SurroPilot：用于临床试验中异质性替代终点评估的大语言模型辅助平台
SurroPilot: An LLM-Assisted Platform for Heterogeneous Surrogate Endpoint Evaluation in Clinical Trials
浏览论文内容
中文总结 AI 辅助
SurroPilot是集成LLM与异质性中介框架的辅助平台，可通过自然语言交互完成临床试验异质性替代终点评估全流程，降低了相关方法的应用技术门槛。
中文摘要 AI 辅助
替代终点被广泛应用于临床试验以加快治疗评估，但其有效性在不同患者亚组间可能存在显著差异。尽管近期异质性因果中介分析的进展支持亚组特异性替代评估，但应用这些方法需要具备因果推断、统计编程和临床试验方法学的专业知识，限制了众多生物医学研究者的使用。我们提出SurroPilot，这是一个用于临床试验中异质性替代终点评估的大语言模型（LLM）辅助平台。通过自然语言交互，SurroPilot支持完整的分析工作流程，包括数据集理解、数据预处理、中介变量与协变量选择、异质性因果中介分析、亚组解释以及自动化报告生成。为提升AI辅助统计计算的可靠性，该平台采用了共享上下文的程序员-检查员框架，用于迭代修正R代码并自动化验证LLM生成的变量选择结果。SurroPilot并未替代统计方法，而是将LLM与经过验证的异质性中介框架相集成，使LLM能协助分析推理，同时通过成熟的因果推断方法执行统计推断。基于ACTG175 III期HIV临床试验，我们证明SurroPilot可提供端到端、可重复的异质性替代终点评估工作流程，大幅降低在临床试验研究中应用先进因果中介方法的技术门槛。
英文摘要
Surrogate endpoints are widely used in clinical trials to accelerate treatment evaluation, yet their validity may vary substantially across patient subgroups. Although recent advances in heterogeneous causal mediation analysis enable subgroup-specific surrogate evaluation, applying these methods requires substantial expertise in causal inference, statistical programming, and clinical trial methodology, limiting their accessibility to many biomedical researchers. We present SurroPilot, a large language model (LLM)-assisted platform for heterogeneous surrogate endpoint evaluation in clinical trials. Through natural-language interaction, SurroPilot supports the complete analytical workflow, including dataset understanding, data preprocessing, mediator and covariate selection, heterogeneous causal mediation analysis, subgroup interpretation, and automated report generation. To improve the reliability of AI-assisted statistical computing, the platform incorporates a shared context programmerinspector framework for iterative R code correction and automated validation of LLM-generated variable selections. Rather than replacing statistical methodology, SurroPilot integrates LLM with a validated heterogeneous mediation framework, allowing the LLM to assist with analytical reasoning while statistical inference is performed using established causal inference methods. Using the ACTG175 Phase III HIV clinical trial, we demonstrate that SurroPilot provides an end-to-end, reproducible workflow for heterogeneous surrogate endpoint evaluation and substantially lowers the technical barriers to applying advanced causal mediation methods in clinical trial research.
