Cancer Institute, the Fourth Hospital of Hebei Medical University, No.12 Jiankang Road, Changan district, Shijiazhuang, 050011, Hebei Province, China.
BMC Pulm Med. 2023 May 24;23(1):182. doi: 10.1186/s12890-023-02480-x.
For North Chinese lung cancer patients, there is limited study on the distribution of air pollution and smoking related features based on analyses of large-scale, high-quality population datasets. The aim of the study was to fully analyze risk factors for 14604 Subjects.
Participants and controls were recruited in 11 cities of North China. Participants' basic information (sex, age, marital status, occupation, height, and weight), blood type, smoking history, alcohol consumption, history of lung-related diseases and family history of cancer were collected. PM2.5 concentration data for each year in each city of the study area from 2005 to 2018 were extracted based on geocoding of each person's residential address at the time of diagnosis. Demographic variables and risk factors were compared between cases and matched controls using a univariate conditional logistic regression model. Multivariate conditional logistic regression models were applied to estimate the odds ratio (OR) and 95% confidence interval (CI) for risk factors in univariate analysis. The nomogram model and the calibration curve were developed to predict lung cancer probability for the probability of lung cancer.
There was a total of 14604 subjects, comprising 7124 lung cancer cases and 7480 healthy controls included in the study. Marital status of unmarried persons, people with a history of lung-related disease, corporate personnel and production /service personnel were protective factors for lung cancer. People younger than 50 years old, people who were smoking and quit smoking, people who had been drinking consistently, people with family history of cancer and PM2.5 exposure were proven to be a risk factor for lung cancer. The risk of lung cancer varied with sex, smoking status and air pollution. Consistent alcohol consumption, persistent smoking and smoking quit were risk factors for lung cancer in men. By smoking status, male was risk factor for lung cancer in never smokers. Consistent alcohol consumption added risk for lung cancer in never smokers. The combined effects of PM2.5 pollution exposure and ever smoking aggravated the incidence of lung cancer. According to air pollution, lung cancer risk factors are completely different in lightly and heavily polluted areas. In lightly polluted areas, a history of lung-related disease was a risk factor for lung cancer. In heavily polluted areas, male, consistent alcohol consumption, a family history of cancer, ever smokers and smoking quit were all risk factors for lung cancer. A nomogram was plotted and the results showed that PM2.5 was the main factor affecting the occurrence of lung cancer.
The large-scale accurate analysis of multiple risk factors in different air quality environments and various populations, provide clear directions and guidance for lung cancer prevention and precise treatment.
对于中国北方的肺癌患者,基于大规模、高质量的人群数据集进行分析,有关空气污染和吸烟相关特征的分布研究还很有限。本研究的目的是全面分析 14604 名受试者的危险因素。
在华北 11 个城市招募了参与者和对照组。收集了参与者的基本信息(性别、年龄、婚姻状况、职业、身高和体重)、血型、吸烟史、饮酒史、肺部相关疾病史和癌症家族史。根据每个人在诊断时的居住地址的地理编码,提取了研究区域内各城市 2005 年至 2018 年每年的 PM2.5 浓度数据。使用单因素条件逻辑回归模型比较病例和匹配对照之间的人口统计学变量和危险因素。应用多因素条件逻辑回归模型估计单因素分析中危险因素的比值比(OR)和 95%置信区间(CI)。建立列线图模型和校准曲线来预测肺癌概率。
共纳入 14604 例,其中 7124 例为肺癌病例,7480 例为健康对照。未婚、有肺部相关疾病史、企业人员和生产/服务人员为肺癌的保护因素。50 岁以下、吸烟和戒烟、持续饮酒、有癌症家族史和 PM2.5 暴露的人被证明是肺癌的危险因素。肺癌的风险因性别、吸烟状况和空气污染而异。持续饮酒、持续吸烟和戒烟是男性肺癌的危险因素。按吸烟状况,从不吸烟者中男性是肺癌的危险因素。持续饮酒增加了从不吸烟者的肺癌风险。PM2.5 污染暴露和持续吸烟的联合作用加重了肺癌的发生。根据空气污染,不同污染程度地区的肺癌危险因素完全不同。在轻度污染地区,肺部相关疾病史是肺癌的危险因素。在重度污染地区,男性、持续饮酒、癌症家族史、曾吸烟者和戒烟者均为肺癌的危险因素。绘制了列线图,结果表明 PM2.5 是影响肺癌发生的主要因素。
在不同空气质量环境和不同人群中对多个危险因素进行大规模准确分析,为肺癌预防和精准治疗提供了明确的方向和指导。