Evidence map›Paper›PMID 25687792›Full record

ArticleDrug safety2015

Using VigiBase to Identify Substandard Medicines: Detection Capacity and Key Prerequisites.

Kristina Juhlin, Ghazaleh Karimi, Maria Andér, Sara Camilli, Mukesh Dheda, Tan Siew Har, Rokiah Isahak, Su-Jung Lee, Sarah Vaughan, Pia Caduff and 1 more

Abstract read
In one paragraph

Article in Drug safety, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
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  9. Observational
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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

11 authors.

Kristina JuhlinUppsala Monitoring Centre, Box 1051, 75140, Uppsala, Sweden, kristina.juhlin@who-umc.org.
Ghazaleh Karimi
Maria Andér
Sara Camilli
Mukesh Dheda
Tan Siew Har
Rokiah Isahak
Su-Jung Lee
Sarah Vaughan
Pia Caduff
G Niklas Norén

Funding

FDA HHS U01 FD005031
6 · The paper itself

Abstract

backgroundSubstandard medicines, whether the result of intentional manipulation or lack of compliance with good manufacturing practice (GMP) or good distribution practice (GDP), pose a significant potential threat to patient safety. Spontaneous adverse drug reaction reporting systems can contribute to identification of quality problems that cause unwanted and/or harmful effects, and to identification of clusters of lack of efficacy. In 2011, the Uppsala Monitoring Centre (UMC) constructed a novel algorithm to identify reporting patterns suggestive of substandard medicines in spontaneous reporting, and applied it to VigiBase(®), the World Health Organization's global individual case safety report database. The algorithm identified some historical clusters related to substandard products, which were later able to be confirmed in the literature or by contact with national centres (NCs). As relevant and detailed information is often lacking in the VigiBase reports but might be available at the reporting NC, further evaluation of the algorithm was undertaken with involvement from NCs.

objectiveTo evaluate the effectiveness of an algorithm that identifies clusters of potentially substandard medicines, when these are assessed directly at the NC concerned.

methodsThe algorithm identifies countries and time periods with disproportionately high reporting of product inadequacy. NCs with at least 20 clusters were eligible to participate in the study, and six NCs-those in the Republic of Korea, Malaysia, Singapore, South Africa, the UK and the USA-were selected, taking into account the geographical spread and prevalence of recent clusters. The clusters were systematically assessed at the NCs, following a standardized protocol, and then compiled centrally at the UMC. The clusters were classified as 'confirmed', 'potential' or 'unlikely' substandard products; or as 'confirmed not substandard' when confirmed by an investigation; or as 'indecisive' when the information available did not allow a sound assessment even at the NC.

resultsThe assessment of a total of 147 clusters resulted in 8 confirmed, 12 potential and 51 unlikely substandard products, and a further 19 clusters were confirmed as not substandard. Reflecting the difficulty of evaluating suspected substandard products retrospectively when additional information from the primary reporter, as well as samples, are no longer available, 57 clusters were classified as indecisive.

conclusionWhile application of the algorithm to VigiBase allowed identification of some substandard medicines, some key prerequisites have been identified that need to be fulfilled at the national level for the algorithm to be useful in practice. Such key factors are fast handling and transfer of incoming reports into VigiBase, detailed information on the product and its distribution channels, the possibility of contacting primary reporters for further information, availability of samples of suspected products and laboratory capacity to analyse suspected products.

Indexed as

Databases, FactualAlgorithmsCluster AnalysisDrug ContaminationDrug IndustryPharmaceutical PreparationsProduct Surveillance, PostmarketingTherapeutic EquivalencyPharmaceutical Preparations

Identifiers

PMID25687792
PMCPMC4544545

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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.