Endometrial Scratch Effect on Pregnancy Rates in Patients Undergoing Egg-donation IVF: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Endometrial Scratch Effect on Pregnancy Rates in Patients Undergoing Egg-donation IVF (NCT03108157), a randomized na study. The primary outcome is Positive Pregnancy Test.

2. Clinical Question

In plain terms, the comparison concerns whether adding a uterine procedure during the cycle before embryo transfer is associated with a different recorded pregnancy-test outcome than conventional preparation alone. Because allocation was randomized, the trial was designed to compare groups formed through random assignment; the registry does not describe the allocation sequence or how it was implemented. It also does not report participant characteristics that would help readers judge how closely the enrolled group resembles other donor-egg IVF populations. The posted outcomes describe counts in each group, but the registry does not state the analysis population or explain how missing outcome information was handled.

3. Trial Design

The registry describes a randomized, parallel-group trial with no masking. It is marked completed, with a start date of 2017-01-12 and a primary completion date of 2018-11-30. The recorded enrollment is 352, and the phase is listed as NA. The sponsor is Procreatec.

Participants were assigned to an intervention group or a no-intervention group. The intervention was an endometrial scratch with a Pipelle Cournier 3 to 4 weeks before embryo transfer, followed by conventional preparation for embryos from egg donation. The comparator group received the conventional preparation protocol without the scratch. The registry does not report how randomization was generated, whether allocation was concealed, or whether any other procedures differed between groups.

No masking was recorded. This means the registry does not identify a masking arrangement for participants, clinicians, or outcome assessors; it does not establish which people, if any, knew each participant’s assigned group. The positive pregnancy test was assessed 12 to 14 days after embryo transfer. Live birth was listed as a secondary outcome, with the timeframe described as pregnancy beyond 24 weeks.

The registry record does not report the original sample-size justification, planned analysis methods, interim analyses, or the prespecified analysis populations. It records enrollment and outcome counts, but does not explain whether the outcome denominators reflect all randomized participants or a subset defined by another rule. The trial design therefore establishes the basic comparison and timing, while important operational details needed to evaluate conduct and analysis 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.

Overall Study

Reasons for not completing this period:

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 Positive Pregnancy Test, measured over 12 to 14 days after embryo transfer.

The primary endpoint is the count of participants with a positive pregnancy test. The registry defines the positive result as hcG >10 UI/ml and sets the measurement timeframe at 12 to 14 days after embryo transfer. The posted results give a count and an outcome denominator for each group.

This endpoint records an early pregnancy-test outcome after transfer. It is used in the trial to compare the number of participants meeting the registry’s positive-test definition between the scratch group and the group receiving conventional preparation alone. It is not the same endpoint as live birth: the registry lists live birth separately as a secondary outcome, defined as pregnancy beyond 24 weeks.

In general, a binary endpoint classifies each participant according to whether an event or defined condition was recorded. Comparing the group counts can describe the observed pattern, while a comparative estimate and its interval convey the direction and uncertainty of the difference. The choice of a positive test as the primary endpoint makes the assessment specific to the stated test definition and measurement time. The registry does not report further details about test procedures, adjudication, or handling of missing or indeterminate test results.

7. Results Posted in the Registry

• GROUP B: no Intervention Group: 65.7% (113/172) versus 69.6% (112/161) on control; risk difference -3.9 percentage points (95% CI -13.9 to 6.2), risk ratio 0.94 (0.81–1.10); unadjusted two-proportion z-test p = 0.451.

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.

Live Birth

• 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:
  • GROUP B: no Intervention Group: 49.4% (85/172) versus 57.1% (92/161) on control; risk difference -7.7 percentage points (95% CI -18.4 to 3.0), risk ratio 0.86 (0.71–1.06); unadjusted two-proportion z-test p = 0.158.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between GROUP B: no Intervention Group and the control. The interval gives the range of effects that remain compatible with the data.

Live birth is the secondary outcome posted in the registry, with the timeframe defined as pregnancy beyond 24 weeks. Its group counts and unadjusted comparison have a direction similar to the primary comparison: the observed proportion is lower in the no-intervention group. Its reported interval spans no difference, so it does not provide a more conclusive answer than the primary outcome.

The two outcomes address different points in the process recorded by the trial. A positive pregnancy test is an early endpoint measured 12 to 14 days after transfer, while live birth is a later endpoint defined by pregnancy beyond 24 weeks. Their broad directional consistency is informative as a pattern in the posted data, but it does not make the estimates independent confirmation of one another. The registry does not report how outcomes were related at the participant level or whether analyses accounted for that relationship.

In general, secondary outcomes can add context, but they often carry less weight than the primary outcome because they may be less central to the trial question and because testing multiple outcomes can increase the chance of finding an apparently notable result by chance. This is why a prespecified multiplicity approach is important when several outcomes or comparisons are assessed. The registry does not report whether such an approach was planned or used. The secondary comparison should therefore be treated as additional descriptive evidence, not as a separate definitive test that settles the primary question.

The registry lists three outcome measures and one posted secondary outcome. Details of other measures and any additional analyses are not reported in the registry record. No subgroup results or adjusted secondary analyses are reported. Taken together, the posted outcomes show a similar direction in the point comparisons but leave substantial uncertainty. The secondary result neither overturns nor resolves the uncertainty attached to the primary result.

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

• Live Birth

9. Statistical Interpretation

10. Statistical Methods Explained

The registry records binary outcomes as participant counts: each outcome is whether a participant met the defined endpoint. The primary outcome is a positive pregnancy test, and the secondary outcome is live birth. For each, the posted results include the number of events and the group denominator. These counts provide the basic descriptive evidence before any comparative statistic is considered.

What does a risk difference describe?

In general, a risk difference compares the proportions with an event in two groups by subtracting one group’s proportion from the other. A value of zero represents no difference in the proportions; a positive or negative value identifies the direction according to the comparison’s stated group order. The posted comparison is for the no-intervention group relative to the intervention group. The registry’s primary risk-difference estimate is negative, while its reported interval crosses zero. This means the point estimate favors a lower recorded event proportion in the no-intervention group, but the interval also allows a difference in the opposite direction.

What does a p-value contribute?

In general, a p-value measures how unusual data at least as incompatible with a specified null model would be if that model and the statistical assumptions were correct. It is not the probability that the null hypothesis is true, nor does it measure the magnitude or practical importance of a difference. The posted primary unadjusted p-value is 0.451, and the live-birth unadjusted p-value is 0.158. Those values describe the comparisons as posted; the registry does not report a detailed analysis plan or state whether these were the only inferential tests conducted.

How should intervals be read?

In general, a confidence interval expresses uncertainty around an estimate under a statistical method and its assumptions. Its width is informative about precision, and its position relative to a no-difference value helps readers assess which effects are compatible with the data. For a risk difference, the no-difference value is zero. The posted risk-difference intervals for both outcomes include zero. The registry does not state the confidence level or provide enough analysis detail to evaluate the interval procedure independently.

The record also posts relative risk and odds-ratio comparisons. In general, a relative risk compares event proportions as a ratio, while an odds ratio compares event odds. Their no-association reference value is one. The posted intervals for both measures span that reference value. These measures present the same group comparison on different scales; they do not remove the uncertainty visible in the risk-difference results. The risk difference is often easier to interpret in absolute terms, while relative measures can give a complementary description.

The comparisons are unadjusted as identified by their posted p-values. In general, an unadjusted comparison uses the observed group outcome summaries without controlling for other variables in a model. Randomization is intended to support a fair group comparison, but it does not make analysis details irrelevant. The registry does not report adjusted estimates, covariate selection, model diagnostics, or an analysis population definition. It is therefore not possible to tell from the registry record whether additional analyses were conducted or how they relate to the posted summaries.

These are binary count outcomes, so over-dispersion is not the central issue in the way it can be for count models of event frequency. In general, over-dispersion matters when observed variability exceeds what a specified count model assumes, potentially making model-based uncertainty too small if not addressed. The registry does not describe a model for the posted comparisons, so no claim about its handling of model dispersion is warranted.

The group counts and comparisons are useful for describing the recorded outcomes, but interpretation also depends on how participants entered the analysis and how missing outcomes were addressed. Those details, along with formal methods for multiplicity and any interim analysis, are not reported in the registry record. The methods that can be described are therefore limited to the randomized parallel design, the defined outcomes, and the unadjusted comparisons posted for them.

11. Confidence Intervals and Precision

Precision concerns how narrowly the data constrain the comparative effect. The posted primary risk-difference interval includes zero and extends to negative and positive values. Thus, the data do not isolate a single direction of difference. The interval is wide enough to leave uncertainty about whether the observed group contrast reflects a true difference, no difference, or a difference in the opposite direction. The point estimate alone gives a less complete account than the estimate together with its interval.

The same broad limitation applies to the secondary live-birth comparison: its risk-difference interval also includes zero. The posted relative-risk and odds-ratio intervals for the outcomes likewise cross their no-association reference value. Different scales describe the comparison differently, but the intervals all signal that the registry’s estimates are not narrowly determined.

In general, an interval is not a guarantee that the true effect lies within its limits. Its interpretation depends on the statistical procedure, assumptions, and confidence level. The registry does not report the confidence level or enough detail about the method to assess those choices. The intervals should therefore be read as the uncertainty measures posted with the comparisons, without attributing an unreported confidence level.

The outcome denominators are 161 for the intervention group and 172 for the no-intervention group in the primary and secondary results. These counts give context for the amount of recorded information, but the registry does not explain whether any participants were excluded from an outcome analysis or had missing results. Greater precision cannot be inferred from group counts alone; it also depends on event frequency and the analysis method. The posted intervals make clear that considerable uncertainty remains around both comparative outcomes.

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 illustrations based on the observed effect, not the trial’s original design assumptions. The registry does not report the original sample-size justification. Because the outcomes are binary rather than time-to-event outcomes, the displayed planning quantities are participants per arm, not total events.

The stated 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. For the primary outcome, planning for 100% of the observed effect gives 2,297 participants per arm for 80% power and 3,074 participants per arm for 90% power. Planning for 75% gives 4,051 participants per arm for 80% power and 5,423 participants per arm for 90% power. Planning for 50% gives 9,042 participants per arm for 80% power and 12,104 participants per arm for 90% power.

For live birth, planning for 100% of the observed effect gives 654 participants per arm for 80% power and 875 participants per arm for 90% power. Planning for 75% gives 1,160 participants per arm for 80% power and 1,553 participants per arm for 90% power. Planning for 50% gives 2,602 participants per arm for 80% power and 3,482 participants per arm for 90% power.

In plain terms, the 80% and 90% columns describe the planned chance of detecting the specified effect under the stated assumptions if that effect were real. A smaller effect requires more participants to detect under those assumptions, which is why the figures rise when the planning effect is reduced. These are planning illustrations, not observed power.

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 = 0.696; treatment proportion p₁ = 0.657; average p̄ = 0.676.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6617 = 1.2969.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6611 = 0.5564.
4. n = (1.2969 + 0.5564)² / (-0.0387)² = 2,296.2, rounded up to 2,297 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 <- 0.695652173913043                          # control proportion
p1 <- 0.656976744186046                          # 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(3108157)
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 = 2,297 (80% power), 3,074 (90% power)
 75% of observed effect: n per arm = 4,051 (80% power), 5,423 (90% power)
 50% of observed effect: n per arm = 9,042 (80% power), 12,104 (90% power)
power.prop.test: 2296.2 
Simulated power at n = 2,297 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.

14. Multiplicity, Missing Data and Analysis Populations

The registry identifies positive pregnancy test as the primary outcome and live birth as a secondary outcome. It also lists three outcome measures, while one secondary outcome is posted. The details of any other outcome measures are not reported in the registry record. No plan for controlling multiplicity is reported, including whether the primary outcome was the sole confirmatory test or how secondary outcomes were to be interpreted if multiple tests were performed.

In general, multiplicity arises when several outcomes, time points, groups, or analyses are tested. Repeated testing can make apparently unusual results more likely even when there is no underlying effect. A prespecified strategy can manage this issue, for example by defining which tests are confirmatory and how interpretation changes across multiple comparisons. Since no such strategy is reported, the unadjusted secondary result should be treated cautiously. The registry does not establish whether additional unposted analyses were performed.

The registry records no separately reported analysis records, although it does post summary outcome comparisons. It does not report whether analyses followed intention-to-treat principles, whether a per-protocol population was used, or how participants were assigned to analysis populations. The denominators accompanying the outcomes are visible, but the reasons for any difference between enrollment and outcome denominators are not reported in the registry record.

Missing-data handling is also not reported. The record does not state how many outcome results were missing, whether missingness differed by group, or whether imputation or sensitivity analyses were used. This matters because excluding participants with unknown outcomes can affect the comparability of groups, depending on why data are missing. No conclusions about the direction or size of such an impact can be drawn from the registry record.

Interim analyses, stopping rules, prespecified covariate adjustments, and detailed statistical methods are not reported in the registry record. Their absence from the registry does not establish that they were not used; it means the posted record does not document them. These omissions limit independent assessment of how the comparisons were selected and how robust they may be to alternative analysis choices.

15. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 1% reporting threshold.

Most frequent non-serious adverse event terms

The registry reports zero serious adverse events in the intervention group and zero in the no-intervention group. It also reports zero deaths in each group. For other adverse events, the registry records 36 in the intervention group and 47 in the no-intervention group. These are counts as recorded in the safety results; the registry does not provide a list of serious adverse-event terms.

In general, adverse-event counts describe events recorded during the trial and do not by themselves establish whether an event was caused by the intervention. The registry does not report event definitions, severity categories for the other adverse events, timing, or an assessment of relatedness. It is also not stated whether the other adverse-event counts refer to participants with at least one event or to event episodes. The counts should therefore be read as registry-reported safety figures, not as a complete safety profile or a causal comparison.

The reported serious-event and death counts are reassuring only in the narrow descriptive sense that no such events were recorded in these posted group results. They do not prove that the risk is absent, and the registry record does not provide enough information to assess how safety events were collected or followed up.

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

The posted results describe a randomized comparison of endometrial scratch before donor-egg IVF embryo transfer with conventional preparation alone. They show 112 positive pregnancy tests in the intervention group and 113 in the no-intervention group, with the reported primary comparison remaining uncertain. The live-birth comparison has a similar direction in its point estimate, but its interval also includes no difference. These data do not establish that the approaches produce identical outcomes, nor do they establish a definitive difference.

A non-significant p-value is not proof of no effect. In general, a p-value addresses compatibility with a specified null model under statistical assumptions; it does not state the probability that a treatment effect exists. The intervals are important because they show that a range of comparative effects remains compatible with the posted data. The registry’s intervals cross the respective no-difference values for both outcomes.

Random allocation is a strength of the recorded design because it aims to create comparable groups on average. However, the registry does not report enough detail to evaluate implementation, participant flow, missing outcomes, or the analysis population. The absence of masking and the lack of reported assessment procedures may also matter when interpreting outcomes, but the registry does not describe whether outcome assessors were masked or how the tests were administered.

The findings apply directly to the trial as recorded: patients undergoing donor-egg IVF, the stated scratch timing, the conventional preparation comparator, and the defined outcomes. The record does not describe participant characteristics or provide subgroup analyses that would support conclusions for narrower populations. Nor does it give detail about other clinical protocols that would allow assessment of broader transferability.

The registry results should be understood as evidence with uncertainty, not as medical advice or a treatment recommendation. They summarize recorded group outcomes and posted unadjusted comparisons. Important elements of the statistical and operational record—including missing-data procedures, multiplicity handling, and original sample-size assumptions—are not reported. Those limitations constrain how strongly the estimates can be interpreted.

17. Why This Trial Matters Statistically

This trial is statistically informative because it illustrates the difference between a point estimate and a precise conclusion. The primary comparison has a direction, but its interval spans no difference and values on either side. Reporting the estimate with its interval prevents the observed direction from being mistaken for a settled result. The p-value alone would not communicate the range of effects compatible with the data.

The comparison also demonstrates why outcome choice matters. A positive pregnancy test is an early binary outcome defined by a specific threshold and timing, while live birth is a later secondary outcome. Looking at both can provide context, but the outcomes are not interchangeable. Their similar direction does not remove uncertainty or make the secondary endpoint a substitute for the primary question.

Planning illustrations provide another statistical lesson: sample size depends on the effect a future study is intended to detect. Under the stated assumptions, planning for smaller fractions of the observed effect requires more participants per arm. Those calculations are not evidence that the trial was designed with those assumptions, nor are they a measure of the trial’s observed power. The original design justification is not reported in the registry record.

Finally, the record highlights the importance of transparent analysis reporting. The randomized parallel design and outcome counts are recorded, but key details about analysis populations, missing data, multiplicity, and methods are absent. Without them, readers can describe the posted comparisons but cannot fully assess their robustness. The lesson is not that missing reporting determines the result; it is that statistical conclusions depend on both estimates and the information needed to evaluate how those estimates were produced.

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.

Several limitations specific to this trial follow from the registry record. The absence of masking is recorded, but the record does not say which participants or staff knew allocation or whether outcome assessors were masked. The procedure and the conventional preparation comparator are described at a high level; further protocol details are not reported. The registry also does not provide participant characteristics, eligibility criteria, or a participant-flow account, limiting assessment of whom the results represent.

The posted outcome denominators are not accompanied by an explanation of missing results or exclusions. The analysis population and handling of missing data are not reported, and the registry does not state whether the comparisons were adjusted for any factors. The statistical analysis plan, original sample-size rationale, and any interim analyses are also not reported. These omissions restrict evaluation of the prespecification and robustness of the comparisons.

The record reports one secondary outcome while listing three outcome measures. Details of the other measures and any multiplicity strategy are not reported. This limits interpretation of the secondary result in the context of all planned outcomes. The safety information is also brief: serious adverse-event and death counts are reported, but event terms, collection methods, severity detail for other adverse events, and relatedness are not provided.

Finally, the comparative intervals include no difference for both posted outcomes. This leaves meaningful uncertainty about effect direction and size. The registry record alone does not establish whether further results or analyses were reported elsewhere, and no conclusions about unreported analyses can be drawn from the information recorded.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Endometrial Scratch Effect on Pregnancy Rates in Patients Undergoing Egg-donation IVF — NCT03108157.
• Registry record last updated 2020-06-23; status last verified 2020-06.
• Results first posted 2019-12-04.
• 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

NCT03108157 is a completed randomized, parallel-group trial sponsored by Procreatec. The registry records no masking and enrollment of 352. It compares endometrial scratch with conventional preparation alone in patients undergoing donor-egg IVF, with the scratch performed 3 to 4 weeks before embryo transfer.

The primary outcome is a positive pregnancy test, defined as hcG >10 UI/ml and measured 12 to 14 days after embryo transfer. Live birth, defined as pregnancy beyond 24 weeks, is posted as a secondary outcome. The posted unadjusted comparisons have intervals that include no difference. The registry does not report the original sample-size justification, detailed analysis plan, analysis populations, or missing-data procedures.