Safety and Efficacy Study of Guaifenesin and Pseudoephedrine for Symptomatic Therapy to Treat Acute RTI: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Safety and Efficacy Study of Guaifenesin and Pseudoephedrine for Symptomatic Therapy to Treat Acute RTI (NCT01202279), a randomized phase 4 study. The primary outcome is Antibiotic Sparing.

2. Clinical Question

3. Trial Design

This was a Phase 4, randomized, quadruple-masked, parallel-group, multicenter study. It compared Mucinex D with placebo in patients seeking treatment for an acute upper respiratory tract infection. The registry records total enrollment of 1179 and a completed study. The recorded start was 2009-10, and primary completion was 2010-04.

The Mucinex D arm received an extended-release bilayer tablet containing 1200 mg guaifenesin and 120 mg pseudoephedrine HCl twice a day for 7 days, with a full glass of water. The placebo arm received placebo on the same twice-daily schedule for 7 days, also with a full glass of water. The registry’s intervention listing names guaifenesin and placebo, while the arm description names Mucinex D as the active study product.

Quadruple masking indicates that the registry classifies the study as masked at four levels, but the identities of those groups and the practical masking procedures are not reported in the registry record. The allocation ratio, randomization method, any stratification, and the sites involved are also not reported in the registry record. The word “multicenter” describes the study design, but the record does not identify the centers in the information available for this analysis.

The primary endpoint was the number of patients who received an antibiotic by Day 7, analyzed in the Per Protocol Population using Fisher’s Exact Test. The arm counts used in the posted endpoint results are 510.0 for Mucinex D and 523.0 for placebo. These are endpoint analysis counts, not the overall enrollment figure. The registry record does not explain the relationship between overall enrollment and the endpoint analysis population, so the reasons some enrolled participants are not represented in those endpoint counts cannot be determined from this record.

The study’s stated purpose was to determine whether Mucinex D lowered antibiotic use compared with placebo. Information about the original sample-size justification, detailed protocol, monitoring arrangements, or any planned interim analyses is 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 Population using Fishers Exact Test.

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 Antibiotic Sparing, measured over Day 7.

The primary endpoint is the number of patients who received an antibiotic by Day 7. The registry describes the measurement unit as participants and specifies the Per Protocol Population as the analysis population. In practical terms, each participant contributes to the event count according to whether an antibiotic was received within the endpoint’s stated timeframe. The endpoint is a binary outcome at the participant level, reported as counts in each study arm.

This outcome is relevant to the study’s stated purpose because the study asked whether treatment was associated with less antibiotic use for an acute upper respiratory tract infection. Counting antibiotic recipients gives a direct measure of antibiotic use during the study period. It does not, by itself, explain why antibiotics were prescribed, whether prescriptions were clinically appropriate, whether a participant completed a course, or whether symptoms changed. Such details are not reported in the registry record.

The registry lists the endpoint timeframe as Day 7 and identifies Fisher’s Exact Test for the primary analysis. That method is designed for comparing categorical outcomes between groups. The analysis is described as per protocol, so the reported endpoint population is not necessarily identical to the total enrolled population. The precise per-protocol criteria and handling of participants with missing endpoint information are not reported in the registry record.

The endpoint should therefore be read narrowly: it records antibiotic receipt by Day 7 in the specified analysis population. It is not a general measure of all treatment decisions or of the full course of an upper respiratory tract infection.

7. Results Posted in the Registry

• Mucinex D: 17.5% (89/510) versus 23.1% (121/523) on control; risk difference -5.7 percentage points (95% CI -10.6 to -0.8), risk ratio 0.75 (0.59–0.96); unadjusted two-proportion z-test p = 0.023.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary at the participant level: a participant either received an antibiotic by Day 7 or did not. The registry reports the numbers of participants with the event in each arm and identifies Fisher’s Exact Test as the primary comparison method. A binary endpoint can be summarized by event counts and by the proportion of participants with the event. The posted arm proportions are 0.174 for Mucinex D and 0.231 for placebo.

What does Fisher’s Exact Test assess?

Fisher’s Exact Test evaluates whether the observed distribution of a categorical outcome between two groups is compatible with the groups having the same event probability, under the test’s assumptions. It is commonly used for comparisons of binary outcomes. The registry identifies this test for the endpoint, but it does not report the full analysis implementation, including any additional covariates, stratification, or other adjustments. No such features should be assumed.

The sponsor’s posted result is a Fisher Exact analysis with p = 0.025. A p-value describes how unusual data at least as incompatible with the null hypothesis as the observed data would be if the null hypothesis and the test assumptions held. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of an effect. Interpretation should therefore consider the estimated difference and its uncertainty as well as the p-value.

What is the risk difference?

A risk difference subtracts one group’s event proportion from the other’s. In the recalculation, the comparison is expressed as Mucinex D relative to placebo, and the estimated risk difference is -0.057. Its sign indicates that the observed event proportion was lower in the Mucinex D group. The associated 95% confidence interval is -0.106 to -0.008. This measure is expressed on the probability scale and retains a direct connection to the observed proportions.

Other relative measures can describe the same binary comparison on different scales. The recalculated risk ratio is 0.754, with a 95% confidence interval from 0.590 to 0.964. The recalculated odds ratio is 0.702, with a 95% confidence interval from 0.517 to 0.954. Risk ratios compare probabilities; odds ratios compare odds. These are unadjusted recalculations from the posted summary statistics, not additional sponsor-reported analyses. Different scales can make the same data look different numerically, so the measure and its reference group should always be stated.

Why distinguish the posted analysis from recalculation?

The recalculated p-value is 0.023, while the registry’s reported Fisher Exact p-value is 0.025. The record does not identify a discrepancy requiring the sponsor result to be set aside. The sponsor’s own analysis remains the study-reported result; the recalculation is a separate, simple unadjusted check based on the posted counts. Small differences can arise from details of the precise statistical implementation or rounding, but the registry does not document the reason for this difference. No explanation should be inferred.

Likewise, confidence intervals attached to the recalculated measures describe uncertainty under the calculation used for those measures. They do not add information about unreported design features, nor do they resolve uncertainty about eligibility, missing outcomes, or generalizability. The primary analysis population is specified as per protocol, but the per-protocol rules and missing-data approach are not reported in the registry record.

What does over-dispersion mean in general?

General statistical explanation: over-dispersion occurs when observed variability is greater than a statistical model expects. It is a concern in some outcome models, especially when counts are modeled with an assumed variance structure. The primary endpoint is reported as a binary count and the stated comparison is Fisher’s Exact Test; the registry does not report an over-dispersion analysis. No claim about over-dispersion in this trial can be made from the posted endpoint information.

General statistical explanation: a confidence interval gives a range of values reasonably compatible with the data and the method used to calculate it. It is not a prediction interval for an individual participant, nor does it ensure that the true value lies within the particular interval. Its width reflects precision under the method’s assumptions. Results from a single trial also depend on the design, how participants entered the analysis, and the quality and completeness of outcome measurement.

10. Confidence Intervals and Precision

The recalculated risk difference is -0.057, with a 95% confidence interval from -0.106 to -0.008. The point estimate describes the observed contrast in antibiotic receipt by Day 7, with Mucinex D relative to placebo. The interval expresses uncertainty around that estimate under the recalculation method. Its limits are on the negative side of zero, but they span a range of possible effect magnitudes rather than identifying one exact value.

A confidence interval is not a statement that there is a 95% probability that the true effect lies within this particular interval. In general, it describes a procedure that, under its assumptions and repeated use, would produce intervals with the stated coverage. For an individual trial, the interval is a useful way to see both direction and precision, but it does not account for every source of uncertainty, such as unreported design details or limitations in outcome ascertainment.

The recalculated risk ratio is 0.754, with a 95% confidence interval from 0.590 to 0.964. The recalculated odds ratio is 0.702, with a 95% confidence interval from 0.517 to 0.954. These measures describe the comparison on relative scales and should not be interchanged with the risk difference. All are unadjusted recalculations from posted summary statistics.

The sponsor’s reported Fisher Exact result is p = 0.025, while the recalculated p-value is 0.023. A p-value and a confidence interval answer related but different questions: the p-value assesses compatibility with a specified null hypothesis, while the interval displays a range of estimates compatible with the data and calculation method. Neither by itself describes the clinical context or resolves the registry’s unreported details about the analysis population and missing data.

11. 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 80% power and participants per arm for 90% power. They are not total event counts. The illustrations use the observed effect as a reference and consider planning for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. For 100% of the observed effect, the figures are 785 participants per arm for 80% power and 1,050 participants per arm for 90% power. For 75% of the observed effect, they are 1,432 and 1,917 participants per arm, respectively. For 50% of the observed effect, they are 3,302 and 4,420 participants per arm, respectively.

In general, power is the probability that a study will detect an effect of a specified size under stated assumptions if that effect is truly present. The 80% and 90% columns represent different target probabilities of detecting the planning effect. The higher target requires more participants under the same assumptions. Smaller effects are harder to distinguish from random variation, so planning for a smaller fraction of the observed effect requires more participants.

The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. These are planning illustrations computed from the observed effect, not the original design assumptions of the trial. The registry record does not report the trial’s own sample-size justification or original assumptions. These figures are not observed power; they are hypothetical planning estimates under the stated assumptions.

12. How the Sample Size Is Derived

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

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.231; treatment proportion p₁ = 0.175; average p̄ = 0.203.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5688 = 1.1148.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5674 = 0.4775.
4. n = (1.1148 + 0.4775)² / (-0.0568)² = 784.5, rounded up to 785 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.231357552581262                          # control proportion
p1 <- 0.174509803921569                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(1202279)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 785 (80% power), 1,050 (90% power)
 75% of observed effect: n per arm = 1,432 (80% power), 1,917 (90% power)
 50% of observed effect: n per arm = 3,302 (80% power), 4,420 (90% power)
power.prop.test: 784.5 
Simulated power at n = 785 per arm: 0.801 (20000 replicates)

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

13. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary comparison as a Fisher Exact analysis with p = 0.025. The recalculation from the posted arm counts gives an unadjusted p-value of 0.023 and an unadjusted risk difference of -0.057, with a 95% confidence interval from -0.106 to -0.008. The recalculated analysis is a simple check using the summary counts, not a substitute for the study’s reported analysis.

The two p-values are close but not identical. The registry does not explain the difference, so it should not be attributed to a particular analytic choice. The sponsor’s own result is the reported trial analysis. The recalculated estimate and interval add a clear effect-size description based on the posted summary data; they do not provide details about any methods that are not documented in the registry record.

The record does not flag a discrepancy between the sponsor analysis and the recalculation. The primary analysis is described as applying Fisher’s Exact Test to the Per Protocol Population. Further details about the analysis implementation and per-protocol rules are not reported in the registry record. Readers should keep those limits in mind when comparing the sponsor result with the unadjusted recalculation.

14. Multiplicity, Missing Data and Analysis Populations

The registry identifies one primary endpoint for the analysis described: antibiotic receipt by Day 7. It also records two outcome measures and two analyses, but no secondary results are posted in the record. No multiplicity adjustment or testing hierarchy is reported in the registry record. It is therefore not possible to determine whether the study planned other comparisons that could affect interpretation of the primary p-value.

Multiplicity arises when many outcomes, time points, subgroups, or analyses are tested. In general, conducting more tests can increase the chance of obtaining at least one apparently notable result by chance. Prespecified hierarchies or adjustment procedures can address this issue, but the registry record does not report whether either was used for this study. It would be inappropriate to assume that no other analyses were planned, or that an unreported adjustment was performed.

The primary endpoint population is described as the Per Protocol Population. The registry record does not provide the detailed criteria for that population, explain exclusions from it, or describe how adherence was evaluated. It also does not report a missing-data strategy for the primary outcome, the number of participants with missing endpoint information, or whether any imputation was used. As a result, the effect of missing data or per-protocol exclusions on the estimate cannot be assessed from the record.

The total enrollment is 1179, while the primary endpoint arm counts are 510.0 for Mucinex D and 523.0 for placebo. Those figures refer to different reported quantities, and the registry record does not explain how participants were handled between enrollment and the endpoint analysis. No assumptions should be made about the reasons for the difference.

In general, analyses based on participants who meet per-protocol criteria can answer a narrower question than analyses based on everyone randomized, because inclusion can depend on post-randomization events or adherence. The registry does not give enough detail to assess whether that concern affected this result. A full interpretation would require the protocol and a transparent account of participant flow, missing outcomes, and analysis choices, none of which is reported in the registry record.

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 0% reporting threshold.

Most frequent non-serious adverse event terms

The posted serious adverse event figures record zero affected participants in both groups: the Mucinex D group lists 593 participants at risk and 0 with a serious adverse event, and the placebo group lists 591 at risk and 0 with a serious adverse event. These are the registry’s reported counts. They should be read as observations within the recorded safety population and reporting period, not as proof that serious events are impossible or that the groups have identical safety profiles.

The registry also lists 37 participants with other adverse events in the Mucinex D group and 21 in the placebo group. These are aggregate counts; the record does not provide the event terms in the information available for this analysis. Death counts are not reported in the registry record. The duration of safety follow-up and details of adverse-event collection are also not reported in the registry record.

Safety counts have different denominators from the primary endpoint counts. The safety groups list 593 and 591 participants at risk, while the primary endpoint is reported for the Per Protocol Population. Those populations should not be treated as interchangeable. The available figures do not establish causation or explain the nature, timing, or severity of the non-serious adverse events.

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

The trial’s primary result describes antibiotic receipt by Day 7 in the reported Per Protocol Population. The posted counts are 89.0 participants in the Mucinex D group and 121.0 in the placebo group. The corresponding proportions are 0.174 and 0.231, and the recalculated unadjusted risk difference is -0.057. The 95% confidence interval for that difference ranges from -0.106 to -0.008. These statistics describe the observed comparison and its uncertainty; they do not establish why antibiotics were prescribed.

The registry’s stated research question concerns whether Mucinex D lowers antibiotic use relative to placebo. The endpoint is a count of participants who received an antibiotic by Day 7. It does not measure symptom relief, duration of illness, complications, or the appropriateness of prescribing. Those outcomes and details are not reported in the registry record. Accordingly, the result should not be recast as evidence about outcomes that the primary endpoint did not measure.

The reported sponsor analysis is Fisher Exact, p = 0.025. The simple unadjusted recalculation gives p = 0.023. The p-values describe statistical compatibility with a null comparison under their respective methods; they do not quantify the probability that the treatment caused the observed difference, nor do they establish its practical importance. The effect estimate and confidence interval provide additional context about direction and precision.

The study was randomized, quadruple-masked, placebo-controlled, parallel-group, and multicenter, which describes important design features. However, the registry record does not provide the randomization implementation, allocation ratio, detailed eligibility criteria, per-protocol rules, missing-data methods, original sample-size justification, or multiplicity plan. The effect of those unreported details cannot be assessed from the posted record alone.

The result applies most directly to the recorded endpoint, study timeframe, and analysis population. The registry’s overall enrollment is 1179, but the primary endpoint counts are reported for the Per Protocol Population, and the record does not explain the relationship between those figures. The record also does not identify the reasons for antibiotic receipt or report secondary outcome results. The statistical finding should therefore be interpreted as a comparison of recorded antibiotic use by Day 7, not as a complete account of treatment decisions or clinical outcomes.

17. Why This Trial Matters Statistically

This trial illustrates why an endpoint must be interpreted according to what it actually counts. “Antibiotic sparing” is the registry’s endpoint title, but the measured outcome is the number of participants who received an antibiotic by Day 7. That measure gives a direct group comparison of antibiotic receipt, while leaving unanswered questions about prescribing rationale, symptoms, and other clinical outcomes.

It also demonstrates the value of reporting effect estimates alongside tests of statistical significance. The recalculated risk difference of -0.057 and its 95% confidence interval communicate direction and uncertainty on the probability scale. The sponsor’s Fisher Exact p-value of 0.025 is useful as part of the reported analysis, but a p-value alone does not show the size or precision of the contrast.

The distinction between the sponsor’s analysis and a simple recalculation is important in registry interpretation. The recalculation uses posted summary counts and yields p = 0.023, while the registry reports p = 0.025. The values are close, but the record does not explain the difference. Keeping the reported result distinct from the unadjusted check avoids implying that a recalculation reproduces undocumented analytic details.

Finally, design labels and endpoint counts do not replace a full account of methods. The registry records randomization and quadruple masking, but does not report the operational details, per-protocol criteria, missing-data handling, or multiplicity plan. Recognizing what the record establishes—and what it leaves unreported—is part of sound statistical interpretation.

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 trial-specific details needed for a fuller assessment are not reported in the registry record. These include the eligibility criteria, the method used to generate and conceal random allocation, the allocation ratio, the identity of the groups included in quadruple masking, and the practical procedures used to maintain masking. The study is described as multicenter, but center-level information is not reported in the record used for this analysis.

The primary outcome is analyzed in the Per Protocol Population, but the registry does not state the criteria for that population or describe adherence assessment. It does not explain the relationship between total enrollment of 1179 and the endpoint arm counts of 510.0 and 523.0. Participant flow, exclusions, and missing endpoint information are not reported in the registry record, so the possible influence of these factors cannot be evaluated.

The registry does not report the original sample-size justification, planned effect size, or any interim analyses. The planning figures are illustrative calculations based on the observed effect and should not be read as evidence about the trial’s original design. The record also does not describe a multiplicity plan, adjustment for other factors, or a missing-data method.

The primary endpoint records whether an antibiotic was received by Day 7, but the reasons for prescribing, details of antibiotic use, and other clinical outcomes are not reported. No secondary results are posted in the record. For safety, serious adverse event counts are listed, but death counts, event-level terms for other adverse events, and the duration and methods of safety follow-up are not reported in the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Safety and Efficacy Study of Guaifenesin and Pseudoephedrine for Symptomatic Therapy to Treat Acute RTI — NCT01202279.
• Registry record last updated 2020-12-30; status last verified 2020-12.
• Results first posted 2012-11-05.
• 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

NCT01202279 is a completed Phase 4 randomized, quadruple-masked, placebo-controlled, parallel-group, multicenter study of Mucinex D in patients with acute upper respiratory tract infection. The registry records enrollment of 1179 and study dates from 2009-10 to primary completion in 2010-04. Mucinex D was described as guaifenesin and pseudoephedrine HCl given twice a day for 7 days; placebo was given on the same schedule.

The primary endpoint was the number of patients who received an antibiotic by Day 7 in the Per Protocol Population. The reported Fisher Exact analysis gives p = 0.025. The unadjusted recalculation estimates a risk difference of -0.057, with a 95% confidence interval from -0.106 to -0.008, and p = 0.023. The registry does not report detailed per-protocol criteria, missing-data handling, or the original sample-size justification.