Statistical Methods for Adherence Issues in HIV Prevention Research
Statistical Methods for Adherence Issues in HIV Prevention Research
批准号:
9292248
负责人:
Ying Qing Chen
金额:
$63.27万
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-07-02 至 2019-06-30
关键词:
AIDS preventionAddressAdherenceAgreementBehavior TherapyBiologicalClinicalClinical TrialsComputer softwareCoupledCouplesDataData AnalysesData CollectionEffectivenessElectronic drug monitoringFumaratesGoalsGoldHIVHIV InfectionsHIV vaccineHealthIncidenceIndividualIntentionKenyaLinear RegressionsMeasuresMediationMediator of activation proteinMethodologyMethodsModelingMonitorOralOral MedicineParticipantPatient Self-ReportPatternPharmaceutical PreparationsPharmacy facilityPlasmaPopulationPopulation Attributable RisksPopulations at RiskPreventionPrevention ResearchPrevention trialPreventive InterventionProceduresPublic HealthRegimenResearch DesignResearch PersonnelRiskRoleSamplingStatistical MethodsTenofovirTestingTimeTranslational ResearchTreatment EfficacyUgandaWomanclinical careclinical practicecost effectivedesigndrug testingemtricitabineflexibilityimprovedinnovationinstrumentmathematical modelmen who have sex with menpillpre-exposure prophylaxispreventpublic health relevancesocialstandard measurestudy populationsuccesstime usetool
中文摘要
英文摘要
DESCRIPTION (provided by applicant): Recent advances in biomedical prevention intervention, e.g., Treatment as Prevention (TasP) and Pre‐ Exposure Prophylaxis (PrEP), have changed how HIV prevention is conceptualized and implemented, while effective HIV vaccine is yet to be developed. For a biological HIV prevention regimen, mostly likely in oral medicine, to be effective, users' adherence to the prescribed regimen is critical. Imperfect adherence reduces the regimen's effectiveness, and also makes it difficult to assess the regimen's efficacy in clinical trial settings. There are various instruments used in clinical practce for researchers trying to measure the adherence. Since each of these instruments has its limitations, we have realized that there is a serious lack of systematic statistical methods, being
flexible and reliable to the different data collection procedures. To address the need, in this application we aim to 1) develop consistent statistical measures that can capture different longitudinal adherence patterns; 2) develop statistical methods to infer the true adherence pattern using data from different measuring instruments; 3) develop statistical methods to detect and analyze the association between the adherence patterns and the level of protection from HIV acquisition; 4) develop a statistical/mathematical modeling framework to predict the population impact of adherence improvement on a population's overall HIV incidence reduction. Upon the completion of this project, an innovative, useful and easy‐to‐implement set of statistical tools and software will be developed for assessing, analyzing and improving adherence in HIV prevention research.
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