Comparative evaluation of three algorithm interpretations of human immunofaction virus (HIV-1) in antiretroic treatment

Postgraduate Thesis uoadl:2867536 534 Read counter

Unit:
Κατεύθυνση Διαχείριση και Οικονομική Αποτίμηση
Library of the School of Health Sciences
Deposit date:
2019-04-09
Year:
2019
Author:
Zhivinaqi Anduela
Supervisors info:
Καντζανού Μαρία, Επίκουρη Καθηγήτρια, Ιατρική Σχολή, ΕΚΠΑ
Ψαλτοπούλου Θεοδώρα, Αναπληρώτρια Καθηγήτρια, Ιατρική Σχολή, ΕΚΠΑ
Ελένη Ριζά, ΕΔΙΠ, Ιατρική Σχολή, ΕΚΠΑ
Original Title:
Συγκριτική αξιολόγηση τριών αλγορίθμων ερμηνείας γονοτυπικής αντοχής του ιού της ανοσοεπάρκειας του ανθρώπου (HIV-1) σε αντιρετροϊκή θεραπεία
Languages:
Greek
Translated title:
Comparative evaluation of three algorithm interpretations of human immunofaction virus (HIV-1) in antiretroic treatment
Summary:
Introduction: The HIV virus due to the genetic heterogeneity presents the ability to develop resistance to antiretroviral drugs. This ability is perfectly linked to the appearance of mutations in the genes encoding the target proteins. The correlation of these mutations with the patient's response to treatment is often quite difficult to assess, making the interpretation of genotypic resistance results in antiretroviral drugs the major limitation. Due to this limitation, groups of genotypic resistance interpretation algorithms have been created based on both bibliographic data and clinical studies.
Objective: The aim of the study is to evaluate and compare resistance levels and response to antiretroviral therapy through three available algorithms, REGA, ANRS and the proprietary algorithm of the commercially available VIROSEQ database.
Methods: Genotypic resistance data from 120 HIV-1 infection patients were interpreted for 19 antiretroviral drugs with 3 algorithms.
Results: Complete concordant results among the 3 algorithms for all the drugs studied were found in 2/19 drugs: lamivudine (3TC) and emptricitabine (FTC). The rest medicines presented discrepancies. In pair-wise comparisons the REGA and VIROSEQ algorithms showed the highest Cohen’s Kappa agreement (K = 0.701). In addition, low concordance in interpretation was observed for more protease inhibitors (PIs), while results agreed highly for reverse transcriptase inhibitors (NRTIs).
Conclusions: This work demonstrates the difficulty of interpreting the results of the genotype, making it imperative to update the algorithms. In addition, the scientific community is needed to achieve a consensus for the interpretation of genotypic data.
Main subject category:
Health Sciences
Keywords:
HIV, Genotypic resistance, Antiretroviral drugs, REGA, ANRS, VIROSEQ
Index:
No
Number of index pages:
0
Contains images:
Yes
Number of references:
50
Number of pages:
144
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