A Study of Silodosin 8 mg Daily for the Treatment of Nocturia in Men With Benign Prostatic Hyperplasia: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study of Silodosin 8 mg Daily for the Treatment of Nocturia in Men With Benign Prostatic Hyperplasia (NCT00793819), a randomized phase 2 study. The primary outcome is Change in Nocturia Episodes.

2. Clinical Question

3. Trial Design

The registry identifies this study as a randomized, double-blind, parallel-group Phase 2 trial comparing silodosin with placebo. Enrollment is recorded as 215. The record lists the trial status as completed, with the start in 2009-01 and primary completion in 2009-10. Watson Pharmaceuticals is listed as the sponsor.

The primary outcome was change in nocturia episodes, measured in episodes at 12 weeks. The record describes the outcome as a continuous measure summarized by its mean and standard deviation. The listed treatment arms are Silodosin 8mg and Placebo. The arm descriptions contain no additional details about the treatments or trial procedures.

The endpoint population note says that the number of participants for analysis was determined by Last Observation Carried Forward (LOCF). The posted outcome groups contain 112 participants for Silodosin 8mg and 97 for Placebo. These are the reported analysis-group sizes for the outcome; the registry record does not explain in detail how they relate to enrollment or describe participant flow, withdrawals, or missing observations.

Other design information, including the randomization method, allocation concealment, the original sample-size justification, and the trial's full statistical analysis plan, is not reported in the registry record. The registry lists one outcome measure and no posted analyses. Accordingly, the interpretation rests on the posted outcome summaries and comparison rather than on a fuller account of the prespecified analysis or trial conduct.

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.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The number of participants for analysis is determined by Last Observation Carried Forward (LOCF).

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.

6. Primary Endpoint

The registry lists the primary outcome as Change in Nocturia Episodes, measured over 12 weeks.

The primary endpoint is the change in the number of nocturia episodes, expressed in episodes and assessed over 12 weeks. Nocturia refers to nighttime urination in the trial description. A change score represents how the measured number of episodes differs from the relevant starting measurement; the registry does not provide further details about the specific baseline assessment or measurement procedures.

Because the outcome is a continuous measure, its group results are reported as means with standard deviations. The mean describes the average change in each group, while the standard deviation describes how much individual changes varied around that average. The posted mean changes were -1.2 episodes with silodosin and -1.0 episodes with placebo. Negative values indicate decreases in the measure as it was coded in the record; interpreting the clinical importance of a change also requires context about baseline values, measurement, and what difference would matter to patients, which is not reported in the registry record.

Comparing the group mean changes provides an estimate of the average difference between the assigned groups for this endpoint. It is useful because it retains the outcome's original unit, episodes, and can be interpreted alongside an interval describing uncertainty. A group average does not describe every participant's experience, and this endpoint alone does not summarize other outcomes or safety.

7. Results Posted in the Registry

• Silodosin 8mg: mean -1.20 versus -1.00 on control; difference -0.20 (95% CI -0.58 to 0.18), standardized effect d = -0.14; z-test p = 0.303.

8. Statistical Interpretation

9. Statistical Methods Explained

What does a mean difference represent?

General statistical explanation: A mean difference compares the average outcome in one group with the average outcome in another. Here, the outcome is change in nocturia episodes, and the registry reports a mean difference of -0.2 episodes for silodosin relative to placebo. A negative estimate means the silodosin group's average change was more negative than the placebo group's average change on the reported scale. It does not say that every participant had that change, and it does not account for individual variation by itself.

The group summaries also include standard deviations: 1.35 episodes for silodosin and 1.44 episodes for placebo. A standard deviation describes the spread of individual values around the group mean. It is not the uncertainty interval for the mean difference and should not be read as a range containing all participant outcomes. The registry does not provide individual-level observations, so the distributions and the presence of unusual values cannot be assessed from these summaries alone.

How should the unadjusted comparison be read?

General statistical explanation: An unadjusted comparison uses the groups' outcome summaries without adjustment for other measured factors in a model. The posted comparison gives a mean difference of -0.2 episodes, a confidence interval from approximately -0.58 to 0.18 episodes, and an unadjusted p-value of 0.303. The confidence interval describes a range of values that are reasonably compatible with the data under the method's assumptions. It indicates uncertainty about the estimated difference, not a range that contains a known fixed proportion of individual participant outcomes.

The p-value addresses compatibility between the observed data and a statistical model in which the groups have no mean difference. A larger p-value does not prove the groups are identical. A smaller p-value would not, by itself, show that a difference is large or important. The interval is especially useful because it displays both the estimated direction and the range of plausible differences. The registry record does not report a complete sponsor statistical analysis, and the record lists no posted analyses beyond the available comparison information.

What does randomization contribute?

General statistical explanation: Random assignment is intended to make treatment groups comparable, on average, with respect to both measured and unmeasured characteristics at allocation. This supports a causal comparison when the trial is conducted and analyzed appropriately. The registry labels allocation as randomized, but does not report the randomization sequence method, concealment procedures, adherence, or detailed participant flow. The label alone cannot answer those operational questions.

Double masking is also recorded. In general, masking can reduce the chance that knowledge of assigned treatment affects participant reports, care, or outcome assessment. The registry does not describe who was masked or how masking was maintained, so the extent and implementation cannot be evaluated from the record.

Why do variability and over-dispersion matter?

General statistical explanation: The outcome is a count-like measure summarized as a continuous change score. Counts can sometimes vary more than a simple model assumes, a feature called over-dispersion. When a model assumes less variability than the data actually have, standard errors may be too small and confidence intervals may be too narrow. Conversely, accounting for extra variability can widen uncertainty estimates. This is a general consideration for count outcomes, not a finding that over-dispersion occurred in this trial. The registry record does not report a count model, a distributional assessment, or an over-dispersion analysis. Since the posted endpoint is analyzed as a mean change with standard deviations, the available summaries do not permit a separate evaluation of those modeling choices.

How does LOCF affect interpretation?

General statistical explanation: Last Observation Carried Forward fills a missing follow-up value by using that participant's most recently observed value. It is one way to create an analysis dataset when follow-up measurements are missing. Its assumptions can be consequential: carrying a past value forward treats that value as an appropriate stand-in for the missing measurement and does not fully represent uncertainty about what happened after the last observation. If outcomes would have changed after dropout, LOCF may misrepresent the unobserved values. The registry notes LOCF for determining the number of participants in the primary outcome analysis but does not report how much data were missing, why they were missing, or sensitivity analyses using alternative assumptions.

The comparison should therefore be understood as an estimate from the posted LOCF-based outcome population, rather than as a result shown to be robust across missing-data methods. No adjustment for baseline measurements or other covariates is described in the registry record. The record also does not report whether any interim analyses or other statistical procedures were used. Those details cannot be inferred from the posted means, standard deviations, confidence interval, or p-value.

10. Confidence Intervals and Precision

The mean difference is -0.2 episodes, with a confidence interval reported from -0.580 to 0.180 episodes. Rounded to no more than three decimal places, the bounds are approximately -0.580 and 0.180 episodes. The interval includes zero, so the posted result is compatible with no difference in mean change. It also includes negative values and positive values, leaving uncertainty about which group had the larger average decrease in the population represented by the analysis.

General statistical explanation: A confidence interval communicates the precision of an estimate under the method's assumptions. A narrower interval indicates a more precise estimate; a wider interval leaves more uncertainty about the magnitude and direction. The interval is not a guarantee that the true value lies inside it, and its interpretation depends on the statistical method and assumptions used.

The interval's span relative to the point estimate matters: the point estimate is not precise enough to settle whether the average difference is meaningfully negative, near zero, or modestly positive. The registry does not report a threshold for a clinically important difference, so statistical precision cannot be translated into a judgment about clinical importance. The standard deviations of 1.35 and 1.44 episodes describe spread among observed changes, whereas the confidence interval describes uncertainty in the between-group estimate; these quantities answer different questions.

The interval should also be interpreted in light of the LOCF analysis note and the absence of a reported missing-data sensitivity analysis. It is an interval for the posted comparison under its analysis assumptions, not a guarantee that alternative approaches would yield the same precision or estimate.

11. 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 entries are planning illustrations based on the observed effect, not a reconstruction of the trial's original design. They give participants per arm, not total events. The stated assumptions are two-sided significance level 0.05, equal allocation between the two arms, and a normal approximation; the effect to detect is the stated fraction of the observed effect. The trial's original sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm for a design that would have an 80% chance of detecting the specified effect under the planning assumptions, if that effect and assumptions were correct. The 90% power column gives the corresponding planning number for a 90% chance. Power is a property of a planned study under specified assumptions; it is not a measure of the probability that the observed result is true.

The entries use 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. For example, planning for 75% of the observed effect gives 1,353 participants per arm for 80% power and 1,811 participants per arm for 90% power. Planning for 50% of the observed effect gives 3,044 participants per arm for 80% power and 4,075 participants per arm for 90% power. Smaller effects require more participants to detect under the same assumptions, because they are harder to distinguish from random variation. These figures are planning illustrations, not observed power.

The sample-size curve should be read as a visual representation of how the illustrative requirement changes with the effect being targeted and the planning assumptions. It is not a prediction of what a future study will achieve. The estimates depend on the observed effect, which itself is uncertain, and on the stated normal-approximation and allocation assumptions. They do not account for design features or analysis choices that are not described in the registry record.

12. 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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.200; pooled standard deviation σ = 1.392.
2. n = 2 × (1.96 + 0.842)² × 1.392² / -0.200² = 760.9, rounded up to 761 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
delta <- -0.2                      # observed difference in means
sigma <- 1.39246262926983                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^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 (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(793819)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 761 (80% power), 1,019 (90% power)
 75% of observed effect: n per arm = 1,353 (80% power), 1,811 (90% power)
 50% of observed effect: n per arm = 3,044 (80% power), 4,075 (90% power)
power.t.test: 761.9 
Simulated power at n = 761 per arm: 0.798 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-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.

13. Multiplicity, Missing Data and Analysis Populations

The registry lists one outcome measure, the primary change in nocturia episodes, and no secondary outcomes. The record lists no posted analyses. It does not report a statistical analysis plan, a hierarchy of endpoints, or a procedure for controlling multiplicity. As a result, the record does not establish whether other outcomes or analyses were prespecified but not posted. There is not enough information to evaluate selective outcome reporting or the role of multiple testing.

The unadjusted p-value of 0.303 is the reported probability measure for the posted comparison. Since the registry does not describe a multiplicity adjustment, it should be treated as unadjusted, not as a value corrected for multiple comparisons. The record also does not specify an alpha threshold for the trial's primary analysis. The planning illustration separately states a two-sided significance level of 0.05, but this is an assumption for those sample-size calculations and is not evidence of the trial's original analysis plan.

The primary outcome population note specifies Last Observation Carried Forward (LOCF). This indicates that the analysis population was determined using that approach, but the record does not give the number or reasons for missing observations, how much follow-up data were carried forward, or how participants were handled in other analyses. It also does not report sensitivity analyses, such as comparisons under alternative missing-data assumptions. Missingness may affect both the estimated mean changes and their uncertainty, so the posted comparison should be interpreted in the context of this limited description.

Further information about analysis populations is not reported in the registry record. It does not specify whether results were analyzed by randomized assignment, treatment received, or another population definition beyond the LOCF note. Nor does it describe protocol deviations or adherence. These omissions limit assessment of how closely the posted outcome analysis follows the randomized comparison and whether findings are robust to different analytic choices.

14. 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 2% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: multiple bone fracture (1.0%), cellulitis (0.9%).

The serious adverse event figures are reported with at-risk denominators: 111 for Silodosin 8mg and 98 for Placebo. One serious adverse event is reported as affecting participants in each group. The record lists “Multiple Bone Fracture” and “Cellulitis” among the top serious-event terms, with reported percentages of 1.0% and 0.9%, respectively. The posted record does not identify which group corresponds to each term, so those terms should not be assigned to an arm based on these figures alone.

For other adverse events, the at-risk denominators are 111 for Silodosin 8mg and 98 for Placebo; the reported affected counts are 39 and 21, respectively. These counts are descriptive and are not a causal comparison. They do not indicate severity, duration, or whether events were judged related to treatment. The registry record does not report death counts, so deaths should not be interpreted as absent. Nor does the record provide enough detail to assess event definitions, exposure time, or statistical comparisons. Safety figures should be read alongside the trial's size, follow-up, and reporting limits rather than as a complete account of risks.

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

The primary result is an estimated mean difference of -0.2 episodes in change over 12 weeks, comparing silodosin 8 mg with placebo. The confidence interval, approximately -0.580 to 0.180 episodes, includes zero and extends in both directions. The unadjusted p-value is 0.303. Together, these figures indicate substantial uncertainty about the direction and size of the average difference; they do not establish that the groups are identical or that a particular effect is present.

The result is specific to the registered population, intervention, placebo comparison, endpoint, and follow-up. It does not answer whether effects differ in subgroups, persist beyond 12 weeks, or apply to other populations or treatment regimens. The registry record does not report secondary outcome results, baseline values, a clinically important difference threshold, or detailed missing-data sensitivity analyses. Those gaps prevent broader conclusions about symptom experience or clinical importance.

The posted outcome summaries are based on the analysis population determined by LOCF. Since the amount and pattern of missing data are not reported, the robustness of the estimate to missing-data assumptions cannot be evaluated. The registry also does not describe a full statistical analysis plan or all trial procedures, which limits assessment of analysis choices and implementation.

The safety record reports serious adverse event counts and other adverse event counts, but does not provide enough context to determine the nature, timing, or treatment relationship of all events. The presence of a small number of recorded events should not be taken as a complete safety assessment. Overall, the statistical result is best viewed as an uncertain estimate from a Phase 2 trial rather than a standalone determination of treatment benefit, lack of benefit, or overall safety.

16. Why This Trial Matters Statistically

This trial illustrates why an estimated effect, its uncertainty, and the analysis context need to be considered together. The mean difference of -0.2 episodes gives a direct estimate on the endpoint's original scale. The confidence interval spans negative and positive values and includes zero, showing that the data do not precisely distinguish a difference in either direction from no mean difference. The unadjusted p-value alone would not convey that range of uncertainty.

It also demonstrates the distinction between variability among participants and precision of a group comparison. The reported standard deviations describe the spread of changes within each arm, while the confidence interval describes uncertainty about the difference between arm means. These are related but not interchangeable summaries. Readers can use the estimate and interval to understand what the observed data support without treating a threshold-based test as the only relevant result.

The LOCF note is another important statistical detail. A stated missing-data method can materially shape an estimate, and reporting the method without describing the amount or pattern of missingness leaves important questions unanswered. Likewise, the absence of a fuller analysis plan and posted secondary results limits evaluation of multiplicity and prespecification.

Finally, the sample-size illustrations emphasize that smaller target effects require larger planned samples under the same assumptions. Their role is prospective planning, not a retrospective judgment of the trial's quality or a measure of observed power. Overall, the record provides a useful example of how to interpret a continuous endpoint, a confidence interval that includes zero, and planning calculations while keeping the limitations of registry reporting in view.

17. 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.

The registry record gives limited detail about eligibility criteria, baseline symptom levels, outcome measurement procedures, and participant flow. It reports enrollment and outcome analysis-group sizes, but does not explain withdrawals or missing observations. This limits assessment of how representative the analyzed population was of all enrolled participants.

The primary endpoint is a change score, but the record does not describe the precise baseline assessment or any threshold for a meaningful change. The clinical significance of the estimated difference therefore cannot be determined from the posted endpoint summaries alone. The result is also limited to the 12-week timeframe; longer-term outcomes are not reported.

LOCF is identified for determining the number of participants for analysis, but the extent and reasons for missingness are not reported. No alternative missing-data analyses are described. The randomized, double-blind labels are recorded, but details of sequence generation, allocation concealment, masking implementation, adherence, and protocol deviations are not reported. The registry also does not provide a complete statistical analysis plan, covariate-adjusted results, interim-analysis information, or a sample-size justification for the original trial.

Only one outcome measure and no analyses are listed in the registry record, limiting assessment of other prespecified endpoints or selective reporting. The posted safety counts are not accompanied by detailed definitions, event timing, treatment attribution, or exposure-adjusted comparisons. These omissions mean that the available record supports a focused reading of the reported mean changes and comparison, not a comprehensive assessment of all efficacy, safety, or trial-conduct questions.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: A Study of Silodosin 8 mg Daily for the Treatment of Nocturia in Men With Benign Prostatic Hyperplasia — NCT00793819.
• Registry record last updated 2012-03-09; status last verified 2012-02.
• Results first posted 2012-03-09.
• 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.

21. Record Summary

NCT00793819 is a completed, randomized, double-blind, parallel-group Phase 2 study sponsored by Watson Pharmaceuticals. It compared silodosin 8 mg daily with placebo in men with benign prostatic hyperplasia and nocturia. The registry reports enrollment of 215 and a primary endpoint of change in nocturia episodes over 12 weeks.

Mean changes were -1.2 episodes with silodosin and -1.0 episodes with placebo. The reported mean difference was -0.2 episodes, with a confidence interval approximately from -0.580 to 0.180 and an unadjusted p-value of 0.303. The endpoint analysis population was determined using LOCF. The registry record does not report a full analysis plan, detailed missing-data information, or secondary outcome analyses.