Toward multimodal signal detection of adverse drug reactions.
Toward multimodal signal detection of adverse drug reactions.
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DOI：
10.1016/j.jbi.2017.10.013
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发表时间：
2017-12
影响因子：
4.5
通讯作者：
Shah NH
中科院分区：
文献类型：
--
作者：
Harpaz R;DuMouchel W;Schuemie M;Bodenreider O;Friedman C;Horvitz E;Ripple A;Sorbello A;White RW;Winnenburg R;Shah NH
完善药品不良反应检测机制是加强药品上市后安全性监测的关键。信号检测目前是单峰的，依赖于单一的信息源。多模态信号检测是基于对多个信息源的联合分析。本文在前人研究的基础上，进一步研究多模态信号检测，探索其潜在优势，并提出其构建和评价方法。调查了四个数据源：FDA的不良事件报告系统、保险索赔、MEDLINE引文数据库和主要Web搜索引擎的日志。已发布的方法用于生成和联合收割机信号，这些信号来自每个数据源。两个不同的参考基准，分别对应于完善的和最近标记的ADR，用于评估多模式信号检测的性能，在ROC曲线下面积（AUC）和前置时间检测，后者相对于标签修订日期。受限于我们的参考基准，多模态信号检测基于广泛使用的评估基准提供了0.04-0.09范围内的AUC改善，并且相对于时间索引基准的标签修订日期，相对增加了7-22个月的交付周期。结果支持的概念，利用和联合分析多个数据源可能会导致改善信号检测。鉴于某些数据和基准限制、发展成果评估的早期阶段和复杂性，目前不可能对这一概念的最终效用作出明确的说明。多模态信号检测的持续发展需要更深入地了解所使用的数据源，额外的基准，以及对生成和合成信号的方法的进一步研究。
Improving mechanisms to detect adverse drug reactions (ADRs) is key to strengthening post-marketing drug safety surveillance. Signal detection is presently unimodal, relying on a single information source. Multimodal signal detection is based on jointly analyzing multiple information sources. Building on, and expanding the work done in prior studies, the aim of the article is to further research on multimodal signal detection, explore its potential benefits, and propose methods for its construction and evaluation. Four data sources are investigated; FDA’s adverse event reporting system, insurance claims, the MEDLINE citation database, and the logs of major Web search engines. Published methods are used to generate and combine signals from each data source. Two distinct reference benchmarks corresponding to well-established and recently labeled ADRs respectively are used to evaluate the performance of multimodal signal detection in terms of area under the ROC curve (AUC) and lead-time-to-detection, with the latter relative to labeling revision dates. Limited to our reference benchmarks, multimodal signal detection provides AUC improvements ranging from 0.04–0.09 based on a widely used evaluation benchmark, and a comparative added lead-time of 7–22 months relative to labeling revision dates from a time-indexed benchmark. The results support the notion that utilizing and jointly analyzing multiple data sources may lead to improved signal detection. Given certain data and benchmark limitations, the early stage of development, and the complexity of ADRs, it is currently not possible to make definitive statements about the ultimate utility of the concept. Continued development of multimodal signal detection requires a deeper understanding the data sources used, additional benchmarks, and further research on methods to generate and synthesize signals.
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影响因子：
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