The Optimal Time to Initiate HIV Therapy Under Ordered Health States

• Published in: Operations research Vol. 56; no. 1; pp. 20 - 33
• Main Authors: Shechter, Steven M, Bailey, Matthew D, Schaefer, Andrew J, Roberts, Mark S
• Format: Journal Article
• Language: English
• Published: Linthicum, MD INFORMS 01-01-2008; Institute for Operations Research and the Management Sciences
• Subjects: Acquired immune deficiency syndrome; AIDS; AIDS (Disease); Anti-HIV agents; Antiretroviral drugs; Antiretrovirals; Antiviral agents; Applied sciences; Care and treatment; Causes of; Decision theory. Utility theory; Drug therapy; dynamic programming; Exact sciences and technology; Health aspects; health-care treatment; Highly active antiretroviral therapy; HIV; HIV (Viruses); HIV/AIDS; Human immunodeficiency virus; Immune system; Markov analysis; Markov decision processes; Markov models; Medical treatment; Modeling; Monte Carlo simulation; Natural history; Operational research and scientific management; Operational research. Management science; Operations research; Optimal policy; Optimization; Patients; Quality of life; stochastic modeling applications; Studies; Viral drug resistance; Viral load; Markov process; Markov decision; Toxicity; Irreversible process; Modeling; Optimization; Minimum time; stochastic modeling applications; Secondary effect; Dynamic programming; Public health; Damaging; Drug; Immunopathology; Retroviridae; Durability; Patient; AIDS; Lentivirus; Infection; Virus; Lifetime; Viral disease; dynamic programming: Markov decision processes; health-care treatment: HIV/AIDS; Human immunodeficiency virus
• ISSN: 0030-364X; 1526-5463
• DOI: 10.1287/opre.1070.0480

The question of when to initiate HIV treatment is considered the most important question in HIV care today. Benefits of delaying therapy include avoiding the negative side effects and toxicities associated with the drugs, delaying selective pressures that induce the development of resistant strains of the virus, and preserving a limited number of treatment options. On the other hand, the risks of delayed therapy include the possibility of irreversible damage to the immune system, development of AIDS-related complications, and death. We use Markov decision processes to develop the first HIV optimization models that aim to maximize the expected lifetime or quality-adjusted lifetime of a patient. We prove conditions that establish structural properties of the optimal solution and compare them to our data and results. Model solutions, based on clinical data, support a strategy of treating HIV earlier in its course as opposed to recent trends toward treating it later.