Cost-effectiveness of different strategies to monitor adults on antiretroviral treatment: a combined analysis of three mathematical models

Abstract

Background: WHO's 2013 revisions to its Consolidated Guidelines on antiretroviral drugs recommend routine viral load monitoring, rather than clinical or immunological monitoring, as the preferred monitoring approach on the basis of clinical evidence. However, HIV programmes in resource-limited settings require guidance on the most cost-effective use of resources in view of other competing priorities such as expansion of antiretroviral therapy coverage. We assessed the cost-effectiveness of alternative patient monitoring strategies.

Methods: We evaluated a range of monitoring strategies, including clinical, CD4 cell count, and viral load monitoring, alone and together, at different frequencies and with different criteria for switching to second-line therapies. We used three independently constructed and validated models simultaneously. We estimated costs on the basis of resource use projected in the models and associated unit costs; we quantified impact as disability-adjusted life years (DALYs) averted. We compared alternatives using incremental cost-effectiveness analysis.

Findings: All models show that clinical monitoring delivers significant benefit compared with a hypothetical baseline scenario with no monitoring or switching. Regular CD4 cell count monitoring confers a benefit over clinical monitoring alone, at an incremental cost that makes it affordable in more settings than viral load monitoring, which is currently more expensive. Viral load monitoring without CD4 cell count every 6-12 months provides the greatest reductions in morbidity and mortality, but incurs a high cost per DALY averted, resulting in lost opportunities to generate health gains if implemented instead of increasing antiretroviral therapy coverage or expanding antiretroviral therapy eligibility.

Interpretation: The priority for HIV programmes should be to expand antiretroviral therapy coverage, firstly at CD4 cell count lower than 350 cells per μL, and then at a CD4 cell count lower than 500 cells per μL, using lower-cost clinical or CD4 monitoring. At current costs, viral load monitoring should be considered only after high antiretroviral therapy coverage has been achieved. Point-of-care technologies and other factors reducing costs might make viral load monitoring more affordable in future.

Funding: Bill & Melinda Gates Foundation, WHO.

Figure 1. Cost-Effectiveness Frontier Plots for Zambia (ICERs per DALY Averted, 2012 US$)

(a) Estill model; (b) Braithwaite et al. model; (c) HIV Synthesis model. Unfavoured (i.e. dominated/extendedly dominated; see Methods) strategies are shown in light grey while most efficient strategies are shown in black and their code is highlighted in bold. The frontier line that represents a most efficient pathway of spending as resources increase is shown in red together with the ICERs, i.e. the incremental cost per DALY averted of moving from one strategy to the next along the frontier.

Figure 2

Costs and benefits (DALYS averted) of alternative uses of resources (Braithwaite model). Results given are per 1 million HIV-infected persons with both benefits and costs discounted at 3%.

Figure 3

Costs per patient lifetime and DALYs averted from alternative uses of resources (Braithwaite model).

Figure 4

Scenario Analyses. The figures show the incremental net monetary benefit (I-NMB) of 12-monthly routine VL monitoring compared to the best alternative non-routine VL strategy at a given cost-effectiveness threshold. A positive value of I-NMB implies that 12-monthly viral load monitoring (vertical axis) is cost-effective at particular cost-effectiveness threshold (horizontal axis), whereas a negative I-NMB indicates it is not cost-effective because the opportunity costs exceed the health gains the intervention offers. Routine VL monitoring becomes “cost-effective” under each scenario at the threshold where the I-NMB line crosses the horizontal axis.