Article open access publication

Improved darunavir genotypic mutation score predicting treatment response for patients infected with HIV-1 subtype B and non-subtype B receiving a salvage regimen

Journal of Antimicrobial Chemotherapy, Oxford University Press (OUP), ISSN 1460-2091

Volume 71, 5, 2016

DOI:10.1093/jac/dkv465, Dimensions: pub.1059736125, PMC: PMC5808835, PMID: 26825119,

Authors

De Luca, Andrea (1) (2)
Reiss, Peter (21) (22)

Affiliations

Organisations

  1. (1) Azienda Ospedaliera Universitaria Senese, grid.411477.0
  2. (2) University of Siena, grid.9024.f
  3. (3) French Institute of Health and Medical Research, grid.7429.8
  4. (4) MRC Clinical Trials Unit, grid.415052.7
  5. (5) University Medical Center Utrecht, grid.7692.a
  6. (6) University of Rome Tor Vergata, grid.6530.0
  7. (7) Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerlandand Institute of Medical Virology, University of Zurich, Zurich, Switzerland
  8. (8) Inserm U897, ISPED, Université de Bordeaux, CHU Bordeaux, France/Cohere in Eurocoord RCC, Bordeaux, France
  9. (9) National and Kapodistrian University of Athens, grid.5216.0
  10. (10) Hospital San Cecilio, Granada, Spain
  11. (11) San Raffaele Hospital, grid.18887.3e
  12. (12) University College London, grid.83440.3b
  13. (13) Brighton and Sussex University Hospitals NHS Trust, grid.410725.5
  14. (14) Centre Hospitalier Universitaire de Saint-Pierre, grid.50545.31
  15. (15) Ruhr University Bochum, grid.5570.7
  16. (16) Bellvitge University Hospital, grid.411129.e
  17. (17) University of Modena and Reggio Emilia, grid.7548.e
  18. (18) Copenhagen University Hospital, grid.4973.9, Capital Region
  19. (19) INMI ‘L. Spallanzani’, Rome, Italy
  20. (20) University of Valencia, grid.5338.d
  21. (21) Stichting HIV Monitoring, Amsterdam, The Netherlands, and Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands/Cohere in Eurocoord RCC, Copenhagen, Denmark
  22. (22) Stichting HIV Monitoring, grid.500326.2
  23. (23) University of Cologne, grid.6190.e
  24. (24) Magna Graecia University, grid.411489.1
  25. (25) University Hospital Innsbruck, grid.410706.4
  26. (26) AP-HP, Hôpital Bichat-Claude Bernard, Laboratoire de Virologie, IAME, UMR_1137, INSERM, Univ Paris Diderot, Sorbonne Paris Cité, Paris, France

Description

OBJECTIVES: The objective of this study was to improve the prediction of the impact of HIV-1 protease mutations in different viral subtypes on virological response to darunavir. METHODS: Darunavir-containing treatment change episodes (TCEs) in patients previously failing PIs were selected from large European databases. HIV-1 subtype B-infected patients were used as the derivation dataset and HIV-1 non-B-infected patients were used as the validation dataset. The adjusted association of each mutation with week 8 HIV RNA change from baseline was analysed by linear regression. A prediction model was derived based on best subset least squares estimation with mutational weights corresponding to regression coefficients. Virological outcome prediction accuracy was compared with that from existing genotypic resistance interpretation systems (GISs) (ANRS 2013, Rega 9.1.0 and HIVdb 7.0). RESULTS: TCEs were selected from 681 subtype B-infected and 199 non-B-infected adults. Accompanying drugs were NRTIs in 87%, NNRTIs in 27% and raltegravir or maraviroc or enfuvirtide in 53%. The prediction model included weighted protease mutations, HIV RNA, CD4 and activity of accompanying drugs. The model's association with week 8 HIV RNA change in the subtype B (derivation) set was R(2) = 0.47 [average squared error (ASE) = 0.67, P < 10(-6)]; in the non-B (validation) set, ASE was 0.91. Accuracy investigated by means of area under the receiver operating characteristic curves with a binary response (above the threshold value of HIV RNA reduction) showed that our final model outperformed models with existing interpretation systems in both training and validation sets. CONCLUSIONS: A model with a new darunavir-weighted mutation score outperformed existing GISs in both B and non-B subtypes in predicting virological response to darunavir.

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Times Cited: 3

Field Citation Ratio (FCR): 0.64

Relative Citation ratio (RCR): 0.28

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