Efficacy and Safety of VVZ-149 Injections in Patients Undergoing Laparoscopic Colectomy: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety of VVZ-149 Injections in Patients Undergoing Laparoscopic Colectomy (NCT05764525), a randomized phase 3 study. The primary outcome is Time-weighted Sum of Pain Intensity Differences for 12 Hours Post-dose (SPID 12).

2. Clinical Question

3. Trial Design

This was a phase 3, randomized, parallel-group, placebo-controlled study of VVZ-149 injections for postoperative pain following laparoscopic colectomy. The registry identifies masking as quadruple. The official title describes the study as double-blind, while the registry’s masking entry says quadruple; which roles were masked is not reported in the registry record. The record lists 285 participants enrolled and reports completed status.

The study start date is 2021-07-19, and the primary completion date is 2022-11-03. The listed sponsor is Vivozon Pharmaceutical Inc. The primary endpoint results are for the mITT population, with 141 participants in the VVZ-149 group and 143 in the placebo group. The record does not explain how the mITT population was defined or how participants were assigned to it.

The primary outcome was a continuous measure, the time-weighted sum of pain intensity differences for 12 hours post-dose (SPID 12). The registry describes one reported statistical analysis, an analysis of variance (ANOVA) comparing the difference of least-squares means. The analysis is labeled as a superiority analysis. Details such as the randomization procedure, allocation concealment, treatment dose, study sites, and the prespecified analysis plan are not reported in the registry record.

Two secondary outcomes are listed: the total number of patient-controlled analgesia (PCA) requests for 12 hours post-dose, and the total amount of PCA and rescue medication consumption for 12 hours post-dose. Their results are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: mITT

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.

6. Primary Endpoint

The registry lists the primary outcome as Time-weighted Sum of Pain Intensity Differences for 12 Hours Post-dose (SPID 12), measured over 0-12 hours post-dose.

The primary endpoint is the time-weighted sum of pain intensity differences over the 12 hours after dosing, called SPID 12. Pain intensity was assessed on an 11-point numerical rating scale, with 0 meaning no pain and 10 meaning the worst pain imaginable. For each assessment, pain intensity difference was based on the predose score minus the score at that time. The endpoint combines these differences across time using the linear trapezoidal rule and is expressed in score-hours.

The registry states that the theoretical SPID 12 range is 0 to 120 and that a higher value indicates greater pain relief. Weighting the differences over time gives a measure of pain relief across the post-dose interval, rather than relying on a single pain rating. This can capture both the size and the duration of differences in pain intensity during the period assessed.

The endpoint’s reported group values are least-squares means, not simple unadjusted group averages. The registry does not report the covariates, if any, included in the model producing those estimates. Nor does it report a threshold for interpreting how large a difference would be clinically important. Statistical evidence about a group difference therefore does not, by itself, establish the practical importance of that difference.

7. Results Posted in the Registry

• VVZ-149 Injections: mean 26.83 versus 19.89 on control; difference 6.94 (95% CI 2.16 to 11.72), standardized effect d = 0.34; z-test p = 0.004.

8. Statistical Interpretation

9. Statistical Methods Explained

The posted primary analysis is an analysis of variance (ANOVA) reporting a difference of least-squares means between the VVZ-149 and placebo groups. The endpoint is continuous: each participant’s SPID 12 is a numerical score on a scale-hours measure. A difference of means is therefore a natural way to describe the average contrast between randomized groups for this outcome.

What does a least-squares mean represent?

In general, a least-squares mean is a model-based estimate of a group mean. It can account for terms included in the statistical model, rather than being only the arithmetic average of all observations in a group. The registry reports least-squares means and an ANOVA comparison, but the model terms and any covariates are not reported in the registry record. It is therefore not possible to identify from the record what adjustment, if any, was made beyond the group comparison.

The registry’s SPID 12 description explains how the outcome is constructed. Pain intensity was assessed on an 11-point numerical rating scale, from 0 (no pain) to 10 (worst pain imaginable). The difference at a given time is defined using the predose pain intensity minus the pain intensity at that time. Differences over the 0-12 hours post-dose interval are combined by a linear trapezoidal rule. In general, trapezoidal integration approximates the area under a curve by connecting adjacent observations with straight lines. This produces a time-weighted summary, with units of score-hours. The registry states that higher SPID indicates greater pain relief.

How should the group comparison be read?

The reported difference of least-squares means is 6.938, with a 95% confidence interval from 2.145 to 11.731 and p = 0.005. The contrast is expressed in the same score-hours units as SPID 12. The positive estimate corresponds to the VVZ-149 group having the higher estimated SPID, given the ordering of the groups and the registry’s interpretation of higher SPID. In general, a confidence interval describes a range of values compatible with the data under the assumptions of the analysis; a p-value describes how surprising data at least as incompatible with a null comparison would be if that null model were true. Neither quantity measures clinical importance.

The reported p-value is for the posted ANOVA analysis. The record does not state whether this p-value was adjusted for testing multiple outcomes or comparisons. It also does not report whether any interim analyses were planned or conducted, or whether there were prespecified subgroup analyses. Those details should not be inferred from the number of results posted.

What does the unadjusted re-calculation add?

The supplementary re-calculation uses the posted group estimates and standard errors to form an approximate, unadjusted comparison. It reports a mean difference of 6.94, a 95% confidence interval from 2.159 to 11.72, and an unadjusted p-value of 0.004. The pooled standard deviation used for the standardized effect calculation is approximate, as indicated in the calculation, because the posted spread values are standard errors rather than standard deviations. The resulting standardized mean difference is 0.338. These re-calculated quantities are useful as a check based on the available summaries, but they are not a substitute for the sponsor’s model-based analysis.

In general, standard errors describe the sampling uncertainty of estimated means, whereas standard deviations describe variability among individual observations. Confusing the two can lead to incorrect conclusions about how dispersed participant-level results are. In this record, the arm-level dispersion is reported as standard error. The re-calculation makes an approximate conversion for its pooled spread; it should consequently be read as an approximation, not as the trial’s prespecified analysis.

Why can over-dispersion matter?

In general, over-dispersion means that observed variability is greater than a model assumes. If a model underestimates variability, its standard errors can be too small and its confidence intervals too narrow. That concern is especially relevant for outcomes such as event counts when their variability does not match a simple count model. The primary endpoint in this trial is continuous, and the registry does not report diagnostics about its distribution or model fit. No conclusion about over-dispersion or a corrective method can be drawn from the registry record.

There is one reported primary analysis, and two secondary outcomes are listed. The record does not report a full statistical analysis plan, how missing observations were handled, the analysis population definition, or a multiplicity procedure. These are important details because they clarify how the reported estimates were produced, how incomplete data were treated, and how the risk of false-positive results across multiple tests was managed. Their absence from the registry record does not establish that no such procedures existed; it means they cannot be assessed from the posted record.

10. Confidence Intervals and Precision

The sponsor’s reported estimate is a difference of least-squares means of 6.938 score-hours. Its 95% confidence interval extends from 2.145 to 11.731. In general, a confidence interval conveys the precision of an estimate by identifying a range of values compatible with the observed data and the statistical model. The reported interval is entirely on the positive side of zero, consistent with the reported p-value of 0.005 for the group comparison.

The interval does not mean there is a 95% probability that the true effect lies within these particular limits. Under the usual repeated-sampling interpretation, the method would produce intervals that contain the underlying parameter at the stated rate when its assumptions hold. The registry does not give enough detail about the model or its assumptions to assess them fully. The interval also does not answer whether an effect is clinically important; no clinical-importance threshold is reported in the registry record.

The unadjusted re-calculation gives a mean difference of 6.94 with a 95% confidence interval from 2.159 to 11.72. This is close to the sponsor’s reported estimate and interval. Small numerical differences between the two sets of values are consistent with the re-calculation being based on posted summary statistics and a different, approximate unadjusted method. The re-calculated interval should not be interpreted as more authoritative than the sponsor’s model-based result.

The arm-level standard errors are 1.73 for VVZ-149 and 1.72 for placebo. They quantify uncertainty in the estimated arm means; they do not show the range of individual pain relief scores. The registry does not provide participant-level distributions, so variation in responses among individuals cannot be described from these summaries. Precision of the mean contrast and variation among individuals are distinct statistical questions.

11. 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, not total events. They are planning illustrations based on the observed effect, not the original trial’s sample-size justification. The registry record does not report the trial’s own original design assumptions or sample-size justification.

The planning calculations assume a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to a stated fraction of the observed effect. The listed scenarios are planning for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. For each scenario, the 80% power column gives the number of participants per arm that the calculation estimates would be needed for an 80% chance of detecting that effect under the stated assumptions. The 90% power column gives the corresponding number of participants per arm for a 90% chance.

For planning at 100% of the observed effect, the figures are 138 participants per arm for 80% power and 185 participants per arm for 90% power. For planning at 75% of the observed effect, they are 245 and 328 participants per arm. For planning at 50% of the observed effect, they are 551 and 738 participants per arm. These are hypothetical planning counts; they are not the observed group sizes and do not show the trial’s actual design rationale.

In general, smaller effects are harder to distinguish from random variation, so detecting a smaller effect requires more participants under otherwise similar assumptions. These calculations are not observed power: they are prospective planning illustrations derived from the observed effect, and they do not measure the probability that the completed trial succeeded.

12. 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 = 6.940; pooled standard deviation σ = 20.556.
2. n = 2 × (1.96 + 0.842)² × 20.556² / 6.940² = 137.7, rounded up to 138 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 <- 6.94                      # observed difference in means
sigma <- 20.5555048967493                     # 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(5764525)
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 = 138 (80% power), 185 (90% power)
 75% of observed effect: n per arm = 245 (80% power), 328 (90% power)
 50% of observed effect: n per arm = 551 (80% power), 738 (90% power)
power.t.test: 138.7 
Simulated power at n = 138 per arm: 0.802 (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.

13. Analyses Reported by the Sponsor

The registry’s own analysis is an ANOVA comparison of least-squares means. It reports a difference of 6.938, a 95% confidence interval from 2.145 to 11.731, and p = 0.005. This is the sponsor-reported analysis for the registered primary endpoint.

The supplementary unadjusted re-calculation from posted summary statistics gives a mean difference of 6.94, a 95% confidence interval from 2.159 to 11.72, and an unadjusted p-value of 0.004. The estimate and inferential results are close to the sponsor’s figures. They are not identical because the re-calculation is an approximate comparison based on summary statistics, while the sponsor reports a model-based least-squares mean difference from ANOVA.

The arm-level standard errors are used in the approximation, and the pooled standard deviation is identified as approximate. The re-calculation therefore serves as a secondary consistency check, not a replacement for the sponsor’s analysis. The registry does not report enough model detail to reproduce the ANOVA or to determine what, if any, covariates were included.

14. Multiplicity, Missing Data and Analysis Populations

The primary endpoint is SPID 12 over 0-12 hours post-dose. The record also lists two secondary outcomes: total PCA requests for 12 hours post-dose, and total PCA and rescue medication consumption for 12 hours post-dose. Results for these secondary outcomes are not reported in the registry record. The record lists one analysis, the ANOVA comparison for the primary endpoint.

When multiple outcomes, time points, or comparisons are tested, the chance of obtaining at least one apparently positive result can increase. In general, multiplicity procedures are used to manage this issue, for example by adjusting the testing threshold or controlling an overall error rate. Whether such a procedure was used for this trial is not reported in the registry record. The reported p-value should therefore be understood as the p-value shown for the posted primary analysis, without assuming an unreported adjustment or correction.

The primary outcome population is identified as mITT. The meaning of that population, including the criteria for inclusion and whether participants were analyzed according to randomized assignment, is not reported in the registry record. The number of participants included for each arm is reported, but those counts alone do not define the analysis population or explain participant flow.

Missing outcome data can affect estimated group differences, particularly if the likelihood of missingness differs between groups or is related to pain scores. In general, statistical plans specify how missing values are handled and whether sensitivity analyses assess alternative assumptions. The missing-data method, amount and pattern of missingness, and any sensitivity analyses are not reported in the registry record. The record also does not report interim analyses, stopping rules, or a complete statistical analysis plan. These omissions limit assessment of the analysis choices; they do not establish that no such plans or procedures existed.

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 non-serious adverse event terms

The registry reports zero serious adverse events among 141 participants at risk in the VVZ-149 group and zero among 143 participants at risk in the placebo group. It also reports zero deaths in each group. No serious adverse event terms are listed. These are counts for the categories recorded in the safety results and should not be interpreted as evidence that no adverse events of any kind occurred.

Other adverse events are reported as affecting 101 participants in the VVZ-149 group and 98 in the placebo group, with 141 and 143 participants at risk, respectively. The record does not provide event types, severity, timing, duration, or an assessment of whether events were considered related to treatment. It also does not provide detail about how participants with multiple events were counted beyond reporting the number affected.

Safety counts are descriptive summaries. The registry record does not report a statistical comparison of these figures, and no inference about relative safety should be based on the counts alone. In general, interpreting safety requires the event definitions, follow-up period, exposure, and clinical context, much of which is not reported in the registry record.

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

The primary result describes an estimated difference in a continuous measure of pain relief during the 12 hours after dosing. The sponsor’s ANOVA reports a positive difference of least-squares means, and the registry defines higher SPID 12 as greater pain relief. The confidence interval and p-value quantify statistical uncertainty under the analysis; they do not establish the size of benefit that would matter to patients or clinicians.

The endpoint combines pain intensity differences across time and is expressed in score-hours. It is not a single pain score, nor does it directly state how many participants experienced a particular level of relief. The registry does not report a clinically important threshold for SPID 12, individual response distributions, or results for the listed secondary outcomes. Those missing details prevent a fuller account of the practical meaning of the group difference.

The trial record supports describing the comparison and its reported statistical uncertainty, but it does not justify broad claims about effects outside the studied setting. The listed population is patients undergoing laparoscopic colectomy, and details needed to assess applicability to other populations are not reported in the registry record. Treatment dose and administration details are also not reported in the registry record.

The safety results report no serious adverse events or deaths in either group, while other adverse events affected participants in both groups. Without event descriptions, severity, timing, and comparative safety analyses, these counts are not a complete safety assessment. The results should be read as what the registry reports, with the boundaries of the available information kept in view.

17. Why This Trial Matters Statistically

This trial illustrates how a continuous clinical outcome can summarize change over a defined period rather than at one isolated assessment. SPID 12 combines pain intensity differences over 0-12 hours post-dose, and its direction is interpretable because the registry states that higher values mean greater pain relief. The endpoint definition is essential to understanding what the reported mean difference represents.

It also illustrates the distinction between a trial’s own model-based analysis and an approximate re-calculation using summary statistics. The ANOVA result is the sponsor-reported analysis, while the supplementary calculation provides a broadly similar estimate using posted group summaries. Because these methods do not necessarily use the same modeling details, agreement is reassuring as a consistency check but does not make them interchangeable.

The reported confidence interval adds information that a p-value alone does not: it conveys the range of estimates compatible with the analysis and data. Even so, statistical precision cannot answer whether the difference is clinically important when no interpretation threshold is reported. The registry’s missing information on the analysis population definition, missing-data handling, and multiplicity also shows why numerical results need to be read alongside reporting detail.

Finally, the planning illustrations show how sample-size requirements depend on the effect assumed for planning. They are distinct from the trial’s original design justification, which is not reported in the registry record, and from observed power. Separating these questions helps prevent retrospective planning calculations from being mistaken for evidence about the trial’s design or the certainty of its findings.

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 record gives a concise account of the trial but leaves several details needed to assess the primary result. It does not report the eligibility criteria, treatment dose or schedule, randomization procedure, allocation concealment, or which specific roles were masked. Although the record identifies quadruple masking and the official title uses double-blind wording, it does not explain those masking details.

The primary analysis population is labeled mITT, but its definition and relationship to the randomized population are not reported. The record gives arm sizes for the primary outcome but does not describe participant flow, exclusions, or missing observations. The approach to missing data and any sensitivity analyses are not reported in the registry record.

The sponsor’s ANOVA results are reported, but the model specification and covariates are not. The registry does not report a multiplicity strategy, interim analyses, subgroup analyses, stopping rules, or a full statistical analysis plan. The listed secondary outcomes have no posted results in this record, limiting assessment beyond the primary endpoint.

The safety summary does not include the specific types, severity, timing, duration, or attribution of other adverse events. The record gives no serious adverse event terms and reports no deaths, but the available summary is not a detailed safety account. Finally, no clinically important difference threshold for SPID 12 is reported. These gaps restrict interpretation of clinical importance, generalizability, and robustness without changing what the posted primary estimate itself reports.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Efficacy and Safety of VVZ-149 Injections in Patients Undergoing Laparoscopic Colectomy — NCT05764525.
• Registry record last updated 2025-02-20; status last verified 2025-02.
• Results first posted 2025-02-20.
• 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

NCT05764525 is a completed phase 3, randomized, parallel-group, placebo-controlled trial of VVZ-149 injections for postoperative pain following laparoscopic colectomy. The registry reports 285 participants enrolled and identifies masking as quadruple. The primary endpoint was SPID 12 over 0-12 hours post-dose in the mITT population.

The sponsor-reported ANOVA estimated a difference of least-squares means of 6.938, with a 95% confidence interval from 2.145 to 11.731 and p = 0.005. Higher SPID indicates greater pain relief. The registry reports zero serious adverse events and zero deaths in both groups; other adverse events affected 101 participants in the VVZ-149 group and 98 in the placebo group. Results for the two listed secondary outcomes are not reported in the registry record.