The 2024 World Conference on Lung Cancer (WCLC) and the European Society for Medical Oncology (ESMO) Annual Meeting, two of the most prestigious events in oncology, have concluded sequentially. As the most authoritative annual gatherings in lung cancer and the entire oncology field, the WCLC and ESMO conferences brought together top oncology experts and scientists from around the world to share, discuss, and publish the latest cutting-edge advancements in oncology. In both conferences, lung cancer immunotherapy remained a hot topic of considerable interest. This article aims to summarize and discuss the important research progress on perioperative immunotherapy for non-small cell lung cancer reported at the two conferences.

Objective To evaluate the reporting quality and influencing factors of patient-reported outcome (PRO) data in randomized controlled trials (RCTs) of lung cancer. Methods RCTs of lung cancer with PRO as either primary or secondary endpoints were searched from PubMed, EMbase, Medline, CNKI, Wanfang Data, and VIP databases between January 1, 2010 and April 20, 2024. Reporting quality of included RCTs were assessed based on the CONSORT-PRO extension. Descriptive statistics and bivariate regression analysis were used to describe the reporting quality and analyze the factors influencing the reporting quality. Results A total of 740 articles were retrieved. After screening, 53 eligible RCTs of lung cancer with 22 780 patients were included. The patients were mainly with non-small cell lung cancer (84.91%), with the median sample size of the included studies was 364.0 (160.5, 599.5) patients. The primary PRO tool used was the EORTC QLQ-C30 (60.38%). There were 52 (98.11%) studies whose PRO measured the domain of "symptom management of cough, dyspnea, fatigue, pain, etc.", and 45 (84.91%) studies measured "health-related quality of life". Multicenter studies accounted for 84.91%, and randomized non-blind trials accounted for 62.26%. PRO was used as the primary endpoint in 33.96% of the studies and as secondary endpoints in 66.04%. The reliability and validity of the PRO tools were explicitly mentioned in 11.32% and 7.55% of the studies, respectively. The average completeness of reporting according to the CONSORT-PRO guidelines was 60.00%, ranging from 25.00% to 93.00%. The main factors affecting the completeness of CONSORT-PRO reporting included sample size and publication year. For every increment in sample size, the completeness of reporting increased by 27.5% (SE=0.00, t=2.040, P=0.046). Additionally, studies published after 2018 had a 67.2% higher completeness of reporting compared to those published in or before 2018 (SE=17.8, t=–3.273, P=0.006). Conclusion The study reveals that the overall reporting quality of PRO in lung cancer RCTs is poor. Particularly, the reporting of PRO measures reliability and validity, PRO assumptions, applicability, and handling of missing data need further improvement. Future research should emphasize comprehensive adherence to the CONSORT-PRO guidelines.

Objective To develop an innovative recognition algorithm that aids physicians in the identification of pulmonary nodules. Methods Patients with pulmonary nodules who underwent thoracoscopic surgery at the Department of Thoracic Surgery, Affiliated Drum Tower Hospital of Nanjing University Medical School in December 2023, were enrolled in the study. Chest surface exploration data were collected at a rate of 60 frames per second and a resolution of 1 920×1 080. Frame images were saved at regular intervals for subsequent block processing. An algorithm database for lung nodule recognition was developed using the collected data. Results A total of 16 patients were enrolled, including 9 males and 7 females, with an average age of (54.9±14.9) years. In the optimized multi-topology convolutional network model, the test results demonstrated an accuracy rate of 94.39% for recognition tasks. Furthermore, the integration of micro-variation amplification technology into the convolutional network model enhanced the accuracy of lung nodule identification to 96.90%. A comprehensive evaluation of the performance of these two models yielded an overall recognition accuracy of 95.59%. Based on these findings, we conclude that the proposed network model is well-suited for the task of lung nodule recognition, with the convolutional network incorporating micro-variation amplification technology exhibiting superior accuracy. Conclusion Compared to traditional methods, our proposed technique significantly enhances the accuracy of lung nodule identification and localization, aiding surgeons in locating lung nodules during thoracoscopic surgery.

The European Society of Cardiology (ESC) released the "2024 ESC guidelines for the management of elevated blood pressure and hypertension" on August 30, 2024. This guideline updates the 2018 "Guidelines for the management of arterial hypertension." One notable update is the introduction of the concept of "elevated blood pressure" (120-139/70-89 mm Hg). Additionally, a new systolic blood pressure target range of 120-129 mm Hg has been proposed for most patients receiving antihypertensive treatment. The guideline also includes numerous additions or revisions in areas such as non-pharmacological interventions and device-based treatments for hypertension. This article interprets the guideline's recommendations on definition and classification of elevated blood pressure and hypertension, and cardiovascular disease risk assessment, diagnosing hypertension and investigating underlying causes, preventing and treating elevated blood pressure and hypertension. We provide a comparison interpretation with the 2018 "Guidelines for the management of arterial hypertension" and the "2017 ACC/AHA guideline on the prevention, detection, evaluation, and management of high blood pressure in adults."

In recent years, the field of cardiovascular surgery has undergone revolutionary changes and made rapid progress in various aspects, bringing more hope and possibilities for the health and well-being of patients. The constant emergence of new technologies brings new opportunities and hope, as well as constant challenges to past concepts. This article aims to provide a comprehensive overview of the latest developments in cardiovascular surgery in recent years, especially since 2023. It introduces cutting-edge knowledge and technologies in the field of cardiovascular surgery, including lifelong management of aortic valve disease, artificial valves, mitral valves, treatment options for hypertrophic obstructive cardiomyopathy, heart transplantation, left ventricular assist, coronary artery surgery, cardiac structural interventions for chronic heart failure, aortic dissection, and comprehensive surgical treatment of atrial fibrillation. It also analyzes and explores future development directions in depth, aiming to provide useful references and inspiration for cardiovascular doctors and jointly promote the continuous progress of cardiovascular surgery in China.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.

Objective To compare the incidence of complications after removal of chest drainage tube in the early and late stages after sublobectomy for non-small cell lung cancer (NSCLC), and to analyze the factors affecting postoperative pleural drainage volume (PDV), so as to explore the countermeasures and achieve rapid postoperative rehabilitation. Methods The patients with NSCLC who underwent minimally invasive sublobectomy in our hospital from January to October 2021 were enrolled. According to the median time of extubation, the patients were divided into an early extubation group (time with tube≤3 days) and a late extubation group (time with tube>3 days). The patients were matched via propensity score matching with a ratio of 1:1 and a caliper value of 0.02. The incidence of complications and perioperative parameters after removal of the thoracic drainage tube were analyzed and compared between the two groups, and univariate and multiple linear regression analyses were performed. Results A total of 157 patients were enrolled, including 79 males and 78 females, with an average age of (58.22±11.06) years. There were 76 patients in the early extubation group, 81 patients in the late extubation group, and 56 patients were in each group after propensity score matching. Compared with late extubation group, there was no significant difference in the incidence of infection after extubation (10.7% vs. 16.1%, P=0.405) or pleural effusion after extubation (5.4% vs. 3.6%, P=0.647) in early extubation group, and there was no second operation in both groups. Univariate analysis showed that smoking history (P=0.001), postoperative serum albumin reduction value (P=0.017), surgical approach (P=0.014), lesion location (P=0.027), differentiation degree (P=0.041), TNM stage (P=0.043), number of dissected lymph nodes (P=0.016), and intraoperative blood loss (P=0.016) were infuencing factors for increased postoperative PDV. Multiple linear regression analysis showed that smoking history (P=0.002), postoperative serum albumin reduction value (P=0.041), and the number of dissected lymph nodes (P=0.023) were independent risk factors for increased postoperative PDV. Conclusion There is no significant difference in the incidence of complications after extubation between early and late extubations. Preoperative smoking history, excessive postoperative serum albumin decreases, and excessive number of dissected lymph nodes during the surgery are independent risk factors for increased postoperative PDV.

Objective To explore the diagnosis and treatment strategies for elderly patients with ground-glass opacity (GGO). Methods The imaging features and postoperative pathological findings of the elderly patients with pulmonary GGO receiving surgery in our hospital from 2017 to 2019 were retrospectively analyzed. The patients were divided into an elderly patient group and a non-elderly patient group based on their age. Results Finally 575 patients were included in the study. There were 281 elderly patients, including 83 males and 198 females, with an average age of (67.0±5.3) years. There were 294 non-elderly patients, including 88 males and 206 females, with an average age of (49.1±7.3) years. Compared with the non-elderly patients, elderly GGO patients showed the following distinct clinical features: long observation time for lesions (P=0.001), high proportion of rough edges of GGO (P<0.001), significant pleural signs (P＜0.001) and bronchial signs (P＜0.001), and high proportion of type Ⅱ-Ⅳ GGO (P<0.001), lobectomy type (P=0.013), and invasive lesions reported in postoperative pathology (P<0.001). There was no statistical difference in the average hospital stay between the two groups (P=0.106). Multivariate logistic regression analysis showed that GGO diameter and GGO type were the main factors affecting the operation. Observation time, GGO diameter, GGO type and pleural signs were the main influencing factors for postoperative pathological infiltrative lesions. The cut-off value of GGO diameter in predicting infiltrating lesions was 10.5 mm in the elderly patients group. Conclusion The size and type of GGO are important factors in predicting invasive lesions and selecting surgical methods. Elderly patients with radiographic manifestations of type Ⅱ-Ⅳ GGO lesions with a diameter greater than 10.5 mm should be closely followed up.

Objective To investigate the correlation between spread through air space (STAS) of sub-centimeter non-small cell lung cancer and clinical characteristics and radiological features, constructing a nomogram risk prediction model for STAS to provide a reference for the preoperative planning of sub-centimeter non-small cell lung cancer patients. Methods The data of patients with sub-centimeter non-small cell lung cancer who underwent surgical treatment in Nanjing Drum Tower Hospital from January 2022 to October 2023 were retrospectively collected. According to the pathological diagnosis of whether the tumor was accompanied with STAS, they were divided into a STAS positive group and a STAS negative group. The clinical and radiological data of the two groups were collected for univariate logistic regression analysis, and the variables with statistical differences were included in the multivariate analysis. Finally, independent risk factors for STAS were screened out and a nomogram model was constructed. The sensitivity and specificity were calculated based on the Youden index, and area under the curve (AUC), calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the model. Results A total of 112 patients were collected, which included 17 patients in the STAS positive group, consisting of 11 males and 6 females, with a mean age of (59.0±10.3) years. The STAS negative group included 95 patients, with 30 males and 65 females, and a mean age of (56.8±10.3) years. Univariate logistic regression analysis showed that male, anti-GAGE7 antibody positive, mean CT value and spiculation were associated with the occurrence of STAS (P＜0.05). Multivariate regression analysis showed that associations between STAS and male (OR=5.974, 95%CI 1.495 to 23.872), anti-GAGE7 antibody positive (OR=11.760, 95%CI 1.619 to 85.408) and mean CT value (OR=1.008, 95%CI 1.004 to 1.013) were still significant (P＜0.05), while the association between STAS and spiculation was not significant anymore (P=0.438). Based on the above three independent predictors, a nomogram model of STAS in sub-centimeter non-small cell lung cancer was constructed. The AUC value of the model was 0.890, the sensitivity was 76.5%, and the specificity was 91.6%. The calibration curve was well fitted, suggesting that the model had a good prediction efficiency for STAS. The DCA plot showed that the model had a good clinically utility. Conclusion Male, anti-GAGE7 antibody positive and mean CT value are independent predictors of STAS positivity of sub-centimeter non-small cell lung cancer, and the nomogram model established in this study has a good predictive value and provides reference for preoperative planning of patients.