ArticleThe journal of pathology. Clinical research2026
Development of a decision tree diagram for classifying study designs in tumour pathology research: a multidisciplinary approach.
Article in The journal of pathology. Clinical research, 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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26 authors.
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Abstract
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.
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