[en] The aim of treating HIV-1-infected patients is to achieve and maintain suppression of viral load (VL). Achievement of this aim is thwarted by variable adherence to prescribed anti-retroviral drugs. Variable adherence to an antiretroviral regimen creates variability in the patient’s internal exposure to the drugs. Structural nested mean models (SNMMs) enabled us to estimate, during the initial phase of treatment, the relationship between variable internal exposure and VL, accounting for measured time-varying confounders and feedback relations using an antiretroviral regimen containing lopinavir/ritonavir (LPV/RTV, LPV/r). Our final SNMM predicts that the short term effect of treatment is modified by the most recent past VL, with higher initial VL’s being associated with larger treatment-induced reductions in VL for a given internal exposure to the drugs. Variation in internal exposure to LPV/r in the interquartile interval (P25%–P75%) only slightly affects the overall reduction in VL, supporting the conclusion that the relatively long duration of action of LPV/r lessens the impact on VL of the most frequently
recurring intermittent lapses in dosing.
Disciplines :
Mathematics Human health sciences: Multidisciplinary, general & others
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Bibliography
Chamberlain, G. (1992). Sequential moment restrictions in panel data - comment. Journal of Business & Economic Statistics 10 20.
Efron, B. and Tibshirani, R.J. (1993). An Introduction to the Bootstrap. Chapman & Hall, San Francisco.
Goetghebeur, E. and Pocock, S. (1993). Statistical issues in allowing for noncompliance and withdrawal. Drug Inform J 27 837-845.
Harter J.G. and Peck C.C. (1991). Chronobiology. Suggestions for integrating it into drug development. Ann N Y Acad Sci 618 563-571.
Lee, J., Ellenberg, J., Hirtz, D. and Nelson, K. (1991). Analysis of clinical trials by treatment actually received: is it really an option? Statist Med 10 1595-1605.
Liang, K.-Y. and Zeger, S. (1986). Longitudinal data analysis using generalized linear models. Biometrika 73 13-22. MR0836430
Molina, J.M., Podsadecki, T.J., Johnson, M.A., Wilkin, A., Domingo, P., Myers, R., Hairrell, J.M., Rode, R.A., King, M.S. and Hanna, G.J. (2007). A lopinavir/ritonavir-based oncedaily regimen results in better compliance and is non-inferior to a twice-daily regimen through 96 weeks. AIDS Res Human Retroviruses 223 1505-1514.
Paterson, D.L., Swindells, S., Mohr, J., Brester, M., Vergis, E.M., Squier, C., Wagener, M.M. and Singh, N. (2000). Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med. 133 21-30.
Pepe, M. and Anderson, G.L. (1994). A cautionary note on inference for marginal regression-models with longitudinal data and general correlated response data. Commun Stat Simul Comput 23 939-951.
Robins, J.M. (1994). Correcting for non-compliance in randomized trials using structural nested mean models. Commun Stat Theory Meth 23 2379-2412.
Robins, J.M. (1997). Causal Inference from Complex Longitudinal Data. Latent Variable Modeling and Applications to Causality. Lecture Notes in Statistics (120), M. Berkane, Editor. NY: Springer Verlag 1997 (pages 69-117).
Robins, J.M. (1999). Marginal structural models versus structural nested models as tools for causal inference. Statistical Models in Epidemiology: The Environment and Clinical Trials 116 95-134.
Vanhove, G.F., Schapiro, J.M., Winters, M.A., Merigan, T.C. and Blaschke, T.F. (1996). Patient compliance and drug failure in protease inhibitor monotherapy. Ann Intern Med. 276(24) 1955-1956.
Vansteelandt, S. (2007). On confounding, prediction and efficiency in the analysis of longitudinal and cross-sectional clustered data. Scand J Statist 34 478-498.
Vrijens, B. and Goetghebeur, E. (1997). Comparing compliance patterns between randomized treatments. Control Clin Trials 18(3) 187-203.
Vrijens, B., Tousset, E., Rode, R., Bertz, R., Mayer, S. and Urquhart, J. (2005). Successful projection of the time course of drug concentration in plasma during a 1-year period from electronically compiled dosing-time data used as input to individually parameterized pharmacokinetic models. J Clin Pharmacol 45(4) 461-467.
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