Clinical trial Recruiting at 1 site Interventional Ages 18 and up

AI helps a multidisciplinary team decide NSCLC treatment

Official title: Evaluating the Efficacy and Safety of AI Localization Models in Multidisciplinary Team Care for NSCLC: a Prospective, Controlled Clinical Trial Protocol

Run by Guangdong Provincial People's Hospital · NCT07626736 · Data updated 2026-11-12

This study tests whether a local AI decision-support model can match or influence treatment choices made by a traditional MDT for non-small cell lung cancer patients.

Quick facts

Study typeInterventional
Ages18 Years and up
SexAll
Enrollment300 (estimated)
SponsorGuangdong Provincial People's Hospital
Academic / other
Locations1 site (Guangzhou, Guangdong)
StatusRecruiting
StartedDecember 1, 2025
Main results expectedOctober 31, 2027
Study endsDecember 31, 2028
Registry record updatedJune 4, 2026
Trial IDNCT07626736 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Adults with non-small cell lung cancer for whom the MDT determines a systemic treatment plan is needed and who have complete clinical, imaging, and molecular data.

Probably not a fit

Patients with incomplete data, early-stage disease (Stage I), or other thoracic tumors are less likely to benefit from this AI-assisted approach.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This trial compares treatment recommendations from a conventional multidisciplinary team with those generated by a locally deployed AI model, and then examines how clinicians adjust their final plan after seeing the AI output. It uses patients’ clinical, imaging, and molecular data to produce independent recommendations from the MDT and the AI, with a final clinician-determined treatment plan after AI review. The study aims to measure agreement, decision modification rates, and efficiency of decision-making in NSCLC care. It does not specify a randomized design or phase, focusing on assessment of concordance and safety in real-world MDT workflows.

Why it matters

Potential benefit: If successful, the approach could streamline MDT decision-making and help ensure consistent treatment recommendations for NSCLC.

How similar studies have gone: Previous work in AI-assisted treatment planning has shown potential in aligning recommendations with clinician consensus, though results vary by context and data quality.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

1. Age ≥ 18 years;
2. MDT (Multidisciplinary Team) discussion deems a systemic treatment plan necessary;
3. Complete clinical, imaging, and molecular pathological data.

Exclusion Criteria:

1. Stage I patients;
2. Diagnosed with a thoracic tumor other than NSCLC;
3. Lack of detailed medical data, or missing data;

Where it's running

  • Guangdong Provincial People's Hospital
    Guangzhou, Guangdong, China
    Recruiting

Study contacts

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How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.