- ICH GCP
- US Clinical Trials Registry
- Klinisk utprøving NCT07654036
Preliminary Evaluation of a Large Language Model-Based Tool for Complex Surgical Decision Support in Lung Cancer
13. juni 2026 oppdatert 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.
Studieoversikt
Status
Påmelding etter invitasjon
Intervensjon / Behandling
Studietype
Intervensjonell
Registrering (Antatt)
12
Fase
- Ikke aktuelt
Kontakter og plasseringer
Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.
Studiesteder
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Beijing Municipality
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Beijing, Beijing Municipality, Kina, 100044
- Peking University People's Hospital
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Deltakelseskriterier
Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.
Kvalifikasjonskriterier
Alder som er kvalifisert for studier
- Voksen
- Eldre voksen
Tar imot friske frivillige
Nei
Beskrivelse
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
Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.
Hvordan er studiet utformet?
Designdetaljer
- Primært formål: Annen
- Tildeling: Randomisert
- Intervensjonsmodell: Parallell tildeling
- Masking: Enkelt
Våpen og intervensjoner
Deltakergruppe / Arm |
Intervensjon / Behandling |
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Eksperimentell: test arm
GAPS-Agent
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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
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Aktiv komparator: control arm
LLM
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Open source large language model that is not specifically enhanced in medical field.
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Hva måler studien?
Primære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
Tidsramme |
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Overall plan Win Ratio
Tidsramme: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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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).
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Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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Sekundære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
Tidsramme |
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Inter-rater agreement
Tidsramme: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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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.
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Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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Redundancy Win Ratio
Tidsramme: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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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).
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Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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Evidence-based medicine adherence Win Ratio
Tidsramme: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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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).
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Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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Actionability Win Ratio
Tidsramme: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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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).
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Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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Completeness Win Ratio
Tidsramme: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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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).
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Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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Safety Win Ratio
Tidsramme: Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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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).
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Measured at the time when experts completed their preference judgements. Calculated up to 3 weeks after the preference judgements.
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GAPS automated rubric score
Tidsramme: Generated up to 3 weeks after residents finished their plan generation.
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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.
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Generated up to 3 weeks after residents finished their plan generation.
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Subject physician's self-confidence score
Tidsramme: Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
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After submitting each case plan, the participating physicians self-rated their confidence in their own plan using a 1-5 point Likert scale.
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Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
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Tool satisfaction score
Tidsramme: Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
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After submitting each case plan, the participating physicians rated their satisfaction with the tool using a 1-5 point Likert scale.
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Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
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Tool trustworthiness score
Tidsramme: Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
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After submitting each case plan, the participating physicians rated the tool's credibility using a 1-5 point Likert scale.
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Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
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Decision-making time
Tidsramme: Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
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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.
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Completed at the time when residents submitted their plans. Calculated up to 3 weeks after the submission.
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Samarbeidspartnere og etterforskere
Det er her du vil finne personer og organisasjoner som er involvert i denne studien.
Studierekorddatoer
Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.
Studer hoveddatoer
Studiestart (Faktiske)
10. juni 2026
Primær fullføring (Antatt)
21. juni 2026
Studiet fullført (Antatt)
21. juni 2026
Datoer for studieregistrering
Først innsendt
10. juni 2026
Først innsendt som oppfylte QC-kriteriene
13. juni 2026
Først lagt ut (Faktiske)
17. juni 2026
Oppdateringer av studieposter
Sist oppdatering lagt ut (Faktiske)
17. juni 2026
Siste oppdatering sendt inn som oppfylte QC-kriteriene
13. juni 2026
Sist bekreftet
1. juni 2026
Mer informasjon
Begreper knyttet til denne studien
Ytterligere relevante MeSH-vilkår
Andre studie-ID-numre
- 2026PHB458-001
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