Improved HIV-1 incidence estimates using the BED capture enzyme immunoassay

Hargrove, John W.; Humphrey, Jean H.; Mutasa, Kuda; Parekh, Bharat; McDougal, J S; Ntozini, Robert; Chidawanyika, Henry; Moulton, Lawrence H.; Ward, Brian J.; Nathoo, Kusum; Iliff, Peter; Kopp, Ekkehard

doi:10.1097/qad.0b013e3282f2a960

Cited by 133 publications

(210 citation statements)

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“…[15][16][17] With some simplifying assumptions (which are often not numerically catastrophic) it has been shown how this ''false-recent'' phenomenon can be intuitively understood as requiring a ''subtraction'' of the estimated number of ''falserecent'' results from the observed number of ''recent'' results. [18][19][20][21] More recently, a very general analysis has been obtained by introducing a convenience recency time cut-off, T (presumed to be 1 year for the purposes of model scenarios throughout this article), which represents the time, postinfection, after which a ''recent'' test result is a ''false-recent'' result. 21 The test properties then are (1) a false-recent rate, b T , which is the (population-dependent) proportion of those individuals infected for more than time T who produce ''recent'' test results, and (2) a somewhat subtly defined mean duration of recent infection, U T , which is the average time spent ''recently'' infected while infected for less than T. 21 Note that 1 -b T is the (population-dependent) specificity of the test if it aimed to identify infections that have occurred within the preceding period T. This leads to the following incidence estimator 21 :…”

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confidence: 99%

Short Communication: Defining Optimality of a Test for Recent Infection for HIV Incidence Surveillance

Kassanjee

McWalter²,

Welte³

2014

AIDS Research and Human Retroviruses

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The estimation of HIV incidence from cross-sectional surveys using tests for recent infection has attracted much interest. It is increasingly recognized that the lack of high performance recent infection tests is hindering the implementation of this surveillance approach. With growing funding opportunities, test developers are currently trying to fill this gap. However, there is a lack of consensus and clear guidance for developers on the evaluation and optimization of candidate tests. A fundamental shift from conventional thinking about test performance is needed: away from metrics relevant in typical public health settings where the detection of a condition in individuals is of primary interest (sensitivity, specificity, and predictive values) and toward metrics that are appropriate when estimating a population-level parameter such as incidence (accuracy and precision). The inappropriate use of individual-level diagnostics performance measures could lead to spurious assessments and suboptimal designs of tests for incidence estimation. In some contexts, such as population-level application to HIV incidence, bias of estimates is essentially negligible, and all that remains is the maximization of precision. The maximization of the precision of incidence estimates provides a completely general criterion for test developers to assess and optimize test designs. Summarizing the test dynamics into the properties relevant for incidence estimation, high precision estimates are obtained when (1) the mean duration of recent infection is large, and (2) the false-recent rate is small. The optimal trade-off between these two test properties will produce the highest precision, and therefore the most epidemiologically useful incidence estimates. T he measurement of HIV incidence, the rate of new infections, is essential in most surveillance and intervention contexts. Recognizing the practical challenges presented by longitudinal studies, the estimation of incidence from cross-sectional surveys using tests for recent infection has attracted considerable interest.1-7 However, the performance, characterization, and optimization of a test that aims to categorize infections as ''recent'' or ''nonrecent,'' specifically for population-level surveillance, requires a shift from conventional diagnostic thinking about test performance.When individual-level detection of a condition is of primary interest, sensitivity, specificity, and predictive values are appropriate metrics of performance. These metrics improve as intersubject variability decreases. However, when estimating a population-level summary parameter, such as incidence, the appropriate performance metrics are accuracy and precision of the statistic measured. Biomarker-based cross-sectional incidence estimation utilizes information on the average behavior of biomarkers, and is relatively insensitive to the variability underlying this averaging. While the appropriate optimization of tests for recent infection has been noted in passing, [3][4][5][6][7] there is neither co...

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mentioning

confidence: 99%

Short Communication: Defining Optimality of a Test for Recent Infection for HIV Incidence Surveillance

Kassanjee

McWalter²,

Welte³

2014

AIDS Research and Human Retroviruses

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“…Similar results were obtained for the two Santa Catarina cities, that presented an overall incidence estimate of 2.6 persons/year (95%CI: ±0.8) 56 , in a virological scenario where subtype C predominates. Considering the WHO criticisms 30 about the sensitivity and specificity of the BED-CEIA to estimate HIV incidence in epidemiological scenarios including non-B HIV-1 subtypes, in a preliminary study we proposed a criterion based on the matching results of two assays (BED-CEIA and Avidity index) aiming to improve the accuracy of these serological approaches to estimate HIV incidence rates 57 .…”

Section: Application Of Serological Methods To Estimate Hiv-1 Incidenmentioning

confidence: 99%

“…Among other studies, an unexpectedly high incidence of 6.1%/year 95%CI: 4.2-8.0 was observed in Masaka and 6.0%/year (95%CI: 4.3-7.7) in Kakira, Uganda, while prospective incidence data in Masaka from the same population were found to be 1.7%/year before and 1.4%/year after the study 28 . In order to improve the accuracy of this method, different types of adjustments have been suggested and will be discussed further in this article 29,30 .…”

Section: Bed-ceia •mentioning

confidence: 99%

“…Due to concerns about studies based on the use of BED-CEIA, conducted in scenarios with high HIV prevalence and/or viral diversity 27 , different adjustments have been proposed aiming to improve its accuracy for HIV estimates. One such adjustment proposes "the exclusion of certain specimens on clinical grounds, by relying on trend differences rather than absolute incidence estimates, by secondary confirmatory testing, or by analytic adjustments for misclassification" 29 (p. 945) and a second strategy adjusts some parameters, with "further estimates of epsilon and of the window period", in order to avoid misclassification of subtype C infected individuals 30 (p. 511).…”

Section: Final Remarksmentioning

confidence: 99%

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Estimates of HIV-1 incidence based on serological methods: a brief methodological review

Morgado

Bastos

2011

Cad. Saúde Pública

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The paper reviews the serological methods employed in the estimation of HIV incidence based on cross-sectional studies, as well as the main findings from studies carried out in Brazil that have used such methods. Each method is briefly described, as well as their advantages and limitations. The different methods are also analyzed as a set of complementary but sometimes contradictory strategies under permanent criticism and review, still far from a gold standard. Finally, an additional question % central to the accurate monitoring of the AIDS epidemic using such methods % is discussed: whether the different methods should or should not be adjusted. The debate is open and controversy should be viewed as an unavoidable consequence of a very dynamic research field, informed by the progress in sciences as diverse as epidemiology, biostatistics, mathematical modeling and different branches of basic science, such as immunology, virology, and molecular biology.

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“…The BED, a commercial enzyme immunoassay (EIA) used by the US CDC, detects the proportion of anti-HIV IgG present in a specimen relative to the total amount of IgG, which is an indicator of disease progression and provides an estimate of the time period since seroconversion [49,50]. Avidity is a measure of the affinity between antibodies and their antigens, the strength of which increases over time as the antibodies mature [51].…”

Section: Estimating Incident Infection Ratesmentioning

confidence: 99%

HIV Diagnostics: Challenges and Opportunities

Wong

Hewlett

2010

HIV Ther.

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Accurate HIV diagnostic testing continues to pose challenges, but there are also opportunities for assay performance improvements in key areas for specific intended-use settings. The genetic diversity of HIV can result in false and discordant results in assays that fail to detect new variant strains. The use of antiretroviral therapies has resulted in drug-resistant variants that require monitoring by sequencing and genotyping methods. Nucleic acid testing is the most sensitive and reliable platform for detection, but it is costly and limited to centralized testing facilities, making implementation difficult in resource-limited settings where HIV has hit the hardest. Rapid antibody tests suitable for point-of-care use are becoming more accessible in resource-limited settings, but these tests may not detect HIV during the acute infection stage. Emerging antigen/antibody combination assays are viable alternatives to nucleic acid testing for diagnosis of recent infections. Although patient monitoring (e.g., via CD4+ T-cell count and viral load determination) and infant diagnoses still rely on clinical laboratory-based testing, point-of-care options are being developed. There are other technical challenges to HIV diagnostic testing and emerging biodetection technologies that may be able to address them, but they are not yet proven.

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Improved HIV-1 incidence estimates using the BED capture enzyme immunoassay

Abstract: The BED method can be used in an African setting, but further estimates of epsilon and of the window period are required, using large samples in a variety of circumstances, before its general utility can be gauged.

Cited by 133 publications

References 9 publications

Short Communication: Defining Optimality of a Test for Recent Infection for HIV Incidence Surveillance

Short Communication: Defining Optimality of a Test for Recent Infection for HIV Incidence Surveillance

Estimates of HIV-1 incidence based on serological methods: a brief methodological review

HIV Diagnostics: Challenges and Opportunities

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