Translational lung cancer research最新文献

{"title":"Surgery without distance: will 5G-based robot-assisted telesurgery redefine modern surgery?","authors":"Xin Xie, Yu Tian, Jia Huang, Qingquan Luo, Tianxiang Chen","doi":"10.21037/tlcr-2025-16","DOIUrl":"10.21037/tlcr-2025-16","url":null,"abstract":"<p><p>The rapid advancement of the 5G technology is catalyzing a paradigm shift in the realm of remote surgery, offering the potential to overcome geographical constraints and to realize optimized allocation of global healthcare resources. We review the evolution of telesurgery, from early pioneering efforts to recent advancements made possible by 5G networks, which offer low latency and high data transfer speeds crucial for real-time surgical operations. Thus, 5G facilitates seamless transmission of control signals, images, and audio, allowing surgeons to perform complex procedures remotely with unprecedented precision. Notable achievements in telemedicine demonstrate the feasibility and safety of this cutting-edge approach. Despite these milestones, challenges such as network reliability, cybersecurity concerns, and the need for standardized global protocols remain critical barriers that impede the broad implementation worldwide. Moreover, ethical considerations surrounding patient autonomy, informed consent, liability assignment, regulatory approval, and data privacy framework in cross-border telesurgery require careful attention. The development of regional robotic surgery centers powered by 5G, alongside advancements in artificial intelligence, holds promise for bridging healthcare disparities and enhancing the precision of remote surgical procedures. As these technologies mature, they have great potential to redefine the landscape of surgery, ushering in an era of more accessible, collaborative, and efficient healthcare delivery worldwide.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 5","pages":"1821-1829"},"PeriodicalIF":4.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12170204/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144326967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chinese expert consensus on shape-sensing robotic-assisted bronchoscopy (ssRAB) in the management of peripheral pulmonary lesions.","authors":"Fangfang Xie, Chunxi Zhang, Chun Li, Dan Liu, Quncheng Zhang, Chuanyong Mu, Gang Hou, Manxiang Li, Chunli Tang, Fei Xu, Hong Chen, Zhongbo Chen, Ye Gu, Zhenbiao Guan, Cheng Ji, Haitao Li, Wei Li, Xuan Li, Yishi Li, Hairong Lian, Jiangrong Liao, Zhuang Luo, Haifeng Ouyang, Yongchun Shen, Yiwei Shi, Nansheng Wan, Tao Wang, Hong Wang, Huaqi Wang, Juan Wang, Jingxiang Wu, Xuemei Wu, Yang Xia, Kui Xiao, Wujian Xu, Huizhen Yang, Junyong Yang, Taosheng Ye, Xianwei Ye, Pengfei Yu, Nan Zhang, Peng Zhang, Qi Zhao, Xiaoxuan Zheng, Jun Zou, Enguo Chen, Hao Zhang, Jiayuan Sun","doi":"10.21037/tlcr-2025-400","DOIUrl":"10.21037/tlcr-2025-400","url":null,"abstract":"<p><strong>Background: </strong>Shape-sensing robotic-assisted bronchoscopy (ssRAB) is a new bronchoscopy technology that utilizes optic fibers to provide accurate position information and robotic-control to deliver improved maneuverability. This technology has been used in the United States since 2019 and investigated in China since 2021. In order to provide a standard practice and make the best use of this technology for managing peripheral pulmonary lesions (PPLs), experts developed the consensus.</p><p><strong>Methods: </strong>This consensus was developed using Delphi method. A panel comprising nine experts formulated eight consensus statements after a thorough review of clinical evidence and practical experience. During the second phase, a questionnaire was distributed to collect feedback on these statements from an external panel of 39 physicians. The percentage of responses and the percentage of agreement on each statement were calculated. The consensus was defined as achieved with an agreement percentage threshold of 80% or above.</p><p><strong>Results: </strong>The eight consensus statements formulated in phase 1 included recommendations for path planning, anesthesia, the use of radial endobronchial ultrasound (EBUS), the use of fluoroscopy and/or cone-beam computed tomography (CBCT) with ssRAB, solving computed tomography (CT)-to-body divergence, the use of sampling tools with ssRAB, cloud biopsy, and the use of rapid on-site evaluation (ROSE) with ssRAB. All panel physicians completed the questionnaire in phase 2. All the statements achieved positive consensus, with six receiving 100% agreement and two reaching 97.4% agreement.</p><p><strong>Conclusions: </strong>The document establishes a consensus on recommended practices for optimal utilization of ssRAB technology in the management of PPLs. The guidelines will be updated as new evidence emerges or additional ssRAB platforms are introduced into practice.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 5","pages":"1500-1515"},"PeriodicalIF":4.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12170130/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144326924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radial endobronchial ultrasound (EBUS)-guided transbronchial needle aspiration (TBNA) enhances diagnostic yield in pulmonary nodule biopsy.","authors":"Rong Lih Ho, Joong Hyun Ahn, Jung Ho Han, Junsu Choe, Sun Hye Shin, Byeong-Ho Jeong, Sang-Won Eom, Hojoong Kim, Kyungjong Lee","doi":"10.21037/tlcr-2025-68","DOIUrl":"10.21037/tlcr-2025-68","url":null,"abstract":"<p><strong>Background: </strong>Diagnosing pulmonary lesions remains challenging despite various modalities. The PeriView Flex aspiration needle offers a promising solution to forceps biopsy limitations. This study aims to assess whether combining radial endobronchial ultrasound (rEBUS)-guided transbronchial needle aspiration (TBNA) and transbronchial lung biopsy (TBLB) may enhance tissue acquisition for inaccessible lesions using forceps.</p><p><strong>Methods: </strong>This retrospective study included 33 patients with pulmonary lesions who underwent a combination of rEBUS-guided TBNA and TBLB between September 2023 and August 2024. Diagnostic yields were calculated using a strict definition and were compared with those of propensity score-matched controls who underwent rEBUS-guided TBLB alone.</p><p><strong>Results: </strong>The median age of the cohort was 68 years, with a male-to-female ratio of 1.2:1.0. About 65% of lesions were in the outer two-thirds of the thorax, with a median size of 16.75 mm (interquartile range: 13.00-23.88 mm). Most lesions were solid (81.8%), followed by consolidation (9.1%), part-solid (6.1%) and cavitary lesions (3%). In our cohort, 21.2% had type Ia and 15.2% had type Ib, classified as favorable bronchial patterns on computed tomography (CT). However, approximately two-thirds had unfavorable bronchial patterns, including type Ic (12.1%), IIa (45.5%), and IIb (6.1%). An adjacent rEBUS view was present in 52% of the cases. The combined TBNA-TBLB approach achieved a diagnostic yield of 66.7%, which was highest in CT bronchus types Ia and Ib (83.3%) and lowest in types Ic, IIa, and IIb (57.1%). Propensity score matching (1:3) showed a higher diagnostic yield with TBNA-TBLB (66.7%) than with TBLB alone (48.5%), P=0.10. Post-procedural pneumothorax occurred in one patient (3.0%) in TBNA-TBLB group compare to 2.3% in TBLB group.</p><p><strong>Conclusions: </strong>Adding TBNA to TBLB improved the diagnostic yield for pulmonary nodules with adjacent or tunnel-type bronchi. This combined approach offers a practical strategy for enhancing diagnostic accuracy.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 5","pages":"1611-1621"},"PeriodicalIF":4.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12170253/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144326964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Bayesian deep learning model with consolidation-to-tumor ratio (CTR) prior revolutionizes the prediction of spread through air spaces (STAS) in stage IA lung adenocarcinoma: a large-scale diagnostic study.","authors":"Jie Cao, Nan Chen, Lingyu Zhou, Le Yi, Zhiyu Peng, Lin Qiu, Haokun Wu, Xiyue Tan, Kunhao Wu, Huahang Lin, Zhaokang Huang, Zetao Liu, Chenglin Guo, Xiuyuan Xu, Zhang Yi, Jiandong Mei","doi":"10.21037/tlcr-24-890","DOIUrl":"10.21037/tlcr-24-890","url":null,"abstract":"<p><strong>Background: </strong>The preoperative prediction of spread through air spaces (STAS) in patients with early-stage lung adenocarcinoma (LUAD) is crucial for selecting the appropriate surgical approach and improving patient outcomes. Previous research has confirmed that there is a significant correlation between consolidation-to-tumor ratio (CTR) and STAS. This study aimed to develop a Bayesian deep learning (DL) model based on the CTR prior to predict STAS in patients with stage IA LUAD.</p><p><strong>Methods: </strong>This large-scale diagnostic study included patients with solitary primary invasive LUAD who underwent complete resection between November 2017 and October 2023. Enrolled patients were randomly assigned to training, validation, and test cohorts in a 7:2:1 ratio. Using a variational Bayesian inference framework, we developed a DL model based on the CTR prior (STAS-DL_{Prior CTR}). The performance of STAS-DL_{Prior CTR} was compared with another DL model without the CTR prior (STAS-DL_{Non-prior CTR}) using the receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC).</p><p><strong>Results: </strong>A total of 1,374 patients were included, with 961 in the training cohort, 275 in the validation cohort, and 138 in the test cohort. The results showed that CTR in the STAS-positive group was significantly higher than that in the STAS-negative group [0.63 (interquartile range, 0.36, 0.98) <i>vs</i>. 0.35 (interquartile range, 0.19, 0.60), P<0.001]. Compared to STAS-DL_{Non-prior CTR}, the area under the ROC curve (AUC) tends to be higher for STAS-DL_{Prior CTR} (0.831 <i>vs</i>. 0.731, P=0.06) in the validation cohort, and STAS-DL_{Prior CTR} demonstrated a significantly higher AUC (0.858 <i>vs</i>. 0.637, P=0.008) in the test cohort. Additionally, the calibration curve suggested better calibration for STAS-DL_{Prior CTR}. DCA and CIC also indicated that STAS-DL_{Prior CTR} conferred higher clinical net benefit.</p><p><strong>Conclusions: </strong>The proposed model based on the CTR prior offers significant advantages in predicting STAS in patients with stage IA LUAD, and incorporating doctors' knowledge as priors can effectively guide the development of DL models.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 5","pages":"1516-1530"},"PeriodicalIF":4.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12170142/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144326920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative effectiveness of pembrolizumab-chemotherapy versus chemotherapy with/without bevacizumab in unresectable, locally advanced or metastatic non-small cell lung cancer: a Chinese multicenter real-world analysis emphasizing PD-L1-negative populations.","authors":"Xiaobei Guo, Hui Zhang, Yuequan Shi, Qi He, Anwen Liu, Zhimin Zeng, Jinghui Wang, Song Wei, Tong Zhang, Cuimin Ding, Jian Fang, Xiaoling Chen, Paul Van Schil, Haoran Zhang, Junyi Pang, Minjiang Chen, Jing Zhao, Wei Zhong, Zhen Huo, Yan Xu, Mengzhao Wang","doi":"10.21037/tlcr-2025-271","DOIUrl":"10.21037/tlcr-2025-271","url":null,"abstract":"<p><strong>Background: </strong>Current limited evidence suggests that the use of pembrolizumab combined with chemotherapy may be effective for treatment-naïve patients with metastatic non-small cell lung cancer (NSCLC) and negative programmed cell death ligand 1 (PD-L1) expression, but real-world data are relatively scarce. This retrospective cohort study analyzed the efficacy, adverse events, and prognostic factors in these patients treated with chemotherapy with or without pembrolizumab.</p><p><strong>Methods: </strong>This retrospective study analyzed the data of patients with unresectable, locally advanced or metastatic NSCLC without sensitive epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) or proto-oncogene receptor tyrosine kinase (ROS1) alterations who had negative PD-L1 expression and received first-line pembrolizumab plus chemotherapy (the Pembro group) or platinum-based dual chemotherapy with or without bevacizumab (the Chemo group). The efficacy outcomes and safety profiles of the two groups were compared.</p><p><strong>Results: </strong>The study included 246 patients (Pembro group, n=114; Chemo group, n=132). The median follow-up period was 28.3 months. The Pembro group significantly prolonged progression-free survival (PFS) compared with the Chemo group [9.5 months, 95% confidence interval (CI): 7.5-11.5 <i>vs</i>. 7.2 months, 95% CI: 5.7-8.7; hazard ratio (HR) =0.64, 95% CI: 0.46-0.87; P=0.004]. Squamous cell lung cancer (SCC) patients demonstrated substantial PFS benefit (13.8 months, 95% CI: 3.2-24.1 <i>vs</i>. 4.8 months, 95% CI: 3.4-6.2; P<0.001), while non-SCC patients showed comparable PFS (9.3 months, 95% CI: 7.6-11.0 <i>vs</i>. 8.0 months, 95% CI: 6.0-10.0; P=0.56). Overall survival (OS) favored the Pembro group (21.2 months, 95% CI: 16.0-26.4 <i>vs</i>. 20.1 months, 95% CI: 15.5-24.7; HR =0.71, 95% CI: 0.50-1.00; P=0.052). The SCC patients in the Pembro group demonstrated a significant survival benefit with a median OS that was not reached, compared to 14.2 months (95% CI: 6.3-22.1) in the chemo group (HR =0.42, 95% CI: 0.22-0.78; P=0.007). Grade ≥3 non-immune-related adverse events (non-irAEs) occurred more often in the Pembro group (46.8%) than the Chemo group (33.1%, P=0.03). Moreover, 45 (39.5%) patients experienced 63 irAEs, and no grade 5 or new irAEs were observed.</p><p><strong>Conclusions: </strong>Pembrolizumab combined with chemotherapy may prolong survival in patients with PD-L1-negative advanced NSCLC, particularly those with squamous histology.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 5","pages":"1804-1820"},"PeriodicalIF":4.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12170236/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144326927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of a checkpoint inhibitor-related pneumonia diagnostic model based on exhaled nitric oxide: a prospective observational study.","authors":"Yimei Gao, Tingyue Luo, Danhui Huang, Zeyu Fu, Shudong Ma, Li Lin, Haohua Huang, Tiantian Liu, Jinming Zhang, Xiaoxiao Jiang, Yanmei Ye, Junwei Chen, Junjie Xi, Jinzhong Zhuo, Kaijun Chen, Jingqi Ai, Laiyu Liu, Shaoxi Cai, Hangming Dong","doi":"10.21037/tlcr-2024-1085","DOIUrl":"10.21037/tlcr-2024-1085","url":null,"abstract":"<p><strong>Background: </strong>Checkpoint inhibitor-related pneumonia (CIP) is a complication of immune checkpoint inhibitors (ICIs) with high mortality. There is still a lack of effective biomarkers to identify CIP. Exhaled nitric oxide (eNO), an airway inflammatory marker, can be obtained by non-invasive methods, but its value in CIP is unknown. The purpose of this study was to investigate the value of eNO in CIP.</p><p><strong>Methods: </strong>Lung cancer patients who received ICIs were included at Nanfang Hospital, Southern Medical University. Fractional eNO at expiratory flow rates of 50 and 200 mL/s (FeNO50 and FeNO200) were measured. The alveolar concentration of nitric oxide (CaNO) was calculated based on the two-compartment model of airway and alveoli. The optimal CaNO cut-off value was determined by the receiver operating characteristic (ROC) curve. eNO, clinical characteristics, and laboratory tests were analyzed to find out the risk factors for CIP by logistic regression analysis. A multi-indicator model based on best risk factors for CIP was developed and internally validated.</p><p><strong>Results: </strong>CaNO was significantly elevated in the CIP group [8.1±5.0 <i>vs</i>. 4.9±3.1 parts per billion (ppb), P<0.001]. The area under the curve (AUC) of CaNO to differentiate CIP was 0.728 [95% confidence interval (CI): 0.670-0.786; P=0.001]. The best cut-off value of CaNO was 6.350 ppb. Increased CaNO [odds ratio (OR), 1.30; 95% CI: 1.19-1.43; P<0.001], emphysema reported on chest computed tomography (CT) (OR, 2.54; 95% CI: 1.41-4.60), a small amount of pleural effusion reported on chest CT (OR, 2.48; 95% CI: 1.37-4.50), pre-existing radiotherapy (OR, 3.89; 95% CI: 1.96-7.73) and the lower counts of lymphocyte cell in peripheral blood (OR, 0.69; 95% CI: 0.44-1.10) were independently associated with CIP. The five factors were incorporated into a multi-indicator model with a good predictive accuracy of 0.821.</p><p><strong>Conclusions: </strong>CaNO may be a new marker for identifying CIP. Increased CaNO, pre-existing radiotherapy and emphysema reported on chest CT, a small amount of pleural effusion reported on chest CT, and lower count of lymphocyte cell in peripheral blood are independently associated with CIP.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 5","pages":"1740-1755"},"PeriodicalIF":4.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12170240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144326945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opportunities and challenges in lung cancer care in the era of large language models and vision language models.","authors":"Yi Luo, Hamed Hooshangnejad, Wilfred Ngwa, Kai Ding","doi":"10.21037/tlcr-24-801","DOIUrl":"10.21037/tlcr-24-801","url":null,"abstract":"<p><p>Lung cancer remains the leading cause of cancer-related deaths globally. Over the past decade, the development of artificial intelligence (AI) has significantly propelled lung cancer care, particularly in areas such as lung cancer early diagnosis, survival prediction, recurrence prediction, medical image processing, medical image registration, medical visual question answering, clinical report writing, medical image generation, and multimodal integration. This review aims to provide a comprehensive summary of the various AI methods utilized in lung cancer care, with a particular emphasis on machine learning and deep learning techniques. Moreover, with the advent and widespread application of large language models (LLMs), vision language models (VLMs), and multimodal integration for downstream clinical tasks, we explore the current landscape these cutting-edge AI tools offer. However, it also presents both significant challenges and opportunities, including data privacy risks, inherent biases that may exacerbate healthcare disparities, model hallucinations, ethical implications, implementation costs, and the lack of standardized evaluation metrics. Furthermore, the translation of these technologies from experimental research to clinical implementation demands comprehensive validation protocols and multidisciplinary collaboration to guarantee patient safety, therapeutic efficacy, and equitable healthcare delivery. This review emphasizes the critical role of AI in enhancing our understanding and management of lung cancer, ultimately striving for precision medicine and equitable healthcare worldwide.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 5","pages":"1830-1847"},"PeriodicalIF":4.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12170128/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144326957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of the number of induction chemotherapy cycles on the efficacy of first-line atezolizumab combined with chemotherapy in extensive-stage small cell lung cancer.","authors":"Mengxing You, Jiayu Liu, Fei Teng, Lige Wu, Haifeng Qin, Yan Zhang, Cuiying Zhang, Ziling Liu, Kewei Ma, Esteban C Gabazza, Jacopo Vannucci, Xuezhi Hao, Junling Li, Puyuan Xing","doi":"10.21037/tlcr-2025-207","DOIUrl":"10.21037/tlcr-2025-207","url":null,"abstract":"<p><strong>Background: </strong>Compared with chemotherapy alone, the addition of atezolizumab to the first-line treatment of extensive-stage small cell lung cancer (ES-SCLC) improves the overall survival (OS), but the benefit remains limited. This study aims at investigating the factors influencing prognosis and to assess the effect of the number of induction chemotherapy cycles on treatment efficacy.</p><p><strong>Methods: </strong>We retrospectively analyzed the data of patients with ES-SCLC treated in five centers between March 2020 and September 2022. All 45 patients received first-line treatment with etoposide plus platinum combined with atezolizumab. The primary endpoints were progression-free survival (PFS) and OS in the total population and subpopulations based on the number of induction chemotherapy cycles. Least absolute shrinkage and selection operator (LASSO) regression were applied to identify the prognostic variables, and the effect of varying the number of induction chemotherapy cycles on the treatment efficacy was evaluated.</p><p><strong>Results: </strong>A total of 45 patients were enrolled in the study. The median PFS for the first-line treatment was 7 months, and the median OS was 17.6 months. The following 10 variables were analyzed using LASSO regression: gender, age, liver metastasis, bone metastasis, brain metastasis, number of first-line induction chemotherapy cycles, first-line immunotherapy maintenance, receipt of cross-line immunotherapy, chest radiotherapy, and brain radiotherapy. The analysis revealed that receiving ≥6 cycles of induction chemotherapy was the most important variable affecting prognosis and the only one significant [concordance index: 0.658; hazard ratio: 0.32 (95% confidence interval: 0.17-0.63)]. Patients who received ≥6 cycles of induction chemotherapy (n=25) had a longer median PFS (8 <i>vs.</i> 5 months) and median OS (18.5 <i>vs.</i> 13.1 months) than those who received <6 cycles (n=20). Subgroup analyses indicated consistent survival benefits of ≥6 induction chemotherapy cycles across key subgroups, including males, patients aged ≤65 years, and those with or without brain metastasis (all P value <0.05).</p><p><strong>Conclusions: </strong>Receiving ≥6 cycles of induction chemotherapy significantly prolonged the median PFS and median OS of patients, highlighting its crucial factor influencing the efficacy of first-line atezolizumab combined with chemotherapy in patients with ES-SCLC.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1408-1417"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082210/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multidisciplinary international expert consensus on perioperative airway management.","authors":"Hengrui Liang, Guowei Che, Fei Cui, Junguo Dong, Weiquan Gu, Chundong Gu, Shun Xu, Yufeng Ba, Kaican Cai, Qingdong Cao, Chang Chen, Chun Chen, Qixun Chen, Liyang Cheng, Gang Feng, Yunjiu Gou, Wenwei Guo, Jinxi He, Junming He, Jian Hu, Ying Huang, Wenxi Wang, Wenjie Jiao, Shunjun Jiang, Jun Liu, Lan Lan, Wei Li, Xiaofei Li, Zhongcheng Li, Yin Li, Zhu Liang, Hongxu Liu, Yingbin Liu, Xinyu Mei, Xicheng Song, Daqiang Sun, Hui Tian, Ziqiang Tian, Jianhua Wang, Guangsuo Wang, Xin Xu, Xudong Xiang, Guobing Xu, Tao Xue, Chao Yang, Xiaolong Yan, Nuo Yang, Feng Yao, Dalong Yin, Xiaochuan Yin, Bentong Yu, Wei Zhai, Yu Zhang, Guangjian Zhang, Xiaowen Zhang, Qiang Zhang, Yi Zhang, Jun Zhao, Haihui Zhong, Alessandro Brunelli, Till Ploenes, Luca Bertolaccini, John Kit Chung Tam, Min P Kim, Majed Refai, Michel Gonzalez, Adam R Dyas, Nicoletta Pia Ardò, Hiran C Fernando, Giulio Maurizi, Gregor J Kocher, Giuseppe Marulli, Álvaro Fuentes-Martín, Gianluca Perroni, Kyung Soo Kim, Maria Rodriguez, Marcus Taylor, Xusen Zou, Wei Wang, Jianxing He","doi":"10.21037/tlcr-2025-273","DOIUrl":"10.21037/tlcr-2025-273","url":null,"abstract":"<p><strong>Background: </strong>Perioperative airway management is critical for patient safety and optimal surgical outcomes. Effective airway management reduces postoperative pulmonary complications and accelerates recovery. This expert consensus aims to update the earlier consensus based on the latest research and emphasize aspects that were previously overlooked.</p><p><strong>Methods: </strong>A comprehensive search up to June 2024 was performed. Earlier consensus documents were reviewed to ensure thorough coverage. A modified Delphi method involved 62 domestic experts from various surgical and anesthetic specialties who discussed and voted on preliminary recommendations in face-to-face meetings, requiring ≥70% agreement. Drafts were then reviewed by 18 international experts via email to incorporate diverse insights.</p><p><strong>Results: </strong>Through the modified Delphi method, consensus was achieved with ≥70% agreement among the 62 domestic experts, ensuring that the preliminary recommendations were robust and widely supported. Additionally, feedback from the 18 international experts provided diverse insights that further refined and validated the recommendations. Recommendations were established for preoperative airway preparation, anesthesia management, surgical approach, postoperative airway management, and managing coexisting respiratory diseases. These recommendations update the perspectives of earlier consensus documents based on the latest research and emphasize non-intubated surgery, inhalation therapy, and individualized treatment for patients with coexisting pulmonary diseases.</p><p><strong>Conclusions: </strong>This expert consensus provides a valuable reference for clinical practice. Further technological optimization and clinical research are needed to improve perioperative airway management.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1042-1060"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular heterogeneity of small cell lung cancer and new therapeutic possibilities: a narrative review of the literature.","authors":"Valeria Cognigni, Ilaria Toscani, Simona D'Agnelli, Federica Pecci, Luisella Righi, Rossana Berardi, Marcello Tiseo","doi":"10.21037/tlcr-24-755","DOIUrl":"10.21037/tlcr-24-755","url":null,"abstract":"<p><strong>Background and objective: </strong>Small cell lung cancer (SCLC) is an aggressive disease commonly occurring in individuals with a history of heavy smoking. Despite recent approvals of chemotherapy and immunotherapy in the first-line treatment of extensive-stage SCLC, it maintains a poor prognosis. Moreover, only a small percentage of patients benefits from the addition of immunotherapy to platinum-based chemotherapy. The lack of significant progress in therapeutic options unrevealed the urgent need for a deeper understanding of tumor biology and easy-to-use predictive biomarkers, aiming to better tailor the treatment strategy. The aim of this review is to summarize recent evidence about the biology, molecular heterogeneity, as well as tumor microenvironment (TME) of SCLC and their forefront therapeutic implications.</p><p><strong>Methods: </strong>A literature search was conducted using PubMed, focusing on articles published in English from 1981 to October 2024. Studies on SCLC biology and subclassification were selected for further analysis and integrated in the current narrative review.</p><p><strong>Key content and findings: </strong>SCLC entity implies four distinct molecular subtypes based on transcription factors expression, specifically achaete-scute homolog 1 (ASCL1), neurogenic differentiation 1 (NEUROD1), POU class 2 homeobox 3 (POU2F3), and yes-associated protein 1 (YAP1), reflecting the tumor heterogeneity in terms of gene expression, transcriptional profiles, immune infiltration, and treatment sensitivity. Recently, a new subgroup, \"SCLC-I\", has been proposed to replace the YAP1 subtype, showing higher responsiveness to immunotherapy. The TME, implying immune cell infiltration and their interactions with cancer cells, plays a crucial role in determining SCLC's sensitivity to immunotherapy.</p><p><strong>Conclusions: </strong>Advances in SCLC molecular characterization and the development of targeted therapies against specific molecular pathways might improve patients' clinical outcome, supporting a more personalized approach to this complex disease.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1441-1455"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082233/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}