Trial to Evaluate the Safety and the Immunogenicity of GSK Biologicals' Influenza Vaccine GSK2186877A in Healthy Children: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Trial to Evaluate the Safety and the Immunogenicity of GSK Biologicals' Influenza Vaccine GSK2186877A in Healthy Children (NCT01096056), a randomized phase 1 study. The primary outcome is Number of Subjects Reporting Fever Grade 2 or Higher.

2. Clinical Question

The central comparison is between two vaccine formulations and schedules, not between vaccination and no vaccination. Both groups also received Fluarix at Month 6. The primary outcome is a safety measure, while the registry record also lists immunogenicity outcomes, including haemagglutination inhibition antibody titers and measures of seropositivity, seroprotection, seroconversion, and antibody rise.

The posted primary counts are 11 of 20 participants in formulation 1 and 7 of 20 in formulation 2. These counts describe the observed frequency of the specified fever outcome in the vaccinated cohort. The comparison is limited to this outcome and these groups; it does not by itself summarize all safety or immunogenicity findings. Results for the other listed outcomes are not described in the posted primary results.

3. Trial Design

The registry record describes NCT01096056 as a completed, randomized, unmasked, parallel-group Phase 1 study. It enrolled 40 participants and was intended to evaluate safety and immunogenicity of the GSK Biologicals influenza vaccine GSK2186877A in healthy children 6 to 35 months of age. The condition listed is influenza. The trial began on 2010-04-05, and primary completion was recorded on 2010-12-13.

Participants were assigned to one of two formulation groups. In the formulation 1 group, subjects received two doses of GSK2186877A at Day 0 and Day 21, then a dose of Fluarix at Month 6. In the formulation 2 group, subjects received one dose of GSK2186877A at Day 0, then Fluarix at Month 6. There were 20 participants in each group for the primary outcome. The registry record states that the total vaccinated cohort included subjects whose vaccine administration was documented.

Randomization describes how group assignment was made; unmasked means masking was not used. Parallel-group means participants were assigned to a group and followed under that group’s regimen, rather than crossing over between regimens. These design features provide the context for interpreting the comparison, but the record does not report the allocation method or further details on how randomization was implemented.

The registry record says the posting was updated following Protocol Amendment 1 in Jun 2010, affecting study design, outcome measures, interventions, and the number of subjects. Further details of those changes are not reported in the registry record. The protocol’s original sample-size justification and the rationale for the group sizes are also 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: The analysis was performed on Total Vaccinated cohort which included all subjects with the vaccine administration documented.

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 Number of Subjects Reporting Fever Grade 2 or Higher, measured over Within 7 days following any vaccination with New generation influenza vaccine GSK2186877A.

The primary endpoint counts participants reporting fever of Grade 2 or higher within 7 days following any vaccination with the new-generation influenza vaccine GSK2186877A. The registry defines Grade 2 or higher fever as an axillary temperature greater than 38 degrees centigrade (°C). The measure is a participant count, rather than a count of fever episodes or a measure of fever duration. The registry record identifies the Total Vaccinated cohort as the analysis population: subjects with vaccine administration documented.

Counting participants with the event is a direct way to describe how commonly the specified safety outcome occurred in each group during the stated observation window. It gives a numerator that can be read alongside the number of vaccinated participants assessed. The outcome is clinically interpretable as a reported fever meeting the registry’s threshold, but it does not capture every possible aspect of reactogenicity or safety. In particular, it does not describe severity beyond the Grade 2-or-higher threshold, the timing of each event within the window, or the duration of fever.

The endpoint is relevant to a study whose stated purpose includes evaluating safety. It is not an immunogenicity measure. Immunogenicity was addressed through separately listed outcomes, including HI antibody titers and responses. Results for those outcomes are not reported in the posted results.

7. Results Posted in the Registry

• Influenza Vaccine GSK2186877A Formulation 2 Group: 35.0% (7/20) versus 55.0% (11/20) on control; risk difference -20.0 percentage points (95% CI -50.2 to 10.2), risk ratio 0.64 (0.31–1.30); unadjusted two-proportion z-test p = 0.204.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary at the participant level: each participant either met the registry’s definition of fever of Grade 2 or higher within the stated window or did not. The posted counts are 11 events among 20 participants for formulation 1 and 7 among 20 for formulation 2. A comparison of event proportions is a natural summary for a binary outcome. The unadjusted recalculated risk difference is -0.2, with formulation 2 compared against formulation 1. The negative value represents a lower observed proportion in formulation 2.

What does a risk difference express?

As a general statistical explanation, a risk difference subtracts the event proportion in one group from the event proportion in the comparison group, using a stated direction. It retains the scale of absolute difference in event probability. Its sign depends on the order of groups. Here, the comparison is formulation 2 relative to formulation 1, so the negative estimate corresponds to fewer observed fever events proportionally in formulation 2. It is an estimate from the observed participants, not a guarantee of the difference that would be seen in another group of children.

How should the p-value be understood?

The posted unadjusted p-value is 0.204. In general, a p-value describes the compatibility of the observed data with a null hypothesis under a particular statistical model and test. It is not the probability that the null hypothesis is true, and it does not quantify the chance that the finding is due to chance. The registry record does not report the statistical plan or the test used for the sponsor’s original analysis. The available comparison is an unadjusted recalculation from the posted summary counts.

Because the record’s discrepancy indicator is false, the posted counts and recalculated comparison do not have a flagged disagreement requiring a sponsor-analysis result to take precedence. This recalculation is nevertheless unadjusted: it does not account for other variables or other outcomes. The registry record does not report an adjusted analysis.

Why is the confidence interval useful?

As a general statistical explanation, a confidence interval represents a range of values compatible with the data under the method’s assumptions. It conveys uncertainty around an estimate more directly than a single point estimate. The risk-difference interval in this comparison crosses zero, so it includes both a negative difference and a positive difference. The data therefore do not tightly determine the direction of the difference. The registry record does not state the confidence level or describe the interval-construction method.

For participant counts, uncertainty depends on both the number of observed events and the number assessed. With 20 participants in each group, one or a few participants can meaningfully affect the proportions. As a general statistical point, estimates from small groups tend to be less precise than estimates from otherwise comparable larger groups. A wide interval is a reminder that the observed point estimate should not be treated as a precise or stable estimate of the population difference.

What does unadjusted mean?

In general, an unadjusted comparison uses the group outcome summaries without correcting for additional covariates, stratification variables, or other modeling terms. It is a straightforward description of the difference in the posted counts. The registry record does not report whether a more extensive model was planned or performed, and no analysis entries are listed in the registry record. The posted recalculation should not be mistaken for an analysis of all 14 outcome measures or for a complete account of the trial’s statistical plan.

Binary-outcome methods generally rely on assumptions about how participants contribute independent observations and how the sampling variation is represented. The registry record does not report diagnostic checks, alternative analysis methods, or details about missing data. As a general point, over-dispersion can matter when variation is greater than a model assumes; accounting for it can affect estimated uncertainty. No over-dispersion measure or adjustment is reported for this participant-count outcome, and the simple recalculation does not add one.

The registry record lists safety and immunogenicity outcomes, but the primary result concerns fever only. HI antibody titers, seropositive and seroprotected participant counts, seroconversion, geometric mean fold rise, and solicited adverse-event outcomes are listed separately. Their listing is not evidence that their results support a particular conclusion. Statistical multiplicity across outcomes is not discussed in the registry record.

10. Confidence Intervals and Precision

The estimated risk difference is -0.2 for formulation 2 relative to formulation 1. Its confidence interval extends across zero, from a negative value to a positive value. That span indicates that the direction of the underlying difference is uncertain given the posted data and the interval method. The interval should be considered alongside the counts of 11 of 20 and 7 of 20, rather than relying on the point estimate alone.

As a general statistical explanation, a confidence interval communicates the range of effect values that remain reasonably compatible with observed data under the assumptions of the calculation. It is not a range containing a fixed proportion of individual participant outcomes, and it does not assign a probability to a particular effect value. The registry record does not report the confidence level or the method used to construct this interval. No confidence interval for the individual arm proportions is reported in the registry record.

The uncertainty is important in this study because each group includes 20 participants. With group sizes of this scale, the observed counts can be sensitive to a small number of participants. The interval’s inclusion of zero means the estimate does not precisely distinguish a reduction from an increase in the outcome proportion. It also does not prove that the groups are equivalent: an interval that crosses zero can still contain differences that may matter, and the registry record does not define an equivalence or non-inferiority margin.

Precision refers to uncertainty in the estimated group difference, not to the quality of the temperature measurement or the completeness of follow-up. Information on those matters, including missing observations and measurement procedures beyond the fever definition, is not reported 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 sample-size figures are planning illustrations based on the observed effect, not the trial’s own design justification. They give participants per arm for 80% power and participants per arm for 90% power. The calculation 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 set at the stated fraction of the observed effect.

At 100% of the observed effect, the illustration gives 96 participants per arm for 80% power and 128 participants per arm for 90% power. At 75% of the observed effect, it gives 173 participants per arm for 80% power and 231 participants per arm for 90% power. At 50% of the observed effect, it gives 392 participants per arm for 80% power and 524 participants per arm for 90% power. These are per-arm figures, not totals across both groups and not total event counts.

In general, power is the probability that a study will detect an effect of the size assumed if that effect is truly present, under the specified analysis assumptions. The 80% and 90% columns therefore describe different target probabilities for detecting the assumed effect. The higher target requires more participants in these illustrations. The rows also show that smaller effects need more participants to detect at the same target power.

These figures are not observed power. They are planning illustrations based on the observed effect and the stated assumptions. The registry record does not report the original sample-size justification or the assumptions used to choose the enrolled sample size. The illustrations should not be read as evidence that the trial was designed to meet those targets.

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 = 0.550; treatment proportion p₁ = 0.350; average p̄ = 0.450.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7036 = 1.3790.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6892 = 0.5800.
4. n = (1.3790 + 0.5800)² / (-0.2000)² = 95.9, rounded up to 96 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 <- 0.55                          # control proportion
p1 <- 0.35                          # 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(1096056)
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 = 96 (80% power), 128 (90% power)
 75% of observed effect: n per arm = 173 (80% power), 231 (90% power)
 50% of observed effect: n per arm = 392 (80% power), 524 (90% power)
power.prop.test: 95.9 
Simulated power at n = 96 per arm: 0.799 (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 14 outcome measures and 13 secondary outcomes posted. The secondary outcomes include HI antibody titers, seropositive, seroprotected, and seroconverted participant counts, HI antibody geometric mean fold rise, solicited local adverse events, their duration, and solicited general adverse events. The primary result described is the count of participants reporting fever of Grade 2 or higher.

When many outcomes or comparisons are assessed, the chance of obtaining at least one apparently unusual result can increase. As a general statistical point, multiplicity procedures may be used to control that risk, or outcomes may be treated as exploratory. The registry record does not report a multiplicity adjustment, a hierarchy among outcomes, or a plan distinguishing confirmatory from exploratory analyses. No claim about adjustment can therefore be made from the record.

No analysis entries are listed in the registry record. The posted primary counts allow an unadjusted recalculation of the comparison, but do not establish which analysis was prespecified or whether any other analyses were conducted. The statistical analysis plan, including approaches to repeated measurements or multiple endpoints, is not reported in the registry record.

The primary analysis population is identified as the Total Vaccinated cohort, which included subjects with vaccine administration documented. The record does not report how participants with missing outcome observations were handled, whether all randomized participants were included in every analysis, or whether any participants were excluded after randomization. It also does not report the number of missing observations for this endpoint. As a result, the posted counts cannot be used to infer a missing-data method or to confirm that follow-up was complete for every participant.

The record’s description of the Total Vaccinated cohort is specific to documented vaccine administration. It is not enough to determine how the analysis would compare with an intention-to-treat population or another analysis set. Those population definitions and analyses are not reported in the registry record.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: bronchopneumonia (5.0%), syncope (5.0%), tonsillitis (5.0%).

The registry lists serious adverse events for each group among 20 participants at risk: 0 affected participants in the formulation 1 group and 3 in the formulation 2 group. The record also lists other adverse events among 20 participants at risk: 19 affected in formulation 1 and 18 in formulation 2. These are group-level participant counts; the serious-event counts are not the primary fever endpoint.

The registry’s listed serious adverse event terms are Bronchopneumonia, Syncope, and Tonsillitis, each shown as 5.0%. The record does not assign these listed terms to a particular group or describe whether they occurred in distinct participants. They should not be added or otherwise combined to infer a participant total.

Counts of participants with serious adverse events and counts with other adverse events describe different safety summaries. They do not indicate, by themselves, the nature, timing, duration, relatedness, or outcome of each event. The registry record does not report deaths for these groups, and a null entry is not interpreted as a numeric death count. The record also lists solicited local and general adverse-event outcomes among the secondary measures, but those outcome results are not included in the posted results.

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

The posted primary data show that fever of Grade 2 or higher was recorded in 11 of 20 participants in the formulation 1 group and 7 of 20 in the formulation 2 group during the specified window. The unadjusted recalculated risk difference is -0.2 for formulation 2 relative to formulation 1, with an unadjusted p-value of 0.204. The confidence interval crosses zero, so the direction and size of the underlying difference remain uncertain.

This result describes the two regimens used in the trial. Formulation 1 was given in two GSK2186877A doses, while formulation 2 was given in one; both groups later received Fluarix at Month 6. The comparison cannot isolate the effect of formulation from the difference in dosing schedule. Nor does this fever outcome measure immune response. The listed immunogenicity outcomes require their own results and interpretation.

The data do not establish that the regimens are equivalent, that one is superior, or that the observed difference would recur in another study. A non-significant p-value does not demonstrate no difference. The confidence interval’s inclusion of zero expresses uncertainty, rather than proof that the true difference is zero. The record also does not state a threshold for a clinically important difference.

The findings apply to the enrolled healthy children 6 to 35 months of age and to the vaccine regimens and observation window recorded. They do not establish outcomes in other age groups, populations, or schedules. Safety is broader than the single primary fever measure, and the posted counts should not be taken as a complete account of every safety outcome. No medical advice or treatment conclusion follows from this statistical comparison.

16. Why This Trial Matters Statistically

This trial illustrates the distinction between an observed difference and a precisely estimated difference. The observed fever counts are 11 of 20 and 7 of 20, and the recalculated risk difference is negative for formulation 2 relative to formulation 1. Yet the confidence interval crosses zero, showing that these small groups do not determine the direction of the underlying difference with precision.

For clinical researchers, this is a useful reminder that a point estimate, p-value, and interval answer different questions. The point estimate describes the observed contrast. The p-value describes compatibility with a null model under a test’s assumptions. The confidence interval conveys uncertainty around the effect estimate. None of these alone establishes clinical importance, and the registry record does not report a threshold defining a meaningful difference.

The trial also illustrates why the comparison must be interpreted in light of the regimens. The groups differed in the GSK2186877A formulation and in whether one or two doses were given, while both received Fluarix later. An outcome contrast between those groups cannot separate the effects of those regimen components. The same caution applies to other outcomes: safety and immunogenicity are related purposes of the study, but the fever finding does not answer the immunogenicity question.

Finally, planning calculations based on the observed effect can demonstrate how sample-size requirements change as the target effect changes. They are not a record of the trial’s original design rationale and are not observed power. Distinguishing these planning illustrations from a trial’s actual design assumptions is important when assessing what a small study can and cannot establish.

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 study enrolled 40 participants, with 20 in each group. This limits the precision of the primary comparison, as reflected by a confidence interval that includes zero and extends in both directions. The trial is identified as Phase 1; the record’s stated purpose includes safety and immunogenicity, and the posted primary result addresses one fever outcome. The registry record does not report the original rationale for the sample size.

The regimens differ in more than formulation: formulation 1 involved two GSK2186877A doses and formulation 2 one dose. Both groups received Fluarix at Month 6. Therefore, the observed comparison cannot attribute any difference solely to formulation. The observation window is defined as within 7 days following any GSK2186877A vaccination, and does not summarize safety beyond that outcome and interval.

The record does not report the statistical analysis plan, the method used for the confidence interval, the confidence level, the original sample-size assumptions, or how missing data were handled. It also does not report detailed results for the listed immunogenicity and other adverse-event outcomes. The presence of an outcome in the registry listing should not be mistaken for a result.

The study was unmasked, and the registry record does not provide further details on outcome assessment or implementation of randomization. These omissions limit assessment of potential bias and analysis choices. The findings are specific to healthy children 6 to 35 months of age and the regimens described; the record does not establish how they apply beyond this study population.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Trial to Evaluate the Safety and the Immunogenicity of GSK Biologicals' Influenza Vaccine GSK2186877A in Healthy Children — NCT01096056.
• Registry record last updated 2018-09-24; status last verified 2016-09.
• Results first posted 2012-05-10.
• 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

NCT01096056 is a completed randomized, unmasked, parallel-group Phase 1 study of GSK2186877A in healthy children 6 to 35 months of age. It enrolled 40 participants. One group received two doses of formulation 1 and later Fluarix; the other received one dose of formulation 2 and later Fluarix.

The primary outcome was the number of participants reporting fever of Grade 2 or higher within 7 days following any GSK2186877A vaccination. The registry reports 11 of 20 participants in formulation 1 and 7 of 20 in formulation 2. The unadjusted recalculated risk difference is -0.2, with an unadjusted p-value of 0.204; the confidence interval crosses zero.

The registry also lists immunogenicity and additional safety outcomes. The statistical analysis plan, original sample-size justification, and missing-data methods are not reported in the registry record.