Simultaneous mRNA COVID-19 and IIV4 Vaccination Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Simultaneous mRNA COVID-19 and IIV4 Vaccination Study (NCT05028361), a randomized phase 4 study. The primary outcome is Total Number of Participants With Moderate or More Severe Fever, Chills, Myalgia, or Arthralgia in the Simultaneous Group and the Sequential Group Following Both Vaccination Visit 1 and 2.

2. Clinical Question

3. Trial Design

The registry describes a randomized, observer-blinded, parallel-group Phase 4 study. Duke University is listed as the sponsor. The study status is completed, with enrollment of 348. The registry lists a start date of 2021-10-04 and a primary completion date of 2023-03-03. The official title describes adults, adolescents, and children, and the registry lists quality of life, injection-site reactions, adverse drug events, and systemic reactions among the conditions studied.

The central design contrast was simultaneous versus sequential administration. The simultaneous group received mRNA COVID-19 vaccine and IIV4 at Visit 1, then saline placebo at Visit 2. The sequential group received mRNA COVID-19 vaccine and saline placebo at Visit 1, then IIV4 at Visit 2, with the visits planned 7-14 days apart. For participants receiving a primary mRNA series, a further mRNA dose was described at Visit 3; the timing depended on the vaccine regimen. Participants receiving a booster dose of mRNA COVID-19 vaccine received a single mRNA dose in the study.

Solicited reactogenicity symptoms and adverse events were assessed on vaccination days and daily during the 7 days after each vaccination visit, using electronic or paper diaries according to participant preference. Quality-of-life data were collected on the day of Visit 1 and daily during the following 7 days. Serious adverse events and adverse events of special interest were collected throughout the study, and participants were followed through Day 121. Serum samples were also planned for determination of SAR, but the registry record does not complete the description of that measurement. Further operational details, including the full randomization procedure and the basis for observer blinding, are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: Of the 348 enrolled participants, 335 met inclusion criteria and were randomized to treatment.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Data combined for combined for Visits 1 and 2.

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 Total Number of Participants With Moderate or More Severe Fever, Chills, Myalgia, or Arthralgia in the Simultaneous Group and the Sequential Group Following Both Vaccination Visit 1 and 2, measured over Up to 7 Days Post Vaccination (combined for Visits 1 and 2).

The primary endpoint counts participants with moderate or more severe fever, chills, myalgia, or arthralgia after Vaccination Visits 1 and 2 combined. The registry defines the timeframe as up to 7 days post vaccination and says participants were asked to complete a memory aid documenting symptoms and measuring temperature daily. The population description also refers to data combined across Visits 1 and 2.

This endpoint captures a defined set of systemic symptoms at a specified severity threshold, rather than counting every symptom of any severity. Such a binary outcome is used to compare how often participants cross the stated threshold in each randomized group. It gives an interpretable count of participants meeting the endpoint, but it does not describe symptom duration, the number of separate symptom episodes, or severity beyond the threshold. Those features cannot be inferred from the primary count alone.

The combined endpoint reflects the experience across both vaccination visits, which took place under different schedules in the two groups. Results for the visits separately are listed as secondary outcomes. The combined primary result therefore addresses the overall occurrence across the specified period, while the secondary results can provide context about when symptoms were recorded. The registry record does not report a clinical threshold for what size of between-group difference would be important to participants or investigators.

7. Results Posted in the Registry

• Sequential Vaccination Group: 31.3% (52/166) versus 25.6% (43/168) on control; risk difference 5.7 percentage points (95% CI -3.9 to 15.4), risk ratio 1.22 (0.87–1.72); unadjusted two-proportion z-test p = 0.246.

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.

Number of Participants With Moderate or More Severe Fever, Chills, Myalgia, or Arthralgia in the Simultaneous Versus the Sequential Group Following the First Vaccination Visit

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Sequential Vaccination Group: 28.3% (47/166) versus 23.8% (40/168) on control; risk difference 4.5 percentage points (95% CI -4.9 to 13.9), risk ratio 1.19 (0.83–1.71); unadjusted two-proportion z-test p = 0.348.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Sequential Vaccination Group and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants With Moderate or More Severe Fever, Chills, Myalgia, or Arthralgia in the Simultaneous Versus Sequential Group Following the Second Vaccination Visit

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Sequential Vaccination Group: 5.4% (9/166) versus 3.0% (5/168) on control; risk difference 2.4 percentage points (95% CI -1.9 to 6.7), risk ratio 1.82 (0.62–5.32); unadjusted two-proportion z-test p = 0.265.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Sequential Vaccination Group and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists secondary symptom outcomes for the first and second vaccination visits, severity-graded solicited local and systemic reactions after vaccination visits, and serious adverse events. In the posted comparative results, moderate-or-more-severe systemic symptoms are reported separately for the first and second visits. The first-visit counts are 40 of 168 in the simultaneous group and 47 of 166 in the sequential group; the second-visit counts are 5 of 168 and 9 of 166, respectively. The registry reports Mantel-Haenszel p-values of 0.385 and 0.289 for these visit-specific comparisons.

The broad pattern is consistent with the primary result in the limited sense that the raw counts are higher in the sequential group for the combined endpoint and for each of the two separately posted visit outcomes. The visit-specific tests do not, by themselves, establish a difference, and they should not be treated as independent confirmation of the primary comparison. The endpoints are related because they concern similar symptoms in the same randomized groups, and the combined primary outcome includes the visit periods represented separately in secondary results.

Secondary results generally carry less weight than the primary result because they may involve multiple outcomes, severity categories, timepoints, and comparisons. Unless a multiplicity strategy is specified, repeated testing increases the chance of at least one apparently notable result arising by chance. The registry record does not report a multiplicity adjustment or a hierarchy for interpreting secondary outcomes. The secondary findings are therefore descriptive context for the primary question, not a basis for broad conclusions. The registry lists four secondary outcome measures, but the available entries do not provide complete comparative estimates for every listed outcome.

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

• Number of Participants With Moderate or More Severe Fever, Chills, Myalgia, or Arthralgia in the Simultaneous Versus the Sequential Group Following the First Vaccination Visit
• Number of Participants With Moderate or More Severe Fever, Chills, Myalgia, or Arthralgia in the Simultaneous Versus Sequential Group Following the Second Vaccination Visit
• Number of Participants in the Simultaneous and Sequential Vaccination Groups With Solicited Local and Systemic Reactogenicity Events According to Severity Grade After the First, Second and Third Vaccination Visit
• Number of Participants With Observed Serious Adverse Events

9. Statistical Interpretation

10. Statistical Methods Explained

For a binary endpoint, each participant is classified according to whether the specified event occurred. The primary outcome is a count of participants meeting the moderate-or-more-severe symptom definition. The recalculated comparison expresses the difference between the groups as a risk difference: the proportion in the sequential group minus the proportion in the simultaneous group. A positive estimate therefore means the observed event proportion is higher in the sequential group under this convention; it does not by itself establish a meaningful or reliable difference.

What does the confidence interval add?

A confidence interval describes the uncertainty around an estimate under the statistical method used. The recalculated primary risk difference is 0.057, and its 95% confidence interval ranges from -0.039 to 0.154. Because the interval includes zero, the data do not clearly distinguish a positive difference from no difference or a negative difference at the interval's stated confidence level. The interval also communicates more than a thresholded p-value: it shows the range of estimates reasonably compatible with the data and method. It does not assign a probability to the true effect or guarantee that the true effect lies inside the interval.

What does the p-value assess?

The recalculated unadjusted p-value is 0.246. In general, a p-value measures how surprising the observed data, or more extreme data, would be under a specified null hypothesis and analysis model. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. The recalculated p-value is unadjusted, meaning it does not account for testing multiple outcomes or comparisons. The registry's reported analysis gives a separate p-value of 0.001, but that value is part of the sponsor's non-inferiority analysis and is affected by the marked discrepancy.

Why distinguish the recalculation from the registry analysis?

The recalculation uses the posted group counts and denominators to produce a simple, unadjusted comparison. It is useful as a transparent check of the observed summary data, but it may not reproduce an analysis that incorporates stratification, covariate adjustment, an analysis population, or other protocol-defined features. The registry identifies the sponsor method as Cochran-Mantel-Haenszel for the primary result. That method can account for stratification when comparing groups, but the registry record does not report the relevant strata or enough implementation detail to reconstruct the analysis. The discrepancy means the recalculation should not be treated as a replacement for the sponsor's analysis.

For the first and second vaccination visit outcomes, the registry lists Mantel-Haenszel analyses with p-values of 0.385 and 0.289, respectively. The registry does not post estimates or confidence intervals for those analyses in the result entries described. Separately calculated risk differences and intervals are simple unadjusted comparisons. Those approaches answer related, but not necessarily identical, statistical questions, especially if the sponsor analysis accounts for design features not reflected in the unadjusted calculations.

What does non-inferiority require?

A non-inferiority analysis asks whether the outcome under one strategy is not worse than the other by more than a prespecified margin. The margin defines the largest difference that would still be considered acceptable for the study's question. The estimate and confidence interval must be interpreted relative to that margin and the direction in which the difference is defined. The registry reports a non-inferiority analysis but does not report its margin in the available result details. Without the margin and analysis conventions, the posted label alone is not enough to independently assess the non-inferiority conclusion.

Why might over-dispersion matter?

Over-dispersion is a general concern when observed variability is greater than a statistical model assumes. It can make uncertainty estimates too narrow if the model understates variation. For a simple binary endpoint, the counts and denominators support a basic comparison, but a reader cannot assess all model assumptions or stratified variation from aggregate totals alone. The registry record does not report a specific over-dispersion assessment for this outcome; there is no basis to claim that it was present or absent.

All of these interpretations depend on the population included in each analysis, how missing diaries were handled, and whether outcome definitions were applied consistently. Those details are not reported in the registry record. Statistical significance, confidence intervals, and a non-inferiority label should therefore be considered alongside the available design and reporting details rather than read as self-sufficient conclusions.

11. Confidence Intervals and Precision

The recalculated primary risk difference is 0.057, with a 95% confidence interval from -0.039 to 0.154. The interval crosses zero, so the estimated direction is uncertain under this unadjusted comparison. Its endpoints also indicate that the posted data are compatible with a range of possible differences, not just the point estimate. The interval does not show that every value within it is equally plausible, and it does not account for uncertainties beyond those represented by the calculation.

The registry's sponsor-reported non-inferiority result gives a difference of -5.6 with a 95% confidence interval from -15.2 to 4.0. That interval also includes zero. However, it is not directly reconciled with the recalculated estimate, and the registry flags a discrepancy. The sponsor's own analysis takes precedence, but the available record does not include the margin or sufficient detail to assess the result independently. In particular, an interval that includes zero cannot be interpreted as proving equivalence; for non-inferiority, the relevant comparison is with the prespecified margin.

Precision is limited by the amount of information in the posted group counts and by the number of participants meeting the endpoint. The primary result reports 43 events in the simultaneous group and 52 in the sequential group. The interval is more informative than a binary declaration based on a p-value because it displays uncertainty in both direction and size. Still, aggregate results cannot show whether precision differs across participant subgroups, whether diary completion was balanced, or how missing observations affected the analysis. Those details are 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 sample-size figures are planning illustrations based on the observed effect, not the trial's original design calculation. The registry's original sample-size justification and design assumptions are not reported in the registry record. For the binary outcomes, the figures are participants per arm, not totals across both arms and not total events. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each row applies a stated fraction of the observed effect as the effect to detect.

The column for 80% power gives the planned number of participants per arm under which the assumed analysis would have an 80% chance of detecting the specified effect if that effect were true and the planning assumptions held. The 90% power column describes the corresponding planning target with a higher chance of detection. These are design calculations, not guarantees for a future study; actual power depends on the true effect, event frequency, follow-up, and analysis. The displayed primary-outcome illustrations include 973 participants per arm for planning at 100% of the observed effect and 3,771 participants per arm for planning at 50% of the observed effect at 80% power. The 90% power figures for those same effect assumptions are 1,302 and 5,048 participants per arm.

Smaller effects generally require more participants to detect with the same power and significance level, which is why planning for a smaller fraction of the observed effect yields larger sample-size figures. The curve is a visual representation of this planning relationship, not a statement about the trial's actual enrollment or a prediction of its result. These figures are not observed power.

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 = 0.256; treatment proportion p₁ = 0.313; average p̄ = 0.285.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6381 = 1.2507.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6368 = 0.5360.
4. n = (1.2507 + 0.5360)² / (0.0573)² = 972.3, rounded up to 973 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 <- 0.255952380952381                          # control proportion
p1 <- 0.313253012048193                          # 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(5028361)
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 = 973 (80% power), 1,302 (90% power)
 75% of observed effect: n per arm = 1,703 (80% power), 2,279 (90% power)
 50% of observed effect: n per arm = 3,771 (80% power), 5,048 (90% power)
power.prop.test: 972.3 
Simulated power at n = 973 per arm: 0.797 (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's primary analysis is identified as a Cochran-Mantel-Haenszel non-inferiority analysis. It reports a difference in proportions of -5.6, a 95% confidence interval from -15.2 to 4.0, and p < 0.001. The simple recalculation from the posted counts gives an unadjusted risk difference of 0.057, with a 95% confidence interval from -0.039 to 0.154 and p = 0.246. These are not directly concordant summaries: the reported estimate has a different sign, and the reported p-value does not match the impression given by its stated interval.

The discrepancy is flagged in the registry record. The sponsor's own analysis takes precedence over the simple unadjusted recalculation, because it is the trial's reported analysis rather than a reconstruction from aggregate counts. That precedence does not remove the need to interpret the result cautiously. The record does not provide enough information to reconcile the difference, including the non-inferiority margin and full details of the analysis population and implementation. The recalculation is best read as a check based on the posted totals, not as a correction to or replacement for the sponsor's analysis.

15. Multiplicity, Missing Data and Analysis Populations

The registry describes one primary endpoint and lists secondary outcomes covering systemic symptoms by vaccination visit, graded solicited reactions, and serious adverse events. These outcomes create more than one opportunity to compare groups. When many outcomes or timepoints are tested, the probability of observing at least one small p-value by chance can increase. General approaches include prespecifying a hierarchy, adjusting significance thresholds, or treating secondary analyses as exploratory. The registry record does not report whether any such multiplicity strategy was planned or applied. The unadjusted recalculated p-values should not be interpreted as if they account for all outcome testing.

Missing-data handling is also not reported in the registry record. The symptom outcomes relied on daily electronic or paper diaries, and the registry states that diary format depended on participant preference. The available record does not state how incomplete diaries, missed vaccination visits, or partially observed follow-up were handled; whether participants with missing symptom entries were excluded, imputed, or counted under another rule; or whether sensitivity analyses were conducted. Those choices can affect both the event counts and uncertainty estimates.

The analysis populations are not fully described in the posted results. The primary arm denominators are 168 and 166, while the safety record gives participants at risk of serious events as 169 and 166. The registry does not explain the differences in denominator across result records or report the criteria defining the populations for each analysis. Randomization can support a fair comparison when analyzed appropriately, but a reader needs the population definition and participant flow to assess how closely the result reflects the randomized groups.

Further details not reported in the registry record include the original statistical analysis plan, handling of protocol deviations, subgroup analyses, and the specific missing-data assumptions. Their absence does not show that these procedures were not performed; it limits what can be independently assessed from the record.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: small bowel obstruction (0.6%), spontaneous complete abortion (0.6%).

The serious adverse event results list 1 affected participant among 169 at risk in the simultaneous group and 1 among 166 at risk in the sequential group. The registry lists 0 deaths in each group. It also lists 18 participants with other adverse events among 169 at risk in the simultaneous group and 9 among 166 at risk in the sequential group. The record names Small Bowel Obstruction and Spontaneous Complete Abortion among the top serious adverse event terms, each reported as 0.6%.

These are descriptive safety counts over the registry's reporting period. The serious-event figures concern participants with serious adverse events, while the other adverse-event figures are a separate category in the posted results; they should not be combined. The small number of serious events provides limited information for comparing groups, and the counts alone do not establish whether a difference is meaningful. The record does not provide enough detail about event timing, attribution, severity beyond the serious classification, or the specific follow-up completeness to support broader safety conclusions. Zero recorded deaths does not mean that every possible safety outcome was ruled out.

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

The primary result shows that the posted counts of participants with moderate or more severe fever, chills, myalgia, or arthralgia were 43 of 168 in the simultaneous group and 52 of 166 in the sequential group, for the combined period after the first and second vaccination visits. A simple unadjusted comparison estimates a risk difference of 0.057 for sequential minus simultaneous, but its 95% confidence interval ranges from -0.039 to 0.154. The interval includes zero and reflects uncertainty in both direction and magnitude.

The result does not establish that the schedules are equivalent, that either schedule is non-inferior, or that a difference of a particular size is clinically important. Those judgments require information such as a prespecified non-inferiority margin, the analysis plan, and the relevance of different outcome magnitudes. The registry reports a sponsor non-inferiority analysis, but the flagged discrepancy between that analysis and the unadjusted recalculation, together with the absence of the margin in the registry record, limits independent interpretation.

The outcome is a selected set of systemic symptoms at a stated severity level over a defined post-vaccination timeframe. It does not capture every possible symptom or adverse event, and the primary count does not describe duration, symptom burden, or individual experience. Separate visit outcomes and safety results add context, but they do not resolve the primary analysis discrepancy or replace complete reporting of missing data and analysis populations.

These results describe the study record and the reported participant counts. They are not medical advice and do not establish that a vaccine works or does not work. The trial compared the timing of two vaccinations, and the registry record alone cannot support conclusions beyond the specified outcomes, follow-up, and analyses.

18. Why This Trial Matters Statistically

This trial addresses a design question that is statistically distinct from comparing vaccination with no vaccination: it compares simultaneous administration with a planned sequential schedule. Random allocation provides a framework for comparing these approaches, while the placebo injection at the visit without IIV4 helps make the visit procedures more similar between groups. The primary endpoint focuses on participant-level symptom occurrence at a defined severity threshold, making the outcome directly interpretable as a count in each randomized group.

The record also illustrates why statistical interpretation should not stop at a p-value or an analysis label. The unadjusted recalculation from the published counts and the sponsor's reported non-inferiority analysis do not align straightforwardly, and the registry flags this discrepancy. Clear reporting of the estimand, group ordering, scale, non-inferiority margin, analysis population, and handling of missing symptom diaries would be important for evaluating how the findings answer the trial question.

Precision matters as much as the point estimate. The recalculated confidence interval spans both negative and positive differences, so the available counts do not sharply identify the direction or size of the contrast. The planning illustrations further show, under their stated assumptions, how sample-size needs increase when planning for smaller effects. Those illustrations are not evidence about the study's original design or the probability that its result is true.

Finally, the study collected outcomes across vaccination visits and followed participants through Day 121, with both symptom-focused and broader safety measures. Interpreting such a record requires keeping primary and secondary outcomes distinct, accounting for multiple comparisons, and understanding how diary completion and analysis populations were handled. The record provides useful descriptive results while leaving several details needed for a fully independent statistical assessment unreported.

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.

Several trial-specific limitations of interpretation follow from the registry record. The primary sponsor analysis is labeled non-inferiority, but the margin and the direction convention for its difference are not reported in the result details. The registry flags a discrepancy between that result and a simple unadjusted recalculation from the posted counts. Without the full statistical analysis plan and method details, the two results cannot be reconciled from the registry record.

The primary symptom outcome combines the first and second vaccination visits. This provides an overall summary across both visits, but it does not show the contribution of each visit; the separately posted visit outcomes provide some context without resolving all questions about symptom timing. Daily symptom reporting used either electronic or paper diaries according to participant preference. The registry record does not report diary completion, missing entries, or how incomplete data were treated.

The study includes participants described broadly as adults, adolescents, and children, but the available outcome summaries do not provide age-specific results or other subgroup estimates. They also do not describe participant characteristics in enough detail to assess how well the enrolled group represents particular populations. The record describes different mRNA vaccination circumstances, including primary series and booster dosing, but does not provide results separated by those circumstances in the posted primary comparison.

The safety summaries report few serious adverse events, but aggregate counts do not describe event timing, causal assessment, or the precision of group differences. The record also does not report a multiplicity plan for the multiple secondary outcomes. These limitations concern what can be evaluated from the registry record; they do not establish that additional analyses or documentation do not exist elsewhere.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Simultaneous mRNA COVID-19 and IIV4 Vaccination Study — NCT05028361.
• Registry record last updated 2024-03-19; status last verified 2024-02.
• Results first posted 2024-03-19.
• 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

NCT05028361 is a completed, randomized, observer-blinded, parallel-group Phase 4 study sponsored by Duke University, with enrollment of 348. It compared simultaneous mRNA COVID-19 and IIV4 vaccination with sequential administration, planned 7-14 days apart. The primary outcome counted participants with moderate or more severe fever, chills, myalgia, or arthralgia after Vaccination Visits 1 and 2 combined, up to 7 days post vaccination.

The posted primary counts are 43 of 168 in the simultaneous group and 52 of 166 in the sequential group. The recalculated unadjusted risk difference is 0.057, with a 95% confidence interval from -0.039 to 0.154. The registry also reports a sponsor non-inferiority analysis and flags a discrepancy with the recalculation; the sponsor's own analysis takes precedence. The non-inferiority margin and several analysis details are not reported in the registry record, limiting independent assessment.