REnal Function in Liver Transplantation: Everolimus With Calcineurin Inhibitor (CNI)-Sparing sTrategy: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for REnal Function in Liver Transplantation: Everolimus With Calcineurin Inhibitor (CNI)-Sparing sTrategy (NCT02115113), a randomized phase 3 study. The primary outcome is Renal Function Assessed by Estimated Glomerular Filtartion Rate (eGFR).

2. Clinical Question

3. Trial Design

This was a Phase 3, randomized, open-label, parallel-group study of everolimus-based immunosuppression strategies in adult liver transplant recipients. The registry describes the comparison as tacrolimus withdrawal versus tacrolimus minimization, with renal function as the primary focus. Enrollment was 78. The study status is completed, and the registry lists a start date of 2014-03-28 and a primary completion date of 2016-09-30.

Both groups began with everolimus and tacrolimus. Group A was the tacrolimus elimination arm; Group B was the tacrolimus minimization arm. The description specifies an everolimus starting dose of 1.0 mg twice daily in each arm and adjustment toward everolimus trough levels between 3-8 ng/mL. Tacrolimus was administered according to center practice. The record describes a follow-up of 6 months after the period through 12 months post-transplant.

Because the trial was open-label, masking was not used. That feature is relevant when considering outcomes that could be influenced by knowledge of treatment assignment. The primary measure, eGFR, is a laboratory-derived continuous measure, although the record does not report whether those assessing or processing the outcome were masked.

The primary analysis population was the safety population, defined in the record as randomized participants who received at least one dose of study medication after randomization. The arm-level primary outcome results include 24 participants assigned to tacrolimus elimination and 26 assigned to tacrolimus minimization. Missing eGFR values at 12 months were imputed using last observation carried forward. The record does not report the number of missing values or provide further detail about their timing.

The registry describes a broader enrollment count than the arm-level primary outcome counts. The reasons for this difference, and the number of participants contributing to each secondary outcome, are not reported in the registry record. The original sample-size justification and the assumptions used to plan the trial are also not 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.

Before assignment: This study included a run-in period and a randomization period. Run-in started 4 weeks post-transplant and ended at 5 months post randomization. After run-in, eligible participants were randomized in a 1:1 ratio to tacrolimus elimination or tacrolimus minimization.

Participants in Run-in Period

Reasons for not completing this period:

Participants Randomized

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The safety population, which included all randomized participants who received at least one dose of study medication post-randomization, was considered for the analysis. eGFR values missing at 12 months post transplantation were imputed using the Last Observation carried Forward (LOCF) approach.

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: Run-in Population: all consented and everolimus-treated patients who entered the run-in treatment period. All 78 enrolled patients were included in the run-in treatment period. Treatment started at the randomization period.

6. Primary Endpoint

The registry lists the primary outcome as Renal Function Assessed by Estimated Glomerular Filtartion Rate (eGFR), measured over At 12 months post-transplant.

The primary endpoint was renal function assessed by estimated glomerular filtration rate at 12 months post-transplant, reported in mL/min/1.73m^2. The registry states that eGFR was calculated using the MDRD-4 formula, which uses serum creatinine and age, with specified factors for women and African American participants. Serum creatinine was measured in mg/dL and age in years for that calculation.

As a general statistical and clinical concept, eGFR is an estimate of filtration rather than a direct measurement of kidney function. Using a continuous measure lets the analysis compare the groups’ estimated levels across a scale rather than reducing the outcome to a yes-or-no event. The value is dependent on the formula and its inputs, so it should be interpreted as the study’s defined estimate, not as a direct measurement.

The registry reports least-squares means with standard errors for the arms at the stated time point. It also says that missing 12-month eGFR values were imputed by last observation carried forward. That choice means the endpoint analysis included carried-forward values when a 12-month value was missing; the record does not report how many values were imputed. The endpoint is therefore best read alongside the analysis population, imputation approach, between-group estimate, and its confidence interval.

7. Results Posted in the Registry

• Group B (Tacrolimus Minimization Arm): mean 80.26 versus 85.50 on control; difference -5.24 (95% CI -16.11 to 5.63), standardized effect d = -0.27; z-test p = 0.345.

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.

Change From Baseline (Randomization) in Serum Creatinine at 12 Months Post-transplant

• 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 errors.
• Result:
  • Group B (Tacrolimus Minimization Arm): mean -0.05 versus -0.11 on control; difference 0.06 (95% CI -0.04 to 0.16), standardized effect d = 0.34; z-test p = 0.230.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Group B (Tacrolimus Minimization Arm) and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes address different aspects of the comparison from the primary eGFR endpoint. One concerns treated biopsy-proven acute rejection, acute rejection, graft loss, or death; the other concerns change in serum creatinine from randomization to 12 months post-transplant. The posted direction of the serum-creatinine estimates is broadly consistent with the primary direction in that the elimination arm has a more negative change estimate. However, the unadjusted comparison is imprecise and does not establish a clear difference.

These secondary results do not resolve the uncertainty in the primary result. eGFR and serum creatinine are related measures, but they are not interchangeable outcomes, and a finding on one cannot be assumed to determine the other. The rejection, graft-loss, and death composite addresses clinical events rather than a continuous renal-function estimate. Each outcome therefore contributes a distinct piece of evidence, and the registry’s posted results should be interpreted according to the endpoint actually measured.

Unadjusted secondary results carry less weight when multiple outcomes are examined because, in general, the chance of finding an apparently notable result can increase as the number of statistical tests grows. A multiplicity adjustment or prespecified hierarchy can address that concern, but such a plan is not reported in the registry record. The secondary results should consequently be viewed as supportive or exploratory rather than as independent confirmation of the primary finding. The record also does not report enough detail to assess the analysis population or missing-data handling for each secondary outcome.

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

• Percentage of Participants With Treated Biopsy Proven Acute Rejection (tBPAR) Acute Rejection (AR), Graft Loss (GL) or Death (D)
• Change From Baseline (Randomization) in Serum Creatinine at 12 Months Post-transplant

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is continuous: eGFR is recorded on a numeric scale, and the registry reports an arm estimate and standard error for each group. In general, a continuous outcome can retain information about variation across the scale that would be lost if it were converted to categories. The interpretation still depends on how the outcome was measured, the chosen time point, the analysis population, and the statistical model.

What does a least-squares mean represent?

A least-squares mean is a model-based estimate of a group mean. In general, such an estimate can account for terms included in the analysis model, whereas an unadjusted arithmetic mean is calculated directly from the observations. The registry labels the arm summaries as least-squares means, but it does not report the covariates or full model specification. It is therefore not possible to determine from the record which adjustments, if any, contributed to those estimates.

The registry reports standard errors alongside the arm estimates. In general, a standard error describes the estimated sampling variability of an estimate, not the spread of individual participants’ measurements. It is smaller when an estimate is more precise and larger when it is less precise. It should not be read as a range containing most individual eGFR values. The posted arm standard errors are 3.97 for elimination and 3.87 for minimization.

How is the between-group comparison read?

The sponsor-reported method is ANOVA, and the reported parameter is a net mean difference. In general, an analysis of variance compares group means relative to the variability in the data, under the model’s assumptions. The record reports a mean difference of 5.24, a 95% confidence interval from -4.86 to 15.34, and p = 0.301. The contrast direction is important: a positive or negative sign depends on which group is subtracted from the other. The arm means and the stated difference describe higher eGFR in the elimination arm, but the interval includes zero and does not provide a clear distinction between the strategies.

The recalculated contrast is an unadjusted comparison from posted summary statistics. It expresses minimization minus elimination and reports -5.24, a 95% confidence interval from -16.11 to 5.626, and p = 0.345. The recalculation estimates variability approximately from the available summary information; it does not reproduce the sponsor’s full ANOVA model. It is useful as a check on the direction and rough scale of the comparison, but it does not replace the reported analysis. The registry does not mark a discrepancy between the analyses.

What does the confidence interval add?

In general, a confidence interval describes the uncertainty around an estimated effect under the assumptions of the statistical procedure. A narrower interval indicates greater precision; a wider interval indicates that a broader range of effects remains compatible with the data. If an interval for a difference includes zero, the data do not rule out no difference at the confidence level used. This does not establish equivalence: an equivalence conclusion requires an appropriate design and prespecified margins, which are not reported in the registry record.

The sponsor’s confidence interval and the recalculated interval differ in width as well as orientation. That is expected to be possible because the recalculation is based on summary statistics and approximate variability, whereas the sponsor used ANOVA. The full analysis specification, including any covariates, assumptions, or handling of other model features, is not reported in the registry record. Thus, the sponsor’s estimate and uncertainty are the primary reference for the trial’s own analysis.

How was missing eGFR handled?

The registry states that the primary analysis used the safety population: all randomized participants who received at least one dose of study medication after randomization. It also states that missing 12-month eGFR observations were imputed using last observation carried forward. In general, this method substitutes a participant’s most recently observed value when the value at the target time point is missing. It can make an analysis possible when follow-up measurements are incomplete, but it assumes the earlier value is an adequate stand-in for the missing later value. That assumption may not hold if the outcome changes over time.

The record does not state how many eGFR observations were missing, when the last available observations occurred, or whether alternative imputation methods were used. The amount and pattern of missingness matter when assessing how sensitive a result may be to the imputation choice. Without those details, the effect of the LOCF approach on the result cannot be assessed from the registry record.

Why can over-dispersion matter?

In general, over-dispersion means that observed variability is greater than a model expects. It matters because a model that understates variability can make standard errors too small and confidence intervals too narrow. This primary outcome is continuous, and the registry does not report an over-dispersion assessment or a specific model adjustment for it. The concept is relevant broadly to statistical modeling, but there is no basis in the record to say that over-dispersion occurred in this analysis.

The posted p-value is a test result under the analysis model, not a measure of the probability that the observed effect is true. Interpretation should give more weight to the estimated difference and its uncertainty than to a threshold judgment about the p-value alone. The absence of a reported difference is not proof of equal outcomes, and a non-significant result does not show that all clinically important differences have been excluded.

11. Confidence Intervals and Precision

The sponsor-reported primary estimate is a mean difference of 5.24, with a 95% confidence interval from -4.86 to 15.34. In general, a confidence interval gives a range of values compatible with the data and the statistical method at the stated confidence level. Its width communicates precision: a broad interval leaves substantial uncertainty about the effect’s size and direction.

This interval includes zero. It therefore does not rule out no between-group difference, and its positive and negative values are compatible with effects in opposite directions under the reported contrast. It also extends to effects that may be important, but the registry does not state a threshold for clinical importance. The interval should not be read as proving equivalence or as a guarantee that the true effect lies within its endpoints.

The unadjusted recalculation gives a contrast of -5.24, with a 95% confidence interval from -16.11 to 5.626. The sign is reversed because the contrast is expressed in the opposite direction. This interval also includes zero. It is a simple recalculation from posted summaries, not the sponsor’s analysis; the sponsor’s ANOVA result takes precedence. The sponsor-reported interval is the appropriate primary reference for the trial’s analysis.

The arm standard errors are 3.97 and 3.87, but these do not describe the range of individual eGFR values. They describe uncertainty in the arm estimates. The record does not report the full model details or missing-data sensitivity analyses, which limits assessment of how robust the precision estimates are to those choices. The most defensible reading is that the posted primary estimate is uncertain and does not distinguish the regimens clearly.

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 participants per arm, not total participants or total events. They are illustrations based on the observed effect, rather than the original trial’s design calculation. The assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. The trial’s own original design assumptions are not reported in the registry record.

For planning for 100% of the observed primary effect, the illustration gives 220 participants per arm for 80% power and 294 participants per arm for 90% power. Planning for 75% of the observed effect gives 391 participants per arm for 80% power and 523 participants per arm for 90% power. Planning for 50% of the observed effect gives 879 participants per arm for 80% power and 1,176 participants per arm for 90% power.

In plain language, the 80% power column gives the illustrated number of participants per arm for a design with an 80% chance of detecting the specified effect under the planning assumptions, if that effect is present. The 90% column describes the corresponding illustration for a 90% chance. Smaller effects need more participants to distinguish them from random variation under the same assumptions. These figures are not observed power and do not describe the probability that the trial’s result is correct.

Because the effect sizes are based on the observed estimate, the illustrations inherit uncertainty from that estimate. They are not a substitute for a prospective sample-size calculation based on a justified target effect and a defined study plan. The registry record does not report the target effect or the original assumptions used to determine enrollment.

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 = -5.240; pooled standard deviation σ = 19.598.
2. n = 2 × (1.96 + 0.842)² × 19.598² / -5.240² = 219.6, rounded up to 220 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 <- -5.23999999999999                      # observed difference in means
sigma <- 19.5975135540201                     # 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(2115113)
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 = 220 (80% power), 294 (90% power)
 75% of observed effect: n per arm = 391 (80% power), 523 (90% power)
 50% of observed effect: n per arm = 879 (80% power), 1,176 (90% power)
power.t.test: 220.5 
Simulated power at n = 220 per arm: 0.799 (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. Analyses Reported by the Sponsor

The sponsor-reported primary analysis is an ANOVA comparison with a mean difference of 5.24, a 95% confidence interval from -4.86 to 15.34, and p = 0.301. That is the trial’s reported analysis and takes precedence over the simple recalculation. The registry does not flag a discrepancy.

The unadjusted recalculation expresses the contrast as minimization minus elimination and gives -5.24, with a 95% confidence interval from -16.11 to 5.626 and p = 0.345. The opposite sign reflects the reversed contrast direction; the group estimates are 85.5 for elimination and 80.26 for minimization. The recalculation uses the posted summary statistics and approximate variability, rather than the full ANOVA model.

Both analyses have confidence intervals that include zero, so neither provides a clear statistical distinction between the groups. Their uncertainty estimates and p-values differ because the recalculation is not a reconstruction of the sponsor’s full analysis. Model details needed to explain that difference more fully are not reported in the registry record. The sponsor’s result should therefore be used when describing the trial’s own primary analysis, while the recalculation is a secondary, unadjusted check.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary endpoint and two secondary outcomes, but the multiplicity strategy is not reported in the registry record. It is therefore unclear whether the secondary outcomes were tested as confirmatory hypotheses, whether any adjustment was planned for multiple comparisons, or whether an endpoint hierarchy was used. In general, testing multiple outcomes without adjustment can increase the chance of a false-positive result across the set of tests. That consideration is especially important when interpreting secondary p-values in isolation.

The original sample-size justification and trial-specific planning assumptions are not reported in the registry record. The planning illustrations based on the observed effect are not evidence of the study’s initial design rationale. Interim analyses, stopping rules, and any prespecified statistical analysis plan are also not reported in the registry record. No assumptions about those procedures can be made from the posted information.

For the primary endpoint, the registry specifies the safety population as randomized participants who received at least one dose of study medication after randomization. It also states that missing 12-month eGFR values were imputed using last observation carried forward. The number of missing measurements and the reasons for missingness are not reported in the registry record. Nor does the record describe sensitivity analyses using alternative approaches to missing data.

The record gives an enrollment of 78, while the reported arm-level primary analysis includes 24 participants in the elimination group and 26 in the minimization group. The reasons that the arm-level analysis counts differ from enrollment are not reported in the registry record. The record does not report whether the analysis population for each secondary outcome matches the primary safety population or how missing observations were handled for those outcomes.

These omissions constrain interpretation of the precision and robustness of the results. The stated population and imputation method are useful, but further details would be needed to assess the effects of missing data, understand the analysis model fully, or determine how the trial handled multiple outcomes.

16. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: aspartate aminotransferase increased (9.0%), cholangitis (8.3%), leukopenia (7.7%), pyrexia (7.7%), blood bilirubin increased (7.7%).

The adverse-event record reports serious events for the randomization treatment period in 4 of 24 participants in the tacrolimus elimination group and 9 of 26 in the tacrolimus minimization group. For other adverse events during that period, it reports 16 of 24 and 15 of 26, respectively. These are counts of participants affected against the listed at-risk group sizes; they should not be interpreted as a causal comparison or as proof that one regimen is safer.

The record also lists serious-event terms with percentages: aspartate aminotransferase increased, 9.0%; cholangitis, 8.3%; leukopenia, 7.7%; pyrexia, 7.7%; blood bilirubin increased, 7.7%; and alanine aminotransferase increased, 6.4%. The registry does not identify the timing for these listed terms in the adverse-event summary. Death counts are not reported in the registry record.

In general, adverse-event counts depend on the definitions, observation period, and population at risk. Differences in counts alone do not establish that treatment caused an event or that a between-group difference is statistically reliable. The posted safety figures describe reported events, not a formal comparative safety analysis.

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

The registry result answers a focused question: how eGFR at 12 months post-transplant compared between two everolimus-based regimens that differed in their tacrolimus strategy. The sponsor-reported estimate is a mean difference of 5.24, with a 95% confidence interval from -4.86 to 15.34 and p = 0.301. The interval includes zero and allows effects in either direction. The posted primary analysis therefore does not establish a clear difference between the regimens.

That conclusion is not the same as saying the regimens are equivalent. A failure to show a statistically clear difference can reflect uncertainty, including limited precision. To establish equivalence or non-inferiority, a trial would need an appropriate objective and prespecified margin; such a margin is not reported in the registry record. The confidence interval is not narrow enough to rule out every potentially important effect, and the record does not specify what magnitude would be clinically important.

The result also does not demonstrate that either regimen is preferable for every outcome or participant. The primary measure is a formula-based eGFR estimate at a single stated time point, and missing values were handled using last observation carried forward. The result does not directly establish longer-term kidney outcomes or resolve the separate rejection, graft-loss, death, and serum-creatinine questions listed as secondary outcomes.

These findings apply to the study’s analyzed population and its methods. The registry record describes randomization and the safety population, but does not provide a full account of missingness, the model specification, or the original design assumptions. Those limits should inform how confidently the estimate is generalized beyond the posted analysis. Overall, the result is best described as inconclusive about a between-group difference in eGFR, rather than as evidence of no difference or proof of benefit for either strategy.

18. Why This Trial Matters Statistically

This trial illustrates why a group estimate, its confidence interval, and the analysis population need to be read together. A single p-value does not show the size of a difference or how precisely it has been estimated. Here, the sponsor’s interval includes zero and also spans effects in both directions, leaving uncertainty that a threshold-based interpretation alone would conceal.

The comparison is also a useful example of two active strategies. Both arms used everolimus and tacrolimus at study start; their intended distinction was tacrolimus elimination versus minimization. The result therefore addresses the relative comparison between those approaches, not the effect of everolimus compared with no everolimus.

The record makes the missing-data method explicit for the primary endpoint: last observation carried forward. That information matters because an imputed value is not the same as an observed value at 12 months. At the same time, the count and pattern of missing measurements are not reported, so readers cannot judge how much the imputation may have influenced the estimate.

The contrast between the sponsor-reported ANOVA and a simple recalculation highlights the limits of reanalysis from summary statistics. A recalculation can help orient the estimated difference, but it cannot reproduce an analysis model that is not fully described. The sponsor’s analysis remains the reference for the trial’s own result.

Finally, the registry’s planning illustrations show how sample-size requirements depend on the effect a future study aims to detect. They are not the original design rationale and are not observed power. Keeping those distinctions clear helps separate the trial’s observed evidence from planning scenarios for future research.

19. Limitations

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

The trial was open-label, so participants and study personnel were not masked to assignment according to the registry. That could matter for outcomes involving judgment or care decisions, although the record does not report whether outcome assessment was masked. The primary endpoint is a calculated laboratory-based estimate, which may be less directly subject to observer judgment than some clinical outcomes, but the registry does not describe measurement procedures beyond the MDRD-4 formula.

The primary analysis used last observation carried forward for missing 12-month eGFR values. The number and timing of missing values, reasons for missingness, and sensitivity of results to other methods are not reported in the registry record. This limits assessment of the impact of imputation.

The record does not report the covariates or full specification of the sponsor’s ANOVA model. A summary-statistic recalculation is consequently not a substitute for the sponsor’s analysis, and the difference between the reported and recalculated uncertainty cannot be fully evaluated. The original sample-size assumptions, interim analyses, stopping rules, and multiplicity approach are also not reported in the registry record.

The primary outcome is specified at 12 months post-transplant. The record lists a 6-month follow-up, but the posted primary result does not establish what happened beyond the reported endpoint. The two secondary outcomes address other clinical and laboratory measures, but secondary analysis details are limited. Finally, the enrollment count and arm-level analysis counts differ; the reasons are not reported in the registry record. These limitations leave important questions about missingness, analysis details, and the breadth of inference unresolved.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: REnal Function in Liver Transplantation: Everolimus With Calcineurin Inhibitor (CNI)-Sparing sTrategy — NCT02115113.
• Registry record last updated 2019-02-28; status last verified 2018-10.
• Results first posted 2019-02-28.
• 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

NCT02115113 is a completed Phase 3 randomized, open-label, parallel-group study in adult liver transplant recipients. It compared everolimus-based regimens using tacrolimus elimination or minimization. The primary endpoint was eGFR at 12 months post-transplant, calculated with the MDRD-4 formula. The primary analysis used the safety population and last observation carried forward for missing 12-month eGFR values.

The sponsor-reported ANOVA estimate was a mean difference of 5.24, with a 95% confidence interval from -4.86 to 15.34 and p = 0.301. The interval includes zero, so the posted primary result does not establish a clear between-group difference. Secondary outcomes concerned rejection-related events, graft loss or death, and change in serum creatinine. The registry does not report the original sample-size assumptions, multiplicity plan, full model specification, or details of missingness.