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. 2021 Mar 12:13:59-69.
doi: 10.2147/EB.S295610. eCollection 2021.

Evaluation of Retinal Layer Thickness Parameters as Biomarkers in a Real-World Multiple Sclerosis Cohort

Affiliations

Evaluation of Retinal Layer Thickness Parameters as Biomarkers in a Real-World Multiple Sclerosis Cohort

Natascha Schurz et al. Eye Brain. .

Abstract

Purpose: Retinal layer thickness parameters measured by optical coherence tomography (OCT) are emerging biomarkers of neuroaxonal degeneration and inflammation in multiple sclerosis (MS). We aimed to evaluate the value of retinal layer thickness for prediction of disability worsening and relapse in a real-world MS cohort.

Patients and methods: For this longitudinal observational study, we included MS patients with spectral-domain OCT scans available and ≥1 year of clinical follow-up. The value of peripapillary retinal nerve fiber layer (pRNFL), macular ganglion-cell-and-inner-plexiform-layer (GCIPL) and inner nuclear layer (INL) thickness for prediction of disability worsening and relapse during the observation period was tested by multivariate models.

Results: We analyzed 60 MS patients during a mean observation period of 2.9 years (SD 1.8). Lower baseline thickness of GCIPL (cut-off <77µm; HR 4.1, p=0.001) and pRNFL (cut-off ≤88µm; HR 3.1, p=0.019) were associated with an increased risk of disability worsening. Longitudinally, mean thinning rates were -0.8µm/year (SD 1.6) for GCIPL, -0.6µm/year (SD 3.5) for pRNFL. GCIPL thinning ≥1.0µm/year and pRNFL >1.5µm/year is associated with higher likelihood of disability worsening (HR 5.7, p=0.009 and HR 6.8, p=0.003, respectively). INL thickened in patients with relapse by a mean 0.9µm while thinning by 0.3µm in patients without relapse (p=0.04). In multivariate analyses, INL thickening was associated with an increased probability of relapse (OR 17.8, p=0.023).

Conclusion: Cross-sectional and longitudinal measurement of GCIPL and pRNFL thinning is reliable as a biomarker of disability worsening in a real-world setting. Change of INL thickness is a promising marker of relapse, i.e. inflammatory activity.

Keywords: biomarker; multiple sclerosis; optical coherence tomography; progression; relapse; retinal thinning.

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Conflict of interest statement

Natascha Schürz and Lydia Sariaslani are co-first authors for this study. Fritz Leutmezer has participated in meetings sponsored by, received speaker honoraria or travel funding from Actelion, Almirall, Biogen, Celgene, MedDay, Merck, Novartis, Roche, Sanofi-Genzyme and Teva, and received honoraria for consulting Biogen, Celgene, Merck, Novartis, Roche, Sanofi-Genzyme and Teva. Christoph Mitsch has received honoraria for consultancy/speaking (incl. funds for e-learning modules) from Bayer, Novartis and Takeda. Berthold Pemp has received honoraria for consulting from Novartis. Paulus Rommer has received honoraria for consultancy/speaking from AbbVie, Almirall, Alexion, Biogen, Merck, Novartis, Roche, Sandoz, Sanofi Genzyme, has received research grants from Amicus, Biogen, Merck, Roche. Thomas Berger has participated in meetings sponsored by and received honoraria (lectures, advisory boards, consultations) from pharmaceutical companies marketing treatments for MS: Allergan, Bayer, Biogen, Bionorica, Celgene, MedDay, Merck, Novartis, Octapharma, Roche, Sanofi-Genzyme, Teva. His institution has received financial support in the past 12 months by unrestricted research grants (Biogen, Bayer, Merck, Novartis, Sanofi Aventis, Teva and for participation in clinical trials in multiple sclerosis sponsored by Alexion, Bayer, Biogen, Merck, Novartis, Octapharma, Roche, Sanofi-Genzyme, Teva. Gabriel Bsteh has participated in meetings sponsored by, received speaker honoraria or travel funding from Biogen, Celgene, Lilly, Merck, Novartis, Sanofi-Genzyme and Teva, and received honoraria for consulting Biogen, Celgene, Merck, Novartis, Roche and Teva. The authors report no other conflicts of interest in this work.

Figures

Figure 1
Figure 1
Patient inclusion flow chart.
Figure 2
Figure 2
Risk of disability worsening according to pRNFL (Panel (A)) and GCIPL (B) at baseline.
Figure 3
Figure 3
Differences in annualized thinning of pRNFL (aLpRNFL), GCIPL (aLGCIPL) and change in INL according to disability worsening (Panel (A)) and relapse activity (B).
Figure 4
Figure 4
Risk of disability worsening according to aLpRNFL (Panel (A)) and aLGCIPL (B).

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