Evidence map›Paper›PMID 41299669›Full record

ArticleWorld journal of surgical oncology2025

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

Huan Han, Shuyi Yin, Xin He, Fangsheng Zhou, Miaoxia He

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Article in World journal of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Huan HanDepartment of Pathology, Changhai Hospital, Naval Medical University, Shanghai, China.
Shuyi YinDepartment of Pathology, Changhai Hospital, Naval Medical University, Shanghai, China.
Xin HeDepartment of Pathology, Changhai Hospital, Naval Medical University, Shanghai, China.
Fangsheng ZhouDepartment of Pathology, Changhai Hospital, Naval Medical University, Shanghai, China.
Miaoxia HeDepartment of Pathology, Changhai Hospital, Naval Medical University, Shanghai, China. hmm_26@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo 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.

methodsA 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.

resultsSignificant 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.

conclusionThe combination of TIL and TSR demonstrates significant predictive value for ALNM in BC patients and warrants consideration for inclusion in future metastasis prediction models.

Indexed as

Breast NeoplasmsLymphatic MetastasisLymph NodesLymphocytes, Tumor-InfiltratingStromal CellsAdultAgedAxillaErb-b2 Receptor Tyrosine KinasesFemaleHumansMiddle AgedPredictive Value of TestsPrognosisRetrospective StudiesROC CurveErb-b2 Receptor Tyrosine KinasesAxillary lymph node metastasis, tumorBreast cancerTumor-infiltrating lymphocytesTumor-stromal ratio

Identifiers

PMID41299669
PMCPMC12764158

What Socratic holds

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.