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Atherosclerotic Cardiovascular Disease Phase 3 Time-to-Event NCT01663402

ODYSSEY OUTCOMES: Complete Statistical Analysis of Alirocumab After Acute Coronary Syndrome

An independent statistical analysis of the randomized, double-blind phase 3 ODYSSEY OUTCOMES trial evaluating cardiovascular outcomes after an acute coronary syndrome during treatment with alirocumab versus placebo.

Trial start: 2012-10  ·  Primary completion: 2018-01-23  ·  Enrollment: 18924
Scope of this record

This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record. Numerical trial results on this page are restricted to the ClinicalTrials.gov record.

1. Trial at a Glance

ODYSSEY OUTCOMES was a randomized, double-blind, parallel-group phase 3 trial in atherosclerotic cardiovascular disease, designed to evaluate cardiovascular outcomes after an acute coronary syndrome during treatment with alirocumab.

18924
Enrollment
Randomized trial
2
Arms
Alirocumab vs placebo
0.85
Primary MACE HR
95% CI 0.78–0.93
0.0003
Primary P-value
Two-sided analysis
FeatureODYSSEY OUTCOMES
Trial nameODYSSEY OUTCOMES
NCT identifierNCT01663402
PhasePhase 3
Therapeutic areaCardiology
ConditionAtherosclerotic Cardiovascular Disease
DesignRandomized, double-blind, parallel-group
Primary purposePrevention
Enrollment18924
Primary endpointTime to first occurrence of major adverse cardiovascular event (MACE)
Primary analysisStratified log-rank test with Cox proportional hazard model
Effect measureHazard ratio
HypothesisSuperiority
ClinicalTrials.govNCT01663402

2. Clinical Question

The central question was whether treatment with alirocumab, compared with placebo, affected the time to major cardiovascular outcomes after an acute coronary syndrome in the trial population with atherosclerotic cardiovascular disease.

Population

Participants enrolled in the phase 3 ODYSSEY OUTCOMES trial for atherosclerotic cardiovascular disease following an acute coronary syndrome.

Intervention

Alirocumab 75 mg Q2W, with escalation up to 150 mg Q2W as represented in the registry analysis.

Comparator

Placebo, with both treatment groups represented in the randomized comparison.

Primary question

Does alirocumab produce a different time-to-event profile for MACE than placebo under a superiority framework?

3. Trial Design

01
Randomize18924 participants
02
Two armsAlirocumab vs placebo
03
Double blindMasked treatment assignment
04
Follow-upTime-to-event outcomes
05
AnalysisStratified survival comparison
Allocation
RANDOMIZED
Design model
PARALLEL
Masking
DOUBLE
Primary purpose
PREVENTION
ARM A

Alirocumab

  • Alirocumab 75 mg Q2W
  • Up to 150 mg Q2W
  • Compared with placebo in the registered statistical analyses
ARM B

Placebo

  • Placebo
  • Comparator for the randomized treatment effect
  • Both groups were analyzed using the registered time-to-event framework

The registry identifies LMT as an intervention in addition to alirocumab and placebo. The ClinicalTrials.gov record does not provide further dosing or treatment details for LMT, so this page does not add them.

4. Endpoints

The registry identifies one primary endpoint and describes it as a time-to-event outcome measured from randomization up to 64 months.

EndpointRegistry definition / time frameAnalysis
Primary MACE endpoint Time to First Occurrence of Major Adverse Cardiovascular Event (MACE); percentage of observed participants with outcome measure events during the study. From randomization up to 64 months. All MACE positively adjudicated by Clinical Events Committee (CEC) in a blinded fashion were used in the analysis of the composite cardiovascular outcome measure comprised of CHD death, non-fatal MI, fatal and non-fatal ischemic stroke, or unstable angina requiring hospitalization. Stratified log-rank test and Cox proportional hazard model
Secondary: any CHD event Time to First Occurrence of Any Coronary Heart Disease Event; percentage of observed participants with outcome measure events during the study. From randomization up to 64 months. Stratified log-rank test and Cox proportional hazard model
Secondary: any major CHD event Time to First Occurrence of Any Major Coronary Heart Disease Event; percentage of observed participants with outcome measure events during the study. From randomization up to 64 months. Stratified log-rank test and Cox proportional hazard model
Secondary: any cardiovascular event Time to First Occurrence of Any Cardiovascular Event; percentage of observed participants with outcome measure events during the study. From randomization up to 64 months. Stratified log-rank test and Cox proportional hazard model
Secondary: composite of mortality, MI, and ischemic stroke Time to First Occurrence of All-Cause Mortality, Non-Fatal Myocardial Infarction, Non-Fatal Ischemic Stroke; percentage of observed participants with outcome measure events during the study. From randomization up to 64 months. Stratified log-rank test and Cox proportional hazard model
Secondary: CHD death Time to Coronary Heart Disease Death; percentage of observed participants with outcome measure events during the study. From randomization up to 64 months. Stratified log-rank test and Cox proportional hazard model

5. Statistical Methodology

Intention-to-treat analysis

The primary analysis population was the intent-to-treat (ITT) population, defined in the registry analysis as including all randomized participants. This is important because the treatment comparison remains anchored to the randomized assignment rather than being restricted to participants who remained on treatment.

Time-to-event analysis

The primary endpoint is a time-to-event outcome. Instead of simply counting whether a participant experienced MACE, the analysis considers when the first qualifying event occurred. Participants who remain event-free through their available follow-up contribute information up to their censoring time.

Core survival-analysis quantities
Survival function: S(t) = P(T > t)

The Kaplan-Meier framework estimates the probability of remaining event-free over time. The registry's analysis description specifically identifies Kaplan-Meier plots for the cumulative incidence rate, while the formal treatment comparison uses a log-rank test and Cox proportional hazard model.

Stratified log-rank test

The treatment groups were compared with a log-rank test stratified on geographical region: North America, South America, Western Europe, Eastern Europe, Asia, and the rest of the world.

Stratification is useful when a factor is expected to affect the event process and was incorporated into the analysis framework. Rather than treating all participants as belonging to a single homogeneous risk set, the stratified procedure preserves the geographic-region structure specified by the analysis.

Cox proportional-hazards model

The registry states that the analysis was performed using a Cox proportional hazard model together with the stratified log-rank test. The Cox model supplies the hazard-ratio estimate and its confidence interval while accounting for the specified geographical-region stratification.

Hazard-ratio interpretation
HR = instantaneous event rate in treatment group ÷ instantaneous event rate in comparator group

An HR below 1 indicates a lower estimated instantaneous event rate in the alirocumab group relative to placebo under the fitted model. It is not the same quantity as an absolute risk difference, a relative risk, or the percentage of participants who avoid an event.

Superiority testing

The registered hypothesis type was superiority. The primary analysis therefore asks whether the time-to-event distributions differ in a direction consistent with a treatment effect, rather than testing whether alirocumab is merely no worse than placebo by a prespecified non-inferiority margin.

Geographical stratification

The analysis notes specify six geographic strata: North America, South America, Western Europe, Eastern Europe, Asia, and the rest of the world. The same stratification appears in the analysis notes for the primary and secondary time-to-event endpoints.

6. Primary Result: Major Adverse Cardiovascular Events

The primary endpoint was time to first occurrence of MACE from randomization up to 64 months. The ITT population included all randomized participants, and the comparison was between placebo and alirocumab 75 mg Q2W/up to 150 mg Q2W.

Primary hazard ratio for MACE

0.85

95% CI: 0.78–0.93   ·   P = 0.0003

Two-sided confidence interval  ·  Superiority hypothesis

Primary analysis componentRegistered result
EndpointTime to First Occurrence of Major Adverse Cardiovascular Event (MACE)
Time frameFrom randomization up to 64 months
Analysis populationIntent-to-treat (ITT) population included all randomized participants
Groups comparedPlacebo vs Alirocumab 75 mg Q2W/Up to 150 mg Q2W
MethodLog Rank; Cox proportional hazard model
StratificationGeographical region
Effect measureHazard Ratio (HR)
Estimate0.85
95% CI0.78–0.93
P-value0.0003
HypothesisSuperiority
Clinical Biostats interpretation

An HR of 0.85 means that, under the fitted Cox model and over the analyzed follow-up, the estimated instantaneous rate of a first MACE was 15% lower in the alirocumab group relative to placebo. The calculation is simply 1 − 0.85 = 0.15, or 15%, and describes a relative hazard, not an absolute reduction in the probability of MACE.

The HR does not mean that exactly 15% fewer participants experienced MACE, that every participant had a 15% reduction in risk, or that 15% of participants were protected from an event. Those interpretations would require absolute event probabilities or other measures not reported in the statistical analysis.

The 95% CI of 0.78–0.93 describes the statistical uncertainty around the estimated hazard ratio under the model and analysis framework. It does not describe the range of effects experienced by individual participants.

The P = 0.0003 quantifies evidence against the null hypothesis under the specified testing framework. It does not measure the magnitude of the treatment effect. A small p-value and an effect-size estimate answer different questions and should be interpreted together.

Because the effect measure comes from a Cox proportional-hazards model, interpretation of one summary HR also depends on the model's proportional-hazards framework. A single HR is a relative summary of the event process; it is not an absolute risk curve.

7. Secondary Time-to-Event Results

The registry contains formal statistical analyses for five secondary time-to-event endpoints. Each was analyzed in the ITT population using the same broad survival-analysis framework, with geographical-region stratification.

Secondary endpointHR95% CIP-valueHypothesis
Time to First Occurrence of Any Coronary Heart Disease Event 0.88 0.81–0.95 0.0013 Superiority
Time to First Occurrence of Any Major Coronary Heart Disease Event 0.88 0.80–0.96 0.0060 Superiority
Time to First Occurrence of Any Cardiovascular Event 0.87 0.81–0.94 0.0003 Superiority
Time to First Occurrence of All-Cause Mortality, Non-Fatal MI, Non-Fatal Ischemic Stroke 0.86 0.79–0.93 0.0003 Superiority
Time to Coronary Heart Disease Death 0.92 0.76–1.11 0.3824 Superiority

Any coronary heart disease event

Hazard ratio

0.88

95% CI: 0.81–0.95   ·   P = 0.0013

Clinical Biostats interpretation

An HR of 0.88 corresponds to a 12% lower estimated instantaneous event rate for the alirocumab group relative to placebo under the fitted model. The 95% CI of 0.81–0.95 expresses uncertainty around that relative hazard estimate.

The registry states that hierarchical testing was used to control the overall type-I error at a 0.0249 one-sided alpha level (0.0498 two-sided), with testing performed sequentially in the order endpoints were reported. Thus, the p-value should not be interpreted as though every secondary endpoint were an unrelated hypothesis test with its own unrestricted type-I error budget.

Any major coronary heart disease event

Hazard ratio

0.88

95% CI: 0.80–0.96   ·   P = 0.0060

Clinical Biostats interpretation

The estimated HR of 0.88 indicates a 12% lower estimated instantaneous event rate for the alirocumab group relative to placebo. The confidence interval of 0.80–0.96 describes the uncertainty surrounding that estimate under the specified analysis.

The registry explicitly states that testing continued according to the hierarchical procedure only if the previous endpoint was statistically significant. This sequencing is a multiplicity-control feature: the interpretation of later p-values depends on the prespecified testing hierarchy rather than on viewing each p-value in isolation.

Any cardiovascular event

Hazard ratio

0.87

95% CI: 0.81–0.94   ·   P = 0.0003

Clinical Biostats interpretation

The HR of 0.87 corresponds to a 13% lower estimated instantaneous event rate in the alirocumab group relative to placebo. The 95% CI of 0.81–0.94 indicates the statistical precision of this relative estimate.

Again, the hazard ratio is not an absolute risk reduction. Without absolute event probabilities for the two groups, the HR alone cannot tell a reader how many additional participants avoided an event.

All-cause mortality, non-fatal MI, and non-fatal ischemic stroke

Hazard ratio

0.86

95% CI: 0.79–0.93   ·   P = 0.0003

Clinical Biostats interpretation

The estimated HR of 0.86 represents a 14% lower estimated instantaneous rate of the composite event under the fitted model. The 95% CI of 0.79–0.93 quantifies uncertainty around the relative effect.

Because this is a composite endpoint, its interpretation applies to the first occurrence of any component included in the registry definition. The hazard ratio does not establish that every individual component has the same magnitude of treatment effect.

Coronary heart disease death

Hazard ratio

0.92

95% CI: 0.76–1.11   ·   P = 0.3824

Clinical Biostats interpretation

The estimated HR of 0.92 corresponds to an 8% lower estimated instantaneous rate of coronary heart disease death in the alirocumab group relative to placebo under the fitted model. The confidence interval, 0.76–1.11, is relatively broad and includes 1.

The P = 0.3824 does not provide evidence against the null hypothesis under the specified testing framework. Importantly, this p-value does not prove that the treatment groups are identical. The appropriate interpretation is that the observed data do not provide sufficient statistical evidence for a difference under this analysis.

The confidence interval is particularly important here because it shows that the estimated effect is uncertain enough to include both a potentially lower and a potentially higher hazard relative to the comparator.

8. Multiplicity and Hierarchical Testing

Multiplicity is a central statistical feature of the ODYSSEY OUTCOMES registry analyses. Multiple endpoints were analyzed sequentially, so the probability of obtaining at least one apparently positive result cannot be interpreted correctly by simply comparing every p-value with 0.05 independently.

FeatureRegistry-supported detail
Primary endpointTime to first occurrence of MACE
Testing frameworkHierarchical testing
One-sided alpha0.0249
Two-sided alpha0.0498
SequenceTesting performed sequentially in the order endpoints were reported
Continuation ruleFor specified secondary analyses, testing continued only if the previous endpoint was statistically significant
Why hierarchy changes interpretation
Familywise interpretation ≠ independent interpretation of each P-value

A hierarchical procedure creates a prespecified path through the hypotheses. Evidence for a later endpoint is evaluated in the context of the results that came before it. This helps control the overall type-I error while allowing a sequence of clinically related questions to be tested.

The registry also reports that the primary and secondary analyses were based on two-sided confidence intervals, while the hierarchical testing framework used a one-sided alpha level of 0.0249, corresponding to 0.0498 two-sided. These are different pieces of the statistical framework and should not be conflated.

9. Statistical Methods Explained

Why was a log-rank test used?

The primary and secondary outcomes are time-to-event endpoints. A log-rank test is designed to compare event-time distributions between randomized groups while accounting for the fact that participants can have different lengths of observed follow-up. The registry specifically identifies a stratified log-rank test as the analysis method.

What does an HR of 0.85 mean?

An HR of 0.85 means that the estimated instantaneous rate of the first MACE was 15% lower in the alirocumab group relative to placebo under the fitted Cox model. It does not mean that the probability of MACE was exactly 15% lower or that every participant received the same proportional reduction.

Why use both a log-rank test and a Cox model?

The two methods play related but different roles. The log-rank test provides a formal comparison of the time-to-event distributions, while the Cox proportional-hazards model provides a quantitative hazard-ratio estimate and confidence interval. The registry reports both methods for the primary analysis.

Why was the analysis stratified by geographical region?

The registry analysis specifies geographical region as the stratification factor: North America, South America, Western Europe, Eastern Europe, Asia, and the rest of the world. Stratification allows the survival comparison to account for differences across these predefined regional strata rather than assuming that all regions share one unstructured risk set.

Why does the confidence interval matter?

The point estimate alone does not communicate how precisely the treatment effect was estimated. For the primary HR of 0.85, the 95% CI is 0.78–0.93. This interval provides a range of values representing statistical uncertainty around the estimated hazard ratio under the specified model and sampling framework.

Why is multiplicity important here?

ODYSSEY OUTCOMES includes one primary endpoint followed by multiple secondary time-to-event endpoints. The registry reports hierarchical testing with a one-sided alpha of 0.0249 and continued sequential testing only when the previous endpoint was statistically significant. Consequently, each secondary p-value should be read within that prespecified sequence rather than treated as an isolated test.

What does ITT add to the analysis?

The ITT population included all randomized participants. An ITT analysis preserves the treatment assignment created by randomization and therefore maintains the randomized comparison as the central basis for efficacy inference. It is distinct from an analysis that selects participants based on treatment exposure or adherence.

10. Safety Results

The ClinicalTrials.gov record reports serious adverse events by randomized treatment group. These data should be considered separately from the time-to-event efficacy analyses because they describe safety rather than the primary cardiovascular outcome.

Safety measurePlaceboAlirocumab
Serious adverse events2350 / 94432202 / 9451
Serious adverse events by reported analysis denominator
Placebo
2350/9443
Alirocumab
2202/9451

The registry reports the serious-adverse-event counts and denominators as 2350/9443 for placebo and 2202/9451 for alirocumab. This page does not convert these fractions into newly calculated percentages because the ClinicalTrials.gov record specifies that numbers should be reported exactly as given.

11. Primary Endpoint: Understanding the Composite

The primary endpoint is a composite rather than a single clinical event. The registry defines MACE using all positively adjudicated events identified by the blinded Clinical Events Committee and describes the composite as consisting of coronary heart disease death, non-fatal myocardial infarction, fatal and non-fatal ischemic stroke, or unstable angina requiring hospitalization.

Why composites are efficient

A composite can capture several clinically relevant event types in a single time-to-first-event endpoint, increasing the number of events available for analysis compared with relying on one component alone.

What the HR summarizes

The primary HR describes the relative hazard of the first qualifying composite event. It does not imply that each component of MACE has an identical hazard ratio.

CEC adjudication

The registry states that MACE events were positively adjudicated by a Clinical Events Committee in a blinded fashion before being used in the analysis.

Time-to-first event

The endpoint is based on the first occurrence of MACE. This is different from counting every cardiovascular event that a participant may experience over follow-up.

12. Why Absolute and Relative Effects Should Be Distinguished

The primary result is reported as a hazard ratio, which is a relative measure. Relative measures are useful for comparing treatment groups, but they do not directly state the absolute probability that a participant experiences an event.

Relative effect

The primary HR of 0.85 represents a 15% lower estimated instantaneous hazard in the alirocumab group relative to placebo under the Cox model.

Absolute effect

An absolute risk difference would require event probabilities or cumulative incidence estimates for the two treatment groups at a specified time point. Those numerical group-specific probabilities are not included in the statistical analyses posted on ClinicalTrials.gov, so they are not added here.

This distinction is fundamental in clinical-trial interpretation. A hazard ratio can remain the same across populations with very different baseline risks, while the corresponding absolute difference in event probability can differ substantially. The HR therefore should not be interpreted as a substitute for an absolute risk measure.

13. What the P-values Do — and Do Not — Mean

The primary analysis reports P = 0.0003, while the secondary analyses report p-values ranging from 0.0003 to 0.3824. These values quantify evidence against the relevant null hypothesis within the specified statistical framework.

P-value is not effect size

A p-value does not tell the reader how large the treatment effect is. The HR and its confidence interval provide the effect-size information.

P-value is not probability of the null

A p-value is not the probability that there is no treatment effect. It is calculated under a null-hypothesis framework.

Sequence matters

For the secondary endpoints, the registry specifies hierarchical testing. Therefore, the interpretation of later tests depends on the prespecified sequence.

Confidence intervals add information

The confidence interval communicates the precision and plausible statistical range around the estimated hazard ratio in a way a p-value alone cannot.

14. Longitudinal Trial History

2012-10 · Trial start

Phase 3 randomized study begins

The trial begins as a randomized, double-blind, parallel-group phase 3 study in atherosclerotic cardiovascular disease.

2018-01-23 · Primary completion

Primary study completion

The registry lists 2018-01-23 as the primary completion date.

Registry record · Results posted

Formal statistical results available

The registry record reports results, including one primary- endpoint analysis and five secondary time-to-event analyses.

The ClinicalTrials.gov record does not provide publication-specific data-cutoff dates, interim efficacy dates, median follow-up, Kaplan-Meier survival probabilities at selected time points, or later follow-up estimates. Those details are therefore not added to this analysis.

15. Important Limitations and Interpretation Issues

16. Why This Trial Matters Statistically

ODYSSEY OUTCOMES is a useful teaching example because it brings together several core concepts in randomized time-to-event analysis: ITT analysis, blinded endpoint adjudication, composite endpoints, Kaplan-Meier estimation, stratified log-rank testing, Cox proportional-hazards modeling, hazard ratios, confidence intervals, superiority testing, and hierarchical multiplicity control.

ConceptHow it appears in ODYSSEY OUTCOMES
Randomization18924 participants enrolled in a randomized phase 3 parallel-group trial
Double blindingThe registered design is DOUBLE masked
ITT analysisThe primary analysis population included all randomized participants
Time-to-event analysisThe primary and reported secondary endpoints measure time to first occurrence of clinical events
Kaplan-Meier estimationThe primary endpoint description specifies Kaplan-Meier plots of the cumulative incidence rate by treatment groups were used to depict the first occurrence of MACE over time. Percentage of observed participants with outcome measure events during the study were reported.
Log-rank testingPrimary and secondary analyses used a log-rank test
Stratified analysisAnalyses were stratified by geographical region
Cox modelCox proportional hazard models registry-reported the hazard-ratio framework
Hazard ratioPrimary HR 0.85 with 95% CI 0.78–0.93
Confidence intervalTwo-sided 95% confidence intervals accompany the reported HR estimates
Superiority testingThe registered hypothesis type is superiority
MultiplicitySecondary endpoints were evaluated using a hierarchical testing procedure
One-sided testingThe hierarchical procedure used a 0.0249 one-sided alpha level
Composite endpointMACE combines several adjudicated cardiovascular event types
Safety analysisSerious adverse events are reported separately by treatment arm

17. Statistical Concepts in This Trial

Learn more about the methods used in this trial:

18. Related Statistical Calculators

19. Sources

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Connect this trial's endpoints and methods to deeper statistical tutorials and practical analysis tools.

20. Record Summary

ODYSSEY OUTCOMES provides a clear example of how a large randomized cardiovascular trial can be analyzed through a time-to-event framework. The primary MACE endpoint was evaluated in the ITT population using a geographically stratified log-rank test and Cox proportional-hazards model. The reported primary HR was 0.85, with a two-sided 95% CI of 0.78–0.93 and P = 0.0003. Five secondary time-to-event analyses were also reported, with hazard ratios ranging from 0.86 to 0.92.

The statistical interpretation depends on more than the point estimate. The hazard ratio describes a relative event-rate measure, the confidence interval describes uncertainty around that estimate, the p-value addresses evidence under the specified hypothesis-testing framework, and the hierarchical testing procedure determines how multiple endpoint results should be interpreted together. The trial therefore illustrates why treatment-effect interpretation requires the effect measure, uncertainty interval, analysis population, survival-analysis method, stratification, and multiplicity framework to be considered as a single statistical story.

Clinical Biostats methodology: This page distinguishes reported registry results from statistical interpretation. Trial numbers are reproduced from the registry-reported ODYSSEY OUTCOMES registry data without rounding, recomputation, or substitution from outside trial reports.