ArticleScientific reports2023
A novel nomogram model of breast cancer-based imaging for predicting the status of axillary lymph nodes after neoadjuvant therapy.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Multimodal nomogram for predicting axillary pathological complete response after neoadjuvant therapy in clinically node-positive breast cancer.Frontiers in oncology · 2026Article
- Axillary Pathological Complete Response After Neoadjuvant Therapy in cN1-2 Breast Cancer: An Internally Validated PET/CT-Integrated Nomogram.Current oncology (Toronto, Ont.) · 2025Article
- Performance of low- and high-temporal-resolution DCE-MRI texture analysis in distinguishing breast lesions from background enhancement.American journal of translational research · 2025Article
- Nomogram for predicting axillary pathologic complete response after neoadjuvant systemic therapy in HER2 positive and triple negative breast cancer.Journal of Cancer · 2025Article
- Albumin-To-Alkaline Phosphatase Ratio as a New Early Predictive Marker of Axillary Response in Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy: A Pilot Study.Medicina (Kaunas, Lithuania) · 2024Article
- A nomogram with Nottingham prognostic index for predicting locoregional recurrence in breast cancer patients.Frontiers in oncology · 2024Article
- simpleNomo: A Python Package of Making Nomograms for Visualizable Calculation of Logistic Regression Models.Health data science · 2023Article
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study is aimed to develop and validate a novel nomogram model that can preoperatively predict axillary lymph node pathological complete response (pCR) after NAT and avoid unnecessary axillary lymph node dissection (ALND) for breast cancer patients. A total of 410 patients who underwent NAT and were pathologically confirmed to be axillary lymph node positive after breast cancer surgery were included. They were divided into two groups: patients with axillary lymph node pCR and patients with residual node lesions after NAT. Then the nomogram prediction model was constructed by univariate and multivariate logistic regression. The result of multivariate logistic regression analysis showed that molecular subtypes, molybdenum target (MG) breast, computerized tomography (CT) breast, ultrasound (US) axilla, magnetic resonance imaging (MRI) axilla, and CT axilla (all p < 0.001) had a significant impact on the evaluation of axillary lymph node status after NAT. The nomogram score appeared that AUC was 0.832 (95% CI 0.786-0.878) in the training cohort and 0.947 (95% CI 0.906-0.988) in the validation cohort, respectively. The decision curve represented that the nomogram has a positive predictive ability, indicating its potential as a practical clinical tool.
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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 Socratic graph.