Abstract
BACKGROUND: Epidemiologic analyses of sarcoma are limited by the heterogeneity and rarity of the disease. Utilizing population-based surveillance data enabled us to evaluate the contribution of census tract-level socioeconomic status (CT-SES) and race/ethnicity on sarcoma incidence rates.
METHODS: We utilized the Surveillance, Epidemiology, and End Results program to evaluate associations between CT-SES and race/ethnicity on the incidence rates of sarcoma. Incidence rate ratios and 99% confidence intervals were estimated from quasi-Poisson models. All models were stratified by broad age groups (pediatric: <20 years, adult: 20-65 years, older adult: 65+ years) and adjusted for sex, age, and year of diagnosis. Within each age group, we conducted analyses stratified by somatic genome (fusion-positive and fusion-negative sarcomas) and for subtypes with >200 total cases. A P value less than 0.01 was considered statistically significant.
RESULTS: We included 55,415 sarcoma cases in 35 sarcoma subtype-age group combinations. Increasing CT-SES was statistically significantly associated with 11 subtype-age group combinations, primarily in the older age group strata (8 subtypes), whereas malignant peripheral nerve sheath tumors in adults were associated with decreasing CT-SES. Nearly every sarcoma subtype-age group combination displayed racial/ethnic disparities in incidence that were independent of CT-SES.
CONCLUSIONS: We found race/ethnicity to be more frequently associated with sarcoma incidence than CT-SES. Our findings suggest that genetic variation associated with ancestry may play a stronger role than area-level SES-related factors in the etiology of sarcoma.
IMPACT: These findings provide direction for future etiologic studies of sarcomas.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2141-2148 |
| Number of pages | 8 |
| Journal | Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology |
| Volume | 29 |
| Issue number | 11 |
| DOIs | |
| State | Published - Nov 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 10 Reduced Inequalities
PubMed: MeSH publication types
- Journal Article
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