Cassidy Adrian, Myles Jonathan P, Liloglou Triantafillos, Duffy Stephen W, Field John K
Roy Castle Lung Cancer Research Programme, University of Liverpool Cancer Research Centre, University of Liverpool, Liverpool L3 9TA, UK.
Int J Oncol. 2006 May;28(5):1295-301.
Within the framework of the Liverpool Lung Project (LLP), population-based case-control and prospective cohort studies are in progress to identify molecular and epidemiological risk factors and define populations and individuals most at risk of developing lung cancer. This report describes a strategy for selection of a high-risk population and further provides support for the inclusion of occupational and genetic risk factors in future models. Data from the case-control study (256 incident cases and 314 population controls) were analysed to define a high-risk population. Detailed lifestyle and occupational information were collected during structured interviews. Models were constructed using conditional logistic regression and included terms for age, tobacco consumption and previous respiratory disease. Smoking duration was chosen as the most important predictor of lung cancer risk [>50 years (OR 15.65, 95% CI 6.10-40.15)]. However, such a model would preclude younger individuals. Several combinations of previous respiratory disease were also considered, of which a history of bronchitis, emphysema or pneumonia (BEP) was the most significant (OR 1.86, 95% CI 1.28-2.69). A high-risk subset (based on combinations of smoking duration and BEP) was identified, which have a 4.5-fold greater risk of developing lung cancer (OR 4.5, 95% CI 2.33-8.68). Future refinement of the risk model to include individuals occupationally exposed to asbestos and with the p21 genotypes is discussed. There is real potential for environmental and genetic factors to improve on risk prediction and targeting of susceptible individuals beyond the traditional models based only on smoking and age. The development of a molecular-epidemiological model will inform the development of effective surveillance, early detection and chemoprevention strategies.
在利物浦肺癌项目(LLP)的框架内,基于人群的病例对照研究和前瞻性队列研究正在进行,以确定分子和流行病学风险因素,并确定肺癌发病风险最高的人群和个体。本报告描述了一种选择高危人群的策略,并进一步支持在未来模型中纳入职业和遗传风险因素。对病例对照研究(256例新发病例和314名人群对照)的数据进行分析,以确定高危人群。在结构化访谈中收集了详细的生活方式和职业信息。使用条件逻辑回归构建模型,模型包括年龄、烟草消费和既往呼吸系统疾病等因素。吸烟持续时间被选为肺癌风险的最重要预测因素[>50年(比值比15.65,95%可信区间6.10 - 40.15)]。然而,这样的模型会排除较年轻的个体。还考虑了既往呼吸系统疾病的几种组合,其中支气管炎、肺气肿或肺炎病史(BEP)最为显著(比值比1.86,95%可信区间1.28 - 2.69)。确定了一个高危亚组(基于吸烟持续时间和BEP的组合),其患肺癌的风险高4.5倍(比值比4.5,95%可信区间2.33 - 8.68)。讨论了未来对风险模型的改进,以纳入职业接触石棉和具有p21基因型的个体。环境和遗传因素确实有可能在仅基于吸烟和年龄的传统模型之外,改善对易感个体的风险预测和靶向。分子流行病学模型的开发将为有效的监测、早期检测和化学预防策略的制定提供信息。