Dataset Information

Short-term MRI measurements as predictors of EDSS progression in relapsing-remitting multiple sclerosis: grey matter atrophy but not lesions are predictive in a real-life setting.

ABSTRACT:

Background

Magnetic resonance imaging (MRI) is the best biomarker of inflammatory disease activity in relapsing remitting Multiple Sclerosis (RRMS) so far but the association with disability is weak. Appearance of new MRI-lesions is used to evaluate response to immunotherapies in individual patients as well as being the most common primary outcome in phase-2 trials. Measurements of brain atrophy show promising outcomes in natural cohort studies and some phase-2 trials. From a theoretical perspective they might represent irreversible neurodegeneration and be more closely associated with disability. However, these atrophy measurements are not yet established as prognostic factors in real-life clinical routine. High field MRI has improved image quality and resolution and new methods to measure atrophy dynamics have become available.

Objective

To investigate the predictive value of MRI classification criteria in to high/low atrophy and inflammation groups, and to explore predictive capacity of two consecutive routine MRI scans for disability progression in RRMS in a real-life prospective cohort.

Methods

82 RRMS-patients (40 untreated, 42 treated with immunotherapies, mean age 40 years, median Expanded Disability Status Scale (EDSS) of 2, underwent two clinically indicated MRI scans (3 Tesla) within 5-14 months, and EDSS assessment after a mean of 3.0 (1.5-4.2) years. We investigated the predictive value of predefined classifications in low/high inflammatory and atrophy groups for EDSS progression (?1.5 if baseline EDSS = 0, ?1.0 if baseline EDSS <5, ?0.5 for other) by chi-square tests and by analysis of variance (ANOVA). The classifications were based on current scientific or clinical recommendation (e.g., treatment response criteria). Brain atrophy was assessed with three different methods (SIENA, SIENAX, and FreeSurfer). Post-hoc analyses aimed to explore clinical data and dynamics of MRI outcomes as predictors in multivariate linear and logit models.

Results

Progression was observed in 24% of patients and was independent from treatment status. None of the predefined classifications were predictive for progression. Explorative post-hoc analyses found lower baseline EDSS and higher grey matter atrophy (FreeSurfer) as best predictors (R (2) = 0.29) for EDSS progression and the accuracy was overall good (Area under the curve = 0.81).

Conclusion

Beside EDSS at baseline, short-term grey matter atrophy is predictive for EDSS progression in treated and untreated RRMS. The development of atrophy measurements for individual risk counselling and evaluation of treatment response seems possible, but needs further validation in larger cohorts. MRI-atrophy estimates from the FreeSurfer toolbox seem to be more reliable than older methods.

SUBMITTER: von Gumberz J

PROVIDER: S-EPMC5036070 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Short-term MRI measurements as predictors of EDSS progression in relapsing-remitting multiple sclerosis: grey matter atrophy but not lesions are predictive in a real-life setting.

von Gumberz Johanna J Mahmoudi Mina M Young Kim K Schippling Sven S Martin Roland R Heesen Christoph C Siemonsen Susanne S Stellmann Jan-Patrick JP

PeerJ 20160920

<h4>Background</h4>Magnetic resonance imaging (MRI) is the best biomarker of inflammatory disease activity in relapsing remitting Multiple Sclerosis (RRMS) so far but the association with disability is weak. Appearance of new MRI-lesions is used to evaluate response to immunotherapies in individual patients as well as being the most common primary outcome in phase-2 trials. Measurements of brain atrophy show promising outcomes in natural cohort studies and some phase-2 trials. From a theoretical ...[more]

PMID: 27688965

Similar Datasets

Project description:Background and objectivesClinical trials in relapsing-remitting multiple sclerosis (RRMS) usually use the Expanded Disability Status Scale (EDSS) as their primary disability outcome measure, while the more recently developed outcomes timed 25-ft walk (T25FW) and 9-hole peg test (NHPT) may be more useful and patient relevant. The objective of this work was to compare the EDSS to the T25FW and NHPT in a large RRMS randomized controlled trial (RCT) dataset.MethodsWe used the dataset from Combination Therapy in Patients With Relapsing-Remitting Multiple Sclerosis (CombiRx) (clinicaltrials.gov identifier NCT00211887), a large phase 3 RCT, to compare the EDSS to the alternative outcomes T25FW and NHPT. We investigated disability worsening vs similarly defined improvement, unconfirmed vs confirmed and sustained disability change, and the presentation methods cumulative Kaplan-Meier survival curves vs cross-sectional disability worsening.ResultsCombiRx included 1,008 participants. A comparison of confirmed and sustained worsening events showed that, throughout the trial, there were substantially fewer sustained than confirmed events, with a positive predictive value of confirmed for sustained worsening at 24 months of 0.73 for the EDSS, 0.73 for the T25FW, and 0.8 for the NHPT. More concerning were the findings that worsening on the EDSS occurred as frequently as similarly defined improvement throughout the 3 years of follow-up and that improvement rates increased in parallel with worsening rates. The T25FW showed low improvement rates of <10% throughout the trial. We also found that Kaplan-Meier survival analysis, the standard presentation and analysis method in modern RRMS trials, yields exaggerated estimates of disability worsening. With the Kaplan-Meier method, the proportion of patients with worsening events steadily increases until it reaches several-fold the number of events seen with more conservative analysis methods. For 3-month confirmed disability worsening up to 36 months, the Kaplan-Meier method yields 2.6-fold higher estimates for the EDSS, 2.9-fold higher estimates for the T25FW, and 5.1-fold higher estimates for the NHPT compared to a more conservative presentation of the same data.DiscussionOur analyses raise concerns about using the EDSS as the standard disability outcome in RRMS trials and suggest that the T25FW may be a more useful measure. These findings are relevant for the design and critical appraisal of RCTs.

Project description:One of our new major finding among the genes that contributes to MS susceptibility is ICSBP1. The so called disease modifying therapies like interferon-beta (IFN-β), possibly acting on the peripheral T-cells, reduce the disease activity and the clinical progression, with a MRI-detectable effect in preventing lesion burden and cerebral atrophy development in RR-MS. It suggests a critical role of peripheral blood mononuclear cells (PBMCs) immune response and modulation in developing inflammation in the brain. We tested the hypothesis that the genetic effect of the susceptible allele ICSBP1 can impact the gene expression profile of molecules belonging to the interferon pathway. We therefore interrogated the PBMC for changes in gene expression profile. We correlate those changes with the minor allele frequency for ICSBP1, performing independent quantitative trait analysis for each treatment category. Expression Quantitative Trait Loci Association with a p value < 0.05 have been used in follow up analysis. The regression coefficient of the Quantitative trait association represents the degree of correlation between the gene expression for each interrogated target gene and the minor allele frequency of the SNP for our gene of interest. This coefficient has been used as input in the subsequent Gene Set Enrichment Analysis performed in a pre-ranked approach. The resulting GSEA-SNP method rests on the assumption that SNPs underlying a disease phenotype might affect genes constituting a signaling pathway or genes with a common regulation. Therefore, GSEA-SNP can facilitate the identification of pathways or of underlying biological mechanisms. We used microarrays to capture gene expression profile of untreated subjects and of subjects under disease modyfing treatment (Interferon Beta and Glatiramer Acetate), in order to correlate gene expression and genotype data and in order to identify sets of genes specifically regulated in the different treatment categories.

Dataset Information

Short-term MRI measurements as predictors of EDSS progression in relapsing-remitting multiple sclerosis: grey matter atrophy but not lesions are predictive in a real-life setting.

Background

Objective

Methods

Results

Conclusion

Publications

Short-term MRI measurements as predictors of EDSS progression in relapsing-remitting multiple sclerosis: grey matter atrophy but not lesions are predictive in a real-life setting.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets