Jacquez Geoffrey M, Meliker Jaymie, Kaufmann Andy
BioMedware, Ann Arbor, USA.
Int J Health Geogr. 2007 Aug 23;6:35. doi: 10.1186/1476-072X-6-35.
Space-time interaction arises when nearby cases occur at about the same time, and may be attributable to an infectious etiology or from exposures that cause a geographically localized increase in risk. But available techniques for detecting interaction do not account for residential mobility, nor do they evaluate sensitivity to induction and latency periods. This is an important problem for cancer, where latencies of a decade or more occur.
New case-only clustering techniques are developed that account for residential mobility, latency and induction periods, relevant covariates (such as age) and risk factors (such as smoking). The statistical behavior of the methods is evaluated using simulated data to assess type I error (false positives) and statistical power. These methods are applied to 374 cases from an ongoing study of bladder cancer in 11 counties in southeastern Michigan, and the ability of the methods to localize space-time interaction at the individual-level is demonstrated.
Significant interaction is found for induction periods of approximately 5 years and latency approximately 19.5 years. Data are still being collected and the observed clusters may be attributable to differential sampling in the study area.
Residential histories are increasingly available, raising the possibility of routine surveillance in a manner that accounts for individual mobility and that incorporates models of cancer latency and induction. These new techniques provide a mechanism for identifying those geographic locations and times associated with increases in cancer risk above and beyond that expected given covariates and risk factors in geographically mobile populations.
当附近病例在大致相同时间出现时,就会出现时空交互作用,这可能归因于感染病因或导致地理局部风险增加的暴露因素。但是现有的检测交互作用的技术没有考虑居住流动性,也没有评估对诱导期和潜伏期的敏感性。对于癌症来说,这是一个重要问题,因为癌症的潜伏期可达十年或更长时间。
开发了仅基于新病例的聚类技术,该技术考虑了居住流动性、潜伏期和诱导期、相关协变量(如年龄)和风险因素(如吸烟)。使用模拟数据评估这些方法的统计行为,以评估I型错误(假阳性)和统计功效。这些方法应用于密歇根州东南部11个县正在进行的膀胱癌研究中的374例病例,并展示了这些方法在个体层面定位时空交互作用的能力。
发现诱导期约为5年、潜伏期约为19.5年时存在显著交互作用。数据仍在收集,观察到的聚类可能归因于研究区域的差异抽样。
居住史越来越容易获取,这增加了以考虑个体流动性并纳入癌症潜伏期和诱导模型的方式进行常规监测的可能性。这些新技术提供了一种机制,用于识别那些与地理流动人群中给定协变量和风险因素之外的癌症风险增加相关的地理位置和时间。