Evidence map›Paper›PMID 40106761›Full record

ArticlePloS one2025

A new marker for predicting sentinel lymph node metastasis in early (cT1-2N0) breast cancer: Tumor-infiltrating lymphocytes (TILs).

Xihao Ni, Weitao Wang, Huimin Sun, Ran An, Ying Lei, Chang-Liang Wang

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Xihao NiSchool of Clinical Medicine, Shandong Second Medical University, Weifang, Shandong Province, People's Republic of China.
Weitao WangSchool of Clinical Medicine, Shandong Second Medical University, Weifang, Shandong Province, People's Republic of China.
Huimin SunDepartment of Pathology, Weifang People's Hospital, Weifang, Shandong Province, People's Republic of China.
Ran AnSchool of Clinical Medicine, Shandong Second Medical University, Weifang, Shandong Province, People's Republic of China.
Ying LeiDepartment of Breast Surgery, Weifang People's Hospital, Weifang, Shandong Province, People's Republic of China.
Chang-Liang WangDepartment of Breast Surgery, Weifang People's Hospital, Weifang, Shandong Province, People's Republic of China.ORCID https://orcid.org/0000-0001-5903-4254

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTumor-infiltrating lymphocytes (TILs) are associated with lymph node metastasis and prognosis in breast cancer. Therefore, we explored the value of TILs in predicting sentinel lymph node metastasis (SLNM) in patients with early-stage (cT1-2N0) breast cancer and provided a new method for preoperative assessment of SLNM status.

methodsThis study included 337 patients with early-stage breast cancer who underwent surgery at our hospital from January 2022 to December 2023. The expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki-67 in the patients was assessed using immunohistochemistry (IHC). TILs in the core needle biopsy samples were evaluated histopathologically, and patients were divided into high and low TILs groups based on the density of TILs. Statistical analysis was conducted, and a predictive model was established.

resultsThe study found that patients with high TILs had a significantly lower rate of SLNM compared to those with low TILs (P < 0.001). The cT stage and the level of TILs were identified as independent predictive factors for SLNM. The ROC curve analysis indicated that the density of TILs has good predictive efficacy for SLNM. Based on the results of the multivariate regression analysis, a nomogram predictive model for SLNM was constructed.

conclusionsOur study showed that the density of TILs and cT stage are independent predictive factors for SLNM in early-stage (cT1-2N0) breast cancer, and the predictive effect of TILs density on SLNM is significant in Luminal and triple-negative breast cancers.

Indexed as

Biomarkers, TumorBreast NeoplasmsLymphatic MetastasisLymphocytes, Tumor-InfiltratingSentinel Lymph NodeAdultAgedErb-b2 Receptor Tyrosine KinasesFemaleHumansMiddle AgedNeoplasm StagingPrognosisReceptors, EstrogenReceptors, ProgesteroneROC CurveBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesReceptors, EstrogenReceptors, Progesterone

Identifiers

PMID40106761
PMCPMC11922523

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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 OpenQuestion graph.