Wayne C Levy1, Anne S Hellkamp2, Daniel B Mark3, Jeanne E Poole4, Ramin Shadman5, Todd F Dardas4, Jill Anderson6, George Johnson6, Daniel P Fishbein4, Kerry L Lee2, David T Linker4, Gust H Bardy7. 1. Division of Cardiology, Department of Medicine, School of Medicine, University of Washington, Seattle, Washington. Electronic address: levywc@uw.edu. 2. Department of Biostatistics, Duke Clinical Research Institute, Duke University, Durham, North Carolina. 3. Division of Cardiology, Duke University Medical Center, Durham, North Carolina. 4. Division of Cardiology, Department of Medicine, School of Medicine, University of Washington, Seattle, Washington. 5. Division of Cardiology, Department of Medicine, Southern California Permanente Medical Group, Los Angeles, California. 6. Seattle Institute for Cardiac Research, Seattle, Washington. 7. Division of Cardiology, Department of Medicine, School of Medicine, University of Washington, Seattle, Washington; Seattle Institute for Cardiac Research, Seattle, Washington.
Abstract
OBJECTIVES: The authors previously developed the Seattle Proportional Risk Model (SPRM) in systolic heart failure patients without implantable cardioverter-defibrillators (ICDs)to predict the proportion of deaths that were sudden. They subsequently validated the SPRM in 2 observational ICD data sets. The objectives in the present study were to determine whether this validated model could improve identification of clinically important variations in the expected magnitude of ICD survival benefit by using a pivotal randomized trial of primary prevention ICD therapy. BACKGROUND: Recent data show that <50% of nominally eligible subjects receive guideline- recommended primary prevention ICDs. METHODS: In the SCD-HeFT (Sudden Cardiac Death in Heart Failure Trial), a placebo-controlled ICD trial in 2,521 patients with an ejection fraction ≤35% and symptomatic heart failure, we tested the use of patient-level SPRM-predicted probability of sudden death (relative to that of non-sudden death) as a summary measurement of the potential for ICD benefit. A Cox proportional hazards model was used to estimate variations in the relationship between patient-level SPRM predictions and ICD benefit. RESULTS: Relative to use of mortality predictions with the Seattle Heart Failure Model, the SPRM was much better at partitioning treatment benefit from ICD therapy (effect size was 2- to 3.6-fold larger for the ICD×SPRM interaction). ICD benefit varied significantly across SPRM-predicted risk quartiles: for all-cause mortality, a +10% increase with ICD therapy in the first quartile (highest risk of death, lowest proportion of sudden death) to a decrease of 66% in the fourth quartile (lowest risk of death, highest proportion of sudden death; p = 0.0013); for sudden death mortality, a 19% reduction in SPRM quartile 1 to 95% reduction in SPRM quartile 4 (p < 0.0001). CONCLUSIONS: In symptomatic systolic heart failure patients with a Class I recommendation for primary prevention ICD therapy, the SPRM offers a useful patient-centric tool for guiding shared decision making.
OBJECTIVES: The authors previously developed the Seattle Proportional Risk Model (SPRM) in systolic heart failurepatients without implantable cardioverter-defibrillators (ICDs)to predict the proportion of deaths that were sudden. They subsequently validated the SPRM in 2 observational ICD data sets. The objectives in the present study were to determine whether this validated model could improve identification of clinically important variations in the expected magnitude of ICD survival benefit by using a pivotal randomized trial of primary prevention ICD therapy. BACKGROUND: Recent data show that <50% of nominally eligible subjects receive guideline- recommended primary prevention ICDs. METHODS: In the SCD-HeFT (Sudden Cardiac Death in Heart Failure Trial), a placebo-controlled ICD trial in 2,521 patients with an ejection fraction ≤35% and symptomatic heart failure, we tested the use of patient-level SPRM-predicted probability of sudden death (relative to that of non-sudden death) as a summary measurement of the potential for ICD benefit. A Cox proportional hazards model was used to estimate variations in the relationship between patient-level SPRM predictions and ICD benefit. RESULTS: Relative to use of mortality predictions with the Seattle Heart Failure Model, the SPRM was much better at partitioning treatment benefit from ICD therapy (effect size was 2- to 3.6-fold larger for the ICD×SPRM interaction). ICD benefit varied significantly across SPRM-predicted risk quartiles: for all-cause mortality, a +10% increase with ICD therapy in the first quartile (highest risk of death, lowest proportion of sudden death) to a decrease of 66% in the fourth quartile (lowest risk of death, highest proportion of sudden death; p = 0.0013); for sudden deathmortality, a 19% reduction in SPRM quartile 1 to 95% reduction in SPRM quartile 4 (p < 0.0001). CONCLUSIONS: In symptomatic systolic heart failurepatients with a Class I recommendation for primary prevention ICD therapy, the SPRM offers a useful patient-centric tool for guiding shared decision making.
Authors: Tristram D Bahnson; Anna Giczewska; Daniel B Mark; Andrea M Russo; Kristi H Monahan; Hussein R Al-Khalidi; Adam P Silverstein; Jeanne E Poole; Kerry L Lee; Douglas L Packer Journal: Circulation Date: 2021-12-22 Impact factor: 39.918
Authors: Kenneth C Bilchick; Yongfei Wang; Jeptha P Curtis; Ramin Shadman; Todd F Dardas; Inder Anand; Lars H Lund; Ulf Dahlström; Ulrik Sartipy; Wayne C Levy Journal: J Am Heart Assoc Date: 2022-06-29 Impact factor: 6.106