ArticleOral diseases2026
Independent Multicentre Validation of the 'Six-Point' Model for Malignant Transformation Risk in Oral Epithelial Dysplasia.
Article in Oral diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predicting Malignant Transformation in Oral Epithelial Dysplasia: A Systematic Comparison of Artificial Intelligence-Based Risk Models and Pathologist-Based Microscopy.Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology · 2026Pooled it
- Pattern-Anchored Diagnosis of Oral Epithelial Dysplasia: A Position Paper From COST Action INTERCEPTOR Working Group 2.Head and neck pathology · 2026Review
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11 authors.
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Abstract
backgroundHistological grading of oral epithelial dysplasia (OED) is used for predicting malignant transformation risk. However, grading is associated with significant subjectivity and observer variability leading to inconsistency in prognosis prediction. Alternate histological feature-specific models ('six-point' and 'two-point') have been shown to have potentially better prognostic reliability than conventional grading. This study conducts a multicentre validation of these models.
methods102 OED cases (dating 2012-2017) were acquired from 4 independent centres (13 (13%) Sheffield; 40 (39%) Belfast; 30 (29%) Birmingham; 19 (19%) Piracicaba, Brazil) were independently scored using the 'six-point' and 'two-point' models. Feature prevalence, observer agreement and malignant transformation risk were evaluated and compared to conventional grading systems.
resultsThe 'six-point' system demonstrated superior predictive value (AUROC of 0.81) compared to the 'two-point' system (AUROC = 0.73, p = 0.004), WHO grading (AUROC = 0.71, p = 0.03) and binary grading (AUROC = 0.68, p = 0.009). Transformation rate for the 'six-point' model was 50% (95% CI 27%-78%) when all 6 features were present compared to 14% (95% CI 5%-32%) when 2-3 features were present.
conclusionsThis study supports the superior performance of the 'six-point' system for transformation prediction on a multicentric sample. Findings indicate that feature-specific models may be more reliable than existing histological grading systems for prognosis prediction.
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