Radioresistance poses a major challenge in nasopharyngeal carcinoma (NPC) treatment. Clinical tumor-node-metastasis (TNM) staging has limited accuracy in predicting NPC radioresponse and determining its therapeutic regimens. To construct a risk score model for predicting NPC radioresistance, immunohistochemistry was used to assess the expression of four proteins (14-3-3σ, Maspin, RKIP, and GRP78) in 149 NPC samples with different radiosensitivity. Sequentially, a logistic regression analysis was performed to identify independent predictors of NPC radioresistance and establish a risk score model. As a result, a risk score model, Z = -3.189 - 1.478 (14-3-3σ) - 1.082 (Maspin) - 1.666 (RKIP) + 2.499 (GRP78) + 2.597 (TNM stage), was constructed, and a patient's risk score was estimated by the formula: e (Z)/(e (Z) + 1) × 100, where "e" is the base of natural logarithm. High-risk score was closely associated with NPC radioresistance, and was observed more frequently in the radioresistant patients than that in the radiosensitive patients. The sensitivity, specificity, and accuracy of the risk score model for predicting NPC radioresistance was 88.00, 86.48, and 87.25 %, respectively, which was clearly superior to each individual protein and TNM stage. Furthermore, Kaplan-Meier survival analysis showed that high-risk score correlated with the markedly reduced overall survival (OS) and disease-free survival (DFS) of the patients, and Cox regression analysis showed that the risk score model was an independent predictor for OS and DFS. This study constructs a risk score model for predicting NPC radioresistance and patient survival, and it may serve as a complement to current radioresistance risk stratification approaches.
Keywords: Biomarkers; Nasopharyngeal carcinoma; Radioresistance; Risk score model; TNM stage.