Evidence map›Paper›PMID 37487906›Full record

ReviewJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer2024

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.

Stephen Lam, Chunxue Bai, David R Baldwin, Yan Chen, Casey Connolly, Harry de Koning, Marjolein A Heuvelmans, Ping Hu, Ella A Kazerooni, Harriet L Lancaster and 10 more

Registry-linked trialAbstract readReview
In one paragraph

Review in Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07524803 (A Prospective Observational Study to Determine the Utility of Lung Cancer Screening for Early Detection of Suspicious Lung Nodules in Latin America), which is not on this map. Cited by 59 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07524803 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

A Prospective Observational Study to Determine the Utility of Lung Cancer Screening for Early Detection of Suspicious Lung Nodules in Latin America

TypeobservationalSponsorLatin American Consortium for the Lung Cancer ResearchRan2026 to 2032Enrolled2,000ConditionsLung Cancer ScreeningArmsChest X-Ray, Low Dose CT scan
3 · Its place in the literature

Who cites it

59 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Stephen LamDepartment of Integrative Oncology, British Columbia Cancer Research Institute, Vancouver, British Columbia, Canada; Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. Electronic address: slam2@bccancer.bc.ca.
Chunxue BaiShanghai Respiratory Research Institute and Chinese Alliance Against Cancer, Shanghai, People's Republic of China.
David R BaldwinNottingham University Hospitals National Health Services (NHS) Trust, Nottingham, United Kingdom.
Yan ChenDigital Screening, Faculty of Medicine & Health Sciences, University of Nottingham Medical School, Nottingham, United Kingdom.
Casey ConnollyInternational Association for the Study of Lung Cancer, Denver, Colorado.
Harry de KoningDepartment of Public Health, Erasmus MC University Medical Centre Rotterdam, The Netherlands.
Marjolein A HeuvelmansUniversity of Groningen, Groningen, The Netherlands; Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands; The Institute for Diagnostic Accuracy, Groningen, The Netherlands.
Ping HuDivision of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Ella A KazerooniDivision of Cardiothoracic Radiology, Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan.
Harriet L LancasterUniversity of Groningen, Groningen, The Netherlands; Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands; The Institute for Diagnostic Accuracy, Groningen, The Netherlands.
Georg LangsComputational Imaging Research Laboratory, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
Annette McWilliamsDepartment of Respiratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia, Australia; Australia University of Western Australia, Nedlands, Western Australia.
Raymond U OsarogiagbonThoracic Oncology Research Group, Baptist Cancer Center, Memphis, Tennessee.
Matthijs OudkerkCenter for Medical Imaging and The Institute for Diagnostic Accuracy, Faculty of Medical Sciences, University of Groningen, Groningen, The Netherlands.
Matthew PetersWoolcock Institute of Respiratory Medicine, Macquarie University, Sydney, New South Wales, Australia.
Hilary A RobbinsGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Liora SaharData Science, American Cancer Society, Atlanta, Georgia.
Robert A SmithEarly Cancer Detection Science, American Cancer Society, Atlanta, Georgia.
Natthaya TriphuridetDepartment of Medicine, Chulabhorn Hospital, Bangkok, Thailand.
John FieldDepartment of Molecular and Clinical Cancer Medicine, The University of Liverpool, Liverpool, United Kingdom.

Funding

Translating Molecular and Clinical Data to Population Lung Cancer Risk AssessmentU19CA203654 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Christopher I. Amos · 2017 to 2026
$23.7M
The Lung EArly Proteins project: A LEAP toward implementing biomarkers in lung cancer screeningR01CA262164 · NCI · INTERNATIONAL AGENCY FOR RES ON CANCER · PI ROBBINS, HILARY A. · 2022 to 2025
$2.0M
Evaluating risk prediction models for use in lung cancer screening in diverse populations around the worldR03CA245979 · NCI · INTERNATIONAL AGENCY FOR RES ON CANCER · PI ROBBINS, HILARY A. · 2020 to 2020
$112k
NCI NIH HHS R01 CA262164NCI NIH HHS R03 CA245979NCI NIH HHS U19 CA203654World Health Organization 001
6 · The paper itself

Abstract

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.

Indexed as

Lung NeoplasmsArtificial IntelligenceEarly Detection of CancerHumansLungMass ScreeningTomography, X-Ray ComputedIncidentally detected lung nodulesLung cancer LDCT screeningNever-smokersQuality indicators

Identifiers

PMID37487906
PMCPMC11253723

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.