Macular ganglion cell–inner plexiform layer thinning as a biomarker of disability progression in relapsing multiple sclerosis

Author:

Bsteh Gabriel1ORCID,Berek Klaus2,Hegen Harald2,Altmann Patrick1ORCID,Wurth Sebastian3ORCID,Auer Michael2,Zinganell Anne2,Di Pauli Franziska2,Rommer Paulus1ORCID,Leutmezer Fritz1,Deisenhammer Florian2ORCID,Berger Thomas1ORCID

Affiliation:

1. Department of Neurology, Medical University of Vienna, Vienna, Austria

2. Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria

3. Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria/Department of Neurology, Medical University of Graz, Austria

Abstract

Background: Macular ganglion cell–inner plexiform layer (mGCIPL) is an emerging biomarker of neuroaxonal degeneration in multiple sclerosis (MS). Objective: We aimed to determine cut-off values of mGCIPL thinning for discriminating between progressing and stable patients in relapsing multiple sclerosis (RMS). Methods: This is a 3-year prospective longitudinal study on 183 RMS patients with annual optical coherence tomography. Best possible cut-off values of baseline mGCIPL and annual loss of macular ganglion cell–inner plexiform layer (aLmGCIPL) for discriminating clinically progressing (physical progression or cognitive decline) from stable patients were defined by receiver operating characteristics analysis and tested using multivariate regression models. Results: Baseline mGCIPL thickness <77 µm was associated with an increased risk (hazard ratio: 2.7, 95% confidence interval (CI): 1.5–4.7, p < 0.001) of disability progression. An aLmGCIPL cut-off ⩾1 µm accurately identified clinically progressing patients (87% sensitivity at 90% specificity) and was a strong predictor of clinical progression (odds ratio: 18.3, 95% CI: 8.8–50.3). Conclusion: We present evidence that cross-sectionally measured mGCIPL thickness and annualized thinning rates of mGCIPL are able to identify clinically progressing RMS with high accuracy.

Publisher

SAGE Publications

Subject

Neurology (clinical),Neurology

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