Evaluation of Preoperative N1539 in Colorectal Surgery: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of Preoperative N1539 in Colorectal Surgery (NCT03323385), a randomized phase 3 study. The primary outcome is Evaluation of Safety and Tolerability - Number of Subjects With an AE.

2. Clinical Question

3. Trial Design

The registry identifies NCT03323385 as a completed phase 3 study titled “Evaluation of Preoperative N1539 in Colorectal Surgery.” Its official title describes a randomized, double-blind, placebo-controlled, multicenter evaluation of safety and efficacy. The design is listed as randomized, with a parallel model and quadruple masking. These labels describe the trial’s recorded design, but the registry record does not provide the full operational details of randomization or masking.

The two listed arms were N1539 30 mg and IV placebo. The arm descriptions state that each was administered every 24 hours. The N1539 formulation is described as meloxicam injection for IV use. The registry summary identifies the primary objective as assessment of safety and tolerability, including clinical laboratory tests, wound healing evaluation, anastomotic leaks, and adverse events and serious adverse events. Among the posted outcome measures, the primary result is the number of subjects with an adverse event.

The record gives an enrollment of 57. The posted outcome counts are 23 of 27 for N1539 and 26 of 28 for placebo. The trial start date is 2017-10-24, and the primary completion date is 2018-09-26. Its status is completed. These dates describe the registry record and do not give the dates of individual participant follow-up.

Although the official title calls the study multicenter, the number and locations of centers are not reported in the registry record. The original sample-size rationale, detailed protocol, randomization procedure, and exact masking roles are also not reported in the registry record. The posted results contain one outcome measure and no posted secondary outcomes.

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: All randomized subjects

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: All randomized subjects

6. Primary Endpoint

The registry lists the primary outcome as Evaluation of Safety and Tolerability - Number of Subjects With an AE, measured over Up to 30 days.

The primary endpoint is the number of participants with an adverse event, assessed up to 30 days. It is a binary participant-level outcome: each participant either had at least one recorded adverse event during the stated period or did not. The reported values are counts, rather than the number of separate adverse-event episodes. The outcome population is listed as all randomized subjects.

This endpoint is used to describe how often participants experienced an adverse event in each randomized group. Such a summary is relevant to the stated safety and tolerability objective. It gives an overall view of participants with events, but does not describe the nature, severity, timing, duration, or likely cause of every event. Those questions require additional outcome details.

The trial summary also names clinical laboratory tests, wound healing evaluation, anastomotic leaks, and serious adverse events as safety areas of interest. The posted primary outcome, however, is specifically the count of subjects with an adverse event. The registry record does not provide posted results for separate primary comparisons of all the other safety areas named in the summary.

Because the endpoint records whether a participant had any event, multiple events in the same participant do not become multiple participants in this measure. The count therefore should not be interpreted as the total number of adverse-event occurrences. Nor does it indicate whether an event was serious or related to study treatment. Those distinctions are not captured by the primary endpoint alone.

7. Results Posted in the Registry

• N1539 30 mg: 85.2% (23/27) versus 92.9% (26/28) on control; risk difference -7.7 percentage points (95% CI -24.1 to 8.8), risk ratio 0.92 (0.76–1.11); unadjusted two-proportion z-test p = 0.362.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary result is a binary participant-level outcome: whether a participant had an adverse event during follow-up. For a binary outcome, each participant contributes to the event count at most once, even if that participant experiences multiple events. The measure is therefore a count of participants with an event, not a count of every event occurrence. The registry specifies the population as all randomized subjects and the timeframe as up to 30 days.

What does a risk difference express?

A risk difference compares the event proportions in two groups by subtracting one group’s proportion from the other. Its natural reference point is zero, which corresponds to equal proportions. A negative estimate for N1539 relative to placebo indicates a lower observed event proportion in the N1539 group; a positive estimate would indicate a higher observed event proportion. The posted estimate is negative. The trial’s comparison gives a risk difference, confidence interval, and an unadjusted p-value. The registry record does not state the precise calculation method or any covariate adjustment for this comparison.

How should a confidence interval be read?

A confidence interval describes a range of values compatible with the data under the method’s assumptions. It communicates uncertainty about the estimated difference, rather than listing the range of individual participant outcomes. When an interval for a risk difference spans zero, it includes no difference and also allows values on either side. The interval in this comparison spans zero. Its width indicates that the estimate is not highly precise; the data allow a range of possible differences rather than a sharply determined effect. A confidence interval does not assign a probability to the true value after the data are observed.

What does the p-value add?

The registry reports an unadjusted p-value of 0.362. In general, a p-value is calculated by comparing the observed data, or data more extreme under a specified test, with what would be expected under a null model. A smaller p-value can indicate greater incompatibility with that model, but it does not quantify the effect’s size or practical importance. It is not the probability that the null model is true. The registry record does not identify the test used, its assumptions, or any planned threshold for interpretation.

The p-value and confidence interval address related but different questions. The interval displays the uncertainty and the range of effect sizes compatible with the analysis. The p-value summarizes evidence against a specified no-difference model under a test. Neither replaces consideration of the observed counts, the breadth of the interval, or the clinical and trial context. The unadjusted label also matters: the record does not describe whether the result was adjusted for other variables or for multiple comparisons.

Why distinguish participants from events?

For a participant-level binary endpoint, a participant with more than one adverse event remains one participant with an event. This makes the outcome straightforward to summarize, but it discards information about event frequency and recurrent events. It also does not distinguish mild from severe events. A separate analysis of event counts would need to address the fact that participants may have different numbers of events. General statistical methods for such counts may need to account for over-dispersion, meaning that observed variability exceeds what a simple count model expects. That issue is relevant in general, but the registry’s primary endpoint is a participant count, and the record does not report a recurrent-event or count analysis.

Similarly, the primary outcome does not establish causation. Randomized assignment supports a group comparison under the trial design, but interpretation also depends on conduct, follow-up, outcome ascertainment, and analysis choices. Details about those processes are not reported in the registry record. The posted endpoint is useful as a broad safety summary, while further clinical detail would be needed to understand the events themselves.

What analysis details are unavailable?

The registry does not report the specific statistical test, model, confidence-interval method, handling of missing outcomes, or whether the primary comparison was adjusted. It also does not provide a detailed analysis population beyond the stated all-randomized-subjects population for the endpoint. The record lists no posted analyses beyond the primary comparison. These absences do not show that no such methods were used; they mean that the methods are not reported in the registry record.

The sample-size illustrations use planning assumptions described separately: a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation, with the effect to detect set to a stated fraction of the observed effect. These are planning illustrations based on the observed effect, not the trial’s original design assumptions. The original sample-size justification and assumptions are not reported in the registry record. Such planning calculations are sensitive to their assumptions and should not be read as estimates of the probability that this completed trial detected an effect.

10. Confidence Intervals and Precision

The primary comparison has an estimated risk difference with a confidence interval that extends from a negative value to a positive value. Because the interval crosses zero, it includes no difference as well as possible differences in either direction. This limits how firmly the observed direction can be distinguished from no difference on the basis of the posted result.

The interval is also broad relative to a single point estimate. A point estimate gives one summary of the observed group contrast, while the interval shows that the underlying contrast remains uncertain across a wider range. This is a precision issue: the data do not determine the size of the difference closely. The registry’s unadjusted p-value is 0.362, but that value does not resolve the uncertainty or establish equivalence.

Precision depends on the amount of information available and on the variability of the outcome. For a binary endpoint, the number of participants and the event pattern both matter. The posted counts are 23 of 27 in the N1539 group and 26 of 28 in the placebo group. The registry does not provide a formal precision target or the original sample-size rationale, so it is not possible to assess the result against a prespecified target from the record alone.

A confidence interval concerns uncertainty in the group-level effect estimate; it does not describe the range of outcomes an individual participant might experience. It also does not account for limitations that are not represented in the calculation, such as unreported missing-data procedures or incomplete reporting of analysis methods. The interval should therefore be read alongside the limited methodological details available in the registry record.

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 display gives participants per arm for the binary outcome; it does not give a total-event count. Its calculations use the observed effect as a reference and then consider planning for 100% of that observed effect, 75% of the observed effect, and 50% of the observed effect. For each assumption, the display gives the participants per arm for 80% power and for 90% power. The figures are planning illustrations, not observed power.

The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect. The planning counts are 260 and 347 participants per arm for 100% of the observed effect; 427 and 571 for 75% of the observed effect; and 878 and 1,175 for 50% of the observed effect. Within each pair, the first figure is for 80% power and the second is for 90% power.

In plain language, power is the chance that a study would meet its statistical detection criterion if a particular effect were truly present, given the planning assumptions. The 90% column targets a higher chance of detection than the 80% column and consequently requires more participants per arm in these illustrations. Smaller effects are harder to distinguish from random variation, so planning for a smaller fraction of the observed effect requires more participants.

These calculations are not a reconstruction of the trial’s original design. The original sample-size assumptions and justification are not reported in the registry record. The observed effect is an uncertain estimate from this trial, so using it as a planning reference does not make the illustrated counts definitive requirements for another study.

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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.929; treatment proportion p₁ = 0.852; average p̄ = 0.890.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4421 = 0.8665.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4388 = 0.3693.
4. n = (0.8665 + 0.3693)² / (-0.0767)² = 259.5, rounded up to 260 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 <- 0.928571428571429                          # control proportion
p1 <- 0.851851851851852                          # 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(3323385)
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 = 260 (80% power), 347 (90% power)
 75% of observed effect: n per arm = 427 (80% power), 571 (90% power)
 50% of observed effect: n per arm = 878 (80% power), 1,175 (90% power)
power.prop.test: 259.5 
Simulated power at n = 260 per arm: 0.810 (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.

13. Multiplicity, Missing Data and Analysis Populations

The registry record lists one posted outcome measure and no posted secondary outcomes. It reports no posted analyses beyond the primary comparison. The trial summary names several safety areas, including laboratory tests, wound healing, anastomotic leaks, and adverse events and serious adverse events, but the record does not provide posted results for separate comparisons of each named area.

Multiplicity arises when several outcomes or statistical tests are considered. In general, the more tests conducted, the greater the chance that at least one result may appear notable by chance if no adjustment or other prespecified strategy is used. The registry record does not report a multiplicity plan, a hierarchy of outcomes, or any adjustment for multiple testing. The reported p-value is explicitly unadjusted. The available record therefore does not show how the broader set of safety objectives was handled analytically.

The record identifies the primary outcome population as all randomized subjects, but it does not describe how missing outcome information was handled. It does not report whether imputation, exclusion, or another approach was used, or how many outcome values, if any, were missing. No such procedure should be inferred from the reported counts alone.

The registry record also does not provide a detailed description of the analysis population beyond the all-randomized-subjects label for the primary endpoint. It does not explain whether every randomized subject contributed to the comparison, how deviations from assigned treatment were handled, or whether other populations were analyzed. These details matter because different analysis populations can answer different questions.

These reporting gaps do not establish that the study lacked a statistical plan or that data were missing. They indicate that multiplicity procedures, missing-data handling, and further analysis-population definitions are not reported in the registry record. The available results should therefore be interpreted as the reported primary comparison, without assuming unreported methods.

14. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: ileus (7.1%), incision site cellulitis (3.7%), wound dehiscence (3.7%), urinary retention (3.7%), hypoglycaemia (3.6%).

The serious adverse-event figures are 3 participants in the N1539 group, with 27 at risk, and 4 participants in the placebo group, with 28 at risk. The registry reports 0 deaths in each group. These are descriptive counts. They do not establish that serious events were caused by the study treatment, and the record does not report a formal comparison for these figures.

The registry also gives counts for other adverse events: 11 among 27 at risk in the N1539 group and 17 among 28 at risk in the placebo group. The record presents these separately from serious adverse events. It does not explain the detailed coding rules or whether the categories can overlap at the participant level, so the counts should not be added together.

The listed serious-event terms include Ileus at 7.1%, Incision site cellulitis at 3.7%, Wound dehiscence at 3.7%, Urinary retention at 3.7%, Hypoglycaemia at 3.6%, and Paranasal sinus benign neoplasm at 3.6%. The registry record does not identify the treatment group for each listed term in this summary. These terms and percentages provide additional descriptive context but do not establish comparative risk or treatment attribution.

Serious-event counts are not the same as the primary endpoint’s count of participants with any adverse event. The categories answer different descriptive questions and should be considered separately.

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

The posted results show that adverse events were recorded in both randomized groups during follow-up up to 30 days. The count was 23 among 27 participants assigned to N1539 30 mg and 26 among 28 assigned to IV placebo. The estimated risk difference is negative, but its confidence interval spans zero and the unadjusted p-value is 0.362. Taken together, these results do not establish a clear difference in the primary endpoint, and they do not establish that the groups are equivalent.

The finding is limited to a broad participant-level outcome. It does not reveal how many separate events occurred, how severe they were, when they happened, how long they lasted, or whether investigators considered them related to treatment. The serious adverse-event counts and the reported absence of deaths add descriptive safety information, but they do not resolve those questions or prove the absence of risk.

The trial’s stated objective included safety and tolerability, and the registry summary also names laboratory tests, wound healing, and anastomotic leaks. The posted primary result alone cannot answer every aspect of those objectives. Results for distinct measures and detailed event-level information are not reported in the registry record.

Randomization and masking are recorded features of the design, but interpretation still depends on details such as outcome ascertainment, follow-up, and analysis methods. The record does not report several of those details, including the handling of missing data and the statistical method used for the comparison. The posted estimate is therefore best understood as the registry’s reported group contrast, with uncertainty, rather than as a definitive account of the treatment’s effects.

These findings should not be generalized automatically to populations or care settings that are not described in the record. The registry does not provide enough participant-characteristic detail to assess how closely the trial population matches other groups. Statistical uncertainty and limited reporting both constrain what can be concluded from the posted result.

16. Why This Trial Matters Statistically

This trial illustrates why a safety comparison needs more than a pair of event counts. The primary endpoint gives the number of participants with any adverse event, but the clinical meaning of that summary depends on event type, severity, timing, and attribution. A binary participant-level measure is easy to interpret at a high level, yet it cannot show whether participants experienced one event or several, or whether events differed in seriousness.

The comparison also demonstrates the role of uncertainty. The risk-difference confidence interval crosses zero, and the unadjusted p-value is 0.362. A point estimate alone could give an overly definite impression of the direction or size of a group difference. The interval makes clear that the data leave a range of possibilities, while the p-value does not provide the probability that a treatment effect is real.

Sample-size planning is another important statistical issue. The registry’s illustrations show that planning for smaller fractions of the observed effect requires more participants per arm under the stated assumptions. Those calculations are separate from the trial’s original design rationale, which is not reported in the registry record. This distinction matters because a planning illustration based on an observed effect should not be mistaken for evidence that the completed trial had a particular level of power.

Finally, registry reporting shapes how confidently readers can interpret results. The record identifies randomization, masking, the primary population, and the timeframe, but leaves analysis methods, missing-data handling, and multiplicity procedures unreported. These are not merely technical details: they help readers understand how estimates were produced and how robust a conclusion may be. The trial is therefore a useful example of interpreting both the numerical result and the boundaries of the available statistical information.

17. Limitations

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

The primary outcome is broad and records whether a participant had any adverse event. It does not summarize event count, severity, duration, timing, or treatment attribution. The posted result therefore cannot show which events drove the group counts or whether the events had similar clinical importance.

The registry record provides limited detail about the study population and setting. It identifies colorectal surgery and describes the study as multicenter, but the number and locations of centers and detailed participant characteristics are not reported in the registry record. This limits assessment of how representative the trial population may be.

The record does not report the statistical test or model used for the primary comparison, the confidence-interval method, missing-data handling, multiplicity procedures, or a detailed analysis population beyond all randomized subjects. It also does not provide the original sample-size justification. These omissions make it difficult to evaluate analysis choices or compare the observed precision with a prespecified target.

Although the study summary mentions laboratory tests, wound healing, anastomotic leaks, and serious adverse events, the posted primary outcome is the count of subjects with any adverse event. The record does not provide results for each of the other named safety areas as separate primary comparisons. The serious-event summary is descriptive, and the record does not report a formal comparison for those counts.

Finally, the timeframe is stated as up to 30 days, but the registry record does not provide individual follow-up completeness or detail how outcome ascertainment was conducted. These limitations do not negate the reported counts; they define the boundaries of what those counts can support.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Evaluation of Preoperative N1539 in Colorectal Surgery — NCT03323385.
• Registry record last updated 2023-06-18; status last verified 2023-05.
• Results first posted 2023-06-18.
• 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.

21. Record Summary

NCT03323385 is a completed phase 3 randomized, parallel-group, quadruple-masked study of preoperative N1539 30 mg and IV placebo in colorectal surgery. The official title describes a double-blind, placebo-controlled, multicenter evaluation. The registry gives an enrollment of 57, a start date of 2017-10-24, and a primary completion date of 2018-09-26.

The primary objective was to evaluate safety and tolerability. The posted primary outcome is the number of subjects with an adverse event up to 30 days among all randomized subjects. The reported counts are 23 of 27 for N1539 and 26 of 28 for placebo. The risk-difference interval spans zero, and the unadjusted p-value is 0.362. Serious adverse events were reported for 3 participants in the N1539 group and 4 in the placebo group, with 0 deaths in each group.

The registry record does not report the detailed statistical plan, missing-data procedures, multiplicity strategy, or original sample-size rationale. The results are descriptive and should be interpreted with the uncertainty and reporting limitations in mind.