Evidence map›Paper›PMID 41169436›Full record

ArticleFrontiers in medicine2025

A model structure for describing uncertainties in benefit-risk assessment of oncology drug applications.

Nikolaos Zafiropoulos, Francesco Pignatti, Andreas Kouroumalis, Lorenzo Guizzaro, Dominik Karres, Pierre Demolis, Olli Tenhunen, Rosanne Janssens, Anne Taams, Lourens T Bloem and 2 more

Abstract read
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Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

12 authors.

Nikolaos ZafiropoulosMedical University Vienna, Vienna, Austria.
Francesco PignattiEuropean Medicines Agency, Amsterdam, Netherlands.
Andreas KouroumalisEuropean Medicines Agency, Amsterdam, Netherlands.
Lorenzo GuizzaroEuropean Medicines Agency, Amsterdam, Netherlands.
Dominik KarresEuropean Medicines Agency, Amsterdam, Netherlands.
Pierre DemolisAgence Nationale de Sécurité du Médicament et des produits de santé (ANSM), Paris, France.
Olli TenhunenFinnish Medicines Agency (FIMEA), Helsinki, Finland.
Rosanne JanssensKatholieke Universiteit Leuven, Leuven, Belgium.
Anne TaamsDivision of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands.
Lourens T BloemDivision of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands.
Franz KoenigMedical University Vienna, Vienna, Austria.
Martin PoschMedical University Vienna, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The European Medicines Agency (EMA) uses structured reports to communicate the scientific review of drug applications. A European Public Assessment Report (EPAR) is published at the end of the review detailing the scientific assessment, which includes benefit-risk analysis and uncertainties in favorable and unfavorable effects. Currently, there is no detailed guidance on how to communicate uncertainties in the EPAR. This study aimed to identify uncertainties described in the benefit-risk section of a series of EPARs and derive a possible model structure for communicating them. Methods: A series of approved oncology drug applications that had used the latest EPAR template at the time of analysis was selected. The model structure was adapted iteratively, aiming to identify a small number of key elements, with input from the study team. Finally, the model structure was discussed with two experienced clinical assessors to determine clarity and potential usefulness. Results: From 64 oncology EPARs published between 2011 and 2017 (26 related to products with orphan designation), 263 uncertainties in the benefit-risk assessment were identified. The final model structure included Cause (what causes the uncertainty), Aspect (what is the uncertainty about, further described as a high-level domain and a specific component), Type (what is the kind of uncertainty, like not enough information or conflicting information), and Strategy (how the uncertainty is addressed). This four-element structure, Cause, Aspect, Type, Strategy (CATS), was discussed with expert assessors and was found to be generally understandable and relevant. Discussion: The CATS model structure has been derived as a starting point for communicating uncertainties in benefit-risk assessment of drug applications. To increase relevance, it was derived based on issues raised during actual reviews and discussed with expert reviewers. Limitations include the narrow focus of the current series and the need for validation. If found useful, this structure could eventually be used to further enhance assessment report templates. Conclusion: The proposed CATS model structure may facilitate communicating uncertainties in the benefit-risk assessment of drug applications. Further refinements, depending on the purpose and validation, aiming at broader applicability, are needed.

Indexed as

benefit risk assessmentEuropean Medicines Agency (EMA)oncology medicinesregulatory decision makinguncerainty

Identifiers

PMID41169436
PMCPMC12568669

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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.