Fig. 2

The overall workflow of the development and validation of the predictive model. First, the CT, PET, and clinical features were extracted from the training dataset, and then the predictive model was developed based on significant factors by logistic regression. Second, ROC and calibration curves were used to examine the performance of the nomogram both in the training and testing datasets. Third, a simplified scoring system was built based on the regression coefficients acquired from the training dataset for every individual feature in the predictive model and then the performance of this simplified scoring system was evaluated in both the training and testing datasets. Last, the simplified scoring tables were presented in both the training and testing datasets