J Korean Soc Clin Pharmacol Ther.  2012 Dec;20(2):155-164.

Statistical Analysis System of Spontaneous Adverse Drug Reaction Reports

Affiliations
  • 1Graduate School of Healthcare Management and Policy, The Catholic of the University, Catholic Medical Center, Seoul, Korea. iychoi@catholic.ac.kr
  • 2Seoul St' Mary Hospital, The Catholic of the University, Catholic Medical Center, Seoul, Korea.
  • 3Department of Pharmacology, The Catholic of the University, Catholic Medical Center, Seoul, Korea.
  • 4Department of Dermatology, The Catholic of the University, Catholic Medical Center, Seoul, Korea.

Abstract

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.

Keyword

Automated analysis system; Signal; Data mining; Spontaneous adverse drug reaction reporting

MeSH Terms

Analgesics
Data Mining
Dizziness
Drug Toxicity
Exanthema
Fentanyl
Ketorolac
Nausea
Odds Ratio
Pruritus
Tramadol
United States Food and Drug Administration
Vomiting
Analgesics
Fentanyl
Ketorolac
Tramadol

Figure

  • Figure 1 Database for ADR-Detector.

  • Figure 2 Process of ADR (Adverse Drug Reaction)-Detector.

  • Figure 3 Programming code of ADR-Detector system.

  • Figure 4 Web main page of ADR-Detector system.

  • Figure 5 Example of signal search with tramadol containing products using ADR-Detector system.

  • Figure 6 Example of single drug adverse event signal using ADR-Detector system (case of tramadol).

  • Figure 7 Example of multi drug (4 types of an algesics) signal research using ADR-Detector.


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