Evidence map›Paper›PMID 40178109›Full record

ArticleJournal of the American Heart Association2025

Development and Validation of Imaging-Free Myocardial Fibrosis Prediction Models, Association with Outcomes, and Sample Size Estimation for Phase 3 Trials.

Nicholas Black, Joshua Bradley, Gavin Lewis, Jakub Lagan, Christopher Orsborne, Fardad Soltani, John P Farrant, Theresa McDonagh, Matthias Schmitt, João L Cavalcante and 5 more

Abstract readValidation Study
In one paragraph

Article in Journal of the American Heart Association, 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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0cells of the map it votes in
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

15 authors.

Nicholas BlackDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre University of Manchester UK.ORCID 0000-0002-0089-6180
Joshua BradleyDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre University of Manchester UK.ORCID 0000-0002-0958-7392
Gavin LewisLiverpool University Hospitals NHS Foundation Trust Royal Liverpool University Hospital Liverpool UK.ORCID 0000-0001-6754-836X
Jakub LaganDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre University of Manchester UK.ORCID 0000-0003-0017-9082
Christopher OrsborneDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre University of Manchester UK.
Fardad SoltaniDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre University of Manchester UK.ORCID 0000-0003-2030-9761
John P FarrantDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre University of Manchester UK.ORCID 0000-0002-9241-2410
Theresa McDonaghKing's College Hospital London UK.
Matthias SchmittDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre University of Manchester UK.ORCID 0000-0001-8514-0261
João L CavalcanteAllina Health Minneapolis Heart Institute Abbott Northwestern Hospital Minneapolis MN USA.ORCID 0000-0002-3632-2074
Martin UganderKolling Institute Royal North Shore Hospital, and University of Sydney Australia.ORCID 0000-0003-3665-2038
Javed ButlerBaylor Scott and White Research Institute Dallas TX USA.ORCID 0000-0001-7683-4720
Mark C PetrieSchool of Cardiovascular and Metabolic Health University of Glasgow UK.ORCID 0000-0002-6333-9496
Christopher A MillerDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre University of Manchester UK.ORCID 0000-0002-5957-7088
Erik B SchelbertAllina Health Minneapolis Heart Institute Abbott Northwestern Hospital Minneapolis MN USA.ORCID 0000-0003-0356-4437

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhase 3 trials testing whether pharmacologic interventions targeting myocardial fibrosis improve outcomes require myocardial fibrosis measurement that does not rely on tomographic imaging with intravenous contrast.

methodsWe developed and externally validated extracellular volume (ECV) prediction models incorporating readily available data (comorbidity and natriuretic peptide variables), excluding tomographic imaging variables. Associations between predicted ECV and incident outcomes (death or hospitalization for heart failure) were tested in survival analysis. We created various sample size estimates for a hypothetical therapeutic clinical trial testing an antifibrotic therapy using (1) predicted ECV, (2) measured ECV, or (3) no ECV.

resultsMultivariable models predicting ECV had reasonable discrimination (optimism corrected C-statistic for predicted ECV ≥27%, 0.78 [95% CI, 0.75-0.80] in the derivation cohort [n=1663] and 0.74 [95% CI, 0.71-0.76] in the validation cohort [n=1578]) and reasonable calibration. Predicted ECV associated with adverse outcomes in Cox regression models: ECV ≥27% (binary variable) hazard ratio 2.21 (95% CI, 1.84-2.66). For a hypothetical clinical trial with an inclusion criterion of ECV ≥27%, use of predicted ECV (with probability threshold of 0.69 and 80% specificity) compared with measured ECV would obviate the need to perform 3940 cardiac magnetic resonance scans, at the cost of an additional 3052 participants screened and 705 participants enrolled.

conclusionsPredicted ECV (derived without tomographic imaging) associates with outcomes and efficiently identifies vulnerable patients who might benefit from treatment. Predicted ECV may foster the design of phase 3 trials targeting myocardial fibrosis with higher numbers of screened and enrolled participants, but with simplified eligibility criteria, avoiding the complexity of tomographic imaging.

Indexed as

CardiomyopathiesClinical Trials, Phase III as TopicHeart FailureMyocardiumAgedFemaleFibrosisHumansMaleMiddle AgedPredictive Value of TestsReproducibility of ResultsSample Sizecardiac magnetic resonanceextracellular volumemyocardial fibrosisphase 3 trial

Identifiers

PMID40178109
PMCPMC12132812

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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.