Evidence map›Paper›PMID 42012089›Full record

ArticleCancer medicine2026

Research on Omitting Sentinel Lymph Node Biopsy after Neoadjuvant Therapy in cN1 Breast Cancer Patients.

Jiabei Shang, Jianzhe Chen, Ruchun Zheng, Zhaoyu Huang, Xinrui Wu, Jie Min, Maoshan Chen, Yi Quan, Bin Wu, Huaiquan Zuo and 4 more

Abstract read
In one paragraph

Article in Cancer medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Jiabei ShangDepartment of Breast Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China.ORCID https://orcid.org/0009-0004-8785-4777
Jianzhe ChenDepartment of Breast Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China.ORCID https://orcid.org/0009-0007-1802-750X
Ruchun ZhengMedical Cosmetology Center, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Zhaoyu HuangSouthwest Medical University, Luzhou, China.
Xinrui WuSouthwest Medical University, Luzhou, China.ORCID https://orcid.org/0009-0009-8324-7271
Jie MinDepartment of Breast, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.
Maoshan ChenDepartment of Breast and Thyroid Surgery, Suining Central Hospital, Suining, China.
Yi QuanDepartment of Breast Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Bin WuDepartment of Breast Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Huaiquan ZuoDepartment of Breast Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Hua FuDepartment of Breast Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Yuepin WanDepartment of Breast Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Jiao BaiRadiology Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Guangrui PanDepartment of Breast Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China.

Funding

Beijing Vlove Charity Foundation JVII2024-0051223016Doctoral Research Initiation Fund of Affiliated Hospital of Southwest Medical University 18098Luzhou Multidisciplinary Precision Diagnosis and Treatment Quality Control Center for Breast Cancer, 2024 YLZK2024050sichuan medical science and technology innovation research association YCH-KY-YCZD2024-234
6 · The paper itself

Abstract

backgroundSome patients with clinically node-positive (cN1) breast cancer (BC) can achieve axillary pathological complete response (apCR) in axillary lymph nodes (ALNs) after neoadjuvant therapy (NAT). This study investigated predictors of post-NAT pathological node-negative (ypN0) status in cN1 breast cancer patients to identify candidates for omitting sentinel lymph node biopsy (SLNB).

methodsThis study included patients diagnosed with stage cT1-4 N1 breast cancer who received NAT followed by breast surgery and axillary lymph node dissection (ALND) at the Breast Surgery Department of the Affiliated Hospital of Southwest Medical University between January 2020 and April 2025. Univariate and multivariate logistic regression analyses were conducted to identify factors predictive of ypN0 status across different molecular subtypes.

resultsThis study enrolled 357 patients: 147 achieved ycN0 after NAT, while 210 remained ycN1. Multivariate analysis revealed: in ycN0 patients, only breast pathological complete response(bpCR) predicted ypN0 (OR: 0.151, 95% CI: 0.055-0.419); in ycN1 patients, both bpCR (OR: 0.038, 95% CI: 0.015-0.098) and MRI radiological complete response of lymph nodes (MRI-rCR(LN))(OR: 0.36, 95% CI: 0.156-0.832) were significant predictors. Univariate analysis identified ten ypN0-associated factors including bpCR. Luminal B HER2+ subtypes showed significantly higher ypN0 rates versus other subtypes.

conclusionsSpecific predictors (notably bpCR and MRI-rCR(LN)) are strongly associated with ypN0 in cN1 BC post-NAT, with Luminal B HER2+ patients demonstrating superior response rates. These findings support selective SLNB omission in cN1 patients achieving these key response markers.

Indexed as

Breast NeoplasmsNeoadjuvant TherapySentinel Lymph Node BiopsyAdultAgedAxillaFemaleHumansLymphatic MetastasisLymph Node ExcisionLymph NodesMiddle AgedNeoplasm StagingPathologic Complete ResponseRetrospective Studiesbreast neoplasmneoadjuvant therapypathological complete responseradiological complete responsesentinel lymph node biopsy

Identifiers

PMID42012089
PMCPMC13098023

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.