Treatment Recommendations for Gastrointestinal Cancers Via Large Language Models
NCT ID: NCT06002425
Last Updated: 2023-09-08
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
RECRUITING
NA
400 participants
INTERVENTIONAL
2023-08-29
2028-12-31
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
AI Prediction of Gastric Cancer Response to Neoadjuvant Chemotherapy
NCT06035250
Multi-center and Multi-modal Deep Learning Study of Gastric Cancer
NCT05001321
Exploring the Predictive Effect of Intestinal and Oral Microbiota on the Efficacy of Neoadjuvant Radiotherapy and Chemotherapy for Locally Advanced Rectal Cancer Based on Machine Learning
NCT07346729
Predicting Gastric Cancer Response to Chemo With Multimodal AI Model
NCT06451393
Recurrence and Prognosis Prediction Model for Gastric Cancer
NCT07243847
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
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.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
RANDOMIZED
PARALLEL
TREATMENT
SINGLE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Control group
In this arm, participants receive treatment plans directly from clinicians without the assistance of ChatGPT.
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.
GPT-Assisted Group
In this arm, participants receive treatment plans from clinicians with the assistance of ChatGPT.
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.
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
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.
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.
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* 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 who receive treatment in multiple hospitals.
18 Years
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
ZhuHai Hospital
OTHER
Fifth Affiliated Hospital, Sun Yat-Sen University
OTHER
Jiangmen Central Hospital
OTHER
Peking University Cancer Hospital (Inner Mongolia Campus)
UNKNOWN
San Raffaele University Hospital, Italy
OTHER
University Hospital Magdeburg, Germany
UNKNOWN
City of Hope Medical Center
OTHER
Chinese Academy of Sciences
OTHER_GOV
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Di Dong
Professor
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
Di Dong, PhD
Role: PRINCIPAL_INVESTIGATOR
Institute of Automation, Chinese Academy of Sciences
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
City of Hope
Duarte, California, United States
Jiangmen Central Hospital
Jiangmen, Guangdong, China
The Fifth Affiliated Hospital of Sun Yat-sen University
Zhuhai, Guangdong, China
Zhuhai People's Hospital
Zhuhai, Guangdong, China
Peking University Cancer Hospital (Inner Mongolia Campus)
Hohhot, Inner Mongolia, China
University Hospital Magdeburg
Magdeburg, Saxony-Anhalt, Germany
San Raffaele University Hospital, Italy
Milan, , Italy
Countries
Review the countries where the study has at least one active or historical site.
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Facility Contacts
Find local site contact details for specific facilities participating in the trial.
Syed Rahmanuddin
Role: primary
Xiaobei Duan
Role: primary
Jing Pang
Role: primary
Guojie Wang
Role: backup
Jie Zhang, Ph.D.
Role: primary
Xiaotian Zhang
Role: primary
Zhenghang Wang
Role: backup
Michael Kreissl
Role: primary
Diego Palumbo
Role: primary
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
CASMI006
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.