Evaluation of Cipro Inhale in Patients With Non-cystic Fibrosis Bronchiectasis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of Cipro Inhale in Patients With Non-cystic Fibrosis Bronchiectasis (NCT00930982), a randomized phase 2 study. The primary outcome is Change From Baseline in Total Bacterial Load in the Sputum at End of Treatment (Day 29)..

2. Clinical Question

The question focuses on a laboratory measure of bacteria in sputum after a defined treatment period. The registry’s brief summary describes the study’s purpose as finding out whether airway bacterial load could be reduced after inhaled ciprofloxacin for 28 days. That purpose should be distinguished from the analysis result: the posted endpoint is a change score, and the statistical comparison describes the difference between groups in that measure.

The clinical context is non-cystic fibrosis bronchiectasis, but the primary measure is not a direct measure of symptoms, lung function, or exacerbations. Those topics appear among the secondary outcomes, which include forced expiratory volume in 1 second, forced vital capacity, time to exacerbation with antibiotic intervention, health-related quality of life, inflammatory markers, and sputum volume. The registry record does not establish how changes in bacterial load relate to those other outcomes.

3. Trial Design

This was a phase 2, randomized, placebo-controlled, parallel-group study of inhaled ciprofloxacin compared with matching placebo in people with non-cystic fibrosis bronchiectasis. Its official title describes the study as double-blind and multicenter, while the registry records quadruple masking. The record does not specify which groups of people were included in the masking designation, so the exact masking roles are not reported in the registry record.

The registry lists 124 participants enrolled. The primary endpoint summaries include 60 participants in the ciprofloxacin arm and 64 in the placebo arm. The analysis population is described as modified intent-to-treat, including randomized participants who received study drug; the record says this was identical to the intent-to-treat population of all randomized participants. Further details about randomization procedures, allocation concealment, or site-level enrollment are not reported in the registry record.

The ciprofloxacin arm received 32.5 mg ciprofloxacin hydrated, corresponding to 50 mg Ciprofloxacin PulmoSphere Inhalation Powder, twice daily. The placebo arm inhaled matching placebo twice a day. The stated treatment period was 28 days, and the primary outcome was assessed at the end of treatment on Day 29. The registry gives baseline and 29 days as the endpoint timeframe.

The study is marked completed. Its recorded start was 2009-06 and its primary completion was 2010-09. Bayer is listed as the sponsor. The registry record does not report the trial’s original sample-size justification, the assumptions used to plan enrollment, or details of any interim analyses. Those omissions limit what can be inferred about how the original design was planned, but they do not prevent description of the posted endpoint estimates.

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: Out of 277 participants screened, 153 failed screening (mostly due to not meeting in-/exclusion criteria or inability to produce adequate sputum samples), and 124 participants were randomized (60 to Ciprofloxacin Inhale and 64 to placebo).

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Modified intent-to-treat (ITT) analyses were performed on all participants who had been randomized and received study drug. This population was identical to the ITT population of all randomized participants.

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 From Baseline in Total Bacterial Load in the Sputum at End of Treatment (Day 29)., measured over Baseline and 29 days.

The primary endpoint was change from baseline in total bacterial load in sputum at the end of treatment on Day 29. The measure is expressed as log10 of CFU per gram of sputum, where CFU means colony forming units and log10 means the decadic logarithm. A change score compares a participant’s measurement at follow-up with that participant’s baseline measurement.

The endpoint is used to quantify bacterial load in a respiratory sample, matching the stated study purpose of assessing whether airway bacterial load could be reduced after inhaled treatment. Its value is a laboratory measure rather than a direct report of how a participant feels or functions. The registry lists lung function, exacerbations, quality of life, inflammatory markers, and sputum volume as secondary outcomes, but those measures address distinct aspects of the condition.

Sputum was collected before inhalation of study drug at the relevant visit. Participants could provide a sample at the visit or bring one produced within the 4 hours before the visit. If a participant could not produce a spontaneously expectorated sample of > 2 mL, induced sputum could be collected. The registry states that last observation carried forward was used for imputation. These collection and analysis details matter because the endpoint depends on an available sputum sample and on how missing measurements were handled.

A lower change value indicates a larger decrease from baseline on this scale. That direction helps interpret the posted group means, but the endpoint alone does not establish the meaning of bacterial-load change for symptoms, lung function, or longer-term outcomes.

7. Results Posted in the Registry

• Ciprofloxacin Inhale (BAYQ3939): mean -2.94 versus -0.32 on control; difference -2.62 (95% CI -3.65 to -1.59), standardized effect d = -0.91; z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous: it is a numerical change in log10 bacterial load per gram of sputum. The registry describes the group summaries as means with standard deviations. A mean gives the arithmetic average of the observed change values, while a standard deviation describes how dispersed those values are around the mean. Neither summary says that all participants experienced a change close to the group average.

What does the unadjusted comparison represent?

The recalculated comparison subtracts the placebo mean change from the ciprofloxacin mean change. It is a direct, unadjusted contrast of the posted summary statistics. The resulting estimate is -2.62 log10 of CFU per gram sputum, with a confidence interval from -3.647 to -1.593 and an unadjusted p-value of < 0.001. This calculation does not account for covariates or other model features that may be used in an adjusted analysis. It is useful as a transparent comparison of the reported group averages, but it is not a replacement for the trial’s own analysis.

A confidence interval expresses uncertainty around an estimate under the assumptions of the calculation. Its endpoints indicate a range of values compatible with the observed data and statistical procedure. A narrower interval indicates greater precision, while a wider interval indicates more uncertainty. An interval that does not include zero is consistent with a difference between group means under the corresponding procedure, but it does not establish clinical importance or resolve questions about bias and generalizability.

What does ANCOVA add?

The registry reports an ANCOVA result as a difference in least-squares means of -2.368, with p < 0.001. ANCOVA, or analysis of covariance, estimates a group contrast while accounting for covariates included in the statistical model. Least-squares means are model-based group means, interpreted in relation to the model rather than as simple raw averages. The registry does not report which covariates were included, how the model was specified, or a confidence interval for this estimate. The reported p-value supports a statistically detectable difference under the fitted model, but the missing model details constrain independent evaluation.

The adjusted and unadjusted estimates answer related but not identical statistical questions. The unadjusted calculation compares the posted means without covariate adjustment. The ANCOVA estimate reflects the registry’s model-based analysis. Since the record does not identify the covariates or other model specifications, it is not possible to determine from the record why the estimates differ. Their shared direction and reported p-value threshold should not be taken to mean that the models are identical.

Why can dispersion matter?

Dispersion is relevant because variability affects how precisely a group mean and the difference between group means can be estimated. In general, greater variability makes it harder to distinguish a group contrast from random variation when other features are held constant. The posted standard deviations are 3.4 for ciprofloxacin and 2.29 for placebo. These values indicate that observed changes varied within both arms. A standard deviation is not a confidence interval and does not show the full shape of the data; participant-level distributions are not reported in the registry record.

The recalculated standardized mean difference is -0.909. A standardized difference expresses a mean contrast in relation to a measure of pooled variability, rather than in the original endpoint units. It can help compare the scale of contrasts measured in different units, but it does not replace the original-unit estimate and does not establish whether a difference matters clinically. The calculation is based on summary data and should be read as an unadjusted descriptive statistic.

What does the p-value say?

A p-value is a measure of how compatible the observed result is with a specified null model, assuming that model and the analysis assumptions apply. A smaller p-value indicates that data at least as inconsistent with the null model would be less common under that model. It is not the probability that the treatment has no effect, and it does not quantify the size or importance of the estimated difference. The registry’s ANCOVA p-value is < 0.001, and the unadjusted recalculation also has p < 0.001. Those results describe statistical evidence for a group difference on this endpoint, not certainty about the broader clinical question.

The endpoint description states that last observation carried forward was used for imputation. This approach uses an earlier observed value to fill in a later missing measurement. Its interpretation depends on assumptions about what missing values would have been and about the timing and reasons for missingness. The registry record does not report the amount or pattern of missing data, reasons for missing measurements, or sensitivity analyses using alternative assumptions. It is therefore not possible to assess from the record how strongly the result depends on the imputation method.

The stated analysis population is modified intent-to-treat: participants who were randomized and received study drug. The record says this population was identical to the intent-to-treat population of all randomized participants. This gives the population definition for the posted primary analysis, but details such as exclusions after randomization or participant-level analysis procedures are not reported in the registry record.

10. Confidence Intervals and Precision

For the unadjusted comparison, the estimated mean difference is -2.62 log10 of CFU per gram sputum, and its confidence interval extends from -3.647 to -1.593. The interval remains on the negative side of zero, matching the direction of a larger average decrease in the ciprofloxacin group. The endpoints convey uncertainty about the magnitude of the unadjusted contrast, not uncertainty about every aspect of the trial or the probability that the result is correct.

Precision concerns how narrowly the data locate an estimate. A confidence interval gives more information about precision than a point estimate alone: the point estimate is one value, while the interval shows a range of values compatible with the data under the calculation’s assumptions. The interval’s location and width should be considered together. Location communicates direction and plausible magnitude; width communicates how much uncertainty remains about the estimate.

The posted group standard deviations are 3.4 for ciprofloxacin and 2.29 for placebo, and the endpoint sample sizes are 60 and 64, respectively. These summaries describe the data used in the simple comparison, but they do not show individual trajectories or the distribution of changes. The confidence interval applies to the unadjusted mean difference, not to the ANCOVA estimate.

The registry reports the ANCOVA difference in least-squares means as -2.368 with p < 0.001, but a confidence interval for that model-based estimate is not reported in the registry record. The unadjusted interval should not be presented as if it were the adjusted interval. Without the model specification and an interval for the ANCOVA estimate, the precision of that adjusted result cannot be evaluated from the record as fully as the unadjusted comparison.

Precision is distinct from clinical importance. Even a relatively precise estimate does not by itself establish the relevance of a change in sputum bacterial load to symptoms, lung function, exacerbations, quality of life, or longer-term outcomes. Those relationships require evidence beyond the uncertainty interval for this primary endpoint.

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 planning figures are expressed as participants per arm, not as total events. They are illustrations based on the observed effect, rather than the trial’s original design calculation. The planning assumptions 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 to a stated fraction of the observed effect.

For planning around 100% of the observed effect, the figures are 19 participants per arm for 80% power and 26 participants per arm for 90% power. For 75% of the observed effect, they are 34 participants per arm for 80% power and 46 participants per arm for 90% power. For 50% of the observed effect, they are 76 participants per arm for 80% power and 102 participants per arm for 90% power.

The 80% power column describes the number of participants per arm that the stated calculation estimates would be needed for an 80% chance of detecting the assumed effect under the planning model and significance level. The 90% power column gives the corresponding planning count for a 90% chance. These are prospective planning interpretations: they do not tell how likely the observed result was to be detected after the trial was completed.

The progression across the effect assumptions illustrates a general feature of sample-size planning: smaller effects are harder to distinguish from random variation and therefore require more participants for the same target power, all else being equal. The displayed values are planning illustrations, not observed power. The trial’s own original sample-size assumptions and justification are not reported in the registry record. No conclusion about the original design can be drawn from these retrospective planning figures.

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 = -2.620; pooled standard deviation σ = 2.881.
2. n = 2 × (1.96 + 0.842)² × 2.881² / -2.620² = 19.0, rounded up to 19 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 <- -2.62                      # observed difference in means
sigma <- 2.88071356711106                     # 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(930982)
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 = 19 (80% power), 26 (90% power)
 75% of observed effect: n per arm = 34 (80% power), 46 (90% power)
 50% of observed effect: n per arm = 76 (80% power), 102 (90% power)
power.t.test: 20 
Simulated power at n = 19 per arm: 0.781 (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. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary endpoint analysis as an ANCOVA difference in least-squares means of -2.368, with p < 0.001. It does not report a confidence interval for that estimate. The recalculated comparison uses the posted group means and standard deviations to produce an unadjusted difference of -2.62, with a confidence interval from -3.647 to -1.593 and p < 0.001.

These estimates are not identical because one is model-based and the other is a simple unadjusted comparison of group summaries. ANCOVA can account for covariates included in its model; the covariates and model details are not reported in the registry record. The recalculation does not reproduce an adjusted analysis, and its confidence interval belongs to the unadjusted estimate only.

The two analyses point in the same direction and both report p-values below 0.001. The registry does not flag a discrepancy between the sponsor analysis and the recalculation. The sponsor’s reported ANCOVA result should therefore be understood as the trial’s own model-based analysis, while the recalculated result provides a separate, transparent summary-data comparison. Neither result alone establishes the clinical meaning of the endpoint difference.

14. Multiplicity, Missing Data and Analysis Populations

The registry identifies total bacterial load in sputum at Day 29 as the primary endpoint and lists secondary outcomes covering lung function, exacerbation timing, health-related quality of life, inflammatory markers, and sputum volume. Testing several outcomes can raise a multiplicity question: when many statistical comparisons are made, the chance of obtaining at least one apparently unusual result can increase. Statistical plans may address this through prespecified testing sequences or other adjustments, but the approach used for this trial is not reported in the registry record.

The record reports an ANCOVA analysis for the primary outcome and does not provide enough information to determine whether that result was part of a broader prespecified testing strategy. The multiplicity adjustment method, if any, and the handling of multiple secondary comparisons are not reported in the registry record. The p-value for the primary endpoint should therefore be read as reported, without assuming that it was or was not adjusted for testing across outcomes.

The primary endpoint description states that last observation carried forward was used for imputation. This specifies one missing-data method, but does not reveal how many participants had missing measurements, when measurements were missing, or why they were missing. The missing-data pattern, the assumptions supporting the imputation, and sensitivity analyses using alternative methods are not reported in the registry record. These details would help assess whether the estimated group contrast is sensitive to the handling of incomplete endpoint data.

The primary analysis population is described as modified intent-to-treat, including participants who were randomized and received study drug. The registry says this was identical to the intent-to-treat population of all randomized participants. That statement defines the reported population at a high level; participant flow, post-randomization exclusions, and detailed analysis-set procedures are not reported in the registry record.

Interim analyses and any associated stopping rules are not reported in the registry record. The registry also does not report the original sample-size justification. These gaps do not change the posted endpoint estimates, but they limit assessment of the full statistical plan and of how the primary analysis fits within all planned decisions.

15. 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: bronchiectasis (7.8%), oesophageal adenocarcinoma (1.7%), complex regional pain syndrome (1.7%), hallucination (1.7%), neutropenia (1.6%).

The registry reports serious adverse events in 4 of 60 participants in the ciprofloxacin arm and 6 of 64 participants in the placebo arm. It reports other adverse events in 38 of 60 and 36 of 64 participants, respectively. These are counts with the corresponding arm totals, not adjusted comparisons. They should not be interpreted as evidence that one group had a higher or lower risk without considering event definitions, timing, severity, and the full safety analysis.

The listed serious-event terms include Bronchiectasis at 7.8%, Oesophageal adenocarcinoma at 1.7%, Complex regional pain syndrome at 1.7%, Hallucination at 1.7%, Neutropenia at 1.6%, and Sepsis at 1.6%. The registry excerpt does not provide enough detail to infer from these terms alone how each event was counted, whether a term occurred in one or both arms, or how the percentages were calculated. The event-level arm breakdown is not reported in the registry record.

Death counts are not reported in the registry record. Nor does the record summary specify the complete event definitions, follow-up window, or severity grading used for these safety counts. The observed counts describe what the registry posts for this study; they do not establish a causal relationship or settle the comparative safety profile.

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

The posted primary endpoint results show a more negative average change in sputum bacterial load in the ciprofloxacin group than in the placebo group. The unadjusted mean difference is -2.62 log10 of CFU per gram sputum, with a confidence interval from -3.647 to -1.593 and p < 0.001. The registry’s ANCOVA analysis also reports a negative difference in least-squares means, -2.368, with p < 0.001. These are statistical descriptions of the primary endpoint over the treatment period.

The result does not, by itself, establish whether the magnitude of the bacterial-load difference is clinically important. The primary measure is a sputum laboratory endpoint, not a direct measure of symptoms, daily functioning, lung function, exacerbations, or quality of life. Although the registry lists outcomes in those areas, the primary endpoint result cannot be used as a substitute for their results. The record does not report enough information to establish how the bacterial-load change relates to those outcomes.

The timing also matters. The primary assessment was at Day 29 following a 28-day treatment period. The endpoint result therefore describes change over that study period, rather than persistence after treatment or longer-term outcomes. Such longer-term primary endpoint results are not reported in the registry record.

The estimates are group averages, and the reported standard deviations indicate variation within both arms. They do not describe what happened to each participant. The record does not report individual outcome distributions or the number of participants with an increase, decrease, or unchanged value. Results from this study should therefore be understood as a comparison of group-level endpoint summaries in the analyzed population.

Randomization and placebo control support a structured comparison, but they do not remove all uncertainty in how to interpret a posted result. The record’s missing detail about the adjusted model, multiplicity, missing-data patterns, and longer-term outcomes limits broader conclusions. The findings describe the reported statistical contrast; they do not establish a general treatment recommendation or a conclusion about outcomes beyond those measured and reported.

17. Why This Trial Matters Statistically

This trial illustrates why an endpoint’s scale and clinical role matter when interpreting a statistically strong comparison. The primary measure is change in log10 bacterial load per gram of sputum. The posted averages and the unadjusted contrast are clearly directional, and both the recalculated comparison and the registry’s ANCOVA analysis report p-values below 0.001. Yet the endpoint is a laboratory measure, so its statistical separation should not be treated as a direct statement about symptoms, lung function, exacerbations, or quality of life.

The record also provides a useful comparison between an unadjusted summary-data calculation and a sponsor-reported ANCOVA analysis. They produce different point estimates, while both report p-values below 0.001. This demonstrates that an adjusted model-based estimate and a direct difference between posted means answer related but distinct questions. Without the ANCOVA covariates and model details, readers can identify that distinction but cannot fully reproduce the sponsor’s analysis.

Missing-data and multiplicity details are important to interpreting any clinical trial result. The endpoint description states that last observation carried forward was used, but the missing-data pattern and sensitivity analyses are not reported in the registry record. Several secondary outcomes are listed, while the multiplicity approach is also not reported. These gaps show why a p-value and point estimate are only part of a complete statistical account.

Finally, planning illustrations help explain how assumed effect size and power relate to participant requirements, but they are not evidence about the trial’s original design or observed power. Keeping design planning, model-based inference, and clinical interpretation distinct leads to a more careful reading of the reported result.

18. 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 primary assessment is at Day 29 after a 28-day treatment period. This provides a short-term endpoint comparison, but longer-term results for bacterial load are not reported in the registry record. The primary outcome is a sputum laboratory measure, and the record does not establish how this measure relates to changes in symptoms, lung function, exacerbations, or quality of life.

Collection depended on participants providing sputum at the visit or bringing a sample produced within the 4 hours before the visit. Induced sputum could be collected when a participant could not produce a spontaneously expectorated sample of > 2 mL. These procedures are described in the record, but the frequency of induced collection, sample availability, and any associated measurement differences are not reported in the registry record.

Last observation carried forward was used for imputation. The record does not report the amount or pattern of missing outcome data, reasons for missingness, or sensitivity analyses. It is therefore not possible to assess how the endpoint estimate would compare under alternative missing-data assumptions. The record also does not provide the covariates or full specification for the ANCOVA model, limiting independent reproduction of the sponsor’s adjusted result.

The record identifies several secondary outcomes but does not report the multiplicity strategy. The original sample-size justification and assumptions, interim analyses, and any stopping rules are also not reported in the registry record. These omissions limit assessment of the prespecified statistical plan. The posted enrollment and analysis summaries do not provide participant-level outcome distributions, so the range of individual responses cannot be evaluated from the registry summaries alone.

Masking is recorded as quadruple, while the official title describes the study as double-blind. The exact roles covered by the masking label are not reported in the registry record. These limitations concern the detail available for interpreting and reproducing the analysis; they do not alter the numerical results that the registry posts.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Evaluation of Cipro Inhale in Patients With Non-cystic Fibrosis Bronchiectasis — NCT00930982.
• Registry record last updated 2014-12-12; status last verified 2014-11.
• Results first posted 2012-01-30.
• 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.

22. Record Summary

The registry describes a completed phase 2 randomized, placebo-controlled, parallel-group study of inhaled ciprofloxacin versus matching placebo in non-cystic fibrosis bronchiectasis. It lists 124 participants enrolled and Bayer as sponsor. The recorded start was 2009-06, and primary completion was 2010-09.

The primary endpoint was change from baseline in total sputum bacterial load at Day 29, measured as log10 of CFU per gram sputum. The posted group means were -2.94 for ciprofloxacin and -0.32 for placebo. The recalculated unadjusted mean difference was -2.62, with a confidence interval from -3.647 to -1.593 and p < 0.001. The registry’s ANCOVA result was -2.368, with p < 0.001.

The record also lists secondary outcomes and adverse-event counts. Important analysis details, including the ANCOVA model specification, multiplicity approach, missing-data patterns, and original sample-size justification, are not reported in the registry record. The posted results describe the primary endpoint comparison but do not alone determine its clinical meaning or longer-term implications.