Treatment Recommendations for Gastrointestinal Cancers Via Large Language Models

September 6, 2023 updated by: Di Dong, Chinese Academy of Sciences

Application of Large Language Models in the Recommendation of Treatment Plans for Gastrointestinal Cancers

This study will evaluate the utility of ChatGPT in recommending treatment plans for patients with gastrointestinal cancers, using both retrospective and prospective data.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

The medical records of over 1,200 patients with gastrointestinal cancers will be collected retrospectively from participating hospitals. This data will be split into an exploratory dataset (n=200) and a validation dataset (n>=1,000). Within the exploratory dataset, various prompt methods will be used to determine the treatment plans suggested by ChatGPT. Additionally, several clinicians of varied seniority levels will provide their treatment recommendations. For the validation dataset, ChatGPT's suggestions for treatment plans will undergo both qualitative and quantitative assessments by a multidisciplinary consultation (MDT) team. The recommendations from ChatGPT will then be compared with those from the clinicians.

Furthermore, this study will incorporate a prospective dataset comprising 400 participants with gastrointestinal cancers. The participants will be randomly allocated to either a control group (n=200) or a ChatGPT-Assisted group (n=200). In the control group, treatment plan recommendations will solely be provided by the clinicians and will guide subsequent treatments. In the ChatGPT-Assisted group, initial treatment plan recommendations will be independently proposed by both ChatGPT and the clinicians. Based on ChatGPT's suggestions, clinicians might selectively adjust their initial plans. Participants will then receive treatments as per these refined plans. Within the ChatGPT-Assisted group, the treatment plans of the initial 100 participants will be evaluated to determine the percentage of patients whose treatment plans are influenced by ChatGPT. Subsequently, the proportion of participants in the entire ChatGPT-Assisted group with treatment plans modified by ChatGPT will be calculated. The study will further monitor the 3-year progression-free survival (PFS) and the 5-year overall survival (OS) rates, contrasting the outcomes between the control and ChatGPT-assisted groups.

Study Type

Interventional

Enrollment (Estimated)

400

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Guangdong
      • Jiangmen, Guangdong, China, 529000
        • Recruiting
        • Jiangmen Central Hospital
        • Contact:
          • Xiaobei Duan
      • Zhuhai, Guangdong, China, 519000
        • Recruiting
        • The Fifth Affiliated Hospital of Sun Yat-sen University
        • Contact:
          • Jing Pang
        • Contact:
          • Guojie Wang
      • Zhuhai, Guangdong, China, 519000
        • Recruiting
        • Zhuhai People's Hospital
        • Contact:
          • Jie Zhang, Ph.D.
    • Inner Mongolia
      • Hohhot, Inner Mongolia, China, 010010
        • Recruiting
        • Peking University Cancer Hospital (Inner Mongolia Campus)
        • Contact:
          • Xiaotian Zhang
        • Contact:
          • Zhenghang Wang
  • Germany
    • Saxony-Anhalt
      • Magdeburg, Saxony-Anhalt, Germany, 39120
        • Not yet recruiting
        • University Hospital Magdeburg
        • Contact:
          • Michael Kreissl
  • Italy
      • Milan, Italy, 20132
        • Not yet recruiting
        • San Raffaele University Hospital, Italy
        • Contact:
          • Diego Palumbo
  • United States
    • California
      • Duarte, California, United States, 91010
        • Not yet recruiting
        • City of Hope
        • Contact:
          • Syed Rahmanuddin

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Age ≥18 years, both male and female.
  • Pathologically confirmed diagnosis of gastrointestinal cancer (gastric cancer or colorectal Cancer).
  • Detailed medical records available prior to treatment (including chief complaint, history of present illness, radiological examinations, pathological examinations, laboratory tests, etc.).
  • Participants will receive complete treatment in the participating hospitals.

Exclusion Criteria:

  • Participants with cancers other than gastrointestinal cancers.
  • Participants who receive treatment in multiple hospitals.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Active Comparator: Control group
In this arm, participants receive treatment plans directly from clinicians without the assistance of ChatGPT.
Other: Clinician-Directed Treatment Plan
In this approach, clinicians do not employ any technological assistance and rely solely on their professional expertise and experience to formulate treatment plans for participants.
Experimental: GPT-Assisted Group
In this arm, participants receive treatment plans from clinicians with the assistance of ChatGPT.
Other: ChatGPT-Assisted Treatment Plan
In this approach, clinicians utilize the ChatGPT technological tool, formulating treatment plans for participants based on its suggestions and their own professional expertise.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Influence Rate of ChatGPT on Treatment Plans
Time Frame: Within 24 hours after the treatment plan is determined from the onset of study participation.
The percentage of the initial 100 participants and the overall participants in the ChatGPT-Assisted group whose treatment plans are adjusted by clinicians after consulting with ChatGPT.
Within 24 hours after the treatment plan is determined from the onset of study participation.

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
3-year Progression-Free Survival (PFS) Rate
Time Frame: 3 years
Percentage of participants without disease progression over a period of 3 years from the start of treatment.
3 years

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
5-year Overall Survival (OS) Rate
Time Frame: 5 years
Percentage of participants who are still alive over a period of 5 years from the start of treatment.
5 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Chinese Academy of Sciences

Collaborators

City of Hope Medical Center
Fifth Affiliated Hospital, Sun Yat-Sen University
ZhuHai Hospital
Jiangmen Central Hospital
San Raffaele University Hospital, Italy
Peking University Cancer Hospital (Inner Mongolia Campus)
University Hospital Magdeburg, Germany

Investigators

  • Principal Investigator: Di Dong, PhD, Institute of Automation, Chinese Academy of Sciences

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

August 29, 2023

Primary Completion (Estimated)

September 30, 2023

Study Completion (Estimated)

December 31, 2028

Study Registration Dates

First Submitted

August 13, 2023

First Submitted That Met QC Criteria

August 13, 2023

First Posted (Actual)

August 21, 2023

Study Record Updates

Last Update Posted (Actual)

September 8, 2023

Last Update Submitted That Met QC Criteria

September 6, 2023

Last Verified

September 1, 2023

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • CASMI006

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

Individual participant data (IPD) may be made available to other researchers upon request. Interested researchers should present a reasonable research proposal and a data usage application. All participating units of this study will review and assess the proposal and application to determine whether to share the data.

IPD Sharing Time Frame

Data will become available 6 months after study completion and will remain available for a period of 5 years.

IPD Sharing Access Criteria

Interested researchers should submit a detailed research proposal and a data usage application for review. All participating units of this study will assess the application to determine eligibility for data access.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP
  • ANALYTIC_CODE

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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