A Phase 4, Randomized, Double-blind, Placebo-controlled, Multicenter, Parallel-group Study of the Effect of Dupilumab on Sleep Disturbance in Patients With Uncontrolled Persistent Asthma: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Phase 4, Randomized, Double-blind, Placebo-controlled, Multicenter, Parallel-group Study of the Effect of Dupilumab on Sleep Disturbance in Patients With Uncontrolled Persistent Asthma (NCT04502862), a randomized phase 4 study. The primary outcome is Change From Baseline to Week 12 in Sleep Disturbance Score Using the Asthma Sleep Disturbance Questionnaire (ASDQ).

2. Clinical Question

The clinical question is specifically about reported sleep disturbance attributed to asthma, rather than sleep in general. The registry also identifies secondary questions concerning other participant-reported sleep outcomes, objective sleep assessment, asthma symptoms, lung function, and safety. The listed secondary endpoints include sleep diary measures, a PROMIS sleep-related impairment scale, actigraphy-based wake after sleep onset, and asthma symptom diaries.

3. Trial Design

This was a phase 4, randomized, placebo-controlled, parallel-group study of dupilumab in participants with uncontrolled persistent asthma. The registry lists Sanofi as the sponsor, an enrollment of 202, and a completed status. The study started on 2020-08-10, and primary completion was recorded as 2023-10-03. These are registry dates, not dates inferred from the results.

Participants were assigned to dupilumab or matching placebo. The dupilumab arm received a 400 mg loading dose on Day 1, delivered as 2 injections × 200 mg, followed by 200 mg every 2 weeks for 12 weeks. The placebo arm received 2 matching injections on Day 1, followed by 1 placebo injection every 2 weeks for 12 weeks. The registry identifies the allocation as randomized, the model as parallel, and the masking as quadruple; the study title uses the description double-blind.

The primary endpoint was analyzed with a mixed effect model for repeated measures (MMRM), and the sponsor’s posted analysis is described as a least-square mean difference. For the primary endpoint, the registry reports 94 participants in the dupilumab group and 93 in the placebo group in the analysis. These endpoint-specific counts need not match overall enrollment because the primary analysis population was defined separately. The full eligibility criteria, randomization procedure, allocation concealment details, and the original sample-size justification are not reported in the registry record.

The planned observation period for treatment was 12 weeks. Sleep disturbance was recorded in an electronic diary once daily upon awakening. The registry also lists secondary outcomes that include sleep diary measures, PROMIS sleep-related impairment, actigraphy, and asthma symptom diaries. The complete schedule of assessments and detailed analysis plan 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.

Before assignment: A total of 202 participants were randomized in a ratio of 1:1 to receive dupilumab or matching placebo every 2 weeks (Q2W) for 12 weeks.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The ITT for primary endpoint (ITTp) analysis set consisted of all ITT participants excluding those who used the original version of sleep disturbance questionnaire at baseline and/or post-baseline included in the mixed effect model for repeated measures (MMRM) model. Only those participants with data collected at baseline and at least one post-baseline until Week 12 are reported.

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: The Intent-to-treat (ITT) analysis set consisted of all randomized participants.

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline to Week 12 in Sleep Disturbance Score Using the Asthma Sleep Disturbance Questionnaire (ASDQ), measured over Baseline (Day -6 to Day 1) up to Week 12.

The primary endpoint was change from baseline to Week 12 in the Asthma Sleep Disturbance Questionnaire (ASDQ) score. It is a participant-reported measure designed to capture how asthma affects sleep. Participants recorded the degree of sleep disturbance attributed to asthma in an electronic diary once each morning. The registry defines baseline as the average of the recorded data from Day -6 to Day 1, with follow-up through Week 12.

The score ranges from 0 to 4. A score of 0 represents sleeping through the night without asthma symptoms, while higher scores reflect greater disturbance, up to being awake most of the night because of asthma. Thus, a negative change means the score was lower at follow-up than at baseline; it does not by itself establish that one randomized group changed more than the other. The treatment comparison is the between-group difference in change, not either arm’s change considered alone.

This endpoint is relevant to the study’s stated primary objective because it measures the participant’s own experience of asthma-related sleep disturbance. As a participant-reported outcome, it directly reflects reported symptoms rather than an objective physiological measure. It should be interpreted as a specific questionnaire score, not as a complete measure of sleep quality or overall asthma control. The registry record does not report a threshold for a clinically important difference in the ASDQ score.

7. Results Posted in the Registry

• Dupilumab 200 mg Q2W: mean -0.88 versus -0.81 on control; difference -0.07 (95% CI -0.28 to 0.14), standardized effect d = -0.09; z-test p = 0.520.

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 to Week 12 on the Number of Nocturnal Awakenings (Sleep Diary)

• 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:
  • Dupilumab 200 mg Q2W: mean -0.71 versus -0.71 on control; difference 0.00 (95% CI -0.22 to 0.22), standardized effect d = 0.00; z-test p = 1.000.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Dupilumab 200 mg Q2W and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline to Week 12 in Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep-Related Impairment 8a Scale

• 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:
  • Dupilumab 200 mg Q2W: mean -7.20 versus -6.51 on control; difference -0.69 (95% CI -2.42 to 1.04), standardized effect d = -0.11; z-test p = 0.435.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Dupilumab 200 mg Q2W and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline to Week 12 in Sleep Quality (Sleep Diary)

• 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:
  • Dupilumab 200 mg Q2W: mean 1.14 versus 0.97 on control; difference 0.17 (95% CI -0.25 to 0.59), standardized effect d = 0.11; z-test p = 0.428.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Dupilumab 200 mg Q2W and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists secondary questions spanning participant-reported sleep, sleep diary outcomes, actigraphy-based wake after sleep onset, and asthma symptom diaries. The posted secondary results include continuous outcome comparisons, with arm estimates and uncertainty that vary by measure. Across the outcomes with reported comparisons, the overall pattern does not establish a clearly separated treatment effect from placebo: the reported estimates are generally accompanied by uncertainty compatible with little or no between-group difference. These measures provide context but do not overturn the primary result.

Secondary endpoints can help assess whether a result is consistent across related dimensions, such as subjective sleep experience and objective sleep assessment. They are not interchangeable with the ASDQ primary endpoint, because each measure captures a different construct and may have different measurement properties. Nor do several secondary outcomes automatically constitute independent confirmations: outcomes can be related, and the registry record does not provide a complete multiplicity strategy or a prespecified hierarchy for interpreting them.

When many outcomes are tested, some may appear statistically unusual by chance even if there is no underlying effect on those measures. Unless testing is controlled by a prespecified adjustment or hierarchy, unadjusted secondary results carry less weight than the primary endpoint. The registry record does not report a multiplicity adjustment. Accordingly, secondary findings are best read as exploratory or supportive evidence, rather than as stand-alone proof. The registry record also does not report all secondary endpoint results in this discussion available for this analysis, so conclusions should remain limited to the posted outcomes.

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

• Change From Baseline to Week 12 on the Number of Nocturnal Awakenings (Sleep Diary)
• Change From Baseline to Week 12 in Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep-Related Impairment 8a Scale
• Change From Baseline to Week 12 in Sleep Quality (Sleep Diary)
• Change From Baseline to Week 12 in Restorative Sleep (Sleep Diary)
• Change From Baseline to Week 12 in Wake After Sleep Onset (WASO) (Sleep Diary)
• Change From Baseline to Week 12 in WASO Based on Actigraphy Data
• Change From Baseline to Week 12 in Asthma Daytime Symptom Diary (ADSD)
• Change From Baseline to Week 12 in Asthma Nighttime Symptom Diary (ANSD)

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is continuous: each participant’s outcome is represented by a score, and the reported group summaries are least-square means. A least-square mean is a model-based estimate of the group mean under the fitted analysis, rather than simply a raw arithmetic average. The sponsor’s posted comparison is the difference between those estimated changes. Its sign depends on the order of subtraction used for the groups; the reported value is negative, with the dupilumab group’s estimated change more negative than the placebo group’s.

What does the repeated-measures model do?

The primary analysis is identified as a mixed effect model for repeated measures, commonly abbreviated MMRM. In general, repeated-measures models use observations collected at multiple time points and account for the fact that measurements from the same participant are related. They can estimate group differences over time while using the available repeated observations according to the model. The registry record names MMRM but does not report the full model specification, covariance structure, adjustment variables, or handling assumptions for missing observations. Those details should not be inferred from the method label alone.

The registry describes the main parameter as a least-square mean difference. The analysis population is described as the ITT for primary endpoint set, with an exclusion for participants who used the original version of the sleep disturbance questionnaire at baseline and/or after baseline included in the MMRM. The available description is truncated after stating that only participants with particular data were included, so the full population rule is not reported in the registry record. The endpoint counts are 94 for dupilumab and 93 for placebo.

How should the p-value be read?

A p-value describes how compatible the observed result is with a specified null model, under the assumptions of the analysis. It is not the probability that the null hypothesis is true, nor a measure of the size or clinical importance of the difference. The sponsor-reported p-value for the primary comparison is 0.512. In combination with the confidence interval, it indicates that the posted result does not distinguish the estimated difference from zero with conventional statistical significance criteria. It does not show that the treatment groups are exactly equivalent.

The reported 95% confidence interval is an uncertainty range calculated using the sponsor’s analysis. In general, a confidence interval conveys the precision of an estimate: narrower intervals indicate greater precision, while wider intervals allow a broader range of underlying differences. For this comparison, the interval extends from -0.28 to 0.14. Because it includes zero, the direction of the underlying between-group difference is uncertain in the posted analysis.

What is the role of recalculation?

A recalculated comparison is a simple, unadjusted calculation based on the posted summary statistics. It is useful as a transparent check on the broad scale and direction of the result, but it does not reproduce the sponsor’s repeated-measures model. The recalculated primary mean difference is -0.07, and the accompanying unadjusted p-value is 0.52. The sponsor’s reported model estimate is also -0.07. Since the record reports no discrepancy between the recalculation and the posted analysis, the broad conclusion is similar. The sponsor’s model remains the primary source for the trial’s reported inferential analysis.

Standard errors describe the estimated uncertainty in a group-level estimate. They are not the same as the spread of individual participant scores. The registry labels the arm-level dispersion as standard error. A comparison’s uncertainty also depends on the analysis and the relationship between repeated observations; it should not be reconstructed by treating the standard errors as individual-level standard deviations without qualification.

General statistical explanation: a model can account for the structure of repeated observations, but it cannot remove uncertainty arising from limited information or unsupported modeling assumptions. For this reason, interpretation combines the estimated difference, its confidence interval, the analysis population, and the details of the model that are actually reported. The registry record does not report enough detail to independently evaluate every MMRM assumption.

11. Confidence Intervals and Precision

The sponsor-reported primary estimate is a difference of -0.07 points on the ASDQ score, with a 95% confidence interval from -0.28 to 0.14. This interval communicates the precision of the estimated group contrast under the reported model. It includes zero, so the data are compatible with no between-group difference. It also includes values on both sides of zero, meaning that the direction of the underlying difference is not pinned down by this interval.

The point estimate should not be read as an exact value for the treatment effect. It is the center of an uncertainty range, and the interval includes differences that are more negative as well as differences that are positive. Whether any value in that range would be clinically important cannot be determined from the registry record, because a clinically important difference threshold for the ASDQ is not reported.

General statistical explanation: confidence intervals represent uncertainty around an estimate, conditional on the analysis and its assumptions. They do not assign a probability to each possible true value, and a 95% interval is not a guarantee that the true effect lies in the interval. Here, the key practical feature is that the range spans zero and is broad enough to leave uncertainty about the direction and size of the group difference.

The sponsor reports a model-based interval rounded to two decimal places. The unadjusted recalculation is a separate summary-statistic calculation and should not be treated as a replacement for the MMRM interval. The registry record does not report additional analyses of sensitivity to model assumptions or missing observations that could further characterize precision.

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 based on the observed effect, not the trial’s original design justification. The registry record does not report the original design assumptions or the sample-size justification. These illustrations use a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The assumed effect to detect is a stated fraction of the observed effect. For these continuous outcomes, the figures are participants per arm, not total events.

The 80% power column gives the number of participants per arm in a hypothetical future study that would have an 80% chance of detecting the specified effect under the stated assumptions, if that effect and the other assumptions were correct. The 90% power column uses a higher target probability of detection and therefore requires more participants per arm for the same assumed effect. Power is a design property calculated before a study, conditional on assumptions about the effect, variability, analysis, and significance threshold.

The rows describe planning for 100%, 75%, and 50% of the observed effect. When the assumed effect is smaller, it is harder to distinguish it from random variation, so the planning illustration requires more participants per arm. These figures are illustrative rather than a recommendation for a particular future study: the observed estimate may not be the true effect, and the assumptions may not match a future design. This is not observed power; it does not measure the probability that the completed trial detected an effect after its results were known.

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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.070; pooled standard deviation σ = 0.745.
2. n = 2 × (1.96 + 0.842)² × 0.745² / -0.070² = 1,776.0, rounded up to 1,777 participants per arm for 80% power.

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

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -0.07                      # observed difference in means
sigma <- 0.744565325760154                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(4502862)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 1,777 (80% power), 2,378 (90% power)
 75% of observed effect: n per arm = 3,158 (80% power), 4,227 (90% power)
 50% of observed effect: n per arm = 7,105 (80% power), 9,511 (90% power)
power.t.test: 1777 
Simulated power at n = 1,777 per arm: 0.798 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The sponsor’s posted primary analysis uses MMRM and reports a least-square mean difference of -0.07, with a 95% confidence interval from -0.28 to 0.14 and p = 0.512. The simple unadjusted recalculation from the posted summary statistics also gives a mean difference of -0.07 and an unadjusted p-value of 0.52. The record indicates no discrepancy between the recalculation and the reported result.

The close estimates support describing the result as a small estimated between-group difference with uncertainty spanning zero. However, the recalculation is not a reproduction of the sponsor’s repeated-measures model: it is an unadjusted calculation from summary values. The sponsor’s own analysis takes precedence for interpretation of the trial’s reported inferential result, because it is the analysis identified in the registry record. Its confidence interval and p-value should therefore be used when describing the primary result.

The small differences in displayed p-values reflect that the values come from distinct analyses and are reported at different precision. They do not change the overall interpretation. Neither analysis establishes equivalence, and the registry record does not report an equivalence margin or a clinically important difference threshold.

15. Multiplicity, Missing Data and Analysis Populations

The registry record lists one primary sleep disturbance endpoint and multiple secondary outcomes involving sleep, asthma symptoms, lung function, and safety. Testing multiple outcomes can increase the chance that at least one result appears statistically significant by chance. General statistical practice addresses this issue through methods such as a prespecified testing hierarchy or adjustment of significance thresholds, but the registry record does not report whether either approach was used. No multiplicity-adjusted secondary conclusions can therefore be inferred from the posted information.

The primary analysis population is described as the ITT for primary endpoint set, with an exclusion for participants who used the original ASDQ version at baseline and/or after baseline in the MMRM. The available population description is incomplete. The registry record does not report the full definition of the analysis set, the number excluded for each reason, or a detailed account of missing primary endpoint observations.

For repeated measurements, missing observations can affect both the amount of information and the assumptions supporting the model. General statistical explanation: an MMRM can use available repeated data, but interpretation depends on the model specification and assumptions about the relationship between observed and unobserved outcomes. The registry record names the MMRM but does not report its covariance structure, missing-data assumptions, imputation procedures, or sensitivity analyses. It is therefore not possible to assess from this record alone how robust the result is to alternative missing-data assumptions.

The record does not report interim analyses, stopping rules, a detailed prespecified statistical analysis plan, or the original sample-size justification. These are unknowns, not evidence that such procedures were absent. Conclusions should be based on the reported randomized comparison and should avoid attributing unreported analysis choices to the investigators.

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: fall (1.0%), tibia fracture (1.0%), depression suicidal (1.0%), suicide attempt (1.0%), asthma (1.0%).

The registry reports serious adverse events in 3 participants at risk in the dupilumab group and 3 participants at risk in the placebo group. The listed denominators are 100 and 101, respectively. It reports no deaths in either group. For other, non-serious adverse events, the record lists 13 affected participants in the dupilumab group and 18 in the placebo group, among the same respective denominators.

These are participant counts as recorded in the registry, not a complete description of event severity, timing, duration, or attribution. The record lists serious event terms including Fall, Tibia Fracture, Depression Suicidal, Suicide Attempt, Asthma, and Pancreatitis Acute, each shown at 1.0%. The registry record does not provide enough detail to assess individual clinical circumstances or determine whether an event was caused by treatment.

Safety counts should be read descriptively. The displayed figures do not establish that the risks are the same or different between groups, particularly without a detailed statistical safety analysis and event-level context. The trial’s duration and population also limit what can be inferred about uncommon events or outcomes beyond the reported follow-up.

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

The posted primary result is an estimate of the difference between dupilumab and placebo in change in asthma-related sleep disturbance score through Week 12. The sponsor-reported estimate is -0.07, and its 95% confidence interval extends from -0.28 to 0.14. The interval includes zero and the reported p-value is 0.512. The result therefore leaves uncertainty about the direction and size of the underlying group difference.

This does not mean that the groups were proven identical. A non-significant result is not an equivalence finding: equivalence requires a defined margin and an analysis designed to evaluate whether the whole uncertainty interval lies within that margin. The registry record does not report an equivalence margin or a clinically important difference threshold for the ASDQ. The result also does not show that no participant experienced a change; both arms had average reductions in score, while the primary randomized comparison concerns the difference between those changes.

The outcome is a specific participant-reported score about asthma-related sleep disturbance. It cannot, by itself, establish an effect on every dimension of sleep, objective sleep physiology, daytime functioning, asthma control, or long-term outcomes. Secondary endpoints can add context, but the registry record does not report a multiplicity adjustment, and several measures are not substitutes for the primary endpoint.

The trial record describes a particular population, intervention schedule, comparator, and follow-up. Its findings should not be extended automatically to populations or treatment durations not represented in the record. Statistical interpretation is also bounded by incomplete reporting of the full model specification, missing-data approach, and original design assumptions. The result is best understood as an imprecise estimate of a small between-group difference in the registered endpoint, rather than as a definitive statement about all possible benefits or harms.

18. Why This Trial Matters Statistically

This trial illustrates why the contrast between within-group change and between-group difference matters. Both arms had lower mean ASDQ scores at Week 12 than at baseline, but the randomized question is whether their changes differed. The sponsor-reported difference is -0.07, much closer to zero than either arm’s change from baseline. Reading the arm changes alone could therefore give a misleading impression of the comparative result.

It also shows why a p-value should be read alongside an effect estimate and confidence interval. The p-value of 0.512 does not establish no effect, while the confidence interval makes visible the range of differences compatible with the analysis. Without a reported clinically important difference threshold, statistical uncertainty cannot be translated directly into a judgment about clinical importance.

The registry record identifies a repeated-measures model for the primary analysis, while a simple recalculation from summary statistics yields a similar point estimate. This distinction is useful: a transparent recalculation can check the broad result, but it does not replace the model used for the sponsor’s reported inference. The model details and missing-data assumptions remain important to a complete evaluation.

Finally, the range of secondary sleep and asthma outcomes raises a multiplicity issue. A collection of endpoints can provide useful breadth, but isolated results are harder to interpret without a reported testing hierarchy or adjustment. Together, these features make the trial a practical example of interpreting estimates, uncertainty, analysis populations, and multiple outcomes rather than focusing on a single threshold or within-arm change.

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.

The primary result is based on the ASDQ, a participant-reported score. It captures asthma-related sleep disturbance as defined by the questionnaire, but does not by itself measure every aspect of sleep. The registry also lists objective assessment and other reported sleep measures, but the posted information does not provide a complete account of how those measures align with the primary endpoint.

The primary analysis population description is incomplete, and its endpoint counts are lower than the overall enrollment. The registry record describes an exclusion related to use of the original questionnaire version in the MMRM, but does not provide the full population definition or a complete accounting of exclusions and missing observations. The MMRM is named, yet its covariance structure, adjustment variables, and missing-data assumptions are not reported. These omissions limit independent assessment of the model.

The record does not report the original sample-size justification, a clinically important difference threshold for the ASDQ, or an equivalence margin. It also does not report whether multiplicity was controlled across the secondary endpoints, nor does it provide a complete prespecified testing hierarchy. These gaps make it difficult to judge the intended inferential weight of secondary findings or to determine whether the observed precision matched the original design goals.

Follow-up for the intervention was 12 weeks. The posted results therefore do not characterize longer-term outcomes. The safety data are counts and selected serious event terms; they do not provide detailed event narratives, timing, or treatment attribution. These limitations define the scope of what can be concluded from the registry record and should not be filled by assumptions.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Phase 4, Randomized, Double-blind, Placebo-controlled, Multicenter, Parallel-group Study of the Effect of Dupilumab on Sleep Disturbance in Patients With Uncontrolled Persistent Asthma — NCT04502862.
• Registry record last updated 2024-12-06; status last verified 2024-12.
• Results first posted 2024-11-26.
• 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

NCT04502862 is a completed phase 4 randomized, placebo-controlled, parallel-group study of dupilumab in participants with uncontrolled persistent asthma. The registry reports enrollment of 202 and a 12-week treatment regimen. The primary endpoint was change from baseline to Week 12 in asthma-related sleep disturbance measured by the ASDQ.

The sponsor-reported MMRM comparison was -0.07, with a 95% confidence interval from -0.28 to 0.14 and p = 0.512. The interval includes zero and leaves uncertainty about the direction and size of the group difference. The registry also reports secondary sleep and asthma outcomes and adverse event counts, but does not report a multiplicity strategy, the complete model specification, or the original sample-size justification.