Retinal layer thickness predicts disability accumulation in early relapsing multiple sclerosis

Abstract

Background and purpose: This study was undertaken to investigate baseline peripapillary retinal nerve fiber layer (pRNFL) and macular ganglion cell and inner plexiform layer (GCIPL) thickness for prediction of disability accumulation in early relapsing multiple sclerosis (RMS).

Methods: From a prospective observational study, we included patients with newly diagnosed RMS and obtained spectral-domain optical coherence tomography scan within 90 days after RMS diagnosis. Impact of pRNFL and GCIPL thickness for prediction of disability accumulation (confirmed Expanded Disability Status Scale [EDSS] score ≥ 3.0) was tested by multivariate (adjusted hazard ratio [HR] with 95% confidence interval [CI]) Cox regression models.

Results: We analyzed 231 MS patients (mean age = 30.3 years, SD = 8.1, 74% female) during a median observation period of 61 months (range = 12-93). Mean pRNFL thickness was 92.6 μm (SD = 12.1), and mean GCIPL thickness was 81.4 μm (SD = 11.8). EDSS ≥ 3 was reached by 28 patients (12.1%) after a median 49 months (range = 9-92). EDSS ≥ 3 was predicted with GCIPL < 77 μm (HR = 2.7, 95% CI = 1.6-4.2, p < 0.001) and pRNFL thickness ≤ 88 μm (HR = 2.0, 95% CI = 1.4-3.3, p < 0.001). Higher age (HR = 1.4 per 10 years, p < 0.001), incomplete remission of first clinical attack (HR = 2.2, p < 0.001), ≥10 magnetic resonance imaging (MRI) lesions (HR = 2.0, p < 0.001), and infratentorial MRI lesions (HR = 1.9, p < 0.001) were associated with increased risk of disability accumulation, whereas highly effective disease-modifying treatment was protective (HR = 0.6, p < 0.001). Type of first clinical attack and presence of oligoclonal bands were not significantly associated.

Conclusions: Retinal layer thickness (GCIPL more than pRNFL) is a useful predictor of future disability accumulation in RMS, independently adding to established markers.

Keywords: biomarker; disability; multiple sclerosis; optical coherence tomography; predictor; retina.