Predictive value of viral load measurements in asymptomatic untreated HIV-1 infection: a mathematical model

AIDS. 1996 Mar;10(3):255-62. doi: 10.1097/00002030-199603000-00003.

Abstract

Objective: To model the predictive value of viral load measurements in asymptomatic patients with HIV-1 infection, who have CD4 cell counts > 500 x 10(6)/l and no prior antiretroviral therapy, when the time of seroconversion and the prior levels of viremia are unknown.

Design: A mathematical model was constructed for the changes in HIV RNA load over time based on data from cohorts of HIV-infected patients followed since the time of seroconversion.

Methods: For different values of viral load, the time to progression to AIDS or an equivalent state [progression to AIDS equivalent (PAE)] was calculated using a wide range of estimates for the time since seroconversion and the rate of change of the viral load over time.

Results: In the absence of antiretroviral treatment, patients with a viral load of 10(5) copies/ml serum are at risk for PAE in less than 3 years (0-3 years) and patients with a viral load half a log higher are at risk in less than 1 year. In contrast, patients with a viral load of 10(4.5) have at least 1.9 years and may have up to 8 years before risk of PAE. Patients with a viral load of 10(4) RNA copies/ml have at least 2.8 years and may have up to 19 years before risk of PAE. The rate of change of the viral load was an important predictor of outcome; the time since seroconversion had only a minor effect.

Conclusions: The viral load in the plasma or serum has predictive value even if the time of seroconversion is unknown. The rate of change of viral load over time may also be an important predictive factor. Serial measurements of viral load over time may provide therapeutic guidance.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • CD4 Lymphocyte Count
  • Cohort Studies
  • HIV Infections / physiopathology
  • HIV Infections / virology*
  • HIV-1 / genetics
  • HIV-1 / isolation & purification*
  • Humans
  • Longitudinal Studies
  • Models, Theoretical
  • RNA, Viral / blood*

Substances

  • RNA, Viral