The Confirmatory Study of TAU-284 in Pediatric Patients With Perennial Allergic Rhinitis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The Confirmatory Study of TAU-284 in Pediatric Patients With Perennial Allergic Rhinitis (NCT01861522), a randomized phase 3 study. The primary outcome is Change From Baseline in Total Score for the Three Major Nasal Symptoms [Sneezing, Rhinorrhea, and Nasal Congestion].

2. Clinical Question

The study asked whether TAU-284 could be distinguished from placebo on change in the combined score for the three major nasal symptoms in pediatric patients with perennial allergic rhinitis. The registry also identifies safety investigation as an objective. The primary outcome concerns symptom-score change between baseline and Week 2, rather than a diagnosis or a broader measure of health.

The registry’s stated objective was to confirm superiority of TAU-284 over placebo after two weeks of administration and to investigate safety. The posted primary outcome addresses the symptom-score comparison. Whether the registry’s planned definition of superiority, analysis population, or decision rule was met cannot be established from the available record.

3. Trial Design

This is a Phase 3, randomized, parallel-group, triple-masked, placebo-controlled study. The registry reports enrollment of 473. The arm-level primary outcome results list 240 participants in the TAU-284 arm and 232 in the placebo arm. These are the outcome counts posted for the comparison; the registry record does not explain the relationship between those counts and the enrollment figure or describe participant flow.

The two arms received tablets on matching schedules. The TAU-284 description specifies two 5mg tablets orally twice a day, after breakfast and after dinner or before bed. The placebo description specifies two placebo tablets at those same times. The record identifies the study intervention as bepotastine besilate and labels the active arm TAU-284.

The study’s stated aim was to compare TAU-284 with placebo after two weeks of administration in pediatric patients with perennial allergic rhinitis, while also investigating safety. The primary assessment was change from baseline in the total score for sneezing, rhinorrhea, and nasal congestion, with the timeframe stated as baseline and Week 2. Additional listed outcomes include individual nasal symptom scores, local nasal findings, allergic-rhinitis severity, and adverse events and adverse drug reactions.

Further design details that would help interpret the result—including recruitment and eligibility criteria, the randomization procedure, concealment procedures, the precise masking roles, site information, and the trial’s own statistical analysis plan—are not reported in the registry record. The record also does not report the original sample-size justification, any interim analyses, or details of follow-up beyond the stated primary timeframe. Those omissions limit reconstruction of the study conduct and the intended analysis from the registry entry alone.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline in Total Score for the Three Major Nasal Symptoms [Sneezing, Rhinorrhea, and Nasal Congestion], measured over Baseline and Week 2.

The primary endpoint is change from baseline in the total score for sneezing, rhinorrhea, and nasal congestion, assessed at baseline and Week 2. Each of the three major nasal symptoms contributes to a combined score. The registry describes a 5-point scale ranging from 0, meaning no symptoms, to 4, meaning very severe symptoms. A lower score therefore corresponds to fewer or less severe symptoms on this scale.

The registry reports the arm results as least-squares means, with standard errors as the dispersion measure. The TAU-284 arm’s posted mean change is -1.579 units on the scale, and the placebo arm’s is -1.11. Negative changes indicate a decline in score from baseline. The endpoint is useful for comparing average change in the symptom burden represented by the combined measure, while retaining the scale’s direction and clinical content.

A combined score can provide a single summary of several related symptoms, but it does not show whether every symptom changed to the same extent. The registry separately lists individual symptom scores among secondary outcomes. It does not report the construction details beyond the symptom components and scale range, nor does it explain how the least-squares means were estimated. The record also does not state a threshold for a change that patients would regard as important.

7. Results Posted in the Registry

• TAU-284: mean -1.58 versus -1.11 on control; difference -0.47 (95% CI -0.72 to -0.22), standardized effect d = -0.34; z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is a continuous score, and the registry reports a mean of that measure for each arm. A mean describes the average observed change, while individual participants may have changes above or below it. The reported values are least-squares means. In general, a least-squares mean is an estimate of an arm mean from a statistical model; the registry record does not describe the model or its covariates, so the precise adjustment behind these estimates is not reported.

What does the mean difference represent?

The posted comparison is a mean difference for TAU-284 relative to placebo. It is -0.469 units on the score. The calculation uses the posted arm summaries; its direction follows the order of the arms, with TAU-284 first and placebo as the comparator. Because a more negative change means a greater reduction in the symptom score, the negative difference describes a larger average decline in the TAU-284 arm. It does not establish that every participant experienced a decline or that every symptom component changed in the same way.

In general, a mean difference preserves the original units of a continuous outcome. That makes its scale interpretable alongside the outcome definition, here a symptom score from 0 to 4. A standardized effect size can express a difference relative to variability, but it no longer uses the score’s original units. The comparison record includes a standardized effect estimate of -0.336; it is a descriptive standardized measure, not a patient-centered threshold. The registry record does not supply a threshold for meaningful benefit.

What role does the standard error play?

The arm summaries report standard errors of 0.09 for TAU-284 and 0.092 for placebo. In general, a standard error describes the statistical uncertainty in an estimated mean, rather than the spread of individual observations. It tends to be smaller when the estimate is more precise. It should not be read as the range containing most participants’ scores. The record does not provide standard deviations directly for the arm summaries; the comparison calculation identifies its pooled standard deviation as approximate.

The recalculated interval for the mean difference uses posted summary statistics and an approximate standard deviation. In general, a confidence interval describes a range of values compatible with the data and the method used, under its assumptions. It provides information about both direction and precision. Here the interval is wholly below zero, but the registry does not report the sponsor’s full model-based interval or enough detail to verify whether the recalculation reproduces the trial’s planned analysis.

How should the p-value be read?

The posted unadjusted p-value is <0.001. In general, a p-value measures how unusual data at least as incompatible with a null hypothesis would be if that hypothesis and the analysis assumptions held. It is not a measure of effect size, a probability that the finding occurred by chance, or evidence about whether a result is important to patients. The registry record does not describe the precise test used for this p-value, so its assumptions cannot be fully assessed from the entry.

The term unadjusted matters because the record lists multiple outcome measures, but no analysis records are posted. A p-value without an adjustment does not account for a broader family of statistical tests. Whether any multiplicity adjustment was planned or applied is not reported in the registry record. The record also does not state whether the primary analysis was prespecified in the same form as the posted summary.

What can be inferred from the analysis record?

The registry reports six outcome measures and five secondary outcomes, but no analyses are posted in the analysis-count field. The available primary comparison therefore offers a limited statistical record. There is no reported model specification, covariate list, missing-data method, protocol deviation handling, or analysis-population definition. In general, these choices can affect an estimate, its uncertainty, and the interpretation of a treatment comparison. Without them, the numerical comparison can be described, but the full analytic pathway cannot be independently reconstructed.

The primary comparison is based on continuous-outcome summaries rather than participant-level records. In general, a recalculation from summary statistics cannot reproduce all features of an analysis that might account for baseline values, site structure, repeated measurements, or other prespecified factors. The registry does not say that those features were included in the original analysis. No such modeling details should be inferred from the phrase least-squares mean alone.

The result should therefore be read on two levels. The descriptive level is clear: the posted TAU-284 mean change is -1.579, the placebo mean change is -1.11, and the stated mean difference is -0.469. The inferential level is more limited: the unadjusted p-value is <0.001, while complete information about the planned analysis and its assumptions is not reported in the registry record. This distinction helps prevent a summary comparison from being mistaken for a full appraisal of trial methods.

10. Confidence Intervals and Precision

The posted arm means are accompanied by standard errors of 0.09 for TAU-284 and 0.092 for placebo. These quantify uncertainty around the estimated means, not the range of symptom changes among individual participants. The comparison gives a mean difference of -0.469 units and a recalculated confidence interval that lies wholly below zero. The bounds are not repeated because their posted precision exceeds the allowed display precision for this explanation.

In general, a confidence interval conveys a range of effect values reasonably compatible with the data under the calculation’s assumptions. Its location indicates the direction of the estimated difference, and its width reflects precision: a narrower interval is more precise than a wider one. The interval for this comparison remains negative, so the recalculated range does not include a zero mean difference. This should be understood as an unadjusted summary-based interval rather than a reconstruction of an undocumented sponsor model.

The arm sample sizes in the outcome summary are 240 for TAU-284 and 232 for placebo. The comparison’s pooled standard deviation is identified as approximate, and the recalculation uses summary statistics. These details matter because precision estimates depend on the variability estimate and the calculation method. The registry record does not report a sponsor confidence interval for the primary comparison, its model specification, or whether its uncertainty estimate incorporated any covariates.

Precision is not the same as clinical importance. Even a relatively precise estimate does not identify a patient-centered threshold, and the registry record does not report such a threshold for this scale. The interval also does not address uncertainty arising from unreported analysis choices, missing-data handling, selection, or generalizability. Thus, the negative direction is apparent in the posted comparison, while the extent to which the estimate is clinically meaningful and robust to analytic choices cannot be determined from the registry record alone.

11. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are expressed as participants per arm, not total event counts. They are illustrations based on the observed effect, not a report of the trial’s original design calculation. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning scenario uses a stated fraction of the observed effect as the effect to detect. The trial’s own original sample-size assumptions and justification are not reported in the registry record.

For planning for 100% of the observed effect, the illustration gives 140 participants per arm for 80% power and 187 participants per arm for 90% power. For planning for 75% of the observed effect, it gives 248 participants per arm for 80% power and 332 participants per arm for 90% power. For planning for 50% of the observed effect, it gives 558 participants per arm for 80% power and 747 participants per arm for 90% power.

In plain terms, the 80% power column shows the illustrative number of participants per arm for a design with an 80% chance of detecting the specified effect under the stated assumptions, if that effect and assumptions were true. The 90% power column uses a higher target chance and therefore gives larger planning figures for each stated effect fraction. Smaller effects need more participants to detect under the same assumptions. These calculations are not observed power; they are planning illustrations rather than a measure of what the completed study achieved.

12. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.469; pooled standard deviation σ = 1.398.
2. n = 2 × (1.96 + 0.842)² × 1.398² / -0.469² = 139.4, rounded up to 140 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 <- -0.469                      # observed difference in means
sigma <- 1.39773272945106                     # 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(1861522)
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 = 140 (80% power), 187 (90% power)
 75% of observed effect: n per arm = 248 (80% power), 332 (90% power)
 50% of observed effect: n per arm = 558 (80% power), 747 (90% power)
power.t.test: 140.4 
Simulated power at n = 140 per arm: 0.793 (20000 replicates)

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

13. Multiplicity, Missing Data and Analysis Populations

The registry lists the combined score for the three major nasal symptoms as the primary outcome and identifies five secondary outcomes. These include the total score, individual nasal symptom scores, local nasal findings, allergic-rhinitis severity, and adverse events and adverse drug reactions. The record reports six outcome measures in all, but does not post analysis records for them. The registry therefore does not provide a complete set of outcome estimates with which to assess the breadth of reported testing.

Multiplicity arises when several hypotheses or outcomes are examined. In general, conducting multiple tests can increase the chance of obtaining at least one apparently unusual result under a collection of null hypotheses. Statistical plans may address this through prespecified testing sequences or adjustments, but the registry record does not report whether such a strategy was planned or used. The posted p-value is unadjusted, and no adjusted primary result is reported in the record.

The registry does not report the analysis population for the primary endpoint. It is therefore unclear whether the posted means represent all randomized participants, participants with observed endpoint data, or another defined set. The record also does not describe missing-data amounts or how missing observations were handled. These details matter because different analysis populations or missing-data approaches can alter the estimate and its uncertainty.

Other key analysis details are also not reported in the registry record, including the prespecified statistical model, covariate adjustments, protocol deviation handling, and sensitivity analyses. Nor is there information on interim analyses or stopping rules. This does not establish that these procedures were absent; it means that they cannot be assessed from the registry entry. Without a fuller analysis plan and outcome record, multiplicity, missing-data assumptions, and population definitions remain unresolved limitations in interpreting the reported comparison.

14. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 3% reporting threshold.

Most frequent non-serious adverse event terms

The safety figures list zero participants with serious adverse events in the TAU-284 arm among 240 at risk, and zero in the placebo arm among 232 at risk. These are counts as posted, not percentages. The registry’s serious-adverse-event term list is empty. The record does not report deaths for either arm; a blank death field should not be interpreted as a reported count of zero.

The separate counts for other adverse events are 17 for TAU-284 and 15 for placebo, with the same respective at-risk counts noted above. The registry record does not provide event-level descriptions, timing, severity, attribution, or exposure-adjusted rates in the information. It also does not clarify whether any participants experienced more than one event, so the counts should not be interpreted as a count of unique participants beyond the arm-level field as labeled.

These registry figures are a limited safety summary. They do not establish that serious events could not occur or that the two arms have equivalent safety profiles. The record does not report enough detail to evaluate event types, follow-up completeness, or the assessment process. Safety interpretation should remain confined to the posted counts and the record’s omissions.

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

The primary outcome comparison describes average change in a combined nasal-symptom score from baseline to Week 2. The TAU-284 mean change is -1.579, compared with -1.11 for placebo, and the stated mean difference is -0.469 units. The negative direction means that the score declined more on average in the TAU-284 arm. The posted unadjusted p-value is <0.001, and the recalculated interval for the difference lies below zero.

These findings describe the particular outcome, timeframe, and population entered in the registry. They do not show whether each of sneezing, rhinorrhea, and nasal congestion changed to the same degree, whether individual participants experienced improvement, or whether the size of the mean difference is important to patients. The registry does not report a meaningful-change threshold for the scale. It also does not provide the detailed results for the listed secondary outcomes in the analysis record.

The comparison is not a complete account of the trial’s statistical evidence. The registry does not report the statistical analysis plan, analysis population, missing-data approach, or multiplicity strategy. The summary-based recalculation is not a substitute for an analysis using participant-level data and a fully described model. The record’s unadjusted p-value should therefore be read alongside these reporting limitations, not as a stand-alone verdict.

The safety information is also limited. Zero serious adverse events are posted in each arm, while other adverse-event counts are listed as 17 and 15. Death counts are not reported in the registry record, and detailed event descriptions are not available in the summarized record. Such counts do not by themselves establish the absence of risk or equivalence between arms.

In short, the posted result supports a descriptive statement about the direction and statistical evidence of the Week 2 score comparison. It does not, from the registry information alone, settle clinical importance, robustness to analysis choices, effects on each symptom, or safety beyond the reported counts. No conclusion about care for an individual follows from these aggregate trial summaries.

16. Why This Trial Matters Statistically

This study illustrates how a continuous patient-symptom score can be used to compare average change between randomized arms. The endpoint combines sneezing, rhinorrhea, and nasal congestion, providing a single summary rather than separate primary tests for each component. That choice makes the primary comparison concise, while leaving the individual symptom outcomes to the listed secondary measures.

The posted result also shows why direction and units matter. The scale runs from 0 for no symptoms to 4 for very severe symptoms, while changes are reported as negative values when scores decline. The mean difference of -0.469 is expressed in scale units, so its direction can be interpreted from the outcome definition. A p-value alone would not convey that direction or the size of the difference.

Precision and clinical interpretation are distinct. The recalculated interval lies below zero, and the unadjusted p-value is <0.001, but the registry does not report a threshold for a change that would be important to patients. A statistically distinguishable mean difference is not automatically a clinically important one. This distinction is central when interpreting symptom scales in clinical research.

The record also makes the limits of registry analysis visible. It includes arm summaries and a comparison, but no posted analysis records, and leaves major statistical-plan details unreported. The planning illustrations show how required sample size depends on the effect targeted, but they are not a record of the original design or an estimate of observed power. Together, these features highlight the value of transparent endpoint definitions, complete analysis reporting, and careful separation of descriptive, inferential, and clinical claims.

17. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Interpretation is limited by gaps in the registry record. It does not provide detailed eligibility criteria, participant flow, baseline characteristics, or the primary analysis population. The arm-level outcome counts are reported, but the record does not explain how those counts relate to the enrollment figure of 473, nor does it describe missing endpoint observations or their handling.

The primary outcome is a combined score, and the record does not provide component-level primary results or a threshold for patient-important change. Although individual symptom scores and other secondary outcomes are listed, detailed analyses are not posted. The registry also does not report the planned model, covariate adjustment, multiplicity strategy, protocol deviation handling, sensitivity analyses, or interim analyses. These omissions prevent a full audit of the intended statistical procedure and its robustness.

The comparison interval is recalculated from summary statistics using an approximate standard deviation. It should not be treated as a substitute for a fully documented sponsor analysis. The record does not provide enough detail to assess whether the posted least-squares means reflect a particular adjustment or how the p-value was calculated.

Safety information is similarly limited. Serious adverse-event counts are posted, but event terms are not listed; deaths are not reported in the registry record. Other adverse-event counts lack detailed event descriptions and attribution information in the summarized record. Finally, the entry does not provide sufficient population detail to judge generalizability beyond the pediatric patients with perennial allergic rhinitis described as the study population.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: The Confirmatory Study of TAU-284 in Pediatric Patients With Perennial Allergic Rhinitis — NCT01861522.
• Registry record last updated 2026-01-08; status last verified 2025-12.
• Results first posted 2015-12-15.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

The registry record describes a completed Phase 3 randomized, parallel-group, triple-masked, placebo-controlled study of TAU-284 in pediatric patients with perennial allergic rhinitis. The primary endpoint is change from baseline to Week 2 in the total score for sneezing, rhinorrhea, and nasal congestion. The score ranges from 0, no symptoms, to 4, very severe symptoms.

The posted mean changes are -1.579 for TAU-284 and -1.11 for placebo; the mean difference is -0.469, with an unadjusted p-value of <0.001. The comparison interval is recalculated from posted summaries with an approximate standard deviation. The registry lists zero serious adverse events in each arm and other adverse-event counts of 17 and 15. Detailed analysis methods, missing-data handling, deaths, and several other interpretation-relevant details are not reported in the registry record.