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Peripapillary retinal nerve fibre layer thinning rate as a biomarker discriminating stable and progressing relapsing–remitting multiple sclerosis
Author(s) -
Bsteh G.,
Hegen H.,
Teuchner B.,
Berek K.,
Wurth S.,
Auer M.,
Di Pauli F.,
Deisenhammer F.,
Berger T.
Publication year - 2019
Publication title -
european journal of neurology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.881
H-Index - 124
eISSN - 1468-1331
pISSN - 1351-5101
DOI - 10.1111/ene.13897
Subject(s) - medicine , retinal , multiple sclerosis , thinning , nerve fibre layer , relapsing remitting , biomarker , nerve fiber layer , ophthalmology , immunology , biochemistry , biology , ecology , chemistry
Background and purpose Peripapillary retinal nerve fibre layer (pRNFL) thickness is a strong candidate as a biomarker of axonal degeneration in multiple sclerosis (MS). The aim was to determine a cut‐off value of pRNFL thinning rates in relapsing–remitting MS (RRMS) to discriminate between stable and progressing patients. Methods In this 3‐year prospective longitudinal study on 141 RRMS patients, annual pRNFL thinning rates (aLpRNFL) were determined by individual linear regression models. The best possible cut‐off value discriminating clinically progressing (physical progression or cognitive decline) and stable patients was defined by receiver operating characteristic analysis. Cut‐off values were validated using a multivariate logistic regression model. Results Average aLpRNFL in progressing patients (2.4 μm, SD 2.1) was significantly higher compared to stable patients (0.5 μm, SD 1.2, P < 0.001). At a predefined specificity of 90%, aLpRNFL >1.5 μm was able to distinguish between stable and progressing RRMS with a sensitivity of 76.1%. aLpRNFL >1.5 μm was associated with a 15‐fold increased risk of clinically progressing MS ( P < 0.001). Conclusions A cut‐off of aLpRNFL discriminating clinically progressing and stable RRMS was identified. After validation in independent cohorts, this cut‐off could be used as a biomarker of axonal degeneration supporting disease monitoring in daily clinical routine.