Effect of Probiotic Lactobacilli (Lacidofil Cap®) for the Prevention of Antibiotic-Associated Diarrhea: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effect of Probiotic Lactobacilli (Lacidofil Cap®) for the Prevention of Antibiotic-Associated Diarrhea (NCT01058356), a registered phase not stated study. The primary outcome is Presence of AAD.

2. Clinical Question

The clinical question concerns whether probiotic Lactobacilli (Lacidofil cap®), compared with placebo, changes the occurrence of antibiotic-associated diarrhea (AAD) in adults receiving antibiotics. The registry record describes the planned study as randomized, double-blind, multicenter, and placebo-controlled. However, the posted comparison does not state the allocation method, so the record does not establish how participants were assigned to the comparison groups.

The registry record identifies pulmonary infection and antibiotic-associated colitis among the conditions associated with the study. Its background describes AAD as a complication of antibiotic use and explains the proposed rationale for probiotic therapy: helping reestablish intestinal microflora disrupted by antibiotics. That rationale is not itself evidence of a treatment effect.

The primary question is about the recorded occurrence of AAD, not symptom severity, duration, or recovery. Those outcomes are not reported in the registry record. The record also names a secondary outcome based on a less stringent bowel-habit-change definition. A comparison of these endpoints would require arm-specific outcome counts and an analysis that accounts for the study design; those results are not reported in the registry record.

3. Trial Design

The official study description identifies a prospective, randomized, double-blind, multicenter study of Lactidofil capsules for preventing AAD, and the brief summary describes the intended design as randomized and placebo-controlled. The registry record reports enrollment of 214 and a completed status. The recorded study start is 2009-01, and the recorded primary completion is 2010-01. The registry does not report the number of centers or the details of recruitment.

There is an important distinction between the design described for the study and what can be verified from the posted results. The comparison record is labeled “Lacidofil Capsule Versus Placebo Drug,” but the allocation method is not stated, and the posted comparison is not identified as a like-for-like randomized control comparison. The registry record therefore does not establish that the participants in the displayed groups were comparable through random assignment. The intended design should not be treated as proof that randomization was implemented in the analyzed comparison.

Additional design details are not reported in the registry record. These include the sequence-generation process, allocation concealment, the people kept unaware of assignment, treatment adherence, antibiotic regimens, and the handling of departures from the intended treatment. The timing and methods of outcome assessment beyond the primary timeframe are also not reported.

The planned follow-up for the primary endpoint is up to 14 days. The registry defines AAD by a stool-frequency and duration threshold, while the named secondary outcome uses a different threshold for bowel habit change. No primary or secondary outcome counts by group, effect estimates, confidence intervals, or hypothesis-test results are reported. As a result, the record describes the study question and some design features but does not permit a numerical assessment of the treatment comparison.

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: Patients who begin receiving antibiotics prior to 48 hours before enrollment in this study

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 Presence of AAD, measured over Up to 14 days.

The primary endpoint is the presence of AAD, measured as the number of participants meeting the registry definition. AAD is defined as watery stools more than 3 times per day for at least 2 days, with the outcome assessed over a timeframe of up to 14 days. This is a binary endpoint: each participant either meets the stated definition or does not, according to the recorded assessment.

Using a prespecified symptom definition can make outcome classification more consistent than relying on an unspecified impression of diarrhea. The threshold also makes clear that a single loose stool, or a short-lived change that does not meet the duration criterion, does not satisfy the registry definition. This endpoint measures whether the threshold was reached; it does not describe how intense or disruptive symptoms were, how long they continued beyond the threshold, or whether a particular cause was confirmed.

In general, a binary endpoint is commonly summarized by the number of participants with the event and the number assessed in each comparison group. A comparison can then be expressed using an appropriate effect estimate and its uncertainty. The registry record does not report the group-specific event counts or an effect estimate for this endpoint. The reason the investigators selected this endpoint, and any additional assessment rules for borderline or missing observations, are not reported in the registry record.

The named secondary outcome is the presence of bowel-habit change, defined as watery stools more than 2 times per day for at least 2 days. Its broader threshold makes it a distinct outcome rather than another presentation of the primary definition. Results for that secondary endpoint are not reported in the registry record.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The available outcome is described as a count of participants with an event, which calls for methods suited to binary data. The registry defines the primary event as meeting a specific stool-frequency and duration rule during follow-up up to 14 days. However, the event counts and denominators for the treatment groups are not reported in the registry record. Without these ingredients, a numerical effect estimate or a reproducible analysis cannot be reconstructed.

What does a binary endpoint represent?

In general, a binary endpoint classifies each participant into one of two outcome states, such as meeting or not meeting an event definition. The count with the event is interpreted alongside the number assessed. A proportion can describe the event frequency within a group, while a between-group effect measure describes the contrast. Different effect measures answer different questions: a difference in proportions describes an absolute contrast, whereas a ratio compares relative event frequencies. No such group-specific quantities are reported for the primary endpoint in the registry record, so none can be interpreted for this trial.

Outcome definitions are part of the statistical method because they determine which observations count as events. Here, the primary and secondary definitions use different thresholds for watery stools and duration. They should not be treated as interchangeable measures. In general, clearly specified thresholds support consistent classification, but the registry record does not describe who assessed the symptoms, how reports were collected, or how uncertain cases were adjudicated.

Why does allocation matter?

In general, random allocation is intended to make comparison groups similar, on average, with respect to measured and unmeasured characteristics at the time of assignment. It does not guarantee that the groups will be identical, and valid interpretation also depends on how the allocation process is implemented and how participants are analyzed. The study description calls the planned trial randomized and double-blind, while the posted comparison does not state the allocation method and is not a like-for-like control comparison. The record therefore does not supply enough information to verify random assignment for the posted comparison.

Blinding is intended to limit the influence of treatment knowledge on participant behavior, care, and outcome assessment. Whether blinding was maintained, which people were blinded, and whether the placebo matched the active treatment are not reported in the registry record. These omissions do not prove that blinding failed; they mean its implementation cannot be evaluated from this record.

What can uncertainty measures tell readers?

In general, a confidence interval pairs an effect estimate with an indication of its statistical uncertainty. It is informative because it shows which effect sizes are reasonably compatible with the analyzed data under the stated method and assumptions. Its interpretation depends on the quality of the underlying data and the appropriateness of the analysis. No confidence interval or effect estimate for AAD is reported in the registry record.

A hypothesis test assesses how unusual the data would be under a specified null model. A p-value is not the probability that the null hypothesis is true, and it does not quantify the magnitude of an effect. A small p-value cannot repair biased allocation, incomplete outcome ascertainment, or a poorly defined analysis population. No hypothesis-test result for the primary endpoint is reported, so a significance claim cannot be made from the registry record.

How should planning calculations be read?

The sample-size assumptions describe a planning illustration based on a fraction of the observed effect, with a two-sided significance level of 0.05, equal allocation, and a normal approximation. The stated convention is participants per arm for non-time-to-event outcomes. These are assumptions for planning illustrations, not a report of the trial’s original design calculation. The registry record does not report the investigators’ sample-size justification, and it does not provide the observed primary effect needed to evaluate an effect-based illustration against the trial’s actual results.

In general, a sample-size calculation asks how much information a proposed study would need to detect an effect under specified assumptions. Changing the effect size or other assumptions changes the planning result. Such a calculation is not observed power, and it cannot establish whether the trial found an effect. The available planning description should therefore be read as conditional methodology rather than a result of the trial.

For binary outcomes, the normal approximation is a method for approximating the distribution of an estimate or test statistic. In general, the reliability of an approximation depends on the amount and pattern of information in the data, including event frequency. The event counts needed to judge that issue are not reported in the registry record. The record also does not report whether an alternative model or small-sample method was prespecified or used.

Why do analysis choices matter?

In general, an analysis plan specifies the outcome definition, the comparison, the analysis population, the handling of missing data, and any adjustments for multiple testing. These choices affect the interpretation of estimates and their uncertainty. The registry record gives a primary outcome and a named secondary outcome, but the statistical analysis methods, analysis populations, and missing-data procedures are not reported. It is therefore not possible to determine whether the posted analyses followed a prespecified plan or how sensitive results might be to alternative choices.

10. Exact Estimates for Each Arm

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

R code and output

arm    <- c("Lacidofil Capsule Versus Placebo Drug")
n      <- c(214)
events <- c(12)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Lacidofil Capsule Versus Placebo Drug  214  12  5.6  2.9  9.6  3.2  9.5  3.3  9.5

11. Multiplicity, Missing Data and Analysis Populations

The registry record identifies the presence of AAD as the primary outcome and names a secondary outcome for bowel-habit change. It reports two outcome measures and two analyses, but does not report the full analysis plan or explain how the analyses correspond to the listed outcomes. The method for controlling, or choosing not to control, the chance of false-positive findings across multiple outcomes or analyses is not reported in the registry record.

In general, testing multiple outcomes or conducting multiple analyses can increase the chance that at least one result appears unusual by chance. A prespecified hierarchy, adjustment method, or clear distinction between confirmatory and exploratory analyses can help readers understand how to interpret multiple findings. The registry record does not report such a strategy. Because no outcome results or test statistics are reported, the impact of multiplicity on any claimed finding cannot be evaluated.

Missing data are another important consideration for an endpoint based on participant reports. The registry record does not report the number of participants with missing primary-outcome information, reasons for missingness, or how missing observations were handled. It also does not report whether participants were analyzed according to assigned group, according to treatment received, or in another analysis population. The term intention-to-treat, a per-protocol population, and any other analysis-population definition are not reported in the registry record.

In general, complete-case analysis uses only observations with the required outcome information, while other approaches may make different assumptions about unobserved outcomes. Each approach relies on assumptions, and different handling choices can change an estimate. Without the number assessed, missingness pattern, analysis population, and chosen procedure, readers cannot judge whether the primary comparison represents all enrolled participants or a selected subset.

The registry record also does not report whether any interim analyses were conducted or how they would have been handled. No interim-analysis plan should be inferred from the completion status or the presence of outcome measures. These reporting gaps limit assessment of the analysis process; they do not establish that a particular method was or was not used.

12. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 2.3% reporting threshold.

The adverse-event entry is labeled “Lacidofil Capsule Versus Placebo Drug.” It reports 214 at risk and 0 affected for the serious-event category, and 214 at risk and 0 affected for the other adverse-event category. The record does not give a separate participant count for each treatment arm within that entry, so these figures should not be interpreted as an arm-by-arm comparison. The deaths count is not reported in the registry record, and no serious-event terms are listed.

In general, “at risk” describes the group counted as eligible for a particular safety summary, while “affected” describes those recorded as having an event in that category. A count of 0 affected means no affected participants are recorded in that entry; it does not establish that every possible event was actively sought, that all participants had complete follow-up, or that the treatment has no safety risks. The registry record does not describe the safety-monitoring methods, observation period, event definitions, or the handling of missing safety information.

These safety figures are distinct from the primary AAD endpoint. They should not be used to infer the number of AAD cases, nor do they resolve the missing primary outcome results. The lack of arm-specific details and the unreported death count limit any comparative safety interpretation.

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

The registry record gives a defined question about preventing AAD, identifies the active product and placebo comparator, and specifies how the primary endpoint is classified. It also records enrollment of 214 and a completed study status. These details establish what the study was intended to examine and provide context for interpreting any reported results.

What the record does not establish is the size or direction of the primary comparison. AAD counts for each group, effect estimates, confidence intervals, and test results are not reported in the registry record. It is therefore not possible to say from these results whether the groups differed, how large any difference was, or how precisely it could be estimated. No conclusion about whether the treatment works or does not work is warranted from the missing outcome results.

The design description indicates an intended randomized, double-blind, placebo-controlled study. The posted comparison nevertheless leaves allocation unstated and is not identified as a like-for-like control comparison. This prevents a confident interpretation of any group contrast as a causal treatment effect, even if outcome counts were available. In general, a treatment comparison is more informative when the allocation process, analysis population, outcome ascertainment, and missing-data handling are adequately described.

The safety entry records zero affected for both serious and other event categories in its comparison-labeled record, but does not provide an arm-specific breakdown. These counts do not replace a systematic safety report, and the death count is not reported in the registry record. Likewise, planning calculations based on an observed effect are not evidence of the result and are not observed power.

The record is therefore useful for identifying the endpoint and the limits of what can be inferred, but it is not sufficient to quantify the primary treatment comparison. A fuller report would need to include group-specific outcome counts and denominators, the analysis method, uncertainty estimates, analysis populations, missing-data handling, and a clear account of allocation and safety reporting.

14. Why This Trial Matters Statistically

This trial illustrates why a clear clinical question and a clearly defined endpoint are necessary but not sufficient for statistical interpretation. The registry identifies a primary AAD outcome with a specific stool-frequency and duration threshold. That definition makes the intended event understandable. Yet without event counts and denominators for the comparison groups, readers cannot estimate the event frequency or quantify a contrast.

It also illustrates the difference between a planned design and a verifiable analysis. The official description calls the study randomized and double-blind, but the posted comparison does not state the allocation method and is not identified as a like-for-like control comparison. Statistical interpretation depends not only on the intended design but also on whether it was implemented and how the participants were analyzed. Registry descriptions should be read alongside the details of the posted results rather than treated as a substitute for them.

The record also demonstrates why enrollment alone does not describe the information available for an outcome. The number enrolled does not identify how many were assigned to each group, assessed for AAD, or included in an analysis. In general, event counts, denominators, and uncertainty measures are needed to understand both the magnitude and precision of a binary-outcome comparison.

Finally, the safety entry shows how aggregate counts can be easy to overinterpret when the record does not identify separate groups or provide full context. A zero count in an entry is a report about that entry, not proof that no harm occurred under all conditions. Clear group-level reporting, outcome methods, analysis populations, and missing-data procedures are essential for readers to distinguish observed findings from unanswered questions.

15. Limitations

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

The primary limitation is that the registry record does not report AAD results by group. It provides the endpoint definition and timeframe but no event counts, denominators, effect estimate, confidence interval, or hypothesis-test result. Thus, the primary comparison cannot be quantified or assessed for precision.

The posted comparison also does not state the allocation method and is not identified as a like-for-like control comparison, despite the study description of an intended randomized, placebo-controlled design. Details of sequence generation, concealment, and implementation are not reported in the registry record. This makes it difficult to assess whether the comparison supports causal interpretation.

Participant eligibility criteria, baseline characteristics, group sizes, treatment dose and duration, antibiotic regimens, adherence, and the number completing endpoint assessment are not reported in the registry record. The outcome-assessment process and the handling of borderline cases are also not described. The record does not provide analysis-population definitions, missing-data methods, or the statistical analysis plan.

Only one secondary outcome is named, while the registry reports two outcome measures and two analyses. Their full correspondence and the approach to multiplicity are not reported. The serious and other adverse-event figures are presented in a single comparison-labeled entry without an arm-specific breakdown; safety-monitoring details and the deaths count are not reported in the registry record.

The registry reports enrollment of 214, but that figure does not reveal the number analyzed for any endpoint. The record’s completed status and dates do not resolve these reporting limitations. These gaps constrain interpretation of the registry record; they do not show that the missing methods or results were absent from other study materials.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Effect of Probiotic Lactobacilli (Lacidofil Cap®) for the Prevention of Antibiotic-Associated Diarrhea — NCT01058356.
• Registry record last updated 2010-04-20; status last verified 2010-04.
• Results first posted 2010-03-31.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

19. Record Summary

The registry record describes a prospective, randomized, double-blind, multicenter study of probiotic Lactobacilli (Lacidofil cap®) versus placebo for prevention of AAD in adults. It reports enrollment of 214, a start date of 2009-01, a primary completion date of 2010-01, and completed status.

The primary endpoint is the presence of AAD, defined as watery stools more than 3 times per day for at least 2 days, assessed up to 14 days. A secondary outcome is bowel-habit change, defined as watery stools more than 2 times per day for at least 2 days.

Primary and secondary outcome results by group, effect estimates, uncertainty measures, and analysis methods are not reported in the registry record. The posted comparison does not state the allocation method and is not identified as a like-for-like control comparison. The adverse-event entry records 0 affected in both serious and other categories, with 214 at risk for each; it does not provide an arm-specific breakdown, and the deaths count is not reported.