Theo Vos

Are β-blockers as efficacious in patients with diabetes mellitus as in patients without diabetes mellitus who have chronic heart failure? A meta-analysis of large-scale clinical trials

BACKGROUND Diabetes mellitus is a frequent comorbid condition in patients with chronic heart failure (CHF) and confers a worse prognosis. Furthermore, although patients with CHF derive considerable benefit from beta-blockers, these agents are thought by many physicians to be contraindicated in patients with diabetes mellitus. Most published studies on beta-blockers in CHF have been unable to reach definitive conclusions about the mortality benefits of these agents in patients with diabetes mellitus. We therefore performed a meta-analysis of beta-blocker trials that reported mortality outcomes in patients with diabetes mellitus who had CHF to pool all available trial evidence on the benefits (or otherwise) of these agents in this setting. METHODS All-cause mortality data on patients with diabetes mellitus were obtained from all completed beta-blocker CHF randomized placebo-controlled trials involving >100 patients exposed to beta-blockers, in which outcomes in patients with diabetes mellitus were described. When events were not directly reported, risk ratios (RRs) were derived from analysis of figures and other manuscript data. Results were pooled with the Mantel-Haenszel method. RESULTS A total of 24.6% of patients were reported to have diabetes mellitus in the 6 studies analyzed (Australia and New Zealand [ANZ]-Carvedilol, Beta-blocker Evaluation of Survival Trial [BEST], Carvedilol US Trials, Cardiac Insufficiency Bisoprolol Study [CIBIS-II], Carvedilol Prospective Randomized Cumulative Survival Trial [COPERNICUS], and Metoprolol Controlled-release Randomized Intervention Trial in Heart Failure [MERIT-HF]). Patients with diabetes mellitus had increased mortality rates overall compared with subjects without diabetes mellitus (RR, 1.25; 95% CI, 1.15-1.36; P <.001). Compared with placebo, beta-blocker therapy for CHF was beneficial in patients with diabetes mellitus (RR, 0.84; 95% CI, 0.73-0.96; P =.011) and in subjects without diabetes mellitus (RR, 0.72; 95% CI, 0.65-0.79; P <.001). The absolute risk reduction in mortality with beta-blocker therapy was greater in patients with heart failure but without diabetes mellitus than in patients with diabetes mellitus (P =.023). CONCLUSIONS Patients with diabetes mellitus and CHF appear to derive prognostic benefit from beta-blocker therapy, although the magnitude of that benefit is somewhat less than that observed in subjects without diabetes mellitus.

A Model for Predicting the Future Incidence of Coronary Heart Disease Within Percentiles of Coronary Heart Disease Risk

Background We present a method (The CHD Prevention Model) for modelling the incidence of fatal and nonfatal coronary heart disease (CHD) within various CHD risk percentiles of an adult population. The model provides a relatively simple tool for lifetime risk prediction for subgroups within a population. It allows an estimation of the absolute primary CHD risk in different populations and will help identify subgroups of the adult population where primary CHD prevention is most appropriate and cost-effective. Methods The CHD risk distribution within the Australian population was modelled, based on the prevalence of CHD risk, individual estimates of integrated CHD risk, and current CHD mortality rates. Predicted incidence of first fatal and nonfatal myocardial infarction within CHD risk strata of the Australian population was determined. Results Approximately 25% of CHD deaths were predicted to occur amongst those in the top 10 percentiles of integrated CHD risk, regardless of age group or gender. It was found that while all causes survival did not differ markedly between percentiles of CHD risk before the ages of around 50-60, event-free survival began visibly to differ about 5 years earlier. Conclusions The CHD Prevention Model provides a means of predicting future CHD incidence amongst various strata of integrated CHD risk within an adult population. It has significant application both in individual risk counselling and in the identification of subgroups of the population where drug therapy to reduce CHD risk is most cost-effective.