A risk factor-based model for upper aerodigestive tract cancers in India: predicting and validating the receiver operating characteristic curve
Author(s)
Gupta, Bhawna
Kumar, Narinder
Johnson, Newell W
Griffith University Author(s)
Year published
2017
Metadata
Show full item recordAbstract
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 ...
View more >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%), falsepositive 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.
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View more >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%), falsepositive 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.
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Journal Title
Journal of Genetic Counseling
Note
This publication has been entered into Griffith Research Online as an Advanced Online Version.
Subject
Clinical sciences not elsewhere classified
Dentistry