A National Multi-center Randomized, Open Label Study to Evaluate Efficacy and Safety of Everolimus With EC-MPS Compared to Standard Treatment Combination Tacrolimus and EC-MPS in de Novo Liver Transplant Recipients: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A National Multi-center Randomized, Open Label Study to Evaluate Efficacy and Safety of Everolimus With EC-MPS Compared to Standard Treatment Combination Tacrolimus and EC-MPS in de Novo Liver Transplant Recipients (NCT01625377), a randomized phase 3 study. The primary outcome is Change From Baseline (Randomization) in Renal Function.

2. Clinical Question

The trial record describes a randomized comparison in de novo liver transplant recipients. Its clinical question focuses on whether the early everolimus strategy was associated with a different short-term change in estimated renal function than the tacrolimus-based standard combination. The primary endpoint is a continuous measurement, so the principal contrast is between average changes rather than counts of participants with an event.

The endpoint timeframe runs from the Day 28 baseline visit to Week 24. The registry’s brief summary frames the renal-function assessment at six months after transplantation; the primary outcome listing uses baseline and Week 24. The record does not report a threshold defining a clinically important difference in GFR, so the statistical contrast alone cannot establish whether the observed difference is clinically meaningful.

3. Trial Design

NCT01625377 is a completed, phase 3, randomized, open-label, parallel-group study sponsored by Novartis Pharmaceuticals. Its title describes a national, multi-center comparison in de novo liver transplant recipients. The registry reports enrollment of 188. The study began in 2012-12, and primary completion was recorded as 2015-03.

The two groups were assigned different post-randomization treatment strategies: everolimus (RAD001) with mycophenolic acid, compared with tacrolimus and mycophenolic acid. The study was not masked. According to the arm descriptions, both groups received basiliximab and tacrolimus early after transplantation, before randomization. The tacrolimus group continued tacrolimus with mycophenolic acid after randomization. The other group was intended to transition to everolimus; the brief summary describes the aim as early introduction of everolimus with tacrolimus discontinuation. The registry’s detailed everolimus dose-target description is truncated, so the full dosing instructions are not reported in the registry record.

The primary outcome measured change in GFR from baseline at randomization to Week 24. The primary population required at least one post-randomization dose and creatinine measurements at Day 28 and at a later time. Missing values were handled with last observation carried forward (LOCF), as stated in the outcome description. The listed analysis-arm counts for the primary outcome are 93 for tacrolimus and 90 for everolimus.

The registry record does not report the original sample-size justification, the intended allocation ratio, or whether interim analyses were planned or conducted. It also does not give further detail in the record about stratification, concealment of allocation, or the statistical analysis plan beyond the reported ANCOVA analysis. Those design details should not be inferred from the randomized, parallel, open-label labels.

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: Total 188 patients were randomized

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The Intent to treat (ITT) population included all randomized patients who received at least one dose of study treatment post-randomization and for whom a creatinine value a Day 28 and a posterior value were available. The last observation carried forward (LOCF) is used as imputation of missing data.

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: Randomized population

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline (Randomization) in Renal Function, measured over Baseline, Week 24.

The primary endpoint is change from baseline in renal function, expressed as GFR in mL/min/1.73m^2, between the Day 28 visit and Week 24. The registry says GFR was calculated with the abbreviated modification of diet in renal disease (aMDRD) formula. The primary outcome is described as a least-squares mean, with standard error as the measure of dispersion.

GFR is used as an estimate of how effectively the kidneys filter blood. A change score compares each participant’s later estimated GFR with the value at the randomization baseline, then the group-level analysis compares those changes. This focus on change can account for where participants started, though the registry’s sponsor-reported analysis is specifically described as ANCOVA and the full model specification is not reported in the registry record.

A continuous endpoint retains information about the amount and direction of change rather than reducing results to whether a participant crossed a binary threshold. It is also an estimate based on a formula, not a direct measurement of filtration. The endpoint therefore describes change in estimated renal function on the stated scale; it does not by itself establish a participant’s overall kidney status, a clinically important threshold, or the balance of benefits and harms of the treatment strategies.

The listed analysis population required creatinine values at Day 28 and a later time, with LOCF used to impute missing data. This definition and imputation approach matter when interpreting the group means: the estimates pertain to the registry-defined analysis population and its missing-data handling, not necessarily to every randomized patient under every possible analysis approach.

7. Results Posted in the Registry

• Everolimus (RAD001): mean 1.05 versus -13.29 on control; difference 14.34 (95% CI 6.63 to 22.05), standardized effect d = 0.54; z-test p = <0.001.

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

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Everolimus (RAD001): mean -1.30 versus 7.20 on control; difference -8.50 (95% CI -19.31 to 2.31), standardized effect d = -0.23; z-test p = 0.123.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Everolimus (RAD001) and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline (Randomization) in Urine Protein/Creatinine Ratio

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Everolimus (RAD001): mean 21.90 versus -2.30 on control; difference 24.20 (95% CI 0.12 to 48.28), standardized effect d = 0.36; z-test p = 0.049.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Everolimus (RAD001) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline (Randomization) in Creatinine Clearance Estimated Using the Adjusted Cockcroft-Gault Formula

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Everolimus (RAD001): mean 0.70 versus -9.00 on control; difference 9.70 (95% CI 1.52 to 17.88), standardized effect d = 0.34; z-test p = 0.020.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Everolimus (RAD001) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes broaden the assessment beyond the primary GFR change, including treatment failures, biopsy-proven acute rejection, severity categories, death or graft loss, serum creatinine, urine protein/creatinine ratio, and estimated creatinine clearance. In the posted renal measures, the pattern is not uniform: estimates differ by measure, and the intervals and unadjusted p-values do not give the same level of evidence across outcomes. This provides context rather than a single independent confirmation of the primary result.

The secondary kidney measures are related to renal function but are not interchangeable. Serum creatinine, urine protein/creatinine ratio, and estimated creatinine clearance reflect different aspects of kidney status and use different scales or calculations. Agreement across several measures can strengthen coherence, while disagreement can signal that conclusions depend on which aspect is examined. Here, the overall secondary pattern is mixed rather than uniformly aligned with the primary endpoint.

The registry reports 12 secondary outcomes, but the listed information does not include sponsor-reported analyses for the three continuous secondary measures described in detail. It also does not report whether multiplicity was addressed. When multiple outcomes are examined, the chance of at least one apparently notable result can increase even if no adjustment is made. Consequently, nominal unadjusted p-values from secondary comparisons carry less weight than a result from a designated primary analysis, especially when the analysis plan and hierarchy are not reported.

Secondary findings should be treated as supportive or exploratory signals in the context of the primary outcome, study design, and uncertainty. They do not independently establish an overall treatment effect or resolve questions about clinical importance, long-term outcomes, or safety.

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

• Number of Patients With Treatment Failures
• Number of Patients With Treated or Not Treated Biopsy Proven Acute Rejection (BPAR)
• Number of Patients Reported With Different Categories of Severity of BPAR According to Banff Classification
• Number of Patients With Treated or Untreated BPAR With RAI Score Greater Than 3
• Number of Patients With Death or Graft Loss
• Change From Baseline (Randomization) in Serum Creatinine
• Change From Baseline (Randomization) in Urine Protein/Creatinine Ratio
• Change From Baseline (Randomization) in Creatinine Clearance Estimated Using the Adjusted Cockcroft-Gault Formula

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous: each participant has a measured change in GFR, and the group summaries describe average change. The primary arm values are least-squares means rather than simple arithmetic means, and their dispersion is reported as standard error. A standard error describes the precision of an estimated mean; it is not the spread of individual participant measurements. The registry does not provide the full model specification used to obtain the least-squares means.

What does the reported ANCOVA do?

ANCOVA, or analysis of covariance, compares groups while accounting for one or more covariates in a statistical model. In a baseline-adjusted clinical-trial analysis, this can improve the comparison’s precision when baseline values are related to the outcome. The registry identifies ANCOVA as the sponsor’s method and reports a net mean difference, confidence interval, and p-value. The particular covariates, model assumptions, and handling of any model diagnostics are not reported in the registry record, so the analysis should not be described as adjusted for any specific variable beyond what the record states.

The re-calculated comparison is a simple, unadjusted contrast reconstructed from the posted arm summaries. It is not a replacement for ANCOVA: it does not reproduce the sponsor’s model adjustment. For the primary result, the posted summary standard errors were used to obtain an approximate standard deviation for this recalculation, as indicated by the calculation method. This approximation is a feature of the re-calculation, not an additional claim about the individual-level data.

How should the contrast and p-value be read?

A mean difference is the difference between the two group estimates in a stated order. For the re-calculated primary contrast, the order is everolimus minus tacrolimus, yielding 14.34 mL/min/1.73m^2. Reversing the order reverses the sign but not the magnitude. The sponsor reports -14.34 for its contrast, so the sign difference is consistent with the groups being subtracted in the opposite order.

The p-value describes how compatible the observed result is with a statistical model in which the contrast is zero, under the assumptions of the analysis. A small p-value is evidence against that zero-difference model, but it does not measure the size or clinical importance of the difference. The sponsor reports p < 0.001, while the simple unadjusted recalculation reports p < 0.001. These are results from different analysis approaches and should not be treated as interchangeable.

What does a confidence interval add?

A confidence interval gives a range of values compatible with the data and the statistical model at the stated confidence level. Narrower intervals indicate greater precision, while wider intervals indicate more uncertainty about the size of the contrast. The sponsor’s ANCOVA interval is explicitly reported as 95%. The re-calculated interval is an unadjusted interval based on the posted summary statistics. Neither interval captures all uncertainty about the endpoint’s measurement, the applicability of the result to other populations, or unreported analytic choices.

Why can dispersion and distribution matter?

Standard error quantifies uncertainty in a group mean, whereas standard deviation describes variability among participant measurements. Confusing them can make a group estimate appear more or less variable than it is. For the primary outcome, the record gives standard errors for the arm estimates. The re-calculation therefore approximates the standard deviation used for its unadjusted comparison rather than recovering it from individual participant values.

For continuous outcomes, a mean difference can be sensitive to skewness or unusually large values. General statistical practice considers the outcome distribution and model assumptions when interpreting mean-based analyses. The registry record does not report distribution checks, transformations, or robust methods, so none should be assumed. Over-dispersion is a general concern when observed variability exceeds that represented by a model; it can make model-based uncertainty too small if not addressed. The registry does not report whether over-dispersion was assessed for these continuous outcomes.

How do missing values affect the analysis?

The primary outcome population included randomized patients who received at least one dose of post-randomization study treatment and had a Day 28 creatinine value and a posterior value. LOCF was used to impute missing data. LOCF carries a participant’s last observed value forward to represent a later missing value. As a general statistical matter, this method can be problematic if the outcome would have changed after the last observation or if missingness is related to health status or treatment. The registry does not report sensitivity analyses comparing LOCF with other approaches, or the amount and reasons for missing data.

The stated population is called intent to treat in the outcome description, but its operational definition includes post-randomization treatment and available creatinine values. That definition is narrower than a literal analysis of every randomized participant regardless of treatment receipt or outcome availability. Readers should use the registry’s stated criteria when interpreting the reported arm counts, rather than assume a different analysis population.

11. Confidence Intervals and Precision

The primary re-calculated interval for the everolimus-minus-tacrolimus difference runs from 6.634 to 22.05 mL/min/1.73m^2. It does not include zero, which is consistent with the small unadjusted p-value and supports a difference in the group-level estimated changes under the recalculation’s assumptions. The interval is not a range of individual participant responses, nor does it indicate where every participant’s change fell.

The sponsor’s ANCOVA result has a 95% confidence interval from -21.34 to -7.34 for its reported contrast. This interval also excludes zero. Its negative direction reflects the sponsor’s contrast ordering, opposite to the re-calculated everolimus-minus-tacrolimus ordering. The two intervals are close in magnitude but arise from different approaches: the sponsor’s adjusted model and the simple unadjusted reconstruction. The registry marks no discrepancy between them.

Precision is about uncertainty in the estimated contrast. The intervals suggest the primary data are more compatible with a difference than with no difference under the respective models, but the range still allows variation in the size of that difference. Statistical precision does not resolve whether the change is important to patients or whether it represents all dimensions of renal function.

For secondary outcomes, uncertainty varies. Some posted intervals span zero and others do not, so the strength of evidence is not the same across measures. These results are secondary, and multiplicity adjustment is not reported in the registry record. Confidence intervals and p-values for those comparisons should therefore be interpreted with the number of outcomes examined in mind, rather than as isolated confirmatory tests.

12. Planning a Similar Trial: Sample Size

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

The sample-size figures are planning illustrations based on the observed effect, not the original trial design. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set at the stated fraction of the observed effect. The registry’s original sample-size assumptions and justification are not reported in the registry record.

For these continuous outcomes, the figures mean participants per arm. They are not total participants across both arms and are not event counts. The 80% power column gives the illustrative number of participants per arm needed for an analysis to have an 80% chance of detecting the chosen effect, assuming the planning model and assumptions hold. The 90% power column gives the corresponding planning target for a 90% chance. These are design calculations for hypothetical future studies, not observed characteristics of this completed trial.

The rows describe planning for 100%, 75%, and 50% of the observed effect. A smaller effect is harder to distinguish from random variation, so the planning illustration requires more participants per arm to detect it at the same stated power. The figures also depend on the observed effect and variability used in the calculation; they do not establish that the original study was adequately or inadequately sized.

The curve should be read as a visualization of how the illustrative sample-size requirement changes with the assumed effect, under the same stated planning assumptions. It is not a record of recruitment or a prediction of the results of another study. This is not observed power: it does not calculate the probability that the completed trial’s result is true or the probability that a treatment effect exists.

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 = 14.340; pooled standard deviation σ = 26.588.
2. n = 2 × (1.96 + 0.842)² × 26.588² / 14.340² = 54.0, rounded up to 54 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 <- 14.34                      # observed difference in means
sigma <- 26.5879662681493                     # 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(1625377)
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 = 54 (80% power), 73 (90% power)
 75% of observed effect: n per arm = 96 (80% power), 129 (90% power)
 50% of observed effect: n per arm = 216 (80% power), 289 (90% power)
power.t.test: 54.9 
Simulated power at n = 54 per arm: 0.786 (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’s reported primary analysis is ANCOVA, with a net mean difference of -14.34, a 95% confidence interval from -21.34 to -7.34, and p < 0.001. The registry lists the group order as tacrolimus and everolimus. The re-calculation reports everolimus minus tacrolimus as 14.34, with an interval from 6.634 to 22.05 and p < 0.001. The estimates have the same magnitude and opposite signs, consistent with reversing the order of subtraction.

The re-calculation is unadjusted and reconstructed from posted summary statistics; the sponsor’s ANCOVA is the trial-reported analysis. It is therefore useful as a transparent check on the broad contrast, but it does not reproduce the sponsor’s model or replace its analysis. The registry marks the discrepancy indicator as false, and the two results point to a difference in the same underlying direction once contrast order is taken into account.

The sponsor’s interval and p-value should be read as the reported inferential result for the primary endpoint. The re-calculated interval and p-value provide a separate summary-based analysis, with its own assumptions. Neither result establishes clinical importance, because the registry record does not state a clinically important difference threshold for GFR.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies a primary renal-function outcome and lists secondary outcomes covering treatment failures, rejection, graft and mortality events, and additional renal measures. The record reports 13 outcome measures and 12 posted secondary outcomes. Testing several outcomes creates a multiplicity issue: as more hypotheses are examined, some results may appear statistically notable by chance even when there is no underlying effect. This is a general property of repeated testing, not a claim that any particular result is false.

Multiplicity can be addressed through a prespecified testing hierarchy, adjusted significance thresholds, family-wise error control, false-discovery procedures, or a clearly exploratory interpretation. The multiplicity strategy and outcome hierarchy are not reported in the registry record. The secondary p-values should therefore be read as unadjusted comparisons, not as evidence that a family-wise error rate was controlled. The registry does not report interim analyses or whether any interim testing affected the final interpretation.

For the primary analysis, the outcome description defines the intent-to-treat population as randomized patients who received at least one dose of post-randomization study treatment and had a Day 28 creatinine value and a later value. That operational definition excludes randomized patients who did not meet those criteria, so it is not a literal all-randomized analysis regardless of treatment receipt and data availability. The listed primary arm counts are 93 and 90. The registry does not give a fuller accounting of exclusions from that analysis population in the information summarized.

LOCF was used to impute missing primary outcome data. This approach carries the last observed measurement forward; it may not reflect the true later value if a participant’s renal function changes after the last observation. The number of missing values, their reasons, the timing of last observations, and sensitivity analyses under other missing-data assumptions are not reported in the registry record. These omissions limit assessment of how robust the primary estimate is to missingness and imputation choices.

The original statistical analysis plan, covariates in the ANCOVA, detailed model checks, and procedures for handling multiple analyses are not reported in the registry record. Those absences do not invalidate the reported estimates, but they limit independent assessment of whether all analytic choices were prespecified and how they affect uncertainty.

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: liver transplant rejection (5.6%), sepsis (5.6%), biliary anastomosis complication (5.6%), diarrhoea (4.3%), renal failure (4.3%).

The registry’s adverse-event summary reports serious adverse events affecting 28 of 94 participants at risk in the tacrolimus group and 42 of 90 at risk in the everolimus group. Other adverse events are reported for 68 of 94 at risk in the tacrolimus group and 64 of 90 at risk in the everolimus group. These are counts of participants recorded as affected, not counts of separate event episodes. The record does not provide death counts in this summary.

The listed serious adverse-event terms and percentages are liver transplant rejection, 5.6%; sepsis, 5.6%; biliary anastomosis complication, 5.6%; diarrhoea, 4.3%; renal failure, 4.3%; and pancytopenia, 2.2%. The summary does not specify an arm attribution for each listed term, so these percentages should not be assigned to one treatment group. The terms may also represent different event types rather than mutually exclusive participant categories.

These figures describe reported safety events during the registry’s reporting period; they do not by themselves establish that treatment caused an event or allow a complete comparative safety assessment. The registry record does not provide further detail about event timing, severity beyond the serious classification, exposure duration, or the method used to judge relatedness.

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

The primary result describes a difference in mean change in estimated GFR between the two treatment groups from the Day 28 baseline to Week 24. The posted estimates and the sponsor’s ANCOVA both support a group difference on this outcome, with the contrast direction depending on which group is subtracted from the other. The result is about the average change in a formula-based measure over the recorded period.

It does not show that every participant’s renal function changed in the same way. Group averages can coexist with substantial individual variation, and standard errors describe uncertainty in the estimated means rather than the range of individual responses. Nor does a statistically clear difference automatically establish that the difference is large enough to matter clinically. The registry record does not report a threshold for clinical importance.

The endpoint is estimated GFR calculated with the aMDRD formula. It is not a direct measurement of filtration and does not capture every aspect of kidney health. The secondary measures offer other perspectives, but their results are mixed and their multiplicity handling is not reported. The primary result should not be treated as a complete account of renal function, rejection, graft outcomes, or overall safety.

The treatment strategies also include more than a single drug in isolation: the arm descriptions include mycophenolic acid, early basiliximab and tacrolimus, and optional oral corticosteroids. The comparison therefore concerns the recorded regimens and transitions, not a head-to-head test of everolimus alone against tacrolimus alone. Details of the full everolimus target regimen are incomplete in the registry record.

Finally, the outcome concerns Week 24. It does not establish longer-term effects, outcomes in populations not described in the record, or the results of a different treatment strategy. The findings are best understood within the randomized, open-label trial and the analysis population, endpoint definition, and missing-data method recorded for this study.

18. Why This Trial Matters Statistically

This study illustrates why a clinical-trial result needs to be read through its endpoint definition, contrast direction, analysis method, and missing-data rules. The primary outcome is a continuous change in estimated GFR, and the sponsor reports an ANCOVA contrast. A summary-based unadjusted recalculation gives the same contrast magnitude with the reverse sign because the comparison order is reversed. Recognizing that distinction prevents a sign convention from being mistaken for a contradictory result.

The study also shows the value of separating a statistical difference from its clinical interpretation. The primary interval excludes zero, but the registry record does not define a clinically important change in GFR. Precision and statistical evidence describe uncertainty around the group contrast; they do not answer whether the scale of change matters to patients or how it compares with other aspects of care.

Several renal outcomes are included, yet the secondary pattern is not entirely consistent and the record does not describe multiplicity adjustment. That makes it important to distinguish the primary analysis from secondary signals and to avoid treating every unadjusted finding as confirmatory. The registry’s LOCF approach and restricted operational analysis population also show why an endpoint estimate depends on who contributes data and how missing measurements are handled.

Finally, the randomized, open-label parallel design provides a structured comparison of treatment strategies, while the absent details on allocation procedures, original sample-size justification, and statistical plan limit what can be independently assessed from the record. Those limits do not erase the reported result; they define the boundary of what the registry record supports.

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 registry record leaves several trial-specific details unresolved. It identifies the study as randomized, open-label, and parallel-group, but does not report the allocation ratio, allocation concealment procedures, stratification factors, or the full protocol. The original sample-size justification and assumptions are not reported, so the planning illustrations based on observed effects should not be mistaken for the trial’s initial design rationale.

The primary endpoint is estimated GFR calculated using the aMDRD formula, rather than a direct filtration measurement. The record does not state a clinically important difference threshold or provide a detailed rationale for choosing the endpoint and Week 24 assessment. The trial is open-label, and the registry does not describe blinding of endpoint assessment or whether it was feasible for this laboratory-based outcome.

The operational analysis population required post-randomization treatment and specified creatinine measurements. LOCF was used for missing data, but the extent and reasons for missingness and sensitivity analyses are not reported in the registry record. The complete ANCOVA specification and model diagnostics are also not reported. These gaps constrain assessment of the impact of population selection, imputation, and model choices.

The registry lists multiple secondary outcomes, but does not report a multiplicity strategy for the comparisons summarized. The secondary analyses therefore have less confirmatory force, and the listed results should not be interpreted as a fully controlled family of tests. The detailed everolimus dose-target description is truncated, and the record does not report longer-term primary renal-function results in the information summarized. Together, these limitations restrict conclusions to the recorded regimens, analysis, and follow-up period.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A National Multi-center Randomized, Open Label Study to Evaluate Efficacy and Safety of Everolimus With EC-MPS Compared to Standard Treatment Combination Tacrolimus and EC-MPS in de Novo Liver Transplant Recipients — NCT01625377.
• Registry record last updated 2016-04-27; status last verified 2016-03.
• Results first posted 2016-04-27.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

NCT01625377 is a completed, phase 3, randomized, open-label, parallel-group study sponsored by Novartis Pharmaceuticals. It enrolled 188 de novo liver transplant recipients and compared everolimus (RAD001) with mycophenolic acid against tacrolimus with mycophenolic acid. The primary endpoint was change in estimated GFR from the Day 28 baseline to Week 24.

The posted primary estimates were -13.29 mL/min/1.73m^2 for tacrolimus and 1.05 mL/min/1.73m^2 for everolimus. The sponsor’s ANCOVA reported a net mean difference of -14.34, with a 95% confidence interval from -21.34 to -7.34 and p < 0.001. The simple unadjusted recalculation gives the opposite contrast sign because it uses the reverse group order.

Interpretation is limited by the estimated nature of the endpoint, the stated analysis population and LOCF imputation, incomplete reporting of the analysis plan, and unreported multiplicity handling for secondary outcomes. The registry does not define a clinically important GFR difference.