BACKGROUND: The Seattle Heart Failure Model (SHFM) is a well validated prediction model of all-cause mortality in patients with heart failure, but its relationship with generic health status measures has not been evaluated. We sought to investigate relationships between SHFM scores and health utility weights, which are necessary to estimate quality-adjusted life-years in cost-effectiveness analyses. METHODS AND RESULTS: We applied mixed linear regression to examine relationships between baseline SHFM scores and EQ-5D-derived health utilities collected longitudinally in a large clinical trial. A 1-unit increase in SHFM score (higher predicted mortality) was associated with a 0.030 decrease in utility (P < .001) and an additional 0.006 decrease per year (P < .001). With SHFM score modeled as a categorical variable, EQ-5D utilities for patients with rounded SHFM scores of 1 or 2 were significantly lower (-0.041 and -0.053, respectively; both P < .001) and declined more rapidly over time (-0.011 and -0.020, respectively; both P ≤ .004) than for patients with scores of -1. CONCLUSIONS: Patients with higher SHFM-predicted mortality had significantly lower health utilities at baseline and greater rates of decline over time, compared with patients with lower SHFM-predicted mortality. These relationships can be applied when examining the cost-effectiveness of heart failure interventions.
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BACKGROUND: The Seattle Heart Failure Model (SHFM) is a well validated prediction model of all-cause mortality in patients with heart failure, but its relationship with generic health status measures has not been evaluated. We sought to investigate relationships between SHFM scores and health utility weights, which are necessary to estimate quality-adjusted life-years in cost-effectiveness analyses. METHODS AND RESULTS: We applied mixed linear regression to examine relationships between baseline SHFM scores and EQ-5D-derived health utilities collected longitudinally in a large clinical trial. A 1-unit increase in SHFM score (higher predicted mortality) was associated with a 0.030 decrease in utility (P < .001) and an additional 0.006 decrease per year (P < .001). With SHFM score modeled as a categorical variable, EQ-5D utilities for patients with rounded SHFM scores of 1 or 2 were significantly lower (-0.041 and -0.053, respectively; both P < .001) and declined more rapidly over time (-0.011 and -0.020, respectively; both P ≤ .004) than for patients with scores of -1. CONCLUSIONS:Patients with higher SHFM-predicted mortality had significantly lower health utilities at baseline and greater rates of decline over time, compared with patients with lower SHFM-predicted mortality. These relationships can be applied when examining the cost-effectiveness of heart failure interventions.
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