Establishing a Risk Prediction Model for Nasopharyngeal Carcinoma Based on Anti-BNLF2b Serological Biomarkers: A Retrospective Study.

Purpose: This study aims to establish a suitable risk prediction model of NPC in regions with relatively low-incidence in southern China. Methods: We retrospectively analysed the data of 198 patients with NPC and 398 healthy individuals admitted to The Second Affiliated Hospital, Zhejiang University School of Medicine, from February 2023 to October 2024. The levels of different serum biomarkers (P85-Ab, VCA-IgA, VCA-IgM, VCA-IgG, Rta-IgG and EA-IgA) were compared between patients with NPC and healthy individuals. Binary logistic regression was used to construct a risk prediction model for NPC, and ROC curves were plotted to evaluate the performance of the model. Results: Compared with healthy individuals, patients with NPC exhibited significantly elevated levels of EA-IgA (P < 0.001), Rta-IgG (P < 0.001), P85-Ab (P < 0.001) and VCA-IgA (chi(2) = 262.25; P < 0.001). Binary logistic regression showed that P85-Ab (HR = 572.225; P < 0.001), VCA-IgA (HR = 31.877; P < 0.001) and Rta-IgG (HR = 10.670; P = 0.004) were independent risk factors for NPC. The AUC of P85-Ab combined with Rta-IgG and VCA-IgA for predicting the risk of NPC was 0.977 (95% CI: 0.959-0.988), which was greater than the AUC values of Rta-IgG and VCA-IgA (P < 0.01 for all). The combination of P85-Ab with Rta-IgG and VCA-IgA had a sensitivity of 91.36% and a specificity of 99.25%. Conclusion: P85-Ab combined with VCA-IgA and Rta-IgG is an optimal serological biomarker for the diagnosis of NPC in low-incidence regions in southern China.