The relative risk of infection in people with multiple sclerosis using disease-modifying treatment: a systematic

M W Y Leung1, E M W Van de Garde1, B M J Uitdehaag2

  • 1Division Pharmacoepidemiology & Clinical Pharmacology, Department of Pharmaceutical Sciences, Faculty of Science, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands.

Abstract

Insights

Observational studies on multiple sclerosis (MS) treatments show sparse infection risk data. Real-world data offers opportunities to study infections in MS patients using disease-modifying therapies (DMTs).

Area of Science:

  • Neurology
  • Infectious Diseases
  • Pharmacovigilance

Background:

  • Disease-modifying treatments (DMTs) for multiple sclerosis (MS) can increase infection risk.
  • Comparative infection risk between clinical trials and real-world observational studies for MS DMTs is not well-established.

Purpose of the Study:

  • To evaluate the current landscape of observational research on infection risk in MS patients using DMTs.
  • To identify gaps in the study of specific DMTs and infection types in real-world MS populations.

Main Methods:

  • Systematic literature search of PubMed and Embase for observational studies up to April 2023.
  • Analysis of studied DMT contrasts, infection types, and frequency.
  • Comparison of observational findings for the most studied DMT with existing clinical trial data from a meta-analysis.

Main Results:

  • 22 observational studies were identified, with only 5 reporting relative risks (RRs).
  • Natalizumab was the most studied DMT, with 12 RRs reported against other DMTs or no DMT.
  • Observed infection risks (respiratory, urinary) in observational data contrasted with clinical trial findings.

Conclusions:

  • Real-world data on infection risk associated with MS DMTs is currently limited.
  • There is a significant opportunity to leverage growing real-world data for robust infection risk assessment in MS.
  • Further research is crucial, especially for populations underrepresented in clinical trials.

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