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Management of Antiretroviral Therapy for HIV Infection: Analyzing When to Change Therapy

Author

Listed:
  • Rebecca M. D'Amato

    (Rand Corporation, Santa Monica, California 90407)

  • Richard T. D'Aquila

    (Infectious Disease Unit and AIDS Research Center, Massachusetts General Hospital, Charlestown, Massachusetts 02129)

  • Lawrence M. Wein

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

We analyze two joint decisions in the management of HIV-infected patients on antiretroviral therapy: how frequently to measure a patient's virus level, and when to switch therapy. The underlying stochastic model captures the initial suppression and eventual rebound of the virus level in the blood of a typical HIV-infected patient undergoing treatment. We consider two classes of policies: a viral load policy, which triggers a change in therapy when the current virus level divided by the smallest level achieved thus far exceeds a prespecified threshold, and a proactive policy, which is similar to the viral load policy but also switches drugs at a prespecified time if no evidence of viral rebound has been seen. We find approximate analytical expressions for the probability of switching before the virus reaches its nadir (minimum value) and the mean delay in detection of viral rebound (i.e., the time interval from when the viral nadir occurs until the switch in therapy). Numerical results show that the proactive policy outperforms (i.e., a smaller detection delay for a given probability of prenadir switching) the viral load policy and recent recommendations by an expert AIDS panel, and may delay the onset of multidrug resistance in a significant proportion of patients who experience drug failure.

Suggested Citation

  • Rebecca M. D'Amato & Richard T. D'Aquila & Lawrence M. Wein, 2000. "Management of Antiretroviral Therapy for HIV Infection: Analyzing When to Change Therapy," Management Science, INFORMS, vol. 46(9), pages 1200-1213, September.
  • Handle: RePEc:inm:ormnsc:v:46:y:2000:i:9:p:1200-1213
    DOI: 10.1287/mnsc.46.9.1200.12235
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    References listed on IDEAS

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    1. D'Amato, Rebecca M. (Rebecca Marie) & D'Aquila, Richard T. & Wein, Lawrence M., 1998. "Management of antiretroviral therapy for HIV infection : analyzing when to change therapy," Working papers WP 4043-98., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. David D. Ho & Avidan U. Neumann & Alan S. Perelson & Wen Chen & John M. Leonard & Martin Markowitz, 1995. "Rapid Turnover of Plasma Virions and CD4 Lymphocytes in HIV-1 Infection," Working Papers 95-01-002, Santa Fe Institute.
    3. Tae-Wook Chun & Lucy Carruth & Diana Finzi & Xuefei Shen & Joseph A. DiGiuseppe & Harry Taylor & Monika Hermankova & Karen Chadwick & Joseph Margolick & Thomas C. Quinn & Yen-Hong Kuo & Ronald Brookme, 1997. "Quantification of latent tissue reservoirs and total body viral load in HIV-1 infection," Nature, Nature, vol. 387(6629), pages 183-188, May.
    4. Charles E. Clark, 1961. "The Greatest of a Finite Set of Random Variables," Operations Research, INFORMS, vol. 9(2), pages 145-162, April.
    5. Alan S. Perelson & Paulina Essunger & Yunzhen Cao & Mika Vesanen & Arlene Hurley & Kalle Saksela & Martin Markowitz & David D. Ho, 1997. "Decay characteristics of HIV-1-infected compartments during combination therapy," Nature, Nature, vol. 387(6629), pages 188-191, May.
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    Cited by:

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    2. Yan Yang & Jeremy D. Goldhaber-Fiebert & Lawrence M. Wein, 2013. "Analyzing Screening Policies for Childhood Obesity," Management Science, INFORMS, vol. 59(4), pages 782-795, April.
    3. Naumzik, Christof & Feuerriegel, Stefan & Nielsen, Anne Molgaard, 2023. "Data-driven dynamic treatment planning for chronic diseases," European Journal of Operational Research, Elsevier, vol. 305(2), pages 853-867.

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