Predictive value of tumor-infiltrating lymphocytes combined with tumor-stromal ratio for axillarylymph node metastasis in breast cancer patients - a retrospective cohort study

To investigate the predictive value of tumor-infiltrating lymphocytes (TIL) combined with tumor-stromal ratio (TSR) for axillary lymph node metastasis (ALNM) in breast cancer (BC) patients. A retrospective study was conducted, including 324 BC patients admitted to our hospital between January 2020 and December 2024. Patients were categorized into the ALNM (n = 129) and non-ALNM (n = 195) groups based on the presence of ALNM. Univariate and binary Logistics regression analyses were used to identify influencing factors, and the predictive value of TIL combined with TSR for ALNM in BC patients was evaluated with receiver operating characteristic (ROC) curve analysis. Significant differences (P < 0.05) in HER-2 status, histological grade, TSR, and TIL were observed between the two groups. Binary Logistics regression analysis indicated that HER-2, TSR, TIL, and histological grade were influencing factors for ALNM in BC patients (P < 0.05). ROC analysis revealed that the predictive value of TSR + TIL was the highest, with an area under the curve (AUC) of 0.720, standard error (95% CI: 0.663–0.777), a Youden’s index of 0.38, a sensitivity of 79.84%, and a specificity of 58.46%. The combined prediction model was formulated as: Logit(P)=-1.693+(0.574HER-2)+(0.548Historical Grade)+(0.660TSR)+(0.608TIL). Application of the model to the external validation set yielded calibration curves approximating the ideal line, indicating excellent agreement between predicted and actual risks. ROC analysis of the validation set demonstrated an AUC of 0.892 (95% CI: 0.858–0.927), with a standard error of 0.018 and a Youden’s index of 0.59. At this time, the sensitivity was 65.9%, and the specificity was 93.3%. There were statistically significant differences (P < 0.05) in the comparison of histological grade and occurrence of ALNM among patients with different TSR + TIL statuses. Patients with high TSR and high TIL showed a significantly lower rate of ALNM metastasis in comparison to other groups. The combination of TIL and TSR demonstrates significant predictive value for ALNM in BC patients and warrants consideration for inclusion in future metastasis prediction models.

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Publication Details

Journal
World Journal of Surgical Oncology
Published
2025-11-27
DOI
https://doi.org/10.1186/s12957-025-04128-y
Primary Topic
Breast Cancer Treatment Studies
Type
article
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article

Predictive value of tumor-infiltrating lymphocytes combined with tumor-stromal ratio for axillarylymph node metastasis in breast cancer patients - a retrospective cohort study

Shu‐Yi Yin, Xin He, Fuping Zhou, Huan Han et al.
World Journal of Surgical Oncology
Breast Cancer Treatment Studies
article

Predictive value of tumor-infiltrating lymphocytes combined with tumor-stromal ratio for axillarylymph node metastasis in breast cancer patients - a retrospective cohort study

Shu‐Yi Yin, Xin He, Fuping Zhou, Huan Han, Miaoxia He
article en

Abstract

To investigate the predictive value of tumor-infiltrating lymphocytes (TIL) combined with tumor-stromal ratio (TSR) for axillary lymph node metastasis (ALNM) in breast cancer (BC) patients. A retrospective study was conducted, including 324 BC patients admitted to our hospital between January 2020 and December 2024. Patients were categorized into the ALNM (n = 129) and non-ALNM (n = 195) groups based on the presence of ALNM. Univariate and binary Logistics regression analyses were used to identify influencing factors, and the predictive value of TIL combined with TSR for ALNM in BC patients was evaluated with receiver operating characteristic (ROC) curve analysis. Significant differences (P < 0.05) in HER-2 status, histological grade, TSR, and TIL were observed between the two groups. Binary Logistics regression analysis indicated that HER-2, TSR, TIL, and histological grade were influencing factors for ALNM in BC patients (P < 0.05). ROC analysis revealed that the predictive value of TSR + TIL was the highest, with an area under the curve (AUC) of 0.720, standard error (95% CI: 0.663–0.777), a Youden’s index of 0.38, a sensitivity of 79.84%, and a specificity of 58.46%. The combined prediction model was formulated as: Logit(P)=-1.693+(0.574HER-2)+(0.548Historical Grade)+(0.660TSR)+(0.608TIL). Application of the model to the external validation set yielded calibration curves approximating the ideal line, indicating excellent agreement between predicted and actual risks. ROC analysis of the validation set demonstrated an AUC of 0.892 (95% CI: 0.858–0.927), with a standard error of 0.018 and a Youden’s index of 0.59. At this time, the sensitivity was 65.9%, and the specificity was 93.3%. There were statistically significant differences (P < 0.05) in the comparison of histological grade and occurrence of ALNM among patients with different TSR + TIL statuses. Patients with high TSR and high TIL showed a significantly lower rate of ALNM metastasis in comparison to other groups. The combination of TIL and TSR demonstrates significant predictive value for ALNM in BC patients and warrants consideration for inclusion in future metastasis prediction models.

World Journal of Surgical OncologyVol. 24(1)
Second Military Medical University (CN), Changhai Hospital (CN)
Openalex Percentile: Top 55%
Breast Cancer Treatment Studies
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