Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comparative Study
. 2016 Feb;88(2):234-43.
doi: 10.1002/jmv.24320. Epub 2015 Jul 17.

Comparison of genotypic and virtual phenotypic drug resistance interpretations with laboratory-based phenotypes among CRF01_AE and subtype B HIV-infected individuals

Awachana Jiamsakul  1 , Romanee Chaiwarith  2 , Nicolas Durier  3 , Sunee Sirivichayakul  4 , Sasisopin Kiertiburanakul  5 , Peter Van Den Eede  6 , Rossana Ditangco  7 , Adeeba Kamarulzaman  8 , Patrick C K Li  9 , Winai Ratanasuwan  10 , Thira Sirisanthana  2 ; TREAT Asia Studies to Evaluate Resistance--Monitoring Study TASER-M
Collaborators, Affiliations
Comparative Study

Comparison of genotypic and virtual phenotypic drug resistance interpretations with laboratory-based phenotypes among CRF01_AE and subtype B HIV-infected individuals

Awachana Jiamsakul et al. J Med Virol. 2016 Feb.

Abstract

HIV drug resistance assessments and interpretations can be obtained from genotyping (GT), virtual phenotyping (VP) and laboratory-based phenotyping (PT). We compared resistance calls obtained from GT and VP with those from PT (GT-PT and VP-PT) among CRF01_AE and subtype B HIV-1 infected patients. GT predictions were obtained from the Stanford HIV database. VP and PT were obtained from Janssen Diagnostics BVBA's vircoType(TM) HIV-1 and Antivirogram®, respectively. With PT assumed as the "gold standard," the area under the curve (AUC) and the Bland-Altman plot were used to assess the level of agreement in resistance interpretations. A total of 80 CRF01_AE samples from Asia and 100 subtype B from Janssen Diagnostics BVBA's database were analysed. CRF01_AE showed discordances ranging from 3 to 27 samples for GT-PT and 1 to 20 samples for VP-PT. The GT-PT and VP-PT AUCs were 0.76-0.97 and 0.81-0.99, respectively. Subtype B showed 3-61 discordances for GT-PT and 2-75 discordances for VP-PT. The AUCs ranged from 0.55 to 0.95 for GT-PT and 0.55 to 0.97 for VP-PT. Didanosine had the highest proportion of discordances and/or AUC in all comparisons. The patient with the largest didanosine FC difference in each subtype harboured Q151M mutation. Overall, GT and VP predictions for CRF01_AE performed significantly better than subtype B for three NRTIs. Although discrepancies exist, GT and VP resistance interpretations in HIV-1 CRF01_AE strains were highly robust in comparison with the gold-standard PT.

Keywords: algorithm; drug resistance; subtype.

PubMed Disclaimer

Conflict of interest statement

Conflicts of interest

PVDE is a full-time employee of Janssen Diagnostics BVBA, though no commercial interest is affiliated to the services provided.

All other authors declared no conflicts of interest.

Figures

Figure 1
Figure 1
Bland-Altman plot for didanosine for the comparison of laboratory-based phenotyping Fold Change values (PT FC) with virtual phenotyping Fold Change values (VP FC) for (a) HIV-1 CRF01_AE and (b) HIV-1 subtype B infected persons. A point above 0 on the vertical axis suggests that the FC obtained from PT is higher than the predicted FC from VP, whereas a point below 0 indicates the predicted VP FC is higher. 95% CI – 95% confidence interval.
See this image and copyright information in PMC

References

    1. Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Department of Health and Human Services;
    1. Altman DG, Bland JM. Measurement in medicine: the analysis of method comparison studies. The Statistician. 1983;32:307–317.
    1. Angelis K, Albert J, Mamais I, Magiorkinis G, Hatzakis A, Hamouda O, Struck D, Vercauteren J, Wensing AM, Alexiev I, Asjo B, Balotta C, Camacho RJ, Coughlan S, Griskevicius A, Grossman Z, Horban A, Kostrikis LG, Lepej S, Liitsola K, Linka M, Nielsen C, Otelea D, Paredes R, Poljak M, Puchhammer-Stockl E, Schmit JC, Sonnerborg A, Stanekova D, Stanojevic M, Boucher CA, Kaplan L, Vandamme AM, Paraskevis D. Global Dispersal Pattern of HIV Type 1 Subtype CRF01_AE: A Genetic Trace of Human Mobility Related to Heterosexual Sexual Activities Centralized in Southeast Asia. J Infect Dis. 2015;211(11):1735–1744. - PubMed
    1. Bennett DE, Camacho RJ, Otelea D, Kuritzkes DR, Fleury H, Kiuchi M, Heneine W, Kantor R, Jordan MR, Schapiro JM, Vandamme AM, Sandstrom P, Boucher CA, van de Vijver D, Rhee SY, Liu TF, Pillay D, Shafer RW. Drug resistance mutations for surveillance of transmitted HIV-1 drug-resistance: 2009 update. PLoS One. 2009;4(3):e4724. - PMC - PubMed
    1. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307–310. - PubMed

Publication types

Substances