Literature DB >> 27465613

The clinical perspective: How to personalise treatment in MS and how may biomarkers including imaging contribute to this?

Patrick Vermersch1, Thomas Berger2, Ralf Gold3, Carsten Lukas4, Alex Rovira5, Bianca Meesen6, Declan Chard7, Manuel Comabella8, Jacqueline Palace9, Maria Trojano10.   

Abstract

BACKGROUND: Multiple sclerosis (MS) is a highly heterogeneous disease, both in its course and in its response to treatments. Effective biomarkers may help predict disability progression and monitor patients' treatment responses.
OBJECTIVE: The aim of this review was to focus on how biomarkers may contribute to treatment individualisation in MS patients.
METHODS: This review reflects the content of presentations, polling results and discussions on the clinical perspective of MS during the first and second Pan-European MS Multi-stakeholder Colloquia in Brussels in May 2014 and 2015.
RESULTS: In clinical practice, magnetic resonance imaging (MRI) measures play a significant role in the diagnosis and follow-up of MS patients. Together with clinical markers, the rate of MRI-visible lesion accrual once a patient has started treatment may also help to predict subsequent treatment responsiveness. In addition, several molecular (immunological, genetic) biomarkers have been established that may play a role in predictive models of MS relapses and progression. To reach personalised treatment decisions, estimates of disability progression and likely treatment response should be carefully considered alongside the risk of serious adverse events, together with the patient's treatment expectations.
CONCLUSION: Although biomarkers may be very useful for individualised decision making in MS, many are still research tools and need to be validated before implementation in clinical practice.
© The Author(s), 2016.

Entities:  

Keywords:  Biological markers; disease progression; drug-related side effects and adverse reactions; magnetic resonance imaging; multiple sclerosis; treatment response

Mesh:

Substances:

Year:  2016        PMID: 27465613     DOI: 10.1177/1352458516650739

Source DB:  PubMed          Journal:  Mult Scler        ISSN: 1352-4585            Impact factor:   6.312


  6 in total

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Authors:  Saeideh Gharehkhani Digehsara; Niloofar Name; Behnaz Esfandiari; Elahe Karim; Saba Taheri; Maryam Tajabadi-Ebrahimi; Javad Arasteh
Journal:  Inflammation       Date:  2020-09-10       Impact factor: 4.092

2.  Perspectives of Patients with Multiple Sclerosis on Drug Treatment: A Qualitative Study.

Authors:  Larry D Lynd; Natalie J Henrich; Celestin Hategeka; Carlo A Marra; Nicole Mittmann; Charity Evans; Anthony L Traboulsee
Journal:  Int J MS Care       Date:  2018 Nov-Dec

3.  Investigating the Role of MicroRNA and Transcription Factor Co-regulatory Networks in Multiple Sclerosis Pathogenesis.

Authors:  Nicoletta Nuzziello; Laura Vilardo; Paride Pelucchi; Arianna Consiglio; Sabino Liuni; Maria Trojano; Maria Liguori
Journal:  Int J Mol Sci       Date:  2018-11-20       Impact factor: 5.923

Review 4.  Molecular biomarkers in multiple sclerosis.

Authors:  Tjalf Ziemssen; Katja Akgün; Wolfgang Brück
Journal:  J Neuroinflammation       Date:  2019-12-23       Impact factor: 8.322

5.  Stratification of multiple sclerosis patients using unsupervised machine learning: a single-visit MRI-driven approach.

Authors:  Giuseppe Pontillo; Simone Penna; Sirio Cocozza; Mario Quarantelli; Michela Gravina; Roberta Lanzillo; Stefano Marrone; Teresa Costabile; Matilde Inglese; Vincenzo Brescia Morra; Daniele Riccio; Andrea Elefante; Maria Petracca; Carlo Sansone; Arturo Brunetti
Journal:  Eur Radiol       Date:  2022-03-14       Impact factor: 7.034

6.  Psychometric properties of the SDM-Q-9 questionnaire for shared decision-making in multiple sclerosis: item response theory modelling and confirmatory factor analysis.

Authors:  Javier Ballesteros; Ester Moral; Luis Brieva; Elena Ruiz-Beato; Daniel Prefasi; Jorge Maurino
Journal:  Health Qual Life Outcomes       Date:  2017-04-22       Impact factor: 3.186

  6 in total

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