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Coronary Artery Disease Phase 4 Completed NCT04006288

DAPT: Complete Statistical Analysis of Dual Pathway Inhibition in Coronary Artery Disease

An independent statistical review of the randomized phase 4 DAPT trial evaluating switching from dual antiplatelet therapy to low-dose rivaroxaban in adjunct to aspirin in patients with coronary artery disease, with maximal platelet aggregation measured by light transmittance aggregometry as the primary endpoint.

Study period: 2019-09-06 to 2022-01-31  ·  Sponsor: University of Florida  ·  Enrollment: 90
Registry context

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

DAPT was a randomized, parallel-design, unmasked phase 4 study in patients with coronary artery disease. The registry describes six arms and an enrollment of 90 participants. The primary endpoint was maximal platelet aggregation (MPA%) by light transmittance aggregometry at 30 days.

90
Enrollment
Six-arm study
6
Arms
Parallel design
4
Phase
Phase 4
30
Primary time frame
Days
FeatureDAPT
AcronymDAPT
NCT IDNCT04006288
PhasePhase 4
StatusCompleted
ConditionCoronary Artery Disease
AllocationRandomized
Design modelParallel
MaskingNone
Primary purposeTreatment
Enrollment90
Number of arms6
Lead sponsorUniversity of Florida
Sponsor typeOther
Start date2019-09-06
Primary completion date2022-01-31

2. Clinical Question

The central question was whether switching from a dual antiplatelet therapy regimen to low-dose rivaroxaban in adjunct to aspirin was associated with a different level of maximal platelet aggregation at 30 days in patients with coronary artery disease.

Population

Patients with coronary artery disease enrolled in the DAPT study.

Interventions

Clopidogrel, prasugrel, ticagrelor, aspirin, and rivaroxaban are listed as study interventions in the registry.

Comparator structure

The primary endpoint compares MPA% measured by LTA using the CATF cocktail between DAPT and low-dose rivaroxaban plus aspirin for each DAPT regimen.

Primary question

How does maximal platelet aggregation at 30 days compare between DAPT and low-dose rivaroxaban plus aspirin for each DAPT regimen?

3. Trial Design

01
Enroll 90 patients
02
Randomize Six arms
03
Treat DAPT or low-dose rivaroxaban + aspirin
04
Assess MPA% by LTA
05
Day 30 Primary endpoint
Allocation
Randomized allocation was used.
Design model
The registry identifies the study as a parallel-design trial.
Masking
The study is listed as having no masking.
Primary purpose
The registry identifies treatment as the primary purpose.

Six-arm structure

The registry reports six arms. The serious-adverse-event records identify six 15-participant arm records, with each record reporting 0 affected participants out of 15 at risk. The arm labels in the registry are reproduced below because the statistical interpretation of a six-arm study depends on keeping the treatment structure explicit.

Registry arm labelSerious adverse events
Aspirin and Clopidogrel0/15
Aspirin and Rivaroxaban From Aspirin and0/15
Aspirin and Prasugrel0/15
Aspirin and Rivaroxaban From Aspirin and0/15
Aspirin and Ticagrelor0/15
Aspirin and Rivaroxaban From Aspirin and0/15

4. Endpoints

EndpointTime frameRegistry definition
Maximal Platelet Aggregation (MPA%) by Light Transmittance Aggregometry (LTA) 30 days The primary end point of this study will be the comparison of MPA% measured by LTA using the CATF cocktail as agonist between DAPT and low-dose rivaroxaban plus aspirin for each DAPT regimen.

What the endpoint measures

MPA% is a continuous laboratory measurement of platelet aggregation obtained using light transmittance aggregometry. In this study, the measurement is made using the CATF cocktail as agonist. The statistical target is therefore different from a time-to-event endpoint such as survival: the primary comparison concerns a quantitative laboratory response measured at a specified follow-up time.

The 30-day time frame is important because the endpoint is explicitly defined at that time point. A treatment comparison at 30 days should not be interpreted as a comparison of longer-term clinical outcomes unless those outcomes are separately registered and reported.

5. Statistical Methodology

Continuous-outcome comparison

Because the primary endpoint is MPA%, the natural statistical framework is a comparison of a continuous outcome between the treatment conditions being compared. The exact statistical model used for the DAPT primary endpoint is not reported in the posted statistical analyses.

For a randomized study with a continuous outcome, an analysis of covariance (ANCOVA) is often useful when a prespecified baseline measurement of the same outcome is available. A simple two-group comparison can instead use a two-sample t-test when its assumptions are appropriate. In a multi-arm study, the model can include treatment group as a categorical factor and then estimate the treatment contrasts specified by the protocol.

Generic continuous-outcome model
Y = β0 + β1Treatment + ε

Here, Y represents the measured MPA%, treatment represents the randomized treatment condition, and β1 represents the estimated mean difference associated with that comparison.

Mean difference

For a continuous endpoint, a mean difference is often the most direct effect measure. If the estimated mean MPA% were lower in one treatment group than another, the difference would quantify the average separation between the groups on the MPA% scale.

Conceptual treatment contrast
Δ = Mean(MPA%)treatment − Mean(MPA%)comparator

A negative value would indicate a lower estimated mean MPA% in the first group under this definition of the contrast; a positive value would indicate a higher estimated mean.

Confidence intervals

A confidence interval around a mean difference quantifies statistical uncertainty in the estimated treatment contrast. Its width depends on factors such as variability in MPA%, sample size, and the statistical model.

The confidence interval should be interpreted as uncertainty around the population-level treatment contrast under the specified statistical framework. It is not the range in which individual patients' MPA% values are expected to fall.

Analysis of a six-arm randomized design

A six-arm design creates an important distinction between the overall treatment factor and the individual pairwise comparisons. A model can first represent treatment as a six-level categorical variable and then estimate prespecified contrasts. The primary endpoint definition specifically describes comparisons between DAPT and low-dose rivaroxaban plus aspirin for each DAPT regimen, so the scientifically relevant contrasts are regimen-specific rather than an undifferentiated comparison across all six arms.

6. Planned Analysis

The registry reports results as posted for the study, but no formal statistical analyses are posted in the ClinicalTrials.gov record for the primary endpoint. The registry reports that the primary endpoint is MPA% measured by LTA using the CATF cocktail as agonist at 30 days, comparing DAPT with low-dose rivaroxaban plus aspirin for each DAPT regimen.

For this type of continuous laboratory endpoint, an appropriate analysis would normally compare the mean MPA% between the prespecified treatment conditions, potentially using ANCOVA if a baseline MPA% measurement is available and was prespecified for adjustment. If no baseline measurement is included, an unadjusted comparison of means or a regression model with treatment as the explanatory variable would be possible. The exact choice should follow the prespecified statistical analysis plan.

Interpretation of the posted record: the ClinicalTrials.gov record identifies the primary endpoint and its 30-day time frame, but it does not post a formal statistical analysis with a treatment estimate, confidence interval, or p-value for that endpoint.

7. Results

The registry reports that results have been posted for the study, but the posted statistical analyses do not include a numerical treatment estimate, confidence interval, or p-value for the primary MPA% endpoint.

Primary endpoint: MPA% by LTA

30-day maximal platelet aggregation

No statistical estimate posted

Endpoint: MPA% by LTA using the CATF cocktail as agonist

Time frame: 30 days

Clinical Biostats interpretation

The endpoint is a continuous laboratory measurement, so the most informative treatment effect would ordinarily be expressed as a difference in mean MPA% between the relevant randomized treatment groups, together with a confidence interval. A ratio or hazard ratio would not be the natural primary effect measure for this endpoint unless a different model or transformation had been prespecified.

The absence of a posted treatment estimate means that the registry record does not provide a numerical magnitude for the difference in MPA% to interpret. It also means there is no posted confidence interval describing the precision of such an estimate and no posted p-value from which statistical evidence against a null hypothesis could be assessed.

A p-value, if available, would address compatibility with a specified null hypothesis; it would not measure the size or clinical importance of the treatment effect. Conversely, a confidence interval would provide information about both the estimated effect and its precision, but would not describe the distribution of individual patients' platelet measurements.

Because this is a randomized six-arm study with regimen-specific comparisons, multiplicity is also relevant if several primary contrasts were tested. The interpretation of individual p-values would depend on the prespecified method for controlling the familywise type I error rate or another multiplicity strategy.

8. Statistical Methods Explained

Why is MPA% a continuous-outcome problem?

MPA% is recorded on a numerical scale rather than as a binary event such as death or occurrence of a serious adverse event. That makes methods for continuous outcomes the natural starting point. The primary question becomes whether the distribution or mean level of MPA% differs between the prespecified treatment conditions at 30 days.

Why might ANCOVA be used?

If MPA% was measured at baseline as well as at 30 days, ANCOVA can compare 30-day MPA% while adjusting for baseline MPA%. This can improve precision when baseline values are predictive of follow-up values. The adjustment should be prespecified rather than selected after examining the treatment results.

What does a mean difference mean?

A mean difference expresses the average separation between two treatment groups on the original MPA% scale. For example, a negative treatment-minus-comparator difference would indicate a lower estimated average MPA% in the treatment group. The clinical meaning of that difference depends on how MPA% relates to platelet inhibition and clinical outcomes, which is distinct from the statistical calculation itself.

Why does the six-arm design matter?

With six randomized arms, there can be multiple possible pairwise comparisons. The primary endpoint is not simply a single six-group omnibus question: the registry specifically defines comparisons between DAPT and low-dose rivaroxaban plus aspirin for each DAPT regimen. The analysis therefore needs to preserve those regimen-specific contrasts.

Why does multiplicity matter?

If several treatment contrasts are tested independently at the same nominal significance level, the probability of obtaining at least one statistically significant result by chance can exceed the nominal level for an individual test. A prespecified multiplicity procedure can control the familywise error rate or otherwise define how the multiple comparisons should be interpreted.

What would a confidence interval add?

A confidence interval would show the precision of the estimated difference in MPA%. A narrow interval indicates greater statistical precision, while a wide interval indicates greater uncertainty. The interval should be considered together with the estimated treatment difference rather than treated as a substitute for the effect estimate itself.

9. Safety Results

The registry reports serious adverse events by arm. Every reported arm record has 0 affected participants out of 15 at risk.

ArmSerious adverse events
Aspirin and Clopidogrel0/15
Aspirin and Rivaroxaban From Aspirin and0/15
Aspirin and Prasugrel0/15
Aspirin and Rivaroxaban From Aspirin and0/15
Aspirin and Ticagrelor0/15
Aspirin and Rivaroxaban From Aspirin and0/15

The reported affected/at-risk values therefore indicate no serious adverse events among the participants represented in each of the six arm records. These are descriptive safety counts; they do not provide a formal statistical comparison of serious-adverse-event rates between treatment groups.

Small-arm interpretation: each reported safety denominator is 15. With relatively small group sizes, an absence of observed serious adverse events does not establish that the underlying risk is zero. It means that no affected participants were recorded among the 15 participants at risk in each listed arm.

10. Study Timeline

2019-09-06

Study start

The registry lists 2019-09-06 as the study start date.

2019–2022

Randomized phase 4 study

The study used randomized allocation, a parallel design, and no masking, with six arms and planned assessment of the primary endpoint at 30 days.

2022-01-31

Primary completion

The registry lists 2022-01-31 as the primary completion date.

Completed

Registry status

The current registry status posted on ClinicalTrials.gov for the study is completed.

11. Interpreting a Continuous Platelet-Aggregation Endpoint

Effect size

The key quantity for MPA% would ordinarily be the difference in MPA% between the randomized groups being compared. This preserves the measurement scale and directly describes how far apart the group averages are.

What an effect estimate would not mean

A difference in average MPA% would not by itself mean that every patient experienced that same difference. Individual measurements can vary substantially around the group mean. Nor would a statistical difference in MPA% automatically establish a corresponding difference in clinical events unless the relationship between the laboratory endpoint and clinical outcomes has been demonstrated.

Why precision matters

A treatment difference should be accompanied by an uncertainty interval whenever possible. The point estimate describes the observed or model-estimated contrast; the confidence interval describes how precisely that contrast has been estimated under the statistical model.

Why the p-value is not the effect size

A p-value addresses evidence against a specified null hypothesis. It does not tell the reader whether the difference in MPA% is large or small, nor does it describe whether the difference is clinically meaningful. Effect size and precision are therefore essential parts of the interpretation.

12. Statistical Issues Specific to the DAPT Design

Randomization

Randomized allocation is the central design feature supporting a causal comparison of the assigned treatment strategies, subject to adherence, missing data, and other post-randomization considerations.

Six treatment arms

The six-arm structure allows comparisons across several treatment conditions but also creates a multiple-comparison problem when several contrasts are evaluated.

30-day endpoint

The primary endpoint is defined at 30 days, making the analysis a fixed-time continuous-outcome comparison rather than a survival analysis.

No masking

The registry identifies the trial as having no masking. For an objective laboratory measurement, this may reduce some concerns about subjective outcome assessment, although other sources of bias remain relevant.

13. What the Registry Does and Does Not Establish Statistically

The ClinicalTrials.gov record establishes the study's randomized, parallel, unmasked design; its six-arm structure; its enrollment of 90; its coronary artery disease population; and its registered 30-day primary endpoint based on MPA% measured by LTA using the CATF cocktail as agonist.

The record also reports serious adverse event counts by arm, with 0/15 reported for each of the six arm records. Those values are useful descriptive safety information, but they are not equivalent to a formal hypothesis test or an estimated treatment effect.

For the primary endpoint, the registry does not post a numerical treatment estimate, confidence interval, or p-value in the statistical-analysis information. Consequently, the statistical interpretation of the primary endpoint is necessarily centered on the design, endpoint definition, appropriate analysis framework, and interpretation of effect measures rather than on a numerical treatment result.

14. Limitations

15. Why This Trial Matters Statistically

DAPT is a useful teaching case because its primary endpoint illustrates a different statistical problem from the time-to-event endpoints that dominate many large clinical-trial reports. The primary outcome is a quantitative laboratory measurement obtained at a fixed follow-up time, while the randomized design contains six treatment arms and regimen-specific comparisons.

ConceptHow it appears in DAPT
RandomizationPatients were allocated randomly to study treatment conditions.
Parallel designThe registry identifies the design model as parallel.
Six-arm comparisonThe study has six arms within an enrollment of 90.
Continuous endpointMPA% is a quantitative laboratory measurement.
Fixed-time analysisThe registered primary endpoint is measured at 30 days.
Mean differenceA natural effect measure for comparing average MPA% between treatment conditions.
ANCOVAA possible framework when baseline MPA% is available and prespecified for adjustment.
MultiplicityMultiple regimen-specific comparisons can require prespecified error control.
Confidence intervalProvides precision information around an estimated continuous-outcome contrast.
Safety descriptivesSerious adverse events are reported as affected participants divided by participants at risk for each arm.

16. Clinical Interpretation vs Statistical Interpretation

Statistical interpretation

The primary endpoint is a continuous MPA% measurement at 30 days. The appropriate statistical question is whether the prespecified randomized treatment contrasts produce different MPA% distributions or means, with effect estimates and uncertainty intervals used to quantify the differences.

Clinical interpretation

MPA% is a laboratory endpoint. Its clinical interpretation requires understanding what a difference in platelet aggregation means for platelet activity and whether that laboratory difference translates into patient-important clinical outcomes. The registry information presented here does not provide those additional outcome estimates.

17. Reading the Safety Data Correctly

The serious-adverse-event data illustrate an important statistical distinction between an observed event count and an estimated risk. Each arm record contains 0 affected participants among 15 at risk. The observed proportion is therefore zero in each reported arm record, but a zero observed count does not mathematically imply that the underlying population probability of a serious adverse event is zero.

Descriptive safety quantity
Observed event proportion = Affected participants / Participants at risk

For each arm record in the registry, the reported numerator is 0 and the reported denominator is 15.

Formal comparison of safety rates would require an appropriate statistical model and an explicit definition of the safety estimand. With no events observed in the reported arm records, ordinary asymptotic methods can also perform poorly in small samples; exact or other methods may be considered depending on the prespecified analysis.

18. Primary Endpoint: A Practical Statistical Framework

StepStatistical question
1. Define outcomeUse MPA% measured by LTA with the CATF cocktail at 30 days.
2. Define contrastCompare DAPT with low-dose rivaroxaban plus aspirin for each DAPT regimen.
3. Select modelUse an appropriate continuous-outcome model, potentially ANCOVA if baseline MPA% adjustment was prespecified.
4. Estimate effectReport the treatment contrast on the MPA% scale, typically as a mean difference when the mean is the target estimand.
5. Quantify precisionReport a confidence interval for each prespecified treatment contrast.
6. Address multiplicityApply the prespecified method for handling multiple regimen-specific comparisons.
7. Interpret clinicallyConsider whether the magnitude of the laboratory difference has meaningful implications beyond statistical significance.

This framework separates the statistical estimand from the biological interpretation. A statistically estimated difference in MPA% answers the measurement question directly; whether that difference represents a clinically meaningful change is a separate question.

19. Sources

Continue through the Clinical Biostats knowledge graph

Explore statistical methods for randomized trials, continuous outcomes, treatment contrasts, confidence intervals, and multiplicity in clinical research.

20. Record Summary

DAPT is a randomized, parallel phase 4 study of patients with coronary artery disease, with 90 participants and six arms. Its primary endpoint is maximal platelet aggregation (MPA%) measured by light transmittance aggregometry using the CATF cocktail as agonist at 30 days, with comparisons between DAPT and low-dose rivaroxaban plus aspirin for each DAPT regimen.

Statistically, the study is best understood as a multi-arm randomized comparison of a continuous laboratory endpoint. The central analytical issues are the definition of regimen-specific treatment contrasts, estimation of differences in MPA%, appropriate use of baseline adjustment when prespecified, confidence-interval interpretation, and control of multiplicity across multiple comparisons.

The registry reports serious adverse events as 0/15 in each of its six arm records. For the primary endpoint, the registry identifies the outcome and time frame but does not post a numerical treatment estimate, confidence interval, or p-value. The most important statistical lesson is therefore how the randomized six-arm design and continuous 30-day endpoint determine the appropriate analysis and interpretation framework.

Clinical Biostats methodology: A rigorous trial-results analysis should distinguish the estimand, the randomized comparison, the statistical model, the precision of the estimate, multiplicity, and the clinical meaning of the endpoint. For DAPT, those distinctions are especially important because the primary outcome is a fixed-time continuous laboratory measurement rather than a clinical time-to-event outcome.