Evidence map›Paper›PMID 42854670›Full record

ReviewJACC. Basic to translational science2026

Cardiac Fibrosis as a Dynamic Therapeutic Target: Overcoming Translational Barriers to Antifibrotic Therapy.

Shuchishmita Maitra, Xander H T Wehrens, Svetlana Reilly

Abstract readReview
In one paragraph

Review in JACC. Basic to translational science, 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

3 authors.

Shuchishmita MaitraDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom.
Xander H T WehrensDepartment of Integrative Physiology, Cardiovascular Research Institute, Baylor College of Medicine, Houston, Texas, USA.
Svetlana ReillyDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom. Electronic address: svetlana.reilly@cardiov.ox.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiac fibrosis is a central feature of many cardiovascular diseases, contributing to myocardial stiffening, electrical dysfunction, and progression to heart failure. Despite its clinical importance, no therapy directly targeting myocardial fibrosis is currently established in practice. Advances in the understanding of cardiac fibroblast biology and profibrotic signaling pathways, including transforming growth factor-β and neurohormonal activation, have driven the development of multiple antifibrotic strategies in preclinical models, ranging from small molecules to gene- and cell-based approaches. However, translation into clinical benefit has remained limited, with existing evidence largely derived from early-phase studies that rely on indirect imaging or biomarker-based assessments. This review examines the mechanisms underpinning cardiac fibrosis and evaluates current antifibrotic strategies across key cardiovascular conditions from a translational perspective. We argue that translational failure arises not simply from ineffective therapies, but from a mismatch between the biological complexity of human fibrotic remodeling and the simplified paradigms underpinning current therapeutic development. We highlight key barriers to translation, including limitations of experimental models, fibroblast heterogeneity, temporal dependence of therapeutic efficacy, challenges in fibrosis assessment, and constraints in trial design. We further outline emerging strategies to bridge the translational gap.

Indexed as

antifibrotic therapiescardiovascular diseasefibrosistranslation

Identifiers

PMID42854670
PMCPMC13677188

What OpenQuestion holds

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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.