A Study to Evaluate a Modified RNA Vaccine Against Influenza in Adults 18 Years of Age or Older: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study to Evaluate a Modified RNA Vaccine Against Influenza in Adults 18 Years of Age or Older (NCT05540522), a randomized phase 3 study. The primary outcome is Percentage of Participants Reporting First Episode of LCI Cases With Associated Per-Protocol ILI Caused by Any Strain at Least 14 Days After Vaccination: 18-64 Years.

2. Clinical Question

3. Trial Design

NCT05540522 is a completed Phase 3 randomized study sponsored by Pfizer. The registry lists an enrollment of 45789 and a start date of 2022-09-12, with primary completion on 2024-03-12. Its official title describes an observer-blinded study comparing a modified RNA influenza vaccine with licensed inactivated influenza vaccine in healthy adults aged 18 years or older. The listed masking is quadruple, and the model is parallel.

The interventions were quadrivalent influenza modRNA vaccine and quadrivalent influenza vaccine. The arm descriptions identify single-dose regimens in adults 18 through 64 years and adults aged 65 years or older. The primary endpoint concerns only the 18-through-64 age group. The trial also has outcomes reported for the older age group and for adults aged 18 years or older.

The primary efficacy population was evaluable rather than simply every person enrolled. It included participants who were eligible, received their randomized intervention, had no important protocol deviations, and began surveillance at least 14 days after vaccination. The registry describes surveillance as running from Day 15 to a sponsor-decided cut-off. The primary endpoint’s timeframe is approximately 6 months; the registry separately describes one older-adult secondary outcome with a timeframe of approximately 1 year.

The registry record does not report the original sample-size justification, the allocation ratio, details of sequence generation, or the full statistical analysis plan. It also does not report whether interim analyses were planned or conducted. Those design details should not be inferred from the enrollment or from the planning illustrations associated with the posted results.

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.

Before assignment: Participants from northern hemisphere 2022-2023 and southern hemisphere 2023 were to be enrolled during respective influenza seasons and were stratified into 2 age groups: 18 to 64 years and more than or equal to (\>=) 65 years.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Evaluable efficacy population included all participants who were eligible, received the study intervention to which they were randomized, and had no important protocol deviations, with surveillance starting at least 14 days after vaccination.

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: Safety population included all participants who received the study intervention at the specified dose level. Participants were included in the vaccination group corresponding to the study intervention that they actually received.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Participants Reporting First Episode of LCI Cases With Associated Per-Protocol ILI Caused by Any Strain at Least 14 Days After Vaccination: 18-64 Years, measured over Day 15 to surveillance cut-off (approximately 6 months).

The primary endpoint is the percentage of participants aged 18 through 64 who reported a first episode of laboratory-confirmed influenza (LCI) with associated per-protocol influenza-like illness (ILI), caused by any strain, at least 14 days after vaccination. LCI was defined as influenza infection confirmed through reverse transcription-polymerase chain reaction or culture at the central laboratory, unless otherwise specified. Per-protocol ILI required at least one respiratory symptom concurrently with at least one systemic symptom; new onset or worsening of a preexisting condition could meet the symptom occurrence component.

This endpoint combines laboratory evidence of influenza with a defined symptomatic illness. That makes it a measure of symptomatic, confirmed episodes rather than a measure of every infection, a symptom-only outcome, or an immune response. The registry’s description of the endpoint and population also makes clear that surveillance began only after the post-vaccination interval and was limited to participants meeting the evaluable efficacy criteria.

A percentage endpoint is useful for comparing how frequently a specified event was reported in the randomized groups over the stated surveillance period. Interpretation nevertheless depends on the operational definitions, the population included, and the surveillance cut-off. The registry record does not report additional endpoint adjudication details beyond the laboratory and symptom definitions stated above.

7. Results Posted in the Registry

• Licensed QIV: 18-64 Years: 1.0% (87/9120) versus 0.6% (57/9118) on control; risk difference 0.3 percentage points (95% CI 0.1 to 0.6), risk ratio 1.53 (1.09–2.13); unadjusted two-proportion z-test p = 0.012.

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 Participants Reporting First Episode of LCI Cases With Associated Per-Protocol ILI Caused by All Matched Strains at Least 14 Days After Vaccination: 18-64 Years

• 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:
  • Licensed QIV: 18-64 Years: 0.3% (31/9120) versus 0.2% (21/9118) on control; risk difference 0.1 percentage points (95% CI -0.0 to 0.3), risk ratio 1.48 (0.85–2.57); unadjusted two-proportion z-test p = 0.165.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Licensed QIV: 18-64 Years and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Participants Reporting First Episode of LCI Cases With Associated Per-Protocol ILI Caused by All Matched Strains at Least 14 Days After Vaccination: >=65 Years

• 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:
  • Licensed QIV: >=65 Years: 0.4% (48/13456) versus 0.3% (46/13392) on control; risk difference 0.0 percentage points (95% CI -0.1 to 0.2), risk ratio 1.04 (0.69–1.56); unadjusted two-proportion z-test p = 0.854.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Licensed QIV: >=65 Years and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Participants Reporting First Episode of Culture Confirmed Influenza (CCI) With Associated Per-Protocol ILI Caused by Any Strain at Least 14 Days After Vaccination: 18-64 Years

• 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:
  • Licensed QIV: 18-64 Years: 0.3% (31/9120) versus 0.2% (21/9118) on control; risk difference 0.1 percentage points (95% CI -0.0 to 0.3), risk ratio 1.48 (0.85–2.57); unadjusted two-proportion z-test p = 0.165.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Licensed QIV: 18-64 Years and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary results cover related influenza outcomes, including outcomes limited to matched strains, culture-confirmed influenza, and alternative ILI definitions, with analyses in the 18-through-64 and 65-years-and-older age groups. Across the available summaries, the direction and degree of separation between groups are not uniform. Some comparisons show small differences with intervals spanning zero, while the primary comparison has an interval above zero. The secondary results therefore offer additional context rather than a single consistent replication of the primary estimate.

The registry lists 46 secondary outcomes. The outcomes vary in strain definition, laboratory confirmation, symptom definition, age group, and surveillance timeframe. These differences matter: related endpoints need not measure the same event, and estimates from different definitions or age groups should not be pooled mentally as if they were interchangeable. The primary outcome remains the registry’s designated primary endpoint for adults 18 through 64.

Unadjusted secondary results carry less weight for confirmatory interpretation when many endpoints are examined. In general, multiple testing increases the chance of apparently unusual findings across a family of comparisons, even when no underlying differences exist. The registry record does not report a multiplicity procedure for the secondary outcomes. Accordingly, secondary p-values and intervals should be treated as exploratory context unless the analysis plan establishes a different interpretation. Their role is to help describe the breadth and consistency of the posted outcomes, not to overturn the primary result by selective emphasis.

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

• Percentage of Participants Reporting First Episode of LCI Cases With Associated Per-Protocol ILI Caused by All Matched Strains at Least 14 Days After Vaccination: 18-64 Years
• Percentage of Participants Reporting First Episode of LCI Cases With Associated Per-Protocol ILI Caused by All Matched Strains at Least 14 Days After Vaccination: >=65 Years
• Percentage of Participants Reporting First Episode of Culture Confirmed Influenza (CCI) With Associated Per-Protocol ILI Caused by Any Strain at Least 14 Days After Vaccination: 18-64 Years
• Percentage of Participants Reporting First Episode of CCI With Associated Per-Protocol ILI Caused by Any Strain at Least 14 Days After Vaccination: >=65 Years
• Percentage of Participants Reporting First Episode of LCI Cases With Associated ILI as Defined by Modified Centers for Disease Control and Prevention (CDC) Caused by Any Strain at Least 14 Days After Vaccination: 18-64 Years
• Percentage of Participants Reporting First Episode of LCI Cases With Associated ILI as Defined by Modified CDC Caused by Any Strain at Least 14 Days After Vaccination: >=65 Years
• Percentage of Participants Reporting First Episode of LCI Cases With Associated ILI as Defined by World Health Organization (WHO) Caused by Any Strain at Least 14 Days After Vaccination: 18-64 Years
• Percentage of Participants Reporting First Episode of LCI Cases With Associated ILI as Defined by WHO Caused by Any Strain at Least 14 Days After Vaccination: >=65 Years

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference represent?

For a binary endpoint, a risk difference compares the proportions with an event in the two groups by subtracting one group’s event proportion from the other’s. It is an absolute measure: it describes the distance between the observed event proportions on the probability scale. The recalculated estimate for the primary endpoint is 0.003. Its direction is consistent with the higher posted event percentage in the licensed QIV group. The estimate does not describe a relative change, and it does not identify why the event percentages differ.

What does the confidence interval add?

A confidence interval is a range of values compatible with the data and the statistical method used to calculate it, subject to the assumptions of that method. For the primary risk difference, the 95% interval runs from 0.001 to 0.006. Its position relative to zero is informative because zero represents no absolute difference on this scale. The interval’s width conveys uncertainty: a narrower interval indicates greater precision than a wider interval, all else equal. A confidence interval is not a guarantee that the true effect lies within its endpoints, and it does not account automatically for unreported design or analysis choices.

How should the p-value be read?

The unadjusted p-value is 0.012. In general, a p-value measures how unusual data at least as discordant with a specified null model would be if that model were correct, under the assumptions of the test. It is not the probability that the null hypothesis is true, nor is it a measure of clinical importance. Because it is explicitly unadjusted, it does not account for the possibility of multiple endpoints or comparisons. The registry record does not report a multiplicity adjustment for this result.

How does the sponsor-reported analysis differ?

The registry reports an RVE estimate of 34.5, with a 95% confidence interval from 7.4 to 53.9. RVE is a relative-effect scale, while risk difference is absolute. General statistical interpretation cautions against comparing the numerical magnitudes of different effect measures as if they were the same quantity. The registry record does not state the analysis method or provide a p-value for the reported RVE analysis. The recalculation is a simple unadjusted calculation from the posted summary statistics; it is not a reconstruction of the sponsor’s full analysis.

Why can event-count comparisons be uncertain?

Binary outcomes depend on how many participants meet the event definition and on the denominator included in each group. When events are relatively uncommon, a modest change in event counts can influence the estimated percentage and its uncertainty. General statistical reasoning also recognizes that the validity of a comparison depends on appropriate handling of the analysis population, missing outcome data, and follow-up. The registry record describes the evaluable efficacy population and surveillance period, but does not report detailed missing-data methods or enough information to assess every implementation choice.

What does randomization contribute?

In general, randomization is intended to make treatment groups comparable with respect to measured and unmeasured baseline factors on average. Observer blinding can reduce some risks of differential assessment. These design features do not eliminate uncertainty, guarantee balanced groups in a particular sample, or address missing data and multiplicity on their own. The record lists randomization and quadruple masking, but does not describe the allocation sequence, implementation details, or which roles were masked. Those details are not reported in the registry record.

How does the endpoint definition shape the estimate?

The primary endpoint requires both laboratory confirmation and associated per-protocol ILI. That definition distinguishes the outcome from an infection identified without symptoms, an illness without laboratory confirmation, or an immune-response measure. The registry describes laboratory confirmation by RT-PCR or culture at the central laboratory unless otherwise specified, and defines ILI using concurrent respiratory and systemic symptoms. In general, a stricter composite event definition can result in fewer events than a broader definition, but no comparison of alternative definitions should be inferred without the corresponding results.

11. Confidence Intervals and Precision

For the primary unadjusted risk difference, the 95% confidence interval is 0.001 to 0.006, around an estimate of 0.003. The interval does not include zero. It nevertheless spans a range of possible absolute differences, so the point estimate should not be read as an exact or certain effect. The bounds describe sampling uncertainty under the recalculation’s assumptions; they do not capture uncertainty arising from unreported analysis decisions, outcome ascertainment, or the applicability of the evaluable population.

The event percentages were 0.63% and 0.95%, while the displayed group sizes were 9118 and 9120. The relatively small event proportions mean that interpretation should attend to both the estimated percentages and their uncertainty rather than focusing only on the p-value. The risk difference interval is the relevant uncertainty interval for the absolute comparison; the separately reported RVE interval is on a different scale and should be interpreted separately.

In general, a confidence interval communicates precision rather than clinical importance. Whether a range is important to decision-making depends on context not established by the interval alone. The registry record does not specify a clinically important threshold for this endpoint. The unadjusted interval also does not account for multiplicity; a multiplicity-adjusted interval or testing procedure is not reported in the registry record.

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 planning illustrations give participants per arm for the binary endpoints. They are not total-event counts. The assumptions stated for these illustrations are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning row uses a stated fraction of the observed effect: 100% of the observed effect, 75% of the observed effect, or 50% of the observed effect. The trial’s own original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm under which the specified effect would be detected in 80% of repeated studies, if the planning assumptions and effect were correct. The 90% power column uses the same idea but targets detection in 90% of repeated studies. These are planning quantities, not guarantees about any particular trial. The figures are illustrations computed from the observed effect rather than evidence about the original design.

Smaller effects require more participants for the same target power under these assumptions. That is why planning for 75% or 50% of the observed effect gives larger participant requirements than planning for the full observed effect. The observed effect is uncertain, however, so using it as the basis for a future-study illustration can produce unstable planning values, especially when the event is uncommon.

These figures are not observed power. They are forward-looking planning illustrations. They do not establish what power the completed trial had under its original design, and they do not substitute for a prespecified sample-size calculation.

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 = 0.006; treatment proportion p₁ = 0.010; average p̄ = 0.008.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.1252 = 0.2453.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.1251 = 0.1053.
4. n = (0.2453 + 0.1053)² / (0.0033)² = 11,371.9, rounded up to 11,372 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 <- 0.00625137091467427                          # control proportion
p1 <- 0.00953947368421053                          # 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(5540522)
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 = 11,372 (80% power), 15,224 (90% power)
 75% of observed effect: n per arm = 19,174 (80% power), 25,667 (90% power)
 50% of observed effect: n per arm = 40,789 (80% power), 54,604 (90% power)
power.prop.test: 11371.9 
Simulated power at n = 11,372 per arm: 0.803 (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. Analyses Reported by the Sponsor

The registry reports the sponsor’s analysis as RVE 34.5, with a 95% confidence interval from 7.4 to 53.9. The record gives no method or p-value for that analysis. The posted summary statistics also support a simple unadjusted recalculation of the absolute risk difference: 0.003, with a 95% confidence interval from 0.001 to 0.006 and an unadjusted p-value of 0.012.

These are not duplicate estimates of the same quantity. RVE is a relative-effect measure, while risk difference is an absolute comparison. Their numerical values and intervals are therefore not directly interchangeable. The recalculation uses posted group summaries and does not reproduce any sponsor adjustment or other analysis choices that may have been used for the reported result.

The registry record marks no discrepancy between the reported analysis and the recalculation. That does not make the measures identical; it indicates that the posted result and the recalculation are not flagged as discrepant. The sponsor’s own analysis remains the relevant reported analysis, while the recalculation is a supplementary unadjusted view of the summarized data.

15. Multiplicity, Missing Data and Analysis Populations

The registry reports 58 outcome measures and 34 analyses. It also lists 46 secondary outcomes. With many outcomes and analyses, multiplicity becomes relevant because repeated testing can increase the chance of at least one result appearing unusual by chance. Statistical approaches may address this through prespecified hierarchies, adjusted significance thresholds, or other procedures. The registry record does not report whether any such procedure was planned or applied.

The primary comparison’s p-value is explicitly unadjusted. The recalculated confidence interval is also an unadjusted interval. Neither should be described as controlling the error rate across the full set of outcomes. The registry’s sponsor-reported RVE result is listed with a 95% confidence interval, but its method and any multiplicity handling are not reported in the registry record.

The primary analysis population is defined as evaluable efficacy participants: eligible participants who received their randomized intervention, had no important protocol deviations, and entered surveillance at least 14 days after vaccination. The registry record does not report detailed methods for handling missing endpoint information, withdrawals, or incomplete surveillance. It also does not report a sensitivity analysis addressing departures from the primary population definition. Those omissions limit assessment of how missingness or exclusions could affect the result.

The registry record does not report the original statistical analysis plan, the timing of any analysis decisions, or interim-analysis procedures. It is therefore not possible from the registry description to determine how endpoint selection, multiplicity, missing data, and analysis populations were handled in the full sponsor analysis. These are reporting limitations, not evidence that a particular method was or was not used.

16. 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 1% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: pneumonia (0.2%), atrial fibrillation (0.2%), acute respiratory failure (0.1%), acute kidney injury (0.1%), cardiac failure congestive (0.1%).

The serious adverse event counts are reported by age group and intervention group. Among adults 18 through 64, the registry lists 83 serious adverse events among 9191 at risk in the qIRV group and 93 among 9197 at risk in the licensed QIV group. Deaths are listed as 7 and 9, respectively. For participants aged 65 years and older, the serious-event counts are 318 among 13557 at risk for qIRV and 296 among 13611 at risk for licensed QIV; deaths are 49 and 46. The registry also provides combined adult-group counts.

These are event counts and numbers at risk as recorded, not estimates of causal effect. The registry does not establish from these figures alone whether an event was caused by vaccination. Serious adverse events should also be distinguished from the broader category of other adverse events, which is reported separately. The listed serious-event terms and percentages are aggregate descriptions, not evidence about comparative risk for each term.

Safety interpretation depends on event definitions, follow-up, exposure, and the analysis population. Further details about causality assessment and event-specific follow-up are not reported in the registry record.

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

The posted primary results describe a comparison of event percentages for laboratory-confirmed influenza accompanied by a defined ILI in the evaluable population of adults aged 18 through 64. The recalculated absolute risk difference is 0.003, and its 95% confidence interval is 0.001 to 0.006. This identifies the direction and uncertainty of the unadjusted comparison on the risk-difference scale; it does not by itself establish the practical importance of the difference.

The estimate applies to the endpoint definition, post-vaccination surveillance period, and participants included in the evaluable efficacy population. It does not directly describe infections without associated ILI, illnesses without laboratory confirmation, other age groups, or outcomes outside the surveillance period. It also does not answer every question about immunogenicity, tolerability, or safety.

In general, statistical evidence and clinical importance are distinct. A confidence interval can help show the range of estimates compatible with the data, but the registry does not report a threshold for a clinically important difference. No treatment recommendation follows from these statistics alone.

The trial was randomized and observer-blinded, but the registry record does not provide the full design and analysis details needed to assess every potential source of bias. The record also does not report multiplicity handling, detailed missing-data methods, or the original sample-size justification. Those limitations affect how broadly the results can be interpreted and how strongly the secondary findings can be treated as confirmatory.

18. Why This Trial Matters Statistically

This trial illustrates why the statistical question must be tied closely to an endpoint definition. A laboratory-confirmed infection accompanied by a specified symptom pattern is not the same outcome as any infection, any respiratory illness, or an immune response. The population restriction and surveillance start also shape what the percentage comparison represents.

It also demonstrates the difference between absolute and relative effect measures. The recalculated risk difference describes an absolute contrast in event proportions, while the registry’s reported RVE is on a relative scale. Reading them as distinct summaries avoids treating their numerical values as contradictory or interchangeable.

Precision and multiplicity are also central. The primary confidence interval indicates uncertainty around the estimated absolute difference, while the registry lists numerous outcomes and analyses without reporting a multiplicity procedure. A nominal unadjusted p-value should therefore be read alongside the endpoint hierarchy and the broader evidence, not in isolation.

Finally, planning illustrations based on observed effects are not evidence about the completed trial’s original power. They show how assumed effect size and target power influence participant requirements under stated planning assumptions. Keeping these design illustrations separate from observed results is important for both trial interpretation and future-study planning.

19. 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.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

Several trial-specific limitations are evident from the registry record. The primary result pertains to adults 18 through 64 in the evaluable efficacy population, rather than every enrolled participant. The endpoint requires both laboratory confirmation and the specified per-protocol ILI symptoms, which narrows its scope to a defined type of symptomatic illness. Surveillance begins at least 14 days after vaccination and ends at a sponsor-decided cut-off described as approximately 6 months for the primary endpoint.

The record describes data collection during the 2022-2023 northern hemisphere influenza season. Results from that surveillance period do not by themselves establish how the event rates would compare in other seasons or under different circulating strains. The registry includes other age groups and outcome definitions, but those are not substitutes for the primary population and endpoint.

Important interpretive details are not reported in the registry record: the original sample-size justification, the full analysis plan, multiplicity handling, missing-data methods, and interim-analysis procedures. The method behind the reported RVE estimate is also not stated. These omissions constrain independent evaluation of the sponsor analysis and of the confirmatory status of secondary findings.

The adverse-event figures are counts by group and do not establish causation. The posted summary statistics also do not provide all the detail needed to evaluate event timing, duration, or participant-level overlap. These limits should be kept in view when drawing conclusions beyond the specific estimates reported.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Study to Evaluate a Modified RNA Vaccine Against Influenza in Adults 18 Years of Age or Older — NCT05540522.
• Registry record last updated 2025-05-08; status last verified 2025-04.
• Results first posted 2025-05-08.
• 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.

23. Record Summary

NCT05540522 is a completed randomized, observer-blinded Phase 3 parallel-group study sponsored by Pfizer. It compared a single dose of quadrivalent influenza modified RNA vaccine with licensed quadrivalent influenza vaccine in healthy adults aged 18 years or older.

The primary endpoint was the percentage of evaluable participants aged 18 through 64 reporting a first episode of laboratory-confirmed influenza with associated per-protocol ILI caused by any strain, at least 14 days after vaccination. Posted percentages were 0.63% for qIRV and 0.95% for licensed QIV. The unadjusted recalculated risk difference was 0.003, with a 95% confidence interval from 0.001 to 0.006 and p = 0.012.

The registry separately reports RVE 34.5, with a 95% confidence interval from 7.4 to 53.9. The registry record does not report the method for that analysis, the original sample-size justification, or multiplicity and missing-data procedures. Secondary outcomes and serious adverse event counts provide additional context but require interpretation within their respective definitions and populations.