Surveillance for Adverse Events Following Pandemic H1N1 Immunization: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Surveillance for Adverse Events Following Pandemic H1N1 Immunization (NCT01289418), a registered phase not stated study. The primary outcome is Number of Participants Who Had Experienced a New Health Problem or the Worsening of an Existing Health Condition That Resulted in a Medical Consultation..

2. Clinical Question

3. Trial Design

The registry record identifies the study as completed and gives a registry enrollment of 6525. It lists Novel Influenza A/H1N1 as the condition and PHAC/CIHR Influenza Research Network as the sponsor. The recorded study dates are 2009-10 for the start and 2010-05 for primary completion. The title describes short- and long-term electronic surveillance of healthcare workers after administration of an adjuvanted pandemic H1N1 vaccine.

The named groups are healthcare workers from CHUQ hospitals, Mount Sinai Hospital, and Queen Elizabeth Hospital. The adverse-event information in the record is for healthcare workers from CHUQ hospitals. These labels identify settings; they do not show that participants were randomly assigned, that each location used the same procedures, or that the groups can be treated as comparable controls. Allocation is not stated, and the record cautions against a like-for-like control comparison.

The record lists three outcome measures, but only the primary outcome is described in the registry record for this explanation. It concerns a new or worsening health problem that led to medical consultation, assessed at day 8, 15 and 29. Further outcome definitions, the surveillance schedule beyond those assessment points, and the approach to collecting responses are not reported in the registry record.

The registry status of completed describes the study's recorded status, not the completeness of its results. Although the record gives an enrollment figure, it does not report how many participants contributed data to each outcome, whether all sites contributed to each analysis, or how many participants completed follow-up. No analysis results are 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.

Day 8 Survey

Reasons for not completing this period:

Day 29 Survey

Reasons for not completing this period:

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 Number of Participants Who Had Experienced a New Health Problem or the Worsening of an Existing Health Condition That Resulted in a Medical Consultation., measured over at day 8, 15 and 29.

The primary endpoint counts participants who experienced a new health problem or worsening of an existing health condition that resulted in a medical consultation. The listed assessment times are day 8, 15 and 29. The endpoint therefore focuses on health problems that reached the threshold of a medical consultation, rather than every symptom or change in health that might have occurred after vaccination. The registry record does not give further criteria for deciding what qualified as a new problem, worsening condition, or consultation.

As a general statistical consideration, a consultation-based outcome can identify events that led participants to seek medical care. It may be useful when surveillance aims to detect health problems with a degree of clinical salience. At the same time, whether someone seeks consultation can depend on access, personal decisions, and care-seeking practices, as well as on the underlying health problem. Those considerations are general; the registry record does not describe how they were addressed in this study.

The endpoint is expressed as a count of participants with an event, according to the record's outcome type. That count needs an interpretable denominator and clear information about follow-up and missing responses to support comparison. The available record does not report the primary endpoint count, its denominator, an effect estimate, or uncertainty around an estimate. It therefore does not permit a conclusion about the frequency of this outcome in the study population.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry classifies the primary outcome as a count of participants with an event. In this case, the event is a new health problem or worsening of an existing condition that resulted in medical consultation. The outcome is recorded at day 8, 15 and 29. These details define the general form and timing of the outcome, but they do not specify the statistical analysis used to estimate or compare it. An analysis plan is not reported in the registry record.

What does a count describe?

A count records how many participants meet an outcome definition. To interpret it, readers also need a denominator: the number of participants who could have had the event and whose outcome information was available. A count alone does not describe how common an event was in the population under observation. For the serious and other adverse-event categories, the registry gives both a count and an at-risk denominator for the CHUQ group. It does not give the primary endpoint count and denominator.

Counts and proportions are not interchangeable. A proportion uses a count relative to a defined denominator; calculating one requires a clear and appropriate denominator. No new proportion is calculated in this explanation. The reported adverse-event counts should be kept attached to their respective at-risk figures, and the denominators should not be assumed to cover all participants enrolled in the study.

How should uncertainty be considered?

As a general statistical concept, a confidence interval describes a range of values compatible with the data and a specified method, reflecting sampling uncertainty. It helps readers distinguish a relatively precise estimate from one that remains uncertain. A confidence interval does not correct bias from non-comparable groups, incomplete follow-up, or outcome misclassification. The registry record does not report confidence intervals for the primary endpoint or the adverse-event counts.

As a general concept, a p-value measures how compatible observed data are with a specified statistical model under a null hypothesis. It is not a measure of the size or clinical importance of an effect, and it does not establish causality. A p-value also depends on the analysis and assumptions used. No p-value or inferential analysis result is reported in the registry record, so statistical significance cannot be assessed from the record.

What does the planning illustration represent?

The sample-size assumptions describe a planning illustration based on the observed effect, not the study's own design. They specify a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is described as a stated fraction of the observed effect. For non-time-to-event outcomes, the illustration is expressed as participants per arm for 80% or 90% power; time-to-event illustrations use a total number of events.

These assumptions describe how planning estimates are framed, not evidence that the study was designed or conducted that way. The record does not report the study's original sample-size justification or its statistical plan. The planning estimates are not observed power, and should not be interpreted as a measure of how likely the completed study was to detect an effect. The registry entries available for this explanation do not give the observed effect or numerical planning estimates, so neither can be interpreted.

Why does the comparison structure matter?

Randomization, if used and properly implemented, can help make groups comparable with respect to measured and unmeasured characteristics. The registry record states that allocation was not stated and cautions that the arms are not a like-for-like control comparison. Thus, any apparent difference between groups could reflect differences in location, participant characteristics, follow-up, or other factors rather than an effect of vaccination. The record does not describe an adjusted analysis that might address measured differences, and no analysis results are reported.

More generally, over-dispersion occurs when variability in count data exceeds what a chosen statistical model expects. If present, it can make standard errors too small and uncertainty appear narrower than it is. This is a general consideration, not a reported feature of these data: the registry record does not report a dispersion estimate or a count-model analysis. The listed primary endpoint is a count of participants with an event, and the record does not specify a model for it.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("Health Care Workers")
n      <- c(6242)
events <- c(234)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Health Care Workers  6242  234  3.7  3.3  4.3  3.3  4.2  3.3  4.2

11. Multiplicity, Missing Data and Analysis Populations

The registry record lists three outcome measures, but the available information describes only the primary endpoint. It does not report the other outcome definitions, which outcomes were tested, or whether any results were adjusted for multiple comparisons. When many outcomes or repeated comparisons are examined, the chance of a seemingly notable result arising by chance can increase. As a general statistical practice, a prespecified outcome hierarchy or multiplicity adjustment can help clarify interpretation. Whether either approach was used is not reported in the registry record.

The primary endpoint is assessed at day 8, 15 and 29. Those assessment times do not, by themselves, reveal whether the analyses treated them as separate outcomes, repeated observations, or a combined measure. The analysis approach for these time points is not reported in the registry record. No analysis results are reported, so it is not possible to tell whether outcomes were selected or interpreted according to a prespecified plan.

Missing-data handling is also not reported. The record does not state how absent electronic responses, incomplete follow-up, or missing outcome information were treated. It does not describe imputation, exclusions, sensitivity analyses, or the number of participants with observed data at each assessment. These omissions matter because the observed participants may not represent everyone enrolled if follow-up is incomplete or differs across groups.

The analysis populations are not reported in the registry record. It is not stated whether analyses included all enrolled participants, only vaccine recipients, or participants with available follow-up. Although the record lists enrollment and at-risk denominators for the CHUQ adverse-event categories, it does not explain the relation between those figures or report participant flow. These limits make it difficult to assess missingness, selection, or how broadly the reported safety counts apply.

12. 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 1% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: gastroenteritis (0.1%), abdominal problems (0.1%), gynecologic problems/obstetrical (0.1%), gynecologic problems (0.1%), respiratory infection (0.1%).

For healthcare workers from CHUQ hospitals, the registry reports 35 participants with a serious adverse event among 3064 at risk, and 383 participants with another adverse event among 4984 at risk. The record presents these as separate categories. They should be read with their own denominators; they are not counts for all participants in the registry enrollment, and the figures should not be added together. The record does not clarify whether the categories overlap or describe the follow-up period for these counts.

The registry lists Gastroenteritis, abdominal problems, gynecologic problems/obstetrical, gynecologic problems, Respiratory infection, and cutaneous infection among the serious-event terms, with 0.1% next to each. The denominator and coding rules for these percentages are not reported in the registry record. The labels may not be mutually exclusive, and the record does not explain whether they represent individual participants, event reports, or coded categories.

These figures are descriptive surveillance data. They do not provide a comparison with a like-for-like control group, and they do not establish that vaccination caused the events. The record states that allocation was not stated and that the arms are not a like-for-like control comparison. It also does not report uncertainty estimates or event adjudication procedures. Those limitations should remain part of any reading of the safety counts.

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

The registry record documents a completed study of electronic surveillance after adjuvanted pandemic H1N1 immunization, with healthcare workers as the population of interest. It identifies a primary health-problem endpoint assessed at day 8, 15 and 29, and reports adverse-event counts for healthcare workers from CHUQ hospitals. These details show what the surveillance record set out to monitor and which adverse-event figures it recorded.

The record does not report a result for the primary endpoint, an analysis of group differences, or uncertainty estimates. The counts for serious and other adverse events are limited to the identified CHUQ group and have separate at-risk denominators. The named serious-event terms are listed with 0.1%, but the percentage denominator is not explained. Therefore, the record does not support a quantitative conclusion about the primary outcome or comparative risk.

The findings also cannot establish cause and effect. Allocation is not stated, and the record cautions that the groups are not like-for-like controls. A descriptive event count can be useful in safety surveillance, but it cannot by itself distinguish events caused by an intervention from events that occurred for other reasons. A comparison requires an appropriate design and clear information about follow-up, outcome definitions, and analysis.

More generally, surveillance and controlled comparative trials answer different questions. Surveillance can record events after immunization in a population and may contribute to safety monitoring. A causal comparison requires a suitable comparator and methods that address differences between groups. This is a general distinction; the registry record does not describe the methods needed to make a causal estimate for this study.

The study's status as completed does not resolve these evidence gaps. Enrollment is recorded as 6525, but the relation of that figure to the adverse-event denominators and endpoint follow-up is not described. The most defensible interpretation is limited to the record's stated study purpose, endpoint definition, group descriptions, and reported CHUQ adverse-event counts. Broader conclusions are not established by the registry information.

14. Why This Trial Matters Statistically

The study reflects a central statistical challenge in safety monitoring: uncommon adverse events may not be observable in small pre-licensure clinical studies, while broader surveillance can record outcomes in a larger population. The registry summary describes concern that adverse events occurring at a rate below 1% may not be detected in clinical trials with only a few hundred vaccine recipients. That concern motivates the surveillance question, but it does not establish the actual frequency of any event in this study.

Surveillance data can be informative because they document events in a defined setting after immunization. However, event detection and causal attribution are different tasks. A count can flag events for further evaluation, while a causal comparison needs an appropriate control group, reliable outcome definitions, and an analysis that accounts for differences in participants and follow-up. The registry record explicitly warns that the groups are not like-for-like controls and does not state allocation.

The record also illustrates why denominators and analysis populations matter. The registry enrollment is 6525, while the CHUQ adverse-event figures use at-risk denominators of 3064 and 4984 for separate categories. Without participant flow and follow-up details, the connection among these figures cannot be fully evaluated. Reporting counts alongside their denominators is useful, but readers still need to know how those populations were defined.

Finally, transparent reporting is part of statistical interpretation. The primary endpoint and its assessment times are identified, but its result, analysis methods, missing-data handling, and uncertainty estimates are not reported in the registry record. Those omissions limit what can be learned from the posted information. The statistical importance of the study lies in its surveillance aim and in the need to distinguish descriptive monitoring from evidence of comparative or causal effects.

15. 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 available registry information leaves important details about study conduct and analysis unspecified. The description of the primary endpoint is brief: it defines a new or worsening health problem resulting in medical consultation and gives assessment at day 8, 15 and 29, but does not explain how events were elicited, classified, or verified. The surveillance procedures, questionnaire content, and rules for handling multiple reports are not reported in the registry record.

The adverse-event figures apply to healthcare workers from CHUQ hospitals. The record names other site groups, but does not provide corresponding adverse-event counts for them in the information available for this explanation. It does not report site-specific enrollment, participant flow, follow-up completeness, or whether the at-risk groups were defined in the same way. The relationship between the registry enrollment of 6525 and the reported denominators is not explained.

Comparative interpretation is limited because allocation is not stated and the record cautions that the arms are not a like-for-like control comparison. No adjustment methods or analysis results are reported. The record also does not describe missing-data handling, analysis populations, confidence intervals, p-values, or outcome adjudication. The meaning of the percentages attached to serious-event terms is not clear because their denominator and coding rules are not reported.

These limitations do not show that any particular procedure was absent; they indicate that it is not described in the registry record. As a result, the posted information supports a narrow descriptive reading and does not allow a comprehensive assessment of study methods or comparative safety.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Surveillance for Adverse Events Following Pandemic H1N1 Immunization — NCT01289418.
• Registry record last updated 2012-08-21; status last verified 2012-08.
• Results first posted 2012-08-14.
• 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.

19. Record Summary

The registry record describes a completed electronic surveillance study following administration of an adjuvanted pandemic H1N1 vaccine to healthcare workers. It records enrollment of 6525, identifies PHAC/CIHR Influenza Research Network as the sponsor, and gives study dates of 2009-10 to 2010-05. Named groups are associated with hospitals in Québec, Toronto, and Halifax.

The primary endpoint counts participants with a new health problem or worsening of an existing condition that resulted in medical consultation, assessed at day 8, 15 and 29. The record does not report a result for this endpoint. For healthcare workers from CHUQ hospitals, it reports 35 participants with a serious adverse event among 3064 at risk and 383 with another adverse event among 4984 at risk. The record does not state allocation and cautions that the groups are not like-for-like controls. Analysis methods, missing-data handling, and uncertainty estimates are not reported in the registry record.