Abstract
Accuracy of new or alternative diagnostic tests is typically estimated in relation to a well-standardized reference test referred to as a gold standard. However, for bovine tuberculosis (bTB), a chronic disease of cattle, affecting animal and public health, no reliable gold standard is available. In this context, latent-class models implemented using a Bayesian approach can help to assess the accuracy of diagnostic tests incorporating previous knowledge on test performance and disease prevalence. In Uruguay, bTB-prevalence has increased in the past decades partially because of the limited accuracy of the diagnostic strategy in place, based on intradermal testing (caudal fold test, CFT, for screening and comparative cervical test, CCT, for confirmation) and slaughter of reactors. Here, we evaluated the performance of two alternative bTB-diagnostic tools, the interferon-gamma assay, IGRA, and the enzyme-linked immunosorbent assay (ELISA), which had never been used in Uruguay in the absence of a gold standard. In order to do so animals from two heavily infected dairy herds and tested with CFT-CCT were also analyzed with the IGRA using two antigens (study 1) and the ELISA (study 2). The accuracy of the IGRA and ELISA was assessed fitting two latent-class models: a two test-one population model (LCA-a) based on the analysis of CFT/CFT-CCT test results and one in-vitro test (IGRA/ELISA), and a one test-one population model (LCA-b) using the IGRA or ELISA information in which the prevalence was modeled using information from the skin tests. Posterior estimates for model LCA-a suggested that IGRA was as sensitive (75–78%) as the CFT and more sensitive than the serial use of CFT-CCT. Its specificity (90–96%) was superior to the one for the CFT and equivalent to the use of CFT-CCT. Estimates from LCA-b models consistently yielded lower posterior Se estimates for the IGRA but similar results for its Sp. Estimates for the Se (52% 95%PPI:44.41-71.28) and the Sp (92% 95%PPI:78.63–98.76) of the ELISA were however similar regardless of the model used. These results suggest that the incorporation of IGRA for detection of bTB in highly infected herds could be a useful tool to improve the sensitivity of the bTB-control in Uruguay.
Highlights
Accuracy of diagnostic tests has been traditionally estimated by comparing the test results with those of a reference test, sometimes referred to as the gold standard, which unequivocally indicates the true status of an individual
Median posterior estimates for the prevalence, Se and Sp of the intradermal tests (CFT, and CFT-CCT) using the latent-class models: a two test-one population model (LCA-a) model were similar regardless the antigen used in the interferon-gamma release assay (IGRA) (IGRAb or IGRAc) (Table 3)
The median posterior IGRAb Sp estimates were slightly lower than those obtained for the IGRAc, whit higher median Sp values for the models integrating CFT-CCT as second test as well, but with the overlapping of the PPIs (Table 3)
Summary
Accuracy of diagnostic tests has been traditionally estimated by comparing the test results with those of a reference test, sometimes referred to as the gold standard, which unequivocally indicates the true status of an individual (infected/not infected). In the absence of such a reference test, latent class analyses based on Bayesian methods provide an alternative strategy for evaluation of diagnostic tests when the true status of the individual is unknown. The use of this approach in the context of veterinary medicine has been described elsewhere [1]. The prior knowledge on test performance is typically obtained through the review of the scientific literature and/or the elicitation of expert opinion [3]. Methodologies to elicit expert opinion have been described elsewhere [3]
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