AIMS Italy is a high-risk area for Multiple Sclerosis (MS) with a prevalence of around 140/105 (2009) with the exception of Sardinia, with about 224 cases/105 (2009). Nowadays, in Italy, prevalence is absolutely higher than the above estimates. Indeed, prevalence is rising due to annual incidence that is higher than annual mortality. In Tuscany a population MS register has been founded but, to date, it’s not yet completed. To monitor disease epidemiology, comorbidities and care pathways, but also to describe the disease burden and to plan its prevention, treatment and management strategies and resource allocation, population-based studies are preferable. Administrative data offer a unique opportunity for population-based prevalence study of chronic diseases such as MS. Our aim is to update the prevalence of MS in Tuscany and to demonstrate its progressive increment. METHODS The prevalence was calculated using a case-finding algorithm based on administrative data: hospitalization, specific MS drug dispensing, disease-specific exemptions from patient copayment, home and residential long-term care and inhabitant registry. To test algorithm sensitivity, we used a true-positive reference cohort of 302 MS patients from the Tuscan MS register. To test algorithm specificity, we used a general population cohort of 2,644,094 individuals who were presumably not affected by MS (who had never effectuated either cranial or spinal cord CT scan or MRI and had never received a neurological outpatient visit within the NHS). We calculated prevalence on three consecutive years (2011, 2012, 2013). RESULTS At prevalence date (31 December), we identified 6,890 cases in 2011, 7,057 in 2012 and 7,330 in 2013 with a rate of 187.9, 191.1 and 195.4/105, respectively. The female:male ratio slightly increased from 2.0 in 2011 to 2.1 in 2012-2013. The sensitivity of algorithm was 98% and its specificity was 99.99%. DISCUSSION We found a progressive increment of prevalence that confirmed our hypothesis of increasing prevalence. Although our validity study demonstrated a high level of sensibility, we could miss some patients, especially individuals with a severe MS, who did not access the healthcare system and who did not use the DMDs included in our algorithm. CONCLUSIONS We confirmed that Tuscany is a high-risk area for MS and that the prevalence is increasing over time. Despite some limitations, we also demonstrated that our algorithm can accurately identify patients and this cohort is suitable to monitor care pathways. Our future aim is to create an integrated dataset with administrative and clinical data from MS register.

Battaglia, M.A., Bezzini, D., Meucci, G., Ulivelli, M., Bartalini, S., Policardo, L., et al. (2015). Increasing prevalence of multiple sclerosis in Tuscany: a study based on validated administrative data. In Atti del congresso nazionale SIN.

Increasing prevalence of multiple sclerosis in Tuscany: a study based on validated administrative data

Mario A. Battaglia;Daiana Bezzini
Writing – Original Draft Preparation
;
Monica Ulivelli;Sabina Bartalini;Laura Policardo;
2015

Abstract

AIMS Italy is a high-risk area for Multiple Sclerosis (MS) with a prevalence of around 140/105 (2009) with the exception of Sardinia, with about 224 cases/105 (2009). Nowadays, in Italy, prevalence is absolutely higher than the above estimates. Indeed, prevalence is rising due to annual incidence that is higher than annual mortality. In Tuscany a population MS register has been founded but, to date, it’s not yet completed. To monitor disease epidemiology, comorbidities and care pathways, but also to describe the disease burden and to plan its prevention, treatment and management strategies and resource allocation, population-based studies are preferable. Administrative data offer a unique opportunity for population-based prevalence study of chronic diseases such as MS. Our aim is to update the prevalence of MS in Tuscany and to demonstrate its progressive increment. METHODS The prevalence was calculated using a case-finding algorithm based on administrative data: hospitalization, specific MS drug dispensing, disease-specific exemptions from patient copayment, home and residential long-term care and inhabitant registry. To test algorithm sensitivity, we used a true-positive reference cohort of 302 MS patients from the Tuscan MS register. To test algorithm specificity, we used a general population cohort of 2,644,094 individuals who were presumably not affected by MS (who had never effectuated either cranial or spinal cord CT scan or MRI and had never received a neurological outpatient visit within the NHS). We calculated prevalence on three consecutive years (2011, 2012, 2013). RESULTS At prevalence date (31 December), we identified 6,890 cases in 2011, 7,057 in 2012 and 7,330 in 2013 with a rate of 187.9, 191.1 and 195.4/105, respectively. The female:male ratio slightly increased from 2.0 in 2011 to 2.1 in 2012-2013. The sensitivity of algorithm was 98% and its specificity was 99.99%. DISCUSSION We found a progressive increment of prevalence that confirmed our hypothesis of increasing prevalence. Although our validity study demonstrated a high level of sensibility, we could miss some patients, especially individuals with a severe MS, who did not access the healthcare system and who did not use the DMDs included in our algorithm. CONCLUSIONS We confirmed that Tuscany is a high-risk area for MS and that the prevalence is increasing over time. Despite some limitations, we also demonstrated that our algorithm can accurately identify patients and this cohort is suitable to monitor care pathways. Our future aim is to create an integrated dataset with administrative and clinical data from MS register.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11365/1035824