Evaluation of Efficacy and Safety of Tablets of Paracetamol, Dimethindene Maleate and Phenylephrine Hydrochloride in Reducing Symptoms of Common Cold and Flu: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of Efficacy and Safety of Tablets of Paracetamol, Dimethindene Maleate and Phenylephrine Hydrochloride in Reducing Symptoms of Common Cold and Flu (NCT01448057), a randomized phase 3 study. The primary outcome is Physician Global Evaluation of Effectiveness on Nasal Symptoms.

2. Clinical Question

3. Trial Design

This was a Phase 3, randomized, parallel-group study with single masking, described in the official title as investigator-blind. It compared three days of treatment with the combination tablets against paracetamol 500 mg alone for nasal congestion and other symptoms due to cold and flu. The registry lists enrollment of 341 and identifies Novartis as the sponsor. The study status is completed; the listed start is 2013-07 and the primary completion is 2015-08.

The two interventions were the combination of paracetamol, dimethindene maleate, and phenylephrine hydrochloride, and paracetamol tablets alone. The registry’s arm descriptions identify a Combination Product arm and a Paracetamol tablets arm. The posted primary result gives mean scores and standard deviations for Arm A and Arm B, with 162 and 170 participants, respectively. The record also notes missing primary assessments for 8 subjects in the combination product arm and 1 subject in the paracetamol arm. Those numbers explain why the endpoint assessment counts need not equal the enrollment figure.

Random allocation and parallel groups support a between-arm comparison, while investigator masking may reduce the influence of assessor expectations on the physician-rated outcome. The record does not report the allocation procedure, the method used to maintain masking, or the original sample-size justification. It also does not report the trial’s own planned statistical model, analysis populations, or interim-analysis arrangements. Those details should not be inferred from the registry’s posted summaries or from the recalculated unadjusted comparisons.

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: In the combination product arm 8 subjects had missing assessment and 1 subject in the paracetamol arm

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 Physician Global Evaluation of Effectiveness on Nasal Symptoms, measured over Day 2.

The primary endpoint was the Physician Global Evaluation of Effectiveness on Nasal Symptoms on Day 2. A physician assessed reduction in nasal congestion, sneezing, and rhinorrhea using a score from 1 to 5. The scale description assigns 1 to excellent, corresponding to 75% to 100% remission of signs and symptoms, and 5 to bad, described as exacerbation of nasal symptoms. Thus, a lower score represents a more favorable assessment on this scale.

A combined global score can provide a compact summary of several related symptoms for a treatment comparison. It also depends on the physician’s assessment and on how the scale categories are interpreted. The score is a continuous-type outcome in the posted analysis, summarized by a mean and standard deviation, although its original categories are ordered response levels. The mean captures the group’s average score but does not show how each individual symptom changed or how many participants fell into each response category.

The Day 2 timing makes this a short-term assessment within a three-day treatment period. The registry does not report a minimum clinically important difference or a threshold defining a clinically meaningful between-arm change. Statistical evidence about a difference in average scores therefore should not be treated as a direct measure of the importance of that difference to participants.

7. Results Posted in the Registry

• Arm B: mean 2.10 versus 1.90 on control; difference 0.20 (95% CI 0.01 to 0.39), standardized effect d = 0.23; z-test p = 0.037.

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.

Daily Average of the Sum of a 100 mm Visual Analog Scale for All Symptoms

• 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:
  • Arm B: mean 225.30 versus 169.20 on control; difference 56.10 (95% CI 2.37 to 109.83), standardized effect d = 0.23; z-test p = 0.041.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Arm B than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry lists one secondary outcome: the daily average of the sum of a 100 mm visual analog scale for all symptoms, assessed on Day 3. The posted summaries and recalculated comparison indicate that Arm B’s average was higher than the control arm’s average. Its unadjusted interval is above zero, and its unadjusted p-value is 0.041. The scale is reported in millimeters, and the outcome differs from the primary physician-rated nasal symptom score in both content and timing.

The direction of the secondary comparison is consistent with the primary comparison’s numerical direction: both place Arm B’s average above the control arm’s average. This consistency is descriptive, not proof that the outcomes independently confirm one another. They measure related but nonidentical aspects of symptoms, are assessed at different times, and may be correlated. The registry record does not report the degree of correlation or a joint analysis.

The secondary result should carry less weight than a single prespecified primary analysis when no multiplicity strategy is documented. If several outcomes are examined, the chance of at least one apparently unusual result can increase. General statistical practice may address this through a prespecified hierarchy or an adjustment, but the registry record does not report whether either was used. The secondary p-value is unadjusted and should not be interpreted as though it accounts for testing multiple outcomes.

The secondary endpoint has substantial variability relative to its reported scale summaries, and its comparison is also a recalculation from posted summary statistics rather than a reported official analysis. Its role is therefore supportive and exploratory in interpretation, not a replacement for the primary endpoint. A full assessment would require the prespecified analysis plan, missing-data handling, and the sponsor’s reported inferential results, which are not reported in the registry record.

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

• Daily Average of the Sum of a 100 mm Visual Analog Scale for All Symptoms

9. Statistical Interpretation

10. Statistical Methods Explained

The posted primary endpoint is a mean of a continuous measure: the physician-rated nasal symptom score on Day 2. The results give a mean and standard deviation for each arm. The mean describes the average score within an arm, while the standard deviation describes the spread of individual scores around that average. They answer different questions: the mean locates the group average on the scale, and the standard deviation indicates how variable participant scores were within the group.

What does the mean difference describe?

The comparison is expressed as Arm B minus the control arm. Its estimate is 0.2. A positive difference means the Arm B average was higher. Since the scale labels 1 as excellent and 5 as bad, a higher score corresponds to a less favorable score on the defined scale. This direction describes the numerical contrast only; it does not by itself identify the arms’ treatment labels or establish clinical importance.

The difference is an unadjusted comparison reconstructed from the posted summary statistics. It does not account for any covariates or other model terms. The registry lists no reported analysis entries, and it does not report a sponsor’s statistical model for the primary result. Accordingly, the recalculated estimate is descriptive and should not be represented as the trial’s official inferential analysis.

What does the confidence interval add?

A confidence interval expresses uncertainty around an estimated difference. In general, it gives a range of values compatible with the observed data under the method’s assumptions. The primary interval has a lower bound above zero and an upper bound of 0.388, placing the estimated contrast on the positive side. The interval does not tell whether a difference is important to patients or clinicians; that requires a meaningful-change threshold, which is not reported in the registry record.

How should the p-value be read?

The primary unadjusted p-value is 0.037. In general, a p-value measures how unusual data at least as incompatible with a null model would be if that model and the calculation assumptions were correct. It is not the probability that the treatment effect is absent, and it does not quantify the chance that a finding will replicate. A p-value also does not describe the size of the difference, so the estimate and its interval are needed for interpretation.

The posted comparison assumes independent groups and uses a pooled standard deviation of 0.876 in the recalculation. The arm-specific standard errors of the means are 0.066 for Arm A and 0.070 for Arm B. A standard error reflects uncertainty in an estimated mean, not the spread of individual participant scores. The standard deviations, in contrast, are 0.84 and 0.91. These distinctions matter because variation among participants and uncertainty about an arm average are not interchangeable.

Why can over-dispersion matter?

In general, over-dispersion means that observed variability is greater than a statistical model expects. When a model assumes less variability than is present, its standard errors may be too small and its intervals too narrow, overstating precision. The primary endpoint is summarized with standard deviations, and the record does not report a model-based dispersion assessment. The concept is relevant when evaluating any model assumptions, but the registry record does not establish that over-dispersion occurred in this trial.

The scale itself is bounded from 1 to 5 and has ordered verbal categories. Treating a mean difference as a useful summary is a statistical choice; it does not imply that the distance between every adjacent category is identical in a clinical sense. The registry reports means and standard deviations, but does not describe an alternative ordinal analysis or explain why a particular model was selected.

For the secondary outcome, the daily average of the sum of a 100 mm visual analog scale for all symptoms is reported on Day 3 in millimeters. Its group means, standard deviations, recalculated mean difference, interval, and unadjusted p-value are distinct from the primary endpoint’s quantities. The same general principles apply: a mean difference estimates a contrast in group averages, the interval represents uncertainty, and the p-value is not a measure of effect size or clinical relevance.

The planning illustrations use a normal approximation, equal allocation between the two arms, and a two-sided significance level of 0.05. They vary the target effect as a stated fraction of the observed effect. These are prospective planning calculations based on observed summary data, not evidence that the original trial was designed with those assumptions. The trial’s original design assumptions are not reported in the registry record.

11. Confidence Intervals and Precision

The primary mean difference is 0.2 for Arm B compared with the control arm, and its recalculated unadjusted confidence interval has a lower bound above zero and an upper bound of 0.388. The interval therefore places the estimated difference on the positive side, while still representing uncertainty about its size. It is not a guarantee that the true difference falls within the interval, nor does it address whether the difference matters clinically.

Precision depends on the amount of information and the variability in the outcome. The primary arm summaries include 162 participants in Arm A and 170 in Arm B, with standard deviations of 0.84 and 0.91. The endpoint assessment was missing for 8 subjects in the combination product arm and 1 subject in the paracetamol arm. The registry record does not state how those missing assessments were handled in the sponsor’s analysis, so the recalculated precision should be read as based on the posted arm summaries rather than as an account of the original missing-data procedure.

The unadjusted p-value of 0.037 is related to the interval but answers a different question. It summarizes compatibility with a null model under the calculation assumptions; it does not measure precision by itself. The interval is more informative about the range of effect estimates consistent with the recalculation. Neither measure accounts for an unreported adjustment for multiple outcomes or an unreported covariate-adjusted analysis.

Precision also does not equal clinical certainty. The registry does not report a clinically important difference threshold for this scale, and the mean score compresses variation and response patterns into a single average. The interval should therefore be interpreted together with the scale direction, group summaries, missing assessments, and the limitations of an unadjusted recalculation.

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 for the continuous outcomes; they are not total event counts. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The target effect is set to a stated fraction of the observed effect. The original trial’s design assumptions and sample-size justification are not reported in the registry record.

For the primary endpoint, planning for 100% of the observed effect gives 302 participants per arm for 80% power and 404 participants per arm for 90% power. Planning for 75% of the observed effect gives 537 participants per arm for 80% power and 718 participants per arm for 90% power. Planning for 50% of the observed effect gives 1,207 participants per arm for 80% power and 1,615 participants per arm for 90% power.

The 80% power column describes the number per arm estimated to give an 80% chance of detecting the chosen effect under the stated assumptions if that effect is present. The 90% column uses a higher probability of detecting that same target effect, and therefore calls for more participants per arm. The figures rise as the assumed effect becomes smaller: a smaller difference is harder to distinguish from random variation, so planning for it requires a larger sample.

These figures are planning illustrations based on the observed effect, not observed power. They do not recover the trial’s original rationale, and the observed effect used as a planning anchor may be uncertain. For the secondary endpoint, the corresponding planning values are 307 and 410 participants per arm for 100% of the observed effect; 545 and 729 for 75%; and 1,225 and 1,639 for 50%, with each pair representing 80% and 90% power, respectively.

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 = 0.200; pooled standard deviation σ = 0.877.
2. n = 2 × (1.96 + 0.842)² × 0.877² / 0.200² = 301.5, rounded up to 302 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 <- 0.2                      # observed difference in means
sigma <- 0.876547117093456                     # 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(1448057)
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 = 302 (80% power), 404 (90% power)
 75% of observed effect: n per arm = 537 (80% power), 718 (90% power)
 50% of observed effect: n per arm = 1,207 (80% power), 1,615 (90% power)
power.t.test: 302.5 
Simulated power at n = 302 per arm: 0.798 (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 lists two outcome measures: the primary physician global evaluation on Day 2 and one secondary symptom-scale outcome on Day 3. It does not report formal analysis entries. No multiplicity procedure, testing hierarchy, or family of confirmatory hypotheses is reported in the registry record. Consequently, the unadjusted p-values for the primary and secondary comparisons should not be read as if they were adjusted for looking across outcomes.

In general, multiplicity arises when more than one hypothesis is tested and the results are considered together. Without a prespecified strategy, an isolated p-value can overstate the strength of evidence because the chance of at least one small p-value increases as more tests are considered. This general concern does not establish that the investigators used an inappropriate procedure; it identifies information needed to judge the inferential status of the posted comparisons. The registry record does not report whether additional outcomes or subgroup tests were planned outside the posted outcome measures.

Missing primary assessments are noted for 8 subjects in the combination product arm and 1 subject in the paracetamol arm. The record does not explain why assessments were missing, whether they were considered related to treatment or symptoms, or how missing values were handled in the original analysis. It does not report whether an intention-to-treat, per-protocol, or other analysis population was used. The recalculated comparison uses the posted arm-level sample sizes and summaries; it cannot establish the sponsor’s approach to missing data or analysis populations.

These omissions limit the ability to evaluate whether the reported comparison follows a prespecified plan and how robust it may be to alternative assumptions. General approaches can include sensitivity analyses under different missing-data assumptions, but none are reported in the registry record. The available results should therefore be interpreted as descriptive arm summaries with unadjusted recalculated comparisons, rather than as a complete account of the trial’s statistical analysis.

15. 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 3% reporting threshold.

Most frequent non-serious adverse event terms

The safety summaries report zero serious adverse events in each of the two groups. The number at risk for serious adverse events is 170 in Arm A and 171 in Arm B. These figures describe what is posted for serious adverse events; they do not establish that no other safety events occurred, and the registry record does not list serious-event terms.

Other adverse events are recorded for 77 of 170 participants in Arm A and 39 of 171 participants in Arm B. These are separate from the serious adverse event counts. The registry summary does not provide event-level detail, severity breakdowns, or an analysis comparing the groups, so these counts alone do not explain the types or clinical context of the events.

Deaths are not reported in the registry record. Safety comparisons can be affected by follow-up duration, how events are defined and collected, and whether participants have complete observation. The registry record does not provide enough detail to assess those factors. The figures should be read as posted group counts, not as a complete safety assessment or as evidence about a treatment’s overall safety.

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

The posted results describe short-term symptom measurements in a randomized comparison of a paracetamol combination product with paracetamol alone. The primary endpoint is a physician-assessed score on Day 2, with lower values representing better remission on the stated scale. The observed arm means were 1.9 and 2.1, and the recalculated unadjusted comparison estimated a mean difference of 0.2 for Arm B relative to the control arm.

That numerical contrast and its interval describe the data under a simple unadjusted calculation. They do not establish a clinically important benefit or harm. The registry does not report a threshold for meaningful change, patient-level response distributions, or a sponsor-reported inferential analysis. The record also notes missing primary assessments and does not explain how missing observations were handled in the original analysis.

The Day 3 secondary symptom-scale result has the same numerical direction, but it is an additional outcome with an unadjusted comparison. Without a reported multiplicity plan, that result should not be treated as independent confirmation of the primary finding. Both outcomes are short-term symptom measures, and neither alone establishes effects beyond the recorded assessments.

Interpretation is further constrained by incomplete reporting of the original statistical plan, analysis populations, sample-size justification, and missing-data approach. The planning calculations are illustrations based on observed effects and stated assumptions, not evidence of the trial’s original design or a measure of observed power. The serious adverse event summaries report zero events in each group, but the registry record does not report deaths, serious-event terms, or enough detail for a comprehensive safety evaluation.

In general, randomized comparisons can help estimate differences between assigned groups, but the meaning of a result depends on the outcome, the quality and completeness of data, the planned analysis, and uncertainty. The posted data support description of the reported scores and recalculated contrasts. They do not by themselves settle whether any observed difference is clinically consequential, how it generalizes beyond the study setting, or what treatment decision an individual should make.

17. Why This Trial Matters Statistically

This trial illustrates why a continuous endpoint should be read through both its scale and its statistical summary. The primary measure is a physician-rated score with an explicit direction: 1 is excellent and 5 is bad. A positive mean difference therefore has a particular interpretation on the score, but it does not automatically communicate clinical importance. Statistical direction, effect size, and practical meaning are related but distinct.

It also shows the value of separating observed group variation from uncertainty in group averages. The arm standard deviations describe variation among participants, while standard errors and confidence intervals describe uncertainty in estimated means and differences. Treating these quantities as interchangeable can lead to misleading claims about how precisely an effect is known.

The record contains a randomized parallel-group design, but its posted outcome summaries do not include a sponsor-reported analysis. The recalculated unadjusted comparisons can clarify what the means imply under a simple approach, while leaving unanswered whether the original analysis adjusted for other factors or followed a prespecified plan. This distinction is important whenever registry summaries and full statistical reporting are not equally detailed.

The primary and secondary outcomes also demonstrate why multiple-result interpretation matters. Similar directions across outcomes can be informative, but unadjusted p-values do not account for testing more than one endpoint. Missing assessments, unreported analysis populations, and the absence of a documented multiplicity plan further limit the strength of confirmatory claims. These are not merely technical details: they determine how much confidence to place in an apparent pattern.

Finally, planning figures based on observed effects can help illustrate how sample size depends on the target difference and desired power. They cannot be mistaken for the trial’s original rationale or for observed power. Keeping these distinctions clear supports a more transparent reading of clinical trial results.

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.

The posted primary comparison is a recalculated unadjusted analysis of summary statistics, and the registry record has no reported analysis entries. It therefore does not establish whether the sponsor’s analysis used covariate adjustment, a different model, or a different analysis population. The original statistical plan and sample-size justification are not reported.

The primary outcome is a physician global score with ordered categories on a bounded scale. Means summarize the arm averages, but they do not show the distribution across response categories or the separate results for congestion, sneezing, and rhinorrhea. The registry does not report a clinically meaningful difference threshold for interpreting the score.

Missing primary assessments are noted for 8 subjects in the combination product arm and 1 subject in the paracetamol arm. The reasons for missingness and the method used to handle it are not reported in the registry record. The assessment counts are not identical to enrollment, and the available summary cannot establish whether missing-data assumptions affect the comparisons.

The secondary endpoint has an unadjusted comparison, and no multiplicity strategy is reported. The posted summaries also do not provide participant-level data, which would allow evaluation of outcome distributions, influential observations, or alternative analyses. Safety information is limited to group counts for serious and other adverse events; deaths are not reported in the registry record, and serious-event terms are not listed.

Finally, the outcomes concern short-term symptoms during the three-day treatment period. The registry record does not report longer-term follow-up results or detailed information on how masking and allocation were implemented. These limitations restrict conclusions about the analysis, clinical meaning, and scope of the results.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Evaluation of Efficacy and Safety of Tablets of Paracetamol, Dimethindene Maleate and Phenylephrine Hydrochloride in Reducing Symptoms of Common Cold and Flu — NCT01448057.
• Registry record last updated 2017-03-03; status last verified 2017-01.
• Results first posted 2017-01-13.
• 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

NCT01448057 was a completed Phase 3 randomized, single-masked, parallel-group study sponsored by Novartis. It compared tablets containing paracetamol (500 mg), dimethindene maleate (1 mg), and phenylephrine hydrochloride (10 mg) with paracetamol (500 mg) tablets alone. Enrollment was 341.

The primary outcome was the physician global evaluation of nasal symptoms on Day 2, scored from 1 to 5, where 1 was excellent and 5 was bad. The posted arm means were 1.9 for Arm A and 2.1 for Arm B. The recalculated unadjusted mean difference was 0.2, with an unadjusted p-value of 0.037. One secondary symptom-scale outcome was posted for Day 3.

The registry record does not report formal analysis entries, the original sample-size rationale, a multiplicity plan, or the missing-data method. Serious adverse events were recorded as zero in both groups. Deaths are not reported in the registry record.