BACKGROUND Particular interest has been generated regarding the possible influence of statin use on sleep quality. However, no conclusive evidence exists that a particular statin is more likely to be associated with sleep disturbances versus others. It remains uncertain whether different statins produce different risks for sleep disturbance. OBJECTIVE To examine the association between statin use and the risk of sleep disturbances, we conducted data mining using the US Food and Drug Administration Adverse Event Reporting System (FAERS) and a large organized database of prescriptions constructed by a database vendor (Japan Medical Information Research Institute, Inc. Japan). METHODS Relevant reports in the FAERS were identified and analyzed. Data from the first quarter of 2004 through the end of 2012 [corrected] were included in this study.The reporting odds ratio (ROR) was used to detect spontaneous report signals, calculated using the case/non-case method. For the ROR, a signal was detected if the lower limit of 95 % two-sided confidence interval (95 % CI) was >1. Additionally, signal detection using the IC was conducted using the IC025 metric, a lower limit of the 95 % CI of the IC, where a signal is detected if the IC025 value exceeds 0. In addition, symmetry analysis was used to identify the risk of insomnia after using statins over the period of January 2006 to August 2013. RESULTS In the analyses of the FAERS database, significant signals for sleep disturbances including disturbances in initiating and maintaining sleep, sleep disorders NEC, sleeping disorders due to a general medical condition, and parasomnias were found. In the prescription sequence symmetry analysis, a significant association between statin use and hypnotic drug use was found, with adjusted sequence ratios of 1.14 (1.03-1.26), 1.20 (1.11-1.29), and 1.18 (1.11-1.25) at intervals of 91, 182, and 365 days, respectively. CONCLUSION Multi-methodological approaches using different algorithms and databases strongly suggest that statin use is associated with an increased risk for sleep disturbances including insomnia.
CITATION STYLE
Poluzzi, E., Raschi, E., Piccinni, C., & De, F. (2012). Data Mining Techniques in Pharmacovigilance: Analysis of the Publicly Accessible FDA Adverse Event Reporting System (AERS). In Data Mining Applications in Engineering and Medicine. InTech. https://doi.org/10.5772/50095
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