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Antimicrob. Agents Chemother. doi:10.1128/AAC.00388-07
Copyright (c) 2007, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved.

A predictive genotypic algorithm for virologic response to lopinavir/ritonavir in protease inhibitor-experienced patients

Global Pharmaceutical Research and Development, Abbott, Abbott Park, IL USA; Abbott Laboratories, Rungis, France; Department of Virology, Pitié-Salpêtrière, Paris, France

^* To whom correspondence should be addressed. Email: martin.king{at}abbott.com.

	Abstract

Several genotypic resistance algorithms have been proposed to quantitate the degree of phenotypic resistance to the human immunodeficiency virus (HIV) protease inhibitor (PI) lopinavir, including the original Lopinavir Mutation Score. In this study, we retrospectively evaluated 21 codons in HIV protease known to be associated with PI resistance in a large antiretroviral-experienced observational patient cohort, "Autorisation Temporaire d'Utilisation" (ATU), to assess whether a more optimal algorithm could be derived by using virologic response data from patients treated with lopinavir/ritonavir (LPV/r). Five of the 11 mutations constituting the Lopinavir Mutation Score were not associated with virologic response while 4 additional mutations not included in this score demonstrated an association. Therefore, the Lopinavir ATU Score, which includes mutations at codons 10, 20, 24, 33, 36, 47, 48, 54, 82, and 84, was constructed and shown in two different types of multivariable analyses of the ATU cohort to be a better predictor of virologic response than the Lopinavir Mutation Score. The Lopinavir ATU Score was also more strongly associated with virologic response when applied to independent clinical trial populations of PI-experienced patients receiving LPV/r. This study provides the basis for a new genotypic resistance algorithm that is useful for predicting the antiviral activity of LPV/r-based regimens in PI-experienced patients. The refined algorithm may be useful in making clinical treatment decisions and in refining genetic and pharmacologic methods for assessing LPV/r activity.