SynthesisEuropean radiology2024
Diagnostic performance of MRI for assessing axillary lymph node status after neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis.
Synthesis in European radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Pretreatment MRI and Ultrasound Features of the Primary Tumor and Axillary Nodes for Predicting Axillary Pathologic Complete Response After Neoadjuvant Chemotherapy: A Cross-Anatomic Comparison.Diagnostics (Basel, Switzerland) · 2026Article
- MRI-Based Radiomics Model for Classifying Axillary Lymph Node Burden and Disease-Free Survival in Patients With Early-Stage Breast Cancer.Journal of magnetic resonance imaging : JMRI · 2026Article
- Diagnosis of axillary lymph node metastasis in breast cancer: a systematic review and meta-analysis of the literature on ultrasound and magnetic resonance imaging published from 2014 to 2025.Quantitative imaging in medicine and surgery · 2026Article
- Radiomics integrated with machine and deep learning analysis of T2-weighted and arterial-phase T1-weighted Magnetic Resonance Imaging for non-invasive detection of metastatic axillary lymph nodes in breast cancer.La Radiologia medica · 2025Article
- Monitoring Pharmacological Treatment of Breast Cancer with MRI.Current issues in molecular biology · 2025Review
- MRI radiomics and biological correlations for predicting axillary lymph node burden in early-stage breast cancer.Journal of translational medicine · 2024Article
- Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis systematic review examined the diagnostic performance of magnetic resonance imaging (MRI) for assessing axillary lymph node status (ALNS) after neoadjuvant chemotherapy (NAC) in breast cancer patients.
methodsWe searched PubMed, Embase, Cochrane Library, and Web of Science to identify relevant studies and used the QUADAS-2 tool to assess methodological quality of eligible studies. We used STATA version 12.0 to perform data pooling, heterogeneity testing, subgroup analysis, and sensitivity analysis.
resultsFor the 21 enrolled studies, including 2875 patients, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were respectively 0.63 (95% CI: 0.53-0.72), 0.75 (95% CI: 0.68-0.81), 2.52 (95% CI: 1.98-3.19), 0.50 (95% CI: 0.39-0.63), and 5.08 (95% CI: 3.38-7.63). The AUC was 0.76 (95% CI: 0.72-0.79). I
conclusionMRI may have suboptimal diagnostic value in assessing ALNS after NAC for breast cancer patients. Due to the inconsistency of NAC regimens, the variability of axillary surgery, and the lack of time interval between MRI and surgery, further studies are needed to confirm our findings. CLINICAL RELEVANCE STATEMENT: Our study provided the diagnostic value of MRI in assessing axillary lymph node status after neoadjuvant chemotherapy for breast cancer patients. KEY POINTS: • MRI may have suboptimal diagnostic value in assessing axillary lymph node status after NAC for general breast cancer patients. • The initial axillary lymph node status has little impact on the diagnostic efficacy of MRI. • The substantial heterogeneity among studies highlights the need for further studies to provide more high-quality evidence in this field.
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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 Socratic graph.