C Funck-Brentano1, R Lancar, S Hansen, S H Hohnloser, E Vanoli. 1. Department of Pharmacology, Saint-Antoine Hospital, Saint-Antoine Faculty of Medicine, Paris, France. christian.funck-brentano@sat.ap-hop-paris.fr
Abstract
AIMS: Predictive factors for medical events and interactions between events were not reported in the Cardiac Insufficiency Bisoprolol Study 2 (CIBIS-2). We examined the interactions among death, permanent treatment withdrawals, nonlethal cardiovascular hospitalizations and their own occurrence in a given patient, the treatment received, and baseline variables during CIBIS-2. METHODS AND RESULTS: A Cox model for censored data was used to analyze the relations among baseline variables, medical events, and their interactions with treatment. We used competitive risk analysis to examine the interactions between successive events in a given patient during follow-up. No baseline variable predicted the reduction of mortality with bisoprolol. Withdrawal from bisoprolol therapy was more frequent in patients whose baseline heart rate was in the lower tertile of the distribution (P =.0002) but otherwise was not different between patients randomized to bisoprolol and to placebo. Event history analysis revealed that bisoprolol reduced mortality (P =.0006) and hospitalizations for nonlethal cardiovascular events (P =.003) in patients in whom treatment was not permanently withdrawn. Analysis of survival curves in patients who permanently discontinued treatment showed that bisoprolol did not reduce mortality compared with placebo in this population (relative risk 1.03, 95% CI 0.67-1.59; P =.88). Recurrent nonlethal events were reduced by bisoprolol. CONCLUSION: In CIBIS-2, medical events were significantly influenced by treatment withdrawal. Patients who derive benefit from bisoprolol therapy are those in whom treatment is not permanently withdrawn.
RCT Entities:
AIMS: Predictive factors for medical events and interactions between events were not reported in the Cardiac InsufficiencyBisoprolol Study 2 (CIBIS-2). We examined the interactions among death, permanent treatment withdrawals, nonlethal cardiovascular hospitalizations and their own occurrence in a given patient, the treatment received, and baseline variables during CIBIS-2. METHODS AND RESULTS: A Cox model for censored data was used to analyze the relations among baseline variables, medical events, and their interactions with treatment. We used competitive risk analysis to examine the interactions between successive events in a given patient during follow-up. No baseline variable predicted the reduction of mortality with bisoprolol. Withdrawal from bisoprolol therapy was more frequent in patients whose baseline heart rate was in the lower tertile of the distribution (P =.0002) but otherwise was not different between patients randomized to bisoprolol and to placebo. Event history analysis revealed that bisoprolol reduced mortality (P =.0006) and hospitalizations for nonlethal cardiovascular events (P =.003) in patients in whom treatment was not permanently withdrawn. Analysis of survival curves in patients who permanently discontinued treatment showed that bisoprolol did not reduce mortality compared with placebo in this population (relative risk 1.03, 95% CI 0.67-1.59; P =.88). Recurrent nonlethal events were reduced by bisoprolol. CONCLUSION: In CIBIS-2, medical events were significantly influenced by treatment withdrawal. Patients who derive benefit from bisoprolol therapy are those in whom treatment is not permanently withdrawn.