Clinical trial Recruiting at 1 site Observational Ages 18 and up

Concordance between a Large Language Model and a Multidisciplinary Team for Rectal Cancer

Official title: A Prospective Single-Center Observational Study Evaluating Concordance Between Large Language Model-Generated Recommendations and Multidisciplinary Team Recommendations in Rectal Cancer

Run by Shandong Cancer Hospital and Institute · NCT07595107 · Data updated 2026-11-12

A large language model will generate treatment recommendations for rectal cancer patients, and researchers will compare those to the real multidisciplinary team recommendations to see how closely they match.

Quick facts

Study typeObservational
Ages18 Years and up
SexAll
Enrollment180 (estimated)
SponsorShandong Cancer Hospital and Institute
Academic / other
Locations1 site (Jinan, Shandong)
StatusRecruiting
StartedJune 1, 2026
Main results expectedJune 1, 2027
Study endsDecember 1, 2027
Registry record updatedOctober 15, 2026
Trial IDNCT07595107 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Adults (18+) with pathologically confirmed rectal adenocarcinoma who are scheduled for routine MDT discussion and have complete standardized decision-making information available.

Probably not a fit

Patients with incomplete data, unusual cases, or cases where MDT decisions are highly individualized may not benefit from AI concordance.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This is a prospective, single-center observational study involving adults with pathologically confirmed rectal adenocarcinoma who are scheduled for a standard multidisciplinary team discussion. For each case, a de-identified clinical summary is prepared and used both by the local large language model and by the actual MDT, with the LLM’s recommendation kept hidden from clinicians. Concordance will be measured using predefined rules and blinded expert review. The study aims to assess the potential role of AI-based decision support in complex rectal cancer management. Management considerations include tumor location, MRI findings, staging, margins, invasion, nodal status, prior treatments, feasibility of surgery, organ preservation, and patient preferences.

Why it matters

Potential benefit: If the LLM concordance is high, AI-supported tools could help streamline MDT workflows and support decision-making in rectal cancer care.

How similar studies have gone: Prior work shows AI tools can process clinical information; however, performance in complex oncologic decision-making like rectal cancer remains to be validated.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

1. Age 18 years or older.
2. Pathologically confirmed rectal adenocarcinoma.
3. Scheduled for routine rectal cancer multidisciplinary team discussion at the study center.
4. Availability of complete or substantially complete standardized decision-making information before multidisciplinary team discussion, including clinical, pathological, and key imaging information.
5. Availability of a structured pelvic magnetic resonance imaging report meeting the requirements of the institutional rectal cancer multidisciplinary team, including at least tumor location, clinical T stage, clinical N stage, circumferential resection margin or mesorectal fascia status, extramural vascular invasion status, and lateral lymph node status.
6. Presence of a defined clinical treatment decision question.
7. Clinical data can be sufficiently de-identified for research use.

Exclusion Criteria:

1. Severely incomplete clinical information preventing preparation of a standardized case summary.
2. Non-rectal primary tumor.
3. Routine follow-up cases without a defined treatment decision question.
4. Absence of a structured pelvic magnetic resonance imaging report meeting the requirements of the institutional rectal cancer multidisciplinary team, or missing pelvic magnetic resonance imaging elements that preclude key rectal cancer decision-making.
5. Cases containing sensitive information considered unsuitable for large language model input by the study team.
6. Cases in which a definitive treatment decision has already been made before the multidisciplinary team discussion and the meeting serves only as a formal review.

Where it's running

  • Department of Radiation Oncology, Shandong Cancer Hospital and Institute
    Jinan, Shandong, China
    Recruiting

Study contacts

  • Principal investigator: Jinbo Yue, MD, PhD — Shandong Cancer Hospital and Institute
  • Study coordinator: Jinbo Yue, MD, PhD
  • Email: jbyue@sdfmu.edu.cn
  • Phone: 053167626929

Similar studies

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How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 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.