Evidence map›Paper›PMID 27747826›Full record

ArticleDrugs - real world outcomes2016

Seasonal and Geographic Variation in Adverse Event Reporting.

Osvaldo Marrero, Eric Y Hung, Manfred Hauben

Abstract read
In one paragraph

Article in Drugs - real world outcomes, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Osvaldo MarreroDepartment of Mathematics and Statistics, Villanova University, Villanova, PA, USA.
Eric Y HungPfizer Inc., New York, NY, USA. eric.hung@pfizer.com.
Manfred HaubenPfizer Inc., New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany illnesses demonstrate seasonal and geographic variations. Pharmacovigilance is unique among public health surveillance systems in terms of the clinical diversity of the events under surveillance. Since many pharmacovigilance signal detection methodologies are geared towards looking for increased frequency of spontaneous adverse drug event (ADE) reporting over variable time frames, seasonality of ADEs may have implications for signal detection.

objectiveThe aim of this study was to investigate whether a set of illnesses that might be expected to display seasonality in general, did so when spontaneously reported as ADEs.

methodsWe performed our analysis with the publically available US FDA Adverse Event Reporting System (FAERS) data. We selected a convenience sample of events possibly triggered by seasonal factors (hypothermia, Raynaud's phenomenon, photosensitivity reaction, heat exhaustion, heat stroke, and sunburn) and events for which previous literature experience suggests seasonality (anencephaly and interstitial lung disease). Our statistical procedures can be explained in terms of a simple physicogeometric setting: the unit circle divided into 6 (semiannual sinusoidal) or 12 (annual sinusoidal) arcs. When reporting frequencies (weights) are more or less evenly distributed across months, the center of mass of the circle would not be significantly displaced from the origin (0, 0). Distinct seasonal patterns will significantly displace the center of mass of the circle.

resultsVarious patterns of seasonality were identified for some, but not all, events and region-event pairs. USA displayed the most instances of seasonality. Scandinavia did not display seasonality for any events. Seasonality was usually annual sinusoidal. Possible explanations for failure to observe seasonality are briefly considered.

conclusionsUnderstanding seasonality of spontaneous ADE reporting may have public health policy and research implications and may mitigate false-positive and missed true-positive pharmacovigilance signals. More systematic study of seasonality of spontaneous ADE reporting, including additional events with more or less biological rationale for seasonality, is a logical extension of this analysis.

Identifiers

PMID27747826
PMCPMC5042937

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.