Tacrolimus and Mycophenolate Mofetil (MMF) in GVHD Prophylactic Regimen Compared to Tacrolimus and Methotrexate (MTX: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Tacrolimus and Mycophenolate Mofetil (MMF) in GVHD Prophylactic Regimen Compared to Tacrolimus and Methotrexate (MTX (NCT00360685), a randomized na study. The primary outcome is Incidence of Severe Mucositis.

2. Clinical Question

3. Trial Design

This was a randomized, open-label, parallel-group trial comparing tacrolimus plus MTX with tacrolimus plus MMF for GVHD prophylaxis in allogeneic HCT. The registry reports enrollment of 89. The primary outcome was designated for the intent-to-treat population. The record does not describe a masking procedure, consistent with its NONE masking entry.

The study began in 2005-09, reached primary completion in 2011-01, and is listed as COMPLETED. Its phase is recorded as NA. The sponsor was H. Lee Moffitt Cancer Center and Research Institute. The registry lists mucositis and GVHD among the conditions relevant to the study.

Participants were assigned to the tacrolimus-and-MTX group or the tacrolimus-and-MMF group. The posted primary outcome counts are 25 of 47 participants in the MTX group and 14 of 42 in the MMF group. The registry describes daily tacrolimus, followed by a taper if GVHD was absent. It also describes tapering of the randomized additional medication in the absence of GVHD. Blood levels were used to guide dose adjustment. Details beyond this summary, including the precise dosing schedules and how protocol deviations were handled, are not reported in the registry record.

Random allocation supports a comparative interpretation, but it does not ensure that the groups will be identical in every characteristic, particularly in a trial of this size. Because masking was NONE, participants and study personnel were not masked according to the registry entry. The registry does not describe whether outcome assessors were independently masked. Details of the original sample-size rationale, the allocation procedure, and any prespecified interim analyses are 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.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Intent to treat

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Incidence of Severe Mucositis, measured over 2 year.

The primary endpoint was the incidence of severe mucositis, expressed as the number of participants with the event. Severe mucositis was defined as grade 3 or grade 4 using the National Cancer Institute Common Terminology Criteria for Adverse Events, version 3.0. The registry states that mucositis was assessed prospectively each day while a participant was hospitalized and graded retrospectively using nurse and clinician assessments. The outcome timeframe is 2 year.

This endpoint is clinically relevant to the trial’s comparison because mucositis was one of the conditions being studied alongside GVHD prophylaxis. The endpoint turns individual clinical assessments into a binary outcome: a participant either met the severe-mucositis definition during the specified assessment period or did not. Comparing the numbers with events across randomized groups gives a direct estimate of the difference in observed event risk.

Retrospective grading based on clinical assessments means that how consistently the criteria were applied matters to interpretation. Open-label trial conduct can also be relevant to outcomes involving clinical assessment, although the registry does not report whether assessors were masked or how disagreements in grading were resolved. The endpoint definition and assessment approach are reported; additional operational details are not reported in the registry record.

7. Results Posted in the Registry

• Tacrolimus And Mycophenolate Mofetil: 33.3% (14/42) versus 53.2% (25/47) on control; risk difference -19.9 percentage points (95% CI -40.0 to 0.3), risk ratio 0.63 (0.38–1.04); unadjusted two-proportion z-test p = 0.059.

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.

Incidence of Acute Graft-vs-host Disease (aGVHD)

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Tacrolimus And Mycophenolate Mofetil: 78.6% (33/42) versus 95.7% (45/47) on control; risk difference -17.2 percentage points (95% CI -30.9 to -3.5), risk ratio 0.82 (0.69–0.97); unadjusted two-proportion z-test p = 0.014.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Tacrolimus And Mycophenolate Mofetil than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Overall Survival

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Tacrolimus And Mycophenolate Mofetil: 64.3% (27/42) versus 59.6% (28/47) on control; risk difference 4.7 percentage points (95% CI -15.5 to 24.9), risk ratio 1.08 (0.78–1.49); unadjusted two-proportion z-test p = 0.648.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tacrolimus And Mycophenolate Mofetil and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes address different aspects of the clinical comparison: acute GVHD is an event outcome at 100 days post transplant, while overall survival is reported at 1 year. They broaden the context beyond severe mucositis, but they do not alter the primary endpoint’s definition or resolve its uncertainty. The secondary results should be interpreted as additional findings, not as substitutes for the primary result.

The posted secondary analyses do not form a single consistent pattern of evidence when the registry tests and simple recalculations are considered together. Acute GVHD has a marked difference in the posted counts and a recalculated risk-difference interval that excludes zero, while the registry-reported test gives p = 0.8. The record does not explain that divergence. For overall survival, the recalculated count-based interval crosses zero and the reported Log Rank test gives p = 0.58. Because these methods do not all address the outcome in the same way, the results should not be collapsed into a single conclusion about the two regimens.

Unadjusted secondary findings generally carry less weight than a prespecified primary comparison. Multiple outcomes create more opportunities to observe apparently notable results by chance, especially when many tests are considered. The registry does not report a multiplicity adjustment or a hierarchy for interpreting secondary outcomes. The record lists three outcome measures and three analyses, but that listing does not establish that multiplicity was controlled or that each analysis was prespecified.

The secondary outcomes can be informative as descriptive evidence and can motivate further study. Their interpretation is limited by the small overall enrollment, the lack of reported details about analysis populations and missing data, and the unexplained difference between the acute GVHD recalculation and registry-reported test. They should be considered alongside the primary result and the stated methods, without treating an individual secondary p-value as decisive.

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

• Incidence of Acute Graft-vs-host Disease (aGVHD)
• Overall Survival

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary: each participant is counted according to whether severe mucositis was recorded. For this kind of outcome, an event count and the number of participants at risk describe the observed frequency in each group. The primary result compares the event risk for tacrolimus plus MMF with the event risk for tacrolimus plus MTX. The sign convention used for the recalculated risk difference is MMF minus MTX, so a negative value corresponds to a lower observed risk in the MMF group.

What does a risk difference express?

A risk difference subtracts the event risk in one group from the event risk in the other group. It is expressed on an absolute scale: zero represents equal observed risks, a negative value indicates a lower observed risk in the MMF group under this sign convention, and a positive value indicates a higher observed risk in that group. The estimate of -0.199 is a recalculation from the posted counts. It is unadjusted, meaning that it does not account for other participant characteristics or use a model-based adjustment.

Absolute differences can be useful because they describe the size of the contrast on the event-risk scale. They do not by themselves explain why the groups differ, and an estimate can be imprecise when the number of participants is limited. The estimate should therefore be read alongside its confidence interval and the trial’s reported analysis.

What does the confidence interval contribute?

A confidence interval describes the precision of an estimate under the statistical method used. In general, a wider interval indicates greater uncertainty about the effect size. The primary 95% confidence interval extends from -0.400 to 0.003. Since this interval includes zero, the posted results are compatible with no difference as well as with differences in either direction. This does not mean that all values in the interval are equally plausible, or that the interval gives the probability that the true effect lies within it.

Why are the tests not identical?

The registry reports a Fisher Exact analysis for the primary endpoint, with p = 0.06. Fisher’s exact test evaluates evidence of association in a two-group table of event and non-event counts. The recalculated p-value of 0.059 is an unadjusted calculation from the posted summary data; the associated recalculated risk difference and confidence interval describe the effect on an absolute-risk scale. A p-value and an effect estimate answer related but distinct questions: the p-value measures how compatible the data are with a specified null model under a test, while the estimate and interval describe the direction, size, and precision of the contrast.

The registry’s p-value is rounded to 0.06, whereas the recalculated value is reported as 0.059. The discrepancy flag is false. The registry record does not provide enough detail to infer further steps in the sponsor’s analysis, so neither the test nor its rounding should be embellished with an unreported explanation.

How should the secondary methods be read?

The secondary outcomes use different analysis entries. For acute GVHD, the registry identifies a K-sample test for comparing the cumulative outcome, but the method description is incomplete in the record; its reported p-value is 0.8. A simple recalculation from the posted counts yields a different unadjusted risk-difference result. The registry does not explain how the reported analysis relates to that recalculation, so the two should not be presented as equivalent results. For overall survival, the reported method is Log Rank, a method that compares event-time experience between groups while accounting for the timing of events. Its p-value of 0.58 is not the same quantity as the p-value from a simple comparison of binary counts. The registry does not provide further detail about the survival analysis, including the handling of censoring.

General statistical context: using a test suited to an outcome’s structure matters. Treating a time-to-event outcome as a simple yes-or-no count can discard timing information; conversely, a binary risk difference is naturally interpretable as an absolute difference in observed event risks. The methods and effect measures should be interpreted according to their own definitions rather than mixed together.

What does randomization add?

Random allocation is intended to make treatment assignment independent of participant characteristics, on average, and supports a causal comparison when conduct and follow-up are appropriate. It does not guarantee balance in every characteristic in a particular trial. With enrollment of 89, chance imbalances remain possible. The registry does not report baseline characteristics or an adjusted analysis in the posted results.

The primary endpoint is designated for the intent-to-treat population, which generally means participants are analyzed according to assigned group, regardless of treatment received after assignment. The record does not detail how missing outcome information, withdrawals, or other deviations were handled. That limitation matters because an intent-to-treat label alone does not specify how unavailable measurements were treated.

11. Confidence Intervals and Precision

The primary risk-difference estimate is -0.199, with a 95% confidence interval from -0.400 to 0.003. The interval is broad relative to the point estimate and crosses zero. It therefore allows for uncertainty about whether the underlying difference favors the MMF group, the MTX group, or is close to no difference. The estimate is not precise enough to distinguish confidently between those possibilities.

Confidence intervals are useful because they put the point estimate in context. In general, an interval describes a range of effect values compatible with the observed data and the method’s assumptions. It does not assign a probability to each value, and it is not a guarantee that the true effect falls within the interval. The interval’s interpretation also depends on the chosen statistical method and the quality of the underlying outcome measurements.

The primary event counts, 25 of 47 and 14 of 42, come from a relatively small trial. Smaller groups commonly produce less precise estimates, though the exact precision depends on event frequencies and the method. The registry does not report the original sample-size justification or the precision target used when the trial was planned.

The secondary outcome intervals also differ in their degree of precision. The acute GVHD recalculation has a 95% confidence interval from -0.309 to -0.035; the overall survival recalculation has an interval from -0.155 to 0.249. Their point estimates and intervals are unadjusted recalculations from posted counts. The registry’s own analyses use different reported methods, particularly Log Rank for overall survival, so these recalculated intervals should not be confused with intervals from those analyses. The registry does not report confidence intervals for the sponsor’s p-value results.

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 illustrations use the observed effect as a starting point and show planning at 100% of that effect, 75% of the observed effect, and 50% of the observed effect. For the binary outcomes, the figures are participants per arm. For a time-to-event planning display, the stated convention is total events using the Schoenfeld approach. The original trial’s own design assumptions and sample-size justification are not reported in the registry record.

The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning scenario asks how many participants per arm, or how many total events for a time-to-event display, would be needed to detect the stated fraction of the observed effect. The 80% power column represents a design that would have an 80% chance of detecting an effect of the specified size if that effect were the true one and the assumptions held. The 90% power column represents a higher chance of detecting that same specified effect under those assumptions.

The planning entries become larger when the target effect is reduced from the observed effect to 75% or 50% of it. This is expected: smaller differences are harder to distinguish from random variation and generally require more information. The values are planning illustrations based on the observed effect, not observed power. Observed power is not a measure of how convincing the completed trial’s result is; the estimate and its uncertainty are more informative for that purpose.

These figures should not be read as a claim that the original trial was designed around the observed effect. They are hypothetical illustrations under the listed assumptions. They also do not account for any unreported features of the original design or analysis.

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 = 0.532; treatment proportion p₁ = 0.333; average p̄ = 0.433.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7007 = 1.3733.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6864 = 0.5777.
4. n = (1.3733 + 0.5777)² / (-0.1986)² = 96.5, rounded up to 97 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 <- 0.531914893617021                          # control proportion
p1 <- 0.333333333333333                          # 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(360685)
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 = 97 (80% power), 129 (90% power)
 75% of observed effect: n per arm = 175 (80% power), 234 (90% power)
 50% of observed effect: n per arm = 397 (80% power), 531 (90% power)
power.prop.test: 96.5 
Simulated power at n = 97 per arm: 0.811 (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

For severe mucositis, the registry reports a Fisher Exact analysis with p = 0.06. A simple unadjusted recalculation from the posted event counts gives a risk difference of -0.199, a 95% confidence interval from -0.400 to 0.003, and p = 0.059. The recalculated p-value is close to the sponsor-reported value, which is rounded to two decimal places. The registry’s discrepancy indicator is false.

The sponsor’s p-value and the recalculated risk difference serve different purposes. Fisher’s exact test reports a test result for the event-count comparison; the recalculated risk difference gives an absolute effect estimate and its uncertainty. The registry does not post a sponsor confidence interval or an adjusted effect estimate for this primary comparison. The recalculation should therefore be read as a supplementary, unadjusted description of the posted counts, not as a replacement for the registry’s reported analysis.

For the secondary outcomes, the reported tests and simple recalculations are not always aligned. Acute GVHD has a registry-reported p-value of 0.8 and a separate recalculated risk difference based on the counts. Overall survival has a registry-reported Log Rank p-value of 0.58, whereas the simple count-based recalculation uses a binary risk difference. These are not identical analytic questions. The registry does not report enough detail to reconcile all differences between the sponsor analyses and the unadjusted calculations.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies severe mucositis as the primary outcome and lists acute GVHD and overall survival as secondary outcomes. It reports three outcome measures and three analyses. The record does not describe a multiplicity adjustment, a testing hierarchy, or a plan for controlling the chance of false-positive findings across outcomes. Without such information, secondary p-values should be interpreted cautiously, particularly when several outcomes are being examined.

Multiplicity matters because evaluating multiple outcomes can increase the chance that at least one result appears unusual by chance, even when no true difference exists. General statistical practice may address this through prespecified ordering, adjusted tests, or cautious interpretation, but the registry record does not state whether any of these approaches was used. It is not appropriate to infer an unreported plan from the number of outcomes or analyses listed.

The primary endpoint is reported for the intent-to-treat population. The analysis population for the secondary outcomes is not reported in the registry record. Further details about whether all randomized participants contributed to each secondary analysis, and how participants who did not complete follow-up were handled, are also not reported.

The registry does not describe the extent or pattern of missing outcome data, the method used to handle missing observations, or any sensitivity analyses for missingness. These omissions limit assessment of whether the posted event counts represent complete follow-up for the intended population. The record also does not report details about protocol deviations or whether any participants were excluded from particular analyses.

For the primary endpoint, the grading process is described as retrospective, based on daily assessments during hospitalization and nurse and clinician assessments. The record does not say whether these assessments were masked, how missing daily assessments were treated, or whether grading disagreements were resolved through a specified process. Those details would help readers assess the reliability and completeness of the outcome measurement.

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

Serious events with the highest arm-level rate: death (53.2%).

The registry’s serious adverse event entries list 25 affected participants among 47 at risk in the tacrolimus-and-MTX group and 19 among 42 at risk in the tacrolimus-and-MMF group. These are counts of participants with serious adverse events in the posted safety record. They are not the primary efficacy endpoint and should be read separately from the severe-mucositis counts.

The registry lists Death as a top serious adverse event term at 53.2%. That entry does not provide an arm-specific count of deaths, and the death counts are not reported in the record. The term’s percentage should therefore not be interpreted as a trial death rate or as a comparison between the randomized groups.

The other adverse event count is recorded as 0 in each group. The registry does not provide further detail in this record about event definitions, duration of safety follow-up, severity grading beyond serious-event status, or the relationship of events to study treatment. These entries describe what is posted, not a complete assessment of comparative safety.

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

The primary data show fewer recorded severe-mucositis events in the tacrolimus-plus-MMF group than in the tacrolimus-plus-MTX group: 14 of 42 compared with 25 of 47. The unadjusted risk-difference estimate is -0.199, but its 95% confidence interval, from -0.400 to 0.003, includes zero. The results therefore leave uncertainty about the size and direction of the underlying difference. The registry-reported Fisher Exact p-value is 0.06.

These findings do not establish that either regimen works or does not work, and they do not determine which regimen is appropriate for an individual. The trial addresses a defined population and a particular prophylaxis comparison, with severe mucositis assessed using the registry’s stated clinical criteria. Its estimates are subject to sampling uncertainty and to the limitations of the reported methods and outcome assessment.

The secondary outcomes add context but do not settle the primary question. Acute GVHD and overall survival have different outcome definitions and analysis entries, and the acute GVHD registry test differs from a simple recalculation based on the posted counts. No multiplicity plan is reported. These features make it important not to treat any single secondary result as definitive evidence.

General statistical interpretation: a nonsignificant test does not prove that groups are equivalent, just as a negative point estimate does not prove a benefit. Establishing equivalence or non-inferiority requires an appropriate design and prespecified margins, neither of which is reported in the registry record. The confidence interval conveys the range of uncertainty for the recalculated effect, while the registry’s analysis conveys its own test result. Both should be read with the trial’s size, design, and reporting limitations in mind.

18. Why This Trial Matters Statistically

This trial illustrates why an event count, an effect estimate, a confidence interval, and a test result answer different statistical questions. The counts show what was recorded in each randomized group. The risk difference gives an absolute comparison, while its confidence interval indicates how imprecisely that difference is estimated. The Fisher Exact p-value summarizes evidence under a test but does not describe the magnitude of the possible effect.

The example also shows how the secondary analysis method affects interpretation. A binary recalculation from event counts is not interchangeable with a Log Rank analysis of survival time. Similarly, the discrepancy between the acute GVHD count-based calculation and the registry-reported analysis cannot be resolved by choosing whichever value seems more persuasive; the record does not explain the relationship between them.

Finally, the trial highlights the importance of reporting decisions that shape interpretation: the original sample-size rationale, analysis populations, missing-data handling, multiplicity plan, and outcome-assessment procedures. Some of these details are absent from the registry record. Their absence does not invalidate the posted counts, but it limits how fully readers can evaluate precision, potential bias, and the intended role of the secondary outcomes.

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 primary result is based on enrollment of 89, with 47 participants in the MTX group and 42 in the MMF group. Its confidence interval is broad and includes zero, limiting precision. The original sample-size justification is not reported, so it is not possible to determine from the registry record what effect the trial was designed to detect or what assumptions informed its planned enrollment.

The trial was open-label. The registry describes retrospective mucositis grading based on nurse and clinician assessments, but does not report whether assessors were masked, how disagreements were resolved, or how incomplete assessments were handled. These are relevant details for an outcome based on clinical grading. The record also does not report baseline characteristics or an adjusted primary analysis.

Missing-data methods and analysis populations for the secondary outcomes are not reported. The registry does not state how withdrawals, missing follow-up, or protocol deviations were handled. It also does not report a multiplicity plan. Those omissions limit confidence in interpreting secondary p-values as confirmatory findings.

The acute GVHD result has a notable difference between the recalculated unadjusted risk-difference analysis and the registry-reported p-value of 0.8. The method description is incomplete, and the registry does not reconcile the difference. Overall survival is reported with a Log Rank test, while the recalculation from posted counts is a binary comparison; these do not represent identical analyses. The record does not provide further survival-analysis details such as handling of censoring.

Safety reporting also has limits: the record lists a serious adverse event term of Death at 53.2%, but does not report death counts by group. The posted adverse-event summaries do not provide sufficient detail to compare the full safety profile of the regimens.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Tacrolimus and Mycophenolate Mofetil (MMF) in GVHD Prophylactic Regimen Compared to Tacrolimus and Methotrexate (MTX — NCT00360685.
• Registry record last updated 2013-05-03; status last verified 2013-03.
• Results first posted 2013-05-03.
• 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

NCT00360685 is a completed randomized, open-label, parallel-group trial of tacrolimus plus MTX versus tacrolimus plus MMF for GVHD prophylaxis in allogeneic HCT. Enrollment was 89. The primary endpoint was severe mucositis, defined as grade 3 or grade 4 and reported for the intent-to-treat population through 2 year.

The primary counts were 25 of 47 in the MTX group and 14 of 42 in the MMF group. The registry reports a Fisher Exact p-value of 0.06. The unadjusted recalculated risk difference is -0.199, with a 95% confidence interval from -0.400 to 0.003. The registry also lists acute GVHD and overall survival as secondary outcomes. Important details about the original sample-size rationale, missing-data handling, and multiplicity are not reported in the registry record.