Treatment of Aspergillus Fumigatus (a Fungal Infection) in Patients With Cystic Fibrosis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Treatment of Aspergillus Fumigatus (a Fungal Infection) in Patients With Cystic Fibrosis (NCT00528190), a randomized phase 4 study. The primary outcome is The Primary Outcome Measure Will be the Number of Patients Who Experience a Respiratory Exacerbation Requiring Intravenous Antibiotics in the Two Treatment Groups Over the 24 Week Trial Treatment Period..

2. Clinical Question

3. Trial Design

The registry describes a randomized, parallel-group, placebo-controlled phase 4 trial. Enrollment was 35. The reported primary-outcome groups contain 18 participants assigned to itraconazole and 16 assigned to placebo. Those outcome group counts do not account for every enrolled participant, and the reason is not reported in the registry record. They should not be treated as a complete account of enrollment or as evidence about exclusions or missing outcome data.

The itraconazole regimen was 5mg/kg/day for 24 weeks; the placebo arm was also described as lasting 24 weeks. The primary outcome timeframe was 24 weeks. The registry status is completed, with a start date of 2007-10 and primary completion date of 2010-08. The sponsor was Ottawa Hospital Research Institute.

The official title calls the study randomized, double-blind, and placebo-controlled, while the registry's masking classification says quadruple. The record does not identify which people or roles were masked, nor does it explain the difference in wording. Randomization is reported, but the sequence-generation method and allocation-concealment procedures are not reported in the registry record. The record also does not describe the trial's original sample-size rationale, protocol deviations, or the statistical analysis plan.

One primary outcome measure is listed, and no secondary outcomes are posted. The listed outcome is a participant count rather than a continuous measurement or a time-to-event endpoint. The record does not supply analyses beyond the posted arm counts and the unadjusted comparison calculated from those summary counts.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as The Primary Outcome Measure Will be the Number of Patients Who Experience a Respiratory Exacerbation Requiring Intravenous Antibiotics in the Two Treatment Groups Over the 24 Week Trial Treatment Period., measured over 24 weeks.

The primary endpoint counted participants who experienced a respiratory exacerbation requiring intravenous antibiotics during the 24-week treatment period. It is a binary participant-level outcome: a participant either met the stated event definition during the period or did not. The posted counts were 4 participants in the itraconazole group and 5 in the placebo group.

This endpoint captures an exacerbation serious enough to require intravenous antibiotics, rather than every possible respiratory symptom or change in health. In general, an event defined by a concrete clinical consequence can be easier to interpret than a broad or subjective symptom measure. It also gives a direct way to compare the proportion of participants meeting the event definition in each randomized group.

That general advantage does not remove the need for clear outcome assessment procedures. The registry description does not report how exacerbations were identified or adjudicated, whether assessment was blinded in practice, or how participants with incomplete follow-up were handled. It also does not report the number of events outside the stated primary definition or provide additional clinical outcomes to place the endpoint in context. The endpoint therefore answers a specific question about exacerbations requiring intravenous antibiotics during the stated period, not every aspect of respiratory health.

7. Results Posted in the Registry

• Itraconazole: 22.2% (4/18) versus 31.2% (5/16) on control; risk difference -9.0 percentage points (95% CI -38.8 to 20.7), risk ratio 0.71 (0.23–2.20); unadjusted two-proportion z-test p = 0.551.

8. Statistical Interpretation

9. Statistical Methods Explained

The comparison concerns a binary endpoint: whether each participant experienced a respiratory exacerbation requiring intravenous antibiotics during the 24-week period. For a binary outcome, the basic group summaries are the number of participants with the event and the number assessed in that group. The posted event counts are 4 for itraconazole and 5 for placebo. The respective outcome group sizes are 18 and 16.

What does a risk difference describe?

A risk difference expresses the contrast between the event proportions in the groups by subtracting one group's proportion from the other's. A value of zero corresponds to equal observed proportions; a negative or positive value depends on which group is subtracted from which. The reported comparison is oriented so that the estimate is negative for itraconazole relative to placebo. The underlying displayed proportions are 0.222 for itraconazole and 0.312 for placebo, while the risk-difference interval crosses zero. Because that interval includes zero and values on both sides, the direction of the point estimate alone should not be treated as conclusive.

What does a p-value tell the reader?

The unadjusted p-value is 0.551. In general, a p-value measures how unusual data at least as discrepant as the observed data would be under a specified null model. It does not give the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. The trial's own prespecified testing procedure and significance threshold are not reported in the registry record. The planning illustration uses a two-sided significance level of 0.05, but that assumption should not be mistaken for documentation of the trial's original analysis plan.

For orientation, a confidence interval describes a range of effect values compatible with the observed data under the method used to construct it. A wider interval indicates less precision. A confidence interval crossing the null value for a risk difference means the data are compatible with no difference as well as with effects in either direction. The registry material does not identify the interval-construction method, so method-specific properties cannot be assessed.

Why are other effect measures sometimes used?

General statistical practice may express a binary comparison as a risk ratio or odds ratio as well as a risk difference. A risk ratio compares the event proportions as a ratio; an odds ratio compares the event odds. The posted comparison includes these measures, but their estimates are imprecise in these small groups. Ratios can be less intuitive than an absolute difference, and neither measure removes the uncertainty created by sparse event counts. No adjusted versions are reported.

What can randomization contribute?

In general, random allocation aims to make treatment groups comparable with respect to measured and unmeasured factors at the point of assignment, on average. It does not guarantee that groups will be balanced in every small trial, and it cannot correct for missing outcomes or departures from the assigned treatment by itself. The record identifies randomization but does not describe the sequence-generation or concealment methods. It also does not state whether the posted analysis follows intention-to-treat principles or another analysis population.

Why does event frequency matter?

General statistical reasoning: estimates based on few observed events tend to be unstable. A change in the classification of a participant can materially alter an event count when the groups are small. This is one reason the confidence interval matters alongside the point estimate and p-value. Over-dispersion is more commonly a concern for count models when observed variability exceeds a model's assumptions; the posted primary endpoint is instead presented as a binary participant outcome, and no count-model analysis is reported. The registry does not give enough detail to assess alternative models, covariate adjustment, or sensitivity analyses.

The reported p-value is unadjusted. It does not account for a family of comparisons, and the record reports no secondary outcome analyses. Without a documented analysis plan, it is not possible to determine whether the posted comparison was the prespecified primary test or whether other analytic decisions were planned. The numerical summaries can describe the observed result, but they cannot fill in those missing methodological details.

10. Confidence Intervals and Precision

The outcome counts are 4 events among 18 participants in the itraconazole group and 5 among 16 in the placebo group. The calculated unadjusted risk-difference estimate is negative for itraconazole relative to placebo. Its confidence interval extends across zero and includes values in both directions. The interval is broad relative to the point estimate, indicating that the magnitude and direction of the underlying difference are not estimated precisely.

In general, a confidence interval conveys uncertainty in an estimate: narrower intervals indicate greater precision, while wider intervals leave more plausible values consistent with the data. The interval does not mean that every value inside it is equally likely, and it is not a guarantee that the true value lies within its limits. Its interpretation depends on the statistical method and assumptions used to construct it; those details are not reported in the registry record.

Here, uncertainty is important because the outcome groups are small and the event counts are sparse. The data are compatible with a reduction in event risk under itraconazole, but also with no difference or an increase. The unadjusted p-value of 0.551 is consistent with the interval's lack of a clear separation from the null. Neither the point estimate nor the p-value should be read alone as a measure of treatment importance.

The registry record does not provide a sponsor-reported confidence interval or explain its construction. The precision assessment is therefore limited to the unadjusted comparison calculated from the posted summary statistics. No adjustment for baseline factors or missing outcome information is reported.

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, not total participants and not total events. They are illustrative calculations based on the observed effect, rather than the trial's original design assumptions. The registry record does not report the original sample-size justification or planning assumptions for the trial.

The calculation assumes a two-sided significance level of 0.05, equal allocation between the arms, and a normal approximation. It considers the full observed effect and smaller assumed effects: 100%, 75%, and 50% of the observed effect. For each assumption, the 80% power column gives the participants per arm calculated for an 80% chance of detecting that assumed effect under the stated planning model if it were the true effect. The 90% power column gives the corresponding per-arm planning figure for a 90% chance.

As the assumed effect becomes smaller, the calculation requires more participants per arm to distinguish it from no difference under the same assumptions. The numbers in the planning display therefore rise as the effect fraction is reduced. The values are 377 and 503 participants per arm for planning around 100% of the observed effect; 688 and 920 for 75%; and 1,585 and 2,122 for 50%, for 80% and 90% power respectively.

These figures are not observed power. They are prospective planning illustrations derived from the observed effect and depend on the stated assumptions. They should not be interpreted as evidence about how likely the trial was to find an effect, nor as a reconstruction of the investigators' original target enrollment.

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 = 0.312; treatment proportion p₁ = 0.222; average p̄ = 0.267.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6259 = 1.2268.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6226 = 0.5240.
4. n = (1.2268 + 0.5240)² / (-0.0903)² = 376.1, rounded up to 377 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 <- 0.3125                          # control proportion
p1 <- 0.222222222222222                          # 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(528190)
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 = 377 (80% power), 503 (90% power)
 75% of observed effect: n per arm = 688 (80% power), 920 (90% power)
 50% of observed effect: n per arm = 1,585 (80% power), 2,122 (90% power)
power.prop.test: 376.1 
Simulated power at n = 377 per arm: 0.804 (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. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study evaluates multiple outcomes, time points, subgroups, or statistical comparisons. In general, making many tests without an appropriate plan can increase the chance of a misleading positive result. The registry record lists one primary outcome measure and reports no secondary outcome measures. It lists no posted analyses, so there is no reported family of outcome tests to assess for multiplicity adjustment.

The record does not report whether the primary endpoint was selected before data collection, whether any interim analyses were planned or conducted, or whether the analysis plan specified a hierarchy of tests or adjustment for multiple comparisons. These details are not reported in the registry record; their absence from the record does not show what was or was not done outside it. The reported p-value is unadjusted.

Missing-data handling is also not described. The enrollment figure is 35, whereas the endpoint group counts are 18 for itraconazole and 16 for placebo. The registry record does not explain why these figures differ. It does not state whether the discrepancy reflects unavailable outcome data, exclusions, analysis-population definitions, or another reason. No imputation method, missingness assessment, or sensitivity analysis is reported.

The analysis population is not identified. The record does not say whether the outcome comparison used all randomized participants, only participants with available outcome data, or another defined population. Nor does it report adherence, treatment discontinuation, crossover, or protocol-deviation information needed to understand how assignment and follow-up were handled. These omissions limit assessment of bias and make it inappropriate to label the posted comparison as an intention-to-treat analysis.

These limitations matter because the interpretation of an unadjusted p-value and confidence interval depends on the analysis being aligned with a prespecified plan and on the outcome data being handled appropriately. Without those details, the posted comparison remains a useful descriptive calculation, but its relation to the original trial analysis cannot be established.

14. 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 serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: spontaneous pneumothorax (5.6%).

The registry reports serious adverse events for the itraconazole group among 18 participants at risk, with 1 participant affected. For placebo, 17 participants were listed as at risk, with 0 affected. The reported counts for other adverse events are 2 among 18 at risk in the itraconazole group and 2 among 16 at risk in the placebo group. These are descriptive counts, and the different listed denominators should not be assumed to represent the same analysis population as the primary endpoint.

Spontaneous Pneumothorax is listed among the leading serious-event terms, with a reported value of 5.6%. The record does not connect that term to a particular arm in the entry available for interpretation, so it should not be assigned to either group based on the summary alone. Death counts are not reported in the registry record.

Adverse-event counts do not, by themselves, establish that an event was caused by treatment or that the groups differ reliably. The registry record does not report event-level detail, severity grading beyond the serious-event classification, relatedness assessments, or a statistical comparison of safety outcomes. The counts should therefore be read as the posted safety summaries rather than as a causal assessment.

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

The posted results describe a small randomized comparison of itraconazole and placebo for a specific endpoint: respiratory exacerbation requiring intravenous antibiotics during the 24-week treatment period. The observed counts were 4 in the itraconazole group and 5 in the placebo group. The unadjusted p-value is 0.551, and the calculated confidence interval for the risk difference spans no difference and effects in either direction.

Statistically, these results do not establish a clear difference between the groups for this endpoint. At the same time, the imprecision means the data do not rule out a difference. A point estimate favoring one group is not enough to settle the question when the interval is broad and the event counts are sparse. The result is best understood as uncertain rather than as proof of equivalence.

The finding applies only to the recorded outcome definition and follow-up period. It does not directly answer questions about other respiratory outcomes, longer-term effects, subgroups, or outcomes that were not posted. The registry record does not provide secondary outcome results, detailed follow-up information, or an analysis population that would clarify how incomplete outcome data were addressed.

These statistics are not medical advice and do not determine the appropriate treatment for an individual. They describe the evidence recorded for this trial and its statistical uncertainty. The limits of the registry information, including the absence of a reported analysis plan and the unexplained difference between enrollment and endpoint group counts, should remain part of any interpretation.

16. Why This Trial Matters Statistically

This trial illustrates why event counts, effect estimates, uncertainty intervals, and analysis details need to be read together. The raw endpoint counts are close, but the comparison is based on small outcome groups and sparse events. A point estimate can suggest a direction while still being too imprecise to distinguish that direction from no difference or the opposite direction.

The registry gives an unadjusted p-value of 0.551. That number alone cannot convey the range of effects compatible with the data, the clinical importance of any effect, or whether the comparison followed a prespecified analysis plan. The confidence interval is therefore essential to interpreting the result; its span across zero makes clear that the estimate is uncertain.

The record also demonstrates the distinction between a completed trial and a complete statistical record. It reports enrollment and outcome group counts, but does not explain their discrepancy, identify the analysis population, describe missing-data handling, or give the original sample-size rationale. Those gaps are relevant to how securely the posted result can be interpreted.

Finally, planning calculations based on an observed effect can look much larger than a trial's outcome groups when the observed effect is uncertain and smaller effects are considered. Such calculations are useful for illustrating design sensitivity under explicit assumptions, but they are not a substitute for the trial's original design record. Keeping descriptive observations, inferential uncertainty, and prospective planning distinct is central to sound clinical-trial interpretation.

17. 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 primary comparison is based on sparse event counts in small outcome groups. The reported endpoint group sizes are 18 for itraconazole and 16 for placebo, while enrollment was 35. The reason for this discrepancy is not reported in the registry record. Without an explanation, the effect of any missing outcomes, exclusions, or analysis-population choices cannot be assessed.

The registry does not report the trial's original sample-size justification, statistical analysis plan, analysis population, missing-data methods, or any interim-analysis plan. It also does not detail randomization procedures or explain the masking classification, which is listed as quadruple even though the official title describes the trial as double-blind. These gaps prevent a full assessment of whether the posted comparison matches the planned analysis.

The endpoint is limited to respiratory exacerbations requiring intravenous antibiotics during the 24-week treatment period. No secondary outcomes are posted, and the record does not provide other clinical outcome results that might clarify the broader pattern of findings. The event-assessment procedures and handling of incomplete follow-up are not described.

The safety summaries use group denominators that do not fully align with the primary-outcome denominators. The record does not report a statistical safety comparison, event relatedness assessments, or death counts. The serious-event term summary also does not identify its treatment group. These limitations mean the safety figures should be interpreted descriptively.

The reported inferential comparison is unadjusted and the registry does not identify its interval-construction method. Consequently, the posted estimates do not answer questions about adjusted effects, robustness to alternative assumptions, or broader outcomes beyond the recorded endpoint.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Treatment of Aspergillus Fumigatus (a Fungal Infection) in Patients With Cystic Fibrosis — NCT00528190.
• Registry record last updated 2017-05-10; status last verified 2017-02.
• Results first posted 2017-03-23.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

NCT00528190 is a completed phase 4 randomized, parallel-group, placebo-controlled trial sponsored by Ottawa Hospital Research Institute. It studied itraconazole in patients with cystic fibrosis and Aspergillus fumigatus infection. Enrollment was 35; the registry lists a start date of 2007-10 and primary completion date of 2010-08.

Itraconazole was described as 5mg/kg/day for 24 weeks, with placebo as the comparator. The primary endpoint counted participants with a respiratory exacerbation requiring intravenous antibiotics during 24 weeks. The posted counts were 4 in the itraconazole group and 5 in the placebo group. The unadjusted p-value was 0.551, and the calculated confidence interval for the risk difference spans no difference.

The registry does not report secondary outcomes, a complete statistical analysis plan, an analysis population, or an explanation for the difference between enrollment and endpoint group counts. Those omissions limit interpretation of the posted comparison.