Purpose: As 2nd-line antiretroviral therapy (ART) availability increases in resource-limited settings, questions remain about the value of laboratory monitoring to guide treatment decisions. Our objective was to assess the incremental benefits and cost-effectiveness of CD4 count and HIV RNA tests to guide the timing of switching ART in HIV-infected patients.
Methods: In a treatment-eligible cohort in Côte d’Ivoire, West Africa, we used a state-transition model (CEPAC-International) to simulate the average life expectancies and total health care costs (2006 US$) associated with different monitoring strategies to guide switching to 2nd-line ART. Monitoring strategies included clinical assessment, CD4 cell count, and HIV RNA testing, with criteria for 1st-line ART failure a single WHO stage III-IV event, 50% decrease in peak CD4, and return to baseline HIV RNA level, respectively. Time on failed 1st-line ART resulted in resistance mutations, which reduced 2nd-line ART efficacy. Data were derived from clinical trials and cohort studies from Côte d’Ivoire and published literature. Sensitivity analyses were conducted to explore the impact of uncertain parameters and assumptions, as well as to assess variations of the three main monitoring strategies.
Result: Compared with 1st-line ART only, the incremental benefits from the availability of 2nd-line ART ranged from a 23% (clinical monitoring) to a 39% (CD4 count) to a 48% (HIV RNA) increase in undiscounted life expectancy. The incremental cost-effectiveness ratio of switching to 2nd-line ART based on clinical monitoring was $1,750 per year of life saved (YLS) compared to 1st-line ART only; biannual CD4 monitoring was $2,300 per YLS. The incremental cost-effectiveness ratio of biannual HIV RNA testing ranged from $3,760 ($87/test) to $2,290/YLS ($25/test), compared to the next best strategy. While continued ART following virologic failure provided life-expectancy gains, the costs associated with never stopping ART were substantial. If 2nd-line ART costs were reduced, the cost-effectiveness of HIV RNA monitoring became more attractive. Results were also influenced by the impact of resistance on 2nd-line ART efficacy.
Conclusion: Use of simulation models to examine the costs and consequences of different laboratory monitoring strategies can assist in rational use of HIV treatment resources in settings like Côte d’Ivoire. Results can inform not only whether CD4 count and HIV RNA monitoring are used, but how they are implemented in clinical care.
Candidate for the Lee B. Lusted Student Prize Competition