A health economic model to determine the long-term costs and clinical outcomes of raising low HDL-cholesterol in the prevention of coronary heart disease.

OBJECTIVES: The aim of this study was to describe a health economic model developed to project lifetime clinical and cost outcomes of lipid-modifying interventions in patients not reaching target lipid levels and to assess the validity of the model.
METHODS: The internet-based, computer simulation model is made up of two decision analytic sub-models, the first utilizing Monte Carlo simulation, and the second applying Markov modeling techniques. Monte Carlo simulation generates a baseline cohort for long-term simulation by assigning an individual lipid profile to each patient, and applying the treatment effects of interventions under investigation. The Markov model then estimates the long-term clinical (coronary heart disease events, life expectancy, and quality-adjusted life expectancy) and cost outcomes up to a lifetime horizon, based on risk equations from the Framingham study. Internal and external validation analyses were performed.
RESULTS: The results of the model validation analyses, plotted against corresponding real-life values from Framingham, 4S, AFCAPS/TexCAPS, and a meta-analysis by Gordon et al., showed that the majority of values were close to the y = x line, which indicates a perfect fit. The R2 value was 0.9575 and the gradient of the regression line was 0.9329, both very close to the perfect fit (= 1).
CONCLUSIONS: Validation analyses of the computer simulation model suggest the model is able to recreate the outcomes from published clinical studies and would be a valuable tool for the evaluation of new and existing therapy options for patients with persistent dyslipidemia.