Background: Although the number of infected persons receiving highly active antiretroviral therapy (HAART) in low- and middle-income countries has increased dramatically, optimal disease management is not well defined.
Methods: We developed a model to compare the costs and benefits of 3 types of human immunodeficiency virus monitoring strategies: symptom-based strategies, CD4-based strategies, and CD4 counts plus viral load strategies for starting, switching, and stopping HAART. We used clinical and cost data from southern Africa and performed a cost-effectiveness analysis. All assumptions were tested in sensitivity analyses.
Results: Compared with the symptom-based approaches, monitoring CD4 counts every 6 months and starting treatment at a threshold of 200/muL was associated with a gain in life expectancy of 6.5 months (61.9 months vs 68.4 months) and a discounted lifetime cost savings of US $464 per person (US $4069 vs US $3605, discounted 2007 dollars). The CD4-based strategies in which treatment was started at the higher threshold of 350/microL provided an additional gain in life expectancy of 5.3 months at a cost-effectiveness of US $107 per life-year gained compared with a threshold of 200/microL. Monitoring viral load with CD4 was more expensive than monitoring CD4 counts alone, added 2.0 months of life, and had an incremental cost-effectiveness ratio of US $5414 per life-year gained relative to monitoring of CD4 counts. In sensitivity analyses, the cost savings from CD4 count monitoring compared with the symptom-based approaches was sensitive to cost of inpatient care, and the cost-effectiveness of viral load monitoring was influenced by the per test costs and rates of virologic failure.
Conclusions: Use of CD4 monitoring and early initiation of HAART in southern Africa provides large health benefits relative to symptom-based approaches for HAART management. In southern African countries with relatively high costs of hospitalization, CD4 monitoring would likely reduce total health care expenditures. The cost-effectiveness of viral load monitoring depends on test prices and rates of virologic failure.