Beta-glucan and Immune Response to Influenza Vaccine: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Beta-glucan and Immune Response to Influenza Vaccine (NCT05074303), a randomized phase 2 study. The primary outcome is Antibody Titer.

2. Clinical Question

In plain terms, the research question is whether assignment to beta-glucan supplementation was associated with a different measured antibody response after influenza vaccination than assignment to cellulose placebo. Randomization establishes the planned comparison, but it does not by itself show whether the groups’ observed outcomes differed or how precisely any difference was estimated. Those conclusions require outcome data and an analysis of the groups’ results.

The study also listed inflammatory cytokine profile, influenza and Covid-19 incidence, fever, and cold and flu symptoms as secondary outcomes. Those outcomes address other aspects of immune response or illness; they are not substitutes for the primary antibody-titer comparison. The registry record does not provide results for them in the information.

3. Trial Design

The registry identifies this as a Phase 2, randomized, triple-masked, parallel-group study. Participants were assigned to beta-glucan or placebo, and both groups received an influenza vaccine. The planned supplement regimens were 500 mg/day beta-glucan and 500 mg/day cellulose placebo. The sponsor was the University of Florida. The trial is listed as completed.

The record reports enrollment of 78 participants: 38 assigned to beta-glucan and 40 to placebo. These are the randomized group counts across two vaccination seasons. They are not the counts available for the primary antibody analysis. The registry states that the antibody titer could be analyzed only in Season 1 because the influenza antigen source was ineffective for the other season. It gives the Season 1 analysis groups as 24 for beta-glucan and 19 for placebo.

That distinction matters when interpreting any group comparison. Randomized counts describe assignment, while an endpoint analysis may involve a narrower set of participants when outcome data are unavailable or unusable. The registry explains the season restriction, but the information available does not detail participant-level reasons for inclusion or exclusion beyond the ineffective antigen source. Further details about missing observations and the analysis population are not reported in the registry record.

The primary outcome is continuous: antibody titer, reported as a mean with standard deviation. The registry describes the measurement as a change from the mean of Day -14 and Day 0 to Day 28, with a timeframe of 42 days. No numerical primary-outcome results or analysis estimates are reported in the registry record. The record also lists five outcome measures and zero analyses, so it does not provide a reported inferential analysis that resolves the primary comparison.

Although randomization and masking are important design features, they do not answer questions about the exact statistical model, handling of missing data, or multiplicity. Those details are not reported in the registry record. The stated design should therefore be distinguished from an analysis plan: the former is described, while the latter cannot be reconstructed from the available 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

Analysis population for the primary outcome, as defined in the registry: A total of 40 participants were randomized to the placebo group and 38 to the beta-glucan group over two vaccination seasons. However, the antibody titer could only be analyzed in Season 1 (19 to placebo and 24 to beta-glucan) due to an ineffective influenza antigen source, which explains the discrepancy.

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 Antibody Titer, measured over 42 days (mean of Day -14 and 0 compared to Day 28).

The primary endpoint is influenza A antibody titer after vaccination, with the registry describing change between the mean of measurements on Day -14 and Day 0 and the measurement on Day 28. Titer is a continuous measure, and the record states that its scale runs from 0 to 1024, with higher titer indicating a stronger immune response. The endpoint therefore represents a laboratory measure of vaccine-associated antibody response, rather than a direct measure of illness or symptoms.

Using a continuous endpoint can preserve information across the measured scale instead of reducing outcomes to categories such as response or no response. Reporting a mean describes the group’s average measured value or change; a standard deviation describes how dispersed individual values are around that mean. These answer different questions: the mean concerns the group’s central level, while the standard deviation concerns variation among participants.

The endpoint’s timing gives a reference period and a later measurement for assessing change. However, the exact calculation and statistical comparison are not fully specified beyond the registry’s description. The record does not report the actual mean changes, standard deviations, contrast between groups, confidence interval, or p-value. As a result, the direction, size, and precision of the primary comparison are not available in the registry record.

As general statistical context, antibody titers can be variable across individuals. A group average alone would not show how much participants differed, and a difference between group averages would need an uncertainty estimate to indicate its precision. Neither the observed group summaries nor such an uncertainty estimate is reported for this endpoint.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is a continuous measurement summarized by a mean and standard deviation. The registry calls the measure antibody titer and describes change from the mean of Day -14 and Day 0 to Day 28. It does not report numerical outcome summaries or identify the statistical test or model used for a group comparison. The explanations below are general statistical context, not a description of an analysis confirmed for this trial.

What does a mean describe?

A mean is a measure of the center of a set of observations. For a continuous outcome, it can summarize the average level or average change in a group. Comparing group means is one way to express a difference between assigned groups, but a mean does not convey how widely individual observations vary. The registry’s choice to describe the endpoint using a mean is consistent with a continuous outcome, but the actual means are not reported in the registry record.

What does a standard deviation add?

A standard deviation describes the spread of observations around the mean. A larger spread indicates more variation among observed values; it is not the same as uncertainty in the estimated mean or uncertainty in a comparison. The standard deviation is useful for understanding the distribution of participant measurements, while a confidence interval for a mean or contrast would address estimation precision. The record identifies standard deviation as the dispersion measure but supplies no numerical standard deviations for the primary endpoint.

How should a treatment contrast be read?

In a randomized parallel-group comparison, an effect estimate might express the difference in average change between the assigned groups. The estimate’s sign depends on the order in which groups are subtracted, so interpretation requires knowing the reported contrast definition. A contrast should be read together with its uncertainty interval and analysis assumptions. No contrast, interval, or inferential test for the antibody outcome is reported in the registry record, and the subtraction convention is not reported there either.

What does a confidence interval mean?

As general explanation, a confidence interval represents uncertainty around an estimated quantity under a specified statistical procedure. A narrow interval indicates greater precision than a wide interval, conditional on the model and assumptions. It is not a range guaranteed to contain the true value in an individual study, and it does not establish clinical importance by itself. Since no confidence interval is reported for the primary comparison, its precision cannot be assessed from the registry record.

Why can variability affect precision?

General statistical reasoning links precision to the amount of information in the data and the variability of observations. More variation can make a group contrast less precise if other aspects of the design are unchanged. A smaller analyzable population can also limit precision. These are general principles, not trial-specific estimates. The record reports a season-specific restriction, but it does not provide the observed variability or a numerical uncertainty estimate with which to quantify its effect.

What is over-dispersion?

As general context, over-dispersion occurs when observed variability is greater than a statistical model assumes. It can make model-based standard errors too small if the extra variation is not addressed, which in turn can make confidence intervals too narrow and tests too optimistic. This concept is especially discussed for count data, though variation and model fit matter more broadly. The primary endpoint is continuous, and the registry does not report a fitted model or any assessment of over-dispersion. It would therefore be inappropriate to claim that over-dispersion was present or that a particular adjustment was used.

What is the role of the endpoint time points?

The registry describes a baseline reference based on the mean of Day -14 and Day 0, followed by a Day 28 measurement, and labels the timeframe as 42 days. Comparing change can account for starting measurements, but details matter: the formula for change, handling of incomplete baseline measurements, and statistical adjustment are not specified in the information reported. The endpoint description alone does not establish which model or test was used.

What can a p-value establish?

As general explanation, a p-value is calculated under a null hypothesis and a statistical model. It describes how compatible the observed data are with that null model, not the probability that the null hypothesis is true and not the probability that a result occurred by chance in a colloquial sense. It also does not state the size or importance of an effect. No primary-outcome p-value is reported in the registry record.

Are sample-size calculations the same as trial results?

No. A planning calculation estimates the number of participants per arm that might be needed under chosen assumptions for a target power and effect. It is not an observed outcome and does not show that a completed study had a particular probability of detecting its true effect. The record describes a planning illustration based on a fraction of an observed effect, with a two-sided significance level of 0.05, equal allocation, and a normal approximation. The numerical planning outputs are not stated in the registry information, and the illustration is not the trial’s own design justification. The record does not report a sample-size justification or observed power.

10. Multiplicity, Missing Data and Analysis Populations

The registry lists five outcome measures and names secondary outcomes concerning inflammatory cytokine profile, influenza and Covid-19 incidence, fever, and cold and flu symptoms. Multiple outcomes or time points can create a multiplicity problem: when many hypotheses are tested, the chance of at least one apparently unusual result can increase. As general statistical context, an analysis plan may address this by defining a primary comparison, ordering tests, or adjusting inference. The registry does not report a multiplicity adjustment or a statistical hierarchy for the listed outcomes.

The primary outcome is described as having several categories or time points and not being reduced to one comparison. That makes it difficult to identify a single inferential result from the registry record. The specific comparisons, any adjustment for multiple testing, and any planned handling of repeated measurements are not reported in the registry record. It would be inappropriate to assume that a particular correction or testing strategy was used.

Missing or unusable data are relevant because the registry says antibody titers could be analyzed only in Season 1, due to an ineffective influenza antigen source. It reports the Season 1 analysis-group counts as 19 for placebo and 24 for beta-glucan, compared with randomized counts of 40 and 38 across the two seasons. The record does not describe further missing-data methods, participant-level exclusions, imputation, or sensitivity analyses. It also does not state whether the endpoint analysis followed intention-to-treat, per-protocol, or another population definition. These items are not reported in the registry record.

As general context, missing-data assumptions can affect estimates if the availability of measurements is related to outcomes or participant characteristics. A sensitivity analysis can test whether conclusions change under alternative assumptions, but no such analysis is reported. The season restriction is explained, yet the record does not provide enough information to evaluate its statistical consequences beyond recognizing that the primary endpoint was not analyzed across both seasons.

11. 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 0% reporting threshold.

The registry reports serious adverse events for the beta-glucan and placebo groups. It lists 0 serious adverse events among 38 participants at risk in the beta-glucan group, and 0 among 40 participants at risk in the placebo group. The record also lists 0 other adverse events in each group and 0 deaths in each group. These are the reported counts; they are not estimates of comparative risk.

As general statistical context, observing zero events does not prove that an event cannot occur or that two groups have identical safety profiles. The interpretation of zero counts depends on the number of people observed, the duration and completeness of follow-up, how events were defined, and how they were collected. The registry information does not provide enough detail to assess those aspects or to estimate a comparative safety effect.

The serious-event counts should also be distinguished from the study’s listed secondary outcomes, such as fever and cold and flu symptoms. Those outcomes are not the same as serious adverse events. The registry’s zero counts do not establish the absence of all possible harms, and they do not support a general safety conclusion. They report only the adverse-event figures recorded for these groups in the registry.

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

The record establishes that this was a randomized, triple-masked, parallel-group Phase 2 study of beta-glucan supplementation compared with cellulose placebo in the setting of influenza vaccination. It describes the primary endpoint as change in influenza A antibody titer, using the mean of Day -14 and Day 0 as the reference and a Day 28 measurement. It also explains that only Season 1 titers could be analyzed because the antigen source in the other season was ineffective.

Those design details do not reveal the study’s primary result. The registry record does not report the observed antibody-titer means, standard deviations, between-group estimate, confidence interval, or p-value. It therefore does not show whether the measured response was higher or lower in either group, how large any difference was, or how precisely it was estimated. No conclusion about the primary comparison should be inferred from the randomized group counts alone.

As general statistical context, an estimate’s magnitude, uncertainty, and relevance are separate considerations. A point estimate describes the observed contrast; an interval describes its precision under an analysis; and interpretation also depends on the endpoint’s meaning and the study population. Here, the numerical estimate and its uncertainty are not reported, so those considerations cannot be applied to the primary outcome.

The registry lists zero serious adverse events, zero other adverse events, and zero deaths in both groups. These figures describe the posted counts, not proof that no adverse event could occur or that the groups have equivalent safety. The record also lists secondary outcomes, but it does not report their results in the information.

Accordingly, the defensible reading is narrow: the registry describes the study design, endpoint, season-related analysis restriction, and adverse-event counts, but it does not provide the primary efficacy result. The absence of a reported endpoint result is not evidence that the groups had the same response, nor evidence that one group had a better response. It means the comparative antibody result cannot be evaluated from the registry record.

13. Why This Trial Matters Statistically

This study illustrates why a trial’s design and its reported results must be read separately. Randomization and masking describe safeguards in the planned comparison, but a reader still needs endpoint estimates and uncertainty to assess what the data show. Without those statistics, the central comparative question remains unanswered in the registry record, even though the study is listed as completed.

The season-specific restriction is statistically important because the full randomized groups and the endpoint-analysis groups are not the same. The record says the antigen source was ineffective in one season and that only Season 1 titers could be analyzed. This makes clear why randomized enrollment should not automatically be treated as the analysis population for every outcome. It also highlights the value of reporting which observations contribute to each endpoint and how exclusions or unusable measurements are handled.

The endpoint itself raises another general lesson: continuous outcomes are most informative when results include both a measure of central tendency and a measure of uncertainty. A mean and standard deviation describe different aspects of the data, while a between-group estimate and confidence interval would address the comparative question and its precision. The record identifies mean and standard deviation as the outcome summary but does not report their values or the inferential comparison.

Finally, several outcomes and time points make clarity about multiplicity and the primary contrast important. The registry does not report a statistical plan or a single reduced comparison for the primary outcome. This limits readers’ ability to distinguish planned inference from exploratory comparisons. The trial is therefore useful as an example of how endpoint definitions, analysis populations, uncertainty, and transparent reporting all shape statistical interpretation.

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 principal limitation for interpreting this trial from the registry record is that it does not report numerical results for the primary antibody-titer endpoint. The group means, standard deviations, treatment contrast, confidence interval, and p-value are not reported. Without them, neither the observed direction nor the size and precision of the comparison can be assessed.

The registry states that antibody titer could be analyzed only in Season 1 because the influenza antigen source was ineffective in the other season. Although it reports the Season 1 group counts, it does not provide the endpoint values for those participants or explain any additional missing measurements. The consequences of limiting the endpoint analysis to one season cannot be quantified from the information reported.

The registry describes the outcome as change from the mean of Day -14 and Day 0 to Day 28, but the exact computational definition and inferential method are not reported. Further details about covariate adjustment, missing-data handling, analysis populations, and sensitivity analyses are also not reported in the registry record. No statistical analysis plan or sample-size justification is reported there.

Multiple outcomes and time points are listed, while the primary outcome is noted as not reduced to one comparison. The record does not state how multiplicity was handled or which specific contrast was designated for inference. Finally, the adverse-event counts are reported without enough follow-up or ascertainment detail to support broad conclusions about safety. These limitations concern what can be learned from the registry information; they do not establish what the complete study report may contain.

15. Related Tutorials

16. Related Statistical Calculators

17. Sources

• ClinicalTrials.gov: Beta-glucan and Immune Response to Influenza Vaccine — NCT05074303.
• Registry record last updated 2025-11-06; status last verified 2025-09.
• Results first posted 2025-03-24.
• 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.

18. Record Summary

The registry identifies NCT05074303 as a completed Phase 2 randomized, triple-masked, parallel-group study sponsored by the University of Florida. It enrolled 78 participants described as healthy adults. The beta-glucan group received 500 mg/day beta-glucan, and the placebo group received 500 mg/day cellulose. Both groups were studied in the context of influenza vaccination.

The primary endpoint was influenza A antibody titer, described as change from the mean of Day -14 and Day 0 to Day 28. The registry states that titers could be analyzed only in Season 1 because the antigen source was ineffective in the other season. It reports Season 1 analysis groups of 24 for beta-glucan and 19 for placebo, but no numerical primary-outcome results or inferential comparison.

The registry lists secondary outcomes involving cytokines, influenza and Covid-19 incidence, fever, and cold and flu symptoms. It reports 0 serious adverse events, 0 other adverse events, and 0 deaths in each group. The statistical analysis plan, multiplicity approach, and further missing-data methods are not reported in the registry record.