Multi-antigen CMV-MVA Triplex Vaccine in Reducing CMV Complications in Patients Previously Infected With CMV and Undergoing Donor Hematopoietic Cell Transplant: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Multi-antigen CMV-MVA Triplex Vaccine in Reducing CMV Complications in Patients Previously Infected With CMV and Undergoing Donor Hematopoietic Cell Transplant (NCT02506933), a randomized phase 2 study. The primary outcome is Cytomegalovirus (CMV) Events to Day 100.

2. Clinical Question

The registry describes the vaccine as a way to induce immunity to CMV and identifies reducing CMV complications and the need for antiviral drugs as the study rationale. The primary endpoint is an event count, not a direct measure of immune response or antiviral drug use alone. The posted results can therefore address the recorded CMV-event comparison, while other proposed effects require their own outcome data. The trial also reports all-cause mortality as a secondary outcome; that outcome concerns a different question and follow-up period.

3. Trial Design

This was a phase II, randomized, double-masked, parallel-group, placebo-controlled, multicenter trial. The official title describes an evaluation of the protective function of the CMV-MVA Triplex vaccine in recipients of an allogeneic hematopoietic stem cell transplant. The registry lists enrollment as 102. The posted outcome groups contain 51 participants in the vaccine arm and 51 in the placebo arm.

Participants in the vaccine arm were assigned multi-peptide CMV-MVA vaccine by intramuscular injection on days 28 and 56 post-HCT. Participants in the comparison arm received placebo by the same route and on the same schedule. Laboratory biomarker analysis is also listed as an intervention, but the registry record does not give further detail about its role in the posted primary comparison.

The study start date is 2015-12-21 and the primary completion date is 2018-01-25. Its current registry status is active, not recruiting. Those record dates and status describe the trial record; they do not establish when all analyses were completed or whether the registry record contains every study result.

Random allocation and masking are features of the design intended to support a fair comparison and limit bias, but the registry record does not describe the randomization procedure, who was masked, or how masking was maintained. The original statistical analysis plan, sample-size justification, analysis populations, and missing-data procedures are not reported in the registry record. Accordingly, the posted summary supports a descriptive comparison between the two assigned groups, while the details of the planned analysis cannot be reconstructed from the registry entry alone.

4. Participant Flow and Accounting

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

Overall Study

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 Cytomegalovirus (CMV) Events to Day 100, measured over Prior to day 100 post-HCT.

The primary endpoint counts participants with at least one qualifying CMV event before day 100 post-HCT. The registry defines an event as CMV reactivation at or above 1250 CMV DNA IU/mL, CMV viremia that prompts antiviral therapy, or CMV disease before day 100. The endpoint is reported as a count of participants, rather than as a continuous measure of viral load or a time-to-event estimate.

Combining these clinically relevant event definitions gives a summary of several ways CMV may become a concern during the stated follow-up window. It can capture reactivation meeting the specified threshold, viremia that leads to treatment, or diagnosed disease. The endpoint therefore reflects the trial's stated focus on CMV complications, but it does not separately show the count for each event type in the posted results.

As with any composite definition, the overall count does not reveal which component contributed to a participant's event, whether more than one component occurred, or the timing of each event within the period. Those component-level details are not reported in the registry record. Nor does this endpoint by itself measure all aspects of safety, immune response, or antiviral use beyond the specific event definition.

7. Results Posted in the Registry

• Arm I (Multi-peptide CMV-MVA Vaccine): 9.8% (5/51) versus 19.6% (10/51) on control; risk difference -9.8 percentage points (95% CI -23.4 to 3.8), risk ratio 0.50 (0.18–1.36); unadjusted two-proportion z-test p = 0.162.

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.

All-cause Mortality

• 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:
  • Arm I (Multi-peptide CMV-MVA Vaccine): 15.7% (8/51) versus 15.7% (8/51) on control; risk difference 0.0 percentage points (95% CI -14.1 to 14.1), risk ratio 1.00 (0.41–2.46); unadjusted two-proportion z-test p = 1.000.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm I (Multi-peptide CMV-MVA Vaccine) and the control. The interval gives the range of effects that remain compatible with the data.

The registry posts all-cause mortality as a secondary outcome, with follow-up up to 1 year post-HCT. The recorded counts show no numerical separation between the arms for this outcome. That pattern differs from the direction of the primary CMV-event estimate, but mortality addresses a broader and distinct outcome and should not be treated as a confirmation or refutation of the primary comparison.

Secondary outcomes can add context, but they generally carry less weight than a prespecified primary endpoint when their analysis plans, emphasis, and multiplicity handling are unclear. Examining more than one outcome creates more opportunities for apparently notable findings to arise by chance. The registry record does not report a multiplicity adjustment strategy, a hierarchy of secondary hypotheses, or reported analyses for the secondary outcome. The secondary result should therefore be read descriptively, without treating it as independent confirmatory evidence.

The primary endpoint concerns specified CMV events before day 100; mortality is recorded over a longer period and does not identify the cause of death. It also does not directly measure CMV reactivation, viremia prompting therapy, or CMV disease. The outcomes are related to the broader transplant context but answer different questions. The registry also does not post secondary data on antiviral drug use or separate counts for the components of the primary endpoint.

Across the posted outcomes, there is no basis for combining them into a single overall conclusion or for claiming a consistent pattern of benefit. The secondary information is limited and should be interpreted in light of its status, distinct definition, and unreported analysis details. It can inform the description of the trial record, but does not resolve the uncertainty in the primary result.

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

• All-cause Mortality

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference express?

A risk difference compares the event proportions in two groups by subtracting one group's proportion from the other's. In this trial, the estimate is expressed for the vaccine arm relative to placebo. A negative estimate means the observed event proportion was lower in the vaccine arm; a positive estimate would mean it was higher. The risk difference is an absolute measure: it expresses the gap between group risks on the probability scale, rather than comparing them as a ratio.

The posted risk difference is -0.098. Its interpretation depends on the outcome definition and follow-up period: it concerns participants with a qualifying CMV event before day 100 post-HCT. It is not a measure of the number of events per participant, the duration of an event, or the frequency of each event component separately.

What do the risk ratio and odds ratio add?

The risk ratio compares the event risk in one group with the event risk in the other. A value of 1 represents equal risks; values below or above 1 indicate a lower or higher risk in the vaccine group relative to placebo, respectively. The odds ratio compares event odds rather than risks. These are relative measures, whereas the risk difference is absolute. Each can be useful for describing a binary outcome, but they answer the comparison on different scales and should not be treated as interchangeable.

The registry reports a risk ratio of 0.5 and an odds ratio of 0.446. The confidence intervals for both include 1, the value corresponding to no relative difference. The relative estimates should be interpreted with the same caution as the risk difference: the number of events is limited, and the uncertainty ranges include no difference.

How should a confidence interval be read?

As a general statistical explanation, a confidence interval describes the uncertainty around an estimate under the method used to construct it. It is not a range in which the true value is guaranteed to lie, and it is not a probability statement about a particular hypothesis. For a risk difference, zero represents no difference. An interval that extends across zero is compatible with a range of possible differences that includes no difference as well as effects in either direction.

What does the p-value describe?

The unadjusted p-value is 0.162. In general, a p-value measures how unusual results at least as discrepant as those observed would be under a specified null model and the assumptions of the test. It is not the probability that the observed result occurred by chance, nor the probability that the intervention has no effect. The registry record does not identify the test or provide enough detail to assess its assumptions fully. The p-value is therefore best read with the estimate, interval, and event counts, not as a stand-alone verdict.

What statistical details are missing?

The primary outcome is binary at the participant level: each participant is counted as having or not having a qualifying event during the stated period. The registry gives group counts and several comparison estimates, but does not report the analysis population, handling of missing outcome information, adjustment variables, or a detailed statistical analysis plan. It does not report whether any interim analyses were planned or conducted. These details are not reported in the registry record, so the statistical procedures beyond the posted estimates cannot be assumed.

General statistical context helps explain why uncertainty matters. With binary outcomes, estimates depend on the number of participants and the number experiencing events. When event counts are limited, estimates can vary substantially across samples, and intervals can remain wide. Randomization can support a causal comparison when the trial is conducted and analyzed as planned, but it does not make chance variation disappear. Masking can reduce some forms of bias, but it cannot resolve uncertainty caused by limited information or missing analysis details.

The registry indicates no discrepancy between the posted comparison and the simple unadjusted re-calculation. That agreement does not substitute for a full report of the analysis plan or confirm details that are not included in the record. The posted figures should be understood as the available group-level statistical summary, not as evidence that every possible source of bias or uncertainty has been addressed.

11. Confidence Intervals and Precision

The primary risk-difference estimate is -0.098, and its 95% confidence interval runs from -0.234 to 0.038. The interval crosses zero, the value for no absolute difference. It therefore includes values that would correspond to a lower event risk in the vaccine arm and values that would correspond to a higher event risk. The estimate points in one direction, but the interval shows that the direction and size of the underlying difference are not determined precisely by these results.

The relative measures convey a similar uncertainty. The risk-ratio interval, 0.184 to 1.36, includes 1; the odds-ratio interval, 0.141 to 1.412, also includes 1. These intervals allow for no relative difference as well as differences in either direction. The point estimates alone are not a substitute for the uncertainty ranges.

A confidence interval is not a guarantee that the true effect lies within its endpoints. In general, it is an estimate of precision under the statistical method and assumptions used. The registry record does not provide the interval-construction method or all analysis details, so the intervals should be read as the uncertainty summaries posted with the result.

Precision is limited by the information in this comparison, including the recorded event counts. The results do not establish equivalence: that would require an appropriate design and a defined margin, neither of which is reported in the registry record. A nonsignificant p-value is likewise not proof of no difference. The most defensible reading is that the observed estimate favors the vaccine arm, while the posted confidence intervals leave substantial uncertainty about the magnitude and direction of the underlying difference.

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 participants per arm, not total events. They are illustrations based on the observed effect, rather than the trial's original design calculation. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to a stated fraction of the observed effect. The original sample-size assumptions for the trial are not reported in the registry record.

The planning scenarios are labeled as planning for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. For each scenario, the 80% power column gives the number of participants per arm needed under those assumptions for an 80% chance of detecting the specified effect if that effect were the true one. The 90% power column gives the corresponding per-arm planning number for a 90% chance. These are design probabilities under the assumed model and effect size, not guarantees about a future study's result.

The listed participant counts rise as the assumed effect becomes smaller: detecting a smaller separation between groups generally requires more information, and under these assumptions that means more participants per arm. The observed effect is uncertain, however, so using it as the basis for planning makes the illustration sensitive to the particular estimate from this trial. The values are planning illustrations and are not observed power. The registry does not report the trial's own sample-size justification, so these figures should not be presented as its original target or rationale.

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 = 0.196; treatment proportion p₁ = 0.098; average p̄ = 0.147.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5009 = 0.9817.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4960 = 0.4175.
4. n = (0.9817 + 0.4175)² / (-0.0980)² = 203.7, rounded up to 204 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 <- 0.196078431372549                          # control proportion
p1 <- 0.0980392156862745                          # 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(2506933)
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 = 204 (80% power), 273 (90% power)
 75% of observed effect: n per arm = 388 (80% power), 519 (90% power)
 50% of observed effect: n per arm = 928 (80% power), 1,241 (90% power)
power.prop.test: 203.7 
Simulated power at n = 204 per arm: 0.805 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The registry record does not report a multiplicity strategy. When a study examines several outcomes, time points, subgroups, or statistical comparisons, the chance of at least one apparently unusual result can increase. A prespecified primary endpoint can help identify the main comparison, but the record does not describe a full testing hierarchy or say whether any adjustment was planned. The posted primary p-value is explicitly unadjusted, and the secondary analyses do not include reported analysis details.

Missing-data procedures are also not reported in the registry record. The posted outcome summaries list the group sizes and participant counts, but the record does not explain whether all assigned participants had outcome status ascertained, how unknown status was handled, or whether any imputation or sensitivity analysis was used. Without this information, the impact of missing outcome information cannot be assessed from the registry summaries.

The analysis population is not specified in the posted primary result. The record does not say whether the comparison used all randomized participants, a modified population, or another analysis set, nor does it describe exclusions after randomization. Randomized assignment is an important design feature, but the label alone does not establish which participants were included in the reported analysis.

The original statistical analysis plan, interim-analysis plan, and trial sample-size justification are not reported in the registry record. It is not possible to infer from the posted results whether these decisions were prespecified or how they were handled. These omissions matter because choices about analysis populations, missing outcomes, interim looks, and multiplicity can affect interpretation. The estimates remain informative as the results recorded, but they cannot be evaluated against a complete analysis plan using the registry entry alone.

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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: diarrhea (9.8%), fever (9.8%), chills (3.9%), dyspnea (3.9%), febrile neutropenia (2.0%).

The registry reports serious adverse events in 15 participants in the vaccine arm and 14 in the placebo arm, with 51 at risk in each arm. Other adverse events are recorded for 50 participants in the vaccine arm and 51 in the placebo arm. The registry also records 8 deaths in each arm. These are descriptive counts; the record does not establish that an event was caused by the vaccine or placebo.

Among the listed serious adverse event terms are diarrhea and fever, each reported as 9.8%; chills and dyspnea, each as 3.9%; and febrile neutropenia and nausea, each as 2.0%. The registry listing does not give further detail in this summary about event timing, severity grading, relatedness, repeat events, or the denominator used for each term. Those percentages should not be interpreted as a complete safety profile.

Safety comparisons require context about follow-up, event definitions, attribution, and the way events were counted. The registry figures provide a snapshot of reported counts, not a powered comparison of safety risks or evidence about causation. They should be read separately from the CMV efficacy endpoint.

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

The primary comparison records fewer participants with a qualifying CMV event in the vaccine arm than in the placebo arm during the specified period. The estimated risk difference is negative, but its confidence interval includes zero and extends to a positive value. The posted evidence therefore does not precisely establish the size or direction of the underlying difference. A p-value of 0.162 does not convert that uncertainty into proof of either benefit or no effect.

The trial is a phase II study in a defined transplant setting: people with prior CMV infection receiving an allogeneic hematopoietic stem cell transplant. Its results should not automatically be extended to other populations, transplant approaches, treatment schedules, or follow-up periods. The registry record does not report detailed eligibility criteria or analysis populations, which further limits judgments about who the results represent.

The endpoint combines CMV reactivation at a specified viral-load threshold, viremia prompting antiviral therapy, and CMV disease before day 100. The posted count does not show which component occurred or provide a separate estimate for each. It also does not, by itself, quantify antiviral use as an independent outcome or establish a mechanism through immune response.

The results do not establish that the vaccine works or does not work, and they do not establish equivalence between the groups. Nor do the safety counts establish that reported events were caused by an intervention. The registry record gives useful information about the randomized comparison and the observed outcomes, but important analytic and reporting details are absent. The appropriate conclusion is limited to the posted estimates and their uncertainty, not a broader claim about clinical use or effects beyond these recorded outcomes.

17. Why This Trial Matters Statistically

This trial illustrates the distinction between an observed difference and a precisely estimated difference. The primary point estimate favors the vaccine arm, but the confidence interval spans zero and allows for a range of possible effects. Reporting the estimate together with its uncertainty prevents a directional point estimate or a p-value from carrying more weight than the data support.

It also shows why absolute and relative measures can usefully complement one another. The risk difference describes an absolute separation in event risk, while the risk ratio and odds ratio describe relative comparisons. Here, the intervals for these measures all include their respective no-difference values. Looking across scales makes clear that the uncertainty is not an artifact of choosing only one summary measure.

Endpoint construction matters as well. The primary measure combines several defined CMV events within a fixed follow-up window, which produces an interpretable participant-level outcome but hides component-specific patterns in the posted summary. Secondary mortality data address a different question and cannot replace detailed information about the primary endpoint.

Finally, a registry result is most informative when read alongside what it does not report. Missing details about analysis populations, missing data, multiplicity, and the original sample-size rationale constrain evaluation of the result. Statistical interpretation requires both the numerical estimate and the context needed to understand how it was produced. This record makes the central comparison visible while leaving several methodological questions unanswered.

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.

Several limitations specific to this record constrain interpretation. The posted primary result is a participant count for a composite CMV endpoint, but the registry does not report separate counts for reactivation, viremia prompting antiviral treatment, or CMV disease. It also does not provide timing within the follow-up period or information about repeat events. Consequently, differences among event types cannot be evaluated.

The registry lists a multicenter phase II randomized trial, but does not give detailed eligibility criteria, transplant characteristics, participant baseline features, or the allocation and masking procedures. The listed conditions are not a substitute for full eligibility and baseline information. Without those details, it is difficult to assess balance between the groups or determine how broadly the findings apply.

The analysis population, missing-outcome handling, statistical test, adjustment methods, and multiplicity plan are not reported in the registry record. The record also does not report the original sample-size calculation or interim-analysis plan. These omissions prevent a full audit of whether the posted analysis follows prespecified methods and how sensitive it may be to analytic choices.

Safety information is also limited in the registry summary. It gives group counts and selected serious adverse event terms, but not detailed attribution, timing, severity, or denominator information for the listed percentages. These limits mean that the safety entries are descriptive rather than a complete comparative assessment. Together, these gaps call for cautious interpretation of both the primary estimate and the broader trial record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Multi-antigen CMV-MVA Triplex Vaccine in Reducing CMV Complications in Patients Previously Infected With CMV and Undergoing Donor Hematopoietic Cell Transplant — NCT02506933.
• Registry record last updated 2026-07-28; status last verified 2026-07.
• Results first posted 2023-04-14.
• 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

NCT02506933 is a randomized, double-masked, placebo-controlled, multicenter phase II trial of multi-peptide CMV-MVA vaccine in recipients of an allogeneic hematopoietic stem cell transplant who had previously been infected with CMV. The registry lists enrollment as 102 and gives a vaccine schedule of intramuscular injections on days 28 and 56 post-HCT, with placebo on the same schedule.

The primary outcome counts participants with a qualifying CMV event before day 100. The posted estimate favors the vaccine arm, but the confidence interval includes no difference and the unadjusted p-value is 0.162. All-cause mortality is also posted as a secondary outcome. The record includes descriptive adverse-event counts but does not report several analysis and safety details needed for a complete evaluation.