Evidence map›Paper›PMID 41344813›Full record

ArticleThe British journal of general practice : the journal of the Royal College of General Practitioners2026

Prediagnostic primary care consultations and imaging in emergency-diagnosed versus referred patients with lung cancer: a population-based linked data study.

Marta Berglund, Becky White, Matthew E Barclay, Emma Whitfield, Cristina Renzi, Meena Rafiq, Neal Navani, Caroline A Thompson, Georgios Lyratzopoulos

Abstract read
In one paragraph

Article in The British journal of general practice : the journal of the Royal College of General Practitioners, 2026. 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

9 authors.

Marta BerglundEpidemiology of Cancer Healthcare & Outcomes Group, Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK marta.berglund@ucl.ac.uk.ORCID 0009-0002-3015-3190
Becky WhiteEpidemiology of Cancer Healthcare & Outcomes Group, Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK.ORCID 0000-0002-0643-7890
Matthew E BarclayEpidemiology of Cancer Healthcare & Outcomes Group, Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK.ORCID 0000-0003-1148-1922
Emma WhitfieldEpidemiology of Cancer Healthcare & Outcomes Group, Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK.ORCID 0000-0001-5427-7150
Cristina RenziEpidemiology of Cancer Healthcare & Outcomes Group, Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK.ORCID 0000-0003-3845-9493
Meena RafiqEpidemiology of Cancer Healthcare & Outcomes Group, Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK.ORCID 0000-0002-1837-1542
Neal NavaniLungs for Living Research Centre, UCL Respiratory, University College London, London, UK.ORCID 0000-0002-6412-7516
Caroline A ThompsonDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, US.ORCID 0000-0001-9990-9756
Georgios LyratzopoulosEpidemiology of Cancer Healthcare & Outcomes Group, Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK.ORCID 0000-0002-2873-7421

Funding

Diagnosis of Cancer in the Emergency Room - Explaining Persistent Disparities - Diversity SupplementR01CA264176 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI THOMPSON, CAROLINE AVERY · 2021 to 2025
$2.0M
Cancer Research UK EDDPJT-NOV24/100036NCI NIH HHS R01 CA264176
6 · The paper itself

Abstract

backgroundEmergency diagnosis of lung cancer is common and associated with worse prognosis.

aimTo compare prediagnostic healthcare use between emergency-diagnosed patients and patients referred routinely or urgently. DESIGN AND

settingPopulation-based linked English primary care, hospital admission, imaging, and cancer registration data were analysed for patients with lung cancer (2007-2018).

methodMonthly prediagnosis rates of consultations (for any clinical reason and selected symptoms) and chest imaging by diagnostic route (emergency, routine referral, and urgent referral) were measured. Multivariable Poisson regression estimated route-specific event rates and inflection points.

resultsThe study examined 4473 patients with lung cancer with features representative of the nationwide incident cohort, of whom 33% (

conclusionSimilar or shorter diagnostic windows suggest similar potential for earlier diagnosis among emergency-diagnosed and referred route patients alike. Earlier detection may be supported through improved management of non-specific symptoms, timely follow-up of imaging, and greater access to chest computed tomography. Future research should measure missed diagnostic opportunities to identify clinical actions to further reduce emergency lung cancer diagnoses.

Indexed as

Lung NeoplasmsPrimary Health CareReferral and ConsultationAgedEarly Detection of CancerEmergency Service, HospitalEnglandFemaleHumansMaleMiddle AgedTomography, X-Ray Computedcancer diagnosisemergencygeneral practicelung cancerprimary health carereferral and consultation

Identifiers

PMID41344813
PMCPMC13060713

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.