Retrospective cohort study to devise a treatment decision score predicting adverse 24-month radiological activity in early multiple sclerosis.

Background: Multiple sclerosis (MS) is a chronic neuroinflammatory disease affecting about 2.8 million people worldwide. Disease course after the most common diagnoses of relapsing-remitting multiple sclerosis (RRMS) and clinically isolated syndrome (CIS) is highly variable and cannot be reliably predicted. This impairs early personalized treatment decisions.
Objectives: The main objective of this study was to algorithmically support clinical decision-making regarding the options of early platform medication or no immediate treatment of patients with early RRMS and CIS.
Design: Retrospective monocentric cohort study within the Data Integration for Future Medicine (DIFUTURE) Consortium.
Methods: Multiple data sources of routine clinical, imaging and laboratory data derived from a large and deeply characterized cohort of patients with MS were integrated to conduct a retrospective study to create and internally validate a treatment decision score [Multiple Sclerosis Treatment Decision Score (MS-TDS)] through model-based random forests (RFs). The MS-TDS predicts the probability of no new or enlarging lesions in cerebral magnetic resonance images (cMRIs) between 6 and 24 months after the first cMRI.
Results: Data from 65 predictors collected for 475 patients between 2008 and 2017 were included. No medication and platform medication were administered to 277 (58.3%) and 198 (41.7%) patients. The MS-TDS predicted individual outcomes with a cross-validated area under the receiver operating characteristics curve (AUROC) of 0.624. The respective RF prediction model provides patient-specific MS-TDS and probabilities of treatment success. The latter may increase by 5-20% for half of the patients if the treatment considered superior by the MS-TDS is used.
Conclusion: Routine clinical data from multiple sources can be successfully integrated to build prediction models to support treatment decision-making. In this study, the resulting MS-TDS estimates individualized treatment success probabilities that can identify patients who benefit from early platform medication. External validation of the MS-TDS is required, and a prospective study is currently being conducted. In addition, the clinical relevance of the MS-TDS needs to be established.
Competing Interests: The authors declared the following potential conflicts of interest with respect to the research, authorship and/or publication of this article: A.H., B.I.O., M.M., A.Be., U.M., A.W., M.Bu., M.Bo., K.K., I.G., H.S., B.W., L.G. and D.S. declare that there is no conflict of interest. J.S.K. is Co-Founder of Bonescreen GmbH. C.G. reports funding from the German Research Foundation (Deutsche Forschungsgesellschaft DFG), the Hertie Foundation, the Hans and Klementia Langmatz and the German Federal Ministry of Education and Research, all of which are not related to this study. A.Ba. reports personal compensation from Merck Serono, Biogen, Novartis, TEVA, Roche, Sanofi/Genzyme, Celgene/Bristol Myers Squibb, Janssen, Sandoz/HEXAL; grants for congress travel and participation from Biogen, TEVA, Novartis, Sanofi/Genzyme, Merck Serono, Celgene and Janssen. None related to this report. M.S. has received consulting and/or speaker honoraria from Alexion, Bayer, Biogen, Bristol Myers Squibb, Merck, Roche and Sanofi Genzyme. She has received travel support from Celgene and TEVA. She has received research funding from the Hertha-Nathorff-Program. None of this related to this study. M.C.K. has served on advisory boards and received speaker fees/travel grants from Merck, Sanofi/Genzyme, Novartis, Biogen, Jansen, Alexion, Celgene/Bristol Myers Squibb and Roche. M.K. also received research grants from Merck, Sanofi/Genzyme and Celgene/Bristol Myers Squibb, Novartis and Janssen, all not related to this study. J.H. reports grants for OCT research from the Friedrich-Baur-Stiftung and Merck, personal fees and nonfinancial support from Celgene, Horizon, Janssen, Bayer, Merck, Alexion, Novartis, Roche, Biogen and non-financial support of the Guthy-Jackson Charitable Foundation, all outside the submitted work. J.H. is partially funded by the German Federal Ministry of Education and Research [(DIFUTURE), grant numbers 01ZZ1603[A-D] and 01ZZ1804[A-H]]. B.H. has served on scientific advisory boards for Novartis; he has served as DMSC member for AllergyCare, Polpharma, Sandoz and TG therapeutics; he or his institution have received speaker honoraria from Desitin; his institution received research grants from Regeneron for multiple sclerosis research. B.H. holds part of two patents; one for the detection of antibodies against KIR4.1 in a subpopulation of patients with multiple sclerosis and one for genetic determinants of neutralizing antibodies to interferon. All of B.H.’s conflicts are not relevant to the topic of the study. B.H. received funding from the Multiple MS EU consortium, the Clinspect-M consortium funded by the Bundesministerium für Bildung und Forschung and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy – ID 390857198).
(© The Author(s), 2023.)