The Joint Risks of Hazadous Air Pollulants Among Childhood Cancer Histotypes

有害空气污染物对儿童癌症组织型的联合风险

• 批准号: 7152032
• 负责人: JAMES A THOMPSON
• 金额: $ 7.28万
• 依托单位: TEXAS A&M AGRILIFE RESEARCH
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7152032
• 关键词: clinical research; joints; model; neoplasm /cancer

DESCRIPTION (provided by applicant): The causes of childhood cancer have been elusive and epidemiologic research has resulted in few prevention strategies. Recent reports implicating maternal exposures to hazardous air pollutants (HAPs) offer potential for prevention strategies. This potential is especially promising because HAPs have been linked to multiple cancer histotypes in a manner analogous to the links between cigarette smoke and cancer. However, the extent of joint or correlated risks and the overall potential for prevention remain unknown. Recent developments in Bayesian hierarchal modeling offer powerful and novel tools for modeling this potential. The objective of this application is to estimate and model environmental risks among multiple childhood cancers. The central hypothesis is that maternal exposures to HAPs present common risks for multiple childhood cancers. This hypothesis will be tested by two specific aims, which are strongly supported by preliminary analysis of the Texas Childhood Cancer Database and birth records from the Texas Department of State Health Services. Specific Aim 1) For specific childhood cancer histotypes, model the risks attributable to county-level HAPs releases. The products of this aim will be county-level risk estimates that will be modeled as functions of county-level HAPs. The results of this Specific Aim will help target specific locations and suspect HAPs for further investigation. Specific Aim 2) Model the gradients of childhood cancer risk around point-source HAPs release-sites. This specific aim will utilize Bayesian hierarchal modeling and will result in the estimation of risk-gradients around the release-sites. The results of this Specific Aim will help design sampling strategies near point-source HAPs releases for future studies. The approach is innovative, because it capitalizes on recently developed multivariate Bayesian mapping and analytical techniques. The proposed research is significant because the results will estimate the extent that common risk to multiple childhood cancer histotypes can be attributed to releases of HAPs. This study will identify the areas of high risk and the associated HAPs exposures, information essential to elucidate the role of HAPs and to guide further study.

描述（由申请人提供）：儿童癌症的原因一直难以捉摸，流行病学研究导致很少的预防策略。最近的报告表明产妇接触危险空气污染物（HAP），这为预防策略提供了可能性。这种潜力特别有希望，因为HAP与多种癌症组织型有关，其方式类似于香烟烟雾与癌症之间的联系。然而，联合或相关风险的程度以及预防的总体潜力仍然未知。贝叶斯层次模型的最新发展提供了强大的和新颖的工具，这种潜力的建模。该应用程序的目的是估计和模拟多种儿童癌症的环境风险。核心假设是母亲暴露于HAP会导致多种儿童癌症的常见风险。这一假设将通过两个具体目标进行检验，这两个目标得到了德克萨斯州儿童癌症数据库和德克萨斯州卫生服务部出生记录的初步分析的有力支持。具体目标1）对于特定的儿童癌症组织型，建立可归因于县级HAP释放的风险模型。这一目标的产品将是县级风险估计，将模拟县级HAP的功能。这一特定目标的结果将有助于针对特定地点和可疑的HAP进行进一步调查。具体目标2）模拟点源HAP释放位点周围的儿童癌症风险梯度。这一特定目标将利用贝叶斯分层建模，并将导致对释放地点周围的风险梯度进行估计。这一特定目标的结果将有助于设计采样策略附近的点源有害生物释放的未来研究。该方法是创新的，因为它利用了最近开发的多元贝叶斯映射和分析技术。这项拟议中的研究意义重大，因为研究结果将估计多种儿童癌症组织类型的共同风险在多大程度上可归因于HAP的释放。这项研究将确定高风险的领域和相关的HAP暴露，这些信息对于阐明HAP的作用和指导进一步的研究至关重要。