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 type | Interventional |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 300 (estimated) |
| Sponsor | Guangdong Provincial People's Hospital Academic / other |
| Locations | 1 site (Guangzhou, Guangdong) |
| Status | Recruiting |
| Started | December 1, 2025 |
| Main results expected | October 31, 2027 |
| Study ends | December 31, 2028 |
| Registry record updated | June 4, 2026 |
| Trial ID | NCT07626736 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
- Study coordinator: qing liang, Dr.
- Email: liangtsing99@163.com
- Phone: +86 17863321987
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.