Dataset Information

Early signal detection of adverse events following influenza vaccination using proportional reporting ratio, Victoria, Australia.

ABSTRACT: INTRODUCTION:Timely adverse event following immunisation (AEFI) signal event detection is essential to minimise further vaccinees receiving unsafe vaccines. We explored the proportional reporting ratio (PRR) ability to detect two known signal events with influenza vaccines with the aim of providing a model for prospective routine signal detection and improving vaccine safety surveillance in Australia. METHODS:Passive AEFI surveillance reports from 2008-2017 relating to influenza vaccines were accessed from the Australian SAEFVIC (Victoria) database. Proportional reporting ratios were calculated for two vaccine-event categories; fever and allergic AEFI. Signal detection sensitivity for two known signal events were determined using weekly data; cumulative data by individual year and; cumulative for all previous years. Signal event thresholds of PRR ?2 and Chi-square ?4 were applied. RESULTS:PRR provided sensitive signal detection when calculated cumulatively by individual year or by all previous years. Known signal events were detected 15 and 11 days earlier than traditional methods used at the time of the actual events. CONCLUSION:Utilising a single jurisdiction's data, PRR improved vaccine pharmacovigilance and showed the potential to detect important safety signals much earlier than previously. It has potential to maximise immunisation safety in Australia. This study progresses the necessary work to establish national cohesion for passive surveillance signal detection and strengthen routine Australian vaccine pharmacovigilance.

SUBMITTER: Clothier HJ

PROVIDER: S-EPMC6824574 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Early signal detection of adverse events following influenza vaccination using proportional reporting ratio, Victoria, Australia.

Clothier Hazel J HJ Lawrie Jock J Russell Melissa A MA Kelly Heath H Buttery Jim P JP

PloS one 20191101 11

<h4>Introduction</h4>Timely adverse event following immunisation (AEFI) signal event detection is essential to minimise further vaccinees receiving unsafe vaccines. We explored the proportional reporting ratio (PRR) ability to detect two known signal events with influenza vaccines with the aim of providing a model for prospective routine signal detection and improving vaccine safety surveillance in Australia.<h4>Methods</h4>Passive AEFI surveillance reports from 2008-2017 relating to influenza v ...[more]

PMID: 31675362

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Project description:Esketamine was approved for the treatment of treatment-resistant depression in 2019. After the approval of esketamine, numerous concerns have been raised regarding its long-term safety and tolerability. A previous systematic pharmacovigilance study on esketamine-related adverse events (AEs) was published in 2020; however, it has not been updated 2 years later. The primary aim of this study was to detect and characterize neurological safety signals of esketamine to partially update the knowledge in this field using the FDA pharmacovigilance database. Reporting odds ratio (ROR) was calculated for esketamine-related neurological AEs from 2019 to 2021 with a signal considered when the lower limit of the 95% confidence interval (CI) of ROR (ROR025) exceeded one. Severe and non-severe cases were compared using an independent samples t-test or chi-squared (χ2) test, and a rating scale was used to prioritize the signals. The database contained 720 cases of esketamine-associated neurological AEs, with 21 signals detected, ranging from a ROR025 of 1.05 (disturbance in attention) to 204.00 (sedation). 16 latest neurological AEs emerged in the second year of marketing approval of esketamine, with eight signals detected. The associations between esketamine and nervous system disorders persisted when stratifying by sex, age, and reporter type, whereas the spectrum of neurological AEs differed in stratification regimens. Esketamine dosage, antidepressant polypharmacy, or co-prescription with benzodiazepines affected AEs severity (t = 2.41, p = 0.017; χ2 = 6.75, p = 0.009; and χ2 = 4.10, p = 0.043; respectively), while age and sex did not (p = 0.053 and p = 0.397, respectively). Three signals were categorized as moderate clinical priority [i.e., sedation, dizziness, and dysgeusia (priority points 7, 5, and 5, respectively)], showing the same early failure type profiles. Notably, seven detected disproportionality signals were not previously detected in clinical trials. Although the majority of results were in line with those obtained in the previous study, there were discrepancies in the spectrum of neurological AEs and the effects of several risk factors on AEs severity among the two studies that should be recognized and managed early in clinical treatments.

Dataset Information

Early signal detection of adverse events following influenza vaccination using proportional reporting ratio, Victoria, Australia.

Publications

Early signal detection of adverse events following influenza vaccination using proportional reporting ratio, Victoria, Australia.

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