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AI vs. PDFs: which tool helps future doctors pick the right cancer treatment?

NCT ID NCT06865534

Knowledge-focused Sponsor: Philipps University Marburg Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed This study
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Aug 19, 2026 · Last updated Aug 20, 2026 · Updated 1 time

Summary

This trial asks whether giving medical students access to large language models (like ChatGPT) helps them choose cancer treatments that align with expert tumor board decisions, compared to using standard treatment guideline PDFs. Around 70 medical students will review case vignettes of gynecologic cancers and select treatments, with their choices and confidence measured. The goal is to see if AI tools can serve as effective decision-support aids in medical education and oncology practice.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
Large language model (LLM) and treatment guideline PDFs
What this could lead to
If LLMs help medical students make treatment decisions that better match expert tumor board recommendations, this could point toward AI as a useful training and decision-support tool in oncology.
What could go wrong
This is a small, early-stage study with 70 participants, and it measures hypothetical decisions on case vignettes, not real patient outcomes. LLMs may also provide inaccurate or biased information, so results may not reflect real-world clinical use.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Phase

Not a phased trial

Phase numbers describe drug development. The registry uses this when they do not apply, as it does for trials of devices, procedures or behaviour changes, and for observational studies.

Participants

70 people

The number who actually took part.

Started

May 2026

Finished

Aug 2026

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: \- Medical students having started with clinical subjects Exclusion Criteria: \- Not being a medical student

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Conditions

The condition(s) this trial relates to.

breast cancer breast neoplasm

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Breast cancer

Contacts and locations

Locations

  • Institute for Digital Medicine, University Hospital of Giessen and Marburg, Philipps University Marburg

    Marburg, 35043, Germany

More trials for these conditions

Other studies related to the condition(s) this trial covers.