Study of 0417 Ointment in the Treatment of Atopic Dermatitis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study of 0417 Ointment in the Treatment of Atopic Dermatitis (NCT01139450), a randomized phase 3 study. The primary outcome is Incidence of Success Based on the Investigator's Global Evaluation at the End of Treatment.

2. Clinical Question

The primary endpoint was assessed at 4 weeks. Its title identifies an investigator’s global evaluation, but the criteria used to classify a participant as a success are not reported in the registry record. The posted results give counts for each arm and comparisons of the Test and Vehicle arms with the Reference arm.

The trial also listed three secondary outcomes: change from baseline in total individual clinical signs and symptoms per body region, change from baseline in pruritus, and change from baseline in the percentage of total body surface area affected. Their detailed results are not reported in the registry record. The clinical question addressed by the posted numerical comparisons is therefore narrower than the full set of outcomes listed for the trial.

3. Trial Design

The study is listed as a completed Phase 3 trial in atopic dermatitis. It used randomized allocation, a parallel-group model, and quadruple masking. The registry record does not identify the four masked parties, describe how randomization was generated or concealed, or give further details of the masking procedures.

The three outcome arms were Test, Reference, and Vehicle. The Test product and Reference product are both described as containing an active pharmaceutical ingredient; the Vehicle is described as placebo without an active pharmaceutical ingredient. Tacrolimus Ointment 0.03% appears in the intervention list, but a specific mapping between that intervention and the arm descriptions is not reported in the registry record. The available information therefore supports describing the comparisons by arm name, rather than assigning an intervention name to an arm when the mapping is not explicit.

Overall enrollment was 899. The primary outcome was recorded at 4 weeks, while the treatment summary describes twice-daily application for approximately 4 weeks. The reported primary-outcome denominators were 226 in Test, 238 in Reference, and 228 in Vehicle. The registry record does not explain how those outcome denominators relate to overall enrollment, or report the numbers randomized, treated, or included in each analysis population.

The record lists a study start of 2008-01 and primary completion of 2009-08. The trial is marked completed. Further details of recruitment, follow-up, protocol deviations, and treatment adherence are not reported in the registry record. The design information establishes the broad comparison and masking structure, but not the operational details needed to reconstruct trial conduct or the original analysis plan.

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 Incidence of Success Based on the Investigator's Global Evaluation at the End of Treatment, measured over 4 weeks.

The primary endpoint is the incidence of success based on the investigator’s global evaluation at the end of treatment, with a timeframe of 4 weeks. It is reported as a number of participants. For this binary outcome, each participant is classified as either a success or not a success according to the evaluation criteria. The record gives the numbers counted as successful and the arm denominators, but the success threshold and handling of indeterminate or unavailable evaluations are not reported in the registry record.

A global evaluation can provide a single overall judgment of the condition at the specified assessment time. Such an endpoint can be useful when the trial question concerns overall status rather than a single sign or symptom. However, its meaning depends on the assessment scale, the definition of success, and the procedures used to assess participants. Those details are not reported in the registry record, so the endpoint can be described as investigator-rated success without further assumptions about its criteria.

The endpoint is distinct from the listed secondary outcomes, which concern changes from baseline in clinical signs and symptoms, pruritus, and affected body surface area. The posted primary results do not, by themselves, report the results of those secondary outcomes.

7. Results Posted in the Registry

• Test: 54.4% (123/226) versus 54.6% (130/238) on control; risk difference -0.2 percentage points (95% CI -9.3 to 8.9), risk ratio 1.00 (0.84–1.18); unadjusted two-proportion z-test p = 0.966.
• Vehicle: 37.7% (86/228) versus 54.6% (130/238) on control; risk difference -16.9 percentage points (95% CI -25.8 to -8.0), risk ratio 0.69 (0.56–0.85); unadjusted two-proportion z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

Binary outcome and risk difference. The primary result is a binary outcome: a participant is counted as a success or not a success. The registry reports the number of successes and the number of participants in each arm. A risk difference expresses the difference between two arms’ proportions with the event. In this trial, the comparisons are oriented against Reference: the Test estimate is -0.002, and the Vehicle estimate is -0.169. A negative value means the success proportion was lower in the named comparison arm than in Reference. A value close to zero describes little estimated difference in the observed proportions, but uncertainty must be considered alongside the point estimate.

Confidence intervals. A confidence interval expresses the range of effect estimates compatible with the observed data under the assumptions of the method. It communicates precision as well as direction. For Test versus Reference, the interval includes zero, so the data are compatible with a small difference in either direction as well as with little difference. For Vehicle versus Reference, the interval is below zero, indicating that the estimated difference is negative across the interval. An interval is not a guarantee that the true effect lies within its bounds, and it does not account for design or measurement limitations that are not represented by the calculation.

Unadjusted p-values. A p-value evaluates how unusual data at least as inconsistent with a specified null hypothesis would be if that null hypothesis and the statistical model were true. It is not the probability that the null hypothesis is true, nor a measure of the size or clinical importance of an effect. The posted p-values are unadjusted: 0.966 for Test versus Reference and <0.001 for Vehicle versus Reference. The registry record does not report whether these p-values were part of a broader confirmatory testing plan or whether an adjustment for multiple comparisons was intended.

Relative measures. The registry also reports relative risks and odds ratios for the comparisons. A relative risk compares the event proportions, while an odds ratio compares the odds of the event. These measures describe the same binary endpoint on different scales. Their interpretation depends on which event is counted and which arm is the reference. The primary presentation uses risk differences, which express the contrast on the absolute proportion scale. No new conversions among these measures are needed to interpret the posted estimates.

Planning calculations. The planning illustrations use the observed effect as a starting point and consider the full observed effect, 75% of it, and 50% of it. Smaller effects require more participants to detect under the stated assumptions. The calculations assume a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. They are planning illustrations, not evidence about the trial’s original design. The registry record does not report the original sample-size justification, design assumptions, or whether these planning assumptions were used in the trial.

Binary-outcome assumptions. A planning calculation for a binary outcome depends on the assumed event proportions in the groups and on the effect size to be detected. The observed effect is not necessarily the effect that a future study should target: it may be uncertain, and smaller target effects require larger samples. The illustrated estimates are conditional on the listed assumptions, including equal allocation, and do not account for unreported features of a future design. They should not be read as a recommendation or as a reconstruction of the trial’s enrollment plan.

Dispersion and model choice. The primary endpoint is a count of participants with an event, not a continuous measurement or event rate over person-time. General statistical note: over-dispersion is especially relevant when count data are modeled with a distribution that assumes a particular relationship between its mean and variance; extra variability can make standard errors too small if it is ignored. That concern is not directly described by the posted binary endpoint counts. The statistical model used for the trial’s original analysis is not reported in the registry record, so no particular model or adjustment can be attributed to the sponsor.

Analysis details. The registry record reports estimates and unadjusted p-values, but does not report whether the analyses were adjusted for baseline factors, how missing endpoint values were handled, whether participants were analyzed according to randomized assignment, or how deviations from the planned treatment were treated. Those choices can affect the estimand and the precision of an analysis. They cannot be inferred from the arm counts or from the labels randomized and quadruple-masked.

10. Confidence Intervals and Precision

The Test-versus-Reference estimate is -0.002. Its confidence interval crosses zero, and the unadjusted p-value is 0.966. The interval therefore allows for estimates on either side of no difference; the result is not a precise demonstration of equality. A confidence interval that includes zero is not proof that the true difference is exactly zero, and the posted analysis is not identified as an equivalence or non-inferiority analysis.

The Vehicle-versus-Reference estimate is -0.169. Its confidence interval remains below zero, with an unadjusted p-value of <0.001. This interval gives a more consistently negative direction for the reported contrast than the Test comparison, while still representing uncertainty about the size of that contrast. The endpoint remains the investigator-rated success count at 4 weeks; the interval does not resolve limitations in endpoint definition, missing-data handling, or analysis population.

Precision is not determined by the point estimate alone. It depends on the amount of information in the comparison and on the statistical method. The posted denominators are 226 for Test, 238 for Reference, and 228 for Vehicle. The record does not report why these endpoint denominators differ from overall enrollment of 899 or give details about participants without endpoint observations. Without those details, the precision measures should be interpreted as applying to the posted comparisons, not as a complete account of all enrolled participants.

Confidence intervals describe statistical uncertainty under the method used; they do not capture every possible source of uncertainty, such as measurement differences or unreported analysis choices. The registry record does not identify the interval construction method. The displayed intervals should therefore be read as the uncertainty estimates reported for the comparisons, without assuming an unreported adjustment or model.

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 estimates are expressed as participants per arm, not as the total number across both arms and not as total events. They compare the Reference arm with either Test or Vehicle. The assumptions stated for these illustrations are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect: 100%, 75%, or 50%. The original trial’s own design assumptions and sample-size justification are not reported in the registry record.

The 80% power column gives the estimated participants per arm for a design with 80% power under those assumptions; the 90% power column gives the corresponding per-arm estimate for 90% power. Power is the probability that a study would meet its specified statistical criterion if the assumed effect and model were true. These figures are planning illustrations, not observed power.

For Test versus Reference, the estimates are 1,002,230 participants per arm for 80% power and 1,341,701 for 90% power when planning for 100% of the observed effect. Planning for 75% gives 1,781,583 and 2,385,033 per arm; planning for 50% gives 4,008,198 and 5,365,840 per arm, respectively.

For Vehicle versus Reference, the corresponding figures are 136 and 181 per arm at 100% of the observed effect, 243 and 325 at 75%, and 549 and 734 at 50%. The estimates increase as the assumed target effect becomes smaller. This is a general feature of power planning: smaller effects are harder to distinguish from sampling variation, so more participants are needed under otherwise unchanged assumptions. These calculations do not describe the actual enrollment or analysis of the completed trial.

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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.546; treatment proportion p₁ = 0.544; average p̄ = 0.545.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7042 = 1.3802.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7042 = 0.5927.
4. n = (1.3802 + 0.5927)² / (-0.0020)² = 1,002,229.7, rounded up to 1,002,230 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 <- 0.546218487394958                          # control proportion
p1 <- 0.544247787610619                          # 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(1139450)
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 = 1,002,230 (80% power), 1,341,701 (90% power)
 75% of observed effect: n per arm = 1,781,583 (80% power), 2,385,033 (90% power)
 50% of observed effect: n per arm = 4,008,198 (80% power), 5,365,840 (90% power)
power.prop.test: 1002230 
Simulated power at n = 1,002,230 per arm: 0.801 (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.

13. Multiplicity, Missing Data and Analysis Populations

The registry reports two primary-outcome comparisons: Test versus Reference and Vehicle versus Reference. Their p-values are unadjusted. The record does not report a multiplicity strategy, a hierarchy for testing the comparisons, a designated primary contrast among them, or whether any adjustment was planned. It also does not report the complete statistical analysis plan. Because multiple outcomes and comparisons can create opportunities for chance findings, the unadjusted values should not be treated as if an unreported adjustment had been applied.

Three secondary outcomes are listed: change from baseline in total individual clinical signs and symptoms per body region, change from baseline in pruritus, and change from baseline in percentage of total body surface area affected. Detailed secondary-outcome results are not reported in the registry record. The record lists four outcome measures overall, but does not supply further outcome-level analysis details beyond the primary result and the named secondary outcomes.

Missing-data handling is not reported in the registry record. The endpoint denominators are 226, 238, and 228 for Test, Reference, and Vehicle, while overall enrollment is 899. The record does not explain how the endpoint populations were formed, how many participants lacked an endpoint assessment, or whether missing values were imputed, excluded, or otherwise handled. The reason for the different denominators cannot be inferred from the posted numbers.

Analysis populations are also not reported. The registry record does not say whether the primary analysis followed randomized assignment, included only participants who received treatment, or used another population definition. Nor does it give details of treatment adherence or protocol deviations. These omissions matter because the population and missing-data rules determine which participants contribute to the estimated effect and can influence the interpretation of a randomized comparison.

The record identifies randomized allocation and quadruple masking, but those design labels do not substitute for a report of the analysis plan, missing-data procedures, or population definitions. Any conclusions should be limited to the posted estimates and the methods that are explicitly described.

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 serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: severe angina pectoris (0.3%), moderate influenza (0.3%), ovarian cyst (0.3%).

The serious adverse event figures are reported as numbers of participants at risk and numbers affected. In Test, 302 participants were at risk and 1 was affected; in Reference, 297 were at risk and 0 were affected; in Vehicle, 300 were at risk and 1 was affected. These are counts, not estimates of comparative risk, and the registry record does not report a statistical comparison of serious adverse events.

The record lists Severe Angina Pectoris, Moderate Influenza, and Ovarian Cyst among the top serious adverse event terms, each with a reported value of 0.3%. The record does not provide enough detail in these entries to infer whether the listed terms correspond to distinct participants or to reconstruct a full event-level account. Deaths are not reported in the registry record.

Other adverse events were reported for 17 of 302 participants in Test, 12 of 297 in Reference, and 20 of 300 in Vehicle. The serious and other adverse-event counts should be interpreted as descriptive registry entries. The record does not provide event definitions, severity grading beyond the listed terms, exposure-adjusted rates, follow-up detail, or a formal safety analysis. These data do not establish a causal explanation for any event or a comparative safety conclusion.

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

The posted primary results describe investigator-rated success at the end of treatment. Test had 123 successes among 226 participants and Reference had 130 among 238. The risk difference for Test versus Reference is -0.002, and its unadjusted p-value is 0.966. The confidence interval crosses zero, leaving uncertainty about the direction and size of the difference. This result is not evidence that the products are equivalent; the registry record does not report an equivalence margin or a non-inferiority design.

Vehicle had 86 successes among 228 participants. Its risk difference versus Reference is -0.169, with an unadjusted p-value of <0.001 and a confidence interval below zero. In the posted data, the Vehicle arm had a lower observed success proportion than the Reference arm. This is a statement about the reported endpoint and comparison, not a conclusion about outcomes beyond the measured assessment or about the cause of the difference.

The registry record does not report the success threshold for the investigator’s global evaluation, missing-data procedures, analysis populations, or a multiplicity plan. These limits matter when interpreting the size and certainty of the reported estimates. The three named secondary outcomes do not have detailed results reported in the registry record, so they cannot be used to broaden the conclusions drawn from the primary endpoint.

The results do not establish longer-term outcomes, explain how the endpoint relates to other measures, or provide a complete analysis of adverse events. Nor do they establish an individual-level prediction. The findings should be read as arm-level comparisons of the specific posted binary outcome at 4 weeks, with the reported precision and the limitations described in the registry record.

16. Why This Trial Matters Statistically

This trial illustrates why a point estimate, its uncertainty, and the endpoint definition need to be read together. The Test-versus-Reference risk difference is close to zero, but its confidence interval includes zero and its unadjusted p-value is 0.966. That pattern does not demonstrate equality: the interval retains uncertainty, and the registry does not report a margin or design for an equivalence or non-inferiority question.

The Vehicle-versus-Reference comparison has a more clearly negative reported risk difference, -0.169, and an unadjusted p-value of <0.001. Contrasting these results shows that an active-reference comparison and a vehicle comparison address different questions. The interpretation remains tied to the arm definitions and the investigator-rated success endpoint, whose classification criteria are not reported in the registry record.

The record also provides an opportunity to distinguish reported analyses from planning illustrations. The planning estimates apply stated assumptions and fractions of the observed effects; they are not a record of the trial’s original design and are not observed power. Particularly when an estimated effect is near zero, planning calculations based on that estimate can yield very large participant requirements. Such calculations are sensitive to the effect chosen for planning and should not be mistaken for proof that a study was adequately or inadequately designed.

Finally, the registry record makes visible important reporting boundaries: secondary-outcome results, missing-data handling, analysis populations, and multiplicity procedures are not reported. Recognizing what an estimate can describe—and what the record does not establish—is central to sound interpretation of clinical trial statistics.

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.

The registry record gives the primary outcome title and timeframe but does not report the operational definition of success for the investigator’s global evaluation. Without the criteria or assessment scale, the exact meaning of the binary classification cannot be reconstructed from the record. Details about who performed the evaluation and how assessments were standardized are also not reported.

Although overall enrollment is 899, the primary-outcome denominators are 226, 238, and 228 across Test, Reference, and Vehicle. The registry record does not explain the relationship between overall enrollment and these analysis denominators. It does not report missing endpoint counts, reasons for missingness, imputation rules, or the analysis populations. This limits assessment of how representative the posted comparisons are of all enrolled participants.

The record identifies a randomized, quadruple-masked, parallel-group design, but does not report the randomization procedure, allocation concealment, which parties were masked, or the original statistical analysis plan. The two primary comparisons have unadjusted p-values, while a multiplicity strategy is not reported. The trial’s original sample-size assumptions and justification are also not reported; the posted planning illustrations use their own stated assumptions.

Detailed results for the three named secondary outcomes are not reported. Safety information is limited to the posted counts and listed serious-event terms, without a formal comparison or fuller event-level detail. These reporting limits mean the available record supports interpretation of the reported primary contrasts, but not a complete reconstruction of trial conduct, analysis, or all outcome results.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Study of 0417 Ointment in the Treatment of Atopic Dermatitis — NCT01139450.
• Registry record last updated 2014-10-09; status last verified 2014-09.
• Results first posted 2014-09-30.
• 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

NCT01139450 is a completed Phase 3, randomized, quadruple-masked, parallel-group trial of 0417 ointment for atopic dermatitis. Overall enrollment was 899. Treatment was described as applying ointment twice daily, approximately 12 hours apart, for approximately 4 weeks. The primary endpoint was investigator-rated success at the end of treatment.

The posted primary outcome counts were 123 of 226 for Test, 130 of 238 for Reference, and 86 of 228 for Vehicle. The Test-versus-Reference risk difference was -0.002, with an unadjusted p-value of 0.966; the Vehicle-versus-Reference risk difference was -0.169, with an unadjusted p-value of <0.001. The registry record does not report the success criteria, detailed secondary-outcome results, missing-data procedures, analysis populations, multiplicity plan, or the trial’s original sample-size justification.