Clustering of cutaneous T-cell lymphoma is associated with increased levels of the environmental toxins benzene and trichloroethylene in the state of Georgia.

CANCER(2020)

引用 12|浏览46
暂无评分
摘要
Background Cutaneous T-cell lymphoma (CTCL) is a rare form of non-Hodgkin lymphoma arising in the skin. Geographic clustering of CTCL has recently been reported, but its association with environmental factors is unknown. Benzene and trichloroethylene (TCE) are environmental toxins with carcinogenic properties. The authors investigated associations between geographic clustering of CTCL incidence in the state of Georgia with benzene and TCE exposure. Methods The statewide county-level incidence of CTCL within Georgia was obtained from the Georgia Cancer Registry for the years 1999 to 2015. Standardized incidence ratios (SIRs) were calculated by dividing observed cases by expected cases using national incidence rates by age, sex, and race. Clustering of CTCL was analyzed using spatial analyses. County-level concentrations of benzene and TCE between 1996 and 2014 were collected from the Environmental Protection Agency's National Air Toxics Assessment database. Linear regression analyses on CTCL incidence were performed comparing SIRs with levels of benzene and TCE by county. Results There was significant geographic clustering of CTCL in Georgia, particularly around Atlanta, which was correlated with an increased concentration of benzene and TCE exposure. Among the 4 most populous counties in Georgia, CTCL incidence was between 1.2 and 1.9 times higher than the state average, and benzene and TCE levels were between 2.9 and 8.8 times higher. Conclusions The current results demonstrate nonrandom geographic clustering of CTCL incidence in Georgia. To the authors' knowledge, this is the first analysis to identify a correlation between geographic clustering of CTCL and environmental toxic exposures.
更多
查看译文
关键词
cutaneous T-cell lymphoma,environmental epidemiology,Environmental Protection Agency (EPA),spatial epidemiology,volatile organic compounds
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要