Efficacy and Safety of Naldemedine in the Treatment of Opioid-induced Constipation: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety of Naldemedine in the Treatment of Opioid-induced Constipation (NCT01965158), a randomized phase 3 study. The primary outcome is Percentage of Participants With a Spontaneous Bowel Movement (SBM) Response.

2. Clinical Question

3. Trial Design

This was a Phase 3 randomized, double-blind, placebo-controlled, parallel-group study of naldemedine for opioid-induced constipation in people with non-malignant chronic pain receiving opioid therapy. The registry identifies the masking as quadruple. It records 547 participants enrolled and the study status as completed. The study start date is 2013-08-29, and the primary completion date is 2015-01-22.

The registry lists two drug groups: naldemedine and placebo. The naldemedine group received 0.2 mg orally once daily; the placebo group received matching placebo on the same daily schedule. Both treatment descriptions specify a 12-week period. The brief summary says the study concerned adults who were not using laxatives. Further eligibility details, such as exact age limits or clinical thresholds, are not reported in the registry record.

The primary outcome was a participant-level responder measure over the 12-week treatment period. The registry identifies its analysis population as intent-to-treat. It also lists secondary measures concerning weekly spontaneous bowel movements, complete spontaneous bowel movements, and spontaneous bowel movements without straining. Numerical results are posted for three secondary measures; a numerical result for the listed measure concerning bowel movements with no straining is not reported in the registry record.

The registry records the sponsor as Shionogi. It does not report the original sample-size justification, the intended analysis plan in full, or details about any interim analyses. Those features cannot be inferred from the fact that the trial enrolled 547 participants or from the posted endpoint 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: Participants were randomized in a 1:1 ratio to 0.2 mg of naldemedine or placebo. Participants were stratified based on their documented opioid use (average total daily dose (TDD) during the 14-consecutive-day qualifying period) as follows: * 30 to 100 mg equivalents of oral morphine sulfate * \> 100 mg equivalents of oral morphine sulfate

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Intent-to-treat population

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 population included all randomized participants; one participant was excluded from each arm due to enrollment at 2 different sites simultaneously.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Participants With a Spontaneous Bowel Movement (SBM) Response, measured over 12-week treatment period.

The primary endpoint is the percentage of participants classified as spontaneous bowel movement responders during the 12-week treatment period. A spontaneous bowel movement, or SBM, was defined as a bowel movement without rescue laxative therapy during the preceding 24 hours. Participants recorded bowel movements and constipation each day using a bowel movement and constipation assessment.

Response required sustained weekly patterns. A participant needed at least 9 positive response weeks during the 12-week period, including at least 3 positive response weeks during the last 4 weeks. Each positive response week required at least 3 SBMs that week and an increase from baseline of at least 1 SBM per week. A week with fewer than 4 days of diary entries counted as a non-response week. Participants with insufficient primary endpoint data—data for fewer than 9 of the 12 treatment weeks or fewer than 3 of the last 4 weeks—were also treated as non-responders.

This responder definition is used to represent a pattern over time rather than an isolated event. It incorporates both a weekly bowel-movement threshold and change relative to baseline, while the final responder classification also depends on repeated weekly success. That makes the endpoint clinically interpretable as a sustained response measure, but it also means the result depends on diary completeness and the specified rules for incomplete weeks and missing endpoint data. The registry does not report additional details about how baseline was calculated.

7. Results Posted in the Registry

• Naldemedine: 47.6% (130/273) versus 34.6% (94/272) on control; risk difference 13.1 percentage points (95% CI 4.9 to 21.2), risk ratio 1.38 (1.12–1.69); unadjusted two-proportion z-test p = 0.002.

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 the Last 2 Weeks of the Treatment Period in the Number of Spontaneous Bowel Movements Per Week

• 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:
  • Naldemedine: mean 3.42 versus 2.12 on control; difference 1.30 (95% CI 0.77 to 1.83), standardized effect d = 0.41; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Naldemedine than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline to Week 1 in the Number of Spontaneous Bowel Movements Per Week

• 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:
  • Naldemedine: mean 3.48 versus 1.36 on control; difference 2.12 (95% CI 1.61 to 2.63), standardized effect d = 0.70; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Naldemedine than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline to the Last 2 Weeks of the Treatment Period in the Number of Complete Spontaneous Bowel Movements Per Week

• 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:
  • Naldemedine: mean 2.58 versus 1.57 on control; difference 1.01 (95% CI 0.54 to 1.48), standardized effect d = 0.36; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Naldemedine than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes with posted numerical results show a broadly consistent pattern: the naldemedine group had larger reported changes than the placebo group for weekly SBMs, including the Week 1 measure, and for complete SBMs over the last 2 weeks. This pattern is directionally consistent with the primary endpoint, which classified more participants in the naldemedine group as responders. The measures nevertheless capture different aspects of bowel-movement experience and use different analysis scales, so they should not be treated as repeated versions of one identical outcome.

The registry lists four secondary outcome titles, but numerical results are posted for three of them. The listed outcome concerning spontaneous bowel movements with no straining does not have a numerical result reported in the registry record. The record also lists five outcome measures and five analyses; it does not provide a complete account of how every listed measure maps to those analysis entries.

Secondary results generally carry less weight than the primary endpoint for confirmatory interpretation, particularly when several outcomes are examined. Repeated testing can increase the chance that at least one result appears persuasive by chance. Whether a multiplicity adjustment or a formal testing hierarchy was planned or used is not reported in the registry record. The posted p-values should therefore be read as outcome-specific results, not as evidence that the collection of secondary tests has been controlled for multiple comparisons.

The secondary findings add information about timing and types of bowel movements, but they do not remove uncertainty about the primary analysis or fill in missing registry entries. They are supportive context for the overall pattern, with the primary endpoint remaining the central registered outcome.

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

• Change From Baseline to the Last 2 Weeks of the Treatment Period in the Number of Spontaneous Bowel Movements Per Week
• Change From Baseline to Week 1 in the Number of Spontaneous Bowel Movements Per Week
• Change From Baseline to the Last 2 Weeks of the Treatment Period in the Number of Complete Spontaneous Bowel Movements Per Week
• Change From Baseline to the Last 2 Weeks of the Treatment Period in the Number of Spontaneous Bowel Movements With No Straining Per Week

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary at the participant level: each participant is classified as a responder or non-responder, and the group result is expressed as a percentage. This differs from a continuous outcome such as a mean change in weekly bowel movements. The responder definition combines several weekly conditions across the treatment period, so the percentage reflects how many participants met all required criteria rather than the size of an average change.

How should the risk difference be read?

A risk difference compares the event proportions in two groups by subtracting one group’s proportion from the other. Here, the event is meeting the responder definition, and the registry’s reported difference is 13.0 percentage points in favor of the naldemedine group. The confidence interval describes uncertainty around the estimated difference under the analysis. It is not a range containing a known fixed treatment effect with certainty, and it does not describe the spread of individual participant outcomes.

The posted recalculation uses the reported responder counts and group sizes to estimate an unadjusted risk difference and its interval. The sponsor analysis is reported as a Cochran-Mantel-Haenszel analysis of the difference. That method is used for comparisons of categorical outcomes and can account for stratification when strata are part of the analysis. The registry record does not identify the stratification factors or provide enough detail to reconstruct the sponsor’s full analysis. The recalculated comparison should therefore be treated as a simple, unadjusted check rather than a substitute for the reported analysis.

What does the continuous-outcome analysis represent?

The secondary results include least-squares mean changes in bowel-movement measures. A least-squares mean is an estimate from a statistical model, rather than necessarily a raw arithmetic average. The registry identifies ANCOVA as the sponsor method for the posted secondary comparisons. ANCOVA is a general approach that can compare groups while accounting for covariates included in the model. Which covariates were included is not reported in the registry record.

The secondary result for change in weekly SBMs over the last 2 weeks is a sponsor-reported least-squares mean difference of 1.30, with a 95% confidence interval from 0.77 to 1.83. For change at Week 1, the sponsor-reported difference is 2.11, with a 95% confidence interval from 1.60 to 2.63. For complete SBMs over the last 2 weeks, the sponsor-reported difference is 1.01, with a 95% confidence interval from 0.54 to 1.48. The recalculated results use the posted group estimates and standard errors as summary inputs; they do not reproduce an ANCOVA model.

Standard error describes the estimated precision of a group mean or model estimate, not the variability among individual participants. A confidence interval for a mean difference is built around the estimated difference and reflects uncertainty in that estimate. When the underlying model, covariate choices, or participant-level data are unavailable, a summary-statistic recalculation can differ slightly from a sponsor model while still giving a broadly similar estimate.

Why can variation matter?

General statistical explanation: outcome variability affects how precisely a group difference can be estimated. In count outcomes, variation can exceed what a simple model assumes; this is called over-dispersion. A model that fails to account for over-dispersion can understate uncertainty. The registry identifies the secondary outcome analyses as ANCOVA, but it does not report a count-model specification or a specific over-dispersion assessment. No such analysis should be assumed.

Finally, a p-value measures how incompatible the observed data are with a specified null model, under the assumptions of the analysis. It does not measure the probability that the null hypothesis is true, the size of an effect, or its importance. Confidence intervals and the actual effect estimates provide complementary information about magnitude and precision. The registry record does not report a complete statistical analysis plan, so the intended hierarchy of tests and any planned adjustments cannot be established from the posted results alone.

11. Confidence Intervals and Precision

The primary sponsor estimate is a 13.0 percentage-point difference in responder percentages, with a 95% confidence interval from 4.8 to 21.3 percentage points. The interval gives a range of values compatible with the data and the assumptions of that analysis. Because the interval does not include zero, the reported comparison is consistent with a higher responder percentage in the naldemedine group. The interval also shows that the exact size of the difference is uncertain: the data do not identify one precise value.

The recalculated interval for the unadjusted risk difference is 0.049 to 0.212. This is close to the sponsor’s interval, though the approaches are not identical. For interpretation, the sponsor’s reported analysis takes precedence. In general, a narrower confidence interval indicates greater statistical precision, while a wider interval indicates more uncertainty about the estimate. Precision is distinct from whether an effect is important in practice, which cannot be judged from an interval alone.

The registry also reports confidence intervals for the continuous secondary comparisons. Their widths describe uncertainty in the estimated between-group differences under the sponsor analyses. They should not be read as ranges for individual participants’ changes, and they do not capture every source of uncertainty, such as unreported design or analysis decisions.

A confidence interval is not a guarantee that the true effect lies within its endpoints. Its usual interpretation is tied to a repeated-sampling procedure and the assumptions behind the model. The registry provides the confidence level and endpoints for the primary comparison, but detailed model diagnostics and all analysis specifications are not reported in the registry record. The interval is therefore useful evidence of statistical precision, alongside the point estimate, while remaining conditional on the analysis used.

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 calculation. For these outcomes, the entries are participants per arm, not total events. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The target effect is a stated fraction of the observed effect: the full observed effect, 75% of it, or 50% of it. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm under which a study would have an 80% chance of detecting the specified effect at the stated significance level, if the planning assumptions and model held. The 90% power column gives the corresponding number for a higher chance of detection. These are planning calculations, not a description of what happened in this completed trial.

As the assumed effect becomes smaller, the planning figures increase: a smaller difference is harder to distinguish from random variation, so more participants are generally needed for the same power under otherwise similar assumptions. The rows using fractions of the observed effect explore how sensitive a future design might be to a less pronounced effect than the one estimated in this trial. Because the observed effect itself is uncertain, these illustrations should not be treated as a guarantee that a future study will achieve its target power. This is 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 = 0.346; treatment proportion p₁ = 0.476; average p̄ = 0.411.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6958 = 1.3637.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6896 = 0.5804.
4. n = (1.3637 + 0.5804)² / (0.1306)² = 221.6, rounded up to 222 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 <- 0.345588235294118                          # control proportion
p1 <- 0.476190476190476                          # 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(1965158)
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 = 222 (80% power), 297 (90% power)
 75% of observed effect: n per arm = 390 (80% power), 522 (90% power)
 50% of observed effect: n per arm = 865 (80% power), 1,157 (90% power)
power.prop.test: 221.6 
Simulated power at n = 222 per arm: 0.801 (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

For the primary endpoint, the sponsor reports a Cochran-Mantel-Haenszel difference of 13.0 percentage points, with a 95% confidence interval from 4.8 to 21.3 and a reported p-value of 0.002. The sponsor’s own analysis takes precedence over the simple recalculation. The recalculated risk difference is 0.131, with an interval from 0.049 to 0.212 and p = 0.002. These results are close in magnitude and direction, but the recalculation is unadjusted and does not reproduce the sponsor’s analysis method.

For the secondary outcomes with numerical results, the sponsor reports ANCOVA least-squares mean differences. Their estimates and confidence intervals are close to the corresponding summary-statistic recalculations. The Week 1 result has a small difference between the reported sponsor estimate and the recalculated estimate; the registry’s model details are insufficient to identify the reason. Differences can arise because a model-based analysis and a calculation from posted group summaries do not use identical information or assumptions.

The recalculated results are checks based on posted summaries, not corrections to the sponsor’s results. They do not account for covariates or other model features unless those are explicitly included in the calculation, and those details are not reported in the registry record. For interpretation of the trial’s formal results, the sponsor analyses remain the primary reference.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several outcomes or statistical tests are considered. If each test is judged separately without adjustment, the chance of at least one apparently notable result can increase as the number of tests grows. This general issue matters because the registry lists multiple outcomes and analyses. It does not report whether the sponsor used a multiplicity adjustment, a prespecified testing hierarchy, or another approach to control the interpretation of multiple results. Those details are not reported in the registry record, so the secondary p-values should be treated as individual results rather than as a multiplicity-controlled set.

Missing data are handled explicitly in the primary endpoint definition. A week with fewer than 4 days of diary entries was treated as a non-response week, and a participant with insufficient primary endpoint data was also treated as a non-responder. This rule means that incomplete diary information can affect the responder classification. The registry identifies the primary analysis population as intent-to-treat, but it does not provide a detailed account of participant-level missingness, the amount of missing diary data, or sensitivity analyses for alternative missing-data assumptions.

The registry record does not report whether the sponsor conducted interim analyses, what stopping rules might have applied, or the full original statistical analysis plan. It also does not report the original sample-size justification. These omissions limit assessment of whether all analysis decisions were prespecified and how robust the conclusions are to alternative assumptions. They do not change the reported results, but they define what can and cannot be assessed from the registry record.

The primary non-responder rule is part of the endpoint definition and should not be confused with a general solution to all missing-data concerns. It provides a specified classification for certain incomplete records, while other missing-data patterns and their handling are not fully described. Interpretation should therefore retain the endpoint’s explicit rules and acknowledge the unreported details.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

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 (0.4%), hypersensitivity (0.4%), dehydration (0.4%), transient ischaemic attack (0.4%), supraventricular tachycardia (0.4%).

The registry reports serious adverse events for 14 participants in the naldemedine group, with 271 participants at risk, and for 5 participants in the placebo group, with 272 participants at risk. It reports other adverse events for 29 participants in the naldemedine group and 11 participants in the placebo group, using the same respective at-risk counts. These are descriptive counts as recorded, not adjusted comparisons or estimates of causation.

The registry lists six serious adverse event terms, each with a reported frequency of 0.4%: appendicitis, hypersensitivity, dehydration, transient ischaemic attack, supraventricular tachycardia, and ventricular extrasystoles. The record does not assign these listed terms to a treatment group in the posted term list, so they should not be attributed to one group on that basis.

Deaths are not reported in the registry record. A missing death count should not be interpreted as a count of zero. The safety figures also do not by themselves establish whether an event was caused by treatment. They provide a limited summary of recorded events during the study and should be interpreted alongside the trial’s duration, population, and the incomplete safety detail in the registry record.

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

The primary result describes a higher percentage of participants meeting the prespecified spontaneous bowel movement responder definition in the naldemedine group than in the placebo group during the 12-week treatment period. The sponsor’s estimated difference is 13.0 percentage points, and its 95% confidence interval ranges from 4.8 to 21.3 percentage points. This expresses the observed comparison and its statistical uncertainty for this trial population and endpoint.

It does not mean every participant in the naldemedine group responded, nor does it mean that no participant in the placebo group responded. The endpoint is a threshold-based classification requiring repeated weekly responses, an increase from baseline, and adequate diary information under the stated rules. It does not measure every aspect of constipation, daily functioning, satisfaction, or longer-term outcomes.

The findings also do not establish how results would apply to people outside the population described in the registry, to different treatment durations, or to other clinical settings. The registry summary describes adults with non-malignant chronic pain receiving opioids who were not using laxatives, and the treatment period was 12 weeks. Longer-term results are not reported in the registry record.

The posted safety counts describe recorded events but do not establish whether events were caused by a study treatment. The registry does not report a death count. The primary efficacy result and the safety summary answer different questions and should not be collapsed into a single judgment about overall benefit or risk.

Finally, statistical evidence is not the same as clinical importance. The confidence interval describes uncertainty in the estimated difference under the analysis assumptions, but the registry does not define a threshold for a clinically important difference. Interpreting importance requires context beyond a p-value or the fact that an interval excludes zero. The results support a description of the observed trial comparison, not a universal conclusion or individual medical advice.

18. Why This Trial Matters Statistically

This trial illustrates how a clinical endpoint can combine frequency, change from baseline, and persistence over time. The primary result is not simply a comparison of average bowel-movement counts: it classifies participants using a sustained-response rule and treats specified incomplete diary records as non-response. That makes the endpoint’s operational definition central to interpreting the percentage difference.

It also demonstrates why the estimand and analysis method matter. The primary outcome is a binary responder percentage, while the secondary outcomes include model-based mean changes. Each answers a different statistical question. The sponsor’s primary analysis and the unadjusted recalculation are similar in direction and magnitude, but they are not identical methods; keeping that distinction clear prevents a summary calculation from being mistaken for the trial’s formal analysis.

Confidence intervals add information beyond a point estimate by showing the uncertainty compatible with the analysis. Here, the reported primary interval is above zero, while still allowing a range of plausible difference sizes. The secondary estimates broaden the description of the outcome pattern, but multiple testing and unreported analysis-plan details limit how strongly they can be treated as confirmatory evidence.

Finally, this record highlights the boundary between a registry summary and a full trial report. It records enrollment, treatment schedules, endpoint definitions, selected results, and some safety counts, but it does not report every design rationale or analysis detail. Statistical interpretation depends both on the numbers that are posted and on recognizing which methodological questions the registry record leaves unanswered.

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 registry record does not report the original sample-size justification, full protocol, or complete statistical analysis plan. It also does not report whether interim analyses were conducted, whether multiplicity adjustment was planned or applied, or the covariates included in the ANCOVA models. These gaps prevent a full assessment of prespecification and model specification from registry information alone.

The primary endpoint depends on daily diary entries and classifies weeks with fewer than 4 diary days as non-response. Participants with insufficient endpoint data are also classified as non-responders. The registry does not report how many participants had incomplete diaries, the distribution of missing data, or sensitivity analyses that might show how alternative missing-data assumptions affect the result.

Although four secondary outcomes are listed, numerical results are posted for only three. The measure concerning spontaneous bowel movements with no straining has no numerical result reported in the registry record. This leaves the secondary outcome record incomplete for readers assessing all listed measures. The registry also does not provide detailed participant-level data that would allow independent reproduction of the sponsor’s model-based analyses.

The posted safety summary is limited. It includes counts for serious and other adverse events and a list of serious-event terms, but the term list does not identify treatment groups. Deaths are not reported in the registry record. The available summaries do not establish event causality or provide a complete account of event timing and severity.

Finally, the findings are tied to the described population and 12-week treatment period. Longer-term outcomes and applicability to populations outside the registry description are not established by the posted results. These are limits on interpretation, not evidence that the reported trial comparisons are incorrect.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy and Safety of Naldemedine in the Treatment of Opioid-induced Constipation — NCT01965158.
• Registry record last updated 2017-05-30; status last verified 2016-04.
• Results first posted 2017-05-30.
• 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

The registry describes a completed Phase 3 randomized, quadruple-masked, parallel-group comparison of naldemedine and placebo for opioid-induced constipation in adults with non-malignant chronic pain receiving opioid therapy. The study enrolled 547 participants. Naldemedine was given orally at 0.2 mg once daily, and matching placebo was given on the same schedule, for 12 weeks.

The primary endpoint was the percentage of participants meeting a sustained SBM responder definition during treatment. The sponsor reports a 13.0 percentage-point difference between groups, with a 95% confidence interval from 4.8 to 21.3. The registry also posts numerical results for three secondary outcomes and selected adverse-event counts. Some protocol, analysis, missing-data, multiplicity, and safety details are not reported in the registry record.