Clinical Trial of the BioMed rTSST-1 Variant Vaccine in Healthy Adults: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Clinical Trial of the BioMed rTSST-1 Variant Vaccine in Healthy Adults (NCT02814708), a randomized phase 2 study. The primary outcome is Number of Participants (Percentage) With Abnormal Laboratory Values and/or Adverse Events That Are Related to Treatment.

2. Clinical Question

3. Trial Design

This was a phase 2, randomized, quadruple-masked trial. The registry labels its model as sequential, but the meaning of that label and the operational details of the sequence are not reported in the registry record. The planned enrollment was 140 healthy adults, male and female, aged 18-64 years. The registry status is completed; the recorded study start is 2016-05 and primary completion is 2020-05.

Seven groups were described. Three received 10µg of the candidate vaccine with 1, 2, or 3 immunizations, and three received 100µg with 1, 2, or 3 immunizations. The remaining group received 1mg of Al(OH)3 adjuvant with 3 immunizations. The brief summary describes repeat immunization timing as 3 months after the first immunization and 6 months after the second immunization in the respective groups. It does not give further schedule details for each group.

The brief summary says participants were monitored for vital signs, hematology, clinical chemistry, and antibodies against TSST-1. Antibodies were to include TSST-1 binding antibodies assessed through ELISA, with neutralizing antibodies described as an exploratory endpoint. Antibody persistence was a stated objective over a period of 12 months. The primary endpoint's timeframe is separately stated as 12 months and 18 months follow up.

The posted primary outcome counts include 20 participants in each group. Random sequence generation, allocation concealment, the identity of the masked parties, and the reasons for the sequential model label are not reported in the registry record. The record also does not explain whether the posted outcome counts include all randomized participants or a defined analysis population.

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.

Only the first 6 of 7 groups are shown.

Overall Study

Analysis population for the primary outcome, as defined in the registry: any suspected related systemic AE

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.

Only the first 6 of 8 groups are shown.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants (Percentage) With Abnormal Laboratory Values and/or Adverse Events That Are Related to Treatment, measured over 12 months and 18 months follow up.

The primary endpoint is titled “Number of Participants (Percentage) With Abnormal Laboratory Values and/or Adverse Events That Are Related to Treatment.” It is a count outcome: for each group, the posted value is the number of participants recorded as having the relevant event, rather than a measurement of event severity or duration. The registry describes the population for this outcome as “any suspected related systemic AE” and gives the timeframe as 12 months and 18 months follow up.

The endpoint is used to characterize safety and tolerability during follow-up. Combining abnormal laboratory values and adverse events can capture more than one kind of safety finding, while counting participants focuses on whether people experienced a qualifying finding rather than how many events each person had. The record does not specify the thresholds used to define an abnormal laboratory value, the detailed rules for judging treatment relatedness, or whether a participant with more than one finding is counted once or more than once. The outcome title includes a percentage, but the posted arm results give counts; no percentages are stated in the posted results.

In the posted results, the group counts range from 9.0 to 13.0 among groups with 20.0 participants each. These are descriptive counts and do not, on their own, show whether differences between groups are statistically distinguishable or clinically important. Interpretation also depends on how outcomes were defined, collected, and handled when follow-up information was incomplete; those details are not reported in the registry record.

7. Results Posted in the Registry

• Dose Group 2: 55.0% (11/20) versus 45.0% (9/20) on control; risk difference 10.0 percentage points (95% CI -20.8 to 40.8), risk ratio 1.22 (0.65–2.29); unadjusted two-proportion z-test p = 0.527.
• Dose Group 3: 55.0% (11/20) versus 45.0% (9/20) on control; risk difference 10.0 percentage points (95% CI -20.8 to 40.8), risk ratio 1.22 (0.65–2.29); unadjusted two-proportion z-test p = 0.527.
• Dose Group 4: 60.0% (12/20) versus 45.0% (9/20) on control; risk difference 15.0 percentage points (95% CI -15.6 to 45.6), risk ratio 1.33 (0.73–2.44); unadjusted two-proportion z-test p = 0.342.
• Dose Group 5: 50.0% (10/20) versus 45.0% (9/20) on control; risk difference 5.0 percentage points (95% CI -25.9 to 35.9), risk ratio 1.11 (0.58–2.14); unadjusted two-proportion z-test p = 0.752.

8. Statistical Interpretation

9. Statistical Methods Explained

What does a risk difference describe?

A risk difference compares the proportions of participants with an event in two groups by subtracting one group’s proportion from the other’s. It is an absolute measure: it expresses the separation on the scale of event occurrence, rather than as a relative ratio. The posted comparisons use Dose Group 1 as the reference and report the estimates as decimals. Their interpretation is tied to the endpoint definition and follow-up used in the registry record.

For example, the risk-difference estimate for Dose Group 6 is 0.2. This is a point estimate based on the posted counts, not a precise account of the underlying difference. Its confidence interval runs from -0.102 to 0.502, so values on both sides of zero remain compatible with the data under the interval method. The estimate alone should not be treated as a definitive comparison.

How should the confidence interval be understood?

A confidence interval describes uncertainty around an estimated effect under the assumptions of the method used. In general, narrower intervals indicate more precision, while wider intervals indicate less precision. An interval that includes the no-difference value does not establish that the groups are equal; it means the data do not rule out no difference at the interval’s stated confidence level. The posted risk-difference intervals all include zero and are wide enough to cover differences in either direction.

Confidence intervals are not a range of outcomes for individual participants, and they do not give the probability that a particular treatment effect is true. They are also not a substitute for deciding whether a difference would matter clinically. The registry record does not report a clinically important difference threshold for this endpoint.

What does an unadjusted p-value tell the reader?

A p-value summarizes how unusual data at least as inconsistent with a specified no-difference model would be, if that model and the analysis assumptions held. It does not measure the magnitude or importance of a difference. It is not the probability that the no-difference model is true. Here, the p-values are labeled unadjusted recalculations. Each comparison is interpreted without a reported adjustment for making several comparisons.

The reported p-values are 0.527 for Dose Groups 2 and 3, 0.342 for Dose Group 4, 0.752 for Dose Groups 5 and 7, and 0.204 for Dose Group 6. None is small enough to distinguish the corresponding comparison from no difference under conventional interpretation. Because the registry record does not report the trial’s statistical plan, these values should not be mistaken for the sponsor’s prespecified analysis.

Why do small groups affect inference?

When group counts are limited, each participant’s outcome can have a substantial influence on the observed proportion. This can make estimates unstable and confidence intervals broad. A similar point estimate across two comparisons does not guarantee identical underlying effects, and a difference between point estimates does not by itself establish a real group difference. This is especially relevant when several dose and schedule groups are compared with one reference group.

For binary outcomes, methods may rely on approximations or alternative procedures, particularly when event counts are sparse. The specific method used for the posted primary endpoint recalculations is not reported in the registry record. The planning illustration separately states that it uses a normal approximation; that assumption applies to the planning illustration and should not be attributed to the trial’s original analysis.

Why can over-dispersion matter?

In general, over-dispersion occurs when observed variability is greater than a statistical model expects. It can lead to uncertainty being understated if the analysis assumes less variability than the data contain. The posted primary endpoint is a participant count by group, and the registry record does not report a model-based variance analysis or an assessment of over-dispersion. This general concern therefore cannot be used to revise the posted estimates or infer what analysis the investigators performed.

The registry record lists no posted analyses for the primary outcome. The displayed risk differences, confidence intervals, and p-values are unadjusted recalculations from the arm summaries. No adjustment for baseline characteristics, stratification variables, or other covariates is reported. The record does not report a prespecified test, a primary contrast hierarchy, or an analysis population definition.

These methods explain what the posted estimates mean, but not how the trial was originally designed to analyze the endpoint. The record’s randomization and masking labels describe broad design features; they do not disclose allocation procedures or analytical choices. A full interpretation of confirmatory inference would require the protocol and statistical analysis plan, neither of which is reported in the registry record.

10. Confidence Intervals and Precision

The risk-difference estimates are imprecise. For Dose Groups 2 and 3, the estimate is 0.1 and the confidence interval extends from -0.208 to 0.408. Dose Group 4 has an estimate of 0.15, with an interval from -0.156 to 0.456. Dose Groups 5 and 7 each have an estimate of 0.05, with an interval from -0.259 to 0.359. Dose Group 6 has an estimate of 0.2, with an interval from -0.102 to 0.502.

All intervals include zero and also extend into positive and negative values. The data therefore leave uncertainty about both the direction and the size of the group differences. The intervals should not be read as proving equivalence or as showing that the groups have identical event risks. The point estimates are only the centers of ranges that remain compatible with the observed summaries under the calculation used.

Precision is limited in part by the posted group sizes and event counts. With 20.0 participants per group, small changes in observed counts can affect estimated proportions. The interval widths also show that the data are compatible with a range of differences, rather than tightly pinning down a single value. No clinically meaningful margin is reported, so the intervals cannot be classified as excluding all differences that might matter.

The ratios reported alongside the risk differences are also uncertain: their confidence intervals span the no-association value of 1. The registry record does not report a multiplicity adjustment or sponsor-conducted inferential analysis for these comparisons. The recalculated intervals are best read as descriptive measures of uncertainty around the posted group summaries, not as a complete substitute for a prespecified analysis.

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 estimates are participants per arm, not total event counts. The assumptions stated for this illustration 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 at the stated fraction of the observed effect. These assumptions describe the planning illustration; the trial’s own original sample-size assumptions are not reported in the registry record.

The 80% power column gives the estimated number of participants per arm for a design that would have an 80% chance of detecting the chosen effect under those assumptions, if that effect and model were correct. The 90% power column gives the corresponding per-arm planning figure for a higher chance of detecting that effect. These are design calculations, not results about how well the completed trial was powered for an effect that actually occurred.

The rows for 100%, 75%, and 50% of the observed effect show how the planning estimate changes when the assumed effect is made smaller. A smaller effect is harder to distinguish from random variation, so it requires more participants per arm for the same target power. For example, planning for 75% of the observed effect in the Dose Group 6 comparison gives 173 participants per arm for 80% power and 231 participants per arm for 90% power; planning for 50% of that effect gives 392 and 524 participants per arm, respectively.

This is not observed power. It is an illustrative planning calculation based on the observed effect, rather than the trial’s original design justification. The registry record does not report the assumptions used by the investigators to choose the actual enrollment target or whether a formal sample-size calculation informed that choice.

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 = 0.450; treatment proportion p₁ = 0.550; average p̄ = 0.500.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7071 = 1.3859.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7036 = 0.5921.
4. n = (1.3859 + 0.5921)² / (0.1000)² = 391.3, rounded up to 392 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 <- 0.45                          # control proportion
p1 <- 0.55                          # 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(2814708)
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 = 392 (80% power), 524 (90% power)
 75% of observed effect: n per arm = 697 (80% power), 932 (90% power)
 50% of observed effect: n per arm = 1,565 (80% power), 2,095 (90% power)
power.prop.test: 391.3 
Simulated power at n = 392 per arm: 0.797 (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 posted comparisons assess Dose Groups 2 through 7 against Dose Group 1. Conducting several comparisons creates a multiplicity issue: even if each comparison is considered separately, the chance of at least one apparently unusual result can increase across a set of tests. The reported p-values are unadjusted. Whether the trial used a multiplicity procedure, prioritized comparisons, or treated these analyses as exploratory is not reported in the registry record.

The registry lists 0 posted analyses for this outcome. The risk differences, confidence intervals, and p-values are unadjusted recalculations from the posted arm summaries. No adjusted model, covariate set, or confirmatory testing hierarchy is described. As a result, the comparisons should not be interpreted as a complete account of a prespecified trial analysis.

The registry record does not report how missing outcome information was handled, whether participants with incomplete follow-up were excluded, or how withdrawals were incorporated. It does not define an intention-to-treat, per-protocol, or safety analysis population for the primary endpoint. The arm counts show 20.0 participants per group, but the record does not explain whether that represents the full randomized group, participants with available outcome data, or another analysis set.

The record also does not report imputation methods, sensitivity analyses for missing data, or reasons for missingness. These details matter because an analysis based only on observed outcomes may be affected if the availability of follow-up differs in relation to group or outcome. Without the analysis population and missing-data rules, the posted results cannot show how robust the comparisons are to incomplete outcome information.

Randomization and quadruple masking are recorded design features, but the specific procedures and their implementation are not reported. The identities of the people masked, allocation concealment, and any deviations from masking are also not reported in the registry record. These missing details limit assessment of both the conduct and the 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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: anaphylactic reaction (5.0%).

The serious adverse event figures are reported by group. Each group lists 20 participants at risk. The number of serious adverse events considered related to treatment is 0 in Dose Groups 1, 2, 3, 4, 6, and 7, and 1 in Dose Group 5. The registry lists 0 deaths in every group. These figures describe the posted safety record; they do not establish that no other adverse events occurred.

The registry also reports that the most common serious adverse event term was “anaphylactic reaction,” at 5.0%. The record does not provide enough context in that summary to assign this term to a particular group or to determine its relationship to the primary endpoint. The event term should therefore be read as a reported safety category, not as an explanation of the group-level primary outcome counts.

Serious adverse events are distinct from the primary endpoint, which includes abnormal laboratory values and/or adverse events related to treatment. The primary counts are not the same as counts of serious events. A zero in the serious-event column means no serious related event was recorded for that group in these results; it does not mean that participants had no adverse events or laboratory findings.

Small group sizes and the follow-up information available in the registry limit what can be inferred about uncommon events. The record does not report detailed event narratives, onset, duration, outcome, or group-specific attribution for the top serious term.

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

The posted results describe safety-related participant counts in healthy adults assigned to different vaccine doses and immunization schedules or to an adjuvant group. Counts ranged from 9.0 to 13.0 in groups with 20.0 participants each. The unadjusted recalculated comparisons with Dose Group 1 have risk-difference confidence intervals that all include zero. These results do not clearly distinguish the groups on the primary endpoint, but they also do not establish that the groups are equivalent.

The data do not show whether the vaccine prevents Toxic Shock Syndrome. The registry record describes the vaccine’s proposed role and the study’s antibody aims, but the posted primary endpoint is not disease incidence or prevention. The brief summary mentions immunogenicity and antibody persistence as objectives, while only one secondary outcome is posted and no analysis results are listed for it. The record therefore does not support conclusions about clinical protection or the durability of a protective effect.

The results also do not establish that a particular dose or immunization schedule is preferable. Point estimates differ, but the intervals are broad and overlap the no-difference value. The group counts alone cannot establish a dose-response relationship, explain the biological meaning of antibody measurements, or determine whether a difference in safety findings would be clinically important.

The serious adverse event results show one related serious event in Dose Group 5 and zero in the other groups; no deaths are listed. These observations are limited by the size of the groups and by the lack of detailed event and analysis information in the registry record. Absence of a recorded event in a group should not be taken to mean that rare events are impossible.

Overall, the registry results are descriptive and imprecise. They provide a snapshot of the recorded safety outcome and exploratory between-group estimates, not a definitive assessment of efficacy, comparative safety, or long-term protection. The trial was conducted in healthy adults, so its results should not be assumed to describe outcomes in people with Toxic Shock Syndrome.

16. Why This Trial Matters Statistically

This trial is statistically useful because it illustrates the distinction between an observed count and the uncertainty around a comparison. The arm results are easy to read as counts, but the recalculated risk differences have broad confidence intervals. That distinction matters: a visible difference in counts is not, on its own, strong evidence that the underlying event frequency differs between groups.

The study also has several dose and schedule groups compared with a single reference group. This structure raises questions about multiplicity and analysis priorities. The registry record does not report how the original investigators planned to handle multiple comparisons, so unadjusted results should be interpreted cautiously rather than treated as independent definitive tests.

The planning illustration emphasizes another general principle: sample size depends on the effect a study is designed to detect. Smaller target effects require more participants per arm to reach the same stated power under the listed assumptions. Those planning figures are not observed power and do not reveal the investigators’ original design rationale.

Finally, the trial distinguishes safety monitoring from immunogenicity measurement. Monitoring laboratory values and adverse events addresses a different question from measuring binding or neutralizing antibodies. A posted safety count cannot stand in for an antibody response, and an antibody response cannot by itself establish prevention of clinical disease. Keeping these outcomes separate helps readers avoid making conclusions that the reported endpoint does not support.

The record’s missing analysis details are also instructive. Randomized and masked design labels do not disclose how outcomes were analyzed, which participants were included, or how missing follow-up was handled. Statistical interpretation depends on those details, especially when estimates are imprecise and several groups are compared.

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 endpoint combines abnormal laboratory values and/or treatment-related adverse events, but the registry record does not define laboratory thresholds, event attribution rules, or how multiple qualifying findings in one participant were counted. It describes the endpoint population as any suspected related systemic AE, which does not fully explain how that phrase relates to abnormal laboratory values in the endpoint title.

The primary timeframe is stated as 12 months and 18 months follow up, but the record does not explain how these timepoints relate to the posted group counts or whether the counts represent events across the full follow-up period. The schedule description gives repeat timing, but does not provide group-specific completion or adherence information.

The trial’s own analysis plan and sample-size justification are not reported in the registry record. The posted primary outcome has no registry-listed analyses; the comparisons are unadjusted recalculations from summary counts. Multiplicity adjustment, missing-data handling, and analysis populations are not described. These omissions limit assessment of whether the estimates match a prespecified analysis.

The record gives no detailed information about participant flow, exclusions, withdrawals, or completeness of follow-up. Although each posted arm count is 20.0, the record does not clarify whether all randomized participants contributed outcome data. It also does not report baseline characteristics or any adjustment for differences between groups.

The trial involved healthy adults and was designed to examine safety, tolerability, and antibody responses. The posted primary results do not establish effects on clinical Toxic Shock Syndrome. The results also provide limited information about uncommon serious events, and the registry does not include detailed narratives or timing for the reported serious adverse events. These limitations should be considered when interpreting the group comparisons.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Clinical Trial of the BioMed rTSST-1 Variant Vaccine in Healthy Adults — NCT02814708.
• Registry record last updated 2022-01-04; status last verified 2021-12.
• Results first posted 2021-12-13.
• 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

NCT02814708 is a completed phase 2 randomized, quadruple-masked trial of the BioMed rTSST-1 Variant Vaccine in healthy adults. The registry records a sequential model, planned enrollment of 140, and study dates of 2016-05 to primary completion in 2020-05. The seven groups varied vaccine dose and number of immunizations, with an Al(OH)3 adjuvant group as comparator.

The primary outcome counts participants with abnormal laboratory values and/or treatment-related adverse events. The posted group counts range from 9.0 to 13.0, with 20.0 participants in each group. Unadjusted recalculated risk-difference intervals for comparisons with Dose Group 1 all include zero and are broad. The record lists no sponsor analyses for this outcome and does not report multiplicity handling, missing-data procedures, or the trial’s original sample-size assumptions.

The registry also reports zero deaths in all groups and one related serious adverse event in Dose Group 5. The posted primary endpoint and available safety summaries do not establish clinical disease prevention or identify a clearly distinguishable difference between groups.