Multiple biomarker strategies for risk stratification in heart failure

• Current risk stratification of heart failure does not fully explain all the risk associated with the condition.
• Heart failure is a complex disease in which development and progression concur several different processes.
• Combination of several biomarkers is the best approach for stratifying the risk associated with heart failure.
• To choice the best combination of biomarkers, rigorous statistical approaches are required.

Biomarkers of cardiovascular diseases are indispensable tools for diagnosis and prognosis, and the use of biomarkers is now considered standard-of-care. New markers continue to be developed, but few prove to be substantially better than established markers. Heart failure (HF) risk stratification may be refined by the use of biomarkers for different pathobiological processes that established mortality risk factors do not directly reflect. Biomarkers that are currently available can provide information about at least seven pathobiological processes operative in HF, help to identify the specific processes involved in individual patients, and aid in constructing management plans. However, the additional prognostic information gained by any biomarker over a clinical risk model plus other biomarkers needs to be determined with adequate statistical tools. A major problem in selecting a biomarker profile is the proportional increase in economic burden; thus, the addition of any biomarker to a profile should be justified by adequate discrimination, calibration, reclassification, and likelihood analyses. This review assesses the value of multimarker strategies in both acutely decompensated (ADHF) and chronic HF. Most data on biomarkers have been derived from patient cohorts with chronic HF. However, risk prediction in patients admitted with ADHF remains a challenge. ADHF is not a single disease, it presents in various manners and different etiologies may underlie ADHF, which are reflected by different biomarkers. The optimal panel of markers, the change in these markers over time, and how these changes might help guide therapeutic interventions remain to be defined.