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Development of a decision tree diagram for classifying study designs in tumour pathology research: a multidisciplinary approach

Lookup NU author(s): Dr Fiona CampbellORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2025 The Author(s). The Journal of Pathology: Clinical Research published by The Pathological Society of Great Britain and Ireland and John Wiley & Sons Ltd.The World Health Organization (WHO) Classification of Tumours: A Living Evidence Gap Map by Tumour Type (WCT EVI MAP) project aims to develop Evidence Gap Maps of the available evidence, primarily to inform the WHO Classification of Tumours. The project, covering all tumour types, faces the challenge of reviewing a huge number of studies by reviewers from multiple backgrounds. The aim was to develop a decision tree (DT) diagram for classifying study designs reporting on tumour pathology studies, in order to support the decision-making process when assigning evidence levels across various disciplines. A modified consensus process, incorporating stakeholder workshops, was conducted in three phases: (1) development of the initial DT diagram draft (literature review and expert evaluation); (2) iterative reviews with project partners; and (3) testing the advanced DT diagram version with several sets of references to refine critical points. A total of 368 records were used for training throughout the entire process. Consensus was achieved when classifications could categorise studies consistently without causing discordance in new example sets. A DT diagram and its Glossary of Operational Definitions with 27 decision nodes and 26 categories were developed. The DT diagram is organised into six sections: WCT EVI MAP selection criteria, evidence synthesis, basic research related studies, descriptive studies, observational and experimental studies, and diagnostic test studies. The DT diagram is a valuable tool for the project's needs, successfully integrating diverse disciplinary perspectives for classifying evidence in tumour pathology research according to study design. It lays the foundation for future advancements in evidence mapping and classification within tumour pathology and related disciplines.


Publication metadata

Author(s): Craciun OM, Garcia-Ovejero E, Campbell F, Montes-Mota M, Holdenrieder S, Trulson I, Worf K, Gabriel S, Kowalewska M, Michalek I, Maslova K, Taraszkiewicz L, del Aguila J, Colling R, Tan PH, Goldman-Levy G, Giesen C, Cierco Jimenez R, Lokuhetty D, Cree IA, Indave I, Perez Gomez B, Chechlinska M, Pollan Santamaria M, Plans-Beriso E, Nasir NDM, Gilch M, Wong CJW, Ong M, Didkowska J, Chow ZL, Shi R

Publication type: Article

Publication status: Published

Journal: Journal of Pathology: Clinical Research

Year: 2026

Volume: 12

Issue: 1

Print publication date: 01/01/2026

Online publication date: 29/11/2025

Acceptance date: 14/10/2025

Date deposited: 15/12/2025

ISSN (electronic): 2056-4538

Publisher: John Wiley and Sons Inc

URL: https://doi.org/10.1002/2056-4538.70056

DOI: 10.1002/2056-4538.70056

Data Access Statement: Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

PubMed id: 41317315


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Funding

Funder referenceFunder name
European Union
HORIZON-HLTH-2021-CARE-05 grant number 101057127

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