This page separates reported trial results from statistical interpretation. The numerical efficacy results presented here are limited to the statistical analyses posted for the two registered primary endpoints. ClinicalTrials.gov provides the official trial registry record. View the EV-302 registry record.
1. Trial at a Glance
EV-302 was a randomized, parallel, open-label phase 3 trial evaluating enfortumab vedotin plus pembrolizumab versus standard of care in untreated locally advanced or metastatic urothelial cancer. The registry reports two primary time-to-event endpoints: progression-free survival and overall survival.
| Feature | EV-302 |
|---|---|
| Trial name | EV-302 |
| Phase | Phase 3 |
| Condition | Urothelial Cancer |
| Population | Untreated locally advanced or metastatic urothelial cancer |
| Allocation | Randomized |
| Design | Parallel |
| Masking | None |
| Primary purpose | Treatment |
| Enrollment | 886 |
| Primary endpoints | Progression-Free Survival (PFS) and Overall Survival (OS) |
| Primary endpoint type | Time-to-event |
| Primary analysis method | Log-rank test |
| Effect measure | Hazard ratio |
| Hypothesis type | Superiority |
| Status | Active, not recruiting |
| Lead sponsor | Astellas Pharma Global Development, Inc. |
| Sponsor type | Industry |
2. Clinical Question
The primary statistical question was whether treatment with enfortumab vedotin plus pembrolizumab produced a different time-to-event profile from standard of care for patients with untreated locally advanced or metastatic urothelial cancer. Both registered primary endpoints were superiority hypotheses.
Population
Participants with untreated locally advanced or metastatic urothelial cancer.
Intervention
Enfortumab vedotin plus pembrolizumab.
Comparator
Standard of care. The registered interventions include cisplatin, carboplatin, and gemcitabine.
Primary question
Does enfortumab vedotin plus pembrolizumab improve progression-free survival and overall survival relative to standard of care?
3. Trial Design
Enfortumab Vedotin + Pembrolizumab
- Enfortumab vedotin
- Pembrolizumab
Standard of Care
- Cisplatin
- Carboplatin
- Gemcitabine
4. Randomization and Analysis Population
The primary efficacy analyses used the intention-to-treat (ITT) analysis set. The registry defines this population as including all randomized participants, with participants analyzed according to the treatment arm assigned at randomization regardless of the actual treatment received.
| Analysis population | Definition / role |
|---|---|
| Intention-to-treat | All randomized participants. Participants were analyzed according to the treatment arm assigned at randomization regardless of the actual treatment received. |
| Primary PFS comparison | Enfortumab vedotin + pembrolizumab versus standard of care. |
| Primary OS comparison | Enfortumab vedotin + pembrolizumab versus standard of care. |
This is an important feature of the statistical analysis. Randomization creates the basis for a causal comparison, and maintaining participants in their randomized groups for the primary efficacy analysis helps preserve that design principle even when actual treatment received differs from assignment.
5. Primary Endpoints
| Endpoint | Registered definition / time frame | Primary analysis |
|---|---|---|
| Progression-Free Survival (PFS) Per Response Evaluation Criteria in Solid Tumors (RECIST) Version (v) 1.1 by Blinded Independent Central Review (BICR) | From the date of randomization to first documentation of PD or death due to any cause, whichever occurred first. | Log-rank test; hazard ratio from a stratified Cox proportional hazards model. |
| Overall Survival (OS) | From randomization to date of death due to any cause or censoring date, whichever occurred first. | Log-rank test; hazard ratio from a stratified Cox proportional hazards model. |
Progression-Free Survival
The registered PFS definition is a time-to-event endpoint beginning at randomization. The event is the first documentation of disease progression or death due to any cause, whichever occurs first. Disease progression is defined using RECIST v1.1 criteria, with BICR providing the central assessment.
Overall Survival
OS is defined as the time from randomization to death from any cause. When death is not observed, the participant is censored at the date the participant was last known to be alive. The registry states that the Kaplan-Meier method was used for analysis.
6. Statistical Methodology
Kaplan-Meier estimation
Both primary endpoints are time-to-event outcomes. Kaplan-Meier estimation is therefore a natural way to describe the distribution of time until progression or death for PFS and time until death for OS.
Here, di is the number of events at time ti and ni is the number of participants at risk immediately before that time. The method allows participants without an observed event to contribute information until censoring.
Log-rank test
The registry reports the log-rank test as the primary comparison method for both PFS and OS. The test compares the observed pattern of events between randomized treatment groups across follow-up rather than comparing only a single time point.
Stratified Cox proportional hazards model
The registry states that the hazard ratio for each primary endpoint was calculated using a stratified Cox proportional hazards model. A Cox model estimates a relative hazard between treatment groups while accounting for the time-to-event structure and censoring.
A hazard ratio is a relative, model-based measure of the event rate over time. It is not the same as a relative risk, an absolute risk difference, a probability of benefit, or a statement that every individual patient experiences the same proportional reduction.
Intention-to-treat analysis
Both primary analyses used the ITT analysis set. This means that treatment assignment at randomization, rather than treatment actually received, defines the groups for the primary efficacy comparison. The approach preserves the treatment contrast created by randomization.
Stratified analysis
The statistical-analysis records identify stratified analysis as part of the primary analyses. The hazard ratios were calculated with stratified Cox proportional hazards models, while the OS p-value was calculated using a stratified log-rank test.
7. Primary Result: Progression-Free Survival
The registry reports a formal statistical analysis of PFS comparing enfortumab vedotin plus pembrolizumab with standard of care in the ITT analysis set.
Hazard ratio for progression or death
95% CI: 0.377–0.538 · P < 0.00001
Two-sided 95% confidence interval; superiority hypothesis.
| Characteristic | Reported analysis |
|---|---|
| Endpoint | PFS per RECIST v1.1 by BICR |
| Population | ITT analysis set |
| Groups | Enfortumab Vedotin + Pembrolizumab vs Standard of Care |
| Method | Log-rank test |
| Effect measure | Hazard ratio |
| Estimate | 0.450 |
| 95% CI | 0.377–0.538 |
| P-value | <0.00001 |
| Hypothesis | Superiority |
| HR model | Stratified Cox proportional hazards model |
The reported PFS hazard ratio of 0.450 means that the estimated instantaneous rate of progression or death was about 55% lower in the enfortumab vedotin plus pembrolizumab group than in the standard-of-care group under the fitted time-to-event model. This is a relative hazard interpretation, not a statement that 55% of participants avoided progression or death.
The 95% confidence interval of 0.377–0.538 describes statistical uncertainty around the estimated hazard ratio under the analysis framework. Because the entire interval is below 1, the interval is consistent with a lower estimated hazard in the intervention group.
The p-value of <0.00001 measures the evidence against the null hypothesis under the specified testing framework. It does not measure the size of the treatment effect, the probability that the treatment works, or the clinical importance of the result.
The interpretation also depends on the Cox proportional-hazards framework and on the censoring and event-assessment procedures used for PFS. The registry does not provide enough information here to independently evaluate the proportional-hazards assumption from the underlying event-time data.
8. Primary Result: Overall Survival
The registry also reports a formal ITT analysis of OS using the same randomized comparison. OS is measured from randomization to death from any cause, with censoring when death is not observed.
Hazard ratio for death
95% CI: 0.376–0.582 · P < 0.00001
Two-sided 95% confidence interval; superiority hypothesis.
| Characteristic | Reported analysis |
|---|---|
| Endpoint | Overall Survival |
| Population | ITT analysis set |
| Groups | Enfortumab Vedotin + Pembrolizumab vs Standard of Care |
| Method | Log-rank test |
| Effect measure | Hazard ratio |
| Estimate | 0.468 |
| 95% CI | 0.376–0.582 |
| P-value | <0.00001 |
| Hypothesis | Superiority |
| HR model | Stratified Cox proportional hazards model |
| Reported significance threshold | 0.01548 |
The reported OS hazard ratio of 0.468 means that the estimated instantaneous rate of death was about 53.2% lower in the enfortumab vedotin plus pembrolizumab group than in the standard-of-care group under the fitted Cox model. It does not mean that 53.2% of patients were saved, that individual mortality risk fell by exactly 53.2%, or that the absolute survival difference is 53.2 percentage points.
The 95% confidence interval of 0.376–0.582 expresses the statistical precision of the estimated hazard ratio. It remains below 1 throughout the interval, so the interval is compatible with a lower estimated hazard of death for the intervention group.
The reported p-value of <0.00001 is a measure of evidence against the relevant null hypothesis under the specified stratified testing procedure. It is not an effect-size measure. A smaller p-value does not by itself mean that an effect is clinically larger.
The registry reports a statistical-significance threshold of 0.01548 for the OS analysis. The reported p-value is below that threshold. The interpretation remains subject to the prespecified multiplicity and testing framework; the ClinicalTrials.gov record does not provide enough detail to reconstruct the complete alpha-allocation scheme across every endpoint and analysis.
As with any Cox-model hazard ratio, interpretation also depends on the proportional-hazards assumption. The single HR summarizes a relative event-rate relationship over follow-up; it should not be interpreted as though the same absolute treatment difference necessarily applies at every time point.
9. Reading the Two Primary Results Together
EV-302 reports hazard ratios below 1 for both registered primary endpoints. The PFS analysis estimates a hazard ratio of 0.450, while the OS analysis estimates a hazard ratio of 0.468. Both confidence intervals lie below 1, and both reported p-values are <0.00001.
| Primary endpoint | Hazard ratio | 95% CI | P-value | Interpretation of direction |
|---|---|---|---|---|
| PFS | 0.450 | 0.377–0.538 | <0.00001 | Lower estimated hazard of progression or death with enfortumab vedotin + pembrolizumab |
| OS | 0.468 | 0.376–0.582 | <0.00001 | Lower estimated hazard of death with enfortumab vedotin + pembrolizumab |
The two endpoints answer related but distinct questions. PFS counts progression or death as the event, whereas OS counts death from any cause. A treatment effect on PFS therefore cannot simply be substituted for an OS effect. In this trial, the registry reports formal analyses for both endpoints.
10. Safety: Serious Adverse Events
The ClinicalTrials.gov record reports serious adverse events by randomized arm as affected participants divided by participants at risk.
| Arm | Participants with serious adverse events | Participants at risk |
|---|---|---|
| Enfortumab Vedotin + Pembrolizumab | 220 | 440 |
| Standard of Care | 169 | 433 |
These figures describe the number of participants affected and the corresponding number at risk reported in the ClinicalTrials.gov record. They should be interpreted separately from the efficacy hazard ratios because safety and efficacy use different outcome definitions and analytical objectives.
11. Statistical Methods Explained
Why was a log-rank test used?
PFS and OS are time-to-event endpoints, so participants can have different follow-up durations and some may be censored before experiencing the event. The log-rank test is designed to compare survival distributions while using the available event-time information across follow-up rather than reducing the analysis to a single fixed time point.
What does a hazard ratio of 0.450 mean?
A hazard ratio of 0.450 indicates that the fitted model estimates a substantially lower instantaneous event rate in the enfortumab vedotin plus pembrolizumab group than in the standard-of-care group. It does not mean that the intervention reduces every individual's probability of an event by exactly 55%.
Why is the confidence interval important?
The point estimate alone does not describe statistical precision. The 95% confidence interval shows the range of hazard-ratio values compatible with the data and model under the specified confidence procedure. A narrower interval generally indicates greater statistical precision than a wider interval, although precision is not the same as clinical importance.
Why does the p-value not measure effect size?
A p-value addresses evidence against a null hypothesis under a specified statistical model. It does not tell us how large the treatment effect is. The hazard ratio describes relative effect size, while the confidence interval describes uncertainty around that effect estimate.
Why use an intention-to-treat analysis?
Analyzing participants according to randomized assignment preserves the comparison created by randomization. This reduces the risk that post-randomization treatment decisions selectively determine who remains in each efficacy group.
Why was a stratified Cox model used?
The registry specifically reports a stratified Cox proportional hazards model for calculation of the primary hazard ratios. Stratification allows the time-to-event comparison to account for the prespecified stratified analysis structure rather than treating all participants as though the relevant strata had no role in the model.
What does censoring mean for OS?
For OS, a participant who has not been observed to die is not treated as though death never occurs. Instead, the participant contributes follow-up information until the date on which they were last known to be alive, at which point the observation is censored. Kaplan-Meier and Cox methods incorporate these censored observations into the time-to-event analysis.
12. Confidence Intervals and the Meaning of Precision
The two primary hazard-ratio estimates are accompanied by two-sided 95% confidence intervals:
| Endpoint | Estimate | Lower bound | Upper bound | Interval width |
|---|---|---|---|---|
| PFS | 0.450 | 0.377 | 0.538 | 0.161 |
| OS | 0.468 | 0.376 | 0.582 | 0.206 |
The confidence intervals provide more information than the point estimates alone. For PFS, the estimated hazard ratio is 0.450 and the interval extends from 0.377 to 0.538. For OS, the estimate is 0.468 and the interval extends from 0.376 to 0.582.
Neither interval should be interpreted as a range containing the true treatment effect with a 95% probability in this particular trial. The conventional frequentist interpretation concerns the long-run performance of the confidence procedure under repeated sampling. For practical interpretation, the key point is that the interval communicates the uncertainty associated with each estimated hazard ratio.
13. P-Values and Statistical Evidence
Both primary analyses report P < 0.00001. These p-values provide very strong statistical evidence against the relevant null hypothesis under the specified analysis framework.
What the p-value tells us
It quantifies how incompatible the observed test statistic is with the null hypothesis under the specified testing procedure.
What it does not tell us
It does not give the probability that the null hypothesis is true, the probability that treatment benefits an individual, or the size of the treatment effect.
For OS, the ClinicalTrials.gov record also specifies a statistical-significance threshold of 0.01548. The reported OS p-value is below that threshold. The ClinicalTrials.gov record does not provide a corresponding numerical threshold for the PFS analysis, so no additional threshold is inferred here.
14. Time-to-Event Endpoints: Why the Analysis Is More Than a Single Number
PFS and OS are fundamentally longitudinal outcomes. Each participant contributes information through time, and the exact timing of progression, death, or censoring matters. This is why the trial uses survival-analysis methods rather than a simple comparison of proportions.
The analysis combines the randomized treatment comparison with the timing of events and the handling of incomplete event observation.
For PFS, progression and death are treated as the event definition reported by the registry. For OS, death is the event and participants who remain alive are censored at their last known alive date. These definitions determine what the hazard ratio actually describes.
15. Stratified Analysis and the Hazard Ratio
The statistical analysis records identify both stratified analysis and a stratified Cox proportional hazards model. This is important because the hazard ratio is not simply a ratio obtained by dividing two crude event percentages.
A Cox hazard ratio compares the modeled instantaneous event rates between treatment groups while incorporating the time dimension of the outcome. Stratification modifies the model structure so that the baseline hazard can differ across strata while the treatment effect is estimated within the specified analysis framework.
A hazard ratio is not a direct measure of absolute benefit. For example, HR 0.468 does not mean that the absolute probability of death is reduced by 53.2 percentage points. Absolute survival probabilities at specified times, when available, are needed to answer absolute-risk questions.
16. Proportional-Hazards Assumption
The Cox model used for both primary hazard ratios is a proportional-hazards model. Its standard interpretation assumes that the relative hazard between groups is adequately represented by a common hazard ratio over the relevant follow-up.
If the treatment effect changes materially over time, a single HR can become a less complete description of the underlying survival experience. In that situation, Kaplan-Meier curves, time-specific survival estimates, restricted mean survival time, or time-varying effect models may provide additional information.
17. What the Primary Results Do — and Do Not — Establish
What is directly reported
The ITT PFS analysis reports HR 0.450 with 95% CI 0.377–0.538 and P < 0.00001. The ITT OS analysis reports HR 0.468 with 95% CI 0.376–0.582 and P < 0.00001.
What the estimates represent
They are relative time-to-event effect measures comparing enfortumab vedotin plus pembrolizumab with standard of care under the reported stratified Cox models.
What cannot be inferred
The hazard ratios do not directly provide absolute survival differences, median survival times, individual treatment benefit probabilities, or the percentage of participants cured.
What requires additional data
Detailed subgroup effects, survival probabilities at selected time points, median PFS or OS, and complete adverse-event category tables require information not reported in the ClinicalTrials.gov record.
18. Limitations
- Summary-level results: the ClinicalTrials.gov record provides two primary endpoint analyses but not the participant-level event and censoring data needed to independently reproduce the hazard ratios.
- No median survival estimates reported: the ClinicalTrials.gov record does not contain median PFS or OS values, so they are not reported.
- No subgroup results reported: the data identify stratified analysis but do not provide subgroup hazard ratios or interaction tests.
- Open-label design: treatment assignment was not masked, although the primary PFS endpoint was assessed by BICR.
- Hazard-ratio assumptions: the Cox proportional-hazards model provides a compact relative measure but depends on its model assumptions for interpretation.
- Multiplicity information is incomplete: the OS analysis reports a significance threshold of 0.01548, but the ClinicalTrials.gov record does not describe the complete endpoint hierarchy or alpha-allocation procedure.
- Safety detail: only serious adverse-event affected/at-risk counts by arm are reported; individual event categories and other safety measures cannot be reconstructed.
- No crossover information: the ClinicalTrials.gov record does not report crossover or subsequent-treatment details, so their effect on OS cannot be quantified here.
- No Bayesian analysis reported: the statistical analyses posted on ClinicalTrials.gov are frequentist log-rank/Cox analyses; no Bayesian method is identified.
- No missing-data or imputation method reported: the registry-reported primary analyses do not specify an imputation procedure, so none is inferred.
19. Design Topics Not Supported by the Supplied Data
| Topic | What the registry-reported EV-302 data support |
|---|---|
| Non-inferiority margin | Not reported. The registered primary hypotheses are superiority hypotheses. |
| Crossover | Not reported in the ClinicalTrials.gov record. |
| Factorial design | Not applicable to the reported parallel two-arm design. |
| Multiplicity | OS has a reported statistical-significance threshold of 0.01548; the complete multiplicity strategy is not reported. |
| Interim analysis | Not reported in the ClinicalTrials.gov record. |
| Missing-data / imputation method | Not reported in the ClinicalTrials.gov record. |
| Bayesian methods | Not reported. The posted primary methods are frequentist log-rank and stratified Cox analyses. |
This distinction matters because a statistical analysis page should not fill gaps in the registry record with assumptions based on how other phase 3 oncology trials are commonly designed. Where the registry-reported EV-302 data do not identify a method, this page does not assign one to the trial.
20. Why This Trial Matters Statistically
EV-302 is a useful teaching example of a modern randomized phase 3 time-to-event analysis because its two registered primary endpoints use the same core statistical framework while measuring different clinical events.
| Statistical concept | How it appears in EV-302 |
|---|---|
| Randomization | The trial uses randomized allocation with two parallel treatment arms. |
| Intention-to-treat analysis | Both primary analyses include all randomized participants and preserve treatment assignment at randomization. |
| Time-to-event endpoint | Both PFS and OS are time-to-event primary endpoints. |
| Kaplan-Meier estimation | The OS registry definition identifies Kaplan-Meier as the analysis method. |
| Log-rank test | The posted statistical analysis uses a log-rank test for both primary endpoints. |
| Hazard ratio | PFS and OS effects are expressed as hazard ratios. |
| Confidence interval | Both primary hazard ratios have two-sided 95% confidence intervals. |
| Stratified analysis | The primary analysis records identify stratified analysis, with HRs calculated using stratified Cox models. |
| BICR | The PFS endpoint is assessed by Blinded Independent Central Review. |
| Superiority testing | Both registered primary analyses use superiority hypotheses. |
21. Statistical Concepts in This Trial
Learn more about the methods used in this trial:
22. Related Statistical Calculators
23. Sources
- ClinicalTrials.gov: NCT04223856.
- PubMed: PMID 41925239.
- PubMed: PMID 41563650.
- PubMed: PMID 41039930.
- PubMed: PMID 40449498.
- PubMed: PMID 38485615.
Continue through the Clinical Biostats statistical pathway
Explore the survival-analysis methods and statistical tools that explain how randomized time-to-event trials are designed and analyzed.
24. Record Summary
EV-302 provides a clear example of a randomized phase 3 trial in which both primary endpoints are time-to-event outcomes analyzed in the ITT population. The registry reports log-rank testing and stratified Cox proportional-hazards models for PFS and OS. The PFS analysis reports a hazard ratio of 0.450 with a two-sided 95% CI of 0.377–0.538 and P < 0.00001. The OS analysis reports a hazard ratio of 0.468 with a two-sided 95% CI of 0.376–0.582 and P < 0.00001. The OS analysis record also specifies a statistical-significance threshold of 0.01548.
The statistical interpretation should remain anchored to what those measures actually describe: relative event hazards under specified survival models, with uncertainty quantified by confidence intervals and evidence summarized by hypothesis-test p-values. The analysis does not by itself provide absolute survival probabilities, median survival times, individual treatment benefit probabilities, or subgroup treatment effects unless those quantities are separately reported.