Current HIV/AIDS Reports

, Volume 7, Issue 3, pp 168–174 | Cite as

Monitoring Antiretroviral Therapy in Resource-Limited Settings: Balancing Clinical Care, Technology, and Human Resources

Article

Abstract

Due to the rapid expansion of first-line antiretroviral therapy in resource-limited settings (RLS), increasing numbers of people are living with HIV for prolonged periods of time. Treatment programs must now decide how to balance monitoring costs necessary to maximize health benefits for those already on treatment with the continued demand to initiate more patients on first-line treatment. We review currently available evidence related to monitoring strategies in RLS and discuss their implications on timing of switching to second-line treatment, development of HIV resistance, and clinical outcome.

Keywords

Immunologic failure Clinical failure Treatment failure Resource-limited settings HIV resistance Monitoring strategies HIV AIDS Antiretroviral therapy Prognosis Second-line therapy 

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.
    UNAIDS: AIDS Epidemic Update 2009. UNAIDS; 2009.Google Scholar
  2. 2.
    WHO, UNAIDS, UNICEF: Towards universal access: scaling up priority HIV/AIDS interventions in the health sector. Progress report, September 2009. WHO; 2009.Google Scholar
  3. 3.
    Braitstein P, Brinkhof MW, Dabis F, et al.: Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries. Lancet 2006, 367:817–824.CrossRefPubMedGoogle Scholar
  4. 4.
    World Health Organization: Antiretroviral therapy for HIV infection in adults and adolescents in resource-limited settings: Toward universal access. Recommendations for a public health approach. Geneva: World Health Organization; 2006.Google Scholar
  5. 5.
    WHO: Rapid advice: antiretroviral therapy for HIV infection in adults and adolescents. Geneva: World Health Organization; 2009.Google Scholar
  6. 6.
    Meintjes G, Lawn SD, Scano F, et al.: Tuberculosis-associated immune reconstitution inflammatory syndrome: case definitions for use in resource-limited settings. Lancet Infect Dis 2008, 8:516–523.CrossRefPubMedGoogle Scholar
  7. 7.
    Reynolds SJ, Nakigozi G, Newell K, et al.: Failure of immunologic criteria to appropriately identify antiretroviral treatment failure in Uganda. AIDS 2009, 23:697–700.CrossRefPubMedGoogle Scholar
  8. 8.
    Mee P, Fielding KL, Charalambous S, et al.: Evaluation of the WHO criteria for antiretroviral treatment failure among adults in South Africa. AIDS 2008, 22:1971–1977.CrossRefPubMedGoogle Scholar
  9. 9.
    Chaiwarith R, Wachirakaphan C, Kotarathititum W, et al.: Sensitivity and specificity of using CD4+ measurement and clinical evaluation to determine antiretroviral treatment failure in Thailand. Int J Infect Dis 2007, 11:413–416.CrossRefPubMedGoogle Scholar
  10. 10.
    Keiser O, MacPhail P, Boulle A, et al.: Accuracy of WHO CD4 cell count criteria for virological failure of antiretroviral therapy. Trop Med Int Health 2009, 14:1220–1225.CrossRefPubMedGoogle Scholar
  11. 11.
    Moore DM, Awor A, Downing R, et al.: CD4+ T-cell count monitoring does not accurately identify HIV-infected adults with virologic failure receiving antiretroviral therapy. J Acquir Immune Defic Syndr 2008, 49:477–484.CrossRefPubMedGoogle Scholar
  12. 12.
    van Oosterhout JJ, Brown L, Weigel R, et al.: Diagnosis of antiretroviral therapy failure in Malawi: poor performance of clinical and immunological WHO criteria. Trop Med Int Health 2009, 14:856–861.CrossRefPubMedGoogle Scholar
  13. 13.
    Kantor R, Diero L, Delong A, et al.: Misclassification of first-line antiretroviral treatment failure based on immunological monitoring of HIV infection in resource-limited settings. Clin Infect Dis 2009, 49:454–462.CrossRefPubMedGoogle Scholar
  14. 14.
    •• DART Trial Team, Mugyenyi P, Walker AS, et al.: Routine versus clinically driven laboratory monitoring of HIV antiretroviral therapy in Africa (DART): a randomised non-inferiority trial. Lancet 2010, 375:123–131. This is a large, multicenter randomized clinical trial addressing monitoring strategies in RLS.Google Scholar
  15. 15.
    Lara AM, Kigozi J, Amurwon J, et al.: Cost effectiveness analysis of routine laboratory or clinically driven strategies for monitoring antiretroviral therapy in Uganda and Zimbabwe (DART trial). Presented at the 5th Conference on HIV Pathogenesis, Treatment, and Prevention. Cape Town, South Africa; 2009.Google Scholar
  16. 16.
    Alex Coutinho, Mermin J, Ekwaru JP, et al.: Utility of routine viral load, CD4 cell count, and clinical monitoring among HIV-infected adults in Uganda: A randomized trial. Presented at the 15th Conference on Retroviruses and Opportunistic Infections. Boston, MA; 2008.Google Scholar
  17. 17.
    Phillips AN, Pillay D, Miners AH, et al.: Outcomes from monitoring of patients on antiretroviral therapy in resource-limited settings with viral load, CD4 cell count, or clinical observation alone: a computer simulation model. Lancet 2008, 371:1443–1451.CrossRefPubMedGoogle Scholar
  18. 18.
    Department of HIV and AIDS Ministry of Health: Quarterly Report of the Antiretroviral Treatment Programme in Malawi with Results up to 30 Sept 2009. In Health MMo. Lilongwe; 2009.Google Scholar
  19. 19.
    Pujades-Rodriguez M, O’Brien D, Humblet P, Calmy A: Second-line antiretroviral therapy in resource-limited settings: the experience of Medecins Sans Frontieres. AIDS 2008, 22:1305–1312.CrossRefPubMedGoogle Scholar
  20. 20.
    Switching to second-line antiretroviral therapy in resource-limited settings: comparison of programmes with and without viral load monitoring. AIDS 2009, 23:1867–1874.Google Scholar
  21. 21.
    • Keiser O, Tweya H, Braitstein P, et al.: Mortality after failure of antiretroviral therapy in sub-Saharan Africa. Trop Med Int Health 2009, 15:251–258. This is a multicenter cohort that outlined the mortality consequences of failing to detect and switch to second-line treatment.Google Scholar
  22. 22.
    Hosseinipour MC, Kumwenda J, Weigel R, et al.: Second-line treatment in the Malawi antiretroviral programme: high early mortality but good outcomes in survivors, despite extensive drug resistance at baseline. HIV Med 2010 Mar 19 (Epub ahead of print).Google Scholar
  23. 23.
    Pillay D, Kityo C, Robertson V, et al.: Emergence and evolution of drug resistance in the absence of viral load monitoring during 48 weeks of combivir/tenofovir within the DART trial. Presented at the Conference on Retroviruses and Opportunistic Infections. Los Angeles, CA; February 25–28, 2007.Google Scholar
  24. 24.
    Reynolds SJ, Kityo C, Mbamanya F, et al.: Evolution of drug resistance after virological failure of a first-line highly active antiretroviral therapy regimen in Uganda. Antivir Ther 2009, 14:293–297.PubMedGoogle Scholar
  25. 25.
    Hoffmann CJ, Charalambous S, Sim J, et al.: Viremia, resuppression, and time to resistance in human immunodeficiency virus (HIV) subtype C during first-line antiretroviral therapy in South Africa. Clin Infect Dis 2009, 49:1928–1935.CrossRefPubMedGoogle Scholar
  26. 26.
    •• Hosseinipour MC, van Oosterhout JJ, Weigel R, et al.: The public health approach to identify antiretroviral therapy failure: high-level nucleoside reverse transcriptase inhibitor resistance among Malawians failing first-line antiretroviral therapy. AIDS 2009, 23:1127–1134. This article outlines the most severe resistance consequences of clinical and immunological monitoring in a public health program.Google Scholar
  27. 27.
    Marconi VC, Sunpath H, Lu Z, et al.: Prevalence of HIV-1 drug resistance after failure of a first highly active antiretroviral therapy regimen in KwaZulu Natal, South Africa. Clin Infect Dis 2008, 46:1589–1597.CrossRefPubMedGoogle Scholar
  28. 28.
    Sungkanuparph S, Manosuthi W, Kiertiburanakul S, et al.: Options for a second-line antiretroviral regimen for HIV type 1-infected patients whose initial regimen of a fixed-dose combination of stavudine, lamivudine, and nevirapine fails. Clin Infect Dis 2007, 44:447–452.CrossRefPubMedGoogle Scholar
  29. 29.
    Kumarasamy N, Madhavan V, Venkatesh KK, et al.: High frequency of clinically significant mutations after first-line generic highly active antiretroviral therapy failure: implications for second-line options in resource-limited settings. Clin Infect Dis 2009, 49:306–309.CrossRefPubMedGoogle Scholar
  30. 30.
    Kouanfack C, Montavon C, Laurent C, et al.: Low levels of antiretroviral-resistant HIV infection in a routine clinic in Cameroon that uses the World Health Organization (WHO) public health approach to monitor antiretroviral treatment and adequacy with the WHO recommendation for second-line treatment. Clin Infect Dis 2009, 48:1318–1322.CrossRefPubMedGoogle Scholar
  31. 31.
    Wallis C, Sanne I, Venter F, et al.: Varied patterns of HIV-1 drug resistance on failing first-line antiretroviral therapy in South Africa. J Acquir Immune Defic Syndr 2010, 53:480–484.CrossRefPubMedGoogle Scholar
  32. 32.
    Gupta RK, Hill A, Sawyer AW, et al.: Virological monitoring and resistance to first-line highly active antiretroviral therapy in adults infected with HIV-1 treated under WHO guidelines: a systematic review and meta-analysis. Lancet Infect Dis 2009, 9:409–417.CrossRefPubMedGoogle Scholar
  33. 33.
    Fox MP, Ive P, Long L, et al.: High rates of survival, immune reconstitution and virologic suppression on second-line antiretroviral therapy in South Africa. J Acquir Immune Defic Syndr 2010, 53:500–506.CrossRefPubMedGoogle Scholar
  34. 34.
    Arribas JR, Pulido F, Delgado R, et al.: Lopinavir/ritonavir as single-drug therapy for maintenance of HIV-1 viral suppression: 48-week results of a randomized, controlled, open-label, proof-of-concept pilot clinical trial (OK Study). J Acquir Immune Defic Syndr 2005, 40:280–287.CrossRefPubMedGoogle Scholar
  35. 35.
    Pulido F, Arribas JR: Noninferiority and lopinavir/ritonavir monotherapy trials. AIDS 2008, 22:1696–1697.CrossRefPubMedGoogle Scholar
  36. 36.
    Pulido F, Delgado R, Perez-Valero I, et al.: Long-term (4 years) efficacy of lopinavir/ritonavir monotherapy for maintenance of HIV suppression. J Antimicrob Chemother 2008, 61:1359–1361.CrossRefPubMedGoogle Scholar
  37. 37.
    Arribas JR, Delgado R, Arranz A, et al.: Lopinavir-ritonavir monotherapy versus lopinavir-ritonavir and 2 nucleosides for maintenance therapy of HIV: 96-week analysis. J Acquir Immune Defic Syndr 2009, 51:147–152.CrossRefPubMedGoogle Scholar
  38. 38.
    Deeks SG, Hoh R, Neilands TB, et al.: Interruption of treatment with individual therapeutic drug classes in adults with multidrug-resistant HIV-1 infection. J Infect Dis 2005, 192:1537–1544.CrossRefPubMedGoogle Scholar
  39. 39.
    Castagna A, Danise A, Menzo S, et al.: Lamivudine monotherapy in HIV-1-infected patients harbouring a lamivudine-resistant virus: a randomized pilot study (E-184V study). AIDS 2006, 20:795–803.CrossRefPubMedGoogle Scholar
  40. 40.
    Bendavid E, Young SD, Katzenstein DA, et al.: Cost-effectiveness of HIV monitoring strategies in resource-limited settings: a southern African analysis. Arch Intern Med 2008, 168:1910–1918.CrossRefPubMedGoogle Scholar
  41. 41.
    Vijayaraghavan A, Efrusy MB, Mazonson PD, et al.: Cost-effectiveness of alternative strategies for initiating and monitoring highly active antiretroviral therapy in the developing world. J Acquir Immune Defic Syndr 2007, 46:91–100.PubMedGoogle Scholar
  42. 42.
    Harries AD, Zachariah R, van Oosterhout JJ, et al.: Diagnosis and management of antiretroviral-therapy failure in resource-limited settings in sub-Saharan Africa: challenges and perspectives. Lancet Infect Dis 2010, 10:60–65.CrossRefPubMedGoogle Scholar
  43. 43.
    Lynen L, Van Griensven J, Elliott J: Monitoring for treatment failure in patients on first-line antiretroviral treatment in resource-constrained settings. Curr Opin HIV AIDS 2010, 5:1–5.CrossRefPubMedGoogle Scholar
  44. 44.
    Fiscus SA, Cheng B, Crowe SM, et al.: HIV-1 viral load assays for resource-limited settings. PLoS Med 2006, 3:e417.CrossRefPubMedGoogle Scholar
  45. 45.
    • Lofgren SM, Morrissey AB, Chevallier CC, et al.: Evaluation of a dried blood spot HIV-1 RNA program for early infant diagnosis and viral load monitoring at rural and remote healthcare facilities. AIDS 2009, 23:2459–2466. This is a pilot program of using dried blood spots and central processing to determine virological failure.Google Scholar
  46. 46.
    Johannessen A, Troseid M, Calmy A: Dried blood spots can expand access to virological monitoring of HIV treatment in resource-limited settings. J Antimicrob Chemother 2009, 64:1126–1129.CrossRefPubMedGoogle Scholar
  47. 47.
    Keiser O, Ojoo S, Mwanji I, Smith N: Cost effective model for reduced sampling of viral loads for monitoring antiretroviral therapy in resource limited settings. Presented at the International AIDS Society 5th Conference on HIV Pathogenesis, Treatment, and Prevention. Cape Town, South Africa; 2009.Google Scholar
  48. 48.
    Lockman S, Shapiro RL, Smeaton LM, et al.: Response to antiretroviral therapy after a single, peripartum dose of nevirapine. N Engl J Med 2007, 356:135–147.CrossRefPubMedGoogle Scholar
  49. 49.
    Colebunders R, Moses KR, Laurence J, et al.: A new model to monitor the virological efficacy of antiretroviral treatment in resource-poor countries. Lancet Infect Dis 2006, 6:53–59.CrossRefPubMedGoogle Scholar
  50. 50.
    • Meya D, Spacek LA, Tibenderana H, et al.: Development and evaluation of a clinical algorithm to monitor patients on antiretrovirals in resource-limited settings using adherence, clinical and CD4 cell count criteria. J Int AIDS Soc 2009, 12:3. This article outlines a strategy for better detection of failure using available clinical information.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.University of North Carolina ProjectKamuzu Central HospitalLilongweMalawi
  2. 2.Universidade Federal do Rio de JaneiroRio de JaneiroBrazil

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