Literature DB >> 23838177

Clinical and magnetic resonance imaging predictors of disease progression in multiple sclerosis: a nine-year follow-up study.

L Lavorgna1, S Bonavita, D Ippolito, R Lanzillo, G Salemi, F Patti, P Valentino, G Coniglio, M Buccafusca, D Paolicelli, A d'Ambrosio, V Bresciamorra, G Savettieri, M Zappia, B Alfano, A Gallo, Il Simone, G Tedeschi.   

Abstract

OBJECTIVE: The objective of this paper is to identify clinical or magnetic resonance imaging (MRI) predictors of long-term clinical progression in a large cohort of multiple sclerosis (MS) patients.
METHODS: A total of 241 relapsing-remitting (RR) MS patients were included in a nine-year follow-up (FU) study. The reference MRIs were acquired at baseline (BL) as part of a multicenter, cross-sectional, clinical-MRI study. Volumetric MRI metrics were measured by a fully automated, operator-independent, multi-parametric segmentation method. Clinical progression was evaluated as defined by: conversion from RR to secondary progressive (SP) disease course; progression of Expanded Disability Status Scale (EDSS); achievement and time to reach EDSS 4.
RESULTS: We concluded that conversion from RR to SP (OR 0.79; CI 0.7-0.9), progression of EDSS (OR 0.85; CI 0.77-0.93), achievement of EDSS 4 (OR 0.8; CI 0.7-0.9), and time to reach EDSS 4 (HR 0.88; CI 0.82-0.94) were all predicted by BL gray matter (GM) volume and, except for progression of EDSS, by BL EDSS (respectively: (OR 2.88; CI 1.9-4.36), (OR 2.7; CI 1.7-4.2), (HR 3.86; CI 1.94-7.70)).
CONCLUSIONS: BL GM volume and EDSS are the best long-term predictors of disease progression in RRMS patients with a relatively long and mild disease.

Entities:  

Keywords:  Magnetic resonance imaging; clinical predictors; follow-up; gray matter atrophy; multiple sclerosis

Mesh:

Year:  2013        PMID: 23838177     DOI: 10.1177/1352458513494958

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


  12 in total

Review 1.  Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis--establishing disease prognosis and monitoring patients.

Authors:  Mike P Wattjes; Àlex Rovira; David Miller; Tarek A Yousry; Maria P Sormani; Maria P de Stefano; Mar Tintoré; Cristina Auger; Carmen Tur; Massimo Filippi; Maria A Rocca; Franz Fazekas; Ludwig Kappos; Chris Polman
Journal:  Nat Rev Neurol       Date:  2015-09-15       Impact factor: 42.937

Review 2.  Clinical relevance of brain volume measures in multiple sclerosis.

Authors:  Nicola De Stefano; Laura Airas; Nikolaos Grigoriadis; Heinrich P Mattle; Jonathan O'Riordan; Celia Oreja-Guevara; Finn Sellebjerg; Bruno Stankoff; Agata Walczak; Heinz Wiendl; Bernd C Kieseier
Journal:  CNS Drugs       Date:  2014-02       Impact factor: 5.749

3.  MRI biomarkers of disease progression in multiple sclerosis: old dog, new tricks?

Authors:  Yael Barnett; Justin Y Garber; Michael H Barnett
Journal:  Quant Imaging Med Surg       Date:  2020-02

Review 4.  The importance of studying sex differences in disease: The example of multiple sclerosis.

Authors:  Lisa C Golden; Rhonda Voskuhl
Journal:  J Neurosci Res       Date:  2017-01-02       Impact factor: 4.164

5.  Magnetic resonance imaging perfusion is associated with disease severity and activity in multiple sclerosis.

Authors:  Piotr Sowa; Gro Owren Nygaard; Atle Bjørnerud; Elisabeth Gulowsen Celius; Hanne Flinstad Harbo; Mona Kristiansen Beyer
Journal:  Neuroradiology       Date:  2017-06-05       Impact factor: 2.804

Review 6.  Thalamus pathology in multiple sclerosis: from biology to clinical application.

Authors:  Markus Kipp; Nina Wagenknecht; Cordian Beyer; Sebastian Samer; Jens Wuerfel; Omid Nikoubashman
Journal:  Cell Mol Life Sci       Date:  2014-11-23       Impact factor: 9.261

7.  Predicting Long-term Disability in Multiple Sclerosis: A Narrative Review of Current Evidence and Future Directions.

Authors:  Bianca Weinstock-Guttman; Maria Pia Sormani; Pavle Repovic
Journal:  Int J MS Care       Date:  2022-10-05

8.  The role of global and regional gray matter volume decrease in multiple sclerosis.

Authors:  Matthias Grothe; Martin Lotze; Sönke Langner; Alexander Dressel
Journal:  J Neurol       Date:  2016-04-19       Impact factor: 4.849

9.  Lesion load may predict long-term cognitive dysfunction in multiple sclerosis patients.

Authors:  Francesco Patti; Manuela De Stefano; Luigi Lavorgna; Silvia Messina; Clara Grazia Chisari; Domenico Ippolito; Roberta Lanzillo; Veria Vacchiano; Sabrina Realmuto; Paola Valentino; Gabriella Coniglio; Maria Buccafusca; Damiano Paolicelli; Alessandro D'Ambrosio; Patrizia Montella; Vincenzo Brescia Morra; Giovanni Savettieri; Bruno Alfano; Antonio Gallo; Isabella Simone; Rosa Viterbo; Mario Zappia; Simona Bonavita; Gioacchino Tedeschi
Journal:  PLoS One       Date:  2015-03-27       Impact factor: 3.240

10.  The Efficacy of Natalizumab versus Fingolimod for Patients with Relapsing-Remitting Multiple Sclerosis: A Systematic Review, Indirect Evidence from Randomized Placebo-Controlled Trials and Meta-Analysis of Observational Head-to-Head Trials.

Authors:  Georgios Tsivgoulis; Aristeidis H Katsanos; Dimitris Mavridis; Nikolaos Grigoriadis; Efthymios Dardiotis; Ioannis Heliopoulos; Panagiotis Papathanasopoulos; Theodoros Karapanayiotides; Constantinos Kilidireas; Georgios M Hadjigeorgiou; Konstantinos Voumvourakis
Journal:  PLoS One       Date:  2016-09-29       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.