Cargando…

Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis

BACKGROUND: Testing for ‘recent HIV infection’ is common in surveillance, where only population-level estimates (of incidence) are reported. Typically, ‘recent infection’ is a category, obtained by applying a threshold on an underlying continuous biomarker from some laboratory assay(s). Interpreting...

Descripción completa

Detalles Bibliográficos
Autores principales: Sempa, Joseph B., Grebe, Eduard, Welte, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9333292/
https://www.ncbi.nlm.nih.gov/pubmed/35901053
http://dx.doi.org/10.1371/journal.pone.0271763
_version_ 1784758842057293824
author Sempa, Joseph B.
Grebe, Eduard
Welte, Alex
author_facet Sempa, Joseph B.
Grebe, Eduard
Welte, Alex
author_sort Sempa, Joseph B.
collection PubMed
description BACKGROUND: Testing for ‘recent HIV infection’ is common in surveillance, where only population-level estimates (of incidence) are reported. Typically, ‘recent infection’ is a category, obtained by applying a threshold on an underlying continuous biomarker from some laboratory assay(s). Interpreting the biomarker values obtained for individual subjects, as estimates of the date of infection, has obvious potential applications in the context of studies of early infection, and has also for some years attracted significant interest as an extra component of post-test counselling and treatment initiation. The applicable analyses have typically run aground on the complexity of the full biomarker growth model, which is in principle a non-linear mixed-effects model of unknown structure, the fitting of which seems infeasible from realistically obtainable data. METHODS: It is known that to estimate Mean Duration of Recent Infection (MDRI) at a given value of the recent/non-recent -infection discrimination threshold, one may compress the full biomarker growth model into a relation capturing the probability of a recent test result as a function of time t since infection, given a value of assay threshold h which defines the recent/non-recent discrimination. We demonstrate that the derivative (gradient), with respect to h. of the probability of recent infection, seen as a function of both t and h, is identical to the formal likelihood relevant to Bayesian inference of the time since seroconversion, for a subject yielding an assay result h, at or close to the date of their first positive HIV test. This observation bypasses the need for fitting a complex detailed biomarker growth model. Using publicly available data from the CEPHIA collaboration, we calibrated this likelihood function for the Sedia Lag assay, and performed Bayesian inference on hypothetical infection data. RESULTS: We demonstrate the generation of posteriors for infection date, for patients with various delays between their last negative and first positive HIV test, and a range of LAg assay results (ODn) hypothetically obtained on the date of the first positive result. CONCLUSION: Depending on the last-negative / first-positive interval, there is a range of ODn values that yields posteriors significantly different from the uniform prior one would be left with based merely on interval censoring. Hence, a LAg ODn obtained on the date of, or soon after, diagnosis contains potentially significant information about infection dating. It seems worth analysing other assays with meaningful dynamic range, especially tests already routinely used in primary HIV diagnosis (for example chemiluminescent assays and reader/cartridge lateral flow tests which admit objective variable line intensity readings) which have a sufficient dynamic range that corresponds to a clinically meaningful range of times-since-infection that are worth distinguishing from each other.
format Online
Article
Text
id pubmed-9333292
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-93332922022-07-29 Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis Sempa, Joseph B. Grebe, Eduard Welte, Alex PLoS One Research Article BACKGROUND: Testing for ‘recent HIV infection’ is common in surveillance, where only population-level estimates (of incidence) are reported. Typically, ‘recent infection’ is a category, obtained by applying a threshold on an underlying continuous biomarker from some laboratory assay(s). Interpreting the biomarker values obtained for individual subjects, as estimates of the date of infection, has obvious potential applications in the context of studies of early infection, and has also for some years attracted significant interest as an extra component of post-test counselling and treatment initiation. The applicable analyses have typically run aground on the complexity of the full biomarker growth model, which is in principle a non-linear mixed-effects model of unknown structure, the fitting of which seems infeasible from realistically obtainable data. METHODS: It is known that to estimate Mean Duration of Recent Infection (MDRI) at a given value of the recent/non-recent -infection discrimination threshold, one may compress the full biomarker growth model into a relation capturing the probability of a recent test result as a function of time t since infection, given a value of assay threshold h which defines the recent/non-recent discrimination. We demonstrate that the derivative (gradient), with respect to h. of the probability of recent infection, seen as a function of both t and h, is identical to the formal likelihood relevant to Bayesian inference of the time since seroconversion, for a subject yielding an assay result h, at or close to the date of their first positive HIV test. This observation bypasses the need for fitting a complex detailed biomarker growth model. Using publicly available data from the CEPHIA collaboration, we calibrated this likelihood function for the Sedia Lag assay, and performed Bayesian inference on hypothetical infection data. RESULTS: We demonstrate the generation of posteriors for infection date, for patients with various delays between their last negative and first positive HIV test, and a range of LAg assay results (ODn) hypothetically obtained on the date of the first positive result. CONCLUSION: Depending on the last-negative / first-positive interval, there is a range of ODn values that yields posteriors significantly different from the uniform prior one would be left with based merely on interval censoring. Hence, a LAg ODn obtained on the date of, or soon after, diagnosis contains potentially significant information about infection dating. It seems worth analysing other assays with meaningful dynamic range, especially tests already routinely used in primary HIV diagnosis (for example chemiluminescent assays and reader/cartridge lateral flow tests which admit objective variable line intensity readings) which have a sufficient dynamic range that corresponds to a clinically meaningful range of times-since-infection that are worth distinguishing from each other. Public Library of Science 2022-07-28 /pmc/articles/PMC9333292/ /pubmed/35901053 http://dx.doi.org/10.1371/journal.pone.0271763 Text en © 2022 Sempa et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sempa, Joseph B.
Grebe, Eduard
Welte, Alex
Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis
title Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis
title_full Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis
title_fullStr Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis
title_full_unstemmed Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis
title_short Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis
title_sort quantitative interpretation of sedia lag assay test results after hiv diagnosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9333292/
https://www.ncbi.nlm.nih.gov/pubmed/35901053
http://dx.doi.org/10.1371/journal.pone.0271763
work_keys_str_mv AT sempajosephb quantitativeinterpretationofsedialagassaytestresultsafterhivdiagnosis
AT grebeeduard quantitativeinterpretationofsedialagassaytestresultsafterhivdiagnosis
AT weltealex quantitativeinterpretationofsedialagassaytestresultsafterhivdiagnosis