Pros and cons of composite endpoints in anesthesia trials.

IT is widely accepted that the randomized controlled trial is the optimal method to evaluate the efficacy of an intervention. Clinical research aiming to inform and improve patient care should evaluate outcomes rated as important by our patients. Unfortunately, many trials focus on surrogate outcomes that are of questionable significance. Given that 5 to 10% of trial patients will suffer a serious postoperative complication, and that perioperative treatments are likely to have only a moderate effect on outcome, large numbers of patients are required to have sufficient trial power to detect a modest but clinically important effect. A systematic review of head injury trials published before December 1998 identified 203 studies in which 16,613 patients were enrolled. Thus, the average number of patients in each trial was 82. Only 4% of these trials were large enough to detect a clinically important difference. We believe similar problems with underpowered studies exist in the anesthesia, perioperative, and pain medicine literature. Large trials can provide definitive evidence to guide clinical practice. They provide insights in a broad range of clinical settings and offer an opportunity to identify patient, clinician, and institutional factors that may influence outcome. They should have sufficient power to address clinically important questions, balance a range of known and unknown confounding factors, and provide precise estimates of effect—the latter being indicated by narrow confidence intervals. However, large multicenter trials take a lot of time and effort to establish and can be expensive to run. The required sample size needed to reliably demonstrate a clinically important effect should be based on the nominated primary endpoint of the study; this is sometimes lacking in anesthesia trials. There may be several secondary study outcomes, and each of these typically relates to mechanisms of action, specific organ effects, and potential adverse effects of therapy. If the primary endpoint of the trial is a serious complication (e.g., death), it may only occur in 1 to 2% of patients, which greatly increases the sample size required to detect a clinically useful effect. For this reason, some investigators combine several outcomes into a single composite, or pooled, endpoint. For example, antithrombotic treatments may reduce nonfatal myocardial infarction (MI), nonfatal stroke, and death. Similar approaches have or are being used in perioperative anesthesia trials. A summary measure of each of these effects can be defined. The composite endpoint will have a higher incidence than each of the individual outcomes, and as long as there is a reasonably similar effect across the individual components of the composite, this will reduce the sample size requirement for the trial. Because of the higher event rate, composite endpoints can provide increased statistical precision and efficiency. Clinical trials can be smaller, less costly, completed earlier, and the results made available sooner. However composite endpoints have an inherent assumption in that each component of the endpoint has a similar burden on health. This is often not the case. Endpoints of least importance to patients, such as a single episode of angina, as opposed to MI-induced heart failure, stroke, or death, typically contribute most to trial events. A recent systematic review found that in approximately half the trials reviewed, there were large or moderate gradients in both importance to patients and magnitude of effect across components. The most serious and highly rated events typically occurred least often, so they provided the least information (in terms of numerical value) to the composite endpoint. This may lead to misleading impressions of the true clinical value of the treatment. Should endpoints be weighted, and if so, how? We believe this should be guided by the perceived clinical importance of each individual endpoint, and emphasis should be placed on patient values. Objective justification can assist in this regard, using patient and clinician surveys, disability scores, and eventual health care utilization. There may be competing risks between endpoints; a positive composite endpoint may conceal a negative individual (more serious) outcome such as death. The most extreme example of this is when early death prevents the possibility of other less serious outcomes, such as subclinical MI or prolonged hospital stay. Clinicians should be wary of post hoc definition of composite endpoints as secondary measures when the primary outcome fails to show a treatment effect. This is one of several reasons why findings from the ENIGMA trial are being followed up with a larger, more specifically designed trial focusing on cardiovascular outcomes. Cardiovascular trials commonly use major adverse cardiac events as a composite primary endpoint. But there is no standard definition for major adverse cardiac events. Most include MI, stroke, and death; others include revascularizaAccepted for publication June 2, 2010. The authors are not supported by, nor maintain any financial interest in, any commercial activity that may be associated with the topic of this article.