A Study of Nalbuphine (Extended Release) ER in Idiopathic Pulmonary Fibrosis (IPF) for Treatment of Cough: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study of Nalbuphine (Extended Release) ER in Idiopathic Pulmonary Fibrosis (IPF) for Treatment of Cough (NCT04030026), a randomized phase 2 study. The primary outcome is Number of Participants Who Experienced at Least One Treatment Emergent Adverse Events (TEAEs).

2. Clinical Question

3. Trial Design

The registry describes a randomized Phase 2, placebo-controlled, two-treatment, two-period crossover study in idiopathic pulmonary fibrosis. Its official title calls the study double-blind, while the registry masking field lists quadruple masking. The record does not explain the difference between those descriptions. The study is marked completed, with enrollment of 42, a start date of 2019-10-29, and primary completion on 2022-05-27.

Participants were assigned to NAL ER followed by placebo or placebo followed by NAL ER. The NAL ER sequence description includes escalation from 27 mg once daily to 54 mg twice daily over a 5-day period, maintenance at 54 mg twice daily for 4 days, escalation to 108 mg twice daily for 1 week, and then 162 mg twice daily for 6 days. One sequence description then identifies 3 weeks of matching placebo. The registry's arm descriptions are truncated, so the complete schedules cannot be established from the record.

A crossover design exposes participants to both treatments in different periods, with treatment order randomized. This can allow within-participant comparisons, but interpretation depends on the design and analysis accounting appropriately for period and sequence. The registry record does not report details of a washout, carryover assessment, or the statistical model used for the primary endpoint. The posted primary safety counts are summarized by actual treatment, with different denominators for NAL ER and placebo; the denominators should not be added to infer a number of participants.

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 56 participants were screened from whom 42 participants were enrolled and randomized to receive treatment in this study.

Treatment Period 1 (22 Days)

Reasons for not completing this period:

Treatment Period 2 (22 Days)

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: SAS included all randomized participants who had received at least 1 dose of the IP. 3 participants did not receive at least one dose of NAL ER but received placebo and 1 participant did not receive at least one dose of placebo but received NAL ER treatment. Data was summarized under actual treatment received (NAL ER or placebo) independently whether this was received in Treatment Period 1 or 2 (participants who received both treatments are counted in both NAL ER and placebo columns).

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: Randomized analysis set included all participants who were randomized.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants Who Experienced at Least One Treatment Emergent Adverse Events (TEAEs), measured over Up to Day 72.

The primary posted endpoint is the number of participants with at least one treatment-emergent adverse event (TEAE), with follow-up described as up to Day 72. An adverse event is defined in the registry as an untoward medical occurrence after administration of a pharmaceutical product, whether or not it is considered related to that product. A TEAE is an adverse event occurring after the first dose of study drug. Serious and non-serious TEAEs are included.

Counting participants with at least one event gives a summary of how many people experienced an event during the stated period. It does not count the total number of events per participant, indicate event severity by itself, or establish that treatment caused an event. The registry uses the endpoint to assess safety and tolerability, which is important when evaluating an investigational treatment alongside symptom outcomes.

The registry summary also identifies mean daytime cough frequency at Day 22 as an efficacy question, but that is not the primary endpoint represented by the posted primary result. It appears as a secondary outcome. Keeping the safety count distinct from the cough measure helps avoid treating a symptom finding as the primary safety result or interpreting the adverse-event count as a measure of cough change.

7. Results Posted in the Registry

• NAL ER: 92.1% (35/38) versus 65.0% (26/40) on control; risk difference 27.1 percentage points (95% CI 10.0 to 44.2), risk ratio 1.42 (1.11–1.81); unadjusted two-proportion z-test p = 0.004.

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 Daytime Cough Frequency at Day 22

• 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:
  • NAL ER: mean -19.39 versus -6.26 on control; difference -13.12 (95% CI -21.29 to -4.96), standardized effect d = -0.82; z-test p = 0.002.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for NAL ER than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Mean Change From Baseline in the Patient Reported Outcomes Measurement Information System (PROMIS) Item Bank v1.0 Fatigue Short Form 7a Scale Total Score at Day 21

• 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:
  • NAL ER: mean 0.90 versus 0.00 on control; difference 0.90 (95% CI -1.02 to 2.82), standardized effect d = 0.26; z-test p = 0.357.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between NAL ER and the control. The interval gives the range of effects that remain compatible with the data.

Clinical Global Impression of Change (CGI-C) Over Time Measured at Day 21

• 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:
  • NAL ER: mean 3.00 versus 3.90 on control; difference -0.90 (95% CI -1.52 to -0.28), standardized effect d = -0.74; z-test p = 0.005.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for NAL ER than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry record lists secondary outcomes covering cough frequency, respiratory symptoms, breathlessness, cough severity, exacerbation-related symptoms, fatigue, and global change. Detailed numerical results in the registry entries are available for daytime cough frequency, PROMIS fatigue, and Clinical Global Impression of Change. The remaining listed outcomes do not have detailed estimates described in this record summary, so an overall conclusion across every secondary measure is not possible.

Among the detailed results, the cough-frequency comparison shows a larger average reduction under NAL ER, while the fatigue comparison is imprecise and compatible with no difference. The global-change comparison also has a confidence interval that does not include zero, but its scale is distinct from the cough measure. Taken together, these results are not a uniform pattern across all domains. The cough finding is relevant to the study's symptom objective, but it remains secondary to the posted primary safety endpoint and should not be treated as a replacement for it.

The secondary p-values are unadjusted. When multiple outcomes are examined, the chance of at least one apparently notable result can increase, so individual unadjusted findings carry less confirmatory weight than a prespecified analysis that accounts for multiplicity. The registry record does not report a multiplicity adjustment or identify which secondary outcomes were designated for confirmatory testing. The outcomes are also measured on different scales and at different time points, so their directions and magnitudes cannot be combined into a single overall effect without additional, unreported methods.

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

• Change From Baseline in Daytime Cough Frequency at Day 22
• Percent Change From Baseline in 24-Hour Cough Frequency at Day 22
• Percent Change From Baseline in Nighttime Cough Frequency at Day 22
• Mean Change From Baseline in the Evaluating Respiratory Symptoms (E-RS) Diary Cough Subscale at Days 9, 16, and 22
• Mean Change From Baseline in E-RS Breathlessness Score at Days 9, 16, and 22
• Mean Change From Baseline in the Cough Severity Numerical Rating Scale (NRS) at Days 8, 15, and 21
• Mean Change From Baseline in the 14-item EXAcerbation of Chronic Pulmonary Disease Tool (EXACT) v1.1 e-Diary Tool Total Score at Days 9, 16, and 22
• Mean Change From Baseline in the Patient Reported Outcomes Measurement Information System (PROMIS) Item Bank v1.0 Fatigue Short Form 7a Scale Total Score at Day 21

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference describe?

A risk difference compares the proportions of participants with an event in two treatment groups. It is an absolute contrast on the event-probability scale, rather than a relative measure. For the primary TEAE outcome, the posted risk difference is 0.271. Its positive direction corresponds to a higher observed event proportion under NAL ER than under placebo in this comparison. The confidence interval expresses uncertainty about the size of that contrast under the calculation used; it does not account for limitations that are not represented in the calculation, such as unreported analysis choices.

What does the continuous-outcome comparison describe?

For continuous outcomes, the posted mean difference compares the treatment-group mean changes or scores. In the daytime cough analysis, the outcome is change from baseline in coughs per hour. A negative change denotes a reduction from baseline, and a negative mean difference indicates a more negative group mean for NAL ER than for placebo. The PROMIS fatigue and Clinical Global Impression of Change outcomes are measured on different scales, so the meaning and favorable direction depend on each scale's definition. The registry record does not give enough information to interpret every scale's clinical thresholds.

What do p-values contribute?

An unadjusted p-value assesses how incompatible the observed comparison is with a specified no-difference model, under the assumptions of the test or calculation. It is not the probability that the null hypothesis is true, and it does not measure effect size or clinical importance. The posted p-values for the main secondary comparisons are labelled unadjusted. A p-value should be read alongside the effect estimate and confidence interval, as well as the design and analysis details.

The PROMIS fatigue result has a reported Student's T-test p-value of 0.360 and a separately recalculated unadjusted p-value of 0.357. The estimates are close, but they are not identical. The registry does not report the full analysis details for this outcome, so the two values should be understood as results from their respective reported and recalculated summaries rather than as interchangeable outputs of a fully documented model. The other detailed secondary outcomes have no reported analyses listed in the registry record.

Why does the crossover design matter?

In a crossover trial, treatment sequence and period can affect how observations should be compared. Measurements from the same participant may be related, unlike measurements from entirely separate groups. General statistical practice accounts for such dependence and may consider period and sequence. The registry record does not report the model or tests used to address these issues. The posted summary-statistic recalculations are unadjusted comparisons and should not be assumed to reproduce a crossover-specific analysis.

The primary endpoint analysis population is described as the safety analysis set, including randomized participants who received at least one dose of investigational product. The record states that 3 participants did not receive at least one dose of NAL ER but received placebo, and 1 participant did not receive at least one dose of placebo but received NAL ER. The primary results are summarized under actual treatment. The complete analysis-population description is truncated in the registry record, and the handling of missing outcome data is not reported there.

What do planning calculations mean?

The sample-size illustrations use an observed effect as a planning reference and show what would be needed to target specified power under stated assumptions. They are not a reconstruction of the original trial design. General planning calculations depend on assumptions about the effect to detect, variability or event rates, allocation, significance level, and the statistical approximation. The registry record does not report the assumptions used for the original study's design or its sample-size justification. In a crossover setting, a planning calculation based on a simple two-group comparison may also omit features of a crossover analysis unless those are explicitly incorporated.

For binary outcomes, the event indicator records whether a participant experienced at least one event. For continuous outcomes, the analysis uses a mean and a measure of spread, such as the posted standard deviation. These summaries compress the underlying participant-level data and cannot show the distribution of outcomes or reveal how missing observations were handled. The unadjusted calculations should therefore be read as descriptive comparisons of the posted summaries, not as substitutes for a fully specified trial analysis.

11. Confidence Intervals and Precision

A confidence interval gives a range of values compatible with the observed data under the calculation and assumptions used. It conveys uncertainty about an estimated contrast, not the probability that a particular value is true. Wider intervals indicate less precision; intervals that include no difference are compatible with both directions of effect under the corresponding comparison.

For the primary TEAE risk difference, the 95% confidence interval runs from 0.100 to 0.442. It is above zero, while still covering a range of possible absolute contrasts. This interval concerns the risk difference calculated from the posted group summaries; it does not resolve whether events were caused by treatment or whether the analysis appropriately accounted for crossover features.

The daytime cough mean-difference interval runs from -21.29 to -4.956 coughs per hour. It is entirely below zero, consistent with a more negative mean change under NAL ER in the posted comparison. Its width indicates that the precise magnitude is uncertain. For PROMIS fatigue, the interval from -1.016 to 2.816 includes zero, so the summary is compatible with no difference as well as effects in either direction. The Clinical Global Impression of Change interval, from -1.522 to -0.278, is below zero.

Precision is not the same as clinical importance. The registry record does not report a threshold for a clinically important difference for these measures. Confidence intervals also do not address every source of uncertainty: unreported missing-data handling, multiplicity, crossover modeling, or design details may affect interpretation. The intervals are best read with the endpoint definitions, sample sizes for each comparison, and limits of the posted analysis in mind.

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 illustrations are planning examples based on the observed effects, not a report of the original design assumptions. For this binary primary outcome, the figures are participants per arm. The general convention is that time-to-event illustrations give total events, while other illustrations give participants per arm; no time-to-event outcome is the primary endpoint.

The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. Each planning row uses a stated fraction of the observed effect as the effect to detect. The 80% power column indicates the participants per arm calculated to give an 80% chance of detecting that assumed effect if the planning model and assumptions hold. The 90% power column uses a higher target chance of detection under those same assumptions. These are prospective planning targets, not a statement about the probability that the completed study found a real effect.

As the assumed effect becomes smaller, more participants are generally needed to distinguish it from random variation under the same planning framework. The illustrated effects are tied to the observed estimate, which can be unstable, especially when based on limited data. The registry record does not report the original trial's sample-size justification, its planned effect size, or whether the original design used these assumptions. These 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 = 0.650; treatment proportion p₁ = 0.921; average p̄ = 0.786.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5805 = 1.1377.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5479 = 0.4611.
4. n = (1.1377 + 0.4611)² / (0.2711)² = 34.8, rounded up to 35 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 <- 0.65                          # control proportion
p1 <- 0.921052631578947                          # 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(4030026)
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 = 35 (80% power), 47 (90% power)
 75% of observed effect: n per arm = 70 (80% power), 93 (90% power)
 50% of observed effect: n per arm = 172 (80% power), 230 (90% power)
power.prop.test: 34.8 
Simulated power at n = 35 per arm: 0.822 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The registry lists multiple secondary outcomes and reports unadjusted comparisons for the detailed results. It does not report a multiplicity adjustment, a hierarchy of testing, or another method controlling the interpretation of multiple outcome comparisons. Without that information, secondary p-values should be treated as exploratory signals rather than a family of confirmatory tests. This is particularly relevant when several symptom and patient-reported measures are examined.

The record does not report whether interim analyses were conducted, whether any stopping rules were used, or how these would affect the stated analyses. The original sample-size justification and complete statistical analysis plan are also not reported in the registry record. No conclusion about planned versus post hoc analysis choices can therefore be drawn from the posted summaries alone.

The registry describes a safety analysis set of randomized participants who received at least one dose of investigational product and says primary data were summarized under actual treatment. Its description is truncated. It also notes that 3 participants did not receive at least one dose of NAL ER but received placebo, and 1 participant did not receive at least one dose of placebo but received NAL ER. The record does not explain how missing observations were handled for each endpoint, whether all randomized participants were included in each secondary analysis, or how incomplete periods were treated.

Because this is a crossover study, details about within-participant correlation, period effects, sequence effects, and possible carryover would inform interpretation. These methods are not reported in the registry record. The posted simple comparisons should not be presumed to incorporate those design features. These reporting gaps do not invalidate the posted summaries, but they limit assessment of how closely the estimates and uncertainty reflect the trial's full design and analysis plan.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: urosepsis (2.6%), pneumonia (2.5%).

For serious adverse events, the registry reports 1 participant at risk with a serious event in the NAL ER group and 1 in the placebo group. The at-risk counts are 38 for NAL ER and 40 for placebo. No deaths are reported in either group. These counts are distinct from the primary endpoint, which includes all TEAEs, both serious and non-serious.

The record also lists Urosepsis at 2.6% and Pneumonia at 2.5% among the top serious terms. The posted registry entries do not identify the treatment group for each term or explain how these terms relate to the participant-level serious-event counts. The figures should therefore be read as reported terms, not assigned to a particular treatment group. Small event counts provide limited precision, and the primary TEAE count does not establish treatment causation. The registry definition includes events whether or not considered related to the medicinal product.

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

The posted results describe more participants with at least one TEAE under NAL ER than under placebo in the actual-treatment summary. The primary risk-difference estimate and its confidence interval quantify that observed contrast. The endpoint includes events that may or may not be considered related to treatment, so the results do not establish that NAL ER caused each event. Serious-event counts and deaths are reported separately and should not be conflated with the broader TEAE endpoint.

For daytime cough frequency, the posted secondary comparison shows a greater average reduction from baseline under NAL ER than under placebo. The confidence interval is below zero, but it still leaves uncertainty about the magnitude. Other detailed secondary outcomes are not uniformly conclusive, and the record lists more outcomes than have detailed numerical results in this summary. The secondary comparisons are unadjusted, with no multiplicity procedure reported.

These findings do not establish how the outcomes would compare in populations beyond the study, nor do they resolve whether the crossover-specific statistical features were fully incorporated. The record does not report a clinically important difference threshold for the symptom measures, the complete missing-data approach, or the original statistical analysis plan. A statistically precise estimate is not automatically clinically important, and an uncertain result does not prove that there is no effect.

The study's stated purpose included evaluating safety and tolerability and the effect on daytime cough frequency. The posted primary endpoint addresses safety-event occurrence, while cough frequency is a secondary measure. The appropriate interpretation is therefore endpoint-specific: the safety counts describe the observed event experience, and the cough comparison describes an observed symptom contrast with its own uncertainty and limitations.

17. Why This Trial Matters Statistically

This trial illustrates why the endpoint named as primary matters when interpreting a clinical study. Although the study summary emphasizes cough frequency, the posted primary result is a count of participants with at least one TEAE. The safety outcome and the symptom outcome answer different questions and have different scales, analysis structures, and implications for uncertainty.

The crossover design also makes design-aware interpretation important. Participants received treatment in sequences, and the registry summarizes outcomes under actual treatment. Understanding a crossover comparison generally requires information about within-participant dependence and period or sequence effects. Those details are not reported in the registry record, so the simple posted contrasts should be distinguished from a fully documented crossover analysis.

The record further demonstrates the value of reading estimates with their confidence intervals and of distinguishing unadjusted secondary findings from multiplicity-controlled evidence. A p-value alone does not convey the size or precision of an effect, and several outcomes can produce a mixed pattern. The sample-size illustrations likewise serve as planning examples based on observed effects, not as evidence about the trial's original design or its achieved power.

For biostatistical interpretation, the key lesson is to keep the estimand, analysis population, design, and uncertainty aligned. A participant-level event count, a change in cough frequency, and a patient-reported score cannot be treated as interchangeable evidence. The registry record provides useful numerical summaries, while missing analysis details constrain how far those summaries can support broader conclusions.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry's arm descriptions are truncated, leaving parts of the treatment schedules incomplete. The record does not report a washout description, a carryover assessment, or the crossover-specific model used for analysis. These omissions limit evaluation of whether the posted comparisons account for treatment period, sequence, and the relationship between measurements from the same participant.

The primary analysis population description is also truncated. Although the record identifies a safety analysis set and gives details about participants who did not receive at least one dose of one treatment, it does not fully document the endpoint-specific populations or how missing data were handled. The posted denominators differ between actual-treatment groups; because this is a crossover study, they should not be summed to infer a participant count.

The registry does not report the original sample-size justification, the full statistical analysis plan, interim analyses, or a multiplicity approach. Detailed numerical results are not available in the record summary for every listed secondary outcome. The serious adverse-event terms are reported without treatment-group attribution in the available details. These limitations affect precision of interpretation and prevent a complete assessment of prespecification, analysis choices, and the relationship between particular serious events and treatment.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: A Study of Nalbuphine (Extended Release) ER in Idiopathic Pulmonary Fibrosis (IPF) for Treatment of Cough — NCT04030026.
• Registry record last updated 2025-05-29; status last verified 2025-05.
• Results first posted 2025-05-29.
• 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

The registry describes a completed randomized Phase 2 crossover study of NAL ER and placebo in idiopathic pulmonary fibrosis, with enrollment of 42. The primary posted outcome is the number of participants experiencing at least one TEAE up to Day 72. The observed count was higher under NAL ER than placebo, with an unadjusted risk difference of 0.271 and a 95% confidence interval from 0.100 to 0.442.

The secondary daytime cough-frequency comparison favored a larger reduction under NAL ER in the posted summary. Other detailed secondary results vary in precision, and the registry does not report multiplicity adjustment or key crossover analysis details. The findings should be interpreted as posted endpoint-specific comparisons, with uncertainty and reporting limitations kept in view.