Should methods of correction for multiple comparisons be applied in pharmacovigilance?

L. Scotti, S. Romio, A. Ghirardi, A. Arfè, M. Casula, L. Hazell, F. Lapi, A. Catapano, M. Sturkenboom, G. Corrao
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引用次数: 1

Abstract

Purpose. In pharmacovigilance, spontaneous reporting databases are devoted to the early detection of adverse event ‘signals’ of marketed drugs. A common limitation of these systems is the wide number of concurrently investigated associations, implying a high probability of generating positive signals simply by chance. However it is not clear if the application of methods aimed to adjust for the multiple testing problems are needed when at least some of the drug-outcome relationship under study are known. To this aim we applied a robust estimation method for the FDR (rFDR) particularly suitable in the pharmacovigilance context. Methods. We exploited the data available for the SAFEGUARD project to apply the rFDR estimation methods to detect potential false positive signals of adverse reactions attributable to the use of non-insulin blood glucose lowering drugs. Specifically, the number of signals generated from the conventional disproportionality measures and after the application of the rFDR adjustment method was compared. Results. Among the 311 evaluable pairs (i.e., drug-event pairs with at least one adverse event report), 106 (34%) signals were considered as significant from the conventional analysis. Among them 1 resulted in false positive signals according to rFDR method. Conclusions. The results of this study seem to suggest that when a restricted number of drug-outcome pairs is considered and warnings about some of them are known, multiple comparisons methods for recognizing false positive signals are not so useful as suggested by theoretical considerations.
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多重比较的校正方法是否应用于药物警戒?
目的。在药物警戒方面,自发报告数据库致力于及早发现已上市药物的不良事件“信号”。这些系统的一个共同限制是同时调查的关联数量很多,这意味着仅仅偶然产生积极信号的概率很高。然而,目前尚不清楚的是,如果至少有一些药物-结果关系是已知的,是否需要应用旨在调整多重测试问题的方法。为此,我们应用了一种特别适用于药物警戒环境的FDR (rFDR)稳健估计方法。方法。我们利用SAFEGUARD项目的现有数据,应用rFDR估计方法检测非胰岛素降糖药物不良反应的潜在假阳性信号。具体来说,比较了传统歧化测量和应用rFDR调整方法后产生的信号数量。结果。在311个可评估的对(即至少有一个不良事件报告的药物事件对)中,106个(34%)信号从常规分析中被认为是显著的。其中1例根据rFDR方法产生假阳性信号。结论。这项研究的结果似乎表明,当考虑到有限数量的药物结局对,并且其中一些警告是已知的,用于识别假阳性信号的多重比较方法并不像理论考虑所建议的那样有用。
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Epidemiology Biostatistics and Public Health
Epidemiology Biostatistics and Public Health PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
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期刊介绍: Epidemiology, Biostatistics, and Public Health (EBPH) is a multidisciplinary journal that has two broad aims: -To support the international public health community with publications on health service research, health care management, health policy, and health economics. -To strengthen the evidences on effective preventive interventions. -To advance public health methods, including biostatistics and epidemiology. EBPH welcomes submissions on all public health issues (including topics like eHealth, big data, personalized prevention, epidemiology and risk factors of chronic and infectious diseases); on basic and applied research in epidemiology; and in biostatistics methodology. Primary studies, systematic reviews, and meta-analyses are all welcome, as are research protocols for observational and experimental studies. EBPH aims to be a cross-discipline, international forum for scientific integration and evidence-based policymaking, combining the methodological aspects of epidemiology, biostatistics, and public health research with their practical applications.
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