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

Breast Cancer Clinical Trial

— NeoMDSS  

Official title:

An MRI-based, Multi-parametric Model for Early Prediction of Pathological Complete Response After the First Cycle of Neoadjuvant Chemotherapy in Breast Cancer: a Multicenter, Prospective Cohort Study

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04909554
• Other study ID #: 20210504
• Status: Recruiting
• Start date: January 1, 2019
• Est. completion date: June 30, 2023

Study information

• Verified date: February 2023
• Source: Guangdong Provincial People's Hospital
• Contact: Kun Wang, MD
• Phone: 020-83827812
• Email: gzwangkun[@]126.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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 chemotherapy (NAC) 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.

Description:

Breast cancer is the most prevalent cancer among women worldwide. NAC 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 NAC 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 200 patients undergoing MRI after the first cycle of neoadjuvant chemotherapy. This project plans to establish and validate a model for determining pCR during NAC 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. Retrospectively 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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 200
• Est. completion date: June 30, 2023
• Est. primary completion date: June 30, 2023
• Accepts healthy volunteers: No
• Gender: Female
• Age group: 18 Years and older

Eligibility

1. For training set:

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;

Exclusion Criteria:

• With chemotherapy contraindications;
• Multifocal of multicentric lesions;
• Poor quality of MRI images;

2. For validation set:

Inclusion Criteria:

• 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;
• Metastatic breast cancer;
• Multifocal of multicentric lesions;

Related Conditions & MeSH terms

• Breast Cancer
• Breast Neoplasms

Locations

Country	Name	City	State
China	Guangdong Provincial People's Hospital	Guangzhou	Guangdong

Sponsors (1)

Lead Sponsor	Collaborator
Guangdong Provincial People's Hospital

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Shrinkage pattern	The difference in tumor regression shrinkage patterns between the different treatment groups. Based on the MRI after the first cycle, the tumor SPs were grouped into three categories: CS, diffuse decrease, and no change or enlargement.	up to 28 weeks
Other	correlation between shrinkage patterns and efficacy	The correlation between tumor regression shrinkage patterns and treatment efficacy.	up to 28 weeks
Primary	Sensitivity	Testing the sensitivity of NeoMDSS model to predict pCR using the area under receiver operating characteristic curve.	up to 28 weeks
Secondary	Specificity	Testing the sensitivity of NeoMDSS model to predict non-pCR using the area under receiver operating characteristic curve.	up to 28 weeks
Secondary	Specificity	Testing the difference in the tumor shrinkage patterns on magnetic resonance imaging (MRI) in triple-negative breast cancer patients receiving neoadjuvant therapy , as well as the correlation between tumor regression pattern and efficacy.	up to 6 weeks