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Seroconverting blood donors as a resource for characterising and optimising recent infection testing algorithms for incidence estimation.

Kassanjee R, Welte A, McWalter TA, Keating SM, Vermeulen M, Stramer SL, Busch MP - PLoS ONE (2011)

Bottom Line: 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.Assessment of the Vitros-LS (n = 108) suggested potentially high false-recent rates.The Vironostika-LS and Vitros-LS warrant further analysis to provide greater precision of estimates.

View Article: PubMed Central - PubMed

Affiliation: South African DST/NRF Centre for Epidemiological Modelling and Analysis, University of Stellenbosch, Stellenbosch, South Africa. r.kassanjee@gmail.com

ABSTRACT

Introduction: Biomarker-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.

Methods: The 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.

Results: For 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.

Discussion: The 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.

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Performance of the Vironostika-LS for incidence estimation, based on estimated RITA characteristics.The estimated performance of the Vironostika-LS, for incidence estimation purposes, is shown, based on estimated RITA characteristics for the South African repeat donor population. In Part A and Part B, estimates of ω and α, respectively, under the simultaneous estimation of these parameters, for T = 1 year, are plotted as a function of test threshold. The minimum and maximum ω and α occurring in the 95% confidence regions (CRs) for these parameters are also displayed. In Part C, the estimated precision of the incidence estimator using the Vironostika-LS is compared to the precision obtained by a BED-like RITA (ω = 155 days and ε = 5.6% [34]), based on the estimated RITA characteristics (assuming ε = α) and assuming constant HIV incidence of 1.5% and prevalence of 17.5%. More specifically, the ratio of the coefficient of variation (CoV, ratio of standard deviation to mean) of the incidence estimator, for the Vironostika-LS to the BED-like RITA, is plotted as a function of the Vironostika-LS test threshold. *A polynomial is fitted by least squares to smooth estimates.
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pone-0020027-g004: Performance of the Vironostika-LS for incidence estimation, based on estimated RITA characteristics.The estimated performance of the Vironostika-LS, for incidence estimation purposes, is shown, based on estimated RITA characteristics for the South African repeat donor population. In Part A and Part B, estimates of ω and α, respectively, under the simultaneous estimation of these parameters, for T = 1 year, are plotted as a function of test threshold. The minimum and maximum ω and α occurring in the 95% confidence regions (CRs) for these parameters are also displayed. In Part C, the estimated precision of the incidence estimator using the Vironostika-LS is compared to the precision obtained by a BED-like RITA (ω = 155 days and ε = 5.6% [34]), based on the estimated RITA characteristics (assuming ε = α) and assuming constant HIV incidence of 1.5% and prevalence of 17.5%. More specifically, the ratio of the coefficient of variation (CoV, ratio of standard deviation to mean) of the incidence estimator, for the Vironostika-LS to the BED-like RITA, is plotted as a function of the Vironostika-LS test threshold. *A polynomial is fitted by least squares to smooth estimates.

Mentions: The ultimate objective is incidence estimation. The precision of the incidence estimator (and hence power to detect changes in incidence) increases with a larger mean recency duration and smaller false-recent rate [15]. However, there is a fundamental trade-off between these RITA characteristics as both parameters increase with increasing threshold, shown for the Vironostika-LS, South Africa (Fig. 4A and Fig. 4B, α provides an indication of the magnitude of the false-recent rate).


Seroconverting blood donors as a resource for characterising and optimising recent infection testing algorithms for incidence estimation.

Kassanjee R, Welte A, McWalter TA, Keating SM, Vermeulen M, Stramer SL, Busch MP - PLoS ONE (2011)

Performance of the Vironostika-LS for incidence estimation, based on estimated RITA characteristics.The estimated performance of the Vironostika-LS, for incidence estimation purposes, is shown, based on estimated RITA characteristics for the South African repeat donor population. In Part A and Part B, estimates of ω and α, respectively, under the simultaneous estimation of these parameters, for T = 1 year, are plotted as a function of test threshold. The minimum and maximum ω and α occurring in the 95% confidence regions (CRs) for these parameters are also displayed. In Part C, the estimated precision of the incidence estimator using the Vironostika-LS is compared to the precision obtained by a BED-like RITA (ω = 155 days and ε = 5.6% [34]), based on the estimated RITA characteristics (assuming ε = α) and assuming constant HIV incidence of 1.5% and prevalence of 17.5%. More specifically, the ratio of the coefficient of variation (CoV, ratio of standard deviation to mean) of the incidence estimator, for the Vironostika-LS to the BED-like RITA, is plotted as a function of the Vironostika-LS test threshold. *A polynomial is fitted by least squares to smooth estimates.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3111407&req=5

pone-0020027-g004: Performance of the Vironostika-LS for incidence estimation, based on estimated RITA characteristics.The estimated performance of the Vironostika-LS, for incidence estimation purposes, is shown, based on estimated RITA characteristics for the South African repeat donor population. In Part A and Part B, estimates of ω and α, respectively, under the simultaneous estimation of these parameters, for T = 1 year, are plotted as a function of test threshold. The minimum and maximum ω and α occurring in the 95% confidence regions (CRs) for these parameters are also displayed. In Part C, the estimated precision of the incidence estimator using the Vironostika-LS is compared to the precision obtained by a BED-like RITA (ω = 155 days and ε = 5.6% [34]), based on the estimated RITA characteristics (assuming ε = α) and assuming constant HIV incidence of 1.5% and prevalence of 17.5%. More specifically, the ratio of the coefficient of variation (CoV, ratio of standard deviation to mean) of the incidence estimator, for the Vironostika-LS to the BED-like RITA, is plotted as a function of the Vironostika-LS test threshold. *A polynomial is fitted by least squares to smooth estimates.
Mentions: The ultimate objective is incidence estimation. The precision of the incidence estimator (and hence power to detect changes in incidence) increases with a larger mean recency duration and smaller false-recent rate [15]. However, there is a fundamental trade-off between these RITA characteristics as both parameters increase with increasing threshold, shown for the Vironostika-LS, South Africa (Fig. 4A and Fig. 4B, α provides an indication of the magnitude of the false-recent rate).

Bottom Line: 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.Assessment of the Vitros-LS (n = 108) suggested potentially high false-recent rates.The Vironostika-LS and Vitros-LS warrant further analysis to provide greater precision of estimates.

View Article: PubMed Central - PubMed

Affiliation: South African DST/NRF Centre for Epidemiological Modelling and Analysis, University of Stellenbosch, Stellenbosch, South Africa. r.kassanjee@gmail.com

ABSTRACT

Introduction: Biomarker-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.

Methods: The 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.

Results: For 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.

Discussion: The 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.

Show MeSH
Related in: MedlinePlus