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

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

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.

Study Overview

• Status: Recruiting
• Conditions: Breast Cancer

Detailed 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.

• Study Type: Observational
• Enrollment (Anticipated): 200

Contacts and Locations

• Study Contact: Name: Kun Wang, MD; Phone Number: 80630 020-83827812; Email: gzwangkun@126.com
• Study Contact Backup: Name: Yuanqi Chen, MS; Phone Number: 80631 13798818919; Email: chen13798818919@163.com

Study Locations

• China
  • Guangdong
    • Guangzhou, Guangdong, China, 510080
      • Recruiting
      • Guangdong Provincial People's Hospital
      • Contact: Kun Wang, MD; Phone Number: 02083827812; Email: gzwangkun@126.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: Female

• Sampling Method: Probability Sample

Study Population

Selection of patients diagnosed with breast cancer and treated with neoadjuvant chemotherapy

Description

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;

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Sensitivity	Testing the sensitivity of NeoMDSS model to predict pCR using the area under receiver operating characteristic curve.	up to 28 weeks

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Specificity	Testing the sensitivity of NeoMDSS model to predict non-pCR using the area under receiver operating characteristic curve.	up to 28 weeks
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

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
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
correlation between shrinkage patterns and efficacy	The correlation between tumor regression shrinkage patterns and treatment efficacy.	up to 28 weeks

Collaborators and Investigators

• Sponsor: Guangdong Provincial People's Hospital
• Investigators: Study Chair: Kun Kun, MD, Guangdong Provincial People's Hospital

Study record dates

Study Major Dates

• Study Start (Actual): January 1, 2019
• Primary Completion (Anticipated): June 30, 2023
• Study Completion (Anticipated): June 30, 2023

Study Registration Dates

• First Submitted: May 9, 2021
• First Submitted That Met QC Criteria: May 28, 2021
• First Posted (Actual): June 1, 2021

Study Record Updates

• Last Update Posted (Actual): February 17, 2023
• Last Update Submitted That Met QC Criteria: February 14, 2023
• Last Verified: February 1, 2023

More Information

Terms related to this study

• Keywords: breast cancer; Magnetic resonance imaging (MRI); therapeutic response; early prediction; Neoadjuvant chemotherapy (NAC)
• Additional Relevant MeSH Terms: Skin Diseases; Neoplasms; Neoplasms by Site; Breast Diseases; Breast Neoplasms
• Other Study ID Numbers: 20210504

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No