A Study of Ibuprofen 250 mg / Acetaminophen 500 mg Comparing The Antipyretic Effects in Healthy Male Volunteers: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study of Ibuprofen 250 mg / Acetaminophen 500 mg Comparing The Antipyretic Effects in Healthy Male Volunteers (NCT02761980), a randomized phase 3 study. The primary outcome is Time Weighted Sum of Temperature Difference (WSTD) From 0 to 8 Hours.

2. Clinical Question

3. Trial Design

This was a randomized, triple-masked, parallel-group, placebo-controlled Phase 3 study. The official title describes a full factorial design and compares a single oral dose of ibuprofen 250 mg plus acetaminophen 500 mg with each component treatment in healthy male volunteers whose fever was induced by an endotoxin. The four groups were the combination, ibuprofen alone, acetaminophen alone, and placebo. The registry lists enrollment of 290 and the study status as completed.

The study began on 2016-12-06, with primary completion on 2017-12-06. The record describes a single-dose evaluation. It does not report details of the randomization sequence, the allocation procedure, or how masking was implemented. The original design’s sample-size assumptions and justification are not reported in the registry record; the planning illustrations calculated from posted effects are separate from those original design decisions.

For the primary endpoint, the registry reports analyzed groups of 27 for placebo, 81 for the combination, 83 for ibuprofen, and 82 for acetaminophen. These endpoint analysis counts should not be treated as interchangeable with the adverse-event groups’ at-risk counts. The primary analysis population is described as modified intent to treat: randomized participants who were dosed, had the stated RSE procedures under the protocol after amendment 4, and had a baseline assessment. The record does not provide a complete explanation of RSE in the available description.

The registry lists four secondary outcomes: time-weighted temperature differences through hours 2, 4, and 6; time to return to normal body temperature; time to rescue medication; and the time-weighted temperature difference from 6 to 8 hours. Results are posted for the latter outcome, but the other secondary outcome 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.

Before assignment: In this study, participants were administered at least 1 test dose of reference standard endotoxin (RSE) intravenously, based on their body weight before randomization, to induce pyrexia in them.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Modified intent to treat (mITT) population included all randomized participants who were dosed with the study medication and RSE per procedures specified in protocol post amendment 4 and had a baseline assessment. Here, "Overall Number of Participants Analyzed" signifies participants who were evaluable for this outcome measure.

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.

Population: Safety analysis set included all participants who received study medication.

6. Primary Endpoint

The registry lists the primary outcome as Time Weighted Sum of Temperature Difference (WSTD) From 0 to 8 Hours, measured over 0 to 8 hours post-dose.

The primary endpoint, the time-weighted sum of temperature differences from baseline through 8 hours, combines serial temperature readings into one measure. At each post-dose time point, the temperature difference is defined as baseline temperature minus the temperature measured after dosing. Each interval’s difference is weighted by the elapsed time between consecutive readings. The listed readings begin at 10 minutes and continue through 8 hours after dosing.

Because the measure accumulates temperature differences across time, it reflects both the size and duration of the observed differences during the measurement period. A larger positive value means a larger time-weighted sum of baseline-minus-post-baseline temperature differences. It is not the same as comparing one temperature at a selected time, nor does the endpoint by itself describe when a participant’s temperature returned to normal.

The registry reports the endpoint as a mean in degrees Fahrenheit, with standard deviation as the dispersion measure. A mean offers a group-level summary for a continuous outcome; the standard deviation describes variation among observations within the group. This type of summary permits comparisons of average endpoint values across the treatment groups, while retaining only limited information about the individual trajectories that contributed to each mean.

The endpoint’s use is consistent with the study’s stated aim of evaluating antipyretic effects over a period after a single dose. The registry record does not report a clinically important difference for this measure, so the clinical importance of a particular numerical contrast cannot be determined from the endpoint definition alone.

7. Results Posted in the Registry

• Ibuprofen 250 mg+Acetaminophen 500 mg: mean 12.54 versus 9.28 on control; difference 3.26 (95% CI 0.56 to 5.96), standardized effect d = 0.57; z-test p = 0.018.
• Ibuprofen 250 mg: mean 11.09 versus 9.28 on control; difference 1.81 (95% CI -0.96 to 4.58), standardized effect d = 0.28; z-test p = 0.201.
• Acetaminophen 500 mg: mean 12.39 versus 9.28 on control; difference 3.11 (95% CI 0.34 to 5.88), standardized effect d = 0.49; z-test p = 0.028.

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.

Time Weighted Sum of Temperature Difference From 6 to 8 Hours

• 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:
  • Ibuprofen 250 mg+Acetaminophen 500 mg: mean 5.69 versus 4.96 on control; difference 0.73 (95% CI -0.21 to 1.67), standardized effect d = 0.37; z-test p = 0.127.
  • Ibuprofen 250 mg: mean 5.49 versus 4.96 on control; difference 0.53 (95% CI -0.44 to 1.50), standardized effect d = 0.24; z-test p = 0.285.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Ibuprofen 250 mg+Acetaminophen 500 mg and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Ibuprofen 250 mg and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists secondary outcomes covering earlier time-weighted temperature summaries, return to normal body temperature, rescue medication timing, and the 6-to-8-hour temperature summary. Results are available for the 6-to-8-hour measure, but results for the other listed secondary outcomes are not reported in the registry record. The available secondary results do not establish a consistent statistically clear separation between the combination and its comparators. This provides a more limited and less conclusive picture than the sponsor’s primary combination-versus-placebo finding.

For the posted 6-to-8-hour outcome, the sponsor reports comparisons of the combination with placebo and with ibuprofen. Both reported confidence intervals include zero, and both p-values are above 0.05. The unadjusted recalculated comparisons presented for this outcome likewise have intervals that include zero. These secondary findings should not be treated as evidence of a confirmed difference over that later time window.

Secondary outcomes can help describe whether a primary endpoint pattern is accompanied by related changes in other measures. However, they carry less weight when the record does not report a complete set of results and does not describe how multiplicity was handled. Examining multiple outcomes and treatment contrasts increases the chance of at least one apparently notable result arising by chance if no adjustment or other prespecified strategy is used. The registry record does not report such a strategy. The secondary analyses are therefore best read as supportive or exploratory context, not as independent confirmation of the primary result.

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

• Time Weighted Sum of Temperature Differences (WSTD) From Baseline Through Hours 2, 4 and 6
• Time to Return to Normal Body Temperature
• Time to Rescue Medication
• Time Weighted Sum of Temperature Difference From 6 to 8 Hours

9. Statistical Interpretation

10. Statistical Methods Explained

What does the reported mean represent?

The primary endpoint is continuous: it is a numerical measurement that can take a range of values, rather than a category such as event or no event. The registry reports a mean for each group. A group mean describes the average endpoint value among the participants included in that group’s analysis. It does not imply that every participant had a value near the mean, and it cannot show the shape of the group’s full distribution.

The registry also reports a standard deviation for each group. In general, standard deviation describes the spread of individual observations around the group mean. Greater spread means individual observations vary more widely. It is distinct from a standard error, which describes the uncertainty of an estimated mean. The record lists standard deviations for the outcome groups and standard errors used in the recalculation; these quantities answer different questions and should not be substituted for one another.

What is a mean difference?

A mean difference compares the average endpoint value in one group with the average in another. The recalculated comparisons are simple, unadjusted contrasts based on the posted summary statistics. For example, the recalculated combination-versus-placebo contrast is the difference between those groups’ reported means. It does not adjust for baseline temperature or other participant characteristics. A positive contrast in these comparisons indicates a higher mean in the treatment group named in the comparison than in placebo.

The sponsor’s reported analyses use ANCOVA and report least-squares mean differences. ANCOVA is a general statistical method that compares group outcomes while adjusting for covariates included in the model. Adjusted, least-squares mean contrasts can therefore differ from direct comparisons of group means. The registry record names ANCOVA but does not report the full model specification, the covariates included, or enough detail to reproduce the sponsor’s estimates.

How should a confidence interval be read?

A confidence interval expresses uncertainty around an estimated contrast. In general, a wider interval indicates less precision, while a narrower interval indicates greater precision, all else being equal. An interval that includes zero is compatible with no difference under the model and assumptions used; an interval that excludes zero indicates that the estimated contrast is not centered on zero at the stated confidence level. An interval does not give the probability that the true effect lies within its particular limits.

The sponsor reports 95% confidence intervals for the ANCOVA contrasts. The recalculated intervals are unadjusted and arise from the posted summary statistics. The two sets of estimates need not match because one is a model-based adjusted analysis and the other is a simple recalculation. The record does not provide enough information to determine which particular modeling or analysis choices account for the observed discrepancy.

What does a p-value add?

A p-value describes how incompatible the observed data are with a specified null hypothesis under the statistical model. Smaller p-values indicate greater incompatibility with that null model, but a p-value is not the probability that the null hypothesis is true. It does not measure the size or clinical importance of a difference. It also does not account automatically for the number of endpoints and comparisons examined.

The sponsor’s p-values accompany its ANCOVA comparisons, and the recalculated p-values accompany unadjusted comparisons. The latter should not be treated as substitutes for the sponsor’s results, particularly because the registry record identifies a discrepancy. The reported results do not specify a multiplicity adjustment, so the p-values should be read as reported rather than as evidence that the overall family of comparisons has controlled error rates.

Why can an adjusted result differ from a recalculation?

A recalculation from group means and standard deviations uses only those summary values and group sizes. ANCOVA can incorporate baseline or other model covariates, depending on the analysis specification. Adjustments can change both the estimated contrast and its uncertainty. In addition, a registry summary may not contain the individual-level data or full model details needed to reproduce the sponsor analysis. The record does not report enough information to identify the precise source of the discrepancy. For that reason, the sponsor’s own analysis takes precedence when describing the sponsor’s finding.

Why do repeated measurements and weighting matter?

The endpoint uses multiple temperature readings over time, with each temperature difference weighted by the elapsed time between consecutive readings. In general, weighting by elapsed time makes intervals of different lengths contribute according to their duration. This produces a summary across the measurement period, rather than treating the endpoint as a simple average of isolated readings. It also means the final score depends on the pattern of measurements across time. The registry describes the measurement schedule and definition, but does not provide individual temperature trajectories in the record summarized for this analysis.

The outcome is reported as a mean continuous measure with standard deviation. It is not a count outcome, so issues such as over-dispersion in counts are not the central concern for these comparisons. General statistical practice still requires attention to the distribution of the continuous outcome, model assumptions, and the effect of missing observations. The registry record does not report diagnostic checks for the ANCOVA model or details of how missing endpoint measurements were handled.

11. Confidence Intervals and Precision

Precision is reflected in the width of a confidence interval: broad intervals leave more uncertainty about the size of the contrast, while narrow intervals constrain it more tightly. For the sponsor’s primary comparison of combination versus placebo, the 95% interval runs from 1.13 to 5.15 around the least-squares mean difference of 3.14. It excludes zero, but still spans a range of possible contrast sizes under the reported analysis.

The sponsor’s intervals for combination versus the single components extend from negative to positive values. They therefore include zero and allow for either direction of difference under the reported model. Their p-values are also not small under the sponsor analysis. These results do not establish that the combination differs from either component on the primary endpoint.

The recalculated combination-versus-placebo interval, from 0.565 to 5.955, is wider and has a different estimate from the sponsor’s ANCOVA interval. The distinction matters: the recalculation is unadjusted, while the sponsor reports an adjusted model. Given the stated discrepancy, the sponsor’s analysis is the appropriate reference for the sponsor’s reported result.

Precision also depends on the amount of information in each comparison. The placebo primary analysis group is smaller than the active-treatment analysis groups, as reflected in its reported count and standard deviation. The registry record does not report a formal precision target or the original design calculations, so it is not possible to determine from this record whether the achieved precision matched the trial’s intended goal. Confidence intervals quantify statistical uncertainty, not clinical importance; the record does not state a threshold for an important difference in this endpoint.

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 illustrations are planning calculations based on the observed effects, not the trial’s original design assumptions. For these continuous-outcome comparisons, the figures are participants per arm, not total event counts. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning scenario uses the stated fraction of the observed effect as the effect to detect.

The 80% power column gives the estimated participants per arm for a future comparison to have an 80% chance of detecting the chosen effect under those assumptions, if that effect and the calculation assumptions hold. The 90% power column expresses the corresponding planning target for a 90% chance. A higher target for power generally requires more participants for the same effect size.

Rows describe planning for the full observed effect, 75% of the observed effect, and 50% of the observed effect. The smaller the effect to be detected, the more participants the calculation requires. This relationship is visible across the planning rows and in the sample-size curve. Values are illustrations rather than observed properties of the completed trial; this is not observed power.

The trial’s own original sample-size justification and design assumptions are not reported in the registry record. These calculations therefore should not be used to infer what the investigators planned before the study or whether the completed study met a prespecified power target.

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 = 3.260; pooled standard deviation σ = 5.746.
2. n = 2 × (1.96 + 0.842)² × 5.746² / 3.260² = 48.8, rounded up to 49 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 <- 3.26                      # observed difference in means
sigma <- 5.74624202873758                     # 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(2761980)
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 = 49 (80% power), 66 (90% power)
 75% of observed effect: n per arm = 87 (80% power), 117 (90% power)
 50% of observed effect: n per arm = 196 (80% power), 262 (90% power)
power.t.test: 49.8 
Simulated power at n = 49 per arm: 0.790 (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 sponsor analyses are ANCOVA comparisons reported as least-squares mean differences, with 95% confidence intervals and p-values. These adjusted results are distinct from the recalculated mean differences, which are simple unadjusted comparisons derived from the posted group summaries. They answer related but not identical statistical questions.

For combination versus placebo, the sponsor reports a least-squares mean difference of 3.14, a 95% confidence interval from 1.13 to 5.15, and p = 0.002. The recalculation yields a mean difference of 3.26, a 95% confidence interval from 0.565 to 5.955, and p = 0.018. The estimate, interval, and p-value differ. The record does not provide the ANCOVA model details needed to reproduce or explain the difference fully.

The recalculations are useful as a check on the direction and scale of the posted group summaries, but they do not supersede the sponsor’s analysis. Because a discrepancy is flagged, the sponsor’s own analysis takes precedence when reporting the trial’s inferential result. The same distinction applies to the other comparisons: unadjusted recalculations should not be presented as though they were the sponsor’s adjusted estimates.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists multiple treatment groups, a primary endpoint, and several secondary outcomes. The reported ANCOVA results include several pairwise treatment comparisons, while the recalculations also cover multiple comparisons. When many hypotheses are assessed, the chance of at least one false-positive result can increase. Statistical methods for addressing this issue may include prespecifying a hierarchy, adjusting significance thresholds, or controlling an error rate across a family of comparisons.

The multiplicity strategy is not reported in the registry record. The reported p-values should therefore be interpreted as the values associated with the individual comparisons, not as evidence that the overall family of comparisons has controlled error rates. This is particularly relevant to secondary outcomes, for which the record does not provide a complete set of outcome results.

The record describes the primary analysis population as modified intent to treat: randomized participants who were dosed, had RSE procedures as specified after protocol amendment 4, and had a baseline assessment. It does not provide a complete explanation of RSE in the available description. The record does not report the number of participants excluded from this population, reasons for exclusion, or missing-data methods for the primary outcome. It also does not report whether sensitivity analyses were conducted to assess the effect of missing observations or alternative analysis populations.

The registry’s total enrollment is 290, while the primary endpoint analyses report group-specific analyzed counts. Those endpoint counts identify the observations contributing to the listed summaries; they do not by themselves explain every difference between enrollment and analysis. The adverse-event at-risk counts are reported separately and differ from the endpoint analysis counts. Reasons for these differences are not reported in the registry record.

Details about interim analyses, a prespecified statistical analysis plan, and the original sample-size justification are not reported in the registry record. Their absence from the record does not establish that they were not performed or planned; it means their methods cannot be assessed from the posted information.

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 non-serious adverse event terms

The registry reports serious adverse events, other adverse events, and deaths by group, using separate at-risk counts for the safety summaries. Serious adverse events were reported for zero participants in each of the four groups. The record lists no serious adverse-event terms. Deaths were also reported as zero in every group.

For other adverse events, one participant was reported in the placebo group and one in the combination group; none were reported in the ibuprofen or acetaminophen groups. These are the counts recorded in the registry, not a complete description of event types, timing, severity, or relationship to treatment. The record does not provide serious event terms because none are listed, and it does not provide enough detail to characterize the reported other events further.

Safety at-risk counts differ from the primary endpoint analysis counts. The figures should be read within their own safety-summary denominators and not substituted for the endpoint analysis populations. Zero reported events in a group do not prove that an event is impossible, and these counts alone do not establish comparative safety. The study’s setting, population, single-dose design, and limited event counts constrain what can be inferred from these summaries.

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

The posted primary endpoint results describe a higher mean time-weighted temperature difference for the combination group than for placebo. The sponsor’s ANCOVA comparison has a confidence interval above zero and a p-value of 0.002. This is evidence of a difference in the measured endpoint under the sponsor’s reported analysis. It is not, by itself, a complete account of the clinical meaning of that difference.

The sponsor’s comparisons of the combination with ibuprofen alone and acetaminophen alone have confidence intervals that include zero. The registry results therefore do not establish a difference between the combination and either single component on the primary measure. The record does not report a threshold for a clinically important difference, so statistical evidence of a contrast versus placebo should not be equated with a judgment about its practical importance.

The finding applies to the studied setting: healthy male volunteers with fever induced by an endotoxin who received a single dose. The registry record does not report evidence from other populations or settings, and the results should not be assumed to characterize those contexts. The primary endpoint is a time-weighted summary over 8 hours, not a direct measure of every aspect of fever experience or a substitute for the listed secondary outcomes.

Nor do the results establish that a treatment works or does not work in a broader clinical sense. They describe group-level statistical comparisons in this study, subject to the analysis methods and limitations of the registry record. The sponsor’s analysis takes precedence over the unadjusted recalculation where they differ. Incomplete reporting of secondary outcomes, missing-data handling, multiplicity methods, and model details further limits what can be concluded from the record alone.

18. Why This Trial Matters Statistically

This trial illustrates why an endpoint definition matters to statistical interpretation. The primary measure is not a single temperature reading: it combines baseline-minus-post-baseline differences across a specified series of time points and weights those differences by elapsed time. The resulting mean describes an accumulated pattern over the assessment period. A reader who treats it as an ordinary endpoint temperature would misunderstand what the reported contrast represents.

It also illustrates the distinction between descriptive group summaries and adjusted model-based comparisons. The registry’s means and standard deviations support a transparent unadjusted recalculation, while the sponsor reports ANCOVA least-squares mean differences. The resulting estimates and intervals differ for the primary combination-versus-placebo comparison. Recognizing the estimand and analysis method is essential; the recalculation is not a replacement for the sponsor’s model-based result.

The placebo comparison and the comparisons with the individual components address different questions. The sponsor’s primary comparison with placebo shows a difference in the measured endpoint, while the comparisons with the components do not establish a difference. Keeping those contrasts separate prevents an overstatement that the combination is distinguishable from each component.

Finally, the record makes visible important limits to registry-based interpretation. It reports multiple outcomes and comparisons but does not report a multiplicity strategy, detailed model specification, complete secondary results, missing-data methods, or the original sample-size justification. Statistical significance, precision, and clinical relevance are separate considerations. A careful reading preserves those distinctions rather than reducing the evidence to a single 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 study population was restricted to healthy male volunteers with endotoxin-induced fever, and the intervention was a single oral dose. The findings therefore describe a specific experimental setting. The registry record does not report evidence that would establish how the results apply to other populations, fever causes, dosing schedules, or clinical settings.

The primary endpoint compresses repeated temperature measurements into a time-weighted sum. This is informative about accumulated differences across the stated period, but it does not show the full time course for individual participants. The record does not provide individual trajectories or a stated threshold for a clinically important difference in the measure.

The sponsor’s reported ANCOVA comparisons cannot be fully reproduced from the registry information because the record does not specify the complete model, including its covariates. The unadjusted recalculations differ from the sponsor analysis, and the sponsor’s estimates take precedence. This discrepancy limits the value of the recalculation as a substitute for the sponsor’s inferential analysis.

Several important reporting details are not reported in the registry record: the multiplicity strategy, missing-data procedures, sensitivity analyses, interim analyses, and original sample-size assumptions. Although four secondary outcomes are listed, results are not reported for all of them. The safety summaries provide event counts but not fuller descriptions of the other adverse events. Together, these constraints mean that the record supports a focused reading of the posted comparisons, not a complete assessment of every planned analysis or broader clinical implication.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Study of Ibuprofen 250 mg / Acetaminophen 500 mg Comparing The Antipyretic Effects in Healthy Male Volunteers — NCT02761980.
• Registry record last updated 2018-12-07; status last verified 2018-11.
• Results first posted 2018-12-07.
• 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

The registry describes a completed, randomized, triple-masked, parallel-group, placebo-controlled Phase 3 study of a single dose of ibuprofen, acetaminophen, their combination, or placebo in healthy male volunteers with endotoxin-induced fever. Enrollment was 290.

The primary endpoint was the time-weighted sum of baseline-minus-post-baseline temperature differences from 0 to 8 hours. The sponsor’s ANCOVA analysis reported a combination-versus-placebo least-squares mean difference of 3.14, with a 95% confidence interval from 1.13 to 5.15 and p = 0.002. The sponsor’s comparisons of the combination with either component had confidence intervals that included zero.

Unadjusted recalculations differ from the sponsor’s analysis, so the sponsor analysis takes precedence. The record does not report several methods needed for a fuller assessment, including the multiplicity approach, missing-data handling, complete model specification, and original sample-size justification. Secondary outcome results are incomplete in the registry record.