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
Age ≥ 18 years;
MDT (Multidisciplinary Team) discussion deems a systemic treatment plan necessary;
Complete clinical, imaging, and molecular pathological data.
Stage I patients;
Diagnosed with a thoracic tumor other than NSCLC;
Lack of detailed medical data, or missing data;
Single group
Treat Regimen
Diagnostic testThe impact of artificial intelligence on clinicians' treatment plans
Consistency rate
Consistency rate between Option 1 and Option 2 (calculated using Kappa value). Consistency rate between Option 1 and Option 3 (decision modification rate).
MDT Discussion Process Time
Time from start to end of multidisciplinary team (MDT) discussion, measured immediately after MDT end.
Quality of AI Recommendations
Physician-rated quality of AI recommendations using a Likert 5-point scale (1 = very poor, 5 = excellent).
Clinical Acceptability of AI
Physician-rated clinical acceptability of AI recommendations using a Likert 5-point scale (1 = unacceptable, 5 = fully acceptable).
MDT Discussion Efficiency
Physician-rated efficiency of MDT discussion process aided by AI using a Likert 5-point scale (1 = very inefficient, 5 = very efficient).
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Wen-zhao ZHONG
Lead sponsor
Guangdong Provincial People's Hospital
Sponsor institution
Guangdong Provincial People's Hospital
Collaborator
