Evidence map›Paper›PMID 32632714›Full record

ArticleEuropean journal of clinical pharmacology2020

Use of the French healthcare insurance database to estimate the prevalence of exposure to potential drug-drug interactions.

Cécile Souty, Titouan Launay, Olivier Steichen, Cécile Conte, Clément Turbelin, Marianne Sarazin, Ana-Maria Vilcu, Louise Rossignol, Thierry Blanchon, Maryse Lapeyre-Mestre and 1 more

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Article in European journal of clinical pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 25% of its field
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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Observational
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  4. Article
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 at 1 institution in 1 country.

Cécile SoutySorbonne Université, INSERM, Institut Pierre Louis d'épidémiologie et de Santé publique, Paris, France. cecile.souty@upmc.fr.ORCID http://orcid.org/0000-0002-4990-5201
Titouan LaunaySorbonne Université, INSERM, Institut Pierre Louis d'épidémiologie et de Santé publique, Paris, France.
Olivier SteichenSorbonne Université, INSERM, Université Paris 13, Laboratoire d'informatique médicale et d'ingénierie des connaissances en e-santé, LIMICS, Paris, France.
Cécile ConteINSERM, Université de Toulouse (LEASP UMR 1027), Service de Pharmacologie médicale et clinique, CIC 1436, Centre Hospitalo-Universitaire de Toulouse (CHU Toulouse), Toulouse, France.
Clément TurbelinSorbonne Université, INSERM, Institut Pierre Louis d'épidémiologie et de Santé publique, Paris, France.
Marianne SarazinSorbonne Université, INSERM, Institut Pierre Louis d'épidémiologie et de Santé publique, Paris, France.
Ana-Maria VilcuSorbonne Université, INSERM, Institut Pierre Louis d'épidémiologie et de Santé publique, Paris, France.
Louise RossignolSorbonne Université, INSERM, Institut Pierre Louis d'épidémiologie et de Santé publique, Paris, France.
Thierry BlanchonSorbonne Université, INSERM, Institut Pierre Louis d'épidémiologie et de Santé publique, Paris, France.
Maryse Lapeyre-MestreINSERM, Université de Toulouse (LEASP UMR 1027), Service de Pharmacologie médicale et clinique, CIC 1436, Centre Hospitalo-Universitaire de Toulouse (CHU Toulouse), Toulouse, France.
Thomas HanslikSorbonne Université, INSERM, Institut Pierre Louis d'épidémiologie et de Santé publique, Paris, France.
Inserm · FR

Funding

Agence Nationale de Sécurité du Médicament et des Produits de Santé AAP-2017-059
6 · The paper itself

Abstract

purposeDrug-drug interactions (DDIs) require monitoring in an aging population with increasing polypharmacy exposure. We aimed to estimate the prevalence of exposure to potential DDIs using the French healthcare insurance system database, for six DDIs with various clinical relevance: angiotensin II receptor blockers or angiotensin-converting enzyme inhibitors and nonsteroidal anti-inflammatory drugs (ARBs-ACEIs + NSAIDs), antiplatelet agents and NSAIDs (AAP + NSAIDs), serotonergic drugs and tramadol (SD + T), statins and macrolides (S + M), oral anticoagulant and NSAIDs (OAC + NSAIDs), and colchicine and macrolides (C + M).

methodsWe used exhaustive healthcare data from a 1/97th random sample of the population covered by the French health insurance system (EGB) between 2006 and 2016. Exposure to a DDI was defined as overlapping exposure to two interacting drugs. The prevalence of exposure was estimated by year.

resultsPrevalence of exposure in 2016 was estimated at 3.7% for ARBs-ACEIs + NSAIDs, 1.5% for AAP + NSAIDs, 0.76% for SD + T, 0.36% for S + M, 0.24% for AOC + NSAIDs, and 0.02% for C + M. In 26% to 58% of episodes of exposure, the two interacting drugs were prescribed by the same physician and dispensed by the same pharmacy the same day. Between 2006 and 2016, the yearly prevalence was increasing for SD + T and for DDIs involving NSAIDs, and it was decreasing for those involving macrolides.

conclusionExposures to potential DDIs in France are not uncommon with a high proportion resulting from a co-prescription by the same physician. Monitoring the prevalence of exposure to DDIs is needed to implement prevention measures. Administrative data enable this surveillance in large and representative cohorts.

Indexed as

Drug InteractionsAdolescentAdultAgedAged, 80 and overAngiotensin-Converting Enzyme InhibitorsAngiotensin Receptor AntagonistsAnticoagulantsAnti-Inflammatory Agents, Non-SteroidalChildChild, PreschoolDatabases, FactualDrug PrescriptionsFemaleFranceHumansAngiotensin-Converting Enzyme InhibitorsAngiotensin Receptor AntagonistsAnticoagulantsAnti-Inflammatory Agents, Non-SteroidalHydroxymethylglutaryl-CoA Reductase InhibitorsPlatelet Aggregation InhibitorsSerotonin AgentsTramadolDrug interactionsDrug safetyPharmacoepidemiologyPrevalence

Identifiers

PMID32632714
OpenAlexW3042043262

What OpenQuestion holds

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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.