Spatial analysis of lung, colorectal, and breast cancer on Cape Cod: an application of generalized additive models to case-control data.
Spatial analysis of lung, colorectal, and breast cancer on Cape Cod: an application of generalized additive models to case-control data.
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DOI：
10.1186/1476-069x-4-11
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发表时间：
2005-06-14
期刊：
影响因子：
--
通讯作者：
Ozonoff, David
中科院分区：
文献类型：
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作者：
Vieira, Veronica;Webster, Thomas;Ozonoff, David
背景技术背景：从癌症和出生缺陷登记处获得的地理信息增加了公众对调查感知疾病群的需求。许多社区级别的聚类调查在方法上存在问题，而根据登记数据绘制的地图往往忽略了延迟和许多已知的风险因素。以人群为基础的病例对照和队列研究提供了一个更强大的基础，空间流行病学，因为潜在的混杂因素和疾病潜伏期可以addressed.METHODS：我们调查了居住和结直肠癌，肺癌和乳腺癌之间的关联上科德角，马萨诸塞州（美国）使用广泛的数据，协变量和居住历史的两个病例对照研究为1983-1993年。我们使用广义加性模型生成地图，在调整协变量的同时对经度和纬度进行平滑。由此产生的连续表面估计相对于整个研究区域的疾病率。我们使用排列检验来检查模型中位置的整体重要性，并确定风险增加和降低的区域。假设有15年的潜伏期，肺癌在马萨诸塞州军事保留地东北部的发病率显著升高，尽管当我们只限于居住时间最长的地区时，结果并不成立。早期的非空间流行病学发现肺癌与保留地上的枪支和迫击炮位置之间的联系很弱。随着我们增加潜伏期并调整协变量，乳腺癌热点的幅度往往会增加，这表明混杂因素部分隐藏了这些区域。显著的乳腺癌热点位于附近已知的地下水羽流和马萨诸塞州军事Reservation.Discussion：空间流行病学的人口为基础的病例对照研究解决了许多方法的批评集群研究，并产生新的曝光假说。我们的研究结果为上科德角乳腺癌的空间聚集性提供了证据。该分析建议根据详细的暴露模型进一步调查乳腺癌和污染羽流之间的潜在联系。
BACKGROUND: The availability of geographic information from cancer and birth defect registries has increased public demands for investigation of perceived disease clusters. Many neighborhood-level cluster investigations are methodologically problematic, while maps made from registry data often ignore latency and many known risk factors. Population-based case-control and cohort studies provide a stronger foundation for spatial epidemiology because potential confounders and disease latency can be addressed.METHODS: We investigated the association between residence and colorectal, lung, and breast cancer on upper Cape Cod, Massachusetts (USA) using extensive data on covariates and residential history from two case-control studies for 1983-1993. We generated maps using generalized additive models, smoothing on longitude and latitude while adjusting for covariates. The resulting continuous surface estimates disease rates relative to the whole study area. We used permutation tests to examine the overall importance of location in the model and identify areas of increased and decreased risk.RESULTS: Maps of colorectal cancer were relatively flat. Assuming 15 years of latency, lung cancer was significantly elevated just northeast of the Massachusetts Military Reservation, although the result did not hold when we restricted to residences of longest duration. Earlier non-spatial epidemiology had found a weak association between lung cancer and proximity to gun and mortar positions on the reservation. Breast cancer hot spots tended to increase in magnitude as we increased latency and adjusted for covariates, indicating that confounders were partly hiding these areas. Significant breast cancer hot spots were located near known groundwater plumes and the Massachusetts Military Reservation.DISCUSSION: Spatial epidemiology of population-based case-control studies addresses many methodological criticisms of cluster studies and generates new exposure hypotheses. Our results provide evidence for spatial clustering of breast cancer on upper Cape Cod. The analysis suggests further investigation of the potential association between breast cancer and pollution plumes based on detailed exposure modeling.