Evaluation of EVO100 for Prevention of Urogenital Chlamydia Trachomatis and Neisseria Gonorrhoeae Infection: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of EVO100 for Prevention of Urogenital Chlamydia Trachomatis and Neisseria Gonorrhoeae Infection (NCT04553068), a randomized phase 3 study. The primary outcome is Percentage of Study Successes in the EVO100 and Placebo Treatment Groups.

2. Clinical Question

3. Trial Design

This was a Phase 3, randomized, triple-masked, parallel-group trial with placebo control. The registry lists an enrollment of 1892 and the status as completed. EVO100 vaginal gel, 5 g, was compared with placebo vaginal gel, 5 g. The listed study start was 2020-10-15, and primary completion was 2022-07-28. The study title and brief identify prevention of urogenital Chlamydia trachomatis and Neisseria gonorrhoeae infection as the objective.

The primary outcome timeframe was 16 weeks, and its population is labelled mITT. The result record reports 906 participants in the EVO100 group and 913 in the placebo group for this outcome. The outcome is expressed as a count of participants meeting the success definition, rather than as a time-to-event measure. The registry also lists safety evaluation of adverse events as a secondary outcome.

Randomization, masking, and parallel-group allocation describe key design features, but the registry record does not report the randomization procedure, allocation concealment, or which people were included in triple masking. It does not report the detailed eligibility criteria, site information, dosing schedule, adherence procedures, or handling of protocol deviations. These details should not be inferred from the trial title or design labels.

The registry record lists no separate analysis records, although it includes a primary outcome comparison. Original protocol details such as the planned statistical model, prespecified significance level, original sample-size justification, and planned interim analyses are not reported in the registry record. The planning illustrations associated with the posted effect are not a substitute for the trial's original design assumptions.

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

Analysis population for the primary outcome, as defined in the registry: mITT

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 Percentage of Study Successes in the EVO100 and Placebo Treatment Groups, measured over 16 weeks.

The primary endpoint is the percentage of participants classified as study successes in the EVO100 and placebo groups over 16 weeks. Success was defined as completing the trial to Visit 5 without CT or GC infection and without using prohibited antibiotics during the study. The outcome is therefore not simply an infection count: it combines infection status, prohibited antibiotic use, and completion through the specified visit. A participant must satisfy all parts of the definition to count as a success.

For a binary endpoint, each participant is classified into one of two categories: success or not success. Reporting the number meeting the definition in each arm gives the basis for comparing the probability of success between groups. The registry reports 684 successes among 906 participants in the EVO100 group and 696 among 913 in the placebo group. It also reports a risk difference, which expresses the contrast in success probabilities as a difference between arms.

A composite outcome can capture more than one way a participant may fail to meet the study's definition, but it also means the result does not isolate the contribution of each component. The registry does not report separate primary results for infection, prohibited antibiotic use, or completion. It therefore does not establish which component accounts for the overall success result.

7. Results Posted in the Registry

• EVO100 Gel: 75.5% (684/906) versus 76.2% (696/913) on control; risk difference -0.7 percentage points (95% CI -4.7 to 3.2), risk ratio 0.99 (0.94–1.04); unadjusted two-proportion z-test p = 0.714.

8. Statistical Interpretation

9. Statistical Methods Explained

What does the risk difference describe?

The endpoint is binary: each participant either met the study-success definition or did not. A risk is the probability of an event in a group; in this trial, the event used for the primary comparison is success. The risk difference subtracts the comparator group's risk from the intervention group's risk. Its sign indicates the direction of the estimated contrast, and zero represents equal risks. Here, the reported risk difference is -0.007. Because the outcome is success, a negative sign indicates a lower estimated success probability in the EVO100 group than in the placebo group.

The risk difference is an absolute measure: it expresses the size of the separation between the two group probabilities on the probability scale. It differs from a relative measure, which expresses one group's probability or odds relative to the other. The registry also reports risk-ratio and odds-ratio estimates. These measures summarize the same comparison using different scales, so their numerical values cannot be compared directly with the risk difference.

How should a confidence interval be understood?

A confidence interval describes statistical uncertainty around an estimate under the method's assumptions. It gives a range of values reasonably compatible with the observed data and the chosen interval procedure. It is not a range containing every participant's outcome, nor does it assign a probability to a particular fixed treatment effect. The risk-difference interval runs from -0.047 to 0.032 and includes zero, the value corresponding to equal group risks. The risk-ratio and odds-ratio intervals also include 1, their respective null values.

What does the p-value test?

A p-value is calculated relative to a null hypothesis, commonly a hypothesis of no group difference. In general, it measures how often a test statistic at least as extreme as the observed one would occur under that null hypothesis, assuming the test's conditions hold. It does not measure the size or importance of an effect, and it does not state the probability that a result occurred by chance. The posted unadjusted p-value is 0.714. The registry record does not report the full statistical test specification or whether a multiplicity procedure was planned, so the p-value should be interpreted as the comparison shown in the result record.

Why do the measures tell a related but not identical story?

The risk difference, risk ratio, and odds ratio use different scales. A difference is expressed as an absolute separation; ratios compare one group with another. The risk ratio and odds ratio can be useful in different settings, but they do not replace an absolute estimate when the question concerns the size of the probability difference. All three posted confidence intervals include their corresponding null values, which is consistent with substantial uncertainty about the exact contrast.

The outcome definition matters to interpretation as much as the statistical measure. Success required completion to Visit 5, absence of CT or GC infection, and no prohibited antibiotic use. A participant could therefore fail the composite definition for more than one reason. The posted primary comparison does not identify which component contributed to group differences. Separate component results and details of the statistical model are not reported in the registry record.

What do the planning figures represent?

The sample-size figures are planning illustrations based on fractions of the observed effect, with two-sided significance level 0.05, equal allocation between arms, and a normal approximation. They describe hypothetical participant requirements under those assumptions; they are not the sample size originally justified for the trial. A power calculation asks how often a planned test would detect a specified effect if that effect were the true one and the assumptions held. The illustrations do not establish the probability that the present trial detected its true effect. Smaller target effects require larger planned samples because they are harder to distinguish from random variation.

In general, statistical inference also depends on data quality, outcome classification, missing observations, and analysis choices. The registry record does not give enough detail to evaluate all of these features. The statistical summaries should therefore be interpreted alongside the stated endpoint definition, the reported population label, and the limits of the registry information, rather than as a complete account of the trial's analysis.

10. Confidence Intervals and Precision

The main precision measure for the primary comparison is the confidence interval around the risk difference. The estimate is -0.007, and the interval extends from -0.047 to 0.032. Because the interval includes zero, the data are compatible with a range of possible group differences, including no difference and contrasts in either direction. The interval is not narrowly concentrated at the point estimate, so the exact size and direction of the underlying contrast remain uncertain.

The relative measures show similar uncertainty on their own scales. The risk ratio is 0.990, with a confidence interval from 0.940 to 1.043. The odds ratio is 0.961, with a confidence interval from 0.775 to 1.191. Each interval includes 1, the value indicating no relative difference. These intervals do not mean all values are equally plausible, and they are not guarantees about the result in another study.

Precision depends on the amount of information in the data and on the variability of the endpoint. A binary outcome records whether each participant met a definition, but estimates still have sampling uncertainty. The registry provides the arm counts and comparison intervals, but does not report a detailed analysis plan or additional information needed to assess all sources of uncertainty. The mITT label is stated, while its exact operational definition and the treatment of missing outcome data are not reported in the registry record.

Confidence intervals communicate more than a binary declaration based on a p-value: they show a range of contrasts that remain compatible with the data under the interval method. Here, the intervals make clear that the observed point estimate should not be treated as a precisely known effect.

11. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm for 80% power and participants per arm for 90% power. They are not totals across both arms and are not total event counts. The calculations assume 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. These are planning assumptions for the illustrations; the trial's original sample-size assumptions are not reported in the registry record.

For planning for 100% of the observed effect, the figures are 53,131 participants per arm for 80% power and 71,127 participants per arm for 90% power. For planning for 75% of the observed effect, they are 94,210 and 126,119 participants per arm, respectively. For planning for 50% of the observed effect, they are 211,418 and 283,028 participants per arm, respectively.

In plain terms, the 80% column describes a hypothetical design that would detect the chosen effect in 80% of repeated studies under the stated assumptions if that effect were true. The 90% column applies the same idea with a higher detection probability. These percentages do not describe the probability that the current trial's result is correct. This is not observed power.

As the target effect becomes smaller, the groups' outcome probabilities are harder to distinguish, so more participants are needed to achieve the same planned power under the calculation assumptions. The figures are illustrative rather than a retrospective score of the completed study, and they do not establish what sample size the investigators originally planned or why.

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 = 0.762; treatment proportion p₁ = 0.755; average p̄ = 0.759.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6051 = 1.1861.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6051 = 0.5093.
4. n = (1.1861 + 0.5093)² / (-0.0074)² = 53,130.4, rounded up to 53,131 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 <- 0.762322015334064                          # control proportion
p1 <- 0.754966887417219                          # 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(4553068)
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 = 53,131 (80% power), 71,127 (90% power)
 75% of observed effect: n per arm = 94,210 (80% power), 126,119 (90% power)
 50% of observed effect: n per arm = 211,418 (80% power), 283,028 (90% power)
power.prop.test: 53130.4 
Simulated power at n = 53,131 per arm: 0.804 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

13. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary outcome and one secondary outcome, safety evaluation of adverse events. It reports two outcome measures and no separate analysis records. The primary comparison is posted, but the registry record does not report a complete statistical analysis plan, a hierarchy of hypotheses, or a method for controlling the chance of false-positive findings across multiple outcomes or analyses. It is therefore not possible to determine from the record whether a multiplicity adjustment was planned or applied. The posted primary p-value is explicitly unadjusted.

The primary population is labelled mITT. This label alone does not define which participants were included, how eligibility for that analysis was determined, or how protocol deviations were handled. The registry's endpoint definition requires completion to Visit 5, but it does not explain how participants without complete follow-up were classified or whether missing primary outcome data were imputed, excluded, or otherwise addressed. Those choices can affect the analyzed population and the interpretation of a binary endpoint.

The registry record also does not report the detailed statistical model, covariate adjustment, subgroup analyses, sensitivity analyses, interim analyses, or a prespecified strategy for handling multiple comparisons. These elements should not be assumed from the randomized, triple-masked design or from the reported comparison. Without them, the posted summaries can be described, but the full analysis process cannot be reconstructed.

Missing-data methods and multiplicity procedures answer different questions. Missing-data methods address incomplete outcome information, while multiplicity methods address the interpretation of several statistical tests. Neither is described in enough detail in the registry record to support a more specific assessment. The primary estimate and interval remain interpretable as the posted comparison, with these reporting gaps kept in view.

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 4% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: ectopic pregnancy (0.2%), abortion missed (0.2%), blood loss anemia (0.1%), alcohol poisoning (0.1%), craniocerebral injury (0.1%).

The safety record reports serious adverse events for 4 of 926 participants at risk in the EVO100 group and 9 of 937 at risk in the placebo group. It reports other adverse events for 39 of 926 participants at risk in the EVO100 group and 28 of 937 at risk in the placebo group. Deaths are reported as 0 in each group. The safety denominators differ from the primary-outcome analysis counts; the registry record does not explain the reason for that difference.

The serious-event terms listed include ectopic pregnancy and abortion missed at 0.2% each, and blood loss anemia, alcohol poisoning, craniocerebral injury, and fall at 0.1% each. These are the registry's listed term frequencies; the record does not provide a separate event count for each term in the information. Adverse-event counts describe events recorded during the study and do not, by themselves, establish that the study product caused them.

Safety counts and primary efficacy outcomes answer different questions. These figures are descriptive; the registry does not report a statistical comparison for the safety outcomes or additional details about event definitions, attribution, or follow-up. Differences in counts should not be interpreted as proof of a causal difference between groups.

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

The primary result describes the observed proportion of participants meeting a composite study-success definition in each randomized group. It does not directly isolate infection prevention, because success also required completion to Visit 5 and no prohibited antibiotic use. The posted risk difference is -0.007, and its confidence interval includes zero. The data therefore do not precisely identify the direction or size of the underlying difference in this endpoint.

The result should not be reduced to the p-value alone. The p-value of 0.714 is a summary under a statistical test, not the probability that EVO100 is effective or ineffective. The confidence interval gives a more direct view of uncertainty about the risk difference, while the arm counts show the observed endpoint totals. Together, these summaries describe the trial result but do not establish what would happen in other populations or under other conditions.

The endpoint's composite structure also limits component-level conclusions. The primary result does not show how many participants had CT infection, GC infection, prohibited antibiotic use, or failure to complete the required visit as separate outcomes. Such component results are not reported in the registry record. The listed safety counts are separate descriptive information and do not resolve the uncertainty in the efficacy endpoint.

The record reports a randomized, placebo-controlled, triple-masked Phase 3 trial and lists it as completed. Those design features provide context for interpreting the comparison, but do not fill gaps in reporting about the analysis population, missing data, multiplicity, or original sample-size justification. The posted data support describing the estimate and its uncertainty, not a treatment recommendation or a claim that the product does or does not work.

16. Why This Trial Matters Statistically

This trial illustrates why a clinical result needs to be read through its endpoint definition, effect measure, and uncertainty together. The primary outcome is not infection alone: it counts participants meeting a definition that includes completion to Visit 5, no CT or GC infection, and no prohibited antibiotic use. That distinction matters because an overall success comparison cannot identify which part of the composite accounts for the result.

The absolute risk difference is useful because it expresses the contrast in success probabilities directly. The risk ratio and odds ratio offer relative scales, but they answer the comparison in different mathematical terms. Here, all the reported confidence intervals include their respective null values, and the risk-difference interval includes zero. The estimate is therefore uncertain in both magnitude and direction, despite the trial's randomized and masked design.

The planning illustrations also demonstrate how assumed effect size changes projected sample requirements. A smaller effect requires more participants for a given planned power under the stated calculation assumptions. These figures are not evidence about the power achieved by the completed trial and do not reveal the original design rationale.

Finally, the record shows the value and limits of registry reporting. It provides trial design labels, arm counts, a primary contrast, and selected safety counts, but does not report important analysis details such as missing-data handling, the exact mITT definition, or multiplicity procedures. Reading the result statistically means distinguishing what the estimates show from what remains unspecified.

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 does not report the full eligibility criteria, so the exact population to which the result applies cannot be assessed from the record alone. It labels the primary analysis population mITT, but does not define that population or specify how participants with missing outcomes, protocol deviations, or incomplete follow-up were handled. This matters because the success definition itself requires completion to Visit 5.

The primary endpoint combines absence of CT or GC infection, absence of prohibited antibiotic use, and completion. The record gives an overall success comparison but does not report separate results for these components. It also does not report details of endpoint ascertainment or the criteria used to determine prohibited antibiotic use.

The registry record does not report the full analysis plan, including the statistical model, covariate adjustment, sensitivity analyses, subgroup analyses, or multiplicity strategy. It does not report the original sample-size justification or planned interim analyses. Triple masking is reported, but which people were masked and the specific masking procedures are not described.

The safety results are presented as counts and listed event terms, without a reported statistical comparison or detailed attribution information. The registry record does not explain why the denominators for safety and the primary outcome differ. These reporting limits do not invalidate the posted summaries, but they restrict how fully the methods and results can be independently evaluated.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Evaluation of EVO100 for Prevention of Urogenital Chlamydia Trachomatis and Neisseria Gonorrhoeae Infection — NCT04553068.
• Registry record last updated 2024-01-30; status last verified 2024-01.
• Results first posted 2024-01-30.
• 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

NCT04553068 is listed as a completed Phase 3 randomized, triple-masked, parallel-group trial of EVO100 vaginal gel versus placebo vaginal gel. The registry reports enrollment of 1892 and a primary outcome timeframe of 16 weeks. Study success required completion to Visit 5 without CT or GC infection and without prohibited antibiotic use.

The primary result reports 684 successes among 906 participants in the EVO100 group and 696 among 913 in the placebo group. The risk difference is -0.007, with a 95% confidence interval from -0.047 to 0.032, and the posted unadjusted p-value is 0.714. Safety information reports serious adverse events, other adverse events, and deaths by group. Details of the original design assumptions and several analysis procedures are not reported in the registry record.