Prevalence of multiple sclerosis in Tuscany: a study based on administrative data

INTRODUCTION Multiple Sclerosis (MS) affects 2.3 million people world-wide [1]. Italy is a high-risk area (with 75,000 cases estimated), with highest morbidity rates in Sardinia [2]. For the continental Italy, the last published prevalence rate was around 140-170/100,000 in 2005-2009 [3, 4]. 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. AIMS To validate a case-finding algorithm based on administrative data and to update the prevalence of MS in Tuscany at 12/31/2011. METHODS The prevalence was calculated using administrative data: hospitalization, 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). RESULTS At prevalence date, we identified 6,890 cases with a rate of 187.9/100,000 (248.3 in females, 122.3 in males). The sensitivity of algorithm was 98% and its specificity was 99.99%. CONCLUSIONS We found a prevalence higher than the data present in literature but it’s similar to the expected rate considering the progressive increment of prevalence due to annual incidence that is higher than annual mortality. 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. REFERENCES 1. MSIF Atlas of MS 2013 Report. 2. Bilancio Sociale AIM 2013 3. Granieri E, Monaldini C, et al.: Multiple sclerosis in the Republic of San Marino: a prevalence and incidence study. Mult Scler 2008; 14(3): 325-329. 4. Puthenparampil M, Seppi D, et al.; Multiple Sclerosis Epidemiology Veneto Study Group (MuSEV): Increased incidence of multiple sclerosis in the Veneto region, Italy. Mult Scler 2013; 19(5): 601-604