Use of DNA Testing to Help Transition Kidney Transplant Recipients to Belatacept-only Immunosuppression: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Use of DNA Testing to Help Transition Kidney Transplant Recipients to Belatacept-only Immunosuppression (NCT04786067), a na phase 4 study. The primary outcome is Number of Patients With Acute Kidney Graft Rejection.

2. Clinical Question

3. Trial Design

This is a Phase 4 study with a single-group model, no masking, and allocation listed as NA. The registry labels the intervention arm Immunosuppression Taper and identifies belatacept as the drug intervention. Although the record also includes observational and 3-Month Lead-In groups, it explicitly cautions that the arms are not a like-for-like control comparison. The design therefore does not support treating those groups as randomized, exchangeable arms.

The study enrolled 25 participants. The primary-endpoint description says 24 entered the treatment period after the observational lead-in. It also states that, among 12 subjects under the observational arm, one was excluded from data analysis after developing de-novo donor-specific antibodies during the lead-in. The number included in each endpoint analysis, and whether the same analysis population was used for every outcome, are not reported in the registry record.

The stated strategy involved a 3 month monitoring period, followed by sequential withdrawal for eligible patients judged immune quiescent. The available arm description ends before giving the full taper procedure. Details such as the exact monitoring schedule, taper steps, criteria for immune quiescence, and handling of participants who did not proceed to taper are not reported in the registry record.

The study began on 2021-07-28, had a primary completion date of 2025-07-10, and is listed as COMPLETED. Its objectives also included AlloMap as a predictor of immune quiescence and iBox prediction of adverse outcomes. The registry lists 8 outcome measures. It does not report a randomized allocation procedure or a formal statistical analysis for comparing the arms.

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: Eligible patients were enrolled in the study for a 3-month lead-in period to demonstrate stability and establish baseline molecular diagnostic markers. During this initial observation period, immune quiescence was assessed using the following criteria: stable renal function (eGFR no more than 20% below the value at inclusion), AlloSure ≤1%, AlloMap \< 11.5, absence of proteinuria (UPCR \<0.5 g/g), and no evidence of de novo DSA or biopsy-proven acute rejection.

Observational Lead-In

Reasons for not completing this period:

Study Treatment

Analysis population for the primary outcome, as defined in the registry: 24 subjects entered the study treatment period from the observational lead-in period. Out of the 12 subjects under the observational arm, 1 subject was excluded from data analysis due to development of de-novo DSA during the lead-in period.

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 Number of Patients With Acute Kidney Graft Rejection, measured over 12 months after the date of the first immunosuppression taper.

The primary endpoint is the number of patients with acute kidney graft rejection confirmed by biopsy according to 2017 Banff Criteria. Its stated timeframe is 12 months after the date of the first immunosuppression taper. The registry describes the measure as a count of participants and characterizes the endpoint as the incidence of biopsy-proven acute kidney graft rejection over that timeframe.

A biopsy-confirmed event makes the endpoint more specific than a measure based only on symptoms or an unspecific change in kidney function: the event definition requires biopsy confirmation and a named set of criteria. As a count, it describes how many participants met the event definition; it does not by itself show when events occurred within follow-up, how severe they were, or whether a change in a laboratory measure preceded them. Those details are not reported in the registry record.

In general, a clinically defined endpoint is useful when it connects the study question to an event of direct relevance to the transplanted organ. Here, the endpoint is aligned with the stated question of monitoring rejection during immunosuppression de-escalation. However, the registry record does not report the number of participants who experienced rejection, an estimate of uncertainty, or a statistical test for this endpoint. The endpoint definition is available, but the observed primary result and its precision are not reported in the registry record.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

What kind of outcome is the primary endpoint?

The primary endpoint is a participant-level event count: it concerns how many participants experienced biopsy-confirmed acute kidney graft rejection during the stated follow-up. In general, a binary outcome records whether each participant did or did not meet a defined event criterion. Counts can then describe the number of participants who met that criterion, but interpretation depends on knowing the analysis population and the number with the event. The registry provides the endpoint definition and a population description, but not the primary event count or a result estimate.

What can a confidence interval tell a reader?

In general, a confidence interval describes uncertainty around an estimated quantity. A narrower interval indicates greater precision under the method used; a wider interval indicates more uncertainty. For a participant event outcome, an interval around an event proportion can help show how compatible the data are with different underlying event frequencies. No primary-endpoint confidence interval is reported in the registry record, so precision for the rejection result cannot be assessed.

Why does the design matter for comparison?

This study is listed as single-group, with allocation NA and no masking. The record also contains observational and lead-in groups, but explicitly warns that the arms are not a like-for-like control comparison. In general, a comparison between groups is most interpretable when the groups are formed in a way that makes them comparable with respect to factors that can affect outcomes. When that condition is not established, observed differences may reflect group composition, timing, or other factors, as well as any intervention. The registry does not report a randomized comparison or an adjusted analysis that addresses such differences.

The study description states that eligible participants judged immune quiescent after a 3 month monitoring period would undergo sequential immunosuppression withdrawal. This selection process is central to interpreting results: findings among those who proceed through monitoring and taper may not describe all kidney transplant recipients. The record does not report the full eligibility rules, how immune quiescence was operationalized, or how outcomes among participants who did not proceed were handled.

Why might over-dispersion matter?

In general, over-dispersion occurs when observed variation in count data is greater than a statistical model expects. If present, methods that assume less variation can give uncertainty estimates that are too small. This is a general statistical consideration for some count outcomes; the primary endpoint is a participant event count, and the registry does not report a model or an over-dispersion assessment. There is therefore no basis for saying that over-dispersion was present or that a particular model was used.

What does the sample-size illustration represent?

The record describes a planning illustration based on the observed effect, with a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. It says the effect to detect is a stated fraction of the observed effect. Such an illustration is not the trial’s design justification: the sample-size assumptions are explicitly described as not being the trial’s own design. In general, a sample-size calculation estimates how many participants would be needed under specified assumptions; it does not measure the probability that a completed study has found a true effect. Any planning figures are illustrations, never observed power.

The record does not report the study’s own sample-size justification, a prespecified statistical analysis plan, interim analyses, or a primary-endpoint hypothesis test. It lists zero analyses. Thus, statistical methods beyond the stated endpoint and planning assumptions are not reported in the registry record. A reader should distinguish those missing inferential details from the descriptive counts that are posted for adverse events.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("Experimental: Immunosuppression Taper", "Observational")
n      <- c(12, 11)
events <- c(0, 0)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Experimental: Immunosuppression Taper  12  0  0.0  0.0  26.5  0.0  24.2  0.2  24.7
ARM  Observational  11  0  0.0  0.0  28.5  -0.0  25.9  0.2  26.5

11. Multiplicity, Missing Data and Analysis Populations

The registry lists 8 outcome measures, including the primary rejection endpoint and secondary outcomes concerning death, kidney graft failure, change in estimated glomerular filtration rate, proteinuria, de-novo donor-specific antibodies, AlloMap level, and iBox prediction score. Considering several outcomes can raise a multiplicity issue: in general, the more statistical tests conducted, the greater the chance of at least one apparently notable result arising by chance. Whether and how to address that issue depends on the prespecified analysis plan and the intended interpretation of each outcome.

A multiplicity adjustment or hierarchy among endpoints is not reported in the registry record. Neither are reported p-values or endpoint-specific estimates for the primary and secondary outcomes. The record does not establish whether every listed outcome was tested, which outcomes were designated for formal inference, or whether any subgroup or repeated-measure analyses were planned. No adjustment strategy should be assumed.

Information about missing data is also limited. The primary-endpoint population description states that 24 subjects entered the treatment period and that one observational-arm subject was excluded from data analysis after developing de-novo donor-specific antibodies during the lead-in. The record does not report reasons for other missing observations, the number with complete follow-up for each outcome, or any method used to handle missing data.

Analysis populations are not fully described. The registry does not report whether the primary analysis followed an intention-to-treat, per-protocol, or other defined population, nor whether participants were analyzed according to the group in which they began. These omissions matter because the population included in an estimate affects what that estimate describes. The number of participants enrolled or entering a treatment period should not be treated as the denominator for every outcome without endpoint-specific information.

12. 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

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: uti (8.3%), acute/subacute right thalamic infarct (8.3%), e. coli bacteremia (8.3%), fever (8.3%), uncontrolled hypertension (8.3%).

The registry reports serious adverse events and other adverse events by group, with separate numbers at risk and affected. In the Immunosuppression Taper group, 12 were at risk for each category; 2 were affected by serious adverse events and 5 by other adverse events. In the Observational group, 12 were at risk for each category; 4 and 6 were affected, respectively. In the 3-Month Lead-In group, 25 were at risk for each category; 1 was affected by a serious adverse event and 0 by other adverse events. Deaths are recorded as 0 in each group.

The serious adverse-event terms listed are UTI, Acute/Subacute Right Thalamic Infarct, E. coli bacteremia, Fever, Uncontrolled Hypertension, and Occluded ulnar artery; each is reported at 8.3%. These are descriptive registry entries. The record does not clarify whether the terms refer to distinct participants, whether participants could have multiple events, or how each term maps to the group-level affected counts.

In general, adverse-event counts alone do not establish causation. The registry also cautions that the arms are not a like-for-like control comparison, so differences in these descriptive counts should not be read as an estimate of an intervention effect. Further detail about event timing and individual-level overlap is not reported in the registry record.

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

The record describes a clinical question about monitoring kidney transplant recipients during a possible transition to belatacept monotherapy. It defines the primary outcome as biopsy-confirmed acute kidney graft rejection at 12 months after the first immunosuppression taper and describes donor-derived cell-free DNA and gene expression as markers used in the study’s strategy. It also gives descriptive adverse-event counts for the named groups.

Those details do not establish whether the marker-guided approach achieved its objective. The primary rejection count, estimate, uncertainty interval, and inferential result are not reported in the registry record. Results for the secondary objectives involving AlloMap, iBox, kidney graft failure, kidney function, proteinuria, de-novo donor-specific antibodies, and death are likewise not reported in the available record. A study objective should not be mistaken for a demonstrated predictive performance or clinical outcome.

The listed groups do not provide a randomized control comparison. Allocation is NA, the study model is single-group, and the registry warns that the arms are not a like-for-like control comparison. Consequently, differences in descriptive adverse-event counts cannot isolate the effect of tapering or belatacept monotherapy. Group composition and the study’s monitoring and selection process may also shape what is observed.

In general, a result applies most directly to the participants and procedures actually studied. Here, the record indicates that eligibility for sequential withdrawal depended on being deemed immune quiescent after monitoring, but it does not provide the full criteria or taper details. The registry therefore does not establish how findings would extend to patients who did not meet those criteria or to settings with different procedures.

The appropriate reading is limited: the registry records a completed study, a defined primary endpoint, stated objectives, and adverse-event counts. It does not report the primary efficacy result or enough inferential information to determine its magnitude or precision. These omissions prevent a conclusion about the primary study question from the record alone.

14. Why This Trial Matters Statistically

This study is statistically interesting because it connects a biomarker-guided decision process with a clinically defined outcome. The intended strategy used donor-derived cell-free DNA and gene expression as markers of immune quiescence while considering a reduction in immunosuppressive therapy. The primary endpoint—biopsy-confirmed acute kidney graft rejection—provides a concrete outcome against which the strategy was meant to be assessed.

The design also illustrates why the distinction between a study objective and an estimate matters. A registry may describe an intended evaluation of whether a marker can guide treatment changes, yet the interpretation depends on reported outcome counts, denominators, uncertainty, and analysis methods. The primary result and its precision are not reported in the registry record, so the central statistical question remains unanswered by the available information.

Another important issue is the role of selection. The description says eligible patients judged immune quiescent after a 3 month monitoring period would undergo sequential withdrawal. In general, results among a selected group may not apply to people who would not pass that selection process. A clear account of eligibility, participant flow, and analysis populations is therefore essential when interpreting biomarker-guided strategies.

Finally, the listed observational and lead-in groups may appear to invite direct comparisons, but the registry explicitly cautions that they are not like-for-like controls. This is a useful reminder that numerical contrasts do not automatically constitute controlled treatment effects. Design, allocation, population definitions, and analysis must support the intended comparison. The record’s limits are as important statistically as the outcomes it names.

15. 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 main limitation for interpretation is that the registry record does not report the primary rejection count, an effect estimate, a confidence interval, or a p-value. The primary endpoint is defined, but its observed result and precision are unavailable. This prevents a quantitative assessment of the central study question.

The design is listed as single-group, allocation is NA, and the registry says the arms are not a like-for-like control comparison. The observational and lead-in groups therefore cannot be assumed to provide an unbiased counterfactual for the Immunosuppression Taper group. No randomized comparison or adjusted comparative analysis is reported.

The study description gives only part of the taper procedure. The complete arm description, detailed eligibility criteria, operational definition of immune quiescence, and handling of participants who did not proceed to taper are not reported in the registry record. This limits assessment of how the intervention was implemented and which population the results would represent.

The primary population description reports that 24 subjects entered the treatment period and that one observational-arm subject was excluded after developing de-novo donor-specific antibodies during the lead-in. The record does not explain the full analysis-population rules or provide endpoint-specific denominators and missing-data methods. It also does not report a multiplicity strategy, interim analyses, or a prespecified statistical analysis plan.

Safety information is presented as aggregate counts and listed terms. Timing, individual overlap among events, and detailed attribution are not reported. Because the groups are not comparable controls, their adverse-event counts should remain descriptive rather than being interpreted as comparative treatment effects.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Use of DNA Testing to Help Transition Kidney Transplant Recipients to Belatacept-only Immunosuppression — NCT04786067.
• Registry record last updated 2026-08-14; status last verified 2025-02.
• Results first posted 2026-08-14.
• 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.

19. Record Summary

NCT04786067 is a completed Phase 4 study sponsored by University of Texas Southwestern Medical Center. It is listed as a single-group, unmasked study with allocation NA and enrollment of 25 participants. The intervention is belatacept, and the study concerns using donor-derived cell-free DNA to help transition kidney transplant recipients toward belatacept-only immunosuppression.

The primary endpoint is the number of patients with biopsy-confirmed acute kidney graft rejection using 2017 Banff Criteria, assessed at 12 months after the first immunosuppression taper. The registry states that 24 subjects entered the treatment period and describes one observational-arm exclusion during the lead-in. It lists 8 outcome measures and reports adverse-event counts by group, but the primary-endpoint result and its statistical precision are not reported in the registry record.