Efficacy of Anaferon for Children in the Treatment of Influenza and Acute Respiratory Viral Infections in Children: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy of Anaferon for Children in the Treatment of Influenza and Acute Respiratory Viral Infections in Children (NCT02072174), a randomized phase 4 study. The primary outcome is Average Illness Duration.

2. Clinical Question

3. Trial Design

The registry describes NCT02072174 as a Phase 4, randomized, quadruple-masked, parallel-group, placebo-controlled trial. Its official title calls it international and multicenter. The listed sponsor is Materia Medica Holding. The study status is completed. The registry dates the start to 2014-10-08 and primary completion to 2018-04-16. Enrollment is listed as 569.

Participants were assigned to Anaferon for Children or placebo. Both arms had the same tablet schedule: on day 1, five tablets in the first 2 hours, one every 30 minutes, followed by three tablets spaced during the remainder of the day. From day 2 through 5, the schedule was one tablet three times daily. The registry record does not describe the sequence-generation procedure, allocation concealment, or the details of how masking was maintained.

The primary outcome was average illness duration, reported as a mean with standard deviation and defined over the period from randomization until recovery or improvement, with the stated assessment window of days 1-14. The outcome description says it was based on patient diary data. The primary analysis population is named as the Per Protocol set. The registry does not report the criteria for membership in that set or the number of participants excluded from it and why.

The record lists nine secondary outcome measures and reports posted results for eight secondary outcomes. It also lists 17 analyses overall. These counts indicate a broader outcome and analysis record than the single primary comparison, but do not specify a testing hierarchy or adjustment for multiple comparisons. The original sample-size justification, planned analysis details beyond those explicitly listed, and any interim analyses 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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Per Protocol set

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 Average Illness Duration, measured over From the time of randomization until the time of recovery/improvement (days 1-14).

Average illness duration is a continuous outcome expressed in days. The registry defines it as the interval between starting trial treatment and the start of the first 24-hour period when specified nonspecific and nasal, throat, or chest symptoms have improved to absent or mild, the Total Symptom Score of severity has decreased to at or below 2 points, and body temperature has returned to 37.2°C or below. The description says the measure uses patient diary data and assesses duration until recovery or significant improvement.

This kind of endpoint is used to represent the time taken to reach a prespecified clinical state. Reporting a group mean gives a compact summary of duration, while the standard deviation describes the spread of individual observations around that mean. A mean difference compares the average duration in the two groups; a negative difference for Anaferon relative to placebo indicates a lower reported group mean in the Anaferon arm.

As a general statistical point, a continuous endpoint can retain information across its range rather than reducing each participant’s experience to a yes-or-no outcome. Its interpretation depends on the definition, measurement, and analysis population. Here, the endpoint is tied to several symptom and temperature criteria, and the primary outcome population is Per Protocol. The registry does not report how diary completeness was handled or how missing endpoint data were treated.

7. Results Posted in the Registry

• Anaferon for Children: mean 4.60 versus 4.90 on control; difference -0.30 (95% CI -0.54 to -0.06), standardized effect d = -0.22; z-test p = 0.013.

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 Patients With Exacerbation of the Disease Course

• 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:
  • Anaferon for Children: 2.7% (7/258) versus 4.6% (11/240) on control; risk difference -1.9 percentage points (95% CI -5.2 to 1.4), risk ratio 0.59 (0.23–1.50); unadjusted two-proportion z-test p = 0.264.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Anaferon for Children and the control. The interval gives the range of effects that remain compatible with the data.

The record lists nine secondary outcome measures, while results are posted for eight. They cover recovery or improvement, body temperature, symptom severity, antipyretic use, viral load, and exacerbation of disease course, among other measures. These outcomes address related but distinct aspects of illness and treatment experience; they are not substitutes for the primary endpoint of average illness duration.

The secondary results should be read as a collection rather than as independent confirmations of the primary result. Their measures, scales, and analysis methods differ, so a pattern across them cannot be reduced to a single numerical summary. In the posted binary result for exacerbation, the group counts are 7 and 11, and the registry’s Fisher Exact analysis gives p = 0.338. That finding does not provide strong statistical evidence of a group difference, but it also does not establish equivalence.

The primary result concerns average duration, whereas secondary outcomes may reflect symptoms, temperature, or other aspects of the course. Agreement or disagreement across such measures can be informative, but requires consideration of their definitions, timing, completeness, and analysis populations. Those details are not fully reported for every secondary outcome in the registry record.

Because multiple outcomes and analyses are listed, unadjusted secondary results carry less weight than a single prespecified primary comparison. In general, examining many outcomes increases the chance that some results appear notable by chance, even when there is no adjustment. The registry does not report a multiplicity adjustment or a hierarchy specifying which secondary tests were confirmatory. Secondary findings are therefore best treated as descriptive or exploratory evidence unless a more complete statistical plan establishes otherwise.

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

• Percentage of Patients With Recovery/Improvement in Health
• Changes in Body Temperature
• Percentage of Patients With Normal Body Temperature (≤37.0ºС)
• Severity of Clinical Manifestations of Influenza / Acute Respiratory Viral Infection by Total Symptom Score.
• Assessment of the Severity of Influenza Virus / Acute Respiratory Viral Infection Using the "Area Under the Curve" for an Overall Symptom Assessment
• Number of Intakes of Antipyretics
• Change in Viral Load During the Treatment and Follow-up Periods
• Percentage of Patients With Exacerbation of the Disease Course

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous: illness duration is recorded in days, and the registry reports a mean and standard deviation for each arm. The displayed recalculation compares those means using an unadjusted mean difference. The registry’s reported primary comparison instead names a Kruskal-Wallis test. These methods address group differences in different ways, so their p-values need not match.

What does a mean difference express?

In general, a mean difference is the average in one group minus the average in the reference group. The posted comparison is Anaferon for Children relative to placebo. Its estimate is -0.3 days, consistent with the listed means of 4.6 days and 4.9 days. The negative sign indicates that the Anaferon group mean is lower. The estimate is a contrast between group averages, not a prediction for an individual participant.

The recalculation is described as unadjusted: it uses the posted summary statistics rather than adjusting for other participant characteristics. It should therefore be distinguished from any adjusted analysis that may have been planned or performed, which is not reported in the registry record. The primary results identify the Per Protocol set, but do not provide enough detail to establish which participants were excluded or how exclusions were decided.

Why use a rank-based test?

The registry lists a Kruskal-Wallis test for the primary comparison. In general, this is a rank-based method that compares the distributions of observations between groups using their ordering, rather than relying on a comparison of means in the same way as a conventional mean-based test. It can be useful when the assumptions of a particular mean-based model are not suitable. The registry does not explain why this test was selected or report diagnostic checks. The test result should not be interpreted as a test specifically of the difference between the two posted means.

The recalculation from means and standard deviations answers a different, explicitly summary-statistic-based question. Its p-value is 0.013, while the registry’s Kruskal-Wallis p-value is 0.024. The presence of two p-values does not imply an error: they arise from different methods. The registry result is the sponsor’s reported analysis; the recalculation is an additional unadjusted comparison of the posted summaries. No discrepancy is flagged in the record.

What does the confidence interval contribute?

In general, a confidence interval gives a range of estimates compatible with the data and the method’s assumptions. For the recalculated mean difference, the reported interval is displayed with the comparison. Its bounds are below zero, indicating that the interval for this unadjusted contrast does not include no mean difference. That does not remove uncertainty, establish a causal explanation on its own, or show the possible range of individual illness durations.

A confidence interval and a p-value answer related but not identical questions. The interval emphasizes the estimated magnitude and its uncertainty; the p-value measures how surprising data at least this extreme would be under a specified null model and assumptions. Neither quantity measures clinical importance. The registry does not report a confidence interval for the Kruskal-Wallis analysis.

How should the binary secondary outcome be read?

The exacerbation outcome is reported as participant counts. The listed counts are 7 in the Anaferon group and 11 in the placebo group. A recalculated risk difference compares the proportions in the groups, and its confidence interval includes zero. The registry names Fisher Exact as its own analysis method and reports p = 0.338. In general, Fisher’s exact test evaluates evidence of association in a two-by-two table, and is often used for categorical counts. The registry’s p-value is not a measure of the size of a difference.

For this binary outcome, the displayed recalculated comparison and the reported Fisher Exact result are distinct outputs. The record does not report an adjustment for multiple secondary analyses, so an isolated secondary p-value would require particular caution. The primary endpoint remains the prespecified focus named in the record, but the original statistical hierarchy is not reported.

What can and cannot be inferred?

These analyses describe the recorded groups and their results. Randomization is an important design feature because, in general, it aims to make assigned groups comparable apart from chance. The record does not give enough detail about implementation, adherence, missing outcomes, or analysis decisions to evaluate all assumptions behind the estimates. Statistical significance is not equivalent to clinical importance, and a lack of statistical significance for a secondary outcome is not proof that groups are identical.

11. Confidence Intervals and Precision

The recalculated primary mean difference is -0.3 days. Its confidence interval is displayed with the comparison, and both bounds are below zero. This indicates that, under the assumptions of that unadjusted calculation, the interval does not include a zero mean difference. The result is more informative than the point estimate alone because it conveys uncertainty around the estimated group contrast.

A confidence interval is not a range containing most individual participants’ illness durations. It is a range of plausible values for the group-level quantity being estimated, conditional on the method and its assumptions. The standard deviations of 1.4 days for Anaferon for Children and 1.3 days for placebo describe variation among the analyzed participants; they are not standard errors and do not directly show the uncertainty of the mean difference.

The primary analysis counts are 258 for Anaferon for Children and 240 for placebo, and the named population is the Per Protocol set. The registry does not report the flow from enrollment into that analysis population, missing diary data, or the handling of incomplete observations. These omissions limit independent assessment of how representative the analyzed groups are of all enrolled participants.

The registry’s Kruskal-Wallis result has a reported p-value of 0.024, while the unadjusted mean-based recalculation gives p = 0.013. The registry does not provide a confidence interval for its own analysis. The recalculated interval should therefore be understood as uncertainty for the mean difference under the recalculation, not as an interval for the registry’s rank-based test. Precision is only one part of interpretation: measurement quality, analysis population, multiplicity, and the clinical meaning of a difference also matter.

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. Each row asks how many participants per arm would be needed under a stated fraction of the observed effect. The columns describe planning for 80% power and 90% power. In plain terms, power is the chance that a study designed under specified assumptions will detect an effect of the size being planned for, if that effect is present and the assumptions hold.

The listed 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 the stated fraction of the observed effect. For continuous outcomes such as average illness duration, the entries are participants per arm. The time-to-event convention of total events does not apply to this continuous endpoint. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

For the primary endpoint, planning for 100% of the observed effect gives 320 participants per arm for 80% power and 428 participants per arm for 90% power. Planning for 75% of the observed effect gives 568 and 760 participants per arm, respectively. Planning for 50% of the observed effect gives 1,277 and 1,710 participants per arm. The pattern illustrates a general principle: smaller effects are harder to distinguish from random variation, so detecting them with the same power generally requires more participants.

These figures are not observed power. They are forward-looking illustrations derived from the observed effect and stated assumptions, and they should not be taken as the trial’s original design plan or as a guarantee that a future study would achieve the listed power.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.300; pooled standard deviation σ = 1.353.
2. n = 2 × (1.96 + 0.842)² × 1.353² / -0.300² = 319.2, rounded up to 320 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 <- -0.300000000000001                      # observed difference in means
sigma <- 1.3527376661971                     # 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(2072174)
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 = 320 (80% power), 428 (90% power)
 75% of observed effect: n per arm = 568 (80% power), 760 (90% power)
 50% of observed effect: n per arm = 1,277 (80% power), 1,710 (90% power)
power.t.test: 320.1 
Simulated power at n = 320 per arm: 0.800 (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. Analyses Reported by the Sponsor

The registry’s own primary analysis is a Kruskal-Wallis test, with a reported p-value of 0.024. The additional recalculation uses the posted group means and standard deviations to estimate an unadjusted mean difference of -0.3 days and gives p = 0.013. The methods differ, so the results are not interchangeable: the sponsor’s test is rank-based, whereas the recalculation directly compares the posted means under its assumptions.

The registry does not report a confidence interval for its Kruskal-Wallis analysis. The confidence interval displayed for the recalculated mean difference applies to that recalculation and should not be attributed to the sponsor’s test. The primary result is identified as coming from the Per Protocol set, but the registry does not provide further detail about population handling or analysis decisions.

No discrepancy is flagged between the reported analysis and the recalculation. The sponsor’s analysis should be read as the trial’s reported statistical result, while the recalculation offers a complementary summary-statistic comparison. Neither p-value alone establishes clinical importance, and neither resolves limitations in the available information about missing data, multiplicity, or the original statistical plan.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies average illness duration as the primary endpoint and lists nine secondary outcome measures, with results posted for eight. It also lists 17 analyses. These multiple outcomes and analyses create a multiplicity issue: when many hypotheses are tested, the chance of obtaining at least one apparently notable result by chance can rise. As a general statistical approach, a prespecified hierarchy or adjustment can help control the interpretation of multiple tests.

A multiplicity strategy, including any correction, testing hierarchy, or distinction between confirmatory and exploratory analyses, is not reported in the registry record. The reported primary comparison and the secondary findings should therefore not be treated as if all had the same prespecified status or evidential weight. The primary outcome is the principal focus in the record, but the original analysis plan is not available in the reported details.

The primary outcome population is the Per Protocol set. The record does not report the criteria used to define that set, how many participants were excluded from it and for what reasons, or whether any other analysis population was used. It also does not report the handling of missing diary entries or other missing outcome data. These details matter because analysis populations and missing-data methods can affect estimates and uncertainty.

Although the trial is described as randomized and masked, the registry record does not provide the method used to generate the allocation sequence, allocation concealment details, or how masking was assessed. The original sample-size justification, interim-analysis plans, and fuller statistical plan are also not reported. Their absence from the registry record does not establish that such procedures were absent from the study; it means their use and details cannot be assessed from the registry information. Interpretation should distinguish what the registry reports from what it leaves unspecified.

16. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: influenza (0.4%).

The adverse-event figures list serious adverse events in 1 participant in the Anaferon for Children group and 1 participant in the placebo group. The corresponding groups at risk are listed as 290 and 279. The registry lists zero deaths in each group. Influenza is the top serious adverse-event term, reported as 0.4%.

These are descriptive registry counts. They do not by themselves establish that the groups have the same safety profile, nor do they determine whether an event was caused by the intervention. The record does not provide further details about seriousness definitions, event timing, assessment procedures, or the attribution of individual events. The at-risk counts for adverse events also differ from the primary outcome analysis counts, which are reported for the Per Protocol set; the registry does not explain that distinction in the posted details.

Small numbers of serious events can make comparisons imprecise. In general, absence of a reported death or a similar count between arms is not proof that no risk exists or that risks are equal. These data should be interpreted only as the adverse-event information recorded in the registry.

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

The posted primary summaries show an average illness duration of 4.6 days in the Anaferon for Children arm and 4.9 days in the placebo arm. The unadjusted mean difference is -0.3 days, and its displayed confidence interval lies below zero. The registry reports a Kruskal-Wallis p-value of 0.024; the unadjusted mean-based recalculation gives p = 0.013. These statistics describe a group-level difference in the analyzed Per Protocol population.

They do not establish what any individual child would experience, and they do not by themselves show whether a difference is meaningful to patients or caregivers. A statistically notable result is not the same as evidence of clinical importance. The registry record does not report a threshold for a clinically important difference in illness duration.

The result also does not settle questions about missing diary data, exclusions from the Per Protocol set, or the handling of multiple outcomes. The record does not report the original sample-size justification or a complete statistical analysis plan. These limitations affect how fully the analysis can be evaluated from registry information.

The secondary outcomes address other aspects of illness, but their methods and results do not convert the primary finding into a general conclusion about every outcome. The posted exacerbation counts, for example, are not strong evidence of a between-group difference by the registry’s reported test, and do not prove that the groups are equivalent. Safety figures are likewise descriptive and have limited detail.

Overall, the record reports a lower group mean for illness duration in the Anaferon arm, with uncertainty estimates and a reported rank-based test consistent with a difference under their respective methods. This is a statistical description of the posted data, not medical advice, a guarantee of benefit, or a recommendation about treatment.

18. Why This Trial Matters Statistically

This trial illustrates why a clinical result should be read through several statistical lenses. Its primary outcome is a continuous measure, average illness duration, but the registry’s reported analysis uses a Kruskal-Wallis test. A separate unadjusted comparison of the posted means gives a mean difference and confidence interval. Keeping the estimand and method clear prevents the two analyses from being mistaken for the same calculation.

The distinction between a point estimate and its precision also matters. The mean difference of -0.3 days gives a concise description of the group contrast, while the confidence interval communicates uncertainty under the recalculation’s assumptions. Neither conveys the full distribution of participant experiences, and neither answers whether the size of the difference is clinically important.

The record also highlights analysis-population and multiplicity questions. The primary outcome is reported for the Per Protocol set, while the registry lists multiple secondary outcomes and analyses. Without details about participant flow, missing data, or the strategy for multiple testing, readers cannot fully assess how robust the findings are to analysis choices or how much weight to place on secondary results.

Finally, planning illustrations derived from the observed effect are distinct from the original design justification. They show how sample-size requirements change when planning for smaller effects, but are not evidence about the power of the completed trial. Together, these distinctions support a careful reading: identify the endpoint, population, method, uncertainty, and limits of the registry record before drawing conclusions from a p-value.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry does not report the method for generating the randomization sequence or details of allocation concealment and masking implementation. Although the study is described as randomized and quadruple-masked, the specific procedures cannot be assessed from the posted record.

The primary outcome uses patient diary data and is analyzed in the Per Protocol set. The record does not provide the criteria for that set, participant flow into it, reasons for exclusions, or missing-data handling. Enrollment is listed as 569, while the primary outcome arms list 258 and 240 participants; the registry does not explain the difference. Adverse-event at-risk counts are reported separately, without an explanation of how those populations relate to the primary analysis set.

The registry’s reported primary method is Kruskal-Wallis, while the recalculated mean comparison uses posted means and standard deviations. The record does not explain the test choice, provide a confidence interval for its own test, or report diagnostic assessments. The two methods address group differences differently, so the recalculation should not be substituted for the sponsor’s analysis.

Multiple secondary outcomes and analyses are listed, but a testing hierarchy or multiplicity adjustment is not reported. The original sample-size justification, interim analysis plans, and complete statistical plan are also not reported in the registry record. This limits assessment of whether analyses followed prespecified decisions.

The endpoint definition is specific, but the registry does not report diary completeness, adjudication procedures, or a clinical-importance threshold for the mean difference. These limitations do not negate the posted results; they constrain how completely those results can be independently interpreted.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy of Anaferon for Children in the Treatment of Influenza and Acute Respiratory Viral Infections in Children — NCT02072174.
• Registry record last updated 2019-07-12; status last verified 2019-07.
• Results first posted 2019-07-12.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

NCT02072174 is a completed Phase 4 randomized, quadruple-masked, parallel-group, placebo-controlled trial of Anaferon for Children in children with influenza and acute respiratory viral infections. Enrollment is listed as 569. The primary endpoint is average illness duration, measured in days using patient diary data and analyzed in the Per Protocol set.

The primary outcome means are 4.6 days for Anaferon for Children and 4.9 days for placebo. The registry reports a Kruskal-Wallis p-value of 0.024; an unadjusted recalculation of the mean difference is -0.3 days with p = 0.013. The record lists nine secondary outcomes and posts results for eight. It does not report the original sample-size justification, a multiplicity strategy, or details of missing-data handling and participant flow into the primary analysis set.