Prevention of Preterm Birth With a Pessary in Singleton Gestations: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Prevention of Preterm Birth With a Pessary in Singleton Gestations (NCT02056652), a randomized na study. The primary outcome is Number of Subjects Experiencing Preterm Birth.

2. Clinical Question

This is a comparison of an assigned device strategy with no device, rather than a comparison of the device with no obstetrical care. The no-pessary group is described as receiving standard obstetrical management. The registry record does not give enough detail to characterize all aspects of care or to determine how other treatments were used.

The title and condition list indicate the clinical setting, but they do not substitute for full eligibility criteria. For example, the record does not report the precise cervical-length threshold, how or when cervical length was measured, or whether additional eligibility conditions applied. Those details matter when judging how closely the enrolled population represents other people with singleton gestations or a short cervix.

3. Trial Design

The registry identifies this as a randomized, parallel-group trial with no masking. Participants were assigned to the pessary group or the no-pessary group. Because masking was listed as none, the record does not describe blinded treatment assignment after randomization. The method used to generate the allocation sequence, allocation concealment, and procedures for maintaining the assigned groups are not reported in the registry record.

The registered enrollment was 122. The primary outcome results list 60 participants in the pessary group and 58 in the no-pessary group. These are the group sizes reported for that outcome; the registry record does not explain the relationship between outcome denominators and the overall enrollment or report whether all enrolled participants were included in the outcome analysis.

The intervention was the Bioteque cup pessary, described as being placed between 18 and 23 6/7 weeks gestation and removed during the 37th week of pregnancy, or earlier if indicated. The comparison group was to receive no pessary and standard obstetrical management. The registry lists the study phase as NA. The study is marked completed, with a start date of 2014-02 and a primary completion date of 2016-09.

The design description does not report the trial’s original sample-size justification, planned statistical model, analysis population, or strategy for handling missing outcome data. It also does not report whether interim analyses were planned or conducted. These omissions limit the ability to compare the posted analysis with a prespecified protocol. The record lists no reported analyses, so the displayed estimates should be read as the posted outcome comparisons rather than as a detailed account of a sponsor-reported analysis plan.

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 Number of Subjects Experiencing Preterm Birth, measured over Before 37 weeks gestation (20 0/7 - 36 6/7 weeks).

The primary endpoint counts participants who experienced birth before 37 weeks gestation. The registry gives the timeframe as 20 0/7 to 36 6/7 weeks and says birth before 37 weeks was captured. This is a binary outcome at the participant level: each participant either met the stated event definition or did not. The endpoint is reported as a count of participants, not as a measure of gestational duration or the number of days gained before delivery.

In general, a threshold-based birth outcome can be used to compare how often an event occurs across trial groups. It translates the timing of birth into an event that can be counted, while not conveying the full distribution of gestational ages or the circumstances of each birth. The registry record does not report additional detail about outcome adjudication, data collection, or whether the outcome was assessed by someone unaware of group assignment.

The endpoint is clinically relevant to the trial’s stated question because it captures birth before the specified gestational threshold. It does not, by itself, summarize every dimension of pregnancy or newborn health. The registry lists separate secondary outcomes, including spontaneous preterm birth, spontaneous rupture of membranes, neonatal death, chorioamnionitis, and average birth weight. Those outcomes address other aspects of the trial, but the primary endpoint remains the count of participants with birth before 37 weeks gestation.

7. Results Posted in the Registry

• No Pessary: 39.7% (23/58) versus 43.3% (26/60) on control; risk difference -3.7 percentage points (95% CI -21.4 to 14.1), risk ratio 0.92 (0.60–1.41); unadjusted two-proportion z-test p = 0.685.

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 That Experienced Spontaneous Preterm Births on Trial

• 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:
  • No Pessary: 32.8% (19/58) versus 38.3% (23/60) on control; risk difference -5.6 percentage points (95% CI -22.8 to 11.7), risk ratio 0.85 (0.52–1.39); unadjusted two-proportion z-test p = 0.527.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between No Pessary and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants Experiencing Spontaneous Rupture of Membranes

• 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:
  • No Pessary: 17.2% (10/58) versus 30.0% (18/60) on control; risk difference -12.8 percentage points (95% CI -27.9 to 2.4), risk ratio 0.57 (0.29–1.14); unadjusted two-proportion z-test p = 0.103.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between No Pessary and the control. The interval gives the range of effects that remain compatible with the data.

Number of Subjects Experiencing Neonatal Death

• 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:
  • No Pessary: 10.3% (6/58) versus 5.0% (3/60) on control; risk difference 5.3 percentage points (95% CI -4.2 to 14.9), risk ratio 2.07 (0.54–7.89); unadjusted two-proportion z-test p = 0.274.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between No Pessary and the control. The interval gives the range of effects that remain compatible with the data.

The registry names five secondary outcomes: average birth weight, spontaneous preterm birth, spontaneous rupture of membranes, neonatal death, and chorioamnionitis. Numerical group comparisons are posted for spontaneous preterm birth, spontaneous rupture of membranes, and neonatal death. Numerical results for average birth weight and chorioamnionitis are not reported in the registry record.

Across the posted secondary comparisons, the estimated directions are not consistent across outcomes. The confidence intervals include the no-difference value, so the secondary comparisons do not give a precise or uniform account of group differences. In broad terms, they do not resolve the uncertainty in the primary result. They also do not provide independent confirmation: the outcomes come from the same trial and may describe related aspects of the same participants’ pregnancies and births.

Secondary endpoints can provide useful context, since they address outcomes beyond the primary measure of birth before 37 weeks. However, interpreting several outcomes raises the possibility of chance findings when many comparisons are examined. The registry record does not report a multiplicity adjustment, a hierarchy among secondary outcomes, or a prespecified plan identifying which secondary comparisons were confirmatory. The posted secondary p-values are unadjusted, and the record lists no reported analyses.

For these reasons, secondary results carry less weight than a clearly prespecified primary analysis when drawing an overall statistical conclusion. They are informative as descriptive findings, but should not be used to overturn or strengthen the primary result without considering their uncertainty, the number of comparisons, and the missing analysis details. The trial’s secondary results do not establish a consistent effect pattern across the listed outcomes.

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

• Average Birth Weight of Babies Born on Trial
• Number of Participants That Experienced Spontaneous Preterm Births on Trial
• Number of Participants Experiencing Spontaneous Rupture of Membranes
• Number of Subjects Experiencing Neonatal Death
• Number of Subjects Experiencing Chorioamnionitis

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference describe?

A risk difference compares the observed proportions with an event in two groups by subtracting one group’s proportion from the other. The posted comparison is for no pessary relative to pessary. A negative estimate therefore indicates that the recorded event proportion was lower in the no-pessary group under that comparison order. The value -0.037 is the posted estimate; it should not be read as a guarantee about the effect in other participants or settings. The registry also gives the event counts and group denominators, which show the observations underlying the comparison.

In general, a risk difference expresses an absolute contrast on the scale of the event proportion. It is often useful when the practical question concerns how much the event frequency differs between groups. Its interpretation depends on the event definition and the comparison order. Reversing the group order would reverse the sign while leaving the underlying comparison unchanged.

How should the risk ratio and odds ratio be read?

The risk ratio compares the event proportions as a ratio, while the odds ratio compares the odds of the event. Both express relative rather than absolute contrasts. The posted risk ratio is 0.915 and its confidence interval is 0.596 to 1.406. The posted odds ratio is 0.859 and its confidence interval is 0.413 to 1.789. For each measure, the interval includes the value that corresponds to no relative association. The estimates are not interchangeable with the risk difference: they use different scales and can convey different impressions when an outcome is common.

In general, ratios are interpreted relative to their no-association value, whereas a risk difference is interpreted relative to no absolute difference. None of these measures alone describes uncertainty; the associated confidence interval is essential. Nor do these summary measures show whether the comparison was adjusted for other factors. The registry record does not report an adjusted analysis.

What does the p-value add?

The unadjusted p-value for the primary comparison is 0.685. In general, a p-value describes how compatible the observed data are with a statistical model that assumes no group difference, under the assumptions of the test. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. A p-value also does not show how likely the result is to be replicated.

The p-value should be considered alongside the estimated effect and its interval. Here, the interval conveys substantial uncertainty about the direction and magnitude of the primary contrast. A p-value alone would not convey that range. The registry record does not identify a test procedure or report enough analysis detail to assess all assumptions underlying the posted p-value.

Why does randomization matter, and what does it not guarantee?

In general, random assignment is intended to make treatment groups comparable, on average, with respect to measured and unmeasured factors at the point of assignment. It provides a basis for comparing outcomes by assigned group. Randomization does not guarantee that the realized groups are identical, does not prevent missing outcome data, and does not ensure that every participant follows the assigned strategy. The registry identifies the allocation as randomized, but the sequence-generation method, concealment process, adherence information, and analysis population are not reported in the registry record.

The trial is listed as having no masking. Lack of masking can matter for outcomes that rely on judgment or participant reporting. The primary outcome is a birth occurring before a specified gestational threshold, but details about assessment and adjudication are not reported. This does not establish that outcome measurement was biased; it identifies information needed to judge that possibility.

What is the role of the confidence interval?

In general, a confidence interval gives a range of effect estimates that are compatible with the observed data under the statistical method used. It is not a statement that the true effect has a particular probability of lying in the reported interval. The primary risk-difference interval, -0.214 to 0.141, includes the no-difference value. It also extends in both directions from the point estimate, indicating that the data do not pin down the direction of the contrast with precision.

The interval’s interpretation depends on the method used to calculate it. The registry record does not report that method. The posted interval can still be read descriptively, but its exact coverage properties and any adjustments cannot be verified from the registry record.

What analysis details are missing?

The registry record lists no reported analyses. It does not report a prespecified statistical analysis plan, a primary analysis population, a missing-data method, an adjustment strategy, or whether analyses followed assigned treatment or treatment received. It also does not report a method for accounting for repeated or clustered observations, although the primary endpoint is described as a participant count. These omissions do not invalidate the posted counts, but they restrict assessment of how the comparisons were produced and whether analysis choices could have affected them.

The posted statistical summaries are unadjusted comparisons. In general, unadjusted comparisons describe group outcomes without accounting for other covariates. Because randomization is the allocation method, the unadjusted comparison is a direct summary of outcomes by group; nevertheless, an analysis plan and details of follow-up are needed to assess whether the comparison preserves the intended randomized contrast. The registry record does not provide those details.

11. Confidence Intervals and Precision

The primary risk-difference estimate is -0.037, and its 95% confidence interval runs from -0.214 to 0.141. Because this interval includes the no-difference value, the posted results are compatible with a range of contrasts in either direction. Its breadth means that the estimate is not precise enough to rule out potentially meaningful differences under the outcome scale. The interval should be interpreted as uncertainty around the estimated contrast, not as a range of observed participant outcomes.

The relative measures also show considerable uncertainty. The risk ratio is 0.915, with a 95% confidence interval from 0.596 to 1.406; the odds ratio is 0.859, with a 95% confidence interval from 0.413 to 1.789. Each interval includes the no-association value for its measure. The three estimates describe the same comparison using distinct scales, so they do not represent separate replications of the result.

The event counts are 26 of 60 in the pessary group and 23 of 58 in the no-pessary group. Those observations are the basis for the posted estimate, but counts alone do not show how much uncertainty surrounds a group contrast. The confidence intervals make that uncertainty visible. The registry record does not report the method used to construct the intervals, so details such as the interval procedure cannot be assessed from the record.

In general, an interval that spans the no-difference value does not establish equivalence. Equivalence requires a prespecified margin and an analysis designed to evaluate whether effects fall within that margin; neither is reported in the registry record. The primary interval therefore supports a cautious conclusion: the direction and magnitude of the difference remain uncertain.

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 expressed as participants per arm, not as total enrollment or total events. They are illustrations based on the observed effect for the primary outcome, with rows considering 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. Each row gives a planning value for 80% power and one for 90% power. The figures are not the trial’s enrollment target or a report of the trial’s original design calculation.

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 the stated fraction of the observed effect. Under these assumptions, the 80% power column represents the participants per arm in a hypothetical study designed to have an 80% chance of detecting the specified effect if that effect were the true one and the assumptions held. The 90% power column describes the corresponding planning target for a higher chance of detection. Greater planned power generally requires more participants for the same effect.

The rows illustrate the relationship between effect size and sample size: smaller effects require more participants to detect, all else being equal. This is why planning for 75% or 50% of the observed effect requires more participants per arm than planning for the full observed effect. The values depend on the observed estimate, which is uncertain; using an observed effect as a planning anchor can therefore produce unstable projections.

These calculations are planning illustrations, not observed power. Observed power is not a useful substitute for interpreting the confidence interval and effect estimate after a trial has been completed. The registry record does not report the assumptions used for the trial’s original design, including its original 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 = 0.433; treatment proportion p₁ = 0.397; average p̄ = 0.415.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6968 = 1.3657.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6963 = 0.5860.
4. n = (1.3657 + 0.5860)² / (-0.0368)² = 2,815.7, rounded up to 2,816 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 <- 0.433333333333333                          # control proportion
p1 <- 0.396551724137931                          # 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(2056652)
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 = 2,816 (80% power), 3,769 (90% power)
 75% of observed effect: n per arm = 5,023 (80% power), 6,723 (90% power)
 50% of observed effect: n per arm = 11,335 (80% power), 15,174 (90% power)
power.prop.test: 2815.7 
Simulated power at n = 2,816 per arm: 0.801 (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 record does not report how the trial addressed multiplicity. Multiplicity arises when statistical comparisons are made across several outcomes or analyses: even if no real effects exist, examining many comparisons can increase the chance that at least one appears unusual by chance. A prespecified outcome hierarchy or adjustment procedure can clarify how such comparisons should be interpreted. No such plan is reported for this trial.

The record identifies one primary endpoint and lists five secondary outcomes, while posting numerical comparisons for three of them. It does not report whether those secondary analyses were planned in advance, whether any subgroup or additional analyses were conducted, or whether the primary and secondary tests were interpreted under a formal family-wise strategy. Consequently, the secondary p-values should be treated as unadjusted findings rather than as multiplicity-controlled evidence.

Missing-data handling is also not reported. The record does not state whether outcome data were complete, how participants with unavailable outcome information were handled, or whether any imputation or sensitivity analysis was used. The reported group denominators describe the primary outcome results, but the registry does not explain whether every randomized participant had outcome data or how the analysis population was defined. No missing-data count can be inferred from the posted information.

The analysis population is not reported in the registry record. It is therefore unclear whether the posted comparisons were based on all randomized participants, participants with available outcome data, or another defined population. The record also does not report whether participants were analyzed according to assigned group or treatment received. This distinction matters because exclusions or switching after randomization can affect the comparability created by random assignment.

Interim analyses and stopping rules are not reported. The statistical analysis plan, model specification, and any adjustment for baseline characteristics are also not reported. These omissions do not show that such procedures were absent; they mean the registry record does not document them. Together, the missing details constrain assessment of multiplicity, missingness, and the relationship between the posted comparisons and the trial’s prespecified analysis.

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.

Most frequent non-serious adverse event terms

The serious adverse-event summary reports 0 participants affected in the pessary group and 0 in the no-pessary group, with 61 at risk in each group. It also reports 0 deaths in each group. No serious adverse-event terms are listed. The at-risk counts in this safety summary differ from the group denominators reported for the primary outcome; the registry record does not explain the difference, so the denominators should be interpreted within their respective outcome summaries rather than reconciled by assumption.

The registry reports 3 participants affected by other adverse events in the pessary group and 6 in the no-pessary group, with 61 at risk in each group. These counts are descriptive. They do not establish whether an event was caused by the intervention, and the record does not provide event types or further detail for these other events.

Zero recorded serious events or deaths in this trial does not demonstrate that serious events cannot occur. In general, safety estimates based on limited observations may be uncertain, especially for uncommon events. The record’s safety figures should be read as the events reported during the trial, not as a complete characterization of safety in other settings or populations.

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

The posted primary results describe births before 37 weeks in the two randomized groups. The event counts were 26 of 60 participants in the pessary group and 23 of 58 in the no-pessary group. The estimated risk difference for no pessary relative to pessary was -0.037, with a 95% confidence interval from -0.214 to 0.141 and an unadjusted p-value of 0.685. The interval includes the no-difference value and allows for effects in either direction.

These data do not establish that the pessary changes the chance of birth before the specified threshold. They also do not establish that there is no difference, or that the two strategies are equivalent. A nonsignificant p-value is not proof of no effect. The uncertainty interval is important because it shows that the trial does not estimate the contrast precisely enough to distinguish a range of plausible effects.

The results apply most directly to the participants enrolled and the care strategies described in the registry. The title identifies singleton gestations, and short cervix is among the listed conditions, but detailed eligibility criteria are not reported. The record also does not describe all aspects of standard obstetrical management, adherence to the assigned strategy, or the analysis population. Those limits make it difficult to determine how closely the posted findings apply to other groups or care settings.

The secondary outcomes and safety counts add descriptive information, but they do not replace the primary comparison or settle its uncertainty. The registry record does not report the multiplicity plan, missing-data methods, or a detailed statistical analysis plan. Accordingly, the posted results support a measured description of what was observed in this trial, rather than a broad claim about effectiveness, equivalence, or safety.

In general, clinical decisions require consideration of evidence beyond a single trial’s statistical summaries. The trial results alone do not provide medical advice, and they should not be interpreted as a recommendation for or against either strategy.

17. Why This Trial Matters Statistically

This trial illustrates the difference between an estimated effect and the certainty of that estimate. The primary point estimate is close to the no-difference value, but the confidence interval spans a broad range that includes both directions. Reporting only the direction of the estimate or only the p-value would leave out important information about precision. The event counts, effect estimate, and interval together give a more complete statistical account.

It also illustrates why sample-size planning based on an observed effect needs careful interpretation. The planning figures use the observed primary effect as an anchor and show how requirements change when planning for smaller fractions of that effect. They are prospective illustrations under stated assumptions, not a measure of the trial’s observed success or a substitute for its confidence interval. The original design assumptions are not reported in the registry record.

The trial’s randomized, parallel-group structure is useful for comparing assigned strategies, while the lack of masking and the absence of reported analysis details leave questions about implementation and analysis. Randomization is an important design feature, but interpretation still depends on follow-up, outcome ascertainment, missing data, and analysis choices. The registry record does not document several of these elements.

Finally, multiple secondary outcomes create interpretive challenges. Their pattern is not uniform, their intervals include the no-difference value, and the record does not describe multiplicity control. This makes it important to distinguish the primary question from exploratory context and to avoid treating multiple unadjusted comparisons as a collection of independent confirmations. The example shows why statistical reporting should connect design, outcome definition, estimation, uncertainty, and analysis planning.

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 trial-specific details needed to assess the findings are not reported in the registry record. These include the detailed eligibility criteria, the cervical-length threshold used to identify a short cervix, and the measurement schedule. The title and listed conditions identify the broad setting, but they do not establish the exact characteristics of the enrolled population or the extent to which it represents other clinical settings.

The registry describes randomization but does not report the sequence-generation method or allocation concealment. It lists no masking. Details of treatment adherence, device placement, removal, treatment crossover, and other care received are not reported beyond the brief intervention descriptions. The record also does not report outcome adjudication procedures or whether outcome assessors were unaware of group assignment.

The primary outcome counts and safety summary use different reported group denominators, and the registry does not explain this. The relationship between the overall enrollment and the participants included in each outcome summary is not reported. Missing-data counts, exclusions, analysis-population definitions, and missing-data methods are not reported, so the completeness of outcome follow-up cannot be assessed from the record.

Statistical reporting is limited. The registry lists no reported analyses and does not report the original sample-size justification, the analysis plan, the interval method, adjustment for covariates, or a multiplicity strategy. The posted primary estimate is consequently difficult to compare with a prespecified analysis. The record also names average birth weight and chorioamnionitis among secondary outcomes but does not report numerical results for them.

These limitations are limits of what the registry record documents; they do not show that a procedure was not performed. They do, however, restrict assessment of bias, precision, generalizability, and the completeness of the reported outcome set.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Prevention of Preterm Birth With a Pessary in Singleton Gestations — NCT02056652.
• Registry record last updated 2018-05-29; status last verified 2018-04.
• Results first posted 2018-05-29.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry identifies NCT02056652 as Prevention of Preterm Birth With a Pessary in Singleton Gestations. It is listed as a completed, randomized, parallel-group study with no masking and phase NA. The sponsor is the University of Pennsylvania. The registry gives a start date of 2014-02, a primary completion date of 2016-09, and enrollment of 122.

The study compared a Bioteque cup pessary with no pessary and standard obstetrical management. The primary outcome was the number of participants experiencing birth before 37 weeks gestation. The posted primary comparison has a risk difference of -0.037, a 95% confidence interval from -0.214 to 0.141, and an unadjusted p-value of 0.685.

The registry lists five secondary outcomes, with numerical comparisons posted for three. Safety results report no serious adverse events or deaths in either group, alongside counts for other adverse events. The record does not report a detailed statistical analysis plan, missing-data methods, multiplicity handling, or the original sample-size assumptions.