Clinical implications of chronic heart failure phenotypes defined by cluster analysis

Tariq Ahmad, Michael J. Pencina, Phillip J. Schulte, Emily O'Brien, David J. Whellan, Ileana L. Pina, Dalane W. Kitzman, Kerry L. Lee, Christopher M. O'Connor, G. Michael Felker

Research output: Contribution to journalArticle

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Abstract

Background Classification of chronic heart failure (HF) is on the basis of criteria that may not adequately capture disease heterogeneity. Improved phenotyping may help inform research and therapeutic strategies. Objectives This study used cluster analysis to explore clinical phenotypes in chronic HF patients

Methods A cluster analysis was performed on 45 baseline clinical variables from 1,619 participants in the HF-ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training) study, which evaluated exercise training versus usual care in chronic systolic HF. An association between identified clusters and clinical outcomes was assessed using Cox proportional hazards modeling. Differential associations between clinical outcomes and exercise testing were examined using interaction testing-absp. Results Four clusters were identified (ranging from 248 to 773 patients in each), in which patients varied considerably among measures of age, sex, race, symptoms, comorbidities, HF etiology, socioeconomic status, quality of life, cardiopulmonary exercise testing parameters, and biomarker levels. Differential associations were observed for hospitalization and mortality risks between and within clusters. Compared with cluster 1, risk of all-cause mortality and/or all-cause hospitalization ranged from 0.65 (95% confidence interval [95% CI]: 0.54 to 0.78) for cluster 4 to 1.02 (95% CI: 0.87 to 1.19) for cluster 3. However, for all-cause mortality, cluster 3 had a disproportionately lower risk of 0.61 (95% CI: 0.44 to 0.86). Evidence suggested differential effects of exercise treatment on changes in peak oxygen consumption and clinical outcomes between clusters (p for interaction <0.04)-absp. Conclusions Cluster analysis of clinical variables identified 4 distinct phenotypes of chronic HF. Our findings underscore the high degree of disease heterogeneity that exists within chronic HF patients and the need for improved phenotyping of the syndrome. (Exercise Training Program to Improve Clinical Outcomes in Individuals With Congestive Heart Failure; NCT00047437).

Original languageEnglish (US)
Pages (from-to)1765-1774
Number of pages10
JournalJournal of the American College of Cardiology
Volume64
Issue number17
DOIs
StatePublished - Oct 28 2014

Fingerprint

Cluster Analysis
Heart Failure
Phenotype
Exercise
Confidence Intervals
Mortality
Hospitalization
Therapeutic Human Experimentation
Systolic Heart Failure
Social Class
Oxygen Consumption
Comorbidity
Biomarkers
Quality of Life
Education

Keywords

  • mortality
  • prognosis
  • rehospitalization
  • socioeconomic

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Cite this

Ahmad, T., Pencina, M. J., Schulte, P. J., O'Brien, E., Whellan, D. J., Pina, I. L., ... Felker, G. M. (2014). Clinical implications of chronic heart failure phenotypes defined by cluster analysis. Journal of the American College of Cardiology, 64(17), 1765-1774. https://doi.org/10.1016/j.jacc.2014.07.979

Clinical implications of chronic heart failure phenotypes defined by cluster analysis. / Ahmad, Tariq; Pencina, Michael J.; Schulte, Phillip J.; O'Brien, Emily; Whellan, David J.; Pina, Ileana L.; Kitzman, Dalane W.; Lee, Kerry L.; O'Connor, Christopher M.; Felker, G. Michael.

In: Journal of the American College of Cardiology, Vol. 64, No. 17, 28.10.2014, p. 1765-1774.

Research output: Contribution to journalArticle

Ahmad, T, Pencina, MJ, Schulte, PJ, O'Brien, E, Whellan, DJ, Pina, IL, Kitzman, DW, Lee, KL, O'Connor, CM & Felker, GM 2014, 'Clinical implications of chronic heart failure phenotypes defined by cluster analysis', Journal of the American College of Cardiology, vol. 64, no. 17, pp. 1765-1774. https://doi.org/10.1016/j.jacc.2014.07.979
Ahmad, Tariq ; Pencina, Michael J. ; Schulte, Phillip J. ; O'Brien, Emily ; Whellan, David J. ; Pina, Ileana L. ; Kitzman, Dalane W. ; Lee, Kerry L. ; O'Connor, Christopher M. ; Felker, G. Michael. / Clinical implications of chronic heart failure phenotypes defined by cluster analysis. In: Journal of the American College of Cardiology. 2014 ; Vol. 64, No. 17. pp. 1765-1774.
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abstract = "Background Classification of chronic heart failure (HF) is on the basis of criteria that may not adequately capture disease heterogeneity. Improved phenotyping may help inform research and therapeutic strategies. Objectives This study used cluster analysis to explore clinical phenotypes in chronic HF patientsMethods A cluster analysis was performed on 45 baseline clinical variables from 1,619 participants in the HF-ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training) study, which evaluated exercise training versus usual care in chronic systolic HF. An association between identified clusters and clinical outcomes was assessed using Cox proportional hazards modeling. Differential associations between clinical outcomes and exercise testing were examined using interaction testing-absp. Results Four clusters were identified (ranging from 248 to 773 patients in each), in which patients varied considerably among measures of age, sex, race, symptoms, comorbidities, HF etiology, socioeconomic status, quality of life, cardiopulmonary exercise testing parameters, and biomarker levels. Differential associations were observed for hospitalization and mortality risks between and within clusters. Compared with cluster 1, risk of all-cause mortality and/or all-cause hospitalization ranged from 0.65 (95{\%} confidence interval [95{\%} CI]: 0.54 to 0.78) for cluster 4 to 1.02 (95{\%} CI: 0.87 to 1.19) for cluster 3. However, for all-cause mortality, cluster 3 had a disproportionately lower risk of 0.61 (95{\%} CI: 0.44 to 0.86). Evidence suggested differential effects of exercise treatment on changes in peak oxygen consumption and clinical outcomes between clusters (p for interaction <0.04)-absp. Conclusions Cluster analysis of clinical variables identified 4 distinct phenotypes of chronic HF. Our findings underscore the high degree of disease heterogeneity that exists within chronic HF patients and the need for improved phenotyping of the syndrome. (Exercise Training Program to Improve Clinical Outcomes in Individuals With Congestive Heart Failure; NCT00047437).",
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