Clinical phenogroups are more effective than left ventricular ejection fraction categories in stratifying heart failure outcomes

Abstract

Aims: Heart failure (HF) guidelines place patients into 3 discrete groups according to left ventricular ejection fraction (LVEF): reduced (<40%), mid-range (40-49%), and preserved LVEF (≥50%). We assessed whether clinical phenogroups offer better prognostication than LVEF.

Methods and results: This was a sub-study of the Patient-Centered Care Transitions in HF trial. We analysed baseline characteristics of hospitalized patients in whom LVEF was recorded. We used unsupervised machine learning to identify clinical phenogroups and, thereafter, determined associations between phenogroups and outcomes. Primary outcome was the composite of all-cause death or rehospitalization at 6 and 12 months. Secondary outcome was the composite cardiovascular death or HF rehospitalization at 6 and 12 months. Cluster analysis of 1693 patients revealed six discrete phenogroups, each characterized by a predominant comorbidity: coronary heart disease, valvular heart disease, atrial fibrillation (AF), sleep apnoea, chronic obstructive pulmonary disease (COPD), or few comorbidities. Phenogroups were LVEF independent, with each phenogroup encompassing a wide range of LVEFs. For the primary composite outcome at 6 months, the hazard ratios (HRs) for phenogroups ranged from 1.25 [95% confidence interval (CI) 1.00-1.58 for AF] to 2.04 (95% CI 1.62-2.57 for COPD) (log-rank P < 0.001); and at 12 months, the HRs for phenogroups ranged from 1.15 (95% CI 0.94-1.41 for AF) to 1.87 (95% 1.52-3.20 for COPD) (P < 0.002). LVEF-based classifications did not separate patients into different risk categories for the primary outcomes at 6 months (P = 0.69) and 12 months (P = 0.30). Phenogroups also stratified risk of the secondary composite outcome at 6 and 12 months more effectively than LVEF.

Conclusion: Among patients hospitalized for HF, clinical phenotypes generated by unsupervised machine learning provided greater prognostic information for a composite of clinical endpoints at 6 and 12 months compared with LVEF-based categories.

Trial registration: ClinicalTrials.gov Identifier: NCT02112227.

Keywords: Aetiology; Characteristics; Clinical Studies; Comorbidities; Ejection fraction; HFmrEF; HFpEF; Heart failure; Machine Learning; Mortality/Survival; Phenogroups; Prognosis; Risk Factors.

Figure 1

Heatmaps of characteristics (rows) and LVEF categories (columns) of 1693 patients. (A) Patient characteristics stratified according to clusters identified by an unbiased, LVEF‐independent approach. (B) Patient characteristics stratified according to the three guideline‐recommended LVEF categories, reduced, mid‐range, and preserved EF. (C) Patient characteristics stratified according to six LVEF categories (per 10%). Darker means higher value, lighter means lower value. AF, atrial fibrillation; CAD, coronary artery disease, COPD, chronic obstructive pulmonary disease; EF, ejection fraction; LVEF, left ventricular ejection fraction; NT‐proBNP, N‐terminal pro brain natriuretic peptide; OSA, obstructive sleep apnoea; PCI/CABG, percutaneous coronary intervention or coronary artery bypass grafting; VHD, valvular heart disease.

Figure 2

Survival curves of heart failure patients stratified according to LVEF‐based classifications or LVEF‐independent phenogroup‐based classification. Survival curves for all‐cause death or rehospitalization at 6 months, adjusted for age and sex. P value from log‐rank test. Survival differs significantly across groups using the LVEF‐independent phenogroup‐based classification (A) but not in LVEF‐based classifications (B,C). (A) Kaplan–Meier curves stratified according to phenogroups. (B) Kaplan–Meier curves stratified according to the three guideline‐recommended LVEF categories, reduced, mid‐range, and preserved EF. (C) Kaplan–Maier curves according to six LVEF categories (per 10%). AF, atrial fibrillation; CAD, coronary artery disease; COPD, chronic obstructive pulmonary disease; EF, ejection fraction; LVEF, left ventricular ejection fraction; OSA, obstructive sleep apnoea; VHD, valvular heart disease.

Figure 3

Survival curves of heart failure patients stratified according to LVEF‐based classifications or LVEF‐independent phenogroup‐based classification. Survival curves for all‐cause death or rehospitalization at 12 months, adjusted for age and sex. P value from log‐rank test. Survival differs significantly across groups using the LVEF‐independent phenogroup‐based classification (A) but not in LVEF‐based classifications (B,C). (A) Kaplan–Meier curves stratified according to phenogroups. (B) Kaplan–Meier curves stratified according to the three guideline‐recommended LVEF categories, reduced, mid‐range, and preserved EF. (C) Kaplan–Meier curves according to six LVEF categories (per 10%). AF, atrial fibrillation; CAD, coronary artery disease; COPD, chronic obstructive pulmonary disease; EF, ejection fraction; LVEF, left ventricular ejection fraction; OSA, obstructive sleep apnoea; VHD, valvular heart disease.

Figure 4

Summary of the study findings. We analysed baseline characteristics of 1693 patients with heart failure included in the Patient‐Centered Care Transitions in Heart Failure randomized clinical trial. Clustering analysis independent of LVEF, better separated survival curves, provided more information and less overlap of clinical phenogroups compared to guideline‐recommended subdivision in three LVEF‐based categories. Through clustering analysis, we found six clinical phenogroups mainly based on comorbidities. COPD, chronic obstructive pulmonary disease; HFmrEF, heart failure with mid‐range ejection fraction; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; HR, hazard ratio; LVEF, left ventricular ejection fraction.