Abstract
A well-known problem in pharmacotherapy is an increased risk of adverse drug reactions (ADRs) in older as compared to younger patients. The Russian pharmacovigilance database includes a significant number of spontaneous reports of suspected ADRs in patients aged 65 and older. An increase in ADRs reporting makes it difficult to identify potential safety signals based on qualitative approaches only, which necessitates the use of statistical methods for signal detection based on disproportionality. The aim of the study was to assess the applicability of quantitative methods for signal detection and analysis of ADR risks in the elderly using the Russian spontaneous report database. Materials and methods: the study covered the reports on patients 65 years of age and older, which were submitted to the spontaneous report database from January 2008 until June 2018. The procedure recommended by the European Medicines Agency was used to identify potential statistical safety signals which were determined based on the following criteria: Reporting Odds Ratio, ROR—lower bound of the 95% confidence interval >1, number of cases ≥2; Proportional Reporting Ratio, PRR ≥ 2, Chi-square value χ 2 ≥ 4, number of cases ≥3, lower bound of the 95% confidence interval >1, number of cases ≥3. Results: 2231 potential statistical signals were identified. Of these, the vast majority of combinations of suspected drugs and ADRs were associated with known drug risks, and were not new safety signals for these drugs. The largest proportion of statistical signals was attributed to the following pharmacological groups: antiplatelet agents, cephalosporins, non-steroidal anti-inflammatory drugs, fluoroquinolones, angiotensin-converting enzyme inhibitors, metabolic agents, and indirect anticoagulants. Conclusion: the results obtained indicate the applicability and effectiveness of statistical methods based on disproportionality of reporting for the analysis of the Russian spontaneous report database in order to identify potential drug safety issues.
Highlights
Несмотря на то что за рубежом проведено значительное число исследований, посвященных сравнению характеристик различных алгоритмов выявления сигналов с точки зрения чувствительности, специфичности, точности и раннего выявления проблем безопасности, единого стандарта методологии пока не существует
An increase in adverse drug reactions (ADRs) reporting makes it difficult to identify potential safety signals based on qualitative approaches only, which necessitates the use of statistical methods for signal detection based on disproportionality
The aim of the study was to assess the applicability of quantitative methods for signal detection and analysis of ADR risks in the elderly using the Russian spontaneous report database
Summary
Российская база данных фармаконадзора содержит значительное количество индивидуальных спонтанных сообщений о нежелательной реакции, касающихся пациентов 65 лет и старше. Рост репортирования о нежелательных реакциях делает затруднительным выявление сигналов о безопасности лекарственных средств исключительно на основе качественных подходов, что ведет к необходимости использования статистических методов выявления сигналов на основе диспропорциональности. Цель работы: оценка возможности использования количественных методов выявления сигналов о безопасности и анализ рисков развития нежелательных реакций у пожилых пациентов по данным спонтанных сообщений, поступивших в отечественную базу данных. Для выявления потенциальных статистических сигналов о безопасности использовалась методика, рекомендованная Европейским агентством по лекарственным средствам. Выводы: полученные результаты позволяют констатировать применимость и эффективность статистических методов, основанных на диспропорциональности отчетности, для анализа российской базы спонтанных сообщений с целью выявления статистических сигналов о безопасности. Анализ нежелательных реакций у пожилых пациентов с использованием количественных методов выявления сигналов. Analysis of Adverse Reactions in Elderly Patients Based on Quantitative Methods of Signal Detection
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