Objectives: The aim of study was to compare salivary and serum concentrations of interleukin 1 beta (IL-1β), interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-α) in patients with oral leukoplakia, oral cancer and healthy controls. Study design: Eighty eight patients (28 with oral cancer, 29 leukoplakia, and 31 healthy controls) were included in this study. Cytokine concentrations were measured by commercial enzyme linked immunoassay. Results: Salivary IL-1β and IL-6 were significantly higher in oral cancer patients than in patients with leukoplakia and control group (p<0.05). No differences in concentrations of salivary TNF-α between either of the groups were observed. Serum concentrations of IL-1β were below level of detection in all but two participants. No significant differences between the groups were observed in serum concentrations of IL-6. Serum TNF-α was significantly higher in control subjects than in oral cancer patients. Conclusions: Patients with oral cancer have elevated levels of inflammatory cytokines in their saliva. Whether this elevation can be used for monitoring the malignant transformation of oral leukoplakia remains to be answered by further follow up studies.

Oral submucous fibrosis (OSF) is a chronic progressive condition affecting the oral cavity, oropharynx and upper third of the oesophagus. It is a potentially malignant disorder. The authors collated and analysed the existing literature to establish the overall malignant transformation rate (MTR). A retrospective analysis of medical and dental scientific literature using online indexed databases was conducted for the period 1956 to 2021. The quality of the enrolled studies was assessed by the Newcastle-Ottawa Scale (NOS). A meta-analysis using a random effects model of a single proportion was performed along with statistical tests for heterogeneity. The overall proportion of malignancy across all studies was 0.06 (95% CI, 0.02–0.10), indicating an overall 6% risk of malignant transformation across all studies and cohorts. Sub-group analyses revealed strong differences in proportion of malignancy according to ethnicity/cohort; Chinese = 0.02 (95% CI 0.01–0.02), Taiwanese = 0.06 (95% CI, 0.03–0.10), Indian = 0.08 (95% CI, 0.03–0.14) and Pakistani = 0.27 (95% CI 0.25–0.29). Overall, the MTR was 6%; however, wide heterogeneity of the included studies was noted. Geographic variations in MTR were noted but were not statistically significant. Further studies are required to analyse the difference between cohort groups.

Objectives: To investigate the epidemiological and clinical characteristics of oral lichen planus (OLP) in a group of Croatian patients seen between 2006 and 2012. Study Design: A group of 563 patients with a diagnosis of OLP was retrospectively reviewed in our clinic. Data regarding age, gender, medical history, drugs, smoking, alcohol, chief complaint, clinical type, localization, histology, treatment and malignant transformation were registered. Results: Of the 563 patients, 414 were females and 149 were males. The average age at the diagnosis was 58 (range 11-94). The most common site was buccal mucosa (82.4%). Most of our patients did not smoke (72.5%) or consume alcohol (69.6%). Patients reported oral soreness (43.3%), mucosal roughness (7%), xerostomia (3%), gingival bleeding (2%) and altered taste (0.5%) as the chief complaint, while almost half of them were asymptomatic (44.2%). The most common types of OLP were reticular (64.8%) and erosive (22.9%). Plaque-like (5.7%) atrophic/erythemtous (4.3%) and bullous (2.3%) type were also observed. Malignant transformation rate of 0.7% was recorded. Conclusions: OLP mostly affects non-smoking middle-aged women. Buccal mucosa is the most commonly affected site. In almost half of the cases patients are asymptomatic. In spite of the small risk for malignant transformation all patients should be regularly monitored.

As a relatively new tool, the use of artificial intelligence (AI) in medicine and dentistry has the potential to significantly transform the healthcare sector. AI has already demonstrated efficacy in medical diagnosis across several specialties, used successfully to detect breast, lung and skin cancer. In Oral Medicine, AI may be applied in a similar fashion, used in the detection and diagnosis of oral cancers and oral potentially malignant diseases. Despite its promise as a transformative diagnostic aid, the use of AI in healthcare presents significant safety, reliability and ethical concerns. There is no formal consensus on the safe and ethical implementation of AI systems in healthcare settings, but the literature converges on several key principles of ethical AI use including transparency, justice and fairness, non‐maleficence, responsibility and privacy. This article provides a narrative review of the key ethical issues surrounding AI use in medicine, and reflects on these, providing view‐points of a bioethicist and Oral Medicine clinicians from several units.