Individual Case Safety Reports – How to Determine the Onset Date of an Adverse Reaction

Klepper, Michael J.; Edwards, Brian

doi:10.2165/11588490-000000000-00000

Cited by 8 publications

(10 citation statements)

References 1 publication

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“…Moreover, the coding habits of the pharmacovigilance centres having recorded the cases may also have had an impact on our results. Indeed, the calculated time to onset depends on the date of initiation of treatment . This date is sometimes difficult to interpret in the database.…”

Section: Discussionmentioning

confidence: 99%

Drug‐induced aseptic meningitis: 329 cases from the French pharmacovigilance database analysis

Bihan

Weiss

Funck‐Brentano

et al. 2019

Brit J Clinical Pharma

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Aims Drug‐induced aseptic meningitis (DIAM) is an adverse drug reaction of exclusion; only few studies have addressed this iatrogenic disease. The aim was to characterize DIAM and to identify suspected drugs. Methods Data were collected from the analysis of the French Pharmacovigilance Database from inception (1 January 1985) to 8 March 2017. All cases were initially analysed according to the French imputability method by institutional pharmacologists (clinicians or pharmacists). Further analyses of well documented cases were then performed. Results In this study, 329 cases of aseptic meningitis were retrieved from the French Pharmacovigilance Database for a total of 429 suspected drugs. Analysis of 203 well documented cases, including 282 drugs, showed that the main reported classes were intravenous polyvalent immunoglobulin, nonsteroidal anti‐inflammatory drugs (NSAIDs), vaccines, antimicrobials, intrathecal antimetabolites, corticosteroids and antalgics/anaesthetics (except NSAIDs). Lymphocytic (33.0%) and purulent (44.8%) meningitis represented the majority of cases of aseptic meningitis. In other cases, the cerebrospinal fluid was mixed (45–55% of neutrophils +45–55% of lymphocytes) or data about cerebrospinal fluid composition were lacking. Most DIAM cases (96%) had a favourable reported outcome with full recovery or minimal residual symptoms. Conclusion The most frequently involved drugs in DIAM were intravenous polyvalent immunoglobulin, NSAIDs, vaccines, and antimicrobials and this without being able to differentiate them in terms of biological characteristics. Although further studies are needed to better understand the pathophysiological mechanisms of DIAM, a continuous enrichment of pharmacovigilance databases is essential to identify new signals and to help clinicians in the understanding of DIAM.

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Section: Discussionmentioning

confidence: 99%

Drug‐induced aseptic meningitis: 329 cases from the French pharmacovigilance database analysis

Bihan

Weiss

Funck‐Brentano

et al. 2019

Brit J Clinical Pharma

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“…A previously discussed phenomenon that may affect the output of aggregated time-to-onset information is how the reporter has defined the onset date of the ADR, which can be recorded as when the first symptom started, when the diagnosis was made, or when the ADR became serious and thereby reportable by the pharmaceutical companies [3]. As ADRs may develop certain seriousness criterion over time, e.g.…”

Section: Discussionmentioning

confidence: 99%

“…In the context of this study we refer to the time span between reported start of drug therapy and reported onset of the ADR as the reported time-to-onset (RTTO), acknowledging the variable information that this may represent [1,3]. …”

Section: Methodsmentioning

confidence: 99%

“…Van Holle et al instead identified drug-ADR pairs with empirical distributions of reported time-to-onset that deviate from other ADRs with the drug of interest and of the ADR of interest with other drugs [2]. However, time-to-onset information from reports is known to be heterogeneously collected [3]. Additionally, such large collections include a multitude of drugs with various durations of use, which might affect any comparison of aggregated reported time-to-onset, if not explicitly adjusted for.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Duration of Treatment on Reported Time-to-Onset in Spontaneous Reporting Systems for Pharmacovigilance

et al. 2013

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Within pharmacovigilance, knowledge of time-to-onset (time from start of drug administration to onset of reaction) is important in causality assessment of drugs and suspected adverse drug reactions (ADRs) and may indicate pharmacological mechanisms involved. It has been suggested that time-to-onset from individual case reports can be used for detection of safety signals. However, some ADRs only occur during treatment, while those that do occur later are less likely to be reported. The aim of this study was to investigate the impact of treatment duration on the reported time-to-onset. Case reports from the WHO Global ICSR database, VigiBase, up until February 5th 2010 were the basis of this study. To examine the effect of duration of treatment on reported time-to-onset, angioedema and hepatitis were selected to represent short and long latency ADRs, respectively. The reported time-to-onset for each of these ADRs was contrasted for a set of drugs expected to be used short- or long-term, respectively. The study included 2,980 unique reports for angioedema and 1,159 for hepatitis. Median reported time-to-onset for angioedema in short-term treatments ranged 0-1 days (median 0.5), for angioedema in long-term treatments 0-26 days (median 8), for hepatitis in short-term treatments 4-12 days (median 7.5) and for hepatitis in long term treatments 19-73 days (median 28). Short-term treatments presented significantly shorter reported time-to-onset than long-term treatments. Of note is that reported time-to-onset for angioedema for long-term treatments (median value of medians being 8 days) was very similar to that of hepatitis for short-term treatments (median value of medians equal 7.5 days). The expected duration of treatment needs to be considered in the interpretation of reported time-to-onset and should be accounted for in signal detection method development and case evaluation.

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“…The structured data in the VAERS database have been widely leveraged in different medical analyses for vaccine adverse events [2,3]. The unstructured nature of the narratives, however, makes the data embedded in them difficult for use in further analyses.…”

Section: Introductionmentioning

confidence: 99%

Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis

Tao

Yang

et al. 2012

J Biomed Sem

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BackgroundThe U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) provides a valuable data source for post-vaccination adverse event analyses. The structured data in the system has been widely used, but the information in the write-up narratives is rarely included in these kinds of analyses. In fact, the unstructured nature of the narratives makes the data embedded in them difficult to be used for any further studies.ResultsWe developed an ontology-based approach to represent the data in the narratives in a “machine-understandable” way, so that it can be easily queried and further analyzed. Our focus is the time aspect in the data for time trending analysis. The Time Event Ontology (TEO), Ontology of Adverse Events (OAE), and Vaccine Ontology (VO) are leveraged for the semantic representation of this purpose. A VAERS case report is presented as a use case for the ontological representations. The advantages of using our ontology-based Semantic web representation and data analysis are emphasized.ConclusionsWe believe that representing both the structured data and the data from write-up narratives in an integrated, unified, and “machine-understandable” way can improve research for vaccine safety analyses, causality assessments, and retrospective studies.

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Individual Case Safety Reports – How to Determine the Onset Date of an Adverse Reaction

Cited by 8 publications

References 1 publication

Drug‐induced aseptic meningitis: 329 cases from the French pharmacovigilance database analysis

Drug‐induced aseptic meningitis: 329 cases from the French pharmacovigilance database analysis

The Impact of Duration of Treatment on Reported Time-to-Onset in Spontaneous Reporting Systems for Pharmacovigilance

Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis

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