This study aims to assess the association between DMT efficacy and the development of PIRA in individuals with relapsing-remitting MS (RRMS).

Disability accumulation in multiple sclerosis (MS) may occur through relapse-associated worsening (RAW) and progression independent of relapse activity (PIRA). Disease-modifying therapies (DMTs) are intended to reduce relapse rates and delay long-term disability. 

This interim analysis is based on data from a prospective, real-world cohort managed at a tertiary MS center in Argentina, including patients who initiated DMTs between 2011-2019. A retrospective observational approach was employed, using a Cox proportional hazards model to evaluate the association between DMT efficacy and the occurrence of PIRA (binary outcome), adjusting for age at onset, disease duration, and number of treatment switches. DMTs were classified as high- (cladribine tables and monoclonal antibodies), moderate/low-efficacy (other treatments), and treatment switches were modelled as time-dependent covariates. 

Among the 176 patients, 55% were female, with a median age of 32 years (IQR 26–39) at the time of treatment initiation. The mean follow-up duration was 9 years (IQR 7–11).At baseline, 6.2% of patients were receiving high-efficacy disease-modifying therapies (DMTs), 37% moderate-efficacy, and 55.3% low-efficacy DMTs. By the time of analysis, 43% of patients initially on moderate-efficacy DMTs and 74% of those on low-efficacy DMTs had switched treatment due to therapeutic failure. High-efficacy DMTs were associated with a significantly reduced risk of developing PIRA. In contrast, moderateand low-efficacy DMTs were associated with an increased risk of PIRA (HR=7.36, 95% CI 1.9–28, p<0.005). Patients who failed their initial treatment and required a switch were also at increased risk of PIRA (HR=2.56, 95% CI 1.5–4.3, p<0.001).

Early initiation of high-efficacy DMTs may reduce the risk of PIRA in individuals with RRMS. Continued follow-up and analysis of the complete cohort are anticipated to validate these findings and enable more granular subgroup analyses.