Safety of Post-transplant Alpha-beta Depleted T-cell Infusion Following Haploidentical Stem Cell Transplant (Haplo SCT): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Safety of Post-transplant Alpha-beta Depleted T-cell Infusion Following Haploidentical Stem Cell Transplant (Haplo SCT) (NCT02193880), a na na study. The primary outcome is Number of Participants That Experience Acute Haploidentical Alpha Beta Depleted Transplant (aGVHD).

2. Clinical Question

3. Trial Design

The registry describes a completed, single-group study with enrollment of 7 participants. The intervention is an alpha-beta depleted T-cell infusion after post-transplant cyclophosphamide in the setting of haploidentical stem cell transplant. The intervention is categorized as a device in the registry. The record lists phase as NA, allocation as NA, and masking as none.

The study purpose focuses on the safety and efficacy of the post-transplant approach, including the intended balance of reducing relapse risk without increasing graft-versus-host disease. Its primary outcome is a count of participants who experience acute aGVHD, assessed from baseline and before day +100 of transplant. The outcome description says participants would be monitored for Grade IV aGVHD and organ toxicity, using modified Keystone (Glucksberg) consensus criteria for acute assessment.

Enrollment and treatment receipt are not equivalent in this record. The primary-outcome population note says 4 participants received the actual therapy, while the other 3 did not receive the experimental therapy because enough CD34 HSCT was not collected. This distinction matters when interpreting the safety figures and the unavailable primary endpoint: the figures relate to the recorded group at risk, while the record does not provide a completed primary-outcome result or a detailed analysis population definition.

There is no randomized allocation or concurrent control group described, so the trial cannot provide a direct treatment-versus-control estimate. A protocol-level statistical plan, sample-size justification, or details of interim analyses are not reported in the registry record. The posted record lists no analyses. Although the study status is completed, completion status alone does not supply the missing endpoint result or analysis details.

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: we report data on 4 patients who received the actual therapy. The other 3 patients did not receive the experimental therapy for NOT collecting enough CD34 HSCT..

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: we report data on 4 patients who received the actual therapy. The other 3 patients did not receive the experimental therapy for NOT collecting enough T cells.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants That Experience Acute Haploidentical Alpha Beta Depleted Transplant (aGVHD), measured over From baseline and before day +100 of transplant..

The primary endpoint is the number of participants experiencing acute haploidentical alpha-beta depleted transplant graft-versus-host disease, abbreviated aGVHD. It is defined as a participant count rather than a continuous measurement. The timeframe begins at baseline and ends before day +100 of transplant. The description specifies monitoring for Grade IV aGVHD and organ toxicity and says acute assessment uses the modified Keystone (Glucksberg) consensus criteria.

Counting affected participants is a way to describe how often an event occurs in the group under observation. In a small single-group study, the count and its denominator are both important: a count without a clear denominator can be difficult to interpret, and a proportion based on few participants can be imprecise. General statistical principle: uncertainty is typically greater when an estimate rests on sparse observations, so a count should not be treated as a precise estimate of risk beyond the study group.

The endpoint is relevant to the study’s stated safety question because acute graft-versus-host disease is the event being monitored in the early post-transplant period. However, the registry record does not report the primary endpoint count. It therefore does not establish how many participants met the endpoint, and no estimate of its frequency can be read from the primary outcome entry.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry identifies the primary outcome as a count of participants who experience an event. This is a binary-outcome framework at the participant level: each person either meets the outcome definition during the stated timeframe or does not. The resulting count is meaningful only with its relevant population and observation period. Here, the timeframe is from baseline and before day +100 of transplant, and the primary-outcome population note identifies 4 participants as having received the actual therapy. The endpoint result itself is not reported in the registry record.

What does a participant count tell us?

A count describes the number of observed participants who meet a definition. General statistical principle: an event count is not, by itself, a complete description of frequency. It should be interpreted alongside the number of people observed and the rules for deciding whether an event qualifies. If a proportion is reported, its denominator must match the population that was actually assessed. This is especially important when some enrolled participants did not receive the intervention. The record distinguishes those who received the actual therapy from those who did not, but it does not provide a primary outcome count or a full analysis-population definition.

Why does a confidence interval matter?

General statistical explanation: a confidence interval describes uncertainty around an estimate under the assumptions of a statistical method. It helps distinguish an estimate that is relatively precise from one that remains compatible with a broad range of underlying values. Sparse binary data commonly yield substantial uncertainty. No confidence interval for the primary outcome is reported in the registry record, and the absent endpoint count prevents a reader from assessing the observed event frequency in the treated participants.

What can a single-group design estimate?

A single-group study can describe outcomes in the group that received the intervention, provided the outcome data and analysis population are reported. It does not by itself produce a randomized contrast with an alternative treatment or usual care. In this record, allocation is NA and the model is single group; no concurrent comparator is described. Therefore, the design does not separate the observed outcomes from other influences that might affect participants during transplant care. It cannot support a direct estimate of how outcomes would differ under a comparison strategy.

How should the planning assumptions be read?

The record states that the sample-size illustration is a planning exercise based on the observed effect, not the trial’s own design. Its assumptions are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect defined as a stated fraction of the observed effect. These are assumptions for an illustrative future-planning calculation, not evidence that the study itself used a two-arm design. The actual study is recorded as single group.

The record does not state numeric sample-size illustration results or the observed effect used for planning. It is therefore not possible to describe a particular required sample size or effect magnitude from this information. General statistical principle: planning calculations depend on assumptions about the target effect, variability or event frequency, significance level, allocation, and analysis method. Changes to those assumptions can change the calculated sample size. Such a calculation is not observed power and does not change what the trial actually observed.

Why can over-dispersion matter in other outcome settings?

General statistical explanation: over-dispersion occurs when the variability in data is greater than a statistical model assumes. If it is ignored, standard errors can be too small and uncertainty can be understated. The primary endpoint in this record is a participant count for a binary event, not a reported rate with a model for repeated or clustered counts. The registry does not report a model-based analysis, so over-dispersion is not identified as an analysis feature. The concept is relevant when considering other count-data analyses, but it should not be presumed to have been applied in this study.

What analysis details are missing?

The registry lists no analyses. A protocol-level statistical analysis plan, analysis method, confidence intervals, hypothesis tests, handling of missing observations, and interim-analysis procedures are not reported in the registry record. These omissions prevent assessment of prespecified versus exploratory analyses, model assumptions, and the treatment of incomplete follow-up. General statistical principle: transparent reporting of definitions, denominators, uncertainty, and analysis choices is necessary to evaluate how robustly an estimate answers a research question. Here, the primary outcome result and the analytic details needed to evaluate it are unavailable.

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("Alpha-beta Depleted T-cell Infusion")
n      <- c(4)
events <- c(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  Alpha-beta Depleted T-cell Infusion  4  0  0.0  0.0  60.2  0.0  49.0  0.5  52.2

11. Multiplicity, Missing Data and Analysis Populations

The registry lists 2 outcome measures and no analyses. A multiplicity strategy for interpreting multiple outcomes or tests is not reported in the registry record. Because no statistical analyses are listed, the record does not establish whether any adjustment for multiple comparisons was planned or performed. The number of outcome measures alone does not show that a particular multiplicity problem occurred; interpretation depends on which outcomes and tests were analyzed and how conclusions were selected.

Missing-data handling is also not reported in the registry record. The primary-outcome population note explains that 4 participants received the actual therapy and the other 3 did not because enough CD34 HSCT was not collected. That is a difference in treatment receipt, but the record does not describe this as missing outcome data, nor does it state how unavailable endpoint assessments were handled. Follow-up completeness and rules for classifying participants without an assessment are not reported.

The analysis population is not fully defined beyond the note distinguishing participants who received the therapy from those who did not. The primary endpoint result is not reported, and the record does not say whether an analysis was intended for all enrolled participants, only those treated, or another group. These details matter because the denominator and population determine what an event count represents. Without an outcome result, an analysis definition, or missing-data procedures, the reader cannot determine how incomplete assessment or nonreceipt of treatment affected the endpoint interpretation.

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 3% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: graft failure (not related to study) (50.0%).

The registry safety entry reports 2 participants with serious adverse events among 4 at risk and 2 participants with other adverse events among 4 at risk. It separately lists 3 deaths. The record does not specify the timing or causes of those deaths, or whether any were considered related to the study intervention. The serious and other adverse-event entries do not establish whether the same participants appear in both categories, so the counts should not be combined.

The listed top serious term is “Graft Failure (not related to study),” reported at 50.0%. The registry labels this term as not related to the study. The record does not provide a term-specific count or further information about timing or clinical context, so the percentage should be read only as reported and not expanded into an inferred count.

These safety figures are descriptive entries from a small group at risk, not a comparison with an untreated or alternative-treatment group. General statistical principle: observed adverse-event counts can describe what was recorded during observation, but they do not by themselves establish causation or comparative risk. The adverse-event timeframe and detailed ascertainment procedures are not reported in the registry record. The safety data also do not replace the missing primary aGVHD result.

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

The registry record establishes the study’s stated question and some descriptive safety information, but it does not report the primary aGVHD count. It therefore cannot show how many treated participants experienced the primary endpoint before day +100, or how precisely that event frequency could be estimated. The study’s aim to assess safety and efficacy and to reduce relapse risk without increasing graft-versus-host disease risk is a rationale, not a result.

Some safety information is reported: serious adverse events affected 2 of 4 participants at risk, other adverse events affected 2 of 4 at risk, and 3 deaths are listed. The record also lists Graft Failure (not related to study) as a serious term at 50.0%. These entries do not establish that the intervention caused the events. Timing, causes of death, and further event context are not reported in the registry record.

The design also limits what can be concluded. It is a single-group study with no concurrent comparator described. Four participants received the actual therapy, while 3 did not because enough CD34 HSCT was not collected. Without a comparison group, an observed event frequency would not by itself quantify how outcomes differ under another treatment strategy. And because the primary outcome result is absent, even a descriptive estimate for that endpoint is unavailable.

Accordingly, the posted information does not establish whether the intervention reduces relapse, changes aGVHD risk, or has a different safety profile from an alternative. It does not provide a basis for medical decisions. It supports only a limited account of the design, treatment receipt, and listed adverse events. General statistical principle: conclusions should track the data actually reported, rather than the study’s intended objectives or assumptions used for planning.

14. Why This Trial Matters Statistically

This trial is statistically instructive because its enrollment and treatment-receipt populations differ. The record reports enrollment of 7 participants, but says that 4 received the actual therapy and the other 3 did not because enough CD34 HSCT was not collected. Those populations answer different descriptive questions. Clear reporting of the group used for each endpoint is essential to interpreting a count or denominator.

The primary outcome is a binary event count in a single group, and its result is not reported in the registry record. This makes the distinction between a defined endpoint and an available estimate especially important: a detailed outcome definition does not substitute for an observed count. The endpoint timeframe and assessment criteria are stated, but the result and its precision are absent.

The safety entry also illustrates why event categories and denominators should be kept distinct. Serious and other adverse events are separately reported among 4 at risk, while deaths are listed separately. The registry does not say whether event categories overlap or provide death causes and timing. It would be inappropriate to combine these entries or infer causation.

Finally, planning assumptions should not be confused with the actual study design or findings. The record describes a planning illustration based on an observed effect and assumptions for a hypothetical two-arm calculation, while the trial itself is single group. General statistical principle: planning calculations can inform future study design, but they are not observed power and cannot fill gaps in outcome reporting. This record demonstrates why transparent results, defined analysis populations, and uncertainty estimates are central to statistical interpretation.

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.

Several limitations are specific to the available record. First, the primary endpoint count is not reported, despite a defined outcome and timeframe. The record therefore does not permit a descriptive estimate of acute aGVHD occurrence for the treated participants. No confidence interval or analysis of that endpoint is listed.

Second, enrollment and intervention receipt differ: 7 participants were enrolled, but the population note states that 4 received the actual therapy and 3 did not because enough CD34 HSCT was not collected. The registry does not explain the consequences of nonreceipt for outcome follow-up or define a complete analysis population. This limits interpretation of the denominator and any potential selection into the treated group.

Third, the single-group design has no concurrent comparator, and allocation is listed as NA. There is no randomized comparison on which to base a treatment contrast. Masking is listed as none. The record does not report a protocol-level statistical plan, sample-size justification, interim analyses, or missing-data procedures. It also lists no analyses.

Finally, the adverse-event details are limited. The record gives counts for serious and other events, a death count, and one serious term with a reported percentage, but does not report death causes or timing, detailed event context, or the relationship between event categories. The timeframe and ascertainment details for the safety entries are not reported in the registry record. These limitations restrict both descriptive interpretation and any inference beyond the recorded observations.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Safety of Post-transplant Alpha-beta Depleted T-cell Infusion Following Haploidentical Stem Cell Transplant (Haplo SCT) — NCT02193880.
• Registry record last updated 2019-04-25; status last verified 2019-04.
• Results first posted 2019-01-08.
• 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

NCT02193880 is a completed, single-group study of alpha-beta depleted T-cell infusion after post-transplant cyclophosphamide in haploidentical stem cell transplant. The registry reports enrollment of 7 participants; 4 received the actual therapy, while 3 did not because enough CD34 HSCT was not collected. Allocation is listed as NA, masking as none, and phase as NA.

The primary endpoint counts participants experiencing acute aGVHD from baseline and before day +100, with acute assessment using modified Keystone (Glucksberg) consensus criteria. The endpoint result is not reported in the registry record. Safety entries report 2 participants with serious adverse events among 4 at risk, 2 with other adverse events among 4 at risk, and 3 deaths. Graft Failure (not related to study) is listed as a serious term at 50.0%. No analyses are listed, and no concurrent comparator is described.