This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record. View NCT00440193 on ClinicalTrials.gov.
1. Trial at a Glance
EINSTEIN-DVT was a randomized, parallel, open-label phase 3 trial evaluating rivaroxaban against enoxaparin followed by vitamin K antagonist therapy in participants with venous thrombosis. The registered primary endpoint was symptomatic recurrent venous thromboembolism through the intended end of study treatment, with the formal primary analysis using a Cox proportional-hazards model.
| Feature | EINSTEIN-DVT |
|---|---|
| Trial name | EINSTEIN-DVT |
| Phase | Phase 3 |
| Condition | Venous Thrombosis |
| Enrollment | 3449 |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | None |
| Primary purpose | Treatment |
| Interventions | Rivaroxaban (Xarelto, BAY59-7939) vs Enoxaparin followed by VKA |
| Primary endpoint type | Binary in the registry endpoint classification; formal posted analysis used time-to-event methodology |
| Primary analysis | Cox proportional-hazards model; hazard ratio |
| Trial status | Completed |
| Lead sponsor | Bayer |
2. Clinical Question
The central statistical question was whether rivaroxaban was at least as effective as enoxaparin followed by VKA for preventing symptomatic recurrent venous thromboembolism during the intended study-treatment period.
Population
Participants in a phase 3 randomized trial for venous thrombosis. The registered primary endpoint concerns acute symptomatic deep vein thrombosis and recurrent venous thromboembolism.
Intervention
Rivaroxaban (Xarelto, BAY59-7939).
Comparator
Enoxaparin followed by VKA.
Primary question
Is rivaroxaban at least as effective as the comparator for the registered symptomatic recurrent VTE endpoint?
3. Trial Design
Rivaroxaban
- Rivaroxaban (Xarelto, BAY59-7939)
Enoxaparin / VKA
- Enoxaparin followed by VKA
4. Endpoints
| Endpoint role | Registered endpoint | Time frame | Formal posted method |
|---|---|---|---|
| Primary | Percentage of Participants With Symptomatic Recurrent Venous Thromboembolism [VTE] (i.e. the Composite of Recurrent Deep Vein Thrombosis [DVT] or Fatal or Non-fatal Pulmonary Embolism [PE]) Until the Intended End of Study Treatment | 3-, 6- or 12-month study treatment period | Cox proportional-hazards model |
| Secondary | Percentage of Participants With the Composite Variable Comprising Recurrent DVT, Non-fatal PE and All Cause Mortality Until the Intended End of Study Treatment | 3-, 6- or 12-month study treatment period | Cox proportional-hazards model |
| Secondary | Percentage of Participants With an Event for Net Clinical Benefit 1 Until the Intended End of Study Treatment | 3-, 6- or 12-month study treatment period | Cox proportional-hazards model |
| Secondary | Percentage of Participants With Clinically Relevant Bleeding, Treatment-emergent (Time Window: Until 2 Days After Last Dose) | 3-, 6- or 12-month study treatment period | Cox proportional-hazards model |
The primary endpoint was registered as a percentage-based binary outcome, but the posted formal statistical analysis classifies the endpoint as time-to-event and reports a hazard ratio from a Cox regression. This distinction matters: the analysis uses not only whether an event occurred, but also the timing of events and censoring.
5. Statistical Methodology
Primary analysis: Cox proportional-hazards model
The primary endpoint was analyzed using a Cox proportional-hazards model. The reported effect measure was the hazard ratio comparing rivaroxaban with enoxaparin/VKA.
The model relates the instantaneous event hazard to treatment and other modeled covariates. The exponentiated treatment coefficient produces the hazard ratio.
Stratification and covariate adjustment
The posted primary analysis states that the model was stratified by intended treatment duration and adjusted for the presence of active malignancy at baseline. The same stratification and adjustment approach is reported for the posted secondary Cox analyses.
Intention-to-treat analysis
The primary efficacy analysis used the intention-to-treat population. The registry defines this population as all randomized participants with valid informed consent, analyzed according to the treatment assigned at randomization.
Two-sided confidence interval
The primary hazard ratio was reported with a 95% confidence interval using two-sided testing. For the non-inferiority assessment, the upper confidence-limit criterion was compared with a prespecified hazard-ratio margin of 2.0.
The registry states that rivaroxaban would be considered at least as effective as the comparator if the upper limit of the confidence interval was less than 2.0.
Safety population
The clinically relevant bleeding analysis used a valid-for-safety population consisting of randomized participants with valid informed consent who received at least one dose of anticoagulant study treatment after randomization. This differs from the ITT population used for the primary efficacy analysis.
6. Non-Inferiority Trial Design
The primary hypothesis was non-inferiority or equivalence. The registry reports a non-inferiority upper confidence-limit margin for the hazard ratio of 2.0, with a two-sided α of 0.05.
What the margin means
The margin defines how large the upper bound of uncertainty around the treatment-effect estimate could be while still meeting the prespecified non-inferiority criterion.
Why the upper limit matters
For a hazard ratio comparing rivaroxaban with the comparator, an upper 95% confidence limit below 2.0 is the registry's stated criterion for concluding that rivaroxaban is at least as effective.
Why the point estimate is not enough
A point estimate below the margin does not by itself establish non-inferiority. The confidence interval must also be sufficiently narrow that its upper limit remains below the prespecified margin.
Power calculation
The registry states that a total of 88 events was calculated to provide 90% power to prove non-inferiority under the stated assumptions.
7. Results: Primary Endpoint
The primary endpoint was symptomatic recurrent VTE, defined as the composite of recurrent DVT or fatal or non-fatal PE, until the intended end of study treatment. The formal analysis used a Cox proportional-hazards model in the ITT population.
Primary hazard ratio
95% CI: 0.44–1.04 · P < 0.0001
Rivaroxaban vs Enoxaparin/VKA
| Primary analysis element | Reported result |
|---|---|
| Effect measure | Hazard Ratio (HR) |
| Estimate | 0.68 |
| 95% CI | 0.44–1.04 |
| P-value | < 0.0001 |
| Hypothesis | Non-inferiority or equivalence |
| Model | Cox proportional-hazards model |
| Analysis population | Intention-to-treat |
| Stratification | Intended treatment duration |
| Baseline adjustment | Presence of active malignancy |
| Non-inferiority criterion | Upper CI limit less than 2.0 |
What the estimate means: An HR of 0.68 corresponds to an estimated hazard that is 32% lower for rivaroxaban relative to enoxaparin/VKA under the fitted Cox model. This is a relative time-to-event measure, not a statement that 32% of participants avoided an event.
What it does not mean: The hazard ratio is not a risk ratio, an absolute risk reduction, or the probability that an individual participant benefits. It also does not mean that the event hazard was exactly 32% lower at every point in time.
What the confidence interval says: The 95% CI of 0.44–1.04 quantifies statistical uncertainty around the estimated hazard ratio under the model and sampling framework. The interval includes 1.0, so the data are compatible with a treatment effect ranging from a lower hazard to a hazard somewhat above that of the comparator.
Why the p-value is different: The P-value < 0.0001 is a measure of evidence under the specified hypothesis-testing framework; it is not a measure of the magnitude or clinical importance of the hazard ratio. In particular, the non-inferiority conclusion is governed by the prespecified confidence-interval margin rather than simply by asking whether the P-value is below 0.05.
Non-inferiority logic: The upper CI limit of 1.04 is below the prespecified margin of 2.0. Therefore, according to the registry's stated decision rule, the primary result satisfies the reported non-inferiority criterion.
Model caution: Because this is a Cox proportional-hazards analysis, interpretation of a single HR relies on the model's proportional-hazards framework. Censoring and the exact timing of events also contribute to the estimate.
8. Results: Secondary Efficacy Endpoint
Composite of recurrent DVT, non-fatal PE, and all-cause mortality
This secondary endpoint combined recurrent DVT, non-fatal PE, and all-cause mortality until the intended end of study treatment. It was analyzed in the ITT population using a stratified Cox proportional-hazards model adjusted for active malignancy at baseline. The posted hypothesis type was superiority.
Secondary hazard ratio
95% CI: 0.53–0.99 · P = 0.044
Rivaroxaban vs Enoxaparin/VKA
What the estimate means: An HR of 0.72 represents an estimated 28% lower instantaneous hazard for the composite endpoint in the rivaroxaban group relative to the comparator under the fitted model.
What it does not mean: It does not mean that 28% of participants avoided recurrent DVT, PE, or death. The estimate summarizes a relative time-to-event comparison for a composite endpoint.
Precision: The 95% CI of 0.53–0.99 lies below 1.0 at its upper boundary. The interval therefore indicates uncertainty around the point estimate while remaining on the lower-hazard side of 1.0.
P-value: The P-value of 0.044 is evidence against the corresponding null hypothesis under the posted superiority analysis. It does not quantify the size of the treatment effect and should not be interpreted as a 4.4% probability that the null hypothesis is true.
Multiplicity caution: This was a secondary endpoint, and the ClinicalTrials.gov record does not provide a broader multiplicity-adjustment framework for interpreting all posted secondary analyses together. The result should therefore be distinguished from the primary non-inferiority analysis.
9. Results: Net Clinical Benefit
The posted secondary analysis evaluated the percentage of participants with an event for Net Clinical Benefit 1 until the intended end of study treatment. The endpoint was analyzed using the ITT population and a Cox proportional-hazards model.
Net clinical benefit hazard ratio
95% CI: 0.47–0.95 · P = 0.027
Rivaroxaban vs Enoxaparin/VKA
What the estimate means: The HR of 0.67 corresponds to an estimated 33% lower instantaneous hazard for the reported Net Clinical Benefit 1 endpoint in the rivaroxaban group under the Cox model.
What it does not mean: The estimate does not imply that one third of participants experienced a benefit, nor does it provide an absolute clinical benefit without the underlying event probabilities.
Precision: The 95% CI of 0.47–0.95 indicates uncertainty around the estimated relative hazard while remaining below 1.0 at the upper confidence limit.
P-value: The P-value of 0.027 describes evidence under the posted superiority testing framework; it is not a measure of effect magnitude.
Interpretive caution: Because this is a secondary endpoint, its statistical interpretation should remain separate from the prespecified primary non-inferiority question.
10. Results: Clinically Relevant Bleeding
Clinically relevant bleeding, treatment-emergent through 2 days after the last dose, was analyzed as a secondary time-to-event endpoint in the valid-for-safety population.
Clinically relevant bleeding hazard ratio
95% CI: 0.76–1.22 · P = 0.77
Rivaroxaban vs Enoxaparin/VKA
What the estimate means: An HR of 0.97 is close to 1.0, corresponding to an estimated hazard approximately 3% lower in the rivaroxaban group under the fitted model.
What it does not mean: It does not establish that the two groups have identical bleeding risk. The confidence interval allows for a range of relative hazards on either side of 1.0.
Precision: The 95% CI of 0.76–1.22 spans 1.0 and is therefore compatible with both a lower and a higher hazard for clinically relevant bleeding in the rivaroxaban group.
P-value: A P-value of 0.77 does not measure how similar the groups are. It indicates that the posted superiority analysis did not provide evidence against its null hypothesis at conventional significance levels.
Population caution: This endpoint used a valid-for-safety population rather than the ITT efficacy population, so the analysis population should be considered when comparing this result with the primary efficacy result.
11. Safety: Serious Adverse Events
The ClinicalTrials.gov record reports serious adverse events by randomized treatment arm as affected participants over participants at risk.
| Safety measure | Rivaroxaban | Enoxaparin/VKA |
|---|---|---|
| Serious adverse events | 222 / 1718 | 252 / 1711 |
Rivaroxaban
222 affected participants among 1718 participants at risk.
Enoxaparin/VKA
252 affected participants among 1711 participants at risk.
These serious-adverse-event counts are descriptive safety information. They should not be substituted for the separately modeled clinically relevant bleeding endpoint, which used a time-to-event analysis and a defined safety population.
12. Statistical Methods Explained
Why was a Cox proportional-hazards model used?
The primary and posted secondary endpoints are naturally time-to-event outcomes. Participants can experience an event at different times, and some participants may be censored before an event is observed. Cox regression uses the timing information rather than reducing every participant to a simple yes/no event indicator.
What does an HR of 0.68 mean?
An HR of 0.68 means that the fitted model estimates the instantaneous event hazard in the rivaroxaban group at approximately 68% of the comparator hazard. Equivalently, 1 − 0.68 = 0.32, so the point estimate corresponds to a 32% lower estimated hazard. This is not an absolute risk reduction.
Why is non-inferiority judged against the margin?
Non-inferiority asks whether the new treatment's effect is sufficiently close to the comparator according to a prespecified clinically acceptable margin. Here, the registry specifies an upper confidence-limit margin of 2.0. The key question is therefore whether the entire relevant confidence boundary remains below 2.0, not simply whether the estimated HR is below 1.0.
Why does the primary CI include 1.0 but still support non-inferiority?
Because the non-inferiority margin is 2.0 rather than 1.0. The primary 95% CI is 0.44–1.04: it includes 1.0, so the data do not exclude equal hazards on a superiority scale, but its upper limit remains well below the non-inferiority boundary of 2.0.
Why was intention-to-treat used?
The ITT principle preserves the randomized treatment assignment in the efficacy comparison. Participants remain analyzed according to their assigned group rather than being reassigned according to treatment actually received. This helps preserve the comparison created by randomization.
Why adjust for active malignancy at baseline?
The posted Cox analyses adjusted for the presence of active malignancy at baseline. Covariate adjustment can account for an important baseline characteristic within the statistical model and can improve the precision or control for its association with the endpoint. It does not change the randomized treatment assignment.
What does stratification by intended treatment duration accomplish?
The Cox analysis was stratified by intended treatment duration. Stratification allows the baseline hazard to differ across the specified strata while estimating a common treatment effect within the model framework. It therefore accommodates the design feature without requiring the same baseline hazard across treatment-duration strata.
13. Confidence Intervals and the Primary Non-Inferiority Result
The primary estimate and its confidence interval illustrate why non-inferiority interpretation requires more than examining whether a hazard ratio is below 1.0.
| Quantity | Primary result | Statistical meaning |
|---|---|---|
| Point estimate | HR 0.68 | Estimated relative hazard under the Cox model |
| Lower 95% CI | 0.44 | Lower confidence boundary |
| Upper 95% CI | 1.04 | Upper confidence boundary |
| Non-inferiority margin | 2.0 | Prespecified upper hazard-ratio boundary |
| Decision relationship | 1.04 < 2.0 | Upper CI is below the registry's NI margin |
| Reported P-value | < 0.0001 | Evidence measure from the posted testing framework |
The distinction between 1.0 and 2.0 is central. A superiority analysis often asks whether the confidence interval excludes 1.0 in the desired direction. A non-inferiority analysis instead asks whether the confidence interval excludes effects worse than the prespecified non-inferiority margin. In this trial's primary analysis, the upper confidence limit of 1.04 is below 2.0.
This is why a confidence interval can include 1.0 while still satisfying a non-inferiority criterion. The two hypotheses use different reference boundaries.
14. The Role of Censoring in Time-to-Event Analysis
Time-to-event analysis is different from simply calculating the percentage of participants who experienced an event. A participant who has not experienced the endpoint by the time follow-up ends can still contribute information up to that point. That observation is generally treated as censored rather than as an event-free observation extending indefinitely.
The survival function is the probability that the event time exceeds t. Cox regression then models the relative hazard between treatment groups while accommodating censored observations.
For EINSTEIN-DVT, this distinction is particularly important because the registered endpoint is worded as a percentage of participants with recurrent VTE, while the formal posted analysis uses a time-to-event model. The statistical analysis therefore incorporates event timing rather than only an end-of-study event count.
15. Analysis Populations
| Population | Role in the registry-reported analysis |
|---|---|
| Intention-to-treat | All randomized participants with valid informed consent; participants analyzed according to treatment assigned at randomization. Used for the primary efficacy analysis and the posted secondary efficacy analyses. |
| Valid-for-safety population | Randomized participants with valid informed consent who received at least one dose of anticoagulant study treatment after randomization. Used for the clinically relevant bleeding analysis. |
The distinction illustrates a recurring principle in trial statistics: efficacy comparisons often remain anchored to randomization, while exposure-related safety analyses may require evidence that participants actually received study treatment.
16. What the Secondary Hazard Ratios Do — and Do Not — Mean
HR 0.72: composite endpoint
The point estimate corresponds to an estimated 28% lower hazard for recurrent DVT, non-fatal PE, or all-cause mortality under the posted Cox model.
HR 0.67: net clinical benefit
The point estimate corresponds to an estimated 33% lower hazard for the reported Net Clinical Benefit 1 endpoint.
HR 0.97: clinically relevant bleeding
The point estimate corresponds to an estimated 3% lower hazard for treatment-emergent clinically relevant bleeding through 2 days after the last dose.
HR is not absolute risk
None of these hazard ratios tells us directly how many additional or fewer participants experienced an event. Absolute event probabilities require different quantities.
The three secondary hazard ratios also answer different clinical questions. Combining them into a single overall "benefit" statistic would discard the endpoint-specific information. Recurrent thromboembolism, net clinical benefit, and clinically relevant bleeding should therefore remain separate statistical outcomes.
17. Multiplicity and Multiple Hypotheses
The ClinicalTrials.gov record identifies one primary endpoint and multiple secondary analyses. The primary endpoint is analyzed under a non-inferiority or equivalence framework, while the posted secondary analyses are labeled as superiority analyses.
| Endpoint | Role | Hypothesis type |
|---|---|---|
| Symptomatic recurrent VTE | Primary | Non-inferiority or equivalence |
| Recurrent DVT + non-fatal PE + all-cause mortality | Secondary | Superiority |
| Net Clinical Benefit 1 | Secondary | Superiority |
| Clinically relevant bleeding | Secondary | Superiority |
When multiple hypotheses are tested, the interpretation of individual P-values can depend on the prespecified multiplicity strategy. The ClinicalTrials.gov record does not specify a multiplicity-adjustment procedure for these secondary analyses. Consequently, the posted P-values should be read as the results of their stated analyses rather than automatically treated as an independently controlled family of confirmatory tests.
18. Randomization and Covariate Adjustment
Randomization establishes the treatment groups before outcomes are observed, creating the principal basis for a comparative treatment-effect analysis. Covariate adjustment then uses specified baseline information within the statistical model.
In EINSTEIN-DVT, the posted Cox analyses were adjusted for presence of active malignancy at baseline and stratified by intended treatment duration.
Adjustment should not be interpreted as evidence that randomization failed to balance baseline characteristics. Rather, it is part of the prespecified modeling strategy reported for the analyses.
19. Limitations
- Non-inferiority margin: the primary conclusion depends on the prespecified upper hazard-ratio margin of 2.0. The statistical result should therefore be interpreted relative to that boundary rather than solely relative to 1.0.
- Open-label design: the registry classifies masking as none. Lack of masking can affect behavior, assessment, reporting, or other aspects of a trial even when a primary endpoint includes independent adjudication.
- Time-to-event assumptions: Cox-model hazard ratios are model-based relative measures and rely on the proportional-hazards framework for their standard interpretation.
- Composite endpoints: the primary endpoint combines recurrent DVT with fatal or non-fatal PE. A composite can contain clinically distinct event types, so its overall hazard ratio should not automatically be interpreted as the effect on every component separately.
- Secondary endpoints: several secondary superiority analyses are reported. The ClinicalTrials.gov record does not specify a multiplicity-adjustment strategy for these analyses.
- Different analysis populations: primary efficacy analyses used ITT, while clinically relevant bleeding used a valid-for-safety population. Estimates from the two populations should not be treated as if they came from the same analysis set.
- Limited numerical detail: the ClinicalTrials.gov record provides hazard ratios, confidence intervals, and P-values for four analyses but do not provide arm-level event percentages for the primary endpoint. Those percentages should not be reconstructed from the hazard ratio.
- Safety counts are descriptive: serious-adverse-event counts by arm do not constitute a formal comparative time-to-event analysis unless such an analysis is separately reported.
20. Why This Trial Matters Statistically
EINSTEIN-DVT is a useful statistical teaching case because it combines randomized treatment assignment, a clinically important time-to-event endpoint, non-inferiority methodology, covariate-adjusted Cox regression, stratification, ITT analysis, secondary superiority analyses, and a separately defined safety population.
| Concept | How it appears in EINSTEIN-DVT |
|---|---|
| Randomization | Randomized, parallel two-arm phase 3 design |
| Intention-to-treat | Primary efficacy analysis based on randomized participants with valid informed consent |
| Time-to-event endpoint | Formal primary analysis uses Cox regression despite the registered percentage-based endpoint classification |
| Hazard ratio | Primary and secondary treatment effects reported as HRs |
| Confidence interval | 95% CIs quantify uncertainty around each HR |
| Non-inferiority | Primary analysis uses an upper HR margin of 2.0 |
| Cox proportional-hazards model | Used for the primary and all four posted statistical analyses |
| Stratified analysis | Analyses stratified by intended treatment duration |
| Covariate adjustment | Analyses adjusted for active malignancy at baseline |
| P-values | Reported for the primary and secondary formal analyses |
| Safety analysis | Clinically relevant bleeding analyzed in a valid-for-safety population |
| Serious adverse events | Reported descriptively by treatment arm |
21. Statistical Interpretation in One View
| Analysis | HR | 95% CI | P-value | Hypothesis |
|---|---|---|---|---|
| Primary: symptomatic recurrent VTE | 0.68 | 0.44–1.04 | < 0.0001 | Non-inferiority or equivalence |
| Secondary: recurrent DVT + non-fatal PE + all-cause mortality | 0.72 | 0.53–0.99 | 0.044 | Superiority |
| Secondary: Net Clinical Benefit 1 | 0.67 | 0.47–0.95 | 0.027 | Superiority |
| Secondary: clinically relevant bleeding | 0.97 | 0.76–1.22 | 0.77 | Superiority |
The most important statistical distinction is between the primary non-inferiority question and the secondary superiority questions. The primary HR of 0.68 has an upper 95% confidence limit of 1.04, which is below the prespecified non-inferiority margin of 2.0. The secondary analyses use different endpoints and a superiority framework, so their estimates should be interpreted on their own terms.
22. A Practical Reading of the Primary Result
The analysis compares the hazard of the registered symptomatic recurrent VTE composite between rivaroxaban and enoxaparin/VKA during the intended study-treatment period.
The treatment effect is estimated with a Cox proportional-hazards model, stratified by intended treatment duration and adjusted for active malignancy at baseline.
The HR of 0.68 indicates a lower estimated event hazard for rivaroxaban relative to the comparator in the fitted model.
The 95% CI of 0.44–1.04 expresses uncertainty around the treatment-effect estimate. Its upper boundary is the critical quantity for the reported non-inferiority criterion.
The upper confidence limit, 1.04, is below the prespecified non-inferiority margin of 2.0. That is the central statistical comparison supporting the registry's non-inferiority interpretation.
23. Related Tutorials
Learn more about the methods used in this trial:
24. Related Statistical Calculators
25. Sources
- ClinicalTrials.gov: NCT00440193 — EINSTEIN-DVT.
- PubMed record: PMID 21128814.
- PubMed record: PMID 22371186.
- PubMed record: PMID 23829521.
- PubMed record: PMID 24053656.
- PubMed record: PMID 24341332.
Continue through the Clinical Biostats statistical pathway
Connect this trial's survival-analysis methods, non-inferiority framework, confidence intervals, and hazard-ratio interpretation to deeper statistical tutorials and calculation tools.
26. Record Summary
EINSTEIN-DVT provides a compact example of how a randomized clinical trial can answer a non-inferiority question using a time-to-event endpoint. The primary analysis reported an HR of 0.68 with a 95% CI of 0.44–1.04, and the registry specifies an upper non-inferiority margin of 2.0. Because the upper confidence limit of 1.04 is below that margin, the primary result meets the registry's stated non-inferiority criterion.
The secondary analyses illustrate a different statistical framework: recurrent DVT, non-fatal PE, and all-cause mortality had an HR of 0.72, Net Clinical Benefit 1 had an HR of 0.67, and treatment-emergent clinically relevant bleeding had an HR of 0.97. All were analyzed using Cox regression, with the efficacy analyses based on ITT and the bleeding analysis based on the valid-for-safety population.