AI-guided management of chemotherapy side effects

A Randomized Controlled Trial of AI-Assisted Chemotherapy Side Effect Management in Solid Tumor Patients

Not applicable Interventional Incheon St.Mary's Hospital · NCT07198581

This trial will try an AI tool that helps clinicians turn patient symptom reports into evidence-based suggestions to manage chemotherapy side effects for adults with breast or colorectal cancer.

Quick facts

PhaseNot applicable
Study typeInterventional
Enrollment174 (estimated)
Ages18 Years and up
SexAll
SponsorIncheon St.Mary's Hospital Academic / other
Drugs / interventionschemotherapy
Locations1 site (Incheon)
Trial IDNCT07198581 on ClinicalTrials.gov

What this trial studies

This is a two-stage, adaptive randomized trial comparing LLM-assisted symptom management to standard care in adults with histologically confirmed breast or colorectal cancer starting at least three months of systemic chemotherapy. In stage 1, 60 patients (30 per arm) will be enrolled with an interim analysis, and unless stopped for safety an additional 114 patients will be added for a maximum of 174 participants (87 per arm). In the intervention arm, clinicians enter anonymized symptom data into an LLM session that does not retain data and receive evidence-based management recommendations which physicians then review and apply as appropriate. The control arm receives usual supportive care, and outcomes will focus on feasibility and preliminary effects on symptom control and related care processes.

Who should consider this trial

Good fit: Adults (≥18) with histologically confirmed breast or colorectal cancer who are scheduled to receive at least three months of systemic chemotherapy and have ECOG performance status 0–2 are ideal candidates.

Not a fit: Patients with severe psychiatric disorders, cognitive impairment that prevents symptom reporting, pre-existing cancer-related symptoms before chemotherapy start, concurrent enrollment in other symptom-management trials, or life expectancy under six months are unlikely to benefit from this intervention.

Why it matters

Potential benefit: If successful, the approach could deliver more timely, standardized symptom management that improves quality of life and helps maintain chemotherapy dose intensity.

How similar studies have performed: Digital health interventions in cancer have shown benefits for quality of life and reduced acute care use, but direct clinical use of large language models for patient-facing symptom management is limited and largely unproven.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Adult patients (≥ 18 years old) diagnosed with histologically confirmed solid malignancies (breast cancer, colorectal cancer)
* Patients scheduled to receive at least 3 months of systemic chemotherapy
* ECOG performance status 0-2

Exclusion Criteria:

* Severe psychiatric disorders
* Cognitive impairment affecting ability to report symptoms
* Presence of cancer-related symptoms prior to chemotherapy initiation
* Concurrent participation in trials evaluating other symptom management interventions Inability to provide informed consent Life expectancy less than 6 months

Where this trial is running

Incheon

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Breast CancerColorectal CancerLarge Language ModelLLMBreast cancerSide effectSupportive carecolorectal cancer
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.