Generative AI Education Tool for Breast Cancer Care
Official title: Accuracy and Effect of Prescribed Generative AI Patient Education Module Within Breast Oncology Care
Run by University of California, San Francisco · NCT07512271 · Data updated 2026-11-12
Researchers are testing an AI-powered teaching tool to help adults with breast cancer understand their care while receiving treatment from UCSF physicians.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 35 (estimated) |
| Sponsor | University of California, San Francisco Academic / other |
| Locations | 1 site (San Francisco, California) |
| Status | Recruiting |
| Started | July 14, 2026 |
| Main results expected | January 31, 2027 |
| Study ends | January 31, 2027 |
| Registry record updated | August 6, 2026 |
| Trial ID | NCT07512271 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults with metastatic breast cancer or recent early-stage breast cancer, who have internet access and basic computer skills, and can consent.
✕Probably not a fit
Patients unlikely to benefit include those unable to use the tool due to cognitive impairment or lack of internet access.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This interventional study examines a retrieval-augmented generation AI tool, OpenEvidence CareConnect, designed to provide general and breast cancer–specific information to patients. The lead-in phase assesses safety in metastatic breast cancer patients, followed by a randomized phase comparing immediate access versus waitlist control. Outcomes include the tool’s accuracy, usefulness, and impact on patient-provider communication, with surveys and provider assessments throughout. Eligible participants include adults with Stage IV or recent Stage I–III breast cancer, who have computer access and can consent. The trial is conducted at UCSF and affiliated sites with a 5-participant lead-in followed by 30 randomized participants.
Why it matters
Potential benefit: If successful, patients may gain clearer, AI-assisted information to support decisions and conversations with their oncology team.
How similar studies have gone: Previous work with patient-facing AI educational tools shows potential for improving information access and communication, though this specific RAG-LLM tool is novel in this setting.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Females or males ages 18 and over. 2. Patients must have either: 1. Stage IV breast cancer facing a treatment change and are expected to have follow-up visits at least once every three months, or 2. Stage I-III breast cancer diagnosed within the past 6 months. 3. Basic computer literacy and regular internet access at home. 4. Able to understand study procedures and to comply with them for the entire length of the study. 5. Ability of individual or legal guardian/representative to understand a written informed consent document, and the willingness to sign it. Exclusion Criteria: 1. Contraindication to any study-related procedure or assessment. 2. Cognitive impairment that would interfere with tool usage or survey completion
Where it's running
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University of California, San Francisco
San Francisco, California, United States Recruiting
Study contacts
- Principal investigator: Michelle Melisko, MD — University of California, San Francisco
- Study coordinator: Ivy Ow
- Email: Ivy.Wong@ucsf.edu
- Phone: 877-827-3222
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.