Evidence map›Paper›PMID 38564178›Full record

ArticleTherapeutic innovation & regulatory science2024

An Open-Source R Package for Detection of Adverse Events Under-Reporting in Clinical Trials: Implementation and Validation by the IMPALA (Inter coMPany quALity Analytics) Consortium.

Björn Koneswarakantha, Ronojit Adyanthaya, Jennifer Emerson, Frederik Collin, Annett Keller, Michaela Mattheus, Ioannis Spyroglou, Sandra Donevska, Timothé Ménard, IMPALA (Inter coMPany quALity Analytics) Consortium

Open access · hybridAbstract readValidation Study
In one paragraph

Article in Therapeutic innovation & regulatory science, 2024. 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
1.4field-weighted citation impact, top 20% 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, 2 citations in OpenAlex.

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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

10 authors at 3 institutions in 3 countries.

Björn KoneswarakanthaF. Hoffmann-La Roche AG, 4070, Basel, Switzerland.ORCID 0000-0003-4585-7799
Ronojit AdyanthayaMerck & Co., Inc., Rahway, NJ, 07065, USA.
Jennifer EmersonBoehringer Ingelheim Pharma GmbH & Co, 88397, Biberach an der Riss, Germany.
Frederik CollinBoehringer Ingelheim Pharma GmbH & Co, 88397, Biberach an der Riss, Germany.
Annett KellerBoehringer Ingelheim Pharma GmbH & Co, 55216, Ingelheim, Germany.
Michaela MattheusBoehringer Ingelheim Pharma GmbH & Co, 55216, Ingelheim, Germany.
Ioannis SpyroglouMerck & Co., Inc., Rahway, NJ, 07065, USA.
Sandra DonevskaMerck & Co., Inc., Rahway, NJ, 07065, USA.
Timothé MénardF. Hoffmann-La Roche AG, 4070, Basel, Switzerland. timothe.menard@roche.com.ORCID 0000-0003-4545-6944
IMPALA (Inter coMPany quALity Analytics) Consortium
Boehringer Ingelheim (Germany) · DEMerck & Co., Inc., Rahway, NJ, USA (United States) · USRoche (Switzerland) · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate and timely reporting of adverse events (AEs) in clinical trials is crucial to ensuring data integrity and patient safety. However, AE under-reporting remains a challenge, often highlighted in Good Clinical Practice (GCP) audits and inspections. Traditional detection methods, such as on-site investigator audits via manual source data verification (SDV), have limitations. Addressing this, the open-source R package {simaerep} was developed to facilitate rapid, comprehensive, and near-real-time detection of AE under-reporting at each clinical trial site. This package leverages patient-level AE and visit data for its analyses. To validate its efficacy, three member companies from the Inter coMPany quALity Analytics (IMPALA) consortium independently assessed the package. Results showed that {simaerep} consistently and effectively identified AE under-reporting across all three companies, particularly when there were significant differences in AE rates between compliant and non-compliant sites. Furthermore, {simaerep}'s detection rates surpassed heuristic methods, and it identified 50% of all detectable sites as early as 25% into the designated study duration. The open-source package can be embedded into audits to enable fast, holistic, and repeatable quality oversight of clinical trials.

Indexed as

Adverse Drug Reaction Reporting SystemsClinical Trials as TopicDrug-Related Side Effects and Adverse ReactionsHumansSoftwareAnalyticsGCPOpen-sourceQuality assuranceTransparencyValidation

Identifiers

PMID38564178
PMCPMC11169048
OpenAlexW4393411492

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.