ReviewJACC. Heart failure2014
Charting a roadmap for heart failure biomarker studies.
Review in JACC. Heart failure, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk of bias in studies investigating novel diagnostic biomarkers for heart failure with preserved ejection fraction. A systematic review.European journal of heart failure · 2020Pooled it
- Plasma Ceramides and Sphingomyelins in Relation to Heart Failure Risk.Circulation. Heart failure · 2019Trial
- Plasma Biomarkers Reflecting Profibrotic Processes in Heart Failure With a Preserved Ejection Fraction: Data From the Prospective Comparison of ARNI With ARB on Management of Heart Failure With Preserved Ejection Fraction Study.Circulation. Heart failure · 2016Trial
- Galectin-3 in heart failure with preserved ejection fraction. A RELAX trial substudy (Phosphodiesterase-5 Inhibition to Improve Clinical Status and Exercise Capacity in Diastolic Heart Failure).JACC. Heart failure · 2015Trial
- Advancements in Biomarkers for Early Detection and Risk Stratification of Cardiovascular Diseases-A Literature Review.Health science reports · 2025Article
- IdentifyingBiomolecules · 2024Article
- New Biomarkers for Cardiovascular Disease.Texas Heart Institute journal · 2023Review
- Do Heart Failure Biomarkers Influence Heart Failure Treatment Response?Current heart failure reports · 2023Review
- Growth Differentiation Factor 15 (GDF-15), a New Biomarker in Heart Failure Management.Current heart failure reports · 2023Review
- Soluble Urokinase Plasminogen Activator Receptor Levels and Outcomes in Patients with Heart Failure.Journal of cardiac failure · 2023Article
- Biomarker prognostication across Universal Definition of Heart Failure stages.ESC heart failure · 2022Article
- Interatrial Block Predicts Life-Threatening Arrhythmias in Dilated Cardiomyopathy.Journal of the American Heart Association · 2022Article
- Review
- Serum parathyroid hormone levels in patients with chronic right heart failure.Biomedical reports · 2020Article
- Cardiac Biomarkers: What Is and What Can Be.Indian journal of cardiovascular disease in women WINCARS · 2018Article
- Role for Cystatin C-Based Risk Stratification for Patients After Acute Coronary Syndrome in the Era of High Sensitivity Cardiac Troponin Assays.Journal of the American Heart Association · 2018Article
- The Trifecta of Precision Care in Heart Failure: Biology, Biomarkers, and Big Data.Journal of the American College of Cardiology · 2018Article
- Using matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) profiling in order to predict clinical outcomes of patients with heart failure.Clinical proteomics · 2018Article
- Plasma proteome analysis in patients with pulmonary arterial hypertension: an observational cohort study.The Lancet. Respiratory medicine · 2017Observational
- What happens to stable heart failure patients when they don't take their medicines?European journal of heart failure · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
Heart failure is a syndrome with a pathophysiological basis that can be traced to dysfunction in several interconnected molecular pathways. Identification of biomarkers of heart failure that allow measurement of the disease on a molecular level has resulted in enthusiasm for their use in prognostication and selection of appropriate therapies. However, despite considerable amounts of information available on numerous biomarkers, inconsistent research methodologies and lack of clinical correlations have made bench-to-bedside translations rare and left the literature with countless publications of varied quality. There is a need for a systematic and collaborative approach aimed at definitively studying the clinical benefits of novel biomarkers. In this review, on the basis of input from academia, industry, and governmental agencies, we propose a systematized approach based on adherence to specific quality measures for studies looking to augment current prediction model or use biomarkers to tailor therapeutics. We suggest that study quality, rather than results, should determine publication and propose a system for grading biomarker studies. We outline the need for collaboration between clinical investigators and statisticians to introduce more advanced statistical methodologies into the field of biomarkers that would allow for data from a large number of variables to be distilled into clinically actionable information. Lastly, we propose the creation of a heart failure biomarker consortium that would allow for a comprehensive list of biomarkers to be concomitantly analyzed in a pooled sample of randomized clinical trials and hypotheses to be generated for testing in biomarker-guided trials. Such a consortium could collaborate in sharing samples to identify biomarkers, undertake meta-analyses on completed trials, and spearhead clinical trials to test the clinical utility of new biomarkers.
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What OpenQuestion holds
Registered trials
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.