Analytical approach:
The analysis was based on a Markov model with a 40-year time horizon. The authors stated that the perspective of the health care system was taken.
Effectiveness data:
The clinical evidence came from a selection of known, relevant studies. The data on treatment efficacy, which was the key model input, were derived from the Respond Trial, a randomised placebo-controlled trial with 1,660 hypertensive patients with dyslipidaemia. The baseline characteristics of eligible patients were from 244 patients included in the 2005 Korean National Health and Nutrition Examination Survey (KNHNES), which was a cross-sectional national survey carried out by the Korean health authority. Other official Korean sources and published studies were used for additional clinical inputs. For example, most of the transition probabilities were from a published observational study, with more than 11,000 Chinese participants, called the United States and People’s Republic of China Collaborative Study of Cardiovascular and Cardiopulmonary Epidemiology.
Monetary benefit and utility valuations:
The utility values were from an analysis of the KNHNES, using the European Quality of life (EQ-5D) questionnaire.
Measure of benefit:
Life-years (LYs) and quality-adjusted life-years (QALYs) were the summary benefit measures and they were discounted at an annual rate of 5%.
Cost data:
The economic analysis included the costs of drugs and treatment of (the incidence or prevalence of) cardiovascular disease. Drug costs were derived from official pharmaceutical price lists, using dosages reported in the Respond Trial, while cardiovascular disease treatment costs and resource consumption were based on reimbursements made by the Korean Health Insurance Review and Assessment Services. All costs were in South Korean won (KRW) and the exchange rate was KRW 1,300 equalled one US dollar. A 5% annual discount rate was applied and the price year was not explicitly reported; some of the costs were from 2008 sources.
Analysis of uncertainty:
One-way sensitivity analyses were carried out on key model inputs, including the efficacy (which was varied using a published 95% confidence interval), cardiovascular risk predictions (± 25%), utility weights (± 25%), cardiovascular disease costs (± 25%), discount rate (0% to 7.5%), annual increase in cardiovascular disease costs (0% to 9%), and the one-year persistence rate (alternative assumptions). A multivariate sensitivity analysis, with 2,000 Monte Carlo simulations, was also carried out.