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Abstract Many biomarkers that could be used to assess ejection fraction, heart failure, or myocardial infarction fail to translate into clinical practice because they lack essential performance characteristics or fail to meet regulatory standards for approval. Despite their potential, new technologies have added to the complexities of successful translation into clinical practice. Biomarker discovery and implementation require a standardized approach that includes: identification of a clinical need; identification of a valid surrogate biomarker; stepwise assay refinement, demonstration of superiority over current standard-of-care; development and understanding of a clinical pathway; and demonstration of real-world performance. Successful biomarkers should improve efficacy or safety of treatment, while being practical at a realistic cost. Everyone involved in cardiovascular healthcare, including researchers, clinicians, and industry partners, are important stakeholders in facilitating the development and implementation of biomarkers. This article provides suggestions for a development pathway for new biomarkers, discusses regulatory issues and challenges, and suggestions for accelerating the pathway to improve patient outcomes. Real-life examples of successful biomarkers—high-sensitivity cardiac troponin, T2* cardiovascular magnetic resonance imaging, and echocardiography—are used to illustrate the value of a standardized development pathway in the translation of concepts into routine clinical practice.
Ejection fraction, pathway, troponin, 610, heart failure, Heart failure, Biomarker, Troponin, magnetic resonance, Myocardial infarction, myocardial infarction, Magnetic resonance, 616, biomarker, ejection fraction, Pathway
Ejection fraction, pathway, troponin, 610, heart failure, Heart failure, Biomarker, Troponin, magnetic resonance, Myocardial infarction, myocardial infarction, Magnetic resonance, 616, biomarker, ejection fraction, Pathway
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 18 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |