Current and Future Perspectives on Computed Tomography Screening for Lung Cancer : A Roadmap From 2023 to 2027 From the International Association for the Study of Lung Cancer
Copyright © 2023 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved..
Low-dose computed tomography (LDCT) screening for lung cancer substantially reduces mortality from lung cancer, as revealed in randomized controlled trials and meta-analyses. This review is based on the ninth CT screening symposium of the International Association for the Study of Lung Cancer, which focuses on the major themes pertinent to the successful global implementation of LDCT screening and develops a strategy to further the implementation of lung cancer screening globally. These recommendations provide a 5-year roadmap to advance the implementation of LDCT screening globally, including the following: (1) establish universal screening program quality indicators; (2) establish evidence-based criteria to identify individuals who have never smoked but are at high-risk of developing lung cancer; (3) develop recommendations for incidentally detected lung nodule tracking and management protocols to complement programmatic lung cancer screening; (4) Integrate artificial intelligence and biomarkers to increase the prediction of malignancy in suspicious CT screen-detected lesions; and (5) standardize high-quality performance artificial intelligence protocols that lead to substantial reductions in costs, resource utilization and radiologist reporting time; (6) personalize CT screening intervals on the basis of an individual's lung cancer risk; (7) develop evidence to support clinical management and cost-effectiveness of other identified abnormalities on a lung cancer screening CT; (8) develop publicly accessible, easy-to-use geospatial tools to plan and monitor equitable access to screening services; and (9) establish a global shared education resource for lung cancer screening CT to ensure high-quality reading and reporting.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:19 |
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| Enthalten in: |
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer - 19(2024), 1 vom: 28. Jan., Seite 36-51 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Lam, Stephen [VerfasserIn] |
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| Links: |
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| Themen: |
Incidentally detected lung nodules |
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| Anmerkungen: |
Date Completed 09.01.2024 Date Revised 24.03.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.jtho.2023.07.019 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM359881203 |
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| 520 | |a Copyright © 2023 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved. | ||
| 520 | |a Low-dose computed tomography (LDCT) screening for lung cancer substantially reduces mortality from lung cancer, as revealed in randomized controlled trials and meta-analyses. This review is based on the ninth CT screening symposium of the International Association for the Study of Lung Cancer, which focuses on the major themes pertinent to the successful global implementation of LDCT screening and develops a strategy to further the implementation of lung cancer screening globally. These recommendations provide a 5-year roadmap to advance the implementation of LDCT screening globally, including the following: (1) establish universal screening program quality indicators; (2) establish evidence-based criteria to identify individuals who have never smoked but are at high-risk of developing lung cancer; (3) develop recommendations for incidentally detected lung nodule tracking and management protocols to complement programmatic lung cancer screening; (4) Integrate artificial intelligence and biomarkers to increase the prediction of malignancy in suspicious CT screen-detected lesions; and (5) standardize high-quality performance artificial intelligence protocols that lead to substantial reductions in costs, resource utilization and radiologist reporting time; (6) personalize CT screening intervals on the basis of an individual's lung cancer risk; (7) develop evidence to support clinical management and cost-effectiveness of other identified abnormalities on a lung cancer screening CT; (8) develop publicly accessible, easy-to-use geospatial tools to plan and monitor equitable access to screening services; and (9) establish a global shared education resource for lung cancer screening CT to ensure high-quality reading and reporting | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Review | |
| 650 | 4 | |a Incidentally detected lung nodules | |
| 650 | 4 | |a Lung cancer LDCT screening | |
| 650 | 4 | |a Never-smokers | |
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| 700 | 1 | |a Bai, Chunxue |e verfasserin |4 aut | |
| 700 | 1 | |a Baldwin, David R |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Yan |e verfasserin |4 aut | |
| 700 | 1 | |a Connolly, Casey |e verfasserin |4 aut | |
| 700 | 1 | |a de Koning, Harry |e verfasserin |4 aut | |
| 700 | 1 | |a Heuvelmans, Marjolein A |e verfasserin |4 aut | |
| 700 | 1 | |a Hu, Ping |e verfasserin |4 aut | |
| 700 | 1 | |a Kazerooni, Ella A |e verfasserin |4 aut | |
| 700 | 1 | |a Lancaster, Harriet L |e verfasserin |4 aut | |
| 700 | 1 | |a Langs, Georg |e verfasserin |4 aut | |
| 700 | 1 | |a McWilliams, Annette |e verfasserin |4 aut | |
| 700 | 1 | |a Osarogiagbon, Raymond U |e verfasserin |4 aut | |
| 700 | 1 | |a Oudkerk, Matthijs |e verfasserin |4 aut | |
| 700 | 1 | |a Peters, Matthew |e verfasserin |4 aut | |
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| 700 | 1 | |a Sahar, Liora |e verfasserin |4 aut | |
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| 700 | 1 | |a Triphuridet, Natthaya |e verfasserin |4 aut | |
| 700 | 1 | |a Field, John |e verfasserin |4 aut | |
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