Summary:Viral load fluctuates during the natural course of asymptomatic HIV-1 infection. It is often assumed that these fluctuations are random around a set point or underlying growth trend. Using longitudinal data, we tested whether fluctuations in viral load can be better explained by changes in CD4+ T-cell count than by a set point or trend of exponential growth. The correspondence between viral load and CD4+ T-cell count could be described by a simple mathematical relation. Using a bootstrapping approach, the hypothesis that viral load fluctuations are random around a set point was rejected with p < .00005. The hypothesis that viral load fluctuations are random around a trend of exponential growth was rejected with p < .005. Viral load data was explained better by changes in CD4+ T-cell counts than by a set point or by a trend of exponential growth. The implications of this finding for improved prognostication are discussed.
Address correspondence and reprint requests to Alun Lloyd, Program in Theoretical Biology, Institute for Advanced Study, Einstein Drive, Princeton, NJ 08540, U.S.A.; email: email@example.com.
R. A. Arnaout is currently affiliated with Harvard Medical School. Boston, Massachusetts, U.S.A.
A. L. Lloyd is currently affiliated with Institute for Advanced Study, Princeton, New Jersey, U.S.A.
Manuscript received October 8, 1999; accepted February 16, 2000.
© 2000 Lippincott Williams & Wilkins, Inc.