Secukinumab Safety and Efficacy in Juvenile Psoriatic Arthritis (JPsA) and Enthesitis-related Arthritis (ERA): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Secukinumab Safety and Efficacy in Juvenile Psoriatic Arthritis (JPsA) and Enthesitis-related Arthritis (ERA) (NCT03031782), a randomized phase 3 study. The primary outcome is Number of Participants Experiencing a Flare During Treatment Period 2.

2. Clinical Question

This is a question about maintaining response after an initial active-treatment period, rather than a comparison of starting secukinumab with starting placebo in an unselected group. Eligibility for the withdrawal comparison depended on having at least an ACR 30 response in Treatment Period 1. The randomized groups therefore represent participants who met that response condition and entered Treatment Period 2.

The registry lists juvenile psoriatic arthritis and enthesitis-related arthritis as the conditions of interest. The primary outcome description says that participants were either in the ERA or JPsA category, but the reported primary analysis combines the Treatment Period 2 comparison. The posted primary result does not give separate estimates for those categories. It therefore addresses the combined randomized withdrawal comparison, not whether the result differs between the two arthritis categories.

3. Trial Design

The registry identifies this as a Phase 3 randomized, parallel-group study with quadruple masking. Its summary describes a double-blind, placebo-controlled, event-driven randomized withdrawal study of secukinumab in juvenile idiopathic arthritis categories of juvenile psoriatic arthritis and enthesitis-related arthritis. Both descriptions identify a blinded placebo comparison in Treatment Period 2; the registry record does not explain the difference in masking terminology.

The study had three treatment periods followed by post-treatment follow-up. Treatment Periods 1 and 3 were open-label, single-arm active treatment. Treatment Period 2 was the randomized, double-blind, placebo-controlled withdrawal period. Participants who achieved at least an ACR 30 response in Treatment Period 1 could be assigned to secukinumab or matched placebo for Treatment Period 2. This design makes the Treatment Period 2 groups a selected responder population rather than all participants who began the study.

The primary outcome was the number of participants experiencing a flare during Treatment Period 2, analyzed as time to flare. The timeframe is From Week 12 until max Week 104. The primary analysis population, called the Full Analysis Set for TP2 in the registry, included randomized participants who received at least one dose in that period. Participants were analyzed according to the treatment assigned at randomization in Treatment Period 2.

The registry reports enrollment of 86 and lists the study as completed. The listed study start was 2017-05-23 and primary completion was 2020-10-07. These overall registry entries do not establish how many participants were included in each particular analysis; the primary arm counts and analysis-population definition are the relevant information for interpreting the randomized comparison.

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.

Before assignment: AIN457 treatment group refers to all subjects who did not take any placebo before or during the period in the study. The term Placebo in TP2 refers to all subjects who took placebo in TP2 and secukinumab in other periods. For ease of reading, Placebo in TP2 treatment group is referred as placebo treatment group or placebo hereafter in this document.

Treatment Period 1

Reasons for not completing this period:

Treatment Period 2

Reasons for not completing this period:

Treatment Period 3

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full Analysis Set for TP2: The FAS TP2 (FAS 2) consisted of all randomized subjects who received at least one dose of study drug in TP2. Following the intent-to-treat principle, subjects were analyzed according to the treatment they were assigned to at randomization in TP2.

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: Safety Set included subjects who received any treatment. TP1 = 86, TP2 = 75

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants Experiencing a Flare During Treatment Period 2, measured over From Week 12 until max Week 104.

The primary endpoint concerns whether a participant experienced a flare during Treatment Period 2 and, in the sponsor analysis, how long it took for a flare to occur. A flare is the event being counted; time to flare also uses the timing of that event to compare the treatment groups. The registry labels the outcome as a participant count and describes the primary analysis as survival analysis of time to flare.

Time-to-event methods are used when the timing of an event matters and participants may have different lengths of observation. These methods can incorporate information about when events occur rather than reducing the outcome to a simple yes-or-no count over a fixed observation span. Participants without a recorded event by the end of their observation may contribute information up to that point, depending on the analysis rules. The detailed censoring and event-handling rules are not reported in the registry record.

The primary timeframe runs from Week 12 until max Week 104. This endpoint is suited to the withdrawal question because it evaluates the occurrence and timing of flare during the randomized period. The registry also posts the number of participants experiencing a flare in each arm. Those counts provide a straightforward description of observed events, but they do not carry all the timing information used by a survival analysis. The registry record does not provide the detailed event-time data needed to reproduce the sponsor’s time-to-event estimate.

7. Results Posted in the Registry

• AIN457 in Treatment Period 2: 27.0% (10/37) versus 55.3% (21/38) on control; risk difference -28.2 percentage points (95% CI -49.6 to -6.9), risk ratio 0.49 (0.27–0.89); unadjusted two-proportion z-test p = 0.013.

8. Statistical Interpretation

9. Statistical Methods Explained

The registry’s primary analysis is described as a log-rank test with a Cox proportional hazards parameter. These are methods for comparing the timing of events between groups. The reported parameter is a hazard ratio, which expresses the relative event rate over time under the Cox model. It is not the same quantity as a risk difference, risk ratio, or odds ratio calculated from whether an event occurred by a particular point.

What does a time-to-event analysis use?

General explanation: a time-to-event analysis uses both whether an event occurred and the time at which it occurred. A participant who has not experienced the event by the last observed point may still contribute information up to that point; this is often called censoring. Such methods can be useful when observation time varies or when not all participants experience the event during the analysis period. The registry record does not report the detailed censoring rules, event adjudication procedures, or follow-up handling used for this analysis.

The log-rank test compares event experience over time between groups. The Cox proportional hazards model estimates a relative hazard while accounting for the event-time information. A key model condition is proportional hazards: broadly, the relative hazard between groups is assumed to remain sufficiently stable over time for a single hazard ratio to be a useful summary. General explanation: if the relative hazard changes substantially over time, one number may not fully describe the pattern. The registry record does not report whether this condition was assessed or what diagnostics were used.

How is the recalculation different?

The recalculation uses the posted counts of participants with a flare and the arm sizes to make an unadjusted binary-outcome comparison. It does not use each participant’s event time or the duration of observation. A risk difference describes the difference between the observed event proportions in the two groups. The associated unadjusted p-value is 0.013. This recalculated comparison is not the same estimand or method as the sponsor’s log-rank and Cox analysis, and the registry flags a discrepancy. The sponsor’s own analysis takes precedence for interpreting the primary result.

General explanation: an unadjusted calculation uses the posted summary counts without adjustment for other characteristics or event timing. It can help readers understand a simple comparison, but it cannot reproduce a time-to-event model from summary counts alone. Results from different methods can differ because they use different information and answer slightly different statistical questions; neither should be silently substituted for the other.

Why can event counts and hazard ratios differ in emphasis?

Two groups can have different counts of participants with events while the time pattern also matters. For example, the same count comparison could conceal whether events tended to occur earlier or later in follow-up. A time-to-event analysis incorporates that timing information, subject to its assumptions and handling of censoring. The posted counts remain useful for describing how many events were recorded, while the sponsor’s estimate summarizes the modeled relative event rate over time.

General explanation: over-dispersion is a concern for some count outcomes when variation exceeds what a simple count model expects. It is not the central issue for the primary endpoint as reported, which is analyzed using time-to-event methods and is also presented as a participant count. The registry does not report a count-model analysis for the primary endpoint. No additional count-model assumptions should be inferred from the posted counts.

What role does randomization play?

Random assignment in Treatment Period 2 supports a comparison between assigned groups among the participants who entered that period, subject to the analysis population and how post-randomization data were handled. The registry says the Full Analysis Set for TP2 included all randomized participants who received at least one dose of study drug in TP2, and participants were analyzed according to their assigned treatment. This description is not identical to an all-randomized population that includes participants who received no dose; the registry record does not describe the outcomes of any such participants or how their data were handled.

The interpretation is also shaped by the withdrawal design. Entry into the randomized period followed active treatment and required at least an ACR 30 response in Treatment Period 1. Therefore, the randomized estimate applies to that selected population and period. It does not, by itself, describe the effect of beginning treatment in all children with either condition.

The reported p-value and confidence interval belong to the sponsor’s time-to-event analysis. The recalculated p-value belongs to the separate unadjusted event-count comparison. A p-value measures compatibility between observed data and a specified statistical null under the method’s assumptions; it is not the probability that the null is true. Nor does it measure the clinical importance of the result. The registry record does not report whether the primary result was adjusted for multiple testing, whether interim analyses were planned, or the original design assumptions.

10. Confidence Intervals and Precision

The sponsor’s hazard ratio is 0.28, with a 95% confidence interval from 0.13 to 0.63. The interval expresses uncertainty around the estimated relative hazard under the sponsor’s time-to-event analysis. Its endpoints are compatible with a range of relative hazard values under that model; they do not show the range of individual participant outcomes or guarantee that the true value lies within the interval.

The interval does not cross 1, the neutral value for a hazard ratio, and the sponsor reports p < 0.001. These are two related summaries of the same time-to-event analysis, not independent confirmations. The interval’s width indicates that the estimate is not exact: plausible values under the model span a range, even though the interval lies on one side of the neutral value. Precision should therefore be discussed separately from whether the result meets a statistical significance threshold.

The posted counts are 10 participants experiencing a flare among 37 in the AIN457 arm and 21 among 38 in the placebo arm. The unadjusted recalculation produces a risk-difference estimate and p-value, but the sponsor’s reported confidence interval is for the hazard ratio, not that binary comparison. These estimates should not be placed on the same scale or treated as interchangeable. The registry does not provide a confidence interval for the arm-specific event counts in the primary outcome display.

General explanation: confidence intervals describe the uncertainty of an estimate under a specified model and sampling framework. They do not account automatically for every possible source of bias, model misspecification, missing data, or multiplicity. The interval’s interpretation depends on the Cox model and its assumptions, including the handling of event times and censoring. Details on these procedures and model checks are not reported in 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 estimates are illustrations based on the observed effect, not a reconstruction of the trial’s original design. For this binary participant-count comparison, the figures are participants per arm, not total events. The assumptions listed for the illustration are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; the effect to detect is the stated fraction of the observed effect. The trial’s own original sample-size assumptions are not reported in the registry record.

For planning for 100% of the observed effect, the illustration lists 47 participants per arm for 80% power and 62 participants per arm for 90% power. For planning for 75% of the observed effect, it lists 86 participants per arm for 80% power and 114 participants per arm for 90% power. For planning for 50% of the observed effect, it lists 196 participants per arm for 80% power and 262 participants per arm for 90% power.

In plain language, the 80% power column gives the illustrated participants per arm for a design with an 80% chance of detecting the specified effect if that effect were the true one and the stated assumptions held. The 90% column gives the corresponding planning figure for a 90% chance. These values are not observed power. They are prospective planning illustrations, not a measure of the probability that the completed trial’s result is correct.

Smaller effects require more participants in these illustrations because they are harder to distinguish from random variation. The estimates depend on the observed effect used as their starting point, so they should not be treated as universal requirements for future studies or as evidence about 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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.553; treatment proportion p₁ = 0.270; average p̄ = 0.411.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6959 = 1.3640.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6667 = 0.5611.
4. n = (1.3640 + 0.5611)² / (-0.2824)² = 46.5, rounded up to 47 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.552631578947368                          # control proportion
p1 <- 0.27027027027027                          # 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(3031782)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 47 (80% power), 62 (90% power)
 75% of observed effect: n per arm = 86 (80% power), 114 (90% power)
 50% of observed effect: n per arm = 196 (80% power), 262 (90% power)
power.prop.test: 46.5 
Simulated power at n = 47 per arm: 0.799 (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. Analyses Reported by the Sponsor

The sponsor reported a log-rank analysis with a Cox proportional hazards parameter for the time-to-flare outcome. The hazard ratio was 0.28, with a 95% confidence interval from 0.13 to 0.63 and p < 0.001. This is the registry’s reported time-to-event result and uses event timing, rather than only the number of participants with a recorded flare.

A separate unadjusted recalculation uses the posted event counts and arm sizes. It compares the binary event outcome and gives an unadjusted p-value of 0.013. The registry flags a discrepancy between the recalculation and the sponsor’s analysis. The methods answer different statistical questions, so the recalculation should not be presented as a correction or replacement for the time-to-event result.

Where the registry marks a discrepancy, the sponsor’s own analysis takes precedence. The recalculation can still serve as a descriptive check on the posted counts, with the clear qualification that it does not incorporate the event timing used in the sponsor analysis. The registry record does not provide the participant-level data or detailed analysis procedures needed to reproduce the sponsor’s model independently.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists 11 outcome measures and 10 posted secondary outcomes, while the primary outcome is the number of participants experiencing a flare during Treatment Period 2. It reports one primary analysis: a log-rank analysis with a Cox proportional hazards parameter. The sponsor’s reported p-value is p < 0.001. The registry record does not report whether the primary test was adjusted for multiple comparisons or how the secondary outcomes were handled as a family of tests.

Multiplicity matters when many outcomes, time points, subgroups, or analyses are tested. General explanation: with repeated testing, the chance of at least one apparently unusual result can increase unless the analysis plan controls that chance or interprets findings with suitable caution. The record does not report a multiplicity procedure, a testing hierarchy, or which secondary outcomes were confirmatory versus exploratory. No adjustment should be assumed.

The primary analysis population is described as the Full Analysis Set for TP2: randomized participants who received at least one dose of study drug in Treatment Period 2. Participants were analyzed according to the treatment assigned at randomization in that period. The registry record does not report the number excluded from this population, the reasons for exclusion, or how missing outcome information was handled.

Details on censoring, withdrawal, incomplete follow-up, and the handling of participants without an observed flare are not reported in the registry record. The record also does not say whether interim analyses were performed or planned. These omissions limit independent assessment of the time-to-event analysis and of how much information contributed to the estimate.

The registry reports a combined primary result for the JPsA and ERA categories, without separate primary estimates by category. It does not report a subgroup analysis plan or treatment-by-category interaction test. Consequently, the posted primary result cannot establish whether the comparative result differed across the two categories. The same caution applies to any unreported participant characteristics or subgroup comparisons.

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 2% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: acute sinusitis (2.6%), pneumonia (2.6%), postoperative wound infection (2.6%), tonsillitis (2.6%), juvenile psoriatic arthritis (2.6%).

The registry’s adverse-event entries use different exposure descriptions for the active-treatment and placebo groups. For AIN457 in the Entire Treatment Period, the record lists 48 at risk, 7 with serious adverse events, and 44 with other adverse events. For Placebo in TP2, it lists 38 at risk, 4 with serious adverse events, and 35 with other adverse events. The total row lists 86 at risk, 11 with serious adverse events, 79 with other adverse events, and 0 deaths.

These entries should be read as registry-reported counts, not as a matched safety comparison across the randomized period. The active-treatment entry covers the entire treatment period, whereas the placebo entry covers Treatment Period 2. The differing exposure periods mean the two group rows do not represent equivalent observation windows. The record does not provide exposure-adjusted rates or enough detail to align the groups’ safety follow-up.

The registry lists Acute sinusitis, Pneumonia, Postoperative wound infection, Tonsillitis, Juvenile psoriatic arthritis, and Adenoidal hypertrophy among the top serious adverse-event terms, each at 2.6%. Serious adverse-event counts and event terms are descriptive safety information; they do not establish that a particular event was caused by study treatment. The record’s adverse-event summaries should not be interpreted as a causal comparison without further details on attribution, exposure, and collection methods.

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

The posted primary results describe a randomized withdrawal comparison in participants who achieved at least an ACR 30 response during Treatment Period 1 and entered Treatment Period 2. The registry reports fewer participants with a recorded flare in the AIN457 arm than in the placebo arm, and the sponsor’s time-to-event analysis reports a hazard ratio of 0.28 with a 95% confidence interval from 0.13 to 0.63 and p < 0.001. These figures describe the observed trial comparison under its design and analysis.

The result does not establish how the groups would compare among all children with juvenile psoriatic arthritis or enthesitis-related arthritis, including those who did not meet the response condition before randomization. Nor does it provide separate primary estimates for JPsA and ERA. The withdrawal design and selected Treatment Period 2 population are central to understanding which question the result addresses.

The hazard ratio is a model-based summary of relative event rates over time. It is not the same as the difference in the proportion of participants who experienced a flare, and it is not a percentage reduction. The separate unadjusted recalculation from posted counts is not the sponsor’s time-to-event analysis; because the registry flags a discrepancy, the sponsor’s reported analysis takes precedence.

Statistical evidence does not by itself determine clinical importance, the experience of any individual participant, or whether a result will apply to other settings. The confidence interval reflects uncertainty under the reported model but does not remove potential limitations from missing data, assumptions, or selective reporting. Those details are not reported in the registry record. The safety counts also have different observation periods for the active-treatment and placebo rows, limiting direct comparison.

Accordingly, the findings should be read as evidence about time to flare in this randomized withdrawal setting, alongside the posted event counts and the stated analysis limitations. They do not establish a universal effect across all participants or substitute for a full assessment of the trial’s methods and safety information.

17. Why This Trial Matters Statistically

This trial is statistically informative because its primary question is about maintaining a response after an initial active-treatment period. The randomized withdrawal design separates the initial open-label treatment experience from the later blinded comparison. That distinction changes the target population: the primary randomized result applies to participants who achieved at least an ACR 30 response and proceeded to Treatment Period 2, not to everyone who might begin treatment.

The endpoint also illustrates why analysis method matters. The registry posts participant counts with a flare, but the sponsor’s primary analysis uses time to flare. A binary count discards event timing; the survival analysis uses timing and can account for differing observation through its analysis rules. The sponsor’s hazard ratio and the unadjusted event-count comparison therefore should not be treated as alternate expressions of the same calculation.

The registry flags a discrepancy between the sponsor analysis and the recalculation, making transparent separation of the two especially important. The sponsor’s model-based result is the reported primary analysis, while the recalculated count comparison offers a simpler descriptive perspective. Clearly stating what each estimate measures helps readers avoid conflating a hazard ratio with an event proportion or risk difference.

The registry also illustrates the limits of interpreting safety counts without aligned exposure periods. The active-treatment serious adverse-event summary covers the entire treatment period, while the placebo summary covers Treatment Period 2. Reporting the scope alongside the counts prevents an unsupported like-for-like comparison. Together, the design, endpoint, analysis, and reporting details show why estimates must be interpreted in relation to the population, timeframe, and method that produced them.

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 primary randomized comparison is restricted to participants who achieved at least an ACR 30 response in Treatment Period 1 and were assigned to Treatment Period 2. This selection means the result does not directly represent all participants who entered the study or all people with either condition. The study summary describes open-label active treatment in Treatment Periods 1 and 3 and a blinded placebo comparison in Treatment Period 2; the result should be interpreted within that sequence.

The primary outcome is described as time to flare from Week 12 until max Week 104, but detailed rules for defining a flare, censoring, handling incomplete follow-up, and analyzing missing data are not reported in the registry record. The model’s proportional-hazards assessment and other diagnostics are also not reported. Without these details or participant-level data, the sponsor estimate cannot be independently reproduced from the registry summary.

The primary result is reported for the combined JPsA and ERA population. Separate primary estimates by category and a test of whether the comparison differs by category are not reported in the registry record. The posted result therefore cannot establish that the estimate is the same in both categories or that one category accounts for the combined finding.

The registry marks a discrepancy between the sponsor’s time-to-event analysis and an unadjusted recalculation based on event counts. The two approaches use different information, and the sponsor’s analysis takes precedence for the primary result. The registry record does not include enough detailed analysis information to investigate the discrepancy further.

Safety summaries use different periods for the active-treatment and placebo rows, limiting direct comparison. The registry does not report the original sample-size assumptions, multiplicity strategy, interim-analysis details, or full missing-data procedures. These reporting gaps constrain interpretation and should not be filled by assumptions.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Secukinumab Safety and Efficacy in Juvenile Psoriatic Arthritis (JPsA) and Enthesitis-related Arthritis (ERA) — NCT03031782.
• Registry record last updated 2022-08-15; status last verified 2022-08.
• Results first posted 2022-08-15.
• 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

NCT03031782 is a completed Phase 3 randomized, parallel-group study of secukinumab in juvenile psoriatic arthritis and enthesitis-related arthritis. The registry describes open-label active treatment in Treatment Periods 1 and 3 and a randomized, double-blind, placebo-controlled withdrawal comparison in Treatment Period 2. The primary outcome was time to flare from Week 12 until max Week 104.

The sponsor’s reported log-rank and Cox analysis gives a hazard ratio of 0.28, a 95% confidence interval from 0.13 to 0.63, and p < 0.001. Posted flare counts were 10 in the AIN457 arm and 21 in the placebo arm. An unadjusted recalculation from those counts differs from the sponsor analysis; the sponsor’s result takes precedence. Interpretation is limited to the selected randomized withdrawal population, and the registry record does not report several analysis details, including missing-data handling and multiplicity procedures.