药物警戒中个例安全性报告的多智能体检索增强因果关系评估（MARCA）
摘要
提出 MARCA 四智能体框架，利用 Gemini 2.5 Pro 和 DeepSeek-V3.2 结合检索增强生成（RAG）对 FAERS 个体案例安全报告进行基于 Naranjo 量表的因果关系评估，最终因果分类与人类专家的一致率达 79.4%（κ=0.587）。
arXiv:2610.33279v1 Announce Type: new
Abstract: Introduction: Increasing volumes of individual case safety reports (ICSRs) challenge expert-led causality assessment in pharmacovigilance. We developed MARCA (Multi-Agent Retrieval-Augmented Causality Assessment), a four-agent framework for Naranjo-based assessment, and evaluated agreement with human experts and exploratory differences between non-RAG and RAG-labelled scores.
Methods: MARCA combined scientific literature retrieval, drug-label assessment, objective-evidence classification, and clinical causality reasoning using Gemini 2.5 Pro and DeepSeek-V3.2. Agent-generated rationales informed human-assisted scoring. A consensus expert reference standard covered 215 ICSRs and 1,562 drug-event combinations (DECs) from FAERS (Q1-Q2 2025). Agreement was measured using percentage agreement and Cohen's kappa.
Results: Question-level agreement was 96.8% for Naranjo Q2 (kappa = 0.491; 95% CI 0.265-0.663), 85.4% for Q5 (kappa = 0.269; 95% CI 0.180-0.340), and 96.8% for Q10 (kappa = 0.922; 95% CI 0.885-0.951). Final causality classification agreement was 79.4% (95% CI 71.8-85.3; kappa = 0.587, 95% CI 0.450-0.690). In a retrospective subset of 60 DECs, agreement was higher for RAG-labelled than non-RAG scores for Q5 (83.3% vs 65.0%) and Q10 (100.0% vs 18.3%).
Discussion: MARCA-assisted assessment showed substantial variation in agreement across Naranjo questions, with lower concordance for alternative causes. Retrospective RAG comparisons are exploratory and do not establish prospective effectiveness.
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# Multi-Agent Retrieval-Augmented Causality Assessment (MARCA) of Individual Case Safety Reports in Pharmacovigilance Source: [https://arxiv.org/abs/2610.33279](https://arxiv.org/abs/2610.33279) [View PDF](https://arxiv.org/pdf/2610.33279) > Abstract:Introduction: Increasing volumes of individual case safety reports \(ICSRs\) challenge expert\-led causality assessment in pharmacovigilance\. We developed MARCA \(Multi\-Agent Retrieval\-Augmented Causality Assessment\), a four\-agent framework for Naranjo\-based assessment, and evaluated agreement with human experts and exploratory differences between non\-RAG and RAG\-labelled scores\. Methods: MARCA combined scientific literature retrieval, drug\-label assessment, objective\-evidence classification, and clinical causality reasoning using Gemini 2\.5 Pro and DeepSeek\-V3\.2\. Agent\-generated rationales informed human\-assisted scoring\. A consensus expert reference standard covered 215 ICSRs and 1,562 drug\-event combinations \(DECs\) from FAERS \(Q1\-Q2 2025\)\. Agreement was measured using percentage agreement and Cohen's kappa\. Results: Question\-level agreement was 96\.8% for Naranjo Q2 \(kappa = 0\.491; 95% CI 0\.265\-0\.663\), 85\.4% for Q5 \(kappa = 0\.269; 95% CI 0\.180\-0\.340\), and 96\.8% for Q10 \(kappa = 0\.922; 95% CI 0\.885\-0\.951\)\. Final causality classification agreement was 79\.4% \(95% CI 71\.8\-85\.3; kappa = 0\.587, 95% CI 0\.450\-0\.690\)\. In a retrospective subset of 60 DECs, agreement was higher for RAG\-labelled than non\-RAG scores for Q5 \(83\.3% vs 65\.0%\) and Q10 \(100\.0% vs 18\.3%\)\. Discussion: MARCA\-assisted assessment showed substantial variation in agreement across Naranjo questions, with lower concordance for alternative causes\. Retrospective RAG comparisons are exploratory and do not establish prospective effectiveness\. ## Submission history From: Maurizio Sessa Dr\. \[[view email](https://arxiv.org/show-email/3457f6c5/2610.33279)\] **\[v1\]**Fri, 23 Oct 2026 20:43:29 UTC \(2,619 KB\)
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