A Pilot Study Comparing the Use of Low-target Versus Conventional Target Advagraf: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Pilot Study Comparing the Use of Low-target Versus Conventional Target Advagraf (NCT01265537), a randomized na study. The primary outcome is Number of Participants With New Onset Diabetes After Transplant (NODAT) or Acute Rejection.

2. Clinical Question

The registry describes a prospective, randomized, open-label, parallel-group pilot study. The comparison concerns two treatment combinations: tacrolimus target and induction therapy both differ between the groups. Consequently, a difference between groups would not isolate the effect of tacrolimus target alone or induction therapy alone.

The clinical rationale recorded for the study is that the drug combination offering the best outcomes with the fewest side effects was not known. The study aimed to assess whether a new combination of drugs already approved for kidney transplantation could be used safely and might have fewer side effects than combinations used at St. Paul's Hospital and other transplant centres. Those aims describe the motivation, not a finding that the combination was safe, safer, or more effective.

The primary endpoint combines two distinct outcomes: biopsy-proven acute rejection and new onset diabetes after transplant. A participant could meet the composite through either component. The posted primary result does not separate how many participants had rejection, diabetes, or both, so the comparison is limited to the combined endpoint.

3. Trial Design

This was a randomized, open-label, parallel-group pilot study. The registry lists the phase as NA, enrollment as 30, and status as completed. The sponsor was the University of British Columbia. The study began on 2011-06-24, and the primary completion date was 2019-02-21. The registry record does not report the method used to generate the random allocation sequence or the allocation concealment process.

The study compared low-target and standard-target Advagraf, both of which are tacrolimus regimens. In the low-target group, induction was rabbit antithymocyte globulin, described as 3 -4 doses of 1.5 mg/kg during the first post transplant week, with IV solumedrol and mycophenolate mofetil or mycophenolate sodium. The standard-target group received basiliximab induction, described as 40 mg total, with IV solumedrol and one of the same mycophenolate options. The registry calls the approach a steroid-avoidance immunosuppressive protocol while also listing IV solumedrol in both arm descriptions; further details on this terminology are not reported in the registry record.

Masking was listed as none. Participants and clinical teams therefore were not described as masked to the assigned group. Whether outcome assessors or those conducting analyses were masked is not reported in the registry record. The primary endpoint timeframe was 6 months post transplant. The registry also lists secondary outcomes covering deaths, graft failure, dialysis, infections, hospitalizations, malignancy, cardiovascular events, and leukopenia. The registry record does not report a sample-size justification, the planned recruitment target beyond the enrollment entry, or detailed procedures for follow-up and outcome assessment.

The primary endpoint data cover 28 participants, 14 in each group, despite an overall enrollment of 30. The registry explicitly notes that this difference arises because 28 participants had outcome measure data available. Reasons the other participants did not contribute primary outcome data 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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The discrepancy in the overall number of participants with outcome measure data and the overall number of participants in the participant flow module is seen because 28 participants in total have outcome measure data available.

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: The discrepancy in the Baseline Analysis Population Description and the Overall Number of Baseline Participants is seen because 28 participants in total completed their baseline assessments.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With New Onset Diabetes After Transplant (NODAT) or Acute Rejection, measured over 6 months post transplant.

The primary endpoint was the number of participants with new onset diabetes after transplant (NODAT) or acute rejection at 6 months post transplant. It is a composite endpoint: the event is counted when a participant has biopsy-proven acute rejection, NODAT, or both. The registry defines NODAT using glucose criteria: fasting plasma glucose above 7.0 mmol/L, symptoms of hyperglycemia with random plasma glucose above 11.1, or a 2-hour plasma glucose above 11.1 during an oral glucose tolerance test. These thresholds are part of the registry’s outcome definition, not findings from the trial.

A composite can capture more than one clinically relevant event within a single outcome measure. That can make a study outcome more inclusive, but it also means the combined result may conceal different patterns in its components. The same number of composite events in two groups does not establish that the numbers of rejection events and diabetes events were separately equal. Component-specific counts for this primary endpoint are not reported in the registry record.

The posted result records 2 participants with the composite outcome in each group, among 14 participants per group with primary outcome data. This answers the registry’s primary comparison as a count of participants meeting either component, not as a measure of event severity, duration, or time to event. The registry does not report the component-specific results or a separate analysis of recurrent events.

7. Results Posted in the Registry

• Low Target Tacrolimus (Advagraf): 14.3% (2/14) versus 14.3% (2/14) on control; risk difference 0.0 percentage points (95% CI -25.9 to 25.9), risk ratio 1.00 (0.16–6.14); unadjusted two-proportion z-test p = 1.000.

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.

Number of Participants With Dialysis Events

• 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:
  • Low Target Tacrolimus (Advagraf): 7.1% (1/14) versus 21.4% (3/14) on control; risk difference -14.3 percentage points (95% CI -39.7 to 11.1), risk ratio 0.33 (0.04–2.83); unadjusted two-proportion z-test p = 0.280.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Low Target Tacrolimus (Advagraf) and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants With Infection Events

• 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:
  • Low Target Tacrolimus (Advagraf): 35.7% (5/14) versus 35.7% (5/14) on control; risk difference 0.0 percentage points (95% CI -35.5 to 35.5), risk ratio 1.00 (0.37–2.70); unadjusted two-proportion z-test p = 1.000.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Low Target Tacrolimus (Advagraf) and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants With Hospitalization Events

• 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:
  • Low Target Tacrolimus (Advagraf): 0.0% (0/14) versus 28.6% (4/14) on control; risk difference -28.6 percentage points (95% CI -52.2 to -4.9); unadjusted two-proportion z-test p = 0.031.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Low Target Tacrolimus (Advagraf) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes offer a broader but still incomplete picture of events reported during 6 months post transplant. Among the secondary comparisons with numerical results, the event counts do not move uniformly in one direction: the dialysis and hospitalization counts are lower in the low-target group, while infection counts are equal. The registry names other secondary outcomes, including death, graft failure, malignancy, cardiovascular events, and leukopenia, but numerical results for most of those outcomes are not reported in the registry record.

These secondary patterns do not change the primary result, which is an equal count for the composite of NODAT or acute rejection. They also do not resolve the uncertainty around that primary comparison. Secondary outcomes address different events and may have different frequencies, definitions, and clinical importance. A result for one secondary measure cannot be substituted for the composite primary outcome, and the primary composite does not establish the effect on each secondary measure.

The hospitalization comparison has an unadjusted p-value of 0.031, while the dialysis comparison has an unadjusted p-value of 0.28 and the infection comparison has an unadjusted p-value of 1.0. These results are not adjusted for testing multiple outcomes according to information in the registry record. With a collection of secondary measures, chance alone can produce a nominally notable result. The analysis plan and multiplicity approach are not reported in the registry record, which limits how strongly the isolated hospitalization finding can be interpreted.

For that reason, secondary outcomes are best read as exploratory context. They can identify patterns that may merit attention in further research, but these data do not establish a definitive difference across the broader range of outcomes. A prespecified analysis plan, complete reporting across outcomes, and adequately precise estimates would be needed to weigh such patterns more firmly. The registry does not report a confirmatory secondary analysis.

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

• Number of Participant Deaths
• Number of Participants With Graft Failure
• Number of Participants With Dialysis Events
• Number of Participants With Infection Events
• Number of Participants With Hospitalization Events
• Number of Participants With Malignancy Events
• Number of Participants With Cardiovascular Event
• Number of Any Leukopenia Events

9. Statistical Interpretation

10. Statistical Methods Explained

What is being compared?

The primary result is a comparison of binary participant-level outcomes: each participant either met the composite endpoint during the stated timeframe or did not. The registry reports counts rather than continuous measurements. The primary comparison uses 14 participants in each group and records 2 participants with the endpoint in each group.

A risk difference expresses the difference between the event proportions in two groups. Its sign depends on the order of groups used in the comparison. In this analysis, the reported primary risk difference is 0.0 because the observed counts and group sizes are the same. A risk difference of zero in the observed data is not proof that the underlying risks are equal; the confidence interval represents the uncertainty around that estimate.

How should the p-value be read?

The reported primary p-value is unadjusted. In general, a p-value measures how unusual data at least as discrepant as those observed would be under a specified null model, subject to the assumptions of the test. It does not measure the size or clinical importance of an effect, and it is not the probability that the null hypothesis is true. The registry record does not report the precise test used for the primary comparison, so the test-specific assumptions cannot be assessed from the posted record.

For secondary outcomes, unadjusted p-values are also reported for the listed comparisons. When many outcomes are examined, some apparently notable results can occur by chance even if no underlying differences exist. That is why an unadjusted result for one secondary outcome should be interpreted in the context of all outcomes considered and any prespecified multiplicity strategy. A multiplicity strategy is not reported in the registry record.

What does the confidence interval add?

A confidence interval gives a range of effect values that are compatible with the data and the method used to calculate the interval. For a risk difference, an interval that crosses zero includes the possibility of no difference and also permits effects in either direction. The primary confidence interval spans both directions. Its width is important: the equal event counts give a point estimate at zero, but the interval indicates that this estimate is imprecise.

Intervals for sparse binary outcomes can be especially wide because a small number of observed events provides limited information. In general, the interval describes sampling uncertainty under a statistical model; it does not account automatically for bias, missing outcome data, or differences in how outcomes were assessed. The method used to calculate the posted intervals is not reported in the registry record.

How should the secondary comparisons be understood?

The secondary outcomes are counts of participants with events, not necessarily counts of all event episodes. For example, a participant with more than one infection is still represented in a measure titled as the number of participants with infection events unless the outcome definition states otherwise. The detailed rules for counting repeated events are not reported in the registry record.

The registry lists a sample-size planning illustration for the dialysis comparison. It assumes a two-sided significance level of 0.05, equal allocation, and a normal approximation, using the observed effect or a stated fraction of it. The illustration gives participants per arm for 80% and 90% power: for planning for 100% of the observed effect, 93 and 124; for 75% of the observed effect, 184 and 245; and for 50% of the observed effect, 451 and 603. These are planning illustrations based on the observed effect, not the trial’s own design justification and not observed power. The registry record does not report a formal design sample-size calculation for this study.

In general, a planning calculation asks how many participants might be needed under specified assumptions to detect a chosen effect with a chosen power. It does not reveal the probability that the completed study has established an effect, and it cannot repair the uncertainty in a small observed dataset. The assumptions and observed effect used for the illustration may not represent the effect that would be expected in a future study.

What analysis details are absent?

The registry lists no reported analyses in the outcome entries. It does not report a full statistical analysis plan, adjustment covariates, handling of missing data, analysis population definitions, or interim analyses. It also does not report whether the primary comparison was prespecified in a protocol or whether the statistical methods changed during the study. Those details cannot be inferred from the reported counts or p-values.

In general, randomization can help balance participant characteristics across groups, but in a small trial chance imbalances can remain. Open-label treatment assignment can also matter when outcome assessment includes judgment or when knowledge of treatment affects care or follow-up. Biopsy-proven rejection is defined with an objective procedure in the endpoint description, but the record does not describe who assessed outcomes or whether assessment was masked. These are considerations for interpreting the design, not evidence that bias occurred.

11. Confidence Intervals and Precision

The primary estimate is centered on no observed risk difference: both groups had 2 participants with the composite outcome among 14 with outcome data. Its confidence interval extends in both directions, so the data do not precisely distinguish a reduction from an increase in the composite outcome. The reported interval is wide relative to the zero point estimate. In practical terms, equal event counts in this sample are compatible with a range of underlying group differences.

Precision is constrained by the small number of participants and events. With only 14 outcome records per group and 2 observed events in each group, a change in a small number of participants’ outcomes could materially alter the estimated comparison. This is a general feature of sparse binary data. It does not mean that the observed counts are incorrect; it means that they carry limited information about the range of possible underlying effects.

The primary confidence interval is more informative about uncertainty than the p-value alone. The p-value of 1.0 reflects the equal observed counts in the unadjusted comparison, whereas the interval makes clear that meaningful differences in either direction remain compatible with the data. Neither measure establishes equivalence. A formal equivalence conclusion would require an appropriate design and a prespecified equivalence margin, neither of which is reported in the registry record.

Other endpoints also have limited precision. For instance, some secondary comparisons involve few events, and the observed counts are therefore not a stable basis for drawing strong conclusions about uncommon outcomes. The registry record does not report adjusted estimates or additional analyses that might address the uncertainty. The number of participants with missing primary outcome data relative to enrollment is stated, but reasons and outcomes for those participants are not reported in the registry record. The possible effect of missing outcome information on the estimates cannot therefore be assessed.

12. Multiplicity, Missing Data and Analysis Populations

The registry lists 12 outcome measures in total and states that 11 secondary outcomes were posted. Considering many endpoints creates a multiplicity issue: the more separate comparisons examined, the greater the opportunity for at least one result to appear notable by chance. This matters when interpreting the unadjusted hospitalization p-value. The registry record does not report a multiplicity adjustment, a hierarchy for testing outcomes, or a plan designating which secondary findings would be confirmatory.

The record states that primary outcome data were available for 28 participants, although overall enrollment was 30. Each treatment group had 14 participants contributing to the primary outcome. The reason the remaining enrolled participants do not appear in the primary outcome data is not reported in the registry record. The record also does not describe imputation, sensitivity analyses, or other procedures for handling missing outcome data. It is therefore not possible to determine from the posted results whether missingness could have affected the comparison.

The analysis populations are not reported in the registry record. In particular, it is not stated whether the reported comparisons followed an intention-to-treat approach, whether participants were analyzed according to treatment received, or how deviations from assigned treatment were handled. These distinctions can affect interpretation in a randomized trial, especially when outcome data are incomplete.

The registry record does not report interim analyses, stopping rules, or a detailed analysis plan. It also does not report whether the outcome definitions, timeframes, or analysis methods were changed after the study began. Their absence from the record does not establish that such procedures did or did not occur; it means the posted information does not permit those features to be evaluated. Overall, the missing details limit assessment of both the risk of selective emphasis among multiple outcomes and the impact of incomplete outcome data.

13. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

Most frequent serious adverse event terms

Serious events with the highest arm-level rate: infections (35.7%), dialysis (14.3%), acute rejection (14.3%), malignancy (7.1%).

The registry reports serious adverse events for 14 participants considered at risk in each group. Seven participants in each group were reported as affected by a serious adverse event. No deaths were reported in either group. The listed serious-event terms included infections at 35.7%, dialysis at 14.3%, acute rejection at 14.3%, and malignancy at 7.1%. The registry also reports zero participants with other adverse events in both groups, among 14 at risk in each group.

These figures describe recorded events and should not be read as proof that the treatment combinations caused or prevented them. The registry record does not report the detailed event-level timing, severity breakdown, attribution to treatment, or whether people could contribute to more than one serious-event term. The percentages should therefore be understood as posted event-term figures, not as a complete comparison of every aspect of safety.

The absence of reported deaths and other adverse events in this small sample does not establish that such events cannot occur. The results concern the participants and follow-up reported in the registry. They do not provide a precise estimate of rare risks or longer-term safety.

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

The primary data show equal observed counts for the composite outcome in the two groups at 6 months post transplant: 2 participants in each group, with 14 participants per group contributing data. The estimated risk difference is 0.0, and the unadjusted p-value is 1.0. This is a description of the observed sample, not evidence that the regimens have identical effects or that a difference is absent in the wider population.

The uncertainty is central to interpretation. The primary confidence interval includes possibilities in both directions, so the study does not rule out a potentially meaningful benefit or harm for either treatment combination. Because component-specific counts are not reported, the equal composite totals also do not establish that acute rejection and NODAT separately occurred at equal rates. The result cannot answer whether one component offset a different pattern in the other.

The intervention comparison changes both tacrolimus target and induction regimen. Therefore, even if a group difference had been observed, this design would not attribute that difference to tacrolimus target alone or induction therapy alone. The record also describes a pilot study and reports a small enrollment. The statistical uncertainty is consequently substantial, and the posted results should not be treated as a definitive evaluation of the treatment combinations.

The secondary results provide additional observations, but they do not resolve the primary uncertainty. The hospitalization result is unadjusted and occurs among multiple secondary outcomes; it should not be treated as conclusive evidence of a group difference. Likewise, equal infection counts and no reported deaths do not establish equivalence or rule out safety concerns. Outcomes not numerically reported cannot be judged from the available record.

In sum, the registry record supports a narrow conclusion: among participants with primary outcome data, equal numbers in the two randomized groups met the combined endpoint by the stated timeframe. It does not establish equivalence, identify which component drove the composite, isolate the effect of any single treatment component, or determine longer-term outcomes.

15. Why This Trial Matters Statistically

This trial is statistically informative as an example of the difference between an observed estimate and the certainty of that estimate. The primary point estimate is exactly at zero because each group had the same number of recorded composite events. Yet the confidence interval remains wide, showing that a small study can produce a simple-looking estimate while leaving a broad range of effects plausible. The p-value alone would not convey that degree of uncertainty.

The study also illustrates why outcome definitions matter. A composite of acute rejection and NODAT creates one primary comparison from two distinct events. The overall count is useful for the stated combined question, but it cannot reveal whether the components followed the same pattern. Component-level reporting is important when a composite contains outcomes with different meanings or mechanisms.

Another statistical issue is the difference between a pilot study and a confirmatory trial. The registry’s planning illustration is based on an observed secondary effect and stated assumptions. It is not the study’s design justification, and it does not show that the completed study had adequate precision. Planning calculations are most useful when their assumptions, target effect, and role in the design are clear. Those details are not reported as a formal sample-size justification in the registry record.

Finally, the comparison involves treatment packages rather than a single isolated change: tacrolimus target and induction therapy differ together. The randomized comparison can describe the contrast between those packages, but it cannot separate their individual contributions. This distinction between the treatment question and the causal effect identifiable from the design is essential when translating trial results into statistical conclusions.

16. Limitations

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

Several limitations specific to this study constrain interpretation. First, the primary outcome data cover 28 of the 30 enrolled participants. The registry explains that 28 participants had outcome measure data, but the reasons for the other participants’ absence from the outcome dataset are not reported in the registry record. No missing-data method or sensitivity analysis is described.

Second, the number of participants and observed primary events is small. The resulting confidence interval is broad, and sparse event counts limit precision for both the primary and secondary comparisons. The sample-size planning illustration concerns the dialysis comparison and is based on the observed effect; it is not a documented prospective design calculation for the trial.

Third, the primary composite combines acute rejection and NODAT, but the registry does not give separate component counts. It is therefore impossible to assess whether the combined result masks different component-level patterns. The registry also does not report the precise statistical test used for the primary comparison, the method used to construct confidence intervals, or the full statistical analysis plan.

Fourth, the trial is open-label, and masking was listed as none. The record does not state whether outcome assessors or analysts were masked. The two groups also differ in both tacrolimus target and induction therapy, so the study cannot identify the independent contribution of either treatment feature. The registry record does not report random sequence generation or allocation concealment details.

Finally, the secondary outcomes involve multiple comparisons, and the registry does not report an adjustment strategy. Several secondary outcomes are listed without numerical results. Follow-up timing for the primary and described secondary outcomes is 6 months post transplant, so longer-term effects are not characterized by these results.

17. Related Tutorials

18. Related Statistical Calculators

19. Sources

• ClinicalTrials.gov: A Pilot Study Comparing the Use of Low-target Versus Conventional Target Advagraf — NCT01265537.
• Registry record last updated 2025-01-23; status last verified 2025-01.
• Results first posted 2020-02-11.
• 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.

20. Record Summary

NCT01265537 was a completed randomized, open-label, parallel-group pilot study sponsored by the University of British Columbia. It compared low-target Advagraf with rabbit antithymocyte globulin induction against standard-target Advagraf with basiliximab induction in de novo renal transplant recipients. Enrollment was 30.

The primary outcome was the number of participants with NODAT or acute rejection at 6 months post transplant. Outcome data were available for 28 participants, 14 in each group; 2 participants in each group met the composite outcome. The reported risk difference was 0.0, with an unadjusted p-value of 1.0. The confidence interval was wide and included effects in either direction.

Secondary results included numerical comparisons for dialysis, infection, and hospitalization. The registry also lists other secondary outcomes, but numerical results for most are not reported in the registry record. The record does not report a full statistical analysis plan, a multiplicity strategy, or the reasons for the difference between enrollment and primary outcome data.