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Detection of subjects with oral potentially malignant disorders in a population is key to early detection of oral cancer (OC) with consequent reduction of cancer-related morbidity and mortality. Our aim was to investigate the prevalence and associated risk factors for OPMD in representative provinces of Indonesia. This cross-sectional study was undertaken in five Indonesian provinces: West Java (WJ), Jakarta (JKT), West Papua (WP), West Kalimantan (WK) and Banda Aceh (BA). Respondents answered a previously validated questionnaire including information on ethnicity, occupation, socioeconomic status (SES), oral health practices, and behaviours associated with oral cancer. An oral examination was undertaken using WHO standardized methodology. Data were analysed using ANOVA, Chi-Square, and logistic regression to assess association between risk factors and mucosal disease. A total of 973 respondents between the ages of 17 and 82 years was enrolled (WJ 35.5%,JKT 13.3% WP 18.3%, WK 9%, BA 23.9%). Tobacco smoking (14.8%), Betel quid (BQ) chewing (12.6%) and alcohol drinking (4%) varied geographically. A well-established OPMD was detected in 137 (14.1%) respondents and 2 (0.2%) presented with chronic ulceration later diagnosed as OC. Leukoplakia was the most common OPMD found (9.7%), while the prevalence of oral submucous fibrosis (OSMF), not previously described in the nation, was 2.3%. Poor knowledge of OC risk factors, poor oral hygiene behaviours, low-income SES and ethnicity were significantly associated with the presence of an OPMD. There is a previously under-reported high prevalence of OPMD in Indonesia. Overall, we found a strong correlation between the presence of an OPMD and individual habituation to known risk factors. [ABSTRACT FROM AUTHOR]

Background: A study was conducted to develop and validate a screening model using risk scores to identify individuals at high risk for developing upper aerodigestive tract (UADT) cancers in an Indian population.Methods: A hospital-based case-control study (n = 480) was conducted in Pune, India. We assessed risk factors for UADT cancers by administering a questionnaire through face-to-face interviews. We developed a risk factor model based on the statistically significant risk factors in multiple logistic regression. A total, single risk score was calculated per individual based on the adjusted odds ratio for each of their risk factors. Standard receiver operator characteristic curve was plotted for the total score and the presence of UADT cancers. The stratification ability of the model was determined using the c-statistic. The optimal criterion value was determined at the point on curve at which the Youden's index was maximal. Confidence intervals were calculated by bootstrapping.Results: Total risk score for each individual ranged from 0 to 26. Area under the receiver operating characteristic curve (95.8; P < 0.001) suggests strong predictive ability. A risk score criterion value of ≤10 produced optimal sensitivity (93.5%), specificity (71.1%), false-positive rate (28.8%), false-negative rate (6.4%), positive predictive value (74.8%), and negative predictive value (96.6%).Conclusion: This risk factor-based model has the potential of satisfactorily screening and detection of UADT cancers at its early stage in a high-risk population like India. The identified at-risk individuals can then be targeted for clinical examination and for focused preventive/treatment measures at the hospital. [ABSTRACT FROM AUTHOR]

Background: Statistical analyses of periodontal data that average site measurements to subject mean values are unable to explore the site-specific nature of periodontal diseases. Multilevel modeling (MLM) overcomes this, taking hierarchical structure into account. MLM was used to investigate longitudinal relationships between the outcomes of lifetime cumulative attachment loss (LCAL) and probing depth (PD) in relation to potential risk factors for periodontal disease progression. Methods: One hundred males (mean age 17 years) received a comprehensive periodontal examination at baseline and at 12 and 30 months. The resulting data were analyzed in two stages. In stage one (reported here), the absolute levels of disease were analyzed in relation to potential risk factors; in stage two (reported in a second paper), changes in disease patterns over time were analyzed in relation to the same risk factors. Each approach yielded substantially different insights. Results: For absolute levels of disease, subject-level risk factors (covariates) had limited prediction for LCAL/PD throughout the 30-month observation period. Tooth position demonstrated a near linear relationship for both outcomes, with disease increasing from anterior to posterior teeth. Sites with subgingival calculus and bleeding on probing demonstrated more LCAL and PD, and supragingival calculus had an apparently protective effect. Covariates had more "explanatory power" for the variation in PD than for the variation in LCAL, suggesting that LCAL and PD might be generally associated with a different profile of covariates. Conclusion: This study provides, for a relatively young cohort, considerable insights into the factors associated with early-life periodontal disease and its progression at all levels of the natural hierarchy of sites within teeth within subjects. [ABSTRACT FROM AUTHOR]