Efficacy of multi-groove silicone drains in single-port video-assisted thoracoscopic lung cancer surgery and their effect on C-reactive protein: a single-center experience

Perioperative Effect of Single-Port Thoracoscopic Segmentectomy and Three-Port Thoracoscopic Segmentectomy in the Treatment of Early Non-Small-Cell Lung Cancer

Background

Clinically, there were few reports on single-hole thoracoscopic segmental resection in non-small-cell lung cancer (NSCLC), and no report on the comparison of single-hole and three-hole thoracoscopic segmental resection. Hence, the purpose of the study was to explore the perioperative role of single-port thoracoscopic segmentectomy and three-port thoracoscopic segmentectomy for early-stage NSCLC.

Methods

The clinical data of 80 patients with early-stage NSCLC who were treated in our hospital from January 2021 to June 2022 were selected as the retrospective research subjects and divided into a comparison/research group with 40 cases in each group according to different surgical methods. Among them, the comparison group was received three-port thoracoscopic segmentectomy, and the research group was received single-port thoracoscopic segmentectomy. The surgical indicators, immune and tumor marker levels, as well as prognostic complications between two groups were compared.

Results

There was no remarkable diversity between the two groups in terms of operation time and the number of lymph nodes dissected during the operation (P > 0.05). The surgical blood loss in research group was lower than comparison group (P < 0.05). After treatment, the levels of CYFRA21-1, CA125, as well as VGEF in the research group were markedly lower than comparison group (P < 0.05). The differences in CD4+, CD3+, and CD4+/CD8+ after treatment were prominent, and the research group was higher than comparison group (P < 0.05). There was no statistical difference in postoperative complications between the two groups (P > 0.05).

Conclusions

Single-hole thoracoscopic lobectomy has obvious advantages in the treatment of NSCLC, which can reduce intraoperative bleeding, enhance the recovery of patients' immune function, and promote postoperative recovery.

Nomogram Prediction Model Analysis of Risk Factors for Conversion to Thoracotomy after Thoracoscopic Resection of Lung Cancer and Prognostic Value of Lung Cancer

This study was aimed at exploring the risk factors for thoracotomy in patients undergoing thoracoscopic resection of lung cancer and further analyzing the factors affecting the prognosis of patients. Ninety-six patients with non-small-cell lung cancer who underwent thoracoscopic pulmonary resection were recruited as the subjects, and they were enrolled into the thoracoscopic group (n = 88) and the thoracotomy group (n = 8) according to whether thoracotomy was performed. Univariate analysis and logistic multivariate regression were performed to analyze the risk factors for conversion to thoracotomy, and nomogram prediction model was employed to analyze the prognostic factors. The results revealed that the proportion of patients over 65 years old, with history of coronary heart disease, diabetes, and pulmonary tuberculosis, etc., in the thoracotomy group and the thoracoscopic group was significantly different (P < 0.05). There were statistically significant differences in the development of interlobular cleft, pleural adhesion, tumor diameter > 3.5 cm, vascular and lymph node invasion, and tumor TNM stage between the thoracotomy group and the thoracoscopic group (P < 0.05). Overall, the age of patients ≥ 65 years old, tumor diameter > 3.5 cm, hypoplasia of interlobular fissure, history of pulmonary tuberculosis, pleural adhesion, and TNM stage IIIa were all independent risk factors for thoracoscopic resection of lung cancer to thoracotomy. Cox model and nomogram prediction model analysis showed that surgery methods, tumor diameter > 3.5 cm, chemotherapy cycle < 4, chemotherapy, and TNM stage IIIa were all independent factors influencing the prognosis of patients undergoing thoracoscopic lung cancer resection. This nomogram prediction model had high application value in patient prognosis prediction.