Background: Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information\r\nfor HIV surveillance. We have previously demonstrated that a patientââ?¬â?¢s antibody reaction pattern in a confirmatory\r\nline immunoassay (INNO-LIAââ??¢ HIV I/II Score) provides information on the duration of infection, which is unaffected\r\nby clinical, immunological and viral variables. In this report we have set out to determine the diagnostic\r\nperformance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection\r\nand evaluated the algorithms in annual cohorts of HIV notifications.\r\nMethods: Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months.\r\nSpecificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and\r\nclassified as either incident (< = 12 m) or older infection by 26 different algorithms. Incident infection rates (IIR)\r\nwere calculated based on diagnostic sensitivity and specificity of each algorithm and the rule that the total of\r\nincident results is the sum of true-incident and false-incident results, which can be calculated by means of the predetermined\r\nsensitivity and specificity.\r\nResults: The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment\r\nfor overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the\r\npreferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual\r\ncohorts of HIV-1 notifications totalling 2ââ?¬â?¢595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline) and of 0.45,\r\n0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing\r\ndecreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative\r\nchanges between the cohorts were identical for all models.\r\nConclusions: The method can be used for comparing IIR in annual cohorts of HIV notifications. The use of several\r\ndifferent algorithms in combination, each with its own sensitivity and specificity to detect incident infection, is\r\nadvisable as this reduces the impact of individual imperfections stemming primarily from relatively low sensitivities\r\nand sampling bias.
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