Development and Validation of a Novel Diagnostic Nomogram Model Using Serum Oxidative Stress Markers and AURKA for Prediction of Nasopharyngeal Carcinoma.

Abstract

The mortality rate of nasopharyngeal carcinoma (NPC) remains high due to the absence of quick and accurate diagnostic approaches at its early stage. Our aim is to evaluate the diagnostic value of the elevated expression of Aurora kinase A (AURKA) and the oxidative stress markers (such as glutathione, superoxide dismutase and malondialdehyde) in serum of NPC patients and to establish a nomogram model for predicting NPC on the ground of these biomarkers. Serum samples from 93 NPC patients and 94 healthy subjects were collected. Enzyme-linked immunosorbent assay (ELISA) was adopted to determine the AURKA level, while oxidative stress markers were measured by commercially available appropriate kits. Logistic regression was used for NPC predictor identification and nomogram construction. The training and validation cohorts (3:1) were randomly split up from the participants. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCAs) were performed to validate the nomogram. AURKA and malondialdehyde (MDA) levels were significantly high in the NPC population compared to the healthy controls (P < 0.0001). The nomogram resulted in an area under the curve (AUC) of 0.897 (95% confidence interval: 0.848-0.947) in the training set and AUC of 0.770 (0.628-0.912) in the validation set. The predicted probability and the actual probability matched well in the nomogram (P > 0.05). DCAs showed good results too. Serum levels of AURKA, SOD, and MDA have diagnostic values in NPC. The nomogram based on the identified biomarkers is favorable for NPC prediction.