Effects of Oral Probiotic Supplementation on Group B Strep (GBS) Rectovaginal Colonization in Pregnancy: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effects of Oral Probiotic Supplementation on Group B Strep (GBS) Rectovaginal Colonization in Pregnancy (NCT01479478), a randomized na study. The primary outcome is Count of Participants With Positive Group B Streptococcus Rectovaginal Colonization Status at 35- 37 Weeks' Gestational Age.

2. Clinical Question

The trial record describes the investigators’ interest in whether oral probiotic supplementation during the second half of pregnancy might reduce maternal rectovaginal GBS colonization near the end of pregnancy. The stated rationale links colonization status to the possible need for maternal antibiotics during labor. The primary endpoint, however, is colonization status at the specified gestational window. It is not itself a measure of antibiotic use, neonatal infection, or the full range of maternal and infant outcomes.

The central statistical question is comparative: whether the observed frequency of a positive colonization result differed between the randomized groups. The posted counts are 20 participants in the probiotic group and 23 in the placebo group, among participants with available primary-outcome data. Those counts should be interpreted alongside their group sizes and the uncertainty around the estimated difference, rather than as evidence on their own. The registry record identifies the primary outcome and the reported group comparison, but it does not report a fuller clinical decision framework or a prespecified threshold for a meaningful difference.

3. Trial Design

The study is listed as a randomized, parallel-group trial with quadruple masking and placebo control. It compared oral probiotic dietary supplementation with a placebo capsule. The intervention descriptions state that participants were to take one capsule daily until delivery. The registry record identifies Stanford University as the sponsor and lists the study as completed.

The enrollment was 251. For the primary analysis, the record says that participants with available data were included. The posted primary outcome counts use 108 participants in the probiotic group and 117 in the placebo group. These analysis group sizes are not the same as the total enrollment, and the record does not explain why primary outcome data were unavailable for other enrolled participants. It also does not report the original target sample size or the assumptions used to set it.

The primary outcome was positive Group B Streptococcus rectovaginal colonization status at 35 to 37 weeks’ gestational age. The registry lists additional outcomes covering infection-related events and gestational age at delivery. Its record contains 18 outcome measures and identifies 17 posted secondary outcomes. The available outcome descriptions include differing follow-up windows, so each outcome concerns its own measurement period and should not be treated as interchangeable with the primary endpoint.

The sponsor reports a Cochran-Mantel-Haenszel superiority analysis, with p = 0.87. The registry record does not report the stratification factors or further details needed to reconstruct that analysis. A separate unadjusted calculation from the posted primary counts gives p = 0.828; it is not the same analysis as the sponsor’s reported test.

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: Only expecting mothers were enrolled in this study. Neonatal data were collected from respective pregnancies, however, the neonates were not considered to be enrolled in this study.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Participants with available data were included in the analysis

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 Count of Participants With Positive Group B Streptococcus Rectovaginal Colonization Status at 35- 37 Weeks' Gestational Age, measured over 35 to 37 weeks gestational age.

The primary endpoint counts participants with a positive Group B Streptococcus rectovaginal colonization result at 35 to 37 weeks’ gestational age. The registry describes gestational age in full weeks and states that participants with available data were included. The endpoint is therefore a binary status recorded during a defined late-pregnancy window, summarized as a count in each randomized group.

This endpoint is relevant to the trial’s stated question because the investigators were interested in maternal GBS colonization during pregnancy. The registry’s rationale notes that colonization may relate to the need for maternal antibiotic administration during labor. That rationale does not make colonization status a direct measurement of antibiotic use or of clinical infection. Those are distinct outcomes, and the primary endpoint should be interpreted specifically as the posted colonization result.

In the probiotic group, 20 of 108 participants with available primary-outcome data had a positive result; in the placebo group, 23 of 117 did. Comparing these counts requires attention to the number assessed in each group, since the groups are not the same size. The registry record does not provide a separate account of the laboratory procedure, the handling of results outside the specified gestational window, or a clinical threshold for a meaningful difference. These details limit how fully the endpoint can be evaluated beyond its stated definition.

7. Results Posted in the Registry

• Probiotic Dietary Supplement: 18.5% (20/108) versus 19.7% (23/117) on control; risk difference -1.1 percentage points (95% CI -11.4 to 9.1), risk ratio 0.94 (0.55–1.62); unadjusted two-proportion z-test p = 0.828.

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.

Count of Participants With Urinary Tract Infection

• 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:
  • Probiotic Dietary Supplement: 6.8% (8/118) versus 7.3% (9/123) on control; risk difference -0.5 percentage points (95% CI -7.0 to 5.9), risk ratio 0.93 (0.37–2.32); unadjusted two-proportion z-test p = 0.871.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Probiotic Dietary Supplement and the control. The interval gives the range of effects that remain compatible with the data.

Count of Participants With Intrapartum Chorioamnionitis

• 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:
  • Probiotic Dietary Supplement: 4.2% (5/118) versus 3.3% (4/121) on control; risk difference 0.9 percentage points (95% CI -3.9 to 5.8), risk ratio 1.28 (0.35–4.66); unadjusted two-proportion z-test p = 0.705.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Probiotic Dietary Supplement and the control. The interval gives the range of effects that remain compatible with the data.

Count of Participants With Endometritis

• 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:
  • Probiotic Dietary Supplement: 0.0% (0/116) versus 1.7% (2/119) on control; risk difference -1.7 percentage points (95% CI -4.0 to 0.6); unadjusted two-proportion z-test p = 0.161.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Probiotic Dietary Supplement and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists secondary outcomes covering urinary tract infection, intrapartum chorioamnionitis, endometritis, cellulitis, bacteremia, sepsis, other infectious morbidity, and gestational age at delivery. It records 17 posted secondary outcomes. These outcomes broaden the subject matter beyond the primary colonization endpoint, but they concern different events and follow-up windows. They should be interpreted on their own definitions rather than combined into a single overall measure.

The detailed secondary results available for review include sparse event counts. With few events, comparisons can be imprecise, and a small change in the number observed can have a noticeable effect on an estimate. The pattern across a collection of endpoints should not be characterized as uniformly favorable or unfavorable without complete outcome-level results and a prespecified way to synthesize them. The registry record does not establish such a synthesis.

Secondary findings do not override the primary comparison. They may provide additional context about outcomes the trial tracked, but they do not answer the primary question of colonization status at 35 to 37 weeks’ gestational age. Conversely, the primary colonization result does not determine the results for maternal infection or delivery outcomes. Each endpoint addresses a distinct question.

Unadjusted secondary results carry less weight when many outcomes are examined because the chance of finding an apparently notable result by chance increases as the number of comparisons grows. This is a general statistical concern. The registry record does not report a multiplicity adjustment or a prespecified hierarchy for interpreting secondary analyses. It is therefore prudent to treat the secondary comparisons as exploratory context rather than definitive evidence of differences. The available record also does not give detailed numerical results for every posted secondary outcome, so no complete cross-outcome pattern can be inferred from the entries.

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

• Count of Participants With Urinary Tract Infection
• Count of Participants With Intrapartum Chorioamnionitis
• Count of Participants With Endometritis
• Count of Participants With Cellulitis
• Count of Participants With Bacteremia
• Count of Participants With Sepsis
• Count of Participants With Other Infectious Morbidity
• Gestational Age at Delivery

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary: each participant with an available result is counted as having either positive or non-positive GBS rectovaginal colonization status during the specified gestational window. The posted data give the number of positive participants and the number assessed in each group. A comparison of these groups can be expressed as a difference in risks, a ratio of risks, or an odds ratio. These measures describe different scales, so their values should not be treated as interchangeable.

What does a risk difference describe?

A risk difference subtracts the event proportion in one group from the event proportion in the other. Its zero value corresponds to equal proportions; negative and positive values indicate opposite directions according to the stated group order. The recalculated primary comparison is presented as probiotic relative to placebo. Its estimate is slightly negative, while its interval includes zero and values on both sides. This means the observed direction is not estimated precisely enough to rule out a difference in either direction.

The posted risk difference is a simple, unadjusted calculation from the group counts. It does not account for any stratification or covariate adjustment. The registry’s sponsor-reported analysis uses the Cochran-Mantel-Haenszel method, which can compare categorical outcomes while accounting for strata. The specific strata and other analysis details are not reported in the registry record, so the sponsor’s result cannot be reconstructed fully from the description alone.

What does a p-value tell the reader?

A p-value measures how unusual data at least as incompatible with a specified null hypothesis would be if that null hypothesis and the model assumptions were true. It does not state the probability that the null hypothesis is true. Nor does a large p-value prove that the groups are identical. The sponsor reports p = 0.87 for its superiority analysis. The unadjusted recalculation gives p = 0.828. The values arise from different methods and should remain clearly distinguished.

A p-value also does not show the size of a difference or its practical importance. For that, the estimate and its interval are more informative. An interval gives a range of values compatible with the data under the method used. If it includes the null value for a difference, it does not exclude no difference at the interval’s stated confidence level. The confidence level for the posted recalculated interval is not reported in the registry record, so it should not be assigned a level by assumption.

Why does the analysis population matter?

The registry states that participants with available data were included in the primary analysis. This is an available-data approach, but the record does not report the reasons for missing outcomes, any imputation method, or a sensitivity analysis for missingness. Random allocation supports a fair comparison at assignment; it does not, by itself, ensure that a subset with observed outcomes remains comparable if outcome availability is selective. The difference between total enrollment and the primary analysis group sizes makes transparent reporting of missing data relevant, while the available registry entries do not allow its potential influence to be quantified.

How should binary-event methods be read?

Counts of participants with an event are appropriate summaries for a binary endpoint. The denominator matters because the same count can correspond to different proportions when group sizes differ. Risk-based comparisons make the group contrast explicit, while the raw counts keep the underlying observed events visible. When events are uncommon, estimates can be sensitive to a small change in the number of events, and intervals may be broad. This is a general statistical consideration, not a claim that any particular modeling assumption was used beyond what the registry record states.

The registry identifies one sponsor-reported analysis for the primary comparison and gives its method as Cochran-Mantel-Haenszel. It does not report a full statistical analysis plan, the test’s sidedness, stratification variables, adjustment choices, or interim analyses. Those details should not be inferred. The recalculated unadjusted comparison is a transparent descriptive complement based on the posted summary counts, not a replacement for the sponsor’s stated method.

11. Confidence Intervals and Precision

The primary comparison has an interval that extends from a negative difference to a positive difference. Because it spans zero, the interval does not rule out no difference under the method used. It also includes values in both directions, so the observed estimate should not be read as establishing a consistent direction of effect. The confidence level for this recalculated interval is not reported in the registry record.

Confidence intervals express uncertainty about an estimated quantity. In general, a narrower interval indicates greater precision, while a wider interval allows a broader range of values to remain compatible with the data. An interval is not a guarantee that the true value falls within its endpoints, and it does not show the probability that a specific value is true. Its interpretation depends on the method and confidence level, and the registry does not state the confidence level for the recalculated interval.

The primary analysis includes 108 participants in the probiotic group and 117 in the placebo group, with 20 and 23 positive results, respectively. These event counts provide limited information for pinning down a difference precisely. The interval’s span across the null and both directions is consistent with uncertainty in the estimated contrast. A non-small p-value does not narrow that uncertainty or prove equivalence.

The sponsor’s p = 0.87 comes from its reported Cochran-Mantel-Haenszel superiority analysis. The recalculated p = 0.828 and interval come from an unadjusted comparison of posted counts. They answer closely related but not identical statistical questions. The registry record does not give enough detail to match the sponsor’s analysis precisely or to attach the recalculated interval to the sponsor’s test. Precision should therefore be assessed from each result within the method that produced it, not by combining them.

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 sample-size figures are planning illustrations based on the observed effect, not the trial’s original design calculations. For this binary-outcome comparison, the listed quantities are participants per arm. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set to the stated fraction of the observed effect. The original trial’s own sample-size assumptions are not reported in the registry record.

For planning at 100% of the observed effect, the illustration gives 18,668 participants per arm for 80% power and 24,990 per arm for 90% power. At 75% of the observed effect, it gives 33,377 per arm for 80% power and 44,681 per arm for 90% power. At 50% of the observed effect, it gives 75,521 per arm for 80% power and 101,101 per arm for 90% power.

In plain language, 80% power means that, under the planning assumptions and if the specified effect were real, a study of the stated size would have an 80% chance of meeting the chosen significance criterion. The 90% column describes a higher chance under those same assumptions, and therefore calls for more participants per arm. Smaller effects are harder to distinguish from random variation, so planning to detect a smaller effect requires more participants. These values are not observed power; they are hypothetical planning estimates built from the observed effect and stated assumptions. They should not be read as the number enrolled or as evidence about the trial’s probability of success.

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 = 0.197; treatment proportion p₁ = 0.185; average p̄ = 0.191.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5558 = 1.0893.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5557 = 0.4677.
4. n = (1.0893 + 0.4677)² / (-0.0114)² = 18,667.4, rounded up to 18,668 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 <- 0.196581196581197                          # control proportion
p1 <- 0.185185185185185                          # 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(1479478)
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 = 18,668 (80% power), 24,990 (90% power)
 75% of observed effect: n per arm = 33,377 (80% power), 44,681 (90% power)
 50% of observed effect: n per arm = 75,521 (80% power), 101,101 (90% power)
power.prop.test: 18667.4 
Simulated power at n = 18,668 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. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary superiority analysis as a Cochran-Mantel-Haenszel test, with p = 0.87. This is the sponsor’s stated inferential result. The record does not provide the full details of the analysis, including any strata used, so the test cannot be independently reproduced from the method label alone.

A separate unadjusted recalculation from the posted counts gives p = 0.828 and a risk-difference estimate with an interval spanning zero. That calculation uses the available group summaries and does not reproduce the sponsor’s stratified method. The two p-values are close, but they should not be treated as interchangeable or as if they came from one analysis. They reflect different procedures and potentially different assumptions.

The registry identifies no discrepancy between the posted summary and the recalculated result. The sponsor’s analysis remains the reported trial analysis, while the unadjusted calculation offers a simple comparison that can be understood from the counts. Neither p-value is a measure of clinical importance or proof of no effect. The effect estimate and its uncertainty, the analysis population, and the limits of the registry’s methodological detail all remain important to interpretation.

15. Multiplicity, Missing Data and Analysis Populations

The registry record lists a primary outcome and 17 posted secondary outcomes, but does not report how the investigators planned to address multiplicity. When several outcomes are tested, the probability of at least one apparently unusual result can increase even when there is no underlying difference. Statistical approaches to this issue include adjusting significance thresholds or defining a hierarchy of outcomes, but the record does not say whether either approach was used. No such plan should be assumed.

The record reports one primary analysis using a Cochran-Mantel-Haenszel method. It does not provide a full statistical analysis plan, details of interim analyses, or information about whether outcomes or analyses were selected after examining the data. These items are not reported in the registry record. Their absence from the record is a limit on assessment, not evidence that a particular procedure was or was not performed.

For the primary outcome, the stated analysis population is participants with available data. The group sizes are 108 for probiotic and 117 for placebo. The overall enrollment was 251. The registry does not describe why primary data were unavailable for some enrolled participants, whether missingness differed by group, or whether any imputation or sensitivity analysis was conducted. Without these details, the possible effect of missing outcome data cannot be assessed from the posted record.

The analysis population description also does not establish that the primary analysis followed an intention-to-treat approach. The record does not report a full account of participants by randomized group, treatment received, adherence, or exclusions from the analysis. Those details are not reported in the registry record. Consequently, the available results support interpretation of the analyzed participants, while leaving open questions about the consequences of missing data and analysis-set selection.

16. 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 5% reporting threshold.

Most frequent serious adverse event terms

Serious events with the highest arm-level rate: any other anticipated or unanticipated life-threatening event:intra-uterine fetal growth restriction (0.8%).

The registry reports serious adverse event information for 125 participants at risk in the probiotic group and 126 in the placebo group. One participant in the probiotic group had a serious adverse event; none did in the placebo group. The reported deaths were zero in both groups. The record lists one serious-event term, “Any other anticipated or unanticipated life-threatening event: intra-uterine fetal growth restriction,” at 0.8%.

No other adverse events were reported in either group in the posted counts. These figures describe events recorded in this trial and the populations listed as at risk. They should not be treated as proof that an intervention is free of risk or as a reliable estimate of the frequency of rare harms. The event count is small, and the registry entry does not provide further case descriptions, timing, relatedness assessments, or a detailed safety-analysis plan.

Serious adverse events are distinct from the primary colonization endpoint. Their counts do not answer the efficacy question, and the primary result does not determine the safety interpretation. The registry record supports a descriptive account of the posted events, not a broad conclusion about safety.

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

The posted primary data show 20 positive GBS rectovaginal colonization results among 108 participants with available data in the probiotic group, and 23 among 117 in the placebo group. The sponsor’s reported superiority test has p = 0.87. An unadjusted recalculation gives p = 0.828, and its interval includes zero. Taken together, the posted results do not show a clear statistical separation between the groups on this endpoint.

That finding does not establish that the groups are equivalent, that any difference is absent, or that a clinically important effect has been ruled out. The interval allows differences in both directions, and the registry record does not report an equivalence margin or a non-inferiority design. A large p-value is not proof of no effect; it indicates that the reported data do not provide strong evidence against the null under the test used.

The endpoint is colonization status at 35 to 37 weeks’ gestational age. It is not a direct measure of antibiotic administration during labor, even though the registry describes antibiotic use as part of the study rationale. Nor does it directly answer questions about every infection-related outcome, delivery outcome, or potential adverse event. Those outcomes require their own results and interpretation.

The result also applies to the participants included in the available-data analysis. The registry does not explain missing primary outcome data or report sensitivity analyses addressing it. This limits confidence in how fully the analyzed comparison represents everyone enrolled. Overall, the result is best understood as an uncertain comparison of the observed colonization counts, not as a definitive statement about all possible clinical consequences of supplementation.

18. Why This Trial Matters Statistically

This trial is statistically instructive because it distinguishes the observed group counts from the uncertainty around a group comparison. The counts are straightforward to report, but they do not by themselves establish a difference. A risk-based estimate and interval clarify both the direction of the observed contrast and the range of values that remain plausible given the data.

It also illustrates why a non-significant result is not the same as evidence of equivalence. The primary interval includes zero and extends in both directions. Without a prespecified equivalence or non-inferiority margin, the analysis does not show that any difference is sufficiently small to be unimportant. The sponsor’s p-value and the unadjusted recalculation both need to be read as tests of a null comparison, not as probabilities that the treatment has no effect.

The contrast between the sponsor’s Cochran-Mantel-Haenszel analysis and the unadjusted recalculation is another useful lesson. Similar-looking p-values can arise from methods with different assumptions and adjustment structures. Reporting the method and distinguishing the sponsor’s result from a simple recalculation helps avoid treating all analyses as interchangeable. The registry record’s limited method detail also demonstrates why a method name alone may not be enough to reproduce an analysis.

Finally, the available-data population and multiple secondary outcomes matter to interpretation. Missing outcomes can affect which participants contribute to a comparison, while numerous secondary tests raise multiplicity concerns. These are not reasons to disregard the results; they are reasons to describe the evidence with appropriate restraint and to distinguish what the record establishes from what it leaves uncertain.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The primary analysis includes participants with available data, but the registry does not explain why outcome data were unavailable for some enrolled participants. It also does not report imputation, sensitivity analyses, or a full account of participants analyzed by randomized group. The effect of missing data on the comparison therefore cannot be evaluated from the record.

The sponsor’s primary analysis is identified as Cochran-Mantel-Haenszel, but the registry does not report the strata or enough other details to reproduce the test. The confidence level for the unadjusted recalculated interval is also not reported. The original design’s sample-size justification and assumptions are not reported; the displayed planning illustrations are based on the observed effect and are not a record of the trial’s design.

The registry lists multiple secondary outcomes, but does not report a multiplicity strategy. This limits the strength of conclusions drawn from individual secondary comparisons. Some secondary outcomes concern uncommon events, which can make estimates unstable and imprecise. The detailed secondary results available in this record do not support a complete assessment of every listed outcome.

The primary endpoint is a colonization result at a specified gestational window, not a direct measure of antibiotic administration or every downstream clinical outcome. The record does not provide enough detail about measurement procedures or missing-result handling to assess those aspects. Safety information is also limited to the posted event counts and does not include detailed case narratives or relatedness assessments. These limits call for a focused interpretation of the registry results rather than broad claims beyond the outcomes and analyses reported.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Effects of Oral Probiotic Supplementation on Group B Strep (GBS) Rectovaginal Colonization in Pregnancy — NCT01479478.
• Registry record last updated 2018-08-20; status last verified 2018-08.
• Results first posted 2018-08-20.
• 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.

23. Record Summary

NCT01479478 is a completed randomized, quadruple-masked, parallel-group, placebo-controlled trial sponsored by Stanford University. It enrolled 251 participants and compared a daily probiotic dietary supplement capsule with a daily placebo capsule until delivery.

The primary endpoint was the count of participants with positive GBS rectovaginal colonization status at 35 to 37 weeks’ gestational age. The available-data analysis recorded 20 positive results among 108 participants in the probiotic group and 23 among 117 in the placebo group. The sponsor reported a Cochran-Mantel-Haenszel superiority analysis with p = 0.87; an unadjusted recalculation gives p = 0.828.

The registry also lists secondary infection and delivery outcomes and reports serious adverse event counts. It does not report the original sample-size assumptions, detailed missing-data methods, or a multiplicity plan. The primary comparison is uncertain and should be interpreted as a result for the stated colonization endpoint, not as a conclusion about every clinical outcome.