Multigenic prognosis assessment model for nasopharyngeal carcinoma via a modified meta-analysis approach

• Main Authors: Sim, Chor Chien, Edmund, Ui Hang Sim, Lee, Choon Weng, Kumaran, Narayanan
• Format: Article
• Language: English
• Published: De Gruyter 2023
• Subjects: R Medicine (General)
• Online Access: http://ir.unimas.my/id/eprint/42002/3/Multigenic.pdf; http://ir.unimas.my/id/eprint/42002/; https://www.degruyter.com/document/doi/10.1515/oncologie-2023-0066/html; https://doi.org/10.1515/oncologie-2023-0066

Objectives Currently, clinically relevant multigene-based prognostic assessment models for nasopharyngeal carcinoma (NPC) are limited. This paper reports a novel NPC prognosis assessment model based on multiple established NPC-associated biomarkers. Methods We used a modified meta-analysis approach to retrieve eligible studies and analyse the data. Different prognostic biomarkers and hazard ratios (HRs) with 95 % confidence intervals (CIs) of overall survival (OS) data were extracted and tabulated from eligible studies. We then used the formula based on Parmar et al. to determine OS (expressed as HR with 95 % CI). Prognosis assessment risk scores assigned to the logarithm of HR were the basis for interpreting the multigene prognosis assessment model. Finally, we explained the biological significance of this model using a multigenic NPC oncogenesis network system. Results We constructed a multigenic NPC prognosis assessment model consisting of 10 prognostic biomarkers to determine the OS rate in NPC patients. Based on the biomarkers’ expression patterns, the model could determine 1,023 possible OS rates of NPC patients. The risk score derived determines the prognosis status of the NPC patients. The higher the total risk assessment score, the poorer the prognosis. An NPC-associated network involving all ten biomarkers was also derived. Conclusions We provided a novel multigenic NPC prognosis assessment model comprising ten prognostic biomarkers on OS rate in NPC patients. A conceptual molecular-based pathophysiological network of NPC oncogenesis supported the biological relevance of this model.