Clinical Adoption of Prognostic Biomarkers: The Case for Heart Failure
Section snippets
Framework for the development of new biomarkers in heart failure
The plethora of biomarkers in cardiovascular disease has necessitated a framework for the evaluation of emerging biomarkers in the context of clinical applications. Building on the original “benchmark criteria” for cardiovascular biomarkers initially proposed by Morrow and de Lemos in 2007,4 Maisel5 has recently proposed a revision to reflect the specific needs of the patients with HF and incorporate the possibilities of biomarker-guided targeted therapy and “biomonitoring” (Table 1). Similar
Current status of HF biomarker development
Recently, van Kimmenade and Januzzi7 have summarized the various domains of established and developing protein-based biomarkers in HF using a pathophysiologic classification. Realizing that several markers contribute to multiple pathways, we follow this classification in Table 2 to summarize the current development status of these markers. Similar to development of new drugs or devices, there are several steps in the process for an investigational biomarker to become a clinical tool for disease
Prognostic biomarkers in heart failure: building consistent evidence
The key to consistent (and comparable) evidence, with the ultimate goal to promote introduction of a new biomarker into practice, is reasonably consistent definitions of the population and the outcome of interest. For HF, these definitions have been drifting over time with little consistency even among contemporary studies.
The fallacy of “incremental value”
Currently, most investigational markers in cardiovascular medicine that target risk prediction undergo the scrutiny of demonstrating risk reclassification value—a concept that goes beyond an independent P value for prediction of outcomes or increment in C statistic.68 We expand on the risk reclassification in the next subheading. Because reclassification by definition requires a clinical risk prediction model as a yardstick to examine the added value of the new biomarker, the bar is invariably
Risk reclassification: the crossroads between statistical and clinical significance
Briefly, risk reclassification implies a change in the projected risk in the right direction with the use of the new marker as compared with the projected risk with the baseline, usually clinical model. This is accomplished when the biomarker-added model assigns higher risk to a substantial proportion of patients who eventually develop the event of interest and, conversely, lower risk to a substantial proportion of patients who do not develop the event. This is best clinically interpretable
Risk classification and clinical decision making in HF
For stable, eligible patients with stage D HF, decisions for LVAD implantation and/or listing for heart transplantation may be facilitated by 1-year mortality projections with multifactorial risk assessment tools.70 Therefore, prognosis refinement with biomarkers could impact decision making in this group. In fact, although biomarker-added models have not been endorsed for decisions in these patients, studies have suggested that biomarkers can meaningfully reclassify risk in these patients.8
Baseline vs serial biomarker measurements for risk assessment
Beyond serial measurements of BNP or NT-proBNP for HF status monitoring purposes, several other biomarkers have been evaluated in serial determinations as risk prediction tools. Cardiac troponins have been extensively studied both in acute77, 78, 79 and chronic80, 81 HF. Despite the potential of serial measurements to provide useful insights, especially in AHF, the issues in terms of a development framework are compounded with serial determinations. For example, in patients with AHF, troponins
Biomarkers for HF management
There are 3 main uses of biomarkers in the management of HF. First, biomarkers can be used as risk stratification tools as discussed above. Second, biomarkers can be used as biomonitoring tools with serial determinations to guide treatment intensity and facilitate decisions for management. In this respect, natriuretic peptide–guided therapy has been already tested extensively in clinical trials. The evidence, however, has been inconsistent thus far.82 A pooled data meta-analysis in 2009 showed
Biomarkers as therapeutic targets for HF treatment
Perhaps the most intriguing potential of biomarkers in HF is patient selection for specific therapies based on underlying pathophysiology as determined by biomarkers. Several post hoc analyses from clinical trials have shown that certain therapies benefit a specific subset of patients characterized by elevated levels of a relevant biomarker. For example, in a post hoc analysis from CORONA (Controlled Rosuvastatin Multinational Trial in Heart Failure), rosuvastatin treatment was associated with
Future directions
For biomarkers to become useful for risk stratification, a consensus is needed on a standardized framework for population and outcome definitions and a finite time horizon. Modeling of outcomes should be adapted to reflect the characteristics of the HF population of interest. On top of standard HF characteristics, a comorbidity score would be important to consider. Clinical application of risk stratification for decision making has persistent challenges before entering mainstream HF practice.
Statement of Conflict of Interest
All authors declare that there are no conflicts of interest.
Acknowledgments
Support: Supported in part by (a) PHS Grant UL1 RR025008 from the Clinical and Translational Science Award program, National Institutes of Health, National Center for Research Resources and (b) Grant 1U10HL110302-01 from the National Institutes of Health, National Heart, Lung, and Blood Institute.
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2016, International Journal of CardiologyCitation Excerpt :Fourth, many current investigations in the field of biomarkers assess risk reclassification over clinical models or older biomarkers. However, reclassification requires a meaningful initial risk classification, which does not currently exist for Stage C HF [45]. Therefore, we did not pursue risk reclassification analysis in our study.
Triple head-to-head comparison of fibrotic biomarkers galectin-3, osteopontin and gremlin-1 for long-term prognosis in suspected and proven acute heart failure patients
2016, International Journal of CardiologyCitation Excerpt :Increasing scientific interest has emerged for biomarkers reflecting the causative pathomechanisms regarding heart failure development, such as myocardial ischemia, cardiac inflammation [6] or cardiac fibrosis being associated with an adverse structural remodeling [7]. Commonly novel cardiac biomarkers for AHF were assessed within different study sites and heterogeneous populations [4]. On the contrary, biomarkers reflecting only one heart failure etiology are rarely investigated in one single representative cohort [4].
New onset heart failure - Clinical characteristics and short-term mortality. A RICA (Spanish registry of acute heart failure) study
2015, European Journal of Internal MedicineNovel prognostic tissue markers in congestive heart failure
2015, Cardiovascular PathologyCitation Excerpt :There are multiple distinct causes of heart failure including atherosclerotic coronary artery disease and nonischemic causes of heart failure such as myocarditis, storage diseases, amyloidosis, and inherited and idiopathic cardiomyopathies. Risk stratification or assessment of prognosis is becoming increasingly important in managing patients with heart failure, with such prognostication affecting choice of therapies, decisions to implant mechanical assist devices and defibrillators, and decision making concerning admission, discharge, and follow-up [2–4]. The hope is that, by defining risk more accurately in patients with heart failure, we will be better able to identify the patients who would benefit from more aggressive therapy and follow-up without incurring the unnecessary expenses of delivering the more aggressive management to low-risk patients not requiring such treatment.
Cardiovascular Biomarker Assessment Across Glycemic Status
2015, Glucose Intake and Utilization in Pre-Diabetes and Diabetes: Implications for Cardiovascular DiseaseHigh-sensitivity C-reactive protein in acute heart failure: Insights from the ASCEND-HF trial
2014, Journal of Cardiac FailureCitation Excerpt :From a clinical perspective, the profound proinflammatory state during acute HF, the slow resolution of inflammation, and the prognostic implications of protracted CRP elevations support the view that hospitalized HF is followed by a vulnerable period that spans several weeks to months after the index event.31 Similarly to neurohormonal activation, inflammation is a stress response that attempts to restore homeostasis.32 However, prolonged unbalanced exposure to a proinflammatory milieu can have detrimental effects to the cardiovascular system,33 and protracted exposure to inflammatory stimuli adversely affects ventricular function.34
Statement of Conflict of Interest: See page 10.