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AI reads scans and genes to predict lung cancer drug success

NCT ID NCT07287904

Knowledge-focused Sponsor: Union Hospital, Tongji Medical College, Huazhong University of Science and Technology 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 This study
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
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study uses artificial intelligence to analyze CT scans, pathology slides, and genetic reports from 1,000 lung cancer patients with EGFR mutations. The goal is to build a model that predicts how well targeted therapy will work after surgery. If successful, it could help doctors choose the best treatment for each patient.

What this could mean

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

What this could lead to
If successful, this AI model could help doctors better predict which lung cancer patients will benefit most from targeted therapy, leading to more personalized treatment.
What could go wrong
This is a retrospective study, meaning it looks back at past data, not a prospective trial. The AI model may not work as well in real-world settings or on new patients.

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.

Participants

About 1,000 people

The number the study aims to enrol. It can still change while the study runs.

Expected to start

Dec 2025

An estimate. Start dates often move.

Expected to finish

Aug 2027

An estimate. End dates often move.

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.

Who is studied

Retrospectively included data from 1000 patients diagnosed with stage IB-IIIA invasive lung adenocarcinoma with EGFR mutations who underwent radical surgery from January 2021 to December 2024.

Ages

18 to 80 years

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

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: 1. Age 18-80 years, undergoing radical surgery for lung cancer (R0 resection); 2. Postoperative pathological stage IB-IIIA, pathology confirmed as adenocarcinoma; 3. EGFR gene testing positive, EGFR 19del/L858R mutation; 4. Receiving postoperative EGFR-TKI targeted adjuvant therapy; 5. Complete and clear preoperative imaging data, genetic testing report, and pathology report available. Exclusion Criteria: 1. Patients negative for EGFR; 2. Incomplete surgical resection (R1, R2); 3. Did not receive EGFR-TKI targeted therapy after surgery; 4. Recurrent or advanced stage patients; 5. Incomplete preoperative or postoperative data; 6. Patients who died within 30 days post-surgery.

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Conditions

The condition(s) this trial relates to.

Adenocarcinoma of Lung lung adenocarcinoma lung cancer lung neoplasm non-small cell lung carcinoma

As listed by the trial registrant

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

Adenocarcinoma lung EGFR activating mutation Lung cancer (NSCLC) Postoperative adjuvant therapy

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • Wuhan Union Hospital

    Wuhan, Hubei, 430022, China

More trials for these conditions

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