Iyakuhin Johogaku
Online ISSN : 1883-423X
Print ISSN : 1345-1464
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Adverse Event Signals of Interstitial Lung Disease in the FDA Adverse Event Reporting System (FAERS) Database and the Japanese Adverse Drug Event Report (JADER) Database
Toshinobu MatsuiRyogo UmetsuYamato KatoNatsumi UedaJunko AbeYoko NakayamaYuuki HaneYasutomi KinosadaMitsuhiro Nakamura
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JOURNALS FREE ACCESS

2015 Volume 17 Issue 3 Pages 145-154

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Abstract

The Japanese Ministry of Health, Labor, and Welfare lists interstitial lung disease as an serious adverse drug event.  The Food and Drug Administration Adverse Event Reporting System (FAERS) and the Japanese Adverse Drug Event Report (JADER) databases are available to detect adverse events signals.  We analyzed reports of interstitial lung disease in FAERS and JADER and calculated the reporting fraction and reporting odds ratio (ROR) of drugs potentially associated with interstitial lung disease.  We applied Weibull shape parameter to time-to-event data in JADER.  We found FAERS to contain 3,522,995 reports from January 2004 to March 2013 and JADER to contain 292,720 reports from April 2004 to November 2013.  In FAERS, the reporting fractions of interstitial lung disease for Gefitinib, Bleomycin, and Amiodarone were 7.4% (285/3,856 reports), 3.2% (86/2,663 reports), and 1.9% (357/18,366 reports), and RORs (95% confidence interval [CI]) were 29.26 (25.89-33.07), 11.99 (9.66-14.88), and 7.29 (6.55-8.11), respectively.  In JADER, the reporting fractions of interstitial lung disease for Gefitinib, Bleomycin, and Amiodarone were 45.6% (1,070/2,348 reports), 22.1% (77/348 reports), and 27.9% (468/1,678 reports), and RORs (95% CI) were 18.46 (16.99-20.06), 5.83 (4.52-7.51), and 8.14 (7.31-9.07), respectively.  Adverse event signals of interstitial lung disease were observed in most drugs, which are warned as a suspected drug in the literature.  With the time-to-event analysis using Weibull shape parameter, time-dependency of adverse events in each drug was different.  Therefore, these drugs should be used carefully in clinical practice.

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© 2015 Japanese Society of Drug Informatics
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