Abstract
OBJECTIVE: 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 (e.g., cholesterol-years or blood pressure-years) to enhance health economic modelling in settings where clinical trials are not possible.</p>
METHODS: 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 randomisation. 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 was 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.</p>
RESULTS: 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.</p>
CONCLUSIONS: We have constructed an open-source health economic model capable of incorporating the cumulative effect of LDL-C (i.e., cholesterol-years), SBP (SBP-years), Lp(a), and smoking on lifetime CVD risk.</p>