- ICH GCP
- Amerikanska kliniska prövningsregistret
- Klinisk prövning NCT07654036
Preliminary Evaluation of a Large Language Model-Based Tool for Complex Surgical Decision Support in Lung Cancer
13 juni 2026 uppdaterad av: XiuYuan Chen, Peking University People's Hospital
This study is an exploratory effect-size estimation study, with the following specific objectives: ① to estimate the point estimate and 95% confidence interval of the Win Ratio for the experimental group (GAPS-Agent) versus the control group (large language model) in blinded pairwise preference judgments by thoracic surgery expert adjudicators, to serve as a sample size planning parameter for subsequent multicenter confirmatory clinical trials; ② to preliminarily evaluate the value of GAPS-Agent within clinical workflows.The hypothesis of this study is as follows: compared with a general-purpose large language model without medical enhancement (control group), a structured agentic workflow optimized on the basis of the GAPS evaluation framework (GAPS-Agent, experimental group) can help junior resident physicians generate clinical decision plans for complex lung cancer cases that are more strongly preferred by senior thoracic surgery expert adjudicators.
Studieöversikt
Status
Anmälan via inbjudan
Betingelser
Intervention / Behandling
Studietyp
Interventionell
Inskrivning (Beräknad)
12
Fas
- Inte tillämpbar
Kontakter och platser
Det här avsnittet innehåller kontaktuppgifter för dem som genomför studien och information om var denna studie genomförs.
Studieorter
-
-
Beijing Municipality
-
Beijing, Beijing Municipality, Kina, 100044
- Peking University People's Hospital
-
-
Deltagandekriterier
Forskare letar efter personer som passar en viss beskrivning, så kallade behörighetskriterier. Några exempel på dessa kriterier är en persons allmänna hälsotillstånd eller tidigare behandlingar.
Urvalskriterier
Åldrar som är berättigade till studier
- Vuxen
- Äldre vuxen
Tar emot friska volontärer
Nej
Beskrivning
Inclusion Criteria:
Resident Physician Subjects:
- Holds a valid and legally effective Physician Practice License of the People's Republic of China;
- Currently holds the rank of resident physician in a thoracic surgery department at a tertiary Class A (3A) hospital;
- Agrees to complete all assessment tasks of the main study phase in accordance with the study protocol;
- Can guarantee the time and effort required to complete all assessment tasks of the main study.
Study Cases:
- The case was discussed at the Thoracic Oncology Multidisciplinary Team (MDT) conference of Peking University People's Hospital between January 2025 and May 2026;
- The current version of the NCCN guidelines does not provide an explicit recommendation covering the management of the case;
- Does not overlap with the GAPS evaluation set;
- The case is presented in pure text in a structured format, with all direct and indirect identifiers removed and complete de-identification performed prior to inclusion;
- From the pool of eligible cases, 12 cases will be randomly drawn using Python (numpy.random, with a fixed and archived seed) to serve as the main study cases. The cases will cover 6 themes (chest mass of undetermined diagnosis, early-stage lung cancer, locally advanced lung cancer, oligometastatic/oligoprogressive disease, special intraoperative situations, and tumor recurrence), with 2 cases per theme.
Adjudication Expert Panel:
- Holds a valid and legally effective Physician Practice License of the People's Republic of China;
- Currently holds the rank of attending physician or above in a thoracic surgery department at a tertiary Class A hospital;
- Chairs or regularly participates in lung cancer multidisciplinary team (MDT) work in their department.
Exclusion Criteria:
Resident Physician Subjects:
- Has previously participated in the construction of the GAPS evaluation set or the development of GAPS-Agent;
- Unable to complete the tasks of the study phase.
Study Cases:
- Key case information is missing, such as text-form data on pathology (including IHC/NGS), imaging, laboratory tests, prior medical history, comorbidities, or PS score;
- Decision-making for the case is strictly dependent on non-text information.
Adjudication Expert Panel:
- Participated in the construction of the GAPS evaluation set, the content validity verification, or the development of GAPS-Agent for this study;
- Has a direct conflict of interest with any specific product among the two-arm tools of this study.
Studieplan
Det här avsnittet ger detaljer om studieplanen, inklusive hur studien är utformad och vad studien mäter.
Hur är studien utformad?
Designdetaljer
- Primärt syfte: Övrig
- Tilldelning: Randomiserad
- Interventionsmodell: Parallellt uppdrag
- Maskning: Enda
Vapen och interventioner
Deltagargrupp / Arm |
Intervention / Behandling |
|---|---|
|
Experimentell: test arm
GAPS-Agent
|
The research group has previously developed the GAPS evaluation framework for complex clinical decision-making in lung cancer.
In this framework, G (Grounding) characterizes the cognitive depth of decision-making (ranging from knowledge retrieval to decisions that go beyond clinical guidelines), A (Authority) corresponds to the grading of evidence strength, P (Perturbation) describes the identification and management of real-world clinical confounding factors, and S (Strength) corresponds to the calibration of recommendation strength.
Within this framework, the research group has completed the construction of a 100-item complex lung cancer decision-making evaluation set along with its corresponding rubrics, and has invited multiple thoracic oncology experts to complete content validity validation.
Based on this, the research group developed GAPS-Agent, which uses an open-source large language model as its foundation and integrates functional modules such as guideline and evidence retri
|
|
Aktiv komparator: control arm
LLM
|
Open source large language model that is not specifically enhanced in medical field.
|
Vad mäter studien?
Primära resultatmått
Resultatmått |
Åtgärdsbeskrivning |
Tidsram |
|---|---|---|
|
Overall plan Win Ratio
Tidsram: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
A total of 10 blinded expert judges made Win/Tie/Loss ternary preference judgments on 192 paired scheme comparisons in terms of overall scheme quality.
The win ratio was calculated as Wins ÷ Losses, and the 95% confidence interval was estimated using a two-level (physician × case) cluster bootstrap resampling method (B = 10,000, quantile method on the log scale).
|
Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
Sekundära resultatmått
Resultatmått |
Åtgärdsbeskrivning |
Tidsram |
|---|---|---|
|
Inter-rater agreement
Tidsram: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
For the ternary preference judgment results of 10 expert judges across 192 paired comparisons and 6 evaluation domains, Fleiss' kappa was used to assess inter-rater agreement.
The kappa value and its 95% confidence interval are reported for each evaluation domain.
|
Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
|
Redundancy Win Ratio
Tidsram: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
A total of 10 blinded expert judges made Win/Tie/Loss ternary preference judgments on 192 paired scheme comparisons in terms of overall scheme quality.
The win ratio was calculated as Wins ÷ Losses, and the 95% confidence interval was estimated using a two-level (physician × case) cluster bootstrap resampling method (B = 10,000, quantile method on the log scale).
|
Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
|
Evidence-based medicine adherence Win Ratio
Tidsram: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
A total of 10 blinded expert judges made Win/Tie/Loss ternary preference judgments on 192 paired scheme comparisons in terms of overall scheme quality.
The win ratio was calculated as Wins ÷ Losses, and the 95% confidence interval was estimated using a two-level (physician × case) cluster bootstrap resampling method (B = 10,000, quantile method on the log scale).
|
Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
|
Actionability Win Ratio
Tidsram: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
A total of 10 blinded expert judges made Win/Tie/Loss ternary preference judgments on 192 paired scheme comparisons in terms of overall scheme quality.
The win ratio was calculated as Wins ÷ Losses, and the 95% confidence interval was estimated using a two-level (physician × case) cluster bootstrap resampling method (B = 10,000, quantile method on the log scale).
|
Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
|
Completeness Win Ratio
Tidsram: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
A total of 10 blinded expert judges made Win/Tie/Loss ternary preference judgments on 192 paired scheme comparisons in terms of overall scheme quality.
The win ratio was calculated as Wins ÷ Losses, and the 95% confidence interval was estimated using a two-level (physician × case) cluster bootstrap resampling method (B = 10,000, quantile method on the log scale).
|
Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
|
Safety Win Ratio
Tidsram: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
A total of 10 blinded expert judges made Win/Tie/Loss ternary preference judgments on 192 paired scheme comparisons in terms of overall scheme quality.
The win ratio was calculated as Wins ÷ Losses, and the 95% confidence interval was estimated using a two-level (physician × case) cluster bootstrap resampling method (B = 10,000, quantile method on the log scale).
|
Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
|
|
GAPS automated rubric score
Tidsram: Generated up to 3 weeks after residents finished their plan generation.
|
A third-party large language model, independent of the two study arms' base models, served as the judge model and automatically scored all 96 plans according to the GAPS rubric.
|
Generated up to 3 weeks after residents finished their plan generation.
|
|
Subject physician's self-confidence score
Tidsram: Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
|
After submitting each case plan, the participating physicians self-rated their confidence in their own plan using a 1-5 point Likert scale.
|
Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
|
|
Tool satisfaction score
Tidsram: Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
|
After submitting each case plan, the participating physicians rated their satisfaction with the tool using a 1-5 point Likert scale.
|
Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
|
|
Tool trustworthiness score
Tidsram: Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
|
After submitting each case plan, the participating physicians rated the tool's credibility using a 1-5 point Likert scale.
|
Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
|
|
Decision-making time
Tidsram: Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
|
The time taken (in minutes) by each participating physician to complete the production of each case plan was automatically recorded by the evaluation platform.
Differences between groups were analyzed using a linear mixed-effects model.
|
Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
|
Samarbetspartners och utredare
Det är här du hittar personer och organisationer som är involverade i denna studie.
Studieavstämningsdatum
Dessa datum spårar framstegen för inlämningar av studieposter och sammanfattande resultat till ClinicalTrials.gov. Studieposter och rapporterade resultat granskas av National Library of Medicine (NLM) för att säkerställa att de uppfyller specifika kvalitetskontrollstandarder innan de publiceras på den offentliga webbplatsen.
Studera stora datum
Studiestart (Faktisk)
10 juni 2026
Primärt slutförande (Beräknad)
21 juni 2026
Avslutad studie (Beräknad)
21 juni 2026
Studieregistreringsdatum
Först inskickad
10 juni 2026
Först inskickad som uppfyllde QC-kriterierna
13 juni 2026
Första postat (Faktisk)
17 juni 2026
Uppdateringar av studier
Senaste uppdatering publicerad (Faktisk)
17 juni 2026
Senaste inskickade uppdateringen som uppfyllde QC-kriterierna
13 juni 2026
Senast verifierad
1 juni 2026
Mer information
Termer relaterade till denna studie
Ytterligare relevanta MeSH-villkor
Andra studie-ID-nummer
- 2026PHB458-001
Plan för individuella deltagardata (IPD)
Planerar du att dela individuella deltagardata (IPD)?
NEJ
Läkemedels- och apparatinformation, studiedokument
Studerar en amerikansk FDA-reglerad läkemedelsprodukt
Nej
Studerar en amerikansk FDA-reglerad produktprodukt
Nej
Denna information hämtades direkt från webbplatsen clinicaltrials.gov utan några ändringar. Om du har några önskemål om att ändra, ta bort eller uppdatera dina studieuppgifter, vänligen kontakta register@clinicaltrials.gov. Så snart en ändring har implementerats på clinicaltrials.gov, kommer denna att uppdateras automatiskt även på vår webbplats .
Kliniska prövningar på Lungcancer (NSCLC)
-
First Affiliated Hospital of Wenzhou Medical UniversityHar inte rekryterat ännuAdvanced Non-Small Cell Lung Cancer (NSCLC)
-
Wen-zhao ZHONGRekrytering
-
CSPC Megalith Biopharmaceutical Co.,Ltd.Har inte rekryterat ännu
-
Tianjin Medical University Cancer Institute and...Rekrytering
-
Shanghai Chest HospitalHar inte rekryterat ännu
-
Jiangsu Province Nanjing Brain HospitalRekrytering
-
Radboud University Medical CenterPfizer; ImaginAb, Inc.; University Hospital TuebingenHar inte rekryterat ännuNSCLCTyskland, Nederländerna
-
Guangdong Provincial People's HospitalAktiv, inte rekryterande
-
Shanghai Zhongshan HospitalAvslutad
-
TYK Medicines, IncAvslutad
Kliniska prövningar på GAPS-Agent
-
Postgraduate Institute of Dental Sciences RohtakRekrytering
-
Universitas DiponegoroRekryteringAkut lungemboli (PE)Indonesien
-
Wyeth is now a wholly owned subsidiary of PfizerAvslutad
-
University of VictoriaAvslutad
-
Assiut UniversityHar inte rekryterat ännuBedöm sambandet mellan glykemisk gab och negativa kliniska resultat hos diabetespatienter som inlagda på sjukhus med hjärtsvikt
-
Wyeth is now a wholly owned subsidiary of PfizerAvslutad
-
Virginia Commonwealth UniversityEunice Kennedy Shriver National Institute of Child Health and Human Development...RekryteringVåld i tonårenFörenta staterna
-
Wyeth is now a wholly owned subsidiary of PfizerAvslutadFriska ämnenFörenta staterna
-
Universidad Autonoma de MadridIlustre Colegio Profesional de Fisioterapeutas de la Comunidad de MadridHar inte rekryterat ännuMuskuloskeletal smärta | Kronisk smärta | Primärsjukvård | Vårdsamordning | Kronisk icke-cancer smärtaSpanien
-
Medical College of WisconsinRekrytering