Evidence map›Paper›PMID 40493357›Full record

ArticleClinical pharmacology and therapeutics2025

FRAME: Framework for Real-World Evidence Assessment to Mitigate Evidence Uncertainties for Efficacy/Effectiveness - An Evaluation of Regulatory and Health Technology Assessment Decision Making.

Gianmario Candore, Claire Martin, Mack J Mills, Annabel Suter, Anna Lloyd, Danitza Chavez-Montoya, Diego Civitelli, Birgit Wolf, Paul Bolot, Juergen Wasem and 3 more

Abstract read
In one paragraph

Article in Clinical pharmacology and therapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

13 authors.

Gianmario CandoreBayer AG, Berlin, Germany.ORCID 0000-0002-7299-7300
Claire MartinBayer AG, Berlin, Germany.
Mack J MillsLondon School of Economics, London, UK.
Annabel SuterWickenstones, Carlow, Ireland.ORCID 0009-0001-7777-1175
Anna LloydWickenstones, Carlow, Ireland.ORCID 0009-0002-4599-331X
Danitza Chavez-MontoyaLondon School of Economics, London, UK.
Diego CivitelliLondon School of Economics, London, UK.
Birgit WolfBayer AG, Berlin, Germany.
Paul BolotBayer Consumer Care AG, Basel, Switzerland.ORCID 0009-0005-8991-3483
Juergen WasemUniversity of Duisburg-Essen, Duisburg, Germany.ORCID 0000-0001-9653-168X
Montse Soriano GabarróBayer AG, Berlin, Germany.ORCID 0000-0002-3825-0182
Panos G KanavosLondon School of Economics, London, UK.
Mark SculpherCentre for Health Economics, University of York, York, UK.ORCID 0000-0003-3746-9913

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real-World Evidence (RWE) is increasingly used in submissions to regulatory agencies and health technology assessment bodies (HTAbs) to support the efficacy and effectiveness of new medicines and indications. However, there is limited information on the RWE characteristics that impact its role in approval and reimbursement decisions. To investigate these characteristics, we developed FRAME: a Framework for Real-world evidence Assessment to Mitigate Evidence uncertainties for efficacy/effectiveness. We compiled a list of medicinal product indications where RWE supported the efficacy of interventional trials or assessed effectiveness in observational settings. FRAME was applied to a prioritized subset of these submissions to authorities from North America, Europe, and Australia. For each product indication, we extracted information on characteristics describing the submission, clinical context, strength of evidence, and process factors from publicly available assessment reports. Of the 87 identified medicinal product indications, 15 were prioritized, covering 68 submissions and 76 RWE studies across 11 authorities in scope. Four main results emerged: (i) low granularity within assessment reports on the analyzed variables, limiting the learnings from analyzing them; (ii) variability in how RWE was assessed within and across regulatory agencies and HTAbs; (iii) a positive association between the proportion of positive comments from authorities on RWE studies and their impact on decision making. Particularly, a large effect size was consistently noted when RWE was considered primary evidence; and (iv) limited use of advanced RWE study designs. These findings support five recommendations to enhance shared learning on RWE, clarify its evidentiary value, and generate evidence to better support authorities' decision making.

Indexed as

Decision MakingDrug ApprovalEvidence-Based MedicineTechnology Assessment, BiomedicalAustraliaHumansUncertainty

Identifiers

PMID40493357
PMCPMC12355015

What OpenQuestion holds

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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.