MRI-based Approaches for Multi-parametric Model to Early Predict Pathological Complete Response to Neoadjuvant Therapy in Breast Cancer

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Total Enrollment

301 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-01-01

Study Completion Date

2023-12-30

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

The purpose of this clinical research is to evaluate the accuracy of a multi-parametric model based on magnetic resonance imaging (MRI) in predicting pathological complete response (pCR) after the first cycle of neoadjuvant therapy (NAT) given to patients with locally advanced breast cancer, thus allowing early chemotherapy regimen modification to increase number of patients achieving pCR or save patients from toxic effects of ineffective chemotherapy.

Related Clinical Trials

Explore similar clinical trials based on study characteristics and research focus.

Radiomics of Mp-MRI Assessing NAC Outcome in Breast Cancer

NCT03592004

Breast Cancer Radiomics Neoadjuvant Chemotherapy +1 more

UNKNOWN

Prospective Radiomics Study for Breast Cancer

NCT06095414

Breast Cancer

COMPLETED

MRI Radiomics Assessing Neoadjuvant Chemotherapy in Breast Cancer to Predict Lymph Node Metastasis and Prognosis(RBC-02)

NCT04004559

Invasive Breast Cancer Neoadjuvant Chemotherapy Radiomics +2 more

UNKNOWN

The Prediction Model of NAC Response for Breast Cancer Based on The Parametric Dynamics Features.

NCT06370234

Breast Cancer Chemotherapy Effect Diffusion Weighted MRI +2 more

COMPLETED NA

MRI and Early Decision-making in Chemotherapy for Breast Cancer

NCT02449824

Breast Neoplasms

COMPLETED

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

Breast cancer is the most prevalent cancer among women worldwide. NAT has been well established in managing breast cancer for patients with locally advanced cancer and early-stage operable breast cancers of specific molecular subtypes. Though pCR has been demonstrated to be associated with better survival, it can only be judged by pathological testing of surgically resected specimens. Thus, predicting pCR earlier during NAT is imperative and can timely switch to a new personalized treatment strategy and exempt from unnecessary chemotherapy toxicity for patients.

This is a multicenter, prospective cohort study of 301 patients undergoing MRI after the first cycle of neoadjuvant chemotherapy. This project plans to establish and validate a model for determining pCR during NAT in breast cancer based on clinical information, imaging and pathological information of patients in multiple centers, in order to provide important references for further early diagnosis and personalized treatment.

1. Collecting MRI images data, clinical and pathological information, treatment regimens, and curative effect information to build an MRI-based, multi-parametric model.
2. Evaluating the performance of model through internal and external validation cohort by using the receiver operating characteristic (ROC) curve, the area under the curve (AUC), discrimination and calibration measures.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Breast Cancer

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

the training cohort

From January 2019 to December 2020, 140 patients from Guangdong Province People's Hospital with complete clinicopathological information and available images of MRI before treatment and after 1st-NAT were retrospectively recruited for the training cohort

No interventions assigned to this group

the internal validation cohort

From June 2021 and December 2023, 120 patients from Guangdong Province People's Hospital were prospectively recruited for the internal validation cohort.

No interventions assigned to this group

the external validation cohort

From June 2021 and December 2023, 41 patients from Shantou Central Hospital, The First Affiliated Hospital of Guangdong Pharmaceutical University and The First People's Hospital of Foshan were prospectively recruited for the external validation cohort.

No interventions assigned to this group

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

* Age ≥18 years;
* Histologically confirmed invasive breast carcinoma;
* Clinical stage II-III at presentation;
* Complete basic information and image data;
* Have MRI imaging data at baseline and after the first cycle of NAC;
* Finish the standard NAC treatment and undergo surgery;

* Age ≥18 years;
* Complete basic information and image data;
* Clinical stage II-III at presentation;
* Scheduled for neoadjuvant chemotherapy;
* Eastern Cooperative Oncology Group (ECOG) performance status of 0-1.
* Signed informed consent;

Exclusion Criteria

* With chemotherapy contraindications;
* Multifocal of multicentric lesions;
* Poor quality of MRI images;
2. For validation cohort:

* With chemotherapy contraindications;
* Metastatic breast cancer;
* Multifocal of multicentric lesions;

Minimum Eligible Age

18 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No