| Literature DB >> 31457019 |
Catalina Picasso-Risso1,2, Andres Perez1, Andres Gil2, Alvaro Nunez3, Ximena Salaberry3, Alejandra Suanes3, Julio Alvarez4,5.
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.Entities:
Keywords: Uruguay; chronically infected; diagnosis; elisa; interferon-gamma release assay; latent class analysis
Year: 2019 PMID: 31457019 PMCID: PMC6701407 DOI: 10.3389/fvets.2019.00261
Source DB: PubMed Journal: Front Vet Sci ISSN: 2297-1769
Figure 1Schematic diagram showing the study design, with the diagnostic tests used for study 1 and study 2, and the Bayesian latent-class fitted models LCA-a and LCA-b.
Prior estimates (Mode and 5th percentiles) for sensitivity, specificity of the intradermal tests (CFT, CFT-CCT) and in-vitro (IGRAb, IGRAc, and ELISA) bTB tests, and prevalence for the two models implemented.
| CFT | 80 (>51) | α: 7.99, β: 2.75 | 90 (>60) | α: 8.3045, β: 1.81 | ( |
| CFT-CCT | 53 (>46) | α: 73.81, β: 65.57 | 97 (>94) | α: 176.39, β: 6.42 | ( |
| IGRAb | 83.5 (>48) | α: 5.99, β: 1.99 | 95 (>80) | α: 21.20, β:2.06 | ( |
| IGRAc | 80 (>60) | α: 14.84, β: 4.46 | 97 (>94) | α: 176.39, β: 6.42 | ( |
| ELISA | 57.1(>33.1) | α: 6.98, β: 5.49 | 95 (>81) | α: 23.25, β: 2.17 | ( |
| Prevalence( | 35 (>15) | α: 3.63, β: 5.88 | Experts opinion | ||
| Prevalence (+) | 85 (>61) | α: 8.46, β: 1.742 | CFT-estimated | ||
Prevalence priors distributions based on expert opinions used in the LCA-a.
(+) Prevalence priors distributions based on results from the intradermal test (CFT) used in the LCA-b.
Cross-tabulated dichotomous diagnostic results for intradermal test (CFT, CFT-CCT) and in-vitro (IGRAb, IGRAc, ELISA) bTB- diagnostic tests.
| 1 | IGRAb | Positive | 35 | 19 | 26 | 28 | 54 |
| Negative | 25 | 42 | 10 | 57 | 67 | ||
| IGRAc | Positive | 34 | 16 | 24 | 26 | 50 | |
| Negative | 26 | 45 | 12 | 59 | 71 | ||
| Total | 60 | 61 | 36 | 85 | 121 | ||
| 2 | ELISA | Positive | 126 | 3 | 91 | 38 | 129 |
| Negative | 108 | 42 | 64 | 86 | 150 | ||
| Total | 234 | 45 | 155 | 124 | 279 | ||
Posterior estimates (median and 95% posterior probability interval) for CFT, CFT-CCT and in-vitro assays (IGRAb, IGRAc, ELISA) sensitivities, specificities, prevalence, and, when applicable, correlation terms (rhoD, rhoDc) distributions obtained for study 1 (121 animals) and study 2 (279 animals), applying the model “a,” or the model “b” in chronic naturally infected dairy herds in Uruguay.
| IGRAb | 75.32 (58.96, 91.63) | 89.96 (77.82, 97.23) | 50.84 (33.80, 67.73) | −4.09 (−28.94, 35.07) | −2.78 (−20.70, 23.68) | |||
| CFT | 19.4 | 73.34 (56.88,89.44) | 77.02 (58.96, 95.48) | |||||
| IGRAc | 19.4 | 75.73 (62.45, 88.08) | 96.49 (93.85, 98.22) | 51.33 (38.11, 65.33) | −3.50 (−24.00, 24.73) | −0.33 (−7.84, 9.23) | ||
| CFT | 72.43 (58.34, 83.75) | 76.23 (59.98, 93.95) | ||||||
| ELISA | 19.4 | 57.82 (48.92, 73.43) | 93.76 (85.57, 98.08) | 76.94 (56.97, 87.80) | 11.17 (−1.96, 29.72) | 4.75 (−1.39, 27.78) | ||
| CFT | 95.48 (88.83, 98.91) | 63.87 (34.15, 94.31) | ||||||
| IGRAb | 18.1 | 78.01 (62.97, 89.53) | 91.43 (78.91, 98.26) | 50.37 (37.38, 63.48) | −2.47 (−31.69, 29.59) | −0.48 (−8.19, 16.20) | ||
| CFT-CCT | 53.27 (45.76, 60.59) | 96.19 (92.78, 98.37) | ||||||
| IGRAc | 17.7 | 76.21 (65.35, 85.86) | 96.56 (93.34, 98.52) | 51.30 (40.28, 62.97) | −6.03 (−28.49, 17.95) | −0.09 (−3.42, 5.10) | ||
| CFT-CCT | 52.89 (45.66, 59.93) | 96.13 (92.66, 98.32) | ||||||
| ELISA | 24.4 | 52.29 (44.96, 60.35) | 92.41 (78.82, 98.48) | 79.73 (73.23, 91.80) | 17.05 (−0.26, 31.64) | −0.08 (−8.02, 16.78) | ||
| CFT-CCT | 60.44 (54.45, 66.59) | 96.14 (92.60, 98.34) | ||||||
| IGRAb | 7.3 | 58.12 (43.14, 86.23) | 92.70 (77.84, 98.85) | 76.57 (48.06, 96.68) | NA | NA | ||
| IGRAc | 7.8 | 66.04 (46.97, 86.68) | 96.72 (93.54, 98.68) | 65.37 (45.68, 91.79) | NA | NA | ||
| ELISA | 8.4 | 53.85 (44.41, 71.28) | 92.42 (78.63, 98.76) | 83.79 (59.92, 97.78) | NA | NA | ||
Model “a”: Two-dependent-test and one population model.
Model “b”: One-test one population model.
IGRAb: Interferon gamma release assay using PPDb-PPDa antigens.
IGRAc: Interferon gamma release assay using peptide cocktail antigens.
ELISA: Commercial Enzyme-immunosorbent assay.
Differences between the use of informative vs. uniform priors reflects a >10.5% variation in the posterior estimates.