This page separates reported trial results from statistical interpretation. Numerical results are restricted to the ClinicalTrials.gov record and the permitted linked sources. ClinicalTrials.gov provides the official trial registry record.
1. Trial at a Glance
PROSPER was a randomized, parallel-group, phase 3 study of enzalutamide versus placebo in patients with nonmetastatic castration-resistant prostate cancer. The registry reports 1401 participants, two treatment arms, quadruple masking, and a primary time-to-event endpoint of metastasis-free survival.
| Feature | PROSPER |
|---|---|
| Trial name | PROSPER |
| NCT ID | NCT02003924 |
| Phase | Phase 3 |
| Status | COMPLETED |
| Therapeutic area | Oncology |
| Condition | Nonmetastatic Castration-Resistant Prostate Cancer; Prostate Cancer; Cancer of the Prostate |
| Allocation | RANDOMIZED |
| Design model | PARALLEL |
| Masking | QUADRUPLE |
| Primary purpose | TREATMENT |
| Enrollment | 1401.0 |
| Interventions | Enzalutamide; Placebo |
| Lead sponsor | Pfizer |
| Results posted | Yes |
| Outcome measures posted | 47 |
| Statistical analyses posted | 9 |
2. Clinical Question
The central statistical question was whether treatment assignment to enzalutamide rather than placebo was associated with a difference in the time from randomization to metastasis-free survival events in patients with nonmetastatic castration-resistant prostate cancer.
Population
Patients with nonmetastatic castration-resistant prostate cancer, as represented by the registered PROSPER study population.
Intervention
Enzalutamide 160 mg.
Comparator
Placebo.
Primary question
Does enzalutamide change metastasis-free survival relative to placebo under the prespecified superiority analysis?
3. Trial Design
Enzalutamide
- Enzalutamide 160 mg.
- Serious adverse events were reported as 372 affected participants among 930 at risk.
Placebo
- Placebo.
- Serious adverse events were reported as 100 affected participants among 465 at risk.
- The registry also reports 12 affected participants among 87 at risk in the category "Placebo Patients Crossover to Enzalutami".
The ClinicalTrials.gov record identifies the study as randomized, parallel, and quadruple-masked. Those design features are important statistically because the treatment comparison is anchored to randomized assignment while masking is intended to reduce the influence of treatment knowledge on trial conduct and assessment.
4. Trial Timing and Registry Record
Study start
The registered study start date was 2013-10-31.
Primary completion
The registered primary completion date was 2017-06-28.
Statistical results available
The ClinicalTrials.gov record contains 47 posted outcome measures and 9 posted statistical analyses, including one formal primary-endpoint analysis.
5. Primary Endpoint
| Endpoint | Registry definition / time frame | Endpoint type | Primary analysis |
|---|---|---|---|
| Metastasis Free Survival (MFS) | Time from randomization to first date of radiographic progression (RP) (by Blinded independent central radiology review [BICR]) at any time or death within 112 days of treatment discontinuation without evidence of RP. RP for bone disease: appearance of 1 or more metastatic lesions on bone scan. RP for soft tissue disease: per Response Evaluation Criteria in Solid Tumors, [RECIST 1.1])-at least a 20 percent (%) increase in the sum of diameters of target lesions,taking as reference the smallest sum on study (includes the baseline sum if smallest on study).Participants who did not have MFS event at the time of analysis data cut-off (28 June 2017) were censored at date of last assessment showing no objective evidence of RP prior to skeletal-related event or two or more consecutive missed tumor assessments. Participants who were randomized but later confirmed to have metastatic disease before randomization were censored on date of randomization. Analysis was based on Kaplan-Meier estimates. | Time-to-event | Log-rank test; hazard ratio from a Cox regression model |
6. Analysis Population and Treatment Comparison
The primary MFS analysis used the intent-to-treat (ITT) population. The registry defines this population as all participants randomly assigned to study treatment and states that the analysis was based on randomized treatment assignment regardless of whether or not treatment was administered.
| Analysis feature | Registry-reported approach |
|---|---|
| Population | Intent-to-treat (ITT) |
| Groups compared | Enzalutamide 160 mg vs Placebo |
| Primary endpoint | Metastasis Free Survival (MFS) |
| Statistical test | Log Rank |
| Effect measure | Hazard Ratio (HR) |
| Hypothesis | Superiority |
| Model note | HR was based on a Cox regression model with treatment as the only covariate, stratified by factors defined in the registry analysis record, and was relative to placebo with < 1 favoring Enzalutamide. |
The ITT principle is particularly important in a randomized trial. Once participants are randomized, analyzing them according to their assigned treatment preserves the treatment comparison created by randomization. It avoids changing the comparison based on what happened after randomization, such as treatment discontinuation or failure to receive treatment.
7. Primary Results: Metastasis-Free Survival
The registry reports a formal statistical analysis for MFS using a log-rank test and a hazard ratio derived from a Cox regression model. The analysis was performed in the ITT population comparing enzalutamide 160 mg with placebo.
Hazard ratio for metastasis-free survival
95% CI: 0.241–0.352 · P < 0.0001
Two-sided confidence interval; superiority hypothesis.
| Endpoint | Analysis population | Method | Effect estimate | 95% CI | P-value |
|---|---|---|---|---|---|
| Metastasis Free Survival (MFS) | ITT | Log-rank test; stratified Cox regression | HR 0.292 | 0.241–0.352 | <0.0001 |
The reported HR of 0.292 means that, under the Cox model used for this analysis, the estimated instantaneous rate of an MFS event in the enzalutamide group was about 29.2% of the corresponding rate in the placebo group. Expressed as a simple relative-hazard interpretation, this corresponds to an estimated 70.8% lower hazard because 1 − 0.292 = 0.708.
This does not mean that 70.8% of participants avoided metastasis, that 70.8% were cured, or that each individual participant experienced exactly a 70.8% reduction in risk. A hazard ratio is a relative time-to-event measure derived from a statistical model.
The 95% CI of 0.241–0.352 describes the statistical uncertainty around the estimated hazard ratio under the model and sampling framework. It is not a range containing the individual treatment effects experienced by patients.
The P-value of <0.0001 addresses the strength of evidence against the null hypothesis under the specified testing framework. It does not measure the size of the treatment effect. Effect size is communicated by the hazard ratio, while precision is communicated by the confidence interval.
Because this is a time-to-event analysis, interpretation also depends on censoring and the assumptions underlying the Cox model. In particular, a single hazard ratio is most straightforward to interpret when the relative hazards are reasonably described by a proportional-hazards model over the analyzed follow-up.
8. Secondary Time-to-Event Results
The registry contains formal statistical analyses for several secondary time-to-event endpoints. These analyses use the ITT population and compare enzalutamide 160 mg with placebo using log-rank testing and hazard ratios.
| Secondary endpoint | Time frame | Effect measure | Estimate | 95% CI | P-value |
|---|---|---|---|---|---|
| Time to Prostate-Specific Antigen (PSA) Progression | From randomization until first PSA progression (until the data cut-off date of 28 June 2017, maximum duration of treatment: 42.8 months) | Hazard ratio | 0.066 | 0.054–0.081 | <0.0001 |
| Time to First Use of New Antineoplastic Therapy | From randomization until first use of new antineoplastic therapy(until the data cut-off date of 28 June 2017, maximum duration of treatment: 42.8 months) | Hazard ratio | 0.208 | 0.168–0.258 | <0.0001 |
| Overall Survival | From randomization until death (up to a maximum of 68.8 months) | Hazard ratio | 0.734 | 0.608–0.885 | 0.0011 |
| Time to Pain Progression | From randomization until onset of pain progression (until the data cut-off date of 28 June 2017, maximum duration of treatment: 42.8 months) | Hazard ratio | 0.959 | 0.801–1.149 | 0.6534 |
| Time to First Use of Cytotoxic Chemotherapy | From randomization up to the first use of cytotoxic chemotherapy (until the data cut-off date of 28 June 2017, maximum duration of treatment: 42.8 months) | Hazard ratio | 0.378 | 0.282–0.507 | <0.0001 |
Reading the secondary hazard ratios
The secondary estimates span a wide range. An HR below 1 indicates a lower estimated event hazard for enzalutamide relative to placebo under the corresponding analysis, while an HR near 1 indicates a smaller estimated relative difference. The time-to-pain-progression analysis, for example, reported an HR of 0.959 with a 95% CI of 0.801–1.149 and P=0.6534. Unlike the other reported time-to-event estimates in this table, that confidence interval includes 1.
These endpoints should not be collapsed into a single treatment-effect statistic. They represent different clinical events occurring at different stages of disease and treatment. A treatment can affect PSA progression, use of subsequent therapy, survival, pain progression, and chemotherapy initiation differently because these events have different definitions, censoring mechanisms, and clinical determinants.
9. Secondary PSA Response Results
The registry also reports three analyses of the binary endpoint Percentage of Participants With Prostate Specific Antigen (PSA) Response. The analysis method was the Cochran-Mantel-Haenszel test, with the effect measure reported as a difference in response rate.
| PSA response definition | Estimate: difference in response rate | 95% CI | P-value |
|---|---|---|---|
| Decrease from Baseline ≥ 50% | 73.96 | 70.91–77.02 | <0.0001 |
| Decrease from Baseline ≥ 90% | 55.52 | 52.28–58.76 | <0.0001 |
| Decrease to Undetectable Level | 9.65 | 7.75–11.54 | <0.0001 |
Unlike MFS and the other time-to-event outcomes, these PSA response measures are binary outcomes. The reported effect measure is therefore a difference in response rate, rather than a hazard ratio. This distinction matters: the number 73.96 represents a difference in the percentage of participants meeting the registered PSA-response criterion, not a relative hazard and not a time-to-event measure.
The registry identifies the ITT population for these analyses and specifies the Cochran-Mantel-Haenszel method. The three response definitions should also be kept conceptually separate because a decrease of at least 50%, a decrease of at least 90%, and a decrease to an undetectable level represent progressively different PSA-response criteria.
10. Statistical Methodology
Kaplan-Meier estimation
Metastasis-free survival, PSA progression, new antineoplastic therapy, overall survival, pain progression, and cytotoxic chemotherapy use are all time-to-event outcomes. A standard way to describe such outcomes is with the Kaplan-Meier estimator, which estimates the probability of remaining event-free over time while accounting for right-censored observations.
where di is the number of events at time ti and ni is the number at risk immediately before that time.
The ClinicalTrials.gov record does not provide Kaplan-Meier estimates or curves themselves. The important statistical point is that the underlying time-to-event framework can accommodate participants whose event has not occurred by the time they leave the observable risk set. Such participants are censored rather than automatically treated as if they experienced the event.
Log-rank test
The registry reports the log-rank test for MFS and the listed secondary time-to-event endpoints. The log-rank procedure compares the observed and expected numbers of events between treatment groups over follow-up.
It is therefore fundamentally different from simply comparing the percentage of participants who eventually experienced an event. The timing of events contributes to the comparison, which is why the log-rank test is a natural method for randomized trials with time-to-event endpoints.
Cox proportional-hazards model
The MFS analysis notes that the hazard ratio was based on a Cox regression model with treatment as the only covariate, stratified by factors defined in the registry analysis record. The ClinicalTrials.gov record does not enumerate those stratification factors, so they are not independently reconstructed here.
A hazard ratio is a relative model-based measure. It is not the same as a relative risk, an absolute risk difference, or the percentage of participants who benefit.
Intention-to-treat analysis
The registry explicitly defines the ITT population as all participants randomly assigned to study treatment, with analyses based on randomized treatment assignment regardless of whether treatment was administered. This approach protects the original randomized comparison.
For educational purposes, this is an important distinction from an analysis that excludes participants after randomization because of treatment discontinuation or other post-randomization events. Excluding such participants can change the population being compared and potentially weaken the protection provided by randomization.
Cochran-Mantel-Haenszel testing
The PSA-response analyses use the Cochran-Mantel-Haenszel test. This family of methods is designed for categorical data and can account for stratification when the analysis includes relevant strata. In PROSPER, the registry identifies the method and the ITT population, while the reported effect measure is a difference in response rate.
11. Statistical Methods Explained
Why was a log-rank test used for MFS?
MFS is a time-to-event endpoint. Participants can experience the event at different times, while others may be censored before an event is observed. The log-rank test uses the timing of events across follow-up rather than reducing the endpoint to a simple yes/no status at a single time point.
What does an MFS hazard ratio of 0.292 mean?
It means the fitted model estimated the instantaneous event hazard in the enzalutamide group to be 0.292 times that in the placebo group. In relative terms, that is an estimated 70.8% lower hazard. It does not mean that 70.8% of participants avoided metastasis or that every patient experienced that same reduction.
Why is the confidence interval important?
The 95% CI of 0.241–0.352 communicates precision around the MFS hazard-ratio estimate. A narrow interval indicates that the estimate is relatively concentrated under the statistical framework used, while the interval itself still should not be interpreted as the range of effects for individual patients.
Why doesn't the P-value measure effect size?
A P-value measures how compatible the observed data are with a specified null hypothesis under the statistical model and testing procedure. It is influenced by both the magnitude of an effect and the amount of information available. The hazard ratio is the effect measure; the confidence interval describes its statistical precision.
Why is ITT important in this trial?
ITT preserves the randomized treatment assignment as the basis of the efficacy comparison. This means that post-randomization events do not determine which randomized group a participant belongs to for the primary efficacy analysis.
Why are PSA response and MFS analyzed differently?
MFS records a time until an event and therefore uses survival-analysis methods. PSA response is a binary outcome based on whether a participant meets a specified response criterion. The registry consequently uses a Cochran-Mantel-Haenszel test and reports a difference in response rate rather than a hazard ratio.
Why does multiplicity matter for the secondary endpoints?
When several hypotheses are tested, the chance of obtaining at least one apparently positive result can increase if every test is treated as an independent 0.05 test. The registry describes an allocated type I error framework and a sequential testing strategy, so the P-values should be interpreted in the context of that prespecified testing structure rather than in isolation.
12. Confidence Intervals and Statistical Precision
The reported confidence intervals show how the same statistical framework communicates uncertainty for different endpoint types.
| Endpoint | Estimate | 95% confidence interval | Measure type |
|---|---|---|---|
| MFS | HR 0.292 | 0.241–0.352 | Hazard ratio |
| Time to PSA progression | HR 0.066 | 0.054–0.081 | Hazard ratio |
| Time to new antineoplastic therapy | HR 0.208 | 0.168–0.258 | Hazard ratio |
| Overall survival | HR 0.734 | 0.608–0.885 | Hazard ratio |
| Time to pain progression | HR 0.959 | 0.801–1.149 | Hazard ratio |
| Time to cytotoxic chemotherapy | HR 0.378 | 0.282–0.507 | Hazard ratio |
| PSA response: decrease from baseline ≥ 50% | 73.96 | 70.91–77.02 | Difference in response rate |
| PSA response: decrease from baseline ≥ 90% | 55.52 | 52.28–58.76 | Difference in response rate |
| PSA response: decrease to undetectable level | 9.65 | 7.75–11.54 | Difference in response rate |
A useful statistical habit is to read an estimate and its confidence interval together. For example, the MFS HR of 0.292 should not be considered independently of its 95% CI of 0.241–0.352. Similarly, the time-to-pain-progression estimate of 0.959 should be read together with its 95% CI of 0.801–1.149 rather than judged solely by whether the point estimate is below 1.
13. Multiplicity and Hierarchical Testing
The registry analysis notes a specific approach to maintaining the family-wise two-sided type I error rate at 0.05. A parallel testing strategy was used between overall survival, with an allocated type I error rate of 0.03, and the remaining key secondary endpoints, including time to PSA progression and time to first use of new antineoplastic therapy, with an allocated type I error rate of 0.02.
Primary endpoint first
The registry states that testing of the relevant secondary endpoints was performed only if the primary endpoint was statistically significant.
Allocated error
The analysis describes an overall two-sided type I error rate of 0.05 distributed through the prespecified testing strategy.
Why this matters
The reported secondary P-values should be interpreted within the trial's testing strategy rather than as a collection of unrelated hypothesis tests.
Different endpoints
MFS, overall survival, PSA progression, pain progression, and treatment-use endpoints represent different clinical questions and should not be treated as interchangeable.
Multiplicity is often misunderstood as a technical adjustment applied only after results are obtained. In a well-specified confirmatory trial, it is instead part of the design. The allocation of type I error determines how evidence is evaluated across the family of prespecified hypotheses.
14. Safety Results
The ClinicalTrials.gov record reports serious adverse events by treatment category. These figures should be read as affected participants divided by the corresponding number at risk, rather than as a comparison of time-to-event efficacy outcomes.
| Safety category | Affected / at risk |
|---|---|
| Enzalutamide 160 mg | 372 / 930 |
| Placebo | 100 / 465 |
| Placebo Patients Crossover to Enzalutami | 12 / 87 |
The ClinicalTrials.gov record does not provide a statistical hypothesis test, confidence interval, or comparative effect measure for these serious-adverse-event figures. Accordingly, the safety information is reported descriptively rather than converted into an unreported statistical comparison.
The crossover category also needs to be kept distinct from the randomized placebo category. Participants who later crossed over represent a post-randomization treatment pathway, whereas the primary efficacy analysis is based on randomized treatment assignment.
15. Crossover and Treatment Assignment
The ClinicalTrials.gov record explicitly identify a category of Placebo Patients Crossover to Enzalutami, with 12 affected participants among 87 at risk for the reported safety measure.
From a statistical perspective, crossover creates an important distinction between assignment and treatment received. The ITT efficacy analysis asks what happened according to the randomized treatment assignment. A treatment-received analysis instead asks what happened according to subsequent exposure. These are different estimands and answer different causal questions.
16. What the MFS Hazard Ratio Does — and Does Not — Mean
The MFS HR of 0.292 is a model-based relative comparison of event hazards. Because the registry specifies that values below 1 favor enzalutamide, the estimate indicates a lower estimated MFS event hazard for enzalutamide relative to placebo.
The HR is not the difference between two percentages of participants who experienced metastasis or death. Without corresponding absolute survival probabilities at a specified time point, the HR alone cannot tell a reader the absolute number of events prevented.
A hazard ratio describes the randomized groups at the population level. It should not be interpreted as saying that an individual participant's personal risk is reduced by exactly the same percentage.
MFS is explicitly defined as a time from randomization to an event or censoring-related endpoint. The interpretation therefore depends on the observed follow-up period, event timing, and censoring rules rather than simply on whether an event occurred at some unspecified point.
17. Time-to-Event Endpoints: Why the Timing of Events Matters
PROSPER provides a useful illustration of why time-to-event analysis is different from ordinary binary analysis. Suppose two treatment groups eventually had the same number of events. That alone would not establish that their clinical courses were equivalent: one group could experience events substantially earlier than the other.
Survival methods preserve information about when events occur. The Kaplan-Meier framework describes the event-free probability over time, the log-rank test compares the treatment groups across follow-up, and the Cox model summarizes the relative event hazard using a hazard ratio.
| Statistical component | Question it helps answer |
|---|---|
| Kaplan-Meier estimation | How does the probability of remaining event-free change over time? |
| Log-rank test | Is there evidence that the time-to-event distributions differ between randomized groups? |
| Cox model | What is the estimated relative hazard between treatment groups? |
| 95% confidence interval | How precise is the estimated relative effect? |
| P-value | How compatible are the data with the specified null hypothesis under the testing framework? |
18. Statistical Interpretation of the Secondary Endpoints
The secondary results illustrate why statistical interpretation should consider both the endpoint and its estimand.
For time to PSA progression, the HR was 0.066 with a 95% CI of 0.054–0.081 and P<0.0001. The point estimate is far below 1, indicating a large relative difference in the estimated event hazard under the reported model.
For time to first use of new antineoplastic therapy, the HR was 0.208 with a 95% CI of 0.168–0.258 and P<0.0001. This measures the time to a subsequent treatment event, not metastasis itself.
For overall survival, the HR was 0.734 with a 95% CI of 0.608–0.885 and P=0.0011. The registry defines this endpoint simply as time from randomization until death, with a maximum duration of 68.8 months in the reported time frame.
For time to pain progression, the HR was 0.959 with a 95% CI of 0.801–1.149 and P=0.6534. The confidence interval extends across 1, so the reported point estimate should not be interpreted independently of that uncertainty.
For time to first use of cytotoxic chemotherapy, the HR was 0.378 with a 95% CI of 0.282–0.507 and P<0.0001. Again, this is a time-to-treatment-use endpoint rather than a direct measure of metastasis-free survival.
19. Limitations and Interpretation Issues
- Registry-level detail: the ClinicalTrials.gov record provides the principal endpoint definitions and reported statistical analyses, but do not provide every element of a full statistical analysis plan.
- Hazard-ratio assumptions: the Cox model is a model-based analysis. Interpretation of a single HR is most straightforward when the proportional-hazards representation is reasonable over the relevant follow-up.
- Censoring: time-to-event methods depend on censoring rules and assumptions about the relationship between censoring and future event risk.
- Multiplicity: several efficacy hypotheses were tested, so individual P-values should be interpreted within the prespecified type I error strategy.
- Secondary endpoints: different secondary outcomes measure different clinical events and should not be treated as interchangeable measures of the same treatment effect.
- Crossover: the registry identifies placebo patients who crossed over to enzalutamide, which complicates any interpretation based solely on treatment actually received.
- Safety denominator: the registry-reported serious-adverse-event figures use their reported at-risk denominators and should not be combined with efficacy populations without further information.
- Absolute effects: the statistical analyses posted on ClinicalTrials.gov report hazard ratios and response-rate differences but do not provide corresponding absolute MFS probabilities or median MFS values in the ClinicalTrials.gov record.
20. Why This Trial Matters Statistically
PROSPER is a useful teaching example because it connects several fundamental clinical-trial methods in a single randomized study. Its primary endpoint is a time-to-event outcome, the primary analysis uses a log-rank framework and Cox-derived hazard ratio, the efficacy population follows the ITT principle, secondary binary outcomes use the Cochran-Mantel-Haenszel test, and the registry describes a multiplicity strategy for key secondary testing.
| Concept | How it appears in PROSPER |
|---|---|
| Randomization | Participants were randomly assigned to enzalutamide or placebo. |
| Blinding | The registry describes the study as quadruple-masked. |
| ITT analysis | The MFS and secondary efficacy analyses use randomized treatment assignment in the ITT population. |
| Time-to-event analysis | MFS, PSA progression, new antineoplastic therapy, overall survival, pain progression, and cytotoxic chemotherapy use are time-to-event endpoints. |
| Log-rank test | Used for the formal time-to-event comparisons reported in the registry. |
| Hazard ratio | Used to quantify relative treatment effects for the time-to-event endpoints. |
| Cox regression | The MFS HR was based on a Cox regression model with treatment as the only covariate and stratification by registry-defined factors. |
| Confidence interval | 95% two-sided confidence intervals accompany the reported effect estimates. |
| Cochran-Mantel-Haenszel test | Used for the reported binary PSA-response analyses. |
| Multiplicity | A parallel testing strategy allocated type I error across OS and key secondary endpoints. |
| Crossover | The registry includes a category for placebo patients crossing over to enzalutamide. |
21. A Practical Reading Framework for PROSPER
A statistically disciplined reading of the PROSPER results can follow a sequence rather than beginning with the P-value.
1. Identify the estimand
Ask what event is being measured and from what starting point. MFS begins at randomization and uses a specific radiographic-progression or death definition.
2. Identify the population
For the reported efficacy analyses, the population is ITT, preserving randomized treatment assignment.
3. Identify the effect measure
Time-to-event outcomes use hazard ratios, while the PSA-response analyses use differences in response rate.
4. Read the interval
The confidence interval provides information about statistical precision and should be read together with the point estimate.
5. Read the P-value in context
The P-value is part of a prespecified hypothesis-testing framework and does not itself quantify clinical effect size.
6. Check design complications
Multiplicity, censoring, crossover, and the assumptions of the Cox model all affect interpretation of time-to-event results.
22. Related Tutorials
Learn more about the methods used in this trial:
23. Related Calculators
24. Sources
- ClinicalTrials.gov: PROSPER — NCT02003924.
- PubMed: PMID 41894648.
- PubMed: PMID 40539499.
- PubMed: PMID 36756959.
- PubMed: PMID 36226865.
- PubMed: PMID 35731340.
Continue through the Clinical Biostats statistical pathway
Use the trial as a practical example of randomized treatment comparison, time-to-event analysis, hazard ratios, confidence intervals, categorical-data methods, and multiplicity.
25. Record Summary
PROSPER provides a compact but rich example of clinical-trial time-to-event statistics. The study was a randomized, parallel-group, quadruple-masked phase 3 trial with 1401 participants and a primary endpoint of metastasis-free survival. The primary analysis used the ITT population, a log-rank test, and a Cox-model hazard ratio. The reported MFS HR was 0.292, with a two-sided 95% CI of 0.241–0.352 and P<0.0001.
The secondary analyses demonstrate why endpoint-specific interpretation matters. Time to PSA progression, time to first use of new antineoplastic therapy, overall survival, time to pain progression, and time to first use of cytotoxic chemotherapy all use time-to-event methodology, while PSA-response outcomes use the Cochran-Mantel-Haenszel test and differences in response rate. The registry also describes a prespecified multiplicity strategy for key secondary testing and reports a crossover category among placebo patients.