Computational models can predict response to HIV therapy without a genotype and may reduce treatment failure in different resource-limited settings

Journal of Antimicrobial Chemotherapy

Volumn 68, Issue 6, 2013, Pages 1406-1414

  Revell, A D ^a   Wang, D ^a   Wood, R ^b   Morrow, C ^b   Tempelman, H ^c   Hamers, R L ^d   Alvarez Uria, G ^e   Streinu Cercel, A ^f   Ene, L ^g   Wensing, A M J ^h   DeWolf, F ⁱ   Nelson, M ^j   Montaner, J S ^k   Lane, H C ^l   Larder, B A ^a  

^a HIV Resistance Response Database Initiative (RDI)   (United Kingdom)

^b Institute of Infectious Disease and Molecular Medicine   (South Africa)

^c NDLOVU CARE GROUP   (South Africa)

^d ACADEMIC MEDICAL CENTER   (Netherlands)

^e Rural Development Trust (RDT) Hospital   (India)

^f National Institute of Infectious Diseases 'Prof Dr Matei Bals'   (Romania)

^g VICTOR BABES NATIONAL INSTITUTE OF PATHOLOGY   (Romania)

^h UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

ⁱ STICHTING HIV MONITORING   (Netherlands)

^j CHELSEA AND WESTMINSTER HOSPITAL   (United Kingdom)

^k BRITISH COLUMBIA CENTRE FOR EXCELLENCE IN HIV AIDS   (Canada)

^l NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES   (United States)

more..

Author keywords

Antiretroviral therapy; Computer models; HIV drug resistance; Predictions; Resource limited settings; Treatment outcomes

Indexed keywords

HUMAN IMMUNODEFICIENCY VIRUS FUSION INHIBITOR; INTEGRASE INHIBITOR; NONNUCLEOSIDE REVERSE TRANSCRIPTASE INHIBITOR; PROTEINASE INHIBITOR; RNA DIRECTED DNA POLYMERASE INHIBITOR;

ACCURACY; ADULT; AREA UNDER THE CURVE; ARTICLE; CD4 LYMPHOCYTE COUNT; COMPUTER ANALYSIS; DRUG TREATMENT FAILURE; FEMALE; GENOTYPE; HIGHLY ACTIVE ANTIRETROVIRAL THERAPY; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; INDIA; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL MODEL; OUTCOME ASSESSMENT; PREDICTION; RANDOM FOREST; ROMANIA; SOUTH AFRICA; TREATMENT RESPONSE; VIRUS LOAD;

ANTIRETROVIRAL THERAPY; COMPUTER MODELS; HIV DRUG RESISTANCE; PREDICTIONS; RESOURCE-LIMITED SETTINGS.; TREATMENT OUTCOMES;

ADULT; AFRICA SOUTH OF THE SAHARA; ANTI-HIV AGENTS; COMPUTER SIMULATION; DATABASES, FACTUAL; FEMALE; FOLLOW-UP STUDIES; HEALTH RESOURCES; HIV; HIV INFECTIONS; HIV PROTEASE INHIBITORS; HUMANS; INDIA; MALE; MIDDLE AGED; MODELS, STATISTICAL; PREDICTIVE VALUE OF TESTS; REVERSE TRANSCRIPTASE INHIBITORS; ROC CURVE; ROMANIA; TREATMENT FAILURE; VIRAL LOAD;

EID: 84885165650     PISSN: 03057453     EISSN: 14602091     Source Type: Journal    
DOI: 10.1093/jac/dkt041     Document Type: Article

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