Evidence map›Paper›PMID 39594779›Full record

ReviewCancers2024

The Use of Blood-Based Biomarkers in the Prediction of Colorectal Neoplasia at the Time of Primary Screening Colonoscopy Among Average-Risk Patients: A Systematic Literature Review.

R Liam Sutherland, Dylan E O'Sullivan, Yibing Ruan, Kristian Chow, Brittany Mah, Dayoung Kim, Robert B Basmadjian, Nauzer Forbes, Winson Y Cheung, Robert J Hilsden and 1 more

Abstract readReview
In one paragraph

Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Long-term survival outcomes in young-onset colorectal cancer: A population-based cohort study.Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland · 2025
    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

11 authors.

R Liam SutherlandDepartment of Community Health Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada.
Dylan E O'SullivanForzani and MacPhail Colorectal Cancer Screening Centre, Alberta Health Services, Calgary, AB T2N 1N4, Canada.
Yibing RuanForzani and MacPhail Colorectal Cancer Screening Centre, Alberta Health Services, Calgary, AB T2N 1N4, Canada.
Kristian ChowForzani and MacPhail Colorectal Cancer Screening Centre, Alberta Health Services, Calgary, AB T2N 1N4, Canada.
Brittany MahForzani and MacPhail Colorectal Cancer Screening Centre, Alberta Health Services, Calgary, AB T2N 1N4, Canada.
Dayoung KimForzani and MacPhail Colorectal Cancer Screening Centre, Alberta Health Services, Calgary, AB T2N 1N4, Canada.
Robert B BasmadjianDepartment of Community Health Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada.ORCID 0000-0002-9535-720X
Nauzer ForbesDepartment of Community Health Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada.
Winson Y CheungDepartment of Community Health Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada.
Robert J HilsdenDepartment of Community Health Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada.
Darren R BrennerDepartment of Community Health Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesRisk prediction models (RPMs) for colorectal cancer (CRC) could facilitate risk-based screening. Models incorporating biomarkers may improve the utility of current RPMs. We performed a systematic review of studies reporting RPMs for CRC that evaluated the impact of blood-based biomarkers on clinical outcome prediction at the time of screening colonoscopy in average-risk populations.

methodsWe conducted a search of MEDLINE, Web of Science, and PubMed databases from inception through April 2024. Studies that developed or validated a model to predict risk of CRC or its precursors were included. Studies were limited to those including patients undergoing average-risk CRC screening.

resultsSixteen studies published between 2015 and 2024 were included. Outcomes included CRC (16 studies) and high-risk adenomas (1 study). Using a complete blood count was the most common biomarker and was able to achieve an AUC of 0.82 and a specificity of 0.88. Other blood-based biomarkers included were various serum proteins/metabolites/enzymes, plasma metabolites, insulin-related factors, and anemia markers. The highest-performing model, with an AUC of 0.99, involved the use of a plasma metabolite panel.

conclusionsThe evidence base of RPMs for CRC screening is expanding and incorporating biomarkers, which remain a prominent aspect of model discovery. Most RPMs included a lack of internal/external validation or discussion as to how the model could be implemented clinically. As biomarkers improve the discriminatory potential of RPMs, more research is needed for the evaluation and implementation of RPMs within existing CRC screening frameworks.

Indexed as

biomarkersbloodcolonoscopycolorectal cancerrisk predictionscreening

Identifiers

PMID39594779
PMCPMC11593258

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.