Entolimod on Immunosenescence in Healthy Geriatric Subjects Receiving Influenza Vaccination: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Entolimod on Immunosenescence in Healthy Geriatric Subjects Receiving Influenza Vaccination (NCT04176133), a randomized phase 2 study. The primary outcome is Change in Anti- A/H1N1 Antibody Titer.

2. Clinical Question

The registry record describes a study of entolimod in the setting of influenza vaccination, with a primary endpoint based on the antibody response to A/H1N1 influenza virus strains. The posted arm summaries give the mean change and standard deviation for each dose group and placebo. The posted comparisons quantify the difference in mean change for the 1 mcg and 3 mcg groups versus placebo; a corresponding comparison for 10 mcg is not reported in the registry record.

This question is about the measured antibody response over the stated follow-up, not whether vaccination prevents infection or whether entolimod changes clinical outcomes. Upper respiratory infections and several functional measures appear among secondary outcomes, but they address different questions. The registry record does not report a primary comparison for every dose group, nor does it report the original statistical plan or the population definition used for the primary analysis.

3. Trial Design

The registry record identifies NCT04176133 as a completed Phase 2, randomized, double-blind, placebo-controlled, parallel-group, dose-escalation study. Its title describes a single administration of entolimod in healthy geriatric subjects receiving influenza vaccination. The enrollment field is 61. The study start date is 2019-10-30, and the primary completion date is 2022-03-30.

The listed groups received a single intramuscular dose of entolimod at 1 mcg, 3 mcg, or 10 mcg, or a single intramuscular placebo administration. The registry record says the placebo looked exactly like the study drug but contained no active ingredient. Influenza vaccine is listed as an intervention, and the brief summary describes entolimod as administered at the same time as the vaccine. Further details about the vaccine regimen are not reported in the registry record.

Randomization and double masking are recorded, but the method of sequence generation, allocation concealment, and who was masked are not reported in the registry record. The record gives arm-level outcome data for the primary measure and several secondary outcomes. The arm sizes vary, including a small 10 mcg group. How participants were assigned to the dose groups, and whether any changes to the planned allocation occurred, are not reported in the registry record.

The primary outcome is change in anti-A/H1N1 antibody titer from baseline to 1 month. Listed secondary outcomes include upper respiratory infections, time of onset for upper-respiratory infections, change in frailty, change in 6-minute walk test, change in grip strength, and change in body mass index. The original design assumptions, sample-size justification, analysis populations, and detailed statistical plan are not reported in the registry record.

4. Participant Flow and Accounting

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

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 Change in Anti- A/H1N1 Antibody Titer, measured over Baseline, 1 month.

The primary endpoint is the change in serum circulating antibodies against A/H1N1 influenza virus strains, assessed using a hemagglutination inhibition assay, from baseline to 1 month. The registry record reports this outcome as a mean change in titer with a standard deviation for each group.

Antibody titer is a laboratory measure of the antibody response. In a study where subjects receive influenza vaccine, measuring change from baseline provides a way to describe how the measured response differs over the follow-up interval. Comparing mean changes between randomized groups can help distinguish the observed response in an entolimod dose group from the response in the placebo group, while retaining the same stated measurement period.

This endpoint is a surrogate laboratory measure, not a direct count of influenza infections or a measure of protection from illness. The registry record does not provide a threshold for a clinically meaningful titer change, a definition of seroprotection, or evidence connecting the reported changes to clinical outcomes. Nor does it describe additional assay details, such as the specific strain composition or handling of values outside the assay range. Those details are not reported in the registry record.

The posted comparison estimates are available for the 1 mcg and 3 mcg groups versus placebo. The 10 mcg group has an arm-level mean and standard deviation, but a comparison with placebo is not reported in the registry record. The endpoint therefore describes measured antibody changes; its interpretation should not be extended beyond the reported measurement and comparisons.

7. Results Posted in the Registry

• Entolimod 1 mcg: mean 65.00 versus 20.30 on control; difference 44.70 (95% CI -19.98 to 109.38), standardized effect d = 0.42; z-test p = 0.176.
• Entolimod 3 mcg: mean 73.20 versus 20.30 on control; difference 52.90 (95% CI -2.57 to 108.37), standardized effect d = 0.60; z-test p = 0.062.

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.

Upper Respiratory Infections

• 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:
  • Entolimod 1 mcg: 50.0% (10/20) versus 18.8% (3/16) on control; risk difference 31.2 percentage points (95% CI 2.2 to 60.3), risk ratio 2.67 (0.88–8.09); unadjusted two-proportion z-test p = 0.052.
  • Entolimod 3 mcg: 47.4% (9/19) versus 18.8% (3/16) on control; risk difference 28.6 percentage points (95% CI -0.9 to 58.1), risk ratio 2.53 (0.82–7.78); unadjusted two-proportion z-test p = 0.076.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Entolimod 1 mcg 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 Entolimod 3 mcg and the control. The interval gives the range of effects that remain compatible with the data.

Change in Frailty

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Entolimod 1 mcg: mean -0.10 versus 0.10 on control; difference -0.20 (95% CI -0.50 to 0.10), standardized effect d = -0.45; z-test p = 0.193.
  • Entolimod 3 mcg: mean -0.20 versus 0.10 on control; difference -0.30 (95% CI -0.66 to 0.06), standardized effect d = -0.54; z-test p = 0.107.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Entolimod 1 mcg 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 Entolimod 3 mcg and the control. The interval gives the range of effects that remain compatible with the data.

Change in 6-minute Walk Test

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Entolimod 1 mcg: mean 5.10 versus -15.80 on control; difference 20.90 (95% CI -13.67 to 55.47), standardized effect d = 0.43; z-test p = 0.236.
  • Entolimod 3 mcg: mean 11.00 versus -15.80 on control; difference 26.80 (95% CI -9.76 to 63.36), standardized effect d = 0.51; z-test p = 0.151.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Entolimod 1 mcg 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 Entolimod 3 mcg and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes address a broader range of questions than the primary antibody measure. The record lists upper respiratory infections and time of onset for those infections, along with changes in frailty, 6-minute walk test, grip strength, and body mass index. Posted numerical results in the registry record include arm summaries and recalculated comparisons for upper respiratory infections, frailty, and the 6-minute walk test. Numerical results for time of onset, grip strength, and body mass index are not reported in the registry record.

Across the posted secondary summaries, estimates vary in direction and precision. The recalculated comparisons have uncertainty intervals that include no difference, and the analyses are unadjusted. This broad pattern does not provide a clear, consistent statistical confirmation that complements the primary result. It also does not establish that there is no difference: estimates from limited data can remain uncertain even when their intervals include zero.

Secondary endpoints do not automatically confirm or overturn the primary endpoint. They concern different measurements and time frames, and some are clinical or functional outcomes rather than laboratory antibody changes. Their relevance depends on the questions prespecified for the trial and how the analyses were planned. The registry record does not report a hierarchy of outcomes or a detailed analysis plan that would clarify how secondary findings were intended to be interpreted.

Unadjusted secondary results carry less weight when many outcomes or comparisons are examined because the chance of finding an apparently notable result can increase across repeated testing. The record does not report whether multiplicity was controlled. The secondary results should therefore be considered exploratory and interpreted alongside their uncertainty, rather than treated as independent proof of a treatment effect. They also cannot establish a relationship between antibody change and clinical outcomes, which is not reported in the registry record.

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

• Time of Onset for Upper-respiratory Infections
• Upper Respiratory Infections
• Change in Frailty
• Change in 6-minute Walk Test
• Change in Grip Strength
• Change in Body Mass Index (BMI)

9. Statistical Interpretation

10. Statistical Methods Explained

Statistical interpretation begins by distinguishing an arm summary from a comparison. An arm mean describes the average observed change among participants represented in that group. A standard deviation describes how dispersed individual observations are around that mean. Neither quantity alone tells whether two groups differ. The mean difference directly compares the two group means, while its confidence interval expresses uncertainty around that estimated contrast.

What does the mean difference represent?

For a continuous outcome such as antibody titer change, a mean difference is expressed in the outcome's units. The posted comparison for 1 mcg versus placebo is 44.7, and the comparison for 3 mcg versus placebo is 52.9. These values are the estimated differences in mean change, not the mean changes within either group. Positive values indicate that the entolimod group had a larger mean change than placebo in these posted comparisons. The estimate does not by itself establish a real or clinically important difference.

What does a confidence interval add?

A confidence interval provides a range of values compatible with the data under the method used to calculate it. For the 1 mcg comparison, the interval runs from -19.98 to 109.4. For the 3 mcg comparison, it runs from -2.567 to 108.4. Both include zero, the value representing no mean difference. This means the posted summaries do not sharply distinguish a positive difference from no difference. A confidence interval is not a guarantee that the true value lies within its endpoints, and it does not assign a probability to any one value.

How should the p-values be read?

The unadjusted p-values are 0.176 for 1 mcg and 0.062 for 3 mcg. A p-value describes how unusual data at least as incompatible with a specified null hypothesis would be under the assumptions of the test. It is not the probability that the null hypothesis is true, nor a measure of clinical importance. These p-values are labelled unadjusted; the registry record does not report a multiplicity adjustment or the sponsor's analysis method. They should not be used as a stand-alone decision rule.

Why does variability matter?

Greater variation makes the group means less precise, particularly when group sizes are limited. Here, the posted standard deviations for the entolimod primary outcome are large, and the 10 mcg group is especially small. A large standard deviation does not mean the mean is wrong; it means individual changes vary widely around the average. It also helps explain why a numerical difference between means can be accompanied by a broad range of plausible differences.

General statistical explanation: when outcome variability is high, a study generally needs more observations to estimate a mean or group difference with comparable precision. Unequal group sizes can also affect how much information each group contributes. The registry record does not report the original design assumptions or whether the analysis adjusted for baseline values or other variables.

Why is a continuous-outcome comparison not a clinical conclusion?

The primary measure is a laboratory titer change. Statistical evidence about its mean difference addresses that measure, as recorded over baseline to 1 month. It does not by itself show that participants experienced fewer infections, that the antibody change is clinically meaningful, or that one dose is preferable. The registry record does not report a threshold for meaningful change or a direct link between this endpoint and clinical protection.

The recalculations are explicitly unadjusted and use posted summary statistics. They do not account for unknown features of the original analysis, such as any prespecified covariate adjustment or the chosen analysis population. The reported analysis details are not reported in the registry record. Where sponsor analyses are available, the sponsor's own analysis takes precedence over simple recalculations; no discrepancy is flagged in this record.

General statistical explanation: unadjusted analyses compare groups without accounting for other variables or for the number of outcomes and comparisons examined. They can be useful for transparent descriptive reading, but the inference may differ from a prespecified model. The absence of reported adjusted analyses means the registry record cannot establish how such methods would affect the estimated effects or uncertainty.

11. Confidence Intervals and Precision

The confidence intervals for the posted primary comparisons are wide. The 1 mcg versus placebo estimate is 44.7, with a 95% confidence interval from -19.98 to 109.4. The 3 mcg versus placebo estimate is 52.9, with a 95% confidence interval from -2.567 to 108.4. Both intervals include zero, so the posted data are compatible with no mean difference as well as with positive differences of varying size. The 3 mcg interval comes closer to zero at its lower endpoint, but that does not make the estimate precise.

Precision depends on the amount of information in the comparison and the variability of the outcome. The primary outcome's standard deviations are substantial, and the group sizes are limited, particularly for 10 mcg. These features are consistent with broad uncertainty. A confidence interval that spans a wide range means the observed estimate should not be read as a precise measurement of the underlying difference.

The intervals are for the 1 mcg and 3 mcg recalculated unadjusted comparisons. The registry record does not report a confidence interval for the 10 mcg comparison. It also does not report sponsor confidence intervals, adjusted estimates, or the original analysis method. Thus, precision statements should be limited to the posted comparisons and their stated recalculation.

General statistical explanation: a confidence interval reflects sampling uncertainty under the calculation method; it does not capture every source of uncertainty, such as limitations in measurement, missing data, or the choice of analysis. The registry record does not give enough detail to assess all such sources. In particular, the presence of a numerical estimate should not be mistaken for certainty about either the magnitude or the clinical meaning of the result.

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 effects, not the trial's original design calculations. For these comparisons, 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. The target effect is the stated fraction of the observed effect.

The 80% power column gives an illustrative number of participants per arm for a planned study to have an 80% chance of detecting the specified effect under the listed assumptions. The 90% power column gives the corresponding number for a higher chance of detecting that effect. These are planning quantities, not estimates of the probability that the current trial found a real effect.

The rows describe planning for the full observed effect, 75% of the observed effect, and 50% of the observed effect. A smaller target effect is harder to distinguish from ordinary sampling variation, so it requires more participants per arm under the same assumptions. The entries are conditional on the observed effect being a suitable planning estimate; an effect estimated in a small trial can itself be uncertain.

These figures are not observed power. Observed power is not a useful substitute for reading the effect estimate and its confidence interval, and the figures do not explain the original enrollment decision. The trial's original sample-size justification, planned power, and design assumptions are not reported in the registry record. The planning values should therefore be read as illustrations of how assumptions about effect size and desired power influence a future study's approximate group size.

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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 44.700; pooled standard deviation σ = 107.537.
2. n = 2 × (1.96 + 0.842)² × 107.537² / 44.700² = 90.9, rounded up to 91 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
delta <- 44.7                      # observed difference in means
sigma <- 107.53665436656                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^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 (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(4176133)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 91 (80% power), 122 (90% power)
 75% of observed effect: n per arm = 162 (80% power), 217 (90% power)
 50% of observed effect: n per arm = 364 (80% power), 487 (90% power)
power.t.test: 91.8 
Simulated power at n = 91 per arm: 0.793 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-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 identifies 10 outcome measures and lists six secondary outcomes, but the reported analyses field is empty. The posted outcome summaries include multiple groups and comparisons, while the inferential comparisons displayed in the data are unadjusted. The record does not report a prespecified testing hierarchy, a family-wise error procedure, a false-discovery procedure, or another multiplicity strategy. It is therefore not possible to determine from the registry record whether the primary endpoint was the sole confirmatory test or how secondary analyses were intended to be interpreted.

Multiplicity matters because examining many outcomes, time points, or dose comparisons creates more opportunities for a result to appear noteworthy by chance. This does not make any one estimate invalid, but it makes isolated unadjusted p-values less compelling as confirmatory evidence. The secondary comparisons should be read as exploratory unless the planned analysis and its error-control approach are available.

Missing-data handling is not reported in the registry record. The record does not state whether all randomized participants contributed to each endpoint, how missing measurements were handled, or whether any imputation or sensitivity analyses were used. The arm-level denominators identify the numbers associated with the posted summaries, but they do not explain why those denominators differ across groups or whether every randomized participant was included in each analysis.

The analysis population is also not reported in the registry record. It is not possible to tell whether the summaries represent an intention-to-treat population, a per-protocol population, or another defined group. Details of exclusions, protocol deviations, and adherence are not reported. These omissions limit assessment of possible bias and prevent a full reconstruction of the trial's inferential approach.

The original statistical plan, interim analyses, and sample-size justification are not reported in the registry record. No inference about these design features should be made from the posted endpoint summaries 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: hypophosphatemia (6.2%).

The registry record reports serious adverse events in the safety groups. There were no serious adverse events reported in the 1 mcg, 3 mcg, or 10 mcg groups. One serious adverse event was reported in the placebo group. Deaths were reported as zero in each group. Hypophosphatemia is listed among the serious adverse event terms with a value of 6.2%.

These are descriptive safety counts from the registry record. They do not by themselves establish that an event was caused by study treatment, nor do they provide a reliable comparison of risk between groups. The groups are small, especially the 10 mcg group, and a rare event may be difficult to assess in a study of this size. The registry record does not provide a detailed event narrative or information sufficient to interpret the listed serious event term in context.

The record also reports other, non-serious adverse events in the group summaries. The serious-event figures should be kept distinct from those broader counts. They describe what was recorded during the study, not a complete measure of longer-term safety or a basis for treatment advice.

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

The posted results describe a randomized study of entolimod given alongside influenza vaccination and report antibody titer change from baseline to 1 month. Mean changes were higher in the entolimod dose groups than in placebo, while the posted unadjusted comparisons for 1 mcg and 3 mcg have confidence intervals that include no difference. The estimates are imprecise, and the registry record does not report an inferential comparison for 10 mcg.

These observations do not establish a precise difference in antibody response, a reliable dose-response pattern, or a clinically meaningful change. The registry record does not state what magnitude of titer change would be clinically important. It also does not establish whether the measured antibody changes correspond to reduced infection or improved clinical outcomes. Those questions cannot be answered by the antibody endpoint alone.

The record's secondary outcomes include upper respiratory infections and functional measures, but the available unadjusted analyses remain uncertain and do not remove the limitations of the primary comparisons. The record does not report a multiplicity strategy, the analysis populations, or missing-data methods, which further limits the strength of confirmatory conclusions.

In general, an observed group difference is an estimate, not a guarantee of a reproducible effect. A confidence interval communicates how much uncertainty surrounds that estimate under its calculation method. Here, the intervals and the variability in the primary outcome caution against treating the numerical estimates as definitive. The results are best understood as a description of the posted data in this study, not as medical advice or a conclusion about whether a treatment works.

17. Why This Trial Matters Statistically

This trial illustrates several recurring statistical challenges in clinical research. First, a difference between group means is only one part of the evidence. The primary comparisons have positive point estimates, but their confidence intervals include zero and extend across a wide range. Reading the estimates together with their uncertainty is more informative than focusing on the means or p-values alone.

Second, variability and group size shape precision. The primary endpoint has substantial standard deviations, and the dose groups are not equally sized. In particular, the 10 mcg group is small, and no comparison estimate for that dose is reported. These features limit what can be inferred about the size and consistency of a dose-related pattern.

Third, a laboratory endpoint and clinical outcomes answer different questions. The primary outcome measures antibody titer change; upper respiratory infections and functional outcomes address other dimensions. Without a reported relationship between these measures, an antibody result cannot be treated as proof of a clinical effect.

Finally, transparent interpretation depends on knowing the analysis plan, multiplicity control, analysis population, and missing-data handling. Those details are not reported in the registry record. The posted information supports descriptive comparisons and recalculations, but leaves important questions about how confirmatory inference was intended to work. The example underscores why statistical significance, effect size, precision, and clinical meaning should be considered separately.

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 are specific to the available record for this study. The 10 mcg group is small, and its posted primary outcome has no comparison estimate or confidence interval against placebo. The other posted primary comparisons are recalculated from summary statistics and are unadjusted; the original analysis method and sponsor-reported inferential results are not reported in the registry record.

The primary outcome has substantial variability, and the confidence intervals for the available comparisons are wide. The record does not provide a threshold for clinically meaningful change in titer or describe how titer values were handled in the analysis. It is therefore difficult to assess the clinical interpretation of the estimated differences beyond their numerical direction and uncertainty.

Important design and analysis details are absent, including the sample-size justification, detailed statistical plan, analysis populations, missing-data methods, and multiplicity strategy. The registry record also does not report whether baseline adjustment or other covariate adjustment was used, or whether interim analyses occurred. These omissions limit assessment of the planned inferential framework and of potential bias.

The study includes multiple outcomes, but numerical secondary results are not reported for every outcome listed. The available secondary analyses are unadjusted, and no hierarchy is reported. Safety summaries are also descriptive and do not establish event attribution. These limitations apply to interpretation of the registry record; they do not imply that unreported analyses were or were not conducted.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Entolimod on Immunosenescence in Healthy Geriatric Subjects Receiving Influenza Vaccination — NCT04176133.
• Registry record last updated 2023-06-22; status last verified 2023-05.
• Results first posted 2023-06-22.
• 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

NCT04176133 is a completed Phase 2 randomized, double-blind, placebo-controlled, parallel-group dose-escalation study in healthy geriatric subjects receiving influenza vaccination. The registry record lists enrollment of 61 and describes single intramuscular doses of entolimod at 1 mcg, 3 mcg, or 10 mcg, or placebo.

The primary outcome is change in anti-A/H1N1 antibody titer from baseline to 1 month. Mean changes were 65.0, 73.2, and 88.4 for the three entolimod groups, and 20.3 for placebo. Recalculated unadjusted comparisons versus placebo are posted for 1 mcg and 3 mcg; both confidence intervals include no difference. A comparison for 10 mcg is not reported in the registry record.

Secondary outcomes include infection and functional measures. The original statistical plan, sample-size justification, analysis populations, missing-data methods, and multiplicity strategy are not reported in the registry record. The results should be interpreted as uncertain estimates of the posted outcomes, not as proof of clinical benefit or lack of benefit.