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| 老年肺癌患者胸腔镜术后心肺并发症的列线图建立 |
| Construction of a Nomogram for thoracoscopic postoperative cardiopulmonary complications in elderly lung cancer patients |
| 投稿时间：2025-10-14 |
| DOI：10.3969/j.issn.1000-0399.2026.06.007 |
| 中文关键词: 老年 肺癌 胸腔镜 术后心肺并发症 Lasso-logistic回归 列线图 |
| 英文关键词: Lasso-logistic regression Elderly Lung cancer Thoracoscopy Postoperative cardiopulmonary complications Nomogram |
| 基金项目:秦皇岛市科学技术研究与发展计划(编号:202501A102) |
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| 中文摘要: |
| 目的 基于最小绝对收缩和选择算法（Lasso）-logistic回归构建老年肺癌患者胸腔镜术后心肺并发症（PCC）发生风险的列线图，为临床个体化风险评估提供工具。方法 回顾性分析2023年6月至2025年6月在秦皇岛市第一医院胸外科行胸腔镜手术的272例老年肺癌患者的临床资料。根据术后30 d内是否发生PCC，将患者分为PCC发生组（80例）与PCC未发生组（192例）。采用Lasso-logistic回归筛选预测老年肺癌患者胸腔镜PCC发生的变量，以此构建列线图，再用受试者工作特征（ROC）曲线、校准曲线、Hosmer-Lemeshow拟合优度检验进行验证。以决策曲线分析（DCA）评估临床净收益。结果 272例行胸腔镜手术的老年肺癌患者，共80例（构成比29.41%）发生PCC。与PCC未发生组比较，PCC发生组中冠心病、衰弱、营养不良、第一秒用力呼气容积占预计值百分比（FEV1%pred）<70%、六分钟步行距离（6 MWD）<300 m、术中出血量>200 mL、术后24 h内未下床活动的患者比例更高，差异有统计学意义（P<0.05）。Lasso-logistic回归分析结果显示，冠心病（OR=3.753,95%CI:1.670～8.433）、衰弱（OR=4.597,95%CI:2.126～9.936）、FEV1%pred<70%（OR=6.954,95%CI:3.135～15.424）、6 MWD<300 m（OR=3.294,95%CI:1.502～7.226）、术中出血量>200 mL（OR=4.564,95%CI:1.909～10.914）、术后24 h内未下床活动（OR=7.125,95%CI:3.253～15.603）是老年肺癌患者胸腔镜PCC发生的独立危险因素。ROC曲线下面积0.913（95%CI:0.870～0.956）。Apparent、Bias-corrected比较贴合Ideal，且Hosmer-Lemeshow拟合优度检验χ2=6.275,P=0.508。列线图预测老年肺癌患者胸腔镜PCC发生风险的灵敏度81.25%、特异度93.75%、准确度90.07%。DCA曲线显示，阈值概率介于0.08～0.83，该列线图对老年肺癌患者胸腔镜PCC发生风险预测更有利。结论 基于Lasso-logistic回归构建的列线图对老年肺癌患者胸腔镜PCC发生风险的具有良好预测能力，可作为临床围手术期风险分层与个体化干预的可靠工具。 |
| 英文摘要: |
| Objective To construct a Nomogram for thoracoscopic postoperative cardiopulmonary complications（PCC） in elderly lung cancer patients based on the Least Absolute Shrinkage and Selection Operator（Lasso）-Logistic regression, providing tools for individualized risk assessment in clinical practice. Methods A retrospective analysis was conducted on the clinical data of 272 elderly lung cancer patients who underwent thoracoscopic surgery in Department of Thoracic Surgery, Qinhuangdao First Hospital from June 2023 to June 2025. Based on whether PCC occurred within 30 days after the surgery, the patients were divided into the PCC occurrence group（80 cases） and the PCC nonoccurrence group（192 cases）. Lasso-Logistic regression was used to screen variables that predicted the occurrence of thoracoscopic PCC in elderly lung cancer patients, and based on this, a Nomogram was constructed. Then receiver operating characteristic（ROC） curves, calibration curves, and Hosmer Lemeshow goodness of fit tests were used for validation. The clinical net benefit was evaluated using Decision Curve Analysis（DCA）. Results AAmong 272 elderly lung cancer patients who underwent thoracoscopic surgery, a total of 80 cases（accounting for 29.41%） developed PCC. Compared with the group without PCC, the proportions of patients with coronary heart disease, frailty, malnutrition, percentage of predicted forced of expiratory volume in one second（FEV1% pred）<70%, 6-minute walking distance（6MWD）<300m, intraoperative blood loss>200 mL, and lack of mobilization within 24 hours after surgery were higher in the PCC occurrence group, and the differences were statistically significant（P < 0.05）. The results of Lasso-Logistic regression analysis showed that coronary heart disease（OR=3.753）, frailty（OR=4.597）, FEV1% pred<70%（OR=6.954）, 6 MWD<300 m（OR=3.294）, intraoperative blood loss>200mL（OR=4.564）, and lack of mobilization within 24 hours after surgery（OR=7.125） were independent risk factors for thoracoscopic PCC in elderly lung cancer patients. The area under the ROC curve was 0.913（95% CI: 0.870～0.956）. Apparel and Bias-corrected fitted well with Ideal, and the Hosmer-Lemeshow goodness of fit test showed χ2=6.275, P=0.508. The sensitivity, specificity, and accuracy of the Nomogram in predicting the risk of thoracoscopic PCC in elderly lung cancer patients was 81.25%, 93.75%, and 90.07%, respectively. The DCA curve showed that the threshold probability ranged from 0.08 to 0.83, this nomogram was more beneficial for predicting the risk of PCC occurrence in elderly lung cancer patients. Conclusion The Nomogram constructed based on Lasso-Logistic regression has a good predictive ability for the risk of thoracoscopic PCC in elderly lung cancer patients, and can be used as a reliable tool for clinical perioperative risk stratification and individualized intervention. |
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