Effect of Probiotics on Gut-Liver Axis of Alcoholic Liver Disease: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effect of Probiotics on Gut-Liver Axis of Alcoholic Liver Disease (NCT01501162), a randomized phase 4 study. The primary outcome is Liver Enzymes(ALT).

2. Clinical Question

This question concerns a short-term comparison between randomized groups, not a comparison of changes over a longer follow-up period. The summary says liver enzymes and other measures were checked at baseline and again after therapy, while the posted primary result is the mean ALT at seven days after probiotics. The registry record does not report a primary-outcome result for change from baseline or an adjusted comparison that accounts for baseline values.

3. Trial Design

The registry identifies this as a completed, randomized, parallel-group Phase 4 trial. It lists an enrollment of 130 and quadruple masking. The trial summary describes a randomized, prospective clinical trial and says participants were assigned to seven days of probiotics or placebo. It also calls the trial “double-controlled,” while the design fields identify quadruple masking. The registry record does not explain that difference in wording or specify which roles were masked.

The summary places the study activity between September 2010 and April 2012. The registry lists a start of 2010-10 and primary completion of 2012-09. These entries describe the study period but do not provide a detailed account of recruitment, follow-up, or the timing of each assessment.

The posted ALT results are reported for 57 participants in the placebo group and 60 in the probiotic group. These are the outcome counts shown with the reported means and standard deviations; the registry record does not explain how they relate to the overall enrollment. It also does not state whether all randomized participants were included in the analysis, how participants with missing measurements were handled, or whether the outcome population followed an intention-to-treat approach.

The trial compared group means for continuous outcomes. The primary outcome was ALT in IU/L at seven days after probiotics. The registry also reports LPS in EU/mL at the same timeframe and identifies pro-inflammatory cytokines in the secondary-outcome description, but a separate posted numerical result for cytokines is not present. No trial-specific statistical analysis plan, sample-size justification, or account of interim analyses is reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

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 Liver Enzymes(ALT), measured over 7 days after probiotics.

The primary endpoint is ALT, a liver enzyme measured in blood, reported in IU/L. The registry describes it as a mean with standard deviation and gives the timeframe as seven days after probiotics. The trial summary says blood analysis used standard methodologies, but the registry record does not give further laboratory details.

As a continuous measure, ALT retains the measured value rather than reducing it to a yes-or-no outcome. Comparing group means can describe whether the average enzyme level differed between randomized groups at the stated assessment. The standard deviation describes how much participant measurements varied around each group mean; it is not the uncertainty interval for the difference between group means.

ALT was selected as the primary outcome in this trial of alcoholic liver disease, and the summary says the investigators explored probiotic effects on liver enzymes and other biological measures. In general, a laboratory endpoint can provide a quantitative measure of a biological response over a specified timeframe. It does not, by itself, establish effects on symptoms, longer-term disease course, or other outcomes. The registry record does not report a rationale for choosing ALT as the primary endpoint or a threshold defining a clinically meaningful difference.

7. Results Posted in the Registry

• Hepatitis, Alcohol, Probiotics: mean 48.00 versus 66.00 on control; difference -18.00 (95% CI -55.42 to 19.42), standardized effect d = -0.18; z-test p = 0.346.

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.

Lipopolysaccharide (LPS) and Pro-inflammatory Cytokines

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Hepatitis, Alcohol, Probiotics: mean 1.70 versus 2.10 on control; difference -0.40 (95% CI -1.21 to 0.41), standardized effect d = -0.18; z-test p = 0.333.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Hepatitis, Alcohol, Probiotics and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists LPS and pro-inflammatory cytokines as secondary outcomes, with LPS reported numerically at seven days after probiotics. The posted LPS comparison has a point estimate in the same direction as the primary ALT estimate, while its confidence interval also includes zero. This offers a similar broad pattern of uncertain short-term biomarker comparisons, rather than a distinct result that resolves the uncertainty in the primary outcome.

The record does not provide a separate numerical result for pro-inflammatory cytokines. Their inclusion in the secondary-outcome description therefore does not support a numerical comparison or an interpretation of the direction and precision of any cytokine result. The registry lists two outcome measures, but the information posted does not establish that every component named in the secondary-outcome description was separately analyzed or reported.

Secondary outcomes can help describe whether findings across related measures tell a coherent story. However, they are generally less definitive than a prespecified primary outcome, especially when the registry record does not state which comparisons were planned, how many analyses were conducted, or whether the results were adjusted for multiple testing. In general, testing several outcomes without accounting for multiplicity makes isolated low p-values less persuasive because chance findings become more likely across a collection of tests.

The secondary results should therefore be read as supporting descriptive information, not as independent proof of the primary comparison. The posted pattern does not remove the uncertainty in the ALT estimate, and the absence of a posted cytokine result leaves that part of the secondary-outcome description unassessed from the registry record.

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

• Lipopolysaccharide (LPS) and Pro-inflammatory Cytokines

9. Statistical Interpretation

10. Statistical Methods Explained

The posted primary comparison uses a difference in group means. The probiotic group's mean ALT was compared with the placebo group's mean ALT, with the reported contrast expressed as probiotic minus placebo. A negative estimate means that the observed mean was lower in the probiotic group; the sign alone does not establish that the underlying group means differ beyond sampling uncertainty.

What does a standard deviation describe?

In general, a standard deviation describes the spread of individual measurements around a group mean. It is different from a standard error, which describes the uncertainty in an estimated quantity such as a mean. The posted ALT standard deviations are 136.0 IU/L for placebo and 49.0 IU/L for probiotics. The difference in spread between groups matters for interpretation because high variability can make the estimated group contrast less precise. A standard deviation is not a range containing all participants, and it should not be read as a confidence interval.

What does the mean difference represent?

The mean difference condenses the two group averages into a single contrast in the outcome's units. For ALT, the posted contrast is -18.0 IU/L. It is a comparison at the stated seven-day assessment, not a reported difference in change from baseline. Although the trial summary says measurements were made at baseline and again after therapy, a baseline-adjusted estimate or change-score analysis is not reported in the registry record. In general, adjustment for baseline values can be useful in randomized trials, but the record does not say whether such an analysis was planned or performed.

How should the confidence interval be read?

In general, a confidence interval gives a range of values compatible with the data and the statistical model at a stated confidence level. The posted 95% interval for the ALT mean difference runs from -55.42 to 19.42 IU/L. Its inclusion of zero means the data are compatible with no mean difference under the analysis, while its negative and positive values also allow for differences in either direction. It is not a range that guarantees the true effect lies within it, and it does not show the probability that a particular treatment effect is correct.

What does the p-value add?

The unadjusted p-value for the ALT comparison is 0.346. In general, a p-value measures how unusual data at least as discrepant as those observed would be under a specified null hypothesis and analysis model. It is not the probability that the null hypothesis is true, nor is it a measure of clinical importance. The registry record labels the value unadjusted, and does not report a multiplicity correction or a full account of the statistical test and its assumptions.

The comparison is presented as a mean difference with a pooled standard deviation in the accompanying statistical output. In general, pooled-variance methods combine information about variability across groups, commonly under an assumption about how the groups' variances relate. Here the group standard deviations differ considerably. The registry record does not describe the sponsor's exact analysis method, so the posted estimate and interval should be interpreted as reported rather than used to infer unreported model details.

Over-dispersion is a general concern when outcome measurements vary more than a simple model anticipates. Greater variability can widen uncertainty and reduce precision; it can also make a model that assumes a particular variance structure less suitable. For continuous outcomes, variability in the observed values is directly relevant to the uncertainty of the mean comparison. The record does not report diagnostic checks, transformations, robust methods, or other steps used to address distributional features.

The reported p-value and confidence interval are unadjusted. In general, examining several outcomes or comparisons increases the chance of at least one apparently notable result arising by chance if each is assessed separately. An adjustment can control that issue, but the registry record does not report a multiplicity plan. This is particularly relevant when considering secondary outcomes as supporting evidence rather than treating each result as a separate confirmatory finding.

In general, random assignment supports a comparison of groups by reducing systematic differences at allocation, provided that assignment and follow-up are implemented appropriately. Masking may reduce some forms of bias, but the registry record does not identify who was masked or detail how the masking was maintained. It also does not describe allocation concealment, adherence, missing-data handling, or the analysis population. Those omissions limit the ability to assess the assumptions behind the posted comparison.

11. Confidence Intervals and Precision

The primary estimate is a mean ALT difference of -18.0 IU/L, and its 95% confidence interval extends from -55.42 to 19.42 IU/L. The interval is broad enough to include zero and estimates on both sides of zero. Consequently, the data do not specify the direction of the underlying group difference with confidence, and the estimate does not tightly constrain its magnitude.

Precision depends on the observed variability as well as the number of measurements and the analysis method. The placebo group's ALT standard deviation is 136.0 IU/L, compared with 49.0 IU/L in the probiotic group. The larger variability in the placebo group contributes to uncertainty in a comparison of means. The registry record does not report whether the outcome distribution was examined or whether alternative methods were used to account for the differing spreads.

A confidence interval should not be interpreted as proof that all values inside it are equally likely, or that values outside it are impossible. In general, it expresses uncertainty under the statistical model and procedure used. Its width is useful for judging how informative the estimate is: an interval spanning zero and substantial differences in either direction leaves the size and direction unresolved.

The unadjusted p-value of 0.346 is consistent with that uncertainty, but it does not replace the interval. A p-value alone does not convey the range of effects compatible with the data. The registry record does not report a prespecified threshold for clinical importance, so statistical precision cannot be translated into a conclusion about whether a particular difference would matter clinically.

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 calculation. For these continuous outcomes, the figures are participants per arm, not total events. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; each planning scenario targets the stated fraction of the observed effect. The trial's own original design assumptions are not reported in the registry record.

The 80% power column gives the number of participants per arm estimated to be needed, under those assumptions, for an 80% chance of detecting the target effect if that effect were the true one. The 90% power column gives the corresponding planning figure for a 90% chance. These are prospective design concepts, not probabilities that the observed trial result is correct. Smaller target effects require more participants to distinguish them from random variation, which is why the illustrations require more participants per arm when planning for a reduced fraction of the observed effect.

The figures are conditional on the observed effect being a useful basis for planning. An effect estimated imprecisely in a small study can be unstable, so basing a future design directly on it may be misleading. The assumptions also simplify the design and do not establish that the trial used those methods. The listed figures are not observed power.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -18.000; pooled standard deviation σ = 101.186.
2. n = 2 × (1.96 + 0.842)² × 101.186² / -18.000² = 496.1, rounded up to 497 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
delta <- -18                      # observed difference in means
sigma <- 101.185795531741                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^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 (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(1501162)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 497 (80% power), 665 (90% power)
 75% of observed effect: n per arm = 882 (80% power), 1,181 (90% power)
 50% of observed effect: n per arm = 1,985 (80% power), 2,657 (90% power)
power.t.test: 497 
Simulated power at n = 497 per arm: 0.802 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The registry identifies ALT as the primary outcome and lists LPS and pro-inflammatory cytokines as secondary outcomes. It does not report a complete statistical analysis plan or explain how the study handled multiple outcomes or tests. The primary p-value is explicitly unadjusted. The registry record does not report a multiplicity correction, a hierarchy of secondary hypotheses, or a rule for interpreting several results together.

In general, multiplicity matters when several outcomes or contrasts are tested. If each result is evaluated separately, the chance of a seemingly notable result arising by chance can increase across the set. Adjustment methods or prespecified testing hierarchies can address this issue, but their use cannot be assumed when it is not reported. The secondary results should accordingly be treated as less conclusive than a single prespecified primary comparison.

The record does not describe missing-data handling, the number of participants with missing measurements, or the reasons for any missingness. The posted arm-specific outcome counts are reported with the means, but the registry does not explain how these counts were determined or whether participants without measurements were excluded. It also does not state whether any imputation, sensitivity analysis, or other missing-data method was used.

The analysis population is not described. In particular, the registry record does not say whether the results include all randomized participants, only those who completed treatment, or another defined group. It does not report adherence or withdrawals in a way that would permit assessment of how these factors affected the estimates. These omissions make it difficult to evaluate potential bias from missing outcomes or departures from assigned treatment.

The posted record also does not give a detailed statistical test specification, baseline-adjustment strategy, or assumptions checks. Without these details, readers cannot fully assess whether the analysis followed a prespecified plan or how robust the result is to alternative analytic choices. These are gaps in the registry record; they do not establish that the trial lacked a plan or did not conduct additional analyses.

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

The posted primary result describes mean ALT at seven days after probiotics in the randomized probiotic and placebo groups. The estimated mean difference is lower in the probiotic group, but the confidence interval includes zero and extends to values in the opposite direction. The result is therefore uncertain about both the direction and size of the underlying difference. It does not establish that the groups differed, and it does not establish that they were equivalent.

The p-value is unadjusted, and the registry record does not report a threshold for a clinically important ALT difference. Statistical uncertainty and clinical importance are separate questions: an estimate can be imprecise even when its point estimate is easy to describe, and the clinical meaning of a difference depends on context not provided in the registry record. No clinical interpretation should be inferred from the enzyme measurement alone.

The trial's endpoint is a short-term laboratory measure. The result does not answer whether there are differences beyond the seven-day assessment, or whether the groups differ on outcomes not reported in the registry. The record does not post a separate numerical result for pro-inflammatory cytokines, and its secondary biomarker information does not resolve the primary estimate's uncertainty.

Randomization and masking are identified in the registry, but the record does not provide enough detail to assess implementation, analysis populations, missing data, or all statistical assumptions. Those reporting gaps affect how confidently the posted estimate can be interpreted as a complete account of the trial. They do not by themselves show that bias occurred.

Overall, the registry result is a short-term, uncertain estimate of a between-group mean ALT difference. It should not be used as proof of benefit, proof of no effect, or a basis for conclusions about patient-important outcomes that are not reported in the record.

16. Why This Trial Matters Statistically

This trial illustrates why a point estimate and its uncertainty need to be read together. The mean ALT difference has a clear numerical direction, but its confidence interval includes zero and spans values in both directions. The estimate alone can sound more definitive than the data support; the interval gives a fuller account of the precision of the comparison.

The variation in ALT is also statistically important. The placebo group has a substantially larger standard deviation than the probiotic group. In general, high outcome variability makes mean comparisons less precise and can complicate assumptions used by common statistical methods. The reported summary values give readers a reason to examine uncertainty rather than focus only on the two group means.

The record also shows how outcome selection and multiplicity affect interpretation. A primary endpoint is distinguished from secondary outcomes, but the record does not report a multiplicity plan or a complete analysis plan. Secondary measures can add context, yet they should not be treated as independent confirmation when the analysis and testing strategy are unclear.

Finally, the planning illustrations demonstrate that future sample-size requirements depend on the effect a study aims to detect: targeting a smaller fraction of the observed effect requires more participants per arm under the stated assumptions. These figures are planning aids, not a retrospective measure of the trial's success or statistical power. Together, the results and reporting gaps emphasize the value of transparent methods, precise estimates, and cautious interpretation.

17. 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 registry record provides limited detail about the trial methods beyond randomization, parallel groups, quadruple masking, and the short treatment period. It does not describe the randomization procedure, allocation concealment, who was masked, or whether masking was maintained. The summary's use of “double-controlled” is not reconciled with the quadruple-masking designation.

The record does not report the probiotic formulation beyond the intervention label and dose of 1500 mg/day, or provide further placebo details. The summary gives an AH definition, but other eligibility criteria and baseline participant characteristics are not included in the posted results. This limits assessment of how representative the analyzed participants are of the stated population.

The primary result is a measurement at seven days. The registry does not post a primary estimate for change from baseline, and it does not report longer-term follow-up results. ALT is a laboratory outcome; the record does not provide a reported clinical outcome that would establish how the short-term biomarker comparison relates to broader health outcomes.

The posted ALT standard deviations differ substantially between groups, while the analysis details are sparse. The registry record does not explain distributional checks, use of baseline adjustment, missing-data handling, or the analysis population. It also does not report a multiplicity strategy, a clinical-importance threshold, or the original sample-size justification. These limitations concern what can be assessed from the registry record and should not be taken as evidence that unreported procedures were absent.

The record lists zero serious adverse events and zero other adverse events in each group, while deaths are not reported. These entries provide limited detail about safety monitoring or how adverse events were collected, and should not be read as a complete account beyond the registry entries.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Effect of Probiotics on Gut-Liver Axis of Alcoholic Liver Disease — NCT01501162.
• Registry record last updated 2015-04-14; status last verified 2014-12.
• Results first posted 2015-01-27.
• 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.

21. Record Summary

NCT01501162 is a completed, randomized, parallel-group Phase 4 trial of probiotics versus placebo in alcoholic liver disease. The registry lists an enrollment of 130 and quadruple masking. The trial summary describes seven days of treatment with probiotics at 1500 mg/day and assessments at baseline and after therapy.

The primary outcome was mean ALT in IU/L at seven days after probiotics. The posted estimate is a mean difference of -18.0 IU/L, with a 95% confidence interval from -55.42 to 19.42 and an unadjusted p-value of 0.346. The interval includes zero and values in either direction, so the result remains uncertain.

LPS is also reported as a secondary outcome. Pro-inflammatory cytokines are named in the secondary-outcome description, but a separate numerical result is not posted. The registry record does not report the original sample-size justification, detailed analysis plan, missing-data methods, or multiplicity approach.