Large Language Models to Aid Gynecological Oncology Treatment
EASING
Medical Students and Their Perception of Large Language Models (LLMs) in Gynecologic Oncology
1 other identifier
interventional
68
1 country
1
Brief Summary
This trial aims to assess the impact of providing medical students with access to large language models, in comparison to treatment guideline pdfs, on treatment concordance with a conventional multidisciplinary tumor board
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P25-P50 for not_applicable breast-cancer
Started Jun 2025
Shorter than P25 for not_applicable breast-cancer
1 active site
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
February 11, 2025
CompletedFirst Posted
Study publicly available on registry
March 10, 2025
CompletedStudy Start
First participant enrolled
June 2, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
August 30, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
September 1, 2025
CompletedAugust 26, 2025
August 1, 2025
3 months
February 11, 2025
August 25, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Treatment concordance with tumor board decisions
Participants in each group select treatment modalities for case vignettes
directly (within 10 minutes) after Intervention
Secondary Outcomes (2)
Treatment confidence
directly (within 10 minutes) after Intervention
Time spent for treatment decision
directly (within 10 minutes) after Intervention
Study Arms (2)
Local language model first
OTHERGroup will be given access to local language model first after using ChatGPT
Guideline pdf first
OTHERGroup will be given access to guideline pdf first after using ChatGPT
Interventions
Group will be given access to local language model first after using ChatGPT and then will get access to pdf file
Group will be given access to pdf file after ChatGPT and then to a local language model
Eligibility Criteria
You may qualify if:
- \- Medical students having started with clinical subjects
You may not qualify if:
- \- Not being a medical student
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Institute for Digital Medicine, University Hospital of Giessen and Marburg, Philipps University Marburg
Marburg, 35043, Germany
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Sebastian Griewing, MD PhD
Philipps University Marburg
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- OUTCOMES ASSESSOR
- Purpose
- TREATMENT
- Intervention Model
- CROSSOVER
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
February 11, 2025
First Posted
March 10, 2025
Study Start
June 2, 2025
Primary Completion
August 30, 2025
Study Completion
September 1, 2025
Last Updated
August 26, 2025
Record last verified: 2025-08
Data Sharing
- IPD Sharing
- Will not share