A spectral CT-based nomogram for predicting the response to induction chemotherapy in nasopharyngeal carcinoma.

AIM: To establish a spectral computed tomography (CT)-based nomogram for predicting the response to induction chemotherapy (ICT) in nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS: Fifty-four patients with NPC who underwent spectral CT examination before ICT were enrolled prospectively. Patients were assigned to response and non-response groups according to response evaluation. The predictive indicators were spectral CT parameters of venous phase, including iodine concentration (IC), normalised IC (NIC), slope of the spectral attenuation curve in Hounsfield units (lambdaHU), effective atomic number (Eff-Z), and water concentration. Multivariate logistic regression was used to construct a predictive model. The receiver operating characteristic (ROC) and calibration curves were used to evaluate the robustness of model, while the bootstrap method was used for internal validation. The Hosmer-Lemeshow test was used to test the goodness of fit of the discriminant model. RESULTS: Multivariate logistic regression analysis showed that NIC, lambdaHU, and Eff-Z were the potential predictors, and the three indicators were further used to establish a predictive model. The nomogram was evaluated to have good predictive performance, the area under the ROC curve was 0.909 (95% confidence interval [CI]: 0.799-0.970), and the model was well calibrated (chi(2) = 8.149, p=0.419). CONCLUSIONS: The spectral CT nomogram has potential clinical value in predicting response to ICT in NPC and may help guide individualised treatment decisions.