TY - JOUR AU - Andersson, Anna-Maria AU - Aspán, Anna AU - Wisselink, Henk J. AU - Smid, Bregtje AU - Ridley, Anne AU - Pelkonen, Sinikka AU - Autio, Tiina AU - Lauritsen, Klara Tølbøll AU - Kensø, Jane AU - Gaurivaud, Patrice AU - Tardy, Florence PY - 2019 DA - 2019/10/25 TI - A European inter-laboratory trial to evaluate the performance of three serological methods for diagnosis of Mycoplasma bovis infection in cattle using latent class analysis JO - BMC Veterinary Research SP - 369 VL - 15 IS - 1 AB - Mycoplasma bovis (M. bovis) is an emerging bovine pathogen, leading to significant economic losses in the livestock industry worldwide. Infection can result in a variety of clinical signs, such as arthritis, pneumonia, mastitis and keratoconjunctivitis, none of which are M. bovis-specific. Laboratory diagnosis is therefore important. Serological tests to detect M. bovis antibodies is considered an effective indicator of infection in a herd and often used as a herd test. Combined with clinical judgement, it can also be used to implement control strategies and/or to estimate the disease prevalence within a country. However, due to lack of harmonisation of approaches to testing, and serological tests used by different laboratories, comparisons of prevalence data between countries is often difficult. A network of researchers from six European countries designed and participated in an inter-laboratory trial, with the aim of evaluating the sensitivity (Se) and specificity (Sp) of two commercially available ELISA tests (ID Screen® ELISA (IDvet) and BIO K302 ELISA (BIO-X Diagnostics)) for diagnosis of M. bovis infection. Each laboratory received a blinded panel of bovine sera and tested independently, according to manufacturer’s instructions. Western blot analyses (WB) performed by one of the participating laboratories was used as a third diagnostic test in the statistical evaluation of Se and Sp values using latent class analysis. SN - 1746-6148 UR - https://doi.org/10.1186/s12917-019-2117-0 DO - 10.1186/s12917-019-2117-0 ID - Andersson2019 ER -