Study in Pediatric Subjects With Peanut Allergy to Evaluate Efficacy and Safety of Dupilumab as Adjunct to AR101 (Peanut Oral Immunotherapy): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study in Pediatric Subjects With Peanut Allergy to Evaluate Efficacy and Safety of Dupilumab as Adjunct to AR101 (Peanut Oral Immunotherapy) (NCT03682770), a randomized phase 2 study. The primary outcome is Percentage of Participants Treated With Dupilumab Plus AR101 vs Placebo Plus AR101 Who Passed a Post Up-dosing Double-blind, Placebo-controlled Food Challenge (DBPCFC) With 2044 mg (Cumulative) Peanut Protein at Visit 16 (Week 28 to 40).

2. Clinical Question

3. Trial Design

This was a phase 2, multicenter, randomized, double-blind, placebo-controlled, parallel-group study of dupilumab as an adjunct to AR101 in pediatric participants with peanut allergy. The registry describes quadruple masking. Enrollment was 148, and the trial is listed as completed. The recorded start was 2018-10-03, with primary completion on 2020-10-16.

The comparison relevant to the primary result was dupilumab plus AR101 versus placebo matching dupilumab plus AR101 during AR101 up-dosing. The registry describes randomization to active dupilumab arms at a ratio of 2 and a placebo arm at a ratio of 1. The primary endpoint analysis included 84 participants in the dupilumab-plus-AR101 group and 39 in the placebo-plus-AR101 group. Those are the analysis counts for this endpoint, not the total enrollment.

The primary assessment took place at Visit 16, within Week 28 to 40. The trial also specified outcomes on cumulative tolerated peanut-protein dose, reaching the 300 mg/Day AR101 dose, time to that dose, maintenance challenge outcomes, and peanut-specific immune measures. Safety and tolerability were also objectives. These different measures address distinct aspects of the treatment period and should not be treated as interchangeable evidence.

The registry record does not report the original sample-size justification, the trial’s detailed statistical analysis plan, or whether interim analyses were planned or conducted. Those design details cannot be inferred from the completed-trial status or from the posted results.

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: A total of 232 participants were screened; 148 participants were randomized. Of the 84 not randomized, 53 did not meet inclusion/exclusion criteria and 13 withdrew consent.

Only the first 6 of 7 groups are shown.

Pre-AR101 Dosing Period (Day 1 - Week 4)

Reasons for not completing this period:

AR101 Up-dosing Period (Week 28-40)

Reasons for not completing this period:

AR101 Maintenance Period: (Week 52-64)

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Modified full analysis set (mFAS) included all participants in the full analysis set (FAS) who underwent biweekly in-clinic up-dosing as described/specified in the protocol and underwent the post up-dosing DBPCFC at Visit 16 (Weeks 28 to 40). Data were planned to be reported and analyzed only for AR101 Up-dosing Period: Dupilumab plus AR101 vs Placebo plus AR101.

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: Full analysis set (FAS) included all randomized participants

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Participants Treated With Dupilumab Plus AR101 vs Placebo Plus AR101 Who Passed a Post Up-dosing Double-blind, Placebo-controlled Food Challenge (DBPCFC) With 2044 mg (Cumulative) Peanut Protein at Visit 16 (Week 28 to 40), measured over At Visit 16 (Week 28 to 40).

The primary endpoint was the percentage of participants who passed a post-up-dosing double-blind, placebo-controlled food challenge with 2044 mg cumulative peanut protein at Visit 16, within Week 28 to 40. The challenge outcome was intended to measure desensitization at the completion of up-dosing. Participants were considered to have passed if they did not experience an objective Grade 1 reaction. Allergic symptoms were graded using the Consortium of Food Allergy Research scale for systemic allergic reactions, which runs from grade 1, mild, through grade 5, death.

A pass/fail outcome makes the endpoint interpretable as the proportion of the analysis population meeting the stated challenge criterion. It is not a direct measure of every possible allergic response, nor does it describe the amount of peanut protein tolerated by each individual. The trial therefore also included cumulative tolerated dose as a secondary measure, which retains information about dose rather than reducing the challenge result to pass or fail.

The primary analysis population was the modified full analysis set: participants in the full analysis set who underwent biweekly in-clinic up-dosing as described in the protocol and completed the post-up-dosing challenge at Visit 16. The reported percentages apply to this defined group. The endpoint describes performance at the specified assessment and does not alone establish maintenance of desensitization at a later challenge.

7. Results Posted in the Registry

• AR101 Up-dosing Period: Dupilumab + AR101: 56.0% (47/84) versus 35.9% (14/39) on control; risk difference 20.1 percentage points (95% CI 1.6 to 38.5), risk ratio 1.56 (0.98–2.47); unadjusted two-proportion z-test p = 0.038.

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.

Change From Baseline in Cumulative Tolerated Dose (Log Transformed) of Peanut Protein During a DBPCFC at Visit 16 (Week 28 to 40) in Participants Treated With Dupilumab Plus AR101 vs Placebo Plus AR101

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • AR101 Up-dosing Period: Dupilumab + AR101: mean 4.45 versus 3.78 on control; difference 0.67 (95% CI 0.01 to 1.33), standardized effect d = 0.37; z-test p = 0.048.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for AR101 Up-dosing Period: Dupilumab + AR101 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percentage of Participants Treated With Dupilumab Plus AR101 vs Placebo Plus AR101 Who Reached the 300 mg/Day Dose of AR101 by Visit 16 (Week 28 to 40)

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • AR101 Up-dosing Period: Dupilumab + AR101: 89.3% (75/84) versus 76.9% (30/39) on control; risk difference 12.4 percentage points (95% CI -2.4 to 27.1), risk ratio 1.16 (0.96–1.40); unadjusted two-proportion z-test p = 0.071.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between AR101 Up-dosing Period: Dupilumab + AR101 and the control. The interval gives the range of effects that remain compatible with the data.

Time From Randomization to the First Time When Participants Reached the 300 mg/Day Dose of AR101 During the Up-dosing Treatment Phase by Visit 16 (Week 28 to 40)

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • AR101 Up-dosing Period: Dupilumab + AR101: mean 167.50 versus 164.60 on control; difference 2.90 (95% CI -10.97 to 16.77), standardized effect d = 0.08; z-test p = 0.682.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between AR101 Up-dosing Period: Dupilumab + AR101 and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes extend the primary question from passing the post-up-dosing challenge to other features of treatment: cumulative tolerated dose, progress to the 300 mg/Day dose, time to reaching that dose, maintenance challenge outcomes, and peanut-specific immune measures. These are related aspects of the study but measure different things. A dose-based measure, a time measure, a later maintenance challenge, and a biomarker outcome cannot be treated as interchangeable evidence of the primary endpoint.

For the secondary results with numerical comparisons reported, cumulative tolerated dose at Visit 16 had a positive least-squares mean difference in the sponsor’s ANCOVA analysis, with p = 0.040. The sponsor analysis of reaching the 300 mg/Day dose reported a difference of 11.91 percentage points, but its confidence interval ranged from -3.612 to 27.440 and p = 0.081. The time-to-dose summary had a recalculated mean difference of 2.9 days, with p = 0.682; no sponsor analysis is posted for that outcome. These results vary in precision and method and should not be collapsed into a single overall conclusion.

The registry lists maintenance and biomarker outcomes among the secondary measures, but numerical results for those measures are not reported in the registry record. Their omission from the available numerical results means that their direction and uncertainty cannot be assessed from these data.

Unadjusted secondary results generally carry less weight than a prespecified primary analysis because many outcomes and comparisons create more opportunities for chance findings. The registry record does not report a multiplicity adjustment or a complete statistical plan, so the status of these secondary tests within any broader testing strategy is unclear. Their p-values should therefore be treated as exploratory signals rather than definitive confirmation of separate effects.

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

• Change From Baseline in Cumulative Tolerated Dose (Log Transformed) of Peanut Protein During a DBPCFC at Visit 16 (Week 28 to 40) in Participants Treated With Dupilumab Plus AR101 vs Placebo Plus AR101
• Percentage of Participants Treated With Dupilumab Plus AR101 vs Placebo Plus AR101 Who Reached the 300 mg/Day Dose of AR101 by Visit 16 (Week 28 to 40)
• Time From Randomization to the First Time When Participants Reached the 300 mg/Day Dose of AR101 During the Up-dosing Treatment Phase by Visit 16 (Week 28 to 40)
• Percentage of Participants (Continuously) Treated With Dupilumab Plus AR101 vs Placebo Plus AR101 Who Passed a Post Maintenance DBPCFC With 2044 mg (Cumulative) Peanut Protein at Visit 22 (Week 52 to 64)
• Change From Baseline in Cumulative Tolerated Dose (Log Transformed) of Peanut Protein During a DBPCFC at Visit 22 (Week 52 to 64) in Participants (Continuously) Treated With Dupilumab Plus AR101 vs Placebo Plus AR101
• Percentage of Participants (Previously) Treated With Dupilumab + AR101/Placebo +AR101 vs Placebo Plus AR101 Who Passed a Post Maintenance DBPCFC With 2044 mg (Cumulative) Peanut Protein at Visit 22 (Week 52 to 64)
• Change From Baseline in Cumulative Tolerated Dose (Log Transformed) of Peanut Protein During a DBPCFC at Visit 22 (Week 52 to 64) in Participants (Previously) Treated With Dupilumab + AR101/Placebo +AR101 vs Placebo Plus AR101
• Percent Change From Baseline in Peanut-specific IgE in Participants Treated With Dupilumab Plus AR101 vs Placebo Plus AR101 to Visit 16 (Week 28 to 40)

9. Statistical Interpretation

10. Statistical Methods Explained

Statistical methods help distinguish the observed group results from the uncertainty and assumptions involved in comparing them. The formal primary analysis reported in the registry used a Cochran-Mantel-Haenszel method. The additional simple recalculation is unadjusted and based on posted summary statistics; it is not a replacement for the sponsor’s analysis.

What does a pass percentage describe?

For a binary endpoint such as passing or not passing a challenge, a group percentage describes the share of analyzed participants meeting the defined criterion. The primary outcome classified a participant as passing if no objective Grade 1 reaction occurred during the specified challenge. The registry reported 55.95% in the dupilumab-plus-AR101 group and 35.9% in the placebo-plus-AR101 group. A percentage is easy to interpret, but it does not show how close each participant came to the threshold or how much peanut protein an individual could tolerate.

What is a risk difference?

In general, a risk difference compares the event proportions between groups by subtracting one proportion from the other. It expresses the absolute separation between the groups on the proportion scale. The reported sponsor analysis expressed its result as a difference in percentage. The unadjusted recalculation is a separate comparison derived from the posted group summaries. Because the formal analysis and simple recalculation do not use the same method, small differences in their estimates and intervals can occur without indicating a contradiction.

Why use Cochran-Mantel-Haenszel?

In general, the Cochran-Mantel-Haenszel method is used to estimate or test a group difference while accounting for specified strata. The registry names this method for the primary outcome, but the stratification details are not reported in the registry record. It would therefore be inappropriate to guess which factors were included or to describe the estimate as adjusted for a particular participant characteristic. The reported result remains the sponsor’s formal analysis as recorded.

What does a p-value convey?

In general, a p-value describes how compatible the observed data are with a specified null hypothesis under the assumptions of the analysis. It is not a probability that the null hypothesis is true, nor a measure of the magnitude or importance of an effect. For the primary endpoint, the registry reported p = 0.042. The unadjusted recalculation reported p = 0.038. These values arise from their respective methods and should be interpreted alongside the estimated difference and its confidence interval, not in isolation.

Why are means and standard errors used for a continuous outcome?

The cumulative tolerated dose outcome was log transformed and reported as a least-squares mean with a standard error. In general, a mean summarizes the central location of a continuous measure, while a standard error describes the uncertainty in the estimated mean. The posted least-squares means at Visit 16 were 3.78 for placebo plus AR101 and 4.45 for dupilumab plus AR101. The reported ANCOVA least-squares mean difference was 0.67, with a 95% confidence interval from 0.031 to 1.305 and p = 0.040. The registry does not provide enough detail to reconstruct the full ANCOVA model.

Why can over-dispersion matter?

In general, over-dispersion occurs when observed variability exceeds what a statistical model assumes. When a model underestimates variability, its standard errors may be too small and its confidence intervals too narrow, making apparent precision misleading. Conversely, an appropriate model for variability can help calibrate uncertainty. The registry record does not report an over-dispersion assessment for the primary binary outcome, so no claim about whether it was assessed or present is justified.

For the time to reach 300 mg/Day AR101, the registry reports group means and standard deviations, and the simple comparison gives a mean difference of 2.9 days with an interval from -10.97 to 16.77 and p = 0.682. Although the endpoint title refers to time from randomization to first reaching the dose, the posted summary is expressed as means rather than a time-to-event analysis. The registry record does not report a sponsor analysis for this outcome. No survival-model interpretation should be inferred from the endpoint title alone.

11. Confidence Intervals and Precision

A confidence interval gives a range of effect values compatible with the data and the analysis procedure, under its assumptions. In general, a narrower interval indicates greater statistical precision, while a wider interval indicates more uncertainty about the effect’s magnitude. An interval is not a guarantee that the true value lies inside it, and it does not describe the range of individual participant responses.

For the primary endpoint, the sponsor-reported difference in percentage was 20.23, with a 95% confidence interval from 1.266 to 39.189. The interval does not include no difference, but it spans a range of effect magnitudes. The separate arm-specific intervals were 44.7 to 66.78 for dupilumab plus AR101 and 21.2 to 52.82 for placebo plus AR101. These intervals describe uncertainty around each group’s percentage, while the interval for the difference addresses uncertainty about the comparison itself.

The unadjusted recalculation also produced an interval that excludes no difference, but it is methodologically distinct from the sponsor’s reported analysis. Its endpoints are not repeated numerically because they are reported with more than three decimal places. The same caution applies to other recalculated intervals with more than three decimal places: the rounded values should not be altered simply to fit a display limit.

For the secondary endpoint of reaching the 300 mg/Day dose, the sponsor-reported difference in percentage was 11.91, with a 95% confidence interval from -3.612 to 27.440. This interval includes no difference and allows both a negative and positive difference under the analysis. For the reported mean time to reaching that dose, the recalculated interval from -10.97 to 16.77 also includes no difference. These intervals indicate less precision about the direction and size of those comparisons than a narrow interval wholly on one side of no difference would indicate.

Confidence intervals should be read with the endpoint, analysis population, and method in view. They do not resolve questions about missing data, multiplicity, or generalizability.

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 planning estimates are illustrations based on observed effects, not the trial’s original design calculations. The registry record does not report the original sample-size justification. The listed assumptions for the illustrations are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set at the stated fraction of the observed effect. The figures for these endpoint comparisons are participants per arm, not total events.

The 80% power column gives the number of participants per arm that the planning calculation estimates would be needed to have an 80% chance of detecting the specified effect under those assumptions, if that effect and model assumptions held. The 90% power column gives the corresponding planning number for a 90% chance. Higher target power generally requires more participants when the other assumptions stay the same. These are hypothetical planning quantities, not evidence that the completed trial had a particular probability of success.

Rows planning for 100%, 75%, and 50% of the observed effect show how the illustrative sample size changes when the target effect is smaller. Smaller effects need more participants to distinguish them from random variation under the same significance and power assumptions. This is particularly important when an observed effect from a completed trial is used as a planning input: the observed estimate is uncertain and may not be the effect that a future study will encounter.

For the time-to-dose endpoint, the sample-size convention would be total events in a time-to-event calculation, but the posted planning entries for the outcomes discussed in this comparison are expressed as participants per arm. The sample-size figures are not observed power.

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 = 0.359; treatment proportion p₁ = 0.560; average p̄ = 0.459.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7048 = 1.3813.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6903 = 0.5810.
4. n = (1.3813 + 0.5810)² / (0.2005)² = 95.7, rounded up to 96 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 <- 0.358974358974359                          # control proportion
p1 <- 0.55952380952381                          # 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(3682770)
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 = 96 (80% power), 128 (90% power)
 75% of observed effect: n per arm = 170 (80% power), 227 (90% power)
 50% of observed effect: n per arm = 377 (80% power), 504 (90% power)
power.prop.test: 95.7 
Simulated power at n = 96 per arm: 0.800 (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. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary comparison using a Cochran-Mantel-Haenszel analysis. The reported difference in percentage was 20.23, with a 95% confidence interval from 1.266 to 39.189 and p = 0.042. This is the formal analysis result recorded for the primary endpoint.

The simple recalculation uses the posted group summaries and is unadjusted. It gives an unadjusted p-value of 0.038 and is useful as a transparent check on the direction and broad pattern of the comparison. It is not the same calculation as the reported analysis, and the unadjusted estimate and interval should not be substituted for the sponsor’s result. The two approaches point in the same direction, but their numerical results are not identical.

The registry does not mark a discrepancy between the recalculation and the sponsor analysis. Even so, readers should distinguish the methods and treat the reported sponsor analysis as the trial’s formal result, while recognizing that the supplementary calculation is based only on summary statistics. The registry record does not provide enough detail to reproduce the full sponsor analysis independently.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study tests several outcomes, comparisons, time points, or subgroups. In general, the more tests conducted, the greater the chance that at least one result will appear statistically notable by chance if no adjustment or testing hierarchy is used. This trial included multiple secondary outcomes, including challenge measures, dose progression, maintenance outcomes, and immune measures. The registry record does not report whether multiplicity was addressed, whether a hierarchy of hypotheses was specified, or which secondary tests, if any, were confirmatory.

The registry record also does not report a full statistical analysis plan, interim analyses, or the trial’s original sample-size justification. Without those details, it is not possible to establish from the posted results whether each analysis followed a prespecified plan, or how planned control of type I error was intended to work. This limitation is especially relevant when interpreting secondary p-values independently of the primary endpoint.

The primary endpoint population is defined as a modified full analysis set: participants in the full analysis set who underwent biweekly in-clinic up-dosing and the Visit 16 challenge. This is narrower than simply all enrolled participants. The endpoint counts reported in the two arms are 39 and 84. The registry record does not report how participants who did not undergo the challenge were handled beyond the population definition, nor does it describe imputation or other missing-data procedures for the primary endpoint.

Missing-data handling can affect estimates if participants with unavailable outcomes differ from those with observed outcomes. In general, excluding participants without an endpoint may produce a different result from including them under a justified missing-data model. The record does not report enough information to assess the extent, reasons, or statistical handling of missing data for the primary analysis. The registry’s stated population criteria should therefore be considered when interpreting the result, without assuming an unreported imputation approach.

16. 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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: appendicitis (2.4%).

The safety results are reported for several treatment periods and groupings, so counts should be read within their stated period rather than combined as if they came from one common analysis population. During the pre-AR101 dosing period, no serious adverse events were reported in either group; other adverse events were reported in 12 of 50 participants receiving placebo-matched dupilumab and 23 of 98 receiving dupilumab. During AR101 up-dosing, no serious adverse events were reported in either group; other adverse events were reported in 34 of 49 participants receiving placebo plus AR101 and 47 of 96 receiving dupilumab plus AR101.

During maintenance, no serious adverse events were reported among 40 participants continuing placebo-matched dupilumab plus AR101, while 1 serious adverse event was reported among 42 continuing dupilumab plus AR101. The group described as dupilumab plus AR101 followed by placebo-matched dupilumab plus AR101 had no serious adverse events among 43 participants. No deaths were reported in any listed group. Appendicitis was the most common serious adverse event term listed, at 2.4%.

These are descriptive counts across periods and groups, not adjusted comparisons of safety risk. The registry record does not provide a statistical comparison of adverse events. Counts alone do not establish whether a difference between groups is meaningful, and the changing treatment periods and group definitions limit direct comparison.

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

The primary result describes the proportion of participants in the defined modified full analysis set who passed a specific post-up-dosing challenge. The observed percentage was higher in the dupilumab-plus-AR101 group than in the placebo-plus-AR101 group, and the registry’s formal analysis reported a difference in percentage with a confidence interval that did not include no difference. This is evidence about the stated endpoint and assessment, within the analyzed participants.

It does not establish how an individual participant would respond, whether every participant would tolerate peanut exposure, or whether the same result would occur in populations not represented by this trial. A group percentage cannot predict an individual outcome. Nor does a successful challenge at Visit 16, by itself, answer whether desensitization was maintained at Visit 22 or under conditions beyond the trial’s challenge protocol.

The result is not a complete account of benefit and harm. The trial also assessed safety, dose progression, cumulative tolerated dose, maintenance, and immune measures, but these outcomes have different definitions and available results. The registry’s adverse-event counts are descriptive and should not be interpreted as a formal comparative safety analysis. Numerical results for some listed secondary outcomes are not reported in the registry record.

Statistical significance is not the same as clinical importance. The confidence interval gives a range of values compatible with the formal analysis, but the registry record does not provide a threshold for what difference would be clinically important. The result should therefore be understood as a comparative statistical finding for the primary challenge outcome, not as a broader claim about all treatment effects or future outcomes.

18. Why This Trial Matters Statistically

This trial illustrates why endpoint definitions and analysis populations matter in clinical research. The primary outcome was not simply a general measure of peanut tolerance: it was passing a specified challenge with 2044 mg cumulative peanut protein at Visit 16, under a rule based on objective Grade 1 reactions. The analysis population further required participants to undergo the specified up-dosing and challenge procedures. Those details define precisely what the reported percentage represents.

It also demonstrates the value of separating a formal sponsor analysis from a simple recalculation using summary data. The sponsor’s reported method and the unadjusted check point in the same direction, yet they are distinct analyses. Readers can use a transparent recalculation as context while retaining the reported analysis as the formal trial result and recognizing that a p-value alone does not describe precision or practical importance.

The secondary outcomes show how one trial can ask connected but non-identical questions. Passing a challenge, reaching a target dose, time to that dose, cumulative tolerated dose, later maintenance, and biomarkers each capture a different dimension. Their results should not be pooled conceptually into a single conclusion, particularly when multiplicity handling and the full analysis plan are not reported.

Finally, the record highlights the limits of registry summaries. It reports group results and selected methods, but does not report the original sample-size justification, missing-data procedures, interim-analysis plans, or multiplicity strategy. Statistical interpretation depends not only on estimates and p-values, but also on knowing how the analysis was planned and which participants contributed to each outcome.

19. 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 primary analysis population is restricted to participants who underwent biweekly in-clinic up-dosing and the Visit 16 challenge. The endpoint result therefore does not automatically describe all 148 enrolled participants. The registry record does not report the number or outcomes of participants excluded from this endpoint population beyond the group analysis counts, or the reasons for any unavailable primary outcomes.

The formal primary analysis is identified as Cochran-Mantel-Haenszel, but the registry record does not report the strata or enough model detail to reproduce the analysis. The simple unadjusted recalculation is based on summary statistics and cannot account for participant-level information or any adjustments that may be included in the sponsor analysis. It should be read as supplementary rather than as an independent replacement.

The record does not report the original sample-size justification, missing-data methods, multiplicity plan, interim analyses, or a complete statistical analysis plan. These omissions limit assessment of whether the study was sized for the primary question, how incomplete outcomes were handled, and how the family of primary and secondary tests was controlled. Planning illustrations derived from observed effects do not fill those gaps.

Some secondary outcomes have numerical results and sponsor analyses, while other listed measures do not have numerical results reported in the registry record. The available secondary evidence is therefore incomplete for judging maintenance and biomarker questions. Safety information is presented as counts for different treatment periods and group definitions, without a reported statistical comparison. These reporting features constrain how broadly the trial’s results can be interpreted.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study in Pediatric Subjects With Peanut Allergy to Evaluate Efficacy and Safety of Dupilumab as Adjunct to AR101 (Peanut Oral Immunotherapy) — NCT03682770.
• Registry record last updated 2024-02-07; status last verified 2024-01.
• Results first posted 2024-02-07.
• 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.

23. Record Summary

NCT03682770 is a completed phase 2 randomized, double-blind, placebo-controlled, parallel-group study of dupilumab as an adjunct to AR101 in pediatric participants with peanut allergy. The registry lists enrollment of 148 and quadruple masking. The primary endpoint was passing a post-up-dosing challenge with 2044 mg cumulative peanut protein at Visit 16.

Among the primary analysis groups, the reported pass percentages were 55.95% with dupilumab plus AR101 and 35.9% with placebo plus AR101. The sponsor’s Cochran-Mantel-Haenszel analysis reported a difference in percentage of 20.23, with a 95% confidence interval from 1.266 to 39.189 and p = 0.042. Interpretation is bounded by the endpoint population, the challenge definition, and the registry’s unreported details on missing data, multiplicity, and the original design assumptions.