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• W2559000664 abstract "Objective: To predict disease activity for patients with Relapsing Remitting Multiple Sclerosis (RRMS) using Electronic Medical Records (EMR). Background: The increased availability of disease modifying therapies for RRMS is placing a greater focus on clinicians to better understand likely disease activity in order to optimize treatment choice. It is important to understand whether routinely collected EMR data can be used to predict disease activity for RRMS since these predictions could potentially be used by clinicians to help improve treatment allocation and patient outcomes. Methods: This was a retrospective EMR database study of 4,129 RRMS patients from the NeuroTransData network of neurology practices in Germany. Disease activity was proxied by a binary outcome indicating whether a patient experienced a relapse over a twelve-month follow-up period. Risk factors included demographics, diagnostic history, treatment, disability status, disability history and cranial and spinal lesion counts. Regularised (elastic-net) logistic regression models were estimated. The Area Under the Curve (AUC) was used as the key performance metric, computed from left-out folds using cross-validation. Patients were assigned to risk bands based on quintiles of predicted probability of relapse. Results: The AUC was 0.692 (CI 0.671-0.712). The actual relapse rate for the highest risk group was 5.6 times higher than the lowest risk group (35.1[percnt] vs. 6.3[percnt]). The probability of a relapse was positively and significantly (p<0.05) associated with recent relapses, younger ages, being born in Central Europe and negatively associated with a pre-index Expanded Disability Status Scale of zero. Amongst other factors, counts of cranial and spinal lesions were not significant. Conclusions: This study demonstrated that real world EMR data could be used to successfully stratify RRMS patients according to the probability of experiencing a relapse. This confirms the feasibility of using routinely collected EMR data to develop risk stratification tools to support clinical decision-making. Disclosure: Dr. Mein has received personal compensation for activities with Novartis Pharma AG as an employee. Dr. Joyeux has received personal compensation for activities with Novartis Pharma AG. Dr. Braune has nothing to disclose. Dr. Bergmann has received personal compensation for activities with Novartis Pharma AG. Dr. Rigg has received personal compensation for activities with IMS Health. Dr. Wang has received personal compensation for activities with IMS Health." @default.
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• W2559000664 date "2016-04-05" @default.
• W2559000664 modified "2023-09-28" @default.
• W2559000664 title "Predicting Disease Activity for Patients with Relapsing Remitting Multiple Sclerosis Using Electronic Medical Records (P1.395)" @default.
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