Ni Jingyi, Qi Xue, Jin Conghui, Xu Weiwei, Li Xinghui, Song Li, Zhang Xunlei
Department of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, Jiangsu, China.
Department of Oncology, Nantong Liangchun Hospital of Traditional Chinese Medicine, Nantong, Jiangsu, China.
Front Immunol. 2025 May 9;16:1514736. doi: 10.3389/fimmu.2025.1514736. eCollection 2025.
The purpose of this study was to evaluate the predictive values of systemic immune-inflammatory index (SII), prognostic nutrition index (PNI), change of SII (ΔSII), change of PNI (ΔPNI) and ΔPNI-ΔSII score in patients with neoadjuvant chemotherapy for breast cancer.
We enrolled in a retrospective study involving 72 patients with breast cancer between February 2020 and January 2022. All patients had clinical features of axillary lymph node metastasis and received neoadjuvant therapy. PNI and SII were detected by hematology before and after treatment. Chi-square test was used to compare the clinicopathological and experimental parameters among all groups. Logistic regression analysis was used to evaluate the prognostic value of each factor.
The prognosis was evaluated and 18 patients (25%) achieved pathological complete response (pCR) after neoadjuvant therapy. The pCR rate of breast cancer patients was significantly correlated with ER, PR, HER-2, molecular subsets, tumor size, vascular invasion, nerve invasion, N stage, clinical stage and chemotherapy regimen. Low ΔPNI, high ΔSII and higher ΔPNI-ΔSII score values had better prediction of therapeutic effect, especially the ΔPNI-ΔSII score.
In breast cancer patients receiving neoadjuvant chemotherapy, ΔPNI-ΔSII score is an effective predictor of efficacy, which helps to identify high-risk groups and evaluate efficacy.
本研究旨在评估全身免疫炎症指数(SII)、预后营养指数(PNI)、SII变化(ΔSII)、PNI变化(ΔPNI)及ΔPNI - ΔSII评分对乳腺癌新辅助化疗患者的预测价值。
我们纳入了一项回顾性研究,该研究涉及2020年2月至2022年1月期间的72例乳腺癌患者。所有患者均有腋窝淋巴结转移的临床特征并接受了新辅助治疗。治疗前后通过血液学检测PNI和SII。采用卡方检验比较各组间的临床病理和实验参数。采用逻辑回归分析评估各因素的预后价值。
评估预后,18例患者(25%)在新辅助治疗后达到病理完全缓解(pCR)。乳腺癌患者的pCR率与ER、PR、HER - 2、分子亚型、肿瘤大小、血管侵犯、神经侵犯、N分期、临床分期及化疗方案显著相关。低ΔPNI、高ΔSII及较高的ΔPNI - ΔSII评分值对治疗效果有更好的预测作用,尤其是ΔPNI - ΔSII评分。
在接受新辅助化疗的乳腺癌患者中,ΔPNI - ΔSII评分是疗效的有效预测指标,有助于识别高危人群并评估疗效。