够从健康经济分析示例中生成可解释和合理的（与现有文献的预期一致）结果。
我们已经构建了一个能够纳入 LDL-C（即胆固醇年）、SBP（SBP 年）、Lp（a）和吸烟对终生 CVD 风险累积效应的开源健康经济模型。
