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Evaluating the Efficacy and Safety of AI Localization Models in Multidisciplinary Team Care for NSCLC

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

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07626736
Enrollment
300
Registered
2026-06-04
Start date
2025-12-01
Completion date
2028-12-31
Last updated
2026-06-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Nonsmall Cell Lung Cancer

Keywords

Non-Small Cell Lung Cancer, Multidisciplinary Team, Locally Deployed AI Model, Large Language Model, Treatment Decision-Making

Brief summary

The goal of this clinical trial is to evaluate the effectiveness and safety of a locally deployed artificial intelligence (AI) decision-support model in the multidisciplinary team (MDT) process for patients with non-small cell lung cancer (NSCLC). The main questions it aims to answer : What is the level of agreement between treatment recommendations generated by the AI model and those made by a traditional MDT? How often do clinicians modify their final treatment decision after reviewing the AI model's recommendation? Researchers will compare treatment plans from the traditional MDT (Arm 1), the AI model (Arm 2), and the clinician's final decision after reviewing the AI output (Arm 3) to assess consistency, decision modification rates, and clinical efficiency. Participants will: Have their clinical, imaging, and molecular data submitted to both the traditional MDT and the AI model for independent treatment recommendations Receive a final treatment plan determined by clinicians after reviewing both recommendations, with follow-up for safety and survival outcomes

Interventions

DIAGNOSTIC_TESTTreat Regimen

The impact of artificial intelligence on clinicians' treatment plans

Sponsors

Wen-zhao ZHONG
Lead SponsorOTHER
Guangdong Provincial People's Hospital
CollaboratorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
TREATMENT
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

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;

Design outcomes

Primary

MeasureTime frameDescription
Consistency rateBaseline(MDT 1 Day)Consistency rate between Option 1 and Option 2 (calculated using Kappa value). Consistency rate between Option 1 and Option 3 (decision modification rate).

Secondary

MeasureTime frameDescription
MDT Discussion Process TimeBaseline(MDT Day 1)Time from start to end of multidisciplinary team (MDT) discussion, measured immediately after MDT end.
Quality of AI RecommendationsBaseline(MDT Day 1)Physician-rated quality of AI recommendations using a Likert 5-point scale (1 = very poor, 5 = excellent).
Clinical Acceptability of AIBaseline(MDT Day 1)Physician-rated clinical acceptability of AI recommendations using a Likert 5-point scale (1 = unacceptable, 5 = fully acceptable).
MDT Discussion EfficiencyBaseline(MDT Day 1)Physician-rated efficiency of MDT discussion process aided by AI using a Likert 5-point scale (1 = very inefficient, 5 = very efficient).
Process ConvenienceBaseline(MDT Day 1)Physician-rated convenience of the AI-integrated workflow using a Likert 5-point scale (1 = very inconvenient, 5 = very convenient).
Added Value to Clinical DecisionBaseline(MDT Day 1)Physician-rated added value of AI to clinical decision-making using a Likert 5-point scale (1 = no added value, 5 = significant added value).
Learning and Training ValueBaseline(MDT Day 1)Physician-rated learning and training value of AI system using a Likert 5-point scale (1 = no value, 5 = high value).
Overall SatisfactionBaseline(MDT Day 1)Physician-rated overall satisfaction with AI-assisted MDT using a Likert 5-point scale (1 = very dissatisfied, 5 = very satisfied).
Willingness to Use in FutureBaseline(MDT Day 1)Physician-rated willingness to use AI system in future clinical practice using a Likert 5-point scale (1 = definitely not willing, 5 = definitely willing).
Disease-Free Survival (DFS)3 yearsTime from treatment initiation to disease recurrence or death from any cause, assessed every 3-6 months during 2-3 years follow-up.
Progression-Free Survival (PFS)3 yearsTime from treatment initiation to disease progression or death from any cause, assessed every 3-6 months during 2-3 years follow-up.
Overall Survival (OS)3 yearsTime from treatment initiation to death from any cause, assessed every 3-6 months during 2-3 years follow-up.

Countries

China

Contacts

CONTACTqing liang, Dr.
liangtsing99@163.com+86 17863321987

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Jun 5, 2026