Evidence map›Paper›PMID 39179310›Full record

ArticleThe Lancet. Digital health2024

Evaluation of risk prediction models to select lung cancer screening participants in Europe: a prospective cohort consortium analysis.

Xiaoshuang Feng, Patrick Goodley, Karine Alcala, Florence Guida, Rudolf Kaaks, Roel Vermeulen, George S Downward, Catalina Bonet, Sandra M Colorado-Yohar, Demetrius Albanes and 8 more

Abstract read
In one paragraph

Article in The Lancet. Digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 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.

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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Improving lung cancer screening diagnostic efficiency.Current opinion in pulmonary medicine · 2026
    Review
  3. Over- and underscreening for lung cancer.Translational lung cancer research · 2026
    Review
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  12. Advances in the Basic Sciences in Thoracic Oncology in the Last 20 Years and Their Translational Impact.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2026
    Review
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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

18 authors.

Xiaoshuang FengGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Patrick GoodleyDivision of Immunology, Immunity to Infection and Respiratory Medicine, University of Manchester, Manchester, UK; Manchester Thoracic Oncology Centre, Manchester University NHS Foundation Trust, Manchester, UK.
Karine AlcalaGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Florence GuidaEnvironment and Lifestyle Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Rudolf KaaksDepartment of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany; Translational Lung Research Center Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany.
Roel VermeulenJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands; Department of Population Health Sciences, Institute for Risk Assessment Sciences, University of Utrecht, Utrecht, Netherlands.
George S DownwardJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands; Department of Population Health Sciences, Institute for Risk Assessment Sciences, University of Utrecht, Utrecht, Netherlands.
Catalina BonetNutrition and Cancer Group, Epidemiology, Public Health, Cancer Prevention and Palliative Care Program, Bellvitge Biomedical Research Institute, L'Hospitalet de Llobregat, Barcelona, Spain; Unit of Nutrition and Cancer, Catalan Institute of Oncology, L'Hospitalet de Llobregat, Barecelona, Spain.
Sandra M Colorado-YoharDepartment of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain; CIBER Epidemiología y Salud Pública, Madrid, Spain; Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia.
Demetrius AlbanesMetabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
Stephanie J WeinsteinMetabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
Marcel GoldbergPopulation-based Epidemiological Cohorts Unit, INSERM UMS 11, Villejuif, France; Paris Cité University, Paris, France.
Marie ZinsPopulation-based Epidemiological Cohorts Unit, INSERM UMS 11, Villejuif, France; Paris Cité University, Paris, France.
Caroline ReltonMRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK; School of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Arnulf LanghammerHUNT Research Center, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway; Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway.
Anne Heidi SkogholtDepartment of Public Health and Nursing, KG Jebsen Centre for Genetic Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway.
Mattias JohanssonGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Hilary A RobbinsGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France. Electronic address: robbinsh@iarc.who.int.

Funding

Translating Molecular and Clinical Data to Population Lung Cancer Risk AssessmentU19CA203654 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Christopher I. Amos, Rayjean J. Hung · 2017 to 2026
$23.7M
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 R03 CA245979NCI NIH HHS U19 CA203654World Health Organization 001
6 · The paper itself

Abstract

backgroundLung cancer risk prediction models might efficiently identify individuals who should be offered lung cancer screening. However, their performance has not been comprehensively evaluated in Europe. We aimed to externally validate and evaluate the performance of several risk prediction models that predict lung cancer incidence or mortality in prospective European cohorts.

methodsWe analysed 240 137 participants aged 45-80 years with a current or former smoking history from nine European countries in four prospective cohorts from the pooled database of the Lung Cancer Cohort Consortium: the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (Finland), the Nord-Trøndelag Health Study (Norway), CONSTANCES (France), and the European Prospective Investigation into Cancer and Nutrition (Denmark, Germany, Italy, Spain, Sweden, the Netherlands, and Norway). We evaluated ten lung cancer risk models, which comprised the Bach, the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 model (PLCO

findingsAmong the participants, 1734 lung cancer cases and 1072 lung cancer deaths occurred within five years of enrolment. Most models had reasonable calibration in most countries, although the LLP version 2 overpredicted risk by more than 50% in eight countries (expected to observed ≥1·50). The PLCO

interpretationSeveral lung cancer risk prediction models showed good performance in European countries and might improve the efficiency of lung cancer screening if used in place of categorical eligibility criteria.

fundingUS National Cancer Institute, l'Institut National du Cancer, Cancer Research UK.

Indexed as

Early Detection of CancerLung NeoplasmsAgedAged, 80 and overEuropeFemaleHumansIncidenceMaleMiddle AgedProspective StudiesRisk AssessmentRisk Factors

Identifiers

PMID39179310
PMCPMC11369914

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.