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Preliminary Evaluation of a Large Language Model-Based Tool for Complex Surgical Decision Support in Lung Cancer

2026年6月13日 更新者：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.

研究概览

地位

邀请报名

条件

干预/治疗

研究类型

介入性

注册 (估计的)

12

阶段

  • 不适用

联系人和位置

本节提供了进行研究的人员的详细联系信息，以及有关进行该研究的地点的信息。

学习地点

  • 中国
    • Beijing Municipality
      • Beijing、Beijing Municipality、中国、100044
        • Peking University People's Hospital

参与标准

研究人员寻找符合特定描述的人，称为资格标准。这些标准的一些例子是一个人的一般健康状况或先前的治疗。

资格标准

适合学习的年龄

  • 成人
  • 年长者

接受健康志愿者

不

描述

Inclusion Criteria:

  1. Resident Physician Subjects:

    1. Holds a valid and legally effective Physician Practice License of the People's Republic of China;
    2. Currently holds the rank of resident physician in a thoracic surgery department at a tertiary Class A (3A) hospital;
    3. Agrees to complete all assessment tasks of the main study phase in accordance with the study protocol;
    4. Can guarantee the time and effort required to complete all assessment tasks of the main study.

  2. Study Cases:

    1. The case was discussed at the Thoracic Oncology Multidisciplinary Team (MDT) conference of Peking University People's Hospital between January 2025 and May 2026;
    2. The current version of the NCCN guidelines does not provide an explicit recommendation covering the management of the case;
    3. Does not overlap with the GAPS evaluation set;
    4. 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;
    5. 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.

  3. Adjudication Expert Panel:

    1. Holds a valid and legally effective Physician Practice License of the People's Republic of China;
    2. Currently holds the rank of attending physician or above in a thoracic surgery department at a tertiary Class A hospital;
    3. Chairs or regularly participates in lung cancer multidisciplinary team (MDT) work in their department.

Exclusion Criteria:

  1. Resident Physician Subjects:

    1. Has previously participated in the construction of the GAPS evaluation set or the development of GAPS-Agent;
    2. Unable to complete the tasks of the study phase.

  2. Study Cases:

    1. 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;
    2. Decision-making for the case is strictly dependent on non-text information.

  3. Adjudication Expert Panel:

    1. Participated in the construction of the GAPS evaluation set, the content validity verification, or the development of GAPS-Agent for this study;
    2. Has a direct conflict of interest with any specific product among the two-arm tools of this study.

学习计划

本节提供研究计划的详细信息，包括研究的设计方式和研究的衡量标准。

研究是如何设计的？

设计细节

  • 主要用途：其他
  • 分配：随机化
  • 介入模型：并行分配
  • 屏蔽：单身的

武器和干预

参与者组/臂
干预/治疗
实验性的：test arm
GAPS-Agent
其他：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
有源比较器：control arm
LLM
其他：LLM
Open source large language model that is not specifically enhanced in medical field.

研究衡量的是什么？

主要结果指标

结果测量
措施说明
大体时间
Overall plan Win Ratio
大体时间：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.

次要结果测量

结果测量
措施说明
大体时间
Inter-rater agreement
大体时间：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
大体时间：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
大体时间：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
大体时间：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
大体时间：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
大体时间：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
大体时间：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
大体时间：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
大体时间：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
大体时间：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
大体时间：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.

合作者和调查者

在这里您可以找到参与这项研究的人员和组织。

赞助

Peking University People's Hospital

研究记录日期

这些日期跟踪向 ClinicalTrials.gov 提交研究记录和摘要结果的进度。研究记录和报告的结果由国家医学图书馆 (NLM) 审查，以确保它们在发布到公共网站之前符合特定的质量控制标准。

研究主要日期

学习开始 (实际的)

2026年6月10日

初级完成 (估计的)

2026年6月21日

研究完成 (估计的)

2026年6月21日

研究注册日期

首次提交

2026年6月10日

首先提交符合 QC 标准的

2026年6月13日

首次发布 (实际的)

2026年6月17日

研究记录更新

最后更新发布 (实际的)

2026年6月17日

上次提交的符合 QC 标准的更新

2026年6月13日

最后验证

2026年6月1日

更多信息

与本研究相关的术语

关键字

其他相关的 MeSH 术语

其他研究编号

  • 2026PHB458-001

计划个人参与者数据 (IPD)

计划共享个人参与者数据 (IPD)？

不

药物和器械信息、研究文件

研究美国 FDA 监管的药品

不

研究美国 FDA 监管的设备产品

不

此信息直接从 clinicaltrials.gov 网站检索，没有任何更改。如果您有任何更改、删除或更新研究详细信息的请求，请联系 register@clinicaltrials.gov. clinicaltrials.gov 上实施更改，我们的网站上也会自动更新.

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GAPS-Agent的临床试验

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赞助者和合作者

医疗条件

药物干预

CROs by country

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条件

罕见疾病

药物干预

膳食补充剂

赞助者/合作者

地点

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