ArticleGland surgery2021
Development and validation of a nomogram for prediction of lymph node metastasis in early-stage breast cancer.
Article in Gland surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- Development and validation of a novel nomogram predicting axillary lymph node metastasis among breast cancer patients in Egypt.Scientific reports · 2026Article
- A balanced view of imaging and molecular markers for predicting axillary lymph node metastasis in T1 breast cancer.Quantitative imaging in medicine and surgery · 2025Article
- Nomogram for development and validation of a prognosis prediction model for cancer-specific survival in young breast cancer patients with stage I-III based on the Surveillance, Epidemiology, and End Results (SEER) database.Translational cancer research · 2025Article
- Role of Progesterone Receptor Level in Predicting Axillary Lymph Node Metastasis in Clinical T1-T2N0 Luminal Type Breast Cancer.Medicina (Kaunas, Lithuania) · 2025Article
- Unveiling the best predictive models for early‑onset metastatic cancer: Insights and innovations (Review).Oncology reports · 2024Review
- Incidence and risk factors of lymph node metastasis in breast cancer patients without preoperative chemoradiotherapy and neoadjuvant therapy: analysis of SEER data.Gland surgery · 2023Article
- Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development.JMIR cancer · 2023Article
- Development and validation of an extended Cox prognostic model for patients with ER/PR+ and HER2- breast cancer: a retrospective cohort study.World journal of surgical oncology · 2022Article
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7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLymph node status is an important factor in determining the prognosis of early-stage breast cancer. We endeavored to build and validate a simple nomogram to predict lymph node metastasis (LNM) in patients with early-stage breast cancer.
methodsPatients with T1-2 and non-metastasis (M0) breast cancer registered in the Surveillance, Epidemiology, and End Results (SEER) database were enrolled. All patients were divided into primary cohort and validation cohort in a 2:1 ratio. In order to assess risk factors for LNM, we performed univariate and multivariate binary logistic regression, and based on results of multivariable analysis, we built the predictive nomogram model. The C-index, receiver operating characteristic (ROC) and calibration plots were applied to assess LNM model performance. Moreover, the nomogram efficiency was further validated through the validation cohort, part of which was from the First Affiliated Hospital of Nanjing Medical University database.
resultsTotally, 184,531 female breast cancer with T1-2 tumor size from SEER database and 1,222 patients from the Chinese institutional data were included. There were 123,019 patients in the primary cohort and 62,734 patients in validation cohort. The LNM nomogram was composed of seven features including age at diagnosis, race, primary site, histologic type, grade, tumor size and subtype. The model showed good discrimination, with a C-index of 0.720 [95% confidence interval (CI): 0.717-0.723] and good calibration. Similar C-index was 0.718 (95% CI: 0.713-0.723) in validation cohort. Consistently, ROC curves presented good discrimination in the primary cohort [area under the curve (AUC) =0.720] and the validation set (AUC =0.718) for the LNM nomogram. Calibration curve of the nomogram demonstrated good agreement.
conclusionsWith the prediction of novel validated nomogram for women with early-stage breast cancer, doctors may distinguish patients with high possibility of LNM and devise individualize treatments.
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