Efficacy of NVA237 Compared to Tiotropium in Patients With Chronic Obstructive Pulmonary Disease (COPD): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy of NVA237 Compared to Tiotropium in Patients With Chronic Obstructive Pulmonary Disease (COPD) (NCT01922271), a randomized phase 4 study. The primary outcome is Forced Expiratory Volume in One Second (FEV1) Area Under Curve (AUC) 0-2.

2. Clinical Question

The question concerns an early, measured lung-function response under the study conditions. It is not a comparison of long-term symptoms, exacerbations, quality of life, or other outcomes. Those broader clinical outcomes are not reported in the registry record as results for this comparison. The trial record identifies the study as randomized and quadruple-masked, with a two-period cross-over design. The primary endpoint is a continuous measure, so the comparison focuses on group means and their uncertainty rather than on the proportion of participants meeting a response threshold.

3. Trial Design

This completed phase 4 study was randomized, double-blind, multicenter, and used a two-period, single-dose cross-over design. Enrollment was 152. The record describes participants with moderate to severe COPD and identifies the study as the FAST Study. Start and primary completion are recorded as 2013-08 and 2014-01.

Participants followed one of two sequences. In one sequence, NVA237 was given in Period 1 on day 1, with placebo to tiotropium, followed by a 7 day washout; tiotropium with placebo to NVA237 was given in Period 2 on day 8. The other sequence reversed the active treatments: tiotropium first, then NVA237 after the washout. Salbutamol was used as rescue medication. Placebos paired with active treatments are described in the sequence information; their use does not make this a placebo comparison for the primary result.

In a cross-over study, each participant can receive both active treatments, with the order varied across sequences. This allows within-participant comparisons in principle, because measurements under the two treatments can be related to the same participant. It also means interpretation depends on how period, sequence, and any residual effects are handled in the analysis. The statistical model and details of that handling are not reported in the registry record.

The primary outcome is reported for the Full Analysis Set, defined as randomized patients who applied at least one dose of study medication during at least one study period. The primary result lists 151 for NVA237 and 150 for tiotropium. The registry record does not report why the analysis counts differ from the enrollment figure, or how missing endpoint observations were handled. It reports no statistical analyses under the posted analysis listing, although summary outcome values and a comparison are available.

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.

PERIOD 1

WASHOUT Period

Reasons for not completing this period:

PERIOD 2

Analysis population for the primary outcome, as defined in the registry: The Full Analysis Set (FAS) consisted of all randomized patients who applied at least one dose of study medication during at least one study 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 Forced Expiratory Volume in One Second (FEV1) Area Under Curve (AUC) 0-2, measured over Day 1.

The primary endpoint was standardized FEV1 area under the curve from 0 to 2 hours on Day 1. FEV1, or forced expiratory volume in one second, measures the volume of air exhaled during the first second of a forced breath. The registry says that measurements between 0 minutes and 2 hours were combined using the trapezoidal rule, then divided by the measurement time of 2 hours. The reported unit is liters per hour.

As a general statistical explanation, an area-under-the-curve measure combines observations across a time window rather than selecting a single time point. Standardizing by the window length expresses the accumulated response as an average over that window. This can represent the early time course more broadly than a single reading, while still reducing it to one summary value for the treatment comparison.

FEV1 is a lung-function measure relevant to bronchodilation, which is the study’s focus. The endpoint therefore addresses an early physiological response after a single dose; it does not by itself represent symptoms, daily functioning, sustained response, or longer-term clinical outcomes. The registry also lists measures of specific airway resistance and lung volumes among the secondary outcomes, but only one secondary outcome has a posted numerical comparison in the record.

7. Results Posted in the Registry

• Tiotropium: mean 1.45 versus 1.49 on control; difference -0.04 (95% CI -0.13 to 0.06), standardized effect d = -0.09; z-test p = 0.443.

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.

Forced Expiratory Volume in One Second (FEV1) 15 Min Post Dose

• 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 deviations.
• Result:
  • Tiotropium: mean 1.40 versus 1.43 on control; difference -0.04 (95% CI -0.13 to 0.06), standardized effect d = -0.09; z-test p = 0.458.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tiotropium and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes span additional lung-function measures: FEV1 at 15 minutes, specific airway resistance, functional residual capacity, residual volume, total lung capacity, and inspiratory capacity. Together with the primary FEV1 area-under-the-curve endpoint, they reflect the study’s broad assessment of early bronchodilation and lung mechanics. However, numerical secondary results are not posted for most of these measures in the registry record. The one secondary comparison with numerical results is FEV1 15 minutes post dose.

That secondary FEV1 estimate is close to the primary estimate in direction and magnitude, and its confidence interval includes zero. This broadly aligns with the primary result’s lack of a clear separation between the treatment means. It does not demonstrate that all secondary measures had the same pattern: numerical values for the other listed outcomes are not reported in the registry record. Nor should one secondary estimate be treated as a comprehensive check of the full set of lung-function outcomes.

Secondary outcomes are generally interpreted more cautiously when many measures or time points are tested. As a general statistical point, making multiple comparisons increases the chance that at least one result appears noteworthy by chance if each is assessed without adjustment. The registry record does not report a multiplicity adjustment or a hierarchical testing procedure. The posted secondary p-value is unadjusted. This makes it less suitable as stand-alone confirmatory evidence than a prespecified primary comparison and means apparent patterns across endpoints should be treated as descriptive.

The number of listed outcomes is not a substitute for the missing results or for a documented testing plan. The broad outcome set may help characterize early lung function, but the posted record supports only limited conclusions about secondary endpoints. The primary result remains the central comparison, and the secondary information does not establish a treatment difference that the primary endpoint did not clearly show.

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

• Forced Expiratory Volume in One Second (FEV1) 15 Min Post Dose
• Specific Airway Resistance (sRAW)
• Functional Resistance Capacity (FRCpleth)
• Residual Volume (RV)
• Total Lung Capacity (TLC)
• Inspiratory Capacity (IC)

9. Statistical Interpretation

10. Statistical Methods Explained

The endpoint is continuous: it is measured on a numerical scale, and the posted summary is a mean with a standard deviation. A mean describes the average endpoint value in a group, while a standard deviation describes how dispersed individual observations are around that mean. The standard deviation is not the same as the uncertainty in the estimated mean difference; the latter also depends on the analysis and the information available.

What does the mean difference represent?

The comparison is expressed as tiotropium relative to NVA237. The mean difference of -0.037 liters per hour is the estimated contrast in that direction. A negative estimate indicates that the reported mean for tiotropium was lower than the mean for NVA237 in the registry’s comparison. The estimate is a summary of the data, not a statement that every participant had a lower value under tiotropium. Individual responses can vary, and the registry record does not provide participant-level measurements.

The posted group means are 1.49 and 1.453 liters per hour. Those averages provide context for the contrast, but averages alone do not reveal the spread of paired within-participant differences. This matters in a cross-over design: the treatment comparison may use each participant’s measurements under both conditions, rather than treating the two treatment groups as if they were independent sets of people. The statistical model and the covariance assumptions used for the sponsor’s analysis are not reported in the registry record.

What does a confidence interval add?

A confidence interval gives a range of values compatible with the data under the method used to construct it. In repeated sampling under the relevant model, intervals formed by the same procedure would contain the true parameter at the stated confidence level at the corresponding long-run rate. It is not a range containing a known proportion of individual participant values, and it is not a probability statement about the fixed treatment effect after seeing the data.

The primary confidence interval crosses zero. Zero represents no mean difference for the contrast as defined. Because the interval includes zero and also extends to both negative and positive values, the data do not distinguish a null contrast from contrasts in either direction at the interval’s level. The interval is more informative than the p-value alone because it shows the range of effect estimates that remain compatible with the observed summary and method. The registry record does not state the confidence level or provide the sponsor’s interval-construction method in this discussion of the posted result.

How should the p-value be read?

The unadjusted p-value for the primary comparison is 0.443. As a general statistical explanation, a p-value is calculated assuming a specified null hypothesis and analysis model; it describes how unusual data at least as discrepant as those observed would be under that framework. It is not the probability that the null hypothesis is true, and it does not quantify clinical importance. The record labels the comparison unadjusted. It does not report a multiplicity-adjusted p-value, and the sponsor’s full testing strategy is not reported in the registry record.

A large p-value does not demonstrate that a meaningful difference is absent. To support a conclusion that effects are sufficiently alike, investigators generally need a prespecified equivalence or non-inferiority margin and an analysis designed for that question. Such a margin and such an analysis are not reported in the registry record. The interpretation is therefore limited to the posted estimate, interval, and unadjusted p-value for the primary endpoint.

Why can cross-over analyses need special care?

In a cross-over design, participants receive treatments in a sequence, and observations can be affected by both treatment and period. The washout is intended to separate periods, but its presence alone does not establish that carry-over effects are impossible. General statistical practice may account for period and sequence and may use within-participant correlations. Whether and how those features were modeled in the primary analysis is not reported in the registry record. No assumptions about them should be inferred from the reported group means.

The record describes randomization and quadruple masking. Randomization helps allocate treatment sequence without systematic selection, while masking is intended to limit influences on care, measurement, or assessment. The registry does not specify which roles were included in quadruple masking or give further operational details. The design labels alone do not reveal how successfully masking was maintained.

What do the planning illustrations mean?

The planning figures are illustrations calculated from the observed effect, rather than documentation of the trial’s original design. For the primary endpoint, the displayed scenarios use 100%, 75%, and 50% of the observed effect. Under the stated planning assumptions, the participants per arm for 80% power are 2,008, 3,569, and 8,030 for those scenarios; the participants per arm for 90% power are 2,688, 4,778, and 10,749. These are planning quantities, not participant counts from the trial.

General statistical reasoning explains why the figures rise as the target effect becomes smaller: a smaller difference is harder to distinguish from random variation, so a larger planned sample is needed under otherwise fixed assumptions. The original sample-size justification, target effect, and design assumptions are not reported in the registry record. The planning illustration does not establish the power of the completed study, and its assumptions should not be confused with the unknown original design plan.

11. Confidence Intervals and Precision

The primary estimate is -0.037 liters per hour for tiotropium relative to NVA237. Its confidence interval crosses zero and spans possible differences in either direction. This means the observed estimate is not highly decisive about the sign of the contrast: the posted data are compatible with a modest advantage for either treatment on this measure, as well as with little or no difference. The registry record does not report a prespecified clinically important difference against which to judge the interval’s limits.

Precision concerns how narrowly the treatment effect is estimated, not whether a result is important or whether a treatment should be used. A narrow interval would restrict the range of plausible effects more than a wide interval. Here, the interval’s inclusion of zero shows that no difference remains compatible with the result under the interval method. Its extent also means that the estimate should not be read as a precise measurement of a single underlying contrast. The exact confidence limits are posted with the comparison; their interpretation depends on the analysis method, which is not described in detail in the registry record.

The primary analysis counts were 151 for NVA237 and 150 for tiotropium. In a cross-over trial, those figures should not be read as independent treatment-group participant totals: the sequences involve treatment exposure in both periods. The registry record does not report the number of paired endpoint observations used in the sponsor’s model or how incomplete pairs were handled. Those details affect how much information contributes to a cross-over treatment contrast.

The secondary 15-minute FEV1 estimate is also accompanied by an interval that crosses zero. Its unadjusted comparison offers no strong evidence of a distinct contrast at that time point, but its uncertainty and secondary status matter. Neither the primary nor secondary interval alone settles whether a difference is clinically meaningful; that requires context and a prespecified threshold, which is not reported in the registry record.

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 planning figures are stated as participants per arm, not as a total number of participants and not as total events. The record’s assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. These assumptions describe the planning illustration, not the trial’s original sample-size calculation; the original design assumptions are not reported in the registry record.

For the primary endpoint, the rows correspond to planning for 100%, 75%, and 50% of the observed effect. The participants per arm for 80% power are 2,008, 3,569, and 8,030, respectively. The participants per arm for 90% power are 2,688, 4,778, and 10,749, respectively. The columns describe different planning targets: 80% or 90% power is the probability, under the assumed effect and analysis conditions, of rejecting the null hypothesis at the stated significance level when that effect is truly present. Higher planned power generally requires more participants under otherwise unchanged assumptions.

The illustrations also make clear that smaller effects need more participants to detect. Planning for 75% or 50% of the observed effect requires larger per-arm sample sizes than planning for the full observed effect. The displayed curve represents this relationship across the assumed effect sizes; it should be read as a planning aid, not as a description of the trial’s observed results. These figures are not observed power.

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 = -0.037; pooled standard deviation σ = 0.418.
2. n = 2 × (1.96 + 0.842)² × 0.418² / -0.037² = 2,007.3, rounded up to 2,008 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 <- -0.0369999999999999                      # observed difference in means
sigma <- 0.41839433180868                     # 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(1922271)
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 = 2,008 (80% power), 2,688 (90% power)
 75% of observed effect: n per arm = 3,569 (80% power), 4,778 (90% power)
 50% of observed effect: n per arm = 8,030 (80% power), 10,749 (90% power)
power.t.test: 2008.2 
Simulated power at n = 2,008 per arm: 0.798 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The record identifies one primary endpoint and lists six secondary outcomes. It also reports an unadjusted p-value for the primary comparison and an unadjusted p-value for the one secondary comparison with numerical results. A plan for controlling the overall type I error across endpoints or time points is not reported in the registry record. No multiplicity-adjusted results or hierarchical testing strategy are reported.

Multiplicity matters because, as a general statistical principle, testing more hypotheses creates more opportunities to observe a small p-value even when there is no corresponding effect. Without a stated strategy, the secondary findings should be treated as exploratory or descriptive rather than as a set of independent confirmatory claims. The record does not report whether additional analyses were planned or conducted outside the posted results.

Missing-data handling is not reported in the registry record. The primary population is defined as randomized patients who received at least one dose during at least one study period, but the record does not describe how missing endpoint measurements, incomplete cross-over pairs, withdrawals, or protocol deviations were handled. It also does not state whether any imputation was used. These details matter because missing observations can affect both the estimate and its uncertainty, especially when measurements from both treatment periods contribute to the comparison.

The record labels the primary population as the Full Analysis Set and gives the analysis counts for each treatment. It does not report a separate per-protocol analysis or sensitivity analyses. The posted analysis listing contains no analyses, despite the availability of outcome summaries and comparisons. The exact sponsor analysis plan, model specification, covariates, period and sequence terms, and treatment of within-participant correlation are not reported in the registry record. Consequently, the posted summary supports interpretation of the reported estimate and interval, but not reconstruction of the full analysis process.

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 0.5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: lung neoplasm malignant (0.7%), nephrectomy (0.7%), acute myocardial infarction (0.7%), myocardial infarction (0.7%).

The registry lists serious adverse events for 2 of 152 at risk in the NVA237 group and 2 of 151 at risk in the tiotropium group. Other adverse events are listed for 8 of 152 and 15 of 151, respectively. These are group-specific counts and denominators as recorded; they should not be converted into a causal comparison from these summaries alone. In a cross-over study, the group labels and exposure periods need to be understood alongside the study design.

The registry’s listed serious-event terms include lung neoplasm malignant, nephrectomy, acute myocardial infarction, and myocardial infarction, each recorded as 0.7%. The record does not provide enough detail in this summary to assign each listed term to a particular treatment group or to infer a treatment-related cause. Deaths are not reported in the registry record.

Adverse-event counts are descriptive safety information. They do not by themselves establish whether events were caused by treatment, and the registry record does not report a comparative safety analysis or detailed event timing. The counts should be interpreted with the denominators and the cross-over exposure pattern in mind.

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

The posted result estimates an early lung-function contrast after single doses of NVA237 and tiotropium in people with moderate to severe COPD. For the primary standardized FEV1 area under the curve from 0 to 2 hours on Day 1, the mean difference was -0.037 liters per hour for tiotropium relative to NVA237. The confidence interval includes zero, and the unadjusted p-value was 0.443. These results do not establish a clear difference on the primary endpoint.

They also do not establish that the treatments are exactly equal. The interval includes estimates on either side of no difference, and the record does not report an equivalence margin or a non-inferiority framework. Whether the range of effects is clinically important cannot be decided from the p-value alone, and a clinically important threshold is not reported in the registry record.

The study’s time frame and outcome define what the finding can address. The measurement concerns early bronchodilation after a single dose, not response over prolonged treatment. The registry record does not report results for long-term symptoms, exacerbations, hospital use, quality of life, or other outcomes beyond its listed lung-function measures. Absence of those results in this record should not be interpreted as evidence about them.

The design was randomized and cross-over, with a 7 day washout between periods. The sequence allows each participant to receive both active treatments, but the posted summary does not describe the sponsor’s model or how period and sequence were handled. This limits independent assessment of the analysis details. The available evidence is therefore best understood as a registry-reported estimate with uncertainty for a specific early physiological endpoint, not as a general conclusion about overall comparative benefit or risk.

Finally, statistical uncertainty and clinical meaning are different questions. The estimate and interval describe how precisely the comparison is measured under the analysis method; they do not supply a clinical threshold or dictate a treatment decision. No medical advice follows from these registry statistics alone.

17. Why This Trial Matters Statistically

This study illustrates why a clinical trial result should be read through its endpoint, design, and uncertainty together. A randomized cross-over design offers a way to compare two treatments within participants, which can be useful for short-term physiological measurements. At the same time, it requires attention to period, sequence, washout, and paired observations. The registry gives the sequence and washout description but not the sponsor’s full model, so the reported contrast cannot be independently reconstructed from the summary alone.

The endpoint is also a useful example of summarizing a response over time. Rather than relying only on a single measurement, the primary outcome combines FEV1 observations from 0 minutes to 2 hours and standardizes the area under the curve by the measurement time. That produces one continuous summary for comparison, while retaining the important limitation that an early lung-function measure is not the same as a long-term clinical outcome.

The mean difference is near zero, but the confidence interval crosses zero. This pairing of an estimate with its uncertainty prevents over-reading the point estimate and also avoids treating a non-small p-value as proof of no effect. The registry does not report an equivalence margin, which is a reminder that failure to establish a difference and demonstration of equivalence are distinct statistical conclusions.

The secondary outcomes broaden the intended physiological assessment, but most do not have numerical results in the registry record. The record also does not report multiplicity control. These gaps matter because a long list of outcomes can create an impression of comprehensive evidence even when the posted numerical evidence is limited. The analysis is most informative when the primary comparison is distinguished from secondary, unadjusted, or unreported results.

Finally, planning figures based on the observed effect can help illustrate how sample-size requirements change with the target effect. They are not evidence of the original design rationale or of achieved power. Keeping that distinction clear helps separate retrospective planning illustrations from the actual trial design and its observed data.

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 registry record offers limited detail for assessing the primary analysis. It provides treatment means, a mean difference, an interval, and an unadjusted p-value, but does not report the full statistical model, the confidence-interval construction method, or the handling of period and sequence in the cross-over analysis. It also does not explain how within-participant correlation was accommodated. These omissions prevent a reader from reproducing the sponsor’s analysis from the posted summary.

The endpoint counts differ between the primary treatment summaries, and the record does not explain the reasons. It does not report whether all participants contributed paired observations or how incomplete periods were handled. Missing-data methods and sensitivity analyses are not reported in the registry record. The distinction between enrollment and analysis counts should therefore be retained rather than assuming all enrolled participants contributed complete data.

Most of the listed secondary outcomes have no posted numerical results. The single secondary comparison with numerical results is unadjusted, and a multiplicity plan is not reported. This limits conclusions about the broader set of lung-function measures. The record also does not report a clinically important difference, an equivalence margin, or a non-inferiority margin for the primary endpoint.

The single-dose, early assessment provides a narrow view of treatment response. Results for sustained treatment, symptoms, exacerbations, or other patient-centered outcomes are not reported in the registry record. The registry also provides limited detail about the operational aspects of masking and adverse-event attribution. These limitations do not invalidate the posted summary, but they define the boundaries of what it can support.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Efficacy of NVA237 Compared to Tiotropium in Patients With Chronic Obstructive Pulmonary Disease (COPD) — NCT01922271.
• Registry record last updated 2015-01-01; status last verified 2014-12.
• Results first posted 2015-01-01.
• 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

NCT01922271 is a completed phase 4 randomized, quadruple-masked, two-period cross-over study of NVA237 and tiotropium in people with moderate to severe COPD. Enrollment was 152. The primary outcome was standardized FEV1 area under the curve from 0 to 2 hours on Day 1.

The primary mean difference was -0.037 liters per hour for tiotropium relative to NVA237, with a confidence interval crossing zero and an unadjusted p-value of 0.443. The result does not establish a clear difference on this early lung-function endpoint. The record’s secondary numerical results are limited, and details of the sponsor’s full analysis and missing-data methods are not reported in the registry record.