Pub Date : 2026-02-01DOI: 10.1016/j.jtho.2025.09.1756
Kimberly A. Shoenbill MD, PhD , Jamie S. Ostroff PhD , Kathryn L. Taylor PhD , Ana Jafarinia MPH , Mara Minion MA , Lou-Anne Chichester MPH , Brandon Omernik MS , Marcia McCall PhD, MBA , Sophia Yeung MHA , Kara Wiseman PhD, MPH , Li-Shiun Chen MD, ScD, MPH , Ramzi G. Salloum PhD, MA, MBA , Graham Warren MD, PhD
Introduction
Although there is widespread acceptance of the importance of assessing and treating tobacco use in cancer care settings, there is much variation in the documentation and reporting of metrics relevant to tobacco treatment. The Cancer Center Cessation Initiative (C3I), as part of the National Cancer Institute’s Cancer Moonshot, convened a Metrics Standardization Workgroup to develop a data dictionary and make recommendations for standardized quality measurement, program evaluation, and tobacco treatment program development.
Methods
A multidisciplinary workgroup of 12 subject matter experts was convened to deliberate and standardize definitions for tobacco assessment and treatment utilization metrics. Decisions on which data elements to include were informed by clinical guidelines, literature reviews, and workgroup members’ expertise. Consensus was reached when all members agreed that the proposed metric was clear, clinically relevant, and could be abstracted and reported.
Results
The group considered metrics in the following categories: (1) patient identification, screening, and referral; (2) tobacco treatment process metrics; and (3) treatment outcomes. Furthermore, the group developed a tobacco screening, referral and engagement workflow, and a data library for the following terms: patient population, screening rate, tobacco use prevalence, referral rate, reach, unsuccessful reach attempts, enrollment, treatment engagement, and counseling dose. Outcome metrics (i.e., varied “quit rate” terms) were collated and defined.
Conclusions
The proposed standardized data definitions can be used to improve communication and measure effectiveness for tobacco use treatment, research, operational performance, policy, quality improvement, and guideline development.
{"title":"Recommendations for Standardization of Tobacco Use Treatment Data","authors":"Kimberly A. Shoenbill MD, PhD , Jamie S. Ostroff PhD , Kathryn L. Taylor PhD , Ana Jafarinia MPH , Mara Minion MA , Lou-Anne Chichester MPH , Brandon Omernik MS , Marcia McCall PhD, MBA , Sophia Yeung MHA , Kara Wiseman PhD, MPH , Li-Shiun Chen MD, ScD, MPH , Ramzi G. Salloum PhD, MA, MBA , Graham Warren MD, PhD","doi":"10.1016/j.jtho.2025.09.1756","DOIUrl":"10.1016/j.jtho.2025.09.1756","url":null,"abstract":"<div><h3>Introduction</h3><div>Although there is widespread acceptance of the importance of assessing and treating tobacco use in cancer care settings, there is much variation in the documentation and reporting of metrics relevant to tobacco treatment. The Cancer Center Cessation Initiative (C3I), as part of the National Cancer Institute’s Cancer Moonshot, convened a Metrics Standardization Workgroup to develop a data dictionary and make recommendations for standardized quality measurement, program evaluation, and tobacco treatment program development.</div></div><div><h3>Methods</h3><div>A multidisciplinary workgroup of 12 subject matter experts was convened to deliberate and standardize definitions for tobacco assessment and treatment utilization metrics. Decisions on which data elements to include were informed by clinical guidelines, literature reviews, and workgroup members’ expertise. Consensus was reached when all members agreed that the proposed metric was clear, clinically relevant, and could be abstracted and reported.</div></div><div><h3>Results</h3><div>The group considered metrics in the following categories: (1) patient identification, screening, and referral; (2) tobacco treatment process metrics; and (3) treatment outcomes. Furthermore, the group developed a tobacco screening, referral and engagement workflow, and a data library for the following terms: patient population, screening rate, tobacco use prevalence, referral rate, reach, unsuccessful reach attempts, enrollment, treatment engagement, and counseling dose. Outcome metrics (i.e., varied “quit rate” terms) were collated and defined.</div></div><div><h3>Conclusions</h3><div>The proposed standardized data definitions can be used to improve communication and measure effectiveness for tobacco use treatment, research, operational performance, policy, quality improvement, and guideline development.</div></div>","PeriodicalId":17515,"journal":{"name":"Journal of Thoracic Oncology","volume":"21 2","pages":"Pages 258-266"},"PeriodicalIF":20.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01DOI: 10.1016/j.jtho.2025.10.017
Ahmed S.K. Al-Khafaji PhD , Fawaz Al-Alloosh MSc, MD , Haydar H. Alabedi MD , Khitam M.A. Al-Obaidi HDip Medicine , Alia H. Al-Khafaji MSc , Sima I. Ghaddar BSc , Mahmood J. Khalsan PhD , Ali S. Baay MBChB, FIBMS Medicine, FIBMS (Pulmonology) , Waleed M. Hussen MBChB, FIBMS (Th.C.V.S) , Faris H. Lami MBChB, PhD, FFPH , Mahdi Sheikh MD, PhD
{"title":"Lung Cancer in Iraq","authors":"Ahmed S.K. Al-Khafaji PhD , Fawaz Al-Alloosh MSc, MD , Haydar H. Alabedi MD , Khitam M.A. Al-Obaidi HDip Medicine , Alia H. Al-Khafaji MSc , Sima I. Ghaddar BSc , Mahmood J. Khalsan PhD , Ali S. Baay MBChB, FIBMS Medicine, FIBMS (Pulmonology) , Waleed M. Hussen MBChB, FIBMS (Th.C.V.S) , Faris H. Lami MBChB, PhD, FFPH , Mahdi Sheikh MD, PhD","doi":"10.1016/j.jtho.2025.10.017","DOIUrl":"10.1016/j.jtho.2025.10.017","url":null,"abstract":"","PeriodicalId":17515,"journal":{"name":"Journal of Thoracic Oncology","volume":"21 2","pages":"Pages 227-234"},"PeriodicalIF":20.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01DOI: 10.1016/j.jtho.2025.12.103
{"title":"Tobacco News Update—From the IASLC Tobacco Control Committee","authors":"","doi":"10.1016/j.jtho.2025.12.103","DOIUrl":"10.1016/j.jtho.2025.12.103","url":null,"abstract":"","PeriodicalId":17515,"journal":{"name":"Journal of Thoracic Oncology","volume":"21 2","pages":"Pages 211-214"},"PeriodicalIF":20.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01DOI: 10.1016/j.jtho.2025.10.009
Xiuning Le MD , Christina Baik MD , Byoung Chul Cho MD , Jonathan W. Riess MD , Zofia Piotrowska MD, MHS , Adrianus Johannes de Langen MD , Sarah B. Goldberg MD , Jonathan W. Goldman MD , Noemi Reguart MD , Yoshimasa Shiraishi MD , Helen Ambrose PhD , Paula G. Fraenkel MD , Brayan Merchan Ruiz MD , Paul E. Smith MSc , Kwan Ho Tang PhD , Helena A. Yu MD
Introduction
The ORCHARD (NCT03944772) study was conducted to characterize resistance mechanisms and identify optimal treatments after progressive disease (PD) on first-line osimertinib. We report results from the osimertinib plus savolitinib module.
Methods
Patients with EGFR-mutated NSCLC with PD on first-line osimertinib with MET gene amplification (≥4 copies of MET over tumor ploidy) per next-generation sequencing of a post-progression biopsy received osimertinib plus savolitinib. Primary end point was investigator-assessed objective response rate (ORR). Secondary end points included progression-free survival, duration of response, overall survival, and safety. Correlation of ORR with baseline molecular alterations was an exploratory analysis.
Results
A total of 32 patients were enrolled; all had tumors with MET amplification. At primary analysis cutoff (January 2023), confirmed ORR was 47% (80% confidence interval [CI]: 34–60). Median duration of response was 14.5 months (95% CI: 5.6–18.7). Median progression-free survival was 7.6 months (95% CI: 3.2–15.9). There was a trend toward increased ORR in patients with high MET gene copy number (≥10 versus <10). Furthermore, 14 patients (44%) had grade 3 or higher treatment-emergent adverse events; most often pneumonia (n = 3; 9%). At final database lock (May 2024), 20 patients (63%) had died; median overall survival was 20.7 months (95% CI: 9.9–34.8).
Conclusions
Osimertinib plus savolitinib demonstrated encouraging clinical benefit in patients with EGFR-mutated advanced NSCLC and MET amplification after PD on first-line osimertinib. Safety was consistent with profiles of the individual drugs.
{"title":"Osimertinib Plus Savolitinib in Patients With EGFR-Mutated Advanced NSCLC With MET Alterations After First-Line Osimertinib: Clinical Outcomes, Safety, and Biomarker Analysis: A Brief Report","authors":"Xiuning Le MD , Christina Baik MD , Byoung Chul Cho MD , Jonathan W. Riess MD , Zofia Piotrowska MD, MHS , Adrianus Johannes de Langen MD , Sarah B. Goldberg MD , Jonathan W. Goldman MD , Noemi Reguart MD , Yoshimasa Shiraishi MD , Helen Ambrose PhD , Paula G. Fraenkel MD , Brayan Merchan Ruiz MD , Paul E. Smith MSc , Kwan Ho Tang PhD , Helena A. Yu MD","doi":"10.1016/j.jtho.2025.10.009","DOIUrl":"10.1016/j.jtho.2025.10.009","url":null,"abstract":"<div><h3>Introduction</h3><div>The ORCHARD (NCT03944772) study was conducted to characterize resistance mechanisms and identify optimal treatments after progressive disease (PD) on first-line osimertinib. We report results from the osimertinib plus savolitinib module.</div></div><div><h3>Methods</h3><div>Patients with <em>EGFR</em>-mutated NSCLC with PD on first-line osimertinib with <em>MET</em> gene amplification (≥4 copies of <em>MET</em> over tumor ploidy) per next-generation sequencing of a post-progression biopsy received osimertinib plus savolitinib. Primary end point was investigator-assessed objective response rate (ORR). Secondary end points included progression-free survival, duration of response, overall survival, and safety. Correlation of ORR with baseline molecular alterations was an exploratory analysis.</div></div><div><h3>Results</h3><div>A total of 32 patients were enrolled; all had tumors with <em>MET</em> amplification. At primary analysis cutoff (January 2023), confirmed ORR was 47% (80% confidence interval [CI]: 34–60). Median duration of response was 14.5 months (95% CI: 5.6–18.7). Median progression-free survival was 7.6 months (95% CI: 3.2–15.9). There was a trend toward increased ORR in patients with high <em>MET</em> gene copy number (≥10 versus <10). Furthermore, 14 patients (44%) had grade 3 or higher treatment-emergent adverse events; most often pneumonia (n = 3; 9%). At final database lock (May 2024), 20 patients (63%) had died; median overall survival was 20.7 months (95% CI: 9.9–34.8).</div></div><div><h3>Conclusions</h3><div>Osimertinib plus savolitinib demonstrated encouraging clinical benefit in patients with <em>EGFR</em>-mutated advanced NSCLC and <em>MET</em> amplification after PD on first-line osimertinib. Safety was consistent with profiles of the individual drugs.</div></div>","PeriodicalId":17515,"journal":{"name":"Journal of Thoracic Oncology","volume":"21 2","pages":"Pages 318-327"},"PeriodicalIF":20.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145355249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01DOI: 10.1016/j.jtho.2025.11.017
Stephen Lam MD, FRCPC , David R. Baldwin MD, FRCP , Anand Devaraj MD , John Field PhD, FRCPath. , Claudia I. Henschke MD, PhD , Marjolein A. Heuvelmans MD, PhD , Rudolf M. Huber MD, PhD , Catherine Jones M.B.B.S., FRCR , Andrea Borondy-Kitts MS, MPH , Molly Siu Ching Li M.B.B.S., FHKAM , Renelle Myers MD, FRCPC , Raymond U. Osarogiagbon M.B.B.S., FACP , Hilary A. Robbins PhD , Martin C. Tammemägi DVM, MSc, PhD , Kathryn L. Taylor PhD , Natthaya Triphuridet MD, PhD , Randi M. Williams PhD, MPH , David Yankelevitz MD
In the past two decades, lung cancer screening (LCS) with low-dose computed tomography (LDCT) has emerged as one of the most effective strategies for reducing lung cancer mortality. Landmark trials, including NLST and NELSON, demonstrated mortality reductions exceeding 20%, establishing LDCT as the standard of care for early detection in high-risk populations. Currently, 13 countries have implemented national or regional LCS programs, with additional nations preparing for rollout. Advances in risk-prediction models, volumetric nodule assessment, and structured management protocols have improved precision and efficiency. Integration of artificial intelligence is enhancing nodule detection, prediction of malignancy risk, individualized screening intervals, and workflow optimization. Real-world evidence confirms improved stage distribution and suggests reduction in lung cancer mortality. Initiatives such as promoting community engagement, equitable access through geospatial mapping, and mobile screening will improve screening uptake and retention. Embedding tobacco dependence treatment within LCS further augments life-years gained. Complementary incidental pulmonary-nodule programs and expanding studies in people who have never smoked are extending the reach of early detection, whereas biomarker research is progressing toward integration with imaging-based screening. The potential to use LDCT scans to detect coronary heart disease and chronic obstructive pulmonary disease may have a major impact on future health care benefits. Ongoing efforts to harmonize data collection standards, establish quality indicators, and strengthen workforce training are essential to sustain high-quality implementation. As LCS evolves into a cornerstone of lung cancer control, continued innovation in risk stratification, imaging technologies, and biomarker integration will be key to maximizing global benefit and equity.
{"title":"A Game-Changing 20 Years: Progress and Future Directions in Lung Cancer Screening","authors":"Stephen Lam MD, FRCPC , David R. Baldwin MD, FRCP , Anand Devaraj MD , John Field PhD, FRCPath. , Claudia I. Henschke MD, PhD , Marjolein A. Heuvelmans MD, PhD , Rudolf M. Huber MD, PhD , Catherine Jones M.B.B.S., FRCR , Andrea Borondy-Kitts MS, MPH , Molly Siu Ching Li M.B.B.S., FHKAM , Renelle Myers MD, FRCPC , Raymond U. Osarogiagbon M.B.B.S., FACP , Hilary A. Robbins PhD , Martin C. Tammemägi DVM, MSc, PhD , Kathryn L. Taylor PhD , Natthaya Triphuridet MD, PhD , Randi M. Williams PhD, MPH , David Yankelevitz MD","doi":"10.1016/j.jtho.2025.11.017","DOIUrl":"10.1016/j.jtho.2025.11.017","url":null,"abstract":"<div><div>In the past two decades, lung cancer screening (LCS) with low-dose computed tomography (LDCT) has emerged as one of the most effective strategies for reducing lung cancer mortality. Landmark trials, including NLST and NELSON, demonstrated mortality reductions exceeding 20%, establishing LDCT as the standard of care for early detection in high-risk populations. Currently, 13 countries have implemented national or regional LCS programs, with additional nations preparing for rollout. Advances in risk-prediction models, volumetric nodule assessment, and structured management protocols have improved precision and efficiency. Integration of artificial intelligence is enhancing nodule detection, prediction of malignancy risk, individualized screening intervals, and workflow optimization. Real-world evidence confirms improved stage distribution and suggests reduction in lung cancer mortality. Initiatives such as promoting community engagement, equitable access through geospatial mapping, and mobile screening will improve screening uptake and retention. Embedding tobacco dependence treatment within LCS further augments life-years gained. Complementary incidental pulmonary-nodule programs and expanding studies in people who have never smoked are extending the reach of early detection, whereas biomarker research is progressing toward integration with imaging-based screening. The potential to use LDCT scans to detect coronary heart disease and chronic obstructive pulmonary disease may have a major impact on future health care benefits. Ongoing efforts to harmonize data collection standards, establish quality indicators, and strengthen workforce training are essential to sustain high-quality implementation. As LCS evolves into a cornerstone of lung cancer control, continued innovation in risk stratification, imaging technologies, and biomarker integration will be key to maximizing global benefit and equity.</div></div>","PeriodicalId":17515,"journal":{"name":"Journal of Thoracic Oncology","volume":"21 2","pages":"Pages 235-252"},"PeriodicalIF":20.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01DOI: 10.1016/j.jtho.2025.11.015
Wei-Chin Chang MD, PhD , Teh-Ying Chou MD, PhD
{"title":"Resolving the Staging Dilemma in Multiple Lung Cancers: A Prevalence-Weighted Bioinformatic Approach to the 2024 IASLC Recommendations","authors":"Wei-Chin Chang MD, PhD , Teh-Ying Chou MD, PhD","doi":"10.1016/j.jtho.2025.11.015","DOIUrl":"10.1016/j.jtho.2025.11.015","url":null,"abstract":"","PeriodicalId":17515,"journal":{"name":"Journal of Thoracic Oncology","volume":"21 2","pages":"Pages 221-223"},"PeriodicalIF":20.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01DOI: 10.1016/j.jtho.2025.08.024
Hyungjin Kim MD, PhD , Eunseo Jo BA , Jinseob Kim MD , Seung Hun Jang MD, PhD , Joo Sung Sun MD , Gong Yong Jin MD, PhD , Hyae Young Kim MD, PhD , Yeol Kim MD, PhD , Jin Mo Goo MD, PhD
Introduction
Interval lung cancers (ILCs) are key indicators of lung cancer screening (LCS) performance. However, data on the proportion, characteristics, and mortality of ILCs under biennial screening in Asian populations remain limited.
Methods
We analyzed participants from the baseline biennial Korean national LCS program between 2019 and 2020. Screening-detected lung cancers (SLCs) were defined as those diagnosed within 1 year of a positive screening result. ILCs were defined as cancers diagnosed more than 1 year after a negative screening result but within 2 years or before the next screening. Risk factors for ILC were assessed using multivariable logistic regression among participants with a negative screening result. All-cause mortality was compared between SLCs and ILCs using multivariable Cox regression analysis.
Results
Among 124,595 participants, SLCs and ILCs occurred in 0.56% and 0.17%, respectively. ILCs accounted for 18.5% of all lung cancers within 2 years; 65.4% were in Lung-RADS category 1. Risk factors for ILC included older age (adjusted odds ratio [OR], 1.14; 95% confidence interval [CI]: 1.11–1.17; p < 0.001), greater smoking exposure (adjusted OR, 1.010; 95% CI: 1.004–1.016; p = 0.002), a history of malignancy (adjusted OR, 2.22; 95% CI: 1.41–3.51; p < 0.001), emphysema (adjusted OR, 2.88; 95% CI: 2.15–3.85; p < 0.001), and interstitial lung abnormalities (adjusted OR, 4.16; 95% CI: 2.88–6.01; p < 0.001). ILCs had higher all-cause mortality than SLCs (adjusted hazard ratio, 1.43; 95% CI: 1.13–1.80; p = 0.002).
Conclusions
ILCs are common under biennial LCS, making them potentially suboptimal for Asian heavy smokers.
{"title":"Screening-Detected Versus Interval Lung Cancer in the Biennial Korean National Lung Cancer Screening Program: Proportion, Characteristics, and Mortality","authors":"Hyungjin Kim MD, PhD , Eunseo Jo BA , Jinseob Kim MD , Seung Hun Jang MD, PhD , Joo Sung Sun MD , Gong Yong Jin MD, PhD , Hyae Young Kim MD, PhD , Yeol Kim MD, PhD , Jin Mo Goo MD, PhD","doi":"10.1016/j.jtho.2025.08.024","DOIUrl":"10.1016/j.jtho.2025.08.024","url":null,"abstract":"<div><h3>Introduction</h3><div>Interval lung cancers (ILCs) are key indicators of lung cancer screening (LCS) performance. However, data on the proportion, characteristics, and mortality of ILCs under biennial screening in Asian populations remain limited.</div></div><div><h3>Methods</h3><div>We analyzed participants from the baseline biennial Korean national LCS program between 2019 and 2020. Screening-detected lung cancers (SLCs) were defined as those diagnosed within 1 year of a positive screening result. ILCs were defined as cancers diagnosed more than 1 year after a negative screening result but within 2 years or before the next screening. Risk factors for ILC were assessed using multivariable logistic regression among participants with a negative screening result. All-cause mortality was compared between SLCs and ILCs using multivariable Cox regression analysis.</div></div><div><h3>Results</h3><div>Among 124,595 participants, SLCs and ILCs occurred in 0.56% and 0.17%, respectively. ILCs accounted for 18.5% of all lung cancers within 2 years; 65.4% were in Lung-RADS category 1. Risk factors for ILC included older age (adjusted odds ratio [OR], 1.14; 95% confidence interval [CI]: 1.11–1.17; <em>p</em> < 0.001), greater smoking exposure (adjusted OR, 1.010; 95% CI: 1.004–1.016; <em>p</em> = 0.002), a history of malignancy (adjusted OR, 2.22; 95% CI: 1.41–3.51; <em>p</em> < 0.001), emphysema (adjusted OR, 2.88; 95% CI: 2.15–3.85; <em>p</em> < 0.001), and interstitial lung abnormalities (adjusted OR, 4.16; 95% CI: 2.88–6.01; <em>p</em> < 0.001). ILCs had higher all-cause mortality than SLCs (adjusted hazard ratio, 1.43; 95% CI: 1.13–1.80; <em>p</em> = 0.002).</div></div><div><h3>Conclusions</h3><div>ILCs are common under biennial LCS, making them potentially suboptimal for Asian heavy smokers.</div></div>","PeriodicalId":17515,"journal":{"name":"Journal of Thoracic Oncology","volume":"21 2","pages":"Pages 283-293"},"PeriodicalIF":20.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145008325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号