BACKGROUND: Spontaneous adverse drug reaction (ADR) reporting data has been used for safety of post-market drug surveillance. A system has been required that is able to detect signals associated with drugs by analyzing the collected ADR data. METHODS: We developed the web-based automated analysis system (ADR-detector). We used the data which reported ADR spontaneously between March 2009 and December 2010 to Korean Food and Drug Administration. We used 3 statistical indicators for evaluating ADR signals: proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC). The ADR reports which were detected as significant signals based on the indicators have been reviewed. RESULTS: Among 153,774 reports, 9,955 cases were related to 4 analgesics which were most frequently reported analgesic drugs during the study period. The numbers of ADR reports associated with each drug are as follow: 5,623 reports in tramadol (56.5 %), 1,720 reports in fentanyl (17.3 %), 1,463 reports in tramadol-combination (14.7 %), and 1,149 reports in ketorolac (11.5 %). Top 5 ADR were nausea (3,351 reports - 33.7 %), vomiting (1,755 reports - 17.6 %), dizziness (1,130 - 11.4 %), rash (412 reports - 4.1 %), and pruritus (354 reports - 3.6 %). 6,674 ADR reports were significant based on PRR and ROR, and 336 reports were significant based on IC. CONCLUSION: By using the automated analysis system, not only statisticians but also general researchers are able to analyze ADR signals in real-time. Also ADR-detector would provide rapid review and cross-check of ADR.
Analgesics ; Data Mining ; Dizziness ; Drug Toxicity ; Exanthema ; Fentanyl ; Ketorolac ; Nausea ; Odds Ratio ; Pruritus ; Tramadol ; United States Food and Drug Administration ; Vomiting