Evidence map›Paper›PMID 39886123›Full record

ArticleBMJ oncology2024

Blood-based DNA methylation markers for lung cancer prediction.

Justina Ucheojor Onwuka, Florence Guida, Ryan Langdon, Mikael Johansson, Gianluca Severi, Roger L Milne, Pierre-Antoine Dugué, Melissa C Southey, Paolo Vineis, Torkjel Sandanger and 6 more

Abstract read
In one paragraph

Article in BMJ oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. 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

16 authors.

Justina Ucheojor OnwukaGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.ORCID 0000-0002-4236-1758
Florence GuidaGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Ryan LangdonPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Mikael JohanssonDepartment of Radiation Sciences Oncology, Umeå University, Umea, Sweden.
Gianluca Severi'Exposome, Heredity, Cancer and Health' Team, Gustave Roussy, Universite Paris-Saclay, Villejuif, Île-de-France, France.
Roger L MilneCancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
Pierre-Antoine DuguéCancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
Melissa C SoutheyCancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
Paolo VineisMRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
Torkjel SandangerDepartment of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromso, Troms, Norway.
Therese Haugdahl NøstDepartment of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromso, Troms, Norway.
Marc Chadeau-HyamSchool of Public Health, Imperial College London, London, UK.
Caroline ReltonMRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, Bristol, UK.
Hilary A RobbinsGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.ORCID 0000-0001-6041-6866
Matthew SudermanMRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, Bristol, UK.
Mattias JohanssonGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.

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
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
NCI NIH HHS R01 CA262164NCI NIH HHS U19 CA203654World Health Organization 001
6 · The paper itself

Abstract

Objective: Screening high-risk individuals with low-dose CT reduces mortality from lung cancer, but many lung cancers occur in individuals who are not eligible for screening. Risk biomarkers may be useful to refine risk models and improve screening eligibility criteria. We evaluated if blood-based DNA methylation markers can improve a traditional lung cancer prediction model. Methods and analysis: This study used four prospective cohorts with blood samples collected prior to lung cancer diagnosis. The study was restricted to participants with a history of smoking, and one control was individually matched to each lung cancer case using incidence density sampling by cohort, sex, date of blood collection, age and smoking status. To train a DNA methylation-based risk score, we used participants from Melbourne Collaborative Cohort Study-Australia (n=648) and Northern Sweden Health and Disease Study-Sweden (n=380) based on five selected CpG sites. The risk discriminative performance of the methylation score was subsequently validated in participants from European Investigation into Cancer and Nutrition-Italy (n=267) and Norwegian Women and Cancer-Norway (n=185) and compared with that of the questionnaire-based PLCOm2012 lung cancer risk model. Results: The area under the receiver operating characteristic curve (AUC) for the PLCOm2012 model in the validation studies was 0.70 (95% CI: 0.65 to 0.75) compared with 0.73 (95% CI: 0.68 to 0.77) for the methylation score model ( Conclusions: This study suggests that the methylation-based risk prediction score alone provides similar lung cancer risk-discriminatory performance as the questionnaire-based PLCOm2012 risk model.

Indexed as

BiomarkersEpidemiologyLung cancer (non-small cell)Lung cancer (small-cell)

Identifiers

PMID39886123
PMCPMC11234992

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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.