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Two Suspected Worksite or Occupational Cancer Clusters Investigated Using the Cancer Data Registry and Multiple Primary Standardized Incidence Ratios in SEER*Stat—Idaho, 2013–2014
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2016
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Source: J Registry Manag. 41(3):128-133
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Alternative Title:J Registry Manag
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Description:Background:
Investigations of suspected cancer clusters are resource intensive and rarely identify true clusters: among 428 publicly reported US investigations during 1990–2011, only 1 etiologic cluster was identified. In 2013, the Cancer Data Registry of Idaho (CDRI) was contacted regarding a suspected cancer cluster at a worksite (Cluster A) and among an occupational cohort (Cluster B). We investigated to determine whether these were true clusters.
Methods:
We derived investigation cohorts for Cluster A from facility-provided employee records and for Cluster B from professional licensing records. We used Registry Plus™ Link Plus to conduct probabilistic linkage of cohort members to the CDRI registry and completed matching through manual review by using LexisNexis®, Accurint®, and the Social Security Death Index. We calculated standardized incidence ratios (SIR) using the MP-SIR session type in SEER*Stat and Idaho and US referent populations.
Results:
For Cluster A, we identified 34 cancer cases during 9,689 person-years; compared with Idaho and US rates, 95% CIs for SIRs included 1.0 for 24 of 24 primary site categories. For Cluster B, we identified 78 cancer cases during 15,154 person-years; compared with Idaho rates, 95% CI for SIRs included 1.0 for 23 of 24 primary site categories and was less than 1.0 for lung and bronchus cancers, and compared with US rates, 95% CI for SIRs included 1.0 for 22 of 24 primary site categories and was less than 1.0 for lung and bronchus and colorectal cancers.
Conclusion:
We identified no statistically significant excess in cancer incidence in either cohort. SEER*Stat’s MP-SIR is an efficient tool for performing SIR assessments, a Centers for Disease Control and Prevention/Council of State and Territorial Epidemiologists–recommended step when investigating suspected cancer clusters.
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Pubmed ID:28121313
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Pubmed Central ID:PMC7147979
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