Evaluation of ColdZyme® Mouth Spray on Prevention and Alleviation of Rhinovirus Induced Common Cold: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of ColdZyme® Mouth Spray on Prevention and Alleviation of Rhinovirus Induced Common Cold (NCT02522949), a randomized na study. The primary outcome is Reduction in Viral Load in the URT.

2. Clinical Question

The study asked whether ColdZyme® mouth spray could affect viral load after healthy volunteers were challenged with rhinovirus, compared with a sugar-based placebo spray designed to mimic it. The registry describes the primary outcome as reduction in viral load in the upper respiratory tract in relation to placebo, measured over 7 days.

This is a question about a measured biological outcome following an experimental challenge, not a direct estimate of effects in every setting where common cold occurs. The record also names outcomes concerning symptomatic and asymptomatic infection, symptom days, proinflammatory proteins and symptom scores. It does not provide numerical findings for those outcomes in the information available for this analysis. The clinical question can therefore be described from the trial plan, but the comparative result cannot be interpreted from the registry entries alone.

3. Trial Design

The registry describes a randomized, parallel-group, quadruple-masked, placebo-controlled study. Participants were healthy volunteers exposed to an induced rhinovirus upper respiratory tract infection. The planned comparison was ColdZyme® mouth spray against a sugar-based spray made to mimic it. Both arms had the same stated schedule: 6 doses per day for 11 days, beginning on the day of inoculation.

Enrollment is recorded as 46. The study status is completed, and the phase is listed as NA. The recorded start is 2013-03 and primary completion is 2013-06. Enzymatica AB is named as sponsor. These administrative details describe the registry entry; they do not establish that every planned measurement was collected or analyzed, nor do they give the findings.

Random allocation is intended to make treatment assignment less dependent on participant characteristics, while masking is intended to limit knowledge of assignment from influencing care, reporting or assessment. Those are general design purposes, not evidence that bias was absent in this particular study. The registry uses the term quadruple masking but does not identify which roles were masked. It also does not report the allocation sequence method, how masking was maintained, or whether masking was assessed.

The parallel design means the two treatment groups are compared as groups rather than through a crossover. The primary endpoint is reduction in viral load in the upper respiratory tract, expressed in log 10 copies/mL, with least squares mean as the stated summary and standard error as the stated dispersion. The time frame is 7 days. However, the record notes that the primary outcome has several categories or time points and was not reduced to one comparison. Details of those categories and the corresponding numerical results 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 Reduction in Viral Load in the URT, measured over 7 days.

The primary endpoint concerns reduction in viral load in the upper respiratory tract after rhinovirus challenge, relative to placebo. Viral load is expressed in log 10 copies/mL, and the specified time frame is 7 days. In general, a viral-load measure is a laboratory-based indicator of the amount of virus detected in a sample; it is distinct from a participant’s reported symptoms or from whether an infection is classified as symptomatic.

The registry identifies the endpoint summary as a least squares mean. In general, a least squares mean is a model-based estimate of a group mean, potentially accounting for terms included in the statistical model. The registry record does not report which model terms were used, so the specific adjustment represented by this estimate cannot be determined. The listed dispersion is a standard error, which generally describes the precision of an estimated mean rather than the spread of individual measurements.

A viral-load endpoint can address a biological response to the induced infection over the specified observation period. It does not, by itself, establish the pattern of symptoms, the number of symptomatic days, or the likelihood of infection in other circumstances. Those are separate outcomes, several of which are named as secondary outcomes in this trial.

No numerical estimate, standard error, confidence interval or test result for the primary endpoint is reported in the registry record available for this analysis. In addition, the primary outcome is described as involving several categories or time points rather than one comparison. Without the corresponding values and analysis details, the direction, magnitude and precision of the primary comparison cannot be assessed.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The statistical details that can be interpreted from the registry are limited but important: the primary measure is continuous, its unit is log 10 copies/mL, its summary is a least squares mean, and its dispersion is a standard error. The primary time frame is 7 days. The registry does not report the model specification, the actual estimates, or a complete analysis plan. The explanations below describe the statistical concepts generally and distinguish them from the methods that can be confirmed for this trial.

What does a least squares mean represent?

In general, a least squares mean is an estimated group mean derived from a statistical model. A model may include terms such as treatment assignment and other prespecified factors; the estimate can then represent a mean adjusted for those terms. The exact meaning depends on the model, its assumptions and the way the estimate is calculated. The registry record does not identify the model terms or estimation procedure for this study. It is therefore possible to describe the reported summary type, but not to say what specific adjustment it reflects.

A model-based mean is not automatically more reliable than a raw average. Its usefulness depends on a suitable model, appropriate data and a clear analysis plan. For repeated measurements, the choice of model may affect how observations from the same participant are related and how measurements at different times contribute to an estimate. Since the primary outcome is described as having several categories or time points, the details of how those observations were represented are particularly relevant, but are not reported.

What does the standard error say?

In general, a standard error describes the sampling uncertainty of an estimated quantity, such as a mean. It is not the same as the standard deviation, which describes variation among individual observations. A standard error is used in statistical inference, including construction of confidence intervals and tests, subject to the assumptions of the analysis. The record identifies standard error as the dispersion measure for the primary outcome but does not provide its value. Precision therefore cannot be evaluated from the registry entry.

A confidence interval, when reported, pairs an estimate with a range of values that reflects uncertainty under a specified method. It helps readers judge which effect sizes remain compatible with the data and model. An interval’s interpretation depends on the analysis assumptions, and it is not a guarantee that the true value lies within the interval. No primary confidence interval is reported in the registry information.

Why does the scale matter?

The endpoint is stated in log 10 copies/mL. A logarithmic scale represents measurements in a transformed form, so differences on that scale are not read in the same way as differences on an untransformed copies-per-milliliter scale. The appropriate interpretation depends on the exact estimand and analysis, including whether estimates were calculated or transformed on the stated scale. The registry does not give enough detail to reconstruct that process. No conversion or numerical interpretation can be made without the underlying estimates and methods.

The endpoint is described as reduction in viral load in relation to placebo. A comparative estimate would need to specify the direction of subtraction or contrast and the time point or summary across time points. Because the record notes multiple categories or time points and does not give a single comparison, neither the direction convention nor the specific primary contrast can be established from the registry description alone.

How should planning illustrations be understood?

In general, a sample-size calculation asks how many participants may be needed under selected assumptions about an effect, variability, significance level, allocation and statistical model. The registry’s planning description says its illustration uses the observed effect, a two-sided significance level of 0.05, equal allocation, and a normal approximation; it also describes planning for stated fractions of the observed effect. These are assumptions for a planning illustration, not evidence that the trial was designed using those assumptions.

The description distinguishes participants per arm for 80% power from participants per arm for 90% power. Those quantities, when calculated, are hypothetical planning requirements under the stated assumptions. They are not observed outcomes and are not “observed power.” The registry record does not report the trial’s own sample-size justification or establish that these planning assumptions were used when the study was designed. A calculation based on an observed effect can also inherit uncertainty from that estimate; it should not be treated as an independent confirmation of the treatment effect.

For a continuous endpoint, the assumed variability and definition of the effect are central to a sample-size calculation. The model and analysis population also matter. Since the primary estimates, uncertainty and model details are not reported, the planning description cannot be independently interpreted as evidence about the precision actually achieved in this trial.

What does randomization contribute?

In general, random allocation helps balance measured and unmeasured baseline factors across groups on average, but it does not guarantee identical groups in a particular trial. Masking can reduce the influence of treatment knowledge on participant reports, clinical behavior or outcome assessment, depending on who is masked and how outcomes are collected. The record states randomized allocation and quadruple masking. It does not give the allocation procedure or identify the masked roles, so the implementation cannot be evaluated from the registry information.

In general, over-dispersion means that observed variability is greater than a statistical model expects under its assumed distribution. When present and ignored, uncertainty estimates may be too small and tests may be poorly calibrated. This concept is useful when assessing count or binary outcomes, but the registry does not report whether over-dispersion was assessed or whether it was relevant to any analysis in this study. It should not be assumed to have occurred.

10. Multiplicity, Missing Data and Analysis Populations

The registry names 12 outcome measures and 3 analyses. It identifies secondary outcomes involving symptomatic and asymptomatic upper respiratory tract infection, days with and without symptoms, proinflammatory proteins, total daily symptom score and individual symptom scores. The primary outcome is described as having several categories or time points, and the record indicates that it was not reduced to one comparison.

In general, multiplicity arises when several outcomes, time points, groups or statistical tests are examined. The more comparisons made, the greater the chance that at least one result may appear notable by chance if each is interpreted without accounting for the others. Statistical plans may address this through prespecification, a hierarchy of outcomes, adjustment procedures or a careful distinction between confirmatory and exploratory analyses. These are general approaches; the registry record does not report which, if any, were used in this trial.

The record does not report a multiplicity strategy, a complete list of planned comparisons, or which analysis corresponds to each outcome and time point. It also does not provide numerical results that would permit a comparison of analyses. Consequently, readers cannot determine whether reported tests, if any, were adjusted or how the primary comparison was selected.

Missing-data methods and analysis populations are also not reported in the registry record. The entry does not state how missing viral-load measurements were handled, whether all randomized participants were included in the primary analysis, or whether exclusions occurred. The adverse-event denominators do not establish the endpoint analysis population. Without these details, the potential influence of incomplete outcome data or analysis exclusions cannot be assessed. These omissions limit interpretation; they do not establish that data were missing or that a particular method was used.

11. Safety Results

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

Other (non-serious) adverse events

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

Most frequent non-serious adverse event terms

The registry lists serious adverse events separately from other adverse events. In the ColdZyme group, 23 participants were recorded as at risk and 0 as affected by a serious adverse event; 23 were at risk for other adverse events and 3 were recorded as affected. In the placebo group, 23 participants were recorded as at risk and 0 as affected by a serious adverse event; 23 were at risk for other adverse events and 4 were recorded as affected.

These entries are counts within the registry’s stated at-risk groups. They do not identify the types, timing, severity details or attribution of the other adverse events. The record also does not describe event-collection procedures or provide a formal comparison between groups. The zero serious-event counts mean that no affected participants are recorded in those entries; they do not establish that a treatment has no safety risks, particularly when the study concerns a limited group of healthy volunteers and a specific experimental setting.

Death counts are not reported in the registry record. The other adverse-event counts should not be treated as a measure of efficacy, and the serious-event entries should not be interpreted as proof of equivalence between groups. Safety information is descriptive as recorded and does not replace a fuller account of event definitions, follow-up and clinical context.

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

The record establishes the question the trial was designed to address: whether ColdZyme® mouth spray was associated with a different reduction in upper-respiratory-tract viral load than a mimicking placebo after rhinovirus challenge. It specifies the endpoint scale, summary type, dispersion type and time frame. Those details help identify what a result would need to describe.

However, no numerical primary-outcome estimate or uncertainty measure is reported in the registry record. It is therefore not possible to state whether the groups differed, in which direction, by how much, or with what precision. The absence of a posted number should not be recast as evidence of no effect. Nor should the trial’s completed status be treated as evidence of a particular result.

Even if a viral-load estimate were available, that endpoint would answer a specific biological question under an induced rhinovirus challenge. It would not by itself answer every question about symptoms, symptomatic illness, infection in everyday circumstances or use in populations other than the healthy volunteers described in the record. The registry names several symptom and infection outcomes, but does not report their numerical findings in the information used.

The sample-size description is a planning illustration based on an observed effect and specified assumptions, not a report of observed treatment benefit or observed power. It cannot be used as a substitute for the primary estimate and its uncertainty. Similarly, the adverse-event counts provide limited descriptive safety information and do not establish a complete safety profile or a causal relationship between treatment and events.

The appropriate interpretation is consequently bounded: the design and intended measurements are documented, while the comparative primary result, detailed analysis methods and several important data-handling details are not reported in the registry record. Stronger conclusions would require those missing estimates and methods, alongside the full outcome and safety reporting.

13. Why This Trial Matters Statistically

This trial is statistically informative as an example of why a design description and a result are not interchangeable. Randomization, masking, a placebo comparator and a clearly named biological endpoint describe how a comparison was intended to be made. They do not reveal the estimated effect or its uncertainty. Without those values, the central statistical question remains unanswered in the registry record.

The outcome’s structure also matters. Viral load is a continuous measure summarized by a least squares mean, but the record describes multiple categories or time points and does not identify one primary comparison. A result is interpretable only when readers can tell which observations and contrast produced it. This illustrates why a concise endpoint label alone may not fully specify the estimand or analysis.

Multiplicity is relevant because the record names several outcome measures and analyses. In general, interpreting many comparisons requires clarity about which questions were primary, how time points were handled and whether any adjustment or hierarchy was planned. Those details are not reported, so the record cannot support a judgment about multiplicity control.

The sample-size illustration is another useful distinction. Calculations using an observed effect and selected assumptions can help explore future planning, but they are not the same as the trial’s original design rationale and do not establish observed power. Keeping planning assumptions separate from results prevents a hypothetical calculation from being mistaken for evidence about the actual comparison.

Finally, the registry’s safety entries demonstrate the limits of simple counts. Counts of affected participants can describe what was recorded, but without event details, attribution and analysis methods, they do not by themselves characterize risk. The trial’s statistical value can be assessed fully only when endpoint results, uncertainty, analysis populations and relevant methods are reported together.

14. 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 main limitation for interpreting this trial from the registry record is that numerical primary-outcome findings are not reported. The record identifies reduction in viral load over 7 days but does not give the group estimates, their standard errors, a confidence interval or a test result. The direction and precision of the comparison therefore remain unknown.

The primary outcome is described as involving several categories or time points, without one comparison being selected in the record information. The endpoint’s precise estimand, time-point handling and contrast are consequently unclear. The model used to obtain the least squares mean, any covariate adjustment and assumptions about repeated measurements are also not reported.

The registry lists secondary outcomes but does not report their numerical results in the available information. It also does not report a multiplicity plan, missing-data methods, the primary analysis population, or how participants with unavailable measurements were handled. These gaps prevent assessment of whether the analysis followed a prespecified hierarchy or how incomplete data may have affected estimates.

The study concerns healthy volunteers exposed to induced rhinovirus infection, so its setting is specific. The registry does not provide further participant characteristics in the record information used for this analysis. Quadruple masking is stated, but the masked roles and practical masking procedures are not described. Allocation sequence and concealment details are likewise not reported.

Safety entries give counts for serious and other adverse events, but not event descriptions, attribution or a detailed collection method. Death counts are not reported in the registry record. These limitations should be kept distinct from the missing efficacy findings: neither the adverse-event entries nor the completed status can resolve the absent primary-outcome estimate.

15. Related Tutorials

16. Related Statistical Calculators

17. Sources

• ClinicalTrials.gov: Evaluation of ColdZyme® Mouth Spray on Prevention and Alleviation of Rhinovirus Induced Common Cold — NCT02522949.
• Registry record last updated 2024-08-23; status last verified 2024-08.
• Results first posted 2024-08-23.
• 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.

18. Record Summary

The registry record describes a completed, randomized, parallel, quadruple-masked, placebo-controlled study sponsored by Enzymatica AB. It enrolled 46 healthy volunteers for an induced rhinovirus upper respiratory tract infection study. The phase is listed as NA; the recorded start is 2013-03 and primary completion is 2013-06.

ColdZyme® mouth spray was compared with a sugar-based spray made to mimic it. Both were scheduled for 6 doses per day for 11 days from inoculation. The primary outcome was reduction in upper-respiratory-tract viral load, expressed in log 10 copies/mL, summarized by least squares mean with standard error, over 7 days.

The record names secondary symptom, infection and protein outcomes, and lists 12 outcome measures and 3 analyses. It does not report a numerical primary-outcome result in the information. Serious adverse events were recorded for 0 affected participants in each group; other adverse events were recorded for 3 in the ColdZyme group and 4 in the placebo group. Death counts are not reported in the registry record.