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Endocrine Abstracts (2018) 56 P616 | DOI: 10.1530/endoabs.56.P616

ECE2018 Poster Presentations: Environment, Society and Governance Neuroendocrinology (1 abstracts)

Use of a new classification algorithm based on administrative health databases to estimate incidence and prevalence of acromegaly in Piedmont Region, Italy

Marina Caputo 1 , Andrealuna Ucciero 2 , Chiara Mele 1 , Lucrezia De Marchi 1 , Corrado Magnani 2 , Paolo Marzullo 1 , Francesco Barone-Adesi 3 & Gianluca Aimaretti 1


1Endocrinology, Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy; 2Statistics and Epidemiology, Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy; 3Epidemiology, Department of Pharmacological Sciences, Università degli Studi del Piemonte Orientale, Novara, Italy.


Background and aim: Information on incidence and prevalence of acromegaly usually originates from studies performed in referral endocrine care centers, whose catchment areas do not generally cover the entire population. Administrative databases can provide key information to assess the impact of acromegaly on patients and health systems. Our study aimed at estimating the prevalence and incidence data of acromegaly stratified by age and sex using data obtained in the Piedmont region, Italy.

Methods: A retrospective study was conducted in the Piedmont region from January 1st 2012 to December 31th 2016 using administrative health databases of hospital discharge forms, certification of chronic diseases, drug prescriptions, specialist outpatients, and radiological data. Cases of acromegaly were defined if at least two claims from the four following databases were accomplished: i) hospital records with acromegaly diagnosis code (ICD-9-CM: 253.0); ii) exemptions from co-payment for acromegaly (code: 001); iii) prescriptions for Octreotide LAR, Lanreotide Autogel, Pegvisomant, Pasireotide LAR; iv) prescriptions for pituitary MRI or CT scans. Cases were excluded if subjects received less than three separate drug prescriptions or if carrying a diagnosis different from acromegaly.

Results: In the period 2012–2016, 369 individuals (M=146, F=223) were documented in the Piedmont population meeting our criteria for acromegaly. Overall incidence was 5.3 per million population per year (95% CI: 4.2–6.7), and overall prevalence was 83 cases per million inhabitants (95% CI: 75–92). Mean age was 50.9 years. Both incidence and prevalence rates were slightly higher among women (Rate Ratio: 1.08, Prevalence Ratio: 1.43). Age-specific incidence rates were similar in the two sexes up to the age of 39 years but seemed to diverge thereafter, with an increasing trend among men. Prevalence was substantially higher in women between 40 and 80 years of age and increased continuously up to 79 years in both sexes.

Conclusions: This is the first population-based study conducted in Italy to estimate incidence and prevalence of acromegaly. Current results are consistent with the available literature on this topic and show a higher prevalence than previously reported. Even if our algorithm requires proper validation, it could represent a comprehensive tool to describe the pattern of acromegaly, to assess its burden on patients and health care systems, and to provide guidance on resources allocation, especially in countries were national registries on acromegaly are not available.

Volume 56

20th European Congress of Endocrinology

Barcelona, Spain
19 May 2018 - 22 May 2018

European Society of Endocrinology 

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