非吸烟女性肺癌风险预测模型的构建研究  

Exploratory research on developing lung cancer risk prediction model in female non-smokers

作　　者：吕章艳 李霓 陈朔华 王刚[3] 谭锋维 冯小双 李鑫 温艳 杨卓煜 王亚龙 李江 陈宏达 林春青 任建松 石菊芳 吴寿岭 代敏 赫捷 Lyu Zhangyan;Li Ni;Chen Shuohua;Wang Gang;Tan Fengwei;Feng Xiaoshuang;Li Xin;Wen Yan;Yang Zhuoyu;Wang Ya long;Li Jiang;Chen Hongda;Lin Chunqing;Ren Jiansong;Shi Jufang;Wu Shouling;Dai Min;He Jie(Office of Cancer Screening,National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100021,China;Health Department of Kailuan(group),Tangshan 063000,China;Department of Oncology,Kailuan General Hospital,Tangshan 063000,China;Department of Thoracic Surgery,National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100021,China)

机构地区：[1]国家癌症中心国家肿瘤临床医学研究中心中国医学科学院北京协和医学院肿瘤医院癌症早诊早治办公室,北京100021 [2]开滦集团员工健康保健中心,唐山063000 [3]开滦总医院肿瘤科,唐山063000 [4]国家癌症中心国家肿瘤临床医学研究中心中国医学科学院北京协和医学院肿瘤医院胸外科,北京100021

出　　处：《中华预防医学杂志》2020年第11期1261-1267,共7页Chinese Journal of Preventive Medicine

基　　金：国家重点研发计划(2O18YFC1315OOO/2O18YFC1315OO1、2018YFC1315000/2O18YFC1315003、2017YFC0907900/2017YFC0907901、2016YFC1302500);中国医学科学院中央级公益性科研院所基本科研业务费(2O19PT32OO27、3332019005、2O18RC33OOO2、2018RC320010、2019PT320023);北京市优秀人才培养资助-青年拔尖团队项目(2017000021223TD05);中国医学科学院医学与健康科技创新工程(2019-I2M-2-002);国家自然科学基金(81871885、81673265);北京协和医学院“协和青年基金”(2017320013);中央保健科研课题(W2017BJ39);北京市科技计划课题(Z181100001718212);中国医学科学院肿瘤医院院所科研课题(LC2017A01)。

摘　　要：目的构建我国非吸烟女性的肺癌风险预测模型。方法于2006年5月至2015年12月,采用巢式病例对照研究设计,基于开滦前瞻性动态队列研究,以随访到的原发性病理学确诊肺癌患者为病例组,以随访期间未发病者为对照组。最终共纳入24701名研究对象,病例组和对照组分别为86、24615名。采用问卷调查、体格检查和实验室检测收集相关信息,采用多因素logistic回归模型建立肺癌风险预测模型,使用曲线下面积(AUC)与Hosmer-Lemeshow检验评价模型的预测效能与拟合度,同时利用十倍交叉验证方法进行预测模型的内部验证。结果共构建了两套风险预测模型:基本模型(纳入年龄与月收入情况2个预测指标)和代谢指标模型(纳入年龄、月收入情况、空腹血糖、总胆固醇和高密度脂蛋白胆固醇5个预测指标)。代谢指标模型的AUC(95%CI)[0.745(0.719~0.771)]大于基本模型的AUC(95%CI)[0.688(0.660~0.716)](P=0.004);基本模型(PHL=0.287)与代谢指标模型(PHL=0.134)的拟合度均良好;十倍交叉验证结果提示代谢指标模型预测效果稳定,平均AUC值为0.699,标准误为0.010。结论通过纳入代谢指标,可构建精准可靠的非吸烟女性肺癌风险预测模型。Objective To develop a lung cancer risk prediction model for female non-smokers.Methods Based on the Kailuan prospective dynamic cohort(2006.05-2015.12),a nested case-control study was conducted.Participants diagnosed with primary pathologically confirmed lung cancer during follow-up were identified as the case group,and others were identified as the control group.A total of 24701 subjects were included in the study,including 86 lung cancer cases and 24615 control population,respectively.Questionnaires,physical examinations,and laboratory tests were conducted to collect relevant information.Multivariable-adjusted logistic regressions were conducted to develop a lung cancer risk prediction model.Area Under the Curve(AUC)and Hosmer-Lemeshow tests were used to evaluate discrimination and calibration,respectively.Ten-fold cross-validation was used for internal validation.Results Two sets of models were developed:the simple model(including age and monthly income)and the metabolic index model[including age,monthly income,fasting blood glucose(FBG),total cholesterol(TC)and high-density lipoprotein cholesterol(HDL-C)].The AUC(95%CI)[0.745(0.719-0.771)]of the metabolic index model was higher than that of the simple prediction model[0.688(0.660-0.716)](P=0.004).Both the simple model(PHL=0.287)and the metabolic index model(PHL=0.134)were well-calibrated.The results of ten-fold cross-validation indicated sufficient stability,with an average AUC of 0.699 and a standard error(SD)of 0.010.Conclusion By incorporating metabolic markers,accurate and reliable lung cancer risk prediction model for female non smokers could be developed.

关 键 词：肿瘤 肺 预测 女性 非吸烟人群 

分 类 号：R734.2[医药卫生—肿瘤]