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Medical Sciences

Maya Petersen

HIV

Institution
Publication Year

Articles 1 - 2 of 2

Full-Text Articles in Medicine and Health Sciences

Long-Term Consequences Of The Delay Between Virologic Failure Of Highly Active Antiretroviral Therapy And Regimen Modification, Maya L. Petersen, Mark J. Van Der Laan, Napravnik Sonia, Joseph J. Eron, Richard G. Moore, Steven G. Deeks Dec 2007

Long-Term Consequences Of The Delay Between Virologic Failure Of Highly Active Antiretroviral Therapy And Regimen Modification, Maya L. Petersen, Mark J. Van Der Laan, Napravnik Sonia, Joseph J. Eron, Richard G. Moore, Steven G. Deeks

Maya Petersen

Objectives: Current treatment guidelines recommend immediate modification of antiretroviral therapy in HIV-infected individuals with incomplete viral suppression. These recommendations have not been tested in observational studies or large randomized trials. We evaluated the consequences of delayed modification following virologic failure. Design/methods: We used prospective data from two clinical cohorts to estimate the effect of time until regimen modification following first regimen failure on all-cause mortality. The impact of regimen type was also assessed. As the effect of delayed switching can be confounded if patients with a poor prognosis modify therapy earlier than those with a good prognosis, we used a …


Identifying Important Explanatory Variables For Time-Varying Outcomes., Oliver Bembom, Maya L. Petersen, Mark J. Van Der Laan Dec 2006

Identifying Important Explanatory Variables For Time-Varying Outcomes., Oliver Bembom, Maya L. Petersen, Mark J. Van Der Laan

Maya Petersen

This chapter describes a systematic and targeted approach for estimating the impact of each of a large number of baseline covariates on an outcome that is measured repeatedly over time. These variable importance estimates can be adjusted for a user-specified set of confounders and lend themselves in a straightforward way to obtaining confidence intervals and p-values. Hence, they can in particular be used to identify a subset of baseline covariates that are the most important explanatory variables for the time-varying outcome of interest. We illustrate the methodology in a data analysis aimed at finding mutations of the human immunodeficiency virus …