Zhang Ziyue, Zeng Yixuan, Liu Wenbo
Faculty of Medicine, Debrecen University, Debrecen, Hungary.
Faculty of Medicine, University of Bonn, Bonn, Germany.
Front Oncol. 2024 Nov 1;14:1437140. doi: 10.3389/fonc.2024.1437140. eCollection 2024.
To investigate the role of systemic immune-inflammation index (SII) in complete pathological response (pCR) of breast cancer patients after neoadjuvant chemotherapy, and to establish and validate a nomogram for predicting pCR.
Breast cancer patients were selected from the First Affiliated Hospital of Xi'an Jiaotong University from January 2020 to December 2023. The optimal cut-off value of SII was calculated via ROC curve. The correlation between SII and clinicopathological characteristics was analyzed by Chi-square test. Logistic regression analysis was performed to evaluate the factors that might affect pCR. Based on the results of Logistic regression analysis, a nomogram for predicting pCR was established and validated.
A total of 112 breast cancer patients were included in this study. 33.04% of the patients achieved pCR after neoadjuvant therapy. Chi-square test showed that SII was significantly correlated with pCR (P=0.001). Logistic regression analysis suggested that Ki-67 (P=0.039), therapy cycle (P<0.001), CEA (P=0.025) and SII (P=0.019) were independent predictors of pCR after neoadjuvant chemotherapy. A nomogram based on Ki-67, therapy cycle, CEA and SII showed a good predictive ability.
Ki-67, therapy cycle, CEA and SII were independent predictors of pCR of breast cancer after neoadjuvant chemotherapy. The nomogram based on the above positive factors showed a good predictive ability.
探讨全身免疫炎症指数(SII)在乳腺癌患者新辅助化疗后完全病理缓解(pCR)中的作用,并建立和验证预测pCR的列线图。
选取2020年1月至2023年12月在西安交通大学第一附属医院就诊的乳腺癌患者。通过受试者工作特征(ROC)曲线计算SII的最佳截断值。采用卡方检验分析SII与临床病理特征之间的相关性。进行逻辑回归分析以评估可能影响pCR的因素。基于逻辑回归分析结果,建立并验证预测pCR的列线图。
本研究共纳入112例乳腺癌患者。33.04%的患者在新辅助治疗后达到pCR。卡方检验显示SII与pCR显著相关(P = 0.001)。逻辑回归分析表明,Ki-67(P = 0.039)、治疗周期(P < 0.001)、癌胚抗原(CEA)(P = 0.025)和SII(P = 0.019)是新辅助化疗后pCR的独立预测因素。基于Ki-67、治疗周期、CEA和SII的列线图显示出良好的预测能力。
Ki-67、治疗周期、CEA和SII是乳腺癌新辅助化疗后pCR的独立预测因素。基于上述阳性因素的列线图显示出良好的预测能力。