Determination of Phenotypic Resistance Cutoffs From Routine Clinical Data. (15th April 2017)

• Record Type: Journal Article
• Authors: Pironti, Alejandro; Walter, Hauke; Pfeifer, Nico; Knops, Elena; Lübke, Nadine; Büch, Joachim; Di Giambenedetto, Simona; Kaiser, Rolf; Lengauer, Thomas
• Is Part Of: Journal of acquired immune deficiency syndromes. Volume 74:Number 5(2017)
• Publication Date: 2017-04-15
• Subjects: phenotypic drug-resistance testing -- clinically relevant cutoffs -- antiretroviral therapy -- human immunodeficiency virus type 1 -- statistical methods; AIDS (Disease) -- Periodicals; Acquired Immunodeficiency Syndrome -- Periodicals; AIDS (Disease); Periodicals; 616.9792005
• DOI: 10.1097/QAI.0000000000001198
• Languages: English
• ISSNs: 1525-4135

Abstract

Abstract : Background: HIV-1 drug resistance can be measured with phenotypic drug-resistance tests. However, the output of these tests, the resistance factor (RF), requires interpretation with respect to the in vivo activity of the tested variant. Specifically, the dynamic range of the RF for each drug has to be divided into a suitable number of clinically meaningful intervals. Methods: We calculated a susceptible-to-intermediate and an intermediate-to-resistant cutoff per drug for RFs predicted by geno2pheno[resistance] . Probability densities for therapeutic success and failure were estimated from 10, 444 treatment episodes. The density estimation procedure corrects for the activity of the backbone drug compounds and for therapy failure without drug resistance. For estimating the probability of therapeutic success given an RF, we fit a sigmoid function. The cutoffs are given by the roots of the third derivative of the sigmoid function. Results: For performance assessment, we used geno2pheno[resistance] RF predictions and the cutoffs for predicting therapeutic success in 2 independent sets of therapy episodes. HIVdb was used for performance comparison. On one test set (n = 807), our cutoffs and HIVdb performed equally well receiver operating characteristic curve [(ROC)–area under the curve (AUC): 0.68]. On the other test set (n = 917), our cutoffs (ROC–AUC: 0.63) and HIVdb (ROC–AUC: 0.65) performed comparatively well. Conclusions: Our method can be used for calculating clinically relevant cutoffs for (predicted) RFs. The method corrects for the activity of the backbone drug compounds and for therapy failure without drug resistance. Our method's performance is comparable with that of HIVdb. RF cutoffs for the latest version of geno2pheno[resistance] have been estimated with this method. Abstract : Supplemental Digital Content is Available in the Text.