A Comparison Study of Models and Fitting Procedures for Biphasic Viral Dynamics in HIV‐1 Infected Patients Treated with Antiviral Therapies

The study of HIV dynamics is one of the most important developments in recent AIDS research. It has led to a new understanding of the pathogenesis of HIV infection. But, although important findings in HIV dynamics have been published in prestigious scientific journals in the last 5 years, the model-fitting procedures used in these publications have not been studied in any detail. In this paper, we evaluate the performance of four model-fitting procedures proposed and used in biphasic HIV dynamic data analysis via extensive Monte Carlo simulations. We propose some guidelines for practitioners to select an appropriate method for their own data analysis. Real data examples from an AIDS clinical trial are provided as illustrations.

[1]  A. Perelson.  Modeling the interaction of the immune system with HIV , 1989 .

[2]  Jim Freeman,et al.  Outliers in Statistical Data (3rd edition) , 1995 .

[3]  F. Hoppensteadt,et al.  A Theory of Epidemics , 1992 .

[4]  M A Nowak,et al.  Viral dynamics in vivo: limitations on estimates of intracellular delay and virus decay. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[5]  M. Lederman,et al.  Characterization of viral dynamics in human immunodeficiency virus type 1-infected patients treated with combination antiretroviral therapy: relationships to host factors, cellular restoration, and virologic end points. , 1999, The Journal of infectious diseases.

[6]  A. Perelson,et al.  Dynamics of HIV infection of CD4+ T cells. , 1993, Mathematical biosciences.

[7]  Andrew N. Phillips,et al.  Reduction of HIV Concentration During Acute Infection: Independence from a Specific Immune Response , 1996, Science.

[8]  J L Sullivan,et al.  Inappropriate model-fitting methods may lead to significant underestimates of viral decay rates in HIV dynamic studies. , 1999, Journal of acquired immune deficiency syndromes.

[9]  Martin A. Nowak,et al.  Viral dynamics in human immunodeficiency virus type 1 infection , 1995, Nature.

[10]  Roy M. Anderson,et al.  Complex dynamical behaviour in the interaction between HIV and the immune system , 1989 .

[11]  A. Perelson,et al.  HIV-1 Dynamics in Vivo: Virion Clearance Rate, Infected Cell Life-Span, and Viral Generation Time , 1996, Science.

[12]  Alan S. Perelson,et al.  Decay characteristics of HIV-1-infected compartments during combination therapy , 1997, Nature.

[13]  A. Perelson,et al.  Rapid turnover of plasma virions and CD4 lymphocytes in HIV-1 infection , 1995, Nature.

[14]  A A Ding,et al.  Relationships between antiviral treatment effects and biphasic viral decay rates in modeling HIV dynamics. , 1999, Mathematical biosciences.

[15]  W. Borkowsky,et al.  Dynamics of Human Immunodeficiency Virus Type 1 Replication in Vertically Infected Infants , 1999, Journal of Virology.

[16]  H Wu,et al.  Population HIV‐1 Dynamics In Vivo: Applicable Models and Inferential Tools for Virological Data from AIDS Clinical Trials , 1999, Biometrics.

[17]  A. Perelson,et al.  A Model for the Immune System Response to HIV: AZT Treatment Studies , 1993 .

[18]  V De Gruttola,et al.  Estimation of HIV dynamic parameters. , 1998, Statistics in medicine.