BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

158 related articles for article (PubMed ID: 20634893)

  • 1. Comparison of HIV-1 genotypic resistance test interpretation systems in predicting virological outcomes over time.
    Frentz D; Boucher CA; Assel M; De Luca A; Fabbiani M; Incardona F; Libin P; Manca N; Müller V; O Nualláin B; Paredes R; Prosperi M; Quiros-Roldan E; Ruiz L; Sloot PM; Torti C; Vandamme AM; Van Laethem K; Zazzi M; van de Vijver DA
    PLoS One; 2010 Jul; 5(7):e11505. PubMed ID: 20634893
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Rules-based HIV-1 genotypic resistance interpretation systems predict 8 week and 24 week virological antiretroviral treatment outcome and benefit from drug potency weighting.
    Zazzi M; Prosperi M; Vicenti I; Di Giambenedetto S; Callegaro A; Bruzzone B; Baldanti F; Gonnelli A; Boeri E; Paolini E; Rusconi S; Giacometti A; Maggiolo F; Menzo S; De Luca A;
    J Antimicrob Chemother; 2009 Sep; 64(3):616-24. PubMed ID: 19620134
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Clinical evaluation of Rega 8: an updated genotypic interpretation system that significantly predicts HIV-therapy response.
    Vercauteren J; Beheydt G; Prosperi M; Libin P; Imbrechts S; Camacho R; Clotet B; De Luca A; Grossman Z; Kaiser R; Sönnerborg A; Torti C; Van Wijngaerden E; Schmit JC; Zazzi M; Geretti AM; Vandamme AM; Van Laethem K
    PLoS One; 2013; 8(4):e61436. PubMed ID: 23613852
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Construction, training and clinical validation of an interpretation system for genotypic HIV-1 drug resistance based on fuzzy rules revised by virological outcomes.
    De Luca A; Vendittelli M; Baldini F; Di Giambenedetto S; Trotta MP; Cingolani A; Bacarelli A; Gori C; Perno CF; Antinori A; Ulivi G
    Antivir Ther; 2004 Aug; 9(4):583-93. PubMed ID: 15456090
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Modelled in vivo HIV fitness under drug selective pressure and estimated genetic barrier towards resistance are predictive for virological response.
    Deforche K; Cozzi-Lepri A; Theys K; Clotet B; Camacho RJ; Kjaer J; Van Laethem K; Phillips A; Moreau Y; Lundgren JD; Vandamme AM;
    Antivir Ther; 2008; 13(3):399-407. PubMed ID: 18572753
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Improved darunavir genotypic mutation score predicting treatment response for patients infected with HIV-1 subtype B and non-subtype B receiving a salvage regimen.
    De Luca A; Flandre P; Dunn D; Zazzi M; Wensing A; Santoro MM; Günthard HF; Wittkop L; Kordossis T; Garcia F; Castagna A; Cozzi-Lepri A; Churchill D; De Wit S; Brockmeyer NH; Imaz A; Mussini C; Obel N; Perno CF; Roca B; Reiss P; Schülter E; Torti C; van Sighem A; Zangerle R; Descamps D;
    J Antimicrob Chemother; 2016 May; 71(5):1352-60. PubMed ID: 26825119
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Similar predictions of etravirine sensitivity regardless of genotypic testing method used: comparison of available scoring systems.
    Vingerhoets J; Nijs S; Tambuyzer L; Hoogstoel A; Anderson D; Picchio G
    Antivir Ther; 2012; 17(8):1571-9. PubMed ID: 22869341
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Baseline resistance and virological outcome in patients with virological failure who start a regimen containing abacavir: EuroSIDA study.
    Cabrera C; Cozzi-Lepri A; Phillips AN; Loveday C; Kirk O; Ait-Khaled M; Reiss P; Kjaer J; Ledergerber B; Lundgren JD; Clotet B; Ruiz L;
    Antivir Ther; 2004 Oct; 9(5):787-800. PubMed ID: 15535417
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Clinically relevant thresholds for ultrasensitive HIV drug resistance testing: a multi-country nested case-control study.
    Inzaule SC; Hamers RL; Noguera-Julian M; Casadellà M; Parera M; Kityo C; Steegen K; Naniche D; Clotet B; Rinke de Wit TF; Paredes R;
    Lancet HIV; 2018 Nov; 5(11):e638-e646. PubMed ID: 30282603
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A comparison of three computational modelling methods for the prediction of virological response to combination HIV therapy.
    Wang D; Larder B; Revell A; Montaner J; Harrigan R; De Wolf F; Lange J; Wegner S; Ruiz L; Pérez-Elías MJ; Emery S; Gatell J; D'Arminio Monforte A; Torti C; Zazzi M; Lane C
    Artif Intell Med; 2009 Sep; 47(1):63-74. PubMed ID: 19524413
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Improved prediction of salvage antiretroviral therapy outcomes using ultrasensitive HIV-1 drug resistance testing.
    Pou C; Noguera-Julian M; Pérez-Álvarez S; García F; Delgado R; Dalmau D; Álvarez-Tejado M; Gonzalez D; Sayada C; Chueca N; Pulido F; Ibáñez L; Rodríguez C; Casadellà M; Santos JR; Ruiz L; Clotet B; Paredes R
    Clin Infect Dis; 2014 Aug; 59(4):578-88. PubMed ID: 24879788
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Interpretation of genotypic HIV-1 resistance to darunavir and virological response: validation of available systems and of a new score.
    De Luca A; Di Giambenedetto S; Maserati R; Gianotti N; Narciso P; Antinori A; Di Perri G; Prosperi MC; Baldanti F; Micheli V; Zazzi M; Perno CF; Santoro MM; ;
    Antivir Ther; 2011; 16(4):489-97. PubMed ID: 21685536
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Algorithm evolution for drug resistance prediction: comparison of systems for HIV-1 genotyping.
    Wagner S; Kurz M; Klimkait T;
    Antivir Ther; 2015; 20(6):661-5. PubMed ID: 25710167
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Baseline HIV-1 resistance, virological outcomes, and emergent resistance in the SECOND-LINE trial: an exploratory analysis.
    Boyd MA; Moore CL; Molina JM; Wood R; Madero JS; Wolff M; Ruxrungtham K; Losso M; Renjifo B; Teppler H; Kelleher AD; Amin J; Emery S; Cooper DA;
    Lancet HIV; 2015 Feb; 2(2):e42-51. PubMed ID: 26424460
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Investigation of expert rule bases, logistic regression, and non-linear machine learning techniques for predicting response to antiretroviral treatment.
    Prosperi MC; Altmann A; Rosen-Zvi M; Aharoni E; Borgulya G; Bazso F; Sönnerborg A; Schülter E; Struck D; Ulivi G; Vandamme AM; Vercauteren J; Zazzi M;
    Antivir Ther; 2009; 14(3):433-42. PubMed ID: 19474477
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A genotypic drug resistance interpretation algorithm that significantly predicts therapy response in HIV-1-infected patients.
    Van Laethem K; De Luca A; Antinori A; Cingolani A; Perna CF; Vandamme AM
    Antivir Ther; 2002 Jun; 7(2):123-9. PubMed ID: 12212924
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Variability in the interpretation of transmitted genotypic HIV-1 drug resistance and prediction of virological outcomes of the initial HAART by distinct systems.
    De Luca A; Cozzi-Lepri A; Perno CF; Balotta C; Di Giambenedetto S; Poggio A; Pagano G; Tositti G; Piscopo R; Del Forno A; Chiodo F; Magnani G; d'Arminio Monforte A; ;
    Antivir Ther; 2004 Oct; 9(5):743-52. PubMed ID: 15535412
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Identification of new genotypic cut-off levels to predict the efficacy of lopinavir/ritonavir and darunavir/ritonavir in the TITAN trial.
    Hill A; Marcelin AG; Calvez V
    HIV Med; 2009 Nov; 10(10):620-6. PubMed ID: 19601995
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Computational models can predict response to HIV therapy without a genotype and may reduce treatment failure in different resource-limited settings.
    Revell AD; Wang D; Wood R; Morrow C; Tempelman H; Hamers RL; Alvarez-Uria G; Streinu-Cercel A; Ene L; Wensing AM; DeWolf F; Nelson M; Montaner JS; Lane HC; Larder BA;
    J Antimicrob Chemother; 2013 Jun; 68(6):1406-14. PubMed ID: 23485767
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Initiatives for developing and comparing genotype interpretation systems: external validation of existing rule-based interpretation systems for abacavir against virological response.
    Cozzi-Lepri A;
    HIV Med; 2008 Jan; 9(1):27-40. PubMed ID: 18199170
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.