A Study of the Effect of Enantone LP 11.25 mg (Leuprorelin) on the Histological Progression of Indolent Prostate Cancer: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study of the Effect of Enantone LP 11.25 mg (Leuprorelin) on the Histological Progression of Indolent Prostate Cancer (NCT02085252), a randomized phase 3 study. The primary outcome is Number of Participants With Negative Biopsies at Month 12.

2. Clinical Question

The clinical question concerns a short-term histological outcome, not every aspect of disease course or patient experience. A negative biopsy at the scheduled assessment is a biopsy finding at that time; it is not, by itself, a measure of long-term progression, symptoms, or quality of life. The registry also lists secondary outcomes relating to histology, urinary symptoms, imaging, PSA, anxiety and depression, and erectile function. Those outcomes address different dimensions of the study question and should not be treated as interchangeable with the primary biopsy result.

3. Trial Design

The registry describes a completed, randomized, open-label, parallel-group Phase III study sponsored by Takeda. Its official title describes it as multicenter. Enrollment was 116 participants. Random allocation helps make the treatment groups comparable on average at the outset, although it does not ensure that every measured or unmeasured characteristic is balanced in a particular trial. Because masking was absent, participants and study personnel knew the assigned strategy; the registry record does not report whether biopsy readers or other outcome assessors were masked.

The two strategies differed in whether participants received androgen deprivation. In the leuprorelin group, the strategy included one injection of leuprorelin 11.25 mg, bicalutamide 50 mg once daily for 15 days to prevent flare-up, and then active surveillance. The comparison group received active surveillance without androgen deprivation. Thus the comparison is between treatment strategies, rather than between leuprorelin and no monitoring.

The primary endpoint was assessed at month 12. The registry reports 53.0 participants in the leuprorelin group and 54.0 in the active-surveillance group for that primary outcome. Its stated analysis population included randomized participants who signed informed consent, but excluded those with missing biopsy results. The record does not report the original sample-size justification, the intended recruitment target beyond the recorded enrollment, or the statistical plan for handling missing biopsy data.

Randomization and the parallel-group design support a between-group comparison, while the open-label structure and biopsy-based endpoint remain important context for interpreting the result. The registry record does not report further details of the randomization procedure, allocation concealment, masking of assessors, or any interim analyses.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: Participants with a diagnosis of Prostate Cancer were randomised equally to one of two arms: leuprorelin 11.25 mg or active surveillance. 116 participants were randomized but 1 patient was excluded due to absence of prostate cancer before treatment.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full Analysis Set included all participants with prostate cancer who signed informed consent and were randomised. Participants with missing biopsy results have been excluded from the analysis.

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

Population: Full Analysis Set included all participants with prostate cancer who signed informed consent and were randomised.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With Negative Biopsies at Month 12, measured over Month 12.

The primary endpoint counted participants with negative biopsies at month 12. The registry describes a staging biopsy sampling at least 12 cores, analyzed through a centralized biopsy procedure intended to confirm the first biopsy findings. The stated criteria included the presence of positive cores, the absence of a core with tumor length greater than 3 millimeters, and the absence of Grade 4 cells, with a Gleason score below 7. The Gleason score grades prostate cancer tissue according to its appearance under a microscope; higher scores indicate tissue more likely to spread.

This endpoint is used to compare histological findings at a defined follow-up time. A count of participants meeting the biopsy definition gives a clinically interpretable summary of how often that particular finding occurred in each group. It does not describe the full range of disease changes or how participants felt, and it is not a time-to-event measure. The registry lists other outcomes, including Gleason score of at least 7 and imaging measures, which capture related but distinct information.

Interpretation depends on the biopsy procedure and the definition of a negative result. Centralized analysis can support consistency in how samples are assessed, but the registry record does not report further operational details of the central review or whether the reviewers were masked to assigned group. Missing biopsy results were excluded from the primary analysis population; the record does not report additional missing-data methods.

7. Results Posted in the Registry

• Active Surveillance: 31.5% (17/54) versus 52.8% (28/53) on control; risk difference -21.3 percentage points (95% CI -39.6 to -3.1), risk ratio 0.60 (0.37–0.95); unadjusted two-proportion z-test p = 0.025.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Number of Participants With Gleason Score ≥ 7

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Active Surveillance: 8.8% (3/34) versus 3.8% (1/26) on control; risk difference 5.0 percentage points (95% CI -7.1 to 17.0), risk ratio 2.29 (0.25–20.80); unadjusted two-proportion z-test p = 0.444.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Active Surveillance and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover several domains: histology, urinary symptoms, prostate imaging, PSA, anxiety and depression, and erectile function. Those outcomes can add context to a biopsy-based primary endpoint, but they measure different things and may change in different directions. A collection of secondary outcomes should therefore be read as a broader set of exploratory or supporting evidence, not as a single composite confirmation of the primary finding.

The registry includes a detailed result for the secondary count of participants with Gleason score of at least 7. The posted comparison is imprecise, with its reported risk-difference interval spanning the null, and its unadjusted p-value is 0.444. This is not a precise estimate of a between-group difference. The record does not report results for the other secondary outcomes in the available result details, so the overall pattern across all secondary endpoints cannot be established from the registry record.

Secondary outcomes generally carry less weight than the primary outcome when many outcomes are examined. Looking at multiple results increases the chance that some may appear notable by chance, particularly when no adjustment or prespecified hierarchy is reported. The registry record does not report a multiplicity strategy or the complete analysis plan. The secondary findings should therefore be interpreted cautiously and should not be used alone to overturn or extend the primary result.

Different follow-up measures also have different measurement properties and missing-data risks. A biopsy count, an imaging measurement, a symptom score, and a questionnaire score cannot be compared as if they were all the same kind of endpoint. The registry record's outcome list shows the intended breadth of assessment, but the limited posted result detail prevents a comprehensive assessment of consistency across those domains.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Number of Participants With Gleason Score ≥ 7
• Change From Baseline in the International Prostate Symptom Score (I-PSS) Total Symptom (S) Score
• Prostatic Volume as a Measure of Tumor Radiologic Progression Using Dynamic Magnetic Resonance Imaging (MRI)
• Highest Diameter of the Lesion as a Measure of Tumor Radiologic Progression Using Dynamic MRI
• Change From Baseline in Prostate-specific Antigen (PSA) Levels
• Change From Baseline in Hospital Anxiety and Depression Scale (HADS) Score
• Change From Baseline in the International Index of Erectile Function (IIEF-5) Questionnaire Score

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is a binary participant count: the registry records whether each analyzed participant had a negative biopsy at month 12. For a binary endpoint, the group count and the number assessed together describe the observed event proportion. The posted summaries include 28.0 negative biopsies among 53.0 participants in the leuprorelin group and 17.0 among 54.0 participants in the active-surveillance group. The comparison is based on these group summaries, not on continuous measurements or event times.

What does the risk difference describe?

A risk difference subtracts one group's event proportion from the other's. In this comparison, the active-surveillance group is contrasted with the leuprorelin group. A negative value therefore points toward a lower observed proportion with negative biopsies in the active-surveillance group. The recalculated unadjusted risk difference is negative, and its reported interval is also entirely on the negative side of the null difference. The precise interval level is not reported in the registry record.

The risk difference is an absolute-scale measure. It describes how far apart the two observed probabilities are, rather than how many times one probability is the other. Absolute measures can be easier to relate to the event frequency in the study, but their values depend on the population, endpoint definition, follow-up time, and analysis set. The risk difference is unadjusted: it is calculated from the posted group-level counts and does not account for covariates.

How do relative measures differ?

The relative risk compares the event probability in one group with the probability in the other. The odds ratio compares event odds rather than probabilities. Both are relative measures, and neither should be read as an absolute difference. When an outcome is not rare, an odds ratio can look more extreme than a risk ratio; this is a general statistical property, not a separate finding about this trial. These measures also require the reference group to be kept clear. The registry comparison is active surveillance relative to leuprorelin.

Relative and absolute measures can complement one another. A relative measure can describe proportional contrast, while the risk difference conveys the change on an absolute scale. Neither measure corrects for bias or replaces examination of the endpoint definition, analysis population, or missing data. The recalculated measures are unadjusted summaries of the posted results.

What does the p-value test?

The simple recalculation reports an unadjusted p-value of 0.025. In general, a p-value describes how incompatible the observed data are with a specified null model, under the assumptions of the test. It is not the probability that the null model is true, the chance that the result occurred randomly, or a measure of clinical importance. The registry also reports a Chi-squared analysis and its own p-value. A Chi-squared test evaluates association between group and a categorical outcome; the exact implementation and any additional analysis details are not reported in the registry record.

The two p-values are not identical. Their difference should not be resolved by guessing which implementation or assumption caused it. The registry record does not report enough detail to identify the reason. The simple recalculation is useful as a transparent, unadjusted check of the posted counts, while the Chi-squared result is the sponsor's reported analysis.

Why can over-dispersion matter?

Over-dispersion is a general issue in count or probability models when the data vary more than a model assumes. If present and ignored, uncertainty estimates can be too narrow and tests can be too optimistic. The primary endpoint is a binary participant outcome, and the registry reports a Chi-squared analysis rather than a model specification that permits assessment of over-dispersion. Whether over-dispersion was considered in any other analyses is not reported in the registry record. It would not be appropriate to assume that a particular adjustment was or was not needed based only on the posted summary.

More broadly, a statistical method is only one part of the interpretation. Random allocation, missing outcomes, masking, endpoint ascertainment, and the number of analyses all affect how strongly a result can be interpreted. The record identifies the randomized, open-label, parallel design and the primary analysis population, but does not report the full statistical analysis plan, details of any interim analyses, adjustment for multiple comparisons, or the original sample-size justification. Those omissions limit what can be inferred about prespecification and the handling of the wider outcome set.

11. Confidence Intervals and Precision

The confidence interval for the primary risk difference is entirely negative. In practical statistical terms, the range of values compatible with that interval points in the same direction as the observed contrast: the active-surveillance group had a lower observed proportion with negative biopsies than the leuprorelin group. The interval nevertheless covers a range of possible magnitudes, so the point estimate should not be treated as an exact description of the underlying difference.

A confidence interval is a range of estimates produced by a method that, under its assumptions and repeated use, has a stated coverage property. It conveys uncertainty about an estimated effect; it does not give the range of individual participant outcomes and does not mean that a particular value has a specified probability of being true. The registry record does not report the confidence level for the posted intervals, so no level should be attached to them by assumption.

Precision is affected by the amount of information available and by the variability of the outcome. Here the primary analysis included 53.0 and 54.0 participants in the two groups, respectively, and the interval remains broad enough to leave substantial uncertainty about the absolute difference's magnitude. The result is more informative about the direction of the observed contrast than it is about its exact size. A statistically detectable contrast does not automatically imply a clinically important one.

Relative measures have their own intervals and can be harder to interpret when event numbers are limited. For the secondary Gleason outcome, the reported risk-difference interval includes values on either side of the null, reflecting uncertainty in that comparison. The secondary endpoint also has fewer participants assessed than the primary outcome. These distinct intervals should not be treated as interchangeable or as direct confirmation of the primary result.

Confidence intervals complement p-values by showing a range of effect estimates compatible with the data and analysis. Their interpretation still depends on the method, analysis population, and assumptions. The registry record does not report further interval-construction details or sensitivity analyses for missing biopsies.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The sample-size illustrations are planning calculations, not observed trial results. They use a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect to detect is set at 100%, 75%, or 50% of the observed effect. For these binary outcomes, the entries are participants per arm, not total events. The registry record does not report the assumptions used to plan the original trial, so these illustrations should not be mistaken for its original design calculation.

For the primary outcome, planning for 100% of the observed effect corresponds to 83 participants per arm for 80% power and 111 participants per arm for 90% power. Planning for 75% of the observed effect corresponds to 151 participants per arm for 80% power and 201 participants per arm for 90% power. Planning for 50% of the observed effect corresponds to 343 participants per arm for 80% power and 458 participants per arm for 90% power.

The 80% power column describes the number of participants per arm the illustration estimates would be needed to detect the specified effect under its assumptions with 80% power. The 90% power column gives the corresponding planning number for 90% power. Power is a design property under an assumed effect and analysis, not a probability that a result is true. These values are not observed power.

Smaller effects require more participants because they are harder to distinguish from random variation. The calculations use a fraction of the observed effect, so they illustrate how sample-size needs change under those assumed effect sizes. They do not establish that the observed effect will recur in another study, nor do they account for differences in outcome definitions, missing data, or analysis methods beyond the stated assumptions.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.528; treatment proportion p₁ = 0.315; average p̄ = 0.422.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6984 = 1.3687.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6818 = 0.5739.
4. n = (1.3687 + 0.5739)² / (-0.2135)² = 82.8, rounded up to 83 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.528301886792453                          # control proportion
p1 <- 0.314814814814815                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(2085252)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 83 (80% power), 111 (90% power)
 75% of observed effect: n per arm = 151 (80% power), 201 (90% power)
 50% of observed effect: n per arm = 343 (80% power), 458 (90% power)
power.prop.test: 82.8 
Simulated power at n = 83 per arm: 0.803 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The registry reports a Chi-squared analysis for the primary comparison, with its own p-value. A simple recalculation from the posted group counts gives an unadjusted p-value of 0.025. The reported and recalculated p-values differ. The registry record does not explain the reason, so no particular analytical choice or data-handling step should be assumed to account for that difference.

The recalculation is a straightforward unadjusted comparison of the posted binary summaries. It is not a reconstruction of the full trial analysis plan, and it does not add covariate adjustment or other methods not reported in the record. The sponsor's result is the trial's posted analysis; the recalculation is a separate check based on the displayed counts. Readers should keep those roles distinct and consider the uncertainty around the effect estimate as well as either p-value.

The record does not report the complete specification of the sponsor's Chi-squared test, the statistical analysis plan, or whether other analyses were prespecified. Consequently, the available information supports noting the difference between the two p-values, but not attributing it to a specific choice. Neither value alone measures clinical importance or resolves the limitations related to the open-label design, missing biopsies, or multiple outcomes.

15. Multiplicity, Missing Data and Analysis Populations

The study includes a primary endpoint and multiple secondary outcomes. When several outcomes are tested, the chance of obtaining one or more small p-values by chance can increase. General approaches to this issue include prespecifying a primary testing hierarchy or adjusting statistical thresholds across a family of tests. The registry record does not report whether such a strategy was used, whether secondary outcomes were treated as confirmatory or exploratory, or whether the analysis plan specified an order for interpreting them. The primary result is therefore best distinguished from the broader set of secondary comparisons rather than treating all results as equally confirmatory.

For the primary endpoint, the stated Full Analysis Set included participants with prostate cancer who signed informed consent and were randomized. Participants with missing biopsy results were excluded from the analysis. Excluding participants with missing outcomes can affect a comparison if missingness is related to assigned group or to the unobserved biopsy result. The registry record does not report how many biopsy results were missing, the reasons for missingness, or sensitivity analyses assessing its effect. The record also does not report imputation or other missing-data methods.

The primary groups have 53.0 and 54.0 participants in the posted analysis, while adverse-event summaries use different at-risk counts. Those differing analysis sets should not be conflated. The registry record does not provide enough detail to reconstruct participant flow from randomization through each endpoint, or to explain the different denominators.

Although the study is randomized, the registry does not report details of allocation concealment, the randomization procedure, or whether outcome assessors were masked. The open-label design is reported. For a biopsy endpoint, centralized assessment is described, but assessor masking is not reported in the registry record. The original sample-size justification and interim-analysis plan are also not reported. These gaps constrain assessment of prespecification, missing-data impact, and the full analytical context.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: erysipelas (1.8%), urinary tract disorder (1.8%), pancreatic neoplasm (1.8%), atrial flutter (1.7%), fatigue (1.7%).

The safety summaries report serious adverse events in 4 of 58 participants at risk in the leuprorelin group and 3 of 57 at risk in the active-surveillance group. Other adverse events were reported for 40 of 58 and 11 of 57 participants at risk, respectively. These are counts of participants affected within the registry's stated at-risk groups; the denominators differ from those in the primary biopsy analysis. They should not be used as substitutes for the primary outcome populations.

The listed serious adverse-event terms include erysipelas, urinary tract disorder, and pancreatic neoplasm, each reported at 1.8%, and atrial flutter, fatigue, and dizziness, each at 1.7%. These percentages are the registry's reported values; the record does not give event counts for each term in this summary. The number of deaths is not reported in the registry record.

Adverse-event summaries describe events recorded during the study, but do not by themselves establish that an event was caused by an assigned strategy. Interpretation depends on definitions, follow-up duration, collection procedures, and the number of participants at risk. The registry record does not report those details here, nor does this summary establish comparative safety beyond the posted counts.

17. What the Result Does, and Does Not, Mean

The primary result describes the observed proportion of participants with negative biopsies at month 12 among those included in the analysis. More participants in the leuprorelin group than in the active-surveillance group had a negative biopsy in the posted counts. The recalculated unadjusted risk difference points in the same direction, and its interval is entirely on the negative side when expressed as active surveillance minus leuprorelin. This is a statement about the specified biopsy outcome and assessment time.

It does not establish what happened beyond month 12, whether differences persisted, or whether the groups differed in every aspect of cancer progression. It also does not describe symptoms, quality of life, imaging, PSA, or other outcomes unless those outcomes are separately reported. The record lists several such secondary endpoints, but most corresponding results are not reported in the registry record.

The study was randomized, which supports interpreting the group contrast as a comparison of assigned strategies, but the trial was open-label and the primary analysis excluded participants with missing biopsy results. The registry record does not report the number or reasons for missing biopsies or sensitivity analyses. Centralized biopsy procedures are described, but masking of biopsy assessors is not reported. These registry entries qualify how confidently the observed contrast can be generalized beyond the analyzed participants.

A p-value is not a measure of the probability that a strategy is beneficial, and a statistically detectable result does not automatically show that an effect is important to patients or durable. The confidence interval gives a range of effect estimates compatible with the analysis, but its confidence level is not reported in the registry record. Relative measures and absolute differences provide complementary descriptions, not independent confirmations.

The findings should therefore be read as evidence about one randomized comparison, one endpoint definition, and one follow-up assessment. The registry record alone does not establish long-term outcomes, overall clinical benefit, or the balance of all benefits and harms. It also does not support medical advice for an individual patient.

18. Why This Trial Matters Statistically

This trial illustrates why defining the estimand matters. The primary question is not simply whether prostate cancer changed, but how often participants met a specific negative-biopsy definition at month 12 under two assigned monitoring and treatment strategies. A result depends on the endpoint definition, assessment time, and the participants included in the analysis. Clear separation of those elements makes the comparison easier to interpret.

It also demonstrates the value of reporting both group counts and effect measures. Counts anchor the analysis in the observed data; an absolute risk difference describes the scale of the contrast; relative measures offer another perspective; and uncertainty intervals show that the estimated effect is not exact. P-values answer a narrower question and should not substitute for the effect estimate or its precision.

The registry record also highlights the practical importance of analysis populations and missing outcomes. The primary analysis excluded participants with missing biopsy results, but the number and reasons for missingness are not reported. A reader cannot assess how strongly that choice might affect the estimated comparison without further information. Similarly, an open-label design and unreported assessor masking matter when interpreting an outcome based on clinical assessment.

Finally, the multiple secondary outcomes illustrate the difference between a prespecified primary question and a wider set of supportive measures. A broad endpoint set can be valuable, but interpretation requires knowledge of the testing strategy and complete results. The record does not report a multiplicity plan or most secondary results, limiting claims about consistency across outcomes.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several trial-specific limitations shape interpretation. The study was open-label, and masking of biopsy assessors is not reported in the registry record. Centralized biopsy procedures are described, but centralization alone does not establish that assessment was blinded to assigned group. The primary endpoint depended on biopsy results, so details of assessment and missing samples matter.

Participants with missing biopsy results were excluded from the primary analysis. The registry record does not report how many results were missing, why they were missing, or whether sensitivity analyses were performed. The posted analysis therefore cannot show how robust the result is to alternative assumptions about missing outcomes. The primary analysis denominators are also different from the denominators used for adverse-event summaries, and the registry record does not explain the participant flow behind that difference.

The trial's original sample-size justification, full statistical analysis plan, multiplicity strategy, and interim-analysis plan are not reported in the registry record. The available sample-size illustrations are based on the observed effect and should not be confused with the original design assumptions. The sponsor's Chi-squared p-value differs from the simple unadjusted recalculation, and the registry record does not explain the difference.

The primary endpoint is a month-12 biopsy outcome, so it does not directly establish longer-term disease course. Although seven secondary outcomes are listed, the registry record does not report results for most of them in the available details. This restricts assessment of consistency across histological, imaging, symptom, and questionnaire outcomes. Finally, the registry's safety summary provides participant counts and selected event terms, but does not report deaths or enough detail to determine causality or fully characterize follow-up and event collection.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Study of the Effect of Enantone LP 11.25 mg (Leuprorelin) on the Histological Progression of Indolent Prostate Cancer — NCT02085252.
• Registry record last updated 2019-06-28; status last verified 2019-06.
• Results first posted 2019-04-16.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

NCT02085252 is a completed, randomized, open-label, parallel-group Phase III study sponsored by Takeda, described as multicenter in its official title. Enrollment was 116. It compared a leuprorelin-based strategy, including short-course bicalutamide and subsequent active surveillance, with active surveillance alone in participants with indolent, localized prostate cancer.

The primary endpoint was the number of participants with negative biopsies at month 12. The posted counts were 28.0 of 53.0 in the leuprorelin group and 17.0 of 54.0 in the active-surveillance group. The sponsor reported a Chi-squared analysis; a simple unadjusted recalculation gives a p-value of 0.025, and the two reported analyses differ.

Interpretation is limited by the open-label design, exclusion of participants with missing biopsy results, unreported missing-data sensitivity analyses, and limited secondary-outcome reporting. The registry record does not report the original sample-size justification, full analysis plan, or multiplicity strategy.