The JUPITER trial: myth or reality?

The JUPITER trial is widely hailed as a landmark trial that has the potential to dramatically change the landscape of primary prevention of cardiovascular disease. Like most trials, however, it is not without its limitations. We address some of the common myths and misunderstandings that are underscored by the JUPITER trial. First, by its intentional and ill-advised exclusion of patients with low levels of high-sensitivity C-reactive protein (hsCRP), it is not possible to assess whether baseline hsCRP modifies treatment response to statins or whether it identifies patients most likely to benefit from statin therapy. Second, by stopping the trial early, one cannot rule out the possibility that the treatment benefit was overestimated and risk was underestimated, thereby precluding a reliable estimate of benefit/risk. Finally, as a consequence of early stopping, it is not possible to reliably assess the cost-effectiveness of primary prevention with rosuvastatin. Given these limitations, the attendant societal health policy implications remain largely unknown.

Rosiglitazone and cardiovascular risk.

A meta-analysis of 42 clinical trials suggested that rosiglitazone, a widely used thiazolidinedione, was associated with a 43% greater risk of myocardial infarction (P = 0.03) and a 64% greater risk of cardiovascular death (P = 0.06). However, a number of criticisms have been raised that potentially undermine the conclusions of this analysis. In this article, we point out some of these limitations, summarize the currently available evidence concerning rosiglitazone and cardiovascular risk, share implications for drug safety evaluation, and offer practical recommendations to health care providers. We conclude that the data showing the increased risk for myocardial infarction and death from cardiovascular disease for diabetic patients taking rosiglitazone are inconclusive.

Uncertain effects of rosiglitazone on the risk for myocardial infarction and cardiovascular death.

A recent, widely publicized meta-analysis of 42 clinical trials concluded that rosiglitazone was associated with an approximately 43% increased risk for myocardial infarction and an approximately 64% increased risk for cardiovascular death. The sensitivity of these conclusions to several methodological choices was not assessed. The meta-analysis was not based on a comprehensive search for all studies that might yield evidence about rosiglitazone's cardiovascular effects. Studies were combined on the basis of a lack of statistical heterogeneity, despite substantial variability in study design and outcome assessment. The meta-analytic approach that was used required the exclusion of studies with zero events in the treatment and control groups. Alternative meta-analytic approaches that use continuity corrections show lower odds ratios that are not statistically significant. We conclude that the risk for myocardial infarction and death from cardiovascular disease for diabetic patients taking rosiglitazone is uncertain: Neither increased nor decreased risk is established.

Role of clopidogrel in managing atherothrombotic cardiovascular disease.

Aspirin is the most widely used antiplatelet agent for preventing and treating vascular events. The thienopyridine derivatives, ticlopidine and clopidogrel, are a suitable alternative in patients who are intolerant to aspirin, and clopidogrel exhibits better tolerability than ticlopidine. The available evidence from randomized trials indicates that dual therapy with clopidogrel and aspirin is modestly but significantly more effective than aspirin in preventing serious vascular events. It is also associated with a favorable benefit-risk profile in patients at high risk (especially in acute coronary syndromes and after stenting). In patients at low risk (stable cardiovascular disease), however, the bleeding risk of dual therapy exceeds its potential benefit. The dose and duration of pretreatment before stenting, the optimal duration of treatment after drug-eluting stent implantation, concurrent administration of platelet glycoprotein IIb/IIIa inhibitors, and the exact mechanism and clinical relevance of clopidogrel resistance are unclear.

An orwellian discourse on the meaning and measurement of noninferiority.

The customary interpretation of active-controlled noninferiority trials is founded on a number of unverifiable assumptions. These assumptions can be circumvented, and the semantic and statistic interpretation of the trials placed on a more rational foundation, if treatment comparisons are analyzed from a Bayesian perspective. In conclusion, the resultant probabilistic measures thereby render the meaning of noninferiority more transparent and clinically relevant.

The things to come of SHAPE: cost and effectiveness of cardiovascular prevention.

It has been proposed recently that asymptomatic adults undergo routine screening for subclinical atherosclerosis using electron-beam computed tomography or carotid ultrasound as the basis for the pharmacologic prevention of cardiovascular events. The expected cost and effectiveness of this conditional test-treatment strategy are herein analyzed in comparison with the conventional conditional strategy, based on Framingham risk factor assessment, and with an unconditional treatment strategy that does not rely on testing. These analyses show that the unconditional treatment strategy, albeit more costly, is more effective and more cost-effective than either conditional testing strategy. In conclusion, greater attention should be paid to improving the population-wide delivery of and long-term adherence to proven preventive therapy than to the identification of "high-risk" treatment targets.

Good enough: a primer on the analysis and interpretation of noninferiority trials.

Active-control noninferiority trials are being performed with increasing frequency when standard placebo-controlled trials are considered unethical. Three attributes are optimally required to establish noninferiority: 1) The treatment under consideration exhibits therapeutic noninferiority to the active control; 2) the treatment would exhibit therapeutic efficacy in a placebo-controlled trial if such a trial were to be performed; and 3) the treatment offers ancillary advantages in safety, tolerability, cost, or convenience. Trials designed to show noninferiority require an appropriate reference population, a proven active control and dose, a high level of adherence to treatment, and adequate statistical power. However, the formal analysis of such trials is founded on several assumptions that cannot be validated explicitly. These assumptions are evaluated in the context of 8 recently published noninferiority trials. The analyses in this paper confirm the establishment of noninferiority in only 4 of the 8 trials. The authors conclude that if noninferiority trials are to be applied to clinical and regulatory decisions about the marketing and use of new treatments, these assumptions must be made explicit and their influence on the resultant conclusions assessed rigorously.

Narrative review: drug-eluting stents for the management of restenosis: a critical appraisal of the evidence.

Interventional cardiologists have quickly replaced bare metal stents with intravascular drug-eluting stents for treating and preventing restenosis, largely on the basis of empirical evidence that shows profound reduction in angiographic and clinical restenosis. A critical reassessment of the published evidence, however, suggests that the putative superiority of intravascular drug-eluting stents is founded on questionable premises, including 1) overestimation of restenosis benefit, 2) underestimation of the risk for stent thrombosis, 3) overreliance on "soft" rather than "hard" outcomes (need for repeated revascularization vs. death or myocardial infarction), and 4) the attendant overestimation of cost-effectiveness. Because the long-term incremental risks, benefits, and costs of drug-eluting stents have not yet been optimally evaluated in a broad spectrum of patient and lesion cohorts, the rational role of these devices in clinical management warrants reappraisal.

Continuous probabilistic prediction of angiographically significant coronary artery disease using electron beam tomography.

BACKGROUND: We sought to incorporate electron beam tomography-derived calcium scores in a model for prediction of angiographically significant coronary artery disease (CAD). Such a model could greatly facilitate clinical triage in symptomatic patients with no known CAD. METHODS AND RESULTS: We examined 1851 patients with suspected CAD who underwent coronary angiography for clinical indications. An electron beam tomographic scan was performed in all patients. Total per-patient calcium scores and separate scores for the major coronary arteries were added to logistic regression models to calculate a posterior probability of the severity and extent of angiographic disease. These models were designed to be continuous, adjusted for age and sex, corrected for verification bias, and independently validated in terms of their incremental diagnostic accuracy. The overall sensitivity was 95%, and specificity was 66% for coronary calcium to predict obstructive disease on angiography. With calcium scores >20, >80, and >100, the sensitivity to predict stenosis decreased to 90%, 79%, and 76%, whereas the specificity increased to 58%, 72%, and 75%, respectively. The logistic regression model exhibited excellent discrimination (receiver operating characteristic curve area, 0.842+/-0.023) and calibration (chi2 goodness of fit, 8.95; P=0.442). CONCLUSIONS: Electron beam tomographic calcium scanning provides incremental and independent power in predicting the severity and extent of angiographically significant CAD in symptomatic patients, in conjunction with pretest probability of disease. This algorithm is most useful when applied to an intermediate-risk population.

Prior convictions: Bayesian approaches to the analysis and interpretation of clinical megatrials.

Large, randomized clinical trials ("megatrials") are key drivers of modern cardiovascular practice, since they are cited frequently as the authoritative foundation for evidence-based management policies. Nevertheless, fundamental limitations in the conventional approach to statistical hypothesis testing undermine the scientific basis of the conclusions drawn from these trials. This review describes the conventional approach to statistical inference, highlights its limitations, and proposes an alternative approach based on Bayes' theorem. Despite its inherent subjectivity, the Bayesian approach possesses a number of practical advantages over the conventional approach: 1). it allows the explicit integration of previous knowledge with new empirical data; 2). it avoids the inevitable misinterpretations of p values derived from megatrial populations; and 3). it replaces the misleading p value with a summary statistic having a natural, clinically relevant interpretation-the probability that the study hypothesis is true given the observations. This posterior probability thereby quantifies the likelihood of various magnitudes of therapeutic benefit rather than the single null magnitude to which the p value refers, and it lends itself to graphical sensitivity analyses with respect to its underlying assumptions. Accordingly, the Bayesian approach should be employed more widely in the design, analysis, and interpretation of clinical megatrials.