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Seattle proportional risk model in GISSI-HF: Estimated benefit of ICD in patients with EF less than 50
Lee B Bockus1, Ramin Shadman2, Jeanne E Poole1
1Department of Medicine,University of Washington, Seattle, WA.
Insights
The Seattle Proportional Risk Model (SPRM) accurately predicts sudden cardiac death (SCD) risk in heart failure patients. This model aids in identifying candidates for implantable cardioverter-defibrillator (ICD) therapy, improving decision-making for primary prevention.
Area of Science:
- Cardiology
- Medical Statistics
- Clinical Trials
Background:
- The Seattle Proportional Risk Model (SPRM) estimates sudden cardiac death (SCD) risk in heart failure (HF) patients to guide implantable cardioverter-defibrillator (ICD) therapy decisions.
- The GISSI-HF trial investigated the efficacy of fish oil and rosuvastatin in HF patients.
- This study evaluates the SPRM's accuracy in predicting ICD benefit within the GISSI-HF cohort, specifically for patients with ejection fraction (EF) ≤50%.
Purpose of the Study:
- To assess the accuracy of the Seattle Proportional Risk Model (SPRM) in predicting sudden cardiac death (SCD) risk.
- To evaluate the SPRM's ability to identify heart failure patients who may benefit from implantable cardioverter-defibrillator (ICD) therapy.
- To compare the SPRM's predictions with traditional criteria for ICD implantation in the GISSI-HF trial population.
Main Methods:
- The SPRM was calculated for patients with an ejection fraction (EF) of 50% or less.
- A logistic regression model was employed to compare sudden cardiac death (SCD) versus non-SCD outcomes.
- The SPRM's performance was analyzed in 6,750 patients from the GISSI-HF trial with EF ≤50%.
Main Results:
- The SPRM accurately predicted SCD risk, with an estimated proportion of 44% versus an observed 41% at one year.
- Fifty percent of patients with EF ≤35% and 43% with EF 36% to 50% had an SPRM score of ≥50%.
- The SPRM identified a distinct patient group (47.8%) eligible for ICDs, including those with EF >35%, suggesting broader applicability than traditional criteria (64.5% eligible).
Conclusions:
- The SPRM effectively discriminated between SCD and non-SCD in heart failure patients across different ejection fraction ranges (≤35% and 36% to 50%).
- The model demonstrated comparable estimated ICD benefit for patients with EF ≤35% and EF 36% to 50% when SPRM was ≥50%.
- These findings support the use of the SPRM for shared decision-making in primary prevention ICD therapy discussions.
Background:
The Seattle Proportional Risk Model (SPRM) estimates the proportion of sudden cardiac death (SCD) in heart failure (HF) patients, identifying those most likely to benefit from implantable cardioverter-defibrillator (ICD) therapy (those with ≥50% estimated proportion of SCD). The GISSI-HF trial tested fish oil and rosuvastatin in HF patients. We used the SPRM to evaluate its accuracy in this cohort in predicting potential ICD benefit in patients with EF ≤50% and an SPRM-predicted proportion of SCD either ≥50% or <50%.
Methods:
The SPRM was estimated in patients with EF ≤50% and in a logistic regression model comparing SCD with non-SCD.
Results:
We evaluated 6,750 patients with EF ≤50%. There were 1,892 all-cause deaths, including 610 SCDs. Fifty percent of EF ≤35% patients and 43% with EF 36% to 50% had an SPRM of ≥50%. The SPRM (OR: 1.92, P < 0.0001) accurately predicted the risk of SCD vs non-SCD with an estimated proportion of SCD of 44% vs the observed proportion of 41% at 1 year. By traditional criteria for ICD implantation (EF ≤35%, NYHA class II or III), 64.5% of GISSI-HF patients would be eligible, with an estimated ICD benefit of 0.81. By SPRM >50%, 47.8% may be eligible, including 30.2% with EF >35%. GISSI-HF participants with EF ≤35% with SPRM ≥50% had an estimated ICD HR of 0.64, comparable to patients with EF 36% to 50% with SPRM ≥50% (HR: 0.65).
Conclusions:
The SPRM discriminated SCD vs non-SCD in GISSI-HF, both in patients with EF ≤35% and with EF 36% to 50%. The comparable estimated ICD benefit in patients with EF ≤35% and EF 36% to 50% supports the use of a proportional risk model for shared decision making with patients being considered for primary prevention ICD therapy.
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