edoc

Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection

Schupbach, J. and Bisset, L. R. and Gebhardt, M. D. and Regenass, S. and Burgisser, P. and Gorgievski, M. and Klimkait, T. and Andreutti, C. and Martinetti, G. and Niederhauser, C. and Yerly, S. and Pfister, S. and Schultze, D. and Brandenberger, M. and Schoni-Affolter, F. and Scherrer, A. U. and Gunthard, H. F. and Swiss HIV Cohort Study, . (2012) Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection. BMC infectious diseases, Vol. 12 , 88.

Full text not available from this repository.

Official URL: http://edoc.unibas.ch/dok/A6338389

Downloads: Statistics Overview

Abstract

Background: Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA (TM) HIV I/II Score) provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. Methods: Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months. Specificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and classified as either incident (> = 12 m) or older infection by 26 different algorithms. Incident infection rates (IIR) were calculated based on diagnostic sensitivity and specificity of each algorithm and the rule that the total of incident results is the sum of true-incident and false-incident results, which can be calculated by means of the predetermined sensitivity and specificity. Results: The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment for overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the preferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual cohorts of HIV-1 notifications totalling 2'595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline) and of 0.45, 0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing decreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative changes between the cohorts were identical for all models. Conclusions: The method can be used for comparing IIR in annual cohorts of HIV notifications. The use of several different algorithms in combination, each with its own sensitivity and specificity to detect incident infection, is advisable as this reduces the impact of individual imperfections stemming primarily from relatively low sensitivities and sampling bias.
Faculties and Departments:03 Faculty of Medicine > Departement Biomedizin > Division of Medical Microbiology > Molecular Virology (Klimkait)
UniBasel Contributors:Klimkait, Thomas
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:BioMed Central
ISSN:1471-2334
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:08 May 2015 08:45
Deposited On:08 May 2015 08:45

Repository Staff Only: item control page