- ICH GCP
- Amerikanska kliniska prövningsregistret
- Klinisk prövning NCT07626736
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
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
Studieöversikt
Status
Betingelser
Intervention / Behandling
Studietyp
Inskrivning (Beräknad)
Fas
- Inte tillämpbar
Kontakter och platser
Studiekontakt
- Namn: qing liang, Dr.
- Telefonnummer: +86 17863321987
- E-post: liangtsing99@163.com
Studieorter
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-
Guangdong
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Guangzhou, Guangdong, Kina, 510000
- Rekrytering
- Guangdong Provincial People's Hospital
-
Kontakt:
- Wenzhao Zhong, Dr.
- Telefonnummer: +8613609777314
- E-post: 13609777314@163.com
-
-
Deltagandekriterier
Urvalskriterier
Åldrar som är berättigade till studier
- Vuxen
- Äldre vuxen
Tar emot friska volontärer
Beskrivning
Inclusion Criteria:
- Age ≥ 18 years;
- MDT (Multidisciplinary Team) discussion deems a systemic treatment plan necessary;
- Complete clinical, imaging, and molecular pathological data.
Exclusion Criteria:
- Stage I patients;
- Diagnosed with a thoracic tumor other than NSCLC;
- Lack of detailed medical data, or missing data;
Studieplan
Hur är studien utformad?
Designdetaljer
- Primärt syfte: Behandling
- Tilldelning: N/A
- Interventionsmodell: Enskild gruppuppgift
- Maskning: Ingen (Open Label)
Vapen och interventioner
Deltagargrupp / Arm |
Intervention / Behandling |
|---|---|
|
Experimentell: AI-Assisted Multidisciplinary Team Decision-Making for Non-Small Cell Lung Cancer
|
The impact of artificial intelligence on clinicians' treatment plans
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Vad mäter studien?
Primära resultatmått
Resultatmått |
Åtgärdsbeskrivning |
Tidsram |
|---|---|---|
|
Consistency rate
Tidsram: Baseline(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).
|
Baseline(MDT 1 Day)
|
Sekundära resultatmått
Resultatmått |
Åtgärdsbeskrivning |
Tidsram |
|---|---|---|
|
MDT Discussion Process Time
Tidsram: Baseline(MDT Day 1)
|
Time from start to end of multidisciplinary team (MDT) discussion, measured immediately after MDT end.
|
Baseline(MDT Day 1)
|
|
Quality of AI Recommendations
Tidsram: Baseline(MDT Day 1)
|
Physician-rated quality of AI recommendations using a Likert 5-point scale (1 = very poor, 5 = excellent).
|
Baseline(MDT Day 1)
|
|
Clinical Acceptability of AI
Tidsram: Baseline(MDT Day 1)
|
Physician-rated clinical acceptability of AI recommendations using a Likert 5-point scale (1 = unacceptable, 5 = fully acceptable).
|
Baseline(MDT Day 1)
|
|
MDT Discussion Efficiency
Tidsram: Baseline(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).
|
Baseline(MDT Day 1)
|
|
Process Convenience
Tidsram: Baseline(MDT Day 1)
|
Physician-rated convenience of the AI-integrated workflow using a Likert 5-point scale (1 = very inconvenient, 5 = very convenient).
|
Baseline(MDT Day 1)
|
|
Added Value to Clinical Decision
Tidsram: Baseline(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).
|
Baseline(MDT Day 1)
|
|
Learning and Training Value
Tidsram: Baseline(MDT Day 1)
|
Physician-rated learning and training value of AI system using a Likert 5-point scale (1 = no value, 5 = high value).
|
Baseline(MDT Day 1)
|
|
Overall Satisfaction
Tidsram: Baseline(MDT Day 1)
|
Physician-rated overall satisfaction with AI-assisted MDT using a Likert 5-point scale (1 = very dissatisfied, 5 = very satisfied).
|
Baseline(MDT Day 1)
|
|
Willingness to Use in Future
Tidsram: Baseline(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).
|
Baseline(MDT Day 1)
|
|
Disease-Free Survival (DFS)
Tidsram: 3 years
|
Time from treatment initiation to disease recurrence or death from any cause, assessed every 3-6 months during 2-3 years follow-up.
|
3 years
|
|
Progression-Free Survival (PFS)
Tidsram: 3 years
|
Time from treatment initiation to disease progression or death from any cause, assessed every 3-6 months during 2-3 years follow-up.
|
3 years
|
|
Overall Survival (OS)
Tidsram: 3 years
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Time from treatment initiation to death from any cause, assessed every 3-6 months during 2-3 years follow-up.
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3 years
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Samarbetspartners och utredare
Sponsor
Samarbetspartners
Publikationer och användbara länkar
Allmänna publikationer
- Pillay B, Wootten AC, Crowe H, Corcoran N, Tran B, Bowden P, Crowe J, Costello AJ. The impact of multidisciplinary team meetings on patient assessment, management and outcomes in oncology settings: A systematic review of the literature. Cancer Treat Rev. 2016 Jan;42:56-72. doi: 10.1016/j.ctrv.2015.11.007. Epub 2015 Nov 24.
- Kim JK, Chua ME, Li TG, Rickard M, Lorenzo AJ. Novel AI applications in systematic review: GPT-4 assisted data extraction, analysis, review of bias. BMJ Evid Based Med. 2025 Sep 22;30(5):313-322. doi: 10.1136/bmjebm-2024-113066.
- Wiegand TLT, Jung LB, Gudera JA, Schuhmacher LS, Moehrle P, Rischewski JF, Mehrzad P, Jeong S, Nguyen LH, Poeschla M, Velezmoro LI, Kruk L, Dimitriadis K, Koerte IK. Demographic inaccuracies and biases in the depiction of patients by artificial intelligence text-to-image generators. NPJ Digit Med. 2025 Jul 19;8(1):459. doi: 10.1038/s41746-025-01817-6.
Studieavstämningsdatum
Studera stora datum
Studiestart (Faktisk)
Primärt slutförande (Beräknad)
Avslutad studie (Beräknad)
Studieregistreringsdatum
Först inskickad
Först inskickad som uppfyllde QC-kriterierna
Första postat (Faktisk)
Uppdateringar av studier
Senaste uppdatering publicerad (Faktisk)
Senaste inskickade uppdateringen som uppfyllde QC-kriterierna
Senast verifierad
Mer information
Termer relaterade till denna studie
Nyckelord
Ytterligare relevanta MeSH-villkor
Andra studie-ID-nummer
- KY2025-1003-02
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