A Risk Prediction Model for Smoking Experimentation in Mexican-American Youth

• Activity Number: 533
• Type: Invited
• Date/Time: Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Sanjay Shete*+ and Rajesh Talluri
• Companies: MD Anderson Cancer Center and MD Anderson Cancer Center
• Keywords: smoking experimentation ; risk prediction ; model development ; AUC ; absolute risk ; youth

Abstract

Early age of smoking experimentation is associated with the higher levels of nicotine dependence. In this study, we developed a risk prediction model for smoking experimentation based on data from a prospective cohort of Mexican American youth. Our approach accounted for variability in the sampled cohort by resampling the data and aggregating the parameter estimates for the resampled datasets. We then used a resampling-based model selection algorithm to select the predictors to include in the final multivariable risk model. This approach guards against over-fitting the model and reduces the variance of the model parameters. The performance of the risk prediction model was evaluated using the area under the receiver operating characteristic curve (AUC). Using the risk prediction model, we computed the absolute risk of smoking experimentation in Mexican American youth. The proposed risk prediction model had an AUC of 0.719 (95% confidence interval [CI], 0.637 to 0.801), 0.688 (95% CI, 0.633 to 0.742), and 0.666 (95% CI, 0.619 to 0.713) for predicting absolute risk for smoking experimentation within 1, 3, and 5 years, respectively.