Treatment Recommendations for Gastrointestinal Cancers Via Large Language Models
Application of Large Language Models in the Recommendation of Treatment Plans for Gastrointestinal Cancers
1 other identifier
interventional
400
4 countries
7
Brief Summary
This study will evaluate the utility of ChatGPT in recommending treatment plans for patients with gastrointestinal cancers, using both retrospective and prospective data.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Aug 2023
Longer than P75 for not_applicable
7 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
August 13, 2023
CompletedFirst Posted
Study publicly available on registry
August 21, 2023
CompletedStudy Start
First participant enrolled
August 29, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
September 30, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2028
ExpectedSeptember 8, 2023
September 1, 2023
1 month
August 13, 2023
September 6, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Influence Rate of ChatGPT on Treatment Plans
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 Outcomes (1)
3-year Progression-Free Survival (PFS) Rate
3 years
Other Outcomes (1)
5-year Overall Survival (OS) Rate
5 years
Study Arms (2)
Control group
ACTIVE COMPARATORIn this arm, participants receive treatment plans directly from clinicians without the assistance of ChatGPT.
GPT-Assisted Group
EXPERIMENTALIn this arm, participants receive treatment plans from clinicians with the assistance of ChatGPT.
Interventions
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.
In this approach, clinicians utilize the ChatGPT technological tool, formulating treatment plans for participants based on its suggestions and their own professional expertise.
Eligibility Criteria
You may qualify if:
- 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.
You may not qualify if:
- Participants with cancers other than gastrointestinal cancers.
- Participants who receive treatment in multiple hospitals.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Chinese Academy of Scienceslead
- ZhuHai Hospitalcollaborator
- Fifth Affiliated Hospital, Sun Yat-Sen Universitycollaborator
- Jiangmen Central Hospitalcollaborator
- Peking University Cancer Hospital (Inner Mongolia Campus)collaborator
- San Raffaele University Hospital, Italycollaborator
- University Hospital Magdeburg, Germanycollaborator
- City of Hope Medical Centercollaborator
Study Sites (7)
City of Hope
Duarte, California, 91010, United States
Jiangmen Central Hospital
Jiangmen, Guangdong, 529000, China
The Fifth Affiliated Hospital of Sun Yat-sen University
Zhuhai, Guangdong, 519000, China
Zhuhai People's Hospital
Zhuhai, Guangdong, 519000, China
Peking University Cancer Hospital (Inner Mongolia Campus)
Hohhot, Inner Mongolia, 010010, China
University Hospital Magdeburg
Magdeburg, Saxony-Anhalt, 39120, Germany
San Raffaele University Hospital, Italy
Milan, 20132, Italy
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Di Dong, PhD
Institute of Automation, Chinese Academy of Sciences
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- PARTICIPANT
- Purpose
- TREATMENT
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER GOV
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor
Study Record Dates
First Submitted
August 13, 2023
First Posted
August 21, 2023
Study Start
August 29, 2023
Primary Completion
September 30, 2023
Study Completion (Estimated)
December 31, 2028
Last Updated
September 8, 2023
Record last verified: 2023-09
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP, ANALYTIC CODE
- Time Frame
- Data will become available 6 months after study completion and will remain available for a period of 5 years.
- 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.
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.