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AI tool aims to predict breast cancer drug success, sparing patients unnecessary side effects

NCT ID NCT07689929

Knowledge-focused Sponsor: Zhejiang Cancer Hospital Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting This study
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jul 08, 2026 · Last updated Jul 09, 2026 · Updated 1 time

Summary

This study is developing an AI tool that analyzes tumor images, proteins, and patient data to predict whether a person with advanced HER2-positive or low-expression breast cancer will benefit from the targeted drug T-DXd. The goal is to avoid giving ineffective treatment, which can cause side effects and financial burden. Researchers will build and test the model using data from 900 patients across multiple hospitals.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
T-DXd (trastuzumab deruxtecan)
What this could lead to
If successful, this AI tool could help doctors identify which breast cancer patients are most likely to benefit from T-DXd, reducing unnecessary side effects and costs.
What could go wrong
This is an observational study using existing data, not a controlled trial. The AI model may not work as well in real-world settings or for all patient groups.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 900 people

The number the study aims to enrol. It can still change while the study runs.

Expected to start

Aug 2026

An estimate. Start dates often move.

Expected to finish

Dec 2028

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Retrospective cohort (modeling and internal validation): We collected data from breast cancer patients at Zhejiang Cancer Hospital who received Youherde treatment from January 2023 to June 2026, to build a dataset for developing an efficacy prediction model. We integrated the following multimodal information: 1. HE-stained slides, blank slides, and IHC-stained tissue slide images for ER, PR, HER-2, and Ki-67 from the most recent biopsy of recurrent or metastatic lesions before starting Youherde treatment; 2. For patients with post-surgery recurrence/metastasis and available surgical specimens, HE-stained slides, blank slides, and IHC-stained tissue slide images for ER, PR, HER-2, and Ki-67 from the primary tumor; 3. Corresponding clinical efficacy data (PFS, ORR, etc.) and proteomics data. Prospective cohort (multicenter external validation): Working together with multiple centers, we will prospectively include breast cancer patients who are planned to receive second-line or higher treatm

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Female participants only

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Retrospective Cohort (Modeling and Validation): 1. Female, 18 years or older; 2. Advanced breast cancer confirmed by pathology (AJCC 8th edition, stage IV); 3. HER2 status known; 4. Received at least 2 cycles of Pyrotinib monotherapy; 5. Complete baseline IHC slides (HER2, ER, PR, Ki-67) and HE-stained slides; 6. Efficacy assessed according to RECIST 1.1, with follow-up data (PFS or ORR). * Prospective Cohort (External Validation): 1. Meet criteria 1-3 above; 2. Planning to receive Pyrotinib monotherapy as second-line or later treatment; if HER2-positive, previously received neoadjuvant/adjuvant H(P) therapy, and had metastatic recurrence within 12 months after completing treatment, with post-recurrence anti-HER2 therapy considered second-line treatment. 3. Signed informed consent, agreeing to provide clinical info like imaging and pathology data before and after treatment. Exclusion Criteria: * All cohorts: 1. Baseline IHC or HE slides of poor quality (e.g., faded, folded, or tissue loss \>10%); 2. Previous treatment with other HER2-ADC drugs; 3. History of other malignancies (except non-melanoma skin cancer or cases with no recurrence for over 5 years); 4. Participation in other interventional clinical trials at the same time (past trials already completed are fine); 5. Lost to follow-up or missing key clinical data during treatment (e.g., efficacy evaluation, dose adjustment records); 6. Special treatment backgrounds that the AI model cannot analyze (e.g., combined local radiotherapy, severe infections, or other confounding factors). * Additional exclusions for the prospective cohort: 1. Pregnant or breastfeeding women; 2. Contraindications to Üher (e.g., history of ILD, left ventricular ejection fraction \<50%, etc.); 3. Unable to comply with regular follow-up (e.g., living in a remote area, mental disorders).

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Conditions

The condition(s) this trial relates to.

breast cancer breast neoplasm HER2 positive breast carcinoma

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Breast cancer

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • Zhejiang Cancer Hospital

    Hangzhou, Zhejiang, 310022, China

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