title: Utilization of chi-square statistics for screening adverse drug-drug interactions in spontaneous reporting systems.
abstract: OBJECTIVE
  We proposed a statistical criterion to detect drug-drug interactions causing adverse drug reactions in spontaneous reporting systems.
  
  
  METHODS
  The used criterion quantitatively measures the discrepancy between the observed and expected number of adverse events via chi-square statistics. We compared the performance of our method with that of Norén et al. (Stat Med 2008; 27 (16): 3057-3070) through a simulation study.
  
  
  RESULTS
  When the number of events for a combination of two drugs was equal to or lower than two, the false positive rate for our method ranged from 0.01 to 0.08, whereas the rate for Norén's method ranged from 0.01 to 0.06. The sensitivity for our method ranged from 0.09 to 0.29, whereas the sensitivity for Norén's method ranged from 0.03 to 0.24. The area-under-the-receiver operating characteristic curve for our method was significantly larger than that for Norén's methods regardless of simulation settings. The proposed method was also applied to the Food and Drug Administration Adverse Event Reporting System database, and a recognized drug-drug interaction was detected.
  
  
  CONCLUSIONS
  The proposed criterion controlled false positives at an acceptable level and had higher sensitivity than that of Norén's method had when events were rare.
authors.affiliation: Department of Clinical Trial and Clinical Epidemiology, Faculty of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8575, Japan. mgosho@md.tsukuba.ac.jp.
authors.forename: Masahiko
authors.identifier: http://orcid.org/0000-0002-5973-9163
authors.initials: M
authors.lastname: Gosho
authors.affiliation: Department of Clinical Epidemiology, Translational Medical Center, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo, 187-8551, Japan.
authors.forename: Kazushi
authors.initials: K
authors.lastname: Maruo
authors.affiliation: Biostatistics & Programming, Sanofi K. K, Tokyo Opera City Tower, 3-20-2, Nishi Shinjuku, Tokyo, 163-1488, Japan.
authors.forename: Keisuke
authors.initials: K
authors.lastname: Tada
authors.affiliation: Center for Advanced Medicine and Clinical Research, Nagoya University Hospital, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8560, Japan.
authors.forename: Akihiro
authors.initials: A
authors.lastname: Hirakawa
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems; D016009:Chi-Square Distribution; D003198:Computer Simulation; D016208:Databases, Factual / Q000706:statistics & numerical data; D004347:Drug Interactions; D064420:Drug-Related Side Effects and Adverse Reactions / Q000175:diagnosis* / Q000453:epidemiology; D005189:False Positive Reactions; D006801:Humans; D012372:ROC Curve; D012680:Sensitivity and Specificity; D014481:United States; D014486:United States Food and Drug Administration
keywords: Adverse event reporting system; False positive; Sensitivity; Signal detection