title: Diagnostic accuracy of clinical illness for bovine respiratory disease (BRD) diagnosis in beef cattle placed in feedlots: A systematic literature review and hierarchical Bayesian latent-class meta-analysis.
abstract: Diagnosis of bovine respiratory disease (BRD) in beef cattle placed in feedlots is typically based on clinical illness (CI) detected by pen-checkers. Unfortunately, the accuracy of this diagnostic approach (namely, sensitivity [Se] and specificity [Sp]) remains poorly understood, in part due to the absence of a reference test for ante-mortem diagnosis of BRD. Our objective was to pool available estimates of CI's diagnostic accuracy for BRD diagnosis in feedlot beef cattle while adjusting for the inaccuracy in the reference test. The presence of lung lesions (LU) at slaughter was used as the reference test. A systematic review of the literature was conducted to identify research articles comparing CI detected by pen-checkers during the feeding period to LU at slaughter. A hierarchical Bayesian latent-class meta-analysis was used to model test accuracy. This approach accounted for imperfections of both tests as well as the within and between study variability in the accuracy of CI. Furthermore, it also predicted the SeCIand SpCIfor future studies. Conditional independence between CI and LU was assumed, as these two tests are not based on similar biological principles. Seven studies were included in the meta-analysis. Estimated pooled SeCIand SpCIwere 0.27 (95% Bayesian credible interval: 0.12-0.65) and 0.92 (0.72-0.98), respectively, whereas estimated pooled SeLUand SpLUwere 0.91 (0.82-0.99) and 0.67 (0.64-0.79). Predicted SeCIand SpCIfor future studies were 0.27 (0.01-0.96) and 0.92 (0.14-1.00), respectively. The wide credible intervals around predicted SeCIand SpCIestimates indicated considerable heterogeneity among studies, which suggests that pooled SeCIand SpCIare not generalizable to individual studies. In conclusion, CI appeared to have poor Se but high Sp for BRD diagnosis in feedlots. Furthermore, considerable heterogeneity among studies highlighted an urgent need to standardize BRD diagnosis in feedlots.
authors.affiliation: Department of Production Animal Health, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada; Feedlot Health Management Services, Okotoks, AB, Canada. Electronic address: eftimsit@ucalgary.ca.
authors.forename: E
authors.initials: E
authors.lastname: Timsit
authors.affiliation: Division of Clinical Epidemiology, McGill University Health Centre, Montreal, QC, Canada. Electronic address: nandini.dendukuri@mcgill.ca.
authors.forename: N
authors.initials: N
authors.lastname: Dendukuri
authors.affiliation: Division of Clinical Epidemiology, McGill University Health Centre, Montreal, QC, Canada. Electronic address: Ian.Schiller@clinepi.mcgill.ca.
authors.forename: I
authors.initials: I
authors.lastname: Schiller
authors.affiliation: Department of Clinical Science, Faculté de Médecine Vétérinaire, Université de Montréal, St-Hyacinthe, QC, Canada. Electronic address: s.buczinski@umontreal.ca.
authors.forename: S
authors.initials: S
authors.lastname: Buczinski
mesh_terms: D000822:Animal Husbandry; D000818:Animals; D001499:Bayes Theorem; D048090:Bovine Respiratory Disease Complex / Q000175:diagnosis* / Q000821:virology; D002417:Cattle; D003948:Diagnostic Techniques, Respiratory System / Q000662:veterinary*; D005260:Female; D008297:Male; D008962:Models, Theoretical; D012680:Sensitivity and Specificity
keywords: Diagnostic test; Imperfect reference; Latent class model; Lung lesion; Pen-rider; Shipping fever