Home Semen Testing in Men Beginning Attempts to Conceive: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Home Semen Testing in Men Beginning Attempts to Conceive (NCT05503862), a randomized na study. The primary outcome is Number of Participants Who Completed the Home Semen Testing.

2. Clinical Question

3. Trial Design

The registry identifies NCT05503862 as a randomized, parallel-group trial with no masking. It lists Northwestern University as the sponsor and an enrollment of 106. The study is marked completed. Its recorded start date is 2022-08-17, and its primary completion date is 2025-06-18. These registry entries describe the study record; they do not establish how many participants were ultimately randomized or included in each analysis.

The two arms were Arm A, at-home semen testing via the YoSperm device, and Arm B, Standard of Care. The primary endpoint is a count of participants who completed home semen testing. Its timeframe is described as the device being mailed immediately following randomization. The registry also lists fertility questionnaire outcomes and measures of length of time attempting to conceive at short-term and long-term follow-up. The listed follow-up definitions include windows of 60-120 days, 60-150 days, and 300-425 days after baseline. Numerical results for these secondary outcomes are not reported in the registry record.

Randomization means assignment is intended to make treatment groups comparable on average, while a parallel design means participants remain in their assigned groups rather than crossing between interventions. Those are general design concepts; the registry record does not describe the randomization sequence, allocation concealment, or procedures used to implement assignments. No masking was used, so participants and study personnel were not blinded according to the record. Further details about recruitment, study sites, protocol deviations, and analysis populations 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: A total of 283 patients were screened. After excluding patients who did not sign the consent (2), did not complete the baseline survey (20), and those subjects who were not randomized due to other exclusion / eligibility criteria or due to attempting to enroll in the study more than once (90), a total of 171 patients were randomized. However, only 106 patients completed all baseline questionnaires and had valid mailing addresses, thus resulting in the enrolled number.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Arm A is comprised of participants in the study who completed the at home semen test. Subjects in arm A were asked to complete an at-home semen test, per the study protocol.

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 Completed the Home Semen Testing, measured over Device mailed to patient immediately following randomization.

The primary endpoint is the number of participants who completed the home semen test. The registry describes this outcome as a way to assess whether participants assigned to home testing used the YoSperm device. This makes the endpoint a measure of feasibility and uptake: it concerns completion of the testing procedure, not the accuracy of a test result or a clinical outcome.

A count can be useful when an early question is whether people can carry out a new procedure in the intended setting. It can indicate how many completions were recorded, but by itself it does not describe the proportion of eligible or assigned participants who completed testing unless the relevant denominator is also clear. Nor does completion establish that the test led to a diagnosis, treatment, or change in fertility-related quality of life.

The posted results list 39.0 for Arm A and 0.0 for Arm B, with a recorded group size of 0.0 for Arm B. The record therefore does not support interpreting the Arm B value as a completion count among a defined group of participants or estimating a comparison between arms. The endpoint is relevant to the study's feasibility aim, but the registry record does not report enough information to quantify comparative uptake.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

What does a randomized parallel design contribute?

In general, random assignment is used to reduce systematic differences between groups at the start of a trial. A parallel-group design compares groups that follow their assigned strategies over the study period. These design features can support a causal comparison when assignment, follow-up, and analysis are adequately documented and when outcomes are available for the groups being compared. The registry identifies this study as randomized and parallel, but details of sequence generation, allocation concealment, and implementation are not reported in the registry record.

The study is listed as unmasked. In general, lack of masking can matter when outcomes depend on participant behavior, reporting, or decisions made by study personnel. Completion of a home test is a behavioral endpoint, so its ascertainment depends on how completion was defined and recorded. The registry gives the endpoint description but does not report further procedures for verifying completion or assessing outcome ascertainment.

How should a count endpoint be understood?

A count records how many participants meet an outcome definition. It is not automatically a proportion. For a proportion, a clearly defined denominator is needed: for example, the number of participants in the relevant analysis group who could have had the outcome assessed. A group-level count may also require a clear description of who was included and the period during which the outcome was observed.

Here, the primary outcome is the number of participants who completed home semen testing. The registry posts 39.0 for Arm A and 0.0 for Arm B, alongside group sizes of 39.0 and 0.0, respectively. The zero group size in Arm B prevents interpreting its posted value as a count observed among an enrolled or analyzed group. This is distinct from observing zero completions in a group with a known, nonzero denominator. The record states that a two-arm comparison for this binary endpoint is not estimable from the posted values.

What would an effect estimate and confidence interval add?

In general, an effect estimate summarizes the contrast between groups on a defined scale, while a confidence interval describes the uncertainty around that estimate under the statistical model. A narrow interval indicates greater precision than a wide one, but neither the interval nor an estimate can repair missing or unusable group data. Because the registry does not report an estimable two-arm contrast, there is no comparative estimate or confidence interval to interpret for the primary endpoint.

A p-value, when calculated under a prespecified model, addresses how compatible the data are with a specified null hypothesis under that model. It does not measure the probability that a treatment works, and it does not convey the size or practical importance of an effect. No primary p-value or comparative analysis is reported in the registry record. The record lists 0 analyses, so a sponsor analysis, model specification, and inferential procedure are not available for review.

What do the sample-size illustrations represent?

In general, sample-size planning depends on assumptions about the outcome, the effect that a future study aims to detect, variability, allocation, and the chosen significance level and power. Planning illustrations are hypothetical design calculations; they are not results from the trial and are not observed power. The registry describes illustrations using a two-sided significance level of 0.05, equal allocation, and a normal approximation, with planning effects expressed as fractions of the observed effect. It also notes that time-to-event planning uses a total event count, while other illustrations use participants per arm.

Those assumptions do not establish the trial's own design rationale. The registry does not report the sample-size justification or the protocol's statistical plan. Since the posted primary endpoint does not support a two-arm effect estimate, a planning illustration based on a fraction of that effect should not be treated as an empirical estimate of precision or as evidence about the trial's ability to detect a difference. The record does not report an observed-power analysis.

Why does over-dispersion matter in general?

For count outcomes, statistical models may assume a particular relationship between the average count and its variability. Over-dispersion occurs when observed variability is greater than the model assumes. If it is ignored, standard errors can be too small and confidence intervals can be too narrow. This is a general consideration for some count-data analyses; the registry does not report an over-dispersion assessment or a count model for this endpoint. The endpoint itself is described as a participant count, and no model-based analysis is listed.

For this record, the central statistical issue is not choosing among count models but the lack of an estimable two-arm comparison and the absence of reported analysis details. Additional information about participant flow, outcome definitions, denominators, and analysis populations would be needed before a comparative statistical interpretation could be made.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("Arm A")
n      <- c(39)
events <- c(39)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Arm A  39  39  100.0  91.0  100.0  91.0  100.0  91.2  99.9

11. Multiplicity, Missing Data and Analysis Populations

The registry lists 8 secondary outcomes. They include fertility questionnaire outcomes at short-term and long-term follow-up, with more than one follow-up definition, and measures of length of time attempting to conceive. It also lists 11 outcome measures overall. Numerical results for the secondary outcomes and their analysis details are not reported in the registry record. The record does not explain whether any outcomes were designated as confirmatory or exploratory.

Multiplicity arises when several outcomes or comparisons are assessed: the chance of at least one apparently notable result can increase as the number of tests grows. General approaches include prespecifying a primary comparison, adjusting inference across a family of tests, or interpreting secondary findings as exploratory. The registry record does not report a multiplicity strategy, a hierarchy of outcomes, or an adjustment method. Without numerical results and a stated analysis plan, no conclusion about multiplicity-adjusted evidence can be made.

Missing-data methods and analysis populations are also not reported in the registry record. The record does not describe how incomplete questionnaires, missed follow-up, or unavailable testing results were handled. It does not identify whether the analysis followed randomized assignment, included only participants with observed outcomes, or used another population definition. These distinctions matter because completion and follow-up can be related to participant characteristics or study assignment, and analyses restricted to observed outcomes may not preserve the comparability created by randomization.

The primary results also do not provide an interpretable Arm B denominator, and the listed analysis count is 0. The registry record therefore does not permit evaluation of attrition, missingness, or the relationship between randomized assignment and analyzed participants.

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

The posted result supports a limited descriptive statement: the registry records a primary completion count of 39.0 for Arm A. It also records 0.0 for Arm B alongside a group size of 0.0, and indicates that a two-arm comparison is not estimable from the posted binary endpoint data. This is not a valid basis for saying that completion was more frequent in one arm, or that the Standard of Care arm had no completions.

Completion of home testing is a feasibility outcome. It does not establish the diagnostic accuracy of the device, whether a participant had male factor infertility, or whether testing changed subsequent clinical care. The registry's study objectives include fertility-related quality of life and diagnosis and treatment of male infertility, but numerical results for the listed secondary outcomes are not reported in the registry record. Those broader questions therefore cannot be answered from the posted results.

The record identifies a randomized, unmasked, parallel-group trial and lists enrollment as 106. However, the arm data do not provide a usable comparative analysis, and details of participant flow and analysis populations are not reported. Randomized assignment alone does not make a result interpretable when the outcome data and denominators needed for comparison are unavailable or unclear.

The adverse-event entries list zero participants at risk and zero events. Because the at-risk counts are also zero, these fields do not establish that no adverse events occurred among enrolled participants. A meaningful safety interpretation would require an interpretable population and follow-up information.

In short, the posted data do not demonstrate the comparative effect of home semen testing versus Standard of Care. They also do not establish a treatment benefit or lack of benefit. They leave uncertainty about the feasibility outcome across arms and do not report numerical evidence for the study's quality-of-life or clinical follow-up aims.

13. Why This Trial Matters Statistically

This trial raises a statistical issue that often appears in feasibility studies: a useful endpoint may be simple to define, but its interpretation still depends on clear denominators and outcome data for the groups being compared. A completion count is directly relevant to whether a home procedure was used. To compare strategies, however, the record must also make clear which participants were assigned, which were eligible for assessment, and how missing outcomes were handled.

The registry identifies randomization and a parallel design, features that can support a fair comparison when the analysis preserves the assigned groups and includes interpretable outcome information. In this record, the listed Arm B group size is 0.0, and the registry indicates that the binary two-arm comparison is not estimable. That makes transparent reporting of participant flow and analysis populations especially important: readers need to distinguish a true absence of events from an absent or unusable denominator.

The study also lists several follow-up questionnaire and time-attempting-to-conceive outcomes. Multiple outcomes can help describe different aspects of feasibility and participant experience, but they make prespecification and clear reporting of the analysis strategy important. Without numerical results, missing-data methods, or a multiplicity plan, readers cannot assess the breadth or precision of the evidence across these outcomes.

The broader statistical lesson is that trial registration and a completed status do not substitute for an interpretable results record. Clear group sizes, outcome denominators, estimates of uncertainty, and analysis details are needed to connect a randomized design to conclusions about comparative outcomes.

14. 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 principal limitation is that the posted primary endpoint does not support an estimable two-arm comparison. The registry reports 39.0 for Arm A and 0.0 for Arm B, but the listed Arm B group size is 0.0. The record explicitly flags the binary comparison as not estimable. Consequently, no comparative effect, uncertainty interval, or significance result can be interpreted from the posted figures.

The registry enrollment is 106, but it does not provide arm-specific enrollment totals or a participant-flow account that reconciles enrollment with the posted arm data. It is not possible to determine from the record how many participants were randomized, assessed, or included in each outcome analysis. The Arm A description also defines that arm in terms of participants who completed the home test, leaving the analyzed population and endpoint denominator unclear.

Numerical results for the listed secondary outcomes are not reported in the registry record. The record does not describe questionnaire scoring, missing follow-up handling, analysis populations, or the statistical methods used. It also does not report the sample-size justification, an interim-analysis plan, or a multiplicity strategy. These absences prevent assessment of precision and of the planned interpretation of secondary outcomes.

The adverse-event fields list no participants at risk in either arm, so the zero event entries do not provide an interpretable safety assessment. In addition, the open-label design may matter for participant-reported or behavior-dependent outcomes, but the record does not describe safeguards for outcome ascertainment. These are limitations of the available registry information and should not be taken as proof that the trial itself lacked such procedures.

15. Related Tutorials

16. Related Statistical Calculators

17. Sources

• ClinicalTrials.gov: Home Semen Testing in Men Beginning Attempts to Conceive — NCT05503862.
• Registry record last updated 2026-09-03; status last verified 2026-03.
• Results first posted 2026-09-03.
• 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.

18. Record Summary

NCT05503862 is a completed randomized, unmasked, parallel-group trial sponsored by Northwestern University. The record lists enrollment of 106 and compares at-home YoSperm testing in Arm A with Standard of Care in Arm B. The primary endpoint is the number of participants completing home testing after the device was mailed following randomization.

The posted primary values are 39.0 for Arm A and 0.0 for Arm B, with a recorded Arm B group size of 0.0. The registry states that a two-arm comparison for this binary endpoint is not estimable. Numerical secondary-outcome results and analysis details are not reported in the registry record. Thus, the available results do not quantify a comparative effect of home testing versus Standard of Care or answer the broader quality-of-life and clinical follow-up questions.