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Background <p>Systemic inflammation is closely correlated with the progression of cancer. Inflammation-related indicators has been recognized as outcome predictors in triple-negative breast cancer (TNBC). Our study aimed to investigate the predictive value of several inflammation-related indicators in TNBC patients underwent chemotherapy (NAC).</p> Methods <p>100 TNBC patients were enrolled in the study. Levels of interleukin-6 (IL-6) were detected by enzyme-linked immunosorbent assays (ELISAs). Platelet-to-lymphocyte ratio (PLR) and immune inflammatory index (SII) were obtained from blood routine. Levels of Ki-67 expression were detected by immunohistochemistry (IHC). Mentioned indicators were divided into two groups based on their median values. The correlation between these indicators and NAC efficacy was analyzed using <i>t</i> tests. Prognostic risk scores were calculated by univariate Cox regression analysis and Lasso-penalized Cox regression. The patients were divided into low- and high-risk groups based on the median risk score. Survival curves were obtained by Kaplan–Meier method. Models for univariate and multivariate Cox regression analyses were performed to determine the independent risk factors. A nomogram was used for the prediction of 1-, 2-, and 3-year disease-free survival (DFS). Accuracy of the prognostic model was validated by receiver operating characteristic curve (ROC).</p> Results <p>IL-6, PLR, SII, and Ki-67 levels were associated with neoadjuvant efficacy. IL-6, PLR, SII, Ki-67, and lymphocyte count were associated with DFS. The risk score for each TNBC patient was obtained using LASSO regression analysis to construct a prognostic model. In the prognostic model, patients in the high-risk score group showed worse DFS than those in the low-risk group. Risk score and tumor size were independently correlated with outcomes in multivariate Cox regression analysis. A nomogram was constructed using IL-6, PLR, SII, Ki-67, and Miller-Payne (MP) scores. Calibration curves demonstrated good consistency between the actual and predictive values of the nomogram.</p> Conclusion <p>A prognostic model was established by combining four prognosis-related indicators in TNBC patients who underwent NAC.</p>

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The value of inflammation-related indicators in chemotherapy efficacy and disease-free survival of triple-negative breast cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月4日

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  • Jie Zhu,
  • Jiale Cheng,
  • Yuyuan Ma,
  • Ying Wang,
  • Zhonghua Zou,
  • Wenjie Wang,
  • Haihua Shi,
  • You Meng

摘要

Background

Systemic inflammation is closely correlated with the progression of cancer. Inflammation-related indicators has been recognized as outcome predictors in triple-negative breast cancer (TNBC). Our study aimed to investigate the predictive value of several inflammation-related indicators in TNBC patients underwent chemotherapy (NAC).

Methods

100 TNBC patients were enrolled in the study. Levels of interleukin-6 (IL-6) were detected by enzyme-linked immunosorbent assays (ELISAs). Platelet-to-lymphocyte ratio (PLR) and immune inflammatory index (SII) were obtained from blood routine. Levels of Ki-67 expression were detected by immunohistochemistry (IHC). Mentioned indicators were divided into two groups based on their median values. The correlation between these indicators and NAC efficacy was analyzed using t tests. Prognostic risk scores were calculated by univariate Cox regression analysis and Lasso-penalized Cox regression. The patients were divided into low- and high-risk groups based on the median risk score. Survival curves were obtained by Kaplan–Meier method. Models for univariate and multivariate Cox regression analyses were performed to determine the independent risk factors. A nomogram was used for the prediction of 1-, 2-, and 3-year disease-free survival (DFS). Accuracy of the prognostic model was validated by receiver operating characteristic curve (ROC).

Results

IL-6, PLR, SII, and Ki-67 levels were associated with neoadjuvant efficacy. IL-6, PLR, SII, Ki-67, and lymphocyte count were associated with DFS. The risk score for each TNBC patient was obtained using LASSO regression analysis to construct a prognostic model. In the prognostic model, patients in the high-risk score group showed worse DFS than those in the low-risk group. Risk score and tumor size were independently correlated with outcomes in multivariate Cox regression analysis. A nomogram was constructed using IL-6, PLR, SII, Ki-67, and Miller-Payne (MP) scores. Calibration curves demonstrated good consistency between the actual and predictive values of the nomogram.

Conclusion

A prognostic model was established by combining four prognosis-related indicators in TNBC patients who underwent NAC.