Feng Fu-Kai, Gao Zi-Xiu, Dai Zhang-Yi, Wu Yong-Ming, Shi Xue-Jun
Department of Thoracic Surgery, Tianjin Medical University Baodi Hospital, Tianjin, China.
Department of Thoracic Surgery, West China hospital, Sichuan University, Chengdu, China.
J Thorac Dis. 2025 Aug 31;17(8):5597-5609. doi: 10.21037/jtd-2025-572. Epub 2025 Aug 25.
Postoperative cough (POC) is a common complication following pulmonary resection, with an incidence of 25-50%. However, it often receives insufficient attention from clinicians. This study aimed to systematically identify the key risk factors associated with POC in lung cancer survivors and to develop and validate a predictive model to assess the likelihood of POC following pulmonary resection.
A systematic review and meta-analysis were conducted by searching PubMed, Embase, Cochrane Library, Web of Science, WANFANG DATA, and CNKI to identify relevant risk factors for POC. Additionally, a cohort of 5,570 patients who underwent pulmonary resection was used to develop and validate the predictive model. Statistically significant independent variables from the meta-analysis were incorporated into the model, with risk factors weighted based on their pooled odds ratios (ORs) and β-coefficients. Model performance was evaluated using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA).
The meta-analysis included 23 cohorts with 5,360 patients, of whom 33.8% experienced POC. Significant risk factors identified were age ≥60 years, body mass index (BMI) <24 kg/m, preoperative cough, right lung surgery, lobectomy, subcarinal and peritracheal lymph node dissection, postoperative acid reflux, and preoperative respiratory training. The predictive model demonstrated robust performance, with AUCs of 0.772 [95% confidence interval (CI): 0.757-0.786] in the training cohort and 0.782 (95% CI: 0.761-0.803) in the validation cohort. Calibration curves showed high accuracy, and DCA confirmed clinical utility across a threshold range of 0 to 0.8.
This study provides a comprehensive, evidence-based predictive model for identifying lung cancer survivors at high risk of POC, offering valuable insights into its risk factors.
术后咳嗽（POC）是肺切除术后常见的并发症，发生率为25%-50%。然而，它往往未得到临床医生的充分关注。本研究旨在系统地确定肺癌幸存者中与POC相关的关键危险因素，并开发和验证一个预测模型，以评估肺切除术后发生POC的可能性。
通过检索PubMed、Embase、Cochrane图书馆、Web of Science、万方数据和中国知网进行系统评价和荟萃分析，以确定POC的相关危险因素。此外，纳入5570例行肺切除术的患者队列来开发和验证预测模型。将荟萃分析中有统计学意义的自变量纳入模型，根据其合并比值比（OR）和β系数对危险因素进行加权。使用曲线下面积（AUC）、校准曲线和决策曲线分析（DCA）评估模型性能。
荟萃分析纳入了23个队列中的5360例患者，其中33.8%发生了POC。确定的显著危险因素包括年龄≥60岁、体重指数（BMI）<24 kg/m²、术前咳嗽、右肺手术、肺叶切除术、隆突下和气管周围淋巴结清扫、术后胃酸反流以及术前呼吸训练。预测模型表现出强大的性能，训练队列中的AUC为0.772[95%置信区间（CI）：0.757-0.786]，验证队列中的AUC为0.782（95%CI：0.761-0.803）。校准曲线显示出高准确性，DCA证实了在0至0.8的阈值范围内的临床实用性。
本研究提供了一个全面的、基于证据的预测模型，用于识别POC高危的肺癌幸存者，为其危险因素提供了有价值的见解。
