Safety and Tolerability Study of Acoziborole in g-HAT Seropositive Subjects: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Safety and Tolerability Study of Acoziborole in g-HAT Seropositive Subjects (NCT05256017), a randomized phase 2, phase 3 study. The primary outcome is Occurrence of Any TEAEs.

2. Clinical Question

3. Trial Design

The registry describes a randomized, quadruple-masked, parallel-group study with placebo control. The listed phases are Phase 2 and Phase 3. Participants received either a single dose of acoziborole or matching placebo. The registry lists enrollment as 1208 and the study status as completed. The listed start date is 2021-12-30, and the primary completion date is 2023-08-03.

The study focused on g-HAT seropositive participants without parasites detected by microscopy in a body fluid. This population differs from participants with parasitologically confirmed infection: the registry background explains that microscopy may fail to demonstrate parasites in some seropositive people. The present study’s stated objective was to gather safety and tolerability information in this setting. The primary endpoint was any TEAE over the period from investigational product administration on Day 1 through the Month 4 follow-up visit, identified as the end of study.

The primary analysis used the safety set, defined in the registry as participants who received at least one tablet of investigational product, based on actual treatment received and confirmed by drug concentration data. The reported group sizes for that endpoint are 906 for acoziborole and 300 for placebo. These safety-set denominators need not be interpreted as the enrollment figure: they describe the groups used for this posted safety analysis.

The registry record does not report the randomization sequence method, allocation concealment procedure, masking implementation details, or the original design assumptions for sample size. It also does not report a full statistical analysis plan in the information used for these results. Those omissions limit reconstruction of the trial’s planned procedures beyond the design features and analysis population explicitly described in the 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.

Treatment Period

Reasons for not completing this period:

Follow-up

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Safety set: participants who received at least 1 tablet of the investigational product (based on the actual treatment received, confirmed by drug concentration data).

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.

Population: Safety set (based on the actual treatment received, determined by the presence/absence of acoziborole in blood)

6. Primary Endpoint

The registry lists the primary outcome as Occurrence of Any TEAEs, measured over From the investigational product administration (Day 1) to the Month 4 follow-up visit (End of Study)..

The primary endpoint is the occurrence of any treatment-emergent adverse event (TEAE), measured as the number of participants who experienced at least one such event. The registry gives the observation period as the time from investigational product administration on Day 1 through the Month 4 follow-up visit, which it identifies as the end of study. The safety population includes participants who received at least one tablet, classified according to actual treatment received and confirmed by drug concentration data.

A participant-level any-event endpoint provides a broad summary of whether a participant experienced at least one event during follow-up. It does not describe how many events an affected participant had, how long events lasted, or their severity. Those questions require separate outcomes or event-level analyses. The registry lists occurrence and excess rate, with a 95% confidence interval, as the primary outcome description.

Safety outcomes are relevant in a study whose stated objective is to collect safety and tolerability data. However, an any-TEAE count combines events that may differ in type and seriousness. It should therefore be read alongside the separate serious adverse event information and the listed secondary outcomes, rather than as a complete account of the nature of all adverse events. The precise operational definition of a TEAE and the detailed rules for event coding are not reported in the registry record.

7. Results Posted in the Registry

• Acoziborole: 21.5% (195/906) versus 23.0% (69/300) on control; risk difference -1.5 percentage points (95% CI -6.9 to 4.0), risk ratio 0.94 (0.74–1.19); unadjusted two-proportion z-test p = 0.592.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary at the participant level: each participant is counted as having experienced any TEAE or not having experienced one during the specified period. For each group, the registry reports the number of participants with an event and the number in the safety set. A comparison of event proportions can be expressed as a risk difference, which subtracts one group’s event proportion from the other’s. The recalculated contrast is oriented as acoziborole relative to placebo, so a negative value corresponds to a lower observed proportion in the acoziborole group. The sponsor reports an excess rate of -1.5 in its own analysis.

What does a risk difference describe?

A risk difference expresses the absolute separation between two event proportions. Unlike a relative measure, it is not expressed as a multiple of one group’s risk. Its sign depends on the order used for the subtraction, so the comparison direction matters. Here, the recalculated comparison is acoziborole minus placebo, while the sponsor’s reported measure is labelled excess rate. The sponsor’s own estimate and interval are the registered analysis; the recalculation is a simple unadjusted check based on the posted summary counts.

What does a confidence interval add?

A confidence interval presents a range of values compatible with the data and the statistical model used to calculate it. In repeated samples under the model’s assumptions, intervals constructed by the same method would capture the true parameter at the stated confidence level at the corresponding long-run rate. It is not a probability statement about this particular interval or about the true value lying within it. For this comparison, the sponsor’s 95% interval runs from -7.2 to 3.7, and the recalculated 95% interval runs from -0.069 to 0.040. Both include the no-difference value. The intervals therefore do not rule out either direction of difference.

What does the p-value tell the reader?

The recalculated unadjusted p-value is 0.592. In general, a p-value measures the compatibility of the observed data, or more extreme data, with a specified null model, assuming the model and test conditions apply. It is not the probability that the null hypothesis is true, and it does not measure the size or importance of a difference. The registry does not report a sponsor p-value for this primary comparison in the posted analysis details.

Why distinguish the sponsor analysis from a recalculation?

The sponsor’s estimate is the analysis reported in the registry. A recalculation from summary counts can help readers understand the comparison, but it may not reproduce adjustments, model choices, or conventions used in a full analysis. The available recalculation is explicitly unadjusted. The registry record does not report a method for the sponsor’s excess-rate analysis in the posted details, so it is not possible to establish all methodological differences from the summary record alone. No discrepancy is flagged, but that does not establish that every unreported analytic detail is identical.

Why can event counts conceal differences?

Any-TEAE counts reduce each participant’s experience to whether at least one event occurred. This makes the endpoint easy to summarize, but it discards information about multiple events in the same participant, event timing, duration, severity, and clinical category. Separate adverse-event outcomes are needed to examine those features. The registry lists secondary outcomes including occurrence of adverse events and changes from baseline in several biochemistry parameters, but the primary comparison remains the participant-level occurrence of any TEAE.

These explanations describe general statistical concepts. The exact test, confidence-interval procedure, treatment of missing observations, and any covariate adjustment for the sponsor’s primary analysis are not reported in the registry record.

10. Confidence Intervals and Precision

The sponsor-reported excess rate is -1.5, with a 95% confidence interval from -7.2 to 3.7. The recalculated unadjusted risk difference is -0.015, with a 95% confidence interval from -0.069 to 0.040. The sponsor’s interval spans negative and positive values, as does the recalculated interval. Both include the value corresponding to no difference between groups, so the results do not pin down the direction of the difference with high precision.

Precision concerns the width and location of an estimate’s uncertainty interval, not whether an estimate is statistically significant on its own. An interval that includes both directions allows for multiple explanations of the observed data: a lower event rate with acoziborole, little or no difference, or a higher event rate. The interval does not assign equal probability to each value, nor does it establish that all values inside it are equally plausible.

The posted group sizes are 906 in the acoziborole safety set and 300 in the placebo safety set. Unequal group sizes can affect the precision of a between-group comparison, and the number of participants with events also contributes to the information available. The registry record does not provide a detailed precision target or the original sample-size justification, so the achieved precision cannot be judged against a reported design objective. The confidence interval should be considered together with the endpoint definition, analysis population, and limitations in the registry’s reporting of analysis methods.

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 for participants per arm, not total events. They use the observed effect as a starting point and consider planning for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. The listed 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 the stated fraction of the observed effect.

For 80% power, the planning values are 12,455 participants per arm for 100% of the observed effect, 22,274 for 75%, and 50,409 for 50%. For 90% power, the corresponding values are 16,673, 29,817, and 67,482 participants per arm. In plain terms, the 80% column represents the planned probability of detecting the chosen effect under the stated assumptions if that effect is real; the 90% column uses a higher target probability of detection. Smaller effects need more participants to distinguish them from random variation at the same significance level and power target.

These are planning illustrations calculated from the observed effect, not the original trial’s design justification. They are not observed power. The registry record does not report the trial’s original sample-size assumptions. The figures also rely on the stated equal-allocation assumption, whereas the posted safety-set group sizes are unequal. Treat the values as hypothetical planning quantities under their stated assumptions, rather than as a description of the study’s actual allocation or as evidence about the result.

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 = 0.230; treatment proportion p₁ = 0.215; average p̄ = 0.223.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5883 = 1.1531.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5882 = 0.4951.
4. n = (1.1531 + 0.4951)² / (-0.0148)² = 12,454.7, rounded up to 12,455 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 <- 0.23                          # control proportion
p1 <- 0.21523178807947                          # 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(5256017)
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 = 12,455 (80% power), 16,673 (90% power)
 75% of observed effect: n per arm = 22,274 (80% power), 29,817 (90% power)
 50% of observed effect: n per arm = 50,409 (80% power), 67,482 (90% power)
power.prop.test: 12454.7 
Simulated power at n = 12,455 per arm: 0.794 (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. Analyses Reported by the Sponsor

The sponsor’s posted primary analysis reports an excess rate of -1.5, with a 95% confidence interval from -7.2 to 3.7. The registry does not list a p-value for this analysis. A simple unadjusted recalculation from the posted summary counts gives a risk difference of -0.015, with a 95% confidence interval from -0.069 to 0.040 and an unadjusted p-value of 0.592.

The recalculation is a check based on the summary event counts and group denominators; it is not a replacement for the sponsor’s analysis. The registry does not report the sponsor’s statistical method in the posted analysis details, so the full calculation cannot be reconstructed from the record. No discrepancy is flagged between the reported analysis and the recalculation. Both estimates have intervals that include no difference and extend in both directions. The sponsor’s analysis is the registered result to prioritize when describing what the study reported.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists 42 outcome measures, 22 analyses, and 27 secondary outcomes posted. These are different counts associated with outcomes and analyses; they should not be treated as interchangeable measures of the number of statistical tests. The primary outcome is occurrence of any TEAE, while the registry also lists secondary outcomes such as adverse events and changes from baseline in biochemistry parameters. With multiple outcomes or comparisons, the chance of at least one apparently unusual result can increase if each is assessed separately.

The registry record does not report whether the trial used a multiplicity adjustment, a hierarchy for testing outcomes, or a prespecified strategy for interpreting multiple secondary comparisons. It is therefore not possible from the posted information to determine whether secondary-outcome p-values, if considered, were adjusted or how they were intended to support inference. The primary safety result should be distinguished from exploratory or additional outcome findings unless the registry record documents a formal testing plan.

The primary analysis population is described: participants who received at least one tablet, classified by actual treatment received and confirmed by drug concentration data. This is a safety set, rather than a stated intention-to-treat population. The record does not report how missing outcome observations were handled, whether any participants were excluded from particular analyses, or whether sensitivity analyses assessed the effect of missingness. It also does not report the reasons for missing data or completeness of follow-up by group.

These omissions matter because outcome definitions, analysis populations, and missing-data handling can influence estimates and their uncertainty. The registry’s summary is sufficient to identify the posted primary counts and sponsor estimate, but it does not provide enough detail to reproduce all analysis decisions or assess their robustness. The protocol’s original statistical analysis plan and its methods for multiplicity and missing data are not reported in the registry record.

15. 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 1% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: appendicitis (0.3%), malaria (0.3%), wound infection (0.3%), abortion induced (0.3%), uterine prolapse (0.1%).

The serious adverse event summary reports 3 affected participants among 906 at risk in the acoziborole group and 4 among 300 at risk in the placebo group. The registry also reports 0 deaths in the acoziborole group and 1 in the placebo group. These are group-specific counts as posted; they should be read separately from the broader any-TEAE endpoint, which includes events not necessarily classified as serious.

The registry lists appendicitis, malaria, wound infection, and abortion induced at 0.3% each among the top serious-event terms. Uterine prolapse and vaginal haemorrhage are listed at 0.1% each. These entries describe the posted serious-event terms and percentages, but they do not establish that an event was caused by the study treatment. The summary does not provide enough detail to assess event onset, duration, relationship assessment, or individual clinical course. Counts from a safety summary are descriptive and should not be interpreted as a causal comparison on their own.

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

The posted primary results describe the occurrence of any TEAE in the safety sets: 195 of 906 participants in the acoziborole group and 69 of 300 in the placebo group. The sponsor’s estimated excess rate was -1.5, with a 95% confidence interval from -7.2 to 3.7. The interval includes no difference and permits values in either direction. The unadjusted recalculation gives the same broad message of uncertainty, with a risk difference of -0.015 and a 95% confidence interval from -0.069 to 0.040.

This result does not establish that the groups had identical safety profiles. A confidence interval that includes no difference can also include differences in either direction, and the estimate’s precision limits how firmly the underlying contrast can be described. Conversely, the result does not show that every type of adverse event occurred at the same frequency. The any-TEAE endpoint combines event types, and the serious-event summary is a separate descriptive view.

The endpoint is limited to the defined safety population and follow-up period, from Day 1 through the Month 4 visit. It does not describe later events, the number of events per participant, or all event-specific features. The registry record does not report the exact operational TEAE definition, detailed missing-data handling, or the full sponsor analysis method. Those limitations constrain how completely the estimate can be interpreted or reproduced.

The study’s question is also specific to seropositive participants without parasites detected by microscopy. The posted primary outcome is safety, not confirmation of infection, parasite clearance, or another efficacy measure. The result should not be extended beyond the reported population, endpoint, and observation period. It is a statistical description of the registry’s posted comparison, not a general conclusion about treatment in other populations or settings.

17. Why This Trial Matters Statistically

This trial raises a statistical question that differs from a conventional comparison in participants with parasitologically confirmed disease. The registry describes seropositive participants without parasites detected by microscopy, a group for whom confirmation may be difficult. In that setting, the study’s stated focus was to collect safety and tolerability information. The primary endpoint therefore summarizes whether participants experienced any TEAE during follow-up rather than measuring a treatment response against confirmed infection.

Statistically, the comparison illustrates why a point estimate should be read with its confidence interval. The sponsor estimate is -1.5, but its 95% interval extends from -7.2 to 3.7. The range includes no difference and values on both sides, so the point estimate alone does not provide a precise account of the possible between-group contrast. A non-significant-looking result or a p-value, considered alone, cannot establish equivalence or rule out meaningful differences.

The record also makes the analysis population important: the primary safety comparison is based on participants who received at least one tablet, classified by actual treatment received and confirmed by drug concentration data. Readers should not assume that this definition is the same as an intention-to-treat analysis. Finally, the registry lists multiple outcomes and analyses but does not report multiplicity procedures or detailed missing-data methods. Clear reporting of those choices would help readers evaluate how the primary result fits within the broader set of safety assessments.

18. 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 sponsor’s statistical method for the excess-rate estimate, the detailed operational definition of a TEAE, or the method used to construct the confidence interval. A simple unadjusted recalculation from summary counts cannot determine whether the sponsor used additional adjustments or conventions. The record does not flag a discrepancy, but not all analysis details can be checked from the posted summary.

The primary endpoint reduces each participant’s experience to whether at least one TEAE occurred. It does not show event frequency per participant, duration, severity, timing, or the distribution of specific event types. The serious adverse event summary provides additional counts and listed terms, but does not give detailed case information or establish treatment causality. The reported follow-up ends at the Month 4 visit, so the primary result does not describe events after that period.

The registry record does not report missing-data handling, follow-up completeness by group, sensitivity analyses, multiplicity adjustment, or the original sample-size justification and design assumptions. It also does not provide the full protocol or statistical analysis plan in the information used for this summary. These gaps limit assessment of robustness and prevent a complete reconstruction of the planned analysis.

The posted analysis population is a safety set defined by treatment received and drug concentration confirmation. It may not answer the same question as an analysis based on randomized assignment. The registry reports the study as randomized, but the posted primary result is explicitly tied to the safety set. Interpretation should therefore remain bounded to that stated population and to the registry’s reported outcome and timeframe.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Safety and Tolerability Study of Acoziborole in g-HAT Seropositive Subjects — NCT05256017.
• Registry record last updated 2025-03-20; status last verified 2025-02.
• Results first posted 2025-03-20.
• 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.

22. Record Summary

The registry record describes a completed, randomized, quadruple-masked, parallel-group study with placebo control and Phase 2 and Phase 3 designations. It lists enrollment as 1208 and reports a safety analysis among 906 participants assigned in the posted results to acoziborole and 300 to placebo. Participants were g-HAT seropositive without parasites detected by microscopy in a body fluid.

The primary endpoint was occurrence of any TEAE from Day 1 through the Month 4 follow-up visit. The sponsor reported an excess rate of -1.5, with a 95% confidence interval from -7.2 to 3.7. The interval includes no difference and leaves uncertainty about the direction of the comparison. The posted summary supports a description of this safety endpoint in the stated population and period; it does not resolve all event-specific safety questions or report an efficacy outcome.