Safety and Efficacy of IDP-118 Lotion in the Treatment of Plaque Psoriasis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Safety and Efficacy of IDP-118 Lotion in the Treatment of Plaque Psoriasis (NCT02785159), a randomized phase 2 study. The primary outcome is Percent of Subjects With Treatment Success, Defined by at Least a 2 Grade Improvement From Baseline in the Investigator Global Assessment (IGA) Score Equating to Clear or Almost Clear..

2. Clinical Question

3. Trial Design

The registry record describes a completed phase 2, multicenter, randomized, double-blinded, vehicle-controlled study with a parallel design. It lists quadruple masking. Which individuals or roles were masked is not reported in the registry record. Enrollment was 152, and the study start is recorded as 2016-02, with primary completion on 2016-11-20.

Four study arms appear in the posted primary outcome: IDP-118 Lotion, Tazorac Cream, IDP 118 Vehicle Lotion, and IDP-118 Vehicle Cream. Their listed primary-outcome denominators are 62, 58, 15, and 17, respectively. These arm denominators sum to the reported enrollment, but the primary-outcome analysis population and the reasons for any differences between enrollment and outcome denominators, if any, are not reported in the registry record.

The official study title identifies the comparison of IDP-118 Lotion with Tazorac Cream, 0.05%, and the registry lists vehicle lotion and vehicle cream as interventions. The posted comparison estimates use the vehicle lotion as the reference for the lotion and Tazorac comparisons, and vehicle cream as the reference for the vehicle cream comparison. The record does not describe the allocation ratio, sequence generation, concealment procedures, or the specific implementation of the vehicle comparisons.

The registry reports one outcome measure, with the primary endpoint assessed at 12 weeks. It reports no analyses and no secondary outcomes. The original sample-size rationale, planned statistical methods, interim analyses, and any prespecified analysis populations are not reported in the registry record. The record status is completed.

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 Percent of Subjects With Treatment Success, Defined by at Least a 2 Grade Improvement From Baseline in the Investigator Global Assessment (IGA) Score Equating to Clear or Almost Clear., measured over 12 Weeks.

The primary endpoint is the percentage of participants meeting a defined treatment-success criterion at 12 weeks. Success required both at least a 2-grade improvement from baseline in the Investigator Global Assessment score and an assessment of clear or almost clear. The endpoint therefore combines improvement from a participant’s starting score with a threshold for the participant’s status at the assessment.

The Investigator Global Assessment uses a 5-point scale ranging from 0 to 4: 0 is clear, 1 is almost clear, 2 is mild, 3 is moderate, and 4 is severe. The improvement requirement and the final-score requirement are both part of the outcome definition; meeting only one condition would not meet the stated definition.

As a binary outcome, each participant is classified as either meeting or not meeting this success criterion for the reported assessment. Reporting the percentage gives a direct summary of how often the defined endpoint occurred in each arm. It does not convey the full distribution of assessment scores or describe changes at time points other than 12 weeks. The registry does not report details about missing assessments or how those participants were handled in calculating the endpoint.

7. Results Posted in the Registry

• IDP-118 Lotion: 32.3% (20/62) versus 13.3% (2/15) on control; risk difference 18.9 percentage points (95% CI -1.8 to 39.7), risk ratio 2.42 (0.63–9.24); unadjusted two-proportion z-test p = 0.145.
• Tazorac Cream: 13.8% (8/58) versus 13.3% (2/15) on control; risk difference 0.5 percentage points (95% CI -18.9 to 19.8), risk ratio 1.03 (0.24–4.37); unadjusted two-proportion z-test p = 0.963.
• IDP-118 Vehicle Cream: 5.9% (1/17) versus 13.3% (2/15) on control; risk difference -7.5 percentage points (95% CI -28.0 to 13.1), risk ratio 0.44 (0.04–4.39); unadjusted two-proportion z-test p = 0.471.

8. Statistical Interpretation

9. Statistical Methods Explained

What does a binary endpoint represent?

In general, a binary endpoint places each participant into one of two categories for the specified outcome: the event occurred or it did not. For this study, the event is meeting the combined treatment-success definition at 12 weeks. A percentage summarizes the share of participants classified as having that event. It is a concise measure, but it does not show how far participants who did not meet the definition were from it, or describe the full range of their IGA scores.

The listed arm-level values are percentages of participants. The comparisons also include event counts and denominators, which show the numerical basis for the unadjusted calculations. The registry does not describe the analysis population or missing-data rules, so the precise way the primary outcome was handled beyond the posted values is not reported in the registry record.

What does a risk difference describe?

In general, a risk difference is the event proportion in one arm minus the event proportion in the reference arm. A value above zero indicates a higher observed event proportion in the first-named arm under that ordering; a value below zero indicates a lower proportion. The comparison estimates in the registry use the vehicle lotion as the reference for IDP-118 Lotion and Tazorac Cream, and vehicle cream as the reference for IDP-118 Vehicle Cream.

For the IDP-118 Lotion comparison, the posted risk difference is 0.189. For Tazorac Cream, it is 0.005, and for IDP-118 Vehicle Cream, it is -0.074. These are proportions on the risk-difference scale, not the arm-level percentages. They are unadjusted recalculations based on the posted counts. They should not be mistaken for adjusted estimates from an analysis model, since the registry reports zero analyses.

How should a confidence interval be understood?

In general, a confidence interval expresses uncertainty around an estimate using a specified statistical method. It identifies values compatible with the observed data and that method; it does not guarantee that the true effect lies inside the particular interval. A narrow interval indicates greater precision than a wide interval, while an interval spanning zero for a risk difference is compatible with no difference as well as with effects in either direction.

All three posted risk-difference intervals include zero. The IDP-118 Lotion interval extends from -0.018 to 0.397; the Tazorac Cream interval extends from -0.189 to 0.198; and the vehicle cream interval extends from -0.280 to 0.131. Their widths show that the estimates do not pin down the size of the differences precisely. The especially limited numbers in the vehicle arms are relevant context when interpreting that uncertainty.

What does an unadjusted p-value tell the reader?

In general, a p-value measures how unusual data at least as incompatible with a specified null hypothesis would be if that hypothesis and the statistical model were correct. It is not the probability that the null hypothesis is true, and it does not measure the clinical importance of an estimate. A p-value also does not resolve the effects of missing data, bias, or analyses that were not reported.

The posted unadjusted p-values are 0.145 for IDP-118 Lotion, 0.963 for Tazorac Cream, and 0.471 for IDP-118 Vehicle Cream, each against its listed vehicle reference. Because the registry reports no analyses and no multiplicity method, these values should be understood as unadjusted comparisons rather than as evidence from a fully documented analysis plan.

Why do small event counts matter?

In general, binary outcomes contain limited information when only a small number of events occur. Estimates based on few events can be sensitive to the outcomes of individual participants, and confidence intervals can be broad. Here, the comparison counts include 2 events in the vehicle lotion reference group for each comparison, and 1 event in the vehicle cream arm. Those counts and the arm denominators help explain why the estimates should be read with attention to precision rather than as exact quantities.

The posted record does not describe use of regression adjustment, stratification, covariate adjustment, or another modeling approach. It also does not report assumptions about the distribution of outcomes or the details of the confidence-interval method. Those items are not reported in the registry record and should not be inferred from the displayed estimates alone.

What does randomization contribute?

In general, random assignment is intended to make treatment groups comparable with respect to measured and unmeasured characteristics on average, reducing selection bias in a comparison. It does not ensure exact balance, particularly in a study with small arms, and it does not correct problems arising from missing outcomes or departures from the planned procedures. The registry identifies the study as randomized, but the sequence-generation and allocation-concealment methods are not reported in the registry record.

The record also identifies the study as double-blinded and lists quadruple masking. The masked roles and practical masking procedures are not reported. Therefore the design labels convey the registry’s classifications, but not the operational details needed to assess how masking was maintained.

10. Confidence Intervals and Precision

Precision concerns how tightly the data locate an effect estimate. The risk-difference intervals are broad relative to their point estimates, and each includes zero. For IDP-118 Lotion versus IDP 118 Vehicle Lotion, the estimate is 0.189 and the interval is -0.018 to 0.397. For Tazorac Cream versus vehicle lotion, the estimate is 0.005 and the interval is -0.189 to 0.198. For IDP-118 Vehicle Cream versus vehicle lotion, the estimate is -0.074 and the interval is -0.280 to 0.131.

In general, the interval describes uncertainty in the estimated contrast under the method used. It is not a range of individual participant outcomes, and it does not mean that every value inside it is equally plausible. An interval that crosses zero does not establish equivalence or prove there is no difference. It indicates that the posted data and method do not rule out zero, while also leaving room for contrasts on either side.

The small reference-arm denominators and low event counts are important to this interpretation. The vehicle lotion comparison group has 15 participants and 2 events; the vehicle cream comparison has 17 participants and 1 event. The denominators for the IDP-118 Lotion and Tazorac Cream outcome arms are 62 and 58. Limited information in the reference groups contributes to uncertainty in the comparisons.

The registry record does not report confidence-interval methods, adjustment variables, or a sponsor analysis. Thus precision should be interpreted from the posted estimates and intervals without assuming that additional model-based adjustments were made. The intervals describe uncertainty in these unadjusted recalculations, not uncertainty about every possible outcome or population.

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 participants across both arms and not total events. They are illustrations based on the observed effect, rather than a report of the trial’s original design calculation. The 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 at the stated fraction of the observed effect. The trial’s original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column means the number of participants per arm estimated under those assumptions to give an 80% chance of detecting the specified effect if that effect and the assumptions were correct. The 90% column makes the same kind of planning calculation at a higher target chance of detection, and therefore generally requires more participants per arm. These are planning calculations, not observed power.

For IDP-118 Lotion compared with vehicle lotion, planning at 100% of the observed effect gives 76 participants per arm for 80% power and 102 participants per arm for 90% power. At 75% of the observed effect, the corresponding figures are 126 and 168 per arm; at 50%, they are 259 and 346 per arm. Detecting a smaller effect requires more participants because a smaller difference is harder to distinguish from random variation under the same assumptions.

The observed Tazorac Cream contrast is close to zero, and the corresponding planning figures at 100% of that effect are 87,059 participants per arm for 80% power and 116,547 for 90% power. The vehicle cream comparison gives 245 and 327 participants per arm at 100% of its observed effect. These are illustrations tied to the observed contrasts, not recommended enrollment targets or a reconstruction of the study’s planning.

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 = 0.133; treatment proportion p₁ = 0.323; average p̄ = 0.228.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5933 = 1.1628.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5780 = 0.4865.
4. n = (1.1628 + 0.4865)² / (0.1892)² = 75.9, rounded up to 76 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 <- 0.133333333333333                          # control proportion
p1 <- 0.32258064516129                          # 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(2785159)
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 = 76 (80% power), 102 (90% power)
 75% of observed effect: n per arm = 126 (80% power), 168 (90% power)
 50% of observed effect: n per arm = 259 (80% power), 346 (90% power)
power.prop.test: 75.9 
Simulated power at n = 76 per arm: 0.808 (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 one outcome measure, identified as the primary endpoint, and zero analyses. It reports zero secondary outcomes. The endpoint is treatment success at 12 weeks, defined by the IGA improvement and ending-score criteria. Beyond that description, the registry does not report a statistical analysis plan or a sponsor analysis.

The record includes three unadjusted comparisons against vehicle arms. It does not report whether these contrasts were all prespecified, whether one was designated as the primary contrast, or how multiplicity was handled. When several comparisons are considered, the chance of at least one apparently notable result can differ from the chance associated with a single planned test. In general, multiplicity procedures may adjust interpretation or thresholds, but no such procedure is reported in the registry record. The posted p-values are explicitly unadjusted.

The record does not report how missing 12-week assessments were handled, whether participants were analyzed according to randomized assignment, or whether any participants were excluded from the primary analysis. The primary population field is blank. Consequently, the analysis population, missing-data assumptions, imputation methods, and sensitivity analyses are not reported in the registry record.

Other analysis details also are not reported in the registry record, including covariate adjustment, stratification factors, subgroup analyses, model specification, and the method used to calculate confidence intervals. Interim analyses and stopping rules are not reported either. These absences do not show that a particular method was or was not used; they mean the registry record does not document it. The unadjusted calculations should therefore be interpreted as limited summaries of the posted counts, not as a substitute for a complete prespecified analysis.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: chest pain (1.8%).

The registry reports serious adverse events among 60 participants at risk in the IDP-118 Lotion arm, with 1 affected; among 57 at risk in the Tazorac Cream arm, with 1 affected; among 15 at risk in the IDP 118 Vehicle Lotion arm, with 0 affected; and among 16 at risk in the IDP-118 Vehicle Cream arm, with 0 affected. These are counts of participants with serious adverse events, not the total number of all events or an adjusted comparison between arms.

The posted adverse-event denominators differ from the primary-outcome denominators. The registry lists Chest pain at 1.8% as the top serious-event term. It does not provide further detail about that term in the record presented. Deaths are not reported in the registry record.

In general, safety counts should be read in the context of the number at risk, observation period, event definitions, and completeness of reporting. The registry gives the listed at-risk counts and serious-event counts, but additional details about event timing, duration, severity categories beyond seriousness, and causal assessment are not reported in the registry record. These figures alone do not establish comparative safety.

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

The posted results describe the percentage meeting a particular IGA-based treatment-success definition at 12 weeks in four randomized study arms. The reported arm values are 31.66% for IDP-118 Lotion, 13.77% for Tazorac Cream, 15.9% for IDP 118 Vehicle Lotion, and 7.96% for IDP-118 Vehicle Cream. The unadjusted risk-difference estimates compare each listed arm with its vehicle reference and have confidence intervals that include zero.

These findings are descriptive of the endpoint, time point, and participants represented in the registry outcome. The confidence intervals indicate that the size and direction of the contrasts are not precisely determined by the posted counts. In particular, the limited vehicle-arm denominators and low event counts make the comparison estimates uncertain. The p-values are unadjusted, and the registry does not report a sponsor analysis or a multiplicity approach.

The record does not establish whether the observed percentages would be similar in other populations, under different assessment conditions, or at other time points. It does not provide secondary outcomes, longer-term outcome data, or details sufficient to evaluate missing data and the analysis population. Nor do these results by themselves establish that the arms are equivalent or that one is superior.

The safety figures report serious adverse events by arm, with the counts and at-risk denominators stated in the registry. They are limited summaries and should not be treated as a complete account of all potential harms or as a definitive comparative safety analysis. The results support a careful reading of the posted trial data, with attention to definitions, uncertainty, and information the registry does not report.

16. Why This Trial Matters Statistically

This study illustrates why an endpoint definition matters. Treatment success was not simply any improvement in IGA score: it required both at least a 2-grade improvement from baseline and a final score of clear or almost clear at 12 weeks. A change in either component alone would not capture the exact outcome reported. Clinical researchers interpreting binary endpoints need to understand this rule before comparing percentages.

The study also illustrates the limits of small reference arms in a randomized comparison. Although the overall enrollment was 152, the vehicle arms contributing to the posted contrasts had 15 and 17 participants in the primary outcome, with few reported events. Randomization is an important design feature, but it cannot make estimates precise when the available outcome information is limited. Confidence intervals show that uncertainty, which a single percentage or point estimate cannot convey.

The registry provides arm values and unadjusted comparison calculations but reports zero analyses. That distinction is important: an arithmetic contrast based on posted counts is not the same as a fully documented sponsor analysis with a prespecified population, missing-data strategy, multiplicity handling, and model specification. When such information is absent, the posted estimates should be read as limited evidence about the reported endpoint, not as a complete statistical account of the trial.

Finally, the planning illustrations show how assumed effect size influences required enrollment. Smaller effects require more participants per arm under the stated planning assumptions. Those calculations are separate from the trial’s own design rationale, which is not reported in the registry record. Keeping observed outcomes, uncertainty, and hypothetical planning distinct is central to responsible 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.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The registry record leaves several trial-specific details undocumented. It does not report eligibility criteria beyond the condition, baseline participant characteristics, the distribution of baseline IGA scores, or the precise analysis population. Without those details, readers cannot assess the representativeness of the participants included in the outcome results or compare baseline characteristics across arms.

The primary-outcome arm denominators differ from some adverse-event denominators, and the registry does not explain the differences. It also does not report missing-outcome counts, the reasons for missing assessments, or how missing data were handled. The record does not describe adherence, treatment discontinuation, protocol deviations, or sensitivity analyses.

The statistical reporting is limited: no analyses are listed, and methods for confidence intervals, adjustment, and multiplicity are not reported in the registry record. The comparison estimates are unadjusted recalculations from posted counts, not documented sponsor analyses. The record also does not report the original sample-size justification or details of random-sequence generation, allocation concealment, and masking roles.

The posted primary outcome is limited to one assessment at 12 weeks. No secondary outcome results are posted, and outcomes beyond that time point are not reported in the registry record. The adverse-event summary gives serious-event counts and one listed serious-event term, but it does not provide a detailed account of event timing, duration, or causal assessment. These limitations constrain interpretation of both comparative outcomes and safety; they do not establish that unreported procedures or data were absent.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Safety and Efficacy of IDP-118 Lotion in the Treatment of Plaque Psoriasis — NCT02785159.
• Registry record last updated 2020-08-20; status last verified 2020-08.
• Results first posted 2020-08-20.
• 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 completed phase 2, multicenter, randomized, double-blinded, vehicle-controlled research with a parallel design and listed quadruple masking. It reports enrollment of 152 and four arms: IDP-118 Lotion, Tazorac Cream, IDP 118 Vehicle Lotion, and IDP-118 Vehicle Cream.

The primary endpoint was treatment success at 12 weeks, defined as at least a 2-grade IGA improvement from baseline and a final status of clear or almost clear. The registry reports arm-level percentages and unadjusted comparisons with confidence intervals, but lists zero analyses and zero secondary outcomes. The comparison intervals include zero, and the record does not report the trial’s original sample-size rationale, analysis population, missing-data methods, or multiplicity handling.

Serious adverse-event counts are reported by arm, with deaths not reported in the registry record. The findings should be read as results for the defined endpoint and the posted data, with attention to the limited arm denominators and uncertainty.