Risk-factor Model Derivation and Validation for the Detection of Oral Potentially Malignant Disorders among General Population of Towns in Pune District, Maharashtra, India

Introduction: India is one among the high burden countries for smokeless tobacco use. Hence, cancer burden is large, among which cancer of the oral cavity and pharynx are important public health problems. The mortality rates for these cancers are high and this burdens the health system. Screening the high risk population can avert this. Aim: The study aimed to develop and validate a risk factor model for detection of oral potentially malignant disorders (OPMD) among the general population of a town in Pimpri Chinchwad Municipality, Pune. Materials and Methods: An analytical, cross-sectional study was planned and sociodemographic characteristics and oral examination of representative sample of 625 participants from general population was done through the systematic random sampling residing in Alandi for Phase 1 of the study. Phase 2 which was validation of the model was carried out at general population residing in Chakan. Univariate and multivariate logistic regression analysis was used to obtain the effect estimates of the potential risk factor on OPMD. Receiver-operator characteristic (ROC) curve was plotted to produce a cutoff point considered as highest Youden’s index for the presence of OPMD. Each risk factor was scored and a total cutoff score was obtained above which screening for OPMD was indicated. Risk factor model validity was assessed using sensitivity, specificity, positive predictive value, and negative predictive value. Results: Males in the age group of 46–60 years who belonged to low socioeconomic status and smoked ≥4 cigarettes/bidis per day, used smokeless tobacco >20 years and was slaked lime user and alcohol consumer with poor oral hygiene had higher odds of developing OPMD. ROC curve plotted produced a cutoff of 15 with a sensitivity of 94.1% and specificity of 68.5% and was thus selected as the cutoff score for the risk factor model. On validation of the risk factor model, the sensitivity, specificity, and the negative predictive value of the model for the detection of OPMD was found to be good. Conclusion: The model is considered good for the early detection of OPMD in districts of Maharashtra and can be used is other states of India by validating the same.