Safety and Immunogenicity of a Novel Vaccine Formulation MV-ZIKA-RSP (V187-001): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Safety and Immunogenicity of a Novel Vaccine Formulation MV-ZIKA-RSP (V187-001) (NCT04033068), a randomized phase 1 study. The primary outcome is Percentage of Participants Who Experienced an Adverse Event (AE) up to Day 56.

2. Clinical Question

The trial also assessed safety through Day 182 and immune-response measures. The central statistical question is descriptive: how frequently did participants experience adverse events in each randomized group, and how much precision do the small group sizes permit? This phase 1 study was designed first to investigate safety and tolerability; the registry record does not report a formal hypothesis about the size of an acceptable difference between schedules.

3. Trial Design

The registry describes a randomized, observer-blinded, parallel-group phase 1 trial. Masking is recorded as quadruple. Enrollment was 48, and the record marks the study completed. The listed start date is 2019-08-02 and the primary completion date is 2020-01-30. The sponsor is Themis Bioscience GmbH.

Participants were allocated across four schedules. Group A received two high-dose MV-ZIKA-RSP vaccinations, on Day 0 and Day 28; Group B received two low-dose vaccinations on those days. Group C received high-dose vaccine on Day 0 and placebo on Day 28. Group D received placebo on both days. The registry lists 14 participants in each of Groups A and B, 12 in Group C, and 8 in Group D. These randomized group sizes are unequal, with the placebo group smallest.

The primary endpoint covers adverse events up to Day 56, and its stated analysis population is all randomized participants who received at least one dose. Secondary safety outcomes include solicited and unsolicited adverse events and serious adverse events through Day 182. Immune-response outcomes include antibody geometric mean titers measured by virus neutralization and ELISA, and T-cell responses measured using IFN-γ and IL-2 ELISpot assays. Laboratory parameters are also listed.

The registry record does not report the original sample-size justification, detailed randomization procedures, or a full statistical analysis plan. It also does not report how missing outcome data were handled or whether analyses were conducted according to treatment received in addition to the stated primary analysis population.

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 were screened within two weeks prior to randomization.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: All randomized participants who received at least one dose of study treatment.

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 Percentage of Participants Who Experienced an Adverse Event (AE) up to Day 56, measured over Up to Day 56.

The primary endpoint is the percentage of participants who experienced an adverse event (AE) up to Day 56. The registry defines an AE as any untoward medical occurrence in a participant who has received an investigational medicinal product; an event does not have to be caused by or related to that product. Thus, the endpoint records whether an event occurred, rather than establishing its cause.

For each group, the percentage expresses the frequency of participants with an AE within the stated follow-up window. It does not count the total number of events per participant, grade their severity, or by itself distinguish events related to vaccination from unrelated medical occurrences. Those questions require additional event-level information and definitions.

General statistical context: a binary endpoint such as “experienced at least one AE” is useful for summarizing how many participants had an event, but it compresses potentially varied experiences into a yes-or-no outcome. The same participant is counted once for this endpoint whether they experienced one event or several. A percentage is therefore a concise group-level safety summary, not a complete description of the kinds, timing, severity, or attribution of events.

The primary results were 92.9% for each two-vaccine group, 91.7% for the high-dose-plus-placebo group, and 62.5% for the placebo group. These percentages describe the observed participants through Day 56. The registry record does not report sponsor confidence intervals for these primary percentages.

7. Results Posted in the Registry

• Group A: V187 (High Dose) - V187 (High Dose): 92.9% (13/14) versus 91.7% (11/12) on control; risk difference 1.2 percentage points (95% CI -19.5 to 21.8), risk ratio 1.01 (0.81–1.27); unadjusted two-proportion z-test p = 0.910.
• Group B: V187 (Low Dose) - V187 (Low Dose): 92.9% (13/14) versus 91.7% (11/12) on control; risk difference 1.2 percentage points (95% CI -19.5 to 21.8), risk ratio 1.01 (0.81–1.27); unadjusted two-proportion z-test p = 0.910.

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 Who Experienced a Solicited AE up to Day 182

• 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:
  • Group A: V187 (High Dose) - V187 (High Dose): 92.9% (13/14) versus 83.3% (10/12) on control; risk difference 9.5 percentage points (95% CI -15.5 to 34.6), risk ratio 1.11 (0.83–1.49); unadjusted two-proportion z-test p = 0.449.
  • Group B: V187 (Low Dose) - V187 (Low Dose): 78.6% (11/14) versus 83.3% (10/12) on control; risk difference -4.8 percentage points (95% CI -34.9 to 25.3), risk ratio 0.94 (0.65–1.37); unadjusted two-proportion z-test p = 0.759.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Group A: V187 (High Dose) - V187 (High Dose) and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Group B: V187 (Low Dose) - V187 (Low Dose) and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Participants Who Experienced an Unsolicited AE up to Day 182

• 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:
  • Group A: V187 (High Dose) - V187 (High Dose): 57.1% (8/14) versus 58.3% (7/12) on control; risk difference -1.2 percentage points (95% CI -39.3 to 36.9), risk ratio 0.98 (0.51–1.89); unadjusted two-proportion z-test p = 0.951.
  • Group B: V187 (Low Dose) - V187 (Low Dose): 71.4% (10/14) versus 58.3% (7/12) on control; risk difference 13.1 percentage points (95% CI -23.5 to 49.7), risk ratio 1.22 (0.68–2.19); unadjusted two-proportion z-test p = 0.484.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Group A: V187 (High Dose) - V187 (High Dose) and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Group B: V187 (Low Dose) - V187 (Low Dose) and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes extend assessment beyond the primary Day 56 AE measure. They include solicited and unsolicited AEs and serious AEs through Day 182; antibody responses measured by virus neutralization and ELISA; IFN-γ and IL-2 T-cell responses; and laboratory parameters. The posted numerical results available for solicited and unsolicited AE percentages show variation across the four groups, but the group sizes remain small. Numerical results for the other listed secondary measures are not reported in the registry record.

The secondary AE results complement the primary safety outcome by describing longer follow-up and distinguishing solicited from unsolicited events. They do not replace the primary endpoint, which uses a broader AE definition through Day 56. Nor do they establish that any event was caused by vaccination. The immune-response outcomes address a different question from AE frequency: they describe measured antibody or cellular responses, rather than clinical protection. The registry record does not report results that would establish a link between those laboratory measures and clinical outcomes.

General statistical context: when many outcomes and comparisons are examined, some results may appear notable by chance even when there is no underlying effect. An adjustment for multiplicity, a prespecified hierarchy, or a clear distinction between confirmatory and exploratory analyses can help readers assess that risk. The registry record does not report a multiplicity strategy. Accordingly, unadjusted secondary results carry less weight than a prespecified primary analysis and should be treated as descriptive or hypothesis-generating, particularly when estimates are imprecise. The record’s outcome and analysis counts reinforce the importance of caution, but do not reveal which results, if any, were intended to be confirmatory.

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

• Percentage of Participants Who Experienced a Solicited AE up to Day 182
• Percentage of Participants Who Experienced an Unsolicited AE up to Day 182
• Percentage of Participants Who Experienced a Serious Adverse Event (SAE) up to Day 182
• Geometric Mean Titer (GMT) of Anti-ZIKA-RSP (Zikavirus Recombinant Subviral Particle) Antibodies by Virus Neutralization Test (VNT) on Days 0, 28 and 56
• GMT of Anti-ZIKA-RSP Antibodies by Enzyme Linked Immunosorbent Assay (ELISA) on Days 0, 28 and 56
• T-Cell Immune Response Assessed by Number of Spot Forming Cells (SFC) Per Million Peripheral Blood Mononuclear Cells (PBMCs) Measured by Interferon (IFN)-γ Enzyme-linked Immune Adsorbent Spot (ELISpot) Assay on Day 56
• T-Cell Immune Response Assessed by Number of SFC Per Million PBMCs Measured by Interleukin-2 (IL-2) ELISpot Assay on Day 56
• Laboratory Parameters (Hematology): Concentration of Basophils, Eosinophils, Leukocytes, Lymphocytes, Monocytes, Neutrophils, Platelets on Days 28 and 56

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary at the participant level: each participant either experienced an AE by Day 56 or did not. The posted group percentages summarize the share meeting that definition. The primary analysis population is described as all randomized participants who received at least one dose of study treatment. The registry record does not report a detailed method for handling participants with incomplete follow-up or missing AE status.

The sponsor reported a Fisher-Freeman-Halton Test across the four groups, with p = 0.200. General statistical context: this is an exact test used to assess whether categorical outcomes are distributed differently across multiple groups. It is an extension of Fisher’s exact test for a larger contingency table. It can be useful when group sizes are small and the approximations used by some large-sample tests may be less reliable. The reported test concerns the overall four-group comparison; it does not identify which specific group contrast accounts for any pattern and does not provide a direct estimate of the size of a pairwise difference.

Alongside the sponsor’s overall test, the recalculated pairwise results compare the two high-dose group and the two low-dose group separately with the high-dose-plus-placebo group. These are simple, unadjusted re-calculations from the posted summary statistics, expressed as risk differences with 95% confidence intervals and unadjusted p-values. A risk difference is the event percentage in one group minus the event percentage in the comparison group, expressed as a proportion. The intervals for both primary pairwise comparisons are -0.195 to 0.218, around an estimate of 0.012. Because the comparison is not adjusted for the set of comparisons, it should be read as exploratory rather than as a multiplicity-controlled confirmatory result.

General statistical context: a risk difference uses the absolute scale and answers how far apart the two observed event proportions are. Other measures, such as a risk ratio or odds ratio, express relative rather than absolute contrasts. Each measure has its own interpretation, and estimates from a small sample can be unstable. The registry does not report a sponsor-selected primary pairwise contrast or a confidence interval for the overall four-group test.

What does the overall test tell readers?

The reported Fisher-Freeman-Halton result evaluates the four groups together. It does not mean that every possible pair of groups was separately tested, nor does it supply evidence that the groups are identical. A non-small p-value can arise when estimates are imprecise, especially with small groups. The test result should therefore be read with the actual observed percentages and the uncertainty around recalculated contrasts, rather than as a standalone conclusion.

What do the recalculated comparisons add?

The pairwise re-calculations put an estimated absolute difference and interval around comparisons of Groups A and B against Group C. They are not a substitute for the sponsor’s reported overall analysis. No discrepancy between the sponsor analysis and the recalculation is flagged in the registry record, but the sponsor’s analysis remains the reported trial analysis. The recalculations are unadjusted and do not account for a broader family of outcomes or comparisons.

The record lists 19 outcome measures and 22 analyses, while 18 secondary outcomes are posted. These counts indicate that the results encompass multiple endpoints and analyses, but the registry record does not report a multiplicity adjustment strategy or a hierarchy for interpreting secondary endpoints. The methods used for the recalculated estimates are simple unadjusted methods; the original detailed statistical plan and the sponsor’s full analysis methods beyond the named overall test are not reported in the registry record.

11. Confidence Intervals and Precision

The primary group percentages are based on small participant groups: 14 in each two-vaccine group, 12 in the high-dose-plus-placebo group, and 8 in the placebo group. With limited group sizes, a small change in the observed count can materially change a percentage. The posted percentages are descriptive estimates, not exact values for a broader population.

The registry record does not report sponsor confidence intervals for the primary AE percentages. The recalculated pairwise risk-difference intervals offer one view of precision: the two high-dose comparison and the two low-dose comparison each have an estimate of 0.012 and a 95% interval from -0.195 to 0.218. These intervals span zero and include differences in either direction. Their width signals substantial uncertainty about the magnitude and direction of the underlying contrast.

General statistical context: a confidence interval is a range of values generated by a method that, over repeated use under its assumptions, would cover the true parameter at the stated rate. It is not a guarantee that the true value lies within a particular calculated interval, nor does it assign probability to each value in that range. A wide interval indicates that the data do not pin down the estimate closely. An interval containing zero for a difference means the data are compatible with no difference as well as with nonzero differences; it does not prove there is no difference.

Unequal group sizes also mean precision is not the same across every potential comparison. The smaller placebo group contributes less information than a larger group would. Interpretation should therefore emphasize the broad uncertainty, not just the point estimates or the sponsor’s overall p-value.

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 figures are illustrations based on observed effects, not the trial’s original design justification. For these binary outcomes, the figures are participants per arm, not total events. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; each scenario uses the stated fraction of the observed effect as the effect to detect. The original trial’s own sample-size assumptions are not reported in the registry record.

The 80% power column describes the number of participants per arm estimated to give an 80% chance of detecting the specified effect under the planning assumptions, if that effect is the true one and the analysis method and assumptions apply. The 90% power column gives the corresponding planning number for a 90% chance. These are design-planning quantities, not statements about the chance that the trial’s result is true. This is not observed power.

Rows planning for 100%, 75%, or 50% of the observed effect illustrate how the assumed target difference changes the projected sample size. Smaller effects require more participants to distinguish them from random variation with the same nominal power and significance level. This is especially important where the observed difference is small: planning based on a small observed estimate can produce very large figures, and the estimate itself is uncertain because the groups were small.

The calculation uses equal allocation between two arms, whereas this trial randomized participants to four groups with unequal sizes. It therefore should not be read as a reconstruction of the trial design or as a recommended enrollment target. It is a conditional illustration of what a future two-arm comparison might require under the listed assumptions.

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 = 0.917; treatment proportion p₁ = 0.929; average p̄ = 0.923.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.3779 = 0.7406.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.3778 = 0.3179.
4. n = (0.7406 + 0.3179)² / (0.0119)² = 7,906.6, rounded up to 7,907 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 <- 0.916666666666667                          # control proportion
p1 <- 0.928571428571429                          # 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(4033068)
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 = 7,907 (80% power), 10,585 (90% power)
 75% of observed effect: n per arm = 14,305 (80% power), 19,149 (90% power)
 50% of observed effect: n per arm = 32,741 (80% power), 43,830 (90% power)
power.prop.test: 7906.6 
Simulated power at n = 7,907 per arm: 0.799 (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 sponsor’s reported primary analysis is the Fisher-Freeman-Halton Test across the four randomized groups, with p = 0.200. That is the trial’s reported overall inferential result. The recalculated pairwise estimates compare Group A and Group B individually with Group C and use the posted counts and percentages to estimate risk differences, confidence intervals, and unadjusted p-values. They answer narrower questions than the sponsor’s four-group test.

For each recalculated primary comparison, the estimated risk difference is 0.012, the 95% confidence interval is -0.195 to 0.218, and the unadjusted p-value is 0.91. The registry record does not flag a discrepancy. Even so, the recalculations do not replace the sponsor analysis: they are unadjusted contrasts from summary statistics, and they are not identified in the record as the prespecified primary analysis.

The record does not report a sponsor confidence interval for the overall test or a complete statistical analysis plan explaining the choice and ordering of contrasts. The sponsor result and the recalculations should therefore be kept distinct: the former is the reported overall comparison, while the latter provide exploratory pairwise estimates with visible uncertainty.

15. Multiplicity, Missing Data and Analysis Populations

The trial evaluates a primary AE outcome and a range of secondary safety, immune-response, and laboratory outcomes. The registry record lists 19 outcome measures and 22 analyses, with 18 secondary outcomes posted. When multiple outcomes or group comparisons are considered, the chance of at least one apparently unusual result can increase. This is the general statistical problem of multiplicity.

The registry record does not report whether the sponsor adjusted p-values or confidence intervals for multiple comparisons, specified a hierarchy among secondary outcomes, or designated some analyses as exploratory. The reported primary overall test is a four-group comparison; the recalculated pairwise contrasts are unadjusted. Secondary findings therefore should not be interpreted as if each were a separately prespecified confirmatory test.

The primary analysis population is stated as all randomized participants who received at least one dose. The registry record does not report how missing endpoint data were handled, whether any participants were excluded after randomization, or how incomplete follow-up affected the denominators. It also does not report the number of participants with missing data for individual outcomes. These omissions limit assessment of the robustness of the percentages, especially for outcomes collected at later time points.

General statistical context: excluding participants or treating missing outcomes as if no event occurred can alter estimated event frequencies. Different missing-data assumptions can lead to different results, particularly when follow-up is incomplete or the likelihood of missingness relates to participants’ outcomes. No particular handling method should be inferred without a report. Interpretation is therefore anchored to the stated analysis population and the posted results, with the missing-data approach and multiplicity plan remaining unreported in the registry 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: injury (7.1%).

The serious adverse event summary reports one affected participant among 14 in Group B, the two low-dose group. It reports zero affected participants among 14 in Group A, 12 in Group C, and 8 in Group D. Deaths are recorded as 0 in all four groups. The summary also lists Injury at 7.1% among the top serious adverse event terms.

These figures are counts and percentages within small groups over the reported safety follow-up. A zero recorded count in a group does not show that the underlying risk is zero; it means no affected participant was recorded in that group during the observed period. Likewise, a single participant can have a substantial influence on a percentage when the group is small.

General statistical context: serious adverse events are a subset of safety events defined by seriousness criteria, and should not be conflated with all AEs. The primary endpoint includes any untoward medical occurrence and does not require a causal relationship to study treatment. The registry’s summary does not establish causation for the serious event or provide enough detail to assess its clinical course. The small sample and limited number of serious events make comparative estimates especially imprecise.

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

The posted results describe adverse-event frequencies and other planned outcomes in a small randomized phase 1 trial of four vaccination schedules. The primary outcome shows that most participants in each vaccine-containing group experienced at least one AE by Day 56, while the observed placebo-group percentage was lower. The sponsor’s overall test did not show a statistically clear difference across the four groups by that test, and the recalculated pairwise intervals are broad.

These observations do not establish that the schedules are equivalent, that differences are absent, or that any observed event was caused by MV-ZIKA-RSP. The AE definition explicitly includes events not necessarily related to the investigational product. The small group sizes mean that estimates are uncertain, and the registry record does not report an equivalence margin or a non-inferiority framework.

The listed immune-response measures concern antibody and T-cell responses. Such measurements can characterize immunogenicity, but the registry record does not report evidence that the measured responses predict protection against Zika virus infection. The record also does not report clinical efficacy outcomes that would answer whether vaccination prevents infection or disease.

General statistical context: randomized allocation can support fairer group comparisons by reducing systematic differences at baseline, but randomization does not eliminate chance imbalance, measurement limits, or uncertainty—particularly in small groups. Statistical results must be interpreted in light of endpoint definitions, follow-up, missing data, multiplicity, and the precision of estimates. Those considerations constrain what can be concluded from these results.

The appropriate reading is therefore descriptive and exploratory: the registry records the observed outcomes under the study schedules and reports one overall safety comparison. It does not provide a definitive estimate of comparative safety, establish causal attribution for events, or demonstrate clinical benefit.

18. Why This Trial Matters Statistically

This trial illustrates a central statistical challenge in early-phase research: useful descriptive information can be collected while the available sample remains too small for precise comparative estimates. The registry reports 48 participants divided among four schedules, including only 8 in the placebo group. The resulting percentages provide a snapshot of observed experience, but uncertainty around group differences remains substantial.

It also highlights why several statistical summaries answer different questions. The sponsor’s Fisher-Freeman-Halton Test assesses an overall four-group pattern. A risk difference instead estimates an absolute contrast between two groups, while a confidence interval conveys uncertainty about that estimate. These results should be considered together rather than treated as interchangeable forms of evidence.

The trial is also a useful example of the distinction between safety and immunogenicity outcomes. AEs describe reported medical occurrences, whereas antibody titers and T-cell measures characterize immune responses. An immune response is not itself a clinical efficacy outcome. The registry lists these different types of outcomes but does not report numerical results for every listed measure.

Finally, the record demonstrates why transparency about analysis populations, missing data, multiplicity, and sample-size planning matters. Some of those details are not reported in the registry record, so readers must limit their interpretation to what is documented. The sample-size illustrations can help explain how planning depends on assumed effects, but they are not the trial’s original design rationale and do not convert an exploratory phase 1 result into a definitive comparison.

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.

The group sizes are small and unequal, with the placebo group smallest. This limits precision and makes percentages sensitive to a small number of participants. The recalculated intervals are broad, so the observed pairwise estimates do not tightly identify the size or direction of a population difference.

The registry record does not report the original sample-size justification, detailed statistical analysis plan, handling of missing outcome data, or a multiplicity strategy. It also does not report sponsor confidence intervals for the primary percentages. The four-group sponsor test and the unadjusted pairwise recalculations consequently have different roles and should not be conflated.

The primary outcome is a broad participant-level AE measure. It counts whether a participant experienced an event, regardless of whether the event was considered related to treatment, and does not by itself capture severity, recurrence, or event-level detail. The serious adverse event summary is sparse, with one affected participant in one group and none recorded in the others; this is not enough to make precise comparative safety estimates.

Although immune-response outcomes are listed, numerical results for most of the secondary measures are not reported in the registry record. The record also does not report clinical efficacy outcomes. Follow-up windows vary across outcomes, and the missing-data approach for later assessments is not reported. Generalizability beyond the stated healthy-adult age range cannot be determined from the registry record.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Safety and Immunogenicity of a Novel Vaccine Formulation MV-ZIKA-RSP (V187-001) — NCT04033068.
• Registry record last updated 2021-12-06; status last verified 2021-10.
• Results first posted 2021-12-06.
• 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

NCT04033068 is a completed randomized, observer-blinded, parallel-group phase 1 trial sponsored by Themis Bioscience GmbH. The registry lists 48 participants and four schedules: two high-dose vaccinations, two low-dose vaccinations, high-dose vaccine followed by placebo, or placebo twice.

The primary endpoint was the percentage of participants with an AE up to Day 56. Posted percentages were 92.9%, 92.9%, 91.7%, and 62.5%, respectively. The sponsor reported an overall Fisher-Freeman-Halton Test result of p = 0.200. Recalculated pairwise estimates are imprecise, with broad confidence intervals.

Secondary outcomes cover longer-term safety and immunogenicity. The registry record does not report the original sample-size justification, missing-data approach, or multiplicity plan. The results are best read as descriptive findings from a small early-phase trial, not as a definitive comparative estimate or evidence of clinical efficacy.