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Determination of Phenotypic Resistance Cutoffs From Routine Clinical Data.

Determination of Phenotypic Resistance Cutoffs From Routine Clinical Data.
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Pironti A, Walter H, Pfeifer N, Knops E, Lübke N, Büch J, Di Giambenedetto S, Kaiser R, Lengauer T, ,


Pironti A, Walter H, Pfeifer N, Knops E, Lübke N, Büch J, Di Giambenedetto S, Kaiser R, Lengauer T, , (click to view)

Pironti A, Walter H, Pfeifer N, Knops E, Lübke N, Büch J, Di Giambenedetto S, Kaiser R, Lengauer T, ,

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Journal of acquired immune deficiency syndromes (1999) 74(5) e129-e137 doi 10.1097/QAI.0000000000001198

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.

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