Lung cancer is the leading cause of cancer-related death worldwide. Even early-stage patients might encounter disease recurrence with relative high risk. Effective postoperative therapy is based on an accurate assessment of treatment failure after surgery. The aim of this study is to construct a disease-free survival (DFS) prediction model and stratify patients into different risk score groups.A total of 356 pathological stage I patients (7th American Joint Committee on Cancer) who underwent lung resection from January 2005 through June 2011 were retrospectively reviewed. Of these patients, 63 patients were eliminated for this study. A total of 293 p-stage I patients were included for further univariate and multivariate analysis. Clinical, surgical, and pathological factors associated with high risk of recurrence were analyzed, including age, gender, smoking status, additional primary malignancy (APM), operation method, histology, visceral pleural invasion, angiolymphatic invasion, tumor necrosis, and tumor size.Of the 293 p-stage I non-small cell lung cancer (NSCLC) patients examined, 143 were female and 150 were male, with a mean age of 62.8-years old (range: 25-83-years old). The 5-year DFS and overall survival rates after surgery were 58.9% and 75.3%, respectively. On multivariate analysis, current smoker (hazards ratio [HR]: 1.63), APM (HR: 1.86), tumor size (HR: 1.54, 2.03), nonanatomic resections (HR: 1.81), adenocarcinoma histology (HR: 2.07), visceral pleural invasion (HR: 1.54), and angiolymphatic invasion (HR: 1.53) were found to be associated with a higher risk of tumor recurrence. The final model showed a fair discrimination ability (C-statistic = 0.68). According to the difference risk group, we found patients with intermediate or higher risk group had a higher distal relapse tendency as compared with low risk group (P = 0.016, odds ratio: 3.31, 95% confidence interval: 1.21-9.03).Greater than 30% of disease recurrences occurred after surgery for stage I NSCLC patients. That is why we try to establish an effective DFS predicting model based on clinical, pathological, and surgical covariates. However, our initial results still need to be validated and refined into greater population for better application in clinical use.

Background: The role of circulating tumor cells (CTCs) for predicting the recurrence of cancer in lung cancer patients after surgery remains unclear. Methods: A negatively selected protocol of CTC identification was applied. For all the enrolled patients, CTC testing was performed before and after surgery on the operation day (day 0), postoperative day 1, and day 3. The daily decline and trend of CTCs were analyzed to correlate with cancer relapse. The mixed model repeated measures (MMRM) adjusted by cancer characteristics was applied for statistical significance. Results: Fifty patients with lung mass undergoing surgery were enrolled. Among 41 primary lung cancers, 26 (63.4%) were pathological stage Tis and I. A total of 200 CTC tests were performed. MMRM analysis indicated that surgery could contribute to a CTC decline after surgery in all patients with statistical significance (p = 0.0005). The daily decrease of CTCs was statistically different between patients with and without recurrence (p = 0.0068). An early rebound of CTC counts on postoperative days 1 and 3 was associated with recurrence months later. Conclusion: CTC testing can potentially serve as a tool for minimal residual disease detection in early-staged lung cancer after curative surgery.

The purpose of this work was to evaluate the performance of an existing commercially available artificial intelligence (AI) software system in differentiating malignant and benign lung nodules. The AI tool consisted of a vessel-suppression function and a deep-learning-based computer-aided-detection (VS-CAD) analyzer. Fifty patients (32 females, mean age 52 years) with 75 lung nodules (47 malignant and 28 benign) underwent low-dose computed tomography (LDCT) followed by surgical excision and the pathological analysis of their 75 nodules within a 3 month time frame. All 50 cases were then processed by the AI software to generate corresponding VS images and CAD outcomes. All 75 pathologically proven lung nodules were well delineated by vessel-suppressed images. Three (6.4%) of the 47 lung cancer cases, and 11 (39.3%) of the 28 benign nodules were ignored and not detected by the AI without showing a CAD analysis summary. The AI system/radiologists produced a sensitivity and specificity (shown in %) of 93.6/89.4 and 39.3/82.1 in distinguishing malignant from benign nodules, respectively. AI sensitivity was higher than that of radiologists, though not statistically significant (p = 0.712). Specificity obtained by the radiologists was significantly higher than that of the VS-CAD AI (p = 0.003). There was no significant difference between the malignant and benign lesions with respect to age, gender, pure ground-glass pattern, the diameter and location of the nodules, or nodules <6 vs. ≥6 mm. However, more part-solid nodules were proven to be malignant than benign (90.9% vs. 9.1%), and more solid nodules were proven to be benign than malignant (86.7% vs. 13.3%) with statistical significance (p = 0.001 and <0.001, respectively). A larger cohort and prospective study are required to validate the AI performance.

Benign lesions, atypical adenomatous hyperplasia (AAH), and malignancies such as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IA) may feature a pure ground-glass nodule (pGGN) on a thin-slide computed tomography (CT) image. According to the World Health Organization (WHO) classification for lung cancer, the prognosis of patients with IA is worse than those with AIS and MIA. It is relatively risky to perform a core needle biopsy of a pGGN less than 2 cm to obtain a reliable pathological diagnosis. The early and adequate management of patients with IA may provide a favorable prognosis. This study aimed to disclose suggestive signs of CT to accurately predict IA among the pGGNs. A total of 181 pGGNs of less than 2 cm, in 171 patients who had preoperative CT-guided localization for surgical excision of a lung nodule between December 2013 and August 2019, were enrolled. All had CT images of 0.625 mm slice thickness during CT-guided intervention to confirm that the nodules were purely ground glass. The clinical data, CT images, and pathological reports of those 171 patients were reviewed. The CT findings of pGGNs including the location, the maximal diameter in the long axis (size-L), the maximal short axis diameter perpendicular to the size-L (size-S), and the mean value of long and short axis diameters (size-M), internal content, shape, interface, margin, lobulation, spiculation, air cavity, vessel relationship, and pleural retraction were recorded and analyzed. The final pathological diagnoses of the 181 pGGNs comprised 29 benign nodules, 14 AAHs, 25 AISs, 55 MIAs, and 58 IAs. Statistical analysis showed that there were significant differences among the aforementioned five groups with respect to size-L, size-S, and size-M (p = 0.029, 0.043, 0.025, respectively). In the univariate analysis, there were significant differences between the invasive adenocarcinomas and the non-invasive adenocarcinomas with respect to the size-L, size-S, size-M, lobulation, and air cavity (p = 0.009, 0.016, 0.008, 0.031, 0.004, respectively) between the invasive adenocarcinomas and the non-invasive adenocarcinomas. The receiver operating characteristic (ROC) curve of size for discriminating invasive adenocarcinoma also revealed similar area under curve (AUC) values among size-L (0.620), size-S (0.614), and size-M (0.623). The cut-off value of 7 mm in size-M had a sensitivity of 50.0% and a specificity of 76.4% for detecting IAs. In the multivariate analysis, the presence of air cavity was a significant predictor of IA (p = 0.042). In conclusion, the possibility of IA is higher in a pGGN when it is associated with a larger size, lobulation, and air cavity. The air cavity is the significant predictor of IA.

Single-port video-assisted thoracoscopic surgery (VATS) has been widely applied recently. However, there are still only few reports describing its use in mediastinum tumor resection. We present the technique of single-port video-assisted thoracoscopic mediastinum tumor resection and compare it with conventional VATS with regard to short-term outcome.We retrospectively enrolled 105 patients who received mediastinum surgery in Chang Gung Memorial Hospital. Sixteen patients received sternotomy or thoracotomy, 29 patients received single-port VATS, and 60 patients received conventional VATS (3 ports). The operative time, blood loss, postoperation day 1 pain score, discharge day pain score, and postoperative hospital stay were compared. In order to establish a well balanced cohort study, we also use propensity scores match (1:1) to compare the short-term clinical outcome in 2 groups.No operative deaths occurred in this study. Single-port VATS was associated with shorter operative time, lower postoperation day 1 pain score, and shorter postoperation hospital stay in our cohort study (P = 0.001, <0.001, and 0.039), and propensity scores matched cohort study (P = 0.003, <0.001, and <0.001).Single-port VATS for mediastinum tumor appears to be a safe and promising technique with short-term outcome not inferior to conventional VATS in our cohort study. The long-term oncology outcome may require time and more enrolled patients to be further evaluated.