Neurological Sciences

, Volume 39, Issue 11, pp 1881–1885 | Cite as

Multiple sclerosis incidence in Tuscany from administrative data

  • Daiana BezziniEmail author
  • L. Policardo
  • F. Profili
  • G. Meucci
  • M. Ulivelli
  • S. Bartalini
  • P. Francesconi
  • M. A. Battaglia
Original Article



Italy is a high-risk area for multiple sclerosis with 110,000 prevalent cases estimated at January 2016 and 3400 annual incident cases. To study multiple sclerosis epidemiology, it is preferable to use population-based studies, e.g., with a registry. A valid alternative to obtain data on entire population is from administrative sources.


To estimate the incidence of multiple sclerosis in Tuscany using a case-finding algorithm based on administrative data.


In a previous study, we calculated the prevalence in Tuscany using a validated case-finding algorithm based on administrative data. Incident cases were identified as a subset of prevalent cases among those patients not traced in the years before the analysis period, and the date of the first multiple sclerosis-related claim was considered the incidence date of multiple sclerosis diagnosis. We examined the period 2011–2015.


We identified 1147 incident cases with annual rates ranged from 5.60 per 100,000 in 2011 to 6.58 in 2015.


We found a high incidence rate, similarly to other Italian areas, especially in women, that may explain the increasing prevalence in Tuscany. To confirm this data and to calculate the possible bias caused by our inclusion method, we will validate our algorithm for incident cases.


Multiple sclerosis Incidence Administrative data Tuscany Italy Sex ratio 



This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interest.


  1. 1.
    Atlas of MS 2013: mapping multiple sclerosis around the world. London: Multiple Sclerosis International Federation; 2013. 2013, Accessed 20 March 2017
  2. 2.
    Melcon MO, Correale J, Melcon CM (2014) Is it time for a new global classification of multiple sclerosis? J Neurol Sci 344(1–2):171–181CrossRefGoogle Scholar
  3. 3.
    Bezzini D, Battaglia MA (2017) Multiple sclerosis epidemiology in Europe. Adv Exp Med Biol 958:141–159CrossRefGoogle Scholar
  4. 4.
    Battaglia MA, Bezzini D (2016) Estimated prevalence of multiple sclerosis in Italy in 2015. Neurol Sci 38(3):473–479CrossRefGoogle Scholar
  5. 5.
    Associazione italiana sclerosi multipla. Barometro della sclerosi multipla. 2016, Accessed 20 March 2017
  6. 6.
    Puthenparampil M, Seppi D, Rinaldi F, Federle L, Calabrese M, Perini P, Gallo P, on behalf of the Multiple Sclerosis Epidemiology Veneto Study Group (MuSEV**) (2013) Multiple Sclerosis Epidemiology Veneto Study Group (MuSEV). Increased incidence of multiple sclerosis in the Veneto region, Italy. Mult Scler 19(5):601–604CrossRefGoogle Scholar
  7. 7.
    Solaro C, Ponzio M, Moran E, Tanganelli P, Pizio R, Ribizzi G, Venturi S, Mancardi GL, Battaglia MA (2015) The changing face of MS: prevalence and incidence in an aging population. Mult Scler 21(10):1244–1250CrossRefGoogle Scholar
  8. 8.
    Cocco E, Sardu C, Massa R, Mamusa E, Musu L, Ferrigno P, Melis M, Montomoli C, Ferretti V, Coghe G, Fenu G, Frau J, Lorefice L, Carboni N, Contu P, Marrosu MG (2011) Epidemiology of multiple sclerosis in south-western Sardinia. Mult Scler 17(11):1282–1289CrossRefGoogle Scholar
  9. 9.
    Lix LM, Yogendran MS, Shaw SY, Burchill C, Metge C, Bond R (2008) Population-based data sources for chronic disease surveillance. Chronic Dis Can 29(1):31–38Google Scholar
  10. 10.
    Di Domenicantonio R, Cappai G, Arcà M et al (2014) Occurrence of inflammatory bowel disease in central Italy: a study based on health information systems. Dig Liver Dis 46(9):777–782CrossRefGoogle Scholar
  11. 11.
    Mechati S, Peyro-St-Paul H (2001) iMed: a new electronic database for monitoring patients with multiple sclerosis. Mult Scler 7(1):S31Google Scholar
  12. 12.
    Trojano M, Paolicelli D, Lepore V, Italian MSDN Group et al (2006) Italian Multiple Sclerosis Database Network. Neurol Sci 27(5):S358–S361CrossRefGoogle Scholar
  13. 13.
    Krysko KM, Ivers NM, Young J, O’Connor P, Tu K (2014) Identifying individuals with multiple sclerosis in an electronic medical record. Mult Scler 21(2):217–224CrossRefGoogle Scholar
  14. 14.
    Marrie RA, Yu BN, Leung S, Elliott L, Caetano P, Warren S, Wolfson C, Patten SB, Svenson LW, Tremlett H, Fisk J, Blanchard JF, CIHR Team in the Epidemiology and Impact of Comorbidity on Multiple Sclerosis (2013) The utility of administrative data for surveillance of comorbidity in multiple sclerosis: a validation study. Neuroepid 40(2):85–92CrossRefGoogle Scholar
  15. 15.
    Gini R, Francesconi P, Mazzaglia G, Cricelli I, Pasqua A, Gallina P, Brugaletta S, Donato D, Donatini A, Marini A, Zocchetti C, Cricelli C, Damiani G, Bellentani M, Sturkenboom MCJM, Schuemie MJ (2013) Chronic disease prevalence from Italian administrative databases in the VALORE project: a validation through comparison of population estimates with general practice databases and national survey. BMC Public Health 13:15CrossRefGoogle Scholar
  16. 16.
    Bezzini D, Policardo L, Meucci G, Ulivelli M, Bartalini S, Profili F, Battaglia MA, Francesconi P (2016) Prevalence of multiple sclerosis in Tuscany (Central Italy): a study based on validated administrative data. Neuroepid 46:37–42CrossRefGoogle Scholar
  17. 17.
    Bargagli AM, Colais P, Agabiti N, Mayer F, Buttari F, Centonze D, di Folco M, Filippini G, Francia A, Galgani S, Gasperini C, Giuliani M, Mirabella M, Nociti V, Pozzilli C, Davoli M (2016) Prevalence of multiple sclerosis in the Lazio region, Italy: use of an algorithm based on health information systems. J Neurol 263(4):751–759CrossRefGoogle Scholar
  18. 18.
    Green C, Yu BN, Marrie RA (2013) Exploring the implications of small-area variation in the incidence of multiple sclerosis. Am J Epidemiol 178(7):1059–1066CrossRefGoogle Scholar
  19. 19.
    Widdifield J, Ivers NM, Young J et al (2015) Development and validation of an administrative data algorithm to estimate the disease burden and epidemiology of multiple sclerosis in Ontario, Canada. MSJ 21(8):1045–1054Google Scholar
  20. 20.
    Bruno G, Pagano E, Rossi E, Cataudella S, de Rosa M, Marchesini G, Miccoli R, Vaccaro O, Bonora E (2016) Incidence, prevalence, costs and quality of care of type 1 diabetes in Italy, age 0-29 years: the population-based CINECA-SID ARNO Observatory, 2002-2012. Nutr Metab Cardiovasc Dis 26(12):1104–1111CrossRefGoogle Scholar
  21. 21.
    Valent F, Candido R, Faleschini E, Tonutti L, Tortul C, Zanatta M, Zanette G, Zanier L (2016) The incidence rate and prevalence of pediatric type 1 diabetes mellitus (age 0-18) in the Italian region Friuli Venezia Giulia: population-based estimates through the analysis of health administrative databases. Acta Diabetol 53(4):629–635CrossRefGoogle Scholar
  22. 22.
    Rossini M, Rossi E, Bernardi D, Viapiana O, Gatti D, Idolazzi L, Caimmi C, DeRosa M, Adami S (2014) Prevalence and incidence of rheumatoid arthritis in Italy. Rheumatol Int 34(5):659–664CrossRefGoogle Scholar
  23. 23.
    Beghi E, Logroscino G, Micheli A et al (2001) Validity of hospital discharge diagnoses for the assessment of the prevalence and incidence of amyotrophic lateral sclerosis. Amyotroph Lateral Scler Other Motor Neuron Disord 2(2):99–104Google Scholar
  24. 24.
    Giussani G, Franchi C, Messina P, Nobili A, Beghi E, the EPIRES Group (2014) Prevalence and incidence of epilepsy in a well-defined population of Northern Italy. Epilepsia 55(10):1526–1533CrossRefGoogle Scholar
  25. 25.
    Goutté N, Sogni P, Bendersky N, Barbare JC, Falissard B, Farges O (2016) Geographical variations in incidence, management and survival of hepatocellular carcinoma in Western country. J Hepatol 66(3):537–544CrossRefGoogle Scholar
  26. 26.
    Istat. Popolazione residente. Anno 2011, Anno 2012, Anno 2013, Anno 2014, Anno 2015. Accessed 30 Dec 2016
  27. 27.
    Ahlgren C, Odén A, Lycke J (2014) High nationwide incidence of multiple sclerosis in Sweden. PLoS One 9:e108599CrossRefGoogle Scholar
  28. 28.
    Kampman MT, Aarseth JH, Grytten N, Benjaminsen E, Celius EG, Dahl OP, Holmøy T, Løken-Amsrud K, Midgard R, Myhr KM, Risberg G, Vatne A, Torkildsen Ø (2013) Sex ratio of multiple sclerosis in persons born from 1930 to 1979 and its relation to latitude in Norway. J Neurol 260:1481–1488CrossRefGoogle Scholar
  29. 29.
    Simpson S Jr, Mina S, Morris H, Mahendran S, Taylor B, Boggild M (2015) The epidemiology of multiple sclerosis in the Isle of Man: 2006–2011. Acta Neurol Scand 132:381–388CrossRefGoogle Scholar
  30. 30.
    Akhtar S, Alroughani R, Ahmed SF, Al-Hashel JY (2016) Retrospective cohort study of gender differential in risk of multiple sclerosis in Kuwait. Neuroepid 46(3):203–208CrossRefGoogle Scholar
  31. 31.
    Hirst C, Ingram G, Pickersgill T et al (2009) Increasing prevalence and incidence of multiple sclerosis in South East Wales. J Neurol Neurosurg Psychiatry 80:386–391CrossRefGoogle Scholar
  32. 32.
    Yaouanq J, Tron I, Kerbrat A, Leray E, Hamonic S, Merienne M, Hinault P, Edan G (2015) Register-based incidence of multiple sclerosis in Brittany (north-western France), 2000–2001. Acta Neurol Scand 131:321–328CrossRefGoogle Scholar
  33. 33.
    Hader WJ, Yee IM (2016) Incidence and prevalence of multiple sclerosis in Saskatoon, Saskatchewan. Neuroepid 46(3):203–208CrossRefGoogle Scholar
  34. 34.
    Ponzio M, Gerzeli S, Brichetto G, Bezzini D, Mancardi GL, Zaratin P, Battaglia MA (2015) Economic impact of multiple sclerosis in Italy: focus on rehabilitation costs. Neurol Sci 36(2):227–234CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Italia S.r.l., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Life SciencesUniversity of SienaSienaItaly
  2. 2.Fondazione Italiana Sclerosi Multipla (FISM)GenoaItaly
  3. 3.Agenzia Regionale di Sanità della ToscanaFlorenceItaly
  4. 4.Unit of NeurologyUSL6LivornoItaly
  5. 5.Department of medicine, surgery and neuroscienceUniversity of SienaSienaItaly

Personalised recommendations