Evaluation of a Vaccine for Reducing Ear and Lung Infections in Children: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of a Vaccine for Reducing Ear and Lung Infections in Children (NCT01545375), a randomized phase 2 study. The primary outcome is Time to Occurrence of Any Acute Otitis Media (AOM) Diagnosed and Verified Against American Academic of Pediatrics (AAP) Criteria.

2. Clinical Question

3. Trial Design

This was a randomized, quadruple-masked, parallel-group Phase 2 study. Its registry title describes evaluation of a vaccine for reducing ear and lung infections in children, and its official title identifies protective efficacy against otitis media and assessment of safety for investigational pneumococcal vaccine 2189242A in healthy infants. The registry lists GlaxoSmithKline as the sponsor and the study status as completed.

The study enrolled 1806 participants. The arm descriptions identify healthy Native American infants aged between and including 6 and 12 weeks at the time of first vaccination. The dPly-PhtD group received GSK2189242A with Prevenar13; the control group received placebo with Prevenar13. Both descriptions give 3 primary doses at 2, 4, and 6 months of age and a booster at 12-15 months. PedvaxHIB is mentioned in both descriptions, but its detailed use is not fully reported in the registry record.

The primary endpoint analysis used 808 participants in the dPly-PhtD group and 831 in the control group. Those counts differ from total enrollment because the primary analysis was conducted in a modified according-to-protocol efficacy cohort, described as evaluable subjects with efficacy outcome data. The complete criteria for membership in that cohort are not reported in the registry record.

The primary observation window began 2 weeks after administration of dose 3 and continued up to Month 22. Study start and primary completion dates were 2012-05-21 and 2016-07-26. Further details about randomization procedures, who was masked, and the original sample-size justification 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: Out of the 1806 subjects enrolled in this study, 1803 were vaccinated and therefore included in the Total Vaccinated Cohort. 3 subjects were excluded for the following reasons: one subject had an invalid Inform Consent form and 2 subjects received subject number but did not receive any vaccine dose.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Analysis was performed on the modified according to protocol cohort for efficacy which included all evaluable subjects for whom data concerning efficacy outcome measures were available (efficacy cohort) and for whom non-compliance with the vaccination intervals during primary vaccination was the only elimination criterion from the efficacy cohort.

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 Time to Occurrence of Any Acute Otitis Media (AOM) Diagnosed and Verified Against American Academic of Pediatrics (AAP) Criteria, measured over Any time from 2 weeks after the administration of dose 3 up to Month 22.

The primary endpoint is the rate of episodes of acute otitis media diagnosed and verified against American Academy of Pediatrics criteria. It covers any time from 2 weeks after dose 3 up to Month 22. The registry expresses the result as episodes per person-year: the number of episodes divided by the sum of participants’ follow-up time in years. This rate representation accounts for differences in observed follow-up time rather than treating every participant as if observed for an identical duration.

For an episode to meet the stated clinical criteria, a treating physician or equivalent licensed medical professional had to judge that there was acute onset of signs and symptoms of middle-ear inflammation and middle-ear effusion. Effusion had to be indicated by a bulging tympanic membrane, limited or absent mobility, an air-fluid level, or otorrhea. In addition, signs of inflammation had to include distinct tympanic-membrane erythema or distinct ear pain that interfered with or precluded normal activity or sleep.

A defined clinical endpoint can make comparisons more consistent than relying on an unrestricted diagnosis alone. The registry also lists healthcare-provider-diagnosed AOM as a secondary outcome, which is a broader endpoint. The primary rate is useful for describing event frequency over follow-up, but its interpretation depends on the diagnostic criteria, follow-up window, and analysis population used.

7. Results Posted in the Registry

• dPly-PhtD Group: 0.42 versus 0.44 (Episodes per person-year) on control; rate ratio 0.96 (95% CI 0.45–2.04, approximate, Poisson model); p ≈ 0.919.

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 to Occurrence of Any Episodes of AOM Diagnosed by Healthcare-provider

• Endpoint type: Event rate: events per unit of follow-up, compared as a rate ratio.
• Test: Poisson rate ratio, based on the estimated number of events and follow-up time.
• Result:
  • dPly-PhtD Group: 0.68 versus 0.70 (Episodes per person-year) on control; rate ratio 0.97 (95% CI 0.53–1.76, approximate, Poisson model); p ≈ 0.920.
• Interpretation:
  • The 95% confidence interval includes no difference (a ratio of 1), so these data do not show a statistically significant difference between dPly-PhtD Group and the control. The interval gives the range of effects that remain compatible with the data.

Time to Occurrence of Any Clinical Acute Otitis Media (AOM) Diagnosed and Verified Against Modified American Academic of Pediatrics (AAP) Criteria

• Endpoint type: Event rate: events per unit of follow-up, compared as a rate ratio.
• Test: Poisson rate ratio, based on the estimated number of events and follow-up time.
• Result:
  • dPly-PhtD Group: 0.57 versus 0.60 (Episodes per person-year) on control; rate ratio 0.95 (95% CI 0.50–1.81, approximate, Poisson model); p ≈ 0.868.
• Interpretation:
  • The 95% confidence interval includes no difference (a ratio of 1), so these data do not show a statistically significant difference between dPly-PhtD Group and the control. The interval gives the range of effects that remain compatible with the data.

Number of Subjects With Any Recurrent Healthcare Provider Diagnosed Acute Otitis Media (AOM)

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • dPly-PhtD Group: 3.3% (30/900) versus 3.5% (32/903) on control; risk difference -0.2 percentage points (95% CI -1.9 to 1.5), risk ratio 0.94 (0.58–1.53); unadjusted two-proportion z-test p = 0.806.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between dPly-PhtD Group and the control. The interval gives the range of effects that remain compatible with the data.

The listed secondary outcomes cover broader healthcare-provider-diagnosed AOM, clinical AOM under modified criteria, recurrent AOM, draining AOM, pneumococcal AOM, AOM with temporally related carriage, and medically attended acute lower respiratory tract infection. The posted secondary results available for interpretation include two event-rate comparisons and a recurrent-participant comparison. Across those results, point estimates are near their respective null values and intervals include the null. The general pattern does not provide a sharply different picture from the primary result: estimates are uncertain, rather than a consistent, precisely measured separation between groups.

Secondary endpoints add context because they examine related but distinct outcomes. Broader diagnosis criteria may capture a different set of episodes than the primary AAP-verified definition, and recurrent-event or participant-count outcomes answer different questions from an episode rate. Similarity among estimates can be reassuring about broad consistency, but it does not make the endpoints equivalent or remove the uncertainty in each estimate.

The registry lists 24 secondary outcomes, but the complete results for each are not reported in the registry record. No multiplicity adjustment is reported. General statistical explanation: when many outcomes are tested, the chance of at least one apparently notable result can increase, even if no true effects exist. Unadjusted secondary p-values therefore carry less weight than a prespecified primary analysis, especially when the analysis hierarchy and multiplicity plan are not reported. Secondary outcomes are best treated as supportive or exploratory rather than as independent confirmation of an effect.

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

• Time to Occurrence of Any Episodes of AOM Diagnosed by Healthcare-provider
• Time to Occurrence of Any Clinical Acute Otitis Media (AOM) Diagnosed and Verified Against Modified American Academic of Pediatrics (AAP) Criteria
• Number of Subjects With Any Recurrent Healthcare Provider Diagnosed Acute Otitis Media (AOM)
• Time to Occurrence of Any Draining Acute Otitis Media (AOM)
• Time to Occurrence of Any Draining Pneumococcal Acute Otitis Media (AOM)
• Number of Subjects With Any Acute Otitis Media (AOM) With Temporally Related Carriage
• Time to Occurrence of Medically Attended Acute Lower Respiratory Tract Infection (ALRI)
• Time to Occurrence of Medically Attended ALRI With Fever Documented at the Visit or History of Fever Within 3 Days Preceding a Given Episode

9. Statistical Interpretation

10. Statistical Methods Explained

General statistical explanation: an event rate uses both the number of events and the time participants were observed. For this endpoint, the unit is episodes per person-year. If participants contribute different amounts of follow-up, rates can express event frequency relative to accumulated observation time. The primary analysis reports group rates, then compares them with a rate ratio. A rate ratio of 1 corresponds to equal rates; a value below 1 indicates a lower estimated rate in the numerator group, while a value above 1 indicates a higher estimated rate. This describes the direction of the estimate and does not establish a cause or clinical importance.

The posted primary rates are 0.425 and 0.442 episodes per person-year. The unadjusted recalculation gives a rate ratio of 0.962. It is based on posted summary statistics rather than the sponsor’s reported regression analysis. The recalculation’s interval is 0.454 to 2.039 and its unadjusted p-value is 0.919. The interval includes the null rate ratio of 1. That is consistent with considerable uncertainty about the relative rates. General statistical explanation: an interval estimate represents uncertainty under the method and assumptions used; it is not a guarantee that the true effect lies within the interval.

The comparison is described as a Poisson rate comparison. General statistical explanation: Poisson models are commonly used for event counts, often with follow-up time taken into account. A basic Poisson model assumes a relationship between the event count’s mean and variance. If real data are more variable than that model assumes, an interval or test that fails to account for over-dispersion may be too optimistic. Dispersion information and further diagnostics are not reported in the registry record, so the extent to which over-dispersion was assessed cannot be determined.

The registry’s own primary analysis is reported as regression using a Cox method, with vaccine efficacy as the effect measure. It gives a value of 3.81, a 95% confidence interval from -11.35 to 16.90, and p = 0.302. A Cox regression analysis typically relates event timing to group while accounting for observed follow-up, subject to its modeling assumptions. The registry record does not report enough detail to characterize covariate adjustment, the handling of tied event times, or other implementation choices. Its reported vaccine-efficacy result and the recalculated rate ratio use different effect measures and analytical approaches.

General statistical explanation: a confidence interval communicates statistical precision, while a p-value summarizes evidence against a particular null model under specified assumptions. Neither quantity directly measures clinical importance. A p-value is not the probability that the null hypothesis is true, nor the probability that a result occurred by chance. Interpretation should consider the point estimate, interval width, endpoint definition, analysis population, and study design together.

What does randomization contribute?

Random allocation is intended to make the groups comparable on average at the start of a trial, including for characteristics that may not be measured. It supports a causal comparison when the analysis preserves the randomized comparison and follow-up and outcome handling are appropriate. The registry identifies allocation as randomized but does not report the sequence-generation or allocation-concealment procedures. The primary result is based on a modified according-to-protocol efficacy cohort, not a description of all enrolled participants. The extent to which exclusions after randomization affected comparability cannot be assessed from the information reported.

What does masking contribute?

The study is labeled quadruple-masked. Masking can reduce the influence of treatment knowledge on participant reports, clinical assessment, and study conduct. The registry does not identify which groups of people were masked or describe the procedures used to maintain masking. The AOM definition includes a clinician’s judgment, making the stated masking relevant to the possibility of assessment differences, but the registry does not report a masking assessment.

What is not specified?

The original statistical plan, sample-size justification, interim analyses, prespecified model details, and multiplicity strategy are not reported in the registry record. The trial’s own planning assumptions should therefore not be inferred from calculations based on the observed effect. The posted primary result can be described using its reported analysis and the unadjusted recalculation, but details absent from the record limit a fuller audit of the statistical plan.

11. Confidence Intervals and Precision

The unadjusted rate-ratio estimate is 0.962, with an interval from 0.454 to 2.039. The null value for a rate ratio is 1, and the interval includes that value. It also extends to values indicating lower and higher rates in the dPly-PhtD group. Thus, the estimate alone should not be read as a precise account of the comparative rate.

General statistical explanation: a confidence interval is a range generated by a statistical procedure to express uncertainty about an effect estimate. A narrower interval indicates greater precision under the method’s assumptions; a wider interval indicates less precision. An interval that includes the null does not prove equality, and an interval that excludes the null would not by itself establish clinical importance. The width and endpoints matter, not only whether the interval crosses a threshold.

The registry’s Cox analysis reports vaccine efficacy of 3.81 and a 95% confidence interval from -11.35 to 16.90. This interval spans zero, which is the no-effect value for an efficacy measure. It is a different analysis and scale from the recalculated rate ratio, so its limits should not be directly compared numerically with the rate-ratio interval. Both reported analyses leave substantial uncertainty about the effect’s direction and magnitude.

The confidence level for the recalculated interval is not reported in the registry record. The sponsor’s interval is explicitly labeled 95%. Neither interval resolves uncertainty about generalizability beyond the efficacy cohort or about outcomes outside the stated endpoint and follow-up window.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning estimates are illustrations based on the observed effect, not the trial’s original design justification. For time-to-event outcomes, the figures represent total events; for other outcomes, they represent participants per arm. The primary endpoint is expressed as time to occurrence, so its planning figures are total events. The recurrent-AOM binary outcome uses participants per arm.

The stated planning 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 as the stated fraction of the observed effect. The original sample-size assumptions and justification are not reported in the registry record.

The 80% power column describes the planned number of events or participants needed under those assumptions to have an 80% chance of detecting the assumed effect if that effect were the true one. The 90% power column gives the corresponding planning quantity for a 90% chance. Greater planned power generally requires more information, through more participants, more events, or both, depending on the outcome and calculation.

The rows use different fractions of the observed effect. Planning for 75% of the observed effect requires more information than planning for 100% of the observed effect, and planning for 50% requires more again. Smaller effects are harder to distinguish from random variation, so they require more participants or events under otherwise unchanged assumptions. These figures are not observed power; they are prospective planning illustrations based on stated assumptions, not a measure of what the completed trial achieved.

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, λ₀ and λ₁ are event rates per patient-year, and T is follow-up per participant in years. This assumes Poisson counts and equal follow-up.

Worked calculation for this trial

1. Control rate λ₀ = 0.4420; treatment rate λ₁ = 0.4250 events per patient-year; follow-up T = 0.04 years.
2. n = (1.96 + 0.842)² × (1/0.4420 + 1/0.4250) / (0.04 × [ln(0.962)]²) = 614,410.6, rounded up to 614,411 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
lambda0 <- 0.442                      # control rate, events per patient-year
lambda1 <- 0.425                      # treatment rate
tt      <- 0.0383288616328095                       # follow-up per participant, years
n_per_arm <- function(power, frac = 1) {
  l1 <- lambda0 * (lambda1 / lambda0)^frac   # smaller effect = fraction of the observed log rate ratio
  ceiling(round((z_a + qnorm(power))^2 * (1 / lambda0 + 1 / l1) / (tt * log(l1 / lambda0)^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 = ",")))

# Simulation 1: Poisson counts. Simulation 2: over-dispersed counts (variance = 1.5 x mean), analysed with the matching variance.
set.seed(1545375)
n    <- n_per_arm(0.80)
reps <- 20000
m0 <- lambda0 * n * tt; m1 <- lambda1 * n * tt
x0 <- rpois(reps, m0); x1 <- rpois(reps, m1)
z  <- log(x1 / x0) / sqrt(1 / x0 + 1 / x1)
cat(sprintf("Simulated power, Poisson counts, n = %s per arm: %.3f\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE)))
phi <- 1.5
y0 <- rnbinom(reps, mu = m0, size = m0 / (phi - 1)); y1 <- rnbinom(reps, mu = m1, size = m1 / (phi - 1))
z2 <- log(y1 / y0) / sqrt(phi * (1 / y0 + 1 / y1))
cat(sprintf("Simulated power, over-dispersed counts (phi = 1.5), same n: %.3f\n", mean(abs(z2) > z_a, na.rm = TRUE)))

Output from running the code

100% of observed effect: n per arm = 614,411 (80% power), 822,522 (90% power)
 75% of observed effect: n per arm = 1,086,853 (80% power), 1,454,987 (90% power)
 50% of observed effect: n per arm = 2,433,312 (80% power), 3,257,514 (90% power)
Simulated power, Poisson counts, n = 614,411 per arm: 0.801
Simulated power, over-dispersed counts (phi = 1.5), same n: 0.629

The first simulation draws Poisson counts and should land close to the target power. The second allows extra variability (variance 1.5 times the mean, a purely illustrative value), which lowers the power at the same sample size, so rate trials usually need more participants than the Poisson formula suggests.

14. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary analysis as a Cox regression with vaccine efficacy of 3.81, a 95% confidence interval from -11.35 to 16.90, and p = 0.302. The unadjusted recalculation from posted summary statistics instead reports a rate ratio of 0.962, an interval from 0.454 to 2.039, and p = 0.919. One result is on the vaccine-efficacy scale and the other is on the rate-ratio scale; the analyses are not interchangeable.

The registry record does not give sufficient detail to reconstruct every aspect of the Cox analysis, such as the complete model specification or any adjustment variables. The recalculation is a simple unadjusted comparison and does not replace the sponsor’s analysis. The record indicates no discrepancy flag, so there is no stated discrepancy requiring one analysis to take precedence over the other. Both results should be interpreted according to their stated estimand and method, with their intervals and limitations considered.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies a primary endpoint and lists multiple secondary outcomes, but a multiplicity strategy is not reported in the registry record. It is therefore unclear whether the sponsor prespecified an order for testing, adjusted significance thresholds across outcomes, or treated secondary analyses as exploratory. General statistical explanation: testing many outcomes increases the chance of finding at least one apparently unusual result under null effects. This is why unadjusted secondary results should be interpreted cautiously and in the context of a prespecified analysis plan.

The primary efficacy analysis population is described as a modified according-to-protocol cohort containing evaluable subjects with available efficacy outcome data. Further details about exclusions, protocol deviations, and the complete cohort definition are not reported in the registry record. The primary endpoint counts follow-up from 2 weeks after dose 3 up to Month 22, but the handling of missed visits, incomplete follow-up, withdrawals, and censoring is not reported. The record also does not explain how missing endpoint data were handled or whether sensitivity analyses assessed the effect of missingness.

The registry reports total enrollment of 1806, while the primary efficacy comparison includes 808 participants in the dPly-PhtD group and 831 in the control group. The posted efficacy population is not the same as a simple description of all enrolled participants. Without full accounting of participant flow and reasons for exclusion, it is not possible to assess from this record how selection into the analysis cohort may have influenced the comparison.

Interim analyses, stopping rules, the original statistical analysis plan, and the trial’s own sample-size justification are not reported in the registry record. Their absence does not establish that such procedures were or were not used; it means their role cannot be evaluated from the registry 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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: bronchiolitis (8.4%), pneumonia (8.2%), respiratory syncytial virus bronchiolitis (7.4%), croup infectious (1.9%), influenza (1.8%).

The registry reports serious adverse events for 900 participants at risk in the dPly/PhtD group, with 229 affected, and 903 participants at risk in the control group, with 232 affected. It reports other adverse events for 200 participants at risk in each group, with 191 and 189 affected, respectively. Deaths are reported as 0 in both groups. These counts describe the posted safety information; they do not establish that an event was caused by vaccination.

The listed serious-event terms include bronchiolitis at 8.4%, pneumonia at 8.2%, respiratory syncytial virus bronchiolitis at 7.4%, croup infectious at 1.9%, influenza at 1.8%, and febrile convulsion at 1.6%. The registry record does not clarify the denominator or whether these term percentages are arm-specific in the information, so they should not be interpreted as comparative risks between groups.

Safety interpretation depends on event definitions, follow-up, exposure, and attribution procedures. Further details about seriousness criteria, event timing, relatedness assessments, and statistical comparisons are not reported in the registry record. The figures are descriptive and should not be read as a complete safety profile.

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

The primary result describes AOM episode rates in the modified according-to-protocol efficacy cohort during the period from 2 weeks after dose 3 up to Month 22. The observed rates were 0.425 and 0.442 episodes per person-year. The unadjusted rate-ratio estimate is close to the null value, but its interval ranges from 0.454 to 2.039. The estimate is therefore not precise enough to identify a narrow range of plausible relative rates.

The sponsor’s Cox analysis reports vaccine efficacy of 3.81, with a 95% confidence interval from -11.35 to 16.90. It uses a different effect measure from the rate-ratio recalculation, and its interval includes zero. The results do not establish a clear difference between groups, but they also do not establish that the groups have identical outcomes. Non-small p-values are not proof of no effect.

These results do not answer every question about ear or lung infections. The primary endpoint is specifically AOM diagnosed and verified using the stated criteria. The registry also lists lower respiratory tract infection outcomes and other secondary endpoints, but the primary result should not be generalized to those outcomes. Nor should it be generalized beyond the described population, analysis cohort, and follow-up period without additional evidence.

General statistical explanation: absence of a statistically clear difference is distinct from evidence of equivalence. Demonstrating equivalence or non-inferiority requires a prespecified margin and an analysis designed for that purpose; such details are not reported in the registry record. The posted result is best understood as an uncertain estimate from a defined trial comparison, not as a universal conclusion about the vaccine or about individual care.

18. Why This Trial Matters Statistically

This study illustrates why endpoint definitions matter in clinical trials. AOM diagnosed by a healthcare provider is not necessarily the same outcome as AOM meeting specific American Academy of Pediatrics criteria. The primary endpoint required clinical evidence of acute middle-ear inflammation and effusion, while secondary outcomes included broader and otherwise distinct definitions. A statistical comparison is only as interpretable as the outcome it counts.

It also illustrates the difference between an event rate and a participant count. The primary outcome is episodes per person-year, which incorporates follow-up time and can include repeated episodes. A recurrent-event count or the number of participants with an outcome answers a different question. Readers should match each estimate to its endpoint and unit rather than comparing numerical values across unlike outcomes.

The result also shows why an estimate and its precision need to be considered together. A rate ratio near 1 may look close to the null, but the broad interval indicates substantial uncertainty. Conversely, a p-value alone cannot convey the size or range of effects compatible with the data. The sponsor’s Cox analysis and the summary-statistic recalculation add another useful distinction: analyses can use different effect measures and methods, and their estimates should be interpreted on their own scales.

Finally, the trial record highlights the importance of transparent reporting. Details about the original sample-size rationale, missing-data handling, multiplicity, and full analysis-population criteria are not reported. Without these, readers can describe the posted findings while recognizing that some aspects of design and analysis cannot be independently assessed.

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.
• Rate comparisons use a Poisson approximation unless the sponsor posted confidence limits; real event counts are often over-dispersed.

The main limitation for interpretation is the breadth of the interval around the unadjusted primary rate ratio. It spans values below and above the null, leaving uncertainty about both direction and magnitude. The sponsor’s reported efficacy interval also spans its null value. These are imprecise estimates rather than narrow bounds on the effect.

The primary comparison uses a modified according-to-protocol efficacy cohort rather than all enrolled participants. The complete cohort criteria, participant-flow details, and reasons for exclusion are not reported in the registry record. The registry also does not report how missing outcome data, withdrawals, or incomplete follow-up were handled. These omissions limit assessment of possible selection and missing-data effects.

The outcome relies on clinical diagnosis against stated criteria and a physician’s judgment. This definition improves specificity but may not capture every episode that would be identified under broader healthcare-provider diagnosis. Although the study is labeled quadruple-masked, which people were masked and how masking was maintained are not reported in the registry record.

Additional limitations include the absence of reported details on model specification, over-dispersion assessment, multiplicity, interim analyses, and the original sample-size justification. The registry lists many secondary outcomes, but the full set of secondary results is not available in the information reported. Generalizability is also bounded by the described population of healthy Native American infants in and around the named reservations; application to other populations is not established by this record.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Evaluation of a Vaccine for Reducing Ear and Lung Infections in Children — NCT01545375.
• Registry record last updated 2019-12-27; status last verified 2019-12.
• Results first posted 2017-09-12.
• 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

NCT01545375 is a completed, randomized, quadruple-masked, parallel-group Phase 2 study sponsored by GlaxoSmithKline, with enrollment of 1806. It compared GSK2189242A with placebo, with both groups described as receiving Prevenar13. The primary outcome was the rate of AOM episodes diagnosed and verified against American Academy of Pediatrics criteria, from 2 weeks after dose 3 up to Month 22.

The efficacy analysis included 808 participants in the dPly-PhtD group and 831 in the control group. The unadjusted rate-ratio recalculation was 0.962, with an interval from 0.454 to 2.039 and p = 0.919. The registry’s Cox analysis reported vaccine efficacy of 3.81, with a 95% confidence interval from -11.35 to 16.90 and p = 0.302. The intervals indicate substantial uncertainty. Details about the original sample-size justification, missing-data handling, and multiplicity are not reported in the registry record.