Targeted multimarker approaches may offer the capability to enhance risk prediction and to better understand underlying biologic abnormalities in HFpEF.

Seiffert, Stuart Prenner, Payman Zamani, Priyanka Bhattacharya, Anupam Kumar, Kenneth B.

Cappola Julio A. Chirinos Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania Bristol-Myers Squibb Company, Lawrenceville, New Jersey Vanderbilt University Medical Center, Nashville, Tennessee Address for correspondence: Dr.

Julio A. Chirinos, South Tower, Room 11-138, Perelman Center for Advanced Medicine, 3400 Civic Center Boulevard, Philadelphia, Pennsylvania 19104.

Twitter: JulioChirinosMd.

Drs. Chirinos and Olenko have contributed equally to this work.

Search for more papers by this author, Alena Orlenko Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania Bristol-Myers Squibb Company, Lawrenceville, New Jersey Vanderbilt University Medical Center, Nashville, Tennessee Drs.

Search for more papers by this author, Lei Zhao Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania Bristol-Myers Squibb Company, Lawrenceville, New Jersey Vanderbilt University Medical Center, Nashville, Tennessee Search for more papers by this author, Michael D.

Margulies Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania Bristol-Myers Squibb Company, Lawrenceville, New Jersey Vanderbilt University Medical Center, Nashville, Tennessee Search for more papers by this author, Bruce D.

Car Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania Bristol-Myers Squibb Company, Lawrenceville, New Jersey Vanderbilt University Medical Center, Nashville, Tennessee Search for more papers by this author, David A.

Gordon Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania Bristol-Myers Squibb Company, Lawrenceville, New Jersey Vanderbilt University Medical Center, Nashville, Tennessee Search for more papers by this author, Jason H.

Moore Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania Bristol-Myers Squibb Company, Lawrenceville, New Jersey Vanderbilt University Medical Center, Nashville, Tennessee Search for more papers by this author, and Thomas P.

Cappola Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania Bristol-Myers Squibb Company, Lawrenceville, New Jersey Vanderbilt University Medical Center, Nashville, Tennessee Search for more papers by this author J Am Coll Cardiol.

Mar, 75 (11) 12811295 Editorial Comment: A Biomarker Approach to Understanding HFpEF Sections Abstract PDF Podcast.

Objectives The purpose of this study was to assess the value of a targeted plasma multi-marker approach to enhance our phenotypic characterization and risk prediction in HFpEF.

The relationship between biomarkers and the risk of all-cause death or heart failure-related hospital admission (DHFA) was assessed.

A tree-based pipeline optimizer platform was used to generate a multimarker predictive model for DHFA.

We validated the model in an independent cohort of HFpEF patients enrolled in the PHFS (Penn Heart Failure Study) (n 156).

A machine-learningderived model using a combination of biomarkers was strongly predictive of the risk of DHFA (standardized hazard ratio: 2.85; 95 confidence interval: 2.03 to 4.02; p Conclusions Various novel circulating biomarkers in key pathophysiological domains are predictive of outcomes in HFpEF, and a multimarker approach coupled with machine-learning represents a promising strategy for enhancing risk stratification in HFpEF.

Introduction The prevalence of heart failure (HF) has markedly increased and now represents an enormous clinical and public health problem.

Heart failure with a preserved ejection fraction (HFpEF) accounts for approximately one-half of all HF cases, a proportion that will likely increase as the population ages.

To date, no pharmacological interventions have clearly proven to improve outcomes in randomized trials in HFpEF.

HFpEF is a heterogeneous condition, and accordingly, patients with HFpEF exhibit a variable clinical course and prognosis.

At present, more accurate risk-stratification strategies are required, which need to be incremental and independent of clinical prediction scores.

Advances in peripheral blood analytical techniques provide an opportunity to measure multiple biomarkers using small volumes of plasma, an approach that could be readily implemented in clinical practice and in participant selection for clinical trials.

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