Donor Stem Cell Transplant Followed by Cyclophosphamide in Treating Patients With Hematological Diseases: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Donor Stem Cell Transplant Followed by Cyclophosphamide in Treating Patients With Hematological Diseases (NCT02248597), a na phase 2 study. The primary outcome is 12 Month Disease Free Survival Probability.

2. Clinical Question

3. Trial Design

This is a phase 2, single-group clinical study, listed as completed, with enrollment of 27. The registry lists no masking and allocation as NA; it does not describe random assignment or a concurrent control group. The study therefore provides an account of outcomes among participants receiving the treatment strategy, not a randomized estimate of the difference between that strategy and another approach.

The intervention is allogeneic hematopoietic stem cell transplantation following a preparative regimen, with graft-versus-host disease prophylaxis. Listed interventions include fludarabine phosphate, busulfan, cyclophosphamide, tacrolimus, and mycophenolate mofetil. The treatment description distinguishes myeloablative and reduced-intensity conditioning for busulfan, but the registry record does not provide a complete schedule for every intervention in the available description.

The registry lists the study start as 2015-02-25 and primary completion as 2022-01-18. These dates describe the study record and do not provide information about follow-up duration for each participant. Eligibility criteria, baseline characteristics, participant flow, and the dates of individual outcome assessments are not reported in the registry record.

Secondary outcomes named in the record are acute GvHD rate, overall survival, progression-free survival, and relapse-free mortality. Although the record lists five outcome measures, a numerical result for the primary endpoint and outcome-specific results are not reported in the registry record. No registry analysis records are listed. This design and reporting context limits interpretation to the planned question and the adverse-event summaries that are posted.

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

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 12 Month Disease Free Survival Probability, measured over At 12 months.

The primary endpoint is titled 12 Month Disease Free Survival Probability and is assessed at 12 months. Disease-free survival is generally intended to describe remaining alive without disease relapse through a specified follow-up period. In this registry description, however, the endpoint is phrased as the percentage of patients who experience death or disease relapse by one year. That wording describes the occurrence of an event, whereas the title describes a probability of remaining disease-free. The record does not clarify how this wording difference was resolved in the reported calculation.

The description states that a 95% confidence interval would be constructed using the normal approximation for binomial proportions. It also says that the survival function would be estimated and plotted using the Kaplan-Meier method. These approaches express related but distinct ways of summarizing outcomes: a binomial proportion treats the endpoint as a proportion at a specified time, while Kaplan-Meier methods use event times and can account for differing follow-up through censoring. The registry record does not explain how these descriptions were combined for the primary analysis.

The endpoint can address the study’s planned question about disease-free status at 12 months, but its numerical estimate and confidence interval are not reported in the registry record. Without those results, the degree of precision and the observed outcome cannot be assessed.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

General: proportions and confidence intervals. A proportion summarizes how many participants in a defined group experienced an event. A confidence interval expresses uncertainty around an estimated quantity using a method with a stated coverage property over repeated applications. It is not a guarantee that the true value lies in a particular interval, nor does it measure the probability that a treatment works. The registry describes a 95% confidence interval using the normal approximation for binomial proportions, but does not report the resulting estimate or interval.

The normal approximation treats uncertainty in a proportion using an approximately bell-shaped sampling distribution. As a general statistical matter, approximation quality depends on the amount of information and the event frequency. If these conditions are not suitable, an interval based on another method may behave differently. The registry record does not say whether alternative interval methods were considered, or give details of any checks on the approximation.

General: time-to-event summaries. Kaplan-Meier methods estimate the probability of remaining event-free over time from observed event times. They can incorporate participants whose follow-up ends before an event is observed by treating their event status as censored at their last known follow-up. This approach relies on assumptions about censoring and requires suitable information on event times and follow-up. The registry says a Kaplan-Meier survival function would be estimated, but does not report the estimate, its uncertainty, censoring details, or the time origin used in the analysis.

The endpoint description also refers to a binomial proportion at 12 months. A fixed-time proportion and a Kaplan-Meier estimate may both describe status at a selected time, but their calculation and interpretation depend on how follow-up and censoring are handled. The record does not specify whether the binomial calculation used only participants with known status at 12 months, how missing status was handled, or how that calculation related to the survival-function estimate. The difference between the endpoint title and the event-based wording adds further uncertainty about the precise estimand, meaning the quantity the analysis is intended to estimate.

General: event counts and adverse-event percentages. Adverse-event summaries can count participants with at least one event, the number of event episodes, or events within a preferred-term category. Those are not interchangeable. A participant can experience multiple event types, and event terms can overlap within a person. The registry lists percentages for serious-event terms but does not state whether each percentage represents participants, event episodes, or a particular analysis window. It also does not report whether categories were coded using a specific terminology or how severity and attribution were determined.

General: over-dispersion. Over-dispersion occurs when variability in the data is greater than a model assumes. For event counts, it can arise when participants differ in their underlying risk or when observations are clustered. If a model assumes less variability than is present, uncertainty estimates may be too small. This is a general consideration for count-based analyses, not a finding about this trial: the registry record does not report an over-dispersion assessment or a model for event counts.

General: single-group inference. A single-group study can estimate outcomes among participants meeting its study criteria, subject to follow-up and measurement limitations. It cannot separate treatment effects from other explanations using a randomized between-group contrast. Changes over time, participant selection, concurrent care, and underlying disease course can all affect observed outcomes. These are general limitations of causal interpretation in an uncontrolled design and do not indicate that any particular factor affected these participants.

General: planning illustrations. Sample-size planning illustrations are hypothetical calculations based on stated assumptions; they are not observed power. The stated illustration assumptions are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect set as a stated fraction of the observed effect. For time-to-event outcomes, the illustration uses a total event count; other illustrations use participants per arm. These assumptions describe hypothetical planning, not the actual single-group design. The registry record does not report the study’s own sample-size justification, targeted effect, or power calculation. Any sample-size illustration must therefore be kept separate from the trial’s observed outcomes and should not be interpreted as evidence that the study had a particular probability of detecting an effect.

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("Treatment (Stem Cell Transplant With GVHD Prophyla")
n      <- c(27)
events <- c(14)
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  Treatment (Stem Cell Transplant With GVHD Prophyla  27  14  51.9  31.9  71.3  34.0  69.3  33.9  69.4

11. Multiplicity, Missing Data and Analysis Populations

The registry lists five outcome measures and names acute GvHD rate, overall survival, progression-free survival, and relapse-free mortality as secondary outcomes. It does not report numerical results for those outcomes or a statistical analysis plan describing how they were tested. No registry analysis records are listed. The record does not state whether formal hypotheses were assigned to secondary outcomes, whether any adjustment for multiple comparisons was planned, or how results would be prioritized if several outcomes were examined.

Multiplicity is a general concern when many outcomes or analyses are considered: repeated testing can increase the chance of at least one apparently unusual result even when no single effect is present. Whether and how to address that concern depends on the scientific purpose and prespecified analysis plan. The registry record does not provide enough information to determine the intended multiplicity strategy. The listed outcome measures should therefore not be treated as a set of confirmed findings.

Missing-data methods are not reported in the registry record. In particular, the record does not specify how participants without known 12-month status were handled, whether follow-up was complete, how censoring was defined, or whether any sensitivity analyses were planned. Analysis populations are also not reported: the registry does not state which participants would be included in the primary analysis or how withdrawals and protocol deviations would be handled.

Interim analyses, stopping rules, and the study’s own sample-size justification are not reported in the registry record. Their absence from the record does not establish whether they were or were not used; it means they cannot be evaluated from the registry information. These omissions matter because they affect interpretation of uncertainty, completeness, and the relationship between planned and reported analyses.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: white blood cell count decreased (88.9%), platelet count decreased (85.2%), lymphocyte count decreased (74.1%), neutrophil count decreased (55.6%), anemia (29.6%).

The adverse-event summary lists 27 participants at risk and 27 affected for serious adverse events. It also lists 27 at risk and 27 affected for other adverse events. These are participant counts recorded for the treatment group; they do not establish that every listed event term occurred in every participant. The registry does not report the event windows, the definitions used for “affected,” or how multiple events in a participant were counted.

The most frequently listed serious-event terms include white blood cell count decreased (88.9%), platelet count decreased (85.2%), lymphocyte count decreased (74.1%), neutrophil count decreased (55.6%), anemia (29.6%), and death (11.1%). These percentages are registry summaries, not comparisons against another group. The record does not specify whether the percentages refer to participants or event episodes, and it does not give severity grades, event timing, or judgments about whether events were related to treatment. The terms may overlap and should not be added together.

The group summary separately lists 13 deaths. The record does not explain how that figure relates to the “Death” serious-event term listed at 11.1%, including whether definitions and time periods match. Neither entry alone establishes cause. Without a comparator, follow-up details, and fuller event definitions, these figures should be read as descriptive safety reporting rather than estimates of excess risk or treatment effect.

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

The registry record describes a phase 2, single-group study of donor stem cell transplantation with graft-versus-host disease prophylaxis and identifies a 12-month disease-free survival endpoint. It also provides adverse-event summaries for the treatment group. These registry entries describe the study’s design and the types of outcomes recorded, but the record does not include the numerical primary-endpoint result or its confidence interval.

As a result, the posted record cannot establish the observed probability of being alive without relapse at 12 months, or the event proportion for death or relapse as worded in the endpoint description. It also cannot show how precise either estimate would be. The distinction matters: an estimate alone gives a point summary, while its uncertainty helps readers understand how much the data constrain plausible values. Neither is reported for the primary endpoint.

The single-group design also means the study does not provide a randomized comparison with an alternative treatment or care strategy. Outcomes observed among these participants cannot by themselves show what would have happened to comparable participants under another approach. This is a design limitation, not a judgment about the clinical value of the strategy.

The safety summaries document serious-event terms and deaths recorded for the group, but do not supply the context needed to interpret causation or comparative risk. Event attribution, timing, definitions, and participant-level overlap are not reported in the registry record. The adverse-event entries should therefore be understood as descriptive reports, not proof that an intervention caused or prevented an event.

In general, a registered endpoint is a planned measure, not a result. The fact that an endpoint and analysis approach are described does not provide their numerical findings. A full interpretation would require outcome estimates, uncertainty intervals, follow-up and missing-data information, and sufficiently detailed methods. Those items are not reported in the registry record.

14. Why This Trial Matters Statistically

This trial illustrates why the distinction between a planned endpoint and a reported result is fundamental in clinical statistics. The registry identifies 12-month disease-free survival as the primary endpoint and names methods for estimating it, but does not report the estimate or its confidence interval. Readers can identify the question the study intended to address, yet cannot judge the observed outcome or its precision from the registry record.

It also highlights how endpoint wording affects interpretation. “Disease-free survival probability” suggests a probability of remaining free of death and relapse, while the endpoint description refers to the percentage experiencing those events. The record’s mention of both a binomial confidence interval and a Kaplan-Meier survival estimate leaves open how the endpoint was operationalized. Clear definitions of the estimand, event, follow-up, and handling of incomplete observation are essential for readers to understand what a result means.

The single-group design is statistically important because it shapes the claims the data can support. It can describe outcomes in the enrolled participants, but it does not supply a randomized treatment contrast. This makes careful separation of descriptive findings from causal conclusions especially important.

Finally, the adverse-event summary shows why event counts and percentages require context. The record lists participant counts and several serious-event terms, but does not report event definitions, timing, attribution, or overlap. Such details are needed to interpret the summaries without treating them as comparative or causal evidence. These issues are broadly relevant when reading registry records, particularly when key endpoint results are absent.

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 statistical interpretation is that the registry record does not report the numerical primary endpoint result, its 95% confidence interval, or results for the named secondary outcomes. Without those estimates, the magnitude and precision of outcomes cannot be evaluated. The registry lists no analysis records, so the results and implementation of the described methods cannot be checked against posted analyses.

The endpoint description is not fully aligned with its title: the title names a disease-free survival probability, while the text refers to the percentage experiencing death or relapse by one year. It also refers to both a normal-approximation interval for a binomial proportion and a Kaplan-Meier survival function without explaining how they relate. This makes the intended estimand and treatment of follow-up unclear.

The single-group design has no concurrent comparator, limiting the ability to distinguish outcomes associated with the treatment strategy from other influences. The record does not report detailed eligibility criteria, baseline characteristics, participant flow, follow-up completeness, or analysis populations. Missing-data handling, censoring rules, multiplicity plans, interim analyses, and the study’s own sample-size justification are not reported in the registry record.

Safety interpretation is also constrained. The record gives adverse-event counts and percentages but does not report event definitions, severity grades, timing, treatment attribution, or participant-level overlap. The relationship between the listed 13 deaths and the serious-event term “Death” at 11.1% is not explained. These limitations prevent a more detailed interpretation of the posted safety summaries.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Donor Stem Cell Transplant Followed by Cyclophosphamide in Treating Patients With Hematological Diseases — NCT02248597.
• Registry record last updated 2023-10-11; status last verified 2023-10.
• Results first posted 2023-10-11.
• 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.

19. Record Summary

NCT02248597 is a completed phase 2, single-group study sponsored by Wake Forest University Health Sciences. Enrollment was 27. The study start is listed as 2015-02-25, and primary completion as 2022-01-18. Masking is listed as none, and allocation as NA.

The study concerns allogeneic hematopoietic stem cell transplantation with graft-versus-host disease prophylaxis. The primary endpoint is titled 12 Month Disease Free Survival Probability. The registry names secondary outcomes of acute GvHD rate, overall survival, progression-free survival, and relapse-free mortality.

The record includes serious and other adverse-event summaries, but no numerical primary-endpoint estimate or registry analysis records. It does not report detailed analysis populations, missing-data handling, or the study’s own sample-size justification.