Joint Shock/Death Risk Prediction Model for Patients Considering Implantable Cardioverter-Defibrillators: A Secondary Analysis of the SCD-HeFT trial. Issue 8 (August 2019)

• Record Type: Journal Article
• Authors: Reeder, Harrison T.; Shen, Changyu; Buxton, Alfred E.; Haneuse, Sebastien J.; Kramer, Daniel B.
• Is Part Of: Circulation. Volume 12:Issue 8(2019)
• Publication Date: 2019-08
• Subjects: defibrillators, implantable -- health services research -- heart failure -- risk; Cardiovascular system -- Diseases -- Treatment -- Periodicals; Cardiovascular system -- Diseases -- Research -- Periodicals; Outcome assessment (Medical care) -- Periodicals; Evidence-based medicine -- Periodicals; 616.1007
• DOI: 10.1161/CIRCOUTCOMES.119.005675
• Languages: English
• ISSNs: 1941-7713

Abstract

Abstract : Background: The risk of death or appropriate therapy varies widely among recipients of implantable cardioverter-defibrillators (ICDs). The goals of this study were to develop a risk prediction tool that jointly considers future outcome probabilities of ICD shock and death. Methods and Results: We performed a secondary analysis of patients receiving ICDs as part of the SCD-HeFT trial (Sudden Cardiac Death in Heart Failure Trial). We applied an illness-death regression model to jointly model both ICD shocks and death under the semi-competing risks framework, which predicts for each patient their probability of having received ICD shocks, dying, or both at any given point in time. Among 803 ICD recipients (mean age, 60 years; 23% women) followed for a median of 41.1 months, 430 (53.5%) patients completed the study without dying or receiving an ICD shock, 206 (25.7%) received at least 1 shock but survived, 113 (14.1%) died before experiencing a shock, and 54 (6.7%) received at least 1 shock and subsequently died. Predicted outcome probabilities based on baseline demographic and clinical variables reveal substantial heterogeneity in joint shock and death risks, both between patients at each time point and for each single patient across time. Overall, predictive performance for ICD shock and death individually was adequate, based on area under the curve at 5 years of 0.65 for shocks and of 0.79 for death. Conclusions: Our analysis of outcomes after ICD implantation provides an alternative predictive model for individual risk of death or ICD shocks. If validated, this may provide a useful tool for individualized counseling regarding likely outcomes after device implantation, while also informing the design of further studies to focus the clinical effectiveness and cost-effectiveness of ICD therapy. Clinical Trial Registration: URL:https://www.clinicaltrials.gov . Unique identifier: NCT00000609. Abstract : Supplemental Digital Content is available in the text.