ArticleJournal of the American Statistical Association2013
Optimal Allocation of Gold Standard Testing under Constrained Availability: Application to Assessment of HIV Treatment Failure.
Article in Journal of the American Statistical Association, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Improved HIV-1 Viral Load Monitoring Capacity Using Pooled Testing With Marker-Assisted Deconvolution.Journal of acquired immune deficiency syndromes (1999) · 2017Pooled it
- Estimation of causal effects of multiple treatments in observational studies with a binary outcome.Statistical methods in medical research · 2020Article
- Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies.Statistics in medicine · 2018Article
- 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.Journal of acquired immune deficiency syndromes (1999) · 2015Article
- Super Learner Analysis of Electronic Adherence Data Improves Viral Prediction and May Provide Strategies for Selective HIV RNA Monitoring.Journal of acquired immune deficiency syndromes (1999) · 2015Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The World Health Organization (WHO) guidelines for monitoring the effectiveness of HIV treatment in resource-limited settings (RLS) are mostly based on clinical and immunological markers (e.g., CD4 cell counts). Recent research indicates that the guidelines are inadequate and can result in high error rates. Viral load (VL) is considered the "gold standard", yet its widespread use is limited by cost and infrastructure. In this paper, we propose a diagnostic algorithm that uses information from routinely-collected clinical and immunological markers to guide a selective use of VL testing for diagnosing HIV treatment failure, under the assumption that VL testing is available only at a certain portion of patient visits. Our algorithm identifies the patient sub-population, such that the use of limited VL testing on them minimizes a pre-defined risk (e.g., misdiagnosis error rate). Diagnostic properties of our proposal algorithm are assessed by simulations. For illustration, data from the Miriam Hospital Immunology Clinic (RI, USA) are analyzed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.