title: Signal Detection of Adverse Drug Reaction of Amoxicillin Using the Korea Adverse Event Reporting System Database.
abstract: We conducted pharmacovigilance data mining for a β-lactam antibiotics, amoxicillin, and compare the adverse events (AEs) with the drug labels of 9 countries including Korea, USA, UK, Japan, Germany, Swiss, Italy, France, and Laos. We used the Korea Adverse Event Reporting System (KAERS) database, a nationwide database of AE reports, between December 1988 and June 2014. Frequentist and Bayesian methods were used to calculate disproportionality distribution of drug-AE pairs. The AE which was detected by all the three indices of proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC) was defined as a signal. The KAERS database contained a total of 807,582 AE reports, among which 1,722 reports were attributed to amoxicillin. Among the 192,510 antibiotics-AE pairs, the number of amoxicillin-AE pairs was 2,913. Among 241 AEs, 52 adverse events were detected as amoxicillin signals. Comparing the drug labels of 9 countries, 12 adverse events including ineffective medicine, bronchitis, rhinitis, sinusitis, dry mouth, gastroesophageal reflux, hypercholesterolemia, gastric carcinoma, abnormal crying, induration, pulmonary carcinoma, and influenza-like symptoms were not listed on any of the labels of nine countries. In conclusion, we detected 12 new signals of amoxicillin which were not listed on the labels of 9 countries. Therefore, it should be followed by signal evaluation including causal association, clinical significance, and preventability.
authors: Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
authors: Mick
authors: http://orcid.org/0000-0003-2958-7936
authors: M
authors: Soukavong
authors: Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
authors: Jungmee
authors: http://orcid.org/0000-0002-1955-843X
authors: J
authors: Kim
authors: Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
authors: Kyounghoon
authors: http://orcid.org/0000-0001-5800-917X
authors: K
authors: Park
authors: Medical Research Collaborating Center, Seoul National University Hospital and Seoul National University College of Medicine, Seoul, Korea.
authors: Bo Ram
authors: http://orcid.org/0000-0002-8771-8829
authors: BR
authors: Yang
authors: Medical Research Collaborating Center, Seoul National University Hospital and Seoul National University College of Medicine, Seoul, Korea.
authors: Joongyub
authors: http://orcid.org/0000-0003-2784-3772
authors: J
authors: Lee
authors: Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
authors: Xue Mei
authors: http://orcid.org/0000-0003-1132-7271
authors: XM
authors: Jin
authors: Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea. bjpark@snu.ac.kr.
authors: Byung Joo
authors: http://orcid.org/0000-0003-4630-4942
authors: BJ
authors: Park
mesh_terms: D000658:Amoxicillin / Q000009:adverse effects*; D000900:Anti-Bacterial Agents / Q000009:adverse effects*; D001499:Bayes Theorem; D057225:Data Mining; D016208:Databases, Factual; D006801:Humans; D016017:Odds Ratio; D060735:Pharmacovigilance; D056910:Republic of Korea
chemical_list: D000900:Anti-Bacterial Agents; D000658:Amoxicillin
keywords: Adverse Event; Amoxicillin; Data Mining; KAERS Database; Patient Safety; Pharmacovigilance