Socioeconomic disparity is associated with faster retinal neurodegeneration in multiple sclerosis.

Disease course in multiple sclerosis is notably heterogeneous, and few prognostic indicators have been consistently associated with multiple sclerosis severity. In the general population, socioeconomic disparity is associated with multimorbidity and may contribute to worse disease outcomes in multiple sclerosis. Herein, we assessed whether indicators of socioeconomic status are associated with disease progression in patients with multiple sclerosis using highly sensitive imaging tools such as optical coherence tomography, and determined whether differential multiple sclerosis management or comorbidity mediate any observed socioeconomic status-associated effects. We included 789 participants with longitudinal optical coherence tomography and low contrast letter acuity (at 1.25 and 2.5%) in whom neighbourhood- (derived via nine-digit postal codes) and participant-level socioeconomic status indicators were available ≤10 years of multiple sclerosis symptom onset. Sensitivity analyses included participants with socioeconomic status indicators available ≤3years of symptom onset (n = 552). Neighbourhood-level indicators included state and national area deprivation indices, median household income and the Agency for Healthcare Research and Quality (AHRQ) Socioeconomic Status Index. Participant-level indicators included education level. Biannual optical coherence tomography scans were segmented to quantify thickness of the composite macular ganglion cell+inner plexiform (GCIPL) layer. We assessed the association between socioeconomic status indicators and GCIPL atrophy or low contrast letter acuity loss using mixed models adjusting for demographic (including race and ethnicity) and disease-related characteristics. We also assessed socioeconomic status indicators in relation to multiple sclerosis therapy changes and comorbidity risk using survival analysis. More disadvantaged neighbourhood-level and patient-level socioeconomic status indicators were associated with faster retinal atrophy. Differences in rate of GCIPL atrophy for individuals in the top quartile (most disadvantaged) relative to the bottom quartile (least) for state area deprivation indices were -0.12 µm/year faster [95% confidence interval (CI): -0.19, -0.04; P = 0.003], for national area deprivation indices were -0.08 µm/year faster (95% CI: -0.15, -0.005; P = 0.02), for household income were -0.11 µm/year faster (95% CI: -0.19, -0.03; P = 0.008), for AHRQ Socioeconomic Status Index were -0.12 µm/year faster (95% CI: -0.19, -0.04) and for education level were -0.17 µm/year faster (95% CI: -0.26, -0.08; P = 0.0002). Similar associations were observed for socioeconomic status indicators and low contrast letter acuity loss. Lower socioeconomic status was associated with higher risk of incident comorbidity during follow-up. Low socioeconomic status individuals had faster rates of therapy escalation, suggesting the association between socioeconomic status and GCIPL atrophy may not be explained by differential contemporaneous multiple sclerosis therapy management. In conclusion, socioeconomic disparity is associated with faster retinal neurodegeneration in multiple sclerosis. As low socioeconomic status was associated with a higher risk of incident comorbidities that may adversely affect multiple sclerosis outcomes, comorbidity prevention may mitigate some of the unfavourable socioeconomic status-associated consequences.