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AI Chatbot for Prostate Radiation Therapy Patient Education

Clinical Evaluation of Large Language Model (LLM) Methods to Support Prostate Cancer Radiation Therapy Patient Education

Status
Not yet recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07719062
Enrollment
50
Registered
2026-07-22
Start date
2026-12-01
Completion date
2027-08-01
Last updated
2026-09-17

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Prostate Cancer Patients

Brief summary

This study will evaluate whether an artificial intelligence chatbot can help patients better understand radiation therapy for localized prostate cancer. Participants will be adults with prostate cancer who are planning definitive radiation therapy at Brigham and Women's Hospital. All participants will receive standard radiation therapy education and clinician-led discussions as part of routine care. In addition, participants will interact with an educational chatbot about prostate cancer radiation therapy. The chatbot is designed to provide plain-language information about treatment logistics, preparation, possible side effects, follow-up, and when to contact the care team. The chatbot will not provide diagnosis, treatment recommendations, individualized medical advice, or replace conversations with clinicians. Participants will complete questionnaires before and after using the chatbot. The study will measure changes in patient understanding, confidence in managing symptoms, usability of the chatbot, and safety-related concerns identified during clinician review of chatbot responses.

Interventions

OTHERAI Educational Chatbot

Participants will interact with an LLM-based educational chatbot focused on prostate cancer radiation therapy. The chatbot provides plain-language information about treatment logistics, preparation, expected follow-up, possible urinary, bowel, sexual, and hormonal side effects, symptom monitoring, and when to contact the care team. The chatbot is used as an adjunct to standard radiation therapy education and clinician-led discussions. The chatbot is based on ChatGPT 5.2 deployed within a secure Mass General Brigham Azure environment and configured with physician-reviewed educational source materials and safety guardrails. It is designed to provide educational information only and does not diagnose, recommend treatment choices, provide individualized medical advice, or alter clinical management. Participant interactions will not be used to train, fine-tune, or update the underlying foundation model.

Sponsors

Brigham and Women's Hospital
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SUPPORTIVE_CARE
Masking
NONE

Eligibility

Sex/Gender
MALE
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Age 18 years or older * Current diagnosis of prostate cancer * Planning to receive definitive prostate cancer radiation therapy at Brigham and Women's Hospital Department of Radiation Oncology * English-speaking * Ability to understand and willingness to provide informed consent

Exclusion criteria

* Adults unable to consent independently * Individuals who are not yet adults * Prisoners

Design outcomes

Primary

MeasureTime frameDescription
Change in PROMIS Self-Efficacy for Managing Symptoms ScoreBaseline before chatbot interaction to immediately after chatbot interaction during the same study sessionWithin-participant change in symptom self-efficacy will be measured using the Patient-Reported Outcomes Measurement Information System (PROMIS) Self-Efficacy for Managing Symptoms instrument. Scores are reported as PROMIS T-scores, with a mean of 50 and standard deviation of 10 in the reference population. Higher scores indicate greater confidence in managing symptoms, which is a better outcome. There is no fixed minimum or maximum T-score, although typical PROMIS T-scores generally range from approximately 20 to 80.

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Sep 18, 2026