The Current State of Clinical Diagnostic Algorithms for Mucosal Oral Lesions: A Scoping Review

This is the authors' abstract. We don't add key points for this paper.

BACKGROUND: Diagnosing oral lesions remains challenging for many dentists. Despite the availability of diagnostic algorithms, there is a dearth of comprehensive evidence synthesis and a discussion on their clinical and pedagogical applicability. METHODS: A scoping review was conducted to identify: (1) algorithms or flow diagrams that help clinicians to diagnose oral lesions in a clinical setting without additional software; (2) publications in English; (3) all age groups; (4) algorithms for oral lesions of soft tissue only. We excluded those that are: (1) black-box; (2) required additional tests; (3) older versions; (4) for non-mucosal lesions, and (5) intended for self-screening. A keyword and MeSH term search was performed across three peer-reviewed publication databases and gray literature. RESULTS: Seventeen algorithms from 15 peer-reviewed manuscripts and 1 online course were identified. Most studies did not mention how the algorithms were developed, and none had been validated in a clinical setting. The algorithms often focused on one or two types of lesions and were incomplete in differential diagnoses. CONCLUSION: Few clinical diagnostic algorithms for oral lesions are available in the literature. Notably, there are no validated and comprehensive clinical diagnostic algorithms for oral mucosal lesions.