The Institute for Medical Information Processing, Biometry, and Epidemiology

Shiny Project Server

switch-ms

An interactive decision support tool developed as part of the study “Validating Therapy Decisions by Reasons for Therapy Switch in Relapsing-Remitting Multiple Sclerosis”. It operationalizes Bayesian predictive models for persons with relapsing-remitting multiple sclerosis (PwRRMS), providing personalized therapy recommendations based on real-world patient data from the OFSEP registry. The underlying models, described in Sakr et al. (2024), were developed using pre-2017 OFSEP data and recalibrated on a temporally distinct patient cohort. This ensures more generalizable predictions when evaluating therapy changes across varying reasons for switching, including efficacy, intolerance, and patient-driven motives.

Contact: anna.sakr@ibe.med.uni-muenchen.de | mail@annamariasakr.de

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