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DOI 10.1111/ene.13897

Медицинская библиотека · European journal of neurology · 2019

Peripapillary retinal nerve fibre layer thinning rate as a biomarker discriminating stable and progressing relapsing-remitting multiple sclerosis.

Bsteh G, Hegen H, Teuchner B, Berek K, Wurth S, Auer M, Di Pauli F, Deisenhammer F, Berger T

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Аннотация

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.

Для цитирования: Bsteh G, Hegen H, Teuchner B, Berek K, Wurth S, Auer M, Di Pauli F, Deisenhammer F, Berger T. Peripapillary retinal nerve fibre layer thinning rate as a biomarker discriminating stable and progressing relapsing-remitting multiple sclerosis.. European journal of neurology. 2019. DOI: 10.1111/ene.13897.

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