美国食品和药物管理局黑盒警告：药物类别和不良反应的特征

摘要(中文译文)

黑框警告是美国食品药品监督管理局最严重的安全警示。目前，这些警告分散于各个产品说明书中，无法在药物或药物类别层面进行系统检索。本研究提供了带有黑框警告药物的全面概览，并识别出类别和分类特异性的不良反应模式，旨在支持风险获益评估和合理治疗。共识别出250个药物类别中的626种药物带有黑框警告。药物类别分布不均，许多类别仅包含单一药物，而少数大类则占据了相当比例的条目，例如μ-阿片受体激动剂、环氧化酶抑制剂、血管紧张素转换酶抑制剂和激酶抑制剂。在所有药物中，共识别出1016项不良反应类别条目，表明多个严重风险常被合并于同一黑框警告中。心脏和心血管不良反应是最常见的类别（18.7%），其次是免疫学和过敏反应（11.4%），此外还存在药物类别特异性模式。标准化不良反应计数从内分泌系统药物的1.1到细胞毒性治疗的2.1不等，表明不同药物类别之间严重不良反应的密度和多样性存在显著差异。黑框警告揭示了药物之间存在显著异质性，但在药物类别和分类层面显示出与机制相关的一致模式。这些模式有助于估计可能的高风险不良反应和风险特征。基于药物类别的结构化黑框警告概览可提高对安全风险的认识，并支持合理处方。意义声明：黑框警告是美国食品药品监督管理局最严重的安全警示，但它们分散于各个产品说明书中。通过系统分析美国食品药品监督管理局针对药物、药物类别和不良反应类别的黑框警告，本研究揭示了单个药物之间存在显著异质性，但存在与机制相关的一致风险模式，中心血管和免疫学不良反应最为常见。基于药物类别的结构化概览能够识别高风险特征，支持风险获益评估和合理处方。

Abstract

Black box warnings represent the most severe US Food and Drug Administration safety alerts. Currently, they are fragmented across individual product labels and not systematically accessible at the level of drugs or drug classes. This study provides a comprehensive overview of drugs with black box warnings and identifies class- and category-specific patterns of adverse effects, aiming to support risk benefit assessments and rational treatment. Six hundred twenty-six drugs across 250 drug classes were identified as carrying black box warnings. Drug classes were unevenly distributed, with many classes represented by a single drug, whereas a small number of large classes accounted for a substantial proportion of entries, for example, μ-opioid receptor agonists, cyclooxygenase inhibitors, angiotensin-converting enzyme inhibitors and kinase inhibitors. Across all drugs, 1016 adverse effect category listings were identified, demonstrating that multiple serious risks are frequently combined within a single boxed warning. Cardiac and cardiovascular adverse effects are the most prevalent category (18.7%), followed by immunologic and allergic reactions (11.4%), beside drug category-specific patterns. The standardized adverse effect count ranged from 1.1 in endocrine system drugs to 2.1 in cytotoxic treatments, indicating marked differences in the density and variety of serious adverse effects between drug categories. Black box warnings reveal pronounced heterogeneity across drugs, but show consistent, mechanism related patterns at the level of drug classes and categories. These patterns allow estimation of probable, high-risk adverse effects and risk profiles. A structured, drug class-based overview of black box warnings can improve awareness of safety risks and support rational prescribing. SIGNIFICANCE STATEMENT: Black box warnings are the most severe US Food and Drug Administration safety alerts, but they are fragmented across individual product labels. By systematically analyzing US Food and Drug Administration boxed warnings across drugs, drug classes, and adverse effect categories, this study reveals pronounced heterogeneity across individual drugs, but consistent, mechanism related risk patterns, with cardiovascular and immunologic adverse effects being most prevalent. A structured, drug class-based overview enables identification of high-risk profiles, supporting risk benefit assessment and rational prescribing.

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