Analytical approach:
The analysis used a probabilistic Markov model with a long-term (lifetime) horizon and a hypothetical cohort of patients aged 15 to 65 years. The authors stated that the perspective of the health care provider was adopted.
Effectiveness data:
The key clinical data were the transition probabilities. These were from a retrospective study, conducted in four regional hospitals in Thailand, which included records of 408 patients on nevirapine and 116 patients on efavirenz, who were followed-up for three years. These data were supplemented with information from a large randomised controlled trial, identified by a published Cochrane review.
Monetary benefit and utility valuations:
The disability weights were from various sources, including the Global Burden of Disease, an Australian study, and expert opinion.
Measure of benefit:
Disability-adjusted life-years (DALYs) and life-years (LYs) were the summary benefit measures and they were discounted at a 3% annual rate.
Cost data:
The economic analysis included the costs of antiretroviral drugs, laboratory tests, medical services, and in-patient and out-patient treatment of complications. These costs were presented as category totals. The drug costs were from official national sources of reference costs for antiretroviral drugs. All other costs were from the retrospective cohort of Thai patients, who produced the transition probabilities. All costs were in Thai baht (THB). Future costs were discounted at a 3% annual rate and the price year was 2006.
Analysis of uncertainty:
A probabilistic Monte Carlo simulation was undertaken on all the input parameters, which were assigned predetermined probability distributions. The details of the probabilistic simulations were reported. Cost-effectiveness acceptability curves were generated for several willingness-to-pay thresholds, including the recommended threshold of THB 300,000, which was three times the gross domestic product per capita. The results were presented for various age groups and baseline cluster of differentiation 4 (CD4) cell counts.