Breast NeoplasmsNCT06856616
Predicting Long-Term Clinical Outcomes in Chinese Breast Cancer Patients Receiving Neoadjuvant Chemotherapy
An observational study of Breast Neoplasms, run by The Third Affiliated Hospital of Harbin Medical University at 1 site in China.
Trial summary
At present, the majority of studies on neoadjuvant chemotherapy (NAC) in patients with breast cancer (BC) use pathological complete response (pCR) as a surrogate marker for patient prognosis, with significant improvements in pCR indicating better long-term survival. Read more about this study
- Who is it for?
- Ages 18 to 80 years, women only
- Conditions the study is for
- Breast Neoplasms
- How many people
- 6,000 participants
- Where
- 1 siteChina
- Study dates
- 13 May 2025to 1 Jun 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: From 2008 to 2019 (with follow-up ending on December 31, 2024), women with invasive breast cancer who received NAC treatment at various hospitals
Who may be able to join
- Women with invasive breast cancer who received neoadjuvant chemotherapy (NAC) treatment in various hospitals from 2008 to 2019 (follow-up endpoint December 31, 2024)
- Women with primary breast cancer (Stage II-III) confirmed by pre-NAC needle biopsy, along with recorded clinical, pathological, and prognostic information
- With MR images before the first cycle of NAC and before surgery
- With pathological HE staining images, including biopsy pathology and postoperative major pathology
Who cannot join
- Any form of treatment was received before NAC, including endocrine therapy, radiotherapy, and chemotherapy
- Disease metastasis occurred during NAC
- Breast cancer patients with secondary malignancies from other cancers
- Patients did not complete surgery and were lost to follow-up
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Machine Learning Models for Predicting Long-Term Clinical Outcomes in Chinese Female Breast Cancer Patients Receiving Neoadjuvant Chemotherapy
At present, the majority of studies on neoadjuvant chemotherapy (NAC) in patients with breast cancer (BC) use pathological complete response (pCR) as a surrogate marker for patient prognosis, with significant improvements in pCR indicating better long-term survival. However, there is still a lack of non-invasive tools for accurately predicting the prognosis and pCR of BC patients undergoing NAC. Recent research has introduced emerging artificial intelligence machine learning (ML) and deep learning (DL) algorithms such as Bayesian methods, K-nearest neighbors (KNN), decision trees, support vector machines (SVM), XGBoost, ResNet, convolutional neural networks, and Transformer models, which have brought new avenues of exploration for cancer researchers.
The integration of AI with imaging, pathology, genomics, and other multi-omics has non-invasively improved preoperative diagnosis of breast cancer and, when combined with clinical factors, can assess postoperative survival. Moreover, current research data is limited, and reliable predictive models require extensive data for training. Therefore, establishing a multi-center database is essential.
- Conditions
- Breast Neoplasms
- Medical subject headings
- Breast Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Harbin Medical University Cancer Hospital | Not described | |
| Quanzhou First Hospital Affiliated to Fujian Medical University | Not described | |
| Xiamen Maternity and Child Healthcare Hospital | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
5-10 year survival rate
5-10 year survival rate of female breast cancer patients treated with neoadjuvant chemotherapy
Measured: 2008-2019
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Mar 2025
- Study start13 May 2025
- Primary completion1 Nov 2025 (estimated)
- Study completion1 Jun 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast NeoplasmsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 6,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- The Third Affiliated Hospital of Harbin Medical University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Ming Niu, The Third Affiliated Hospital of Harbin Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06856616
- Sponsor's protocol ID
- MNiu
- Status last verified
- Feb 2025
- First submitted
- 26 Feb 2025
- Last updated
- 31 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Reasonable needs can be in contact with the research head
Study at a glance
From the registry record, last updated by the sponsor on 31 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Machine Learning Models for Predicting Long-Term Clinical Outcomes in Chinese Female Breast Cancer Patients Receiving Neoadjuvant Chemotherapy
- ClinicalTrials.gov ID
- NCT06856616
- Acronym / sponsor ID
- MNiu
- Conditions
- Breast Neoplasms
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 6,000 participants (estimated)
- Lead sponsor
- The Third Affiliated Hospital of Harbin Medical UniversityUniversity, hospital or other
- Study start
- 13 May 2025 (actual)
- Primary completion
- 1 Nov 2025 (estimated)
- Study completion
- 1 Jun 2026 (estimated)
- First posted
- 4 Mar 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
At present, the majority of studies on neoadjuvant chemotherapy (NAC) in patients with breast cancer (BC) use pathological complete response (pCR) as a surrogate marker for patient prognosis, with significant improvements in pCR indicating better long-term survival. However, there is still a lack of non-invasive tools for accurately predicting the prognosis and pCR of BC patients undergoing NAC. Recent research has introduced emerging artificial intelligence machine learning (ML) and deep learning (DL) algorithms such as Bayesian methods, K-nearest neighbors (KNN), decision trees, support vector machines (SVM), XGBoost, ResNet, convolutional neural networks, and Transformer models, which have brought new avenues of exploration for cancer researchers.
The integration of AI with imaging, pathology, genomics, and other multi-omics has non-invasively improved preoperative diagnosis of breast cancer and, when combined with clinical factors, can assess postoperative survival. Moreover, current research data is limited, and reliable predictive models require extensive data for training. Therefore, establishing a multi-center database is essential.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Harbin Medical University Cancer Hospital | – | – |
| Quanzhou First Hospital Affiliated to Fujian Medical University | – | – |
| Xiamen Maternity and Child Healthcare Hospital | – | – |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- From 2008 to 2019 (with follow-up ending on December 31, 2024), women with invasive breast cancer who received NAC treatment at various hospitals
Key inclusion criteria (4 listed)
- Women with invasive breast cancer who received neoadjuvant chemotherapy (NAC) treatment in various hospitals from 2008 to 2019 (follow-up endpoint December 31, 2024)
- Women with primary breast cancer (Stage II-III) confirmed by pre-NAC needle biopsy, along with recorded clinical, pathological, and prognostic information
- With MR images before the first cycle of NAC and before surgery
- With pathological HE staining images, including biopsy pathology and postoperative major pathology
Key exclusion criteria (4 listed)
- Any form of treatment was received before NAC, including endocrine therapy, radiotherapy, and chemotherapy
- Disease metastasis occurred during NAC
- Breast cancer patients with secondary malignancies from other cancers
- Patients did not complete surgery and were lost to follow-up
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
5-10 year survival rate
Time frame: 2008-2019
5-10 year survival rate of female breast cancer patients treated with neoadjuvant chemotherapy
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 31 May 2025.
- Individual participant dataSharing planned: No. Reasonable needs can be in contact with the research head
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Breast Neoplasms, run by The Third Affiliated Hospital of Harbin Medical University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 31 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
5-10 year survival rate (time frame: 2008-2019). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 31 May 2025.