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Multimarker approach for heart failure management: perspectives and limitations
1Laboratory of Cardiovascular Biochemistry - CNR - Institute of Clinical Physiology and Fondazione CNR-Regione Toscana "G. Monasterio", Via G. Moruzzi 1, 56125 Pisa, Italy. danielag@ifc.cnr.it
Insights
A multimarker approach using various laboratory data offers a cost-effective way to accurately assess heart failure (HF) risk and guide patient care. This strategy improves patient management and reduces healthcare costs.
Area of Science:
- Cardiology
- Biochemistry
- Genomics
Background:
- Heart failure (HF) presents a significant public health challenge, necessitating personalized risk assessment beyond clinical and imaging data.
- Current methods struggle to fully capture HF complexity, highlighting the need for advanced diagnostic tools.
- Identifying vulnerable patients is crucial for timely therapeutic interventions.
Purpose of the Study:
- To review the utility of a multimarker approach in heart failure (HF) risk stratification and management.
- To explore the potential of transcriptomic biomarkers for individual HF risk assessment.
- To emphasize the importance of cost-effective biomarker selection for optimal patient care.
Main Methods:
- Review of studies utilizing multimarker strategies for HF risk stratification.
- Analysis of biomarker combinations for predicting HF incidence and treatment response.
- Inclusion of insights into novel transcriptomic biomarkers for HF.
Main Results:
- Multimarker approaches demonstrate improved characterization of HF patients compared to single markers.
- Combined biomarkers enhance risk stratification, prediction of HF incidence, and evaluation of therapy response.
- Transcriptomic biomarkers show promise for personalized HF risk assessment.
Conclusions:
- A multimarker strategy, particularly a parsimonious and cost-effective selection, is essential for accurate HF management.
- This approach can optimize patient care by identifying individuals requiring closer monitoring.
- Integrating diverse biomarkers, including transcriptomic data, can reduce healthcare costs without compromising patient outcomes.
Abstract:
Heart failure (HF) is a major public health problem and the approach for an accurate individualization of HF risk and care should include a profile of laboratory data, in addition to clinical and imaging data. The possibility of identifying the most vulnerable patients is clinically important, especially considering that many therapeutic interventions are available today. This goal has not been yet reached although many novel biomarkers have been proposed and tested. The complexity of the biochemical network at the basis of HF pathophysiology clearly suggests that a single marker cannot reflect all the features of this syndrome, whereas the combined use of more indices would better characterize HF patients and create new options for their management, helping identify which patients to follow more closely. The multimarker approach, considering various biochemical pathways simultaneously, bases its robustness on a suitable choice of indices known to be individually associated with HF. The choice of biomarker combination is essential to the performance of the multimarker strategy. A major problem in selecting the biomarker profile is the proportional increase in economic burden; thus a "parsimonious" biomarker combination has to be used in a cost-effective evaluation. Statistical analysis and analytical performance of the different elements of the combination, in turn, may heavily influence results. This review summarizes the results obtained using a multimarker approach for HF risk stratification, for predicting HF incidence in a population, and evaluating the response to therapy. An insight into transcriptomic biomarkers, recently proposed for HF individual risk assessment, is also reported. A reliable selection of biomarkers for the careful management of HF patients is of pivotal importance in reducing healthcare costs without reducing patient care.
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