Evidence map›Paper›PMID 41737214›Full record

ArticleFrontiers in immunology2026

Association of immuno-inflammatory biomarkers with response to neoadjuvant chemotherapy and prognosis in HER2-positive breast cancer: dual-center clinical evidence.

Xuanlin Wu, Siqi Wu, Mankai Tang, Longgui Xie, Jianhui Liu, Jiexu Liao, Jie Wang, Huawei Yang

Abstract readMulticenter Study
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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

8 authors.

Xuanlin WuDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.
Siqi WuDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.
Mankai TangDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.
Longgui XieDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.
Jianhui LiuDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.
Jiexu LiaoDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.
Jie WangDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.
Huawei YangDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Peripheral blood immuno-inflammatory biomarkers (IIBs) may help predict response to neoadjuvant chemotherapy (NAC) and prognosis in HER2-positive breast cancer. This study compared the predictive value of neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) for pathological complete response (pCR) and disease-free survival (DFS). Patients and methods: A total of 224 female patients with HER2-positive invasive breast cancer who received NAC followed by surgery at two medical centers (2015-2023) were retrospectively analyzed. Baseline IIBs were calculated from complete blood counts. Receiver operating characteristic (ROC) curves identified optimal cut-offs. Logistic and Cox regression analyses combined with the least absolute shrinkage and selection operator (LASSO) method were used to determine factors associated with pCR and DFS. Subgroup analyses were performed to assess consistency across clinical and treatment variables. Results: SII demonstrated the highest discriminatory ability among tested IIBs for predicting pCR (AUC = 0.739) and was significantly associated with longer DFS (P < 0.001). Patients with low SII had higher pCR rates and improved DFS. These associations remained stable across prespecified subgroups. Other factors related to better response included lower CA15-3/CEA levels, ≥6 NAC cycles, receipt of HER2-targeted therapy, and breast-conserving surgery. Conclusions: Among common inflammatory indices, SII demonstrated the strongest association with treatment response and prognosis in HER2-positive breast cancer. As an inexpensive, readily available biomarker, it may assist clinical risk stratification. However, given the retrospective design and substantial heterogeneity in treatment regimens, these findings should be interpreted cautiously and validated in prospective studies.

Indexed as

Biomarkers, TumorBreast NeoplasmsErb-b2 Receptor Tyrosine KinasesAdultAgedAntineoplastic Combined Chemotherapy ProtocolsChemotherapy, AdjuvantFemaleHumansInflammationMiddle AgedNeoadjuvant TherapyNeutrophilsPathologic Complete ResponsePrognosisRetrospective StudiesBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine Kinasescorrelation analysisdisease-free survivalneoadjuvant chemotherapypathological complete responsesystemic immune-inflammation index

Identifiers

PMID41737214
PMCPMC12926385

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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.