Zhao Di, Ma Anqun, Li Shuang, Fan Jiaming, Li Tianpei, Wang Gongchao
School of Nursing and Rehabilitation, Shandong University, Jinan, China.
Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Front Oncol. 2023 Oct 13;13:1265204. doi: 10.3389/fonc.2023.1265204. eCollection 2023.
Postoperative pulmonary complications (PPCs) significantly increase the morbidity and mortality in elderly patients with lung cancer. Considering the adverse effects of PPCs, we aimed to derive and validate a nomogram to predict pulmonary complications after video-assisted thoracoscopic surgery in elderly patients with lung cancer and to assist surgeons in optimizing patient-centered treatment plans.
The study enrolled 854 eligible elderly patients with lung cancer who underwent sub-lobectomy or lobectomy. A clinical prediction model for the probability of PPCs was developed using univariate and multivariate analyses. Furthermore, data from one center were used to derive the model, and data from another were used for external validation. The model's discriminatory capability, predictive accuracy, and clinical usefulness were assessed using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis, respectively.
Among the eligible elderly patients with lung cancer, 214 (25.06%) developed pulmonary complications after video-assisted thoracoscopic surgery. Age, chronic obstructive pulmonary disease, surgical procedure, operative time, forced expiratory volume in one second, and the carbon monoxide diffusing capacity of the lung were independent predictors of PPCs and were included in the final model. The areas under the ROC curves (AUC) of the training and validation sets were 0.844 and 0.796, respectively. Ten-fold cross-validation was used to evaluate the generalizability of the predictive model, with an average AUC value of 0.839. The calibration curve showed good consistency between the observed and predicted probabilities. The proposed nomogram showed good net benefit with a relatively wide range of threshold probabilities.
A nomogram for elderly patients with lung cancer can be derived using preoperative and intraoperative variables. Our model can also be accessed using the online web server https://pulmonary-disease-predictor.shinyapps.io/dynnomapp/. Combining both may help surgeons as a clinically easy-to-use tool for minimizing the prevalence of pulmonary complications after lung resection in elderly patients.
术后肺部并发症（PPCs）显著增加老年肺癌患者的发病率和死亡率。考虑到PPCs的不良影响，我们旨在推导并验证一个列线图，以预测老年肺癌患者电视辅助胸腔镜手术后的肺部并发症，并协助外科医生优化以患者为中心的治疗方案。
该研究纳入了854例接受亚肺叶切除术或肺叶切除术的符合条件的老年肺癌患者。使用单因素和多因素分析建立了PPCs发生概率的临床预测模型。此外，一个中心的数据用于推导模型，另一个中心的数据用于外部验证。分别使用受试者工作特征（ROC）曲线、校准曲线和决策曲线分析评估模型的辨别能力、预测准确性和临床实用性。
在符合条件的老年肺癌患者中，214例（25.06%）在电视辅助胸腔镜手术后发生了肺部并发症。年龄、慢性阻塞性肺疾病、手术方式、手术时间、一秒用力呼气量和肺一氧化碳弥散量是PPCs的独立预测因素，并被纳入最终模型。训练集和验证集的ROC曲线下面积（AUC）分别为0.844和0.796。采用十折交叉验证评估预测模型的可推广性，平均AUC值为0.839。校准曲线显示观察到的概率和预测的概率之间具有良好的一致性。所提出的列线图在较宽的阈值概率范围内显示出良好的净效益。
可以使用术前和术中变量推导老年肺癌患者的列线图。我们的模型也可以通过在线网络服务器https://pulmonary-disease-predictor.shinyapps.io/dynnomapp/访问。将两者结合起来可能有助于外科医生作为一种临床易用的工具，以尽量减少老年患者肺切除术后肺部并发症的发生率。
