Comparison Trial of OPA-15406 Ointment in Pediatric Patients With Atopic Dermatitis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comparison Trial of OPA-15406 Ointment in Pediatric Patients With Atopic Dermatitis (NCT03911401), a randomized phase 3 study. The primary outcome is Responder Rate of Investigator's Global Assesment (IGA) of Disease Severity.

2. Clinical Question

3. Trial Design

The registry record describes a Phase 3, randomized, triple-masked, parallel-group trial comparing 0.3% OPA-15406 ointment and 1% OPA-15406 ointment with vehicle in pediatric patients with atopic dermatitis. The stated enrollment was 251. Each treatment was administered twice daily, and the primary outcome was assessed at Week 4.

The trial is listed as completed. The recorded start date is 2019-05-07, and the primary completion date is 2019-12-13. Otsuka Pharmaceutical Co., Ltd. is named as sponsor. These record details describe the trial’s administrative status and design; they do not establish how participants were recruited or how the study was conducted at individual sites.

Randomization allocates participants to groups using a chance-based procedure, which is intended to support comparable groups at the start of a trial. Triple masking indicates that the registry classifies the study as masked at three levels, but the identities of the masked parties and the procedures used to maintain masking are not reported in the registry record. The parallel-group model means the listed treatment groups were compared during the same trial rather than participants moving through each treatment in sequence.

The record gives no further detail about allocation procedures, treatment adherence, permitted additional care, eligibility criteria, or the exact analysis populations. Those details are not reported in the registry record. As a result, the design can be described from the registered classifications and treatment schedule, but not reconstructed beyond them.

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 Responder Rate of Investigator's Global Assesment (IGA) of Disease Severity, measured over At Week 4.

The primary endpoint is the responder rate for Investigator’s Global Assessment of disease severity at Week 4. Investigators or subinvestigators assessed overall symptoms in the treatment area, including erythema, infiltration, papules, effusion, and scab formation. They scored severity from 0, clear, through 4, severe or very severe. Success required both a Week 4 score of 0 or 1 and an improvement of at least 2 grades from baseline.

This endpoint combines the severity rating at the assessment time with change from baseline. Requiring both conditions distinguishes a low final score from a low score that reflects improvement during treatment. Reporting the endpoint as a percentage of participants makes the outcome interpretable as the share meeting the stated response definition. It does not capture every aspect of atopic dermatitis or every participant’s symptom experience; it records whether the prespecified IGA criteria were met.

The registry record identifies this as the primary endpoint and gives the assessment time as Week 4. The rationale for choosing this particular endpoint, the procedures for resolving disagreements between assessors, and any additional validation or training details are not reported in the registry record.

7. Results Posted in the Registry

• 0.3% OPA-15406: 44.6% (37/83) versus 18.1% (15/83) on control; risk difference 26.5 percentage points (95% CI 13.0 to 40.0), risk ratio 2.47 (1.47–4.14); unadjusted two-proportion z-test p = <0.001.
• 1% OPA-15406: 47.1% (40/85) versus 18.1% (15/83) on control; risk difference 29.0 percentage points (95% CI 15.5 to 42.4), risk ratio 2.60 (1.56–4.34); unadjusted two-proportion z-test p = <0.001.

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.

Change From Baseline in Eczema Area and Severity Index (EASI) Score

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • 0.3% OPA-15406: mean -4.97 versus 0.35 on control; difference -5.32 (95% CI -7.73 to -2.91), standardized effect d = -0.74; z-test p = <0.001.
  • 1% OPA-15406: mean -6.07 versus 0.35 on control; difference -6.42 (95% CI -8.83 to -4.01), standardized effect d = -0.89; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for 0.3% OPA-15406 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for 1% OPA-15406 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in Verbal Rating Scale (VRS) for Pruritus Score

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • 0.3% OPA-15406: mean -0.80 versus -0.33 on control; difference -0.47 (95% CI -0.82 to -0.12), standardized effect d = -0.63; z-test p = 0.008.
  • 1% OPA-15406: mean -0.68 versus -0.33 on control; difference -0.35 (95% CI -0.70 to -0.00), standardized effect d = -0.46; z-test p = 0.048.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for 0.3% OPA-15406 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for 1% OPA-15406 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes describe change from baseline in EASI score and VRS for pruritus score, assessed at Baseline and Week 4. Across these measures, the posted mean changes and unadjusted comparisons generally point toward differences between the active-treatment groups and placebo. The EASI comparisons have p < 0.001 for both active groups; for VRS, the posted p-values are 0.008 and 0.048. These findings offer additional context about disease severity and pruritus, but they are not the registered primary endpoint.

The secondary outcomes relate to the primary result by measuring different aspects of the clinical picture. The primary IGA outcome applies a categorical responder definition to the investigator’s overall assessment. EASI summarizes change in a score, and VRS captures change in pruritus rating. Similar directional patterns across distinct measures can be informative, but they do not make the outcomes interchangeable or establish that one measure validates another.

These secondary findings carry less inferential weight because the comparisons are unadjusted and the registry record does not report a multiplicity procedure. When several outcomes or comparisons are examined, the chance of at least one apparently notable result can increase unless the analysis plan accounts for multiple testing. The record does not state how the secondary outcomes were prioritized or whether any were intended to support formal confirmatory claims.

Outcome-specific counts are smaller for these measures than for the primary endpoint, particularly for VRS. The reasons for the different counts are not reported in the registry record. Accordingly, the secondary results should be interpreted as additional posted evidence with their own availability and uncertainty, not as a substitute for the primary comparison or a complete account of the planned statistical analysis.

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

• Change From Baseline in Eczema Area and Severity Index (EASI) Score
• Change From Baseline in Verbal Rating Scale (VRS) for Pruritus Score

9. Statistical Interpretation

10. Statistical Methods Explained

What does a responder rate represent?

A responder rate is the proportion of assessed participants who satisfy a defined outcome rule. In this trial, the rule required an IGA score of 0 or 1 at Week 4 and improvement of at least 2 grades from baseline. The rate is therefore not simply the share of participants with a clear or almost-clear score: the required change from baseline is also part of the definition.

For a binary outcome, each participant contributes either a response or a nonresponse. The resulting group proportion is easy to interpret, but it compresses information. Participants who do not meet the response rule may still have had different degrees of change, and the responder rate does not distinguish among those outcomes. The secondary continuous outcomes provide a different view by summarizing mean change in scores.

What does the risk difference express?

A risk difference compares the response proportions between two groups by subtracting one proportion from the other. Its interpretation is on the probability scale, so it describes the absolute separation between group response rates rather than a relative comparison. The posted primary comparisons use placebo as the reference group. The estimate and its confidence interval describe the observed group contrast and the range of values compatible with the data under the method used.

The registry record also includes unadjusted p-values for these comparisons. A p-value evaluates how compatible the observed data are with a specified null hypothesis under the test’s assumptions. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of the difference. The estimates and confidence intervals are needed to understand magnitude and precision alongside the p-values.

How should confidence intervals be understood?

A confidence interval expresses uncertainty in an estimate using a range of values. In repeated use of the same method under its assumptions, intervals constructed at a stated confidence level would cover the underlying quantity at that frequency. A 95% confidence interval is not a statement that there is a 95% probability that this particular fixed quantity lies inside the calculated interval. The interval’s width gives information about precision: a wider interval indicates less precision than a narrower interval, all else being equal.

For group response rates, the registry gives 95% confidence intervals around each rate. For comparisons, a confidence interval around a difference helps assess the range of plausible group contrasts. Whether a comparison interval includes the null value is relevant to statistical evidence under the method, but interpretation should also consider the size of the effect and the analysis plan. The registry record does not report a sponsor analysis or the method used to construct the comparison intervals.

Why do sample size and missing outcomes matter?

Precision depends in part on the amount of outcome information available. Fewer observations generally leave more uncertainty, while the amount of information also depends on the variability or frequency of the outcome. A denominator is therefore important when reading a rate or mean. The number assessed can differ between endpoints, and those differences should not be attributed to a particular reason unless the record reports one.

The primary endpoint group counts are 83, 85, and 83. For the secondary EASI outcome, the posted group counts are 77, 77, and 59; for VRS, they are 38, 41, and 33. The reasons these outcome-specific counts differ are not reported in the registry record. Missing outcome data can affect both precision and the interpretation of a comparison, especially if the availability of outcomes is related to participants’ responses or treatment group.

What does over-dispersion mean in general?

Over-dispersion is a general statistical concept: it occurs when observed variability is greater than a model assumes. If a model understates variability, standard errors may be too small and confidence intervals may be too narrow. It is not possible to determine from the registry record whether over-dispersion was assessed or relevant to the primary analysis; that information is not reported.

More broadly, the registered outcome summaries do not state the precise statistical test, covariate adjustment, missing-data strategy, or multiplicity procedure. The displayed unadjusted comparisons can be described, but they cannot establish what the full prespecified analysis would have been. General statistical explanations should not be mistaken for confirmation that a particular method was used in this trial.

11. Confidence Intervals and Precision

The primary response-rate confidence intervals are 33.66% to 55.9% for 0.3% OPA-15406, 36.13% to 58.19% for 1% OPA-15406, and 10.48% to 28.05% for placebo. Each interval gives a range of values compatible with the observed rate under the interval method and its assumptions. The intervals show that the rates are estimates rather than exact values for a broader population.

The posted comparison confidence intervals are also informative: the interval for the 0.3% comparison is 0.130 to 0.400, and the interval for the 1% comparison is 0.155 to 0.424. Both are on the risk-difference scale, with placebo as the reference. Their positive bounds indicate that the posted estimates favor higher response proportions in the active-treatment groups. The registry does not identify the method used to construct these comparison intervals, so their assumptions cannot be evaluated from the record alone.

Precision is distinct from statistical significance. An estimate can be directionally clear while still having uncertainty about its exact magnitude. Confidence intervals do not resolve questions about generalizability, outcome availability, or unreported analysis choices. Those issues require information beyond the numerical interval itself.

The secondary endpoints have their own estimates and uncertainty, but their outcome-specific participant counts differ from the primary endpoint counts. Those results should be read in the context of their denominators and unadjusted status, rather than assumed to have the same precision or evidential role as the primary outcome.

12. Planning a Similar Trial: Sample Size

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

The sample-size figures are participants per arm for 80% power and participants per arm for 90% power. They are not total events. The planning illustration assumes a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. It uses the observed effect as a reference and considers detecting 100%, 75%, or 50% of that observed effect. The trial’s own original design assumptions are not reported in the registry record.

The 80% power column gives the estimated number of participants per arm for a planning scenario in which the test would have an 80% chance of detecting the specified effect if that effect were the true one and the assumptions held. The 90% power column uses a higher target chance of detection and therefore generally calls for more participants under the same assumptions. For example, for the primary comparison with 0.3% OPA-15406, the planning figures at 100% of the observed effect are 47 participants per arm for 80% power and 63 for 90% power. For 1% OPA-15406, the corresponding figures are 40 and 53 participants per arm.

Planning for a smaller effect requires more participants because a smaller group separation is harder to distinguish from sampling variation. The illustrations are calculated from observed effects and are not the trial’s original design justification. They are not observed power: they do not describe the probability that this completed trial detected its actual effect after the results were known. No trial-specific sample-size assumptions or justification are 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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.181; treatment proportion p₁ = 0.446; average p̄ = 0.313.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6559 = 1.2856.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6286 = 0.5290.
4. n = (1.2856 + 0.5290)² / (0.2651)² = 46.9, rounded up to 47 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
p0 <- 0.180722891566265                          # control proportion
p1 <- 0.44578313253012                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(3911401)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 47 (80% power), 63 (90% power)
 75% of observed effect: n per arm = 79 (80% power), 106 (90% power)
 50% of observed effect: n per arm = 166 (80% power), 221 (90% power)
power.prop.test: 46.9 
Simulated power at n = 47 per arm: 0.810 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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 trial compares two OPA-15406 strengths with a shared vehicle group on the primary endpoint, and it also posts two secondary outcomes. Multiple comparisons raise a multiplicity question: when several hypotheses are tested, unadjusted p-values do not account for the full set of opportunities to observe small p-values by chance. A prespecified approach might control a family-wise error rate, use a hierarchical testing sequence, or treat some analyses as exploratory. The registry record does not report which approach, if any, was planned or used.

The posted primary comparison p-values are unadjusted. The registry record contains no reported analyses from the sponsor and does not specify whether these values correspond to the trial’s confirmatory analysis. The absence of reported adjustment information means the p-values should not be interpreted as establishing control of error across all comparisons. The statistical plan, including any interim analyses or decision rules, is not reported in the registry record.

Missing outcome information is another consideration. The posted participant counts differ by outcome and group: the primary IGA counts are 83, 85, and 83; the EASI counts are 77, 77, and 59; and the VRS counts are 38, 41, and 33. The registry record does not explain these differences or describe how missing observations were handled. It also does not identify the analysis populations, such as whether results use all randomized participants or a subset with available assessments.

These omissions limit assessment of potential bias and the reproducibility of the reported comparisons. If outcome availability differs for reasons related to response or group assignment, a complete-case summary could represent a selected subset. That is a general concern, not evidence that such bias occurred in this trial. The record does not provide enough information to determine whether imputation, sensitivity analyses, or other methods were used.

15. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent non-serious adverse event terms

The posted serious adverse event figures are zero in each group: 0 among 83 participants receiving 0.3% OPA-15406, 0 among 85 receiving 1% OPA-15406, and 0 among 83 receiving placebo. The deaths count is also 0 in each group. These are counts within the groups and observation reported in the registry record; they do not establish that no serious events could occur in other circumstances.

Other adverse events affected 11 participants in the 0.3% group, 9 in the 1% group, and 7 in the placebo group, with the corresponding at-risk counts of 83, 85, and 83. The record does not list serious adverse event terms. It also does not provide further details about event types, timing, severity beyond the serious classification, or whether events were considered related to treatment. A zero count should be read as no serious events recorded in these group counts, not as proof of absence of risk.

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

The posted primary outcome shows higher Week 4 IGA responder rates in both OPA-15406 groups than in the placebo group. The active-group rates were 44.58% and 47.06%, compared with 18.07% for placebo. The unadjusted comparison p-values are p < 0.001 for each active group. These results describe the observed participants and the defined IGA response rule in this trial.

The results do not mean that every participant receiving OPA-15406 met the response definition, or that participants who did not meet it had no improvement. The endpoint is a threshold-based classification, and it does not fully describe individual trajectories or all dimensions of atopic dermatitis. The posted rates also do not establish the degree of benefit for a particular person.

The estimates do not answer questions about outcomes beyond Week 4, longer-term safety, or effects in populations not represented by this trial. The registry record reports pediatric patients with atopic dermatitis but does not provide detailed participant characteristics or subgroup results in the information presented. Generalization to other populations or settings cannot be determined from these summaries alone.

Statistical evidence should also be distinguished from clinical importance. The p-values indicate the compatibility of the data with a null comparison under an unadjusted test, not the probability that a treatment is effective or the importance of the observed difference. The record does not report a threshold for a clinically meaningful difference, a sponsor analysis, or a multiplicity strategy. Those limits matter when interpreting the posted comparisons and secondary outcomes.

In short, the registry results report higher responder proportions in the two active groups than in vehicle at the specified assessment. They do not provide a complete account of analysis methods, missing data, longer-term outcomes, or the clinical importance of the observed differences.

17. Why This Trial Matters Statistically

This trial illustrates how a binary primary endpoint can translate a clinical assessment into a clearly defined responder rate. The IGA rule includes both a Week 4 severity threshold and a required improvement from baseline. That construction makes the outcome more specific than a final score alone, while also making the result dependent on the chosen cut points and assessment process.

The trial also shows why effect estimates and uncertainty matter alongside p-values. The posted group rates describe the observed response proportions, while the comparison estimates and confidence intervals describe the separation and its precision. The p-values alone cannot communicate the size of a difference or its uncertainty. Reading these elements together supports a more complete statistical interpretation.

Multiple treatment comparisons and multiple endpoints create questions about how evidence is organized. The record posts unadjusted comparisons for two active treatments and secondary outcomes but does not report a multiplicity strategy. This is important because the evidential meaning of a p-value depends in part on the analysis plan and the family of comparisons being considered.

Finally, the outcome-specific participant counts differ, while the reasons and missing-data procedures are not reported. This illustrates the value of transparent reporting about analysis populations and incomplete outcomes. Such details help readers evaluate how closely the posted estimates represent the randomized groups and how robust they may be to alternative assumptions.

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.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The registry record does not report the full statistical analysis plan, the method used for the primary comparison, or whether the posted unadjusted p-values reflect the planned confirmatory analysis. It also does not report any multiplicity adjustment or interim analysis details. These gaps prevent a full assessment of the inferential framework.

The record gives different participant counts across the primary and secondary outcomes, with especially fewer participants represented in the VRS results. Reasons for these differences, the handling of missing observations, and the analysis populations are not reported. Consequently, it is not possible to determine from the registry summaries whether the outcome results use all randomized participants or how missing values may affect the estimates.

Further limitations include the lack of detailed participant characteristics, subgroup outcomes, and information about the assessment process beyond the IGA scoring description. The registry record does not explain how masking was maintained, how treatment adherence was measured, or how disagreements between assessors were handled. The reported primary assessment is at Week 4, so the posted results do not describe longer-term outcomes.

The safety summary reports no serious adverse events or deaths in the listed groups, but the registry record provides limited event detail. These figures alone cannot characterize all aspects of safety or establish what might occur with longer exposure or in a different population. These are limits of the available registry record, not evidence that unreported procedures or outcomes did or did not occur.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Comparison Trial of OPA-15406 Ointment in Pediatric Patients With Atopic Dermatitis — NCT03911401.
• Registry record last updated 2021-01-25; status last verified 2021-01.
• Results first posted 2021-01-25.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry record describes a completed, randomized, triple-masked, parallel-group Phase 3 trial of 0.3% OPA-15406 ointment and 1% OPA-15406 ointment versus vehicle in pediatric patients with atopic dermatitis. Enrollment was 251, and each treatment was administered twice daily for 4 weeks. Otsuka Pharmaceutical Co., Ltd. is listed as sponsor.

The primary outcome was the Week 4 IGA responder rate. Posted rates were 44.58% for 0.3% OPA-15406, 47.06% for 1% OPA-15406, and 18.07% for placebo, with unadjusted p < 0.001 for each active-treatment comparison. EASI and VRS change scores were also posted as secondary outcomes. The record does not report the full statistical plan, multiplicity procedures, analysis populations, or missing-data methods.