Evidence map›Paper›PMID 42536993›Full record

ArticleJCO clinical cancer informatics

Consensus-Based Minimum Requirements for the Adoption of a Computational Pathology Algorithm for Tumor Budding in Colorectal Cancer: An Early Health Technology Assessment.

Julie E M Swillens, Iris D Nagtegaal, Alessandro Lugli, Jeroen A W M Van der Laak, Marcia Tummers

Abstract read
In one paragraph

Article in JCO clinical cancer informatics. 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

5 authors.

Julie E M SwillensRadboud University Medical Center, IQ Health Science Department, Nijmegen, the Netherlands.ORCID 0000-0001-9337-1318
Iris D NagtegaalDepartment of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands.ORCID 0000-0003-0887-4127
Alessandro LugliInstitute of Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.
Jeroen A W M Van der LaakDepartment of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands.ORCID 0000-0001-7982-0754
Marcia TummersRadboud University Medical Center, IQ Health Science Department, Nijmegen, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTumor budding (TB) is an independent prognostic biomarker for colorectal cancer (CRC), yet its clinical adoption is limited by labor-intensive and subjective visual scoring. Computational pathology (CPath) algorithms using deep learning offer potential to improve efficiency and reproducibility. Using an international Delphi study, we established consensus requirements to guide validation and clinical adoption of CPath algorithms, aiming to enhance diagnostic accuracy and patient care.

methodsA two-round international Delphi process was conducted, involving international experts, to reach consensus on predefined statements. In round 1, baseline characteristics were collected and participants were asked to rank statements representing the minimal requirements for the implementation of a CPath algorithm for TB assessment. After completion of this round, participants received a personalized feedback report summarizing interim results for items that lacked consensus. In round 2, participants re-evaluated their initial responses to statements without consensus, in the light of anonymized group feedback provided in their personalized report.

resultsFifty-nine pathologists participated in round 1, with a 90% response rate in round 2. Consensus was reached for 21 of 29 (72%) minimal requirements. All reached consensus by agreement. Eight statements (28%) remained without consensus after round 2.

conclusionAgreement was reached on the technical, organizational, ethical, and legal aspects, although some requirements were not agreed upon. This highlights the importance of evaluations that take specific contexts into account, as well as the need for continuous stakeholder engagement throughout the development and implementation phases.

Indexed as

AlgorithmsColorectal NeoplasmsTechnology Assessment, BiomedicalBiomarkers, TumorConsensusDelphi TechniqueHumansPrognosisReproducibility of ResultsBiomarkers, Tumor

Identifiers

PMID42536993
PMCPMC13456570

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.