Department of Community Health Sciences, Brock University, St Catharines, Ontario L2S 3A1, Canada.
Cancer Prev Res (Phila). 2011 Apr;4(4):552-61. doi: 10.1158/1940-6207.CAPR-10-0183. Epub 2011 Mar 16.
Lung cancer is the leading cause of cancer death worldwide. Accurate prediction of lung cancer risk is of value for individuals, clinicians, and researchers. The aims of this study were to characterize the associations between pulmonary function and sputum DNA image cytometry (SDIC) and lung cancer, and their contributions to risk prediction. During 1990 to 2007, 2,596 high-risk individuals were enrolled and followed prospectively for development of lung cancer (n = 139; median follow-up 7.7 years) in trials at the British Columbia Cancer Agency. At baseline, an epidemiologic questionnaire was administered, sputum was collected for aneuploidy measurement and spirometry was obtained. Multivariable logistic models were prepared including known lung cancer predictors (model 1), that additionally included percent-expected-forced expiratory volume in 1 second [forced expiratory volume in 1 second (FEV(1)%), model 2], and that additionally included SDIC (model 3). Prediction was assessed by evaluating discrimination (receiver operator characteristic area under the curve (ROC AUC)) and calibration. Net reclassification indices (NRI) were calculated with cutoff points for 8-year risks identifying low, intermediate, and high risk at 1.5% and 3%. Lung cancer risk increased with decline in FEV(1)%, but did so more for men than for women (interaction P < 0.001). SDIC demonstrated a dose-response with lung cancer (P = 0.022). The ROC AUCs for models 1, 2, and 3 were 0.718 (95% CI: 0.671-0.765), 0.767 (95% CI: 0.725-0.809), and 0.773 (95% CI: 0.732-0.815), respectively. Model 2 versus 1 had a NRI of 12.6% (P < 0.0001) and model 3 versus 2 had a NRI of 3.1% (P = 0.059). Spirometry and SDIC data substantially and minimally improved lung cancer prediction, respectively.
肺癌是全球癌症死亡的主要原因。准确预测肺癌风险对个人、临床医生和研究人员都具有重要价值。本研究的目的是描述肺功能和痰液 DNA 图像细胞计量术（SDIC）与肺癌之间的关联，并探讨它们对风险预测的贡献。1990 年至 2007 年期间，在不列颠哥伦比亚癌症署的试验中，有 2596 名高危个体入组并前瞻性随访其肺癌发生情况（n=139；中位随访时间为 7.7 年）。基线时，进行了流行病学问卷调查、收集痰液进行非整倍体测量以及进行了肺活量测定。多变量逻辑模型包括已知的肺癌预测因子（模型 1），该模型还包括预期 1 秒用力呼气量百分比（FEV1%）（模型 2），该模型还包括 SDIC（模型 3）。通过评估判别能力（受试者工作特征曲线下面积（ROC AUC））和校准来评估预测。计算了净重新分类指数（NRI），使用 8 年风险的切点确定低、中、高危的 1.5%和 3%。肺癌风险随 FEV1%的下降而增加，但男性的增加幅度大于女性（交互 P <0.001）。SDIC 与肺癌呈剂量反应关系（P=0.022）。模型 1、2 和 3 的 ROC AUC 分别为 0.718（95%CI：0.671-0.765）、0.767（95%CI：0.725-0.809）和 0.773（95%CI：0.732-0.815）。模型 2 与模型 1 相比 NRI 为 12.6%（P<0.0001），模型 3 与模型 2 相比 NRI 为 3.1%（P=0.059）。肺功能和 SDIC 数据分别显著和最小程度地改善了肺癌的预测。
