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Original Contribution |

β-Blocker Use and Clinical Outcomes in Stable Outpatients With and Without Coronary Artery Disease FREE

Sripal Bangalore , MD, MHA; Gabriel Steg, MD; Prakash Deedwania, MD; Kevin Crowley, MS; Kim A. Eagle, MD; Shinya Goto, MD, PhD; E. Magnus Ohman, MD; Christopher P. Cannon, MD; Sidney C. Smith, MD; Uwe Zeymer, MD; Elaine B. Hoffman, PhD; Franz H. Messerli, MD; Deepak L. Bhatt, MD, MPH ; for the REACH Registry Investigators
[+] Author Affiliations

Author Affiliations: Cardiovascular Clinical Research Center, New York University School of Medicine, New York, New York (Dr Bangalore); INSERM U-698, University Paris Diderot, Hospital Bichat, AP-HP, Paris, France (Dr Steg); Department of Internal Medicine/Cardiology, University of California San Francisco School of Medicine, Fresno (Dr Deedwania); TIMI Study Group, Boston, Massachusetts (Drs Cannon, Hoffman, and Bhatt and Mr Crowley); Cardiovascular Center, University of Michigan Health System, Ann Arbor (Dr Eagle); Tokai University School of Medicine, Isehara, Japan (Dr Goto); Duke University Medical Center, Durham, North Carolina (Dr Ohman); Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts (Drs Cannon and Bhatt); Center for Cardiovascular Science and Medicine, University of North Carolina, Chapel Hill (Dr Smith); Herzzentrum Ludwigshafen and Institut fur Herzinfarktforschung Ludwigshafen, Ludwigshafen, Germany (Dr Zeymer); St Luke's Roosevelt Hospital, New York, New York (Dr Messerli); and VA Boston Healthcare System, Boston, Massachusetts (Dr Bhatt).


JAMA. 2012;308(13):1340-1349. doi:10.1001/jama.2012.12559.
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Published online

Context β-Blockers remain the standard of care after a myocardial infarction (MI). However, the benefit of β-blocker use in patients with coronary artery disease (CAD) but no history of MI, those with a remote history of MI, and those with only risk factors for CAD is unclear.

Objective To assess the association of β-blocker use with cardiovascular events in stable patients with a prior history of MI, in those with CAD but no history of MI, and in those with only risk factors for CAD.

Design, Setting, and Patients Longitudinal, observational study of patients in the Reduction of Atherothrombosis for Continued Health (REACH) registry who were divided into 3 cohorts: known prior MI (n = 14 043), known CAD without MI (n = 12 012), or those with CAD risk factors only (n = 18 653). Propensity score matching was used for the primary analyses. The last follow-up data collection was April 2009.

Main Outcome Measures The primary outcome was a composite of cardiovascular death, nonfatal MI, or nonfatal stroke. The secondary outcome was the primary outcome plus hospitalization for atherothrombotic events or a revascularization procedure.

Results Among the 44 708 patients, 21 860 were included in the propensity score–matched analysis. With a median follow-up of 44 months (interquartile range, 35-45 months), event rates were not significantly different in patients with β-blocker use compared with those without β-blocker use for any of the outcomes tested, even in the prior MI cohort (489 [16.93%] vs 532 [18.60%], respectively; hazard ratio [HR], 0.90 [95% CI, 0.79-1.03]; P = .14). In the CAD without MI cohort, the associated event rates were not significantly different in those with β-blocker use for the primary outcome (391 [12.94%]) vs without β-blocker use (405 [13.55%]) (HR, 0.92 [95% CI, 0.79-1.08]; P = .31), with higher rates for the secondary outcome (1101 [30.59%] vs 1002 [27.84%]; odds ratio [OR], 1.14 [95% CI, 1.03-1.27]; P = .01) and for the tertiary outcome of hospitalization (870 [24.17%] vs 773 [21.48%]; OR, 1.17 [95% CI, 1.04-1.30]; P = .01). In the cohort with CAD risk factors only, the event rates were higher for the primary outcome with β-blocker use (467 [14.22%]) vs without β-blocker use (403 [12.11%]) (HR, 1.18 [95% CI, 1.02-1.36]; P = .02), for the secondary outcome (870 [22.01%] vs 797 [20.17%]; OR, 1.12 [95% CI, 1.00-1.24]; P = .04) but not for the tertiary outcomes of MI (89 [2.82%] vs 68 [2.00%]; HR, 1.36 [95% CI, 0.97-1.90]; P = .08) and stroke (210 [6.55%] vs 168 [5.12%]; HR, 1.22 [95% CI, 0.99-1.52]; P = .06). However, in those with recent MI (≤1 year), β-blocker use was associated with a lower incidence of the secondary outcome (OR, 0.77 [95% CI, 0.64-0.92]).

Conclusion In this observational study of patients with either CAD risk factors only, known prior MI, or known CAD without MI, the use of β-blockers was not associated with a lower risk of composite cardiovascular events.

Figures in this Article

Treatment with β-blockers remains the standard of care for patients with coronary artery disease (CAD), especially when they have had a myocardial infarction (MI).1,2 The evidence is derived from relatively old post-MI studies, most of which antedate modern reperfusion or medical therapy, and from heart failure trials, but has been widely extrapolated to patients with CAD and even to patients at high risk for but without established CAD. It is not known if these extrapolations are justified. Moreover, the long-term efficacy of these agents in patients treated with contemporary medical therapies is not known, even in patients with prior MI.

β-Blockers are not without adverse effects and their tolerability is not ideal. Among 17 035 patients with MI, only 45% of patients were adherent to β-blocker use 1-year after an MI.3 The objective of the present longitudinal, observational study was to evaluate the differential association of β-blocker use on long-term cardiovascular outcomes in patients with known prior MI, in patients with known CAD without MI, and in patients with only risk factors for CAD.

The design, methods, and results of the Reduction of Atherothrombosis for Continued Health (REACH) registry, an international, prospective, observational registry, have been published elsewhere.47 Briefly, REACH enrolled consecutive eligible patients aged 45 years or older with established CAD, cerebrovascular disease, or peripheral arterial disease, or with at least 3 atherothrombotic risk factors during a 7-month recruitment period between December 2003 and June 2004; because of regulatory requirements in Japan, the enrollment in that country was delayed and occurred between August 2004 and December 2004. The last patient was enrolled in December 2004 and the date of final data collection was April 2009. Signed informed consent was obtained from all patients and the institutional review board in each country approved the protocol. The study participants were from 7 geographical regions.

Patients with data on β-blocker use were divided into 3 groups: known prior MI, CAD without known MI, and CAD risk factors only. Each of these groups was divided into 2 subgroups based on β-blocker use at the time of enrollment. The CAD cohort was identified by documented history of percutaneous coronary intervention, coronary artery bypass graft surgery, or ischemia but without a known history of MI. Data were collected centrally using standardized case report forms. Patients were followed-up prospectively for up to 4 years for the occurrence of cardiovascular outcomes, hospitalization, or vascular interventions. The primary outcome was a composite of cardiovascular death, nonfatal MI, or nonfatal stroke. The secondary outcome was the primary outcome plus hospitalization for atherothrombotic events or a revascularization procedure (coronary, cerebral, or peripheral). Tertiary outcomes were all-cause mortality, cardiovascular mortality, nonfatal MI, nonfatal stroke, and hospitalization, which were considered as separate outcomes.

Statistical Analysis

All analyses were performed using SAS software version 9.2 (SAS Institute Inc). Power calculations were performed using accrual over 7 months and a median follow-up of 44 months. For the known prior MI cohort, which had 14 000 patients and 30% without β-blocker use, there was 80% power to detect a hazard ratio (HR) of 0.87. Similarly, for the known CAD without MI cohort, which had 12 000 patients and 40% without β-blocker use, there was 80% power to detect an HR of 0.87 to show benefit and 1.14 to show harm. For the cohort with only risk factors for CAD, which had 19 000 patients and 75% without β-blocker use, there was 80% power to detect an HR of 0.89 to show benefit and 1.13 to show harm.

Propensity Score Matching

The analysis was based on the intention-to-treat principle regardless of subsequent β-blocker use. Because of differences in key baseline characteristics (Table 1, Table 2, and Table 3), we used propensity score matching for the 3 cohorts to assemble a cohort for each comparison, in which all the measured covariates would be well balanced across comparator groups. The propensity score is the conditional probability of having a particular exposure (β-blocker use) given a set of measured baseline covariates.8,9 Propensity scores were estimated using a non–parsimonious multivariable logistic regression model,10 with the dependent variable of β-blocker use, and the 27 baseline characteristics entered as covariates. Matching was performed using a SAS macro with a greedy matching protocol (matching ratio of 1 to 1 without replacement) and a caliper width of 0.6 of the standard deviation. We estimated standardized differences for all covariates before and after matching to assess prematch imbalance and postmatch balance.11 Standardized differences of less than 10% for a given covariate indicate a relatively small imbalance.11

Table Graphic Jump LocationTable 1. Baseline Characteristics of Cohort With Known Prior Myocardial Infarction
Table Graphic Jump LocationTable 2. Baseline Characteristics of the Cohort With Known Coronary Artery Disease Without Myocardial Infarction
Table Graphic Jump LocationTable 3. Baseline Characteristics of the Cohort With Risk Factors Only But No Known Coronary Artery Disease

Paired comparisons were performed using conditional logistic regression analysis for categorical variables and paired t test for continuous variables. The risk of outcomes in the group with β-blocker use vs without β-blocker use was estimated using a Cox proportional hazard regression model stratified on the matched pairs. The analyses were exploratory in nature so no P value adjustment for multiple testing was applied.

In the propensity score–matched analysis, many patients remained unmatched and were thus excluded from the analysis (which may lead to slightly reduced efficiency). Therefore, a regression adjustment with the propensity score (as a continuous variable) was also performed,12 in which all the patients in the cohort were analyzed.

For both the propensity score–matched and propensity score–adjusted analyses, the proportional hazards assumptions were violated for hospitalization-related outcomes because the exact dates of hospitalization were not available. For these outcomes, odds ratios (ORs) are reported rather than HRs. The proportional hazards assumption was tested using Schoenfeld residuals, which help determine nonproportionality over time either graphically or by testing for a nonzero slope in a regression model of residuals on time.

The differential association of β-blocker use across the 3 cohorts was tested using a test for interaction with a P value of less than .10 considered statistically significant. All tests were 2-tailed and (aside from the test for interaction) a P value of less than .05 was considered statistically significant.

Sensitivity Analysis

Given the well-known, beneficial association of β-blocker use with reduction in morbidity and mortality among patients with heart failure, a sensitivity analysis was conducted after excluding patients with known heart failure. In addition, analyses were performed using β-blocker use as a time-dependent covariate that incorporates changes in β-blocker use over time. In addition, analyses based on inverse probability weighting were performed.13 For this purpose, a propensity score weight, also referred to as the inverse probability of treatment weight, was calculated as the inverse of the propensity score. Analyses were conducted to test for internal validity of the data set using one cohort with recent MI (≤1 year) and another with known heart failure, both of which have shown utility of β-blocker use in prior studies.

From the REACH registry, 44 708 patients satisfied the inclusion criteria of whom 14 043 patients (31%) had prior MI, 12 012 patients (27%) had documented CAD but without MI, and 18 653 patients (42%) had CAD risk factors only. In the included cohort, 96% of patients had 2-year follow-up and 74% of the cohort had 4-year follow-up. The overall median follow-up was 44 months (interquartile range [IQR], 35-45 months). Among the 44 708 patients, 21 860 were included in the propensity score–matched analysis.

Prior MI Cohort

In the prior MI cohort, there were 9451 patients (67%) with β-blocker use. There were significant differences between patients with β-blocker use and those without β-blocker use in the baseline characteristics prior to matching (Table 1). Propensity score matching matched 3379 patients with β-blocker use (36% of the cohort) with 3379 patients without β-blocker use (74% of the cohort) with similar propensity scores. After propensity score matching, there were no significant differences in baseline variables (Table 1), with absolute standardized differences of less than 10% for all variables, indicating an adequate match (eFigure 1). The median follow-up was 43 months (IQR, 30-45 months) in the group with β-blocker use vs 43 months (IQR, 29-45 months) in the group without β-blocker use.

The event rates were not significantly different in those with β-blocker use (489 [16.93%]) vs those without β-blocker use (532 [18.60%]) for the primary outcome (HR, 0.90 [95% CI, 0.79-1.03]; P = .14; Figure 1), the secondary outcome (30.96% vs 33.12%, respectively; OR, 0.91 [95% CI, 0.82-1.00]; Figure 2), or any of the tertiary outcomes (Figure 2; eFigures 2-4) of cardiovascular death (9.68% vs 10.27%; P = .31), MI (5.50% vs 5.51%; P = .42), and stroke (4.44% vs 5.21%; P = .28) in the matched cohort. The results were similar in the propensity score–adjusted model (eFigure 5).

Place holder to copy figure label and caption
Figure 1. Cumulative Incidence Curve for the Risk of Primary Outcome by β-Blocker Use
Graphic Jump Location

Y-axis range shown in blue indicates event rate from 0% to 14%. The primary outcome was a composite of cardiovascular death, nonfatal MI, or nonfatal stroke. CAD indicates coronary artery disease; HR, hazard ratio; and MI, myocardial infarction.

Place holder to copy figure label and caption
Figure 2. Risk of Event Outcomes in the Matched Cohort
Graphic Jump Location

The primary outcome was a composite of cardiovascular death, nonfatal MI, or nonfatal stroke. The secondary outcome was the primary outcome plus hospitalization for atherothombotic events or a revascularization procedure. CAD indicates coronary artery disease; HR, hazard ratio; and MI, myocardial infarction.aOutcomes analyzed using a logistic regression analysis.

CAD Without MI Cohort

In the CAD without MI cohort, there were 6864 patients (57%) with β-blocker use. There were significant differences between patients with β-blocker use vs those without β-blocker use in the baseline characteristics prior to matching (Table 2). Propensity score matching matched 3599 patients with β-blocker use (52% of the cohort) with 3599 patients without β-blocker use (70% of the cohort) with similar propensity scores. After propensity score matching (Table 2), the absolute standardized differences were less than 10% for all matched variables, indicating an adequate match (eFigure 6). The median follow-up was 43 months (IQR, 31-45 months) in the group with β-blocker use vs 43 months (IQR, 31-45 months) in the group without β-blocker use.

The event rates were not different in those with β-blocker use (391 [12.94%]) vs those without β-blocker use (405 [13.55%]) for the primary outcome (HR, 0.92 [95% CI, 0.79-1.08]; P = .31; Figure 1), for cardiovascular death (5.90% vs 6.97%, respectively; P = .32; eFigure 7), for stroke (4.84% vs 4.79%; P = .39; eFigure 8), and for MI (3.79% vs 2.98%; OR, 1.24 [95% CI, 0.91-1.69]; P = .16; eFigure 9). The event rates were higher in those with β-blocker use (1101 [30.59%]) vs those without β-blocker use (1002 [27.84%]) for the secondary outcome (OR, 1.14 [95% CI, 1.03-1.27]; P = .01) and for hospitalization (870 [24.17%] vs 773 [21.48%], respectively; OR, 1.17 [95% CI, 1.04-1.30]; P = .01) in the propensity score–matched model (Figure 2). The results were similar in the propensity score–adjusted model (eFigure ).

Risk Factors Alone Cohort

In the risk factors alone cohort, there were 4854 patients (26%) with β-blocker use. Prior to propensity score matching, there were significant differences between patients with β-blocker use vs those without β-blocker use in the baseline characteristics (Table 3). Propensity score matching matched 3952 patients with β-blocker use (81% of the cohort) with 3952 patients without β-blocker use (29% of the cohort) with similar propensity scores. After propensity score matching (Table 3), the absolute standardized differences were less than 10% for all matched variables, indicating an adequate match (eFigure 10). The median follow-up was 43 months (IQR, 32-45 months) in the group with β-blocker use vs 43 months (IQR, 31-45 months) in the group without β-blocker use.

The event rates were higher in those with β-blocker use (467 [14.22%]) vs those without β-blocker use (403 [12.11%]) for the primary outcome (HR, 1.18 [95% CI, 1.02-1.36]; P = .02; Figure 1), for the secondary outcome (870 [22.01%] vs 797 [20.17%], respectively; OR, 1.12 [95% CI, 1.00-1.24]; P = .04) but not for MI (89 [2.82%] vs 68 [2.00%]; HR, 1.36 [95% CI, 0.97-1.90]; P = .08; eFigure 11), and for stroke (210 [6.55%] vs 168 [5.12%]; HR, 1.22 [95% CI, 0.99-1.52]; P = .06; eFigure 12). In the propensity score–matched model, there were similar event rates for cardiovascular death (6.41% in patients with β-blocker use vs 6.40% in those without β-blocker use; P = .66; eFigure 13) and for hospitalization (14.62% vs 13.74%, respectively; P = .26; Figure 2). The results were similar in a propensity score–adjusted model (eFigure ).

β-Blocker Use Cohort Interaction

A significant interaction was found for secondary outcome risk both in the propensity score–matched (P = .003 for interaction; Figure 2) and the propensity score–adjusted models (P = .006 for interaction; eFigure ), such that the effect of β-blocker use was not uniform across the cohorts. The secondary outcome risk was not different in the prior MI cohort, whereas in the CAD cohort and the risk factors alone cohort, patients with β-blocker use had a 12% to 14% higher secondary outcome risk compared with the group without β-blocker use. A similar interaction was noted for the outcomes of MI (P = .08 for interaction) and hospitalization (P = .03 for interaction; Figure 2), such that the effect of β-blocker use was not uniform across the cohorts.

Sensitivity Analysis

A sensitivity analysis that was performed in the cohort of patients without known heart failure yielded largely similar results (eFigure 14-15). Similar results were seen for the primary outcome across various statistical models including models using β-blocker as a time-dependent covariate for both propensity-adjusted and inverse probability weighting (eTable). The analysis performed in the cohort with recent MI (≤1 year) showed an association of β-blocker use with a lower incidence of the secondary outcome (OR, 0.77 [95% CI, 0.64-0.92]) and hospitalization (OR, 0.77 [95% CI, 0.62-0.95]), but not with the primary outcome (HR, 0.79 [95% CI, 0.60-1.04]). Propensity score–adjusted analysis restricted to the cohort with heart failure (n = 6056) showed no benefit for the primary outcome (HR, 0.89 [95% CI, 0.79-1.01]; P = .08).

In this analysis of 44 708 patients from the REACH registry, β-blocker use was not associated with a lower incidence of cardiovascular events among individuals with a prior history of MI, among individuals with CAD but no MI history, or among individuals with risk factors only for atherosclerotic disease.

β-Blocker Use After MI

In patients after MI, there is evidence that β-blocker use reduces mortality.1416 In a meta-analysis published in 1999,17 a 23% reduction in death in trials of β-blocker use was observed. However, in this meta-analysis,17 the mean follow-up was only 1.4 years, the median publication date of the 82 randomized trials included was 1982, and most of the trials were performed in the era before modern reperfusion or medical therapy was routine for MI. A reperfused, viable myocardium has little in common with a necrotic or scarred myocardium, which generates arrhythmias because of reentry mechanisms, enhancing the capability of β-blockers to prevent sudden death. In the present study, more than 80% of patients with prior MI and with β-blocker use also used aspirin or lipid-lowering agents and more than 50% used an angiotensin-converting enzyme inhibitor. In a subgroup analysis from a cohort with prior MI from the International Verapamil-Trandolapril Study (INVEST), a non–β-blocker−based strategy (verapamil-trandolapril) did not significantly differ from a β-blocker–based strategy for the prevention of cardiovascular events, and was also associated with a greater subjective feeling of well-being and a trend toward lower incidence of angina pectoris and stroke.18

Our observation that β-blocker use was not associated with a lower rate of cardiovascular events among patients with MI and among those with CAD but no history of MI are consistent with the recently updated American Heart Association secondary prevention guidelines in which β-blocker therapy is a class I recommendation for heart failure, MI, or acute coronary syndrome for up to 3 years after MI, but it is a class IIa recommendation for longer-term therapy.19 Moreover, β-blocker therapy for all other patients with coronary or other vascular disease was downgraded to a class IIb recommendation.19 Similarly, the updated 2011 European Society of Cardiology secondary prevention guidelines recommend long-term β-blocker therapy only in patients with reduced left ventricular systolic function (class I).20

In our analyses, we did not have data on the type of β-blocker used. However, our results are important for several reasons. First, although guidelines recommend β-blocker therapy, there are no clear recommendations as to the β-blocker type (except for heart failure). Second, in the only randomized trial (Carvedilol Acute Myocardial Infarction Study; CAMIS)21 comparing carvedilol with atenolol in patients with acute coronary syndrome (left ventricular ejection fraction of 53.9%), there was no superiority of the newer β-blocker compared with the older one for composite cardiovascular events (P = .99). Third, atenolol is still the second most commonly prescribed β-blocker in the United States with more than 33.8 million prescriptions,22 and a total retail cost of more than $260 million in 201023; even if atenolol was the most commonly prescribed β-blocker in the study, the results would be widely applicable.

β-Blocker Use in Patients Without MI

Ever since the landmark studies of β-blocker use in patients after MI or heart failure, β-blockers have been considered to be a cardioprotective therapy. Their benefits have been extrapolated to patients with CAD without MI or heart failure and also to patients at high risk for CAD.

In the CAD and risk factors only cohorts in the present analysis, we observed higher event rates for certain outcomes with β-blocker therapy. The paucity of evidence for β-blocker therapy is described in the European Society of Cardiology guidelines on stable angina. As noted in these guidelines,24 a cardioprotective benefit of β-blockers has not been demonstrated in randomized controlled trials of patients with stable coronary disease.

Prior studies in patients with hypertension2534 have shown that when compared with placebo, β-blocker use is not associated with reduction in all-cause mortality or MI.35,36 β-Blocker use is associated with a 19% to 20% reduction in stroke,35,36 but this reduction is less than that observed with other antihypertensive agents.37 Based on this evidence, β-blocker therapy has been downgraded by the European Society on Hypertension, the American Heart Association, and others3841 to a fourth-line agent for the treatment of hypertension.

Some of the purported mechanism for lack of efficacy of β-blockers include reduced efficacy at reducing central aortic pressure42,43 and metabolic adverse effects, including the risk of new diabetes and dyslipidemia.30,44 In addition, β-blockers are often not well tolerated and adherence may be suboptimal.4547

Available evidence suggests that β-blocker use is associated with benefit in patients with acute MI (without impending shock or heart block),48 and may be efficacious in the short-to-intermediate term duration for patients after MI and in those with chronic heart failure.

Limitations

We did not have data on the type of β-blocker, the medication dosage, or the reason patients were without β-blocker use. In addition, we did not have data on type of MI or prior β-blocker use. Anginal status and history of heart failure were controlled for, although ejection fraction was not recorded. However, the results were largely similar in a sensitivity analysis excluding patients with known heart failure. Although propensity score matching adjusts for known confounders, other unmeasured confounders cannot be accounted for and the possibility of residual confounding by indication cannot be completely ruled out. Although our data are from a registry and are limited by the lack of nonrandomized design, contemporary data from a well-designed large registry such as the CRUSADE (Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes With Early Implementation of the ACC/AHA guidelines) registry,49 have been used to modify guideline recommendations (morphine use in non–ST-segment elevation acute coronary syndrome downgraded from a class I to class IIb). In addition, in an analysis from the REACH registry,7 statin use was associated with a significant reduction in the risk of events (HR, 0.73 [95% CI, 0.69-0.77]; P < .001), providing another internal validation of the data set.

Among patients enrolled in the international REACH registry, β-blocker use was not associated with a lower event rate of cardiovascular events at 44-month follow-up, even among patients with prior history of MI. Further research is warranted to identify subgroups that benefit from β-blocker therapy and the optimal duration of β-blocker therapy.

Corresponding Author: Sripal Bangalore, MD, MHA, New York University School of Medicine, 550 First Ave, New York, NY 10016 (sripalbangalore@gmail.com).

Author Contributions: Dr Bangalore had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Bangalore, Steg, Deedwania, Eagle, Ohman, Cannon, Bhatt.

Acquisition of data: Steg, Crowley, Goto, Zeymer, Bhatt.

Analysis and interpretation of data: Bangalore, Steg, Deedwania, Crowley, Eagle, Cannon, Smith, Zeymer, Hoffman, Messerli, Bhatt.

Drafting of the manuscript: Bangalore, Crowley, Messerli.

Critical revision of the manuscript for important intellectual content: Bangalore, Steg, Deedwania, Crowley, Eagle, Goto, Ohman, Cannon, Smith, Zeymer, Hoffman, Messerli, Bhatt.

Statistical analysis: Crowley, Hoffman.

Obtained funding: Steg, Goto, Cannon.

Administrative, technical, or material support: Steg, Eagle, Ohman, Cannon.

Study supervision: Bangalore, Steg, Deedwania, Goto, Messerli, Bhatt.

Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Steg reported receiving a research grant from sanofi-aventis and Servier awarded to INSERM U-698 and the New York University School of Medicine; serving as a consultant or receiving speakers fees from Ablynx, Amarin, Amgen, Astellas, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Meyers Squibb, Daiichi Sankyo, Eisai, GlaxoSmithKline, Lilly, Medtronic, Merck Sharp & Dohme, Novartis, Otsuka, Pfizer, Roche, sanofi-aventis, Servier, the Medicines Company; and holding stock in Aterovax. Dr Deedwania reported serving as a consultant or receiving speakers fees from Forest Pharmaceuticals, Novartis, Daichii Sankyo, Servier, and Pfizer. Dr Goto reported receiving consulting fees and honoraria from Eisai, sanofi-aventis, Otsuka, Bayer, Novartis, AstraZeneca, Asteras, Pfizer, Medtronics Japan, Mitsubishi Tanabe, Takeda, Daiichi Sankyo, Mochida, Merck Sharp & Dohme; and receiving research grants from sanofi-aventis, Eisai, Boehringer Ingelheim, Otsuka, and Daiichi Sankyo. Dr Ohman reported receiving research grants from Daiichi Sankyo, Eli Lilly & Company, Maquet; serving as a consultant to AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Gilead Sciences, LipoScience, Merck, Pozen, Roche, sanofi-aventis, the Medicines Company, and WebMD; and serving on the speakers bureau for Boehringer Ingelheim, Gilead Sciences, and the Medicines Company. Dr Cannon reported receiving research grants or support from Accumetrics, AstraZeneca, Essentials, GlaxoSmithKline, Merck, Regeneron, sanofi-aventis, and Takeda; serving on advisory boards (but funds donated to charity) for Bristol-Myers Squibb, Alnylam, Pfizer, and CSL; receiving honoraria for the development of independent educational symposia for Pfizer and AstraZeneca; and serving as a clinical advisor for and owning equity in Automedics Medical Systems. Dr Bhatt reported serving on an advisory board for Medscape Cardiology; serving on the boards of directors for Boston VA Research Institute and the Society of Chest Pain Centers; serving as chair for the American Heart Association Get With The Guidelines Science Subcommittee; receiving honoraria from the American College of Cardiology for serving as editor of Clinical Trials, Cardiosource, Duke Clinical Research Institute for serving on clinical trial steering committees, Slack Publications for serving as chief medical editor of Cardiology Today Intervention, and WebMD for serving on continuing medical education steering committees; serving as senior associate editor for the Journal of Invasive Cardiology ; receiving research grants from Amarin, AstraZeneca, Bristol-Myers Squibb, Eisai, Ethicon, Medtronic, sanofi-aventis, and the Medicines Company; and unfunded research from FlowCo, PLx Pharma, and Takeda. Drs Bangalore, Eagle, Smith Jr, Zeymer, Hoffman, and Messerli and Mr Crowley did not report any disclosures.

Funding Source: The REACH Registry is sponsored by sanofi-aventis, Bristol-Myers Squibb, and the Waksman Foundation (Tokyo, Japan) and is endorsed by the World Heart Federation. Statistical analyses of the REACH database by TIMI Study Group statisticians were funded by sanofi-aventis.

Role of the Sponsor: The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; or in the preparation, review, or approval of the manuscript.

Additional Contributions: We thank Sabina Murphy, MPH, of the TIMI study group for statistical support and supervision.

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Bhatt DL, Steg PG, Ohman EM,  et al; REACH Registry Investigators.  International prevalence, recognition, and treatment of cardiovascular risk factors in outpatients with atherothrombosis.  JAMA. 2006;295(2):180-189
PubMed   |  Link to Article
Ohman EM, Bhatt DL, Steg PG,  et al; REACH Registry Investigators.  The Reduction of Atherothrombosis for Continued Health (REACH) Registry: an international, prospective, observational investigation in subjects at risk for atherothrombotic events-study design.  Am Heart J. 2006;151(4):786, e1-e10
PubMed   |  Link to Article
Steg PG, Bhatt DL, Wilson PW,  et al; REACH Registry Investigators.  One-year cardiovascular event rates in outpatients with atherothrombosis.  JAMA. 2007;297(11):1197-1206
PubMed   |  Link to Article
Bhatt DL, Eagle KA, Ohman EM,  et al; REACH Registry Investigators.  Comparative determinants of 4-year cardiovascular event rates in stable outpatients at risk of or with atherothrombosis.  JAMA. 2010;304(12):1350-1357
PubMed   |  Link to Article
Rosenbaum P, Rubin D. The central role of propensity score in observational studies for causal effects.  Biometrika. 1983;70:41-55
Link to Article
Rubin D. Using propensity score to help design observational studies: application to the tobacco litigation.  Health Serv Outcomes Res Methodol. 2001;2:169-188
Link to Article
Ahmed A, Husain A, Love TE,  et al.  Heart failure, chronic diuretic use, and increase in mortality and hospitalization: an observational study using propensity score methods.  Eur Heart J. 2006;27(12):1431-1439
PubMed   |  Link to Article
Normand ST, Landrum MB, Guadagnoli E,  et al.  Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: a matched analysis using propensity scores.  J Clin Epidemiol. 2001;54(4):387-398
PubMed   |  Link to Article
Kurth T, Walker AM, Glynn RJ,  et al.  Results of multivariable logistic regression, propensity matching, propensity adjustment, and propensity-based weighting under conditions of nonuniform effect.  Am J Epidemiol. 2006;163(3):262-270
PubMed   |  Link to Article
Cole SR, Hernán MA. Adjusted survival curves with inverse probability weights.  Comput Methods Programs Biomed. 2004;75(1):45-49
PubMed   |  Link to Article
Snow PJ. Effect of propranolol in myocardial infarction.  Lancet. 1965;2(7412):551-553
PubMed   |  Link to Article
Yusuf S, Peto R, Lewis J, Collins R, Sleight P. Beta blockade during and after myocardial infarction: an overview of the randomized trials.  Prog Cardiovasc Dis. 1985;27(5):335-371
PubMed   |  Link to Article
Gottlieb SS, McCarter RJ, Vogel RA. Effect of beta-blockade on mortality among high-risk and low-risk patients after myocardial infarction.  N Engl J Med. 1998;339(8):489-497
PubMed   |  Link to Article
Freemantle N, Cleland J, Young P, Mason J, Harrison J. Beta blockade after myocardial infarction: systematic review and meta regression analysis.  BMJ. 1999;318(7200):1730-1737
PubMed   |  Link to Article
Bangalore S, Messerli FH, Cohen JD,  et al;  INVEST Investigators.  Verapamil-sustained release-based treatment strategy is equivalent to atenolol-based treatment strategy at reducing cardiovascular events in patients with prior myocardial infarction: an International Verapamil SR-Trandolapril (INVEST) substudy.  Am Heart J. 2008;156(2):241-247
PubMed   |  Link to Article
Smith SC Jr, Benjamin EJ, Bonow RO,  et al; World Heart Federation and the Preventive Cardiovascular Nurses Association.  AHA/ACCF Secondary Prevention and Risk Reduction Therapy for Patients With Coronary and Other Atherosclerotic Vascular Disease: 2011 update: a guideline from the American Heart Association and American College of Cardiology Foundation.  Circulation. 2011;124(22):2458-2473
PubMed   |  Link to Article
Hamm CW, Bassand JP, Agewall S,  et al; ESC Committee for Practice Guidelines; Document Reviewers.  ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: the task force for the management of acute coronary syndromes (ACS) in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC).  Eur Heart J. 2011;32(23):2999-3054
PubMed   |  Link to Article
Jonsson G, Abdelnoor M, Müller C, Kjeldsen SE, Os I, Westheim A. A comparison of the two beta-blockers carvedilol and atenolol on left ventricular ejection fraction and clinical endpoints after myocardial infarction: a single-centre, randomized study of 232 patients.  Cardiology. 2005;103(3):148-155
PubMed   |  Link to Article
Modern Medicine website.  Top 200 generic drugs by total prescriptions. http://drugtopics.modernmedicine.com/drugtopics/data/articlestandard//drugtopics/252011/727243/article.pdf. Accessed March 23, 2012
Modern Medicine website.  Top 200 generic drugs by retail dollars. http://drugtopics.modernmedicine.com/drugtopics/data/articlestandard//drugtopics/252011/727239/article.pdf. Accessed March 23, 2012
Fox K, Garcia MA, Ardissino D,  et al; Task Force on the Management of Stable Angina Pectoris of the European Society of Cardiology; ESC Committee for Practice Guidelines (CPG).  Guidelines on the management of stable angina pectoris: executive summary: The Task Force on the Management of Stable Angina Pectoris of the European Society of Cardiology.  Eur Heart J. 2006;27(11):1341-1381
PubMed   |  Link to Article
Bangalore S, Kamalakkannan G, Messerli FH. Beta-blockers: no longer an option for uncomplicated hypertension.  Curr Cardiol Rep. 2007;9(6):441-446
PubMed   |  Link to Article
Bangalore S, Messerli FH. Beta-blockers and exercise.  J Am Coll Cardiol. 2006;48(6):1284-1285
PubMed   |  Link to Article
Bangalore S, Messerli FH. Hypertension in the elderly: a compelling contraindication for beta-blockers?  J Hum Hypertens. 2007;21(4):259-260
PubMed
Bangalore S, Messerli FH. Beta-blockers as fourth-line therapy for hypertension: stay the course.  Int J Clin Pract. 2008;62(11):1643-1646
PubMed   |  Link to Article
Bangalore S, Messerli FH, Kostis JB, Pepine CJ. Cardiovascular protection using beta-blockers: a critical review of the evidence.  J Am Coll Cardiol. 2007;50(7):563-572
PubMed   |  Link to Article
Bangalore S, Parkar S, Grossman E, Messerli FH. A meta-analysis of 94,492 patients with hypertension treated with beta blockers to determine the risk of new-onset diabetes mellitus.  Am J Cardiol. 2007;100(8):1254-1262
PubMed   |  Link to Article
Bangalore S, Parkar S, Messerli FH. How useful are beta-blockers in cardiovascular disease?  Anadolu Kardiyol Derg. 2006;6(4):358-363
PubMed
Bangalore S, Sawhney S, Messerli FH. Relation of beta-blocker-induced heart rate lowering and cardioprotection in hypertension.  J Am Coll Cardiol. 2008;52(18):1482-1489
PubMed   |  Link to Article
Bangalore S, Wild D, Parkar S, Kukin M, Messerli FH. Beta-blockers for primary prevention of heart failure in patients with hypertension insights from a meta-analysis.  J Am Coll Cardiol. 2008;52(13):1062-1072
PubMed   |  Link to Article
Messerli FH, Bangalore S. Resting heart rate and cardiovascular disease: the beta-blocker-hypertension paradox.  J Am Coll Cardiol. 2008;51(3):330-331
PubMed   |  Link to Article
Lindholm LH, Carlberg B, Samuelsson O. Should beta blockers remain first choice in the treatment of primary hypertension? a meta-analysis.  Lancet. 2005;366(9496):1545-1553
PubMed   |  Link to Article
Wiysonge CS, Bradley H, Mayosi BM,  et al.  Beta-blockers for hypertension.  Cochrane Database Syst Rev. 2007;(1):CD002003
PubMed
Collins R, Peto R, MacMahon S,  et al.  Blood pressure, stroke, and coronary heart disease, part 2, short-term reductions in blood pressure: overview of randomised drug trials in their epidemiological context.  Lancet. 1990;335(8693):827-838
PubMed   |  Link to Article
Nice website.  The clinical management of primary hypertension in adults. http://www.nice.org.uk/guidance/index.jsp?action=download&o=53228. Accessed December 3, 2011
National Collaborating Centre for Chronic Conditions.  Hypertension: Management of Hypertension in Adults in Primary Care: Partial Update.  London, England: Royal College of Physicians; 2006
Mancia G, De Backer G, Dominiczak A,  et al; Task force for the management of arterial hypertension of the European Society of Hypertension; Task force for the management of arterial hypertension of the European Society of Cardiology.  2007 Guidelines for the management of arterial hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC).  Eur Heart J. 2007;28(12):1462-1536
PubMed
Rosendorff C, Black HR, Cannon CP,  et al; American Heart Association Council for High Blood Pressure Research; American Heart Association Council on Clinical Cardiology; American Heart Association Council on Epidemiology and Prevention.  Treatment of hypertension in the prevention and management of ischemic heart disease: a scientific statement from the American Heart Association Council for High Blood Pressure Research and the Councils on Clinical Cardiology and Epidemiology and Prevention.  Circulation. 2007;115(21):2761-2788
PubMed   |  Link to Article
Hirata K, Vlachopoulos C, Adji A, O’Rourke MF. Benefits from angiotensin-converting enzyme inhibitor ‘beyond blood pressure lowering’: beyond blood pressure or beyond the brachial artery?  J Hypertens. 2005;23(3):551-556
PubMed   |  Link to Article
Morgan T, Lauri J, Bertram D, Anderson A. Effect of different antihypertensive drug classes on central aortic pressure.  Am J Hypertens. 2004;17(2):118-123
PubMed   |  Link to Article
Weir MR, Moser M. Diuretics and beta-blockers: is there a risk for dyslipidemia?  Am Heart J. 2000;139(1 pt 1):174-183
PubMed   |  Link to Article
MRC Working Party.  Medical Research Council trial of treatment of hypertension in older adults: principal results.  BMJ. 1992;304(6824):405-412
PubMed   |  Link to Article
Messerli FH, Grossman E. β-blocker therapy and depression.  JAMA. 2002;288(15):1845-1846
PubMed   |  Link to Article
Bradley HA, Wiysonge CS, Volmink JA, Mayosi BM, Opie LH. How strong is the evidence for use of beta-blockers as first-line therapy for hypertension? systematic review and meta-analysis.  J Hypertens. 2006;24(11):2131-2141
PubMed   |  Link to Article
Chen ZM, Pan HC, Chen YP,  et al; COMMIT (Clopidogrel and Metoprolol in Myocardial Infarction Trial) collaborative group.  Early intravenous then oral metoprolol in 45,852 patients with acute myocardial infarction: randomised placebo-controlled trial.  Lancet. 2005;366(9497):1622-1632
PubMed   |  Link to Article
Meine TJ, Roe MT, Chen AY,  et al; CRUSADE Investigators.  Association of intravenous morphine use and outcomes in acute coronary syndromes: results from the CRUSADE Quality Improvement Initiative.  Am Heart J. 2005;149(6):1043-1049
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1. Cumulative Incidence Curve for the Risk of Primary Outcome by β-Blocker Use
Graphic Jump Location

Y-axis range shown in blue indicates event rate from 0% to 14%. The primary outcome was a composite of cardiovascular death, nonfatal MI, or nonfatal stroke. CAD indicates coronary artery disease; HR, hazard ratio; and MI, myocardial infarction.

Place holder to copy figure label and caption
Figure 2. Risk of Event Outcomes in the Matched Cohort
Graphic Jump Location

The primary outcome was a composite of cardiovascular death, nonfatal MI, or nonfatal stroke. The secondary outcome was the primary outcome plus hospitalization for atherothombotic events or a revascularization procedure. CAD indicates coronary artery disease; HR, hazard ratio; and MI, myocardial infarction.aOutcomes analyzed using a logistic regression analysis.

Tables

Table Graphic Jump LocationTable 1. Baseline Characteristics of Cohort With Known Prior Myocardial Infarction
Table Graphic Jump LocationTable 2. Baseline Characteristics of the Cohort With Known Coronary Artery Disease Without Myocardial Infarction
Table Graphic Jump LocationTable 3. Baseline Characteristics of the Cohort With Risk Factors Only But No Known Coronary Artery Disease

References

Dargie HJ. Effect of carvedilol on outcome after myocardial infarction in patients with left-ventricular dysfunction: the CAPRICORN randomised trial.  Lancet. 2001;357(9266):1385-1390
PubMed   |  Link to Article
Chen J, Radford MJ, Wang Y, Marciniak TA, Krumholz HM. Are β-blockers effective in elderly patients who undergo coronary revascularization after acute myocardial infarction?  Arch Intern Med. 2000;160(7):947-952
PubMed   |  Link to Article
Kramer JM, Hammill B, Anstrom KJ,  et al.  National evaluation of adherence to beta-blocker therapy for 1 year after acute myocardial infarction in patients with commercial health insurance.  Am Heart J. 2006;152(3):454, e1-e8
PubMed   |  Link to Article
Bhatt DL, Steg PG, Ohman EM,  et al; REACH Registry Investigators.  International prevalence, recognition, and treatment of cardiovascular risk factors in outpatients with atherothrombosis.  JAMA. 2006;295(2):180-189
PubMed   |  Link to Article
Ohman EM, Bhatt DL, Steg PG,  et al; REACH Registry Investigators.  The Reduction of Atherothrombosis for Continued Health (REACH) Registry: an international, prospective, observational investigation in subjects at risk for atherothrombotic events-study design.  Am Heart J. 2006;151(4):786, e1-e10
PubMed   |  Link to Article
Steg PG, Bhatt DL, Wilson PW,  et al; REACH Registry Investigators.  One-year cardiovascular event rates in outpatients with atherothrombosis.  JAMA. 2007;297(11):1197-1206
PubMed   |  Link to Article
Bhatt DL, Eagle KA, Ohman EM,  et al; REACH Registry Investigators.  Comparative determinants of 4-year cardiovascular event rates in stable outpatients at risk of or with atherothrombosis.  JAMA. 2010;304(12):1350-1357
PubMed   |  Link to Article
Rosenbaum P, Rubin D. The central role of propensity score in observational studies for causal effects.  Biometrika. 1983;70:41-55
Link to Article
Rubin D. Using propensity score to help design observational studies: application to the tobacco litigation.  Health Serv Outcomes Res Methodol. 2001;2:169-188
Link to Article
Ahmed A, Husain A, Love TE,  et al.  Heart failure, chronic diuretic use, and increase in mortality and hospitalization: an observational study using propensity score methods.  Eur Heart J. 2006;27(12):1431-1439
PubMed   |  Link to Article
Normand ST, Landrum MB, Guadagnoli E,  et al.  Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: a matched analysis using propensity scores.  J Clin Epidemiol. 2001;54(4):387-398
PubMed   |  Link to Article
Kurth T, Walker AM, Glynn RJ,  et al.  Results of multivariable logistic regression, propensity matching, propensity adjustment, and propensity-based weighting under conditions of nonuniform effect.  Am J Epidemiol. 2006;163(3):262-270
PubMed   |  Link to Article
Cole SR, Hernán MA. Adjusted survival curves with inverse probability weights.  Comput Methods Programs Biomed. 2004;75(1):45-49
PubMed   |  Link to Article
Snow PJ. Effect of propranolol in myocardial infarction.  Lancet. 1965;2(7412):551-553
PubMed   |  Link to Article
Yusuf S, Peto R, Lewis J, Collins R, Sleight P. Beta blockade during and after myocardial infarction: an overview of the randomized trials.  Prog Cardiovasc Dis. 1985;27(5):335-371
PubMed   |  Link to Article
Gottlieb SS, McCarter RJ, Vogel RA. Effect of beta-blockade on mortality among high-risk and low-risk patients after myocardial infarction.  N Engl J Med. 1998;339(8):489-497
PubMed   |  Link to Article
Freemantle N, Cleland J, Young P, Mason J, Harrison J. Beta blockade after myocardial infarction: systematic review and meta regression analysis.  BMJ. 1999;318(7200):1730-1737
PubMed   |  Link to Article
Bangalore S, Messerli FH, Cohen JD,  et al;  INVEST Investigators.  Verapamil-sustained release-based treatment strategy is equivalent to atenolol-based treatment strategy at reducing cardiovascular events in patients with prior myocardial infarction: an International Verapamil SR-Trandolapril (INVEST) substudy.  Am Heart J. 2008;156(2):241-247
PubMed   |  Link to Article
Smith SC Jr, Benjamin EJ, Bonow RO,  et al; World Heart Federation and the Preventive Cardiovascular Nurses Association.  AHA/ACCF Secondary Prevention and Risk Reduction Therapy for Patients With Coronary and Other Atherosclerotic Vascular Disease: 2011 update: a guideline from the American Heart Association and American College of Cardiology Foundation.  Circulation. 2011;124(22):2458-2473
PubMed   |  Link to Article
Hamm CW, Bassand JP, Agewall S,  et al; ESC Committee for Practice Guidelines; Document Reviewers.  ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: the task force for the management of acute coronary syndromes (ACS) in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC).  Eur Heart J. 2011;32(23):2999-3054
PubMed   |  Link to Article
Jonsson G, Abdelnoor M, Müller C, Kjeldsen SE, Os I, Westheim A. A comparison of the two beta-blockers carvedilol and atenolol on left ventricular ejection fraction and clinical endpoints after myocardial infarction: a single-centre, randomized study of 232 patients.  Cardiology. 2005;103(3):148-155
PubMed   |  Link to Article
Modern Medicine website.  Top 200 generic drugs by total prescriptions. http://drugtopics.modernmedicine.com/drugtopics/data/articlestandard//drugtopics/252011/727243/article.pdf. Accessed March 23, 2012
Modern Medicine website.  Top 200 generic drugs by retail dollars. http://drugtopics.modernmedicine.com/drugtopics/data/articlestandard//drugtopics/252011/727239/article.pdf. Accessed March 23, 2012
Fox K, Garcia MA, Ardissino D,  et al; Task Force on the Management of Stable Angina Pectoris of the European Society of Cardiology; ESC Committee for Practice Guidelines (CPG).  Guidelines on the management of stable angina pectoris: executive summary: The Task Force on the Management of Stable Angina Pectoris of the European Society of Cardiology.  Eur Heart J. 2006;27(11):1341-1381
PubMed   |  Link to Article
Bangalore S, Kamalakkannan G, Messerli FH. Beta-blockers: no longer an option for uncomplicated hypertension.  Curr Cardiol Rep. 2007;9(6):441-446
PubMed   |  Link to Article
Bangalore S, Messerli FH. Beta-blockers and exercise.  J Am Coll Cardiol. 2006;48(6):1284-1285
PubMed   |  Link to Article
Bangalore S, Messerli FH. Hypertension in the elderly: a compelling contraindication for beta-blockers?  J Hum Hypertens. 2007;21(4):259-260
PubMed
Bangalore S, Messerli FH. Beta-blockers as fourth-line therapy for hypertension: stay the course.  Int J Clin Pract. 2008;62(11):1643-1646
PubMed   |  Link to Article
Bangalore S, Messerli FH, Kostis JB, Pepine CJ. Cardiovascular protection using beta-blockers: a critical review of the evidence.  J Am Coll Cardiol. 2007;50(7):563-572
PubMed   |  Link to Article
Bangalore S, Parkar S, Grossman E, Messerli FH. A meta-analysis of 94,492 patients with hypertension treated with beta blockers to determine the risk of new-onset diabetes mellitus.  Am J Cardiol. 2007;100(8):1254-1262
PubMed   |  Link to Article
Bangalore S, Parkar S, Messerli FH. How useful are beta-blockers in cardiovascular disease?  Anadolu Kardiyol Derg. 2006;6(4):358-363
PubMed
Bangalore S, Sawhney S, Messerli FH. Relation of beta-blocker-induced heart rate lowering and cardioprotection in hypertension.  J Am Coll Cardiol. 2008;52(18):1482-1489
PubMed   |  Link to Article
Bangalore S, Wild D, Parkar S, Kukin M, Messerli FH. Beta-blockers for primary prevention of heart failure in patients with hypertension insights from a meta-analysis.  J Am Coll Cardiol. 2008;52(13):1062-1072
PubMed   |  Link to Article
Messerli FH, Bangalore S. Resting heart rate and cardiovascular disease: the beta-blocker-hypertension paradox.  J Am Coll Cardiol. 2008;51(3):330-331
PubMed   |  Link to Article
Lindholm LH, Carlberg B, Samuelsson O. Should beta blockers remain first choice in the treatment of primary hypertension? a meta-analysis.  Lancet. 2005;366(9496):1545-1553
PubMed   |  Link to Article
Wiysonge CS, Bradley H, Mayosi BM,  et al.  Beta-blockers for hypertension.  Cochrane Database Syst Rev. 2007;(1):CD002003
PubMed
Collins R, Peto R, MacMahon S,  et al.  Blood pressure, stroke, and coronary heart disease, part 2, short-term reductions in blood pressure: overview of randomised drug trials in their epidemiological context.  Lancet. 1990;335(8693):827-838
PubMed   |  Link to Article
Nice website.  The clinical management of primary hypertension in adults. http://www.nice.org.uk/guidance/index.jsp?action=download&o=53228. Accessed December 3, 2011
National Collaborating Centre for Chronic Conditions.  Hypertension: Management of Hypertension in Adults in Primary Care: Partial Update.  London, England: Royal College of Physicians; 2006
Mancia G, De Backer G, Dominiczak A,  et al; Task force for the management of arterial hypertension of the European Society of Hypertension; Task force for the management of arterial hypertension of the European Society of Cardiology.  2007 Guidelines for the management of arterial hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC).  Eur Heart J. 2007;28(12):1462-1536
PubMed
Rosendorff C, Black HR, Cannon CP,  et al; American Heart Association Council for High Blood Pressure Research; American Heart Association Council on Clinical Cardiology; American Heart Association Council on Epidemiology and Prevention.  Treatment of hypertension in the prevention and management of ischemic heart disease: a scientific statement from the American Heart Association Council for High Blood Pressure Research and the Councils on Clinical Cardiology and Epidemiology and Prevention.  Circulation. 2007;115(21):2761-2788
PubMed   |  Link to Article
Hirata K, Vlachopoulos C, Adji A, O’Rourke MF. Benefits from angiotensin-converting enzyme inhibitor ‘beyond blood pressure lowering’: beyond blood pressure or beyond the brachial artery?  J Hypertens. 2005;23(3):551-556
PubMed   |  Link to Article
Morgan T, Lauri J, Bertram D, Anderson A. Effect of different antihypertensive drug classes on central aortic pressure.  Am J Hypertens. 2004;17(2):118-123
PubMed   |  Link to Article
Weir MR, Moser M. Diuretics and beta-blockers: is there a risk for dyslipidemia?  Am Heart J. 2000;139(1 pt 1):174-183
PubMed   |  Link to Article
MRC Working Party.  Medical Research Council trial of treatment of hypertension in older adults: principal results.  BMJ. 1992;304(6824):405-412
PubMed   |  Link to Article
Messerli FH, Grossman E. β-blocker therapy and depression.  JAMA. 2002;288(15):1845-1846
PubMed   |  Link to Article
Bradley HA, Wiysonge CS, Volmink JA, Mayosi BM, Opie LH. How strong is the evidence for use of beta-blockers as first-line therapy for hypertension? systematic review and meta-analysis.  J Hypertens. 2006;24(11):2131-2141
PubMed   |  Link to Article
Chen ZM, Pan HC, Chen YP,  et al; COMMIT (Clopidogrel and Metoprolol in Myocardial Infarction Trial) collaborative group.  Early intravenous then oral metoprolol in 45,852 patients with acute myocardial infarction: randomised placebo-controlled trial.  Lancet. 2005;366(9497):1622-1632
PubMed   |  Link to Article
Meine TJ, Roe MT, Chen AY,  et al; CRUSADE Investigators.  Association of intravenous morphine use and outcomes in acute coronary syndromes: results from the CRUSADE Quality Improvement Initiative.  Am Heart J. 2005;149(6):1043-1049
PubMed   |  Link to Article

Letters

February 6, 2013
Charles Shang, MD
JAMA. 2013;309(5):438. doi:10.1001/jama.2012.128869.
February 6, 2013
Frans H. Rutten, MD, PhD; Rolf H. H. Groenwold, MD, PhD
JAMA. 2013;309(5):438. doi:10.1001/jama.2012.128865.
February 6, 2013
Dominique Costagliola, PhD; Miguel A. Hernán, MD, PhD
JAMA. 2013;309(5):438. doi:10.1001/jama.2012.128862.
February 6, 2013
Sripal Bangalore, MD, MHA; P. Gabriel Steg, MD; Deepak L. Bhatt, MD, MPH
JAMA. 2013;309(5):438. doi:10.1001/jama.2012.128872.
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Supplemental Content

Bangalore S, Steg PG, Deedwania P, et al, for the REACH Registry Investigators. ß-Blocker use and clinical outcomes in stable outpatients with and without coronary artery disease. JAMA. 2012;308(13):doi:10.1001/jama.2012.929.

eFigure 1. Absolute standardized difference before and after propensity score matching: prior MI cohort

eFigure 2. Cumulative incidence curve for the risk of cardiovascular (CV) death in the prior MI matched cohort by ß-blocker status

eFigure 3. Cumulative incidence curve for the risk of non-fatal myocardial infarction in the prior MI cohort by ß-blocker status

eFigure 4. Cumulative incidence curve for the risk of non-fatal stroke in the prior MI matched cohort by ß-blocker status

eFigure 5. Risk of outcomes based on a regression model adjusted for a propensity score

eFigure 6. Absolute standardized difference before and after propensity score matching: known CAD without MI cohort

eFigure 7. Cumulative incidence curve for the risk of cardiovascular (CV) death in the known CAD without MI matched cohort by ß-blocker status

eFigure 8. Cumulative incidence curve for the risk of non-fatal stroke in the known CAD without MI matched cohort by ß-blocker status

eFigure 9. Cumulative incidence curve for the risk of non-fatal myocardial infarction in the known CAD without MI matched cohort by ß-blocker status

eFigure 10. Absolute standardized difference before and after propensity score matching: risk factors alone cohort

eFigure 11. Cumulative incidence curve for the risk of non-fatal myocardial infarction in RF-alone matched CAD cohort by ß-blocker status

eFigure 12. Cumulative incidence curve for the risk of non-fatal stroke in the RF-alone matched cohort by ß-blocker status

eFigure 13. Cumulative incidence curve for the risk of cardiovascular (CV) death in the RF-alone matched cohort by ß-blocker status

eFigure 14. Sensitivity analysis in the cohort without heart failure: risk of outcomes based on a regression model adjusted for a propensity score

eFigure 15. Sensitivity analysis in the cohort without heart failure: risk of outcomes in the matched cohort

eTable. Primary outcome: effect size across various statistical models

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