Multimodal diagnostics in multiple sclerosis: predicting disability and conversion from relapsing-remitting to secondary progressive disease course - protocol for systematic review and meta-analysis
Issued Date
2023-07-14
Resource Type
eISSN
20446055
Scopus ID
2-s2.0-85164757444
Pubmed ID
37451729
Journal Title
BMJ open
Volume
13
Issue
7
Rights Holder(s)
SCOPUS
Bibliographic Citation
BMJ open Vol.13 No.7 (2023) , e068608
Suggested Citation
Statsenko Y., Smetanina D., Arora T., Östlundh L., Habuza T., Simiyu G.L., Meribout S., Talako T., King F.C., Makhnevych I., Gelovani J.G., Das K.M., Gorkom K.N.V., Almansoori T.M., Al Zahmi F., Szólics M., Ismail F., Ljubisavljevic M. Multimodal diagnostics in multiple sclerosis: predicting disability and conversion from relapsing-remitting to secondary progressive disease course - protocol for systematic review and meta-analysis. BMJ open Vol.13 No.7 (2023) , e068608. doi:10.1136/bmjopen-2022-068608 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/88051
Title
Multimodal diagnostics in multiple sclerosis: predicting disability and conversion from relapsing-remitting to secondary progressive disease course - protocol for systematic review and meta-analysis
Author's Affiliation
Siriraj Hospital
Mohammed Bin Rashid University of Medicine and Health Sciences
College of Medicine and Health Sciences United Arab Emirates University
Zayed University
Tawam Hospital
Maimonides Medical Center
Wayne State University
United Arab Emirates University
Örebro Universitet
ASPIRE Precision Medicine Research Institute Abu Dhabi
Medical Imaging Platform
Transplantology and Hematology
Mediclinic Parkview Hospital
Mohammed Bin Rashid University of Medicine and Health Sciences
College of Medicine and Health Sciences United Arab Emirates University
Zayed University
Tawam Hospital
Maimonides Medical Center
Wayne State University
United Arab Emirates University
Örebro Universitet
ASPIRE Precision Medicine Research Institute Abu Dhabi
Medical Imaging Platform
Transplantology and Hematology
Mediclinic Parkview Hospital
Other Contributor(s)
Abstract
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.