Seattle Heart Failure and Proportional Risk Models Predict Benefit From Implantable Cardioverter-Defibrillators

Kenneth C. Bilchick, Yongfei Wang, Alan Cheng, Jeptha P. Curtis, Kumar Dharmarajan, George J. Stukenborg, Ramin Shadman, Inder Anand, Lars H. Lund, Ulf Dahlström, Ulrik Sartipy, Aldo Maggioni, Karl Swedberg, Chris O’Conner, Wayne C. Levy

Recent clinical trials highlight the need for better models to identify patients at higher risk of sudden death. The authors hypothesized that the Seattle Heart Failure Model (SHFM) for overall survival and the Seattle Proportional Risk Model (SPRM) for proportional risk of sudden death, including death from ventricular arrhythmias, would predict the survival benefit with an implantable cardioverter-defibrillator (ICD). Patients with primary prevention ICDs from the National Cardiovascular Data Registry (NCDR) were compared with control patients with heart failure (HF) without ICDs with respect to 5-year survival using multivariable Cox proportional hazards regression. Among 98,846 patients with HF (87,914 with ICDs and 10,932 without ICDs), the SHFM was strongly associated with all-cause mortality (p < 0.0001). The ICD-SPRM interaction was significant (p < 0.0001), such that SPRM quintile 5 patients had approximately twice the reduction in mortality with the ICD versus SPRM quintile 1 patients (adjusted hazard ratios [HR]: 0.602; 95% confidence interval [CI]: 0.537 to 0.675 vs. 0.793; 95% CI: 0.736 to 0.855, respectively). Among patients with SHFM-predicted annual mortality ≤5.7%, those with a SPRM-predicted risk of sudden death below the median had no reduction in mortality with the ICD (adjusted ICD HR: 0.921; 95% CI: 0.787 to 1.08; p = 0.31), whereas those with SPRM above the median derived the greatest benefit (adjusted HR: 0.599; 95% CI: 0.530 to 0.677; p < 0.0001). The SHFM predicted all-cause mortality in a large cohort with and without ICDs, and the SPRM discriminated and calibrated the potential ICD benefit. Together, the models identified patients less likely to derive a survival benefit from primary prevention ICDs.