Li Xinyang, Cheng Xiang, Han Yikai, Liu Xiaodan, Fang Yujin, Ren Shengju, Dong Xiangwen, Lei Ziwen, Zhang Yue, Zhang Tengfei
Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Department of Oncology, Dengzhou Central Hospital, , Dengzhou, Henan, China.
Front Oncol. 2025 Aug 15;15:1534545. doi: 10.3389/fonc.2025.1534545. eCollection 2025.
There has been a persistent upward trend in breast cancer (BC) incidence in recent years. The advancement of immunotherapy has introduced promising therapeutic options. This study focuses on identify potential biomarkers to predict clinical outcomes in advanced BC patients receiving immunotherapy.
In accordance with the predefined inclusion and exclusion criteria, a cohort of 154 patients were enrolled in this study. Progression-free survival (PFS) and overall survival (OS) were the primary endpoints. The end of follow-up is October 2024. Statistical analyses were performed utilizing IBM SPSS Statistics, version 26.0, and R software, version 4.3.1.
Univariate Cox regression analysis demonstrated a statistically significant association between the prognostic nutritional index (PNI) and both PFS and OS (p<0.05). Kaplan-Meier survival analysis, complemented by log-rank tests, revealed statistically differences in survival outcomes stratified by PNI levels (p<0.05). After adjusting for potential confounders in multivariate Cox regression analysis, PNI remained an independent prognostic factor in advanced BC patients undergoing immunotherapy. The predictive accuracy of the nomograms, as measured by the concordance indices (C-indices), was 0.710 for PFS and 0.705 for OS. The area under the ROC (AUC) for the predicted model at 6-, 12-, 18- and 24- months were 0.756, 0.761, 0.684, and 0.779. For OS, the AUC values were 0.753, 0.722, 0.641 and 0.576. The calibration curves revealed good concordance between the observed outcomes and the predicted probabilities.
PNI is an independent prognostic factor for advanced BC receiving immunotherapy and the prognostic model based on PNI has good discrimination, authenticity and consistency.
近年来乳腺癌（BC）发病率持续呈上升趋势。免疫疗法的进展带来了有前景的治疗选择。本研究聚焦于识别潜在生物标志物，以预测接受免疫疗法的晚期BC患者的临床结局。
根据预定义的纳入和排除标准，本研究纳入了154例患者。无进展生存期（PFS）和总生存期（OS）为主要终点。随访截止于2024年10月。使用IBM SPSS Statistics 26.0版和R软件4.3.1版进行统计分析。
单因素Cox回归分析表明，预后营养指数（PNI）与PFS和OS均存在统计学显著关联（p<0.05）。Kaplan-Meier生存分析辅以对数秩检验，显示按PNI水平分层的生存结局存在统计学差异（p<0.05）。在多因素Cox回归分析中对潜在混杂因素进行校正后，PNI仍是接受免疫疗法的晚期BC患者的独立预后因素。列线图的预测准确性，以一致性指数（C指数）衡量，PFS为0.710，OS为0.705。预测模型在6个月、12个月、18个月和24个月时的ROC曲线下面积（AUC）分别为0.756、0.761、0.684和0.779。对于OS，AUC值分别为0.753、0.722、0.641和0.576。校准曲线显示观察到的结局与预测概率之间具有良好的一致性。
PNI是接受免疫疗法的晚期BC的独立预后因素，基于PNI的预后模型具有良好的区分度、真实性和一致性。
