This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record.
1. Trial at a Glance
COMPLETE was a randomized, parallel-group clinical trial evaluating complete revascularization compared with culprit-only revascularization after early PCI for STEMI in patients with multivessel disease.
| Feature | COMPLETE |
|---|---|
| NCT ID | NCT01740479 |
| Status | Completed |
| Phase | NA |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | Single |
| Primary purpose | Prevention |
| Lead sponsor | Population Health Research Institute |
2. Clinical Question
Population
Patients with acute myocardial infarction and coronary artery disease enrolled after early PCI for STEMI with multivessel disease.
Intervention
Complete Revascularization Strategy (procedure).
Comparator
Culprit-only revascularization.
Primary question
Does complete revascularization improve composite cardiovascular outcomes compared with culprit-only treatment?
3. Trial Design
4. Endpoints
| Endpoint | Time frame | Description |
|---|---|---|
| Composite of cardiovascular death or new myocardial infarction | Over duration of follow-up (average of approximately 4 years) | Co-primary outcome: CV death or new MI |
| Composite of cardiovascular death, new myocardial infarction or ischemia-driven revascularization | Over duration of follow-up (average of approximately 4 years) | Co-primary outcome: CV death, new MI or IDR |
5. Planned Analysis
The ClinicalTrials.gov record identifies the primary outcomes but does not report posted statistical analyses or outcome estimates. The registry does not report formal endpoint results for the co-primary outcomes.
For composite cardiovascular time-to-event outcomes of this type, a typical analysis evaluates time from randomization to the first occurrence of any component event. Statistical methods commonly include survival analysis approaches such as Kaplan-Meier estimation for event-free probability over time and regression models such as Cox proportional-hazards models to estimate relative treatment effects.
How composite endpoints are interpreted
A composite endpoint combines multiple clinically relevant events into a single outcome. The analysis generally counts the first qualifying event experienced by each participant. Interpretation requires understanding which components drive the overall result because components may differ in clinical importance and frequency.
6. Statistical Methodology
Randomization
Randomization is designed to create comparable treatment groups at baseline, allowing differences in outcomes to be attributed more confidently to the assigned strategies rather than measured and unmeasured baseline differences.
Time-to-event analysis
Because cardiovascular death, myocardial infarction, and revascularization occur over follow-up time, survival analysis methods are appropriate. These methods account for participants who have not experienced an event by the end of observation or who have incomplete follow-up.
The survival function represents the probability that an event has not occurred by time t.
Hazard ratios
A Cox proportional-hazards model is commonly used for randomized cardiovascular trials because it compares event rates over time while accounting for follow-up duration.
A hazard ratio below 1 would indicate a lower estimated instantaneous event rate in the intervention group relative to the comparator. It would not represent the percentage of patients prevented from having an event, and it would not describe the experience of every individual participant.
Confidence intervals describe uncertainty around an estimate. A narrow interval suggests greater precision than a wide interval, while a p-value addresses compatibility with a statistical hypothesis and does not measure the size or importance of an effect.
7. Statistical Methods Explained
Why use a composite endpoint?
A composite endpoint can increase statistical efficiency by counting multiple clinically relevant outcomes together, particularly when individual events are less frequent.
Why does time-to-event analysis matter?
Participants are followed for different lengths of time. Survival methods allow researchers to use available follow-up information without requiring every participant to experience an event.
What does randomization accomplish?
Randomization balances known and unknown prognostic factors between groups on average, supporting an unbiased comparison of assigned strategies.
Why analyze cardiovascular death and myocardial infarction together?
The combined endpoint reflects a broader cardiovascular outcome measure, but interpretation requires consideration of the contribution of each component.
Why are confidence intervals important?
An estimate alone does not show how much uncertainty surrounds the finding. Confidence intervals provide a range of values compatible with the observed data under the statistical model.
8. Limitations
- No posted analyses: The ClinicalTrials.gov record does not report statistical estimates, confidence intervals, p-values, or endpoint results.
- Composite interpretation: A composite endpoint may be influenced disproportionately by the more frequent components.
- Time-to-event assumptions: Hazard-based models depend on assumptions about how event rates behave over follow-up.
- Follow-up duration: The primary endpoint time frame is described as the duration of follow-up with an average of approximately 4 years.
9. Why This Trial Matters Statistically
COMPLETE is a useful statistical teaching example because it illustrates several important principles in cardiovascular clinical trials.
| Concept | Application |
|---|---|
| Randomization | Comparison of complete revascularization and culprit-only strategies |
| Composite endpoints | Combining cardiovascular death, myocardial infarction, and ischemia-driven revascularization outcomes |
| Time-to-event analysis | Evaluation of outcomes occurring over follow-up |
| Clinical interpretation | Separating statistical estimates from individual patient outcomes |