A study was conducted to develop and validate a screening model using risk scores to identify individuals at high risk for developing UADT cancers in an Indian population.
A hospital-based case-control study (n=480) in Pune, India was conducted. 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 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.
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%).
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.
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