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β-Blockers in Congestive Heart Failure: A Bayesian Meta-Analysis

James M. Brophy, MD, PhD; Lawrence Joseph, PhD; and Jean L. Rouleau, MD
[+] Article and Author Information

From the Centre Hospitalier de l'Université de Montréal, McGill University, and Montreal General Hospital, Montreal, Quebec; and University Health Network and Mount Sinai Hospitals, Toronto, Ontario, Canada.


Grant Support: Drs. Brophy and Joseph receive funding from Les Fonds de la Recherche en Santé du Québec.

Requests for Single Reprints: James Brophy, MD, PhD, Service de Cardiologie, Centre Hospitalier de l'Université de Montréal, Pavillon Notre-Dame, 1560 rue Sherbrooke Est, Montreal, Quebec H2L 4M1, Canada; e-mail, jbroph@po-box.mcgill.ca.

Current Author Addresses: Dr. Brophy: Service de Cardiologie, Centre Hospitalier de l'Université de Montréal, Pavillon Notre-Dame, 1560 rue Sherbrooke Est, Montreal, Quebec H2L 4M1, Canada.

Dr. Joseph: Department of Epidemiology and Biostatistics, McGill University, 1650 Cedar Avenue, Montreal, Quebec H3G 1A4, Canada.

Dr. Rouleau: Department of Medicine, University Health Network and Mount Sinai Hospital, 200 Elizabeth Street, Eaton North 13-212, Toronto, Ontario M5G 2C4, Canada.

Author Contributions: Conception and design: J.M. Brophy, L. Joseph.

Analysis and interpretation of the data: J.M. Brophy, L. Joseph, J.L. Rouleau.

Drafting of the article: J.M. Brophy, L. Joseph, J.L. Rouleau.

Critical revision of the article for important intellectual content: J.M. Brophy, L. Joseph, J.L. Rouleau.

Final approval of the article: J.M. Brophy, L. Joseph, J.L. Rouleau.

Provision of study materials or patients: Statistical expertise: J.M. Brophy, L. Joseph.

Administrative, technical, or logistic support: J.M. Brophy, J.L. Rouleau.

Collection and assembly of data: J.M. Brophy.


Ann Intern Med. 2001;134(7):550-560. doi:10.7326/0003-4819-134-7-200104030-00008
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Congestive heart failure has reached pan-epidemic proportions in industrialized countries and is responsible for vast patient morbidity and mortality (14). Mortality associated with moderate to severe congestive heart failure may exceed that associated with many neoplasms, and the 1-year survival rate is as dismal as 50% (5). Quality of life is also adversely affected, and congestive heart failure is the most common cause of hospital admission in elderly persons in North America (6). Clearly, additional therapies are urgently needed.

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Figure 1.
Mortality in the placebo and β-blocker groups of 22 studies.

Arrows indicate that the credible interval exceeds the scale; circles indicate point estimates; the bottom circle (in the “Total” row) indicates the overall best estimate of the effect. Aust/NZ = Australia/New Zealand Heart Failure Research Collaborative Group; CIBIS = Cardiac Insufficiency Bisoprolol Study; MERIT-HF = Metoprolol CR/XL Randomized Intervention Trial in Congestive Heart Failure; RESOLVD = Randomized Evaluation of Strategies for Left Ventricular Dysfunction Pilot Study.

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Figure 2.
Hospital admission for congestive heart failure in the placebo and β-blocker groups of 22 studies.

Arrows indicate that the credible interval exceeds the scale; circles indicate point estimates; the bottom circle (in the “Total” row) indicates the overall best estimate of the effect. Aust/NZ = Australia/New Zealand Heart Failure Research Collaborative Group; CIBIS = Cardiac Insufficiency Bisoprolol Study; MERIT-HF = Metoprolol CR/XL Randomized Intervention Trial in Congestive Heart Failure; n/a = not available; RESOLVD = Randomized Evaluation of Strategies for Left Ventricular Dysfunction Pilot Study.

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Figure 3.
Probability density curves for improvement in mortality rate (solid line) and hospital admission (dotted line) due to congestive heart failure among patients taking β-blockers.

The probability density functions for the number of lives saved and hospitalizations for congestive heart failure were calculated assuming a baseline annual mortality rate of 12% and a hospitalization rate of 14%. The area under the curve and to the right of any specified point on the abscissa is proportional to the probability of that event. For example, the probability of saving at least 2 lives per 100 patients treated is approximately 99% (almost the entire area to the right); the probability of saving 3 or more lives is 85%.

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Figure 4.
Probability density curves for improvement in survival with β-blocker therapy, according to sequential accumulation of data from trials published before 1999 (dotted line) and including those published in 1999 and 2000 (solid line).[17][18][34]

The probability density functions for the number of lives saved on the basis of data available before 1999 (at the time of previous meta-analyses) and by the end of 2000 (after publication of the Cardiac Insufficiency Bisoprolol Study II , the Metoprolol CR/XL Randomized Intervention Trial in Congestive Heart Failure trial , and the Randomized Evaluation of Strategies for Left Ventricular Dysfunction Pilot Study ) were calculated assuming a baseline annual mortality rate of 12%. The progressive narrowing of the curves shows the improved precision in estimation of the benefit of β-blocker therapy. This benefit is not only statistically but also clinically significant, as indicated by the virtual lack of an area under the curve to the left of 0.02 (that is, at least 2 lives saved per 100 persons).

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Summary for Patients

Beta-Blockers Improve Survival and Decrease Hospitalizations in Patients with Heart Failure

The summary below is from the full report titled “β-Blockers in Congestive Heart Failure. A Bayesian Meta-Analysis.” It is in the 3 April 2001 issue of Annals of Internal Medicine (volume 134, pages 550-560). The authors are JM Brophy, L Joseph, and JL Rouleau.

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