ArticleBMC cancer2017
Development of nomograms to predict axillary lymph node status in breast cancer patients.
Article in BMC cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled 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.
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
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging-a systematic review and meta-analysis.Systematic reviews · 2025Pooled it
- Predictive nomogram based on serum tumor markers and clinicopathological features for stratifying lymph node metastasis in breast cancer.BMC cancer · 2022Trial
- A negative binomial regression model for risk estimation of 0-2 axillary lymph node metastases in breast cancer patients.Scientific reports · 2020Trial
- Differences in distant metastasis risk of breast cancer originating from various primary sites: a retrospective analysis based on the SEER database.Scientific reports · 2026Article
- Sustainability in radiation oncology: opportunities for enhancing patient care and reducing COStrahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2025Article
- Preoperative ultrasonography-guided core-needle biopsy-based factors for predicting the upgrade of axillary lymph nodes in breast cancer.Quantitative imaging in medicine and surgery · 2025Article
- Long-term Outcomes of Early Breast Cancer Stratified by Axillary Ultrasound Assessment.Journal of breast cancer · 2025Article
- Breast-conserving surgery versus modified radical mastectomy in T1-2N3M0 stage breast cancer: a propensity score matching analysis.Breast cancer (Tokyo, Japan) · 2024Article
- Assessment of the axilla in women with early-stage breast cancer undergoing primary surgery: a review.World journal of surgical oncology · 2024Review
- Article
- Nomogram based on multiparametric analysis of early-stage breast cancer: Prediction of high burden metastatic axillary lymph nodes.Thoracic cancer · 2023Article
- Multi-center study on predicting breast cancer lymph node status from core needle biopsy specimens using multi-modal and multi-instance deep learning.NPJ breast cancer · 2023Article
- Novel nomograms for predicting survival for immediate breast reconstruction patients diagnosed with invasive breast cancer-a single-center 15-year experience.Frontiers in oncology · 2023Article
- Analysis on factors behind sentinel lymph node metastasis in breast cancer by color ultrasonography, molybdenum target, and pathological detection.World journal of surgical oncology · 2022Article
- Nomogram models for stratified prediction of axillary lymph node metastasis in breast cancer patients (cN0).Frontiers in endocrinology · 2022Article
- Elaboration and Validation of a Nomogram Based on Axillary Ultrasound and Tumor Clinicopathological Features to Predict Axillary Lymph Node Metastasis in Patients With Breast Cancer.Frontiers in oncology · 2022Article
- Predicting of Sentinel Lymph Node Status in Breast Cancer Patients with Clinically Negative Nodes: A Validation Study.Cancers · 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
- Artificial neural network models to predict nodal status in clinically node-negative breast cancer.BMC cancer · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrediction of axillary lymph node (ALN) status preoperatively is critical in the management of breast cancer patients. This study aims to develop a new set of nomograms to accurately predict ALN status.
methodsWe searched the National Cancer Database to identify eligible female breast cancer patients with profiles containing critical information. Patients diagnosed in 2010-2011 and 2012-2013 were designated the training (n = 99,618) and validation (n = 101,834) cohorts, respectively. We used binary logistic regression to investigate risk factors for ALN status and to develop a new set of nomograms to determine the probability of having any positive ALNs and N2-3 disease. We used ROC analysis and calibration plots to assess the discriminative ability and accuracy of the nomograms, respectively.
resultsIn the training cohort, we identified age, quadrant of the tumor, tumor size, histology, ER, PR, HER2, tumor grade and lymphovascular invasion as significant predictors of ALNs status. Nomogram-A was developed to predict the probability of having any positive ALNs (P_any) in the full population with a C-index of 0.788 and 0.786 in the training and validation cohorts, respectively. In patients with positive ALNs, Nomogram-B was developed to predict the conditional probability of having N2-3 disease (P_con) with a C-index of 0.680 and 0.677 in the training and validation cohorts, respectively. The absolute probability of having N2-3 disease can be estimated by P_any*P_con. Both of the nomograms were well-calibrated.
conclusionsWe developed a set of nomograms to predict the ALN status in breast cancer patients.
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.