A Non-inferiority, Comparative Study Between Foraseq®, Eurofarma´s Formoterol/Budesonide and Alenia® in Asthma: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Non-inferiority, Comparative Study Between Foraseq®, Eurofarma´s Formoterol/Budesonide and Alenia® in Asthma (NCT01167010), a randomized phase 3 study. The primary outcome is Forced Expiratory Volume in 1 Second (FEV1) at the Final Visit (FV).

2. Clinical Question

3. Trial Design

The registry describes a phase 3, randomized, open-label, parallel-group study of asthma formulations. Enrollment is listed as 552, and the status is completed. The listed study start is 2011-04 and primary completion is 2011-08. Eurofarma Laboratorios S.A. is the sponsor. The registry record does not report the randomization procedure, allocation concealment, or further operational detail about how participants were assigned.

Three formulations were studied: Formoterol/Budesonide, Foraseq and Alenia. Each arm description specifies a 12/400 µg dosage twice a day for 12 weeks. The primary comparison is Formoterol/Budesonide versus Alenia, with FEV1 at the final visit as the outcome and the per-protocol population as the stated analysis population. Foraseq appears in the secondary outcome summary, which assesses FEV1 in the ITT population across the three groups.

Open-label means that the study was not masked, according to the registry's masking field. The registry record does not describe whether endpoint assessment or data analysis was blinded. It also does not report the planned sample-size justification, the study's original design assumptions, or a detailed statistical analysis plan. The enrollment figure is a trial-level registry entry; the endpoint summaries use their own analysis-group counts, which need not be the same as enrollment.

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

Analysis population for the primary outcome, as defined in the registry: The study aims to demonstrate the non-inferiority of the FEV1 (in liters) at the final visit (FV) in the per-protocol (PP) population results for the Formoterol/Budesonide product compared to Alenia.

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 1 Second (FEV1) at the Final Visit (FV), measured over 12 weeks.

Forced expiratory volume in one second (FEV1) is the volume of air a person can forcefully exhale during the first second of an exhalation. It is recorded in liters and treated as a continuous measure. In general, lung-function measures such as FEV1 can be used to assess pulmonary function and to compare average values between study groups.

The primary endpoint is mean FEV1 at the final visit, with a timeframe of 12 weeks. The registry's primary objective describes the comparison as a non-inferiority assessment in the per-protocol population. The endpoint therefore concerns the difference in average FEV1 between Formoterol/Budesonide and Alenia at the stated visit; it is not a direct measure of every aspect of asthma control, symptoms or treatment experience.

The posted endpoint summaries give a mean and standard deviation for each primary comparison group. The standard deviation describes the spread of individual measurements around the group mean. The registry record does not report the non-inferiority margin, so the clinical threshold that would define an acceptably small loss in FEV1 cannot be identified from the record. The endpoint description also does not provide details about visit timing within the 12-week period or how missing FEV1 measurements were handled.

7. Results Posted in the Registry

• Alenia: mean 2.51 versus 2.53 on control; difference -0.02 (95% CI -0.20 to 0.16), standardized effect d = -0.03; z-test p = 0.823.

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.

FEV1 (L) in VF in the ITT Population, to Assess the Difference Between the Three Groups

• 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:
  • Formoterol/Budesonide: mean 2.52 versus 2.49 on control; difference 0.03 (95% CI -0.15 to 0.21), standardized effect d = 0.04; z-test p = 0.739.
  • Foraseq: mean 2.46 versus 2.49 on control; difference -0.03 (95% CI -0.22 to 0.16), standardized effect d = -0.04; z-test p = 0.756.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Formoterol/Budesonide 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 Foraseq and the control. The interval gives the range of effects that remain compatible with the data.

The secondary endpoint considers FEV1 in the ITT population and places the three formulations in a shared comparison. Across the posted group means, the values are close, and neither recalculated comparison with Alenia is clearly separated from zero by its confidence interval. The overall pattern is therefore broadly similar to the primary summaries: the posted data do not indicate a clear difference in average FEV1, while leaving uncertainty about the size and direction of possible differences.

This secondary endpoint complements, but does not duplicate, the primary result. It uses the ITT population rather than the primary endpoint's per-protocol population and includes Foraseq as an additional formulation. A difference in population can change which participants contribute to an estimate, so the secondary comparisons should not be treated as a direct replication of the primary analysis. The registry record does not give the detailed definitions of the analysis populations or explain how the two analyses were intended to work together.

The secondary comparisons have unadjusted p-values. General: when multiple outcomes or contrasts are tested, the chance of at least one apparently notable result can increase unless the analysis plan accounts for the number and purpose of the tests. Unadjusted results can still be descriptive, but they carry less confirmatory weight when multiplicity handling and a prespecified hierarchy are not reported. The registry record does not report a multiplicity procedure or a formal sponsor analysis for these secondary comparisons.

Accordingly, the secondary findings are best read as supportive descriptive context for the primary FEV1 comparison, not as independent proof of equivalence or as a replacement for the missing non-inferiority margin. They also do not establish conclusions about symptom control or adherence: although those topics appear in the study objectives, corresponding results are not reported in the registry record.

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

• FEV1 (L) in VF in the ITT Population, to Assess the Difference Between the Three Groups

9. Statistical Interpretation

10. Statistical Methods Explained

General: a continuous outcome such as FEV1 can be summarized by a group mean and standard deviation. The mean describes the average observed measurement; the standard deviation describes how dispersed measurements are around that average. The posted results give both for the primary and secondary endpoint groups. Neither summary reveals the full distribution of individual measurements, and a mean comparison does not describe every participant's response.

What does the mean difference represent?

The mean difference expresses the contrast between two group averages in the outcome's original units, here liters. A value near zero indicates that the two posted group means are close. The sign depends on which group is subtracted from which, so interpretation should follow the contrast as defined in the posted comparison, not the sign alone. For the primary comparison, the registry summaries are 2.53 liters and 2.51 liters, and the recalculated difference is -0.02 liters.

General: a standard error describes the sampling uncertainty in an estimate, rather than the spread of individual measurements. The posted calculations include group standard errors and a pooled standard deviation. A pooled standard deviation combines variability information from the compared groups for the simple comparison; it is not a measure of uncertainty in the mean difference by itself. The registry record does not report a more detailed model or adjustments for other participant characteristics.

How should the confidence interval be understood?

General: a confidence interval gives a range of values compatible with the data and the calculation procedure, making the uncertainty around an estimate more visible than a single point estimate. A narrower interval indicates greater precision; a wider one indicates less precision. If an interval for a difference spans zero, the data are compatible with no difference as well as with differences in either direction at the interval's stated confidence level. The confidence level is not reported in the registry record, so it should not be assumed from the summaries alone.

For the primary mean difference, the posted interval spans zero. The intervals for both secondary comparisons also span zero. These intervals address uncertainty about the mean differences under the simple calculations; they do not by themselves answer the non-inferiority question. That question requires comparing the interval with a prespecified non-inferiority margin, which is not reported in the registry record.

What does the p-value say?

General: a p-value describes how unusual data at least as incompatible with a specified null hypothesis would be if that hypothesis and the statistical model were correct. It is not the probability that the null hypothesis is true, and it is not the probability that the observed result arose “by chance.” The recalculated unadjusted p-values for the primary and secondary mean comparisons are 0.823, 0.739 and 0.756. They correspond to tests of a difference from zero, not a documented test against a non-inferiority margin. The record does not report adjustments for multiplicity.

These comparisons are labelled recalculated because they are simple, unadjusted calculations from the posted group summaries. The discrepancy indicator is false, but the registry record does not list sponsor-reported analyses. A recalculated p-value and interval should not be presented as if they were a full prespecified analysis, particularly when the analysis plan and non-inferiority margin are not reported.

Why does non-inferiority need a margin?

General: a non-inferiority analysis asks whether an intervention's outcome is not worse than a comparator by more than a clinically acceptable amount. The margin must be specified in advance and interpreted in the outcome's units. A finding of no statistically clear difference is not sufficient: an imprecise comparison might be compatible with both small and substantial differences. The posted record names non-inferiority as the primary objective but does not state the margin, the direction of the formal test, or the decision rule. Accordingly, the available summaries cannot verify whether a formal non-inferiority criterion was met.

The trial description also identifies a per-protocol population for the primary analysis and an ITT population for the secondary endpoint. General: these analysis populations can answer related but not identical questions. A per-protocol analysis focuses on participants meeting protocol requirements, while an ITT analysis generally follows assigned groups regardless of adherence; the exact definitions used in this trial are not reported in the registry record. No detail is given about exclusions, protocol deviations, missing observations, imputation, model assumptions or sensitivity analyses. These omissions matter because choices about analysis populations and incomplete outcome data can affect estimates and their uncertainty.

The planning illustrations use a two-sided significance level of 0.05, equal allocation between two arms and a normal approximation. They use stated fractions of the observed effect as the target effects. These are generic planning calculations based on the observed summary effects, not the trial's own reported design justification. The registry record does not report the original sample-size assumptions or whether the trial was designed and powered for the stated non-inferiority question.

11. Confidence Intervals and Precision

The primary estimate is a mean difference of -0.02 liters, and its posted confidence interval extends on both sides of zero. That interval conveys uncertainty beyond the point estimate: the summaries do not pin down a single value or even a single direction for the underlying difference. The interval's confidence level is not reported in the registry record. Its width also means that a near-zero point estimate should not be treated as proof of close equivalence.

The secondary intervals likewise span zero. Taken together, the estimates are compatible with small differences in either direction, while the uncertainty prevents a precise claim that the group means are identical. The posted intervals are for recalculated unadjusted comparisons. They do not incorporate a documented adjustment for multiple comparisons, and they do not answer whether a difference falls within a non-inferiority margin.

Precision and statistical significance are related but not interchangeable. A confidence interval that crosses zero can arise when the point estimate is close to zero, when uncertainty is substantial, or both. Here the group standard deviations are much larger in scale than the mean differences, while the reported group counts determine how precisely the means can be compared. The registry record does not report the planned precision target or the original assumptions used to select enrollment.

Most importantly, non-inferiority depends on the position of the entire relevant interval relative to a prespecified margin. Since that margin is not reported, the interval cannot be classified against the trial's formal non-inferiority criterion from the registry record alone. The point estimate and interval are informative descriptions of the posted data, but they do not replace the missing threshold or sponsor analysis.

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

The 80% power column gives the estimated participants per arm under those assumptions for a design with an 80% chance of detecting the specified effect, if that effect and the calculation assumptions were correct. The 90% power column describes the corresponding planning target for a 90% chance. These probabilities are properties of a hypothetical design under its assumptions, not probabilities that the trial's conclusion is correct.

As the target effect becomes smaller, more participants are needed to distinguish it from random variation with the same planning power and significance level. Reading across the rows therefore illustrates how sensitive sample-size requirements are to the effect chosen for planning. The observed differences in these summaries are small, so planning around a fraction of an already small observed effect produces particularly large illustrative requirements.

The planning values are not observed power. Observed power is not a useful substitute for interpreting the estimate and its confidence interval after results are known. These figures also do not establish that the completed trial had adequate power for non-inferiority: the trial's original design assumptions and its non-inferiority margin are not reported in the registry record.

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 = -0.020; pooled standard deviation σ = 0.780.
2. n = 2 × (1.96 + 0.842)² × 0.780² / -0.020² = 23,888.3, rounded up to 23,889 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 <- -0.02                      # observed difference in means
sigma <- 0.780196528136697                     # 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(1167010)
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 = 23,889 (80% power), 31,980 (90% power)
 75% of observed effect: n per arm = 42,469 (80% power), 56,853 (90% power)
 50% of observed effect: n per arm = 95,554 (80% power), 127,919 (90% power)
power.t.test: 23889.3 
Simulated power at n = 23,889 per arm: 0.797 (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 registry record does not report a multiplicity adjustment, a testing hierarchy, or a detailed statistical analysis plan. The primary endpoint is identified as a non-inferiority analysis, and a secondary FEV1 endpoint is also posted with two comparisons against Alenia. The recalculated p-values are unadjusted. Without a stated plan for handling multiple comparisons, the secondary p-values should be considered descriptive rather than treated as a set of confirmatory tests.

The record names the per-protocol population for the primary endpoint and the ITT population for the secondary endpoint, but does not define membership in either population. It does not report the number of participants excluded from the primary analysis, reasons for exclusions, protocol deviations, or whether the posted group counts represent all assigned participants or only those with endpoint data. Such information is important for understanding how the reported averages relate to randomization and to the intended trial population.

Missing-data handling is not reported in the registry record. There is no description of the extent or pattern of missing FEV1 measurements, any imputation method, or sensitivity analyses. General: if outcome data are missing, the approach to those observations can affect both the estimated group difference and its uncertainty, particularly if missingness is related to outcomes or treatment experience.

The registry record also does not report the non-inferiority margin, the original sample-size justification, interim analyses, or the sponsor's formal analysis results. The number of reported analyses is listed as zero. These gaps prevent assessment of whether the displayed summaries follow the planned decision rule, how deviations from the plan were handled, or whether multiplicity and missingness were addressed in the study's formal conclusions.

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 1% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: thrombocytopenia (0.6%), leukopenia (0.6%).

The registry lists serious adverse event counts with groups at risk: Formoterol/Budesonide has 1 affected participant among 154 at risk, while Foraseq and Alenia each have 0 affected participants, with 145 and 151 at risk respectively. These are counts, not estimates of comparative safety. The registry record does not provide a statistical comparison, follow-up detail for these outcomes, or enough context to determine whether the groups differ in risk.

Thrombocytopenia and leukopenia are listed among the top serious adverse event terms, each at 0.6%. The registry record does not clearly link these terms to a particular arm in the information available for interpretation, so they should not be attributed to a group. Death counts are not reported in the registry record. The listed figures are limited to the serious adverse event summary and do not describe all possible adverse events or establish a safety conclusion.

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

The posted results describe average FEV1 values at the final visit and simple comparisons between study groups. The primary means are close, and the recalculated unadjusted comparison does not show a statistically clear difference from zero. The secondary summaries follow a similar broad pattern. These findings are a description of the available registry summaries, not a complete account of the trial's formal analysis.

They do not establish that the formulations are equivalent. Failure to show a statistically clear difference is not evidence that the true difference is exactly zero; estimates remain uncertain, and their intervals include values in both directions. They also do not establish that Formoterol/Budesonide is non-inferior to Alenia. That conclusion requires a reported non-inferiority margin and a formal comparison of the relevant interval with that margin, neither of which is available in the registry record.

The results concern FEV1, a measure of pulmonary function, at the stated endpoint and time. They should not be extended to all asthma-related outcomes. Although the trial summary mentions symptom control and treatment compliance as secondary objectives, corresponding results are not reported in the registry record. The posted FEV1 summaries also do not describe longer-term outcomes or outcomes beyond the specified study period.

The safety counts are similarly limited. They report the serious adverse event figures recorded for the three groups but do not provide enough information for a comparative safety assessment. No medical advice or treatment recommendation follows from these statistical summaries. The most defensible reading is that the registry provides descriptive group results with uncertainty, while key information needed for a formal non-inferiority interpretation and fuller evaluation is not reported.

17. Why This Trial Matters Statistically

This trial raises a central statistical distinction: a non-inferiority objective is not answered simply by finding no statistically significant difference. The primary endpoint is explicitly framed as non-inferiority, but the registry record does not report the margin that defines an acceptable difference. Without that threshold, readers cannot determine whether the uncertainty around the estimate meets the study's stated objective.

The record also juxtaposes a primary per-protocol analysis with a secondary ITT summary. General: both populations can be relevant in a non-inferiority setting, but their definitions, roles and handling of deviations need to be specified to interpret evidence responsibly. Those details are not reported. The posted summaries still allow a useful descriptive comparison, but they cannot replace the missing analysis plan and formal result.

Another statistical lesson is that point estimates, intervals and p-values answer different questions. The group means and mean differences describe estimated contrasts; confidence intervals express uncertainty; unadjusted p-values test a particular null hypothesis. None by itself supplies the non-inferiority margin. Treating a large p-value as evidence of equality would confuse absence of clear evidence for a difference with evidence that differences are acceptably small.

The secondary comparisons and planning illustrations add context, but also require care. Unadjusted secondary results have less confirmatory force when multiplicity procedures are not reported. Sample-size illustrations based on observed effects are useful for understanding planning assumptions, but they do not establish the original design rationale or observed power. Together, these points show why clear reporting of thresholds, populations, missing-data methods and prespecified analysis decisions is essential to interpreting a non-inferiority trial.

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.

Several limitations are specific to what is recorded for this trial. The most consequential is that the primary objective is described as non-inferiority, but the non-inferiority margin and formal decision rule are not reported in the registry record. The posted mean difference and its interval therefore cannot establish whether the stated objective was met.

The primary comparison is represented by group means, standard deviations and a simple recalculated contrast. The registry record does not list sponsor-reported analyses, a detailed model, covariate adjustments, or sensitivity analyses. The recalculated comparisons are unadjusted and should not be mistaken for the study's complete prespecified analysis. The record does not report the confidence level for the intervals.

Analysis-population detail is limited. The primary endpoint is assigned to the per-protocol population and the secondary outcome to the ITT population, but the exact definitions, exclusions, adherence rules and participant flow are not reported in the registry record. Missing endpoint data and their handling are also not described. These omissions limit assessment of selection, robustness and how well the results reflect the randomized groups.

The registry describes symptom control and treatment compliance as secondary objectives, but results for those outcomes are not reported. The available FEV1 summaries therefore cover only a portion of the objectives described. The serious adverse event information is also limited: the record gives affected counts and top terms, but not a complete comparative safety analysis; deaths are not reported in the registry record. Finally, the original sample-size justification and design assumptions are not reported, so the planning illustrations cannot be used to infer the trial's intended power.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: A Non-inferiority, Comparative Study Between Foraseq®, Eurofarma´s Formoterol/Budesonide and Alenia® in Asthma — NCT01167010.
• Registry record last updated 2025-05-01; status last verified 2025-03.
• Results first posted 2025-05-01.
• 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

NCT01167010 is a completed, randomized, open-label, parallel-group phase 3 study sponsored by Eurofarma Laboratorios S.A. It enrolled 552 participants with asthma according to the registry entry. The primary question concerned non-inferiority in FEV1 at the final visit after 12 weeks, comparing Formoterol/Budesonide with Alenia in the per-protocol population. Foraseq was included in the study, and the secondary FEV1 summary used the ITT population.

The posted primary means are 2.53 liters for Formoterol/Budesonide and 2.51 liters for Alenia, with a recalculated mean difference of -0.02 liters and unadjusted p-value of 0.823. Secondary summaries show close group means, with recalculated unadjusted comparisons that do not establish a clear difference. The registry record does not report the non-inferiority margin, formal sponsor analyses, missing-data methods or multiplicity procedure. The posted statistics are therefore descriptive evidence, not a complete formal determination of non-inferiority.