Use of Multiple Biomarkers in Heart Failure

Abstract

Biomarkers are becoming increasingly available for clinical use, particularly in the care of patients with heart failure. For health care providers, a major difficulty is how to interpret and apply these increasing amounts of diagnostic and prognostic information. Consequently, the scientific challenge is evolving from the discovery of biomarkers to the selection and validation of select panels of clinically useful markers that balance performance and practicality. Optimal combinations of biomarkers will vary based on the intended use (eg, diagnosis vs prognosis). The final goal must be to generate more actionable knowledge that improves patient management and outcomes, rather than merely creating greater complexity. Here we conceptually define multiple biomarker strategies, provide examples of emerging biomarker panels used in the care of patients with heart failure, and address key statistical and clinical issues for this rapidly evolving field.

Charting a Roadmap for Heart Failure Biomarker Studies

“…Additionally, elevations in natriuretic peptide levels can occur as a result of several cardiac and noncardiac disease states, making the negative predictive value of the test most clinically helpful (13). As a result of these limitations, there is a need for better diagnostic algorithms, potentially through addition of novel biomarker information, to objective clinical and natriuretic peptide data (15). Ideal diagnostic biomarkers would feature rapid sustained elevation, high tissue specificity (myocardial origin), release proportional to disease extent, and assay features conducive to high quality point-of-care testing (16).…”

“…Effective therapies in heart failure such as implanted devices and cardiac transplantation are complex, costly, and rely on accurate risk stratification (17). Therefore, an ideal prognostic biomarker in heart failure should allow for early identification of individuals at risk for adverse clinical outcomes and should be relatively easy to measure, with acceptable costs (5,15). The biomarker measurement should display accuracy (the test is measuring what it is supposed to measure and generalizability (capacity to provide accurate predictions in population samples different than that in which the biomarker was originally validated).…”

Red cell distribution width predicts short- and long-term outcomes of acute congestive heart failure more effectively than hemoglobin

“…Therefore, accurate risk stratification is critically important in identifying high-risk patients who may benefit from advanced treatment (1–4). A number of clinical variables and biological markers have been applied over the last decade in predictive models of survival for patients with CHF (5,6), including inflammatory cytokines (7,8) high-sensitivity C-reactive protein (CRP) (9) natriuretic peptides (10,11) neurohormones (12) and oxidative stress (13), all of which are useful for diagnosis and prognosis. However, these biomarkers are very expensive to analyze and cost effectiveness must be considered when including markers in predictive models.…”

Correlation of noninvasive markers of cardiac allograft rejection with endomyocardial biopsy: A case report

“…15 Gene expression profiling (GEP) is a useful noninvasive biomarker that was designed specifically for this purpose to aid the diagnosis of acute cellular rejection in post-transplant recipients. 16 However, the true clinical utility of the gene expression profiling test remains relatively unknown because it seems to have been validated in low-risk cardiac transplant receipients not in the early postoperative period. 17 However, the Early Invasive Monitoring Attenuation through Gene Expression (EIMAGE) study by Kobashigawa and colleagues is under way, which aims to compare the use of AlloMap Molecular Expression Testing (AlloMap Ò ) with routine EMB for surveillance monitoring in the 2-to 6-month period after heart transplantation.…”