A Study to Determine Safety and Efficacy of B244 in Subjects With Mild to Moderate Rosacea: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study to Determine Safety and Efficacy of B244 in Subjects With Mild to Moderate Rosacea (NCT03590366), a randomized phase 2 study. The primary outcome is Number of Participants With Treatment-related Adverse Events as Assessed by CTCAE v4.0.

2. Clinical Question

3. Trial Design

This was a randomized, vehicle-controlled Phase II study of B244 in subjects with mild to moderate rosacea. The registry describes the study as prospective, double-blind, and multicenter, with a parallel-group model and quadruple masking. The planned enrollment was 140. The registry status is completed. The listed study dates are 2018-07-02 for study start and 2019-02-11 for primary completion.

Participants were assigned to B244 or vehicle. Both arm descriptions specify topical application to the face twice daily, with four pumps per application from a 30ml bottle. The brief study description identifies an 8-week treatment comparison. The primary endpoint timeframe, however, is listed as baseline to Day 84; the registry record does not explain the relationship between that endpoint timeframe and the 8-week application period.

The reported arm sizes for the primary endpoint were 73 for B244 and 67 for vehicle. The primary population is described as mITT. It included participants who met all inclusion and exclusion criteria, were randomized, received dispensed treatment, and had at least one post-treatment efficacy evaluation. This definition is the population specified for the primary endpoint; the registry record does not report further details about how participants without those characteristics were handled.

The comparator was vehicle rather than no treatment. This design allows the reported arm outcomes to be contrasted within the randomized study, while the vehicle arm accounts for outcomes observed under the study’s vehicle application and follow-up. The registry record does not report the method used to generate the randomization sequence, the allocation concealment procedure, or which roles were included in quadruple masking. Further protocol details, including the trial’s original sample-size justification, are not reported in the registry record.

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:

Analysis population for the primary outcome, as defined in the registry: Modified Intent to Treat (mITT) Population, which included all subjects who all subjects who met all inclusion/exclusion criteria, were randomized, dispensed treatment, and had at least one post-treatment efficacy evaluation.

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.

Population: Modified Intent to Treat (mITT) Population: all subjects who all subjects who met all inclusion/exclusion criteria, were randomized, dispensed treatment, and had at least one post-treatment efficacy evaluation.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With Treatment-related Adverse Events as Assessed by CTCAE v4.0, measured over Baseline to Day 84.

The primary endpoint counted the number of participants with treatment-related adverse events assessed using CTCAE v4.0. Its timeframe was baseline to Day 84, and the endpoint description characterizes the safety and tolerability outcomes as all treatment-related adverse events reported during the study duration. The posted count was 5 participants in the B244 arm and 6 in the vehicle arm. The corresponding arm sizes were 73 and 67.

A participant count is a binary-outcome summary: each participant is classified according to whether the event occurred, and the arm result reports how many participants met that definition. The endpoint is used to describe safety and tolerability during the study period. It is distinct from the secondary outcomes that measure rosacea-related changes, such as IGA and CEA improvement. The record does not give further detail about how investigators judged an adverse event to be treatment-related, nor does it report event-level descriptions for the treatment-related events contributing to this primary count.

Counts are useful for communicating how many participants experienced an endpoint, but the arm counts alone do not express the precision of the comparison. The accompanying risk-difference estimate and confidence interval describe the contrast between arms and its uncertainty. They should be interpreted in light of the modest number of participants and events, as well as the registry’s lack of detail on missing-data handling and the analysis plan.

7. Results Posted in the Registry

• B244: 6.8% (5/73) versus 9.0% (6/67) on control; risk difference -2.1 percentage points (95% CI -11.1 to 6.9), risk ratio 0.76 (0.24–2.39); unadjusted two-proportion z-test p = 0.644.

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.

Proportion of Subjects With IGA Improvement at Week 8 Relative to Baseline.

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • B244: 69.9% (51/73) versus 56.7% (38/67) on control; risk difference 13.1 percentage points (95% CI -2.7 to 29.0), risk ratio 1.23 (0.95–1.59); unadjusted two-proportion z-test p = 0.106.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between B244 and the control. The interval gives the range of effects that remain compatible with the data.

Proportion of Subjects With CEA Improvement at Week 8 Relative to Baseline.

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • B244: 67.1% (49/73) versus 56.7% (38/67) on control; risk difference 10.4 percentage points (95% CI -5.6 to 26.4), risk ratio 1.18 (0.91–1.54); unadjusted two-proportion z-test p = 0.205.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between B244 and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists six secondary outcomes, covering IGA and CEA improvement, changes in those measures, Skindex 16 scores and subscores, and changes in PSA. Numerical arm results are posted for the Week 8 IGA improvement and CEA improvement outcomes. Numerical results for the other listed secondary outcomes are not reported in the registry record. The available secondary results therefore offer only a partial view of the broader outcome set described in the record.

The two posted improvement estimates are positive for B244 relative to vehicle, while their confidence intervals include zero. This general direction differs from the negative point estimate for the primary safety risk difference, but the endpoints measure different things: the primary endpoint counts treatment-related adverse events, whereas IGA and CEA improvement assess clinical changes. The results should not be combined into a single conclusion about benefit or safety, and one endpoint does not validate another.

The secondary findings carry less evidential weight in part because they are among multiple outcomes. When many outcomes or comparisons are examined, the chance of seeing an apparently notable result by chance can increase. In general, a prespecified multiplicity strategy can address that issue, but whether such a strategy was specified or used is not reported in the registry record. The posted secondary p-values are unadjusted.

The registry also does not report a complete set of analyses for the six listed secondary outcomes. Without those results and a reported analysis plan, the available findings should be treated as limited evidence about the specific posted comparisons, not as a complete account of all secondary endpoints. The secondary outcomes can help describe what was assessed, but their incomplete posting and unadjusted status make them less decisive than a fully reported, prespecified analysis set.

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

• Proportion of Subjects With IGA Improvement at Week 8 Relative to Baseline.
• Proportion of Subjects With CEA Improvement at Week 8 Relative to Baseline.
• Change in IGA From Week 8 to Baseline.
• Change in CEA From Week 8 to Baseline.
• Change in Skindex 16 and Skindex 16 Sub Scores at Week 1, Week 4, Week 8 and Week 12 From Baseline.
• Proportion of Subjects With Change in PSA at Week 1, Week 4, Week 8 and Week 12 From Baseline.

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference describe?

In general, a risk difference compares the proportion of participants meeting an endpoint in one arm with the proportion in another arm. The reported comparison is for B244 versus vehicle. A negative estimate for the primary endpoint means the observed event proportion was numerically lower in the B244 arm; a positive estimate for the improvement outcomes means the observed improvement proportion was numerically higher in that arm. These are descriptions of the posted estimates, not evidence by themselves that an intervention caused a difference.

For the primary endpoint, the risk-difference estimate was -0.021. The registry also reports the arm proportions as 0.090 for vehicle and 0.069 for B244. For IGA improvement, the reported proportions were 0.567 for vehicle and 0.699 for B244, with a risk difference of 0.132. For CEA improvement, the reported proportions were 0.567 for vehicle and 0.671 for B244, with a risk difference of 0.104. These arm summaries and comparisons use the posted participant counts and arm sizes.

How should a confidence interval be understood?

In general, a confidence interval expresses uncertainty around an estimated effect. A narrower interval indicates greater precision than a wider interval, under the assumptions of the method used. An interval that includes zero for a risk difference is compatible with no difference between arms as well as with differences in either direction. For the primary endpoint and both posted improvement outcomes, the reported intervals include zero. This does not establish that the arms are identical; it indicates that the estimates do not pin down a nonzero difference with precision in these data.

The primary risk-difference interval runs from -0.111 to 0.069. For IGA improvement it runs from -0.027 to 0.290, and for CEA improvement it runs from -0.056 to 0.264. The registry does not identify the confidence level or describe the interval-construction method, so those details are not reported in the registry record.

What do the p-values add?

In general, a p-value describes 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, nor does it measure the size or clinical importance of an effect. The unadjusted p-values reported for the primary endpoint, IGA improvement, and CEA improvement are 0.644, 0.106, and 0.205, respectively. The registry record does not report an adjusted p-value for these comparisons. The p-values should be considered alongside the effect estimates and intervals, not used as a substitute for them.

The planning illustration uses a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. That assumption describes the posted planning illustration only; the original trial’s design assumptions are not reported in the registry record. The registry also does not report the test or model used for its own comparisons, so the calculation method behind the posted comparison statistics is not reported in the registry record.

Why can event counts be imprecise?

In general, estimates based on relatively few events can be sensitive to the outcomes of individual participants. The primary comparison reports 5 and 6 participants with the endpoint. With few observed events, even a difference of a small number of participants can correspond to considerable uncertainty in an arm comparison. A confidence interval helps make that uncertainty visible; the point estimate alone does not.

In general, over-dispersion matters when observed variability exceeds what a statistical model assumes. It can make standard errors and intervals too small if ignored. The primary and secondary outcomes are participant counts for binary outcomes, and the registry provides no dispersion estimate or model details that would allow over-dispersion to be assessed. No claim about over-dispersion in this trial can be made from the posted record.

What is not specified about the analysis?

The primary population is defined in the registry, but the analysis plan, handling of missing outcome data, and method for adjusting secondary comparisons are not reported in the registry record. Interim analyses are also not reported in the registry record. The posted results should therefore be read as registry-reported arm summaries and comparisons, without assuming unreported protocol procedures or analysis choices.

11. Confidence Intervals and Precision

The primary risk-difference estimate is -0.021, with a confidence interval from -0.111 to 0.069. The interval spans zero and includes values on both sides of it. This means the point estimate alone gives an incomplete picture: the data are compatible with a negative difference as well as a positive difference across the interval. The posted interval does not support a precise estimate of the direction or magnitude of the primary comparison.

The secondary IGA improvement comparison has a risk difference of 0.132 and a confidence interval from -0.027 to 0.290. The CEA improvement comparison has a risk difference of 0.104 and a confidence interval from -0.056 to 0.264. Both intervals include zero and cover a range of possible differences, including values in the opposite direction from each positive point estimate. The registry record does not identify the confidence level or interval method, so those details cannot be assessed from the record.

Precision is affected by the number of participants and the number of observed events or improvements. The primary comparison uses arm sizes of 73 and 67 and has 5 and 6 endpoint events. The secondary comparisons also use those arm sizes, with fewer than all participants meeting the improvement definitions. These sample sizes and event counts are important context for reading the intervals; a point estimate that appears directionally notable can still be uncertain.

The p-values for the three posted comparisons are unadjusted. They do not narrow the confidence intervals or remove their uncertainty. The registry does not report an adjustment for multiple comparisons, a confidence level, or a complete statistical analysis plan. The most transparent reading is therefore to focus on the observed estimates and their reported intervals, while recognizing that the record does not supply enough methodological detail to reconstruct every analysis choice.

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 planning illustrations derived from the observed effect, not the original trial’s reported design justification. The original design assumptions and sample-size justification are not reported in the registry record. The illustrations assume a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. They show the participants per arm associated with 80% power and with 90% power for the stated fraction of the observed effect.

The 80% power column describes a planning scenario in which the assumed effect and model would yield an 80% chance of detecting that effect at the stated significance level. The 90% power column describes the corresponding 90% planning scenario. These are prospective planning quantities; they do not describe the chance that the completed study found a true effect. The figures are not observed power.

For these participant-count outcomes, the figures are participants per arm, not a total across both arms. The stated fractions refer to planning for 100%, 75%, or 50% of the observed effect. Smaller effects require more participants per arm to reach the same planned power under the listed assumptions. The curve represents this same relationship between assumed effect size and planning sample size; it should be read as an illustration, not as a new result from the trial.

The planning values are sensitive to the observed effect used as their starting point. If that effect is imprecisely estimated, the resulting planning illustration can also be uncertain. These figures do not establish that the trial was adequately or inadequately sized for its original objectives, because the registry record does not report the original assumptions, target effect, or sample-size justification.

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 = 0.090; treatment proportion p₁ = 0.068; average p̄ = 0.079.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.3815 = 0.7478.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.3812 = 0.3208.
4. n = (0.7478 + 0.3208)² / (-0.0211)² = 2,574.9, rounded up to 2,575 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 <- 0.0895522388059701                          # control proportion
p1 <- 0.0684931506849315                          # 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(3590366)
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 = 2,575 (80% power), 3,447 (90% power)
 75% of observed effect: n per arm = 4,718 (80% power), 6,315 (90% power)
 50% of observed effect: n per arm = 10,927 (80% power), 14,628 (90% power)
power.prop.test: 2574.9 
Simulated power at n = 2,575 per arm: 0.797 (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 registry lists six secondary outcomes in addition to the primary safety endpoint. Numerical results are posted for two secondary outcomes, IGA improvement and CEA improvement. Results for the other listed secondary outcomes are not reported in the registry record. The record does not describe a hierarchy among the outcomes or say whether one or more secondary outcomes were intended to support a confirmatory claim.

In general, testing multiple outcomes creates a multiplicity issue: as the number of comparisons increases, an apparently unusual result may occur by chance more often than in a single comparison. Statistical plans can address this by specifying a hierarchy, an adjustment method, or an explicitly exploratory interpretation. Whether any of these approaches was used is not reported in the registry record. The posted secondary p-values are unadjusted, so they should not be interpreted as if multiplicity had been addressed.

The primary population is described as mITT and includes participants who met the inclusion and exclusion criteria, were randomized, received dispensed treatment, and had at least one post-treatment efficacy evaluation. The registry does not report how missing data were handled, whether participants were excluded after randomization for other reasons, or whether another analysis population was used for particular endpoints. These details matter because missing outcome data and changes in analysis populations can affect the arm summaries and comparisons.

The statistical analysis plan, interim-analysis procedures, and methods for estimating the posted comparisons are not reported in the registry record. Nor is the original sample-size justification reported. These omissions do not show that the trial lacked such procedures; they mean the registry record does not permit readers to verify them or to determine how closely the posted analyses followed a prespecified plan. The safest interpretation is limited to the definitions, counts, estimates, intervals, and unadjusted p-values that are reported.

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 0% reporting threshold.

Most frequent non-serious adverse event terms

The primary treatment-related adverse-event endpoint recorded 5 participants in the B244 arm and 6 in the vehicle arm, with 73 and 67 participants at risk, respectively. Its timeframe was baseline to Day 84, and events were assessed using CTCAE v4.0. The comparison estimate is imprecise, with a risk difference of -0.021 and a confidence interval from -0.111 to 0.069.

The registry’s separate adverse-event summary reports 0 serious adverse events in each arm and 0 deaths in each arm. It also reports other adverse events affecting 19 of 73 participants receiving B244 and 12 of 67 receiving vehicle. These “other” adverse-event figures are distinct from the primary endpoint’s treatment-related count; the record does not provide enough detail to establish how the event categories overlap.

Zero reported serious adverse events in the posted groups means none were recorded in those groups in the registry summary. It does not establish that serious events are impossible or settle comparative safety for other populations or durations. The registry does not report serious-event terms, and no serious terms are listed. Interpretation is also limited by the study size and the registry’s lack of event-level detail.

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

The posted results describe outcomes among participants in this randomized Phase II study of B244 and vehicle for mild to moderate rosacea. For the primary safety endpoint, the registry reports 5 participants with treatment-related adverse events in the B244 arm and 6 in the vehicle arm. The risk-difference estimate is -0.021, with an interval from -0.111 to 0.069. This is a numerical contrast with substantial uncertainty, not a definitive estimate of a difference.

For the two secondary improvement outcomes with numerical results, the estimates are positive for B244, but their confidence intervals include zero. The registry does not post numerical results for all listed secondary outcomes, and it does not report adjustment for multiple comparisons. These findings therefore describe particular posted comparisons rather than establish an overall conclusion across the trial’s outcome set.

In general, a randomized comparison can help distinguish outcomes between assigned study arms within the trial, but the meaning of any contrast depends on study conduct, outcome definitions, follow-up, analysis choices, and uncertainty. The registry record gives some of these details, including the primary population definition and endpoint timeframe, but it does not report the complete statistical plan, missing-data methods, or original sample-size rationale. These omissions limit assessment of the full analysis process.

The results do not establish that B244 is effective or ineffective, and they do not provide medical advice. They do not show that all participants experienced the same outcomes, nor do they determine what would happen in other settings or over different periods. The primary result concerns treatment-related adverse-event counts; the secondary results concern specific improvement measures. The estimates and intervals should be read as the posted evidence for those outcomes, not as a substitute for a complete clinical evaluation or a fully reported analysis.

17. Why This Trial Matters Statistically

This trial is statistically informative as an example of why effect estimates and uncertainty matter alongside participant counts. The primary endpoint counts were close in absolute terms, and its risk-difference interval includes zero while extending in both directions. Reporting only the counts, or focusing only on the point estimate, would conceal how uncertain the comparison remains.

The study also illustrates the distinction between an endpoint’s statistical role and its subject matter. The primary endpoint measures treatment-related adverse events, while the secondary IGA and CEA outcomes concern improvement. A result in one category cannot be treated as a substitute for another. Considering the endpoints separately helps prevent a safety summary from being mistaken for an efficacy finding, or a secondary improvement estimate from being taken as a complete account of the trial.

The registry’s secondary outcomes raise a further statistical issue: multiple outcomes require careful interpretation. The record lists six secondary outcomes but posts numerical comparisons for two, and the reported secondary p-values are unadjusted. Without a reported multiplicity strategy and complete results, readers cannot determine how the full outcome set was handled. This makes clear reporting of prespecified methods and all planned outcomes important for judging the strength of evidence.

Finally, planning illustrations based on observed effects are not a substitute for a prospectively documented sample-size rationale. They can show how assumptions about the effect size relate to participant requirements, but cannot establish what the original investigators intended or whether the completed study met its original design goals. The registry record’s available information supports a bounded statistical reading, while also showing why full analysis-plan and outcome reporting matter.

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.

The registry record leaves important details unspecified. It does not report the original sample-size justification, the statistical analysis plan, or the method used to calculate the posted comparison statistics. It also does not report a confidence level or interval-construction method. These omissions limit independent assessment of the analysis and prevent a full reconstruction of the trial’s planned statistical approach.

Missing-data handling is not reported in the registry record. The primary population definition requires at least one post-treatment efficacy evaluation, but the record does not explain how participants without such an evaluation were treated in the analyses, or how missing values for particular outcomes were addressed. The registry also does not report whether interim analyses occurred.

Although six secondary outcomes are listed, numerical results are posted for only two. The other listed secondary results are not reported in the registry record. The available secondary p-values are unadjusted, and any multiplicity strategy is not reported. This limits interpretation across the full set of secondary measures.

The trial enrolled 140 participants, with primary endpoint arm sizes of 73 and 67. The primary event counts were 5 and 6. The comparatively limited number of events contributes to uncertainty in the primary comparison, as reflected in its reported interval. The registry also does not provide event-level descriptions for the treatment-related events or serious-event terms. These limitations are specific to the information and outcomes available in the record and should temper conclusions drawn from individual estimates.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: A Study to Determine Safety and Efficacy of B244 in Subjects With Mild to Moderate Rosacea — NCT03590366.
• Registry record last updated 2022-09-16; status last verified 2022-08.
• Results first posted 2022-09-16.
• 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

NCT03590366 is a completed, randomized, vehicle-controlled, double-blind, multicenter Phase II study of topical B244 for mild to moderate rosacea. The parallel-group trial planned enrollment of 140 participants and compared twice-daily application of B244 with vehicle for 8 weeks. The primary endpoint counted participants with treatment-related adverse events assessed using CTCAE v4.0 from baseline to Day 84.

The primary endpoint results were 5 of 73 participants in the B244 arm and 6 of 67 in the vehicle arm. The risk-difference estimate was -0.021, with a confidence interval from -0.111 to 0.069 and an unadjusted p-value of 0.644. Numerical secondary results were posted for IGA and CEA improvement; both risk-difference intervals include zero. The registry lists six secondary outcomes, but numerical results for the other listed outcomes are not reported in the registry record. The record does not report the full statistical plan, missing-data methods, multiplicity strategy, or original sample-size justification.