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  • Title: Incidence and prevalence of Amyotrophic Lateral Sclerosis in three Italian Regions: a study based on health administrative databases.
    Author: Bacigalupo I, Finocchietti M, Paoletti O, Bargagli AM, Brunori P, Lombardi N, Sciancalepore F, Agabiti N, Kirchmayer U.
    Journal: Epidemiol Prev; 2024; 48(3):201-209. PubMed ID: 38995133.
    Abstract:
    OBJECTIVES: to estimate Amyotrophic Lateral Sclerosis (ALS) incidence and prevalence in three Italian Regions (Lazio, Tuscany, and Umbria), using health administrative databases. DESIGN: retrospective population-based study. SETTING AND PARTICIPANTS: ALS patients residing in Lazio, Umbria, and Tuscany were identified through an algorithm based on three different administrative databases: hospital discharge records, exemptions from health care co-payment, and emergency departments (study period 2014-2019). Crude, age- and gender-specific prevalence were calculated on 31.12.2019 and incidence rates of ALS were standardised by region, year, and gender between 2014-2019. Using a clinical dataset available in the Lazio Region, the proportion of individuals residing in the region correctly identified as ALS cases by the algorithm were calculated. MAIN OUTCOMES MEASURES: prevalence and incidence rates. RESULTS: a total of 1,031 ALS patients (>=18 years) were identified: 408 cases in Tuscany, 546 in Lazio, and 77 in Umbria. ALS standardised prevalence (per 100,000) was similar among regions: 12.31 in Tuscany, 11.52 in Lazio, and 9.90 in Umbria. The 5-year crude rates were higher in men, and in people aged 65-79 years. Among 310 patients included in the clinical dataset, 263 (84.8%) were correctly identified by the algorithm based on health administrative databases. CONCLUSIONS: ALS prevalence and incidence in three Central Italy Regions are rather similar, but slightly higher than those previously reported. This finding is plausible, given that previous results relate to at least ten years ago and evidenced increasing trends. Overall, the results of this paper encourage the use of administrative data to produce occurrence estimates, useful to both epidemiological surveillance and research and healthcare policies.
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