ArticleArthritis care & research2025
Geographic Clustering of Systemic Sclerosis in Areas of Environmental Pollution.
Article in Arthritis care & research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Development and Validation of Algorithms for Systemic Sclerosis Identification in Electronic Health Record Data.ACR open rheumatology · 2026Article
- Correlation of TTLL7-IT1/Hsa-miR-29c-3p/GLS with limited cutaneous systemic sclerosis and exploration of the underlying mechanisms.Frontiers in immunology · 2026Article
- Chromosomal Instability and Telomere Attrition in Systemic Sclerosis: A Historical Perspective.Genes · 2025Review
- Fibrotic Disease of the Skin and Lung: Shared Pathways, Environmental Drivers, and Therapeutic Opportunities in a Changing Climate.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
objectiveSystemic sclerosis (SSc) is a rare autoimmune disease characterized by fibrosis of the skin and other organs. SSc is thought to arise in genetically predisposed individuals with occupational triggers, although further environmental etiologies still need to be identified. Limited research exists detailing which environmental factors lead to the downstream inflammatory and fibrotic symptoms experienced by patients with SSc across the United States. This study describes a retrospective cohort of 179,188 individuals with an SSc or SSc-related diagnosis code enrolled in the Medicare beneficiary program between the years 2014 and 2018.
methodsThe incidence of SSc and SSc-related diagnosis codes in all US zip codes with beneficiary counts greater than 11 was calculated. We conducted global and local Moran's Index (Moran's I) as well as a hot spot analysis with the Getis Ord Gi statistic to determine whether SSc and SSc-related diagnosis codes exhibited clustered or dispersed patterns across the United States. We identified clusters of SSc and SSc-related diagnosis code with high incidences in or around Superfund sites, which are federally identified areas of environmental contamination.
resultsSSc exhibited clustered patterns in two analyzed cohorts based on global Moran's I statistics of 0.588 and 0.521. Results of local Moran's I indicated clusters of disease in Mississippi, New York, Wisconsin, and Michigan, among others. Some zip codes with high disease incidences were home to at least one Superfund site.
conclusionSSc exhibits nonrandom, clustered distributions in a US Medicare beneficiary cohort composed of 179,188 individuals from 2014 to 2018.
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Registered trials
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