Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 256

The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Establishing pathological cut-offs of brain atrophy rates in multiple sclerosis

Open access
De Stefano, Nicola, Stromillo, Maria Laura, Giorgio, Antonio, Bartolozzi, Maria Letizia, Battaglini, Marco, Baldini, Mariella, Portaccio, Emilio, Amato, Maria Pia, Sormani, Maria Pia·2015·Journal of Neurology, Neurosurgery & Psychiatry

Abstract

OBJECTIVE: To assess whether it is feasible to establish specific cut-off values able to discriminate 'physiological' or 'pathological' brain volume rates in patients with multiple sclerosis (MS). METHODS: The study was based on the analysis of longitudinal MRI data sets of patients with MS (n=206, 87% relapsing-remitting, 7% secondary progressive and 6% primary progressive) and healthy controls (HC; n=35). Brain atrophy rates were computed over a mean follow-up of 7.5 years (range 1-12) for patients with MS and 6.3 years (range 1-12.5) for HC with the SIENA software and expressed as annualised per cent brain volume change (PBVC/y). A weighted (on the follow-up length) receiver operating characteristic analysis and the area under the curve (AUC) were used for statistics. RESULTS: The weighted PBVC/y was -0.51±0.27% in patients with MS and -0.27±0.15% in HC (p<0.0001). There was a significant age-related difference in PBVC/y between HC older and younger than 35 years of age (p=0.02), but not in patients with MS (p=0.8). The cut-off of PBVC/y, as measured by SIENA that could maximise the accuracy in discriminating patients with MS from HC, was -0.37%, with 67% sensitivity and 80% specificity. According to the observed distribution, values of PBVC/y as measured by SIENA that could define a pathological range were above -0.52% with 95% specificity, above -0.46% with 90% specificity and above -0.40% with 80% specificity. CONCLUSIONS: Our evidence-based criteria provide values able to discriminate the presence or absence of 'pathological' brain volume loss in MS with high specificity. Such results could be of great value in a clinical setting, particularly in assessing treatment efficacy in MS.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1136/jnnp-2014-309903

Cites

35 of 35 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 35 references

Cited by

See all 256

Metadata

Authors
De Stefano, N., Stromillo, M. L., Giorgio, A., Bartolozzi, M. L., Battaglini, M., Baldini, M., Portaccio, E., Amato, M. P., & Sormani, M. P.
Venue
Journal of Neurology, Neurosurgery & Psychiatry
Publisher
BMJ
Published
2015-04-22
Volume
87
Issue
1
Pages
jnnp-2014-309903
ISSN
  • 0022-3050 (ISSN-L)
  • 1468-330X
OpenAlex
W2123968065
Cited by
256
References
35
FWCI
19.50
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Establishing pathological cut-offs of brain atrophy rates in multiple sclerosis. https://app.cochat.ai/papers/10.1136/jnnp-2014-309903
The paper
De Stefano, N., Stromillo, M. L., Giorgio, A., Bartolozzi, M. L., Battaglini, M., Baldini, M., Portaccio, E., Amato, M. P., & Sormani, M. P. (2015). Establishing pathological cut-offs of brain atrophy rates in multiple sclerosis. Journal of Neurology, Neurosurgery & Psychiatry. https://doi.org/10.1136/jnnp-2014-309903

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.