Prediction of Neoadjuvant Therapy Efficacy and Prognosis for Breast Cancer Based on Multimodal Data
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: To explore the value of a multimodal deep learning model integrating MRI, ultrasound, digital pathology and clinical information in predicting pCR and long-term prognosis..
- Who it may be relevant to
- Registry conditions: Breast Carcinoma. Basic parameters: 18 years — 80 years · Female.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Prediction of Neoadjuvant Therapy Efficacy and Prognosis for Breast Cancer Based on Multimodal Data: A Multicenter Retrospective and Prospective Validation
Overview
This study aims to develop a multimodal deep learning model integrating MRI, ultrasound, digital pathology and clinical information based on multicenter retrospective data. To externally validate the model in an independent prospective cohort, and evaluate its accuracy in predicting pathological complete response (pCR), 3-year and 5-year disease-free survival (DFS). To establish visual tools such as nomograms, assisting clinicians in identifying patients with chemoresistance and facilitating individualized de-escalation or escalation treatment strategies.
Interventions
- Diagnostic test To explore the value of a multimodal deep learning model integrating MRI, ultrasound, digital pathology and clinical information in predicting pCR and long-term prognosis.
MRI and ultrasound were performed in addition to conventional treatment regimens
Primary outcome measures
- Predictive value of multimodal data for neoadjuvant therapy efficacy in breast cancer [Time frame: From enrollment to the end of surgery]
Secondary outcome measures (1)
- Prognostic predictive value of multimodal data for breast cancer [Time frame: From enrollment to the end of surgery]
Eligibility criteria
Inclusion criteria
- Histopathologically confirmed invasive breast cancer;
- Planned to receive a full course of neoadjuvant therapy;
- Complete baseline imaging data (MRI/ultrasound/mammography) and core needle pathology results available.
Exclusion criteria
- Previous history of ipsilateral breast cancer or chest radiotherapy;
- Distant metastasis (Stage IV);
- Poor image quality or missing clinical data exceeding 20%.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- N/A
- Model
- Single group
- Masking
- Open label
- Primary purpose
- Diagnostic
Study locations
Center list to be confirmed — check the primary protocol.
Identifiers
NCT: NCT07671690 · KYLX2026-205