Abeer Abu-Zeitone1, Derick R Peterson2, Bronislava Polonsky3, Scott McNitt3, Arthur J Moss3. 1. Cardiology Division, Department of Medicine, University of Rochester Medical Center, Rochester, New York. Electronic address: abeer_abuzeitone@urmc.rochester.edu. 2. Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York. 3. Cardiology Division, Department of Medicine, University of Rochester Medical Center, Rochester, New York.
Abstract
BACKGROUND: In LQTS, β-blocker therapy is effective in reducing the risk of cardiac events (syncope, aborted cardiac arrest, sudden cardiac death). Limited studies have compared the efficacy of different β-blockers. OBJECTIVES: The goal of this study was to compare the efficacy of different β-blockers in long QT syndrome (LQTS) and in genotype-positive patients with LQT1 and LQT2. METHODS: The study included 1,530 patients from the Rochester, New York-based LQTS Registry who were prescribed common β-blockers (atenolol, metoprolol, propranolol, or nadolol). Time-dependent Cox regression analyses were used to compare the efficacy of different β-blockers with the risk of cardiac events in LQTS. RESULTS: Relative to being off β-blockers, the hazard ratios and 95% confidence intervals (CIs) for first cardiac events for atenolol, metoprolol, propranolol, and nadolol were 0.71 (0.50 to 1.01), 0.70 (0.43 to 1.15) 0.65 (0.46 to 0.90), and 0.51 (0.35 to 0.74), respectively. In LQT1, the risk reduction for first cardiac events was similar among the 4 β-blockers, but in LQT2, nadolol provided the only significant risk reduction (hazard ratio: 0.40 [0.16 to 0.98]). Among patients who had a prior cardiac event while taking β-blockers, efficacy for recurrent events differed by drug (p = 0.004), and propranolol was the least effective compared with the other β-blockers. CONCLUSIONS: Although the 4 β-blockers are equally effective in reducing the risk of a first cardiac event in LQTS, their efficacy differed by genotype; nadolol was the only β-blocker associated with a significant risk reduction in patients with LQT2. Patients experiencing cardiac events during β-blocker therapy are at high risk for subsequent cardiac events, and propranolol is the least effective drug in this high-risk group.
BACKGROUND: In LQTS, β-blocker therapy is effective in reducing the risk of cardiac events (syncope, aborted cardiac arrest, sudden cardiac death). Limited studies have compared the efficacy of different β-blockers. OBJECTIVES: The goal of this study was to compare the efficacy of different β-blockers in long QT syndrome (LQTS) and in genotype-positive patients with LQT1 and LQT2. METHODS: The study included 1,530 patients from the Rochester, New York-based LQTS Registry who were prescribed common β-blockers (atenolol, metoprolol, propranolol, or nadolol). Time-dependent Cox regression analyses were used to compare the efficacy of different β-blockers with the risk of cardiac events in LQTS. RESULTS: Relative to being off β-blockers, the hazard ratios and 95% confidence intervals (CIs) for first cardiac events for atenolol, metoprolol, propranolol, and nadolol were 0.71 (0.50 to 1.01), 0.70 (0.43 to 1.15) 0.65 (0.46 to 0.90), and 0.51 (0.35 to 0.74), respectively. In LQT1, the risk reduction for first cardiac events was similar among the 4 β-blockers, but in LQT2, nadolol provided the only significant risk reduction (hazard ratio: 0.40 [0.16 to 0.98]). Among patients who had a prior cardiac event while taking β-blockers, efficacy for recurrent events differed by drug (p = 0.004), and propranolol was the least effective compared with the other β-blockers. CONCLUSIONS: Although the 4 β-blockers are equally effective in reducing the risk of a first cardiac event in LQTS, their efficacy differed by genotype; nadolol was the only β-blocker associated with a significant risk reduction in patients with LQT2. Patients experiencing cardiac events during β-blocker therapy are at high risk for subsequent cardiac events, and propranolol is the least effective drug in this high-risk group.
Authors: Christian Steinberg; Gareth J Padfield; Basil Al-Sabeq; Arnon Adler; John A Yeung-Lai-Wah; Charles R Kerr; Marc W Deyell; Jason G Andrade; Matthew T Bennett; Raymond Yee; George J Klein; Martin Green; Zachary W M Laksman; Andrew D Krahn; Santabhanu Chakrabarti Journal: J Interv Card Electrophysiol Date: 2016-07-09 Impact factor: 1.900
Authors: Valentina Kutyifa; Usama A Daimee; Scott McNitt; Bronislava Polonsky; Charles Lowenstein; Kris Cutter; Coeli Lopes; Wojciech Zareba; Arthur J Moss Journal: Ann Noninvasive Electrocardiol Date: 2018-03-05 Impact factor: 1.468