Safety and Immunogenicity of the Bris10 M2SR and Sing2016 M2SR H3N2 Monovalent Influenza Vaccines: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Safety and Immunogenicity of the Bris10 M2SR and Sing2016 M2SR H3N2 Monovalent Influenza Vaccines (NCT03999554), a randomized phase 1 study. The primary outcome is Number of Participants With Local and Systemic Adverse Events (AEs) Through 29 Days Post-vaccination With Bris10 M2SR and Cumulatively Through Day 209.

2. Clinical Question

The trial’s primary objective was to assess safety and reactogenicity of a monovalent live single-replication influenza H3N2 M2SR vaccine. Immunogenicity was also examined through secondary outcomes concerning seroconversion and mucosal responses to vaccine HA. These are distinct questions: adverse-event counts describe reported safety outcomes, while immune-response percentages describe measured responses to vaccination. Neither type of result alone establishes prevention of influenza.

The registry’s brief summary frames the study as a dose-escalation investigation of safety, tolerability/reactogenicity, and immunogenicity. Its stated rationale includes evaluating higher dosages or two administrations. The study record does not report clinical influenza prevention as an outcome in the posted results.

3. Trial Design

This was a randomized, quadruple-masked, parallel Phase 1b study with a placebo control. The registry lists enrollment as 206 and status as completed. It records a start date of 2019-09-03 and primary completion on 2020-07-01. The brief summary describes 250 healthy adults aged 18–49, while the enrollment field records 206; the registry record does not explain the difference.

Five groups are described: low-, medium-, and high-dose Sing2016 M2SR; low-dose Bris10 M2SR; and placebo. The arm descriptions state that each intervention was administered intranasally on days 1 and 29, with saline used for placebo. The brief summary describes two administrations 28 days apart. Allocation is recorded as randomized, but the randomization procedure and details of sequence generation are not reported in the registry record.

The primary posted comparison is low-dose Bris10 M2SR versus placebo. The primary outcome title concerns participants with local and systemic adverse events through 29 days post-vaccination and cumulatively through Day 209. The outcome description refers to vaccine-associated adverse events and serious adverse events after Bris10 M2SR or placebo administration. Secondary result entries concern seroconversion and mucosal responses, with their stated timeframe extending from baseline through 28 days post-dose 1 (Day 29).

The record does not report the trial’s original sample-size justification or detailed statistical analysis plan. It also does not report how masking was implemented, whether any interim analyses occurred, or the methods used to address missing outcome data.

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: Study participants who received at least one inoculation were included.

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 Participants With Local and Systemic Adverse Events (AEs) Through 29 Days Post-vaccination With Bris10 M2SR and Cumulatively Through Day 209, measured over From baseline through study completion (Day 209).

The primary outcome is the number of participants with local and systemic adverse events, described as assessed through 29 days post-vaccination with Bris10 M2SR and cumulatively through Day 209. The outcome description says that adverse events and serious adverse events after Bris10 M2SR or placebo administration were recorded to determine the number and percentage of participants experiencing them. The stated timeframe is from baseline through study completion (Day 209).

For the posted primary comparison, the registry reports 28 participants in the low-dose Bris10 M2SR group and 24 in the placebo group with the outcome, among 42 and 41 participants, respectively. These are participant counts, not counts of every individual event. A participant may experience more than one event, but the registry’s primary result is expressed as participants with the outcome.

Adverse-event outcomes are used in early-phase trials to describe the observed safety and reactogenicity profile over the stated follow-up. Comparing counts across randomized groups can show how often the recorded outcome occurred in each group. Such a comparison is descriptive and remains subject to uncertainty, particularly when group sizes are limited. The registry does not provide a detailed definition of each event, its severity grading, or attribution rules beyond the outcome description.

7. Results Posted in the Registry

• Low Dose Bris10 M2SR: 66.7% (28/42) versus 58.5% (24/41) on control; risk difference 8.1 percentage points (95% CI -12.6 to 28.9), risk ratio 1.14 (0.81–1.59); unadjusted two-proportion z-test p = 0.444.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Percentage of Bris10 M2SR Subjects Demonstrating Seroconversion to Vaccine HA

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Low Dose Bris10 M2SR: 28.9% (11/38) versus 10.5% (4/38) on control; risk difference 18.4 percentage points (95% CI 1.0 to 35.8), risk ratio 2.75 (0.96–7.88); unadjusted two-proportion z-test p = 0.044.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Low Dose Bris10 M2SR than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percentage of Sing2016 M2SR Subjects Demonstrating Seroconversion to Vaccine HA

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Low Dose Sing2016 M2SR: 27.5% (11/40) versus 0.0% (0/38) on control; risk difference 27.5 percentage points (95% CI 13.7 to 41.3); unadjusted two-proportion z-test p = <0.001.
  • Medium Dose Sing2016 M2SR: 36.8% (14/38) versus 0.0% (0/38) on control; risk difference 36.8 percentage points (95% CI 21.5 to 52.2); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Low Dose Sing2016 M2SR than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Medium Dose Sing2016 M2SR than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percentage of Bris10 M2SR Subjects Demonstrating Mucosal Responses to Vaccine HA

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Low Dose Bris10 M2SR: 22.2% (8/36) versus 25.0% (9/36) on control; risk difference -2.8 percentage points (95% CI -22.4 to 16.8), risk ratio 0.89 (0.39–2.04); unadjusted two-proportion z-test p = 0.781.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Low Dose Bris10 M2SR and the control. The interval gives the range of effects that remain compatible with the data.

The secondary results concern two kinds of immune response: seroconversion to vaccine HA and mucosal responses to vaccine HA. The posted percentages and comparison estimates vary across outcomes and groups. The registry lists several secondary outcome measures, but only three secondary result entries are posted. The full set of planned analyses and the reason some measures lack posted results are not reported in the registry record.

These outcomes complement the primary adverse-event count by describing immunogenicity, not by measuring the same clinical or safety construct. A measured immune response can inform an understanding of biological response to a vaccine, but the posted secondary outcomes do not establish prevention of influenza. They also cannot be substituted for the primary safety outcome or interpreted as proof of benefit.

Unadjusted secondary results carry less weight when many outcomes or comparisons are considered. With multiple tests, the chance of at least one apparently unusual result can increase, even if all null hypotheses are true. In general, a prespecified multiplicity strategy can help manage this issue, but no such strategy is reported in the registry record. The secondary p-values should therefore be treated as exploratory rather than as a set of definitive confirmatory findings.

Interpretation should also account for the differing analysis denominators reported for secondary measures. The registry does not explain all differences between those denominators and the primary groups, nor does it report missing-data methods. The secondary pattern is best read as a collection of outcome-specific observations with varying precision, not as a single overall test of vaccine performance.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Percentage of Bris10 M2SR Subjects Demonstrating Seroconversion to Vaccine HA
• Percentage of Sing2016 M2SR Subjects Demonstrating Seroconversion to Vaccine HA
• Percentage of Bris10 M2SR Subjects Demonstrating Seroconversion to Vaccine HA
• Percentage of Sing2016 M2SR Subjects Demonstrating Seroconversion to Vaccine HA
• Percentage of Bris10 M2SR Subjects Demonstrating Mucosal Responses to Vaccine HA
• Percentage of Bris10 M2SR Subjects Demonstrating Mucosal Responses to Vaccine HA
• Percentage of Sing2016 M2SR Subjects Demonstrating Mucosal Responses to Vaccine HA
• Percentage of Sing2016 M2SR Subjects Demonstrating Mucosal Responses to Vaccine HA

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference describe?

A risk difference compares the proportion with an outcome in one group with the proportion in another. A value above zero means the observed proportion is higher in the first group as the comparison is defined; a value below zero means it is lower. The primary comparison reports a risk difference of 0.081 for low-dose Bris10 M2SR versus placebo. This is an unadjusted comparison based on the posted group counts, not an estimate adjusted for other participant characteristics.

Risk differences are often easier to interpret than relative measures because they express the contrast on the same scale as the outcome proportions. They do not, by themselves, explain why a difference occurred, establish causation beyond the trial’s design and analysis assumptions, or establish clinical importance. The registry does not report a clinically meaningful threshold for this outcome.

How should the p-value be read?

The primary comparison has an unadjusted p-value of 0.444. In general, a p-value summarizes how unusual the observed data, or data more extreme, would be under a specified null hypothesis and statistical model. It does not give the probability that the observed difference is due to chance, and it does not measure the probability that a treatment works. A p-value should be interpreted alongside the effect estimate, interval, outcome definition, and study design.

The registry record does not report the sponsor’s full testing procedure, covariate adjustment, or any prespecified threshold for interpreting the primary result. The comparison should therefore be described as an unadjusted result rather than as evidence from a fully documented analysis plan.

Why do confidence intervals matter?

A confidence interval describes statistical uncertainty around an estimate under the method used to calculate it. In repeated use of a method under its assumptions, intervals constructed in this way have a stated coverage property. For an individual trial, the interval does not give a probability distribution for the true effect; it indicates which values remain compatible with the data and method.

The primary interval extends from -0.126 to 0.289. Its span signals that the estimate is not precise. It includes zero, so the data are compatible with no difference under the stated comparison, but it also includes differences in either direction. The interval should not be reduced to a yes-or-no significance label.

Why can small samples produce imprecise estimates?

In general, an estimate based on fewer observations tends to have greater sampling variability than an estimate based on more observations, all else being equal. Binary outcomes can be especially uncertain when the event is uncommon or when the number of participants in each group is limited. This is a general statistical principle, not a claim about an unreported feature of the trial’s design.

For the primary endpoint, the registry gives group sizes of 42 and 41. The reported confidence interval is broad, consistent with limited precision. The record does not report a sample-size justification, a target precision, or the assumptions used in the original trial design. Planning illustrations based on observed effects are separate from the original design rationale.

What does unadjusted mean?

An unadjusted comparison uses the outcome summaries for the groups without statistical adjustment for other variables. Randomization is intended to balance participant characteristics on average, but with limited group sizes, observed characteristics can still differ. The registry record does not report covariate-adjusted primary results, so the posted comparison should not be described as adjusted for baseline factors.

Adjustment can sometimes improve precision or account for prespecified prognostic variables, but it requires a documented model and suitable data. Neither the specific covariates nor an adjusted analysis are reported in the registry record. It would not be appropriate to infer that an adjustment was performed.

Why can over-dispersion matter?

For count outcomes, a statistical model may assume a particular relationship between the mean and variability. Over-dispersion occurs when the observed variability exceeds what a model assumes. In general, ignoring over-dispersion can make standard errors too small and intervals too narrow. This concept is most relevant when analyzing event counts, rates, or clustered observations; it is not a finding about this trial.

The primary result is reported as the number of participants with an event, rather than a total event rate or repeated-event count. The registry does not report a model for recurrent events or a dispersion estimate. No conclusion about over-dispersion in this trial can be drawn from the posted summary alone.

How do the secondary estimates differ from the primary analysis?

The secondary outcomes are percentages of participants demonstrating seroconversion or mucosal responses to vaccine HA. Their reported confidence intervals describe uncertainty in those percentages, while comparison entries give unadjusted group contrasts. They answer questions about measured immune responses, not the primary question about adverse events. For example, a seroconversion estimate cannot be interpreted as an estimate of influenza cases prevented.

Some secondary outcomes have multiple vaccine groups, while others compare Bris10 M2SR with placebo. The registry does not report a single prespecified model covering all secondary measures, nor does it report a multiplicity procedure. The posted p-values should therefore be treated as unadjusted evidence for individual exploratory comparisons, with caution about interpreting multiple tests together.

For binary outcomes, confidence intervals can be asymmetric around the percentage or difference, particularly when estimates are near zero or one. General methods for such outcomes may use approximations or exact procedures, but the registry record does not identify the specific interval method. The displayed values should be used as posted rather than reverse-engineered into an undocumented method.

11. Confidence Intervals and Precision

Precision concerns how narrowly the data estimate an outcome or contrast. The primary risk-difference interval runs from -0.126 to 0.289 around the estimate of 0.081. Because it includes zero and extends to values in both directions, the primary comparison is uncertain about both the direction and magnitude of the difference. Its p-value of 0.444 is consistent with that uncertainty, but the interval conveys more about the range of estimates compatible with the data.

The secondary outcomes also report 95% confidence intervals for percentages. Their widths vary across outcomes and groups, indicating different degrees of precision. Wider intervals mean a broader range of values remains compatible with the observations under the interval method; narrower intervals indicate greater precision. They do not establish that a result is clinically important, and overlap or non-overlap alone is not a complete test of a group contrast.

Precision depends on the observed data and the statistical method. In general, more observations can improve precision, though the amount depends on outcome frequency and design. The registry record does not report a target interval width or a precision-based sample-size rationale. The recorded group sizes and posted intervals can be considered when assessing uncertainty, but they do not justify claims beyond the outcomes measured and follow-up reported.

Small or zero observed percentages require particular care: an observed zero does not demonstrate that the underlying rate is zero. The registry’s secondary results include a placebo seroconversion estimate of 0.0% with an interval from 0.0% to 9.3%. That interval illustrates why an observed zero should not be read as proof of impossibility. Interpretation should account for the interval, not just the point estimate.

12. 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 illustrations are planning calculations based on observed effects, not the trial’s original design justification. For these binary outcomes, the displayed figures mean participants per arm. They do not refer to total events. The sample size assumptions field states a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; the target effect is the stated fraction of the observed effect.

The 80% power column gives the illustrative number of participants per arm for a design that would have 80% power under those assumptions and effect size. The 90% power column gives the corresponding planning number for 90% power. In general, power is the probability that a study will detect an effect of the specified size under the model and assumptions if that effect is present. These figures are not observed power.

The rows planning for 100%, 75%, and 50% of the observed effect illustrate how the assumed effect size changes the planning requirement. Smaller effects are harder to distinguish from random variation, so the illustrations require more participants per arm for smaller effects. This relationship is a general planning principle, not a statement that the original study was designed to detect those effects.

The curve should be read as a visual representation of the planning relationship between sample size and assumed effect, using the same underlying assumptions as the corresponding illustration. It is not a plot of participants enrolled or an estimate of what the completed trial achieved. The trial’s original power target, sample-size assumptions, and justification are not reported in the registry record.

13. 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 = 0.585; treatment proportion p₁ = 0.667; average p̄ = 0.626.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6843 = 1.3412.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6819 = 0.5739.
4. n = (1.3412 + 0.5739)² / (0.0813)² = 554.8, rounded up to 555 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 <- 0.585365853658537                          # control proportion
p1 <- 0.666666666666667                          # 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(3999554)
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 = 555 (80% power), 743 (90% power)
 75% of observed effect: n per arm = 998 (80% power), 1,336 (90% power)
 50% of observed effect: n per arm = 2,268 (80% power), 3,036 (90% power)
power.prop.test: 554.8 
Simulated power at n = 555 per arm: 0.804 (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.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists multiple secondary outcomes, including seroconversion and mucosal-response measures, and several vaccine groups. Testing multiple outcomes creates a multiplicity issue: even when there is no true effect, conducting many tests can increase the chance of at least one result appearing statistically notable. This is a general statistical concern, not evidence that any posted result is false.

No multiplicity correction, hierarchy of outcomes, or family-wise testing strategy is reported in the registry record. The record also reports no analyses in its analysis count and no secondary reported-analyses entries. Therefore, the displayed unadjusted comparisons should not be treated as if they were protected by an unreported correction. The registry does not state which secondary results were planned as confirmatory and which were exploratory.

Missing-data handling is not reported in the registry record. The primary outcome population is described as participants who received at least one inoculation, but the record does not say how participants with incomplete follow-up, unavailable measurements, or missing outcome values were handled. It also does not report whether an intention-to-treat or per-protocol analysis was used for the immune-response outcomes.

The secondary denominators differ across measures and groups. Without a reported explanation, they should be read as the analysis counts attached to those outcome results, not assumed to represent identical populations or a particular missing-data procedure. The registry record also does not report imputation methods, sensitivity analyses, or reasons for unavailable results. These omissions limit assessment of possible bias arising from missing measurements or selective outcome reporting.

15. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: papillary thyroid cancer (2.4%).

The safety results list serious adverse events for each group. The Sing2016 low-, medium-, and high-dose groups have 0 serious adverse events, as does the low-dose Bris10 group. The placebo group has 1 serious adverse event among 41 participants. Deaths are recorded as 0 in every group. These counts describe what was recorded during the study; they do not establish that an event cannot occur.

The registry lists papillary thyroid cancer as a serious-event term at 2.4%. The term listing does not identify the group attribution, so it should not be assigned to a specific arm from this record alone. The primary comparison’s local and systemic adverse-event count is a separate outcome from the serious-event counts.

Serious adverse events are uncommon outcomes in many study settings, and small counts provide limited precision. A zero count is not proof of zero risk, while a single reported event does not by itself show that a treatment caused it. The registry record does not provide detailed event narratives or an attribution assessment for this term.

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

The results describe a Phase 1b study’s posted safety and immunogenicity observations for Bris10 and Sing2016 M2SR H3N2 vaccines and placebo. The primary comparison reports participants with the adverse-event outcome in each group, alongside an unadjusted risk difference and confidence interval. The interval is broad and includes zero, so the estimate does not precisely determine the direction or size of the group difference.

The immune-response outcomes show observed seroconversion and mucosal-response percentages over the stated follow-up. These measurements concern responses to vaccine HA; they are not direct measures of influenza prevention. Their interpretation is limited by the absence of a reported multiplicity strategy and by incomplete information about analysis populations and missing data.

The results do not establish that a vaccine prevents influenza, that the groups are equivalent, or that no safety risk exists. A non-significant comparison is not evidence of equivalence, and a zero serious-event count is not proof that serious events cannot occur. Similarly, an observed immune response does not by itself demonstrate clinical protection.

Generalization is also constrained by the Phase 1b setting, the recorded group sizes, and the healthy adult population described in the brief summary. The registry record does not provide evidence about other populations or outcomes beyond those posted. Its record of 206 enrollment differs from the brief summary’s description of a study in 250 adults, and no explanation for that difference is reported.

The appropriate statistical reading is therefore descriptive and cautious: the registry provides group-level observations and uncertainty estimates, but limited precision and missing analysis details leave important questions unresolved. Conclusions should remain tied to the specified outcomes, populations, and follow-up rather than extending to unmeasured clinical effects.

17. Why This Trial Matters Statistically

This trial illustrates why early-phase clinical studies are read differently from large confirmatory trials. Its stated focus is safety, reactogenicity, and immunogenicity, and its posted outcomes include participant adverse-event counts and immune-response measures. Such outcomes can characterize observations in the studied groups, but they do not automatically answer whether a vaccine prevents clinical illness.

The primary comparison is a useful example of reading an effect estimate together with its confidence interval. The point estimate alone might seem to suggest a difference, but the interval includes zero and covers a broad range of possible values. The p-value is not a substitute for that uncertainty assessment. The same principle applies to secondary percentages: the point estimates need to be interpreted with their intervals and the context of multiple outcomes.

The record also demonstrates how reporting completeness affects statistical interpretation. Enrollment is recorded as 206, while the brief summary describes a study in 250 adults. The registry does not explain this difference. It does not report the original sample-size justification, missing-data handling, or multiplicity plan. These omissions do not invalidate the posted counts, but they limit the ability to assess how the analyses were planned and how representative the analyzed groups are of the randomized participants.

Finally, the serious-event results show why rare outcomes require caution. No serious events are listed in the vaccine groups, and one is listed in placebo, but these small counts cannot establish absence of risk or a causal relationship. Statistical interpretation depends not only on calculations, but also on the outcome definitions, follow-up, and completeness of the record.

18. 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 contains an inconsistency between its recorded enrollment of 206 and the brief summary’s description of a study in 250 healthy adults. The reason is not reported. The record also does not explain the relationship between the registered groups and the differing denominators attached to some secondary results. Those differences should not be interpreted as evidence of a particular exclusion or missing-data mechanism.

The primary endpoint description combines local and systemic adverse events and refers to cumulative follow-up through Day 209, while its title also specifies events through 29 days post-vaccination and cumulatively through Day 209. The registry does not provide detailed definitions, event severity grading, or participant-level event timelines. The posted count therefore cannot support a more detailed account of event types or timing.

The record does not report the original sample-size calculation, the statistical analysis plan, adjustment for baseline characteristics, missing-data methods, or a multiplicity strategy. It also does not describe interim analyses. These omissions limit assessment of prespecification and analytical choices. They should not be filled in by assumption.

Only three secondary result entries are posted, although the registry lists eight secondary outcome measures. The reason for the difference is not reported. The secondary results should be interpreted as posted outcome-specific findings, not as a complete account of every planned immune-response analysis.

The registry’s serious-event term listing does not state the group attribution for papillary thyroid cancer. Event counts are limited, and the posted results do not include detailed narratives or causal assessments. Finally, the study population is described in the brief summary as healthy adults aged 18–49. The record does not support extending the findings to other populations or to clinical influenza outcomes that were not posted.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Safety and Immunogenicity of the Bris10 M2SR and Sing2016 M2SR H3N2 Monovalent Influenza Vaccines — NCT03999554.
• Registry record last updated 2022-03-04; status last verified 2021-12.
• Results first posted 2022-03-04.
• 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.

22. Record Summary

NCT03999554 is a completed randomized, quadruple-masked, parallel Phase 1b study of Bris10 and Sing2016 M2SR H3N2 monovalent influenza vaccines and placebo. The registry records enrollment of 206 and describes intranasal administrations on days 1 and 29. The primary posted comparison reports adverse-event counts for low-dose Bris10 M2SR and placebo, with an unadjusted risk difference of 0.081 and a 95% confidence interval from -0.126 to 0.289.

Secondary results concern seroconversion and mucosal responses to vaccine HA. Safety results list no serious adverse events in the vaccine groups and 1 in placebo, with 0 deaths in all groups. The record does not report the original sample-size justification, missing-data handling, or multiplicity strategy. The results describe observed outcomes and uncertainty; they do not establish clinical influenza prevention or absence of safety risk.