Quantitative Detection of Increasing HIV Type 1 Antibodies after Seroconversion: A Simple Assay for Detecting Recent HIV Infection and Estimating Incidence

Parekh, Bharat; Kennedy, Melanie S.; Dobbs, Trudy; Pau, Chou‐Pong; Byers, Robert H.; Green, Timothy; Hu, Dale J.; Vanichseni, Suphak; Young, Nancy L.; Choopanya, Kachit; Mastro, Timothy D.; McDougal, J. Steven

doi:10.1089/088922202753472874

Cited by 319 publications

(331 citation statements)

References 19 publications

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“…[24][25][26][27][28][29][30] As would be appropriate in the more familiar diagnostic applications, values close to 100% have been regarded as realistic targets, with these two measures summarized into, for example, receiver operating characteristic (ROC) curves and the overall classification accuracy. This line of thinking runs into three major obstacles.…”

Section: Optimal Tests For Recent Infectionmentioning

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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Section: Optimal Tests For Recent Infectionmentioning

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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“…A BED-capture enzyme immunoassay (BED-CEIA) was used for HIV-1 incidence (Calypte Biomedical Corporation, Portland, USA) 5 . Incidence calculations and 95% confidence intervals were performed with the spreadsheet provided by the South African Centre for Epidemiological Modeling and Analysis (SACEMA; http://www.…”

Section: No Brasil a Epidemia Do Hiv-1 Adquiriu Novas Característicamentioning

confidence: 99%

HIV-1 incidence among people seeking voluntary counseling and testing centers, including pregnant women, in Pernambuco State, Northeast Brazil

Lima

Salustiano²,

Cavalcanti³

et al. 2015

Cad. Saúde Pública

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The HIV-1 epidemic in Brazil has displayed new characteristics over time, with an increase in heterosexual transmission and a decline in the male-to-female ratio in AIDS cases. HIV screening was offered to patients attending the Voluntary Counseling and Testing Center in Paulista, Greater Metropolitan Recife, Pernambuco State, in Northeast Brazil, to determine HIV-1 incidence. BED capture enzyme immunoassay (BED-CEIA) was used to measure HIV-1 incidence, comparing it to the AxSYM avidity index method (Ax-AI). From 2006 to 2009, 14,014 individuals were tested, and only 18 pregnant women were diagnosed with HIV infection, resulting in 0.15% annual incidence (95%CI: 0-0.33), significantly lower than in men (1.03; 95%CI: 0.45-1.61) and non-pregnant women (0.50; 95%CI: 0.11-0.89). Despite the low HIV-1 incidence in pregnant women, the high rate of recent infection detected during prenatal care emphasizes the need to increase measures to prevent vertical transmission.

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“…BED window period: A window period was chosen randomly from an estimate of the window period distribution. This estimate is based on data from a series of blood samples obtained from newly infected persons [10]. For the BED test a generalized log-logistic distribution fits this distribution (R. H. Byers, CDC, personal communication).…”

Section: Hiv Test Datesmentioning

confidence: 99%

Estimating HIV incidence in the United States from HIV/AIDS surveillance data and biomarker HIV test results

Karon

Song

Brookmeyer

et al. 2008

Statistics in Medicine

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SUMMARYThe development of an human immunodeficiency virus (HIV) test that detects recent infection has enabled the U.S. Centers for Disease Control and Prevention (CDC) to estimate annual HIV incidence (number of new infections per year, not per person at risk) in the United States from data on new HIV and acquired immunodeficiency syndrome (AIDS) diagnoses reported to HIV/AIDS surveillance. We developed statistical procedures to estimate the probability that an infected person will be detected as recently infected, accounting for individuals choosing whether and how frequently to seek HIV testing, variation of testing frequency, the reporting of test results only for infected persons, and infected persons who never had an HIV-negative test. The incidence estimate is the number of persons detected as recently infected divided by the estimated probability of detection. We used simulation to show that, under the assumptions we make, our procedures have acceptable bias and correct confidence interval coverage. Because data on the biomarker for recent infection or on testing history were missing for many persons, we used multiple imputation to apply our models to surveillance data. CDC has used these procedures to estimate HIV incidence in the United States.

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Quantitative Detection of Increasing HIV Type 1 Antibodies after Seroconversion: A Simple Assay for Detecting Recent HIV Infection and Estimating Incidence

Cited by 319 publications

References 19 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

HIV-1 incidence among people seeking voluntary counseling and testing centers, including pregnant women, in Pernambuco State, Northeast Brazil

Estimating HIV incidence in the United States from HIV/AIDS surveillance data and biomarker HIV test results

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