Evidence map›Paper›PMID 40624650›Full record

ArticleWorld journal of surgical oncology2025

Development of a preoperative nomogram to identify low-risk early-stage breast cancer patients eligible for SLNB omission.

Latif Yilmaz, Tulay Kus, Deniz Esin Tekcan Sanli

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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. Cited by 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Latif YilmazDepartment of General Surgery, Faculty of Medicine, Gaziantep University, Gaziantep, Turkey. latifyilmaz@gantep.edu.tr.
Tulay KusDivision of Medical Oncology, Faculty of Medicine, Gaziantep University, Gaziantep, Turkey.
Deniz Esin Tekcan SanliDepartment of Radiology, Faculty of Medicine, Gaziantep University, Gaziantep, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSentinel lymph node biopsy (SLNB) is the standard axillary staging method in early-stage breast cancer; however, its associated morbidity and evolving systemic treatment paradigms have prompted reconsideration of its necessity in selected low-risk patients. This study aimed to develop a preoperative nomogram based on ultrasonographic (USG) findings and clinical parameters to predict axillary metastasis risk and define a truly low-risk subgroup eligible for selective SLNB omission.

methodsA total of 452 patients with early-stage, clinically node-negative (cN0) invasive breast cancer who underwent upfront surgery between 2010 and 2024 were retrospectively analyzed. Preoperative imaging included axillary USG and ancillary 18F-FDG PET/CT, the latter used solely to exclude patients with hypermetabolic axillary nodes. A multivariate logistic regression model was constructed using clinical T stage, axillary USG findings, tumor location, and multicentricity. Patients with unicentric, non-retroareolar tumors classified as T1a-b or T1c ≤ 1.7 cm, and negative axillary USG findings, whose predicted axillary metastasis probability was < 5%, were considered low risk. This threshold was retrospectively tested for clinical validity by assessing the observed false-negative rate (FNR) in the identified low-risk population.

resultsAxillary USG findings, tumor size, tumor location, and multicentricity were significant predictors of axillary metastasis. The nomogram demonstrated good discriminatory performance, yielding an AUC of 0.816 in the development cohort and 0.830 following internal validation.A total of 123 patients (27.2%) met the criteria for the low-risk group. In this group, the observed macrometastasis rate was 4.1%, and an additional 0.7% had micrometastasis, yielding a total FNR of 4.8%. Aggressive molecular subtypes and premenopausal status were not associated with increased metastasis rates in the low-risk group. However, guideline recommendations emphasize caution when considering SLNB omission in these populations.

conclusionThis USG-based preoperative nomogram provides a clinically applicable tool to identify early-stage breast cancer patients with a truly low risk of axillary metastasis, in whom SLNB may be safely omitted. The < 5% predicted probability threshold was confirmed to correspond to an observed FNR < 5%, supporting its clinical validity. Prospective validation studies are warranted to further confirm these findings and optimize axillary management strategies.

Indexed as

Breast NeoplasmsNomogramsSentinel Lymph Node BiopsyAdultAgedAged, 80 and overAxillaFemaleFollow-Up StudiesHumansLymphatic MetastasisLymph NodesMiddle AgedNeoplasm StagingPositron Emission Tomography Computed TomographyPreoperative CareAxillary lymph node metastasisEarly-stage breast cancerPreoperative nomogramSentinel lymph node biopsySLNB omissionUltrasonography

Identifiers

PMID40624650
PMCPMC12235989

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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.