Evidence map›Paper›PMID 28130773›Full record

ArticleDrug safety2017

Identification of Substandard Medicines via Disproportionality Analysis of Individual Case Safety Reports.

Zahra Anita Trippe, Bruno Brendani, Christoph Meier, David Lewis

Abstract read
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Article in Drug safety, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
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  11. Pharmacovigilance and Appropriate Drug Use.Healthcare (Basel, Switzerland) · 2024
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  12. Article
  13. Review
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  16. [Establishment of a rapid identification of adverse drug reaction program in R language implementation based on monitoring data].Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2020
    Article
  17. Article
  18. Observational
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

4 authors.

Zahra Anita TrippePatient Safety, Novartis Pharma AG, Basel, Switzerland. zahra_anita.trippe@novartis.com.
Bruno BrendaniPatient Safety, Novartis Pharma AG, Basel, Switzerland.
Christoph MeierDivision of Clinical Pharmacy and Epidemiology, Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland.
David LewisPatient Safety, Novartis Pharma AG, Basel, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe distribution and use of substandard medicines (SSMs) is a public health concern worldwide. The detection of SSMs is currently limited to expensive large-scale assay techniques such as high-performance liquid chromatography (HPLC). Since 2013, the Pharmacovigilance Department at Novartis Pharma AG has been analyzing drug-associated adverse events related to 'product quality issues' with the aim of detecting defective medicines using spontaneous reporting. The method of identifying SSMs with spontaneous reporting was pioneered by the Monitoring Medicines project in 2011.

methodsThis retrospective review was based on data from the World Health Organization (WHO) Global individual case safety report (ICSR) database VigiBase

resultsThe analysis of ICSRs based on the specified selection criteria and threshold yielded 2506 hits including medicinal products with an excess of reports of product quality defects relative to other medicines in the database. Further investigations and a pilot study in five authorized medicinal products (proprietary and generic) licensed by a single marketing authorization holder, containing valsartan, methylphenidate, rivastigmine, clozapine, or carbamazepine, were performed. This resulted in an output of 23 potential SSMs. The literature search identified two communications issued to health professionals concerning a substandard rivastigmine patch, which validated our initial findings. Furthermore, we identified excess reporting of product quality issues with an ethinyl estradiol/norgestrel combination and with salbutamol. These were categorized as confirmed clusters of substandard/spurious/falsely labelled/falsified/counterfeit (SSFFC) medical products by the UMC in 2014.

conclusionThis study illustrates the value of data mining of spontaneous adverse event reports and the applicability of disproportionality analysis to identify potential SSMs.

Indexed as

Adverse Drug Reaction Reporting SystemsPharmacovigilanceAlgorithmsBayes TheoremDatabases, FactualData MiningDrug-Related Side Effects and Adverse ReactionsHumansPharmaceutical PreparationsPilot ProjectsRetrospective StudiesPharmaceutical Preparations

Identifiers

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Registered trials

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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.