Evidence map›Paper›PMID 29124666›Full record

ArticleDrug safety2018

Study Design and Evaluation of Risk Minimization Measures: A Review of Studies Submitted to the European Medicines Agency for Cardiovascular, Endocrinology, and Metabolic Drugs.

Giampiero Mazzaglia, Sabine M J Straus, Peter Arlett, Daniela da Silva, Heidi Janssen, June Raine, Enrica Alteri

Abstract read
In one paragraph

Article in Drug safety, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 pooled it
–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

19 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  16. EU postmarket surveillance plans for medical devices.Pharmacoepidemiology and drug safety · 2019
    Review
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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

7 authors.

Giampiero MazzagliaHuman Medicines Evaluation Division, Scientific and Regulatory Management Department, European Medicines Agency, 30 Churchill Place, Canary Wharf, London, E14 5EU, UK. giampiero.mazzaglia@ema.europa.eu.ORCID http://orcid.org/0000-0003-4933-2148
Sabine M J StrausDutch Medicines Evaluation Board, PO Box 8275, 3503 RG, Utrecht, The Netherlands.
Peter ArlettPharmacovigilance and Epidemiology Department, European Medicines Agency, 30 Churchill Place, London, E14 5EU, UK.
Daniela da SilvaHuman Medicines Evaluation Division, Scientific and Regulatory Management Department, European Medicines Agency, 30 Churchill Place, Canary Wharf, London, E14 5EU, UK.
Heidi JanssenHuman Medicines Evaluation Division, Scientific and Regulatory Management Department, European Medicines Agency, 30 Churchill Place, Canary Wharf, London, E14 5EU, UK.
June RaineVigilance and Risk Management of Medicines, Medicines and Healthcare Products Regulatory Agency, 151 Buckingham Palace Road, Victoria, London, SW1W 9SZ, UK.
Enrica AlteriHuman Medicines Research and Development Support Division, European Medicines Agency, 30 Churchill Place, London, E14 5EU, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionStudies measuring the effectiveness of risk minimization measures (RMMs) submitted by pharmaceutical companies to the European Medicines Agency are part of the post-authorization regulatory requirements and represent an important source of data covering a range of medicinal products and safety-related issues. Their objectives, design, and the associated regulatory outcomes were reviewed, and conclusions were drawn that may support future progress in risk minimization evaluation.

methodsInformation was obtained from risk management plans, study protocols, clinical study reports, and assessment reports of 157 medicinal products authorized for cardiovascular, endocrinology, and metabolic indications. We selected observational studies measuring, as outcomes of interest, the relationship between the RMMs in place and (1) implementation measures, such as clinical knowledge or physicians` compliance to recommendations contained in the RMMs; and (2) occurrence or reduced severity of the adverse drug reactions for which the RMMs were required.

resultsOf 59 eligible studies (24 completed, 35 ongoing), 44 assessed implementation measures, whereas only 15 assessed safety outcomes (1 study as a single endpoint and 14 studies with other endpoints). Fifty-one studies used non-experimental designs and 25 studies employed electronic healthcare databases for analysis. Of the 24 completed studies, 17 were considered satisfactory and supported immediate regulatory decision making, 6 were considered inconclusive and required new evaluations, and 1 was terminated early because new safety restrictions were required, thereby necessitating a new evaluation. Compliance with agreed deadlines was considered acceptable in 21 of 24 completed studies; the average time for a submission was 37 months (standard deviation ± 17), with differences observed by type of data source employed.

conclusionsThree important gaps in the evaluation plans of RMMs were identified: lack of early feedback on implementation, limited evaluation of safety outcomes, and inability to provide information on the effectiveness from an integrated measurement of different elements of a set of risk minimization tools. More robust evidence is needed to advance regulatory science and support more rapid adjustment of risk minimization strategies as needed.

Indexed as

Cardiovascular AgentsDatabases, FactualDrug-Related Side Effects and Adverse ReactionsEndocrinologyHumansObservational Studies as TopicPharmaceutical PreparationsResearch DesignRiskCardiovascular AgentsPharmaceutical Preparations

Identifiers

PMID29124666
PMCPMC5808048

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Registered trials

None linked

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.