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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Breast Cancer
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1437140

The role of systemic immune-inflammation index in predicting pathological complete response of breast cancer after neoadjuvant therapy and the establishment of related predictive model

Provisionally accepted
Ziyue Zhang Ziyue Zhang 1Yixuan Zeng Yixuan Zeng 2Wenbo Liu Wenbo Liu 3*
  • 1 University of Debrecen, Debrecen, Hajdu-Bihar, Hungary
  • 2 Semmelweis University, Budapest, Hungary
  • 3 The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

The final, formatted version of the article will be published soon.

    Objective: 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.Methods: 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 may affect pCR. Based on the results of Logistic regression analysis, a nomogram for predicting pCR was established and validated.Results: 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.

    Keywords: breast cancer, Neoadjuvant chemotherapy, Pathological complete response, nomogram, Prediction model

    Received: 23 May 2024; Accepted: 17 Oct 2024.

    Copyright: © 2024 Zhang, Zeng and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Wenbo Liu, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

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