[1]李 迪),段书音),何霞霞),等.基于logistic回归的肺癌危险度评价模型的构建[J].郑州大学学报(医学版),2019,(06):832-834.[doi:10.13705/j.issn.1671-6825.2018.12.127]
 LI Di),DUAN Shuyin),HE Xiaxia),et al.Construction of lung cancer risk assessment model based on logistic regression[J].JOURNAL OF ZHENGZHOU UNIVERSITY(MEDICAL SCIENCES),2019,(06):832-834.[doi:10.13705/j.issn.1671-6825.2018.12.127]
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基于logistic回归的肺癌危险度评价模型的构建()
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《郑州大学学报(医学版)》[ISSN:1671-6825/CN:41-1340/R]

卷:
期数:
2019年06期
页码:
832-834
栏目:
论著
出版日期:
2019-11-20

文章信息/Info

Title:
Construction of lung cancer risk assessment model based on logistic regression
作者:
李 迪1)段书音1)何霞霞1)程明超2)吴拥军1)
1)郑州大学公共卫生学院卫生化学教研室 郑州 450001 2)郑州方达医药科技有限公司 郑州 450000
Author(s):
LI Di1)DUAN Shuyin1)HE Xiaxia1)CHENG Mingchao2)WU Yongjun1)
1)Department of Sanitary Chemistry,College of Public Health,Zhengzhou University, Zhengzhou 450001 2)Zhengzhou Fangda Pharmaceutical Technology Co.Ltd.,Zhengzhou 450000
关键词:
肺癌 早期筛查 危险度评价
Keywords:
lung cancer early screening risk assessment
分类号:
R734.2
DOI:
10.13705/j.issn.1671-6825.2018.12.127
摘要:
目的:应用流行病学资料及临床资料建立肺癌危险度评价模型。方法:收集355例原发性肺癌和444例肺良性疾病患者流行病学资料及临床资料; 另外收集472例为对照组样本,总计1 271例。运用无序多分类logistic回归对1 271例样本的流行病学与临床资料建立肺癌危险度评价模型。结果:性别、抽烟史、肺部良性疾病史、胸闷胸痛、痰中带血、咳嗽、发热出汗、肿瘤家族史、咯血与年龄等10项因素被筛选出(P<0.05),并由此经过logistic回归构建肺癌风险评估模型,该模型总体预测的正确率是70.4%。结论:通过应用流行病学资料及临床资料进行肺癌危险度评价模型构建,对于提高肺癌的早期筛查率具有潜在的应用价值。
Abstract:
Aim:The epidemiological and clinical data were applied to build a risk assessment model for lung cancer.Methods:The epidemiological data and clinical data of 355 patients with primary lung cancer and 444 patients with benign pulmonary diseases were collected, and 472 normal controls accepted physical examination were collected.A disorderly multi-class logistic regression was used to establish a lung cancer risk assessment model using the epidemiological and clinical data of the 3 groups.Results:Some main factors including gender, smoking history, history of benign lung disease, chest distress and chest pain, blood stasis, cough, fever and sweating, family history of cancer, hemoptysis and age were selected(P<0.05), and the risk assessment model for lung cancer had been constructed by logistic regression. The overall prediction accuracy rate of the model was 70.4%.Conclusion:The lung cancer risk assessment model using epidemiological data and clinical data has potential application value for improving the early screening rate of lung cancer.

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备注/Memo

备注/Memo:
【基金项目】国家自然科学基金项目(81573203) 【作者简介】吴拥军,通信作者,男,1968年1月生,博士,教授,研究方向:肺癌早期诊断,E-mail:wuyongjun@zzu.edu.cn
更新日期/Last Update: 2019-11-20