Evidence map›Paper›PMID 36600392›Full record

ArticleBMJ open2022

Lung CAncer SCreening in French women using low-dose CT and Artificial intelligence for DEtection: the CASCADE study protocol.

Marie-Pierre Revel, Hendy Abdoul, Guillaume Chassagnon, Emma Canniff, Isabelle Durand-Zaleski, Marie Wislez

Registry-linked trialOpen access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05195385 (Lung Cancer Screening With Low-dose CT Scan in Women), which is not on this map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
2.6field-weighted citation impact, top 9% of its field
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.

NCT05195385 narecruitingnot on this map

Lung Cancer Screening With Low-dose CT Scan in Women : Implementation Study

TypeinterventionalSponsorAssistance Publique - Hôpitaux de ParisRan2022 to 2027Enrolled2,635ConditionsLung Cancer ScreeningArmsLow-dose computed tomography of the chest
3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Guideline
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. Low dose CT for lung cancer screening.Journal of thoracic disease · 2025
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
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 at 2 institutions in 1 country.

Marie-Pierre RevelUniversité Paris Cité, Paris, France marie-pierre.revel@aphp.fr.ORCID 0000-0001-8213-7817
Hendy AbdoulAssistance Publique-Hopitaux de Paris, URC Necker/Cochin, Paris, France.
Guillaume ChassagnonUniversité Paris Cité, Paris, France.
Emma CanniffAssistance Publique- Hopitaux de Paris, Cochin hospital Radiology department, Paris, France.
Isabelle Durand-ZaleskiUniversité Paris Cité, Paris, France.ORCID 0000-0002-4078-1476
Marie WislezUniversité Paris Cité, Paris, France.
Université Paris Cité · FRAssistance Publique – Hôpitaux de Paris · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLung cancer screening (LCS) using low-dose CT has been demonstrated to reduce lung cancer-related mortality in large randomised controlled trials. Moving from trials to practice requires answering practical questions about the level of expertise of CT readers, the need for double reading as in trials and the potential role of artificial intelligence (AI). In addition, most LCS studies have predominantly included male participants with women being under-represented, even though the benefit of screening is greater for them. Thus, this study aims to compare the performance of a single CT reading by general radiologists trained in LCS using AI as a second reader to that of a double reading by expert thoracic radiologists, in a campaign for low-dose CT screening in high-risk women. METHODS AND ANALYSIS: This observational cohort study will recruit 2400 asymptomatic women aged between 50 and 74 years, current or former smokers with at least a 20 pack-year smoking history, in 4 different French district areas. Assistance with smoking cessation will be offered to current smokers. An initial low-dose CT scan will be performed, with subsequent follow-ups at 1 year and 2 years. The primary objective is to compare CT scan readings by a single LCS-trained, AI-assisted radiologist to that of an expert double reading. The secondary objectives are: to evaluate the performance of AI as a stand-alone reader; the adherence to screening of female participants; the influence on smoking cessation; the psychological consequences of screening; the detection of chronic obstructive pulmonary disease (COPD), coronary artery disease and osteoporosis on low-dose CT scans and the costs incurred by screening. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Comité de Protection des Personnes Sud-Est 1 (ethics approval number: 2021-A02265-36 with an amendment on 15 July 2022). Trial results will be disseminated at conferences, through relevant patient groups and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT05195385.

Indexed as

Lung NeoplasmsPulmonary Disease, Chronic ObstructiveAgedArtificial IntelligenceEarly Detection of CancerFemaleHumansMiddle AgedObservational Studies as TopicResearch DesignTomography, X-Ray ComputedAdult oncologyChest imagingClinical trialsComputed tomographyDiagnostic radiologyRespiratory tract tumours

Identifiers

PMID36600392
PMCPMC9743404
OpenAlexW4310904873

What OpenQuestion holds

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LicenceCC BY-NC
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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.