Bladder Scan of Residual Urine With New Catheter: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Bladder Scan of Residual Urine With New Catheter (NCT01048541), a randomized phase 2, phase 3 study. The primary outcome is Mean Residual Urine Volume.

2. Clinical Question

3. Trial Design

This was a randomized, triple-masked, crossover study listed in the registry as phase 2 and phase 3. It enrolled 37 participants and is marked completed. The record lists the study start as 2010-01 and primary completion as 2010-06. Coloplast A/S is listed as the sponsor.

The crossover model means the study is recorded as comparing the catheter conditions within a crossover design, rather than as a conventional parallel-group trial in which each participant remains in one treatment group. The record names the test catheter as SpeediCath Compact Male and the standard comparator as SpeediCath. It describes the primary measurement as residual urine volume after catheterisation, assessed by ultrasound.

The posted outcome summaries report 36 participants for the test catheter and 36 for the standard catheter. Those are the summary counts for the two catheter conditions; they should not be read as a new total enrollment figure. The registry record does not explain the relationship between these outcome counts and the enrollment of 37, nor does it report the order in which participants used the catheters, any washout period, or the handling of possible period or sequence effects.

Although the title identifies the study as a non-inferiority investigation, the registry record does not report the non-inferiority margin, the original sample-size justification, or a complete statistical analysis plan. It also has no posted analysis entries. These absences limit what can be concluded about whether the planned design and analysis were carried out as intended. The results below should therefore be read as a description of the registry’s posted summaries and an unadjusted comparison, not as a reconstruction of an undocumented protocol.

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:

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 Mean Residual Urine Volume, measured over 3 catheterisations on 1 day.

The primary endpoint was mean residual urine volume, measured in mL. According to the registry description, ultrasound was used to measure bladder content after intermittent catheterisation. The specified timeframe was 3 catheterisations on 1 day. The summary reports a mean and standard deviation for each catheter condition.

Residual urine is a direct measure of how much urine remains in the bladder after catheterisation. It is used to assess the study’s stated question about bladder emptying with the new, shorter catheter compared with a standard-length catheter. The endpoint is continuous: individual measurements can take a range of values rather than being only a yes-or-no outcome. The reported mean describes the group’s average residual volume, while the standard deviation describes the spread of measurements around that average.

The registry record does not specify whether the reported value for each participant was an average across the 3 catheterisations, a summary of individual measurements, or another aggregation. It also does not report details such as the timing of ultrasound readings or how measurements were processed. Those details matter for interpreting the exact measurement procedure, but they do not change the basic meaning of the posted endpoint: residual urine volume after catheterisation, assessed by ultrasound.

7. Results Posted in the Registry

• Test Catheter: mean 12.40 versus 9.40 on control; difference 3.00 (95% CI -3.34 to 9.34), standardized effect d = 0.22; z-test p = 0.354.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary endpoint is a continuous measurement: residual urine volume in mL. For a continuous endpoint, a group mean summarizes the average observed value, while the standard deviation describes the spread of observations around that mean. In this record, the test-catheter mean is 12.4 mL with a standard deviation of 15.7 mL, and the standard-catheter mean is 9.4 mL with a standard deviation of 11.4 mL. These summaries are descriptive; they do not reveal the shape of the distribution or the values for individual participants.

What does the mean difference describe?

The posted comparison gives a mean difference of 3.0 mL, with the test catheter as the first condition and the standard catheter as the reference. A difference of zero would mean equal means under this summary measure. Positive values indicate a larger test-catheter mean, while negative values indicate a smaller test-catheter mean. The estimated difference is a summary of the observed means, not a measure of the difference for every participant.

The comparison is an unadjusted recalculation from posted summary statistics. The registry lists a crossover model, so each participant may contribute information under both catheter conditions. In general, a crossover analysis can use the pairing of measurements within a participant. That pairing can affect the uncertainty of the treatment contrast. The posted summary comparison does not provide a participant-level paired analysis, and the registry record does not report the trial’s own analysis. Consequently, the displayed unadjusted calculation should not be assumed to account for the crossover structure, period effects, or sequence effects.

How should the p-value be understood?

The unadjusted p-value is 0.354. In general, a p-value describes how unusual data at least as discrepant as those observed would be under a specified statistical model in which the reference hypothesis holds. It is not the probability that the devices have the same effect, and it does not measure clinical importance. Its interpretation also depends on the analysis model. Here, the registry record does not report an analysis plan or a sponsor analysis, so the p-value should be read as part of the unadjusted summary comparison rather than as the result of a documented crossover model.

A p-value above a conventional significance threshold does not establish equality. The estimate and its interval are also important: the interval runs from -3.338 to 9.338 mL, so values on either side of zero remain compatible with the posted comparison. This is one reason it is more informative to discuss the estimated difference and its uncertainty together than to focus on the p-value alone.

Why does the crossover design matter?

In general, crossover trials compare conditions within participants, which can help account for stable differences between people. The validity and precision of that comparison can depend on the relationship between a participant’s measurements under the different conditions, as well as on period and sequence effects. The registry record identifies a crossover model but does not report catheter order, washout procedures, or the analysis used to address these considerations. Without those details or participant-level results, the displayed group summaries cannot show how the within-participant information affected the estimate.

The record lists 36 participants in each catheter summary, while enrollment is 37. These entries describe different aspects of the registry record: enrollment and outcome-summary counts. The record does not explain the difference. It also does not report an analysis population such as intention-to-treat or per-protocol, or how missing measurements were handled.

What does non-inferiority require?

In general, a non-inferiority study asks whether the data rule out a loss greater than a prespecified acceptable margin. The margin must be defined before interpreting the results, and the analysis must estimate the treatment contrast with appropriate attention to its uncertainty and design. A failure to find a statistically significant difference in an ordinary difference test is not the same as demonstrating non-inferiority. The registry title says non-inferiority, but the margin, analysis plan, and sponsor’s analysis are not reported in the registry record. The posted unadjusted comparison therefore does not answer the formal non-inferiority question.

Why can variation and over-dispersion matter?

In general, greater variability makes a mean less precise when the number of observations is held constant. If the data are more dispersed than an analysis model assumes, standard errors and p-values based on that model may not accurately represent uncertainty; this is often described as over-dispersion relative to the model. The record gives standard deviations but does not report a distributional assessment or model diagnostics. The summaries alone are not enough to determine whether over-dispersion occurred. This is a general statistical consideration, not a claim that the trial data had a particular distribution.

Overall, the available registry results support a descriptive comparison of the posted means and an unadjusted estimate. They do not document the complete analysis needed to assess a crossover non-inferiority trial. The missing statistical details should remain explicit rather than being filled in by assumptions.

10. Confidence Intervals and Precision

The interval reported with the unadjusted mean difference extends from -3.338 to 9.338 mL around an estimate of 3.0 mL. A confidence interval is a range of values that, under its statistical method and assumptions, expresses uncertainty about an estimated quantity. It is not a range containing every participant’s measurement, and it does not show the distribution of individual residual urine volumes.

Because the interval includes zero and values on both sides of zero, the posted summaries do not pin down whether the average residual volume was lower or higher with the test catheter. The interval also includes differences that are not close to the point estimate. This indicates limited precision for the unadjusted contrast. The interval’s endpoints should be interpreted in light of the calculation used; the registry record does not report the trial’s own analysis or an interval from a crossover model.

Precision is different from statistical significance and from clinical importance. A narrow interval can be precise without showing a clinically meaningful effect, while a wide interval can leave important possibilities unresolved. The registry record does not report a threshold for clinical importance or a non-inferiority margin, so the interval cannot be judged against either criterion.

The standard deviations, 15.7 mL and 11.4 mL, also indicate spread in the posted measurements. They are not uncertainty intervals for the means. The outcome summaries do not provide participant-level values, the correlation between paired measurements, or distribution details. Those omissions limit a fuller assessment of precision in this crossover study.

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 table and curve are planning illustrations based on the observed effect, not a report of the trial’s original design calculation. The table gives participants per arm for 80% power and participants per arm for 90% power. These are not total event counts: the record’s planning assumptions specify equal allocation between two arms, and the entries are participants per arm.

The planning assumptions listed are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set at the stated fraction of the observed effect. The displayed rows consider planning for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. For 80% power, The table shows 329, 584, and 1,314 participants per arm across those rows. For 90% power, it lists 440, 782, and 1,759 participants per arm.

In plain language, the 80% power column describes the planned number per arm under which the calculation would have an 80% chance of detecting the specified effect, if the stated assumptions and model held. The 90% column describes the corresponding planning target for a 90% chance. These are design probabilities under assumptions, not guarantees about what a particular study will detect. Smaller effects require more participants because they are harder to distinguish from random variation.

This is not observed power. The table does not show what power the completed trial achieved, and it does not establish the original sample-size rationale. The registry record does not report the trial’s own sample-size assumptions or justification. The planning figures should therefore be used to understand the scale of a hypothetical design based on the posted effect, not as a verdict on the completed study.

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 = 3.000; pooled standard deviation σ = 13.720.
2. n = 2 × (1.96 + 0.842)² × 13.720² / 3.000² = 328.3, rounded up to 329 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 <- 3                      # observed difference in means
sigma <- 13.7195116531165                     # 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(1048541)
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 = 329 (80% power), 440 (90% power)
 75% of observed effect: n per arm = 584 (80% power), 782 (90% power)
 50% of observed effect: n per arm = 1,314 (80% power), 1,759 (90% power)
power.t.test: 329.3 
Simulated power at n = 329 per arm: 0.802 (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 record lists 3 outcome measures in total and identifies 2 secondary outcomes: the difference in incidence of adverse events and adverse device events, and median absolute residual urine volume. It does not provide a full set of endpoint definitions and analysis results for those outcomes in the record. The primary endpoint is mean residual urine volume. The registry lists no analysis entries.

When a study evaluates multiple outcomes or makes multiple comparisons, the chance of at least one apparently unusual result can increase. In general, a multiplicity plan may specify which outcomes are primary, how comparisons are ordered, or whether statistical tests are adjusted. The registry record does not report whether any such plan was used, whether a hierarchy of outcomes was prespecified, or whether any adjustment was made. It would therefore be inappropriate to assume either that multiplicity was controlled or that it was ignored in the trial’s own analysis.

The study is described as randomized and crossover, but the analysis population is not reported in the registry record. In particular, the record does not say whether the analysis included all randomized participants, only participants who completed both catheter conditions, or another defined group. It does not report how missing outcome measurements were handled, whether any imputation was used, or how protocol deviations were treated. These details can influence an estimate, especially in a crossover comparison where paired measurements are relevant.

The registry reports enrollment of 37 and primary-outcome summary counts of 36 for each catheter condition. It does not explain the count difference or identify missing-data reasons. The counts alone do not show whether a participant lacked measurements, was excluded from a particular analysis, or was handled in another way.

These omissions do not establish that the trial lacked appropriate methods; they establish only that the methods are not documented in the registry record. The displayed estimate and p-value should accordingly be treated as an unadjusted summary, without attributing a particular missing-data, multiplicity, or analysis-population strategy to the investigators.

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 0% reporting threshold.

Most frequent non-serious adverse event terms

The serious adverse event summaries list 36 participants at risk in each catheter condition. The number recorded as affected by a serious adverse event is 0 for the test catheter and 0 for the standard catheter. No serious-event terms are listed in the record.

The registry also reports other adverse events affecting 1 participant in the test-catheter group and 0 in the standard-catheter group, with 36 at risk in each condition. The summary does not provide further details about the event, its timing, severity, or relationship to the device. The adverse-outcome section names adverse events and adverse device events as secondary outcomes, but these posted group figures do not by themselves explain how attribution was assessed.

These are counts in a small study, not proof that serious events cannot occur. The record’s deaths entries are null, so deaths are not reported in the registry record; null should not be interpreted as a reported count of zero. The safety figures describe what is recorded and should not be extended beyond this study’s participants and observation period.

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

The posted data show mean residual urine volumes of 12.4 mL with the test catheter and 9.4 mL with the standard catheter. The unadjusted mean difference is 3.0 mL, with an interval from -3.338 to 9.338 mL and an unadjusted p-value of 0.354. Those results describe the available summary comparison. They do not precisely determine the direction or size of a difference.

The registry record frames the study as a non-inferiority investigation, but it does not report a non-inferiority margin or the trial’s own statistical analysis. Non-inferiority cannot be established just because an ordinary test does not show a statistically significant difference. It requires a defined margin and an analysis designed to evaluate whether the data rule out an unacceptable loss. That information is missing here, so the posted summaries should not be presented as proving non-inferiority or equivalence.

The study was randomized and crossover, but the comparison is an unadjusted recalculation from group summaries. It does not provide the participant-level pairing, catheter sequence, or analysis of possible period effects. The crossover design may be important to the precision and interpretation of the treatment contrast, but those details are not reported in the registry record.

Nor do these results establish a general outcome for all users or settings. The record describes male subjects and reports a particular ultrasound endpoint over 3 catheterisations on 1 day. It does not provide longer-term results or enough information to assess how closely the analyzed participants represent other populations.

The defensible conclusion is limited: the posted means are close in scale, and the unadjusted interval is broad enough to include values on either side of no difference. The available record does not support a definitive claim of equivalence, non-inferiority, or a device effect. It is a description of a small completed study’s registry summaries, not medical advice.

16. Why This Trial Matters Statistically

This trial is statistically interesting because it combines a continuous measurement with a randomized crossover design and a non-inferiority framing. Each feature affects interpretation. Mean residual urine volume gives a quantitative way to compare bladder contents after catheterisation, while the crossover design makes the relationship between measurements from the same participant potentially important.

The posted comparison is an unadjusted recalculation from summary statistics. That makes it useful for a transparent description of the difference between the reported means, but it is not the same as a documented analysis of the randomized crossover trial. Without participant-level paired data or the trial’s analysis plan, readers cannot assess how the within-person comparison, sequence, or period may have been handled.

The study title also makes clear why non-inferiority methods matter. A non-inferiority conclusion needs a prespecified margin and an analysis that evaluates the estimate against that margin. The registry record does not report either the margin or the sponsor’s analysis. Consequently, an unadjusted p-value and an interval around a mean difference cannot settle the stated non-inferiority question on their own.

Finally, the sample-size illustrations show how planning depends on the effect one aims to detect: smaller target effects require larger planned samples under the stated assumptions. Those calculations are not the original trial’s justification and are not observed power. Keeping the planning illustration separate from the completed study’s results avoids treating hypothetical design quantities as evidence about what the trial demonstrated.

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 summaries do not include participant-level measurements, the within-participant correlation, or a documented crossover analysis. As a result, the unadjusted comparison cannot show how pairing affected the estimate or its precision. Catheter order, washout procedures, and any approach to period or sequence effects are not reported in the registry record.

The title describes a non-inferiority study, but the non-inferiority margin and original sample-size justification are not reported. No sponsor analysis is posted in the registry record, and the record lists 0 analysis entries. The posted difference and p-value are therefore not a substitute for the trial’s prespecified analysis.

The registry reports enrollment of 37, while the primary-outcome summaries list 36 participants for each catheter condition. The reason for this difference is not reported. The analysis population, reasons for missing measurements, and any missing-data handling are also not reported. The record does not specify how measurements across 3 catheterisations on 1 day were combined for each participant.

There are no posted results for the secondary outcomes beyond their names, and the safety summary gives little detail about the one other adverse event recorded in the test-catheter group. The deaths entries are not reported. These limitations restrict what can be inferred from the registry record, but they should not be mistaken for proof that unreported analyses or procedures were not performed.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Bladder Scan of Residual Urine With New Catheter — NCT01048541.
• Registry record last updated 2012-09-03; status last verified 2012-08.
• Results first posted 2012-09-03.
• 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

This completed randomized, triple-masked crossover study enrolled 37 participants and compared SpeediCath Compact Male with standard SpeediCath. The primary endpoint was mean residual urine volume, measured by ultrasound after catheterisation over 3 catheterisations on 1 day. The posted summaries list 36 participants for each catheter condition.

Mean residual urine volume was 12.4 mL for the test catheter and 9.4 mL for the standard catheter. The unadjusted mean difference was 3.0 mL, with an interval from -3.338 to 9.338 mL and a p-value of 0.354. The record does not report the non-inferiority margin or the trial’s own analysis, so these summaries do not establish non-inferiority.

The registry lists 2 secondary outcomes and no analysis entries. It records no participants affected by serious adverse events in either group, and one participant affected by another adverse event in the test group. Further methodological and safety details are not reported in the registry record.