Impact of DNA Fragmentation in Sperm on Pregnancy Outcome After Intra-uterine Insemination in a Spontaneous Cycle: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Impact of DNA Fragmentation in Sperm on Pregnancy Outcome After Intra-uterine Insemination in a Spontaneous Cycle (NCT03319654), a na na study. The primary outcome is DNA Fragmentation as a Predictor of Live Birth Rate.

2. Clinical Question

The study addresses a prediction question: whether a laboratory measure of sperm DNA fragmentation is associated with the chance of live birth following spontaneous-cycle IUI. The record’s background explains that conventional semen analysis focuses on concentration, motility and morphology, and describes interest in sperm function testing. Those statements provide the motivation for investigating DNA fragmentation; they are not results from this cohort.

The primary measure refers to fragmentation in the diagnostic sample, not necessarily to every fragmentation measurement collected. The record separately lists secondary measures for total and vital fractions in diagnostic and IUI-related samples. It does not report how these measurements relate to one another or which, if any, provide more useful prediction.

3. Trial Design

The registry describes a prospective cohort study of spontaneous-cycle IUI. The model is listed as single group, allocation as NA, and masking as none. These features distinguish the study from a randomized trial comparing assigned treatments. The record describes DNA fragmentation testing as a diagnostic test, with an assay at diagnostic work-up and again at insemination.

Enrollment is recorded as 120. The study status is completed. The recorded start date is 2017-10-05 and primary completion date is 2021-05-31. The sponsor is University Hospital, Antwerp. The registry lists phase as NA, which is consistent with the record not presenting this as a drug-development phase study.

In a cohort design, an exposure or marker can be measured and related to a later outcome without random assignment to marker levels. Here, the marker is sperm DNA fragmentation, and the outcome of primary interest is live birth after IUI. Such an association can support a prediction question, but the design alone does not establish that changing the marker would change the outcome. The registry record does not report a separate treatment-control comparison, and its listed arms should not be read as independent randomized groups.

The assay schedule includes measurement during diagnostic work-up and at the time of insemination. Secondary outcomes describe fragmentation in total and vital fractions, before and in samples associated with IUI, including after density gradient processing. This indicates that the study recorded multiple sample contexts; it does not establish that each measure was used in the primary analysis.

The registry record does not report detailed eligibility criteria, recruitment procedures, follow-up procedures, the number of insemination cycles per participant, or how repeated observations were handled. It also does not report a protocol-level sample-size justification or a full statistical analysis plan. The sample-size assumptions described for a planning illustration should not be mistaken for the design or analysis actually used in this cohort.

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: 6 included patients did not proceed to treatment; 1 due to spontaneous pregnancy - 5 loss to follow-up

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.

Population: Since this study relates to fertility, we have included "couples". 114 couples were included hence 114 women and 114 men.

6. Primary Endpoint

The registry lists the primary outcome as DNA Fragmentation as a Predictor of Live Birth Rate, measured over up to 36 months.

The primary endpoint is live birth, considered in relation to the percentage of total sperm DNA fragmentation in the diagnostic sample. The registry’s endpoint title describes DNA fragmentation as a predictor of live-birth rate; its description specifies an odds ratio for live birth per unit increase in the fragmentation percentage. The recorded timeframe is up to 36 months.

An odds ratio expresses how the odds of an outcome compare across different values of a predictor. In this setting, the intended interpretation concerns the change in the odds of live birth associated with a one-unit increase in the fragmentation measure. The unit increase is part of the registry’s endpoint description; the record does not state how the fragmentation measure was scaled or modeled in the analysis. The odds ratio itself is not reported.

Live birth is a clinically important endpoint for a fertility study because it describes an outcome beyond laboratory measurements or an earlier stage of pregnancy. The registry record does not provide its operational definition, how birth information was obtained, or how pregnancies and births were attributed when participants had more than one treatment cycle. Those details are not reported in the registry record.

The endpoint entry labels its parameter as a count of participants and gives the unit as participants, while the narrative description frames the main analysis as an odds ratio. This difference in presentation makes it important to distinguish the stated scientific question from the result fields available in the record. Neither the number of live births nor an estimate of the association is reported. Without an estimate and its uncertainty, the direction, magnitude and precision of any relationship cannot be assessed from the registry record.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The endpoint description uses an odds ratio to express the relationship between a continuous marker and a binary outcome. Live birth is the outcome of interest, and the marker is the percentage of total sperm DNA fragmentation in the diagnostic sample. In general, an odds ratio compares the odds of an outcome between levels of a predictor. An odds ratio equal to the null value represents no change in odds for the specified contrast; values on either side indicate different directions of association. The numerical estimate and its uncertainty are not reported in the registry record.

What does “per unit increase” mean?

The phrase “per unit increase” defines the contrast used to describe the predictor’s association with live birth. Its interpretation depends on the scale and coding of the marker. For example, a unit on a percentage scale can represent a different increment from a unit on a transformed or standardized scale. The registry record does not state whether the percentage was entered as recorded, rescaled, categorized, or transformed. The size of the contrast therefore cannot be clarified beyond the endpoint’s wording.

In general, a model relating a continuous predictor to a binary outcome may impose assumptions about how the outcome odds change across the predictor’s range. If the model assumes a constant change in log odds for each unit, that relationship may not capture a curved or threshold-like pattern. The registry record does not report the model form, checks of the relationship, or any alternative analyses. These are general considerations, not claims about analyses performed in this study.

How should uncertainty be evaluated?

A point estimate gives one summary of an association, while a confidence interval communicates its statistical precision under the model and sampling assumptions. A confidence interval can include values corresponding to materially different interpretations, so its width and limits matter. A p-value, if reported, addresses compatibility with a specified null hypothesis under assumptions; it does not measure the size or clinical importance of an association. No confidence interval or p-value for the primary endpoint is reported in the registry record.

Prediction requires more than estimating an association. A marker can be associated with an outcome yet predict individual outcomes poorly. General assessments of prediction can include calibration, which compares predicted risks with observed outcomes, and discrimination, which concerns how well predictions distinguish people with different outcomes. The registry record does not report these assessments, a prediction rule, or validation in a separate sample. It therefore does not show whether DNA fragmentation improves prediction beyond other information.

What do the planning assumptions represent?

The sample-size material is described as a planning illustration based on an observed effect, not as the trial’s own design justification. It specifies a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation; it also describes detecting a stated fraction of the observed effect. For time-to-event calculations, the stated quantity is a total event count, while other calculations are expressed as participants per arm. These are planning conventions, not observed trial outcomes and not observed power.

The assumptions do not establish that the cohort was randomized or that it had two treatment arms. The registry describes a single-group prospective cohort with allocation listed as NA. A hypothetical two-arm calculation is therefore distinct from the study’s actual design. The record does not report the trial’s own sample-size justification, and the planning illustration cannot establish whether enrollment was sufficient for the intended prediction analysis.

More generally, planning calculations depend on assumed effect size, variability, allocation and analysis method. If those assumptions differ from the study’s actual design or data, the calculation may not describe the precision achieved. A planning illustration based on an observed effect also should not be read as evidence that the effect is reproducible. The registry record does not report an independently specified target effect for the primary endpoint.

Why do the multiple measurements matter?

The record lists measurements of total and vital sperm fractions in diagnostic samples and in samples associated with IUI, including after density gradient processing. These are related but distinct measurements. Their values may differ because they describe different fractions or collection contexts. An analysis must specify which measurement addresses the primary question and how the others are treated. The registry identifies diagnostic-sample total fragmentation for the primary endpoint and lists the other measures as secondary outcomes, but it does not report their results or the detailed modeling strategy.

Because the primary estimate, its uncertainty, model details, and prediction assessments are not reported, statistical interpretation remains limited to explaining the intended analysis. No recalculated estimate can be derived from the registry record, and no claim about the magnitude or precision of an association is supported.

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("Spontaneous Cycle IUI - Sperm DNA Fragmentation An")
n      <- c(114)
events <- c(32)
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  Spontaneous Cycle IUI - Sperm DNA Fragmentation An  114  32  28.1  20.1  37.3  20.6  36.9  20.6  37.0

11. Multiplicity, Missing Data and Analysis Populations

The record lists seven outcome measures and two analyses. It does not describe how the analyses were allocated across outcomes, whether outcomes were ranked, or whether any adjustment was made for multiple comparisons. When several outcomes or analyses are examined, the chance of obtaining at least one apparently notable result can increase. General approaches include prespecifying a primary endpoint, controlling the family-wise error rate, using false-discovery procedures, or treating secondary analyses as exploratory. The record does not say which approach, if any, was used.

The primary outcome is identified as live birth in relation to diagnostic-sample total sperm DNA fragmentation. The listed secondary outcomes concern fragmentation in total and vital fractions across diagnostic and IUI-related samples. Multiple measurements can answer related but nonidentical questions. Without a reported analysis plan and results, it is not possible to tell whether all were analyzed, how their findings were interpreted, or whether multiplicity influenced the reported conclusions.

Missing-data methods are not reported in the registry record. It does not state how missing fragmentation measurements, unavailable birth outcomes, withdrawals, or incomplete follow-up were handled. The analysis population is also not described: the record does not specify whether analyses included all enrolled participants, only those with a successful assay, or another defined group. The enrollment of 120 alone cannot identify the number contributing to the primary endpoint analysis.

The record also does not report a participant flow, counts with missing data, or sensitivity analyses for missing outcomes. These omissions matter because estimates can be affected when outcome availability is related to participant characteristics or study measurements. No conclusion about the extent or effect of missingness can be made from the registry record.

12. 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 serious adverse event record lists 228 participants at risk, zero serious events, zero other events, and zero deaths for the spontaneous-cycle IUI sperm DNA fragmentation analysis group. No serious adverse event terms are listed. These are the safety figures recorded for the study; they do not establish that no events occurred outside the recorded categories or reporting period.

The safety denominator is 228, while enrollment is recorded as 120. The registry record does not explain this difference, so the denominator should not be interpreted as a count of distinct enrolled participants without further information. It may reflect a different reporting unit or accumulation, but the record does not say which. No explanation should be inferred from the figures alone.

Zero recorded events is a descriptive result, not proof that the underlying risk is absent. The safety entry does not provide event definitions, collection procedures, exposure duration, or a breakdown by timing. It also does not describe how events were assessed for relatedness. These details are not reported in the registry record.

The safety numbers should be kept separate from the primary efficacy question. They do not indicate whether sperm DNA fragmentation predicts live birth, and they do not provide an estimate of live-birth frequency. That primary result is not reported in the registry record.

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

The record identifies a focused question: whether the percentage of total sperm DNA fragmentation in a diagnostic sample predicts live birth after spontaneous-cycle IUI. It describes prospective measurement of the marker and names an odds ratio per unit increase as the primary association measure. This establishes the intended research question, not the answer.

The primary effect estimate, confidence interval, p-value and live-birth count are not reported in the registry record. As a result, the posted record does not show the direction or size of the association, how precisely it was estimated, or whether the data were compatible with a wide range of effects. It cannot support a conclusion that the marker did or did not predict live birth in this cohort.

Even an observed association would not by itself show that the marker causes a change in live birth. The study is described as a prospective cohort with a single group and no randomized allocation. Prediction and causation are different questions: a marker may forecast an outcome because it is related to other factors, without being a cause that can be altered to change the outcome. The record does not report adjusted analyses or causal methods.

Nor does an association alone establish practical predictive value. A useful prediction tool must give sufficiently accurate and calibrated risk estimates for the intended setting. The registry record does not report a prediction model, performance measures, or validation. The role of DNA fragmentation alongside conventional semen analysis or other clinical information is not quantified in the posted results.

The recorded enrollment of 120 describes the study’s enrollment, not the number with complete primary outcome data. The safety entry reports no serious or other adverse events and no deaths among 228 listed at risk, but the record does not explain that denominator. These safety figures do not fill the gap in primary outcome reporting.

The appropriate conclusion is therefore narrow: this completed cohort was intended to study sperm DNA fragmentation as a predictor of live birth following IUI, but the registry record does not report the results required to judge the association or its precision. Broader claims about clinical utility or treatment effects are not established by the record.

14. Why This Trial Matters Statistically

The study addresses a statistical question about a biomarker and a patient-relevant outcome. It asks whether a laboratory measure collected during diagnostic work-up can provide information about later live birth after spontaneous-cycle IUI. This is distinct from asking whether the assay itself changes outcomes or whether one treatment is superior to another.

The design makes the distinction especially important. A prospective cohort can examine whether variation in a marker is associated with later outcomes, but it does not randomly assign people to marker values. Statistical adjustment can sometimes address measured differences, but the registry record does not report adjusted estimates, covariates, or a causal analysis. The design and available reporting therefore support a prediction question more directly than a treatment-effect question.

The record also illustrates why an endpoint definition is not enough for interpretation. The primary endpoint names an odds ratio per unit increase in diagnostic-sample fragmentation, but without the estimate and confidence interval, readers cannot assess direction, size or precision. Without predictive performance measures, an association would not establish that the marker can classify or calibrate individual outcomes.

Several sample contexts and fractions are listed, alongside secondary measurements. This creates a need for clear prespecification: the primary measurement should be distinguished from exploratory alternatives, and the handling of multiple analyses should be transparent. The registry record does not report multiplicity procedures or the detailed analysis plan.

Finally, enrollment, safety reporting and primary-outcome evidence answer different questions. The enrollment count describes recruitment, and the safety figures describe recorded adverse events. Neither provides the missing live-birth association. Transparent reporting of effect estimates, uncertainty, analysis populations and missing-data handling is necessary for readers to assess the evidence. Those primary statistical details are not reported in the registry record.

15. 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 main limitation for interpretation is that the registry record does not report results for the primary endpoint. No odds ratio, confidence interval, p-value, or live-birth count is available in the record. The association’s direction, magnitude and precision therefore cannot be evaluated.

The endpoint is described as an odds ratio per unit increase in a percentage measure, but the scale and coding of the predictor are not specified. The model form, assumptions, adjustment variables and diagnostic checks are not reported. These omissions prevent assessment of how the estimate was constructed or whether the assumed relationship was appropriate.

The study is a single-group prospective cohort, with allocation listed as NA and masking as none. There is no randomized comparison described. Any association could reflect other characteristics related to both fragmentation and live birth; the registry record does not report whether such factors were measured or adjusted for. The result, even if reported, would not by itself establish causality.

Enrollment is recorded as 120, but the number included in the primary analysis and the completeness of follow-up are not reported. Missing-data procedures, analysis populations, participant flow, and sensitivity analyses are also not reported. The safety denominator of 228 is not reconciled with enrollment in the registry record.

The registry lists multiple fragmentation measures and seven outcome measures, with two analyses, but does not report multiplicity handling or results for the secondary measures. The detailed protocol, eligibility criteria, number of IUI cycles, sample-size justification, and statistical analysis plan are not reported in the registry record. The planning illustration’s assumptions are not evidence about the precision achieved in the cohort.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Impact of DNA Fragmentation in Sperm on Pregnancy Outcome After Intra-uterine Insemination in a Spontaneous Cycle — NCT03319654.
• Registry record last updated 2024-11-15; status last verified 2024-09.
• Results first posted 2024-11-15.
• 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.

19. Record Summary

This completed prospective cohort examined sperm DNA fragmentation as a potential predictor of live birth after spontaneous-cycle intra-uterine insemination. The registry records enrollment of 120 and describes DNA fragmentation assessment by TUNEL assay during diagnostic work-up and at insemination.

The primary endpoint concerns the odds ratio for live birth per unit increase in total sperm DNA fragmentation in the diagnostic sample, with a timeframe of up to 36 months. Secondary measures concern fragmentation in total and vital fractions across diagnostic and IUI-related samples. The study is listed as single group, with no masking and allocation recorded as NA.

The registry record does not report the primary effect estimate, confidence interval, p-value, live-birth count, or detailed analysis plan. Safety reporting lists zero serious events, zero other events and zero deaths among 228 at risk; the relationship between that denominator and enrollment is not explained. The record therefore establishes the study question and design, but does not provide the outcome evidence needed to judge the primary association.