Short-term Survival of Subjects With Acute-on-chronic Liver Failure After Plasma Exchange With Human Serum Albumin 5%: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Short-term Survival of Subjects With Acute-on-chronic Liver Failure After Plasma Exchange With Human Serum Albumin 5% (NCT03702920), a randomized phase 3 study. The primary outcome is Time to Death Without a Prior Liver Transplant Through Day 90 After Randomization.

2. Clinical Question

The study evaluated a treatment strategy in a high-risk ACLF population rather than plasma exchange in isolation: both groups received standard medical treatment, while one group also received PE-A 5%. The primary outcome therefore addresses the comparison between those treatment strategies under the study conditions. The registry record also lists time to liver transplant or death through Day 90 and time to death without a prior liver transplant through Day 28 as secondary outcomes. These outcomes add different views of the course after randomization, but they do not replace the primary question. The posted results include a reported Cox proportional-hazards analysis for the primary outcome and event counts by group. The record does not report the reason the study was terminated or the original design rationale for selecting the primary endpoint.

3. Trial Design

This was a Phase 3, multicenter, randomized, controlled, parallel-group, open-label study. The registry record lists an enrollment of 274 and describes recruitment at approximately 40 study centers in the United States, Canada, and Europe. Participants were randomized in a 1:1 allocation to standard medical treatment plus PE-A 5% or standard medical treatment alone. The record lists the study status as terminated; the reason for termination is not reported in the registry record.

The intervention used 5% albumin as the main replacement fluid for plasma exchange, administered intravenously. Standard medical treatment in both groups followed institutional standards. The described treatment period for the PE-A 5% group ranged from 7 to 17 days depending on ACLF evolution. For the control group, treatment was described as a minimum of 7 days and up to 17 days, also depending on ACLF evolution. Follow-up for participants in both groups was 90 days.

The registry record lists 135 participants in the SMT + PE-A 5% arm and 139 in the SMT Alone arm for the primary outcome. The reported primary analysis used a Cox proportional-hazards model. Randomization helps create a basis for comparing the groups, while the open-label design means participants and study personnel were not masked to treatment assignment. The registry record does not report further details about allocation concealment, site-level implementation, protocol deviations, or the original sample-size justification. The listed start and primary completion dates are 2019-06-17 and 2025-04-14.

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: 318 participants with ACLF were screened of which 274 participants were randomized in a 1:1 ratio to receive either the Standard Medical Treatment (SMT) + PE-A 5% or the SMT Alone.

Overall Study

Analysis population for the primary outcome, as defined in the registry: ITT population included all participants who were randomized.

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.

Population: Intent-to-treat (ITT) population included all participants who were randomized.

6. Primary Endpoint

The registry lists the primary outcome as Time to Death Without a Prior Liver Transplant Through Day 90 After Randomization, measured over Up to Day 90.

The primary endpoint is time to death without a prior liver transplant through Day 90 after randomization. The registry description defines the event time as the date of death minus the randomization date for participants who died without having a liver transplant on or before 90 days. Participants who did not die, or who had a liver transplant before death, were censored at the earliest of last contact, transplant, or the cutoff date.

This endpoint focuses on death occurring before transplant, rather than treating transplant itself as a death event. Censoring recognizes that a participant who has not experienced the event by the relevant observation point does not contribute an observed event time in the same way as a participant who died without a prior transplant. The registry record also says that event percentages were calculated using the number of participants with an event up to the analysis cutoff divided by the ITT group size.

Time-to-event methods are used because they incorporate both whether an event occurred and when it occurred, while allowing for censoring. The registry record reports a Cox proportional-hazards model for this endpoint. The reason this specific primary endpoint was selected, and any protocol rationale for its clinical interpretation, are not reported in the registry record.

7. Results Posted in the Registry

• SMT Alone: 49.6% (69/139) versus 37.8% (51/135) on control; risk difference 11.9 percentage points (95% CI 0.2 to 23.5), risk ratio 1.31 (1.00–1.73); unadjusted two-proportion z-test p = 0.048.

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.

Time to Liver Transplant or Death Through Day 90 After Randomization

• 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:
  • SMT Alone: 64.0% (89/139) versus 64.4% (87/135) on control; risk difference -0.4 percentage points (95% CI -11.8 to 10.9), risk ratio 0.99 (0.83–1.19); unadjusted two-proportion z-test p = 0.943.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SMT Alone and the control. The interval gives the range of effects that remain compatible with the data.

Time to Death Without a Prior Liver Transplant Through Day 28 After Randomization

• 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:
  • SMT Alone: 36.7% (51/139) versus 28.9% (39/135) on control; risk difference 7.8 percentage points (95% CI -3.3 to 18.9), risk ratio 1.27 (0.90–1.79); unadjusted two-proportion z-test p = 0.169.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SMT Alone and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes provide a broader but not definitive view of the pattern across follow-up. Their estimates do not give a uniformly precise separation between the groups: the registry-reported confidence intervals for both secondary Cox analyses include the no-difference value, and their p-values are 0.22 and 0.06. The unadjusted intervals for the corresponding risk differences also include 0. This contrasts with the primary result, whose reported Cox interval does not include 1, while the general direction of the posted estimates is broadly aligned rather than contradictory.

The secondary outcomes address related but distinct events. One combines liver transplant or death through Day 90, while the other concerns death without a prior transplant through Day 28. A combined endpoint treats its component events as part of the same outcome, so its interpretation is not identical to an endpoint limited to death. A shorter follow-up window also captures a different period of risk than the primary endpoint. These distinctions make the secondary outcomes useful context, but they should not be treated as independent replications of the primary result.

Unadjusted secondary results generally carry less evidential weight when multiple outcomes are examined, because looking across several results increases the chance of finding an apparently notable result by chance. The registry record does not report a multiplicity adjustment or a hierarchy for interpreting secondary outcomes. Their estimates are best read as supportive or exploratory evidence, alongside their uncertainty and the primary analysis, rather than as stand-alone confirmation.

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

• Time to Liver Transplant or Death Through Day 90 After Randomization
• Time to Death Without a Prior Liver Transplant Through Day 28 After Randomization

9. Statistical Interpretation

10. Statistical Methods Explained

The registry reports a Cox proportional-hazards model for the primary endpoint. This is a time-to-event method: it uses information about when events occurred and accommodates participants whose event time is censored. A hazard describes the instantaneous event rate among participants still under observation and event-free at a given time. A hazard ratio compares those rates between groups under the model. It is not an event count ratio, a risk difference, or a direct statement about an individual participant’s chance of an event.

The proportional-hazards model assumes that the relative hazard between groups is constant over time, unless an approach allowing variation is used. The registry record does not report a diagnostic assessment of this assumption or a model allowing the relative hazard to vary. A single hazard ratio can be difficult to interpret if the relative event pattern changes during follow-up. The reported confidence interval reflects uncertainty under the fitted model and its assumptions; it does not account automatically for every possible model limitation.

The primary endpoint includes censoring. According to the registry description, a participant who did not die, or who had a transplant before death, was censored at the earliest of last contact, transplant date, or cutoff date. In general, censoring allows time-to-event methods to use partial follow-up, but interpretation depends on the censoring process. If the chance of being censored is related to the underlying event risk in ways not adequately handled by the analysis, estimates can be affected. The registry record does not report additional analyses of the censoring process.

The posted event counts also support an unadjusted comparison of proportions. The recalculated risk difference is 0.119 for SMT Alone relative to SMT + PE-A 5%, with a confidence interval from 0.002 to 0.235 and p = 0.048. A risk difference expresses an absolute contrast in the observed proportions. This calculation does not use event timing, and it does not substitute for the registered Cox analysis. The two results can differ because they summarize the data in different ways, even when both concern the same endpoint.

A confidence interval describes a range of estimates compatible with the observed data and the statistical procedure, under its assumptions. For a hazard ratio, the no-difference value is 1; for a risk difference, it is 0. A confidence interval that crosses its no-difference value indicates that the data are compatible with that value at the stated confidence level. It does not prove that there is no difference. A p-value summarizes how unusual the data, or more extreme data, would be under a specified null hypothesis and analysis model. It does not give the probability that the null hypothesis is true, and it does not measure clinical importance.

The primary analysis population is described as ITT, including all randomized participants. In general, an ITT approach preserves the randomized comparison by analyzing participants according to assigned group, but the registry record does not report whether every randomized participant contributed to every analysis or how missing endpoint information was handled. The endpoint description gives censoring rules but does not provide a full account of missing-data methods, exclusions, or sensitivity analyses.

The secondary outcomes also use time-to-event framing, and their reported analyses use Cox proportional-hazards models. The posted counts and recalculated unadjusted contrasts provide simpler summaries, while the sponsor-reported model estimates account for event timing and censoring as specified by that analysis. Neither method eliminates uncertainty. The registry record does not report a detailed statistical analysis plan, a multiplicity procedure, or whether interim analyses were conducted.

Finally, the study was open-label. Randomization supports a comparative analysis, but lack of masking can affect care decisions, co-interventions, outcome assessment, or follow-up procedures in some settings. The primary outcome is death without prior transplant, which is relatively objective, but the registry record does not report additional safeguards or adjudication procedures. These methodological considerations help define what the estimates can support; they do not determine the result on their own.

11. Confidence Intervals and Precision

The primary Cox estimate is a hazard ratio of 0.65 with a 95% confidence interval from 0.45 to 0.94. The interval excludes 1, the no-difference value for a hazard ratio, but it spans a range of possible relative hazard values. The point estimate alone is not a complete description: the interval communicates that the underlying association is not known exactly. The reported p-value is 0.021.

The unadjusted risk difference is 0.119, with a confidence interval from 0.002 to 0.235. For this measure, 0 is the no-difference value. The interval is close to that value at one end and also permits a larger absolute difference at the other. Its p-value is 0.048. Because this is an unadjusted comparison of proportions, its precision and interpretation differ from those of the time-to-event model.

Confidence intervals are not guarantees that the true value lies within the reported range, nor do they capture uncertainty from every design or analysis limitation. They are calculated under statistical assumptions and are sensitive to the data and method used. The record does not report whether the Cox model assumptions were checked or whether alternative analyses produced similar intervals.

For clinical interpretation, precision should be considered together with the endpoint definition, event counts, study design, and other outcomes. The interval conveys uncertainty around an average group contrast; it does not describe the range of individual outcomes. It also does not establish the importance of any particular value within the interval. The registry record does not report a threshold for a clinically meaningful difference.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are illustrations based on the observed effect, not the trial’s original design assumptions. For the time-to-event outcomes, the sample-size calculations are expressed as the total number of events, using the Schoenfeld approach; they are not participants per arm. The record’s planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each scenario uses the stated fraction of the observed effect as the effect to detect. The trial’s own original sample-size justification and assumptions are not reported in the registry record.

The 80% power column describes the planned event total or participant count associated with an 80% chance of detecting the specified effect if that effect were real and the planning assumptions held. The 90% power column uses a higher probability of detecting that same specified effect, and therefore generally calls for a larger planning quantity. These are design illustrations, not descriptions of the study’s achieved ability to detect an effect. This is not observed power.

The rows for planning for 100%, 75%, and 50% of the observed effect illustrate how the assumed effect size changes the required planning quantity. A smaller effect is harder to distinguish from random variation, so the illustration requires more events or participants to detect it at the stated power and significance level. The figures should be read as conditional planning scenarios, not as evidence that the trial would necessarily produce a particular result at those sizes. They are not a replacement for the registered analysis or a justification for interpreting a result as positive or negative.

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 = 0.378; treatment proportion p₁ = 0.496; average p̄ = 0.437.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7015 = 1.3749.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6965 = 0.5862.
4. n = (1.3749 + 0.5862)² / (0.1186)² = 273.3, rounded up to 274 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 <- 0.377777777777778                          # control proportion
p1 <- 0.496402877697842                          # 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(3702920)
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 = 274 (80% power), 366 (90% power)
 75% of observed effect: n per arm = 483 (80% power), 646 (90% power)
 50% of observed effect: n per arm = 1,077 (80% power), 1,441 (90% power)
power.prop.test: 273.3 
Simulated power at n = 274 per arm: 0.808 (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’s own primary analysis is the Cox proportional-hazards result: hazard ratio 0.65, 95% confidence interval 0.45 to 0.94, and p = 0.021. The separate recalculation uses the posted group event counts to estimate an unadjusted risk difference of 0.119, with a confidence interval from 0.002 to 0.235 and p = 0.048. These estimates are related but not interchangeable. One compares event rates over time with a Cox model; the other compares observed event proportions without adjusting for timing or censoring in the same way.

The registry record does not flag a discrepancy between the reported analysis and the recalculation. The sponsor’s analysis is therefore the primary analysis to use when describing the trial’s reported time-to-event result. The unadjusted calculation can serve as a transparent companion summary of the posted counts, but it should not displace the model specified in the registry results. Neither estimate alone establishes clinical importance, and both remain subject to their respective assumptions and uncertainty.

The record does not report enough detail to reconstruct the full analysis plan or determine whether additional sponsor analyses were conducted. The reported Cox result should be interpreted as the analysis recorded for the primary endpoint, rather than as a complete account of every analysis that may have informed the study.

15. Multiplicity, Missing Data and Analysis Populations

The registry record lists one primary endpoint and two secondary outcomes, but it does not report a multiplicity adjustment, a testing hierarchy, or a family-wise error strategy. When several outcomes or analyses are considered, the chance of at least one apparently notable finding can increase. Multiplicity methods manage that issue by controlling how evidence is interpreted across the planned tests. Without a reported approach, the secondary p-values should be treated cautiously and should not be read as if each were the sole confirmatory test.

The record also does not report whether interim analyses were planned or conducted, whether stopping boundaries were used, or whether the analysis plan changed during the study. The study status is terminated, but the reason is not reported in the registry record. These absent details limit assessment of how the observed results relate to any monitoring or stopping decisions.

The primary analysis population is the ITT population, defined as all randomized participants. That definition supports interpretation according to randomized assignment, but the registry record does not describe the completeness of endpoint follow-up for each participant or how missing outcomes were handled. It does state that participants without an event, and participants transplanted before death, were censored according to the endpoint rules. Additional missing-data methods, imputation procedures, sensitivity analyses, and details about withdrawals are not reported in the registry record.

These omissions do not invalidate the posted estimates, but they leave important questions unanswered about robustness and the overall testing strategy. The Cox estimates depend on model assumptions and censoring; the unadjusted comparisons summarize the observed counts without addressing all time-to-event features. The posted results should therefore be interpreted with attention to the analysis that is documented, while avoiding conclusions about undocumented procedures.

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

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: shock haemorrhagic (2.3%), transfusion-related acute lung injury (2.3%), septic shock (2.2%), covid-19 (2.2%), pneumonia (1.6%).

The serious adverse event figures report 37 affected participants among 128 at risk in the SMT + PE-A 5% group, and 28 among 139 at risk in the SMT Alone group. The reported other adverse event figures are 79 among 128 at risk and 58 among 139 at risk, respectively. These are counts with the corresponding at-risk denominators; no rate comparison or adjusted safety analysis is reported in the registry record.

The listed serious adverse event terms include shock haemorrhagic and transfusion-related acute lung injury at 2.3% each, septic shock and COVID-19 at 2.2% each, and pneumonia and Escherichia bacteraemia at 1.6% each. These are the registry’s listed terms and percentages, not a complete account of every possible event or a causal attribution to a treatment.

The adverse-event record also lists deaths as 51 in the SMT + PE-A 5% group and 70 in the SMT Alone group. The definition and analysis context for these safety death counts are not described in the posted safety figures. They should not be assumed to match the primary endpoint counts, which specifically concern death without a prior liver transplant and have stated censoring rules. The safety counts alone do not establish whether an event was caused by assigned treatment.

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

The posted primary analysis shows a Cox hazard ratio of 0.65 for the comparison, with a 95% confidence interval from 0.45 to 0.94 and p = 0.021. The endpoint event counts are 51 of 135 in the SMT + PE-A 5% arm and 69 of 139 in the SMT Alone arm. These data describe the observed randomized-group comparison for death without a prior liver transplant through Day 90. They do not establish what would happen to any particular participant.

The estimate is a group-level statistical association under the reported Cox model. It does not mean that the outcome was prevented for every participant, and it does not translate directly into a personal probability or guarantee. The unadjusted risk-difference calculation gives a complementary summary of observed proportions, but it answers a different statistical question from the time-to-event analysis. Both estimates have uncertainty, and the record does not report a threshold for deciding whether an effect is clinically important.

The trial compared standard medical treatment plus PE-A 5% with standard medical treatment alone in a high-risk ACLF population, using institutional practice for standard medical treatment. Results should be understood in that context. The registry record does not establish that the same estimates apply to other populations, treatment settings, or follow-up periods. It also does not report the reason for the terminated status or sufficient detail about missing-data sensitivity analyses and multiplicity to resolve those issues.

The secondary outcomes and safety counts add context, but they do not remove uncertainty in the primary estimate. A statistically notable result is not by itself a complete assessment of benefit, harm, or clinical suitability. The statistical record supports describing the observed comparisons and their precision; it does not support individualized medical advice or a universal conclusion about treatment.

18. Why This Trial Matters Statistically

This trial is statistically informative because it compares two defined treatment strategies through random allocation: standard medical treatment plus plasma exchange using human serum albumin 5%, and standard medical treatment alone. Randomization provides a framework for comparing outcomes while reducing the risk that baseline differences systematically determine group assignment. The open-label design remains important context, particularly for care and outcome processes that may be influenced by treatment knowledge.

The primary endpoint is time-to-event and includes censoring for participants who did not die or received a transplant before death. That makes the distinction between a Cox hazard ratio and a simple comparison of event proportions especially important. The registry reports both the model-based analysis and counts that permit an unadjusted summary. Seeing how these estimands differ helps readers avoid treating a hazard ratio, a risk difference, and an event count as interchangeable quantities.

The posted estimates also illustrate the role of precision. The primary Cox interval excludes its no-difference value, while the secondary Cox intervals include theirs. That pattern supports attention to the pre-specified primary outcome and restraint in interpreting secondary findings, especially because multiplicity procedures are not reported. The result is not defined by a p-value alone: endpoint construction, censoring, analysis population, study status, and uncertainty all matter.

Finally, the registry record identifies gaps that affect interpretation, including the unreported reason for termination, original sample-size rationale, multiplicity approach, and missing-data procedures. Recognizing these gaps is part of sound statistical reading. It keeps the conclusion tied to the analyses and design features actually documented.

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.

Several trial-specific details needed for a fuller assessment are not reported in the registry record. The study is listed as terminated, but the reason for termination is not reported. The original sample-size calculation and its assumptions are also not reported, so the planning illustrations based on the observed effect should not be mistaken for the trial’s original design rationale.

The registry does not describe allocation concealment, procedures for outcome adjudication, or whether the proportional-hazards assumption was assessed. It provides censoring rules for the primary endpoint, but does not report further analyses of censoring or sensitivity analyses for missing data. Although the primary population is defined as ITT, the record does not explain how incomplete follow-up or missing information was handled in each analysis.

The open-label design may be relevant to co-interventions, clinical management, or follow-up, even though the primary endpoint is a death outcome. The standard medical treatment was according to institutional practice, so the registry does not define one uniform SMT regimen across settings. The record also does not report a multiplicity strategy for the secondary outcomes, or whether interim analyses occurred.

The primary analysis and unadjusted re-calculation use different statistical summaries. The Cox model accounts for event timing and censoring under its assumptions; the risk-difference calculation compares observed event proportions. Both are useful descriptions, but neither resolves the limitations not addressed in the registry record. These considerations constrain the scope of interpretation and should accompany discussion of the posted results.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Short-term Survival of Subjects With Acute-on-chronic Liver Failure After Plasma Exchange With Human Serum Albumin 5% — NCT03702920.
• Registry record last updated 2026-06-04; status last verified 2026-05.
• Results first posted 2026-06-04.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

The registry record describes a Phase 3, randomized, parallel-group, open-label study of standard medical treatment plus PE-A 5% versus standard medical treatment alone in participants with acute-on-chronic liver failure at high risk of hospital mortality. The listed enrollment is 274, and the study status is terminated. The primary endpoint is time to death without a prior liver transplant through Day 90.

The registry-reported primary Cox analysis gives a hazard ratio of 0.65, a 95% confidence interval from 0.45 to 0.94, and p = 0.021. The unadjusted re-calculation of the posted primary event counts gives a risk difference of 0.119 for SMT Alone relative to SMT + PE-A 5%, with a confidence interval from 0.002 to 0.235 and p = 0.048. Secondary outcomes and adverse-event counts provide additional context, but their interpretation is limited by uncertainty and details not reported in the registry record.