ObjectiveTo explore the predictive value of the modified frailty index-11 (mFI-11) for postoperative complications in elderly lung cancer patients undergoing robot-assisted lobectomy. MethodsRetrospective collection of clinical data from lung cancer patients aged ≥65 years who underwent robot-assisted lobectomy at the Department of Thoracic Surgery, Gansu Provincial Hospital, from January 2022 to June 2025. Based on the optimal grouping threshold of 0.27 in previous studies for the mFI-11 score, patients were divided into a frail and a non-frail group. Postoperative complications of the two groups were analyzed, and multivariate logistic regression was used to assess the relationship between mFI-11 and postoperative complications. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive efficiency of mFI-11 for postoperative complications. ResultsA total of 161 patients were included, with 77 males and 84 females, and an average age of (68.48±2.90) years. Among them, 103 (64.0%) patients were in the non-frail group and 58 (36%) in the frail group. Differences between the two groups in terms of independent functional status, hypertension requiring drug control, history of type 2 diabetes, history of chronic obstructive pulmonary disease, American Society of Anesthesiologists classification, and tumor staging were all statistically significant (P<0.05). The length of postoperative hospital stay in the frail group was longer than that in the non-frail group [5.50 (5.00, 8.25) d vs. 5.00 (4.00, 5.00) d, P<0.001]. The incidence rates of general respiratory diseases (25.9% vs. 8.7%), hypoproteinemia (15.5% vs. 4.9%), arrhythmia (12.1% vs. 1.9%), bronchopleural fistula (5.2% vs. 0.0%), transfer to ICU for severe complications (10.3% vs. 1.0%), and readmission within 30 days after discharge (12.1% vs. 1.9%) were all higher in the frail group compared to the non-frail group (P<0.05). Multivariate logistic regression analysis found that mFI-11 had a better predictive efficiency for postoperative complications: general respiratory diseases [area under the curve (AUC)=0.759], hypoproteinemia (AUC=0.723), arrhythmia (AUC=0.795), transfer to ICU for severe complications (AUC=0.713), and readmission within 30 days after discharge (AUC=0.702). ConclusionmFI-11 can effectively predict postoperative complications in elderly lung cancer patients undergoing robot-assisted lobectomy and can serve as an objective indicator for identifying high-risk elderly lung cancer patients.
ObjectiveTo evaluate the efficacy, safety, and long-term recurrence rate of thoracoscopic bullae resection combined with parietal pleurectomy or pleural abrasion for the treatment of spontaneous pneumothorax. MethodsRelevant literatures were searched in PubMed, Web of Science, EMbase, The Cochrane Library, CNKI, Wanfang and VIP databases from the establishment of each database to February 1, 2025. According to the inclusion and exclusion criteria, the literatures were screened. Meta-analysis was conducted using Review Manager 5.3 software, and the quality of the literatures was evaluated using the Cochrane Bias Risk Assessment Tool and the NOS scale. ResultsA total of 23 articles were included, including 6 randomized controlled studies and 17 retrospective cohort studies, with NOS scores≥7. A total of 3 296 patients were enrolled, including 1 245 in the parietal pleurectomy group and 2 051 in the pleural abrasion group. The meta-analysis results showed that the pleural abrasion group had shorter operation time [MD=19.68, 95%CI (14.12-25.25)], less intraoperative blood loss [MD=11.31, 95%CI (4.20-18.41)], lower postoperative pain score [MD=0.48, 95%CI (0.04-0.91)], lower total postoperative drainage volume [MD=44.31, 95%CI (11.92-76.71)], shorter postoperative drainage time [MD=0.32, 95%CI (0.03-0.60)], and shorter hospital stay [MD=0.40, 95%CI (0.23-0.57)] compared with the parietal pleurectomy group, and the differences were statistically significant (P<0.05). In terms of safety, the parietal pleurectomy group increased the incidence of postoperative pulmonary hemorrhage [OR=3.99, 95%CI (1.49-10.65), P<0.05], but there were no statistically significant differences in the incidence of postoperative atelectasis, pneumothorax leakage and pulmonary infection (P>0.05). In addition, the parietal pleurectomy group could effectively reduce the long-term recurrence rate of patients [OR=0.48, 95%CI (0.36-0.64)], and the difference was statistically significant (P<0.05). ConclusionDecortication inevitably imposes a greater perioperative burden on patients with spontaneous pneumothorax and pulmonary bullae, yet it effectively reduces the risk of postoperative recurrence. While both surgical approaches exhibit similar safety profiles, parietal pleurectomy may elevate the risk of postoperative pulmonary hemorrhage. Therefore, the optimal treatment strategy should be determined based on individual patient characteristics.
Lung cancer is the malignant tumor with the highest incidence and mortality in China and even worldwide. Non-small cell lung cancer (NSCLC) constitutes the vast majority of cases. The current innovation in lung cancer diagnosis and treatment systems is progressively transitioning from traditional pathological classification to molecular characteristic-guided precision medicine. However, the conventional gold standard for molecular detection, tissue biopsy, faces limitations including invasive procedures and non-repeatable sample acquisition. The breakthrough in liquid biopsy technology has provided new clinical pathways, particularly through circulating tumor DNA (ctDNA) detection for molecular residual disease (MRD) monitoring, which has emerged as a research hotspot in the liquid biopsy field. Through continuous optimization, this approach has achieved breakthroughs in high sensitivity and specificity. Its non-invasive nature eliminates the risks associated with tissue puncture, demonstrating significant potential in various clinical applications including early and advanced NSCLC diagnosis, treatment response monitoring, drug resistance evaluation, and prognosis prediction.