REVEAL: Randomized EValuation of the Effects of Anacetrapib Through Lipid-modification: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for REVEAL: Randomized EValuation of the Effects of Anacetrapib Through Lipid-modification (NCT01252953), a randomized phase 3 study. The primary outcome is Number of Participants With Major Coronary Event.

2. Clinical Question

This is a randomized comparison of treatment allocation, rather than a comparison based on which treatment participants actually took. The primary assessment is described as intention-to-treat and includes all randomized participants. That framing preserves the allocation groups for the comparison, although details about adherence, treatment changes, and handling of missing outcome information are not reported in the registry record.

The endpoint combines three clinically distinct events into one outcome. A composite can capture whether any component occurred and can provide a broader summary of the clinical question than any one component alone. Its interpretation depends on the component definitions and on how the components contribute to the combined result. The registry record defines the components but does not report component-specific primary results in the material available.

3. Trial Design

REVEAL is a Phase 3, randomized, quadruple-masked, parallel-group trial sponsored by the University of Oxford. It compared anacetrapib with placebo anacetrapib among people with established vascular disease. The registry lists enrollment of 30,449 participants. The primary outcome arm counts use 15,220 participants in each group; the registry record does not explain the difference between the overall enrollment figure and those outcome denominators.

The trial summary describes anacetrapib at 100mg daily and frames the study question in patients whose LDL cholesterol was treated with a statin. Arm descriptions beyond the intervention names are blank, so further details about background treatment or treatment delivery are not reported in the registry record. The primary assessment is an intention-to-treat comparison during the scheduled treatment period.

The primary outcome timeframe is the randomized treatment phase during a median follow-up period of 4.1years. The registry lists the study start as 2011-06 and primary completion as 2017-01-31. Its status is active, not recruiting. These registry fields describe the trial record and do not, by themselves, establish how long each participant was followed or what happened after the recorded treatment phase.

Parallel-group randomization assigns participants to groups that are followed as distinct treatment-allocation arms. Masking is intended, in general, to limit the influence of knowledge of assigned treatment on trial conduct or assessment. The record specifies quadruple masking but does not identify which roles were masked or describe the masking procedures. The randomization sequence, allocation concealment, eligibility criteria, and detailed follow-up procedures 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: Successfully screened participants were entered into a run-in period. Attendees were discouraged from continuing to randomization if it was thought unlikely they would be able to continue attending follow-up visits for at least 4-5years. During run-in participants were issued atorvastatin (1 tablet/day) and placebo anacetrapib (1 tablet/day).

Overall Study

Reasons for not completing this period:

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 Number of Participants With Major Coronary Event, measured over Randomized treatment phase during median follow-up period of 4.1years.

The primary endpoint is the number of participants with a first major coronary event during the scheduled randomized treatment period. The registry defines a major coronary event as coronary death, myocardial infarction, or coronary revascularization. The outcome is therefore a participant count for a composite endpoint, rather than a measure of the severity of an event or the total number of recurrent events.

The registry reports 1,640 participants with an event in the anacetrapib group and 1,803 in the placebo group, with 15,220 participants in each group for this outcome. The event counts are presented for the first major coronary event. The specified primary comparison is intention-to-treat, meaning participants are compared according to randomized allocation, regardless of later treatment received.

As a general statistical concept, a composite endpoint can summarize the occurrence of any of its defined components and may capture more events than an individual component. It is important to keep the endpoint’s meaning tied to its components: the composite result does not show that each component changed to the same degree. The registry record does not report separate primary estimates for coronary death, myocardial infarction, and coronary revascularization, or explain the rationale for choosing this composite.

7. Results Posted in the Registry

• Anacetrapib: 10.8% (1640/15225) versus 11.8% (1803/15224) on control; risk difference -1.1 percentage points (95% CI -1.8 to -0.4), risk ratio 0.91 (0.85–0.97); unadjusted two-proportion z-test p = 0.003.

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.

Number of Participants With Major Atherosclerotic Event

• 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:
  • Anacetrapib: 9.1% (1383/15225) versus 9.7% (1483/15224) on control; risk difference -0.7 percentage points (95% CI -1.3 to -0.0), risk ratio 0.93 (0.87–1.00); unadjusted two-proportion z-test p = 0.049.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Anacetrapib than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Number of Participants With Presumed Ischaemic 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:
  • Anacetrapib: 3.2% (485/15225) versus 3.2% (489/15224) on control; risk difference -0.0 percentage points (95% CI -0.4 to 0.4), risk ratio 0.99 (0.88–1.12); unadjusted two-proportion z-test p = 0.896.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Anacetrapib and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants With Major Vascular Event

• 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:
  • Anacetrapib: 13.6% (2068/15225) versus 14.5% (2214/15224) on control; risk difference -1.0 percentage points (95% CI -1.7 to -0.2), risk ratio 0.93 (0.88–0.99); unadjusted two-proportion z-test p = 0.016.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Anacetrapib than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes show a less uniform pattern than the primary comparison. The posted estimates for major atherosclerotic events and major vascular events point in the same general direction as the primary endpoint, while the presumed ischaemic stroke comparison is close to no difference in the posted counts. The sponsor-reported analyses also vary in their p-values and confidence intervals. These outcomes add context but do not replace the primary result.

Secondary endpoints are related to the broader vascular question but are not identical to the primary composite. Their definitions, components, and event frequencies differ. A consistent direction across some outcomes may be informative, but it does not prove that the primary composite’s components all contributed in the same way. The record does not report component-level results for the primary endpoint or further detail on the relationship among all outcome definitions.

The secondary comparisons are unadjusted in the simple recalculations. As a general statistical concern, testing multiple outcomes creates more opportunities for apparently notable results to arise by chance. When many tests are considered, a nominal p-value for one outcome can overstate the strength of evidence if the testing strategy is not accounted for. The registry record does not report a multiplicity adjustment or a hierarchy for interpreting the secondary outcomes.

Accordingly, secondary findings should be treated as supportive or exploratory unless the analysis plan establishes a confirmatory role. Their uncertainty, the number of outcomes examined, and any relationships among the outcomes all matter. The registry lists three secondary outcomes, but the record does not state whether these were the only secondary outcomes planned or how decisions about reporting were made. This limits the strength of conclusions that can be drawn from the secondary pattern alone.

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

• Number of Participants With Major Atherosclerotic Event
• Number of Participants With Presumed Ischaemic Stroke
• Number of Participants With Major Vascular Event

9. Statistical Interpretation

10. Statistical Methods Explained

The registry presents two statistical views of the primary comparison. The sponsor’s reported analysis uses a log-rank method and reports a rate ratio. The simple recalculation uses the posted event counts and arm denominators to estimate a risk difference. These methods answer related but not identical statistical questions, so their numerical estimates and p-values can differ without implying that one is a direct transcription of the other.

What does the risk difference describe?

As a general statistical concept, a risk difference compares the proportion of participants with an outcome in one group with the proportion in the other group. A value below zero for an anacetrapib-minus-placebo contrast means the event proportion is lower in the anacetrapib group in that calculation. The recalculated estimate and confidence interval are based on the posted summary counts. They do not adjust for event timing or other covariates. The registry’s sponsor analysis instead reports a rate ratio using a log-rank method.

What does the rate ratio describe?

The sponsor-reported rate ratio is a relative comparison of event rates as analyzed in the trial record. A rate ratio of 1 is the no-difference reference value: values below 1 indicate a lower rate in the first group in the comparison as reported. The log-rank method is commonly used for time-to-event comparisons and can account for when events occur and for follow-up that ends at different times, subject to the analysis details. The registry does not provide enough information to specify all features of the sponsor’s calculation, such as censoring rules or any stratification.

The sponsor’s primary result is 0.91, with a 95% confidence interval from 0.85 to 0.97 and p = 0.004. The recalculated risk-difference result has p = 0.003. Both results point in the same direction, but the measures should not be treated as interchangeable. A rate ratio expresses a relative event-rate comparison; a risk difference expresses an absolute difference in outcome proportions over the reported follow-up context.

How should a confidence interval be understood?

In general, a confidence interval expresses the statistical uncertainty around an estimate under the assumptions of its method. It gives a range of estimates compatible with the observed data and model, rather than a range that is guaranteed to contain the true effect. The interval’s location relative to the relevant null value helps describe whether the data are compatible with no difference under that analysis. Its width conveys precision: narrower intervals indicate less statistical uncertainty than wider intervals, all else equal.

Why do the analysis populations matter?

The primary assessment is described as an intention-to-treat comparison among all randomized participants. In general, retaining participants in their assigned groups preserves the comparison created by randomization and estimates the effect of allocation. The registry does not detail how participants with missing outcome information were handled, whether any participants were excluded from the sponsor analysis, or how changes in assigned treatment were addressed. These omissions limit independent assessment of the analysis population and the assumptions behind the result.

The registry reports a binary outcome kind and counts of participants with events. The primary outcome specifies the first major coronary event. A count of participants with at least one event differs from a count of all recurrent events, which is why the definition matters when interpreting the result. The registry lists three secondary outcomes in addition to the primary outcome, but does not provide a full account of how their analyses were prioritized or adjusted for multiple testing.

What is the role of p-values?

As a general explanation, a p-value measures the compatibility of observed data with a null model and assumptions. Smaller values indicate that the observed data would be less typical if that null model and those assumptions held. It does not quantify the probability that the null is true, the size of the effect, or the importance of an outcome. A p-value also does not resolve limitations in the study design or reporting.

The posted primary sponsor p-value and the recalculated p-value are close but not identical. The sponsor analysis is based on a log-rank rate-ratio approach, while the recalculation is a simple unadjusted comparison from summary counts. The record gives no evidence of a discrepancy requiring one result to replace the other; the two should instead be understood as results from different methods. Details of the trial’s original analysis plan, including any interim analyses, are not reported in the registry record.

11. Confidence Intervals and Precision

The sponsor-reported primary rate ratio is 0.91, with a 95% confidence interval from 0.85 to 0.97. This interval is entirely below the rate-ratio reference value of 1, and the posted p-value is 0.004. The recalculated primary risk-difference interval also lies below zero, with p = 0.003. The estimates therefore indicate a consistent direction across the reported sponsor analysis and the simple recalculation, while retaining uncertainty about the magnitude of the comparison.

Confidence intervals describe statistical precision, not certainty. In general, an interval is a range of values compatible with the data and the method’s assumptions. It does not mean that every value within the interval is equally plausible, nor does it incorporate all uncertainty about trial conduct, missing data, endpoint definitions, or analysis choices. A confidence interval cannot by itself determine whether a difference is clinically important.

The registry’s rate-ratio interval is comparatively compact around the reported estimate, but it still allows a range of relative effects. The recalculated interval is expressed on a different scale, so its width should not be compared directly with the rate-ratio interval. Comparing absolute and relative measures can help communicate different aspects of an effect, but one measure cannot be converted into the other without additional assumptions and data.

The sponsor analysis is a time-to-event method, while the recalculation uses summary event counts. The interval widths and endpoints reflect these distinct methods and their information use. The registry record does not provide individual event times, censoring information, or full analysis details that would allow an independent reconstruction of the sponsor’s interval. Precision should therefore be interpreted from the posted estimates and methods, not as a guarantee that the same interval would result from another analysis.

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 sample-size illustrations show the number of participants per arm for the binary outcomes in this trial. They are based on an equal allocation between two arms, a two-sided significance level of 0.05, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect: the full observed effect, 75% of the observed effect, or 50% of the observed effect. The time-to-event planning convention would use total events, but the displayed planning figures for these outcomes are participants per arm.

For each assumed effect, the 80% power column gives the approximate number of participants per arm for a design with an 80% chance of detecting that effect under the planning assumptions, if the effect and model assumptions are correct. The 90% power column gives the corresponding planning number for a 90% chance. Greater planned power generally requires more participants for the same assumed effect. The figures are planning illustrations computed from the observed effect, not the trial’s original design justification; the trial’s own original sample-size assumptions are not reported in the registry record.

Each row changes the effect size used for planning. A smaller effect requires more participants to detect, so the illustrations increase as the assumed fraction of the observed effect decreases. This is a general consequence of the greater difficulty of distinguishing a smaller effect from random variation. The figures are not observed power: observed power is not a useful substitute for interpreting the estimate and its confidence interval after results are available. The curve should be read as a visual representation of the relationship between planning assumptions and sample size, not as evidence about the trial’s actual design process.

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 = 0.118; treatment proportion p₁ = 0.108; average p̄ = 0.113.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4479 = 0.8778.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4478 = 0.3769.
4. n = (0.8778 + 0.3769)² / (-0.0107)² = 13,713.9, rounded up to 13,714 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 <- 0.118431424067262                          # control proportion
p1 <- 0.107717569786535                          # 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(1252953)
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 = 13,714 (80% power), 18,359 (90% power)
 75% of observed effect: n per arm = 24,633 (80% power), 32,976 (90% power)
 50% of observed effect: n per arm = 55,990 (80% power), 74,953 (90% power)
power.prop.test: 13713.9 
Simulated power at n = 13,714 per arm: 0.802 (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. Analyses Reported by the Sponsor

The sponsor’s reported primary analysis is a log-rank analysis with a rate-ratio estimate of 0.91, a 95% confidence interval from 0.85 to 0.97, and p = 0.004. The simple recalculation is an unadjusted risk-difference analysis of the posted counts and denominators, with p = 0.003. Both analyses point toward a lower primary-event measure in the anacetrapib allocation group, but they use different effect measures and different statistical approaches.

The rate ratio reflects the sponsor’s time-to-event analysis, while the recalculation compares arm-level proportions from summary data. Differences in estimates, intervals, or p-values are therefore not unexpected. The recalculation does not reproduce the event-time analysis and should not be presented as if it did. Conversely, the rate ratio does not directly state the absolute difference in the proportion of participants with an event.

The registry record does not provide the individual-level data or full analysis plan needed to reconstruct the sponsor’s method independently. The sponsor result is the trial’s reported analysis; the recalculation is a transparent, simpler analysis of the posted summaries. Neither removes the need to consider the endpoint definition, analysis population, and unreported handling of missing data.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary outcome and three secondary outcomes. It does not report whether the trial used a multiplicity adjustment, a testing hierarchy, or another prespecified strategy to control the chance of false-positive findings across outcomes. Without that information, the posted secondary p-values should be read as unadjusted evidence for their individual comparisons, not as results with a documented overall error rate across all tests.

The registry identifies the primary comparison as intention-to-treat among all randomized participants. That is a useful description of the target analysis population, but it does not explain how missing outcome data were handled. The record does not report the amount or pattern of missingness, imputation methods, assumptions about participants lost to follow-up, or sensitivity analyses. These details matter because an analysis may be affected if outcome availability differs between groups or is related to the chance of an event.

The primary outcome is a first event during a randomized treatment phase with median follow-up of 4.1years. The sponsor’s reported log-rank method indicates a time-to-event analysis, but the registry does not report censoring rules, follow-up completeness, or the handling of participants who did not experience an event before follow-up ended. The recalculation from summary counts does not supply those missing details.

Interim analyses and stopping rules are not reported in the registry record. The full statistical analysis plan, including any prespecified subgroup analyses or covariate adjustment, is also not reported. These are unknowns, not evidence that a particular procedure was or was not used. They limit assessment of whether every reported analysis followed a prespecified plan and how the uncertainty should be interpreted across outcomes and analyses.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: surgical and medical procedures (22.8%), cardiac disorders (18.2%), infections and infestations (10.2%), nervous system disorders (9.6%), neoplasms benign, malignant and unspecified (incl cycts and polyps) (8.7%).

The safety record lists serious adverse events for 15,225 participants at risk in the anacetrapib group, with 8,898 affected, and 15,224 at risk in the placebo group, with 8,912 affected. It separately lists other adverse events for 3,048 participants at risk, with 2,493 affected, in the anacetrapib group, and 3,034 at risk, with 2,503 affected, in the placebo group. Deaths are listed as 1,122 and 1,155, respectively. These are registry counts; the record does not provide detailed definitions or additional adjusted comparisons for these figures.

The listed serious-event terms include surgical and medical procedures (22.8%), cardiac disorders (18.2%), infections and infestations (10.2%), nervous system disorders (9.6%), neoplasms benign, malignant and unspecified (incl cycts and polyps) (8.7%), and investigations (7.5%). The record does not specify the denominator or arm attribution for these term percentages, so they should not be interpreted as arm-specific rates.

Counts of participants affected do not by themselves establish whether events were caused by treatment. Interpretation also depends on event definitions, follow-up, and how events were collected, which are not detailed in the registry record. These summaries support descriptive comparison only and do not establish a complete safety profile.

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

The posted primary results show fewer participants with a first major coronary event in the anacetrapib allocation group than in the placebo group, and the sponsor’s rate-ratio analysis and the simple recalculation point in the same direction. The confidence intervals and p-values describe statistical uncertainty under their respective methods. They do not establish the size of benefit for every individual or guarantee the same result in other settings.

The primary outcome combines coronary death, myocardial infarction, and coronary revascularization. The result concerns that composite during the randomized treatment phase; it does not demonstrate that each component changed similarly. Nor does it describe outcomes beyond those reported in the registry. The record’s secondary results provide additional outcome-specific information, but they do not resolve every question about the components or about multiplicity.

A statistically distinguishable estimate is not equivalent to proof of clinical importance. Clinical importance depends on factors beyond a p-value, including the outcome’s meaning, the size and precision of the estimate, the population, and the balance of benefits and harms. The registry record does not provide enough information to make a broad judgment about those considerations, and no treatment recommendation follows from these statistical summaries.

General statistical interpretation also depends on how the analysis assumptions fit the data. Randomized allocation supports a comparison between groups, but missing data, follow-up, adherence, and analysis choices remain relevant. The record does not report enough detail to assess all of these issues. The most defensible reading is therefore bounded: the posted primary comparison favors a lower event measure for the anacetrapib allocation group, with uncertainty represented by the reported intervals, and with important limits on what can be inferred beyond that comparison.

18. Why This Trial Matters Statistically

REVEAL illustrates how one clinical trial can present the same primary question through more than one statistical measure. The sponsor’s time-to-event rate ratio and the recalculated risk difference are both useful, but they describe different aspects of the comparison. Reading them together helps distinguish an event-rate comparison from an absolute difference in the proportion of participants with an event.

The trial also demonstrates why endpoint definitions matter. A first-event composite combines coronary death, myocardial infarction, and coronary revascularization into a single primary outcome. That choice creates a broad summary of major coronary events, while leaving component-specific questions unanswered in the registry record. Statistical interpretation should follow the stated outcome rather than treating the composite as interchangeable with each component.

Another important statistical issue is the distinction between a trial’s reported analysis and a simple recalculation from summary counts. A count-based recalculation can make the direction and basic uncertainty accessible, but it cannot reproduce an analysis that uses event timing. The posted sponsor analysis and the recalculation are best read as complementary descriptions with different assumptions and estimands.

Finally, the record highlights the role of uncertainty beyond a headline p-value. Confidence intervals convey the range of estimates compatible with a method, while missing analysis-plan details and unreported multiplicity procedures limit broader conclusions. The secondary outcomes and planning illustrations should be understood in that context rather than treated as independent confirmation or as evidence of the trial’s original design rationale.

19. 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 unresolved. It does not report eligibility criteria beyond the broad description of established vascular disease, baseline participant characteristics, the randomization sequence, allocation concealment, or the practical procedures used to maintain quadruple masking. Arm descriptions are blank, limiting detail about treatment delivery and background care.

The record lists enrollment of 30,449 participants, while the primary outcome denominators are 15,220 per group. It does not explain the difference between those figures. The adverse-event risk-set counts also differ from the primary outcome denominators. These figures refer to different registry summaries, and the record does not provide an explanation for the differences.

For the primary outcome, the registry identifies an intention-to-treat analysis and the first major coronary event, but does not provide event-time data, censoring details, missing-data methods, follow-up completeness, or the full statistical analysis plan. The sponsor’s log-rank analysis therefore cannot be independently reconstructed from the record. Interim analyses, stopping rules, and the original sample-size justification are not reported.

The registry also does not report a multiplicity strategy for the secondary outcomes or separate primary estimates for the composite components. Safety summaries lack further detail on definitions, attribution, and the denominator for the listed serious-event term percentages. These reporting gaps constrain interpretation; they do not establish that the procedures or information were absent from the trial itself.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: REVEAL: Randomized EValuation of the Effects of Anacetrapib Through Lipid-modification — NCT01252953.
• Registry record last updated 2024-06-25; status last verified 2024-06.
• Results first posted 2018-05-04.
• 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.

23. Record Summary

REVEAL is a Phase 3 randomized, quadruple-masked, parallel-group trial sponsored by the University of Oxford. It compared anacetrapib with placebo among people with established vascular disease whose LDL cholesterol was treated with a statin. The registry lists enrollment of 30,449 participants and a median follow-up period of 4.1years.

The primary outcome was the first major coronary event, defined as coronary death, myocardial infarction, or coronary revascularization. The posted counts were 1,640 among 15,220 participants allocated to anacetrapib and 1,803 among 15,220 allocated to placebo. The sponsor reported a log-rank rate ratio of 0.91, with a 95% confidence interval from 0.85 to 0.97 and p = 0.004. The simple recalculation points in the same direction.

The record also lists three secondary outcomes and adverse-event summaries. Details about multiplicity, missing data, the full analysis plan, and the trial’s original sample-size assumptions are not reported in the registry record.