Viral load monitoring could be cost-effective

Sustainable HIV treatment in Africa through viral-load-informed differentiated care.

Working Group on Modelling of Antiretroviral Therapy Monitoring Strategies in Sub-Saharan Africa, Phillips A, Shroufi A, Vojnov L, Cohn J, Roberts T, Ellman T, Bonner K, Rousseau C, Garnett G, Cambiano V, Nakagawa F, Ford D, Bansi-Matharu L, Miners A, Lundgren JD, Eaton JW, Parkes-Ratanshi R, Katz Z, Maman D, Ford N, Vitoria M, Doherty M, Dowdy D, Nichols B, Murtagh M, Wareham M, Palamountain KM, Chakanyuka Musanhu C, Stevens W, Katzenstein D, Ciaranello A, Barnabas R, Braithwaite RS, Bendavid E, Nathoo KJ, van de Vijver D, Wilson DP, Holmes C, Bershteyn A, Walker S, Raizes E, Jani I, Nelson LJ, Peeling R, Terris-Prestholt F, Murungu J, Mutasa-Apollo T, Hallett TB, Revill P. Nature. 2015 Dec 3;528(7580):S68-76. doi: 10.1038/nature16046.

There are inefficiencies in current approaches to monitoring patients on antiretroviral therapy in sub-Saharan Africa. Patients typically attend clinics every 1 to 3 months for clinical assessment. The clinic costs are comparable with the costs of the drugs themselves and CD4 counts are measured every 6 months, but patients are rarely switched to second-line therapies. To ensure sustainability of treatment programmes, a transition to more cost-effective delivery of antiretroviral therapy is needed. In contrast to the CD4 count, measurement of the level of HIV RNA in plasma (the viral load) provides a direct measure of the current treatment effect. Viral-load-informed differentiated care is a means of tailoring care so that those with suppressed viral load visit the clinic less frequently and attention is focussed on those with unsuppressed viral load to promote adherence and timely switching to a second-line regimen. The most feasible approach to measuring viral load in many countries is to collect dried blood spot samples for testing in regional laboratories; however, there have been concerns over the sensitivity and specificity of this approach to define treatment failure and the delay in returning results to the clinic. We use modelling to synthesize evidence and evaluate the cost-effectiveness of viral-load-informed differentiated care, accounting for limitations of dried blood sample testing. We find that viral-load-informed differentiated care using dried blood sample testing is cost-effective and is a recommended strategy for patient monitoring, although further empirical evidence as the approach is rolled out would be of value. We also explore the potential benefits of point-of-care viral load tests that may become available in the future.

Abstract [1] Full-text [free] access [2]

 Editor’s notes: There has been much debate concerning how best to monitor antiretroviral therapy (ART) in resource-limited settings. In the early stages of ART roll-out, there were concerns that if ART monitoring required laboratory testing, the high cost would divert resources away from treatment delivery. Guidelines were drawn up to allow monitoring based on clinical features, alone or with CD4 count monitoring. However, clinical and CD4 monitoring proved to be neither sensitive nor specific when compared to viral load monitoring. In practice, the number of people switched to second-line ART in resource-limited settings has been lower than predicted, particularly where monitoring is clinical or CD4-based. This raises concerns that, in the absence of viral load monitoring, some people will acquire resistance to first-line ART, and this will remain undetected, with the person receiving ineffective treatment for a prolonged period, resulting in the accumulation of resistance mutations. This could threaten the effectiveness of future treatment options, and increases the risk of transmission of drug-resistant viruses. In addition, the poor specificity of clinical and CD4-based definitions of “treatment failure” means that if these definitions are used to make decisions about switching to second line ART, many people who, in reality, have virologic suppression may be inappropriately switched to second-line ART.

Increasingly, there are calls for viral load monitoring to be made more widely available. This is technically challenging, particularly in remote areas. Dried blood spot samples are an alternative method for specimen collection and transport which is practical for remote facilities. Viral load monitoring using dried blood spots has been implemented in some settings. Interpretation of results needs to take account of the lower sensitivity and specificity when compared to viral load assays based on plasma.

This study used a mathematical model to explore outcomes and cost-effectiveness of a range of ART monitoring strategies. The authors found that monitoring based on viral load measurements using dried blood spots was cost-effective. The model assumed that in scenarios with clinical and/or CD4 monitoring patient visits would be three-monthly, whereas in the viral load monitoring scenario, individuals with suppressed viral load would attend clinic for monitoring less frequently (hence the term “viral load-informed differentiated care”). The reduction in visit frequency for people with suppressed viral load was the main driver of cost saving in this scenario.

The cost-effectiveness estimates considered only health sector costs and ignored any patient costs.  Even when treatment and care are free of charge, people incur substantial costs to attend clinics for HIV care, particularly because of loss of income and transport costs. If patient costs had been included, the savings due to reduced visit frequency would almost certainly be even greater.

The accuracy of models is inevitably dependent on the underlying assumptions (described in detail and with admirable clarity in the paper’s accompanying on-line supplement [3]). Cost-effectiveness was sensitive to the cost of viral load monitoring, assumed to be $22 per test based on dried blood spots. These results support efforts to increase access to viral load monitoring. As the authors comment, empirical data from programmes employing viral load-informed differentiated care as a monitoring strategy would be very useful. 

Africa [9]
Zimbabwe [10]
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