Evidence map›Paper›PMID 40340737›Full record

ReviewFuture oncology (London, England)2025

The present and future of lung cancer screening: latest evidence.

Juan Gutiérrez Alliende, Ella A Kazerooni, Philip A J Crosbie, Xueqian Xie, Ankur Sharma, Joana Reis

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Future oncology (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Juan Gutiérrez AlliendeMedical Affairs for Digital Radiology, Bayer AG, Berlin, Germany.ORCID 0009-0000-3262-6276
Ella A KazerooniDepartments of Radiology & Internal Medicine, University of Michigan Medical School, Michigan, MI, USA.ORCID 0000-0001-5859-8744
Philip A J CrosbieDivision of Immunology, Immunity to Infection & Respiratory Medicine, University of Manchester, Manchester, UK.
Xueqian XieRadiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0002-6669-0097
Ankur SharmaMedical Affairs for Digital Radiology, Bayer AG, Berlin, Germany.
Joana ReisMedical Affairs for Digital Radiology, Bayer AG, Berlin, Germany.ORCID 0000-0003-0515-2022

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is the leading cause of cancer-related mortality worldwide. Early lung cancer detection improves lung cancer-related mortality and survival. This report summarizes presentations and panel discussions from a webinar, "The Present and Future of Lung Cancer Screening: Latest Evidence and AI Perspectives." The webinar provided the perspectives of experts from the United States, United Kingdom, and China on evidence-based recommendations and management in lung cancer screening (LCS), barriers, and the role of artificial intelligence (AI). With several countries now incorporating the utilization of AI in their screening programs, AI offers potential solutions to some of the challenges associated with LCS.

Indexed as

Early Detection of CancerLung NeoplasmsArtificial IntelligenceEvidence-Based MedicineHumansMass ScreeningUnited Kingdomartificial intelligencelow-dose computed tomographyLung cancerradiologyscreening

Identifiers

PMID40340737
PMCPMC12150595

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.