ArticleOncotarget2017
A nomogram to predict the probability of axillary lymph node metastasis in female patients with breast cancer in China: A nationwide, multicenter, 10-year epidemiological study.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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.
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.
Who cites it
23 citing papers in PubMed, 40 citations in OpenAlex.
- Predicting preoperative axillary lymph node metastasis to guide surgical decisions in invasive breast cancer.Frontiers in oncology · 2026Article
- A preoperative prediction model for ipsilateral axillary lymph node metastasis of breast cancer based on clinicopathological and ultrasonography features: a prospective cohort study.Frontiers in oncology · 2025Article
- Predicting Axillary Lymph Node Metastasis in Breast Cancer Using Ultrasound and Machine Learning with SHAP.Cancer management and research · 2025Article
- Association between postoperative pathological results and non-sentinel nodal metastasis in breast cancer patients with sentinel lymph node-positive breast cancer.World journal of surgical oncology · 2024Article
- Article
- Nomogram based on multiparametric analysis of early-stage breast cancer: Prediction of high burden metastatic axillary lymph nodes.Thoracic cancer · 2023Article
- Development and validation of a point-based scoring system for predicting axillary lymph node metastasis and disease outcome in breast cancer using clinicopathological and multiparametric MRI features.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023Article
- Nomogram for predicting preoperative axillary lymph node status in male breast carcinoma: a SEER population-based study.Translational cancer research · 2023Article
- Opening the black box: interpretable machine learning for predictor finding of metabolic syndrome.BMC endocrine disorders · 2022Article
- A preoperative nomogram for predicting the risk of sentinel lymph node metastasis in patients with T1-2N0 breast cancer.Japanese journal of radiology · 2022Article
- Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2022Article
- Construction of Xinjiang metabolic syndrome risk prediction model based on interpretable models.BMC public health · 2022Article
- Article
- Development and validation of a nomogram for prediction of lymph node metastasis in early-stage breast cancer.Gland surgery · 2021Article
- Development and external validation of a nomogram to predict four or more positive nodes in breast cancer patients with one to three positive sentinel lymph nodes.Breast (Edinburgh, Scotland) · 2020Article
- Independent risk factors for axillary lymph node metastasis in breast cancer patients with one or two positive sentinel lymph nodes.BMC women's health · 2020Article
- A Model to Predict the Risk of Lymph Node Metastasis in Breast Cancer Based on Clinicopathological Characteristics.Cancer management and research · 2020Article
- Establishment of Simple Nomograms for Predicting Axillary Lymph Node Involvement in Early Breast Cancer.Cancer management and research · 2020Article
- Nomogram for the diagnosis of suspected papillary thyroid carcinomas based on sonographic patterns: a retrospective study.Gland surgery · 2019Article
- Facilitating validation of prediction models: a comparison of manual and semi-automated validation using registry-based data of breast cancer patients in the Netherlands.BMC medical research methodology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Axillary lymph node dissection (ALND) or sentinel lymph node biopsy (SLNB) alone may lead to postoperative complications. Among patients with positive ALN in the preoperative examination, approximately 40% patients do not have SLN metastasis. Herein, we aimed to develop a model to predict the probability of ALN metastasis as a preoperative tool to support clinical decision-making. We retrospectively analyzed the clinicopathological features of 4211 female patients with breast cancer who were diagnosed in seven breast cancer centers representing entire China, over 10 years (1999-2008). The patients were randomly categorized into a training cohort or validation cohort (3:1 ratio). Multivariate logistic regression analysis was performed for 1869 patients with complete information on the study variables. Age at diagnosis, tumor size, tumor quadrant, clinical nodal status, local invasion status, pathological type, and molecular subtypes were the independent predictors of ALN metastasis. The nomogram was then developed using the seven variables. Further, it was subsequently validated in 642 patients with complete data on variables in the validation cohort. Coefficient of determination (R²) and the area under the receiver-operating characteristic (ROC) curve (AUC) were calculated to be 0.979 and 0.7007, showing good calibration and discrimination of the model, respectively. The false-negative rates of the nomogram were 0 and 6.9% for the predicted risk cut-off values of 14.03% and 20%, respectively. Therefore, when the predicted risk is less than 20%, SLNB may be avoided. After further validation in various patient populations, this model may support increasingly limited axillary surgery in breast cancer.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.