TY - JOUR
T1 - Statistical analysis system of spontaneous adverse drug reaction reports
AU - Kim, Sira
AU - Wang, Boram
AU - Lee, Jungsun
AU - Kim, Bori
AU - La, Hyeno
AU - Park, Young Min
AU - Choi, Inyoung
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Automated analysis system
KW - Data mining
KW - Signal
KW - Spontaneous adverse drug reaction reporting
UR - http://www.scopus.com/inward/record.url?scp=84945497617&partnerID=8YFLogxK
U2 - 10.12793/jkscpt.2012.20.2.155
DO - 10.12793/jkscpt.2012.20.2.155
M3 - Review article
AN - SCOPUS:84945497617
SN - 1225-5467
VL - 20
SP - 155
EP - 164
JO - Journal of Korean Society for Clinical Pharmacology and Therapeutics
JF - Journal of Korean Society for Clinical Pharmacology and Therapeutics
IS - 2
ER -