Temporal Trends in Use of Composite End Points in Major Cardiovascular Randomized Clinical Trials in Prominent Medical Journals
Bibliographic record
Abstract
Background— Cardiovascular mortality has decreased over the past 5 decades, making it increasingly difficult to demonstrate significant benefits of new therapies in randomized clinical trials. We sought to determine whether the use of composite end points in major cardiovascular trials has changed over time and examine temporal trends in the clinical importance of individual components of these composite end points. Methods and Results— Using a validated search strategy, we searched MEDLINE for randomized trials of therapies for primary or secondary cardiovascular prevention published in New England Journal of Medicine , The Lancet , and the Journal of the American Medical Association between 1986 and 2015. We abstracted and categorized study population demographics, type of intervention, and primary and secondary outcomes. Composite end point components were ranked according to importance (minor, moderate, major, critical, and death) and temporal trends analyzed. In total, 604 of 2607 trials retrieved met inclusion criteria. Use of composite end points increased significantly over time from 18.8% between 1986 and 1990 to 83.0% between 2011 and 2015 ( P <0.001). The number of components in the primary end point also increased significantly (median 1 in 1986–1990, median 3 in 2011–2015; P <0.001). Contemporary trials were more likely to include end points of lesser importance to patients (minor 3.1% and moderate 6.3% in 1986–1990, minor 4.5% and moderate 44.6% in 2011–2015; P <0.001). Use of death as the sole primary end point declined significantly over time (53.1% in 1986–1990, 17.9% in 2011–2015; P <0.001). Conclusions— Contemporary cardiovascular randomized clinical trials are more likely to use primary composite end points that contain a larger number of components. Furthermore, these composite end points have increasingly incorporated components of lesser clinical importance. Clinicians and policymakers interpreting results of randomized trials should recognize that the significance of individual components in a composite end point is often heterogeneous.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.523 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.036 | 0.013 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".