Development of early progression independent of relapse activity significantly impacts on disability accumulation in

María Agustina Zárate1, Mariano Marrodan1, María Agustina Piedrabuena1

  • 1Departamento de Neurología, Fleni, Buenos Aires, Argentina.

Abstract

Insights

Early progression independent of relapse activity (PIRA) in multiple sclerosis (MS) affects half of patients and is linked to spinal cord onset and older age at diagnosis. Identifying these patients early is crucial for managing long-term disability.

Area of Science:

  • Neurology
  • Clinical Research
  • Epidemiology

Background:

  • Multiple sclerosis (MS) disability accrual stems from relapse-associated worsening (RAW) and progression independent of relapse activity (PIRA).
  • Early PIRA (EP), defined as PIRA within five years of disease onset, is a potential indicator of poor prognosis.
  • Risk factors for EP remain inadequately defined.

Purpose of the Study:

  • To pinpoint clinical and demographic factors linked to EP in MS patients.
  • To evaluate the influence of EP on long-term disability accumulation.

Main Methods:

  • Retrospective cohort study of 143 relapsing-remitting MS patients with PIRA-driven disability progression (EDSS 4, 6, or 8).
  • Patients classified as EP (PIRA within 5 years) or late PIRA (LP, >5 years).
  • Cox regression and Kaplan-Meier analyses used to identify risk factors and assess disability progression.

Main Results:

  • EP occurred in 51% of PIRA patients.
  • EP patients were older at diagnosis (38.6 vs. 34 years), more likely female, and had higher rates of spinal cord onset.
  • EP patients experienced significantly faster accumulation of disability (EDSS 4, 6, 8) compared to LP patients.
  • Spinal cord onset was the strongest predictor of EP (HR=2.1).

Conclusions:

  • EP is prevalent in PIRA patients and associated with spinal cord onset and older age at diagnosis.
  • Early identification and aggressive treatment are vital for mitigating long-term MS disability.
  • Further research is needed to refine predictive models and optimize treatment for high-risk MS patients.