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. 2015 Dec 7;10(12):e0144263.
doi: 10.1371/journal.pone.0144263. eCollection 2015.

Factors Affecting the Timing of Signal Detection of Adverse Drug Reactions

Affiliations

Factors Affecting the Timing of Signal Detection of Adverse Drug Reactions

Masayuki Hashiguchi et al. PLoS One. .

Abstract

We investigated factors affecting the timing of signal detection by comparing variations in reporting time of known and unknown ADRs after initial drug release in the USA. Data on adverse event reactions (AERs) submitted to U.S. FDA was used. Six ADRs associated with 6 drugs (rosuvastatin, aripiprazole, teriparatide, telithromycin, exenatide, varenicline) were investigated: Changes in the proportional reporting ratio, reporting odds ratio, and information component as indexes of signal detection were followed every 3 months after each drugs release, and the time for detection of signals was investigated. The time for the detection of signal to be detected after drug release in the USA was 2-10 months for known ADRs and 19-44 months for unknown ones. The median lag time for known and unknown ADRs was 99.0-122.5 days and 185.5-306.0 days, respectively. When the FDA released advisory information on rare but potentially serious health risks of an unknown ADR, the time lag to report from the onset of ADRs to the FDA was shorter. This study suggested that one factor affecting signal detection time is whether an ADR was known or unknown at release.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Time lag from the onset of known and unknown ADRs until report to the FDA for each study drug and effect of FDA advisory information on reporting time.

References

    1. Evans SJ, Waller PC, Davis S. Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiol Drug Saf 2011; 10: 483–486. - PubMed
    1. Sakaeda T, Tamon A, Kadoyama K, Okuno Y. Data mining of the public version of the FDA Adverse Event Reporting System. Int J Med Sci. 2013; 10:796–803. 10.7150/ijms.6048 - DOI - PMC - PubMed
    1. Tatonetti NP, Fernald GH, Altman RB. A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports. J Am Med Inform Assoc. 2012; 19:79–85. 10.1136/amiajnl-2011-000214 - DOI - PMC - PubMed
    1. Takarabe M, Kotera M, Nishimura Y, Goto S, Yamanishi Y. Drug target prediction using adverse event report systems: a pharmacogenomic approach. Bioinformatics. 2012;28:i611–i618 10.1093/bioinformatics/bts413 - DOI - PMC - PubMed
    1. van Puijenbroek EP, Bate A, Leufkens HG, Lindquist M, Orre R, Egberts AC. A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions. Pharmacoepidemiol Drug Saf 2002; 11: 3–10. - PubMed

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