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Prospective study validating a multidimensional treatment decision score predicting the 24-month outcome in untreated patients with clinically isolated syndrome and early relapsing-remitting multiple sclerosis, the ProVal-MS study.
Bayas, Antonios; Mansmann, Ulrich; Ön, Begum Irmak; Hoffmann, Verena S; Berthele, Achim; Mühlau, Mark; Kowarik, Markus C; Krumbholz, Markus; Senel, Makbule; Steuerwald, Verena; Naumann, Markus; Hartberger, Julia; Kerschensteiner, Martin; Oswald, Eva; Ruschil, Christoph; Ziemann, Ulf; Tumani, Hayrettin; Vardakas, Ioannis; Albashiti, Fady; Kramer, Frank; Soto-Rey, Iñaki; Spengler, Helmut; Mayer, Gerhard; Kestler, Hans Armin; Kohlbacher, Oliver; Hagedorn, Marlien; Boeker, Martin; Kuhn, Klaus; Buchka, Stefan; Kohlmayer, Florian; Kirschke, Jan S; Behrens, Lars; Zimmermann, Hanna; Bender, Benjamin; Sollmann, Nico; Havla, Joachim; Hemmer, Bernhard.
  • Bayas A; Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Stenglinstrasse 2, 86156, Augsburg, Germany. antonios.bayas@uk-augsburg.de.
  • Mansmann U; Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.
  • Ön BI; Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.
  • Hoffmann VS; Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.
  • Berthele A; Department of Neurology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany.
  • Mühlau M; Department of Neurology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany.
  • Kowarik MC; Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany.
  • Krumbholz M; Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany.
  • Senel M; Department of Neurology, University Hospital Ulm, Ulm, Germany.
  • Steuerwald V; Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Stenglinstrasse 2, 86156, Augsburg, Germany.
  • Naumann M; Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Stenglinstrasse 2, 86156, Augsburg, Germany.
  • Hartberger J; Department of Neurology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany.
  • Kerschensteiner M; Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
  • Oswald E; Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
  • Ruschil C; Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany.
  • Ziemann U; Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany.
  • Tumani H; Department of Neurology, University Hospital Ulm, Ulm, Germany.
  • Vardakas I; Department of Neurology, University Hospital Ulm, Ulm, Germany.
  • Albashiti F; Medical Data Integration Center, University Hospital, LMU Munich, Munich, Germany.
  • Kramer F; IT-Infrastructure for Translational Medical Research, University of Augsburg, Augsburg, Germany.
  • Soto-Rey I; Medical Data Integration Center, Institute of Digital Medicine, University Hospital Augsburg, Augsburg, Germany.
  • Spengler H; Medical Data Integration Center, Medical Center rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
  • Mayer G; Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany.
  • Kestler HA; Institute of Medical Systems Biology, Ulm University, Ulm, Germany.
  • Kohlbacher O; Institute for Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany.
  • Hagedorn M; Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • Boeker M; Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany.
  • Kuhn K; Medical Data Integration Center, University Hospital, LMU Munich, Munich, Germany.
  • Buchka S; Institute for Artificial Intelligence and Informatics in Medicine, Medical Center rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
  • Kohlmayer F; Institute for Artificial Intelligence and Informatics in Medicine, Medical Center rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
  • Kirschke JS; Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.
  • Behrens L; Bitcare GmbH, Munich, Germany.
  • Zimmermann H; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
  • Bender B; Diagnostic and Interventional Neuroradiology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
  • Sollmann N; Institute of Neuroradiology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
  • Havla J; Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany.
  • Hemmer B; Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.
Neurol Res Pract ; 6(1): 15, 2024 Mar 07.
Article en En | MEDLINE | ID: mdl-38449051
ABSTRACT

INTRODUCTION:

In Multiple Sclerosis (MS), patients´ characteristics and (bio)markers that reliably predict the individual disease prognosis at disease onset are lacking. Cohort studies allow a close follow-up of MS histories and a thorough phenotyping of patients. Therefore, a multicenter cohort study was initiated to implement a wide spectrum of data and (bio)markers in newly diagnosed patients.

METHODS:

ProVal-MS (Prospective study to validate a multidimensional decision score that predicts treatment outcome at 24 months in untreated patients with clinically isolated syndrome or early Relapsing-Remitting-MS) is a prospective cohort study in patients with clinically isolated syndrome (CIS) or Relapsing-Remitting (RR)-MS (McDonald 2017 criteria), diagnosed within the last two years, conducted at five academic centers in Southern Germany. The collection of clinical, laboratory, imaging, and paraclinical data as well as biosamples is harmonized across centers. The primary goal is to validate (discrimination and calibration) the previously published DIFUTURE MS-Treatment Decision score (MS-TDS). The score supports clinical decision-making regarding the options of early (within 6 months after study baseline) platform medication (Interferon beta, glatiramer acetate, dimethyl/diroximel fumarate, teriflunomide), or no immediate treatment (> 6 months after baseline) of patients with early RR-MS and CIS by predicting the probability of new or enlarging lesions in cerebral magnetic resonance images (MRIs) between 6 and 24 months. Further objectives are refining the MS-TDS score and providing data to identify new markers reflecting disease course and severity. The project also provides a technical evaluation of the ProVal-MS cohort within the IT-infrastructure of the DIFUTURE consortium (Data Integration for Future Medicine) and assesses the efficacy of the data sharing techniques developed. PERSPECTIVE Clinical cohorts provide the infrastructure to discover and to validate relevant disease-specific findings. A successful validation of the MS-TDS will add a new clinical decision tool to the armamentarium of practicing MS neurologists from which newly diagnosed MS patients may take advantage. Trial registration ProVal-MS has been registered in the German Clinical Trials Register, `Deutsches Register Klinischer Studien` (DRKS)-ID DRKS00014034, date of registration 21 December 2018; https//drks.de/search/en/trial/DRKS00014034.
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