A Nomogram Based on S100A7 and Clinicopathological Characteristics to Predict the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer: A Retrospective Study

基于S100A7和临床病理特征的列线图预测乳腺癌新辅助化疗疗效:一项回顾性研究

阅读:2

Abstract

BACKGROUND: We have previously found that S100 calcium-binding protein A7 (S100A7) is strongly associated with chemoresistance in breast cancer (BC). In this study, we investigated whether S100A7 can be used to predict the efficacy of neoadjuvant chemotherapy (NAC) and assessed its relationship with clinicopathological characteristics in BC. METHODS: We retrospectively analyzed the clinicopathological data of patients with BC who underwent NAC at the Fourth Hospital of Hebei Medical University between January 2021 and December 2021. The t-test, Wilcoxon test, and chi-square test were used to compare clinicopathological characteristics between the NAC-sensitive and NAC-insensitive groups and assess the relationship between S100A7 expression and clinicopathological characteristics. Binomial logistic regression analysis was used to identify the predictors of NAC efficacy. A prediction model was constructed and visualized using a nomogram for clinical prediction of NAC efficacy. RESULTS: A total of 76 patients with BC who underwent NAC were included in this study; of these patients, 49 were sensitive to NAC, whereas 27 were insensitive to NAC. Statistically significant differences were observed in age, menstrual status, histological grade, T stage, Ki67, and S100A7 expression between the NAC-sensitive and NAC-insensitive groups. Regression analysis showed that age, histological grade, Ki67, subtype, menstrual status, TILs and S100A7 expression were predictors of NAC efficacy. However, only histological grade III (OR, 25.613; 95% CI, 1.254-523.077; P = 0.035), Ki67 (OR, 9.781; 95% CI, 2.022-47.317; P = 0.005), TILs (OR, 1.227; 95% CI, 1.064-1.415; P = 0.005), and S100A7 expression (OR, 0.042; 95% CI, 0.010-0.174; P<0.001) were independent predictors. Therefore, we constructed a model incorporating these four characteristics and visualised the model in a nomogram to predict NAC efficacy in clinical settings, with a model prediction accuracy of 0.927. CONCLUSION: S100A7 may serve as a predictor of NAC efficacy in patients with BC.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。