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Multimodal diagnostics in multiple sclerosis: predicting disability and conversion from relapsing-remitting to secondary progressive disease course - protocol for systematic review and meta-analysis
Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE; Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE; Big Data Analytics Center, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE.
Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate; Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE.
Psychology Department, College of Natural and Health Sciences, Zayed University, Abu Dhabi, Abu Dhabi Emirate, UAE.
Örebro University, University Library. National Medical Library, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE.ORCID iD: 0000-0001-5091-604X
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2023 (English)In: BMJ Open, E-ISSN 2044-6055, Vol. 13, no 7, article id e068608Article, review/survey (Refereed) Published
Abstract [en]

BACKGROUND: The number of patients diagnosed with multiple sclerosis (MS) has increased significantly over the last decade. The challenge is to identify the transition from relapsing-remitting to secondary progressive MS. Since available methods to examine patients with MS are limited, both the diagnostics and prognostication of disease progression would benefit from the multimodal approach. The latter combines the evidence obtained from disparate radiologic modalities, neurophysiological evaluation, cognitive assessment and molecular diagnostics. In this systematic review we will analyse the advantages of multimodal studies in predicting the risk of conversion to secondary progressive MS.

METHODS AND ANALYSIS: We will use peer-reviewed publications available in Web of Science, Medline/PubMed, Scopus, Embase and CINAHL databases. In vivo studies reporting the predictive value of diagnostic methods will be considered. Selected publications will be processed through Covidence software for automatic deduplication and blind screening. Two reviewers will use a predefined template to extract the data from eligible studies. We will analyse the performance metrics (1) for the classification models reflecting the risk of secondary progression: sensitivity, specificity, accuracy, area under the receiver operating characteristic curve, positive and negative predictive values; (2) for the regression models forecasting disability scores: the ratio of mean absolute error to the range of values. Then, we will create ranking charts representing performance of the algorithms for calculating disability level and MS progression. Finally, we will compare the predictive power of radiological and radiomical correlates of clinical disability and cognitive impairment in patients with MS.

ETHICS AND DISSEMINATION: The study does not require ethical approval because we will analyse publicly available literature. The project results will be published in a peer-review journal and presented at scientific conferences.

PROSPERO REGISTRATION NUMBER: CRD42022354179.

Place, publisher, year, edition, pages
BMJ Publishing Group Ltd, 2023. Vol. 13, no 7, article id e068608
Keywords [en]
Delirium & cognitive disorders, Magnetic resonance imaging, Multiple sclerosis, Neurophysiology
National Category
Neurology
Identifiers
URN: urn:nbn:se:oru:diva-107496DOI: 10.1136/bmjopen-2022-068608ISI: 001042144500061PubMedID: 37451729Scopus ID: 2-s2.0-85164757444OAI: oai:DiVA.org:oru-107496DiVA, id: diva2:1788541
Note

Study protocol

Funding agency:

ASPIRE grant AARE19-060

Available from: 2023-08-16 Created: 2023-08-16 Last updated: 2025-01-20Bibliographically approved

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Östlundh, Linda

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