Diagnostic Accuracy of Anti-CN1A on the Diagnosis of Inclusion Body Myositis. A Hierarchical Bivariate and Bayesian Meta-analysis

Abstract Sporadic inclusion body myositis (IBM) is an acquired muscle disease and the most common idiopathic inflammatory myopathy over the age of 50. It is characterized by male predominance, with a prevalence rate between 1 and 71 cases per million, reaching 139 cases per million over the age of 50 globally. The diagnosis of IBM is based on clinical presentation and muscle biopsy findings. However, there is increasing evidence for the role of genetics and serum biomarkers in supporting a diagnosis. Antibodies against the cytosolic 5′-nucleotidase 1A (Anti-CN1A), an enzyme catalyzing the conversion of adenosine monophosphate into adenosine and phosphate and is abundant in skeletal muscle, has been reported to be present in IBM and could be of crucial significance in the diagnosis of the disease. In this study, we investigated the diagnostic accuracy of anti-CN1A antibodies for sporadic IBM in comparison with other inflammatory myopathies, autoimmune disorders, motor neurone disease, using a hierarchical bivariate approach, and a Bayesian model taking into account the variable prevalence. The results of the present analysis show that anti-CN1A antibodies have moderate sensitivity, and despite having high specificity, they are not useful biomarkers for the diagnosis of IBM, polymyositis or dermatomyositis, other autoimmune conditions, or neuromuscular disorders. Neither the hierarchical bivariate nor the Bayesian analysis showed any significant usefulness of anti-CN1A antibodies in the diagnosis of IBM.