Prevalence of Oral Leukoplakia in 9954 Central Indian Patients: a Prospective, Cross-sectional Study

Introduction India is one of the leading producers and consumer of tobacco. Additionally, India has one of the highest global prevalence of oral leukoplakia (OL). However, large epidemiological studies from Madhya Pradesh (Central India), the state with maximum consumers of tobacco products in India, are lacking. Objective Thus, we assessed the prevalence of OL among individuals residing in Central India and evaluated its association with age, gender, and history of adverse habits. Methods This was a prospective, cross-sectional study involving 9954 patients visiting the out-patient Department of Oral Medicine and Radiology over a period of 15 months (January 2019 to March 2020). The clinical diagnosis of OL was arrived by exclusion of all the lesions mimicking OL. Univariate and multivariate analyses were performed to assess the association between OL and age, sex, and history of adverse habits. Results The prevalence of OL was 5.6% (557/9954). It was predominant in males (male-to-female ratio=3.9:1) and increased with advancing age. The odds of developing OL was higher among patients aged ≥50 years (OR=1.08; 95%CI: 1.07–1.08, p-value<0.0001), those with history of smoking tobacco (OR=1.32; 95%CI: 1.05–1.68, p-value=0.02), consuming smokeless tobacco (OR=318.60; 95%CI: 101.68–998.30, p-value<0.0001), and alcohol (OR=1.15; 95%CI: 9.0–1.49, p-value=0.269). Females had lower odds of developing OL (OR=0.77; 95%CI: 0.60–0.99, p-value=0.042). Conclusion We observed high prevalence of OL (5.6%). OL was significantly associated with older age, male sex, and tobacco-related adverse habits. While, alcohol consumption may possibly be a risk factor, no statistically significant relation was observed.

Deep Learning Predicts the Malignant-Transformation-Free Survival of Oral Potentially Malignant Disorders

Machine-intelligence platforms for the prediction of the probability of malignant transformation of oral potentially malignant disorders are required as adjunctive decision-making platforms in contemporary clinical practice. This study utilized time-to-event learning models to predict malignant transformation in oral leukoplakia and oral lichenoid lesions. A total of 1098 patients with oral white lesions from two institutions were included in this study. In all, 26 features available from electronic health records were used to train four learning algorithms—Cox-Time, DeepHit, DeepSurv, random survival forest (RSF)—and one standard statistical method—Cox proportional hazards model. Discriminatory performance, calibration of survival estimates, and model stability were assessed using a concordance index (c-index), integrated Brier score (IBS), and standard deviation of the averaged c-index and IBS following training cross-validation. This study found that DeepSurv (c-index: 0.95, IBS: 0.04) and RSF (c-index: 0.91, IBS: 0.03) were the two outperforming models based on discrimination and calibration following internal validation. However, DeepSurv was more stable than RSF upon cross-validation. External validation confirmed the utility of DeepSurv for discrimination (c-index—0.82 vs. 0.73) and RSF for individual survival estimates (0.18 vs. 0.03). We deployed the DeepSurv model to encourage incipient application in clinical practice. Overall, time-to-event models are successful in predicting the malignant transformation of oral leukoplakia and oral lichenoid lesions.

The role of family history of Cancer in Oral Cavity Cancer

Objectives Oral and oropharyngeal squamous cell carcinoma (SCC) is the 10th most common cancer in the United States (8th in males, 13th in females), with an estimated 54,010 new cases expected in 2021, and is primarily associated with smoked tobacco, heavy alcohol consumption, areca nut use and persistent high-risk human papillomavirus (HPV). Family history of cancer (FHC) and family history of head and neck cancer (FHHNC) have been reported to play an important role in the development of OSCC. We aimed to investigate the role of FHC, FHHNC and personal history of cancer in first/second degree-relatives as co-risk factors for oral cancer. Methods This was a retrospective study of patients diagnosed with OSCC at the Division of Oral Medicine and Dentistry at Brigham and Women’s Hospital and at the Division of Head and Neck Oncology at Dana Farber Cancer Institute. Conditional logistic regressions were performed to examine whether OSCC was associated with FHC and FHHNC of FDRs and SDRs, personal history of cancer and secondary risk factors. Results Overall, we did not find an association between FHC, FHHNC and OSCC risk, whereas patients with a cancer history in one of their siblings were 1.6-times more likely to present with an OSCC. When secondary risk factors were considered, patients with a history of oral leukoplakia and dysplasia had a 16-times higher risk of having an OSCC. Conclusions Our study confirmed that a previous history of oral leukoplakia or dysplasia was an independent risk factor for OSCC. A positive family history of cancer in one or more siblings may be an additional risk factor for OSCC.

Correlation of Soluble CD44 Expression in Saliva and CD44 Protein in Oral Leukoplakia Tissues

The aim of this study was to determine whether and how pan-CD44 protein expression in leukoplakia tissues correlates with positive SolCD44 test presence and their role in oral leukoplakia. SolCD44 and total protein expression in saliva were determined using an OncAlert® Oral Cancer Rapid test. Comparison of paired associations of total protein, SolCD44, mean number of CD44 expressed epithelial layers in leukoplakia tissue, and macrophages below the basement membrane between control group and patients with leukoplakia showed statistically significant results (p < 0.0001). It is shown that the total protein indicates low or elevated risk of possible malignant transformation processes in leukoplakia. Statistically significant differences between higher total protein level and clinical forms of oral leukoplakia (p < 0.0001), as well as CD44-labeled epithelial cell layer decrease (p < 0.0001), were found. This possibly points to the onset of the stemness loss in leukoplakia tissue. CD9 antigen expression in the exosomes of the oral epithelium explained the intercellular flow of SolCD44 and other fluids in the leukoplakia area. We conclude that the OncAlert® Oral Cancer Rapid test is a valuable screening method in daily clinical practice, in terms of complementing clinical diagnostics methods and to assess the potential for early malignancy.