OBJECTIVES: : Cardiovascular disease is the leading cause of death worldwide. Three-quarters of these occur in low-middle income countries. HIV-positive patients are living longer because of anti-retroviral treatment (ART). However, the HIV infection and the ART has put them at twice the risk of cardiovascular disease events compared to non-HIV-infected people. Statins have been proved to be both effective and cost-effective in reducing this risk. This research aims to carry out a Cost-utility analysis of Statins for primary prevention of myocardial infarction in this group of people, who have double the baseline risk than the general population.

METHODS: A Markov model was used to assess the cost-effectiveness of Rosuvastatin compared to Atorvastatin. A hypothetical cohort of 1000 HIV-positive patients, stable on ART, was simulated through 4 Markov states over a lifetime. The treatment effectiveness and cost parameters were derived from published studies. The primary outcomes are QALYs, and ICER. A deterministic and probabilistic sensitivity analysis were done to assess the uncertainty around the parameters and the model.

RESULTS: Results from the analysis show that in the base case, Rosuvastatin prevented more myocardial infarctions and yielded more QALYs. An ICER of $21,595 (20991, 22199) was generated, which is not cost-effective for Uganda’s WTP. In the deterministic sensitivity analysis, the ICER was most sensitive to the cost of Rosuvastatin. Probabilistic sensitivity analysis showed that the probability of Rosuvastatin being cost-effective at the current willingness to pay threshold is only 26%.

CONCLUSIONS: Rosuvastatin is not Cost-effective in Uganda for primary prevention of myocardial infarction in HIV-positive patients. Its comparator in this analysis appears not to be cost-effective either. Given the limited local data and the big stretch on the data used in this analysis, these results are inconclusive. Future research needs to provide good quality local data on HIV/AIDS and cardiovascular disease co-morbidity.