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Behçet’s syndrome incidence and prevalence in Sardinia: implications of a latent class analysis combining administrative and clinical data

1, 2, 3, 4, 5, 6, 7, 8, 9, 10

 

  1. Department of Medicine and Public Health, University of Cagliari; and Rheumatology Unit, AOU Cagliari, Italy. matteo.piga@unica.it
  2. Department of Medicine and Public Health, University of Cagliari, Italy.
  3. Department of Medicine and Public Health, University of Cagliari, Italy.
  4. Department of Medicine and Public Health, University of Cagliari; and Rheumatology Unit, AOU Cagliari, Italy.
  5. Regional Epidemiological Observatory, Department of Health and Hygiene, Sardinian Regional Government, Cagliari, Italy.
  6. SSD Reumatologia, ASL Sulcis Iglesiente, Iglesias, Italy.
  7. Ambulatorio di Reumatologia, ASL Nuoro, Italy.
  8. Dipartimento di Medicina, Chirurgia e Farmacia, Università degli Studi di Sassari; and SSD Reumatologia, Azienda Ospedaliero-Universitaria di Sassari, Italy.
  9. Paediatric Clinic and Rare Diseases, Microcitemico Hospital, Department of Medicine and Public Health, University of Cagliari, Italy.
  10. Department of Medicine and Public Health, University of Cagliari; and Rheumatology Unit, AOU Cagliari, Italy.

CER19331
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PMID: 42207566 [PubMed]

Received: 19/09/2025
Accepted : 16/01/2026
In Press: 28/05/2026

Abstract

OBJECTIVES:
To estimate the epidemiology of Behçet’s syndrome (BS) in Sardinia using a combined administrative and clinical data latent class analysis (LCA).
METHODS:
Cases with a diagnosis of BS were retrieved from 2006-2016 in the Hospital Discharge Records (HDRs), 2006-2016 Rare Diseases Regional Register (RDRR), and 2014-2016 in the Specialist Outpatient Database (SOD). Medical records from regional rheumatology clinics were reviewed and classified by the International Criteria for Behçet’s Disease (ICBD) and International Study Group (ISG) criteria. Statistical analysis involved cross-referencing databases and applying LCA to estimate the probability of a BS diagnosis. Prevalence and incidence of BS in Sardinia were calculated, as well as the sensitivity and specificity of each database source.
RESULTS:
Administrative databases analysis retrieved 271 unique cases. A medical record review of 133 patients identified 116 BS cases, of which 107 matched administrative records and 9 were new. After excluding two deaths, 280 cases were considered for analysis (164 administrative-only, 107 mixed, 9 clinical-only). Using ICBD, the LCA confirmed 193 (68.9%) as BS cases (68.3% female, mean age 47). This yielded a 2016 Sardinian BS prevalence of 11.7 per 100,000 inhabitants (15.7) for women and 7.6 for men), with annual incidence rates ranging from 0.24 to 0.48 per 100,000 inhabitants (2014-2016). Prevalence and incidence were lower using the ISG criteria. Database sensitivity varies from 40.6% to 70.5%, while specificity ranges from 16.3% to 99.0%.
CONCLUSIONS:
BS in Sardinia is a rare disease. Relying on a single data source to estimate

DOI: https://doi.org/10.55563/clinexprheumatol/g80tlj

Rheumatology Article