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Abstract
BACKGROUND: Optic neuritis can be the initial manifestation of multiple sclerosis (MS). The purpose of this study was to develop a prognostic model for predicting the risk of MS development among patients with optic neuritis.METHODS: The data from 388 patients with optic neuritis were retrieved from the Optic Neuritis Treatment Trial (ONTT). Cox proportional hazards regression analysis was used to develop a prognostic model. The performance of the model was assessed by using Harrell's C-index and calibration curves. The rates of MS development were estimated using the Kaplan-Meier method.RESULTS: Among the enrolled subjects, a total of 154 (39.7%) patients developed clinically definite MS during a median follow-up period of 15.8 years (interquartile range, 7.2-16.9 years). The factors associated with the development of MS were the presence of brain lesions as on baseline MRI, previous nonspecific neurologic symptoms, commencing low-dose corticosteroids treatment, ocular pain, and absence of optic disc/peripapillary hemorrhage. After incorporating these 5 factors into the prognostic model, a C-index of 0.72 (95% confidence interval [CI], 0.69-0.76) and good calibration curves were obtained. The C-index of the model was significantly higher than the C-indexes of any single factor (P < 0.001 in all cases). The model was able to stratify the ONTT patient cohort into 3 risk groups with significantly different intergroup rates of developing MS (rates for developing MS within a 15-year period: high-risk group, 75.7% [95% CI, 65.6%-82.9%], intermediate-risk group, 44.7% [95% CI, 31.4%-55.4%]; and low-risk group, 20.8% [95% CI, 14.2%-26.8%]; log-rank P < 0.001).CONCLUSIONS: This prognostic model had a better prediction ability when compared with the standard practice that relies solely on using brain lesions on MRI. It can, therefore, help guide decision-making to initiate earlier disease-modifying therapy for patients with optic neuritis at risk of developing MS.
View details for DOI 10.1097/WNO.0000000000001424
View details for PubMedID 34860745