Trial reportEuropean radiology2022
Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer.
Trial report in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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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
21 citing papers in PubMed, 36 citations in OpenAlex.
- Construction and validation of a pretreatment DCE-MRI-based radiomics prediction model for axillary pathologic response after neoadjuvant therapy in node-positive breast cancer.Gland surgery · 2026Article
- Development and multicenter validation of an immunoinflammatory marker-MRI model for pathological complete response after neoadjuvant chemotherapy in invasive breast cancer.Translational cancer research · 2026Article
- Joint synthesis of longitudinal MRI and enhanced prediction of neoadjuvant chemotherapy response in breast cancer: a multicohort study.BMC cancer · 2026Article
- Imaging- and Tumor Biomarker-Based Multivariable Model for Early Prediction of Pathologic Complete Response to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer.JCO precision oncology · 2025Article
- Monitoring Pharmacological Treatment of Breast Cancer with MRI.Current issues in molecular biology · 2025Review
- The impact of circWWC3 on neoadjuvant therapy for triple-negative breast cancer and the construction of a nomogram for predicting pathological complete response after neoadjuvant therapy.Frontiers in oncology · 2025Article
- Association between programmed cell death ligand-1 expression in patients with cervical cancer and apparent diffusion coefficient values: a promising tool for patient´s immunotherapy selection.European radiology · 2024Article
- Prediction of early clinical response to neoadjuvant chemotherapy in Triple-negative breast cancer: Incorporating Radiomics through breast MRI.Scientific reports · 2024Article
- Predictors of pathological complete response to neoadjuvant treatment in invasive breast cancer with different human epidermal growth factor receptor 2 (HER2) subcategories.Quantitative imaging in medicine and surgery · 2024Article
- Predictive value of MRI-based deep learning model for lymphovascular invasion status in node-negative invasive breast cancer.Scientific reports · 2024Article
- Development and validation of a nomogram model based on pretreatment ultrasound and contrast-enhanced ultrasound to predict the efficacy of neoadjuvant chemotherapy in patients with borderline resectable or locally advanced pancreatic cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Diagnostic Accuracy of Combined 3.0T Magnetic Resonance Imaging and Molybdenum Target X-Ray in Triple-Negative Breast Cancer: Correlation with Prognosis in Patients Undergoing Sentinel Lymph Node Biopsy.Women's health reports (New Rochelle, N.Y.) · 2024Article
- Review
- Multiparametric Contrast-Enhanced Ultrasound in Early Prediction of Response to Neoadjuvant Chemotherapy and Recurrence-Free Survival in Breast Cancer.Diagnostics (Basel, Switzerland) · 2023Article
- Machine learning for predicting breast-conserving surgery candidates after neoadjuvant chemotherapy based on DCE-MRI.Frontiers in oncology · 2023Article
- Multiparametric MRI radiomics fusion for predicting the response and shrinkage pattern to neoadjuvant chemotherapy in breast cancer.Frontiers in oncology · 2023Article
- A novel conditional survival nomogram for monitoring real-time prognosis of non-metastatic triple-negative breast cancer.Frontiers in endocrinology · 2023Article
- Review
- Review
- Preoperative prediction of lymphovascular invasion in patients with T1 breast invasive ductal carcinoma based on radiomics nomogram using grayscale ultrasound.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
objectivesTo develop a nomogram based on pretreatment dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in patients with triple-negative breast cancer (TNBC).
methodsA total of 108 female patients with TNBC treated with neoadjuvant chemotherapy followed by surgery between January 2017 and October 2020 were enrolled. The patients were randomly divided into the primary cohort (n = 87) and validation cohort (n = 21) at a ratio of 4:1. The pretreatment DCE-MRI and clinicopathological features were reviewed and recorded. Univariate analysis and multivariate logistic regression analyses were used to determine the independent predictors of pCR in the primary cohort. A nomogram was developed based on the predictors, and the predictive performance of the nomogram was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). The validation cohort was used to test the predictive model.
resultsTumor volume measured on DCE-MRI, time to peak (TTP), and androgen receptor (AR) status were identified as independent predictors of pCR. The AUCs of the nomogram were 0.84 (95% CI: 0.75-0.93) and 0.79 (95% CI: 0.59-0.99) in the primary cohort and validation cohort, respectively.
conclusionsPretreatment DCE-MRI could predict pCR after NAC in patients with TNBC. The nomogram can be used to predict the probability of pCR and may help individualize treatment. KEY POINTS: • Pretreatment DCE-MRI findings can predict pathologic complete response (pCR) after neoadjuvant chemotherapy in patients with triple-negative breast cancer. • A nomogram based on the independent predictors of tumor volume measured on DCE-MRI, time to peak, and androgen receptor status could help personalized cancer treatment in TNBC patients.
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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 OpenQuestion graph.