A Study to Evaluate the Safety and Immunogenicity of Inactivated Varicella Zoster Virus (VZV) Vaccine in Adults With Autoimmune Disease (V212-009): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study to Evaluate the Safety and Immunogenicity of Inactivated Varicella Zoster Virus (VZV) Vaccine in Adults With Autoimmune Disease (V212-009) (NCT01527383), a randomized phase 2 study. The primary outcome is Percentage of Participants With a Serious Adverse Event.

2. Clinical Question

These are related but distinct questions. Immunogenicity concerns the immune response measured after vaccination, whereas the posted primary endpoint is a safety measure based on serious adverse events. The record’s stated statistical criterion for the immune-response hypothesis is that the lower bound of a two-sided 95% confidence interval for geometric mean fold rise in vaccine recipients is >1.0. The record does not include the immune-response estimate or its confidence interval, so that criterion cannot be assessed from the posted results.

The safety comparison describes event percentages in the V212 and placebo groups during follow-up through the stated timeframe. It does not, by itself, answer every safety or immunogenicity question raised by the trial’s broader purpose. The record also lists injection-site, systemic, and elevated-temperature adverse events as secondary outcomes; numerical details are not reported for all of those outcomes.

3. Trial Design

This was a phase II, randomized, placebo-controlled, triple-masked, parallel-group clinical trial. The registry lists an enrollment of 354 and a completed status. Participants had autoimmune disease, with several example conditions named in the record. The study was designed to evaluate V212 safety and immunogenicity in this population.

Participants assigned to V212 were scheduled to receive four 0.5 mL subcutaneous injections approximately 30 days apart. The placebo group was assigned injections using the same stated volume and schedule. The record recommends the deltoid area and alternating arms for each dose. Further details about the randomization procedure, allocation concealment, masking procedures, or how treatment assignments were implemented are not reported in the registry record.

The posted primary safety endpoint is the percentage of participants with one or more serious adverse events up to approximately 28 days after the fourth vaccination, approximately Day 118. Its analysis population is described as participants who received at least one dose of vaccine and had safety follow-up. The arm denominators shown for this endpoint are 289 for V212 and 62 for placebo. These are safety-analysis denominators; the record does not explain in the posted results why they differ.

The brief study description focuses on VZV-specific immune responses around 28 days after the fourth vaccination and states a confidence-interval criterion for that hypothesis. However, the numerical primary result posted in the registry concerns serious adverse events. The immune-response results and the relationship between the stated hypothesis and the posted safety outcome are not reported in the registry record. The record lists six outcome measures and two analyses, but does not provide a full statistical analysis plan or details about which analyses were prespecified.

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: A total of 362 participants were screened and 354 were enrolled.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Participants with Day 1 and/or postdose data available. This outcome measure applied only to participants who received V212; placebo participants were not assessed for this outcome.

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: All enrolled participants

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Participants With a Serious Adverse Event, measured over Up to ~28 days after Vaccination 4 (~Day 118).

The primary endpoint is the percentage of participants with one or more serious adverse events during follow-up up to approximately 28 days after the fourth vaccination, approximately Day 118. A serious adverse event is defined in the registry as an event resulting in death, being life threatening, causing persistent or significant disability or incapacity, resulting in or prolonging hospitalization, being a congenital anomaly or birth defect, being cancer, being an overdose, or being an important medical event based on appropriate medical judgment.

Reporting the percentage with at least one serious event gives a participant-level summary: a participant is counted as having the endpoint if one or more qualifying events occurred. This is different from counting every event, since one participant may experience multiple events. The endpoint is used to summarize serious safety outcomes over the stated follow-up period. It does not capture all possible adverse events, and it does not measure the immune response that the brief study description identifies as the primary hypothesis.

The safety population is defined as participants who received at least one dose and had safety follow-up. The posted arm percentages are 2.8% for V212 and 1.6% for placebo. The record also contains inconsistent V212 serious-event counts in separate result summaries, so the count-level detail requires caution. The registry record does not report a causal assessment for individual events.

7. Results Posted in the Registry

• V212: 2.8% (8/289) versus 1.6% (1/62) on control; risk difference 1.2 percentage points (95% CI -2.5 to 4.8), risk ratio 1.72 (0.22–13.47); unadjusted two-proportion z-test p = 0.602.

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 With Elevated Temperature Prompted on the Vaccination Report Card

• 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:
  • V212: 7.0% (20/284) versus 4.9% (3/61) on control; risk difference 2.1 percentage points (95% CI -4.1 to 8.3), risk ratio 1.43 (0.44–4.67); unadjusted two-proportion z-test p = 0.546.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between V212 and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists injection-site adverse events, systemic adverse events, and elevated temperature as secondary outcomes. The detailed numerical secondary comparison in the posted results concerns elevated temperature. The other listed secondary outcomes’ numerical estimates are not reported in the registry record, so the full pattern across all named outcomes cannot be compared from the available results.

For elevated temperature, the posted estimate is an unadjusted comparison and its confidence interval includes zero. It therefore does not provide a clear distinction between the groups. This is broadly consistent with the primary safety comparison in the limited sense that neither posted comparison provides a precise separation between the arms. It does not show that the outcomes are the same, and the endpoints concern different event types.

Secondary outcomes can help describe safety patterns, but their interpretation depends on how many outcomes and comparisons were examined and whether the analysis plan accounted for that multiplicity. When several hypotheses are tested, the chance of at least one apparently unusual result can increase. The registry record does not report a multiplicity adjustment or a prespecified hierarchy for the secondary outcomes. The unadjusted secondary results therefore carry less weight than a single prespecified confirmatory comparison and should be treated as descriptive evidence.

The registry lists six outcome measures and two analyses, but does not give enough detail to establish how the posted secondary outcomes relate to all measured outcomes or whether all analyses were prespecified. The reported secondary information should not be used to infer a comprehensive adverse-event profile or to replace the missing immune-response result.

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

• Percentage of Participants With an Injection-site Adverse Event Prompted on the Vaccination Report Card
• Percentage of Participants With a Systemic Adverse Event Prompted on the Vaccination Report Card
• Percentage of Participants With Elevated Temperature Prompted on the Vaccination Report Card

9. Statistical Interpretation

10. Statistical Methods Explained

A percentage with an event is a binary outcome: each participant is classified as having or not having at least one event during the specified period. The arm percentages describe the observed proportion in each group. The risk difference expresses the contrast between those proportions on the absolute scale. A positive estimate in the posted comparison means the observed proportion was higher in V212 than in placebo; it does not, on its own, show that the difference is precise or reliable.

A confidence interval describes a range of values compatible with the observed data under the statistical method used. It is not a guarantee that the true value lies in that range, and it does not remove uncertainty caused by limited information. For the primary safety comparison, the interval extends from a negative to a positive risk difference and includes zero. This means the data do not distinguish clearly between a lower, similar, or higher event proportion in V212 relative to placebo. The p-value is another summary of compatibility with a null comparison under the specified test; it is not the probability that the null hypothesis is true.

The posted comparisons include risk differences and also relative measures, including risk ratios and odds ratios. A risk ratio compares event proportions as a ratio; an odds ratio compares event odds. These measures use different scales and may be less intuitive than an absolute difference. With sparse events, relative measures can be especially uncertain, so they should be read together with their confidence intervals and the observed counts. The registry record does not describe a sponsor-adjusted model for these comparisons. The posted p-values are unadjusted.

The primary endpoint counts participants with one or more serious adverse events, not the total number of serious events. That distinction matters when an individual can have more than one event. The record’s event-count summaries are also inconsistent for V212, listing eight in the comparison data and nine in the safety summary. Because no reconciliation is reported, interpreting the event count as a single settled value would go beyond the registry record.

Why can an interval include zero?

For an absolute difference, zero represents no difference between the groups. An interval spanning zero indicates that the observed data are not precise enough to exclude that possibility at the interval’s stated confidence level. It also includes values on both sides of zero, so the direction of the underlying difference is not resolved by the estimate alone. This is not proof that the groups are equivalent. Establishing equivalence or non-inferiority requires a prespecified margin and an analysis designed for that purpose; such details are not reported in the registry record.

Why does event rarity matter?

When few participants experience an outcome, each event can have a noticeable influence on the estimated proportion and on the comparison. Sparse data tend to yield less precise estimates, particularly in a smaller arm. The observed event counts and confidence interval should therefore be considered alongside the percentages. A non-significant result in this setting does not demonstrate that a meaningful difference is absent; it indicates that the posted comparison does not provide a precise distinction.

What does over-dispersion mean in general?

In general, over-dispersion means that observed variability is greater than a statistical model expects. It is relevant to some count and rate analyses, where failing to account for extra variability can make uncertainty appear too small. The primary outcome is reported as a participant percentage, and the registry record does not report an over-dispersion model or another adjusted analysis. It would therefore be inappropriate to assert that over-dispersion was present or addressed in this trial.

How should the stated immune-response criterion be understood?

In general, a geometric mean fold rise summarizes multiplicative changes in a measured quantity across participants. A confidence interval for that summary conveys uncertainty about the estimated response. The record states that the lower bound of a two-sided 95% interval must be >1.0 for the stated criterion to be satisfied. The immune-response estimate and interval are not reported in the registry record, so the criterion cannot be evaluated from the posted safety result.

The registry record does not report the trial’s original sample-size justification, the complete prespecified analysis plan, an interim-analysis plan, multiplicity procedures, or detailed missing-data methods. Those omissions limit the ability to assess whether the posted analyses match the original design or how much confidence to place in analyses beyond the descriptive safety comparison.

11. Confidence Intervals and Precision

The primary comparison’s risk-difference estimate is 0.011, with a 95% confidence interval from -0.025 to 0.048. The range crosses zero and includes values in both directions. This is a broad range relative to the estimate, indicating that the comparison does not pin down the direction or size of a group difference with much precision. The interval should be read as uncertainty about the contrast, not as evidence of equivalence.

The confidence interval is more informative than the point estimate alone. The estimate is a single summary of the observed comparison; the interval conveys how much uncertainty remains under the method used. The p-value of 0.602 is consistent with the lack of a clear distinction in the posted comparison, but it does not quantify the probability that there is no difference.

The unequal safety denominators, 289 for V212 and 62 for placebo, are relevant to precision. In general, a smaller comparison group contributes less information, especially when events are uncommon. The event-count inconsistency for V212 adds a separate interpretive limitation: the comparison data list eight participants with serious adverse events, whereas the safety summary lists nine. The registry record does not explain which count should be used to reconcile those summaries.

No confidence intervals for the individual arm percentages are reported in the registry record. Precision should therefore be judged using the posted comparison interval rather than inferred from the percentages alone. The immune-response confidence interval described as part of the study hypothesis is also not reported, so precision for that outcome cannot be assessed from these results.

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 justification. For these binary outcomes, the figures are participants per arm; they are not total event counts. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect used for each illustration is the stated fraction of the observed effect.

The 80% power column describes the number of participants per arm that the planning calculation estimates would be needed to have an 80% chance of detecting the specified effect under those assumptions, if that effect were the true effect and the model assumptions held. The 90% power column uses a higher probability of detecting the specified effect, and consequently requires a larger planned sample under the same assumptions. These are prospective planning quantities, not evidence about what the completed trial was able to detect.

Rows for a smaller fraction of the observed effect represent a smaller target difference. Smaller effects are harder to distinguish from random variation, so the planning calculation requires more participants per arm. The displayed values depend on treating the observed effect as a planning reference, which can be unstable when event counts are sparse. They should not be read as a reconstruction of the study’s original sample-size target, since the original design assumptions and justification are not reported in the registry record.

This is not observed power. The completed trial’s results are better interpreted through the estimated effect and its confidence interval, which describe the observed comparison and its uncertainty.

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 = 0.016; treatment proportion p₁ = 0.028; average p̄ = 0.022.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.2070 = 0.4057.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.2068 = 0.1741.
4. n = (0.4057 + 0.1741)² / (0.0116)² = 2,518.9, rounded up to 2,519 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 <- 0.0161290322580645                          # control proportion
p1 <- 0.027681660899654                          # 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(1527383)
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 = 2,519 (80% power), 3,372 (90% power)
 75% of observed effect: n per arm = 4,190 (80% power), 5,609 (90% power)
 50% of observed effect: n per arm = 8,776 (80% power), 11,748 (90% power)
power.prop.test: 2518.9 
Simulated power at n = 2,519 per arm: 0.806 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study examines several outcomes, comparisons, time points, or subgroups. Even if each individual statistical test uses the same significance threshold, conducting multiple tests can increase the chance that at least one result appears noteworthy by chance. Common approaches include adjusting the testing threshold, controlling a family-wise error rate, controlling a false discovery rate, or specifying an ordered testing strategy. The registry record does not report whether any such approach was used.

This matters because the record lists six outcome measures, names three secondary adverse-event outcomes, and reports two analyses. Without a prespecified hierarchy or multiplicity plan, the relative confirmatory status of the results is unclear. The unadjusted comparisons should not be read as though they were protected from the interpretive concerns that arise when multiple outcomes are examined.

Missing-data methods are also not reported in the registry record. The primary safety population is described as participants who received at least one dose and had safety follow-up, but the record does not describe how participants without complete follow-up were handled, whether any outcome data were missing, or whether sensitivity analyses were performed. The arm denominators are reported, but the reasons for the different denominators are not explained.

The record does not report the detailed analysis populations for all endpoints, a complete statistical analysis plan, or interim-analysis procedures. It also does not report how the analysis handled protocol deviations or whether any covariate adjustment was planned. These omissions do not establish that such procedures were absent; they mean that they are not available in the registry record for assessment.

Finally, the record’s stated primary hypothesis concerns immunogenicity, while the numerical primary result posted is a serious adverse event endpoint. The statistical criterion for the immune-response hypothesis is described, but the corresponding estimate and confidence interval are not reported. This gap prevents assessment of the stated hypothesis and makes it important to distinguish the stated study objective from the endpoint with posted numerical results.

15. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: upper respiratory tract infection (1.6%), pneumonia (0.7%), anaemia haemolytic autoimmune (0.3%), keratitis (0.3%), urinary tract infection (0.3%).

The serious adverse event percentages reported for the primary safety comparison are 2.8% for V212 and 1.6% for placebo, through up to approximately 28 days after the fourth vaccination. The associated comparison is imprecise: its confidence interval spans zero, and the unadjusted p-value is 0.602. These results describe the observed data in the two safety groups; they do not establish that the underlying rates are the same or different.

The registry’s separate safety summary lists nine V212 participants and one placebo participant with serious adverse events, while the comparison data list eight V212 participants and one placebo participant. No explanation for the V212 count difference is reported in the registry record. The arm percentages and comparison should be interpreted with that inconsistency in mind rather than attempting to resolve it from the posted information.

The safety summary also lists one death in V212 and none in placebo. The registry record does not report a causal assessment linking the death or other individual events to study treatment. Serious adverse event counts should not be treated as proof of causation, and the follow-up period and safety population delimit what these figures describe.

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

The posted results show the percentages of participants with at least one serious adverse event during the stated safety follow-up and an unadjusted comparison between V212 and placebo. The estimated risk difference is 0.011, with a 95% confidence interval from -0.025 to 0.048. Because that interval includes zero and extends in both directions, the result does not precisely establish the direction or size of a difference in this trial population during this follow-up period.

This does not mean the two groups are proven equivalent, nor does it show that no serious adverse events occurred. Events are reported in both groups, and the registry’s separate V212 event count conflicts with the comparison count. The record does not explain the discrepancy. The safety result also applies to the stated analysis population and timeframe, rather than to all possible populations, durations, or outcomes.

The trial’s brief description identifies an immunogenicity hypothesis and a criterion based on the lower bound of a confidence interval for geometric mean fold rise. The numerical immune-response result is not reported in the registry record. The posted serious adverse event comparison therefore cannot establish whether the immunogenicity criterion was met.

The registry record does not report enough information to evaluate the original sample-size rationale, missing-data handling, multiplicity procedures, or the full analysis plan. The planning illustrations based on the observed effect are not evidence of the trial’s actual power. Overall, the posted data support a cautious description of the recorded safety comparison, not a broad conclusion about vaccine effects or the complete study objective.

17. Why This Trial Matters Statistically

This trial illustrates why a study’s stated scientific question and its posted numerical endpoint need to be distinguished. The brief description focuses on VZV-specific immune responses and gives a statistical criterion for that hypothesis. The numerical primary result available in the registry concerns serious adverse events. Since the immune-response estimate is not reported, the central immunogenicity question cannot be evaluated from these results.

It also demonstrates the importance of reading effect estimates with their intervals. The point estimate may attract attention, but the interval shows that the comparison remains uncertain and includes no difference. A non-significant p-value does not demonstrate equivalence, while a confidence interval makes the range of plausible contrasts more visible.

Trial records are most useful when outcome definitions, analysis populations, event counts, and planned statistical methods align clearly. In this record, V212 serious-event counts differ between the comparison and safety summaries, and the reason is not reported. That inconsistency limits confidence in count-level interpretation and highlights the value of transparent result reporting.

Finally, planning illustrations should not be confused with the trial’s original design or with observed power. The registry does not report its original sample-size justification, and the posted planning quantities use the observed effect as a reference. Keeping these distinctions clear helps readers separate what the results directly describe from what remains unknown.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The posted primary safety comparison uses 289 V212 participants and 62 placebo participants. This imbalance limits the information contributed by the smaller group, particularly for an outcome with relatively few events. The registry record does not explain why the safety denominators differ or how they relate to the randomized enrollment.

The V212 serious-event count is inconsistent across the posted summaries: the comparison data list eight participants, and the safety summary lists nine. The placebo count is one in both. No reconciliation is reported, which limits interpretation of the event counts and complicates independent checking of the displayed percentages.

The follow-up for the primary endpoint extends only up to approximately 28 days after the fourth vaccination, approximately Day 118. The result therefore describes the stated period and does not characterize longer-term safety. The record does not provide numerical results for all named secondary adverse-event outcomes, and it does not report the immunogenicity estimate despite describing an immunogenicity hypothesis.

The registry record does not report the original sample-size justification, detailed missing-data methods, multiplicity procedures, interim analyses, or a full statistical analysis plan. It also does not provide detailed information on randomization implementation, masking procedures, or reasons for differences in endpoint denominators. These limits restrict assessment of the analysis and its relationship to the original design, without establishing that any particular procedure was or was not used.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: A Study to Evaluate the Safety and Immunogenicity of Inactivated Varicella Zoster Virus (VZV) Vaccine in Adults With Autoimmune Disease (V212-009) — NCT01527383.
• Registry record last updated 2019-01-14; status last verified 2019-01.
• Results first posted 2019-01-14.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

This completed phase II trial randomized adults with autoimmune disease to V212 or placebo in a triple-masked, parallel-group design. The registry lists enrollment of 354 and a four-dose injection regimen, with doses approximately 30 days apart.

The posted primary endpoint is the percentage of participants with one or more serious adverse events through up to approximately 28 days after the fourth vaccination. The reported arm percentages are 2.8% for V212 and 1.6% for placebo; the unadjusted risk-difference interval includes zero. The V212 serious-event count differs between two registry summaries.

The study description states an immunogenicity hypothesis, but its numerical immune-response results are not reported in the registry record. Details about multiplicity, missing-data methods, and the original sample-size justification are also not reported.