Effect of Pimecrolimus Cream on Cathelicidin Levels in Subjects With Eczema: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effect of Pimecrolimus Cream on Cathelicidin Levels in Subjects With Eczema (NCT00946478), a randomized na study. The primary outcome is Cathelicidin mRNA Expression Levels in Adult Skin From Patients With AD.

2. Clinical Question

The registry's hypothesis was that topical pimecrolimus would increase antimicrobial peptides in skin. The posted comparison estimates a difference in mean cathelicidin mRNA expression between the randomized groups. It does not by itself answer whether patients experienced a change in symptoms, disease severity, or other clinical outcomes. Such outcomes are not reported as secondary results in the registry record.

3. Trial Design

The record describes a randomized, double-blind, parallel-group study of pimecrolimus cream and vehicle cream. The listed enrollment is 40. The intervention groups each have a posted sample size of 20. The study is marked completed; its recorded start is 2009-10 and its primary completion is 2011-02. The phase is listed as NA, which does not provide a clinical development phase.

The study's official title describes a three-week evaluation of pimecrolimus cream 1% and cathelicidin expression in skin from subjects with atopic dermatitis. The primary outcome description says that delta-delta CT values were measured by RT-PCR in human biopsy samples at baseline and again 3 weeks after treatment with pimecrolimus or placebo. The comparator intervention is listed as vehicle cream. More detailed descriptions of the treatment schedule, allocation procedure, concealment, masking procedures, or biopsy procedures are not reported in the registry record.

Randomization is intended, in general, to make treatment groups comparable on average with respect to factors that could influence an outcome. Double masking is intended, in general, to limit the influence of treatment knowledge on participants' experiences or outcome assessment. These are general purposes of the design labels; the registry record does not describe how randomization or masking was implemented or assessed.

The record names one primary outcome and posts no secondary outcome results. It lists no analysis records. The statistical plan, trial-specific sample-size rationale, analysis populations, handling of missing measurements, and any interim analyses are not reported in the registry record. The planning illustrations associated with the posted effect are not the study's original enrollment justification.

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

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 Cathelicidin mRNA Expression Levels in Adult Skin From Patients With AD, measured over 3 weeks.

The primary endpoint is titled “Cathelicidin mRNA Expression Levels in Adult Skin From Patients With AD.” It is measured in delta-delta ct units on PCR. The outcome description says cathelicidin mRNA was measured by RT-PCR in skin biopsy samples at baseline and 3 weeks after treatment. The record reports mean values and standard errors for the pimecrolimus and vehicle cream groups, together with a mean difference and confidence interval.

Cathelicidin is an antimicrobial peptide, so measuring its mRNA expression is a way to study a biological process in the skin. In general, a molecular endpoint can help characterize a biological response to an intervention. It is not automatically a measure of how symptoms or disease status change, and the registry record does not establish that a change in this marker corresponds to a clinical benefit or harm.

The posted information does not clarify whether the group means represent values at the end of treatment, changes from baseline, or another summary derived from the baseline and follow-up measurements. The outcome description mentions both time points, but the result label and units alone do not resolve that detail. The distinction matters because an endpoint value and a change-from-baseline value answer different statistical questions.

7. Results Posted in the Registry

• Pimecrolimus: mean 0.00 versus 0.00 on control; difference -0.00 (95% CI -0.01 to 0.01), standardized effect d = -0.06; z-test p = 0.858.

8. Statistical Interpretation

9. Statistical Methods Explained

What does a mean difference describe?

For a continuous outcome, a group mean summarizes the average measured value among the participants included in that group's analysis. A mean difference compares the two group means on the outcome's original scale. In this record, the comparison is pimecrolimus minus vehicle cream: the group means are 0.002 and 0.002, and the reported mean difference is -0.001 delta-delta ct units on PCR. A negative difference means the pimecrolimus group mean is lower on the stated scale. Whether a lower value is desirable is not established by the statistical comparison alone.

The record says baseline and 3-week samples were measured, but it does not specify clearly whether the posted means summarize follow-up values, changes from baseline, or another constructed measure. That uncertainty about the precise outcome summary matters for interpreting what the mean difference represents. The registry record does not report an adjusted model or a more detailed definition of the analysis variable.

What is a standard error?

In general, a standard error describes the precision of an estimated quantity, such as a sample mean. It is not the same as a standard deviation: a standard deviation describes variability among measurements, while a standard error describes variability in the estimate across hypothetical repetitions of the sampling process. The posted standard errors are 0.002 for pimecrolimus and 0.004 for vehicle cream. The registry record identifies the dispersion measure as standard error. It does not give further details about how the means and standard errors were calculated or whether the analysis accounted for the paired baseline and follow-up measurements.

The comparison also reports a pooled standard deviation of 0.014. In general, pooling combines information about variability across groups under assumptions about the relationship between their variances. It can be used in standardized effect summaries. The analysis method and assumptions behind this reported pooled value are not described in the registry record, so it should be treated as a posted summary rather than evidence of a fully specified modeling approach.

How should the p-value be read?

The unadjusted p-value is 0.858. In general, a p-value describes how unusual data at least as incompatible with a specified null model would be if that model and the test assumptions held. It is not the probability that the null hypothesis is true, and it does not measure the probability that the result will replicate. A relatively large p-value does not establish equivalence or prove that there is no effect. Here, the p-value is one part of the evidence; the confidence interval and the scale of the estimate also matter.

The record labels this p-value unadjusted. It does not report a multiplicity adjustment or the complete statistical analysis plan. Because only one primary outcome is posted and no secondary outcomes are posted, the record does not permit a full evaluation of how many comparisons were considered during analysis or whether the displayed test was selected in advance.

What does a standardized effect add?

The reported standardized effect estimate is -0.057. In general, a standardized effect expresses a difference relative to a measure of variability, allowing outcomes on different scales to be compared more readily. Unlike the raw mean difference, it does not retain the original outcome units. Its interpretation depends on the variability estimate and the method used to calculate it. The registry record does not provide a detailed formula or additional assumptions for this effect estimate. It should not replace the raw difference and its confidence interval when interpreting the outcome in its original units.

What does uncertainty from over-dispersion mean?

In general, over-dispersion refers to observed variability exceeding what a statistical model assumes. When relevant, ignoring it can make standard errors too small and confidence intervals too narrow. The posted endpoint is continuous, and the record does not report an over-dispersion assessment or indicate that over-dispersion was modeled. This is a general statistical consideration, not a claim that over-dispersion occurred in this study. The outcome's measurement scale and the reported spread make it important to understand how variability was handled, but the necessary analysis details are not reported in the registry record.

What can the design tell us?

Random allocation and double masking are design features that can reduce certain sources of bias in general. Their presence in the registry does not establish that allocation was concealed, that masking remained intact, or that all randomized participants contributed outcome data. Those implementation details and the analysis population are not reported in the registry record. The result is therefore interpreted as the posted group comparison, with these reporting limits in mind.

10. Confidence Intervals and Precision

The estimated mean difference is -0.001 delta-delta ct units on PCR, and its 95% confidence interval ranges from -0.010 to 0.008. In general, a confidence interval expresses uncertainty about an estimated effect under the statistical procedure and assumptions used to construct it. It is not a guarantee that the true effect lies within the interval, nor does it describe the range of individual participant measurements.

The interval contains zero and includes both negative and positive values. Thus, the data are compatible with a lower mean in the pimecrolimus group as well as a higher mean, within the reported interval. The interval is broad relative to the point estimate, so the direction and magnitude of the group difference are not estimated precisely. The displayed estimate should not be read as proof of no difference simply because the interval includes zero.

The group standard errors are 0.002 for pimecrolimus and 0.004 for vehicle cream. These values concern precision of group means, not individual variation; the reported pooled standard deviation is 0.014. The registry record does not give the confidence-interval construction method, the assumptions used for the calculation, or a detailed account of the analysis population. Those omissions limit independent assessment of the interval's coverage properties.

The confidence interval and p-value address statistical uncertainty for the posted comparison, not clinical importance. The record does not specify a clinically meaningful threshold for cathelicidin expression, and the endpoint is not a reported clinical measure. Consequently, the precision of the estimate can be described statistically, but the clinical relevance of values within the interval is not established by the registry record.

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 participants per arm, not total events. They are illustrations based on the observed effect, not the trial's own original design assumptions; those original assumptions are not reported in the registry record. The listed planning assumptions 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.

For planning at 100% of the observed effect, the figures are 4,906 participants per arm for 80% power and 6,568 participants per arm for 90% power. At 75% of the observed effect, they are 8,721 participants per arm for 80% power and 11,675 participants per arm for 90% power. At 50% of the observed effect, they are 19,623 participants per arm for 80% power and 26,269 participants per arm for 90% power.

In general, power is the chance that a specified analysis will reject its null hypothesis when a particular effect is true, given the planning assumptions. The 80% column describes a planning target of 80% power under those assumptions; the 90% column uses a higher target. Smaller effects are harder to distinguish from random variation, so planning to detect a smaller effect requires more participants. These figures are not observed power and do not show the probability that the trial's result is correct.

The displayed curve should be read as a visual companion to these planning illustrations: it relates the assumed effect size to the participant requirement under the same planning framework. Its values are conditional on the assumptions listed, and do not revise the trial's observed results or establish what the original investigators planned.

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 = -0.001; pooled standard deviation σ = 0.014.
2. n = 2 × (1.96 + 0.842)² × 0.014² / -0.001² = 4,905.5, rounded up to 4,906 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 <- -0.0008                      # observed difference in means
sigma <- 0.014142135623731                     # 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(946478)
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 = 4,906 (80% power), 6,568 (90% power)
 75% of observed effect: n per arm = 8,721 (80% power), 11,675 (90% power)
 50% of observed effect: n per arm = 19,623 (80% power), 26,269 (90% power)
power.t.test: 4906.5 
Simulated power at n = 4,906 per arm: 0.802 (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

Multiplicity arises when several outcomes, time points, subgroups, or statistical comparisons are examined. In general, making many tests increases the chance that at least one result will appear statistically notable by chance, unless the analysis plan accounts for the testing strategy. Whether an adjustment is appropriate depends on the study questions and planned analyses; the registry record does not provide enough detail to determine the full testing family for this study.

The record posts one primary outcome and no secondary outcome results. It reports an unadjusted p-value of 0.858 for the mean difference. No multiplicity adjustment is reported. The record does not state whether additional outcomes or analyses were planned, whether any were conducted but not posted, or whether the primary endpoint was the only analysis considered. Therefore, it is not possible to assess the full extent of multiple testing or selective reporting from the registry record alone.

Missing-data handling is also not reported. The listed group sample sizes are 20 in each arm, but the record does not clarify whether all participants with an allocated intervention contributed an evaluable biopsy result, whether measurements were missing, or how missing observations were treated. Nor does it specify an intention-to-treat, per-protocol, or other analysis population. The listed enrollment and group sizes should not be taken as a full account of the data included in the estimate.

The registry record lists no analysis records, despite posting an outcome comparison. It does not describe a statistical analysis plan, covariate adjustment, baseline handling, model choice, or interim monitoring. These gaps do not establish that such procedures were absent; they mean that they are not reported in the registry record. Interpretation therefore rests on the posted unadjusted comparison and its stated uncertainty, without assuming undocumented analysis choices.

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 0% reporting threshold.

For serious adverse events, the record lists 20 participants at risk in the pimecrolimus group and 20 in the vehicle cream group, with 0 affected in each group. It also lists 20 at risk and 0 affected for other adverse events in each group. These are the posted counts; the record does not provide event descriptions for these groups.

Zero reported affected participants in these groups does not establish that no adverse events occurred outside the recorded categories or reporting period. The registry record does not describe the safety surveillance procedures, event definitions, duration of safety follow-up, or whether all participants were assessed. Death counts are not reported in the registry record. The safety figures should therefore be read as the adverse-event counts posted for the listed groups, not as a complete characterization of safety or as evidence that rare or unrecorded events could not occur.

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

The result estimates a difference in mean cathelicidin mRNA expression between the pimecrolimus and vehicle cream groups on the reported delta-delta ct scale. The posted group means are 0.002 and 0.002, and the mean difference is -0.001. The confidence interval ranges from -0.010 to 0.008, while the unadjusted p-value is 0.858. Together, these statistics describe a small point estimate with substantial uncertainty about its direction and magnitude.

The result does not demonstrate that the two groups are equivalent. Equivalence requires a prespecified margin and an analysis designed to assess whether the plausible difference falls within that margin; neither is reported in the registry record. A non-significant result also does not prove that a treatment has no biological effect. It indicates that this posted comparison does not sharply distinguish the groups under the reported analysis.

The endpoint is a molecular marker measured in skin, not a reported measure of symptoms, eczema severity, or another patient-centered clinical outcome. Although the study description hypothesizes that topical pimecrolimus will increase antimicrobial peptides, the posted comparison cannot establish that the immune system was repaired, nor whether any biological change would improve clinical outcomes. A result on a biomarker and a result on a clinical outcome answer different questions.

The registry record does not clarify whether the reported means are endpoint values or changes from baseline, and it does not provide a detailed analysis population or missing-data approach. It also does not report a clinically meaningful threshold for the marker. These limitations constrain the biological and clinical interpretation of the estimate. The result is best understood as an imprecise comparison on the stated laboratory endpoint, rather than a conclusive statement about treatment efficacy or clinical benefit.

16. Why This Trial Matters Statistically

This trial highlights the distinction between an observed estimate and the precision with which it is known. The mean difference is -0.001, but its confidence interval extends from -0.010 to 0.008. A reader who focuses only on the point estimate could overstate what the data establish; the interval makes clear that effects on either side of zero remain compatible with the posted results.

It also illustrates why a non-significant p-value is not the same as evidence of equivalence. The unadjusted p-value is 0.858, but the registry record does not report an equivalence margin or a design intended to rule out differences of a specified size. The appropriate statistical reading is uncertainty about the comparison, not proof that the group outcomes are identical.

The study's biological endpoint raises another important distinction: statistical evidence about a molecular measure does not automatically translate into evidence about a clinical outcome. Cathelicidin mRNA expression can inform a biological question, but the record posts no secondary clinical outcomes. The hypothesized pathway and the measured endpoint should not be conflated with symptoms or disease control.

Finally, the planning illustrations make the observed effect's uncertainty consequential for future-study planning. Their large participant requirements reflect the stated assumptions and effect fractions, not the original study design or a guarantee of success. Clear reporting of outcome definitions, analysis populations, missing-data methods, and prespecified plans would help readers judge both the result and the appropriate design of later research.

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.

Several limitations are specific to the information recorded for this study. The intervention groups have 20 participants each, and the result is a single posted comparison for a molecular endpoint. The confidence interval is broad and includes effects in either direction, limiting how precisely the mean difference can be characterized. The record does not provide a clinically meaningful threshold for the biomarker.

The primary outcome description notes measurement at baseline and 3 weeks, but it does not make clear whether the posted means represent follow-up expression, change from baseline, or another summary. This leaves uncertainty about the exact estimand. Further details about RT-PCR processing, biopsy collection, assay variability, and quality control are not reported in the registry record.

The record does not provide a detailed analysis plan, the analysis population, missing-data handling, or an account of participants without evaluable results. It lists no secondary outcome results and no analysis records. These reporting gaps prevent assessment of whether the comparison accounts for baseline measurements or whether other planned outcomes could contextualize the biomarker finding.

The registry identifies the study as randomized and double-blind, but the methods used to generate and conceal allocation and maintain masking are not described. Safety follow-up details are also not reported. Finally, a three-week biological measurement cannot on its own establish longer-term effects, and this record does not post clinical outcomes that would show whether the marker result corresponds to changes in patients' condition.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Effect of Pimecrolimus Cream on Cathelicidin Levels in Subjects With Eczema — NCT00946478.
• Registry record last updated 2014-03-10; status last verified 2014-01.
• Results first posted 2014-03-10.
• 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, randomized, double-blind, parallel study of pimecrolimus cream 1% versus vehicle cream in people with atopic dermatitis. The recorded enrollment is 40, with 20 participants listed in each intervention group. The study's start is recorded as 2009-10 and primary completion as 2011-02.

The primary outcome is cathelicidin mRNA expression in adult skin, measured in delta-delta ct units on PCR. At 3 weeks, the posted group means are 0.002 for pimecrolimus and 0.002 for vehicle cream. The mean difference is -0.001, with a 95% confidence interval from -0.010 to 0.008 and an unadjusted p-value of 0.858.

No secondary outcome results are posted. The analysis population, missing-data methods, detailed statistical plan, and deaths are not reported in the registry record. The posted endpoint is a laboratory measure and does not directly report clinical symptoms or disease outcomes.