False-recent Rates Research Articles

Computational analysis of antibody dynamics identifies recent HIV-1 infection.

Accurate HIV-1 incidence estimation is critical to the success of HIV-1 prevention strategies. Current assays are limited by high false recent rates (FRRs) in certain populations and a short mean duration of recent infection (MDRI). Dynamic early HIV-1 antibody response kinetics were harnessed to identify biomarkers for improved incidence assays. We conducted retrospective analyses on circulating antibodies from known recent and longstanding infections and evaluated binding and avidity measurements of Env and non-Env antigens and multiple antibody forms (i.e., IgG, IgA, IgG3, IgG4, dIgA, and IgM) in a diverse panel of 164 HIV-1-infected participants (clades A, B, C). Discriminant function analysis identified an optimal set of measurements that were subsequently evaluated in a 324-specimen blinded biomarker validation panel. These biomarkers included clade C gp140 IgG3, transmitted/founder clade C gp140 IgG4 avidity, clade B gp140 IgG4 avidity, and gp41 immunodominant region IgG avidity. MDRI was estimated at 215 day or alternatively, 267 days. FRRs in untreated and treated subjects were 5.0% and 3.6%, respectively. Thus, computational analysis of dynamic HIV-1 antibody isotype and antigen interactions during infection enabled design of a promising HIV-1 recency assay for improved cross-sectional incidence estimation.

Infection Staging and Incidence Surveillance Applications of High Dynamic Range Diagnostic Immuno-Assay Platforms

Custom HIV staging assays, including the Sedia HIV-1 Limiting Antigen (LAg) Avidity EIA and avidity modifications of the Ortho VITROS anti-HIV-1+2 and Abbott ARCHITECT HIV Ag/Ab Combo assays, are used to identify "recent" infections in clinical settings and for cross-sectional HIV incidence estimation. However, the high dynamic range of chemiluminescent platforms allows differentiating recent and long-standing infection on signal intensity, and this raises the prospect of using unmodified diagnostic assays for infection timing and surveillance applications. We tested a panel of 2500 well-characterized specimens with estimable duration of HIV infection with the 3 assays and the unmodified ARCHITECT. Regression models were used to estimate mean durations of recent infection (MDRIs), context-specific false-recent rates (FRRs) and correlation between diagnostic signal intensity and LAg measurements. Hypothetical epidemiological scenarios were constructed to evaluate utility in surveillance applications. Over a range of MDRIs (reflecting recency discrimination thresholds), a diluted ARCHITECT-based RITA produced lower FRRs than the VITROS platform (FRR ≈ 0.5% and 1.5%, respectively at MDRI ≈ 200 days), and the unmodified diagnostic ARCHITECT produces incidence estimates with comparable precision to LAg (relative SE ≈ 17.5% and 15%, respectively at MDRI ≈ 200 days). ARCHITECT S/CO measurements were highly correlated with LAg optical density measurements (r = 0.80), and values below 200 are strongly predictive of LAg recency and duration of infection less than 1 year. Low quantitative measurements from the unmodified ARCHITECT obviate the need for additional recency testing, and its use is feasible in clinical staging and incidence surveillance applications.

Evaluation of a Multiplex Assay for Estimation of HIV-1 Incidence

ObjectivesAccurate methods of estimating HIV-1 incidence are critical for monitoring the status of the epidemic and the impact of prevention strategies. Although several laboratory-based tests have been developed strictly for this purpose, several limitations exist and improved methods or technologies are needed. We sought to further optimize a previously described bead-based, HIV-1-specific multiplex assay with the capability of measuring multiple immune responses for determining recent infection.MethodsWe refined the customized HIV-1 Bio-Plex assay by determining cutoffs and mean durations of recency (MDR), based on the reactivity to longitudinal seroconversion specimens (n = 1347) from 311 ART-naïve, HIV-1-infected subjects. False-recent rates (FRRs) were calculated for various long-term cohorts, including AIDS patients, individuals on ART, and subtype C specimens. Incidence was estimated for each individual assay analyte from a simulated population with a known incidence of 1%. For improved incidence estimates, multi-analyte algorithms based on combinations of 3 to 6 analytes were evaluated and compared to the performance of each individual analyte.ResultsThe MDR for the six analytes varied from 164.2 to 279.4 days, while the multi-analyte algorithm MDRs were less variable with a minimum and maximum value of 228.4 and 277.9 days, respectively. The FRRs for the 7 multi-analyte algorithms evaluated in this study varied from 0.3% to 3.1%, in a population of ART-naïve, long-term individuals. All algorithms yielded improved incidence estimates as compared to the individual analytes, predicting an incidence of 0.95% to 1.02%.ConclusionsThe HIV-specific multiplex assay described here measures several distinct immune responses in a single assay, allowing for the consideration of multi-analyte algorithms for improved HIV incidence estimates.

How Should We Best Estimate the Mean Recency Duration for the BED Method?

BED estimates of HIV incidence from cross-sectional surveys are obtained by restricting, to fixed time T, the period over which incidence is estimated. The appropriate mean recency duration () then refers to the time where BED optical density (OD) is less than a pre-set cut-off C, given the patient has been HIV positive for at most time T. Five methods, tested using data for postpartum women in Zimbabwe, provided similar estimates of for C = 0.8: i) The ratio (r/s) of the number of BED-recent infections to all seroconversions over T = 365 days: 192 days [95% CI 168–216]. ii) Linear mixed modeling (LMM): 191 days [95% CI 174–208]. iii) Non-linear mixed modeling (NLMM): 196 days [95% CrI 188–204]. iv) Survival analysis (SA): 192 days [95% CI 168–216]. Graphical analysis: 193 days. NLMM estimates of - based on a biologically more appropriate functional relationship than LMM – resulted in best fits to OD data, the smallest variance in estimates of , and best correspondence between BED and follow-up estimates of HIV incidence, for the same subjects over the same time period. SA and NLMM produced very similar estimates of but the coefficient of variation of the former was >3 times as high. The r/s method requires uniformly distributed seroconversion events but is useful if data are available only from a single follow-up. The graphical method produces the most variable results, involves unsound methodology and should not be used to provide estimates of . False-recent rates increased as a quadratic function of C: for incidence estimation C should thus be chosen as small as possible, consistent with an adequate resultant number of recent cases, and accurate estimation of . Inaccuracies in the estimation of should not now provide an impediment to incidence estimation.

Specificity of Four Laboratory Approaches for Cross-Sectional HIV Incidence Determination: Analysis of Samples from Adults with Known Nonrecent HIV Infection from Five African Countries

Assays to determine cross-sectional HIV incidence misclassify some individuals with nonrecent HIV infection as recently infected, overestimating HIV incidence. We analyzed factors associated with false-recent misclassification in five African countries. Samples from 2197 adults from Botswana, Kenya, South Africa, Tanzania, and Uganda who were HIV infected > 12 months were tested using the (1) BED capture enzyme immunoassay (BED), (2) avidity assay, (3) BED and avidity assays with higher assay cutoffs (BED+ avidity screen), and (4) multiassay algorithm (MAA) that includes the BED+ avidity screen, CD4 cell count, and HIV viral load. Logistic regression identified factors associated with misclassification. False-recent misclassification rates and 95% confidence intervals were BED alone: 7.6% (6.6, 8.8); avidity assay alone: 3.5% (2.7, 4.3); BED+ avidity screen: 2.2% (1.7, 2.9); and MAA: 1.2% (0.8, 1.8). The misclassification rate for the MAA was significantly lower than the rates for the other three methods (each p < 0.05). Misclassification rates were lower when the analysis was limited to subtype C-endemic countries, with the lowest rate obtained for the MAA [0.8% (0.2, 1.9)]. Factors associated with misclassification were for BED alone: country of origin, antiretroviral treatment (ART), viral load, and CD4 cell count; for avidity assay alone: country of origin; for BED+ avidity screen: country of origin and ART. No factors were associated with misclassification using the MAA. In a multivariate model, these associations remained significant with one exception: the association of ART with misclassification was completely attenuated. A MAA that included CD4 cell count and viral load had lower false-recent misclassification than the BED or avidity assays (alone or in combination). Studies are underway to compare the sensitivity of these methods for detection of recent HIV infection.

BED estimates of HIV incidence: resolving the differences, making things simpler.

ObjectiveDevelop a simple method for optimal estimation of HIV incidence using the BED capture enzyme immunoassay.DesignUse existing BED data to estimate mean recency duration, false recency rates and HIV incidence with reference to a fixed time period, T.MethodsCompare BED and cohort estimates of incidence referring to identical time frames. Generalize this approach to suggest a method for estimating HIV incidence from any cross-sectional survey.ResultsFollow-up and BED analyses of the same, initially HIV negative, cases followed over the same set time period T, produce estimates of the same HIV incidence, permitting the estimation of the BED mean recency period for cases who have been HIV positive for less than T. Follow-up of HIV positive cases over T, similarly, provides estimates of the false-recent rate appropriate for T. Knowledge of these two parameters for a given population allows the estimation of HIV incidence during T by applying the BED method to samples from cross-sectional surveys. An algorithm is derived for providing these estimates, adjusted for the false-recent rate. The resulting estimator is identical to one derived independently using a more formal mathematical analysis. Adjustments improve the accuracy of HIV incidence estimates. Negative incidence estimates result from the use of inappropriate estimates of the false-recent rate and/or from sampling error, not from any error in the adjustment procedure.ConclusionsReferring all estimates of mean recency periods, false-recent rates and incidence estimates to a fixed period T simplifies estimation procedures and allows the development of a consistent method for producing adjusted estimates of HIV incidence of improved accuracy. Unadjusted BED estimates of incidence, based on life-time recency periods, would be both extremely difficult to produce and of doubtful value.

Correlation of Prospective and Cross-Sectional Measures of HIV Type 1 Incidence in a Higher-Risk Cohort in Ho Chi Minh City, Vietnam

The primary aim of this study was to estimate HIV incidence within a high-risk population in Ho Chi Minh City (HCMC), Vietnam using both cross-sectional and prospective methodologies. A secondary aim was to develop a local correction factor for the BED and avidity index incidence assays. The research study design consisted of three phases: (1) cross-sectional, (2) prospective, and (3) BED false recent (BED FR). A total of 1619 high-risk, sexually active individuals were enrolled in the cross-sectional phase and 355 of the opiate-negative, HIV-negative women were subsequently enrolled in the prospective phase. Four-hundred and three men and women with known HIV infection duration of greater than 12 months were enrolled in the BED FR phase. The HIV prevalence for all participants in the cross-sectional phase was 15.8%. HIV incidence in the cross-sectional group was estimated using the BED IgG capture assay and AxSYM avidity index assay for recent HIV infection and incidence within the prospective cohort was determined by observations of HIV seroconversion. HIV incidence in opiate-negative women was estimated using the BED assay to be 0.8% unadjusted and 0.5% after applying the locally derived BED false recent rate of 1.7%; no seroconversions were observed in the prospective cohort. We also screened the cross-sectional samples for evidence of acute infection using nucleic acid testing, 4th generation HIV EIA, and SMARTube coupled with Genscreen and Determine diagnostic tests; no confirmed acute infections were identified by any method. HIV incidence within this opiate-negative study population was low and incidence estimates from the two methods compared favorably with each other. Incidence estimates and false recent rates using the AxSYM assay were higher: AI FRR of 2.7% and adjusted incidence of 1.7% per year (95% CI, 0.6, 2.8). By comparison, both HIV prevalence and incidence estimates for the opiate-positive group were higher.

Seroconverting Blood Donors as a Resource for Characterising and Optimising Recent Infection Testing Algorithms for Incidence Estimation

IntroductionBiomarker-based cross-sectional incidence estimation requires a Recent Infection Testing Algorithm (RITA) with an adequately large mean recency duration, to achieve reasonable survey counts, and a low false-recent rate, to minimise exposure to further bias and imprecision. Estimating these characteristics requires specimens from individuals with well-known seroconversion dates or confirmed long-standing infection. Specimens with well-known seroconversion dates are typically rare and precious, presenting a bottleneck in the development of RITAs.MethodsThe mean recency duration and a ‘false-recent rate’ are estimated from data on seroconverting blood donors. Within an idealised model for the dynamics of false-recent results, blood donor specimens were used to characterise RITAs by a new method that maximises the likelihood of cohort-level recency classifications, rather than modelling individual sojourn times in recency.ResultsFor a range of assumptions about the false-recent results (0% to 20% of biomarker response curves failing to reach the threshold distinguishing test-recent and test-non-recent infection), the mean recency duration of the Vironostika-LS ranged from 154 (95% CI: 96–231) to 274 (95% CI: 234–313) days in the South African donor population (n = 282), and from 145 (95% CI: 67–226) to 252 (95% CI: 194–308) days in the American donor population (n = 106). The significance of gender and clade on performance was rejected (p−value = 10%), and utility in incidence estimation appeared comparable to that of a BED-like RITA. Assessment of the Vitros-LS (n = 108) suggested potentially high false-recent rates.DiscussionThe new method facilitates RITA characterisation using widely available specimens that were previously overlooked, at the cost of possible artefacts. While accuracy and precision are insufficient to provide estimates suitable for incidence surveillance, a low-cost approach for preliminary assessments of new RITAs has been demonstrated. The Vironostika-LS and Vitros-LS warrant further analysis to provide greater precision of estimates.

Dual Testing Algorithm of BED-CEIA and AxSYM Avidity Index Assays Performs Best in Identifying Recent HIV Infection in a Sample of Rwandan Sex Workers

BackgroundTo assess the performance of BED-CEIA (BED) and AxSYM Avidity Index (Ax-AI) assays in estimating HIV incidence among female sex workers (FSW) in Kigali, Rwanda.Methodology and FindingsEight hundred FSW of unknown HIV status were HIV tested; HIV-positive women had BED and Ax-AI testing at baseline and ≥12 months later to estimate assay false-recent rates (FRR). STARHS-based HIV incidence was estimated using the McWalter/Welte formula, and adjusted with locally derived FRR and CD4 results. HIV incidence and local assay window periods were estimated from a prospective cohort of FSW. At baseline, 190 HIV-positive women were BED and Ax-AI tested; 23 were classified as recent infection (RI). Assay FRR with 95% confidence intervals were: 3.6% (1.2–8.1) (BED); 10.6% (6.1–17.0) (Ax-AI); and 2.1% (0.4–6.1) (BED/Ax-AI combined). After FRR-adjustment, incidence estimates by BED, Ax-AI, and BED/Ax-AI were: 5.5/100 person-years (95% CI 2.2–8.7); 7.7 (3.2–12.3); and 4.4 (1.4–7.3). After CD4-adjustment, BED, Ax-AI, and BED/Ax-AI incidence estimates were: 5.6 (2.6–8.6); 9.7 (5.0–14.4); and 4.7 (2.0–7.5). HIV incidence rates in the first and second 6 months of the cohort were 4.6 (1.6–7.7) and 2.2 (0.1–4.4).ConclusionsAdjusted incidence estimates by BED/Ax-AI combined were similar to incidence in the first 6 months of the cohort. Furthermore, false-recent rate on the combined BED/Ax-AI algorithm was low and substantially lower than for either assay alone. Improved assay specificity with time since seroconversion suggests that specificity would be higher in population-based testing where more individuals have long-term infection.

Current and future assays for identifying recent HIV infections at the population level

SummaryThe precise diagnosis of recent human immunodeficiency virus (HIV) infection is crucial for estimating HIV incidence, defined as the number of new infections in a population, per person at risk, during a specified time period. Incidence assessment is considered to be a tool for surveillance, public health and research. Differentiating recent from long-term HIV infections is possible thanks to the evaluation of HIV-specific immune response development or viral markers measurement. Several methods that enable the recognition of recent HIV-1 infection with the use of a single blood specimen have been developed, and their value for use in population level studies has been demonstrated. However, they are still inadequate due to a variable window period and false recent rates among HIV clades and across populations. Application of these assays at an individual level is far more questionable because of person-to-person variability in the antibody response and the course of HIV infection, and because of the prospective regulatory approval requirements.In this article we review the principles and the limitations of the currently available major laboratory techniques that allow detection of recent HIV infection. The assays based on the alteration of serological parameters, as well as the newest method based on an increase of HIV genetic diversity with the progress of infection, are described.

Beyond detuning: 10 years of progress and new challenges in the development and application of assays for HIV incidence estimation

Beyond detuning: 10 years of progress and new challenges in the development and application of assays for HIV incidence estimation