Prevalence of multiple sclerosis in the Lazio region, Italy: use of an algorithm based on health information systems

Anna Maria Bargagli, Paola Colais, Nera Agabiti, F. Mayer, F. Buttari, Diego Centonze, Marta Di Folco, Graziella Filippini, Ada Francia, Simonetta Galgani, C. Gasperini, Manuela Giuliani, Massimiliano Mirabella, Viviana Nociti, C. Pozzilli, Marina Davoli

Research output: Contribution to journalArticlepeer-review


Compared with other areas of the country, very limited data are available on multiple sclerosis (MS) prevalence in Central Italy. We aimed to estimate MS prevalence in the Lazio region and its geographical distribution using regional health information systems (HIS). To identify MS cases we used data from drug prescription, hospital discharge and ticket exemption registries. Crude, age- and gender-specific prevalence estimates on December 31, 2011 were calculated. To compare MS prevalence between different areas within the region, we calculated age- and gender-adjusted prevalence and prevalence ratios using a multivariate Poisson regression model. Crude prevalence rate was 130.5/100,000 (95 % CI 127.5–133.5): 89.7/100,000 for males and 167.9/100,000 for females. The overall prevalence rate standardized to the European Standard Population was 119.6/100,000 (95 % CI 116.8–122.4). We observed significant differences in MS prevalence within the region, with estimates ranging from 96.3 (95 % CI 86.4–107.3) for Latina to 169.6 (95 % CI 147.6–194.9) for Rieti. Most districts close to the coast showed lower prevalence estimates compared to those situated in the eastern mountainous area of the region. In conclusion, this study produced a MS prevalence estimate at regional level using population-based health administrative databases. Our results showed the Lazio region is a high-risk area for MS, although with an uneven geographical distribution. While some limitations must be considered including possible prevalence underestimation, HIS represent a valuable source of information to measure the burden of SM, useful for epidemiological surveillance and healthcare planning.

Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalJournal of Neurology
Publication statusAccepted/In press - Feb 17 2016


  • Epidemiology
  • Health administrative data
  • Health information systems
  • Multiple sclerosis
  • Prevalence

ASJC Scopus subject areas

  • Clinical Neurology
  • Neurology


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