Effects of Long-Term Administration of Human Albumin in Participants With Decompensated Cirrhosis and Ascites: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effects of Long-Term Administration of Human Albumin in Participants With Decompensated Cirrhosis and Ascites (NCT03451292), a randomized phase 3 study. The primary outcome is Time to Liver Transplantation or Death Through 1 Year After Randomization: Percentage of Participants With an Event.

2. Clinical Question

3. Trial Design

This was a phase 3, multicenter, randomized, controlled, parallel-group, open-label study. The registry lists enrollment of 410 and describes the study population as participants discharged after hospitalization for acute decompensation of cirrhosis with ascites, or with a prior history of ascites requiring diuretic therapy. Participants could have had ACLF at admission or during hospitalization but had to be without ACLF at discharge. The ITT population included all randomized participants.

The intervention combined SMT with Albutein 20%. The listed dose was 1.5 grams/kilograms based on body weight, with a maximum of 100 grams per participant, given intravenously on Day 1 and then at the same dose every 10±2 days. The arm description also says Albutein was given along with SMT, but the registry record does not report the remainder of the dosing description. The comparator received SMT for up to 12 months according to institutional standards.

The registry reports 203 participants in the SMT plus Albutein 20% arm and 207 in the SMT-alone arm for the primary result. The study began on 2018-07-24, had primary completion on 2024-05-21, and is listed as completed. Masking was none, so the study was open-label. The registry record does not report further detail about the randomization procedure, allocation concealment, protocol adherence, or the original statistical design assumptions. Those details should not be inferred from the reported allocation and outcomes.

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: 476 participants with decompensated cirrhosis and ascites were screened of which 410 participants were randomized in a 1:1 ratio to receive either the Standard Medical Treatment (SMT) + Albutein 20% or the SMT alone.

Overall Study

Reasons for not completing this period:

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 Liver Transplantation or Death Through 1 Year After Randomization: Percentage of Participants With an Event, measured over Up to Day 361.

The primary endpoint is the percentage of participants with liver transplantation or death through Day 361 after randomization. An event was the earlier of transplantation or death within the analysis period. Participants without either event were censored at the earlier of last contact or the cut-off date. Participants who ended study participation early for reasons other than death were followed at months 3, 6, and 12 for information about transplantation and death; events reported by Day 361 were counted.

This endpoint is used to capture whether participants remained alive without liver transplantation over the specified follow-up. Combining transplantation and death makes the endpoint broader than mortality alone, and it should not be interpreted as a death-only outcome. The registry gives the percentage with events using the ITT population, defined as all randomized participants. It also reports a sponsor analysis of time to event using a Cox proportional-hazards model. That analysis addresses the timing of events, whereas the posted arm percentages describe the proportion with an event by the cut-off. The registry record does not report a separate sponsor model for the posted percentage comparison.

7. Results Posted in the Registry

• SMT Alone: 38.6% (80/207) versus 33.5% (68/203) on control; risk difference 5.1 percentage points (95% CI -4.1 to 14.4), risk ratio 1.15 (0.89–1.49); unadjusted two-proportion z-test p = 0.278.

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 Transplantation or Death Through 3 Months After Randomization: Percentage of Participants With an Event

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • SMT Alone: 17.9% (37/207) versus 10.8% (22/203) on control; risk difference 7.0 percentage points (95% CI 0.3 to 13.8), risk ratio 1.65 (1.01–2.69); unadjusted two-proportion z-test p = 0.042.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for SMT Alone than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Time to Liver Transplantation or Death Through 6 Months After Randomization: Percentage of Participants With an Event

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • SMT Alone: 28.5% (59/207) versus 22.7% (46/203) on control; risk difference 5.8 percentage points (95% CI -2.6 to 14.3), risk ratio 1.26 (0.90–1.76); unadjusted two-proportion z-test p = 0.175.
• 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 Through 3 Months After Randomization: Percentage of Participants With an Event

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • SMT Alone: 14.0% (29/207) versus 9.4% (19/203) on control; risk difference 4.7 percentage points (95% CI -1.5 to 10.8), risk ratio 1.50 (0.87–2.58); unadjusted two-proportion z-test p = 0.143.
• 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 registry includes secondary outcomes for liver transplantation or death at shorter follow-up, death at several follow-up periods, total paracenteses, and refractory ascites. Among the posted comparisons with results, the direction of the event-percentage estimates generally places the lower observed percentage in the SMT plus Albutein 20% arm. The uncertainty differs across outcomes and follow-up periods: one short-term composite comparison has a confidence interval that does not include zero, while the other posted secondary intervals include zero. Results for the remaining listed secondary outcomes are not reported in the registry record.

This overall pattern does not replace the primary finding. The primary endpoint is the one-year composite of liver transplantation or death, and the sponsor’s main analysis is the time-to-event model for that endpoint. Secondary outcomes can add context about the timing and type of events, but they do not independently establish the primary claim, particularly when their statistical results are unadjusted.

Multiplicity matters because examining multiple outcomes and time points creates more opportunities for an apparently unusual result to occur by chance. The registry record does not report a multiplicity adjustment or testing hierarchy for the secondary analyses. Their p-values and confidence intervals should therefore be interpreted as exploratory or supportive rather than as a collection of confirmatory tests. This is especially important for a secondary comparison whose interval excludes zero: that finding does not by itself resolve the uncertainty in the primary endpoint or show that a treatment effect is established.

The listed secondary outcomes also differ in what they measure. A composite of transplantation or death is not equivalent to death alone; paracentesis frequency and refractory ascites address other aspects of the clinical course. Because several of their posted results are absent, the record does not permit a complete assessment of how those outcomes align with the primary result.

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

• Time to Liver Transplantation or Death Through 3 Months After Randomization: Percentage of Participants With an Event
• Time to Liver Transplantation or Death Through 6 Months After Randomization: Percentage of Participants With an Event
• Time to Death Through 3 Months After Randomization: Percentage of Participants With an Event
• Time to Death Through 6 Months After Randomization: Percentage of Participants With an Event
• Time to Death Through 1 Year After Randomization: Percentage of Participants With an Event
• Total Number of Paracenteses Through 1 Year After Randomization
• Number of Participants With Refractory Ascites According to the International Club of Ascites (ICA) Through 1 Year After Randomization

9. Statistical Interpretation

10. Statistical Methods Explained

What does the primary percentage describe?

The endpoint is a binary event measure: each randomized participant is classified according to whether liver transplantation or death occurred by Day 361. The posted percentages are the proportions with an event in each arm. They do not show the time of each event, and they are not mortality percentages alone. The endpoint’s event definition takes the earlier of transplantation or death. The registry states that people without an event were censored at the earlier of last contact or the cut-off date, with follow-up after early termination for non-death reasons as described in the endpoint definition.

The primary summary uses the ITT population, which includes all randomized participants. This preserves assignment as the basis for the comparison, regardless of treatment received after randomization, although the registry record does not provide detail about treatment discontinuation, adherence, or crossovers. The posted arm percentages are 33.5% for SMT plus Albutein 20% and 38.6% for SMT alone.

What is the unadjusted recalculation?

The recalculated risk difference compares the event proportion in SMT alone with the event proportion in SMT plus Albutein 20%. The estimate is 0.051, and the 95% confidence interval runs from -0.041 to 0.144. A positive value in this comparison’s direction means the observed proportion is higher in the SMT-alone arm; an interval spanning zero is compatible with no difference as well as differences in either direction. The recalculation is unadjusted: it uses the posted arm summaries and does not apply the sponsor’s time-to-event model or adjust for other variables.

The recalculated p-value is 0.278. A p-value describes how unusual data at least as incompatible with a specified null hypothesis would be under that hypothesis and the analysis assumptions. It is not the probability that the null hypothesis is true, nor a measure of clinical importance. The registry’s own reported analysis takes precedence for the sponsor’s prespecified inference; the unadjusted calculation is a separate way to describe the posted proportions.

Why does the time-to-event method differ?

The sponsor reports a Cox proportional-hazards model with a hazard ratio of 0.80, a 95% confidence interval from 0.58 to 1.10, and p=0.17. A hazard ratio compares event rates over follow-up under the model, rather than simply comparing the proportions with an event at the cut-off. This approach can use event timing and censored follow-up. It relies on model assumptions, including proportional hazards: broadly, that the relative hazard between groups is sufficiently stable over time. The registry record does not give diagnostic checks or further model details, so those assumptions cannot be evaluated from the record alone.

The sponsor’s interval includes 1, the null value for a hazard ratio. The reported result therefore does not demonstrate a clear separation in event hazard under that analysis. The risk-difference interval includes zero, the corresponding null value for a difference in proportions. The results are directionally distinct statistical summaries, and neither should be substituted for the other.

Why can over-dispersion matter in other trials?

General statistical explanation: for outcomes such as counts, the variability can be greater than a simple model assumes. This is called over-dispersion. If it is ignored, standard errors and confidence intervals may be too small, making results look more precise than they are. The primary endpoint in this record is a percentage with an event, not a count outcome; over-dispersion is not reported as an issue for this analysis.

What analysis details remain uncertain?

The registry lists one primary analysis using a Cox proportional-hazards model, but the detailed statistical analysis plan, covariates, treatment of missing observations beyond the stated censoring rules, and any checks of model assumptions are not reported in the registry record. The registry record also does not report the original sample-size justification, whether interim analyses were conducted, or a multiplicity procedure. The general statistical concepts above explain how to read the reported methods; they do not fill in those missing trial-specific details.

11. Confidence Intervals and Precision

The primary unadjusted risk-difference estimate is 0.051, with a 95% confidence interval from -0.041 to 0.144. The interval crosses zero, so the posted summary statistics are compatible with no difference in event proportions. They are also compatible with differences in either direction. Its width indicates that the estimate is not precise enough to rule out a range of effects. The interval should be interpreted as uncertainty around the unadjusted comparison, not as a range containing a fixed proportion of individual outcomes.

The sponsor’s hazard ratio is 0.80, with a 95% confidence interval from 0.58 to 1.10. Because the interval includes 1, it does not establish a clear difference in event hazard under the reported model. The interval describes uncertainty in a different estimand from the risk difference: it concerns the relative hazard over follow-up, not the difference between endpoint percentages at the cut-off.

For the secondary comparisons posted in the registry record, the three-month composite risk-difference interval is 0.003 to 0.138; the six-month composite interval is -0.026 to 0.143; and the three-month death interval is -0.015 to 0.108. These intervals differ in whether they include zero, but they are unadjusted secondary comparisons and should be read with that context in mind.

Confidence intervals are general measures of statistical precision under the method and its assumptions. They do not account automatically for every source of uncertainty, such as unreported analysis choices, missing-data mechanisms, or multiplicity. The registry record does not report enough detail to assess those sources fully.

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 original design justification; the original assumptions are not reported in the registry record. For this primary binary endpoint, the figures refer to participants per arm. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation. The target effect is set to the stated fraction of the observed effect. For time-to-event planning, the figures instead represent total events using the Schoenfeld method; other planning figures represent participants per arm.

The 80% power column means the number of participants per arm that the illustration estimates would be needed to have an 80% chance of detecting the specified effect under those assumptions, if that effect were the true one. The 90% power column uses a higher chance of detection and therefore gives a larger planning requirement. For the primary endpoint, the listed figures are 1,364 participants per arm for 80% power and 1,826 participants per arm for 90% power when planning for 100% of the observed effect. Planning for 75% of the observed effect gives 2,407 and 3,221 participants per arm, respectively; planning for 50% gives 5,370 and 7,189.

Smaller effects are harder to distinguish from random variation, so the planning illustration requires more participants as the target effect becomes smaller. These are planning estimates, not observed power; they do not describe the probability that the completed trial detected an effect after its results were known. The registry record does not report the trial’s own original design assumptions.

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 = 0.335; treatment proportion p₁ = 0.386; average p̄ = 0.361.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6791 = 1.3311.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6781 = 0.5707.
4. n = (1.3311 + 0.5707)² / (0.0515)² = 1,363.8, rounded up to 1,364 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 <- 0.334975369458128                          # control proportion
p1 <- 0.386473429951691                          # 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(3451292)
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 = 1,364 (80% power), 1,826 (90% power)
 75% of observed effect: n per arm = 2,407 (80% power), 3,221 (90% power)
 50% of observed effect: n per arm = 5,370 (80% power), 7,189 (90% power)
power.prop.test: 1363.8 
Simulated power at n = 1,364 per arm: 0.792 (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 analysis as a Cox proportional-hazards model comparing the randomized groups. The reported hazard ratio is 0.80, with a 95% confidence interval from 0.58 to 1.10 and p=0.17. The analysis is a time-to-event comparison, so it is not the same quantity as the unadjusted risk difference recalculated from the posted event percentages.

The recalculated comparison gives a risk difference of 0.051 for SMT alone relative to SMT plus Albutein 20%, with a 95% confidence interval from -0.041 to 0.144 and p=0.278. Both summaries have intervals that include their respective null values: 1 for the hazard ratio and zero for the risk difference. The registry record marks no discrepancy between the posted result and the recalculation. The sponsor’s analysis remains the trial’s reported inferential analysis; the recalculation is a simple, unadjusted description of the arm percentages and does not replace it.

The registry record does not report enough detail to reconstruct the sponsor’s model, including all modeling choices or diagnostics. The two results can be compared as complementary summaries, but they should not be treated as identical estimates or as a test of one another.

15. Multiplicity, Missing Data and Analysis Populations

The registry record identifies an ITT population that includes all randomized participants, and it describes censoring for participants who had no liver transplantation or death within the analysis period. It also states that participants who terminated early for reasons other than death were followed at months 3, 6, and 12 to collect information on transplantation and death. Events reported by Day 361 were counted for the primary endpoint. These details clarify the endpoint’s follow-up and event handling, but they do not describe every missing-data decision.

The registry record does not report how missing outcome information was handled if follow-up status could not be determined, whether sensitivity analyses were performed, or the assumptions used for missing data. Censoring is part of the time-to-event endpoint definition; it should not be taken to mean that all missingness is harmless or unrelated to outcome. The record also does not report detailed analysis-population counts for each outcome beyond the stated ITT population and the arm counts associated with the posted results.

Multiplicity arises because the study lists multiple secondary outcomes and follow-up periods. If many hypotheses are tested, the chance of at least one apparently positive result can increase. The registry record does not report whether the sponsor controlled the family-wise error rate, adjusted secondary p-values, or used a prespecified testing hierarchy. No particular procedure should be assumed. Consequently, the secondary p-values should not be read as if each were the sole, prespecified confirmatory test.

The registry record does not report whether interim analyses were conducted, the original sample-size justification, or the full statistical analysis plan. It also does not provide enough information to assess whether endpoint definitions, exclusions, and analysis decisions were finalized before outcome data were examined. These omissions limit independent evaluation of the analysis strategy, but they do not alter the values reported for the primary endpoint and sponsor analysis.

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: gastrointestinal haemorrhage (5.4%), pneumonia (3.9%), urinary tract infection (3.4%), death (2.5%), sepsis (2.4%).

The registry lists serious adverse events affecting 52 participants in the SMT plus Albutein 20% group and 70 in the SMT-alone group. It lists other adverse events affecting 51 and 47 participants, respectively. Deaths are listed as 53 in the SMT plus Albutein 20% group and 67 in the SMT-alone group. These are separate registry safety counts; they should not be added together or treated as interchangeable categories.

The listed serious adverse-event terms include gastrointestinal haemorrhage (5.4%), pneumonia (3.9%), urinary tract infection (3.4%), death (2.5%), sepsis (2.4%), and respiratory failure (2.4%). The registry excerpt does not clarify the analysis window, attribution to study treatment, or the denominator behind each listed percentage. The term list and group counts therefore describe the posted safety record but do not establish comparative safety or causation. The death count in the safety listing is also not a substitute for the primary endpoint result, which includes transplantation as well as death and has its own follow-up definition.

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

The primary endpoint data show that the observed percentage with liver transplantation or death through Day 361 was 33.5% with SMT plus Albutein 20% and 38.6% with SMT alone. The recalculated risk-difference interval includes zero, and the sponsor’s hazard-ratio interval includes 1. The sponsor reports p=0.17. Taken together, the posted results do not establish a clear difference for the primary endpoint under the reported analyses.

That conclusion is not the same as proving that the groups are equivalent, or that there is no potentially meaningful effect. The intervals remain compatible with a range of values, including differences in either direction for the unadjusted event proportion. Nor does a numerical difference in observed percentages by itself demonstrate a causal treatment effect. The trial’s randomization supports a comparative design, but the registry record gives limited detail about adherence, missing data, and modeling checks.

The result concerns a composite endpoint, not death alone. It also concerns participants meeting the study’s discharge criteria, rather than every person with decompensated cirrhosis and ascites. The study was open-label, and the registry record describes treatment strategies in the context of institutional SMT. These features should be kept in mind when considering how broadly the results apply.

The secondary results offer context but are not a substitute for the primary analysis. Some outcome results are absent from the registry record, and the record does not report a multiplicity procedure. The most defensible reading is therefore descriptive: the registry posts the stated event percentages, an uncertain unadjusted comparison, and a sponsor time-to-event estimate whose interval includes the null. These statistics alone do not support medical advice or a conclusion that one strategy works or fails.

18. Why This Trial Matters Statistically

This trial illustrates why a clinical endpoint can have more than one valid statistical summary. The primary registry endpoint is a proportion experiencing transplantation or death by a defined cut-off, while the sponsor’s Cox model uses time to event and accounts for censoring as described in the endpoint definition. These analyses answer related but distinct questions. Their estimates, intervals, and p-values should be interpreted according to the estimand each represents.

It also demonstrates why uncertainty matters alongside the observed arm percentages. The numerical proportions differ, but the unadjusted confidence interval spans zero; the sponsor’s hazard-ratio interval spans 1. Reporting only a direction or a p-value would omit information about the range of effects compatible with the data. Conversely, an interval that includes a null value does not prove there is no effect.

The record is useful for distinguishing the randomized population, the event definition, the sponsor’s analysis, and secondary outcomes. It also shows the limits of registry reporting: the original design assumptions, multiplicity strategy, and several secondary results are not reported. Those omissions matter for evaluating how confirmatory the analyses are and how fully the findings can be independently assessed.

Finally, the planning illustrations should not be confused with trial performance. They show how participant requirements change when planning around different fractions of the observed effect under stated assumptions. They are not evidence that the completed study had a particular probability of detecting an effect. Together, these points make the trial a practical example of interpreting endpoints, model-based and unadjusted comparisons, precision, multiplicity, and planning estimates without overclaiming what registry results establish.

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.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The study was open-label, with no masking. This may matter for clinical decisions, co-interventions, and outcome ascertainment, although the registry record does not report whether or how those processes affected these results. SMT in the comparator arm followed institutional standards, and the record does not provide a detailed common SMT regimen. The Albutein arm description is also truncated after stating that the treatment was administered along with SMT, so the remainder of that description is not reported in the registry record.

The primary endpoint combines liver transplantation and death. A difference in the composite could reflect either component, and the primary summary does not separate their contributions. The sponsor’s time-to-event model provides a different summary, but model details and diagnostics are not reported in the registry record. The posted recalculation is unadjusted and does not address potential covariates or model the timing of events.

The registry record does not report the original sample-size justification, interim analyses, a full statistical analysis plan, or a multiplicity method. Several listed secondary outcomes have no posted results, limiting assessment of the full outcome pattern. Missing-data handling beyond the stated censoring and follow-up rules is not reported in the registry record. These limitations constrain interpretation; they do not justify assuming particular methods or results that are absent from the record.

Generalizability is also bounded by the described eligibility context: participants were being discharged after hospitalization for acute decompensation and had to be without ACLF at discharge. The results therefore should not automatically be extended to populations outside that description. The registry record does not provide additional details about participant characteristics that would permit a fuller assessment of how representative the trial population was.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Effects of Long-Term Administration of Human Albumin in Participants With Decompensated Cirrhosis and Ascites — NCT03451292.
• Registry record last updated 2025-06-06; status last verified 2025-05.
• Results first posted 2025-06-06.
• 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 completed phase 3, multicenter, randomized, controlled, parallel-group, open-label trial of SMT plus Albutein 20% versus SMT alone in participants with decompensated cirrhosis and ascites. Enrollment was 410. The primary outcome was the percentage with liver transplantation or death through Day 361 in the ITT population.

The posted primary event percentages were 33.5% with SMT plus Albutein 20% and 38.6% with SMT alone. The sponsor reported a Cox-model hazard ratio of 0.80, with a 95% confidence interval from 0.58 to 1.10 and p=0.17. The unadjusted recalculation gives a risk difference of 0.051, with a 95% confidence interval from -0.041 to 0.144 and p=0.278. Both intervals include their respective null values. The registry record does not report the original design assumptions, multiplicity procedure, or results for all listed secondary outcomes.