Evidence map›Paper›PMID 40866911›Full record

ArticleBMC medicine2025

External validation of the COLOFIT colorectal cancer risk prediction model in the Oxford-FIT dataset: the importance of population characteristics and clinically relevant evaluation metrics.

Andres Tamm, Brian Shine, Tim James, Jaimie Withers, Hizni Salih, Theresa Noble, Kinga A Várnai, James E East, Gary Abel, Willie Hamilton and 4 more

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

14 authors.

Andres TammNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK. andres.tamm@phc.ox.ac.uk.
Brian ShineDepartment of Clinical Biochemistry, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Tim JamesDepartment of Clinical Biochemistry, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Jaimie WithersNIHR Oxford Biomedical Research Centre, Oxford, UK.
Hizni SalihNIHR Oxford Biomedical Research Centre, Oxford, UK.
Theresa NobleNIHR Oxford Biomedical Research Centre, Oxford, UK.
Kinga A VárnaiNIHR Oxford Biomedical Research Centre, Oxford, UK.
James E EastNIHR Oxford Biomedical Research Centre, Oxford, UK.
Gary AbelMedical School, University of Exeter, University of Exeter, Exeter, UK.
Willie HamiltonMedical School, University of Exeter, University of Exeter, Exeter, UK.
Colin ReesPopulation Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK.
Eva J A MorrisBig Data Institute, University of Oxford, Oxford, UK.
Jim DaviesBig Data Institute, University of Oxford, Oxford, UK.
Brian D NicholsonNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Funding

Cancer Research UK C23434/A23706Cancer Research UK RCCPDF\100005Engineering and Physical Sciences Research Council EP/S02428X/1National Institute for Health and Care Research NIHR133852
6 · The paper itself

Abstract

backgroundA faecal immunochemical test (FIT) result ≥ 10 µg/g is recommended in the UK to triage patients with symptoms of colorectal cancer (CRC) in primary care for urgent cancer investigation. The COLOFIT model combining FIT results with demographics and blood tests was developed to reduce the proportion of people referred without CRC. This study aims to externally validate the COLOFIT using data from Oxford University Hospitals (OUH).

methodsFITs requested by GPs between January 2017 and February 2024 were extracted from the OUH Clinical Data warehouse. Adults with COLOFIT predictors and 180-day follow-up for CRC were included. External validation of the COLOFIT equation was conducted overall and for six independent time periods. Risk score thresholds where the model captured the same number of cancers as FIT ≥ 10 µg/g were estimated to understand the number of urgent referrals avoided.

resultsA total of 51,477 individuals (659 CRC) were included; 6194 (12%) had FIT ≥ 10 µg/g. FIT positivity and testing volume increased over time, associated with a gradual change from testing lower-risk patients to including those with higher-risk symptoms. COLOFIT was poorly calibrated overall (observed/expected [O/E] ratio 1.52 with calibration slope 1.05), but calibration improved over time (up to O/E ratio 1.09 with calibration slope 1.05). COLOFIT reduced referrals by 8% overall without missing colorectal cancers compared to FIT ≥ 10 µg/g, but this varied from 23% reduction to 2% increase depending on the period evaluated.

conclusionsThe potential benefit of COLOFIT varied depending on FIT testing rates, the proportion of FIT ≥ 10 µg/g, and the symptoms in the tested population. Adopting COLOFIT into current clinical practice demands, therefore, FIT positivity of at least 17% and CRC rates within 1.3-1.6%. Further validation in local and different populations would also be of significant value and help to maximise COLOFIT's ability to improve diagnostic pathways.

Indexed as

Colorectal NeoplasmsEarly Detection of CancerOccult BloodAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedRisk AssessmentUnited KingdomColorectal cancerExternal validationFaecal immunochemical testPrimary careRisk prediction

Identifiers

PMID40866911
PMCPMC12392603

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