Information on the incidence of HIV infection is crucial for monitoring the dynamics of the HIV epidemic in affected countries. Consequently, serologic testing algorithms for recent HIV seroconversion (STARHS) have been developed [1–4]. These tests make use of the fact that the HIV antibody response evolves during the first few months of infection with respect to concentration [5–7], proportion of the amount of total IgG , isotype , and avidity . The time during which these properties remain below a predetermined cutoff may greatly differ individually, and its mean duration or 'window-period' has to be established by testing specimens from individuals with known date of HIV seroconversion . Estimation of the incidence in a population is based on the relationship 'Prevalence = Incidence × Duration', as described by others [4, 12]. The performance of STARHS, i.e. the sensitivity and specificity with which they recognize or exclude an incident infection in an individual patient is low and does not meet the standards required for tests used for diagnostic purposes. Therefore, STARHS should not be used for individual diagnosis. Recently, new procedures based on HIV genetic diversity, as detected by single-genome analysis, have been developed, which in the future may lead to more reliable results also enabling diagnosis of incident infection in individual patients [13–15].
STARHS require a special assay of reduced analytical sensitivity; hence they are also called 'detuned' assays. The reduced sensitivity renders these tests unsuitable for diagnosis of HIV infection and restricts their use to epidemiological studies. However, for systematic epidemiologic monitoring it would be convenient if information on incident infections could be gained prospectively and systematically from the same tests used anyway to diagnose HIV.
We have previously shown that a patient's antibody reaction in a widely used commercial line immunoassay, the Inno-Lia™ HIV I/II Score (Inno-Lia), provides information on the duration of infection similar to that of a commercial enzyme immunoassay (EIA), the so-called BED Incidence EIA [8, 16]. The Inno-Lia is a type of second-generation Western blot (WB) that measures antibodies to different HIV antigens in a semi-quantitative way and is used for confirming HIV infection and to differentiate between HIV-1 and HIV-2 [17, 18]. Timely diagnosis of HIV-2 is important, because this virus requires different tests for viral load quantification than the widely used and FDA-approved tests from Roche, Abbott, BioMérieux, or Bayer. Furthermore, HIV-2 treatment requires different antiretroviral drug regimens, as the virus is naturally resistant to some frequently used drugs including the whole class of non-nucleoside reverse transcriptase inhibitors (NNRTI) [19–22]. In some countries, the Inno-Lia is thus used routinely at the time of diagnosis, and in Switzerland the test has become a mandatory confirmatory test for HIV in 2006 .
As the pattern and intensity of HIV-specific antibodies both evolve during the first weeks to months after infection, it is possible to define algorithms which differentiate between early and late antibody patterns. Each of these algorithms has its own characteristic sensitivity and specificity for detecting incident infections. Of note, the utilization of the Inno-Lia results for population-based studies of HIV-1 incidence comes at no additional costs -- no additional test is needed.
As for STARHS, it is possible to determine window periods for the different Inno-Lia antibody patterns seen in early infection and to estimate the incidence based on these windows. Work in this direction is in progress. Alternatively, if the diagnostic sensitivity and specificity of an algorithm are known, which requires prior testing of suitable reference groups of infections of either less or more than 12 months duration, it is also possible to estimate the incidence by means of the basic diagnostic rule ntested incident = ntrue incident + nfalse incident, whereby true-incident and false-incident are calculated based on the pre-determined values for diagnostic sensitivity and specificity . The advantage of this approach is that the imperfections of most diagnostic tests -- a sensitivity and a specificity below 100% -- are already accounted for. In contrast, with other STARHS and particularly the widely used BED Incidence EIA , the incidence estimates based on the relationship 'Prevalence = Incidence × Duration' are frequently too high [24–29]. Correction factors for imperfect sensitivity and specificity in both early, i.e. patients who remain in recent state well beyond the window period, and late stage infection, i.e., patients in very advanced disease who return to recent state, have had to be implemented [30–35]. This has required determination of the locally measured false-negative and false-positive ratios, i.e. investigations of the same type as those that are the basis of our true-incident/false-incident approach.
A unique advantage of the Inno-Lia method is the fact that it tests the antibody response to various HIV antigens at the same time in a semi-quantitative way and therefore allows identification of various antibody patterns that are characteristic of early infection. Antibodies to five different HIV-1 antigens are assessed in the test, allowing many combinations characteristic of early stage infection to be defined. Thus, a number of different algorithms, each with its own sensitivity and specificity and yielding its own set of samples ruled recent can be applied to a test population, consequently reducing the sampling error associated with a single test. As the Inno-Lia is a confirmatory HIV test, it permits prospective testing of all newly diagnosed patients and notification of the results to the respective health authority, which may then periodically calculate the proportion of recent infections among the notified new cases or determine the incidence if the total number of HIV tests performed is also known.
Precise information on the diagnostic sensitivity and specificity of each algorithm is crucial for the method. If these parameters are not correct, estimates of incident infections will not be accurate. Originally, we estimated these parameters in a study of newly diagnosed patients with HIV-1 infection of either less or more than 12 months duration, as judged by the treating physicians of these patients. As the study was prospective and no follow-up data was available, it was uncertain whether these judgments were correct. In this regard, the diagnostic performance figures thus generated were of a preliminary nature, and the true diagnostic sensitivity and specificity of the algorithms remain to be established. Furthermore, as the specificity of STARHS might be impaired when testing patients infected with non-B subtypes of HIV-1  or in advanced disease, it was deemed necessary to investigate whether or not these and other variables affect the outcome of the algorithms.
We have conducted two studies aimed towards establishing this goal. One study, published elsewhere , investigated the specificity of Inno-Lia algorithms in 714 patients of the Swiss HIV Cohort Study (SHCS) infected for at least 12 months and representing all clinical stages and major clades of HIV-1. That study showed that none of these parameters affected the algorithms. Although a viral RNA load below 50 copies/mL significantly reduced the specificity among patients receiving ART, age was the sole factor which could weakly impair the test specificity in untreated patients.
The second study, presented here, now addresses the diagnostic sensitivity of the Inno-Lia algorithms in a new cohort of patients infected for less than one year. It also investigates the overall diagnostic performance of the algorithms, i.e., their ability to distinguish between incident and older infection, and thus provides a basis for selecting the best algorithms for assessing annual cohorts of HIV notifications.