A Comparison of Ticagrelor (AZD6140) and Clopidogrel in Patients With Acute Coronary Syndrome: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Comparison of Ticagrelor (AZD6140) and Clopidogrel in Patients With Acute Coronary Syndrome (NCT00391872), a randomized phase 3 study. The primary outcome is Participants With Any Event From the Composite of Death From Vascular Causes, Myocardial Infarction (MI), and Stroke.

2. Clinical Question

The clinical question is framed around a composite outcome rather than a single event. It combines death from vascular causes, myocardial infarction, and stroke, and the registry specifies that events were adjudicated by an endpoint committee. The primary outcome description says that the analysis was intention to treat in the full population. Participants without an event could be censored at the earliest of withdrawal of consent or the scheduled withdrawal-from-therapy date.

The comparison is randomized and parallel group, so the question concerns outcomes in the groups assigned to ticagrelor and clopidogrel, not a comparison of people who chose their treatment. The record identifies acute coronary syndrome as the condition and gives the trial title as a comparison of the two medicines in this population. It does not report detailed eligibility criteria or the specific clinical rationale for choosing the endpoint components.

3. Trial Design

The registry identifies this as a Phase 3, randomized, quadruple-masked, parallel-group study. The record lists enrollment as 18624 and status as completed. The study start is recorded as 2006-10, and primary completion as 2009-03. AstraZeneca is identified as the sponsor. The official title describes a randomized, double-blind efficacy and safety study, while the registry masking field specifies quadruple masking.

The two intervention groups received oral ticagrelor or oral clopidogrel. The brief summary describes the medicines as being compared in conjunction with aspirin. The registry record does not report doses, treatment duration beyond the outcome timeframe, adherence, or other details of concomitant care. It also does not report the original statistical design assumptions or the sample-size justification.

For the primary outcome, the analysis population is described as the full analysis set, including all randomized patients, and the endpoint description specifies an intention-to-treat analysis. The primary outcome timeframe runs from randomization up to 12 months. The outcome is a count of participants with at least one event in the specified composite; it is not a count of all events experienced by each participant. Event adjudication by an endpoint committee is reported.

The record includes secondary outcomes involving other composites and individual events, including myocardial infarction, vascular death, stroke, death from any cause, and non-CABG-related major bleeding. It lists 16 outcome measures and 14 posted secondary outcomes. Detailed secondary comparisons are available for three secondary composites. Statistical methods beyond the listed comparisons, the handling of all secondary endpoints, and the original analysis plan are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: Participants will already be hospitalized due to their acute condition, and must be enrolled and randomized within 24 hours of the onset of their most recent cardiac ischemic symptoms. Randomization should take place as soon as possible after presentation.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The population was the full analysis set, which included all randomized patients

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Participants With Any Event From the Composite of Death From Vascular Causes, Myocardial Infarction (MI), and Stroke, measured over Randomization up to 12 months.

The primary endpoint counts participants who experienced at least one of three events: death from vascular causes, myocardial infarction, or stroke. The timeframe is randomization up to 12 months. Participants with no event could be censored at the earliest of withdrawal of consent or the scheduled withdrawal-from-therapy date. The record states that the analysis used the intention-to-treat approach in the full analysis set, which included all randomized patients, and that events were adjudicated by an endpoint committee.

A composite endpoint combines multiple outcomes into one measure. As a general statistical concept, this can capture a broader range of important events and can make an overall comparison more informative than focusing on a single component alone. However, a composite can also conceal differences among its components: a treatment-group contrast in the combined outcome does not establish that every component moved in the same direction or contributed equally. Component-specific primary results are not reported in the primary outcome entry.

The primary result is expressed as the number of participants with an event in each group, with a risk difference comparing the groups. This answers how the observed event proportions differed over the stated follow-up, rather than how many total events occurred. The record does not report a detailed rationale for selecting these three components or the statistical method used to handle censoring.

7. Results Posted in the Registry

• CLOPIDOGREL: 10.9% (1014/9291) versus 9.3% (864/9333) on control; risk difference 1.7 percentage points (95% CI 0.8 to 2.5), risk ratio 1.18 (1.08–1.28); unadjusted two-proportion z-test p = <0.001.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Participants With Any Event From the Composite of Death From Vascular Causes, MI, and Stroke for the Subgroup of Patients With Intent for Invasive Management at Randomization

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • CLOPIDOGREL: 10.0% (668/6676) versus 8.5% (569/6732) on control; risk difference 1.6 percentage points (95% CI 0.6 to 2.5), risk ratio 1.18 (1.06–1.32); unadjusted two-proportion z-test p = 0.002.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for CLOPIDOGREL than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Participants With Any Event From the Composite of All-cause Mortality, MI, and Stroke

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • CLOPIDOGREL: 11.5% (1065/9291) versus 9.7% (901/9333) on control; risk difference 1.8 percentage points (95% CI 0.9 to 2.7), risk ratio 1.19 (1.09–1.29); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for CLOPIDOGREL than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Participants With Any Event From the Composite of Death From Vascular Causes, MI (Including Silent), Stroke, Recurrent Ischemia, Transient Ischemic Attack (TIA) and Other Arterial Thrombotic Events.

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • CLOPIDOGREL: 15.7% (1456/9291) versus 13.8% (1290/9333) on control; risk difference 1.8 percentage points (95% CI 0.8 to 2.9), risk ratio 1.13 (1.06–1.22); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for CLOPIDOGREL than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Among the secondary endpoints with detailed arm-level comparisons, the point estimates consistently indicate a higher event proportion in the clopidogrel group than in the ticagrelor group. The posted risk-difference intervals for these comparisons are above zero, and the unadjusted p-values are 0.002 or <0.001. This general direction is compatible with the primary composite result. It does not establish that every secondary endpoint in the registry, or every individual component within a composite, has the same pattern.

The secondary outcomes broaden the question in different ways. They include a composite restricted to participants with intent for invasive management at randomization, a composite including all-cause mortality, myocardial infarction, and stroke, and a broader composite that also includes recurrent ischemia, transient ischemic attack, and other arterial thrombotic events. The registry also lists individual outcomes and safety outcomes, but detailed comparative estimates are not present for every listed outcome in the secondary entries.

Secondary outcomes can help describe whether the primary finding sits within a broader pattern of outcomes, but they do not replace the primary endpoint. In general, testing many outcomes increases the chance that some may appear statistically notable by chance, especially when results are considered without adjustment. The reported secondary p-values are explicitly unadjusted, and the registry record does not report a multiplicity-control strategy or a hierarchy for interpreting secondary outcomes. Consequently, the secondary comparisons carry less confirmatory weight than the primary comparison and should be interpreted as supportive or exploratory evidence, not independent proof of a broad treatment effect.

The subgroup endpoint concerns patients with intent for invasive management at randomization. A subgroup result is specific to that selected population and should not automatically be generalized to all randomized patients. The registry does not report a formal interaction analysis comparing subgroup and overall effects. Without such an analysis, a result within a subgroup does not establish that the treatment contrast differs between subgroups.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Participants With Any Event From the Composite of Death From Vascular Causes, MI, and Stroke for the Subgroup of Patients With Intent for Invasive Management at Randomization
• Participants With Any Event From the Composite of All-cause Mortality, MI, and Stroke
• Participants With Any Event From the Composite of Death From Vascular Causes, MI (Including Silent), Stroke, Recurrent Ischemia, Transient Ischemic Attack (TIA) and Other Arterial Thrombotic Events.
• Participants With MI Event
• Participants With Death From Vascular Causes
• Participants With Stroke
• Participants With Death From Any Cause
• Participants With Non-CABG (Coronary Artery Bypass Graft) Related Major Bleeding

9. Statistical Interpretation

10. Statistical Methods Explained

The registry presents a binary outcome: each participant is counted as having or not having at least one event in the endpoint definition during the specified timeframe. The primary outcome is a participant count, not a total event count. A participant with multiple components of the composite still contributes as a participant with an event in this outcome description. The record does not provide component-specific primary counts.

What does the risk difference describe?

The risk difference subtracts one group's event proportion from the other group's proportion. In the posted comparison, the order is clopidogrel minus ticagrelor. The estimate is 0.017, with a confidence interval from 0.008 to 0.025. A positive value in this ordering means the observed event proportion is higher in the clopidogrel group. Unlike a relative measure, the risk difference stays on the scale of the absolute separation in event proportions. The record gives the group proportions as 0.093 and 0.109.

How do relative measures differ?

The risk ratio compares the event proportions between groups, while the odds ratio compares event odds. Their posted estimates are 1.179 and 1.201, respectively. Their confidence intervals are 1.082 to 1.285 for the risk ratio and 1.091 to 1.321 for the odds ratio. Because these measures use different scales, their numerical values are not directly comparable to the risk difference. For binary outcomes that are not rare, the odds ratio can be farther from 1 than the risk ratio; this is a general statistical property, not a claim about a specific analysis choice in this trial.

What does the p-value contribute?

The primary unadjusted p-value is <0.001. In general, a p-value describes the probability, assuming a specified null model and its assumptions, of data at least as incompatible with that model as the observed data. It is not the probability that the treatment groups are truly identical, and it does not describe the size or importance of the contrast. The registry record does not report details of the test used to produce this p-value, such as its exact form or adjustment for covariates.

Why are confidence intervals useful?

A confidence interval expresses uncertainty around an estimate. In general, a confidence interval constructed by a method with a stated coverage level would cover the underlying parameter at that rate over repeated studies, if the method's assumptions hold. It is not a guarantee that the true value lies within the interval for this particular trial. The interval also helps show whether the data are compatible with a narrow or a wide range of effects. The posted primary interval does not cross zero on the risk-difference scale, but its endpoints still allow a range of positive contrasts.

Random allocation is intended to make baseline prognostic factors comparable between groups on average. Masking can reduce the risk that knowledge of assignment influences care or outcome assessment. The registry lists randomization and quadruple masking, but the specific people masked and the procedures used to maintain masking are not reported in the registry record. Endpoint adjudication by a committee is reported for the primary outcome.

The primary outcome description identifies an intention-to-treat analysis in the full analysis set, which includes all randomized patients. In general, intention-to-treat analyses preserve the comparison based on assigned treatment and are less vulnerable to bias from excluding participants after randomization. The endpoint description also mentions censoring for participants without an event at the earliest of consent withdrawal or scheduled withdrawal from therapy. The statistical handling of censoring, missing outcomes, and any departures from assigned treatment is not described in detail.

The registry gives event counts and group sizes, and the posted comparison provides an unadjusted risk difference, relative measures, confidence intervals, and p-value. It does not report the model specification, covariate adjustment, test procedure, or the full statistical analysis plan. Therefore, these details should not be inferred from the numbers alone. The registry record also does not state whether interim analyses were planned or conducted.

11. Confidence Intervals and Precision

The primary risk-difference estimate is 0.017, with a confidence interval from 0.008 to 0.025. The endpoints are both positive, so the interval is consistent with a higher observed event proportion in the clopidogrel group under the comparison's stated ordering. The interval's width conveys uncertainty about the size of that contrast; the estimate should not be read as an exact value known without error.

The posted risk-ratio estimate is 1.179, with a confidence interval from 1.082 to 1.285. The odds-ratio estimate is 1.201, with a confidence interval from 1.091 to 1.321. These intervals likewise lie above 1, the no-difference value for those relative measures. Each interval refers to its own effect scale, so their limits should not be compared as if they measured the same quantity.

Confidence intervals are general statistical summaries of uncertainty, conditional on the method and its assumptions. The registry record does not identify the interval-construction method, nor does it report adjusted intervals. The unadjusted p-value is <0.001, but statistical significance does not eliminate uncertainty about the precise effect size. A confidence interval does not measure the likelihood of a treatment being beneficial, and it does not resolve uncertainty about the trial's applicability to other populations or follow-up periods.

For the secondary composites with posted comparisons, the risk-difference intervals are also entirely above zero. Their estimates and uncertainty should be considered in the context of the multiple endpoints assessed. The registry does not report a multiplicity plan, and the apparent precision of an individual interval does not account for the broader set of outcomes unless an appropriate adjustment has been made. Whether such adjustments were used is not reported in the registry record.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm for 80% power and participants per arm for 90% power. They are not totals across both arms, and they are not observed participant counts from the trial. For the primary outcome, the planning illustration gives 5,188 participants per arm for 80% power and 6,945 participants per arm for 90% power when planning for 100% of the observed effect. The entries for planning for 75% and 50% of the observed effect require larger numbers per arm.

The assumptions listed for this illustration are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to be detected is the stated fraction of the observed effect. The trial's own original sample-size assumptions and design justification are not reported in the registry record. These figures are a planning illustration based on the observed effect, not observed power.

In general, the 80% power column indicates the planned group size for a design intended to have an 80% probability of detecting the specified effect under the stated assumptions, if that effect is present and the assumptions hold. The 90% column uses a higher target probability of detecting that effect and therefore calls for a larger group size. These are design probabilities, not probabilities that the findings are correct.

The planning curve should be read as expressing the same relationship: choosing a smaller target effect requires more participants per arm under the stated assumptions. It is not a forecast of the actual result, and the observed enrollment does not validate the assumptions used in the illustration. For the binary outcomes in these planning entries, the stated quantities are participants per arm; the total-events convention noted for time-to-event outcomes does not apply to these entries.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.093; treatment proportion p₁ = 0.109; average p̄ = 0.101.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4259 = 0.8347.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4257 = 0.3583.
4. n = (0.8347 + 0.3583)² / (0.0166)² = 5,187.8, rounded up to 5,188 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.0925747348119576                          # control proportion
p1 <- 0.109137875363255                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(391872)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 5,188 (80% power), 6,945 (90% power)
 75% of observed effect: n per arm = 9,056 (80% power), 12,122 (90% power)
 50% of observed effect: n per arm = 19,995 (80% power), 26,767 (90% power)
power.prop.test: 5187.8 
Simulated power at n = 5,188 per arm: 0.798 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The primary endpoint is clearly identified in the registry record, but a full statistical analysis plan is not reported. The record lists 16 outcome measures and 14 posted secondary outcomes. It does not describe a prespecified testing hierarchy, a familywise error strategy, or another approach to controlling multiplicity across secondary endpoints. The secondary p-values are unadjusted. This matters because multiple comparisons can increase the chance of at least one apparently unusual result when all are interpreted as confirmatory.

Multiplicity does not make the observed estimates meaningless. It changes how strongly isolated secondary results should be treated as evidence, particularly when several outcomes have been assessed. The consistent direction among the secondary comparisons with detailed estimates is relevant descriptive context, but it does not substitute for a reported multiplicity plan. The registry does not report interim analyses, stopping rules, or whether any such procedures affected the final inference.

The primary outcome entry states that the analysis used the intention-to-treat approach in the full analysis set, which included all randomized patients. It also states that participants without an event could be censored at the earliest of withdrawal of consent or scheduled withdrawal from therapy. The record does not explain the censoring model, how incomplete follow-up was handled in practice, or whether sensitivity analyses were performed. The numbers of participants with missing outcome information and the reasons for missingness are not reported in the registry record.

The distinction matters because missing outcomes can affect estimates if the probability of missingness is related to outcome risk or treatment assignment. In general, statistical approaches rely on assumptions about the data that are missing and the censoring process. Those assumptions and any checks on them are not described in the registry. The record's stated intention-to-treat population and censoring description are useful, but they do not provide enough detail to reconstruct the full analysis or evaluate every missing-data assumption.

15. What the Result Does, and Does Not, Mean

The posted primary comparison shows fewer participants with the composite event in the ticagrelor group than in the clopidogrel group during randomization up to 12 months. The estimated risk difference is 0.017, with a confidence interval from 0.008 to 0.025, and the unadjusted p-value is <0.001. These statistics describe the observed randomized-group comparison for the endpoint as defined in the registry.

The result does not show that every participant assigned to one group had a better outcome, nor does it indicate that every component of the composite changed in the same way. It also does not provide component-specific primary estimates, an estimate beyond the stated timeframe, or a comparison of all possible benefits and harms. A composite result can be driven by one or more components, and the primary outcome entry does not provide enough information to determine the contribution of each component.

The trial was randomized and the primary analysis is described as intention to treat, features that support interpreting the contrast by assigned group. Still, the registry result is not a guarantee of causation under every circumstance: interpretation depends on trial conduct, outcome ascertainment, follow-up, and analysis assumptions. The registry reports endpoint committee adjudication, but does not provide detailed methods for adjudication or for handling incomplete observations.

Statistical significance is not the same as clinical importance. The p-value does not quantify the size of the outcome difference, while the risk difference and its confidence interval describe the magnitude and precision on an absolute scale. Whether an observed difference is important to patients or clinicians requires clinical context that is not established by the registry statistics alone. No medical advice follows from this statistical description.

The record does not establish how well the findings apply to patients outside the enrolled population. Detailed eligibility criteria, treatment doses, adherence, and the original statistical analysis plan are not reported in the registry record. Nor do the posted comparisons resolve uncertainty about unreported secondary analyses or multiplicity. The result should therefore be read as evidence about the specified randomized comparison and composite endpoint, rather than as a complete account of every outcome or every clinical decision.

16. Why This Trial Matters Statistically

This trial illustrates how a large randomized comparison can be described on several statistical scales. The primary outcome is reported as participant counts and proportions, an absolute risk difference, relative measures, confidence intervals, and an unadjusted p-value. Each presents a different aspect of the same comparison. Considering the absolute and relative scales together helps prevent a p-value from standing in for the size and precision of the estimated contrast.

The endpoint also demonstrates an important feature of composite outcomes. Combining vascular death, myocardial infarction, and stroke gives a single primary measure covering multiple events, but the combined estimate does not reveal which components account for the result. The presence of other registry outcomes underscores why endpoint definitions and analysis populations matter when interpreting a trial.

The trial record identifies randomization, masking, an intention-to-treat primary analysis, a full analysis set, and endpoint adjudication. These design and analysis details help readers assess the basis of the comparison. At the same time, the record does not report the original statistical plan, multiplicity strategy, or detailed missing-data methods. Recognizing what is specified and what remains unreported is part of sound statistical interpretation.

Finally, the planning illustration shows why sample-size calculations depend on the effect a study aims to detect. Under the stated planning assumptions, smaller effects require more participants per arm. Because the illustration is based on the observed effect and is not the trial's original design calculation, it should not be confused with evidence about the trial's actual power. These distinctions are useful when moving from interpreting one trial to planning or assessing future research.

17. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record leaves several trial-specific details unavailable. It does not report the full eligibility criteria, treatment doses, duration of assigned treatment, adherence, or detailed concomitant treatment procedures. The summary describes both medicines in conjunction with aspirin, but does not specify the treatment regimens in enough detail to assess those aspects of trial conduct.

The primary outcome is a composite, and the registry entry does not provide separate primary estimates for vascular death, myocardial infarction, and stroke. The combined result therefore cannot establish whether each component contributed similarly. Nor does the primary timeframe support conclusions about outcomes beyond randomization up to 12 months.

The record provides counts for adverse-event entries but does not report the at-risk denominators for those entries. Serious adverse-event counts are 2108 for ticagrelor and 2117 for clopidogrel; other adverse-event counts are 2278 and 1665, respectively. Without the relevant denominators and further definitions, these counts alone do not provide comparative event rates. The record lists cardiac failure at 1.4%, non-cardiac chest pain at 1.1%, pneumonia at 1.0%, cerebrovascular accident at 0.8%, dyspnoea at 0.8%, and atrial fibrillation at 0.8% among the leading serious terms, but does not provide enough context in this entry to interpret these as a complete safety comparison.

Further limitations include the absence of a reported full analysis plan, multiplicity strategy, interim-analysis information, and detailed missing-data methods. The registry describes censoring and an intention-to-treat population, but not the full procedures used to implement those approaches. These omissions limit independent reconstruction of the analysis and assessment of its sensitivity to assumptions.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: A Comparison of Ticagrelor (AZD6140) and Clopidogrel in Patients With Acute Coronary Syndrome — NCT00391872.
• Registry record last updated 2012-03-13; status last verified 2012-02.
• Results first posted 2012-03-13.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

The registry record describes a completed, randomized, quadruple-masked, parallel-group Phase 3 trial of oral ticagrelor versus oral clopidogrel in patients with acute coronary syndrome. Enrollment is listed as 18624; the start is 2006-10 and primary completion is 2009-03. The primary outcome is the number of participants with vascular death, myocardial infarction, or stroke from randomization up to 12 months, analyzed in the full analysis set according to the intention-to-treat description.

The primary event counts were 864 with ticagrelor and 1014 with clopidogrel. The risk difference, clopidogrel minus ticagrelor, was 0.017, with a confidence interval from 0.008 to 0.025; the unadjusted p-value was <0.001. Secondary comparisons generally point in the same direction among those with detailed estimates, but the registry does not report a multiplicity strategy. The original design assumptions, detailed analysis plan, and full missing-data methods are not reported in the registry record.