Construction and Validation of an Assessment Model of PCR After NAT on Breast Cancer Patients With AI Technology

June 30, 2022 updated by: Peng Yuan, Cancer Institute and Hospital, Chinese Academy of Medical Sciences

Construction and Validation of an Assessment Model of Pathological Complete Response After Neoadjuvant Treatment (NAT) on Breast Cancer Patients With Artificial Intelligence (AI) Technology

Breast cancer is a major cause of survival for women worldwide. Neoadjuvant therapy as an important treatment for locally advanced breast cancer has had many positive effects for breast cancer patients. As drug therapy for breast cancer continues to evolve, the percentage of pathologic complete responses continues to increase. However, at present, pCR can only be judged by pathological testing of surgically resected specimens, and the question of whether pCR can be accurately judged preoperatively has become an urgent issue.Therefore, this project plans to establish and validate a model for determining pCR after NAT in breast cancer based on clinical information, imaging and pathological information of breast cancer patients in multiple centers using artificial intelligence technology in accordance with international guidelines and domestic expert consensus on breast cancer NAT, in order to solve the problem of surgical decision making for patients after NAT, by combining experts from breast medicine, surgery, pathology and imaging departments in several tertiary care hospitals across China. The model will be validated to solve the problem of surgical decision making for post-NAT patients.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Recruiting

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.

Detailed Description

Breast cancer is the most prevalent cancer among women worldwide. Neoadjuvant treatment (NAT) is part of the standardized treatment of breast cancer and is especially important for locally advanced breast cancer. Numerous studies have shown that patients who achieve pathological complete response (pCR) after NAT may have better disease-free and overall survival rates, thus making the survival advantage of radical surgery less significant. However, at present, pCR can only be judged by pathological testing of surgically resected specimens, and the question of whether pCR can be accurately judged preoperatively has become an urgent issue.

Artificial intelligence (AI) technology is a branch of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a similar way to human intelligence, of which image recognition is widely used in clinical research as an important component of AI. In recent years, with the development of AI and related algorithms, more and more researchers are working on the use of image images to determine the efficacy of NAT more precisely, trying to exempt a fraction of patients who achieve pCR from radical surgery and never achieve a better appearance and quality of survival.

Simon's team selected 246 patients who attended Salzburg Oncology Center in Australia from 2006-2016, had pre-surgical DCE-MRI read by imaging scientists with more than 10 years of experience, and gave a judgment of complete remission, only to obtain a more pessimistic result: a positive predictive value of only 48%. jinsun's team selected patients who underwent NAT at Samsung Medical Center from 2007-2016. The results showed that the kappa value of the concordance test between radiologic complete response (rCR) and breast pCR was 0.459, and the kappa value of the concordance test between axillary rCR and axillary pCR Woo's and Erika's teams analyzed the subgroups that led to false-negative MRI determinations of pCR and suggested that patients with G1-2, Luminal A/B subtypes, and non-lumpy enhancement had difficulty assessing complete remission by MRI. It is evident that it is now difficult to use traditional modeling approaches for pCR to determine the level of clinical application.

Elizabeth's team used preoperative MRI, AI technology for feature extraction, and clinicopathological information to construct a pCR determination model, which performed well in the independent validation set with an AUC of 0.83 (95% CI: 0.71-0.94). Imon's team used Riesz feature extraction to determine pCR in triple-negative breast cancer patients undergoing NAT, and the final model ROC reached 0.85. Professor Yang Fan's team from the Department of Radiology, Wuhan Union Medical College Hospital, Wuhan, China, used multi-phase DCE-MRI parameters and machine learning algorithms to build the model, and the highest ROC area under the curve reached 0.919. The above results show that the pCR determination model of imaging histology with AI technology is a big improvement compared with the traditional model.

Although an increasing number of studies have confirmed the importance of imaging histology for NAT pCR determination, many of the current studies have some flaws. When evaluated using the international standard imaging histology RQS score, it was found that most of the studies: (i) lacked external validation cohorts; (ii) did not provide appropriate descriptions of parameter extraction; (iii) lacked a standardized process for imaging parameters; and (iv) had small sample sizes. Therefore more systematic and standardized studies are yet to be carried out by the majority of researchers.

Therefore, this project plans to establish and validate a model for determining pCR after NAT in breast cancer based on clinical information, imaging and pathological information of breast cancer patients in multiple centers using artificial intelligence technology in accordance with international guidelines and domestic expert consensus on breast cancer NAT, in order to solve the problem of surgical decision making for patients after NAT, by combining experts from breast medicine, surgery, pathology and imaging departments in several tertiary care hospitals across China. The model will be validated to solve the problem of surgical decision making for post-NAT patients.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Anticipated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
1821

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact

The name and contact information for the person who can answer enrollment questions for a clinical study. Each location where the study is being conducted may also have a specific contact, who may be better able to answer those questions.

Study Locations

  • China
    • Beijing
      • Beijing, Beijing, China, 100021
        • Recruiting
        • National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences
        • Contact:
          • Jian Yue, MD
          • Phone Number: +86 18612621749
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

18 years and older (ADULT, OLDER_ADULT)

Accepts Healthy Volunteers

No

Genders Eligible for Study

Female

Sampling Method

Non-Probability Sample

Study Population

Patients with breast cancer treated with neoadjuvant therapy and with MRI data attending each center from 2010-2020.

Description

Inclusion Criteria:

  1. patients admitted to each study center between January 1, 2010 and December 31, 2021.
  2. ≥18 years of age, female, with an ECOG score ≤2.
  3. pathological biopsy confirmed invasive breast cancer.
  4. were initially treated with neoadjuvant therapy.
  5. have MRI imaging data prior to radical surgery after neoadjuvant treatment.
  6. underwent surgery as planned after neoadjuvant therapy and obtained postoperative pathology information.

Exclusion Criteria:

  1. Bilateral breast cancer, multiple lesions or occult breast cancer.
  2. no data related to breast MRI.
  3. no surgery after neoadjuvant therapy, no postoperative pathology results.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort

Group / Cohort

A group or subgroup of participants in an observational study that is assessed for biomedical or health outcomes.
Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.
Neoadjuvant therapy
Patients with breast cancer treated with neoadjuvant therapy attending each center from 2010-2020.
Other: Neoadjuvant therapy
Preoperative systemic therapy for breast cancer patients

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
pathological complete response
Time Frame: Post surgery based on up to approximately 24 weeks neoadjuvant therapy
Complete disappearance of breast cancer lesions from the pathology after chemotherapy
Post surgery based on up to approximately 24 weeks neoadjuvant therapy

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
Cancer Institute and Hospital, Chinese Academy of Medical Sciences

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (ACTUAL)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
April 1, 2022

Primary Completion (ACTUAL)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
June 1, 2022

Study Completion (ANTICIPATED)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
December 31, 2022

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
June 28, 2022

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
June 30, 2022

First Posted (ACTUAL)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
July 1, 2022

Study Record Updates

Last Update Posted (ACTUAL)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
July 1, 2022

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
June 30, 2022

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
June 1, 2022

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • NCC3299

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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