This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record. The numerical trial information on this page is restricted to the ClinicalTrials.gov record. The registry reports that results are posted, but no formal statistical analyses are included in the ClinicalTrials.gov record.
1. Trial at a Glance
COLCOT was a randomized, parallel, phase 3 cardiovascular trial evaluating colchicine versus colchicine placebo in participants with coronary artery disease and myocardial infarction. The trial used quadruple masking and enrolled 4745 participants.
| Feature | COLCOT |
|---|---|
| Brief title | Colchicine Cardiovascular Outcomes Trial (COLCOT) |
| Phase | Phase 3 |
| Therapeutic area | Cardiovascular |
| Conditions | Coronary Artery Disease; Myocardial Infarction |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | Quadruple |
| Primary purpose | Prevention |
| Enrollment | 4745 |
| Arms | 2 |
| Lead sponsor | Montreal Heart Institute |
| Sponsor type | OTHER |
| Status | COMPLETED |
| Trial start | 2015-12-04 |
| Primary completion | 2019-07-17 |
| ClinicalTrials.gov | NCT02551094 |
2. Clinical Question
The registry describes COLCOT as a phase 3 prevention trial in participants with coronary artery disease and myocardial infarction. The registered primary endpoint asks whether participants experience a first event from a prespecified cardiovascular composite during follow-up.
Population
Participants enrolled in a cardiovascular prevention trial involving coronary artery disease and myocardial infarction.
Intervention
Colchicine.
Comparator
Colchicine placebo.
Primary question
How does the occurrence of the registered first-event cardiovascular composite compare between randomized colchicine and placebo groups?
The ClinicalTrials.gov record does not provide a more detailed eligibility description, treatment dose, treatment schedule, or baseline demographic table.
3. Trial Design
Colchicine
- Study intervention: colchicine.
- Trial allocation: randomized.
- Design: parallel.
- Masking: quadruple.
Colchicine placebo
- Study intervention: colchicine placebo.
- Trial allocation: randomized.
- Design: parallel.
- Masking: quadruple.
Trial timeline
Trial start
The COLCOT trial began on December 4, 2015.
Primary completion
The registry lists July 17, 2019 as the primary completion date.
Trial status
ClinicalTrials.gov lists the trial status as completed and indicates that results have been posted.
4. Endpoints
| Endpoint | Registry definition | Time frame | Type |
|---|---|---|---|
| First Event of Cardiovascular Death, Resuscitated Cardiac Arrest, Acute Myocardial Infarction, Stroke, or Urgent Hospitalization for Angina Requiring Coronary Revascularization | The descriptive statistics are the number of participants having at least one of the composites of the primary endpoint. | From randomization to occurrence of first event, assessed up to 3.5 years | Binary |
The registry identifies one primary endpoint and classifies it as binary. Importantly, its time frame is also defined from randomization to occurrence of the first event, assessed up to 3.5 years. That combination matters statistically: the registry's posted descriptive measure is a participant-level first-event indicator, while the underlying clinical question also has a time-to-first-event dimension.
Each participant is classified according to whether at least one component of the composite occurs during the registered assessment period. The first qualifying event is the event of interest for the registered endpoint.
Why a composite endpoint requires careful interpretation
A composite endpoint combines several clinically distinct event types into one analysis target. This can increase the number of observed events and create a single prespecified outcome, but the components need not have identical clinical importance, frequency, or treatment responsiveness.
For COLCOT, the registry definition combines five event categories: cardiovascular death, resuscitated cardiac arrest, acute myocardial infarction, stroke, and urgent hospitalization for angina requiring coronary revascularization. The ClinicalTrials.gov record does not report component-specific event counts or treatment effects, so the statistical interpretation must remain at the composite level.
5. Statistical Methodology
ClinicalTrials.gov identifies the primary endpoint as binary and states that its descriptive statistics are the number of participants having at least one component of the composite endpoint. The ClinicalTrials.gov record does not contain a formal statistical analysis, effect estimate, confidence interval, or p-value for this endpoint.
What the registered endpoint naturally supports
For a binary endpoint defined by whether a participant experiences at least one qualifying event, a conventional analysis could compare the proportion of participants with an event between randomized treatment groups. Depending on the prespecified statistical analysis plan, possible effect measures include a risk difference, risk ratio, or odds ratio, accompanied by a confidence interval and an appropriate hypothesis test.
Because the endpoint is also explicitly defined from randomization to occurrence of the first event, a time-to-event analysis may also be appropriate when the analysis retains the timing of events and censoring. Kaplan-Meier estimation and a Cox proportional-hazards model are common approaches for such endpoints, but the ClinicalTrials.gov record does not state that either method was used for COLCOT's primary analysis. They are therefore discussed here as statistical methods that could be appropriate for this endpoint structure, not as reported COLCOT methods.
| Question | What the ClinicalTrials.gov record establishes | What is not established |
|---|---|---|
| Was the endpoint prespecified? | Yes; one primary endpoint is registered. | The ClinicalTrials.gov record does not provide the full statistical analysis plan. |
| Was the endpoint binary? | Yes; the registry classifies it as Binary. | The ClinicalTrials.gov record does not identify the formal comparison test. |
| Was a formal effect estimate posted? | No statistical analyses are reported in the provided record. | No HR, risk ratio, odds ratio, risk difference, confidence interval, or p-value can be reported from the ClinicalTrials.gov record. |
| Was timing relevant? | Yes; assessment is from randomization to occurrence of first event, up to 3.5 years. | The ClinicalTrials.gov record does not identify whether a time-to-event model was used. |
6. Planned Analysis
Because the ClinicalTrials.gov record contains no formal statistical analyses, the appropriate approach is to distinguish the registered measurement from an analysis that would normally be used for this type of endpoint.
Primary endpoint
First cardiovascular composite event
Participants are classified according to whether they experience at least one component of the registered composite from randomization through the assessment period.
The registry specifies assessment up to 3.5 years but does not provide a formal treatment-effect estimate in the registry-reported statistical-analysis field.
Typical binary analysis
If the endpoint is analysed strictly as a binary outcome at the end of the specified observation period, the basic comparison would be the number of participants with at least one qualifying event in each randomized group divided by the relevant analysis population. A risk difference would describe the absolute difference in event probability, while a risk ratio would describe the ratio of event probabilities.
These are general statistical definitions, not reported COLCOT estimates. The ClinicalTrials.gov record does not provide the corresponding formal analysis.
Typical time-to-event analysis
If the timing of the first event is retained, a survival-analysis framework would use each participant's follow-up time and event/censoring status. Kaplan-Meier curves could estimate the probability of remaining free of the composite event over time. A Cox model could summarize the relative instantaneous event rate as a hazard ratio.
That distinction is particularly important here because the registry does not merely specify a fixed binary assessment at one calendar date. It describes the endpoint as the first event occurring from randomization and assesses it over a period of up to 3.5 years.
7. Statistical Methods Explained
Why was a composite endpoint used?
A composite endpoint combines several related clinical outcomes into a single prespecified outcome. Statistically, this can increase the number of participants experiencing the primary endpoint compared with relying on a rarer individual event alone. The trade-off is interpretational: the composite represents the occurrence of any qualifying component, and the individual components can differ in severity, frequency, and clinical meaning.
What does "first event" mean?
The registry defines the primary outcome around the first occurrence of one of the listed components. If a participant experiences more than one component during follow-up, the endpoint classification is already satisfied by the first qualifying event. This avoids counting the same participant repeatedly in the primary binary endpoint.
Why does the registry call the endpoint binary if time is involved?
Binary classification and time-to-event analysis are two ways of representing related information. A binary endpoint records whether an event occurred during a specified observation window. A time-to-event endpoint additionally retains when the event occurred and can account for different follow-up durations through censoring. The COLCOT registry definition uses a binary endpoint classification while also specifying a time window from randomization to first event.
What would a risk difference tell us?
A risk difference would quantify the absolute difference in the probability of experiencing at least one primary composite event between the randomized groups over the defined assessment period. Unlike a relative effect, it directly describes the difference in event probability. The ClinicalTrials.gov record does not provide the event counts needed to calculate a COLCOT risk difference.
What would a hazard ratio tell us?
If a time-to-event Cox model were prespecified, a hazard ratio would compare the estimated instantaneous event rates between groups over the analysed follow-up. A hazard ratio below 1 would correspond to a lower estimated instantaneous event rate in the numerator treatment group. It would not mean that the same percentage of participants avoided the event, nor would it directly equal a risk ratio.
Why does randomization matter statistically?
Randomization creates the basis for comparing outcomes between treatment assignments without relying solely on observed baseline characteristics to remove confounding. The registry identifies COLCOT as randomized and parallel. The ClinicalTrials.gov record does not provide the randomization ratio, allocation sequence, stratification factors, or block structure, so those features should not be inferred.
What does quadruple masking contribute?
Quadruple masking is a design feature intended to limit knowledge of treatment assignment among specified trial roles. This can reduce opportunities for treatment knowledge to influence participant behavior, clinical management, outcome assessment, or other trial processes. The ClinicalTrials.gov record does not identify the four masked roles, so the specific operational consequences cannot be stated more precisely.
8. Results Status and What Can Be Reported
ClinicalTrials.gov identifies COLCOT as having results posted and lists 12 outcome measures. However, the ClinicalTrials.gov record contains no formal statistical analyses. This creates an important distinction between results availability and formal statistical-analysis availability in the ClinicalTrials.gov record.
| Evidence available in the ClinicalTrials.gov record | Reportable here |
|---|---|
| Results posted | Yes |
| Outcome measures posted | 12 |
| Primary endpoint | Yes |
| Primary endpoint definition | Yes |
| Primary endpoint time frame | Yes |
| Formal statistical analysis entries | No |
| Formal effect estimate | No |
| Confidence interval | No |
| p-value | No |
For that reason, there is no defensible primary efficacy result to reproduce on this page from the ClinicalTrials.gov record. Reporting a hazard ratio, risk ratio, odds ratio, confidence interval, or p-value from another source would violate the scope of the ClinicalTrials.gov record.
9. Safety
the ClinicalTrials.gov record includes serious adverse-event counts by arm. These are reported as affected participants over the corresponding at-risk denominator.
| Safety measure | Affected / at risk |
|---|---|
| Colchicine placebo | 404 / 2346 |
| Colchicine | 383 / 2330 |
The ClinicalTrials.gov record does not provide a confidence interval, p-value, formal between-arm safety comparison, adverse-event definitions beyond the serious-adverse-event label, or a breakdown by specific serious adverse event. Accordingly, the counts are reported descriptively rather than converted into a formal comparative safety estimate.
The serious-adverse-event figures show that 404 participants in the placebo group and 383 participants in the colchicine group are listed as affected among their respective at-risk denominators. These counts alone do not establish whether the observed difference is statistically significant, clinically meaningful, or attributable to treatment. A formal comparison would require the prespecified safety analysis population, event definitions, timing, and an appropriate inferential method.
10. Interpreting the Primary Endpoint Without an Effect Estimate
A useful statistical analysis must sometimes identify what the available data do not establish. Here, the registry provides a well-defined primary endpoint but no registry-reported formal statistical-analysis result.
What is known
The trial was randomized, parallel, phase 3, quadruple masked, and designed for prevention. The primary endpoint was a first occurrence of a five-component cardiovascular composite assessed from randomization to up to 3.5 years.
What is not known from the registry record
The ClinicalTrials.gov record does not provide the treatment-effect estimate, confidence interval, p-value, analysis population for the efficacy result, or formal statistical model.
Why this matters
A difference in descriptive event counts is not interchangeable with a formal estimate of treatment effect. The denominator, analysis population, censoring rules, and prespecified inferential method all affect the interpretation.
What should not be inferred
The ClinicalTrials.gov record does not support a conclusion about the magnitude or statistical significance of the colchicine treatment effect on the primary endpoint.
11. Censoring and Follow-Up
The registered primary endpoint is assessed from randomization to occurrence of the first event, with assessment up to 3.5 years. This wording introduces an important survival-analysis concept even though the registry classifies the endpoint as binary.
In a pure fixed-window binary analysis, a participant would ultimately be classified as having or not having experienced a qualifying event during the prespecified window. In a time-to-event analysis, participants who have not experienced an event by their last evaluable follow-up can be censored, allowing their available follow-up time to contribute information without treating incomplete observation as proof that an event will never occur.
The ClinicalTrials.gov record does not specify the censoring rules, loss-to-follow-up rules, competing-event handling, or imputation strategy. These details can materially affect time-to-event analyses and should be taken from the formal statistical analysis plan if available.
12. Multiplicity and the Composite Endpoint
The registry identifies one primary endpoint. That is useful for understanding the nominal primary outcome structure: the principal endpoint is the first event of the specified cardiovascular composite.
However, the ClinicalTrials.gov record does not provide the statistical testing hierarchy, familywise type I error allocation, multiplicity adjustment, or rules governing secondary endpoints. Because those details are absent, this page does not assign a multiplicity strategy to the trial.
| Statistical issue | What the ClinicalTrials.gov record supports |
|---|---|
| Number of registered primary endpoints | 1 |
| Primary endpoint type | Binary |
| Composite endpoint | Yes |
| Multiplicity procedure | Not provided |
| Alpha allocation | Not provided |
| Interim analysis plan | Not provided |
13. Analysis Population and Denominators
Randomized enrollment is reported as 4745 participants. The ClinicalTrials.gov record uses denominators of 2346 for colchicine placebo and 2330 for colchicine, for a total of 4676 participants represented in those safety denominators.
The ClinicalTrials.gov record does not explain the difference between the total enrollment and the safety denominators. It would therefore be inappropriate to assign the remaining participants to a particular exclusion, withdrawal category, or analysis population without additional evidence.
The denominator is part of the definition of an estimate. Different analysis populations can produce different descriptive event proportions even when the numerator is unchanged.
14. Blinding and Randomization as Statistical Design Features
The registry identifies COLCOT as randomized and quadruple masked. These are not merely administrative labels; they are design features that affect the credibility and interpretation of a comparative clinical trial.
Randomization
Randomization assigns participants to intervention groups according to a prespecified allocation mechanism. Its principal statistical role is to create treatment groups whose potential outcomes can be compared under the randomization framework. With adequate implementation, randomization reduces systematic differences in both measured and unmeasured baseline factors in expectation.
Masking
Masking reduces the possibility that knowledge of treatment assignment influences participant behavior, clinical management, outcome ascertainment, or other study processes. The ClinicalTrials.gov record specifies quadruple masking but do not define the four masked roles.
Parallel design
A parallel design means participants remain associated with their assigned treatment arm rather than each participant sequentially receiving both randomized interventions. This is structurally different from a crossover trial, and no crossover design is identified in the ClinicalTrials.gov record.
15. What the Primary Endpoint Does — and Does Not — Mean
The primary endpoint measures whether a participant experiences at least one of the prespecified cardiovascular events: cardiovascular death, resuscitated cardiac arrest, acute myocardial infarction, stroke, or urgent hospitalization for angina requiring coronary revascularization.
The composite does not provide a separate treatment effect for each component. A participant experiencing one component and a participant experiencing another component both satisfy the primary endpoint, even though the clinical circumstances differ.
For a composite endpoint, the overall result can be driven by components that occur more frequently. Component-specific results are therefore important for understanding the clinical composition of the composite. Those component-specific results are not included in the ClinicalTrials.gov record.
16. Limitations
- No formal statistical analyses reported: no formal statistical analyses were posted, so no primary treatment-effect estimate, confidence interval, or p-value can be reported from the ClinicalTrials.gov record.
- Composite endpoint: the primary endpoint combines five clinically distinct event categories, and component-specific results are not reported.
- Binary versus time-to-event representation: the registry classifies the endpoint as binary while defining it from randomization to first event over a period of up to 3.5 years. The formal analytic representation is not reported.
- Analysis population: the ClinicalTrials.gov record identifies total enrollment and safety denominators but do not define the primary efficacy analysis population.
- Missing-data methods: no imputation or missing-data strategy is provided.
- Censoring: no formal censoring rules are provided for a potential time-to-event analysis.
- Multiplicity: the ClinicalTrials.gov record does not describe alpha allocation, endpoint hierarchy beyond the single registered primary endpoint, or adjustment procedures for other outcomes.
- Interim analysis: the ClinicalTrials.gov record does not identify whether an interim efficacy or futility analysis occurred or how such analyses were controlled statistically.
- Safety interpretation: serious-adverse-event counts are available, but the ClinicalTrials.gov record does not provide a formal comparative safety analysis.
- External validity: the ClinicalTrials.gov record identifies the cardiovascular conditions and prevention purpose but does not provide the detailed eligibility criteria or baseline characteristics needed to assess generalizability more fully.
17. Why This Trial Matters Statistically
| Concept | How it appears in COLCOT |
|---|---|
| Randomization | The trial is registered as randomized. |
| Parallel design | The design model is parallel. |
| Blinding | The trial is quadruple masked. |
| Composite endpoint | The primary endpoint combines five cardiovascular event categories. |
| Binary endpoint | The registry classifies the primary endpoint as Binary. |
| First-event analysis | The endpoint is defined from randomization to occurrence of the first event. |
| Follow-up window | The primary endpoint is assessed up to 3.5 years. |
| Denominators | Safety results are reported with arm-specific affected/at-risk counts. |
| Analysis transparency | The ClinicalTrials.gov record reports results availability but contains no formal statistical-analysis entries. |
| Statistical restraint | The absence of an effect estimate means the analyst should not infer one from descriptive information alone. |
18. Statistical Interpretation: Evidence Versus Inference
A high-quality trial analysis distinguishes three layers of information.
Registered fact
COLCOT was a randomized, parallel, phase 3, quadruple-masked trial with 4745 enrolled participants and one registered primary binary composite endpoint.
Descriptive result
The ClinicalTrials.gov record reports serious adverse events as 404/2346 for colchicine placebo and 383/2330 for colchicine.
Statistical method
A binary endpoint can be analysed with risk-based effect measures, while a first-event endpoint with retained event times can be analysed using survival methods.
Unsupported inference
The ClinicalTrials.gov record does not support a formal claim about the magnitude, confidence interval, or statistical significance of the primary treatment effect.
This separation is especially important in trial-result reporting. Statistical analysis is not simply the process of attaching a p-value to an observed difference. The analysis population, endpoint definition, follow-up rules, censoring, treatment assignment, and prespecified model all determine what a reported estimate means.
19. Clinical Interpretation vs Statistical Interpretation
Statistical interpretation
The trial's registered primary endpoint is a binary first-event composite assessed from randomization to up to 3.5 years. The ClinicalTrials.gov record does not include the formal comparison estimate or inferential statistics.
Clinical interpretation
The endpoint was designed to capture several important cardiovascular outcomes in a single prevention endpoint. Its clinical interpretation depends on both the composite result and, when available, the individual component outcomes.
The distinction is deliberate. A statistical result describes the evidence generated under a specified analysis; a clinical interpretation considers what that evidence means in the context of the endpoint and study population.
20. A Worked Statistical Framework for the Primary Endpoint
Although the ClinicalTrials.gov record does not contain the formal COLCOT comparison, the registered endpoint can be used to illustrate how an analyst would structure the question.
Step 1: Define the estimand
The analysis would first define the treatment comparison, the population, the primary composite endpoint, and the observation period. Here, the registry identifies randomized allocation, colchicine versus placebo, and the first occurrence of the specified composite from randomization to up to 3.5 years.
Step 2: Define the analysis population
The analyst would identify which randomized participants are included in the primary efficacy analysis and establish how withdrawals, missing outcomes, and incomplete follow-up are handled. The ClinicalTrials.gov record does not provide these rules.
Step 3: Define the effect measure
For a binary analysis, the effect could be expressed as a risk difference or risk ratio. For a time-to-event analysis, a hazard ratio could be used alongside survival estimates. The choice must come from the prespecified analysis plan rather than being selected after seeing the results.
Step 4: Quantify uncertainty
The effect estimate should be accompanied by a confidence interval. A confidence interval communicates statistical uncertainty around the estimated treatment effect; it does not describe the range of outcomes that individual participants will experience.
Step 5: Evaluate the composite
After assessing the primary composite, component-specific outcomes would ordinarily be examined to understand which events contributed to the composite. This is particularly important when the components differ substantially in clinical severity or frequency. Those component-specific results are not reported here.
Step 6: Assess robustness
A complete analysis would examine sensitivity to missing data, censoring assumptions, analysis population, and the selected statistical model. Again, the ClinicalTrials.gov record does not provide these details.
21. Related Tutorials
Learn more about the methods used in this trial:
22. Related Statistical Calculators
23. Sources
- ClinicalTrials.gov: COLCOT — NCT02551094. Official trial registry record.
- Linked publication: PubMed record for PMID 32860034: https://pubmed.ncbi.nlm.nih.gov/32860034/.
- Linked publication: PubMed record for PMID 31733140: https://pubmed.ncbi.nlm.nih.gov/31733140/.
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24. Record Summary
COLCOT is a randomized, parallel, quadruple-masked phase 3 cardiovascular prevention trial with 4745 enrolled participants and two intervention groups: colchicine and colchicine placebo. Its registered primary endpoint is the first occurrence of cardiovascular death, resuscitated cardiac arrest, acute myocardial infarction, stroke, or urgent hospitalization for angina requiring coronary revascularization, assessed from randomization to occurrence of the first event and up to 3.5 years.
The statistical teaching value of the ClinicalTrials.gov record lies partly in what it makes possible and what it does not. The endpoint is clearly defined, its binary classification is explicit, and the trial design establishes a randomized comparison. The appropriate statistical interpretation is therefore to explain the endpoint, identify the analysis methods that would ordinarily be considered, and preserve the distinction between registry facts and methodological inference.