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Multiple endocrine neoplasia type 1: extensive analysis of a large database of Florentine patients
Francesca Marini1, Francesca Giusti1, Maria Luisa Brandi2
1Department of Surgery and Translational Medicine, University of Florence, Largo Palagi 1, 50139, Florence, Italy.
Background:
Multiple endocrine neoplasia (MEN1) is a rare inherited multi-tumour syndrome, affecting specific neuroendocrine organs and non-endocrine tissues with a variable spectrum of over 20 possible different combinations, caused by inactivating heterozygote mutations of the MEN1 gene. Disease onset, penetrance, clinical presentation, course and prognosis are all extremely variable, even among individuals bearing the same causative mutation, which doesn't allow prediction of the individual clinical phenotype (based on the specific result of the genetic test), thus compelling all patients and mutation carriers to undergo a common routine general screening program.
Results:
We performed an extensive epidemiological, clinical and genetic analysis of the Florentine MEN1 patient database, which includes 145 MEN1 patients and 20 asymptomatic MEN1 carriers, constantly followed up at the Regional Referral Centre for Inherited Endocrine Tumours of the Tuscany Region, during the last three decades. We reported, here, the results of clinical, epidemiological and genetic descriptive statistics, as well as correlation analyses between tumours and mutation types and localisation. No direct genotype-phenotype correlation was described, but the importance of the genetic testing was confirmed for an early diagnosis and the identification of asymptomatic carriers.
Conclusions:
As with all rare diseases, the possibility to collect and analyse data on a relatively large number of patients is important for increasing our knowledge of the epidemiologic aspects of the disease, and its natural course and prognosis of single manifestations of the syndrome, in order to set up the best diagnostic and therapeutic plans for patients. In this light, the creation and constant updating of large patient databases is fundamental. Results from database study can provide useful epidemiological, clinical and genetic information about MEN1 syndrome, which could help clinicians in the diagnostic and therapeutic management of single MEN1 patients.
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