ArticleOrphanet journal of rare diseases2021
Epidemiology of systemic sclerosis: a multi-database population-based study in Tuscany (Italy).
Article in Orphanet journal of rare diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 17 citations in OpenAlex.
- Clinical characteristics and treatment patterns of systemic sclerosis patients in China: a single-center retrospective study.Clinical and experimental medicine · 2025Observational
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- Geographic Clustering of Systemic Sclerosis in Areas of Environmental Pollution.Arthritis care & research · 2025Article
- Real-World Research on Retinal Diseases Using Health Claims Database: A Narrative Review.Diagnostics (Basel, Switzerland) · 2024Review
- Steady decrease in systemic sclerosis mortality rates at younger ages over the past five decades.Rheumatology (Oxford, England) · 2024Article
- Current Concepts on the Pathogenesis of Systemic Sclerosis.Clinical reviews in allergy & immunology · 2023Review
- Clinical significance of serum ferritin in patients with systemic sclerosis.Journal of clinical laboratory analysis · 2022Article
- Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling.Human molecular genetics · 2022Article
- Healthcare Burden of Rare Diseases: A Population-Based Study in Tuscany (Italy).International journal of environmental research and public health · 2022Article
- Orphan Drug Use in Patients With Rare Diseases: A Population-Based Cohort Study.Frontiers in pharmacology · 2022Article
- Clinical and serological characteristics of systemic sclerosis: Experience of a tertiary care center in Pakistan.Archives of rheumatology · 2021Article
- Survival of patients with rare diseases: a population-based study in Tuscany (Italy).Orphanet journal of rare diseases · 2021Article
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Authors and funding
19 authors at 7 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundSystemic Sclerosis (SSc) is a chronic autoimmune disease with a complex pathogenesis that includes vascular injury, abnormal immune activation, and tissue fibrosis. We provided a complete epidemiological characterization of SSc in the Tuscany region (Italy), considering prevalence and incidence, survival, comorbidities and drug prescriptions, by using a multi-database population-based approach. Cases of SSc diagnosed between 1st January 2003 and 31st December 2017 among residents in Tuscany were collected from the population-based Rare Diseases Registry of Tuscany. All cases were linked to regional health and demographic databases to obtain information about vital statistics, principal causes of hospitalization, complications and comorbidities, and drug prescriptions.
resultsThe prevalence of SSc in Tuscany population resulted to be 22.2 per 100,000, with the highest prevalence observed for the cases aged ≥ 65 years (33.2 per 100,000, CI 95% 29.6-37.3). In females, SSc was predominant (86.7% on the total) with an overall sex ratio F/M of 6.5. Nevertheless, males presented a more severe disease, with a lower survival and significant differences in respiratory complications and metabolic comorbidities. Complications and comorbidities such as pulmonary involvement (HR = 1.66, CI 95% 1.17-2.35), congestive heart failure (HR = 2.76, CI 95% 1.80-4.25), subarachnoid and intracerebral haemorrhage (HR = 2.33, CI 95% 1.21-4.48) and malignant neoplasms (HR = 1.63, CI 95% 1.06-2.52), were significantly associated to a lower survival, also after adjustment for age, sex and other SSc-related complications. Disease-modifying antirheumatic drugs, endothelin receptor antagonists, and phosphodiesterase-5 inhibitors were the drugs with the more increasing prevalence of use in the 2008-2017 period.
conclusionsThe multi-database approach is important in the investigation of rare diseases where it is often difficult to provide accurate epidemiological indicators. A population-based registry can be exploited in synergy with health databases, to provide evidence related to disease outcomes and therapies and to assess the burden of disease, relying on a large cohort of cases. Building an integrated archive of data from multiple databases linking a cohort of patients to their comorbidities, clinical outcomes and survival, is important both in terms of treatment and prevention.
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