Lung Cancer最新文献

{"title":"Comparison of molecular subtype composition between independent sets of primary and brain metastatic small cell lung carcinoma and matched samples","authors":"Dániel Sztankovics,&nbsp;Fatime Szalai,&nbsp;Dorottya Moldvai,&nbsp;Titanilla Dankó,&nbsp;Bálint Scheich,&nbsp;Judit Pápay,&nbsp;Anna Sebestyén,&nbsp;Ildikó Krencz","doi":"10.1016/j.lungcan.2024.108071","DOIUrl":"10.1016/j.lungcan.2024.108071","url":null,"abstract":"<div><h3>Introduction</h3><div>Recent advances in the subclassification of small cell lung carcinomas (SCLCs) may help to overcome the unmet need for targeted therapies and improve survival. However, limited information is available on how the expression of the subtype markers changes during tumour progression. Our study aimed to compare the expression of these markers in primary and brain metastatic SCLCs.</div></div><div><h3>Materials and methods</h3><div>Immunohistochemical analysis of the subtype markers was performed on 120 SCLCs (including 10 matched samples) and SCLC xenografts.</div></div><div><h3>Results</h3><div>Compared to primary SCLCs, there was a significant increase in the proportion of mixed subtypes in brain metastases, with a rate of ASCL1^high/NeuroD1^high and ASCL1^high/NeuroD1^high/YAP1^high subtypes increasing to 48 % and 18 %, respectively. The subtype of the paired samples matched in only one-third of the cases. Although we did not observe a significant change after chemotherapy, a continuous decrease in ASCL1 expression coupled with an increase in the NeuroD1 expression was detected in the xenografts in a long-term experiment.</div></div><div><h3>Discussion</h3><div>Our results indicate that the expression of subtype markers frequently changes during disease progression, and subtype analysis of the primary SCLC may not provide accurate information about the characteristics of the recurrent or metastatic tumour. Therefore, repeated sampling and subtyping may be necessary for subtype-specific targeted therapy.</div></div>","PeriodicalId":18129,"journal":{"name":"Lung Cancer","volume":"199 ","pages":"Article 108071"},"PeriodicalIF":4.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142895704","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":"Immunotherapy or targeted therapy with or without stereotactic radiosurgery for patients with brain metastases from melanoma or non-small cell lung cancer – The ETOP 19-21 USZ-STRIKE study","authors":"Michael Weller ,&nbsp;Emilie Le Rhun ,&nbsp;Lydia Tsamtsouri ,&nbsp;Reinhard Dummer ,&nbsp;Matthias Guckenberger ,&nbsp;Karin Ribi ,&nbsp;Anna Maria di Giacomo ,&nbsp;Gabriele Minuti ,&nbsp;Ana Collazo-Lorduy ,&nbsp;Dieta Brandsma ,&nbsp;Mary O’Brien ,&nbsp;Ekin Ermis ,&nbsp;Natalie Fischer ,&nbsp;Paolo Ascierto ,&nbsp;Mario Mandala ,&nbsp;Giuseppe Minniti ,&nbsp;Patricia Iranzo ,&nbsp;Heidi Roschitzki-Voser ,&nbsp;Barbara Ruepp ,&nbsp;Eva Grolimund ,&nbsp;Rolf Stahel","doi":"10.1016/j.lungcan.2024.108069","DOIUrl":"10.1016/j.lungcan.2024.108069","url":null,"abstract":"","PeriodicalId":18129,"journal":{"name":"Lung Cancer","volume":"199 ","pages":"Article 108069"},"PeriodicalIF":4.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142895746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the feasibility and external validity of natural language processing-extracted data for advanced lung cancer patients","authors":"Yuchen Li ,&nbsp;Jennifer Law ,&nbsp;Lisa W. Le ,&nbsp;Janice J.N. Li ,&nbsp;Christopher Pettengell ,&nbsp;Patricia Demarco ,&nbsp;Michael Duong ,&nbsp;David Merritt ,&nbsp;Sean Davidson ,&nbsp;Mike Sung ,&nbsp;Qixuan Li ,&nbsp;Sally CM Lau ,&nbsp;Sajda Zahir ,&nbsp;Ryan Chu ,&nbsp;Malcom Ryan ,&nbsp;Khizar Karim ,&nbsp;Josh Morganstein ,&nbsp;Adrian Sacher ,&nbsp;Lawson Eng ,&nbsp;Frances A. Shepherd ,&nbsp;Natasha B. Leighl","doi":"10.1016/j.lungcan.2025.108080","DOIUrl":"10.1016/j.lungcan.2025.108080","url":null,"abstract":"<div><h3>Background</h3><div>Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with advanced lung cancer (aLC). We assessed the external validity of our NLP-extracted data by comparing our findings to those reported in the literature.</div></div><div><h3>Methods</h3><div>Patients diagnosed with stage IIIB or IV lung cancer between January 2015 to December 2017 at Princess Margaret Cancer Centre who received at least one dose of systemic therapy were included. Their electronic health records were provided to Pentavere’s NLP platform, DARWEN^TM, in March 2019. Descriptive statistics summarized baseline patient and cancer characteristics, molecular biomarkers, and first-line systemic therapies. Cox multivariate models were used to evaluate prognostic factors for advanced non-small cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) cohort.</div></div><div><h3>Result</h3><div>NLP extracted clinical information (n = 333 patients) in a total of 8 hours, with only a few missing data for smoking status (n = 2), and Eastern Cooperative Oncology Group (ECOG) status (n = 5). Baseline patient and cancer characteristics summarized from NLP-extracted data were comparable to those in previous studies and population reports. For NSCLC patients, being male (HR 1.44, 95 % CI [1.04, 2.00]), having worse ECOG (1.48 [1.22, 1.81]), and having liver (2.24 [1.45, 3.46]), bone (2.09 [1.48, 2.96]), or lung metastases (2.54 [1.05, 2.26]) were associated with worse survival outcomes. For SCLC patients, having older age (HR 1.70 per 10 years, 95 % CI [1.10, 2.63]) and liver metastases (3.81 [1.61, 9.01]) were associated with worse survival outcomes.</div></div><div><h3>Conclusion</h3><div>Our study demonstrated that automated data extraction using NLP is feasible and time efficient. Additionally, the NLP-extracted data can be used to identify valid and useful clinical endpoints for research. NLP holds significant potential to accelerate the extraction of real-world data for future observational studies.</div></div>","PeriodicalId":18129,"journal":{"name":"Lung Cancer","volume":"199 ","pages":"Article 108080"},"PeriodicalIF":4.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142950817","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":"Geographic variation in delay to surgical treatment among non-small cell lung cancer patients","authors":"Getayeneh Antehunegn Tesema ,&nbsp;Rob G. Stirling ,&nbsp;Win Wah ,&nbsp;Zemenu Tadesse Tessema ,&nbsp;Stephane Heritier ,&nbsp;Arul Earnest","doi":"10.1016/j.lungcan.2024.108077","DOIUrl":"10.1016/j.lungcan.2024.108077","url":null,"abstract":"<div><h3>Objectives</h3><div>Delayed surgery is significantly associated with an increased risk of disease progression and adverse outcomes in lung cancer. Evidence is available on the variation in delayed surgical treatment among patients with Non-Small Cell Lung Cancer (NSCLC). However, the relative contribution of patient- and area-level risk factors to the geographic patterns of delayed surgery in patients with NSCLC is poorly understood. Therefore, we aimed to explore the geographic variation in delay to surgical treatment among patients with NSCLC.</div></div><div><h3>Materials and Methods</h3><div>This study utilized data from the Victorian Lung Cancer Registry (VLCR) and the Australian Bureau of Statistics (ABS). A total of 3,088 patients with NSCLC who had undergone surgery were included. We applied a Bayesian spatial multilevel model incorporating spatially structured and unstructured random effects to examine patient and area-level risk factors associated with delays to surgical treatment. Model comparison was conducted using the Deviance Information Criterion (DIC).</div></div><div><h3>Results</h3><div>Over one-third (40.45 %) of NSCLC patients experienced delayed surgical treatment. Significant geographic variation in delayed surgical treatment among NSCLC patients across Local Government Areas (LGAs) was observed. Factors significantly associated with higher odds of delayed surgical treatment included clinical stage II (AOR = 1.56, 95 % CrI: 1.26–1.92), stage III (AOR = 1.90, 95 % CrI: 1.46–2.47), stage IV (AOR = 2.04, 95 % CrI: 1.15–3.61), treatment at inner regional hospitals (AOR = 2.86, 95 % CrI: 2.17–3.70), presence of comorbidities (AOR = 1.19, 95 % CrI: 1.02–1.40), and diagnosis during the COVID-19 pandemic (AOR = 1.32, 95 % CrI: 1.10–1.57).</div></div><div><h3>Conclusions</h3><div>This study highlights the need to improve the treatment pathway for patients with NSCLC by reducing the time between diagnosis and surgery. Future targeted initiatives are essential to promote timely surgeries for NSCLC patients, especially in high-need areas.</div></div>","PeriodicalId":18129,"journal":{"name":"Lung Cancer","volume":"199 ","pages":"Article 108077"},"PeriodicalIF":4.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142965522","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":"Impact of locoregional recurrence versus distant metastasis on overall survival in patients with Non-Small cell lung cancer after Surgery: A secondary analysis of PORT-C RCT","authors":"Zeliang Ma ,&nbsp;Yunsong Liu ,&nbsp;Yongxing Bao ,&nbsp;Meiqi Wang ,&nbsp;Xu Yang ,&nbsp;Yu Men ,&nbsp;Jianyang Wang ,&nbsp;Lei Deng ,&nbsp;Yirui Zhai ,&nbsp;Chen Hu ,&nbsp;Nan Bi ,&nbsp;Luhua Wang ,&nbsp;Zhouguang Hui","doi":"10.1016/j.lungcan.2024.108063","DOIUrl":"10.1016/j.lungcan.2024.108063","url":null,"abstract":"<div><h3>Purpose</h3><div>The therapeutic advantage of postoperative radiation therapy (PORT) for non-small cell lung cancer (NSCLC) has not been shown to benefit overall survival (OS) according to two randomized controlled trials (RCTs), albeit an enhancement in locoregional-free survival was observed. We aimed to evaluate the relative influence of locoregional recurrence (LR) and distant metastasis (DM) on OS for patients with NSCLC after surgery.</div></div><div><h3>Methods</h3><div>This was a secondary analysis of PORT-C RCT. Patients with pN2 NSCLC undergoing complete resection followed by chemotherapy were included. A dynamic prediction model was developed to evaluate the impact of LR and DM on OS. The endpoint was OS. Age, sex, smoking history, histology, Karnofsky Performance Status, tumor side, T stage, and positive lymph node were baseline factors, whereas LR and DM status were time-dependent covariates.</div></div><div><h3>Results</h3><div>In total, 364 patients were eligible, including 214 and 150 in the non-PORT and PORT groups, respectively. DM significantly decreased OS in both the non-PORT (odds ratio [OR], 4.74; 95 % CI, 2.70–8.30; P &lt; 0.01) and PORT (OR, 5.43; 95 % CI, 2.56–11.48; P &lt; 0.01) groups. LR also significantly impacted OS in the non-PORT (OR, 2.09; 95 % CI, 1.12–3.93; P = 0.02) and the PORT (OR, 3.44; 95 % CI, 1.53–7.75; P &lt; 0.01) groups. Multivariate Cox analysis identified the pT stage, positive lymph nodes, and histology as variables correlated with DM. A nomogram was developed to estimate the risk of DM. PORT did not significantly enhance OS in either the low (HR, 1.42; 95 % CI, 0.63–3.19, P = 0.40) or high-risk (HR, 0.62; 95 % CI, 0.35–1.09, P = 0.10) subgroup but in the medium-risk subgroup (HR, 0.20; 95 % CI, 0.05–0.86, P = 0.02).</div></div><div><h3>Conclusion</h3><div>DM and LR significantly impacted OS in patients with NSCLC after surgery. DM emerged as the dominant failure pattern, emphasizing more effective control of DM. PORT was beneficial for patients with a medium risk of DM.</div></div>","PeriodicalId":18129,"journal":{"name":"Lung Cancer","volume":"199 ","pages":"Article 108063"},"PeriodicalIF":4.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142864323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring machine learning tools in a retrospective case-study of patients with metastatic non-small cell lung cancer treated with first-line immunotherapy: A feasibility single-centre experience","authors":"Francesca Rita Ogliari ,&nbsp;Alberto Traverso ,&nbsp;Simone Barbieri ,&nbsp;Marco Montagna ,&nbsp;Filippo Chiabrando ,&nbsp;Enrico Versino ,&nbsp;Antonio Bosco ,&nbsp;Alessia Lin ,&nbsp;Roberto Ferrara ,&nbsp;Sara Oresti ,&nbsp;Giuseppe Damiano ,&nbsp;Maria Grazia Viganò ,&nbsp;Michele Ferrara ,&nbsp;Silvia Teresa Riva ,&nbsp;Antonio Nuccio ,&nbsp;Francesco Maria Venanzi ,&nbsp;Davide Vignale ,&nbsp;Giuseppe Cicala ,&nbsp;Anna Palmisano ,&nbsp;Stefano Cascinu ,&nbsp;Michele Reni","doi":"10.1016/j.lungcan.2024.108075","DOIUrl":"10.1016/j.lungcan.2024.108075","url":null,"abstract":"<div><h3>Background</h3><div>Artificial intelligence (AI) models are emerging as promising tools to identify predictive features among data coming from health records. Their application in clinical routine is still challenging, due to technical limits and to explainability issues in this specific setting. Response to standard first-line immunotherapy (ICI) in metastatic Non-Small-Cell Lung Cancer (NSCLC) is an interesting population for machine learning (ML), since up to 30% of patients do not benefit.</div></div><div><h3>Methods</h3><div>We retrospectively collected all consecutive patients with PD-L1 ≥ 50 % metastatic NSCLC treated with first-line ICI at our institution between 2017 and 2021. Demographic, laboratory, molecular and clinical data were retrieved manually or automatically according to data sources. Primary aim was to explore feasibility of ML models in clinical routine setting and to detect problems and solutions for everyday implementation. Early progression was used as preliminary endpoint to test our algorithm.</div></div><div><h3>Results</h3><div>Out of 123 patients, 106 were included, 52/106 (49 %) had disease progression or died within 3 months of start of ICI. Early progression correlated with increased neutrophil percentage (&gt;80 % of white blood cells), neutrophil/lymphocyte ratio (≥8) and lower-range PD-L1 status (&lt;70 %) at baseline, which was consistent with literature. Automated ML (AutoML) models run on our dataset reached precision scores around 80 %, with Voting Ensemble emerging as best performing model, while white-box models (such as Shapley Additive exPlanations) provided better explainability. In all AutoML models, laboratory features were the top selected features, whilst clinical ones needed more pre-processing before gaining relevance, which was consistent with different data extraction (automatic versus manual) and missing data rates.</div></div><div><h3>Conclusions</h3><div>ML models’ application is feasible in clinical practice and can trustworthily predict early progression during first-line ICI for metastatic NSCLC. Solving pre-analytical issues is key for future improvement, focusing on automatic tools for data extraction, collection and explainability.</div></div>","PeriodicalId":18129,"journal":{"name":"Lung Cancer","volume":"199 ","pages":"Article 108075"},"PeriodicalIF":4.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142927465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic analysis of comprehensive next generation sequencing data to explore the criteria for MET amplification as an actionable biomarker in NSCLC","authors":"David Chun Cheong Tsui ,&nbsp;Jessica K. Lee ,&nbsp;Candice Francheska B. Tambaoan ,&nbsp;Jason Hughes ,&nbsp;Bernard Fendler ,&nbsp;Brennan Decker ,&nbsp;Garrett M. Frampton ,&nbsp;Alexa B. Schrock ,&nbsp;D. Ross Camidge","doi":"10.1016/j.lungcan.2025.108081","DOIUrl":"10.1016/j.lungcan.2025.108081","url":null,"abstract":"<div><h3>Introduction</h3><div><em>MET</em> amplification (<em>MET</em>amp) can be a <em>de novo</em> or acquired resistance driver; however, the definition of <em>MET</em>amp that best captures patients who may respond to targeted therapy remains debated. We explored the genomic landscape of <em>MET</em>amp NSCLC including degree of amplification, co-drivers, amplicon size, and outcomes to MET inhibitors.</div></div><div><h3>Methods</h3><div>Hybrid-capture NGS-based genomic profiling from 88,547 tissue and 12,428 liquid NSCLC samples were queried for <em>MET</em>amp (copy number (CN) ≥ ploidy + 4, or amplification ratio (AmpRatio; [CN/sample ploidy] ≥ 3). A nationwide de-identified real-world (rw) clinico-genomic database (CGDB) of NGS results linked to deidentified, electronic health record-derived clinical data was used to assess treatment and outcomes.</div></div><div><h3>Results</h3><div>Among 10,760 evaluable patients in CGDB, 362 (3.4%) had a <em>MET</em>amp. In targeted therapy-naïve cases, <em>MET</em> AmpRatio negatively correlated with non-<em>MET</em>ex14 co-drivers (median 4.1 vs 2.9, p &lt; 0.0001). <em>MET</em> AmpRatio was not significantly correlated with tumor mutational burden (p = 0.79) but was inversely correlated with amplicon size (p &lt; 0.001). Among paired <em>MET</em>amp tissue samples, 8/30 had <em>MET</em>amp detected in liquid; higher tumor fraction and AmpRatio were associated with liquid detection. Among 39 <em>MET</em>amp patients receiving MET inhibitors, longer median real-world progression free survival was observed with <em>MET</em> AmpRatio ≥ 3 vs &lt; 3 (4.9 vs. 1.7mos, HR 0.53 [95 %CI:0.21–1.3]).</div></div><div><h3>Conclusions</h3><div><em>MET</em> AmpRatio positively correlated with focal amplification and absence of co-drivers and trended with increased benefit from MET inhibitors. Further studies evaluating<!--> <!-->combinatorial data including <em>MET</em> AmpRatio, amplicon size and presence of other potential drivers, as predictive biomarkers for therapies targeting <em>MET</em> amplification in NSCLC are warranted.</div></div>","PeriodicalId":18129,"journal":{"name":"Lung Cancer","volume":"199 ","pages":"Article 108081"},"PeriodicalIF":4.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142965520","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":"Continuing immune checkpoint inhibitors after progression: Real-world patterns of care and outcomes in second-line treatment for extensive-stage small-cell lung cancer","authors":"Baishen Zhang ,&nbsp;Hejing Bao ,&nbsp;Zhanquan Li ,&nbsp;Jing Chen ,&nbsp;Hui Yu ,&nbsp;Meichen Li ,&nbsp;Muyan Cai ,&nbsp;Likun Chen","doi":"10.1016/j.lungcan.2024.108021","DOIUrl":"10.1016/j.lungcan.2024.108021","url":null,"abstract":"<div><h3>Introduction</h3><div>Small cell lung cancer (SCLC) is a highly malignant tumor with an extremely poor prognosis. In the current<!--> <!-->era of immunotherapy, the role of immune checkpoint inhibitors (ICIs) in the second-line treatment of patients with extensive-stage SCLC (ES-SCLC) who have progressed to initial chemoimmunotherapy remains unclear.</div></div><div><h3>Methods</h3><div>A multicenter retrospective study were conducted, involving patients with ES-SCLC who received second-line (2L) therapy after progression to first-line chemoimmunotherapy. Patients were divided into 2L-ICIs group and 2L-non-ICIs group according to whether ICIs were added to the 2L treatment. The efficacy and adverse events of the two groups were analyzed and compared.</div></div><div><h3>Results</h3><div>A total of 103 patients were included in this study, with 53 in the 2L-ICIs group and 50 in the 2L-non-ICIs group. The 2L-ICIs group demonstrated a longer median progression-free survival (PFS) compared to the 2L-non-ICIs group (4.4 months vs 3.9 months, HR = 0.45, <em>p</em> = 0.001). Similarly, median overall survival was also prolonged in the 2L-ICIs group (10.0 months vs 6.9 months, HR = 0.56, <em>p</em> = 0.015). Cox regression analysis revealed that the addition of ICIs to 2L treatment was an independent prognostic factor for both PFS and OS in ES-SCLC patients. Subgroup analysis indicated that patients with a first-line PFS of ≥6 months could potentially benefit more from 2L ICIs. Furthermore, the occurrence of adverse events in the two groups exhibited a similar pattern.</div></div><div><h3>Conclusion</h3><div>For ES-SCLC patients who have progressed to first-line chemoimmunotherapy, adding ICIs to second-line treatment may be considered as an option with limited benefit but manageable adverse effects.</div></div>","PeriodicalId":18129,"journal":{"name":"Lung Cancer","volume":"199 ","pages":"Article 108021"},"PeriodicalIF":4.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CT-assessed sarcopenia and immune-related adverse events in patients with lung cancer: A competing risk time-to-event analysis","authors":"Erick Suazo-Zepeda ,&nbsp;Alain R. Viddeleer ,&nbsp;Willemijn J. Maas ,&nbsp;Douwe Postmus ,&nbsp;Marjolein A. Heuvelmans ,&nbsp;T. Jeroen N. Hiltermann ,&nbsp;Geertruida H. De Bock","doi":"10.1016/j.lungcan.2024.108054","DOIUrl":"10.1016/j.lungcan.2024.108054","url":null,"abstract":"<div><h3>Background</h3><div>Immune checkpoint inhibitors (ICIs) can induce immune-related adverse events (irAEs). This study investigates the relationship between CT-assessed sarcopenia and irAEs in patients with lung cancer who are receiving ICIs.</div></div><div><h3>Methods</h3><div>Patients were enrolled if they had lung cancer treated with ICIs at the University Medical Center Groningen (2015–2021) and had undergone low-dose CT scans that included the third lumbar vertebral level (L3). CT-assessed sarcopenia was defined based on reported L3 skeletal muscle mass index (L3SMI) thresholds. Patients were categorized into no, any-grade, and severe irAE groups. The association between CT-assessed sarcopenia and irAEs was assessed by competing risk time-to-event analysis, accounting for the risk of death. Sub-distribution hazard ratios (_SDHR) were calculated using Fine–Gray regression models adjusted for relevant confounders. The association between CT-assessed sarcopenia and overall survival (OS) was evaluated through survival analyses.</div></div><div><h3>Results</h3><div>We included 363 patients; most were male (60.9 %), had favorable Eastern Cooperative Oncology Group (ECOG) performance statuses (0–1; 90.1 %), had stage IV disease (92.8 %), and received ICI monotherapy (82.9 %). Of these, 45.6 % developed any-grade irAEs and 21 % developed severe irAEs. Endocrine disorders were the most common mild irAEs (24.8 %), while respiratory disorders were the most common severe irAEs (24.7 %). CT-assessed sarcopenia was more prevalent in the no irAE group (87 %) compared with the any-grade (77 %) and severe (79 %) irAE groups. Presence of CT-assessed sarcopenia was associated with a lower risk of developing any irAEs (_SDHR = 0.62 [95 % CI: 0.41–0.92]). No significant association was found between CT-assessed sarcopenia and severe irAEs (fully adjusted model, _SDHR = 0.74 [95 % CI: 0.39–1.4]), or between CT-assessed sarcopenia and OS.</div></div><div><h3>Conclusion</h3><div>CT-assessed sarcopenia is associated with a reduced risk of any irAEs in patients with lung cancer receiving ICIs, possibly because higher muscle mass enhances the host response to immunological stimulation. Recognizing sarcopenia as a predictive factor for irAEs is relevant for personalizing treatments.</div></div>","PeriodicalId":18129,"journal":{"name":"Lung Cancer","volume":"199 ","pages":"Article 108054"},"PeriodicalIF":4.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872512","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":"FURVENT: Phase 3 trial of firmonertinib vs chemotherapy as first-line treatment for advanced NSCLC with EGFR exon 20 insertion mutations (FURMO-004)","authors":"Alexander Spira ,&nbsp;Byoung Chul Cho ,&nbsp;Enriqueta Felip ,&nbsp;Edward B. Garon ,&nbsp;Koichi Goto ,&nbsp;Melissa Johnson ,&nbsp;Natasha Leighl ,&nbsp;Antonio Passaro ,&nbsp;David Planchard ,&nbsp;Sanjay Popat ,&nbsp;James Chih-Hsin Yang ,&nbsp;Xiaoqian Lu ,&nbsp;Yong Jiang ,&nbsp;Jack Huang ,&nbsp;Morgan Lam ,&nbsp;Marcin Kowanetz ,&nbsp;Shirley Wang ,&nbsp;John Le ,&nbsp;Jerry Y. Hsu ,&nbsp;Cai-Cun Zhou","doi":"10.1016/j.lungcan.2024.108066","DOIUrl":"10.1016/j.lungcan.2024.108066","url":null,"abstract":"","PeriodicalId":18129,"journal":{"name":"Lung Cancer","volume":"199 ","pages":"Article 108066"},"PeriodicalIF":4.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143070993","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}