Integration of an Evidence-Based Algorithm for Inpatient Autoimmune and Paraneoplastic Neurologic Syndrome Autoantibody Panel Ordering Practice to Improve Diagnostic Evaluation Quality

Objective: At a single academic hospital, autoantibody panels were frequently ordered which provided duplicated data or omitted tests pertinent to the clinical syndrome. With a large volume of orders for autoimmune and paraneoplastic panels being placed without consistency, we aimed to standardize and improve ordering practices. Background: Currently, there are over 150 autoimmune and paraneoplastic panels commercially available from Clinical Laboratory Improvement Amendments certified laboratories. Laboratories follow testing algorithms that include different antibodies and testing techniques resulting in varied sensitivities and specificities. Further, what is known about the clinical sensitivity, specificity, and positive predictive value focuses on specific antibodies, not the autoimmune and paraneoplastic panels as a whole. Design/Methods: To accomplish this task, all orders for autoimmune and paraneoplastic panels placed in 2018 at University of Louisville Hospital were reviewed and divided by panel type and body fluid tested. A total percent positive for each panel type and body fluid was obtained, and detected antibodies recorded. Based on current literature, an algorithm was synthesized that utilizes diagnostic criteria from the 2016 autoimmune encephalitis criteria (Graus et. al), the APE2 score (Dubey et. al.), and clinical description and autoantibody correlation (Damato et. al.)6,7,8. We also included a component for antibodies associated with demyelinating disease based on imaging. Results: There were 36 autoimmune and 37 paraneoplastic panels sent in 2018. There were 6 paraneoplastic and 5 autoimmune positive panels, with the autoimmune coming from 2 cases with both serum and CSF tested with congruent results: NMDAR and GAD-65. When the new algorithm was applied to these cases, the APE2 portion of algorithm showed 100% sensitivity and 71% specificity for neural specific autoantibodies. Conclusions: The project data and algorithm was presented to the Diagnostic Stewardship Committee and implemented in July 2019 with a goal of improved diagnostic yield and fiscal responsibility in suspected autoimmune and paraneoplastic neurology cases. Disclosure: Dr. Fletcher has nothing to disclose. Dr. Sharp has nothing to disclose. Dr. Sweeney has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Genentech and Novartis.