METHODS: Two villages were selected as the sampling frame based on prevalence of tobacco and betel quid chewing habit. Respondents were asked to check their mouth for presence of lesion or abnormalities. Education on oral cancer, including MSE, was provided. Subsequently, respondents were asked to perform MSE. Finally, a clinical oral examination (COE) was done by a specialist and the presence of oral mucosal lesions was recorded.
RESULTS: Almost 64.5 percent of respondents exhibited high levels of difficulty and low mucosal visualization and retracting ability, whereas 3.0 percent demonstrated high attention level when performing MSE. Prevalence of oral mucosal lesions was 59.0 percent, whereas the prevalence of oral potentially malignant disorders (OPMDs) was 9.0 percent. Detection of oral lesions by respondents using MSE was lower than detection by the gold standard. Sensitivity and specificity of MSE for detection of all types of lesions were 8.6 and 95.0 percent respectively. When analyzing each lesion type separately, MSE was found to be most sensitive in detection of swellings (10.0 percent), and most specific in identifying white lesions (97.8 percent). For detection of OPMDs, although specificity was high (98.9 percent), sensitivity (0 percent), and +LR (0) was poor.
CONCLUSION: MSE is not an effective self-screening tool for early detection of potentially malignant lesions for this population.
METHODS: This retrospective case-control study involves 790 cases of cancers of the oral cavity and 450 controls presenting with non-malignant oral diseases, recruited from seven hospital-based centres nationwide. Data on risk habits (smoking, drinking, chewing) were obtained using a structured questionnaire via face-to-face interviews. Multiple logistic regression was used to determine association between risk habits and oral cancer risk; chi-square test was used to assess association between risk habits and ethnicity. Population attributable risks were calculated for all habits.
RESULTS: Except for alcohol consumption, increased risk was observed for all habits; the highest risk was for smoking + chewing + drinking (aOR 22.37 95% CI 5.06, 98.95). Significant ethnic differences were observed in the practice of habits. The most common habit among Malays was smoking (24.2%); smoking + drinking were most common among Chinese (16.8%), whereas chewing was the most prevalent among Indians (45.2%) and Indigenous people (24.8%). Cessation of chewing, smoking and drinking is estimated to reduce cancer incidence by 22.6%, 8.5% and 6.9%, respectively.
CONCLUSION: Ethnic variations in the practice of oral cancer risk habits are evident. Betel quid chewing is the biggest attributable factor for this population.
SUBJECTS AND METHODS: A prospective study of 355 participants, including 280 with oral lesions/variants was conducted. Adults aged ≥18 treated at tertiary referral centres were included. Images of the oral cavity were taken using MeMoSA®. The identification of the presence of lesion/variant and referral decision made using MeMoSA® were compared to clinical oral examination, using kappa statistics for intra-rater agreement. Sensitivity, specificity, concordance and F1 score were computed. Images were reviewed by an off-site specialist and inter-rater agreement was evaluated. Images from sequential clinical visits were compared to evaluate observable changes in the lesions.
RESULTS: Kappa values comparing MeMoSA® with clinical oral examination in detecting a lesion and referral decision was 0.604 and 0.892, respectively. Sensitivity and specificity for referral decision were 94.0% and 95.5%. Concordance and F1 score were 94.9% and 93.3%, respectively. Inter-rater agreement for a referral decision was 0.825. Progression or regression of lesions were systematically documented using MeMoSA®.
CONCLUSION: Referral decisions made through MeMoSA® is highly comparable to clinical examination demonstrating it is a reliable telemedicine tool to facilitate the identification of high-risk lesions for early management.
MATERIALS AND METHODS: We developed a web-interface, hosted on a web server to collect oral lesions images from international partners. Further, we developed a customised annotation tool, also a web-interface for systematic annotation of images to build a rich clinically labelled dataset. We evaluated the sensitivities comparing referral decisions through the annotation process with the clinical diagnosis of the lesions.
RESULTS: The image repository hosts 2474 images of oral lesions consisting of oral cancer, oral potentially malignant disorders and other oral lesions that were collected through MeMoSA® UPLOAD. Eight-hundred images were annotated by seven oral medicine specialists on MeMoSA® ANNOTATE, to mark the lesion and to collect clinical labels. The sensitivity in referral decision for all lesions that required a referral for cancer management/surveillance was moderate to high depending on the type of lesion (64.3%-100%).
CONCLUSION: This is the first description of a database with clinically labelled oral lesions. This database could accelerate the improvement of AI algorithms that can promote the early detection of high-risk oral lesions.
METHODS: A total of 328 final-year dental students were trained across six cohorts. Three cohorts (175 students) received F2F training from the academic years 2016/2017 to 2018/2019, and the remaining three (153 students) underwent online training during the Covid-19 pandemic from 2019/2020 to 2021/2022. Participant scores were analysed using the Wilcoxon signed rank test, the Mann-Whitney test, Cohen's d effect size, and multiple linear regression.
RESULTS: Both F2F and online training showed increases in mean scores from pre-test to post-test 3: from 67.66 ± 11.81 to 92.06 ± 5.27 and 75.89 ± 11.03 to 90.95 ± 5.22, respectively. Comparison between F2F and online methods revealed significant differences in mean scores with large effect sizes at the pre-test stage (p