Efficacy and Safety of 2 Doses of Tiotropium Respimat Compared to Placebo in Adolescents With Severe Persistent Asthma: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety of 2 Doses of Tiotropium Respimat Compared to Placebo in Adolescents With Severe Persistent Asthma (NCT01277523), a randomized phase 3 study. The primary outcome is FEV1 peak0-3 Change From Baseline.

2. Clinical Question

The clinical comparison is between each tiotropium dose and placebo, rather than between the two active doses. The outcome is a change from baseline, so the comparison concerns improvement relative to each group’s starting measurement, not simply the final lung-function value. Registry results are reported as adjusted means, and the primary outcome unit is litres.

The trial also assessed other pulmonary function measures and measures of asthma control, as well as safety. Those outcomes add context to the primary comparison but do not replace it. The registry record does not report the original sample-size justification or the full set of analysis-plan details.

3. Trial Design

NCT01277523 is a completed phase 3 randomized, double-blind, placebo-controlled, parallel-group trial sponsored by Boehringer Ingelheim. The registry lists enrollment as 392 and the condition as asthma. The study began in 2011-01, and primary completion was recorded in 2013-10.

Participants were assigned to placebo Respimat, tiotropium Respimat 2.5 mcg, or tiotropium Respimat 5 mcg. Treatment was intended as add-on controller therapy on top of usual care, over 12 weeks. The official trial title describes once-daily inhalation solution and adolescents aged 12 to 17 years with severe persistent asthma. The brief summary states that the primary objective was to evaluate superiority of tiotropium over placebo for the primary pulmonary function endpoint after treatment.

Randomization helps create comparable groups at the outset, while double masking is intended to limit the influence of treatment knowledge on care, reporting, and assessment. A parallel-group design assigns participants to a treatment group for the comparison rather than having each participant receive multiple study treatments in sequence. These are general features of the stated design; the registry record does not report details of the randomization procedure, masking implementation, or adherence to assigned treatment.

The primary outcome analysis population was the Full Analysis Set, described as the treated set: randomized patients who were dispensed and received at least one documented dose. The arm counts attached to the primary outcome are 132.0 for placebo, 126.0 for Tio R2.5, and 130.0 for Tio R5. These outcome-analysis counts are not interchangeable with the registry’s enrollment figure. The record does not give a complete account of participant flow or explain every difference among analysis populations.

The record lists 15 outcome measures and 24 analyses. It reports the primary outcome and several secondary outcomes, including pulmonary function and asthma-control measures. The original statistical analysis plan, the trial’s own sample-size assumptions, and details of any interim analyses are not reported in the registry record.

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: Full Analysis Set (FAS) was the same as the treated set which included all randomised patients who were dispensed and received at least one documented dose of trial medication. Missing data at a visit was imputed by the available data from the patient at that visit. Completely missing data were handled by the statistical model.

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: Treated set which included all randomised patients who were dispensed and received, at least one documented dose of trial medication.

6. Primary Endpoint

The registry lists the primary outcome as FEV1 peak0-3 Change From Baseline, measured over Baseline and 12 weeks.

The primary endpoint is change from baseline in peak forced expiratory volume in one second within the first 3 hours after dosing, measured at week 12. FEV1 is the volume of air that can be forcibly exhaled in one second. The endpoint is recorded in litres, and the registry says the values presented are adjusted means.

Using a change from baseline focuses the comparison on how the measure shifted during the study, rather than on the week 12 value alone. Measuring peak FEV1 within the stated post-dose interval is intended to capture pulmonary function during that period after administration. This explains the measurement’s role; the registry record does not report a rationale establishing that it is a surrogate for how participants feel or function in daily life.

The trial’s primary objective was to compare each tiotropium dose with placebo on this endpoint. A mean summarizes the average change in a group, while the estimated mean difference describes the contrast between the treatment group and placebo. The standard error reported beside each arm mean conveys uncertainty in estimating that mean; it is not a description of the spread of individual participant measurements.

The registry describes the primary population as the Full Analysis Set and says missing data at a visit were imputed using available data from that patient at that visit. Its description of handling completely missing data is incomplete, so the method for those cases is not reported in the registry record.

7. Results Posted in the Registry

• Tio R2.5: mean 0.55 versus 0.44 on control; difference 0.11 (95% CI -0.01 to 0.24), standardized effect d = 0.22; z-test p = 0.082.
• Tio R5: mean 0.53 versus 0.44 on control; difference 0.09 (95% CI -0.03 to 0.21), standardized effect d = 0.17; z-test p = 0.157.

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.

Trough FEV1 Change From Baseline

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Tio R2.5: mean 0.34 versus 0.23 on control; difference 0.11 (95% CI -0.02 to 0.25), standardized effect d = 0.21; z-test p = 0.090.
  • Tio R5: mean 0.28 versus 0.23 on control; difference 0.05 (95% CI -0.08 to 0.19), standardized effect d = 0.10; z-test p = 0.426.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tio R2.5 and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tio R5 and the control. The interval gives the range of effects that remain compatible with the data.

FVC peak0-3 Change From Baseline

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Tio R2.5: mean 0.37 versus 0.28 on control; difference 0.09 (95% CI -0.04 to 0.23), standardized effect d = 0.17; z-test p = 0.185.
  • Tio R5: mean 0.34 versus 0.28 on control; difference 0.06 (95% CI -0.07 to 0.20), standardized effect d = 0.11; z-test p = 0.353.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tio R2.5 and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tio R5 and the control. The interval gives the range of effects that remain compatible with the data.

FEV1 AUC (0-3h) Change From Baseline

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Tio R2.5: mean 0.45 versus 0.34 on control; difference 0.11 (95% CI -0.01 to 0.23), standardized effect d = 0.23; z-test p = 0.063.
  • Tio R5: mean 0.42 versus 0.34 on control; difference 0.09 (95% CI -0.03 to 0.21), standardized effect d = 0.18; z-test p = 0.153.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tio R2.5 and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tio R5 and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes span additional pulmonary function measurements and measures of asthma control. Across the posted secondary pulmonary function summaries, the mean changes in both tiotropium groups are numerically higher than the placebo mean. This broad directional pattern is consistent with the direction of the primary arm means, but it does not independently establish a treatment effect or resolve the uncertainty in the primary comparison.

The secondary measures also include asthma-control scores and responder outcomes. Their clinical and statistical interpretation depends on the specific endpoint definition and its analysis. The registry record lists 14 secondary outcomes, but the available numerical summaries do not cover every listed outcome. Further numerical details for those outcomes are not reported in the registry record.

Secondary endpoints can help assess whether a pattern is coherent across different measures, but they are generally less conclusive when many outcomes are examined. Each additional comparison creates more opportunity for apparently notable findings to arise by chance. Unless the testing plan accounts for multiplicity, isolated secondary p-values should be treated as exploratory rather than as confirmatory evidence. The registry record does not report whether or how multiplicity was controlled.

Secondary endpoints also do not substitute for the prespecified primary question. They may measure related but distinct aspects of lung function or asthma control, and agreement across them can be informative without proving that the same effect applies to all outcomes. Results should be interpreted with attention to their own estimates, uncertainty, definitions, and analysis methods, rather than by counting how many outcomes appear favorable.

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

• Trough FEV1 Change From Baseline
• FVC peak0-3 Change From Baseline
• FEV1 AUC (0-3h) Change From Baseline
• FVC AUC (0-3h) Change From Baseline
• Control of Asthma as Assessed by ACQ6 Score.
• ACQ6 Score Responders
• Control of Asthma as Assessed by ACQ Total Score
• ACQ Total Score Responders

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean difference represent? The primary outcome is continuous and is summarized with a mean. A mean difference compares the average change in one group with the average change in placebo. A positive difference in these comparisons means the reported average change was numerically higher in the tiotropium group. This is a general interpretation of the direction of a contrast, not a judgment about clinical importance.

The registry’s arm values are adjusted means. The re-calculated contrasts use the posted arm means as simple, unadjusted summaries. Although the two sets of estimates are close numerically for the primary outcome, they arise from different analyses. The registry reports that its own comparison used a mixed models analysis, with the parameter described as a mean difference in final values. The model specification, covariates, and other details are not reported in the registry record.

What does the standard error describe? The primary arm summaries give standard errors. In general, a standard error describes the uncertainty in an estimated quantity, such as a group mean. It is not the standard deviation of individual outcomes and does not show the range of participant responses. The re-calculation uses the posted standard errors to estimate uncertainty around the unadjusted mean differences. Without participant-level data and the full analysis model, it cannot reproduce every feature of the sponsor’s analysis.

How should a confidence interval be read? A confidence interval gives a range of values reasonably compatible with the data and the method used, under the procedure’s assumptions. Its width reflects precision: a narrower interval is more precise than a wider one. For a difference, an interval that includes zero is compatible with no difference under that analysis. An interval that does not include zero is evidence against a zero difference under the stated method, but it does not by itself indicate whether the difference is important to patients.

What does the p-value add? In general, a p-value describes how surprising the observed data, or data more extreme, would be if the null hypothesis and the analysis assumptions held. It is not the probability that the null hypothesis is true. Nor does it give the probability that a finding will reproduce. The registry’s p-values belong to the sponsor’s reported mixed-model analyses; the re-calculated p-values are unadjusted comparisons derived from posted summary statistics and should not be treated as substitutes.

Why can the two analyses differ? A summary-statistic re-calculation is limited to the group means, standard errors, and group sizes available in the record. A mixed model can account for the structure of the observations and specified model terms. The registry record does not state enough about the model to explain the discrepancy in detail. Because the record flags a discrepancy, the sponsor’s own analysis takes precedence for interpreting the trial’s formal results. The recalculation remains useful as a transparent, simple comparison of the posted summaries, provided its different basis is kept clear.

Why does the design matter? Random allocation is intended to make treatment groups comparable with respect to factors known and unknown at baseline. Masking is intended to limit bias from knowledge of assignment. A parallel-group design compares separate assigned groups. These design features support interpretation of between-group differences, but they do not eliminate uncertainty or solve limitations in reporting. The registry does not report the sequence-generation method, allocation concealment procedures, or masking details.

How is missing information relevant? The record states that missing data at a visit were imputed using available data from the patient at that visit. It also includes an incomplete phrase about completely missing data, so that part of the procedure cannot be established from the registry record. General statistical reasoning is that missing-data methods rely on assumptions about why values are missing and how observed values relate to unobserved ones. The registry’s abbreviated description does not allow those assumptions to be assessed.

The primary objective was superiority over placebo. The record does not report the complete hypothesis-testing plan, whether multiplicity adjustments were used, or how the primary comparisons were ordered. The reported p-values and confidence intervals should therefore be read as posted analyses, not as evidence that every analysis-plan detail is known. General statistical interpretation also distinguishes statistical evidence from clinical meaning: a numerical contrast can be estimated without establishing a threshold that patients would consider worthwhile.

11. Confidence Intervals and Precision

The sponsor-reported 95% confidence interval for Tio R2.5 versus placebo on the primary endpoint is 0.002 to 0.220 litres. It is relatively close to zero at its lower end, so the estimated positive difference is not highly precise in the sense of being tightly bounded away from zero. For Tio R5 versus placebo, the sponsor-reported 95% interval is -0.019 to 0.198 litres. That interval includes zero and also permits a range of positive differences.

These intervals describe uncertainty in the estimated group contrast under the sponsor’s mixed-model analysis. They do not describe the range of changes among individual participants, and they do not guarantee that the true contrast lies within the interval. Their interpretation depends on the analysis and its assumptions. A confidence interval is most useful when read alongside the point estimate: the point estimate gives the central estimated contrast, while the interval shows how much uncertainty remains around it.

The simple re-calculations from the arm summaries produce 95% intervals from -0.014 to 0.238 litres for Tio R2.5 and from -0.035 to 0.215 litres for Tio R5. Both include zero. These re-calculated intervals do not match the sponsor’s intervals, consistent with the registry’s flagged discrepancy. The sponsor’s own analysis takes precedence; the reconstructed intervals are not a replacement for it.

Precision is limited by the uncertainty in the estimates and by what the registry reports. Standard errors are available for the arm means, but the record does not provide participant-level data or a full model specification. The intervals therefore support cautious interpretation of the average differences, not fine-grained conclusions about individual responses or unreported outcomes.

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 figures are planning illustrations expressed as participants per arm. They are not total event counts; the registry’s planning description reserves total event counts for time-to-event outcomes, while these outcomes are continuous. The original design assumptions used to plan this trial are not reported in the registry record.

The illustration uses a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. It uses the observed effect as a reference and shows planning for 100%, 75%, and 50% of that observed effect. The 80% power column gives the estimated participants per arm for a design with an 80% chance of detecting the stated effect under those assumptions, if that effect were the true effect. The 90% power column describes the corresponding planning target for a 90% chance.

As the effect used for planning becomes smaller, the required number of participants per arm becomes larger. This follows the general statistical principle that smaller differences are harder to distinguish from random variation, all else equal. For example, the listed planning figures for 75% of the observed primary comparison are 594 participants per arm for 80% power and 796 participants per arm for 90% power for Tio R2.5 versus placebo. These are illustrative design calculations, not statements about what the trial planned to recruit.

The figures are not observed power. They do not describe the probability that the completed trial’s finding is true, and they do not update the evidence from the trial. They answer a hypothetical planning question using the stated assumptions and an effect based on the observed estimate. Different assumptions or a different effect of interest would produce different planning figures.

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

Worked calculation for this trial

1. Observed difference Δ = 0.112; pooled standard deviation σ = 0.517.
2. n = 2 × (1.96 + 0.842)² × 0.517² / 0.112² = 334.1, rounded up to 335 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 <- 0.112                      # observed difference in means
sigma <- 0.516687541580983                     # 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(1277523)
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 = 335 (80% power), 448 (90% power)
 75% of observed effect: n per arm = 594 (80% power), 796 (90% power)
 50% of observed effect: n per arm = 1,337 (80% power), 1,789 (90% power)
power.t.test: 335 
Simulated power at n = 335 per arm: 0.799 (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.

14. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary comparisons from a mixed models analysis. For Tio R2.5 versus placebo, the sponsor reports a mean difference of 0.111 litres, a 95% confidence interval from 0.002 to 0.220, and p = 0.046. For Tio R5 versus placebo, the reported mean difference is 0.090 litres, with a 95% confidence interval from -0.019 to 0.198 and p = 0.104.

The re-calculation uses the posted arm means and standard errors to form simple unadjusted comparisons. It gives mean differences of 0.112 litres for Tio R2.5 and 0.09 litres for Tio R5, but its intervals and unadjusted p-values differ from the sponsor’s reported results. Similar point estimates do not make the inferential analyses interchangeable: the confidence intervals and p-values depend on the analysis method and its assumptions.

The registry flags a discrepancy between the re-calculation and the sponsor analysis. The sponsor’s own analysis takes precedence for the trial’s reported inferential conclusions. The unadjusted re-calculation is best understood as a check on the posted group summaries, not a correction to the sponsor’s model-based analysis. The registry record does not report enough detail about the mixed model to identify why the results differ.

15. Multiplicity, Missing Data and Analysis Populations

The trial has a primary endpoint and multiple secondary outcomes. The registry lists 15 outcome measures and 24 analyses, while 14 secondary outcomes are recorded. When several outcomes or comparisons are tested, the chance of at least one apparently unusual result can increase. Statistical methods such as an adjustment to the testing procedure or a prespecified hierarchy can address this concern, but the registry record does not report whether such a method was used or describe a hierarchy for the endpoints.

The primary objective describes superiority comparisons of each tiotropium dose with placebo. The registry reports a p-value and confidence interval for each sponsor comparison, but the complete testing strategy is not reported. The available record therefore does not establish whether the reported p-values are adjusted for multiple comparisons. Secondary findings should be interpreted with particular caution for this reason, and the primary comparison should remain distinct from exploratory patterns across additional endpoints.

Missing-data handling is described only in part. The registry says that missing data at a visit were imputed using available data from the patient at that visit. The text describing completely missing data ends mid-description, so the handling of those cases is not reported in the registry record. The record does not provide enough detail to assess assumptions about why measurements were missing or whether sensitivity analyses were conducted.

The primary analysis population is described as the Full Analysis Set, defined as randomized patients who were dispensed and received at least one documented dose. The record calls this the treated set. It does not give a full participant-flow account or describe analysis populations for every outcome. No interim analyses or complete statistical analysis plan are reported in the registry record. These omissions limit assessment of how the final analyses relate to the original protocol and how robust the findings are to alternative analysis choices.

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: pyoderma (0.8%), dermatitis atopic (0.8%), ligament sprain (0.8%), asthma (0.8%).

The serious adverse event counts are reported separately for each group. The registry lists 0 serious adverse events among 135 at risk in the placebo group, 1 among 127 at risk with Tio R2.5, and 2 among 130 at risk with Tio R5. These figures describe observed counts in the registry record; they do not by themselves establish a causal relationship to study treatment.

The record also lists Pyoderma, Dermatitis atopic, Ligament sprain, and Asthma as the top serious-event terms, each reported as 0.8%. The listing does not identify a treatment group for each term, so it should not be read as a group-specific comparison. The registry record does not report the death figures.

Small counts provide limited information about the frequency or comparative risk of uncommon events. A group with no recorded event is not proof that the event cannot occur. These safety figures should be read alongside the trial’s limited duration and the registry’s reporting detail; the record does not provide enough information to characterize longer-term safety.

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

The registry results describe average changes in a pulmonary function measure over 12 weeks among adolescents with severe persistent asthma who were included in the stated analysis population. The sponsor’s model-based estimates show a positive mean difference for both tiotropium comparisons, with different degrees of statistical uncertainty. For the 2.5 mcg comparison, the sponsor’s 95% confidence interval lies just above zero; for the 5 mcg comparison, the interval includes zero.

These findings do not establish what any individual participant experienced. Group averages can conceal variation in response, and the registry does not report individual-level distributions in the information. A statistically detectable average difference is also not automatically a clinically important difference. The registry record does not provide a threshold for a meaningful change that would allow that judgment.

The findings do not answer every question about asthma control, day-to-day functioning, long-term outcomes, or safety. The trial includes secondary measures, but the statistical weight of those results depends on endpoint definitions, uncertainty, and whether multiplicity was addressed. The registry does not report the complete analysis plan or all secondary numerical results.

Nor does the comparison establish that one tiotropium dose is better than the other: the primary objective and reported comparisons are each against placebo. The results apply to the trial population and setting described in the registry and should not be generalized beyond that information without additional evidence. No medical advice follows from the registry estimates alone.

18. Why This Trial Matters Statistically

This trial illustrates why statistical interpretation requires more than comparing group means. The posted adjusted means are numerically higher in the tiotropium groups, but the strength and precision of a treatment contrast depend on the analysis and its uncertainty. The sponsor’s mixed-model analysis and the unadjusted re-calculation from summary statistics do not yield identical inferential results. Recognizing that distinction prevents a transparent but simplified re-calculation from being mistaken for the trial’s formal analysis.

It also demonstrates the role of confidence intervals. The primary estimates are not equally precise, and their intervals convey information that a point estimate alone cannot. A positive estimate does not mean the same thing as a precisely established difference, and a p-value does not quantify clinical importance.

Multiplicity matters because the record includes a primary outcome alongside numerous secondary measures and analyses. Without the testing strategy, the strength of isolated secondary results is difficult to assess. Likewise, incomplete reporting of missing-data handling and model details constrains independent evaluation. These are not merely technical omissions: they affect how confidently readers can connect a reported estimate to the planned question.

The planning illustrations add another useful distinction. Sample-size calculations based on observed effects can help readers understand what future study sizes might be needed under stated assumptions, but they are not evidence about the trial’s power after completion and do not reveal its original design rationale. Separating planning, estimation, and inference is central to responsible interpretation of clinical trial statistics.

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.

The registry record provides an incomplete description of the primary analysis. It identifies a mixed models analysis but does not report the full model specification, covariates, or the assumptions needed to reproduce the sponsor’s estimates. The re-calculation from arm summaries therefore cannot fully explain the difference from the sponsor’s results.

Missing-data reporting is also incomplete. The record describes imputation for missing data at a visit using available data from that patient at that visit, but its description of completely missing data is truncated. The registry does not report whether sensitivity analyses examined the impact of missingness or alternative assumptions.

The full multiplicity strategy is not reported, despite the number of outcomes and analyses listed. The registry also does not provide all numerical secondary outcome results in the information available for this analysis. This makes it difficult to assess the consistency of every secondary result or whether confirmatory claims were protected against multiple testing.

The adverse-event summary gives counts and selected serious-event terms, but deaths are not reported in the registry record. These limited figures cannot characterize uncommon risks precisely or provide a complete account of safety. The record also does not report the full participant flow, the original sample-size justification, or interim-analysis details. These limitations concern what can be established from registry reporting and should not be mistaken for proof that the trial did not conduct those procedures.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy and Safety of 2 Doses of Tiotropium Respimat Compared to Placebo in Adolescents With Severe Persistent Asthma — NCT01277523.
• Registry record last updated 2014-10-20; status last verified 2014-10.
• Results first posted 2014-10-20.
• 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

NCT01277523 was a completed phase 3 randomized, double-blind, parallel-group trial of tiotropium Respimat 2.5 mcg or 5 mcg versus placebo, added to usual care for adolescents aged 12 to 17 years with severe persistent asthma. Treatment was assessed over 12 weeks.

The primary endpoint was change from baseline in peak FEV1 within the first 3 hours after dosing at week 12. The sponsor’s mixed-model analysis reports a positive mean difference for each tiotropium dose versus placebo, with the 95% confidence interval excluding zero for the 2.5 mcg comparison and including zero for the 5 mcg comparison. The registry flags a discrepancy with simple unadjusted re-calculations, so the sponsor analysis takes precedence.

Interpretation is limited by incomplete reporting of model details, missing-data handling, multiplicity, and some secondary and safety information. The record’s planning illustrations are hypothetical calculations, not observed power or the trial’s original design assumptions.