Evaluation of the Effect of Nabiximols Oromucosal Spray on Clinical Measures of Spasticity in Participants With Multiple Sclerosis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of the Effect of Nabiximols Oromucosal Spray on Clinical Measures of Spasticity in Participants With Multiple Sclerosis (NCT04984278), a randomized phase 3 study. The primary outcome is Change From Baseline in Lower Limb Muscle Tone-6 (LLMT-6).

2. Clinical Question

The clinical question is about a measured change in muscle tone, not a broad assessment of all symptoms or daily functioning. LLMT-6 combines transformed scores from six muscle groups in the lower limbs. The outcome was measured from baseline before Treatment Period 1 through the end of Treatment Period 2, and the primary result combines information from both treatment periods.

3. Trial Design

The registry record describes a randomized, triple-masked, placebo-controlled, two-way crossover trial in participants with multiple sclerosis. In a crossover design, participants receive both treatments in different periods, so each participant can contribute measurements under nabiximols and placebo. The record identifies the trial as Phase 3 and lists an enrollment of 56. Its status is terminated. The start date is 2021-08-16 and the primary completion date is 2022-11-11.

The two interventions were nabiximols and placebo, both described as oromucosal sprays. The record specifies that the placebo contained no active ingredients. The primary outcome combines treatment-period data, with the stated timeframe running from baseline before Treatment Period 1 to the end of Treatment Period 2. It reports primary arm summaries for 30 participants in each arm. Those summary counts do not explain how many participants completed both treatment periods or contributed to each part of the crossover analysis.

Some design details that would help interpret a crossover study, including treatment sequence allocation, the interval between periods, and how possible carryover effects were handled, are not reported in the registry record. The trial’s original sample-size justification and the rationale for termination are also not reported in the registry record. The masking level is listed as triple, but the identities of the masked parties are not reported in the registry record.

A crossover design can make within-participant comparisons useful because each participant receives both interventions. General explanation: this depends on measurements being available for the relevant periods and on the analysis accounting appropriately for the repeated observations and treatment sequence. The registry record identifies a mixed models analysis for the primary comparison, but does not provide enough detail to reconstruct all model specifications.

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: After signing the ICF, participants with spasticity associated with MS participated in a Screening Period of up to 28 days; changes in the dosing regimen of the participants' current MS antispasticity medications, if any, were not made during this period.

Period 1

Reasons for not completing this period:

Period 2

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: LLMT-6 was assessed in the Full Analysis Set.

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: Baseline characteristics were assessed in the Full Analysis Set.

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline in Lower Limb Muscle Tone-6 (LLMT-6), measured over Baseline (predose Day 1 of Treatment Period 1) up to Day 51 (end of treatment of Treatment Period 2).

The primary endpoint was change from baseline in Lower Limb Muscle Tone-6 (LLMT-6), measured in units on a scale. LLMT-6 is the average of six Modified Ashworth Scale-transformed scores: knee flexors, knee extensors, and plantar flexors on both sides of the body. The transformed scores range from 0, indicating no increase in muscle tone, to 5, indicating that the affected part is rigid in flexion or extension.

The endpoint is intended to capture velocity-dependent muscle tone in the lower limbs through a combined measure across these muscle groups. Averaging the six scores gives a single measure of lower-limb tone for analysis rather than treating each muscle group as a separate primary outcome. The registry record states that negative values of change indicate improvement in muscle tone.

The reported primary outcome is the combined least-squares mean change from baseline across Treatment Period 1 and Treatment Period 2. Its timeframe begins at predose Day 1 of Treatment Period 1 and ends at Day 51, the end of treatment in Treatment Period 2. The Full Analysis Set was used for the primary endpoint. The record does not describe how the scale’s clinical importance was defined, so the statistical result alone cannot establish what size of change would be meaningful to participants.

7. Results Posted in the Registry

• Nabiximols: mean -0.32 versus -0.04 on control; difference -0.28 (95% CI -0.48 to -0.08), standardized effect d = -0.70; z-test p = 0.007.

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 Lower Limb Muscle Tone-4 (LLMT-4)

• 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:
  • Nabiximols: mean -0.34 versus -0.09 on control; difference -0.25 (95% CI -0.47 to -0.03), standardized effect d = -0.57; z-test p = 0.028.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Nabiximols than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in Heart Rate

• 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:
  • Nabiximols: mean 0.90 versus -0.10 on control; difference 1.00 (95% CI -3.75 to 5.75), standardized effect d = 0.11; z-test p = 0.680.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Nabiximols and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in Erythrocytes

• 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:
  • Nabiximols: mean -0.14 versus -0.09 on control; difference -0.05 (95% CI -0.15 to 0.06), standardized effect d = -0.25; z-test p = 0.366.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Nabiximols and the control. The interval gives the range of effects that remain compatible with the data.

The additional outcomes cover another lower-limb muscle-tone measure, heart rate, blood pressure, laboratory values, and treatment-emergent adverse events, among others. The detailed numerical comparisons posted for some continuous outcomes do not all point in the same direction or have the same level of precision. In broad terms, the second muscle-tone measure has a direction consistent with the primary endpoint, while the available heart-rate and erythrocyte comparisons are less clearly distinguished from no difference by their confidence intervals.

This broad pattern is compatible with the primary result being most directly supported by the primary muscle-tone analysis, rather than establishing a consistent effect across all measured outcomes. The secondary endpoints assess different features and use different scales or units. Their estimates should not be treated as interchangeable with LLMT-6, and results for selected measures cannot establish a pattern for every outcome listed in the record.

The registry lists 13 secondary outcomes as posted, but the record does not provide detailed numerical results for every outcome in the information described. The overall secondary-outcome pattern is therefore incomplete. The full multiplicity plan, including whether any secondary tests were adjusted or ranked in a formal testing hierarchy, is not reported in the registry record.

General explanation: when many outcomes are tested, the chance of at least one apparently notable result can increase, even if no underlying effects exist. Unadjusted secondary p-values do not account for that family of tests. They can be useful descriptively and for generating questions, but usually carry less confirmatory weight than a prespecified primary analysis. No unadjusted secondary result should be interpreted as independent confirmation of the primary endpoint without considering multiplicity and the trial’s analysis plan.

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

• Change From Baseline in Lower Limb Muscle Tone-4 (LLMT-4)
• Number of Participants With Any Treatment-emergent Adverse Events (TEAEs)
• Change From Baseline in Blood Pressure
• Change From Baseline in Heart Rate
• Change From Baseline in Clinical Laboratory Test Values
• Change From Baseline in Erythrocytes
• Change From Baseline in Hemoglobin
• Change From Baseline in Hematocrit Ratio

9. Statistical Interpretation

10. Statistical Methods Explained

What does the reported estimate represent?

The primary outcome is continuous: it is a score whose values can vary across a scale. The registry reports least-squares means for changes in LLMT-6 and a combined least-squares mean difference between nabiximols and placebo. A least-squares mean is generally a model-based estimate of an average, potentially accounting for features specified in the analysis model. The registry identifies the primary method as a mixed models analysis, but details such as the exact model terms and covariance structure are not reported in the registry record. The posted estimate should therefore be understood as the reported model-based contrast, not as a fully reproducible calculation from the registry description alone.

The reported difference is negative, and the endpoint description says negative change indicates improvement in muscle tone. The comparison is between treatment conditions, not simply a before-and-after change in one arm. The placebo arm also has a reported change from baseline, so the treatment contrast reflects the relative changes summarized by the analysis.

Why use a mixed model?

General explanation: mixed models can represent repeated measurements and correlations among observations from the same participant. That is relevant to crossover studies, in which a participant receives both treatments in different periods. A well-specified model can use available observations while accounting for within-participant structure. However, the registry record does not report the model’s full specification, including which participant, period, sequence, or carryover terms were included. It is therefore not possible to assess those choices from the posted description alone.

The primary endpoint combines Treatment Period 1 and Treatment Period 2. The model-based analysis reports a combined least-squares mean difference of -0.29, with a 95% confidence interval from -0.48 to -0.10 and a p-value of 0.005. Those are the sponsor-reported primary inferential results. They should not be conflated with a calculation that treats the two treatment groups as independent samples.

What does the recalculation add?

The accompanying recalculation uses posted arm summaries to form a simple unadjusted mean comparison. It estimates a difference of -0.28 and an approximate 95% confidence interval from -0.484 to -0.076, with an unadjusted p-value of 0.007. The standard deviations used in this calculation are approximated from the posted standard errors. As a result, it does not reproduce the mixed model or its handling of the crossover structure. Its role is to provide a transparent, rough comparison from the summary values, not to replace the sponsor’s own analysis. In this record, the discrepancy flag is false and the recalculated and reported estimates are close.

General explanation: a standard error measures uncertainty in an estimated quantity, while a standard deviation describes variation among observations. They are not interchangeable. For least-squares means reported with standard errors, converting those summaries into an approximate standard deviation involves assumptions; the recalculation is consequently less tailored to the trial’s actual crossover analysis.

What does the p-value say?

The reported p-value is 0.005. In general, a p-value describes how unusual data at least as incompatible with a specified null hypothesis would be if that hypothesis and the analysis assumptions held. It is not the probability that the null hypothesis is true, nor does it measure clinical importance. The record labels the analysis as superiority and reports the p-value with the confidence interval. The registry description does not provide details about any broader family of tests or adjustment for multiple comparisons.

The recalculated p-value of 0.007 is explicitly unadjusted and is based on the simple summary-statistic comparison. It is not the reported mixed models p-value. Differences between the two can arise because the model-based analysis and the approximate unadjusted calculation use different information and assumptions.

Why can over-dispersion matter?

General explanation: over-dispersion occurs when observed variability exceeds what a statistical model assumes. If the analysis underestimates variability, standard errors may be too small and confidence intervals too narrow; if it accounts for variability appropriately, uncertainty estimates can be more credible. The primary endpoint is continuous, and the registry reports standard errors for its least-squares means. The registry record does not report an over-dispersion assessment, and it would not be appropriate to infer one from the posted summaries.

For planning, the accompanying sample-size illustrations use a normal approximation and the observed effect as their starting point. General explanation: normal approximations can be useful for planning, but are not a substitute for a design-specific calculation that incorporates the crossover structure, expected missingness, and the original analysis model. Those original design assumptions are not reported in the registry record.

11. Confidence Intervals and Precision

The sponsor-reported primary comparison has a 95% confidence interval from -0.48 to -0.10 around a combined least-squares mean difference of -0.29 units. The interval lies on the negative side of zero, consistent with the endpoint’s stated direction in which negative change indicates improvement in muscle tone. Its range conveys uncertainty in the estimated contrast: the result is not a single exact value, and the interval includes a range of plausible magnitudes under the analysis assumptions.

General explanation: a confidence interval is produced by a method that, over repeated studies under its assumptions, would cover the target parameter at the stated rate. It does not mean that there is a 95% probability that this particular interval contains the true effect. Nor does it account automatically for biases, missing data, model misspecification, or unreported design features.

The simple unadjusted recalculation gives an approximate 95% confidence interval from -0.484 to -0.076. It is similar in direction and scope to the sponsor-reported interval, but it is not the same analysis: the recalculation relies on arm summaries and approximate standard deviations rather than the mixed model. The sponsor-reported interval is the primary inferential result in the registry record.

Precision should be interpreted in context. The registry does not define a clinically important difference for LLMT-6, so the interval cannot determine whether every value it contains would be important to participants. The record also does not report period-specific estimates, sequence results, or the full model specification. These limits constrain how much can be inferred about precision across treatment periods or about the robustness of the estimate to alternative analytic choices.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm for 80% power and participants per arm for 90% power. They are not total-event counts. The illustrations assume a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. They use the observed effect as a reference and show planning for 100%, 75%, and 50% of that observed effect.

The 80% power column gives the illustrative number of participants per arm for a design with an 80% chance of detecting the specified effect under the planning assumptions, if that effect and the assumptions are correct. The 90% column gives the corresponding number for a 90% chance. Power is a design property calculated before a study, conditional on assumptions; it does not tell whether a finding is true or important.

The figures become larger when planning for a smaller effect. This is expected: a smaller difference is harder to distinguish from random variation, so more participants are generally needed to detect it at the same significance level and target power. The listed values are planning illustrations based on the observed effect, not the original trial’s design calculation. The original sample-size justification and its assumptions are not reported in the registry record. These figures are not observed power.

Because this trial is a crossover study, a design-specific calculation would ordinarily need to reflect its within-participant comparison and analysis structure. The illustrations state equal allocation between two arms and use a normal approximation; they do not report a crossover-specific sample-size model. They should therefore be read as general planning references rather than as a reconstruction of the trial’s original design or as a prediction of the result in another study.

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 = -0.280; pooled standard deviation σ = 0.403.
2. n = 2 × (1.96 + 0.842)² × 0.403² / -0.280² = 32.5, rounded up to 33 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 <- -0.28                      # observed difference in means
sigma <- 0.402659906124263                     # 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(4984278)
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 = 33 (80% power), 44 (90% power)
 75% of observed effect: n per arm = 58 (80% power), 78 (90% power)
 50% of observed effect: n per arm = 130 (80% power), 174 (90% power)
power.t.test: 33.5 
Simulated power at n = 33 per arm: 0.796 (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 registry’s sponsor-reported primary analysis is a mixed models analysis. It gives a combined least-squares mean difference of -0.29, a 95% confidence interval from -0.48 to -0.10, and a p-value of 0.005. This is the main inferential result to use when describing the trial’s primary endpoint.

The recalculation from posted arm summaries estimates a mean difference of -0.28, with an approximate 95% confidence interval from -0.484 to -0.076 and an unadjusted p-value of 0.007. These estimates are close to the sponsor’s result, but the methods differ. The recalculation uses summary statistics and approximated standard deviations; it does not reproduce the mixed model or fully represent the crossover design.

The registry record does not flag a discrepancy between the two results. The close estimates offer a basic cross-check that the direction and approximate size of the primary contrast are consistent across the reported analysis and simple recalculation. They do not make the methods interchangeable. The sponsor’s model-based result remains the reported primary analysis, while the recalculation is a secondary, approximate interpretation of the arm summaries.

15. Multiplicity, Missing Data and Analysis Populations

The registry record identifies a primary endpoint and reports a primary mixed models analysis. It also lists multiple secondary outcomes. However, a multiplicity strategy—such as a hierarchy of tests, an adjustment method, or a statement that secondary tests are exploratory—is not reported in the registry record. Without that information, the secondary p-values should not be treated as if they were necessarily controlled for the number of outcomes examined.

General explanation: multiplicity arises when multiple hypotheses are tested. Even when each test uses the same nominal significance threshold, the chance of at least one false-positive result across a family of tests can rise. Adjustments or prespecified testing sequences can address this, but they change how results should be interpreted. The record does not state whether such procedures were used for the secondary outcomes.

The Full Analysis Set is identified for the primary endpoint. The registry record does not provide a fuller definition of this population, nor does it specify the handling of missing observations, withdrawals, protocol deviations, or incomplete treatment periods. It also does not report a missing-data sensitivity analysis. These omissions matter because crossover analyses may depend on which participants have usable measurements under both treatments and on how incomplete period data are handled.

The primary endpoint timeframe spans both treatment periods, and the analysis is described as mixed models. General explanation: likelihood-based mixed models can use available observations under particular assumptions about missingness, but the appropriateness of those assumptions depends on why data are missing and on model specification. The registry record does not provide enough detail to establish how missingness was addressed or to assess the assumptions.

Treatment sequence, period effects, and carryover handling are also not described in the posted analysis details. These are relevant considerations in a crossover study, but the absence of detail is not evidence that the analysis failed to address them. It means that their treatment cannot be evaluated from the registry record.

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 non-serious adverse event terms

The posted adverse-event summary lists 30 participants at risk for serious adverse events in each treatment group. It reports zero serious adverse events in the nabiximols group and zero in the placebo group. It also reports zero deaths in each group. These are the serious adverse event figures recorded for the groups; they should be read as counts in the observed trial sample, not as proof that serious events cannot occur.

The record also lists six participants with other, non-serious adverse events in the nabiximols group and zero in the placebo group. That is a separate category from serious adverse events. The serious adverse event terms list is empty, so no specific serious-event terms are posted there.

General explanation: when event counts are small or zero, estimates of event risk can remain uncertain, and a limited trial sample may not characterize uncommon events well. The registry record does not provide further detail about event timing, duration, severity beyond the serious/non-serious classification, or causal assessment. The safety figures should therefore be understood as a description of the recorded counts, not as a comprehensive characterization of safety.

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

The primary result describes a statistically distinguishable difference in the combined change in LLMT-6 between nabiximols and placebo in this trial. The reported difference is -0.29 units, with a 95% confidence interval from -0.48 to -0.10 and a p-value of 0.005. Since negative change indicates improvement on the scale, the direction of the estimate favors a more negative change with nabiximols than with placebo.

This finding applies to the measured lower-limb muscle-tone endpoint and the trial population and analysis described in the registry record. It does not establish effects on every symptom of multiple sclerosis, daily activities, quality of life, or outcomes not reported in the record. The result is also not a treatment recommendation. The record does not specify a threshold for a clinically important LLMT-6 difference, so statistical evidence alone cannot determine the practical importance of the observed contrast.

The trial’s crossover design means that participants received both interventions in different periods. The primary result combines information across those periods, but period-specific estimates and treatment-sequence details are not reported in the registry record. The record does not report the original sample-size justification, the reason for trial termination, or a full account of missing data. Those limitations leave uncertainty about aspects of the design and analysis that could help readers assess generalizability and robustness.

There is also a distinction between the sponsor’s model-based result and the simple recalculation from arm summaries. They are close in magnitude and direction, but the recalculation is approximate and does not replace the mixed models analysis. The result should be interpreted as the posted analysis of one primary endpoint, alongside the uncertainty interval and the limits of the information recorded.

18. Why This Trial Matters Statistically

This trial is statistically notable because a crossover design allows treatment comparisons within participants, while also requiring analysis that recognizes the repeated and period-based structure. The registry identifies a mixed models analysis for the primary endpoint, which is appropriate in broad terms for repeated observations, but the model specification is not reported in enough detail to reproduce or fully evaluate its assumptions.

The primary result is relatively clear in direction: the reported interval lies below zero, and the simple recalculation from arm summaries is close to the sponsor-reported estimate. Considering both supports a transparent distinction between the prespecified model-based result and a rough, unadjusted check. They are related evidence, not independent replications.

The record also illustrates why statistical significance does not settle clinical meaning. A confidence interval can indicate uncertainty in the estimated contrast, but without a clinically important threshold for LLMT-6, it cannot establish how consequential the difference is. The additional outcomes raise the separate issue of multiplicity: a primary result has a different evidential role from unadjusted findings among many secondary measures.

Finally, the registry’s limitations are instructive for interpretation. Enrollment is listed as 56, while primary arm summaries each include 30; treatment-period completion and missing-data details are not reported. The trial is marked terminated, but the reason is not reported. These registry entries do not erase the posted result; they define what can be responsibly concluded from the registry record and what remains uncertain.

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.

Several limitations specific to this trial affect interpretation. It uses a crossover design, but the registry record does not report the treatment sequences, interval between periods, period-specific results, or how potential carryover was assessed. The combined treatment-period estimate therefore provides limited visibility into whether the contrast was consistent across periods.

The primary endpoint summaries each include 30 participants, while total enrollment is listed as 56. The record does not explain the participant flow or the difference between enrollment and the reported arm counts. The Full Analysis Set is named, but its definition and the handling of incomplete crossover data are not reported in the registry record.

The primary result is reported from a mixed models analysis, but the full model specification is not posted in the details described. This limits independent assessment of covariate adjustment, correlation structure, and treatment of period or sequence. The recalculation is an approximate unadjusted comparison and cannot resolve those limitations.

The original sample-size rationale, analysis plan for multiplicity, and missing-data sensitivity analyses are not reported in the registry record. The trial is terminated, but the reason is not reported. The clinical importance threshold for LLMT-6 is also not reported. These gaps limit conclusions about power as originally planned, robustness across analytic assumptions, and the practical meaning of the estimated difference.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Evaluation of the Effect of Nabiximols Oromucosal Spray on Clinical Measures of Spasticity in Participants With Multiple Sclerosis — NCT04984278.
• Registry record last updated 2024-12-11; status last verified 2024-12.
• Results first posted 2024-02-05.
• 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 record describes a randomized, triple-masked, placebo-controlled, two-way crossover Phase 3 trial of nabiximols versus placebo in participants with multiple sclerosis and spasticity. Enrollment is listed as 56, and the trial status is terminated.

The primary endpoint was combined change from baseline in LLMT-6 across the treatment periods. The sponsor-reported mixed models analysis gives a least-squares mean difference of -0.29 units, with a 95% confidence interval from -0.48 to -0.10 and a p-value of 0.005. Negative changes indicate improvement in muscle tone on this measure.

The record also posts secondary outcomes and adverse-event counts. Key details—including the reason for termination, original sample-size justification, full model specification, and missing-data handling—are not reported in the registry record.