中老年男性慢性阻塞性肺病合并肺癌患者的临床特征分析及数学预测模型的建立

Analysis of Clinical Features and Establishment of Mathematical Prediction Model in Middle-Aged and Elderly Male Patients with Chronic Obstructive Pulmonary Disease Complicated with Lung Cancer

摘要: 目的：分析慢性阻塞性肺病(Chronic Obstructive Pulmonary Disease, COPD)合并肺癌患者的临床资料特征，并建立其风险预测模型。方法：回顾性收集并分析79例COPD合并肺癌患者(共病组)和150例COPD组的临床资料，包括：年龄、体重指数(Body Mass Index, BMI)、吸烟指数、相关实验室检验指标及肺癌病理诊断结果等；使用SPSS 27.0对数据进行单因素及多因素Logistic回归分析筛选出独立危险因素，建立数学预测模型，通过R软件进行模型内部验证及评价。结果：该数学模型由三项危险因素组成，分别为血沉(ESR)、NLR (中性粒细胞计数与淋巴细胞计数比值)、碱性磷酸酶(ALP)。ROC曲线下面积为0.913 (95% CI, 0.844~0.982, P < 0.05)，采用Bootstrap方法进行模型内部验证，抽样次数设置为1000次，在内部验证集，本模型的敏感度为0.828，特异度为0.861，C指数为0.913 (95%置信区间0.839~0.971)，此外校准曲线代表了该模型良好的性能，临床决策曲线(DCA决策曲线)显示该模型可以做出有价值的判断。结论：基于慢性阻塞性肺病合并肺癌的3项危险因素建立的预测模型有较好的预测能力，对于70岁以下男性COPD患者中肺癌的高危人群筛查有一定指导价值。

Abstract: Objective: To analyze the clinical data characteristics of chronic obstructive pulmonary disease (COPD) combined with lung cancer, and to establish a risk prediction model for the patients. Methods: Clinical data of 79 patients with COPD complicated with lung cancer (comorbidity group) and 150 patients with COPD were retrospectively collected and analyzed, including age, body mass index (BMI), smoking index, relevant laboratory test indexes and pathological diagnosis results of lung cancer. SPSS 27.0 was used for single factor and multiple factor Logistic regression analysis to screen out independent risk factors, and a mathematical prediction model was established. R software was used for internal verification and evaluation of the model. Results: The mathematical model was composed of three risk factors, namely erythrocyte sedimentation rate (ESR), NLR (ratio of neutrophil count to lymphocyte count) and alkaline phosphatase. The area under ROC curve was 0.913 (95% CI, 0.844~0.982, P < 0.05). Bootstrap method was used for internal verification of the model, and the sampling times were set to 1000 times. The sensitivity and specificity of this model were 0.828 and 0.861. The C-index was 0.913 (95% confidence interval 0.839~0.971), and the calibration curve represented a good performance of the model, and the clinical decision curve (DCA decision curve) showed that the model could make valuable judgments. Conclusion: The prediction model based on three risk factors of COPD combined with lung cancer has a good predictive ability, and has a certain guiding value for screening high-risk groups of lung cancer in male COPD patients under 70 years old.