Andrew N Phillips1, Valentina Cambiano2, Alec Miners3, Paul Revill4, Deenan Pillay5, Jens D Lundgren6, Diane Bennett7, Elliott Raizes7, Fumiyo Nakagawa2, Andrea De Luca8, Marco Vitoria9, Jhoney Barcarolo9, Joseph Perriens9, Michael R Jordan10, Silvia Bertagnolio11. 1. Research Department of Infection and Population Health, University College London, London, UK. Electronic address: andrew.phillips@ucl.ac.uk. 2. Research Department of Infection and Population Health, University College London, London, UK. 3. London School of Hygiene & Tropical Medicine, London, UK. 4. University of York, York, UK. 5. Africa Centre, KwaZulu Natal, South Africa. 6. Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark. 7. Centers for Disease Control and Prevention, Atlanta, GA, USA. 8. University Division of Infectious Diseases, Siena University Hospital, Siena, Italy. 9. World Health Organization, Geneva, Switzerland. 10. Tufts University School of Medicine and Tufts Medical Center, Boston, MA, USA. 11. World Health Organization, Geneva, Switzerland. Electronic address: bertagnolios@who.int.
Abstract
BACKGROUND: With continued roll-out of antiretroviral therapy (ART) in resource-limited settings, evidence is emerging of increasing levels of transmitted drug-resistant HIV. We aimed to compare the effectiveness and cost-effectiveness of different potential public health responses to substantial levels of transmitted drug resistance. METHODS: We created a model of HIV transmission, progression, and the effects of ART, which accounted for resistance generation, transmission, and disappearance of resistance from majority virus in the absence of drug pressure. We simulated 5000 ART programmatic scenarios with different prevalence levels of detectable resistance in people starting ART in 2017 (t0) who had not previously been exposed to antiretroviral drugs. We used the model to predict cost-effectiveness of various potential changes in policy triggered by different prevalence levels of resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs) measured in the population starting ART. FINDINGS: Individual-level resistance testing before ART initiation was not generally a cost-effective option, irrespective of the cost-effectiveness threshold. At a cost-effectiveness threshold of US$500 per quality-adjusted life-year (QALY), no change in policy was cost effective (ie, no change in policy would involve paying less than $500 per QALY gained), irrespective of the prevalence of pretreatment NNRTI resistance, because of the increased cost of the policy alternatives. At thresholds of $1000 or higher, and with the prevalence of pretreatment NNRTI resistance greater than 10%, a policy to measure viral load 6 months after ART initiation became cost effective. The policy option to change the standard first-line treatment to a boosted protease inhibitor regimen became cost effective at a prevalence of NNRTI resistance higher than 15%, for cost-effectiveness thresholds greater than $2000. INTERPRETATION: Cost-effectiveness of potential policies to adopt in response to different levels of pretreatment HIV drug resistance depends on competing budgetary claims, reflected in the cost-effectiveness threshold. Results from our model will help inform WHO recommendations on monitoring of HIV drug resistance in people starting ART. FUNDING: WHO (with funds provided by the Bill & Melinda Gates Foundation), CHAIN (European Commission).
BACKGROUND: With continued roll-out of antiretroviral therapy (ART) in resource-limited settings, evidence is emerging of increasing levels of transmitted drug-resistant HIV. We aimed to compare the effectiveness and cost-effectiveness of different potential public health responses to substantial levels of transmitted drug resistance. METHODS: We created a model of HIV transmission, progression, and the effects of ART, which accounted for resistance generation, transmission, and disappearance of resistance from majority virus in the absence of drug pressure. We simulated 5000 ART programmatic scenarios with different prevalence levels of detectable resistance in people starting ART in 2017 (t0) who had not previously been exposed to antiretroviral drugs. We used the model to predict cost-effectiveness of various potential changes in policy triggered by different prevalence levels of resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs) measured in the population starting ART. FINDINGS: Individual-level resistance testing before ART initiation was not generally a cost-effective option, irrespective of the cost-effectiveness threshold. At a cost-effectiveness threshold of US$500 per quality-adjusted life-year (QALY), no change in policy was cost effective (ie, no change in policy would involve paying less than $500 per QALY gained), irrespective of the prevalence of pretreatment NNRTI resistance, because of the increased cost of the policy alternatives. At thresholds of $1000 or higher, and with the prevalence of pretreatment NNRTI resistance greater than 10%, a policy to measure viral load 6 months after ART initiation became cost effective. The policy option to change the standard first-line treatment to a boosted protease inhibitor regimen became cost effective at a prevalence of NNRTI resistance higher than 15%, for cost-effectiveness thresholds greater than $2000. INTERPRETATION: Cost-effectiveness of potential policies to adopt in response to different levels of pretreatment HIV drug resistance depends on competing budgetary claims, reflected in the cost-effectiveness threshold. Results from our model will help inform WHO recommendations on monitoring of HIV drug resistance in people starting ART. FUNDING: WHO (with funds provided by the Bill & Melinda Gates Foundation), CHAIN (European Commission).
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