Trial Title:
Treatment Recommendations for Gastrointestinal Cancers Via Large Language Models
NCT ID:
NCT06002425
Condition:
Gastrointestinal Neoplasm Malignant
Conditions: Official terms:
Gastrointestinal Neoplasms
Digestive System Neoplasms
Neoplasms
Conditions: Keywords:
Artificial Intelligence
Large Language Model
Gastrointestinal Cancers
Treatment Recommendation
Study type:
Interventional
Study phase:
N/A
Overall status:
Recruiting
Study design:
Allocation:
Randomized
Intervention model:
Parallel Assignment
Primary purpose:
Treatment
Masking:
Single (Participant)
Intervention:
Intervention type:
Other
Intervention name:
Clinician-Directed Treatment Plan
Description:
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.
Arm group label:
Control group
Intervention type:
Other
Intervention name:
ChatGPT-Assisted Treatment Plan
Description:
In this approach, clinicians utilize the ChatGPT technological tool, formulating
treatment plans for participants based on its suggestions and their own professional
expertise.
Arm group label:
GPT-Assisted Group
Summary:
This study will evaluate the utility of ChatGPT in recommending treatment plans for
patients with gastrointestinal cancers, using both retrospective and prospective data.
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.
Criteria for eligibility:
Criteria:
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.
Gender:
All
Minimum age:
18 Years
Maximum age:
N/A
Healthy volunteers:
No
Locations:
Facility:
Name:
City of Hope
Address:
City:
Duarte
Zip:
91010
Country:
United States
Status:
Not yet recruiting
Contact:
Last name:
Syed Rahmanuddin
Facility:
Name:
Jiangmen Central Hospital
Address:
City:
Jiangmen
Zip:
529000
Country:
China
Status:
Recruiting
Contact:
Last name:
Xiaobei Duan
Facility:
Name:
The Fifth Affiliated Hospital of Sun Yat-sen University
Address:
City:
Zhuhai
Zip:
519000
Country:
China
Status:
Recruiting
Contact:
Last name:
Jing Pang
Contact backup:
Last name:
Guojie Wang
Facility:
Name:
Zhuhai People's Hospital
Address:
City:
Zhuhai
Zip:
519000
Country:
China
Status:
Recruiting
Contact:
Last name:
Jie Zhang, Ph.D.
Facility:
Name:
Peking University Cancer Hospital (Inner Mongolia Campus)
Address:
City:
Hohhot
Zip:
010010
Country:
China
Status:
Recruiting
Contact:
Last name:
Xiaotian Zhang
Contact backup:
Last name:
Zhenghang Wang
Facility:
Name:
University Hospital Magdeburg
Address:
City:
Magdeburg
Zip:
39120
Country:
Germany
Status:
Not yet recruiting
Contact:
Last name:
Michael Kreissl
Facility:
Name:
San Raffaele University Hospital, Italy
Address:
City:
Milan
Zip:
20132
Country:
Italy
Status:
Not yet recruiting
Contact:
Last name:
Diego Palumbo
Start date:
August 29, 2023
Completion date:
December 31, 2028
Lead sponsor:
Agency:
Chinese Academy of Sciences
Agency class:
Other
Collaborator:
Agency:
ZhuHai Hospital
Agency class:
Other
Collaborator:
Agency:
Fifth Affiliated Hospital, Sun Yat-Sen University
Agency class:
Other
Collaborator:
Agency:
Jiangmen Central Hospital
Agency class:
Other
Collaborator:
Agency:
Peking University Cancer Hospital (Inner Mongolia Campus)
Agency class:
Other
Collaborator:
Agency:
San Raffaele University Hospital, Italy
Agency class:
Other
Collaborator:
Agency:
University Hospital Magdeburg, Germany
Agency class:
Other
Collaborator:
Agency:
City of Hope Medical Center
Agency class:
Other
Source:
Chinese Academy of Sciences
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT06002425
