Evidence map›Paper›PMID 41703012›Full record

ArticleScientific reports2026

Development and validation of a novel nomogram predicting axillary lymph node metastasis among breast cancer patients in Egypt.

Horeya Mohamed Ismail, Mostafa Ahmed Arafa, Amr Abdel Aziz Elsaid, Mohamed Mostafa Tahoun

Abstract readValidation Study
In one paragraph

Article in Scientific reports, 2026. 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Horeya Mohamed IsmailDepartment of Epidemiology, High Institute of Public Health, Alexandria University, 65 El-Horeya Road, Al Ibrahimeyah Qebli WA Al Hadrah Bahri, Bab Shar', 5422031, Alexandria Governorate, Egypt. hiph.horeya@alexu.edu.eg.ORCID http://orcid.org/0000-0002-5932-2165
Mostafa Ahmed ArafaDepartment of Epidemiology, High Institute of Public Health, Alexandria University, 65 El-Horeya Road, Al Ibrahimeyah Qebli WA Al Hadrah Bahri, Bab Shar', 5422031, Alexandria Governorate, Egypt.
Amr Abdel Aziz ElsaidDepartment of Clinical Oncology, Faculty of Medicine, Alexandria University, Alexandria, Egypt.
Mohamed Mostafa TahounDepartment of Epidemiology, High Institute of Public Health, Alexandria University, 65 El-Horeya Road, Al Ibrahimeyah Qebli WA Al Hadrah Bahri, Bab Shar', 5422031, Alexandria Governorate, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Axillary lymph node dissection (ALND) remains widely used in the management of breast cancer in Egypt despite its association with significant morbidity. A reliable tool for predicting axillary lymph node metastasis (ALNM) could help reduce unnecessary surgical interventions. This study aimed to develop and validate a predictive nomogram to estimate the risk of ALNM in patients with breast cancer. We conducted a retrospective study of 1246 women with invasive breast cancer (stages I-III) treated at a tertiary center in Alexandria, Egypt (2018-2024). A perioperative, pathology-assisted model was developed as the primary tool, and a secondary, preoperative-only model was evaluated as a sensitivity analysis. A nomogram was constructed using multivariable logistic regression to predict ALNM, and model performance was assessed using the area under the ROC curve (AUC), calibration plots, and decision curve analysis (DCA). Five independent predictors of ALNM were identified. The primary model, which was developed using all clinically important and statistically significant variables, demonstrated excellent discrimination (AUC = 0.917) with good calibration. A sensitivity analysis yielded a preoperative-only model with highly comparable performance (AUC = 0.898). Decision curve analysis supported the use of a 20% risk threshold, at which the model achieved 93.9% sensitivity, 59.5% specificity, and a negative predictive value of 87.7%. It also confirmed a superior clinical net benefit compared to axillary sonography alone or default strategies. Our nomogram offers a practical, noninvasive tool to guide personalized axillary management in Egyptian patients with breast cancer, supporting risk-stratified decisions that may safely reduce unnecessary axillary surgery and align with global de-escalation principles.

Indexed as

Breast NeoplasmsLymphatic MetastasisLymph NodesNomogramsAdultAgedAxillaEgyptFemaleHumansLymph Node ExcisionMiddle AgedRetrospective StudiesROC CurveAxillary lymph node dissection (ALND)Decision curve analysisNomogramPersonalized axillary management

Identifiers

PMID41703012
PMCPMC12921286

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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.