Multiple sclerosis clinical decision support system based on projection to reference datasets
Objective Multiple sclerosis (MS) is a multifactorial disease with increasingly complicated management. Our objective is to use on‐demand computational power to address the challenges of dynamically managing MS. Methods A phase 3 clinical trial data (NCT00906399) were used to contextualize the medic...
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Published in | Annals of clinical and translational neurology Vol. 9; no. 12; pp. 1863 - 1873 |
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Main Authors | , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
John Wiley & Sons, Inc
01.12.2022
Wiley John Wiley and Sons Inc |
Subjects | |
Online Access | Get full text |
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Summary: | Objective
Multiple sclerosis (MS) is a multifactorial disease with increasingly complicated management. Our objective is to use on‐demand computational power to address the challenges of dynamically managing MS.
Methods
A phase 3 clinical trial data (NCT00906399) were used to contextualize the medication efficacy of peg‐interferon beta‐1a vs placebo on patients with relapsing–remitting MS (RRMS). Using a set of reference patients (PORs), selected based on adequate features similar to those of an individual patient, we visualize disease activity by measuring the percentage of relapses, accumulation of new T2 lesions on MRI, and worsening EDSS during the clinical trial.
Results
We developed MS Vista, a functional prototype of clinical decision support system (CDSS), with a user‐centered design and distributed infrastructure. MS Vista shows the medication efficacy of peginterferon beta‐1a versus placebo for each individual patient with RRMS. In addition, MS Vista initiated the integration of a longitudinal magnetic resonance imaging (MRI) viewer and interactive dual physician‐patient data display to facilitate communication.
Interpretation
The pioneer use of PORs for each individual patient enables personalized analytics sustaining the dialog between neurologists, patients and caregivers with quantified evidence. |
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Bibliography: | This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 754995, and the scholarship “Bourse Région Pays de la Loire” number 2019_11235. MS Vista is part of the PRIMUS project. This work was supported in part by the French National Research Agency (Agence Nationale de la Recherche, ANR) as its 3rd PIA, integrated to France 2030 plan under reference [ANR‐21‐RHUS‐0014]. Funding Information ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 PMCID: PMC9735373 |
ISSN: | 2328-9503 2328-9503 |
DOI: | 10.1002/acn3.51649 |