Evidence map›Paper›PMID 38262635›Full record

ArticleBMJ open2024

Determining the feasibility of calculating pancreatic cancer risk scores for people with new-onset diabetes in primary care (DEFEND PRIME): study protocol.

Hugh Claridge, Claire A Price, Rofique Ali, Elizabeth A Cooke, Simon de Lusignan, Adam Harvey-Sullivan, Catherine Hodges, Natalia Khalaf, Dean O'Callaghan, Ali Stunt and 3 more

Abstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
  2. Review
  3. Prediagnostic prescription patterns in pancreatic cancer: a retrospective primary care cohort study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
    Article
  4. Decision support tools for pancreatic cancer detection: external validation in Australian primary care - a retrospective cohort study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
    Article
  5. Review
  6. Review
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

13 authors.

Hugh ClaridgeSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK h.claridge@surrey.ac.uk.ORCID 0000-0001-5998-2860
Claire A PriceSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
Rofique AliTower Hamlets Network 1 Primary Care Network, London, UK.
Elizabeth A CookeNational Physical Laboratory, Teddington, UK.
Simon de LusignanNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID 0000-0001-5613-6810
Adam Harvey-SullivanTower Hamlets Network 1 Primary Care Network, London, UK.
Catherine HodgesSurrey and Sussex Cancer Alliance, Guildford, UK.
Natalia KhalafSection of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, Center for Innovations in Quality, Effectiveness, and Safety (IQuESt), Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA.
Dean O'CallaghanTower Hamlets Network 1 Primary Care Network, London, UK.
Ali StuntPancreatic Cancer Action, Oakhanger, Hampshire, UK.
Spencer A ThomasNational Physical Laboratory, Teddington, UK.
Joanna ThomsonSurrey and Sussex Cancer Alliance, Guildford, UK.
Agnieszka LemanskaSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.ORCID 0000-0003-4849-2430

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionWorldwide, pancreatic cancer has a poor prognosis. Early diagnosis may improve survival by enabling curative treatment. Statistical and machine learning diagnostic prediction models using risk factors such as patient demographics and blood tests are being developed for clinical use to improve early diagnosis. One example is the Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) model, which employs patients' age, blood glucose and weight changes to provide pancreatic cancer risk scores. These values are routinely collected in primary care in the UK. Primary care's central role in cancer diagnosis makes it an ideal setting to implement ENDPAC but it has yet to be used in clinical settings. This study aims to determine the feasibility of applying ENDPAC to data held by UK primary care practices. METHODS AND ANALYSIS: This will be a multicentre observational study with a cohort design, determining the feasibility of applying ENDPAC in UK primary care. We will develop software to search, extract and process anonymised data from 20 primary care providers' electronic patient record management systems on participants aged 50+ years, with a glycated haemoglobin (HbA1c) test result of ≥48 mmol/mol (6.5%) and no previous abnormal HbA1c results. Software to calculate ENDPAC scores will be developed, and descriptive statistics used to summarise the cohort's demographics and assess data quality. Findings will inform the development of a future UK clinical trial to test ENDPAC's effectiveness for the early detection of pancreatic cancer. ETHICS AND DISSEMINATION: This project has been reviewed by the University of Surrey University Ethics Committee and received a favourable ethical opinion (FHMS 22-23151 EGA). Study findings will be presented at scientific meetings and published in international peer-reviewed journals. Participating primary care practices, clinical leads and policy makers will be provided with summaries of the findings.

Indexed as

Diabetes MellitusPancreatic NeoplasmsAgedFeasibility StudiesGlycated HemoglobinHumansMiddle AgedMulticenter Studies as TopicObservational Studies as TopicPrimary Health CareRisk FactorsGlycated HemoglobinElectronic Health RecordsFeasibility StudiesPancreatic diseasePrimary CareProtocols & guidelines

Identifiers

PMID38262635
PMCPMC10806670

What OpenQuestion holds

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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.