Safety and Efficacy of Pagibaximab Injection in Very Low Birth Weight Neonates for Prevention of Staphylococcal Sepsis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Safety and Efficacy of Pagibaximab Injection in Very Low Birth Weight Neonates for Prevention of Staphylococcal Sepsis (NCT00646399), a randomized phase 2, phase 3 study. The primary outcome is The Number of Participants With Staphylococcal Sepsis From Study Days 0 to 35..

2. Clinical Question

3. Trial Design

This was a Phase 2b/3, randomized, double-blind, placebo-controlled, parallel-group trial of pagibaximab in very low birth weight neonates. The registry lists Biosynexus Incorporated as sponsor and the trial as completed. The study start is recorded as 2009-03, and primary completion as 2011-05. Enrollment is recorded as 1579. The brief summary describes an intended enrollment of 1550 infants before 48 hours of life and randomization in a 1:1 ratio. The registry does not explain the difference between the intended enrollment in that summary and the enrollment figure in the record.

Participants assigned to pagibaximab were to receive 100 mg/kg intravenously on study Days 0, 1, 2, 9, 16, and 23. The placebo was phosphate buffered saline. The primary outcome was the number of participants with staphylococcal sepsis over 35 days. The primary outcome description states that 1579 subjects were included in the ITT population. The posted arm counts for this outcome are 792 for pagibaximab and 787 for placebo.

Although the registry identifies the trial as randomized and double-blind, further operational details are not reported in the registry record. This includes the method used to generate the allocation sequence, how allocation was concealed, which groups of people were masked, and how masking was maintained. The trial's original design assumptions, including its planned statistical power and target effect, are not reported in the registry record. The record does not provide details of an interim monitoring plan or of protocol changes.

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: 1579 very low birth weight subjects were included in the ITT.

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 The Number of Participants With Staphylococcal Sepsis From Study Days 0 to 35., measured over 35 days.

The primary endpoint counts participants with staphylococcal sepsis from study Days 0 to 35. It is a binary outcome at the participant level: each participant is counted according to whether the event occurred during the stated follow-up period. The registry describes the measure as a number of participants and gives the timeframe as 35 days. It does not provide a more detailed case definition, diagnostic criteria, or adjudication process for staphylococcal sepsis.

A participant count is useful for comparing how often an event was observed in the randomized groups over a specified period. It gives a direct clinical summary of the endpoint, while an effect estimate such as a risk difference or risk ratio expresses the comparison between groups. Counts alone do not convey the uncertainty in that comparison, so the estimates and confidence intervals are also important when interpreting the posted result.

The primary endpoint is not a measure of all infections, all episodes of sepsis, or time until sepsis. It is specifically the number of participants with staphylococcal sepsis within the stated period. The registry identifies safety and efficacy as the outcome description, but details about how the endpoint was defined and analyzed beyond the posted summary are not reported in the registry record.

7. Results Posted in the Registry

• Pagibaximab: 10.7% (85/792) versus 10.0% (79/787) on control; risk difference 0.7 percentage points (95% CI -2.3 to 3.7), risk ratio 1.07 (0.80–1.43); unadjusted two-proportion z-test p = 0.651.

8. Statistical Interpretation

9. Statistical Methods Explained

What does a risk difference describe?

A risk difference compares the observed proportions of participants with an event in two groups by subtracting one group’s proportion from the other’s. Its sign depends on the order of the comparison. In the posted comparison, the pagibaximab group is compared with placebo, and the risk difference is 0.007. A positive value means the observed event proportion was higher in the pagibaximab group; a negative value would indicate a lower observed proportion. The estimate is a contrast in the trial data, not proof of a causal effect or a judgment about clinical importance.

The risk difference is an absolute measure. It can be informative because it describes the difference in event frequency on the outcome’s original risk scale. Its interpretation depends on the particular population, outcome definition, and follow-up period. Here, the endpoint is participants with staphylococcal sepsis over 35 days, so the estimate pertains to that defined outcome and period rather than to sepsis in general or to a different duration.

How do relative measures differ?

A risk ratio compares the event proportions as a ratio, and an odds ratio compares the odds of an event. A ratio of 1 represents no relative difference between groups; values on either side represent different directions of association under the comparison's ordering. The posted risk ratio is 1.069, and its interval is 0.8 to 1.429. The posted odds ratio is 1.077, and its interval is 0.780 to 1.489. These ratio measures can look numerically different from an absolute risk difference because they use different scales. They should not be treated as interchangeable.

For outcomes that are not common, odds ratios may sometimes approximate risk ratios, but that is a general statistical observation and does not make the two quantities identical. The posted estimates should be read on their stated scales. The registry does not describe an adjusted model or covariates for the comparison, so the reported results should not be characterized as adjusted for baseline characteristics.

What does the p-value contribute?

The unadjusted p-value is 0.651. In general, a p-value measures how compatible observed data are with a statistical model that assumes no group difference, taking account of the test used. It is not the probability that the null hypothesis is true, nor is it a measure of the size or importance of an effect. A large p-value does not show that two treatments are equivalent. Establishing equivalence or noninferiority would require a suitable design and a prespecified margin, neither of which is reported in the registry record.

The p-value should be interpreted alongside the effect estimate and its confidence interval. A test result alone does not show the range of effects compatible with the data. Here, the point estimate and interval are more useful for seeing both the direction of the observed contrast and the uncertainty around it. The registry does not report a detailed account of the test procedure or the trial's original statistical analysis plan.

Why use a confidence interval?

A confidence interval gives a range of effect estimates that are reasonably compatible with the observed data under the assumptions of the method. In general, a wider interval indicates less precision, while a narrower interval indicates greater precision. A confidence interval is not a guarantee that the true effect lies within its bounds, and it does not assign probabilities to particular values after the data have been observed. Its coverage interpretation depends on the statistical procedure and its assumptions.

For a risk difference, zero represents no difference. The posted interval extends from -0.023 to 0.037 and includes zero. This indicates that the data are compatible with effects in either direction under the interval method. For a ratio measure, 1 represents no relative difference; both posted ratio intervals include 1. These features align with the unadjusted p-value and indicate that the estimates are not precise enough to rule out no difference or a range of effects in either direction.

What does the ITT label mean in this record?

The primary outcome description states that 1579 very low birth weight subjects were included in the ITT population. In general, an intention-to-treat approach analyzes participants according to their randomized assignment, regardless of treatment adherence, but the exact implementation can vary. The registry does not report how the ITT population was defined in detail, how participants with missing endpoint information were handled, or whether all randomized participants contributed to the primary comparison. Therefore, the label should be reported as it appears rather than treated as evidence about unreported analysis procedures.

The posted outcome counts are participant counts, not counts of repeated episodes. No time-to-event estimate is posted for the primary endpoint. The registry record lists no posted analysis records and no posted secondary outcome measures. The analysis details beyond the outcome summaries, including model choices, covariate adjustment, and sensitivity analyses, are not reported in the registry record.

10. Confidence Intervals and Precision

The risk-difference estimate is 0.007, with a 95% confidence interval from -0.023 to 0.037. The interval crosses zero, the value corresponding to no absolute difference. It therefore includes the possibility of a lower event proportion with pagibaximab, as well as a higher event proportion. The width of the interval indicates that the estimate is not highly precise: the observed data do not narrow the plausible range to one direction.

The relative estimates tell a similar story. The risk ratio is 1.069, with an interval from 0.8 to 1.429, and the odds ratio is 1.077, with an interval from 0.780 to 1.489. Each interval includes 1, the value corresponding to no relative difference. The estimates are centered slightly above their no-difference values, but the intervals leave substantial room for effects in either direction.

In general, confidence intervals communicate uncertainty around an estimate; they are not a guarantee about the true effect and do not show which values are clinically important. The registry record does not report a threshold for a clinically meaningful risk difference, so clinical importance cannot be judged from statistical precision alone. The unadjusted p-value of 0.651 is consistent with the intervals not excluding the no-difference values, but the interval estimates provide more information about the range of effects compatible with the observed data.

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 participants or total events. They illustrate the sample size that would be needed under stated assumptions to detect a chosen fraction of the observed effect. For 100% of the observed effect, the figures are 30,314 participants per arm for 80% power and 40,582 participants per arm for 90% power. For 75% of the observed effect, they are 53,494 per arm for 80% power and 71,613 per arm for 90% power. For 50% of the observed effect, they are 119,464 per arm for 80% power and 159,928 per arm for 90% power.

In plain terms, 80% power means that, if the assumed effect and planning model were correct, a study of the stated size would have an 80% chance of detecting an effect at the specified significance level. The 90% column represents a higher chance of detection under those same assumptions and therefore requires a larger sample size. Smaller effects are harder to distinguish from random variation, so the planning figures increase as the assumed fraction of the observed effect becomes smaller.

The planning 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. These are illustrative calculations based on the observed effect, not the trial's original design assumptions; those original assumptions are not reported in the registry record. The planning figures are not observed power.

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 = 0.100; treatment proportion p₁ = 0.107; average p̄ = 0.104.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4314 = 0.8456.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4314 = 0.3631.
4. n = (0.8456 + 0.3631)² / (0.0069)² = 30,313.9, rounded up to 30,314 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 <- 0.100381194409149                          # control proportion
p1 <- 0.107323232323232                          # 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(646399)
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 = 30,314 (80% power), 40,582 (90% power)
 75% of observed effect: n per arm = 53,494 (80% power), 71,613 (90% power)
 50% of observed effect: n per arm = 119,464 (80% power), 159,928 (90% power)
power.prop.test: 30313.9 
Simulated power at n = 30,314 per arm: 0.800 (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 no posted secondary outcome measures and no posted analysis records. The primary endpoint is identified as the number of participants with staphylococcal sepsis from study Days 0 to 35. The trial summary also refers to safety and pharmacokinetics, but results for additional efficacy or pharmacokinetic endpoints are not reported in the registry record. This limits the scope of conclusions to the posted primary outcome and the adverse-event summaries.

Multiplicity arises when several outcomes, comparisons, subgroups, or repeated analyses are tested: the chance of at least one apparently positive result can increase as the number of tests grows. In general, prespecifying a primary outcome and planning how to account for multiple tests can help control that risk. The registry identifies a primary outcome, but multiplicity procedures, any hierarchy of outcomes, and any adjustment to significance thresholds are not reported in the registry record. With no secondary analyses posted, their role in the trial's interpretation cannot be assessed.

The primary outcome description says that 1579 subjects were included in the ITT population. The registry does not give detailed definitions of that population, explain how participants were assigned for analysis, or state how missing endpoint data were handled. It does not report the amount or pattern of missing outcome data, imputation procedures, or sensitivity analyses for missingness. These omissions matter because conclusions from a randomized comparison can depend on how incomplete outcome information is addressed.

Subgroup analyses, protocol deviations, and per-protocol or other analysis populations are also not reported in the registry record. The posted group counts and effect estimates can be described as recorded, but they do not provide enough detail to reconstruct the full analysis plan or to evaluate its implementation.

14. 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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: patent ductus arteriosus (14.1%), intraventricular haemorrhage (7.3%), necrotizing colitis (6.6%), intestinal perforation (3.6%), pulmonary interstitial emphysema (3.3%).

Serious adverse events were recorded for 284 of 784 participants at risk in the pagibaximab group and 273 of 778 participants at risk in the placebo group. Other adverse events were recorded for 770 of 784 participants at risk in the pagibaximab group and 758 of 778 participants at risk in the placebo group. These are descriptive counts and denominators; no between-group inferential comparison for these adverse-event summaries is reported in the registry record.

The registry lists Patent Ductus Arteriosus at 14.1%, Intraventricular Haemorrhage at 7.3%, Necrotizing Colitis at 6.6%, Intestinal Perforation at 3.6%, Pulmonary Interstitial Emphysema at 3.3%, and Thrombocytopenia at 2.3% among the leading serious-event terms. The registry record does not provide enough detail in these summaries to determine how event terms were coded, whether participants could contribute to more than one term, or the group-specific rates for each listed term.

Deaths are not reported in the registry record. These summaries describe the events recorded during the trial and should not be read as proof that a treatment caused or prevented an event. The record does not provide additional detail on event severity grading, relatedness assessments, or the timing of adverse events.

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

The posted primary outcome describes participants with staphylococcal sepsis over 35 days. The observed counts were 85 in the pagibaximab group and 79 in the placebo group. The estimated risk difference is 0.007, and the unadjusted p-value is 0.651. The 95% confidence interval for the risk difference ranges from -0.023 to 0.037, so the data do not precisely establish the direction or size of a difference between groups.

This result does not demonstrate that pagibaximab prevents staphylococcal sepsis, and it does not demonstrate that it increases the risk. The estimate is a summary of this trial's observed data, while its interval includes values representing effects in either direction. A lack of statistical evidence for a difference is not evidence that the treatments are equivalent. Equivalence would require an appropriate design, a prespecified equivalence margin, and an analysis addressing that question; such information is not reported in the registry record.

The result also does not answer questions about outcomes other than the posted primary endpoint. Although the trial summary mentions safety and pharmacokinetics, the registry does not post secondary outcome measures or pharmacokinetic results. The adverse-event summaries provide descriptive event counts, but the record does not report inferential comparisons for those outcomes. Death counts are not reported in the registry record.

Interpretation is limited to the enrolled very low birth weight population, the stated 35-day period, and the way the endpoint was defined and recorded in the trial. Detailed eligibility criteria, endpoint adjudication procedures, missing-data handling, and the full statistical analysis plan are not reported in the registry record. The results therefore support a cautious description of the observed endpoint and its uncertainty, rather than a broad conclusion about all infants, longer-term outcomes, or other uses of pagibaximab.

16. Why This Trial Matters Statistically

This trial presents a useful example of why an event count, an effect estimate, and an uncertainty interval answer different questions. The counts show what was observed in each randomized group. The risk difference describes the absolute contrast, while the risk ratio and odds ratio describe relative contrasts. The confidence intervals show how much uncertainty remains around those estimates. Considering these quantities together gives a fuller statistical reading than relying on a p-value alone.

The posted risk-difference interval spans values below and above zero, and the relative intervals span values below and above 1. Thus, the data do not identify a clear direction of effect. This illustrates an important distinction: a result that does not provide clear statistical evidence of a difference is not the same as proof that there is no difference. Precision and clinical relevance depend on the range of effects that remain compatible with the data, as well as on what differences would matter clinically. A threshold for clinical importance is not reported in the registry record.

The planning illustrations also demonstrate how sample-size needs depend on the effect size one aims to detect. Under the stated planning assumptions, detecting a smaller fraction of the observed effect requires more participants per arm. Such calculations are planning aids, not a retrospective measure of whether the completed trial was adequately powered according to its original design. The original design assumptions are not reported in the registry record.

Finally, the record highlights the value of complete reporting. Details about missing data, multiplicity, endpoint adjudication, and the analysis plan would help readers assess the robustness and scope of the findings. Without those details and without posted secondary results, statistical interpretation should stay close to the primary endpoint and the summaries actually reported.

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 registry record does not provide a detailed definition of staphylococcal sepsis, diagnostic thresholds, or procedures for confirming and adjudicating endpoint events. Without those details, readers cannot assess how consistently the endpoint was applied or whether outcome classification could have differed across sites. The record identifies the outcome period as 35 days but does not give further information on follow-up completeness or ascertainment.

Eligibility criteria beyond the description of very low birth weight neonates and enrollment before 48 hours of life are not reported in the registry record. This limits assessment of how closely the enrolled population represents other clinical populations. The record also does not explain the difference between the planned enrollment stated in the brief summary and the enrollment figure in the registry.

Details about random-sequence generation, allocation concealment, masking procedures, and adherence to assigned treatment are not reported. Nor are missing outcome data, handling of missingness, protocol deviations, or sensitivity analyses described. The ITT population is named, but its implementation is not detailed. These gaps make it difficult to evaluate possible sources of bias beyond the information conveyed by the randomized, double-blind design label.

The registry lists no posted analysis records and no secondary outcome measures. The original statistical plan, including any multiplicity strategy, sample-size justification, and interim monitoring procedures, is not reported in the registry record. Consequently, the posted comparison cannot be evaluated against a complete prespecified analysis plan. The safety summaries are descriptive, deaths are not reported, and further detail about event coding, severity, relatedness, and timing is absent.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Safety and Efficacy of Pagibaximab Injection in Very Low Birth Weight Neonates for Prevention of Staphylococcal Sepsis — NCT00646399.
• Registry record last updated 2011-10-24; status last verified 2011-10.
• Results first posted 2011-10-24.
• 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

NCT00646399 is a completed Phase 2b/3 randomized, double-blind, placebo-controlled, parallel-group trial sponsored by Biosynexus Incorporated. The registry lists enrollment of 1579, a start date of 2009-03, and primary completion in 2011-05. The intervention was pagibaximab 50 mg/mL, given intravenously at 100 mg/kg on study Days 0, 1, 2, 9, 16, and 23; the comparator was phosphate buffered saline.

The primary outcome was the number of participants with staphylococcal sepsis from study Days 0 to 35. The posted counts were 85 of 792 for pagibaximab and 79 of 787 for placebo. The risk difference was 0.007, with a 95% confidence interval from -0.023 to 0.037 and an unadjusted p-value of 0.651. The registry includes descriptive adverse-event summaries but does not report secondary outcome measures or analysis records.