Sustained Aeration of Infant Lungs Trial: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Sustained Aeration of Infant Lungs Trial (NCT02139800), a randomized na study. The primary outcome is Combined Outcome of Death or Bronchopulmonary Dysplasia.

2. Clinical Question

3. Trial Design

The Sustained Aeration of Infant Lungs Trial is recorded as a randomized, parallel, two-arm study with no masking. Its brief description calls it a controlled, multicenter clinical trial. The two strategies were delivery-room Sustained Inflation with PEEP/CPAP and standard-of-care PEEP/CPAP. Both are described with PEEP/CPAP of 5-7 cm H2O.

The registry lists enrollment of 460. The brief description states that the study would determine outcomes in 600 infants; the registry record does not explain the difference between that stated target and the enrollment figure. The groups shown with primary outcome results have denominators of 211 for standard care and 215 for Sustained Inflation. These are the denominators attached to the posted outcome values, not a statement about the number enrolled.

The listed start date is 2014-08-27, and the primary completion date is 2018-02-15. The study status is completed. The phase is listed as NA. The registry record does not report the trial's original sample-size justification or the full protocol-level analysis plan. Although the brief description names 600 infants, it does not establish the assumptions behind that target.

The study description also identifies other outcomes, including oxygen profiles, delivery-room heart rate, intubation, and pneumothorax or new chest drains. The registry lists 21 posted secondary outcomes. Those measures provide context for the breadth of outcomes considered, but the primary comparison addressed is the combined death-or-bronchopulmonary-dysplasia endpoint at 36 weeks.

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 Combined Outcome of Death or Bronchopulmonary Dysplasia, measured over 36 weeks.

The primary endpoint counts participants who experienced either death or bronchopulmonary dysplasia by the stated 36-week time point. It is a combined, or composite, outcome: a participant is counted if either component occurs. The registry describes the endpoint as a count of participants and gives the population as infants born at 23-26 weeks gestational age who required respiratory support at birth.

The study description uses this combined endpoint to compare the two delivery-room strategies in terms of an outcome assessed at 36 weeks. In general, combining outcomes can capture more than one important event within a single primary measure. However, the components may differ in severity or frequency, and a combined estimate does not show which component accounts for the observed result. The registry record does not report separate primary results for death and bronchopulmonary dysplasia, nor does it give the diagnostic criteria used for bronchopulmonary dysplasia.

The posted outcome values are event counts within each group, alongside the group denominators. Interpreting the endpoint therefore requires keeping the combined nature of the measure in mind: the estimate pertains to having either event, not to death alone, bronchopulmonary dysplasia alone, or a measure of lung aeration itself.

7. Results Posted in the Registry

• Sustained Intervention: 63.7% (137/215) versus 59.2% (125/211) on control; risk difference 4.5 percentage points (95% CI -4.8 to 13.7), risk ratio 1.08 (0.93–1.25); unadjusted two-proportion z-test p = 0.342.

8. Statistical Interpretation

9. Statistical Methods Explained

The posted primary outcome is binary at the participant level: each participant is counted as having or not having the combined outcome of death or bronchopulmonary dysplasia. The registry reports event counts and denominators for each randomized group, and the comparison expresses the outcome on several scales. General explanations of those scales are given; they describe statistical concepts rather than additional trial findings.

What does a risk difference describe?

A risk difference subtracts the event proportion in one group from the event proportion in the other. In this comparison, the reported estimate is 0.045, with Sustained Inflation contrasted against standard care. A value of zero would correspond to equal proportions. A positive value means the observed proportion is higher in the Sustained Inflation group; a negative value would mean it is lower. The estimate is unadjusted, so it is a direct group comparison rather than an estimate corrected for other variables.

How do relative risk and odds ratio differ?

The relative risk compares the event proportions as a ratio. The reported relative risk is 1.076. A value of one represents equal risks, while a value above or below one indicates a higher or lower risk in the group used as the numerator. The odds ratio compares event odds rather than event proportions. The reported odds ratio is 1.208, and one is its null value as well. Odds and risks are different quantities; they should not be treated as interchangeable, particularly when an outcome is common. Both measures are unadjusted in the posted comparison.

What do the confidence intervals add?

A confidence interval conveys uncertainty around an estimate under the assumptions of the method used to construct it. In general, a wider interval indicates less precision, while an interval that includes the null value does not establish a clear direction of effect. The risk-difference interval is -0.048 to 0.137; the relative-risk interval is 0.925 to 1.251; and the odds-ratio interval is 0.818 to 1.786. The record does not report the specific method used to calculate these intervals, so the calculation method should not be inferred.

What does the p-value represent?

The unadjusted p-value is 0.342. In general, a p-value describes how compatible the observed data are with a specified null hypothesis under the statistical model; it is not the probability that the null hypothesis is true. It does not measure the size or clinical importance of an effect, and it does not replace the confidence interval. The registry record does not report the prespecified significance threshold for the trial's primary analysis, so the posted p-value is best read together with the effect estimate and its interval.

Why can over-dispersion matter?

Over-dispersion is a general concern when count data vary more than a model expects. If present and not accounted for, it can make uncertainty estimates too narrow. The primary endpoint is reported as participant counts for a binary outcome, rather than a repeated count outcome; over-dispersion is therefore not a feature established by these posted primary results. The registry record does not report a model-based adjustment for over-dispersion or a reason to apply one to this endpoint.

The record lists zero analysis entries, while also posting the primary outcome values and a comparison estimate. It does not identify whether these estimates reproduce the trial's prespecified analysis, nor does it report adjusted modeling details. The reported results should be distinguished from assumptions about analyses that are not documented in the registry record.

10. Confidence Intervals and Precision

Precision is the degree to which an estimate is constrained by its uncertainty interval. The primary risk difference is 0.045, and its 95% confidence interval extends from -0.048 to 0.137. Because the interval crosses zero, the posted data are compatible with a difference in either direction. The interval also covers a range of magnitudes, so the point estimate alone gives an incomplete account of the uncertainty.

The relative risk is 1.076, with a 95% confidence interval from 0.925 to 1.251. The odds ratio is 1.208, with a 95% confidence interval from 0.818 to 1.786. For these ratio measures, one is the value corresponding to no difference. Each interval includes that value. The measures use different scales, but their intervals likewise do not establish a clear separation between the groups.

In general, a confidence interval is a range generated by a statistical procedure that, under its assumptions, reflects uncertainty about an underlying effect. It is not a guarantee that the true effect lies within the particular interval, and it does not show the probability that a particular value is true. The registry record does not report the interval-construction method or the assumptions used for it. The posted intervals are therefore most useful as a direct description of the uncertainty attached to the estimates, without attributing an undocumented method.

The interval widths matter for interpretation: the point estimates should not be treated as exact effects. The posted data leave uncertainty about both direction and size for the primary comparison. The combined endpoint also limits precision about its individual components, since component-specific estimates are not reported in the registry record.

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 sample-size figures are planning illustrations based on the observed effect, not the trial's original design calculation. The assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. The registry record does not report the assumptions used for the trial's own original design or sample-size justification.

The listed rows consider planning for 100%, 75%, and 50% of the observed effect. For this binary outcome, the figures are participants per arm. The 80% power column gives the number of participants per arm under the stated assumptions for a design with an 80% chance of detecting the specified effect if that effect is present and the assumptions hold. The 90% power column gives the corresponding planning number for a design with a 90% chance under those assumptions. These are hypothetical design calculations, not descriptions of the enrolled groups.

The posted illustrations list 1,852 participants per arm for 80% power and 2,479 for 90% power when planning for 100% of the observed effect. For 75% of the observed effect, the figures are 3,311 and 4,432. For 50% of the observed effect, they are 7,487 and 10,023. The accompanying curve should be read as a visual representation of the same planning relationship, not as an additional trial result.

Smaller effects are harder to distinguish from random variation, so detecting them under the same assumptions requires more participants. These figures are planning illustrations and are not observed power.

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 = 0.592; treatment proportion p₁ = 0.637; average p̄ = 0.615.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6882 = 1.3489.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6875 = 0.5786.
4. n = (1.3489 + 0.5786)² / (0.0448)² = 1,851.7, rounded up to 1,852 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 <- 0.592417061611374                          # control proportion
p1 <- 0.637209302325581                          # 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(2139800)
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 = 1,852 (80% power), 2,479 (90% power)
 75% of observed effect: n per arm = 3,311 (80% power), 4,432 (90% power)
 50% of observed effect: n per arm = 7,487 (80% power), 10,023 (90% power)
power.prop.test: 1851.7 
Simulated power at n = 1,852 per arm: 0.792 (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

The trial description includes a primary endpoint and a range of secondary outcomes. The registry lists 21 posted secondary outcomes, including oxygen profiles, delivery-room heart rate, intubation, and pneumothorax or new chest drains. When many outcomes are assessed, the chance of obtaining at least one apparently unusual result can increase. In general, multiplicity procedures can address that issue, but the registry record does not report whether any adjustment was planned or used for secondary outcomes.

The registry lists zero analysis entries, although primary outcome counts and an unadjusted comparison are posted. It does not report a full statistical analysis plan, the prespecified handling of multiple comparisons, or whether any interim analyses were conducted. The record also does not state whether the posted comparison follows the originally planned primary analysis.

Missing-data handling is not reported in the registry record. The record does not describe whether any primary outcome status was unavailable, how missing outcomes were handled, or whether sensitivity analyses were performed. It also does not specify the analysis population, such as whether the primary comparison used all randomized participants or a different defined set. The denominators attached to the posted outcome counts do not by themselves establish the analysis-population rule.

Adjustment for baseline characteristics or other covariates is not reported for the primary comparison. The presented risk difference, relative risk, and odds ratio are unadjusted estimates. Without a documented analysis plan, it is not possible to determine from the registry record which adjustment, missing-data, or multiplicity choices were prespecified. These unknowns do not change the values posted, but they limit assessment of how the posted estimates relate to the trial's intended analysis.

14. 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 serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: grade 3 or 4 ivh (10.4%), pneumothorax (9.0%), death (7.4%), administration of epinephrine or chest compressions (3.8%), pulmonary interstitial emphysemia (pie) (3.3%).

The registry reports serious adverse event counts for the two groups. In standard care, 51 participants are listed as affected among 211 at risk; for Sustained Inflation, 45 are listed as affected among 215 at risk. Other adverse events are listed for 146 of 211 at risk in standard care and 157 of 215 at risk in Sustained Inflation. These are counts and denominators as recorded, not adjusted comparisons.

The registry also reports deaths of 35 in the standard-care group and 48 in the Sustained Inflation group. The record does not explain how these safety listings relate to the primary combined endpoint, and these counts should not be substituted for the primary outcome values.

Across the serious-event terms listed, the registry reports Grade 3 or 4 IVH at 10.4%, pneumothorax at 9.0%, death at 7.4%, administration of epinephrine or chest compressions at 3.8%, and Pulmonary Interstitial Emphysemia (PIE) at 3.3%. The record does not identify these percentages as arm-specific, so they should be read as reported rather than assigned to either group. Event definitions, attribution, overlap among events, and the method used to calculate these percentages are not reported in the registry record. These descriptive counts alone do not establish that an intervention caused an event.

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

The posted primary results describe the frequency of a combined outcome of death or bronchopulmonary dysplasia at 36 weeks in the two trial groups. The recorded event proportions are 0.592 for standard care and 0.637 for Sustained Inflation. The unadjusted risk difference is 0.045, and its confidence interval spans -0.048 to 0.137. The unadjusted p-value is 0.342. Together, these results leave substantial uncertainty about the direction and size of the difference represented by this comparison.

These findings do not establish that the strategies are equivalent. A comparison that does not show a clear statistical separation is not the same as evidence that their effects are identical; demonstrating equivalence would require an appropriate design and margin, neither of which is reported in the registry record. Nor do the estimates prove that one strategy is superior or inferior. They describe the posted group comparison, with the uncertainty captured by the confidence interval.

The outcome is composite, so the result cannot determine whether death, bronchopulmonary dysplasia, or both account for the observed values. Separate primary estimates for the components are not reported. The comparison also does not, on its own, answer questions about the secondary outcomes, the safety profile, or other populations and settings. The registry record does not report enough analysis detail to assess adjustment, missing-data handling, or the precise analysis population.

In general, statistical uncertainty and clinical importance are distinct. A point estimate, confidence interval, and p-value describe statistical features of the observed comparison; they do not by themselves define which differences would matter clinically. No threshold for a clinically important difference is reported in the registry record. The results should therefore be interpreted as an uncertain comparison for this trial's specified combined endpoint, not as a treatment recommendation or a conclusion about outcomes beyond those reported.

16. Why This Trial Matters Statistically

This trial poses a clear statistical comparison: two randomized delivery-room strategies and a participant-level primary outcome assessed at 36 weeks. Its parallel design and recorded allocation make the group contrast straightforward to describe, while the combined endpoint gives one primary measure for the study's stated question.

The example also shows why an estimate should be read with its uncertainty. The risk difference is 0.045, but its confidence interval includes values on both sides of zero. The relative risk and odds ratio intervals likewise include their null values. The point estimates alone would not convey the uncertainty in direction and size. Looking at the count data, the absolute-scale estimate, the ratio measures, the p-value, and the intervals together gives a more balanced account of the posted result.

The composite outcome raises an additional interpretive issue. Combining death and bronchopulmonary dysplasia can summarize either event, but the combined estimate does not show how each component contributes. Component-specific results would be needed to answer that separate question; they are not reported in the registry record.

The planning illustrations also demonstrate a general relationship between effect size and sample size: smaller effects require more participants under fixed assumptions. These illustrations are distinct from evidence about what the trial observed, and they do not recover the trial's original design calculation. The registry record lists an enrollment of 460 while the brief description refers to 600 infants, without explaining the difference. Taken together, the record illustrates why statistical interpretation depends not only on a point estimate, but also on design, uncertainty, endpoint definition, planning assumptions, and transparent reporting.

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 registry record leaves several trial-specific questions unanswered. Its brief description refers to 600 infants, while recorded enrollment is 460; no explanation for that difference is reported. The outcome denominators are 211 for standard care and 215 for Sustained Inflation, but the record does not state how the primary analysis population was defined or why those denominators apply.

The trial is recorded as unmasked. The registry record does not describe whether outcome assessors were masked or how the potential influence of unmasked treatment assignment was addressed. It also does not report the diagnostic criteria for bronchopulmonary dysplasia, the adjudication process for the combined endpoint, or separate primary results for death and bronchopulmonary dysplasia.

Analysis details are limited. The record does not report the original sample-size justification, prespecified significance threshold for the primary analysis, method for calculating confidence intervals, handling of missing data, covariate adjustment, or any interim analysis plan. It lists zero analysis entries despite posting a primary comparison. The available comparison is unadjusted, and the registry record does not establish whether it matches the trial's original analysis plan.

Safety reporting is also descriptive: the event definitions, attribution, overlap, and denominators for the listed serious-event percentages are not specified. These limitations do not invalidate the posted values, but they restrict how fully the analysis and safety summaries can be assessed from the registry record alone.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Sustained Aeration of Infant Lungs Trial — NCT02139800.
• Registry record last updated 2023-04-06; status last verified 2023-04.
• Results first posted 2020-06-25.
• 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

The Sustained Aeration of Infant Lungs Trial is recorded as a completed, randomized, parallel, unmasked study. It compared delivery-room Sustained Inflation with standard-of-care PEEP/CPAP in preterm infants requiring respiratory support at birth. The registry lists enrollment of 460 and gives 2014-08-27 as the start date and 2018-02-15 as the primary completion date.

The primary outcome was the combined count of participants with death or bronchopulmonary dysplasia at 36 weeks. The posted event proportions are 0.592 for standard care and 0.637 for Sustained Inflation. The unadjusted risk difference is 0.045, with a confidence interval from -0.048 to 0.137 and a p-value of 0.342. The posted estimates leave uncertainty about the direction and size of the comparison.

The registry record does not report the trial's original sample-size assumptions, full analysis plan, missing-data approach, or separate primary results for the endpoint components.