Evidence map›Paper›PMID 41491904›Full record

ArticleDrug safety2026

Standardizing and Comparing Management Recommendations for Potential Drug-Drug Interactions Across Different Interaction Checkers.

Lelio Crupi, Louis Letinier, Vianney Jouhet, Sébastien Cossin, Antoine Pariente, Clement Mathieu, Guillaume L Martin, François Konschelle, Julie Rouanet, Massimo Carollo and 3 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Drug safety, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Lelio CrupiUniversité de Bordeaux, INSERM, BPH, Team AHeaD, INSERM U1219, 33000, Bordeaux, France.ORCID http://orcid.org/0009-0003-4888-2604
Louis LetinierSynapse Médicine, 33000, Bordeaux, France.ORCID http://orcid.org/0000-0001-5082-4866
Vianney JouhetService d'Information Médicale, Pôle de Santé Publique, CHU de Bordeaux, Team AHeaD, INSERM U1219, 33000, Bordeaux, France.ORCID http://orcid.org/0000-0001-5272-2265
Sébastien CossinEquipe EDS, CHU de Poitiers, 86000, Poitiers, France.ORCID http://orcid.org/0000-0002-3845-8127
Antoine ParienteUniversité de Bordeaux, INSERM, BPH, Team AHeaD, INSERM U1219, 33000, Bordeaux, France.ORCID http://orcid.org/0000-0002-7873-5483
Clement MathieuUniversité de Bordeaux, INSERM, BPH, Team AHeaD, INSERM U1219, 33000, Bordeaux, France.ORCID http://orcid.org/0000-0002-3615-148X
Guillaume L MartinSynapse Médicine, 33000, Bordeaux, France.
François KonschelleService d'Information Médicale, Pôle de Santé Publique, CHU de Bordeaux, Team AHeaD, INSERM U1219, 33000, Bordeaux, France.ORCID http://orcid.org/0000-0002-8193-2832
Julie RouanetUniversité de Bordeaux, INSERM, BPH, Team AHeaD, INSERM U1219, 33000, Bordeaux, France.
Massimo CarolloDepartment of Diagnostics and Public Health, University of Verona, 37134, Verona, Italy.ORCID http://orcid.org/0000-0002-6523-6036
Gianluca TrifiròDepartment of Diagnostics and Public Health, University of Verona, 37134, Verona, Italy.ORCID http://orcid.org/0000-0003-1147-7296
Emanuela EspositoDepartment of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, 98166, Messina, Italy.ORCID http://orcid.org/0000-0002-2663-6387
Francesco SalvoUniversité de Bordeaux, INSERM, BPH, Team AHeaD, INSERM U1219, 33000, Bordeaux, France. francesco.salvo@u-bordeaux.fr.ORCID http://orcid.org/0000-0003-3210-7171

Funding

French Ministry of Health 19-0170French Ministry of Health 2019French Ministry of Health PREPS
6 · The paper itself

Abstract

backgroundPotential drug-drug interactions (pDDIs) are frequent in clinical care, particularly among older patients. Accurate identification and management of pDDIs are essential for patient safety. Prescribers often rely on interaction checkers (ICs) to screen for pDDIs. However, these tools may provide inconsistent recommendations, potentially leading to suboptimal clinical decisions.

objectiveThis study aimed to develop a standardized approach for classifying and prioritizing pDDIs based on the clinical relevance of their management recommendations and to compare how these pDDIs are categorized across ICs.

methodsA scale was developed through a structured iterative process to classify pDDIs into four management categories (high priority, intermediate priority, low priority, data unavailable), based on the management recommendations extracted from six ICs. This scale was applied to 218 real-world pDDIs identified from 1923 patients, and the agreement was primarily assessed using Gwet's AC1. MAIN

resultsOverall agreement among the ICs was moderate (Gwet's AC1 = 0.44; 95% CI 0.39-0.50), with values ranging from 0.58 (0.51, 0.65) to 0.38 (0.31, 0.44) in leave-one-out analyses. The agreement was higher in binary analyses dichotomizing the scale into high- and intermediate-priority versus low-priority pDDIs (AC1 = 0.72; 95% CI 0.65-0.79), and in the classification of high-priority versus all other pDDIs (AC1 = 0.62; 95% CI 0.54-0.69).

conclusionThis study developed and tested a structured approach to systematically compare pDDI management across ICs and prioritize clinically relevant interactions. Its application revealed a generally limited agreement between ICs, pointing to the need for harmonized approaches and further studies to support more consistent, evidence-aligned pDDI management.

Indexed as

Drug-Related Side Effects and Adverse ReactionsAgedDrug InteractionsFemaleHumansMale

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.