Using electronic methods of adherence monitoring and therapeutic drug monitoring (TDM) to eliminate discordance between antiretroviral adherence and virological failure

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dc.contributor.advisorWood, Robinen_ZA
dc.contributor.advisorMaartens, Garyen_ZA
dc.contributor.authorOrrell, Catherineen_ZA
dc.date.accessioned2016-07-14T12:22:26Z
dc.date.available2016-07-14T12:22:26Z
dc.date.issued2016en_ZA
dc.description.abstractBackground: Adherence to antiretroviral therapy (ART) is critical: only 70% achieve viral suppression at a year. Current adherence methodologies, with slow reaction to missed dosing, inadequately predict virological outcomes. Ideal adherence methods would be cheap, easy to use, and allow rapid response to missed doses to improve outcomes. We explored ideal adherence monitoring methodology for a large public sector ART clinic in Cape Town. Methods: We designed a randomised controlled study for ART-naïve individuals to determine whether text messaging after a missed dose would improve adherence recorded by an electronic adherence monitoring device (EAMD), reduce treatment interruptions or impact on virological outcome (using regression modelling). Five other measures of adherence were captured prospectively during the study: selfrecall (SR), clinic-based pill count (CPC), pharmacy refill data (PR-average or PR-gaps) and efavirenz concentration. The predictive value of each adherence methodology on virological and HIV-1 resistance outcomes was compared by calculating the area under the receiver operating characteristic curve, from logistic regression models. The impact of efavirenz concentration and CYP2B6 metaboliser genotype data on failure was examined using Cox proportion hazard modelling; and the most predictive lower limit for EFV concentration was determined. Antiretroviral cohort and pharmacy refill data were compared, using simple statistics, to determine which provided the best method of determining those retained in care.en_ZA
dc.identifier.apacitationOrrell, C. (2016). <i>Using electronic methods of adherence monitoring and therapeutic drug monitoring (TDM) to eliminate discordance between antiretroviral adherence and virological failure</i>. (Thesis). University of Cape Town ,Faculty of Health Sciences ,Department of Medicine. Retrieved from http://hdl.handle.net/11427/20349en_ZA
dc.identifier.chicagocitationOrrell, Catherine. <i>"Using electronic methods of adherence monitoring and therapeutic drug monitoring (TDM) to eliminate discordance between antiretroviral adherence and virological failure."</i> Thesis., University of Cape Town ,Faculty of Health Sciences ,Department of Medicine, 2016. http://hdl.handle.net/11427/20349en_ZA
dc.identifier.citationOrrell, C. 2016. Using electronic methods of adherence monitoring and therapeutic drug monitoring (TDM) to eliminate discordance between antiretroviral adherence and virological failure. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Orrell, Catherine AB - Background: Adherence to antiretroviral therapy (ART) is critical: only 70% achieve viral suppression at a year. Current adherence methodologies, with slow reaction to missed dosing, inadequately predict virological outcomes. Ideal adherence methods would be cheap, easy to use, and allow rapid response to missed doses to improve outcomes. We explored ideal adherence monitoring methodology for a large public sector ART clinic in Cape Town. Methods: We designed a randomised controlled study for ART-naïve individuals to determine whether text messaging after a missed dose would improve adherence recorded by an electronic adherence monitoring device (EAMD), reduce treatment interruptions or impact on virological outcome (using regression modelling). Five other measures of adherence were captured prospectively during the study: selfrecall (SR), clinic-based pill count (CPC), pharmacy refill data (PR-average or PR-gaps) and efavirenz concentration. The predictive value of each adherence methodology on virological and HIV-1 resistance outcomes was compared by calculating the area under the receiver operating characteristic curve, from logistic regression models. The impact of efavirenz concentration and CYP2B6 metaboliser genotype data on failure was examined using Cox proportion hazard modelling; and the most predictive lower limit for EFV concentration was determined. Antiretroviral cohort and pharmacy refill data were compared, using simple statistics, to determine which provided the best method of determining those retained in care. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - Using electronic methods of adherence monitoring and therapeutic drug monitoring (TDM) to eliminate discordance between antiretroviral adherence and virological failure TI - Using electronic methods of adherence monitoring and therapeutic drug monitoring (TDM) to eliminate discordance between antiretroviral adherence and virological failure UR - http://hdl.handle.net/11427/20349 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/20349
dc.identifier.vancouvercitationOrrell C. Using electronic methods of adherence monitoring and therapeutic drug monitoring (TDM) to eliminate discordance between antiretroviral adherence and virological failure. [Thesis]. University of Cape Town ,Faculty of Health Sciences ,Department of Medicine, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/20349en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Medicineen_ZA
dc.publisher.facultyFaculty of Health Sciencesen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherInfectious Disease and Molecular Medicineen_ZA
dc.subject.otherMonitoringen_ZA
dc.titleUsing electronic methods of adherence monitoring and therapeutic drug monitoring (TDM) to eliminate discordance between antiretroviral adherence and virological failureen_ZA
dc.typeDoctoral Thesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnamePhDen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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