Reports Outline Multiple Sclerosis Study Findings from F. Hoffmann-La Roche Ltd. (Claims-based algorithm to estimate the Expanded Disability Status Scale for multiple sclerosis in a German health insurance fund: a validation study using patient …): Autoimmune Diseases and Conditions – Multiple Sclerosis

2023 DEC 21 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Business Daily -- New research on multiple sclerosis is the subject of a new report. According to news originating from Basel, Switzerland, by NewsRx correspondents, research stated, “BackgroundThe Expanded Disability Status Scale (EDSS) quantifies disability and measures disease progression in multiple sclerosis (MS), however is not available in administrative claims databases. ObjectivesTo develop a claims-based algorithm for deriving EDSS and validate it against a clinical dataset capturing true EDSS values from medical records.”

Our news correspondents obtained a quote from the research from F. Hoffmann-La Roche Ltd.: “MethodsWe built a unique linked dataset combining claims data from the German AOK PLUS sickness fund and medical records from the Multiple Sclerosis Management System 3D (MSDS3D). Data were deterministically linked based on insurance numbers. We used 69 MS-related diagnostic indicators recorded with ICD-10-GM codes within 3 months before and after recorded true EDSS measures to estimate a claims-based EDSS proxy (pEDSS). Predictive performance of the pEDSS was assessed as an eight-fold (EDSS 1.0-7.0, 8.0), three-fold (EDSS 1.0-3.0, 4.0-5.0, 6.0), and binary classifier (EDSS <6.0, 6.0). For each classifier, predictive performance measures were determined, and overall performance was summarized using a macro F1-score. Finally, we implemented the algorithm to determine pEDSS among an overall cohort of patients with MS in AOK PLUS, who were alive and insured 12 months prior to and after index diagnosis. ResultsWe recruited 100 people with MS insured by AOK PLUS who had 1 EDSS measure in MSDS3D between 01/10/2015 and 30/06/2019 (620 measurements overall). Patients had a mean rescaled EDSS of 3.2 and pEDSS of 3.0. The pEDSS deviated from the true EDSS by 1.2 points, resulting in a mean squared error of prediction of 2.6. For the eight-fold classifier, the macro F1-score of 0.25 indicated low overall predictive performance. Broader severity groupings were better performing, with the three-fold and binary classifiers for severe disability achieving a F1-score of 0.68 and 0.84, respectively. In the overall AOK PLUS cohort (3,756 patients, 71.9% female, mean 51.9 years), older patients, patients with progressive forms of MS and those with higher comorbidity burden showed higher pEDSS.”

According to the news reporters, the research concluded: “Generally, EDSS was underestimated by the algorithm as mild-to-moderate symptoms were poorly captured in claims across all functional systems. While the proxy-based approach using claims data may not allow for granular description of MS disability, broader severity groupings show good predictive performance.”

For more information on this research see: Claims-based algorithm to estimate the Expanded Disability Status Scale for multiple sclerosis in a German health insurance fund: a validation study using patient medical records. Frontiers in Neurology, 2023,14. (Frontiers in Neurology - http://frontiersin.org/neurology). The publisher for Frontiers in Neurology is Frontiers Media S.A.

A free version of this journal article is available at https://doi.org/10.3389/fneur.2023.1253557.

Our news editors report that more information may be obtained by contacting Erwan Muros-Le Rouzic, F. Hoffmann-La Roche Ltd., Basel, Switzerland. Additional authors for this research include Marco Ghiani, Evi Zhuleku, Anja Dillenseger, Ulf Maywald, Thomas Wilke, Tjalf Ziemssen, Licinio Craveiro.

(Our reports deliver fact-based news of research and discoveries from around the world.)