Development of Childhood Anti-Influenza Immunity: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Development of Childhood Anti-Influenza Immunity (NCT03673345), a non-randomized phase 4 study. The primary outcome is Frequency of CD4 T Cells With a Given Functional Potential.

2. Clinical Question

3. Trial Design

The registry lists this as a completed Phase 4, non-randomized, parallel study with no masking. It was sponsored by the National Institute of Allergy and Infectious Diseases. The recorded start date is 2018-09-25, and the primary completion date is 2020-12-22. The study summary describes prospective surveillance over 2 influenza seasons plus 1 optional season at one domestic site.

The cohorts reflect different exposure histories and age groups. The study summary describes children receiving inactivated influenza vaccine and children presenting with natural influenza infection before vaccination. The arm descriptions further distinguish cohorts by age or birth period, previous vaccination, and infection during the first study year. Vaccine schedules differ across these groups; the registry describes age-appropriate doses and administration schedules rather than a single uniform regimen for all participants.

The registry lists enrollment as 125. The brief summary describes a plan for approximately 220 participants, with 140 children in vaccination cohorts and 80 in infection cohorts. These enrollment descriptions differ, and the registry record does not explain the discrepancy. The arm descriptions include Cohort 4B, but the primary outcome record states that participants could not be enrolled into that cohort.

Because exposure history determined cohort membership, differences in outcomes between cohorts would not by themselves establish that vaccination or infection caused those differences. The registry record does not report random assignment, masking, or a randomized control group. It also does not report a statistical analysis plan, methods for addressing differences between cohorts, or a rationale for the enrollment target.

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.

Only the first 6 of 8 groups are shown.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Unable to enroll participants into Cohort 4B

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: Unable to enroll in participants in Cohort 4B

Only the first 6 of 9 groups are shown.

6. Primary Endpoint

The registry lists the primary outcome as Frequency of CD4 T Cells With a Given Functional Potential, measured over Year 2 (Visit 5).

The primary outcome is the frequency of CD4 T cells with a specified functional potential, expressed as a percentage. More specifically, it is the percent of ICOS/PD1-expressing cells within the CXCR5-positive CD4 T-cell population, assessed at Year 2, Visit 5. The registry specifies a mean and standard deviation as the summary format.

As general background, a cell-frequency measure describes the proportion of cells meeting a defined marker profile within a selected parent population. Here, the outcome focuses on marker expression within a particular CD4 T-cell subset. Such a measure can characterize an aspect of immune-cell response; it is not, by itself, a direct measure of clinical protection or of the full immune response described in the study hypothesis.

The endpoint is relevant to the study’s interest in how previous exposures relate to immune reactivity. However, the hypothesis also refers to specificity, magnitude, and functionality across CD4 T-cell and B-cell responses, while the registered primary outcome is one percentage measure in a CD4 T-cell population. The registry record does not report the endpoint’s observed mean, standard deviation, number of participants measured, or a comparison between exposure cohorts. It states that Cohort 4B could not be enrolled, but does not give further information about the endpoint population or other missing measurements.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry describes a continuous outcome summarized as a mean and standard deviation. These statistics answer different questions. The mean describes the average measured percentage in a group, while the standard deviation describes the spread of individual measurements around that average. Neither statistic alone establishes whether groups differ or how precisely a difference has been estimated.

What would a confidence interval contribute?

As general statistical explanation, a confidence interval gives a range of values compatible with the data and the assumptions of the analysis. A narrow interval indicates greater precision than a wide interval, though precision does not determine whether a result is clinically important or free of bias. No confidence interval for the primary endpoint is reported in the registry record, so its precision cannot be assessed from the posted results.

What does a comparison require?

A comparison would need to define which cohorts are being contrasted, what outcome summary is being estimated, and how the analysis handles the study design. In a randomized study, treatment assignment can support a direct comparison under the planned analysis. In this non-randomized study, cohorts differ by exposure history and may also differ in other characteristics. As general background, an unadjusted difference in group means describes the observed groups, but it does not isolate an exposure effect when other relevant characteristics are imbalanced. The registry record does not report a specified contrast, adjusted model, or analysis result.

Why is the design important?

The parallel cohort structure organizes participants into groups followed within the study, but it does not make the groups exchangeable. Children with a prior infection, prior vaccination, or differing ages and birth periods entered distinct cohorts. Such factors are integral to the study question, but they also mean that a cohort contrast may reflect several differences together. General statistical methods for observational comparisons may include adjustment or stratification, but the registry record does not report whether either approach was used.

What can the planning illustration say?

As general explanation, a sample-size calculation estimates the amount of information that might be needed to detect a specified effect under stated assumptions. The planning illustration described for this analysis uses a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect set as a stated fraction of the observed effect. Such figures are planning illustrations, not observed power and not evidence that the study was designed with those assumptions. Equal allocation between two arms does not describe every feature of the study’s multiple exposure-history cohorts. The registry record does not report the trial’s own sample-size justification or confirm that the illustration’s assumptions were part of the study design.

Why does over-dispersion matter?

As general statistical explanation, over-dispersion occurs when observed variability exceeds what a model assumes. If a model understates variability, standard errors may be too small and confidence intervals too narrow. The registered endpoint is a percentage, but the registry record does not describe a fitted model, its distributional assumptions, or a check for over-dispersion. It is therefore not possible to assess whether this issue arose or how it was handled.

What is recalculation?

When a recalculation is available, it is a simple unadjusted re-analysis of posted summary statistics and is not a substitute for the sponsor’s own analysis. If the recalculated value conflicts with the sponsor’s result, the sponsor’s own analysis takes precedence. The registry record lists no analyses and reports no endpoint summary statistics, so no recalculation can be interpreted from this record.

10. Confidence Intervals for Each Arm

No two-arm comparison is shown for this trial, but each arm's mean can be given with a t-based 95% confidence interval computed from the posted mean, spread and number of participants.

R code and output

arm <- c("Cohort 1A", "Cohort 1B", "Cohort 2A", "Cohort 2B", "Cohort 3A", "Cohort 3B")
n   <- c(2, 3, 42, 6, 18, 6)
m   <- c(0.7, 0.55, 0.52, 0.38, 0.4, 0.34)
sp  <- c(0.24, 0.31, 0.32, 0.27, 0.37, 0.17)
sd  <- sp      # posted standard deviations
for (i in seq_along(n)) {
  se <- sd[i] / sqrt(n[i]); h <- qt(0.975, n[i] - 1) * se
  cat(sprintf("CARM|%s|%d|%.3f|%.3f|%.3f|%.3f\n", arm[i], n[i], m[i], sd[i], m[i] - h, m[i] + h))
}

CARM  Cohort 1A  2  0.700  0.240  -1.456  2.856
CARM  Cohort 1B  3  0.550  0.310  -0.220  1.320
CARM  Cohort 2A  42  0.520  0.320  0.420  0.620
CARM  Cohort 2B  6  0.380  0.270  0.097  0.663
CARM  Cohort 3A  18  0.400  0.370  0.216  0.584
CARM  Cohort 3B  6  0.340  0.170  0.162  0.518

11. Multiplicity, Missing Data and Analysis Populations

The study hypothesis covers several dimensions of immune reactivity, including specificity, magnitude, and functionality, and refers to both CD4 T-cell and B-cell responses. The registry lists one primary outcome measure, but it does not report how other outcomes or multiple cohort contrasts were handled. A multiplicity strategy, such as prioritizing a single contrast or adjusting inference across several comparisons, is not reported in the registry record.

Missing-data methods are also not reported in the registry record. The primary outcome population is described as unable to enroll participants into Cohort 4B. That statement identifies a cohort enrollment issue, but does not provide a participant flow, the number of measurements obtained, reasons for any missing endpoint values, or methods for handling missing observations. It is not possible to infer whether missingness occurred in other cohorts or how it affected any analysis.

The registry record does not define an analysis population, such as a population based on all enrolled participants or only those with endpoint measurements. It also does not report whether exclusions, protocol deviations, or incomplete follow-up were considered. These details matter because the participants contributing measurements may not represent every participant initially enrolled or intended for a cohort.

Without reported analysis methods and results, neither multiplicity control nor the influence of missing data can be evaluated. The record also does not report interim analyses or a prespecified statistical plan. Those aspects are not reported in the registry record and should not be assumed from the study design or from the stated hypothesis.

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

The registry record establishes that the study was designed to examine immune responses in children with differing influenza exposure histories and that a percentage-based CD4 T-cell outcome was designated as primary. It does not establish what that endpoint showed: numerical outcome results and statistical comparisons are not reported in the registry record. Accordingly, the posted information supports describing the study question and design, but not drawing a conclusion about the direction, size, or precision of any cohort difference.

The study’s non-randomized structure is important to interpretation. As general statistical context, an observed difference between cohorts in an observational study may reflect the exposure of interest, other differences between participants, or a combination. The registry record does not report an adjusted analysis that would help distinguish these possibilities. The stated hypothesis should therefore be understood as the question the study set out to examine, not as a finding.

The primary endpoint is a cellular percentage, rather than a direct clinical outcome. A measurement of immune-cell markers may describe a particular aspect of immune response, but the registry record does not report how it relates to clinical protection, and the endpoint alone would not establish that relationship. No medical conclusion about vaccination or infection follows from the information recorded.

Finally, zero entries in the adverse-event categories do not demonstrate an absence of events because the listed numbers at risk are also zero. The record’s enrollment descriptions differ, and Cohort 4B could not be enrolled; the implications for analyses are not reported. These limitations leave the study’s quantitative findings and their generalizability unclear in the registry record.

13. Why This Trial Matters Statistically

This study is statistically notable for asking about immune responses across distinct histories of influenza vaccination and infection in children, while using a non-randomized cohort design. That combination makes the distinction between describing group patterns and estimating an exposure effect especially important. Cohort differences may be informative about the study question, but their interpretation depends on the design and on analysis methods that are not reported in the registry record.

The primary outcome also illustrates the difference between a biological measurement and a clinical endpoint. The registered measure is a percentage within a defined CD4 T-cell population, while the stated hypothesis spans broader features of CD4 T-cell and B-cell reactivity. Clear specification of the exact measurement helps define what the primary outcome can address, while also marking the limits of what that measure represents.

For statistical readers, the record highlights why reporting matters as much as design. Without outcome summaries, estimates, uncertainty intervals, or analysis methods, readers cannot assess the magnitude, precision, or robustness of findings. The difference between the registry enrollment figure and the approximate enrollment described in the study summary, along with the inability to enroll Cohort 4B, further underscores the value of transparent participant-flow and analysis-population reporting.

The record therefore offers a useful example of how to distinguish a research hypothesis, a registered endpoint, and an interpretable result. The first two are described; the last is not reported in the registry record.

14. 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 main limitation for interpreting the registered primary outcome is the absence of reported results. The record gives the measure and assessment time but not the observed mean, standard deviation, number analyzed, estimated differences, confidence intervals, or p-values. The registry also lists no analyses, so no inferential result can be evaluated.

The non-randomized design limits causal interpretation of any cohort differences. Groups are defined by age and prior exposure histories, and the registry record does not report methods for controlling potential differences between them. Masking is listed as none. The record does not explain whether measurement procedures or outcome assessment were protected from knowledge of cohort membership.

The enrollment information is not internally reconciled: the registry lists 125, while the brief summary describes approximately 220 planned participants. Cohort 4B could not be enrolled, but the record does not detail how that affected the endpoint population or intended comparisons. Participant flow, cohort-specific enrollment totals for all groups, and the numbers with endpoint data are not reported in the registry record.

Other important details are also absent, including the statistical analysis plan, sample-size justification, handling of multiplicity, missing-data methods, and any adjustments or sensitivity analyses. The adverse-event entries list zero values alongside zero numbers at risk, which prevents meaningful interpretation as event evidence. These limitations arise from what the registry record reports and should not be filled in by assumption.

15. Related Tutorials

16. Related Statistical Calculators

17. Sources

• ClinicalTrials.gov: Development of Childhood Anti-Influenza Immunity — NCT03673345.
• Registry record last updated 2022-03-18; status last verified 2021-03-29.
• Results first posted 2022-03-18.
• 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.

18. Record Summary

NCT03673345, titled “Development of Childhood Anti-Influenza Immunity,” is recorded as a completed Phase 4, non-randomized, parallel study with no masking. It concerns children grouped by influenza vaccination and infection histories, with quadrivalent inactivated vaccine used in the vaccination cohorts. The study summary describes surveillance over 2 influenza seasons plus 1 optional season at one domestic site.

The primary outcome is the percentage of ICOS/PD1-expressing cells within the CXCR5-positive CD4 T-cell population at Year 2, Visit 5, summarized as a mean and standard deviation. The registry lists enrollment as 125, while the brief summary describes approximately 220 planned participants. The primary outcome record notes that Cohort 4B could not be enrolled.

Numerical outcome results, statistical analyses, and methods for missing data or multiplicity are not reported in the registry record. The record therefore describes the study question and endpoint, but does not provide a quantitative basis for interpreting differences between cohorts.