A Comprehensive HIV Prevention Package for South African Adolescent Girls and Young Women: IMARA SA: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Comprehensive HIV Prevention Package for South African Adolescent Girls and Young Women: IMARA SA (NCT05504954), a randomized na study. The primary outcome is Number of AGYW Who Tested Positive for a Sexually Transmitted Infection (STI).

2. Clinical Question

This was a pilot study intended to assess feasibility in preparation for a randomized controlled trial, while also examining preliminary outcomes. The registry also describes interest in HIV testing and counseling, pre-exposure prophylaxis uptake, implementation, and other behavioral outcomes. The primary endpoint is narrower: a positive test for either of two specified STIs at follow-up. The registry identifies the follow-up timeframe for that endpoint as 8-17 months post baseline. The brief summary describes assessments approximately 6 months after randomization, so the endpoint-specific timeframe is the appropriate reference for interpreting this particular result.

3. Trial Design

The registry describes IMARA-SA as a randomized, single-masked, parallel-group behavioral study. Participants were allocated to the IMARA-SA intervention arm or the health-promotion control arm. The record gives enrollment as 61 and status as completed. It identifies University of Illinois Chicago as the sponsor. The phase is listed as NA, which is not a clinical drug-development phase designation in this record.

The intervention was adapted from an evidence-based HIV-prevention program for adolescent girls and young women and their female caregivers. The registry describes a group workshop with activities conducted jointly and separately for mothers and daughters. Both arms received a behavioral intervention: IMARA-SA in the intervention arm and health promotion in the control arm. The record does not report which people were masked, how masking was implemented, or whether masking was maintained throughout follow-up.

The brief summary describes baseline assessment and follow-up assessment approximately 6 months later. Measures included surveys, testing for chlamydia and gonorrhea, and assessment of HIV testing and counseling and a 1-month PrEP prescription. The primary endpoint has its own stated timeframe of 8-17 months post baseline. These descriptions do not establish that every participant completed every assessment or that follow-up occurred at the same time for all participants.

The primary endpoint denominator is those who completed STI testing at follow-up, subject to the record's stated exclusion of one participant who completed that test but did not receive STI treatment at baseline. The registry lists 18 tested participants in the IMARA-SA arm and 16 in the control arm for this endpoint. These are endpoint-specific denominators and should not be read as the total randomized population. Details of the original sample-size justification, allocation concealment, and the trial's prespecified statistical analysis plan are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: 61 dyads were enrolled. Two dyads were withdrawn due to ineligibility. A total of 118 participants (59 dyads) were allocated to either IMARA-SA or the Health Promotion Control Arm.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Data represents AGYW. Denominator is those who completed STI testing at follow-up. Excludes one participant who completed STI testing at follow-up but did not receive STI treatment at baseline.

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: Adolescent Girls and Young Women (AGYW, N=59) and Female Caregivers (FC, N=59) contributed data for Age, Sex, Region of Enrollment, Highest Education Achieved, and Supporting Self Financially variables. AGYW (N=59) contributed data for Type of Female Caregiver, Sexual Behavior, HIV Testing and Counseling, Sexually Transmitted Infections, Prescribed PrEP, and Adherence to PrEP variables.

6. Primary Endpoint

The registry lists the primary outcome as Number of AGYW Who Tested Positive for a Sexually Transmitted Infection (STI), measured over 8-17 months post baseline.

The primary endpoint counts AGYW with a positive test for at least one of two sexually transmitted infections: chlamydia and/or gonorrhea. It is a participant count, not a count of positive tests; a participant with both infections would still meet the stated definition of a positive result for at least one STI. The record specifies that the denominator is participants who completed STI testing at follow-up, with one additional exclusion described for a participant who did not receive STI treatment at baseline.

The posted count is 4 among 18 participants tested in the IMARA-SA arm and 6 among 16 tested in the health-promotion control arm. Because the endpoint is based on follow-up testing, it describes detected infections in the tested groups at that time. It does not, on its own, describe when an infection began, whether a participant had an infection at baseline, or infection status among participants without follow-up testing.

General: A biological test endpoint can complement self-reported behavior measures because it records a test result rather than relying solely on a participant's account. The measure is useful for comparing the recorded follow-up outcomes between randomized groups, while interpretation still depends on who was tested, the timing of testing, and the analysis used. The registry describes the endpoint timeframe as 8-17 months post baseline.

7. Results Posted in the Registry

• IMARA-SA Intervention Arm: 22.2% (4/18) versus 37.5% (6/16) on control; risk difference -15.3 percentage points (95% CI -45.8 to 15.2), risk ratio 0.59 (0.20–1.73); unadjusted two-proportion z-test p = 0.329.

8. Statistical Interpretation

9. Statistical Methods Explained

General: A randomized parallel-group design assigns participants to separate intervention groups and compares outcomes between those groups. Random allocation is intended to make the groups comparable on average, including with respect to factors that were not measured. In a small pilot, however, chance imbalances can remain, and the data may be too limited for precise estimates. The registry identifies randomized allocation and a parallel model, but details of allocation concealment and the exact randomization procedure are not reported in the registry record.

What does the primary count represent?

The endpoint is a binary participant-level outcome: each tested participant either met the definition of a positive result for at least one of chlamydia or gonorrhea, or did not. The posted arm summaries give both the event count and the tested denominator. The simple recalculation compares those observed group counts without regression adjustment. It is an unadjusted comparison, not the sponsor's regression result.

General: For binary outcomes, a risk difference describes the difference between the proportions with an event in two groups, while an odds ratio compares the odds of an event. They use different scales and can produce estimates that are not numerically interchangeable. The simple recalculation also reports a risk-difference interval and an unadjusted p-value. The registry does not specify the confidence level for that recalculated interval, so the interval's level is not reported in the registry record.

What does the logistic regression add?

The sponsor-reported analysis is labeled regression, logistic, and gives an odds ratio, a 95% confidence interval, and a p-value. General: Logistic regression models the log odds of a binary outcome and can include explanatory variables to adjust a comparison. Whether an estimate is adjusted, and which variables are included, depends on the model specification. The registry does not report the covariates, model diagnostics, or other specification details. Therefore, the reported odds ratio can be described, but the extent and nature of any adjustment cannot be reconstructed from the registry record.

The odds ratio is 0.26, with a 95% confidence interval from 0.04 to 1.59, and p = 0.15. General: An odds ratio of 1 represents equal odds under the comparison being made. An interval that includes 1 means that the data do not rule out that reference value at the stated confidence level. The interval also permits values on either side of 1, underscoring that the estimate does not sharply determine the direction or magnitude of the association.

Why do the reported and recalculated results differ?

The recalculation is a direct, unadjusted comparison of the posted counts and denominators. The sponsor's analysis is a logistic regression. A regression model may use information or assumptions that differ from a simple group-summary calculation, but the covariates and full model details are not reported. The registry's reported analysis therefore takes precedence as the sponsor's own analysis, while the recalculation is best treated as a transparent descriptive check based on the posted summary statistics. The record marks no discrepancy between the posted result and the recalculation.

General: A p-value is calculated under a null model and summarizes how unusual the observed data, or more extreme data, would be if that model were correct. It is not an effect-size measure and does not quantify clinical importance. The recalculated unadjusted p-value is 0.329; the sponsor-reported p-value is 0.15. These values answer questions within their respective analyses and should not be treated as interchangeable or as proof that the groups are the same.

What assumptions accompany the planning illustrations?

The sample-size planning illustrations are based on the observed effect and assume a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation. Each planning scenario uses a stated fraction of the observed effect as the effect to detect. These are planning assumptions for the illustrations, not documented assumptions from the original trial design. The original design's sample-size rationale and any prespecified effect size are not reported in the registry record.

General: A normal approximation uses a continuous reference distribution to approximate the behavior of a test statistic. Whether that approximation is adequate depends on the design and data. The registry's planning description names the approximation but does not report further simulation or assumption checks. The endpoint counts are modest, so results and planning illustrations should be understood as uncertain rather than as precise forecasts for a future study.

What analysis details remain unavailable?

The registry does not report the original statistical analysis plan, the method used to handle missing outcome data, the primary analysis population definition beyond the endpoint denominator description, interim analyses, or a multiplicity strategy. It also does not state whether analyses were prespecified before outcomes were examined. These omissions limit the ability to evaluate whether the posted analysis followed a protocol-defined approach or how selective reporting was managed. General: Multiple outcomes and analyses can raise the chance of at least one apparently notable result when many tests are considered; a multiplicity strategy specifies how that issue is addressed. Without a reported strategy, the role of multiplicity cannot be determined.

10. Confidence Intervals and Precision

The sponsor's logistic regression estimate is an odds ratio of 0.26, with a reported 95% confidence interval from 0.04 to 1.59. The interval is wide and includes 1, the reference value for equal odds. It therefore accommodates a range of possible associations, including values below and above the reference. The estimate alone should not be read as a precise measure of the difference between the groups.

General: A confidence interval expresses uncertainty in an estimate under the assumptions of the method used to construct it. A narrower interval indicates greater precision on that scale, while a wider interval indicates more uncertainty. A confidence interval is not a guarantee that the true value lies within the particular interval, nor does a 95% interval mean there is a 95% probability that the fixed true value is inside it.

The simple unadjusted recalculation gives a risk-difference estimate and interval whose endpoints fall on opposite sides of zero. This indicates that the interval includes no difference as well as differences in either direction. The confidence level for this recalculated interval is not reported in the registry record. The recalculated unadjusted p-value is 0.329. The sponsor's regression estimate has its own reported 95% interval and p-value; those should be interpreted as results from a different analysis rather than as a correction to the unadjusted result.

Precision is constrained by the number of participants with endpoint testing: 18 in the intervention arm and 16 in the control arm. The enrollment count is 61, but not all enrolled participants are included in the primary endpoint denominators. The registry does not report why participants were not included in endpoint testing beyond the specific exclusion noted, or a missing-data analysis that would quantify its consequences. General: When only a limited number of outcomes contribute information, estimates can vary substantially with the observed results, and confidence intervals can remain broad even when a point estimate appears to favor one group.

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 illustrations report participants per arm for 80% power and participants per arm for 90% power. They are not total sample sizes for both arms. The scenarios are labeled as planning for 100%, 75%, or 50% of the observed effect. The corresponding figures are 140 and 187 participants per arm for planning around 100% of the observed effect; 258 and 345 for 75% of the observed effect; and 600 and 803 for 50% of the observed effect, with the 80% power figure stated first in each pair and the 90% figure second.

The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect equal to the stated fraction of the observed effect. The registry does not report the original trial's sample-size assumptions or justification. These planning numbers are illustrations based on the observed result, not a description of how enrollment was originally chosen.

General: Power is the probability that a statistical test will detect an effect of a specified size under its assumptions, if that effect is present. The 80% and 90% columns therefore describe different target probabilities of detecting the selected effect; the higher target generally requires more participants under the same assumptions. Smaller effects are harder to distinguish from random variation and require more participants, which is reflected in the larger planning figures for the smaller fractions of the observed effect. This is not observed power. These estimates are planning illustrations, not evidence about what the completed study was capable of detecting after the results were known.

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 = 0.375; treatment proportion p₁ = 0.222; average p̄ = 0.299.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6472 = 1.2685.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6381 = 0.5371.
4. n = (1.2685 + 0.5371)² / (-0.1528)² = 139.7, rounded up to 140 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 <- 0.375                          # control proportion
p1 <- 0.222222222222222                          # 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(5504954)
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 = 140 (80% power), 187 (90% power)
 75% of observed effect: n per arm = 258 (80% power), 345 (90% power)
 50% of observed effect: n per arm = 600 (80% power), 803 (90% power)
power.prop.test: 139.7 
Simulated power at n = 140 per arm: 0.803 (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 registry reports the sponsor's analysis as logistic regression, with an odds ratio of 0.26, a 95% confidence interval from 0.04 to 1.59, and p = 0.15. This is the sponsor's own analysis and takes precedence over the simple unadjusted recalculation when describing the registry's reported inferential result. The reported interval includes 1, and the estimate is therefore imprecise with respect to the no-association reference.

The recalculation compares the posted event counts and denominators without regression adjustment. It gives an unadjusted p-value of 0.329 and a risk-difference interval spanning zero. The analyses use different methods and effect scales, so their point estimates and p-values need not match. The registry does not report which covariates, if any, were included in the logistic regression, nor does it give other model details that would explain the difference.

The record marks no discrepancy between the reported result and the recalculation. That does not make the methods identical: it means the record does not flag a discrepancy. The sponsor's model result and the simple recalculation should each be interpreted according to the analysis that generated it, with the sponsor-reported analysis treated as the primary reported inferential result.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists 18 outcome measures and 7 analyses. It also identifies five secondary outcomes: AGYW's report of adherence to PrEP, condom use at last sex, consistency of condom use, substance use during sex in the past 6 months, and number of partners in the past 6 months. The record does not report a multiplicity adjustment or a strategy for controlling the overall chance of false-positive findings across outcomes and analyses.

General: When several outcomes or statistical tests are examined, the chance of obtaining at least one result that appears unusual under a null model can increase. A prespecified multiplicity approach can define which comparisons are confirmatory and how uncertainty is interpreted across them. Since such an approach is not reported in the registry record, it is not possible to determine whether the primary endpoint was treated differently from other outcomes, or how secondary findings should be evaluated as a family.

The endpoint description gives a specific denominator: AGYW who completed STI testing at follow-up, excluding one participant who completed testing but did not receive STI treatment at baseline. The registry does not report the number of participants with missing primary endpoint data by randomized arm beyond the endpoint-specific counts and denominators. Nor does it describe imputation, weighting, sensitivity analyses, or another method for handling missing outcome data. The consequences of missing follow-up testing therefore cannot be assessed from the record.

The primary analysis population is not described as intention-to-treat or per-protocol. The registry identifies the tested population for the endpoint but does not give a broader population definition for the sponsor's regression analysis. It does not report interim analyses, stopping rules, or whether the statistical methods were prespecified. These details are relevant to assessing how the analysis was conducted and how much weight to place on a particular result, but they are not reported in the registry record.

These gaps do not establish that the study used an inappropriate method; they limit what can be verified from the public record. General: Transparent reporting of analysis populations, missing-data methods, and multiplicity plans helps readers distinguish a primary confirmatory result from exploratory findings and evaluate the assumptions behind reported estimates.

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 0% reporting threshold.

The registry reports serious adverse events in 0 of 29 participants at risk in the IMARA-SA arm and 0 of 30 participants at risk in the health-promotion control arm. It also reports 0 other adverse events in each of those respective groups, and 0 deaths in both groups. No top serious adverse event terms are listed.

These figures describe the adverse-event entries recorded for the populations identified as at risk. The safety denominators are different from the primary STI endpoint denominators, which are 18 and 16 participants tested at follow-up. They should not be substituted for one another or interpreted as the number completing the primary endpoint.

General: A report of zero events means no events were recorded in the stated group and reporting category; it does not prove that an event is impossible or that no unrecorded event occurred. The registry does not provide additional detail about adverse-event definitions, collection procedures, event timing, or the monitoring period. The listed counts therefore describe the posted safety record without establishing a broader safety conclusion.

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

The posted primary endpoint counts are 4 positive STI tests among 18 tested participants in the IMARA-SA arm and 6 among 16 tested participants in the health-promotion control arm. The simple unadjusted recalculation does not provide precise evidence distinguishing the groups: its p-value is 0.329, and its risk-difference interval spans zero. The sponsor-reported logistic regression gives an odds ratio of 0.26, with a 95% confidence interval from 0.04 to 1.59 and p = 0.15. That interval includes the no-association reference and allows a range of possible effects.

These results do not establish that IMARA-SA reduces STI outcomes, and they do not establish that the groups are equivalent. They show the observed follow-up test counts in the analyzed population and the uncertainty reflected by the two reported analyses. Because this was a pilot study with limited endpoint testing, the estimates are not precise enough to support a definitive conclusion about the magnitude or direction of a difference.

The endpoint specifically concerns a positive test for chlamydia and/or gonorrhea at follow-up. It does not measure all sexually transmitted infections, HIV incidence, HIV testing uptake, PrEP uptake, or every behavior listed among the secondary outcomes. The registry describes these as other interests or measures, but their results are not part of the primary endpoint counts presented in the record details.

The study's pilot purpose also matters. Feasibility and implementation were part of the stated aims, alongside preliminary examination of effectiveness. The registry does not report a formal feasibility result in the registry record described for this endpoint, so the STI count alone cannot answer whether implementation was acceptable or feasible. Nor can the endpoint establish what outcomes would occur in a larger or different population. General: A pilot estimate can inform the design and uncertainty of later research, but it is not a substitute for a larger confirmatory comparison.

17. Why This Trial Matters Statistically

This study illustrates how a randomized pilot can combine an intervention comparison with feasibility aims. The intervention is multilevel in the sense that the registry describes activities for AGYW and female caregivers, rather than an individual-only behavior-change program. The control group also received a behavioral health-promotion intervention, so the comparison is between two program approaches rather than between intervention and no intervention.

Statistically, the distinction between the observed counts and the inferential estimates is important. The counts are direct descriptions of the participants tested, while the unadjusted recalculation and logistic regression summarize the comparison using different statistical approaches. The sponsor's reported odds ratio has a broad 95% confidence interval that crosses the no-association reference. This demonstrates why a point estimate alone is not enough to convey certainty.

The endpoint denominator also makes clear that randomized enrollment and outcome availability are not the same quantity. The primary result is limited to those who completed STI testing under the record's endpoint definition. Knowing how many participants were tested and how the denominator was defined is essential to judging what population the result describes. Missing-data methods and analysis-population definitions are not reported, limiting further assessment.

The planning illustrations show the consequences of basing future sample-size scenarios on observed effects of different sizes. Under the stated assumptions, smaller target effects require larger participant counts per arm. These are not the original trial's design calculations and should not be mistaken for observed power or evidence of a required enrollment target for a future study. Their statistical value is as planning illustrations, conditional on the assumptions stated in the record.

Together, these features make the study useful for understanding the reporting and interpretation challenges of early clinical research: small endpoint groups, multiple outcomes, different analytic methods, and uncertainty about missing data and prespecification. The statistical reading should remain proportional to the pilot's scope and the precision of its estimates.

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 primary endpoint is based on a subset of the enrolled population: 18 participants tested in the IMARA-SA arm and 16 in the control arm. The registry specifies that participants who completed follow-up STI testing form the denominator and notes one exclusion related to baseline STI treatment. It does not report additional reasons for missing testing, missingness by other participant characteristics, or a sensitivity analysis. The outcome may therefore describe the tested participants more directly than all randomized participants.

The endpoint timeframe is recorded as 8-17 months post baseline, while the brief summary describes follow-up assessments approximately 6 months later. The registry does not explain the relationship between these descriptions or provide individual timing information. This limits assessment of variation in exposure or follow-up time for the endpoint.

The study enrolled 61 participants and is described as a pilot. The primary endpoint counts are modest, and the sponsor-reported 95% confidence interval is broad. The original sample-size justification, prespecified target effect, and statistical analysis plan are not reported in the registry record. Planning illustrations based on the observed effect should not be treated as the trial's original design rationale.

The registry does not report which individuals were masked, allocation concealment, covariates in the logistic regression, model diagnostics, or a multiplicity strategy. It also does not report whether the primary analysis was intention-to-treat, how missing outcome data were handled, or whether interim analyses were conducted. These omissions prevent a full audit of the analysis and reporting process.

The primary endpoint covers chlamydia and gonorrhea testing at follow-up, not every outcome the study set out to explore. The registry lists other behavioral and prevention outcomes, but those cannot be inferred from the STI counts. These limitations qualify how broadly the primary result can be interpreted; they do not by themselves determine the direction or validity of the observed result.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: A Comprehensive HIV Prevention Package for South African Adolescent Girls and Young Women: IMARA SA — NCT05504954.
• Registry record last updated 2025-08-22; status last verified 2025-08.
• Results first posted 2025-08-22.
• 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 NCT05504954, titled “A Comprehensive HIV Prevention Package for South African Adolescent Girls and Young Women: IMARA SA,” as a completed randomized, single-masked, parallel behavioral pilot study sponsored by University of Illinois Chicago. Enrollment was 61. Participants were assigned to IMARA-SA or a health-promotion control intervention.

The primary endpoint counts AGYW who tested positive for chlamydia and/or gonorrhea at 8-17 months post baseline. The posted counts are 4 of 18 tested in the intervention arm and 6 of 16 tested in the control arm. The sponsor-reported logistic regression gives an odds ratio of 0.26, a 95% confidence interval from 0.04 to 1.59, and p = 0.15. The simple unadjusted recalculation reports p = 0.329.

The record describes feasibility and preliminary effectiveness as study aims. Original sample-size justification, full statistical analysis details, missing-data methods, and multiplicity procedures are not reported in the registry record.