Validity of composite end points in clinical trialsBMJ 2005; 330 doi: https://doi.org/10.1136/bmj.330.7491.594 (Published 10 March 2005) Cite this as: BMJ 2005;330:594
- Victor M Montori, assistant professor1,
- Gaietà Permanyer-Miralda, senior consultant ()2⇑,
- Ignacio Ferreira-González, research fellow3,
- Jason W Busse, research associate4,
- Valeria Pacheco-Huergo, general practitioner6,
- Dianne Bryant, instructor4,
- Jordi Alonso, head7,
- Elie A Akl, research assistant professor8,
- Antònia Domingo-Salvany, senior scientist7,
- Edward Mills, director of research9,
- Ping Wu, research assistant9,
- Holger J Schünemann, associate professor8,
- Roman Jaeschke, clinical professor5,
- Gordon H Guyatt, professor4
- 1 Department of Medicine, Mayo Clinic College of Medicine, Rochester, MN 55905, USA
- 2 Cardiology Service, Epidemiology Unit, Hospital General Vall d'Hebron, Barcelona 08035, Spain
- 3 Department de Medicina, Universitat Autònoma de Barcelona, Hospital General Vall d'Hebron
- 4 Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON L8N 3Z5, Canada
- 5 Department of Medicine, McMaster University
- 6 Primary Care Centre TurÓ, EAP Vilapicina, Institut Català de la Salut, Barcelona, Spain
- 7 Health Services Research Unit, Institut Municipal d'InvestigaciÓ Mèdica, Barcelona, Spain
- 8 Department of Medicine and of Social and Preventive Medicine, University at Buffalo, Buffalo, NY 14214, USA
- 9 Department of Research, Canadian College of Naturopathic Medicine, Toronto, Canada M2K 1E2
- Correspondence to: G Permanyer-Miralda
- Accepted 10 January 2005
Use of composite end points as the main outcome in randomised trials can hide wide differences in the individual measures. How should you apply the results to clinical practice?
Improvements in medical care over the past two decades have decreased the frequency with which patients with common conditions such as myocardial infarction develop subsequent adverse events. Although welcome for patients, low event rates provide challenges for clinical investigators, who consequently require large sample sizes and long follow up to test the incremental benefits of new treatments. Clinical trialists have responded to these challenges by relying increasingly on composite end points, which capture the number of patients experiencing any one of several adverse events—for example, death, myocardial infarction, or hospital admission.1
Use of composite end points is usually justified by the assumption that the effect on each of the components will be similar and that patients will attach similar importance to each component.1 But this is not always the case. In this article we provide a strategy to interpret the results of clinical trials when investigators measure the effect of treatment on an aggregate of end points of varying importance.
Consider a 76 year old man who has disabling angina despite taking β blockers, nitrates, aspirin, an angiotensin converting enzyme inhibitor, and a statin. His doctor suggests cardiac catheterisation and possible revascularisation. The patient is reluctant to have invasive management, and wonders how much benefit he might expect from surgery.
The trial of invasive versus medical therapy in elderly patients (TIME) is relevant.2 The study randomised 301 patients aged 75 years or older with resistant angina to optimised drug treatment or cardiac catheterisation and possible revascularisation. Although the groups showed no difference in quality of life at 12 months, the frequency of a composite end point (death, non-fatal myocardial infarction, and hospital admission for acute coronary syndrome) was much lower in the revascularisation group (25.5%) than in the medical management arm (64.2%; hazard ratio 0.31, 95% confidence interval 0.21 to 0.45).
Although the overall result suggests invasive treatment would be beneficial, marked differences existed in the absolute reduction in risk across components (table 1). In the invasive group, five more patients died but there were six fewer myocardial infarctions and 78 fewer hospital admissions. How should you interpret these results and inform the patient?
Evaluating composite end points
Clinicians can use three questions to help decide whether to base a clinical decision on the effect of treatment on a composite end point or on the component end points (box). We will not expand on statistical issues here, but box A on bmj.com gives a brief outline.
Importance of individual components to patients
When all components of a composite end point are of equal importance to the patient, it will not be misleading to assume that the effect of the intervention on each component is similar, in both relative and absolute terms. If patients consider death, stroke, and myocardial infarction of equal importance, it does not much matter how a 5% absolute risk reduction in the composite end point is distributed. The decision will be the same, even if treatment effects differ substantially.
Guide to interpreting composite end points
Are the component end points of similar importance to patients?
Did the more and less important end points occur with similar frequency?
Are the component end points likely to have similar relative risk reductions?
Is the underlying biology of the component end points similar?
Are the point estimates of the relative risk reductions similar and the confidence intervals sufficiently narrow?
The extent to which the answers to these questions are no will determine whether you need to examine the component end points separately
Patients almost invariably, however, assign varying importance to different health outcomes. As a result, we can seldom ignore possible differences in treatment effects between component end points on the grounds that patients give them identical importance. The magnitude of the gradient in importance between end points therefore becomes the issue.
For instance, consider a trial of four doses of perioperative aspirin in patients having carotid endarterectomy in which the composite end point included death and stroke.3 Many patients would consider a stroke as having a negative value approaching that of death. The relatively small gradient in importance between the components increases the likely usefulness of the composite end point in clinical decision making. In a trial of corticosteroids among patients with acute exacerbation of chronic obstructive lung disease, however, the investigators chose a combined end point of death from any cause, need for intubation and mechanical ventilation, and administration of unblinded steroids.4 Patients are likely to consider the need for short term steroids of trivial importance compared with mechanical ventilation and death, raising questions about the suitability of combining these components.
Frequency of component end points
The heart outcomes prevention evaluation (HOPE) study randomised 9297 patients at high risk of cardiac events to ramipril or placebo.5 Ramipril reduced cardiovascular deaths from 8.1% to 6.1% (relative risk reduction 26%, 95% confidence interval 13% to 36%), myocardial infarction from 12.3% to 9.9% (20%, 10% to 30%), and stroke from 4.9% to 3.4% (32%, 16% to 44%). The gradient in rates of death, myocardial infarction, and stroke in the control group (8.1%, 12.3%, and 4.9%) is relatively small. The difference in events between treatment and control (2.0% for deaths, 2.4% for myocardial infarction, and 1.5% for stroke) is even more similar. This provides support for focusing on the composite end point in clinical decision making. In some studies, however, the frequency of component end points differs greatly (see box B on bmj.com).
Treatment effects on component end points
Confidence in a composite end point rests partly on a belief that similar reductions in relative risk apply to all the components. Investigators should therefore construct composite end points in which the biology would lead us to expect similar effects across components.
For example, the authors of the CAPRIE study, a randomised trial of aspirin versus clopidogrel in patients at risk of ischaemic events, argued explicitly for the biological sense of their composite end point.6 Citing results of a meta-analysis of 142 trials of antiplatelet drugs versus placebo, they note the similar biological determinants of ischaemic stroke, myocardial infarction, and vascular death. Their argument strengthens the case for assuming, barring contrary evidence, that relative risk reductions are consistent across components of the composite end point. Box C on bmj.com describes a trial in which biology argues against expecting similar relative risk reductions across component end points.
No matter how strong the biological rationale, only evidence of similar relative risk reductions can strongly increase our comfort with a composite end point. In the HOPE trial described above, the risk reductions were similar for all components.5 In the losartan intervention for end point reduction in hypertension study, however, the relative risk reductions of the component end points differed greatly (−7% for myocardial infarction, 25% for stroke, and 11% for cardiovascular death),7 even though the rationale for using a combined end point was the same as in the CAPRIE study.6 In this case it would be better to consider individual component end points. Sometimes the risk reductions of component end points look similar but the confidence intervals are wide (box D on bmj.com).
Applying the questions
Let us return to the scenario of the patient reluctant to have surgery to control his angina. Is it reasonable to use the composite end point from the TIME trial (death, myocardial infarction, and hospital admission for acute coronary syndrome) to guide the decision, or should we focus on individual results of the three components?
To determine the answer, we can ask the three questions in the box. In response to the first question, most patients will find death and serious myocardial infarction with subsequent disability far more important than a short admission for acute coronary syndrome with rapid return to previous function.
Composite end points are outcomes that capture the number of patients experiencing one or more of several adverse events
The validity of composite end points depends on similarity in patient importance, treatment effect, and number of events across the components
When large variations exist between components the composite end point should be abandoned
The answers to the other two questions are also negative. Hospital admissions occurred far more frequently than the two more important events (table). Biological rationale fails to support a presumption that the invasive strategy will have similar effects on all three end points. Indeed, the investigators explicitly state that they expect an increase in short term deaths with surgery, while achieving benefits in terms of decreased angina and associated hospital admissions. The trend toward increased deaths, with a large reduction in admissions, with the invasive strategy provides support for this hypothesis. The composite end point thus fails all three criteria and provides little useful information for clinical decision making.
The widespread use of composite end points reflects their elegant simplicity as a solution to the problem of declining event rates. Unfortunately, use of composite end points makes the interpretation of the results of randomised trials for clinical decision making challenging. Investigators and their sponsors may claim treatment effects over a broad range of outcomes, whereas the effect may in fact be limited to one component. Occasionally, composite end points prove useful and informative for clinical decision making. Often, they do not. These users' guides will help clinicians differentiate between these situations.
Further examples are available on bmj.com
Contributors and sources The authors are clinicians, methodologists, and trialists with expertise in the conduct or the interpretation of clinical trials. In preparation for this article we reviewed Medline and the Cochrane Methodology Register for studies, editorials, and commentaries about the use of composite end points in clinical trials. GP-M, IF-G, and GHG conceived the idea for the article; VMM, GP-M, IF-G, and GHG reviewed the methodological literature and contributed to the framework presented in this manuscript; VMM and GHG created the first draft, and edited subsequent revisions; all authors offered critical revisions to the manuscript and the illustrative examples we used in the manuscript; all approved the final version; GHG is the guarantor.
Funding VMM is a Mayo Foundation Scholar. JWB is funded by a Canadian Institutes of Health research fellowship award. G P-M and JA are partially supported by funds from the Fondo de InvestigaciÓn Sanitaria. EM is funded by an Ontario HIV Treatment Network research award.
Competing interests None declared.