We included parallel group randomised controlled trials that involved humans exposed to any cardiovascular therapeutic intervention and reported at least one composite end point. We defined a cardiovascular clinical trial as any randomised controlled trial in which the target population of the study had to have coronary artery disease, valvular heart disease, arrhythmia, cardiomyopathy, or congestive heart failure on entry. We also included randomised controlled trials investigating primary prevention of cardiovascular disease. We excluded trials that reported composite end points with components relating to toxicity or safety or with no outcomes important to patients (that is, including only surrogate outcomes) or subgroup analyses that ignored random allocation.
We used Medline to search electronically four high impact general medicine journals (Lancet, Annals of Internal Medicine, JAMA
, and New England Journal of Medicine
) and two leading cardiology journals (Circulation
and European Heart Journal
), from 1 January 2002 to 30 June 2003. We used the publication type function to restrict our search to “randomized controlled trial” and “human” subjects; the National Library of Medicine and the US Cochrane Center have collaborated to use these terms to accurately index randomised controlled trials in the Medline database.4
Eight investigators (JWB, EAA, DMB, PA-C, AW, SU, VP-H, and AD-S), working in pairs, used standardised forms to establish if abstracts of articles identified in our electronic search were parallel group randomised controlled trials studying humans and covered a cardiology topic (as defined above). We retrieved the full text of all potentially eligible articles. The same reviewers independently assessed eligibility of the full text articles with standardised forms and resolved discrepancies by discussion. An arbitrator (VMM) resolved any discrepancies that remained.
Seven reviewers (JWB, EAA, DMB, PA-C, AW, SU, and IF-G) trained in health research methods worked in pairs to extract data independently and in duplicate, using a standardised form and a data collection manual. Reviewers collected information on content area and the type of interventions tested, sample size, the length of follow-up, the number of composite end points presented, and the declared source(s) of funding.
To avoid confounding, we explored only data associated with each trial's primary composite end point. When authors reported more than one composite end point, we established the primary one by using the following hierarchy: (a) authors' explicit declaration of primacy, (b) the composite end point used to calculate the sample size, (c) authors' attribution of importance to the composite end point in their description of the results, and (d) the composite end point that appeared first in the methods section. Two reviewers (JWB and IF-G) independently selected the primary composite end point, resolving discrepancies by discussion.
For each composite end point we extracted the number of components, the effect of the intervention on the composite end point, and the number of events attributed to the composite end point. For the component end points of each composite end point we recorded the effect of the intervention and the number of patients who achieved the outcome. When authors reported results from the same composite end point for more than one time point, we used data from the longest interval. A statistician (DH-A) entered all data into an electronic database and reviewed them for errors and missing data.
Ranking of outcomes according to importance to patients
Patients will typically assign varying importance to different health outcomes.5
We sought, but were unable to find, a published hierarchical categorisation of importance to patients for cardiovascular outcomes. Therefore, to explore the variability in importance to patients across components, we developed a hierarchical categorisation of importance to patients for the component end points included in eligible studies. Two cardiologists (GP-M and IF-G) and nine internists (GHG, HJS, VMM, EAA, RJ, JA, VP-H, PA-C, and AD-S) independently categorised each of 72 outcomes used as components of composite end points in the eligible trials into five categories (I to V, in descending order of importance): I=death, II=critical, III=major, IV=moderate, and V=minor. Estimates of utility associated with the outcomes guided the process.6
Group members met to resolve disagreements and succeeded in coming to consensus.
The κ statistic provided a measure of interobserver agreement independent of chance on the eligibility of randomised controlled trials. We calculated, for each of the five categories of outcomes, the median event rate and the interquartile range for the control group as well as the effect of the intervention within the category by using the authors' reporting of relative risk, odds ratio, or hazard ratio. To ensure independence of observations within categories of importance to patients, we selected only one end point in each category for each composite end point to make these calculations; where a composite included more than one end point in the same category, we selected the end point with the highest event rate in the control group. To estimate the effect of the intervention across trials and within each category, we used random effects meta-analyses with an inverse variance approach. This method is conservative, in that it considers both within study and between study differences in estimating the pooled estimate. We used the I2
statistic, the percentage of between study variability that is due to true differences between studies (heterogeneity) rather than sampling error (chance), to quantify inconsistency among trials.7
To describe the gradient of importance to patients among component end points, we considered a large gradient to be present in composite end points combining outcomes from categories I or II (fatal and critical) with outcomes from category V (minor). We considered a moderate gradient to be present when composite end points combined outcomes from categories I or II with outcomes from category IV (moderate) without any component from category V. We assigned a minor or absent gradient to composite end points not included in the other two categories.
We limited analysis of the gradient of efficacy across components to those composite end points that provided data on at least two of their individual end points. We assigned a large gradient in the effect of the intervention if the difference between the smallest and largest reported treatment effects (relative risk, odds ratio, or hazard ratio) was >0.4, a moderate gradient when the difference was 0.2 to 0.4, and a small gradient when the difference was <0.2.
Among composite end points with moderate or large gradients in importance to patients, we explored the impact of the outcomes with less importance to patients on both the total event rate for the composite end point in the control group and the magnitude of effect of the intervention. Our approach was to quantify, in sequence, the impact of adding component end points from importance to patients category III (major end points) and categories IV and V (moderate and minor end points) to end points allocated to categories I and II (fatal and critical end points). This was only possible for those studies that supplied data for each component of the composite in categories I, II, and III (fatal, critical, and major). For each study, we first calculated the event rate in the control group and the relative risk reduction on the basis of a composite of all the end points in categories I and II included in the original composite. We then repeated these calculations for another composite including all end points in categories I, II, and III. When adding the moderate and minor components (categories IV and V), we used the data for the original composite end point reported in the paper to calculate the control event rate and the relative risk reduction. Thus, we did not need component data for end points in categories IV and V.
Calculation of the exact impact would require joint distributions for all the components; because authors did not provide this level of detail, we made estimations by using a conservative approach to assess the impact of the outcomes of moderate and minor importance to patients. To establish the effect on the event rate for the control group, we estimated the impact of fatal and critical end points under the assumption that no patient had both a critical and a fatal event or more than one critical event. For instance, if the rate of death for the control group was 1% and that of large stroke was 2%, we calculated an event rate for the end points within importance to patients categories I and II of 3%. We then estimated the effect of adding the events associated with end points grouped in category III of importance to patients, again assuming mutually exclusive events, to the more serious events. Thus, if the rate of non-fatal myocardial infarctions was 2%, the event rate for the control group would increase from 3% to 5%. We considered the end points grouped in categories IV and V of importance to patients to account for the total composite end point event rate left unaccounted. Thus, if the composite end point event rate for the control group was 10%, the effect of adding the less important outcomes (categories IV and V) would increase the control event rate from 5% to 10%.
A similar approach allowed assessment of the impact of outcomes grouped according to importance to patients on the effect of the intervention. We calculated the median and associated interquartile range for both the control group event rate and the effect of the intervention. We calculated a test of proportions (χ2 test) to explore associations between gradients in either importance to patients or of the effect of treatment on components within composite end points by declared source of funding (industry versus non-industry funded). We used SAS version 9.1 and S-PLUS version 6.2 (Insightful Corporation, Seattle, Washington) for analyses; we chose a 5% threshold for statistical significance for all analyses.