AUTHOR=Wang Fujue , Yang Qiao , Yang Dong , Cao Chuangjie , Chen Xinghua , Ning Jiancheng , Wu Tianyu , Zhou Wei , Fang Zhe , Li Pian 

TITLE=Establishment and validation of a prognostic model for nasopharyngeal carcinoma patients based on partial response rates

JOURNAL=Frontiers in Oncology

VOLUME=Volume 15 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2025.1705634

DOI=10.3389/fonc.2025.1705634

ISSN=2234-943X

ABSTRACT=ObjectiveThis study aims to investigate the impact of varying rates of partial response (PR) on survival outcomes in nasopharyngeal carcinoma (NPC) patients following induction chemotherapy (IC) and to develop a nomogram for predicting overall survival (OS).MethodsClinical data from 561 NPC patients with PR after IC at two institutions between 2014 and 2019 were analyzed using Cox regression. A nomogram was developed and assessed with the concordance index (C-index), calibration curves, Receiver Operating Characteristic (ROC) curves, and Decision Curve Analysis (DCA). Patients were stratified into risk groups based on nomogram scores, followed by the subgroup analyses.ResultsAge, M stage, primary tumor volume post-IC, cervical lymph nodes volume post-IC, lymphocyte-to-monocyte ratio (LMR), and PR rate were independent OS predictor for NPC patients. The nomogram showed strong discrimination (C-index: 0.769) and outperformed TNM staging in predicting OS. The nomogram’s risk scores effectively stratified patients into high- and low-risk groups, with low-risk patients had better OS, progression‐free survival (PFS) and distant metastasis-free survival (DMFS). Subgroup analyses revealed a significant association between the cumulative dose of cisplatin chemotherapy and survival outcomes in patients with a PR rate below 49%. For those with a PR rate above 49%, cervical lymph nodes volume and the LMR were independent prognostic factors after IC.ConclusionWe developed and validated a nomogram that predicts the OS of NPC patients undergoing induction chemotherapy based on their PR rates. This tool helps clinicians forecast patient survival. Additionally, it provides valuable insights for optimizing treatment strategies.