Evidence map›Paper›PMID 42152068›Full record

ArticleJournal of translational medicine2026

Validation of the biomarker toolkit using diagnostic colorectal cancer biomarkers - an evidence-based tool to support clinical adoption of biomarkers.

Alice E Baggaley, Yue Wu, Katerina-Vanessa Savva, Komal Khan, Prerana Gogoi, Hateem Rafeeque, Maxime Giot, Marina Siakalli, Constantinos Panayiotou, Melody Zhifang Ni and 1 more

Abstract readValidation Study
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Article in Journal of translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Alice E Baggaley *Department of Surgery and Cancer, Imperial College London, London, UK. a.baggaley@imperial.ac.uk.ORCID 0000-0002-8371-0010
Yue Wu *Department of Surgery and Cancer, Imperial College London, London, UK.
Katerina-Vanessa SavvaDepartment of Surgery and Cancer, Imperial College London, London, UK.
Komal KhanDepartment of Surgery and Cancer, Imperial College London, London, UK.
Prerana GogoiDepartment of Surgery and Cancer, Imperial College London, London, UK.
Hateem RafeequeDepartment of Surgery and Cancer, Imperial College London, London, UK.
Maxime GiotDepartment of Surgery and Cancer, Imperial College London, London, UK.
Marina SiakalliDepartment of Surgery and Cancer, Imperial College London, London, UK.
Constantinos PanayiotouDepartment of Surgery and Cancer, Imperial College London, London, UK.
Melody Zhifang NiDepartment of Surgery and Cancer, Imperial College London, London, UK.
Christopher J PetersDepartment of Surgery and Cancer, Imperial College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBiomarkers offer valuable insights into diseases and bodily functions, yet many fail to achieve clinical implementation. Our recent research revealed a substantial translational gap, with only 0.94% of prognostic breast cancer biomarkers and 0.14% of diagnostic colorectal cancer biomarkers reaching clinical practice. To address this challenge, we developed the Biomarker Toolkit, designed to enhance translational outcomes by identifying cancer biomarkers most likely to succeed and highlighting areas requiring further research. This study aims to validate the Toolkit using a new dataset of diagnostic colorectal cancer biomarkers.

methodsSystematic literature searches were conducted to identify clinical studies for successful and stalled diagnostic colorectal cancer biomarker groups. 'Successful' biomarkers were defined as those approved for diagnostic use in colorectal cancer by regulatory bodies. For the stalled cohort, a random selection of biomarkers associated with > 5 publications was drawn from a previous review, until the number of clinical studies in each cohort was equal. Each clinical study was examined for the presence or absence of 125 attributes present in the Toolkit, with a binary score (1 or 0) assigned accordingly. Total and category scores were calculated and compared between the successful and stalled biomarker groups, using Mann Whitney U Test, binary logistic and Cox regression analyses.

resultsUsing the Toolkit, successful diagnostic colorectal cancer biomarkers demonstrated significantly higher total scores compared to the stalled group (44.7% versus 25.1%, p < 0.001). Successful biomarkers exhibited higher clinical utility scores even before receiving regulatory approval (42.1% versus 20.2%, p < 0.001). Additionally, the frequency and diversity of clinical utility publications for successful biomarkers continued to rise beyond the initial five-year period following the first biomarker publication.

conclusionsThis study provides independent validation of the Biomarker Toolkit, having been initially validated using prognostic breast cancer biomarkers. The significantly higher Toolkit scores observed in successful diagnostic colorectal cancer biomarkers, particularly in clinical utility, even before regulatory approval, underscore the Toolkit's strong potential for predicting translational success.

Indexed as

Biomarkers, TumorColorectal NeoplasmsEvidence-Based MedicineHumansReproducibility of ResultsTranslational Research, BiomedicalBiomarkers, TumorBiomarkersClinical utilityColorectal cancerTranslational research

Identifiers

PMID42152068
PMCPMC13366890

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