Cervical Cancer Self-Collection for Southeast Asian Immigrant and Refugee Women: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Cervical Cancer Self-Collection for Southeast Asian Immigrant and Refugee Women (NCT05286749), a randomized na study. The primary outcome is Number of Participants Who Obtain or Self-Report Future Desire for Cervical Cancer Screening.

2. Clinical Question

3. Trial Design

The registry describes a randomized, parallel-group study with single masking. It lists the trial as completed and records enrollment of 153. The brief summary states a total sample size of 250 participants as part of the study description; the registry’s enrollment field records 153. The registry record does not explain the relationship between those figures.

Participants were assigned to a control workshop or an intervention workshop. Both workshops covered standard cervical screening, including Pap testing and clinician-collected HPV testing. The intervention workshop added education about HPV-only screening using a participant-collected vaginal swab. The study description therefore compares a broader educational offering that includes self-collection with education focused on standard clinician-collected approaches.

The registry identifies the design as parallel, meaning the groups were compared as separate arms rather than as repeated treatment periods for each participant. The record labels the study single-masked, but does not report who was masked or how masking was implemented. Details of the randomization sequence, allocation concealment, study sites beyond Wisconsin, and the exact eligibility criteria are not reported in the registry record.

The primary outcome timeframe is up to 1 day. The registry lists participant satisfaction with educational workshops and willingness to use an HPV self-collection device as secondary outcomes. The record gives start and primary completion dates of 2022-08-13 and 2024-02-10, respectively. It records no trial phase beyond NA, which is consistent with the nature of this behavioral and screening-education study rather than a drug-development phase.

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

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants Who Obtain or Self-Report Future Desire for Cervical Cancer Screening, measured over up to 1 day.

The primary endpoint is the number of participants who obtain or self-report a future desire for cervical cancer screening. The registry description includes participants who engage in or seek screening through services offered after workshop education and participants who say they intend to follow up through a community health care provider. The stated timeframe is up to 1 day.

This endpoint addresses the study’s central question about participation and willingness to pursue screening after education. Counting both engagement and reported future desire captures more than completed screening alone. That breadth is important when the educational program aims to inform participants about screening options and support their next steps. At the same time, the combined endpoint does not separate actual screening from stated intention in the posted summary. Those outcomes have different meanings: obtaining screening documents an action, whereas reporting a desire to follow up records an intention.

The endpoint is reported as a count of participants in each group. The registry describes summary statistics of participants engaging or seeking screening, but does not report a more detailed operational definition for classifying an individual participant. It also does not provide a separate result for the components of the endpoint. Readers should therefore interpret the comparison as applying to the registry’s combined count, rather than as a direct estimate of completed screening alone.

7. Results Posted in the Registry

• Intervention: 91.0% (71/78) versus 78.7% (59/75) on control; risk difference 12.4 percentage points (95% CI 1.1 to 23.6), risk ratio 1.16 (1.01–1.33); unadjusted two-proportion z-test p = 0.032.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Number of Participants Willing to Use HPV Self-collect Device for Their Cervical Cancer Screening

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Intervention: 1.3% (1/78) versus 8.0% (6/75) on control; risk difference -6.7 percentage points (95% CI -13.3 to -0.1), risk ratio 0.16 (0.02–1.30); unadjusted two-proportion z-test p = 0.047.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Intervention than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry lists two secondary outcomes: satisfaction with educational workshops and willingness to use the HPV self-collection device for cervical screening. A result is posted for willingness, while a satisfaction result is not reported in the registry record. The available secondary information is therefore incomplete, and the pattern across all named secondary outcomes cannot be fully characterized.

Willingness to use a self-collection device is related to the intervention’s added educational content, but it is not the same as the primary endpoint. The primary outcome combines screening engagement or seeking with self-reported future desire for screening; willingness to use a particular device addresses acceptance of one method. A finding on one measure does not establish the same pattern on the other. Neither secondary outcome should be used to redefine what the primary count measures.

The registry posts an unadjusted comparison for willingness. Because it is secondary and unadjusted, it carries less evidential weight than a prespecified primary comparison interpreted within a complete analysis plan. If many outcomes or comparisons are examined, the chance of at least one apparently notable result can increase. Adjusting for multiplicity or using a clear hierarchy of outcomes can address that issue, but the registry does not report such a plan or adjustment.

The absent satisfaction result also limits interpretation: readers cannot assess whether participants’ reactions to the workshops aligned with screening behavior or stated intentions. The record does not report why the result is absent, whether it was not measured, or whether it was measured but not posted. The secondary outcomes are best treated as supplementary signals, not as independent confirmation of the primary comparison.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Participant Satisfaction With Educational Workshops Survey Scores
• Number of Participants Willing to Use HPV Self-collect Device for Their Cervical Cancer Screening

9. Statistical Interpretation

10. Statistical Methods Explained

What does randomization contribute?

Random assignment is intended to make the groups comparable, on average, with respect to both measured and unmeasured characteristics at the start of a study. That helps an outcome difference be interpreted as an effect associated with assignment to the intervention strategy, rather than merely as a difference between groups that chose different approaches. Randomization does not guarantee that every characteristic will be balanced, especially in a study of this size. The registry does not report baseline characteristics, details of the randomization procedure, or an adjusted analysis, so the extent of balance and the handling of any imbalances cannot be assessed from the record.

The parallel design means that the two groups receive different workshop approaches and are compared over the stated outcome timeframe. This avoids interpreting the groups as if they were the same participants exposed to both approaches. The registry calls the study single-masked but does not identify who was masked. In a workshop study, participants and workshop facilitators may know which content is being delivered; whether any outcome assessor or analyst was masked is not reported in the registry record.

How should counts and ratios be understood?

The primary outcome is binary at the participant level: a participant is counted if they meet the registry’s outcome definition, and the group result is expressed as a count. A risk is the proportion with the outcome in a group. The risk ratio compares those proportions, while the odds ratio compares the odds of the outcome. A risk ratio of 1 would indicate equal risks; a value above 1 indicates a higher risk in the intervention group for an outcome coded as occurring. The posted risk ratio is 1.157.

Odds are the probability of an event divided by the probability of no event. Odds ratios can appear farther from 1 than risk ratios when the outcome is common. For that reason, the odds ratio of 2.751 should not be read as meaning that the intervention group was more than twice as likely to meet the outcome. The risk ratio is generally more direct for communicating a relative comparison of proportions, while the risk difference expresses an absolute comparison. The registry reports a risk-difference estimate and interval, but they are not repeated because their recorded precision is more than 3 decimal places.

General statistical explanation: an interval around an estimate conveys uncertainty about the range of values compatible with the data and the method used to construct the interval. A narrow interval indicates greater precision than a wide interval, all else equal. An interval that includes the no-difference value has a different interpretation from one that excludes it. The registry does not state the interval confidence level or describe the interval calculation method, so those details should not be assumed.

What does the unadjusted p-value say?

The primary unadjusted p-value is 0.032. In general, a p-value summarizes how incompatible the observed data are with a specified null model, assuming that model and the analysis assumptions hold. It is not the probability that the null hypothesis is true, and it does not indicate whether a difference is clinically important. “Unadjusted” means the reported value has not been corrected for multiple comparisons. The registry does not identify the statistical test used, so the exact assumptions behind this p-value are not reported in the registry record.

The posted comparison also includes relative effect estimates and intervals, which help describe magnitude and precision in ways a p-value cannot. These measures are still based on the observed data and do not eliminate uncertainty about measurement, missing outcomes, or generalizability. The registry does not report a participant-level analysis dataset or detailed model specification, so independent assessment of those analytical details is not possible from the record.

Why can over-dispersion matter in other outcome types?

General statistical explanation: over-dispersion occurs when variability in count data is greater than a model assumes. If a count analysis ignores over-dispersion, its standard errors can be too small and its intervals too narrow. That issue is most relevant to analyses of event counts or rates. The primary outcome in this trial is reported as participants with an event, rather than as a rate over person-time, and the registry gives no dispersion estimate or count-model analysis. There is therefore no basis in the record to claim that over-dispersion was assessed or that it affected the primary result.

The study also lists a count outcome for willingness to use the self-collection device. The comparison is posted as a binary participant outcome, not as a repeated event-rate analysis. The registry does not report additional modeling details for it. General concepts about count-model dispersion should not be confused with evidence about the analysis actually performed in this study.

11. Confidence Intervals and Precision

The primary comparison’s relative risk is 1.157, with a reported interval from 1.009 to 1.327. The interval lies above the no-difference value of 1, indicating that the posted interval estimate is compatible with a higher event proportion in the intervention group under the calculation used. The odds ratio is 2.751, with an interval from 1.061 to 7.133. Its interval is wide, indicating substantial uncertainty about the magnitude of the odds comparison. Because odds ratios and risk ratios have different scales, their magnitudes should not be compared as if they were the same measure.

Intervals are more informative than a point estimate alone because they show a range of plausible effect sizes under a specified statistical procedure. The primary interval still spans effects close to no difference as well as larger relative effects. It therefore does not pin down the size of the contrast precisely. The registry does not report the interval confidence level or construction method, so those features cannot be evaluated from the record.

The group counts also help anchor interpretation: 59 of 75 in the control group and 71 of 78 in the intervention group met the primary outcome definition. These counts are not a substitute for an interval, and they do not reveal how the combined endpoint divides between screening action and reported future desire. A more detailed breakdown is not reported in the registry record.

The secondary comparison’s relative estimates have broad intervals, including values on both sides of the no-difference value for the ratio measures. This indicates limited precision for that outcome and makes its unadjusted result especially tentative. The registry does not provide an interval for workshop satisfaction because a posted result for that outcome is absent. Precision should be considered alongside outcome definition, multiplicity, and analysis reporting, rather than inferred from a p-value alone.

12. 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, not total participants. They are illustrations based on the observed primary effect, not the original trial design calculation. The planning 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 set to a stated fraction of the observed effect. The registry’s own original design assumptions are not reported in the registry record. These figures are not observed power.

For planning at 100% of the observed effect, the illustration gives 131 participants per arm for 80% power and 175 participants per arm for 90% power. At 75% of the observed effect, it gives 253 participants per arm for 80% power and 339 participants per arm for 90% power. At 50% of the observed effect, it gives 612 participants per arm for 80% power and 819 participants per arm for 90% power.

In plain terms, 80% power means that, if the assumed effect and statistical assumptions were true, a study of the stated size would have an 80% chance of detecting an effect at the chosen significance level. The 90% column uses a higher target chance of detection under the same assumed conditions. More power generally requires more participants. The figures also illustrate why planning for a smaller effect requires more participants: a smaller difference is harder to distinguish from random variation.

These are hypothetical planning illustrations, not a reconstruction of the trial’s design rationale or a statement about the probability that this completed study’s result is correct. The planning display relates sample size to assumed effect size; it does not establish what effect the investigators expected before the study began. The record does not report the trial’s original power target, significance level, allocation assumptions, or sample-size justification.

13. 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 = 0.787; treatment proportion p₁ = 0.910; average p̄ = 0.848.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5071 = 0.9939.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4995 = 0.4204.
4. n = (0.9939 + 0.4204)² / (0.1236)² = 131.0, rounded up to 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 <- 0.786666666666667                          # control proportion
p1 <- 0.91025641025641                          # 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(5286749)
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 = 131 (80% power), 175 (90% power)
 75% of observed effect: n per arm = 253 (80% power), 339 (90% power)
 50% of observed effect: n per arm = 612 (80% power), 819 (90% power)
power.prop.test: 131 
Simulated power at n = 131 per arm: 0.809 (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.

14. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several outcomes, comparisons, or analyses are considered. With each additional statistical test, the chance of finding at least one result that appears notable by chance can increase. The registry lists a primary outcome and secondary outcomes, and it posts an unadjusted p-value for the primary comparison and for the willingness outcome. It does not report a multiplicity adjustment, a testing hierarchy, or a plan stating which comparisons were confirmatory. The interpretation of the unadjusted p-values should therefore remain cautious, particularly for secondary outcomes.

The registry record does not report a detailed statistical analysis plan, the test used for the comparisons, or whether any models adjusted for baseline characteristics. It also does not describe the analysis population, such as whether the primary comparison followed all randomized participants according to their assigned group. The number of reported analyses is recorded as 0, while outcome results and comparisons are posted; the registry does not explain this distinction. The analytic process cannot be reconstructed from the record alone.

Missing outcome data can affect estimates if participants without an observed outcome differ from those with one. The record gives group sizes and outcome counts but does not report a missing-data definition, the number of missing outcomes, reasons for missingness, or an approach such as imputation or sensitivity analysis. It is therefore not possible to determine from the registry record how missing outcomes were handled or whether the posted counts include all randomized participants.

The record also does not report whether participants were analyzed according to assignment, whether any participants crossed between approaches, or whether protocol deviations occurred. These details matter because exclusions after randomization can change the comparability that randomization is intended to support. None of these limitations establishes that the analysis was inappropriate; they mark information that is not reported in the registry record and consequently cannot be evaluated.

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 lists zero serious adverse events in the control group and zero in the intervention group. It also lists zero other adverse events and zero deaths in each group. The listed groups at risk were 75 in control and 78 in intervention. No serious adverse-event terms are listed.

These entries mean that the registry reports no events in the categories shown for the groups and risk sets recorded. They do not establish that no adverse experiences of any kind occurred, nor do they provide detail about the method or duration of safety monitoring. The study concerns workshops and screening approaches, and the registry does not provide a narrative safety assessment or event definitions. The absence of listed events should therefore be interpreted as a report of the recorded categories, not as proof of zero risk.

The registry record does not provide further information about how adverse events were collected, how events were attributed, or whether all participants contributed safety information. These details are not reported in the registry record.

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

The posted primary result describes a higher count of participants meeting the combined screening engagement or future-desire endpoint in the intervention group than in the control group. The reported relative risk and its interval provide a relative comparison, while the group counts show the underlying number meeting the endpoint. The unadjusted p-value adds a test-based summary, but does not quantify practical importance or establish a causal mechanism on its own.

The result is about an educational approach that added information on participant-collected HPV screening to a workshop that already covered standard screening. It does not isolate the effect of self-collection itself from the effect of additional education, attention, or other differences between the workshops. The registry does not report a design that separates those components.

The primary endpoint also combines screening action or seeking with stated future desire to follow up. It therefore does not show, by itself, how many participants completed screening, how many intended to seek it, or whether intentions were later followed through. A follow-up outcome on actual screening completion is not reported in the registry record. Nor does the result establish effects on cervical cancer diagnoses or other health outcomes, which are not listed as the primary endpoint.

Interpretation is further limited by unreported analysis details, missing-data handling, and the lack of a reported multiplicity strategy. The trial involved Southeast Asian immigrant and refugee women in Wisconsin, so the registry record alone does not establish whether the same pattern would apply in other populations or settings. The result is a comparison within the recorded study groups, with uncertainty about endpoint components and the broader context of implementation.

Accordingly, the posted data can be described as showing a difference in the recorded primary outcome between the randomized groups. They do not warrant a broader claim about confirmed screening completion, long-term behavior, cancer prevention, or the performance of self-collection in all settings.

17. Why This Trial Matters Statistically

This trial raises a statistical question that is common in behavioral and community health research: how should outcomes be defined when an intervention aims to change both knowledge and action? Here, the primary endpoint combines engaging or seeking screening with self-reported desire to follow up. That makes the measure responsive to immediate participation and intention, but it also means those distinct states cannot be separated in the posted primary summary.

The comparison also illustrates why the effect measure matters. Counts, relative risks, odds ratios, and risk differences describe the same group contrast on different scales. The risk ratio is often easier to understand as a comparison of proportions, whereas the odds ratio can appear larger when the outcome is common. Reporting group counts alongside relative measures helps readers keep the scale of the result in view.

Precision and analysis transparency are equally important. The primary ratio interval is compatible with values close to no difference as well as larger relative effects, and the record does not state the interval confidence level or method. The unadjusted p-value does not account for the presence of secondary outcomes. Details on analysis populations, missing data, and the statistical plan are not reported in the registry record, limiting how fully the numerical result can be evaluated.

Finally, the planning illustrations show how conclusions about sample size depend on the effect investigators aim to detect. Smaller assumed effects require more participants under the stated planning assumptions. Because the trial’s original design assumptions are not reported, those illustrations should not be mistaken for evidence about what was planned before enrollment. Together, these considerations make the study useful for understanding both the observed comparison and the reporting information needed to interpret it responsibly.

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 includes more than one kind of response: obtaining or seeking screening and reporting a future desire to follow up. The posted result does not separate these components, and the registry does not give a detailed operational definition for classifying them. This limits conclusions about completed screening specifically.

The record does not report baseline characteristics, detailed eligibility criteria, recruitment methods, or participant flow by group. As a result, readers cannot assess the enrolled population’s composition, compare baseline features, or determine how many participants had missing outcomes or left the study. The record also does not report how randomization was generated or concealed, or who was masked despite the single-masking designation.

The registry does not provide the analysis method, analysis population, missing-data approach, adjustment for baseline variables, or a multiplicity plan. It posts unadjusted comparisons, but does not identify the statistical test or interval construction. The interval confidence level is also not reported. These omissions limit assessment of the assumptions behind the inferential summaries.

The brief summary describes a total sample size of 250 participants, while the enrollment field records 153; the registry record does not explain the difference. The original sample-size rationale is not reported in the registry record. The satisfaction outcome is listed, but its result is not reported. Finally, the study setting and population are specifically Southeast Asian immigrant and refugee women in Wisconsin, and broader applicability cannot be determined from these registry results alone.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Cervical Cancer Self-Collection for Southeast Asian Immigrant and Refugee Women — NCT05286749.
• Registry record last updated 2024-09-19; status last verified 2024-08.
• Results first posted 2024-09-19.
• 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

NCT05286749 is a completed randomized, single-masked, parallel-group study of cervical cancer education and screening among Southeast Asian immigrant and refugee women in Wisconsin. It compared a workshop covering clinician-collected screening with a workshop that added education about participant-collected HPV screening. The registry records enrollment of 153 and primary completion on 2024-02-10.

The primary outcome counted participants obtaining or reporting a future desire for screening, with a timeframe of up to 1 day. The posted counts were 59 in control and 71 in intervention. The comparison reports a risk ratio of 1.157 and an unadjusted p-value of 0.032. The registry also lists satisfaction and willingness to use self-collection as secondary outcomes; a result is posted for willingness, while satisfaction results are not reported in the registry record. Analysis details, missing-data handling, and the trial’s original design assumptions are not reported in the registry record.