Faculty Bibliography

BACKGROUND:Oral cavity cancer represents a public health challenge in Latin America and the Caribbean (LAC), where exposure to modifiable risk factors such as tobacco and alcohol remains high and inequalities in access to health services contribute to delayed diagnosis and poor outcomes. This study aimed to develop consensus-based recommendations to strengthen the prevention and early detection of oral cavity cancer and oral potentially malignant disorders in LAC. METHODS:A multi-phase study using a Delphi approach was conducted. An initial qualitative survey with regional experts identified barriers, facilitators, and priority actions for oral cavity cancer prevention and early detection. Preliminary recommendations were refined through feasibility assessment by international advisors and subsequently evaluated in a quantitative Delphi round using a Likert scale. RESULTS:Twenty-four experts from 12 LAC countries participated in the Delphi process, including research investigators, clinicians, and health service managers. The panel had a mean age of 49.4 (SD 10.3) years and included 41.7 % women. Seven recommendations achieved consensus, addressing key domains of oral cavity cancer control including primary prevention interventions, screening of high-risk individuals, establishment of structured referral pathways, improved surveillance systems, and expansion of access to diagnostic services in underserved populations. High levels of agreement were observed across all recommendations. CONCLUSIONS:These consensus-based recommendations provide a regionally informed framework to guide oral cavity cancer prevention and early detection strategies in LAC. Strengthening coordinated actions across the continuum of care, including primary prevention, screening, referral, and diagnostic capacity, may contribute to reducing diagnostic delays and improving outcomes in the region.

Oral potentially malignant disorders (OPMDs) such as leukoplakia and erythroplakia may harbor dysplasia or progress to oral squamous cell carcinoma (OSCC), yet visual inspection alone is unreliable for risk assessment. Cytology offers a minimally invasive adjunct, but conventional approaches depend on manual feature extraction and subjective review. Herein we report a deep learning (DL) object detection model that directly classifies four cell phenotypes: differentiated squamous epithelial (DSE) cells, small round (SR) cells, leukocytes, and lone nuclei. The DL model produced cytology-derived parameters that correlated strongly with histopathologic diagnoses across 692 subjects with OPMDs, OSCC, and healthy controls, including declining DSE cell proportion and increasing SR cells and leukocytes with disease severity (p < 0.0001). The oral cancer numerical index (OCNI) achieved AUROC values up to 0.99 for malignant versus healthy lesions, with excellent reliability (intra-class correlation coefficient ≥ 0.96). This reproducible, minimally invasive test provides a robust platform for early detection and surveillance of OPMDs.

BACKGROUND:Identifying oral potentially malignant disorders and oral cavity cancer early can lead to better patient outcomes. The guideline panel evaluated the usefulness of light-based adjuncts for screening adults without mucosal abnormalities and for determining the need for biopsy among adults with mucosal abnormalities in the oral cavity or on the lip. TYPES OF STUDIES REVIEWED/METHODS:The authors conducted a living systematic review to evaluate evidence on the benefits and harms of light-based adjuncts and a scoping review to assess people and clinician values and preferences regarding the use of light-based adjuncts and biopsy of mucosal abnormalities. The guideline panel used this evidence to formulate recommendations according to the Grading of Recommendations Assessment, Development and Evaluation Evidence to Decision framework. The framework also guided the panel's consideration of required resources, equity, acceptability, and feasibility in shaping the final recommendations. RESULTS:The guideline panel formulated 2 recommendations and 2 good practice statements. For adults with and without mucosal abnormalities, they formulated conditional recommendations against the use of light-based adjuncts on the basis of very low certainty evidence. The good practice statements urge clinicians to perform a clinical oral examination in all adult patients. CONCLUSIONS AND PRACTICAL IMPLICATIONS/CONCLUSIONS:Biopsy remains the reference standard for establishing a definitive diagnosis of an oral potentially malignant disorder and oral squamous cell carcinoma. All adults should undergo a clinical oral examination in primary care settings. When implementing or adapting these recommendations, local contexts should be considered to promote equitable access to early detection.

BACKGROUND:Early detection of oral potentially malignant disorders (OPMDs) and oral cavity cancer can improve patient prognosis. In this guideline, the authors address the use of vital staining, specifically toluidine blue, as an adjunct to screen adults without mucosal abnormalities and to determine the need for biopsy among adults with mucosal abnormalities in the oral cavity. TYPES OF STUDIES REVIEWED/METHODS:The authors conducted systematic searches to identify evidence on the benefits and harms of using vital staining as an adjunct as well as patient and clinician values and preferences regarding the use of this adjunct. The guideline panel used the Grading of Recommendations Assessment, Development and Evaluation Evidence to Decision framework to formulate recommendations. As part of the framework, the panel also considered the resources required, equity, acceptability, and feasibility when formulating recommendations. RESULTS:The panel formulated 2 recommendations and 2 good practice statements. For adults with and without mucosal abnormalities, the panel recommend against the use of vital staining as an adjunct (conditional recommendation, very low certainty). The good practice statements encourage clinicians to perform a clinical oral examination in all adult patients. CONCLUSIONS AND PRACTICAL IMPLICATIONS/CONCLUSIONS:Biopsy remains the first choice for obtaining a definitive diagnosis of an OPMD and oral squamous cell carcinoma. Clinical oral examination should be performed in all asymptomatic adults with no clinically evident mucosal abnormality. When implementing or adapting these recommendations, local contexts should be taken into account to ensure equitable access to early detection.

BACKGROUND:Early detection of oral potentially malignant disorders and oral cavity cancer can improve patient prognosis. The guideline panel addressed the use of cytology adjuncts to screen adults without mucosal abnormalities and determine the need for biopsy among adults with mucosal abnormalities. TYPES OF STUDIES REVIEWED/METHODS:The guideline panel used the Grading of Recommendations Assessment, Development and Evaluation Evidence to Decision framework to formulate recommendations. The authors conducted reviews to assess the benefits and harms of cytology adjuncts and people and clinician values and preferences as they relate to adjunct tests and biopsy of mucosal abnormalities. As part of the framework, the panel also considered resources required, equity, acceptability, and feasibility when formulating recommendations. RESULTS:The panel formulated 3 recommendations and 3 good practice statements. For adults with and without mucosal abnormalities, they formulated conditional recommendations against cytology adjuncts. Their use should be reserved for specific circumstances among adults with mucosal abnormalities when a biopsy is not possible or indicated. In the good practice statements, clinicians are urged to perform a clinical oral examination in all adult patients. CONCLUSIONS AND PRACTICAL IMPLICATIONS/CONCLUSIONS:Biopsy remains the first choice for reaching a definitive diagnosis of an oral potentially malignant disorder and oral squamous cell carcinoma, and cytology adjuncts should be reserved for specific situations when the clinician and patient agree it is the best course of action. When implementing or adapting these recommendations, local contexts should be considered to ensure equitable access to early detection.

The rising incidence of oral cancer and associated poor prognosis, primarily due to delayed diagnosis, highlight the urgent need for artificial intelligence tools in clinical detection. However, efforts in this regard are hampered by the lack of large and ethnically heterogenous image datasets of oral lesions with clinically validated diagnoses. To address this gap, oral mucosa images captured with mobile device cameras were collected from cohorts spanning five countries. The images were systematically annotated with lesion type classifications as well as specific clinical diagnoses, then assessed for quality. The diagnoses were verified retrospectively by biopsy, where applicable, or by consensus verification by dental experts. The final dataset consists of 30,039 oral mucosa images supplemented by clinical metadata, made available on the MeMoSA Workbench platform. We believe that the MeMoSA dataset will serve as a significant resource to drive the training, evaluation, and refinement of AI-driven diagnostic algorithms, potentially improving diagnostic accuracy and enabling rigorous benchmarking against clinical expert assessments, for the early detection of oral cancer.

Oral medicine is the dental specialty dedicated to the oral health of medically complex patients and the diagnosis and management of medically-related diseases, disorders, and conditions affecting the oral and maxillofacial region. In addition to direct patient care, Oral Medicine specialists often engage in indirect patient care activities such as patient education and practice administration and/or academic activities such as student education and research. Artificial intelligence (AI) tools have been increasingly studied to facilitate these domains and contribute to more positive outcomes for practitioners, patients, and students alike. A review of the literature on these AI applications in Oral Medicine and related medical and dental fields provides an understanding of their current advantages and limitations.

Oral medicine is the dental specialty dedicated to the oral health care of medically complex patients and the diagnosis and management of medically related diseases, disorders, and conditions affecting the oral and maxillofacial region. Like other dental and medical specialties, oral medicine patient care is often impacted by challenges such as limited manpower, time, or resources. Artificial intelligence (AI) tools seek to supersede these challenges by automating human tasks and ushering greater efficiency and productivity. For direct patient care in oral medicine, AI has applications in risk prediction modeling, diagnosis establishment, treatment decision-making, and prognosis and outcomes prediction modeling.

BACKGROUND:Inferring risk for malignant transformation (MT) in patients with lesions diagnosed as mild or moderate oral epithelial dysplasia (low-grade OED) remains challenging. We developed two models assessing the risk of progression to high-grade OED (severe dysplasia or carcinoma in situ) or OSCC in patients with low-grade OED lesions. METHODS:We included demographic, risk habit and clinical data from participants with low-grade OED lesions enrolled in the BC Oral Cancer Prevention Program's Oral Cancer Prediction Longitudinal study. Cox proportional hazard models were fit to estimate the effects of anatomic site and toluidine blue findings and adjusted for confounders, as both are associated with MT in the literature but without a North American-specific cohort analysis. Our primary model included both variables of interest. A secondary model included only anatomic site since toluidine blue is not in widespread use. RESULTS:Five hundred and thirty-four participants with 605 lesions met final inclusion criteria, with 339 mild and 266 moderate OED at baseline. In the primary model, lesions at a high-risk anatomic site or with positive toluidine blue staining were associated with a 2.6 and 2.4-fold increased risk of progression, respectively. In the second model that did not incorporate toluidine blue, high-risk anatomic site remained a highly associated risk factor (2.7-fold increased risk of progression). CONCLUSION/CONCLUSIONS:Lesion anatomic site is associated with higher risk of MT for the general practitioner, while a specialist with access to toluidine blue results can assume additional risk associated with positive staining. These models may inform decisions for surveillance and intervention for OED.