Breast DiseasesNCT06765395
Explore Association Models Between Environmental Hormones andBreast Cancer
An observational study of Breast Diseases and Breast Adenocarcinoma, run by Pei-Hung Liao at 1 site in Taiwan.
Trial summary
investigated the association model between environmental hormone-related living habits and breast cancer, as well as dietary improvement programs through machine learning and clinical validation of patients with breast cancer. Read more about this study
- Who is it for?
- Ages 20 years and older, women onlyHealthy volunteers can take part
- Conditions the study is for
- Breast Diseases, Breast Adenocarcinoma
- How many people
- 687 participants
- Where
- 1 siteTaiwan
- Study dates
- 20 Mar 2023to 31 Mar 2025
- 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 20 years and older
- Women only
- Healthy volunteers accepted
- Adult, Older adult
Study population: This study recruited research subjects from an outpatient clinic and ward of the Department of General Surgery of the Cheng Hsing General Hospital.
Who may be able to join
- (1) patients aged 20 years or above; (2) patients with breast cancer.
Who cannot join
- non-patients with breast cancer
Trial locations and contacts
1 site in 1 country.
Taiwan1 site
National Taipei university of Nursing and health science
Taipei, Peitou, 112
About this study
Official title: Applying Machine Learning to Explore Association Models Between Environmental Hormones, Breast Cancer, and a Dietary and Health Education Improvement Program: An Investigative Study
investigated the association model between environmental hormone-related living habits and breast cancer, as well as dietary improvement programs through machine learning and clinical validation of patients with breast cancer.
Read the detailed description
Female breast cancer is the second most common cancer worldwide and the age at diagnosis is decreasing. Traditional risk factor screening for breast cancer focuses on reproductive history, family history, age at menarche, and age at menopause; however, young patients diagnosed with breast cancer who do not meet the above risk factors are becoming common.This study established an association model between environmental hormones and breast cancer through machine learning to improve dietary programs to reduce the incidence of breast cancer.
- Conditions
- Breast Diseases, Breast Adenocarcinoma
- Keywords
- Machine learning; association model; environmental hormones; breast cancer
- Medical subject headings
- Breast Diseases, Breast Neoplasms
What is being measured
The primary outcome is the main question the study is designed to answer.
established an association model between environmental hormones and breast cancer
The basic personal information of the participants included gender, age, height, weight, past disease history, family history, reproductive history, postoperative medication, chemotherapy type, breast cancer pathology type, stage, etc.
Measured: 2015~2024
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Jan 2025
- Study start20 Mar 2023
- Primary completion31 Mar 2025 (estimated)
- Study completion31 Mar 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Breast DiseasesStudies 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
- Case only
- Time perspective
- Retrospective
- Enrolment
- 687 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Pei-Hung Liao
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Pei-Hung Liao, National Taipei University of Nursing and Health Sciences
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06765395
- Sponsor's protocol ID
- (956)111-35
- Status last verified
- Jan 2025
- First submitted
- 3 Jan 2025
- Last updated
- 9 Jan 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Chang CY, Su CH, Chang CH, Ho CS, Liao PH. Applying machine learning to explore association models between environmental hormones, breast cancer, and a dietary and health education improvement program: an investigative study. Int J Environ Health Res. 2026 Jun;36(6):1387-1396. doi: 10.1080/09603123.2025.2576144. Epub 2025 Oct 16.
PubMed 41103105
Study at a glance
From the registry record, last updated by the sponsor on 9 Jan 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Applying Machine Learning to Explore Association Models Between Environmental Hormones, Breast Cancer, and a Dietary and Health Education Improvement Program: An Investigative Study
- ClinicalTrials.gov ID
- NCT06765395
- Acronym / sponsor ID
- (956)111-35
- Conditions
- Breast Diseases, Breast Adenocarcinoma
- Keywords
- Machine learning; association model; environmental hormones; breast cancer
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 687 participants (estimated)
- Lead sponsor
- Pei-Hung LiaoUniversity, hospital or other
- Study start
- 20 Mar 2023 (actual)
- Primary completion
- 31 Mar 2025 (estimated)
- Study completion
- 31 Mar 2025 (estimated)
- First posted
- 9 Jan 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.
investigated the association model between environmental hormone-related living habits and breast cancer, as well as dietary improvement programs through machine learning and clinical validation of patients with breast cancer.
Detailed description
Female breast cancer is the second most common cancer worldwide and the age at diagnosis is decreasing. Traditional risk factor screening for breast cancer focuses on reproductive history, family history, age at menarche, and age at menopause; however, young patients diagnosed with breast cancer who do not meet the above risk factors are becoming common.This study established an association model between environmental hormones and breast cancer through machine learning to improve dietary programs to reduce the incidence of breast cancer.
Study design
- Observational model
- Case only
- Time perspective
- Retrospective
Who may qualify
- Ages
- 20 years and older
- Sex
- Female only
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- This study recruited research subjects from an outpatient clinic and ward of the Department of General Surgery of the Cheng Hsing General Hospital.
Key inclusion criteria (1 listed)
- (1) patients aged 20 years or above; (2) patients with breast cancer.
Key exclusion criteria (1 listed)
- non-patients with breast cancer
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
established an association model between environmental hormones and breast cancer
Time frame: 2015~2024
The basic personal information of the participants included gender, age, height, weight, past disease history, family history, reproductive history, postoperative medication, chemotherapy type, breast cancer pathology type, stage, etc.
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 9 Jan 2025.
- Derived from this study: PubMed 41103105Chang CY, Su CH, Chang CH, Ho CS, Liao PH. Applying machine learning to explore association models between environmental hormones, breast cancer, and a dietary and health education improvement program: an investigative study. Int J Environ Health Res. 2026 Jun;36(6):1387-1396. doi: 10.1080/09603123.2025.2576144. Epub 2025 Oct 16.
- Individual participant dataSharing planned: No
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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 Diseases and Breast Adenocarcinoma, run by Pei-Hung Liao at 1 site in Taiwan.
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 1 inclusion and 1 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 9 Jan 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 Taiwan. 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?
established an association model between environmental hormones and breast cancer (time frame: 2015~2024). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06765395, which also lists 1 linked publication.
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 9 Jan 2025.