Dataset Information

Implementation and Operational Research: Risk Charts to Guide Targeted HIV-1 Viral Load Monitoring of ART: Development and Validation in Patients From Resource-Limited Settings.

ABSTRACT: BACKGROUND:HIV-1 RNA viral load (VL) testing is recommended to monitor antiretroviral therapy (ART) but not available in many resource-limited settings. We developed and validated CD4-based risk charts to guide targeted VL testing. METHODS:We modeled the probability of virologic failure up to 5 years of ART based on current and baseline CD4 counts, developed decision rules for targeted VL testing of 10%, 20%, or 40% of patients in 7 cohorts of patients starting ART in South Africa, and plotted cutoffs for VL testing on colour-coded risk charts. We assessed the accuracy of risk chart-guided VL testing to detect virologic failure in validation cohorts from South Africa, Zambia, and the Asia-Pacific. RESULTS:In total, 31,450 adult patients were included in the derivation and 25,294 patients in the validation cohorts. Positive predictive values increased with the percentage of patients tested: from 79% (10% tested) to 98% (40% tested) in the South African cohort, from 64% to 93% in the Zambian cohort, and from 73% to 96% in the Asia-Pacific cohort. Corresponding increases in sensitivity were from 35% to 68% in South Africa, from 55% to 82% in Zambia, and from 37% to 71% in Asia-Pacific. The area under the receiver operating curve increased from 0.75 to 0.91 in South Africa, from 0.76 to 0.91 in Zambia, and from 0.77 to 0.92 in Asia-Pacific. CONCLUSIONS:CD4-based risk charts with optimal cutoffs for targeted VL testing maybe useful to monitor ART in settings where VL capacity is limited.

SUBMITTER: Koller M

PROVIDER: S-EPMC5395665 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Publications

Implementation and Operational Research: Risk Charts to Guide Targeted HIV-1 Viral Load Monitoring of ART: Development and Validation in Patients From Resource-Limited Settings.

Koller Manuel M Fatti Geoffrey G Chi Benjamin H BH Keiser Olivia O Hoffmann Christopher J CJ Wood Robin R Prozesky Hans H Stinson Kathryn K Giddy Janet J Mutevedzi Portia P Fox Matthew P MP Law Matthew M Boulle Andrew A Egger Matthias M

Journal of acquired immune deficiency syndromes (1999) 20151101 3

<h4>Background</h4>HIV-1 RNA viral load (VL) testing is recommended to monitor antiretroviral therapy (ART) but not available in many resource-limited settings. We developed and validated CD4-based risk charts to guide targeted VL testing.<h4>Methods</h4>We modeled the probability of virologic failure up to 5 years of ART based on current and baseline CD4 counts, developed decision rules for targeted VL testing of 10%, 20%, or 40% of patients in 7 cohorts of patients starting ART in South Africa ...[more]

PMID: 26470034

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Project description:Background Failing to account for the resources required to successfully implement public health interventions can lead to an underestimation of costs and budget impact, optimistic cost-effectiveness estimates, and ultimately a disconnect between published evidence and public health decision-making. Methods We developed a conceptual framework for assessing implementation costs. We illustrate the use of this framework with case studies involving interventions for tuberculosis and HIV/AIDS in resource-limited settings. Results Costs of implementing public health interventions may be conceptualized as occurring across three phases: design, initiation, and maintenance. In the design phase, activities include developing intervention components and establishing necessary infrastructure (e.g., technology, standard operating procedures). Initiation phase activities include training, initiation of supply chains and quality assurance procedures, and installation of equipment. Implementation costs in the maintenance phase include ongoing technical support, monitoring and evaluation, and troubleshooting unexpected obstacles. Within each phase, implementation costs can be incurred at the site of delivery (“site-specific” costs) or more centrally (“above-service” or “central” costs). For interventions evaluated in the context of research studies, implementation costs should be classified as programmatic, research-related, or shared research/program costs. Purely research-related costs are often excluded from analysis of programmatic implementation. Conclusions In evaluating public health interventions in resource-limited settings, accounting for implementation costs enables more realistic estimates of budget impact and cost-effectiveness and provides important insights into program feasibility, scale-up, and sustainability. Assessment of implementation costs should be planned prospectively and performed in a standardized manner to ensure generalizability.

Project description:IntroductionAccurate measurement of adherence is necessary to ensure that therapeutic outcomes can be attributed to the recommended treatment. Phone-based unannounced pill counts were shown to be feasible and reliable measures of adherence in developed settings; and have been further used as part of medication adherence interventions. However, it is not clear whether this method can be implemented successfully in resource-limited settings, where cellular network and mobile phone coverage may be low. Our objective is to describe operational issues surrounding the use of phone-based unannounced pill counts in Lesotho and Ethiopia.MethodsPhone-based monthly unannounced pill counts, using an adaptation of a standardized protocol from previous US-based studies, were utilized to measure anti-TB and antiretroviral medication adherence in two implementation science studies in resource-limited settings, START (Lesotho) and ENRICH (Ethiopia).ResultsIn START, 19.6% of calls were completed, with 71.9% of participants reached at least once; majority of failed call attempts were due to phones not being available (54.8%) or because participants were away from the pills (32.7%). In ENRICH, 33.5% of calls were completed, with 86.7% of participants reached at least once; the main reasons for failed call attempts were phones being switched off (31.5%), participants not answering (27.3%), participants' discomfort speaking on the phone (15.4%), and network problems (13.2%). Structural, facility-level, participant-level, and data collection challenges were encountered in these settings.DiscussionPhone-based unannounced pill counts were found to be challenging, and response rates suboptimal. While some of these challenges were specific to local contexts, most of them are generalizable to resource-limited settings. In a research study context, a possible solution to ease operational challenges may be to focus phone-based unannounced pill count efforts on a randomly selected sample from participants who are provided with study phones and rigorously ensure that call attempts are made for these participants.

Dataset Information

Implementation and Operational Research: Risk Charts to Guide Targeted HIV-1 Viral Load Monitoring of ART: Development and Validation in Patients From Resource-Limited Settings.

Publications

Implementation and Operational Research: Risk Charts to Guide Targeted HIV-1 Viral Load Monitoring of ART: Development and Validation in Patients From Resource-Limited Settings.

Similar Datasets

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