{"doi":"10.1371/journal.pone.0290284","title":"Clustering of uveal melanoma: County wide analysis within Ohio","abstract":"PURPOSE: To determine if a greater than expected number of cases (clustering) of uveal melanoma occurred within Ohio for any specific region or time period as compared to others. DESIGN: Analysis of population database. METHODS: Ohio Cancer Incidence Surveillance System (OCISS) database (2000-2019) was accessed for the diagnosis of uveal melanoma using the International Classification of Disease for Oncology codes: C69.3 (choroid), C69.4 (ciliary body and iris). Counties within Ohio were grouped by geographic regions (7) and socioeconomic variables. Age- and race-standardized incidence ratios (SIR) were calculated to determine temporal or geographic clustering. RESULTS: Over the twenty-year period, the total number of uveal melanoma cases reported within Ohio were 1,617 with the overall age-adjusted annual incidence of 6.72 cases per million population (95% CI 6.30-7.16). There was an increase in the incidence of uveal melanoma over 20 years (p<0.001) across seven geographic regions, but no significant difference in incidence rates between the regions. There was no difference in incidence based on county classification by age composition (p = 0.14) or education level (p = 0.11). Counties with a low median household income (p<0.001), those classified as urban (p = 0.004), and those with a greater minority population (p = 0.004) had lower incidence. Less populated counties had a higher incidence of uveal melanoma (p<0.001). CONCLUSIONS: There is no evidence of geographic or temporal clustering of uveal melanoma within Ohio from 2000 to 2019.","journal":"PLoS ONE","year":2023,"id":356322,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8459,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1105466,"name":"Jacquelyn D. Wrenn","orcid":null,"position":1,"is_corresponding":false},{"id":294485,"name":"James Bena","orcid":"0000-0002-7592-0480","position":2,"is_corresponding":false},{"id":1105467,"name":"Guneet S. Sodhi","orcid":null,"position":3,"is_corresponding":false},{"id":1105468,"name":"Katherine Tullio","orcid":null,"position":4,"is_corresponding":false},{"id":268513,"name":"Arun D. Singh","orcid":"0000-0001-9411-0320","position":5,"is_corresponding":false},{"id":1105048,"name":"Leanne M. Clevenger","orcid":"0000-0002-5235-4869","position":0,"is_corresponding":true}],"reference_count":12,"raw_metadata":null,"created_at":"2026-07-19T01:13:25.429924Z","pmid":"37594976","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}