This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record.
1. Trial at a Glance
PALISADE is a randomized, parallel, quadruple-masked phase 3 trial studying factor XI inhibition in adult participants with peripheral artery disease. The registry describes 7050 participants, two arms, and two primary time-to-event endpoints involving thrombotic vascular events and bleeding.
| Feature | PALISADE |
|---|---|
| Acronym | PALISADE |
| ClinicalTrials.gov identifier | NCT07318610 |
| Phase | Phase 3 |
| Status | Recruiting |
| Condition | Peripheral Artery Disease (PAD) |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | Quadruple |
| Primary purpose | Treatment |
| Enrollment | 7050 |
| Number of arms | 2 |
| Lead sponsor | Regeneron Pharmaceuticals |
| Sponsor type | Industry |
| Start date | 2026-07-10 |
| Primary completion date | 2029-08-18 |
2. Clinical Question
The central statistical question is whether a randomized factor XI inhibition strategy in adults with peripheral artery disease changes the time until major thrombotic vascular events, while also characterizing the time until ISTH major or clinically relevant non-major bleeding.
Population
Adult participants with peripheral artery disease.
Intervention
The registry lists REGN7508 and REGN9933 as drug interventions within the study of factor XI inhibition.
Comparator
The registry lists placebo and rivaroxaban among the study drug interventions.
Primary question
How does randomized treatment assignment affect the time-to-first occurrence of major thrombotic vascular events and bleeding?
3. Trial Design
Factor XI inhibition program
- REGN7508
- REGN9933
Comparator / reference interventions
- Placebo
- Rivaroxaban
The registry identifies the trial as randomized, parallel, and quadruple-masked. Those design features are particularly important for interpretation of time-to-event outcomes because randomization establishes the principal comparison while masking can reduce the influence of treatment knowledge on participant care, outcome assessment, and other aspects of trial conduct.
4. Trial Timeline
Trial start
The registry lists 2026-07-10 as the study start date.
Primary completion
The registry lists 2029-08-18 as the primary completion date.
5. Primary Endpoints
| Endpoint | Registry definition | Time frame | Cohort |
|---|---|---|---|
| Major thrombotic vascular event | Time-to-first occurrence of a major thrombotic vascular event, consisting of Acute Limb Ischemia (ALI), major amputation (above the ankle) of vascular etiology, Myocardial Infarction (MI), ischemic stroke, or Cardiovascular (CV) death | Approximately up to 42 months | Cohort 1 |
| ISTH major or CRNM bleeding | Time-to-first occurrence of International Society of Thrombosis and Hemostasis (ISTH) major or Clinically Relevant Non-major (CRNM) bleeding | Approximately up to 42 months | Cohort 1 and 2 |
Why these are time-to-event endpoints
Both primary endpoints are defined by the time until a first qualifying event occurs. This differs from a simple proportion measured at one fixed visit. Participants can therefore contribute different amounts of follow-up, and participants who have not experienced the endpoint by the end of their available follow-up can be treated as censored in a conventional time-to-event analysis.
The first endpoint is a composite. It combines acute limb ischemia, major amputation above the ankle of vascular etiology, myocardial infarction, ischemic stroke, and cardiovascular death into a single first-event outcome. Statistically, that creates a broad measure of major thrombotic vascular morbidity and mortality, but it also means that the composite effect is a weighted consequence of the individual component event patterns.
6. Statistical Methodology
The registry identifies both primary endpoints as time-to-first-event outcomes. For this type of endpoint, a conventional analysis would generally use survival-analysis methods rather than a simple comparison of event proportions.
Kaplan-Meier estimation
A Kaplan-Meier analysis would estimate the probability of remaining free of the first qualifying event over time. It naturally accommodates right censoring, allowing participants who have not yet experienced the event to contribute information through their last known event-free follow-up.
Here, di represents the number of events at an event time and ni represents the number at risk immediately before that time.
Hazard ratio
A Cox proportional-hazards model would commonly be used to estimate the relative instantaneous event rate between randomized treatment groups. A hazard ratio below 1 would indicate a lower estimated instantaneous event rate in the treatment group relative to the comparator under the fitted model.
The hazard ratio is not the same as a relative risk, an absolute risk difference, or the percentage of participants who avoid the event.
Log-rank comparison
A log-rank test would commonly provide a formal comparison of the time-to-event distributions between randomized groups. Unlike a comparison at a single time point, it uses event and risk-set information across the follow-up period.
Composite endpoint analysis
The major thrombotic vascular event endpoint combines several clinically distinct events. A time-to-first composite analysis treats the first qualifying component as the endpoint event. Consequently, the overall composite estimate should be interpreted alongside the individual component event patterns when those component results become available.
Bleeding endpoint analysis
The bleeding endpoint is likewise defined as time to the first occurrence of either ISTH major or clinically relevant non-major bleeding. A standard time-to-first-event framework can estimate the distribution of time free from the combined bleeding endpoint and compare those distributions between randomized groups.
7. Planned Analysis
Primary endpoint 1
Time-to-first occurrence of ALI, major amputation above the ankle of vascular etiology, MI, ischemic stroke, or CV death.
Time frame: approximately up to 42 months; Cohort 1.
For a time-to-first-event endpoint of this type, the typical analysis would use Kaplan-Meier estimation to describe event-free survival, a log-rank comparison to compare randomized groups, and a Cox proportional-hazards model to estimate a hazard ratio with a confidence interval. The composite should also be interpreted in terms of its individual components when those data are available.
Primary endpoint 2
Time-to-first occurrence of International Society of Thrombosis and Hemostasis major or Clinically Relevant Non-major bleeding.
Time frame: approximately up to 42 months; Cohort 1 and 2.
For this endpoint, the typical analysis would similarly use time-to-event methods such as Kaplan-Meier estimation, a log-rank comparison, and a Cox proportional-hazards model. The analysis would distinguish the time until the first qualifying bleeding event from the total number of bleeding episodes.
8. Statistical Methods Explained
Why is a time-to-first-event analysis appropriate?
The primary endpoints are explicitly defined by the time until a participant first experiences a qualifying event. Participants may have different lengths of observable follow-up, making a time-to-event framework more informative than simply classifying everyone as having or not having an event at a single calendar date.
What does a hazard ratio measure?
A hazard ratio compares estimated instantaneous event rates between treatment groups within a time-to-event model. For example, an HR of 0.70 would be interpreted as an estimated instantaneous event rate 30% lower in one group under the model. It would not mean that exactly 30% fewer participants experience the event, nor that each participant has the same reduction in risk.
Why use Kaplan-Meier curves?
Kaplan-Meier estimation provides an estimate of the probability of remaining free of the endpoint as follow-up progresses. It is useful when participants enter an analysis with different amounts of observable follow-up or when some participants have not experienced the endpoint by the time their follow-up ends.
Why does the composite thrombotic endpoint require careful interpretation?
The major thrombotic vascular endpoint combines ALI, major amputation above the ankle of vascular etiology, MI, ischemic stroke, and CV death. These events differ in clinical manifestation and frequency. A statistically meaningful composite result therefore describes the combined endpoint; it should not automatically be interpreted as evidence that every individual component changes to the same extent.
Why is the bleeding endpoint also time-to-first-event?
The registry defines the endpoint as the time to the first occurrence of ISTH major or CRNM bleeding. A participant with a first qualifying bleeding event therefore reaches the endpoint at that first event. Recurrent bleeding episodes would represent a different estimand and would require a recurrent-event analysis rather than a simple time-to-first-event analysis.
What does censoring mean in these analyses?
Censoring occurs when a participant's event status is no longer observed beyond a particular time without the qualifying endpoint having occurred. In a conventional survival analysis, that participant contributes information up to the censoring time. The validity of the resulting estimate depends on assumptions about the relationship between censoring and the event process.
9. Interpreting the Two Primary Endpoints Together
PALISADE has two primary endpoints that represent different clinical dimensions of treatment effect: thrombotic vascular outcomes and bleeding. This creates an important statistical distinction between efficacy and safety outcomes.
Thrombotic endpoint
The first primary endpoint combines acute limb ischemia, major amputation above the ankle of vascular etiology, myocardial infarction, ischemic stroke, and cardiovascular death.
Bleeding endpoint
The second primary endpoint captures the first occurrence of ISTH major or clinically relevant non-major bleeding.
Different estimands
A treatment effect on thrombotic events and a treatment effect on bleeding answer different questions and should not be collapsed into one generic measure of treatment benefit.
Time-to-event interpretation
Both endpoints concern when the first event occurs, not simply whether an event occurred at any point without regard to follow-up time.
For a treatment that changes both thrombotic and bleeding outcomes, interpretation ultimately requires consideration of the two endpoint distributions together. Statistical evidence for one endpoint does not mathematically determine the result for the other.
10. Composite Endpoint: Statistical Considerations
The first primary endpoint is a composite of five event types: acute limb ischemia, major amputation above the ankle of vascular etiology, myocardial infarction, ischemic stroke, and cardiovascular death.
| Component | Role in the primary endpoint |
|---|---|
| Acute Limb Ischemia (ALI) | Qualifying component of the major thrombotic vascular event endpoint |
| Major amputation above the ankle of vascular etiology | Qualifying component of the major thrombotic vascular event endpoint |
| Myocardial Infarction (MI) | Qualifying component of the major thrombotic vascular event endpoint |
| Ischemic stroke | Qualifying component of the major thrombotic vascular event endpoint |
| Cardiovascular death | Qualifying component of the major thrombotic vascular event endpoint |
A composite endpoint can increase the number of observed events and therefore provide more information for a time-to-event comparison. However, the interpretation depends on the clinical and statistical contribution of its components. If one component occurs much more frequently than the others, the overall composite estimate can be driven largely by that component.
The endpoint is also defined as time-to-first occurrence. Once a participant experiences one qualifying component, later qualifying events do not create additional first-event observations for that participant in this primary analysis.
11. Bleeding Endpoint: Statistical Considerations
The second primary endpoint combines two bleeding categories: ISTH major bleeding and clinically relevant non-major bleeding. The endpoint is again defined by the time to the first occurrence.
The statistical target is the distribution of time until the first qualifying event, rather than the total number of bleeding episodes experienced during follow-up.
The combined endpoint broadens the number of events that qualify as an endpoint event. Its interpretation should nevertheless retain the distinction between ISTH major bleeding and clinically relevant non-major bleeding because those categories represent different levels of bleeding severity.
12. Analysis Population and Randomization
The registry identifies the trial as randomized. In a conventional primary efficacy analysis, participants would ordinarily be analyzed according to their randomized treatment assignment, preserving the principal benefit of randomization for comparison of the time-to-event outcomes.
The distinction between randomized efficacy analysis and exposure-based safety analysis is especially important in clinical trials. The ClinicalTrials.gov record does not specify separate analysis-population definitions, so those details should not be assumed.
13. Censoring and Follow-Up
The primary endpoint time frame is approximately up to 42 months. In a survival analysis, not every participant necessarily contributes the same amount of event-free follow-up. Participants may experience an endpoint before the end of the observation period, while others may remain event-free through their last assessment.
Observed event
A participant who experiences the qualifying endpoint contributes an event time corresponding to the first qualifying event.
Censored observation
A participant without a qualifying event through the end of available follow-up contributes information through the time at which observation ends.
Why this matters
Ignoring different follow-up durations can distort a simple event-rate comparison when participants are observed for different lengths of time.
Model assumptions
Time-to-event estimates rely on assumptions concerning censoring and, for Cox models, the relationship between hazards over time.
14. Hazard Ratios and Proportional Hazards
A Cox proportional-hazards model is a standard approach for estimating a hazard ratio in randomized time-to-event trials. The model compares the instantaneous event rates between treatment groups while using information from the entire observed follow-up period.
A hazard ratio below 1 indicates a lower estimated instantaneous event rate in the treatment group relative to the comparator under the fitted model. A hazard ratio of 1 indicates equal estimated hazards, while a value above 1 indicates a higher estimated hazard.
A hazard ratio is not an absolute risk difference, not a difference in median event-free time, and not the percentage of participants who experience or avoid the event. It is a relative time-to-event measure.
The usual Cox interpretation assumes that the relative hazard is adequately represented by a proportional-hazards structure. If the treatment effect changes substantially over time, a single hazard ratio may summarize a complex pattern imperfectly. Kaplan-Meier estimates and clinically meaningful time-specific measures can therefore add important context.
15. Confidence Intervals and P-Values
When the PALISADE results are posted, a treatment-effect estimate should be accompanied by an uncertainty interval and its associated inferential result where applicable. These quantities answer different statistical questions.
| Quantity | What it communicates |
|---|---|
| Hazard ratio | The estimated relative instantaneous event rate under the fitted time-to-event model. |
| Confidence interval | The statistical uncertainty surrounding the estimated treatment effect under the specified inferential framework. |
| P-value | The compatibility of the observed data with a specified null hypothesis under the statistical model and testing procedure. |
| Absolute event-free probability | The estimated probability of remaining free of the endpoint at a specified time. |
A p-value does not measure the magnitude of a treatment effect. A very small p-value can accompany a modest effect when information is abundant, while a clinically important estimate can have substantial uncertainty when relatively few events are observed. The confidence interval is therefore essential for understanding precision.
16. Multiplicity and Two Primary Endpoints
PALISADE has two registered primary endpoints. When a trial has more than one primary endpoint, the interpretation of statistical significance depends on the prespecified testing strategy. If formal hypothesis tests are conducted for multiple primary endpoints, the overall type I error may need to be controlled according to the trial's statistical analysis plan.
| Primary endpoint | Statistical role | Key interpretation issue |
|---|---|---|
| Major thrombotic vascular event | Primary endpoint, Cohort 1 | Composite time-to-first-event outcome |
| ISTH major or CRNM bleeding | Primary endpoint, Cohort 1 and 2 | Combined bleeding time-to-first-event outcome |
The registry information available here does not specify an alpha-allocation or hierarchical testing strategy between these two primary endpoints. Those details should therefore be taken from the protocol or statistical analysis plan when available rather than inferred from the endpoint list alone.
17. Missing Data and Imputation
Time-to-event analyses differ from many cross-sectional analyses because missing outcome measurements do not necessarily require conventional mean or multiple-imputation procedures. A participant's available follow-up can contribute information until an endpoint event or censoring time.
However, loss to follow-up and informative censoring can still affect inference. If participants who become unobservable have systematically different future event risks from those who remain under observation, standard survival estimates may be biased. The appropriate handling of censoring, protocol deviations, and other analysis-population issues should therefore be specified in the statistical analysis plan.
The registry information available here does not specify a particular missing-data or imputation method.
18. Interim Analysis and Design Features
The registry information available here identifies the trial as randomized, parallel, quadruple-masked, and phase 3, with a primary endpoint time frame of approximately up to 42 months. It does not specify an interim-analysis schedule, alpha-spending procedure, stopping boundaries, or a formal group-sequential method.
Interim monitoring
If interim efficacy or safety looks are planned, their timing and statistical boundaries would normally be prespecified to preserve the intended operating characteristics of the trial.
Stopping rules
An interim decision to stop early can affect the interpretation and precision of the eventual treatment-effect estimate and therefore requires prespecified statistical control.
Non-inferiority
No non-inferiority margin is identified in the registry information available here, so a non-inferiority analysis should not be assumed.
Bayesian methods
No Bayesian analysis is identified in the registry information available here, so Bayesian posterior probabilities should not be assumed for the primary endpoints.
19. Limitations
- No posted effect estimates: the current registry record does not provide numerical treatment-effect estimates, confidence intervals, p-values, or event counts for the primary endpoints.
- Composite endpoint: the major thrombotic vascular endpoint combines five distinct clinical outcomes, so an overall treatment effect would not necessarily imply identical effects across all components.
- Time-to-first-event focus: the primary endpoints concern the first qualifying event and therefore do not by themselves describe recurrent events after the first endpoint occurrence.
- Censoring: survival analyses depend on assumptions concerning censoring and the completeness of follow-up.
- Hazard-ratio interpretation: a single Cox hazard ratio summarizes a relative time-to-event effect and depends on the adequacy of the proportional-hazards model.
- Multiplicity: two primary endpoints require a prespecified inferential strategy if formal statistical testing is used for both.
- Unspecified analysis details: the available registry information does not identify the precise analysis population definitions, stratification variables, missing-data procedures, interim-analysis framework, or multiplicity procedure.
- Follow-up duration: the primary endpoints are assessed over approximately up to 42 months, so event-free survival estimates should be interpreted in relation to the available follow-up period.
20. Why This Trial Matters Statistically
PALISADE is a useful teaching case because it combines randomized clinical-trial design with two clinically different time-to-event endpoints. The study also illustrates why endpoint definition is inseparable from statistical interpretation: the thrombotic endpoint is a multi-component composite, while the bleeding endpoint combines two bleeding categories.
| Concept | How it appears in PALISADE |
|---|---|
| Randomization | The trial uses randomized allocation between two parallel arms. |
| Quadruple masking | The registry identifies quadruple masking as a design feature. |
| Time-to-event analysis | Both primary endpoints are defined as time to first occurrence. |
| Composite endpoint | The thrombotic endpoint combines ALI, major amputation, MI, ischemic stroke, and CV death. |
| Bleeding endpoint | The second primary endpoint combines ISTH major and CRNM bleeding. |
| Kaplan-Meier estimation | A standard framework for describing time free from the first qualifying event. |
| Hazard ratio | A conventional relative measure for comparing instantaneous event rates between randomized groups. |
| Censoring | Participants may contribute differing amounts of event-free follow-up. |
| Multiplicity | Two registered primary endpoints require attention to the prespecified testing strategy. |
| Component interpretation | A composite result should be distinguished from the effects on its individual event components. |
21. Sources
- ClinicalTrials.gov: PALISADE (NCT07318610).
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22. Record Summary
PALISADE is a randomized, parallel, quadruple-masked phase 3 trial enrolling 7050 adult participants with peripheral artery disease. Its two registered primary endpoints are both time-to-first-event outcomes: a major thrombotic vascular event composed of acute limb ischemia, major amputation above the ankle of vascular etiology, myocardial infarction, ischemic stroke, or cardiovascular death; and ISTH major or clinically relevant non-major bleeding. Both are assessed over approximately up to 42 months.
Statistically, the trial provides a clear framework for teaching randomized time-to-event analysis. Kaplan-Meier methods can describe event-free survival, log-rank methods can compare treatment groups, and Cox models can express relative treatment effects through hazard ratios. At the same time, the composite nature of the thrombotic endpoint, the combined bleeding definition, censoring, proportional-hazards assumptions, and multiplicity across two primary endpoints all matter when interpreting the eventual results.