A non-linear mixed effect dynamic model incorporating prior exposure and adherence to treatment to describe long-term therapy outcome in HIV-patients

Journal of Pharmacokinetics and Pharmacodynamics

Volumn 33, Issue 4, 2006, Pages 519-542

  Labbé, Line ^a,b   Verotta, Davide ^a,b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Adherence; Bayes; Hierarchical non linear model; HIV; Mixed effect

Indexed keywords

ABACAVIR; ADEFOVIR DIPIVOXIL; AMPRENAVIR; ANTIRETROVIRUS AGENT; CARNITINE; EFAVIRENZ; INDINAVIR; NELFINAVIR; PLACEBO; PROTEINASE INHIBITOR; RNA DIRECTED DNA POLYMERASE INHIBITOR; SAQUINAVIR; VIRUS RNA;

ARTICLE; CLINICAL STUDY; COVARIANCE; DATA ANALYSIS; DRUG EXPOSURE; DRUG TREATMENT FAILURE; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS 1; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; LONG TERM CARE; MATHEMATICAL MODEL; MORTALITY; NONLINEAR SYSTEM; PATIENT COMPLIANCE; PHARMACODYNAMICS; PHARMACOLOGICAL PARAMETERS; PRIORITY JOURNAL; REPRODUCTION; SIMULATION; TREATMENT OUTCOME; VIRUS LOAD;

ALGORITHMS; ANTI-HIV AGENTS; ANTIRETROVIRAL THERAPY, HIGHLY ACTIVE; BAYES THEOREM; CLINICAL TRIALS, PHASE II; HIV INFECTIONS; HIV-1; HUMANS; MODELS, BIOLOGICAL; PATIENT COMPLIANCE; RANDOMIZED CONTROLLED TRIALS; REVERSE TRANSCRIPTASE INHIBITORS; T-LYMPHOCYTES; TREATMENT OUTCOME; VIRAL LOAD;

EID: 33745619788     PISSN: 1567567X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10928-006-9022-4     Document Type: Article

References (49)

1. D. W. Haas, et al. Therapy with efavirenz plus indinavir in patients with extensive prior nucleoside reverse-transcriptase inhibitor experience: a randomized, double-blind, placebo-controlled trial. J. Infect. Dis. 183:392-400 (2001).
2. R. M. Gulick, et al. Treatment with indinavir, zidovudine, and lamivudine in adults with human immunodeficiency virus infection and prior antiretroviral therapy. N. Engl. J. Med. 337:734-739 (1997).
3. A. L. Gifford, et al. Predictors of self-reported adherence and plasma HIV concentrations in patients on multidrug antiretroviral regimens. J. Acquir. Immun Defic. Syndr. 23:386-395 (2000).
4. R. H. Haubrich, et al. The value of patient-reported adherence to antiretroviral therapy in predicting virologic and immunologic response. California Collaborative Treatment Group. AIDS 13, 1099-1107 (1999).
5. J. L. Casado, et al. Percentage of adherence correlates with the risk of protease inhibitor (PI) treatment failure in HIV-infected patients. Antivir Ther 4:157-161 (1999).
6. D. R. Bangsberg, et al. Adherence to protease inhibitors, HIV-1 viral load, and development of drug resistance in an indigent population. AIDS 14:357-366 (2000).
7. B. Vrijens, et al. Modelling the association between adherence and viral load in HIV-infected patients. Stat. Med. 24:2719-2731 (2005).
8. S. M. Hammer, et al. Dual vs. single protease inhibitor therapy following antiretroviral treatment failure: a randomized trial. JAMA 288:169-180 (2002).
9. D. Verotta and F. Schaedeli. Non-linear dynamics models characterizing long-term virological data from AIDS clinical trials. Math. Biosci. 176:163-183 (2002).
10. D. Verotta. Models and estimation methods for clinical HIV-1 data. J. Comput. Appl. Math. 184:275-300 (2005).
11. M. A. Nowak and C. R. M. Bangham. Population dynamics of immune response to persistent viruses. Science 272:74-79 (1996).
12. M. A. Nowak, S. Bonhoeffer, G. M. Shaw, and R. M. May. Anti-viral drug treatment: dynamics of resistence in free virus and infected cell population. J. Theor. Biol. 184:203-217 (1997).
13. A. S. Perelson, et al. Decay characteristics of HIV-1-infected compartments during combination therapy. Nature 387:188-191 (1997).
14. A. S. Perelson, A. U. Neumann, M. Markowitz, J. M. Leonard, and D. D. Ho. HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time. Science 271:1582-1587 (1996).
15. T. W. Chun, et al. Quantification of latent tissue reservoirs and total body viral load in HIV-1 infection. Nature 387:183-188 (1997).
16. T. W. Chun, K. Chadwick, J. Margolick, and R. F. Siliciano. Differential susceptibility of naive and memory CD4+ T cells to the cytopathic effects of infection with human immunodeficiency virus type 1 strain LAI. J. Virol. 71:4436-4444 (1997).
17. M. Davidian and D. M. Giltinan. Nonlinear Models for Repeated Measurement Data. Chapman & Hall, London, 1995.
18. B. Efron and D. Feldman. Compliance as an explanatory variable in clinical trial. J. Am. Stat. Assoc. 86:9-17 (1991).
19. J. Urquhart and E. De Klerk. Contending paradigms for the interpretation of data on patient compliance with therapeutic drug regimens. Stat. Med. 17:251-267; discussion 387-389 (1998).
20. A. J. Boeckmann, S. L. Beal, and L. B. Sheiner. NONMEM V Users Guides. Technical Report, Division of Clinical Pharmacology, University of California at San Francisco, California, 1998.
21. N. Draper and H. Smith. Applied regression analysis, second edition. Wiley, New York, 1981.
22. E. J. Hannan. Rational transfer function approximation. Statist. Sci. 2:1029-1054 (1987).
23. M. Davidian and A. R. Gallant. The nonlinear mixed effect model with a smooth random effects density. Biometrika 80: 475-488 (2003).
24. J. C. Pinheiro and D. M. Bates. Statistics and Computing. Mixed-effects Models in S and S-plus. Springer, New York, 2000.
25. In Insightful Corporation, http://www.insightful.com/.
26. J. H. Friedman. A variable span smoother. Tech. Rep. No. 5, Laboratory for Computational Statistics, Department of Statistics, Stanford University, California, 1984.
27. S. Bonhoeffer, J. M. Coffin, and M. A. Nowak. Human immunodeficiency virus drug therapy and virus load. J. Virol. 71:3275-3278 (1997).
28. M. A. Nowak and R. M. May. Mathematical biology of HIV infections: antigenetic variation and diversity threshold. Math. Biosci. 106:1-21 (1991).
29. M. A. Nowak, and R. M. May. Coexistence and competition in HIV infections. J. Theor. Biol. 159:329-342 (1992).
30. L. M. Wein, R. M. DAmato, and A. S. Perelson. Mathematical analysis of antiretroviral therapy aimed at HIV-1 eradication or maintenance of low viral loads. J. Theoret. Biol. 192:81-98 (1998).
31. M. A. Stafford, et al. Modeling plasma virus concentration during primary HIV infection. J. Theor. Biol. 203:285-301 (2000).
32. D. D. Ho, et al. Rapid turnover of plasma virions and CD4 lymphocytes in HIV-1 infection. Nature 373:123-126 (1995).
33. H. L. Wu and A. A. Ding. Population HIV-1 dynamics in vivo: applicable models and inferential tools for virological data from AIDS clinical trials. Biometrics 55:410-418 (1999).
34. A. A. Ding and H. A. Wu. comparison study of models and fitting procedures for biphasic viral dynamics in HIV-1 infected patients treated with antiviral therapies. Biometrics 56:293-300 (2000).
35. D. L. Paterson, et al. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann. Intern. Med. 133:21-30 (2000).
36. H. Wu, A. A. Ding, and V. De Gruttola. Estimation of HIV dynamic parameters. Stat. Med. 17:2463-2485 (1998).
37. Y. Huang, L. Susan, S. L. Rosenkranz, and H. Wu. Modeling HIV dynamics and antiviral response with consideration of time-varying drug exposures, adherence and phenotypic sensitivity. Math. Biosci. 184:165-186 (2003).
38. Y. Huang and L. Wu. In D. Z. D'Argenio (ed.), Advanced Methods of Pharmacokinetic and Pharmacodynamic Systems Analysis. Kluwer Academic Publishers, Boston, 2004, pp. 221-238.
39. N. M. Dixit and A. S. Perelson, Complex patterns of viral load decay under antiretroviral therapy: influence of pharmacokinetics and intracellular delay. J. Theoretical Biol. 226:95-109 (2004).
40. P. Essunger and A. S. Perelson. Modeling HIV infection of CD4+ T-cell subpopulations. J. Theor. Biol. 170:367-391 (1994).
41. D. J. Austin, N. J. White, and R. M. Anderson. The dynamics of drug action on the within-host population growth of infectious agents: melding pharmacokinetics with pathogen population dynamics. J. Theor. Biol. 194:313-339 (1998).
42. L. J. Eldred, A. W. Wu, R. E. Chaisson, and R. D. Moore. Adherence to antiretroviral and pneumocystis prophylaxis in HIV disease. J. Acquir. Immune Defic. Syndr. Hum. Retrovirol. 18:117-125 (1998).
43. F. Mostashari, E. Riley, P. A. Selwyn, and F. L. Altice. Acceptance and adherence with antiretroviral therapy among HIV-infected women in a correctional facility. J. Acquir. Immune Defic. Syndr. Hum. Retrovirol. 18:341-348 (1998).
44. M. S. Hirsch, et al. Antiretroviral drug resistance testing in adults with HIV infection: implications for clinical management. International AIDS Society-USA Panel. JAMA 279:1984-1991 (1998).
45. M. A. Wainberg and G. Friedland. Public health implications of antiretroviral therapy and HIV drug resistance. JAMA 279:1977-1983 (1998).
46. A. F. M. Smith and J. M. Bernardo. Bayesian Theory. Wiley, New York, 1994.
47. Y. Huang, S. L. Rosenkranz, and H. Wu. Modeling HIV dynamics and antiviral response with consideration of time-varying drug exposures, adherence and phenotypic sensitivity. Math. Biosci. 184:165-186 (2003).
48. C. Cobelli, A. Lepschy, and G. R. Jacur. Identifiability of compartmental systems and related structural properties. Math. Biosci. 44:1-18 (1979).
49. J. J. Jacquez and P. Greif. Numerical parameter identifiability and estimability: integrating identifiability, estimability, and optimal sampling design. Math. Biosci. 77:201-227 (1985).