Stem Cell Transplantation for Stiff Person Syndrome (SPS): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Stem Cell Transplantation for Stiff Person Syndrome (SPS) (NCT02282514), a na phase 1, phase 2 study. The primary outcome is Overall Survival.

2. Clinical Question

3. Trial Design

This was a Phase 1 and Phase 2, single-group study sponsored by Northwestern University. The registry lists enrollment as 23. Allocation is recorded as NA, and masking as none. These features mean that the design was not a masked, randomized comparison: participants were not assigned through a reported allocation process to study treatment or a control intervention. There is consequently no concurrent control group against which to distinguish effects associated with the intervention from the course of the condition, other care, or other influences.

The study began in 2014-10, and the primary completion date is 2019-08-19. Its status is terminated. The registry record does not report the reason for termination, whether the planned enrollment was reached, or how termination affected follow-up or outcome collection. The record lists the study as investigating non-myeloablative hematopoietic stem cell transplantation for SPS, with its official title also including PERM and adult-onset autoimmune anti-GAD-positive cerebellar ataxia.

The intervention description names autologous hematopoietic stem cells and several accompanying drugs. The record describes cyclophosphamide and mesna as part of conditioning and mentions rATG, but the available regimen text ends before the full description is complete. The precise treatment delivered to each participant, adherence, modifications, and timing are not reported in the registry record. Nor are detailed eligibility criteria, baseline characteristics, follow-up completeness, or the analysis population. These omissions constrain interpretation: the listed enrollment and design identify the study structure, but do not by themselves establish how many participants contributed to each endpoint or how representative the analyzed group was.

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 Overall Survival, measured over Mean 3.6 years.

The primary outcome is titled Overall Survival, but its description specifies the number of participants who did not experience treatment-related mortality. The listed timeframe is Mean 3.6 years. This wording matters: a count of participants without treatment-related mortality is not necessarily the same as a conventional all-cause overall-survival measure. The registry record does not report an operational definition of treatment-related mortality, how attribution was determined, whether the timeframe applies to each participant, or the primary outcome count.

Mortality is an important safety outcome in a study involving an intensive immune-suppressing regimen and stem cell support. A prespecified mortality endpoint can make treatment-related deaths a central outcome rather than leaving safety assessment to less direct measures. However, a meaningful estimate also depends on clear definitions, complete follow-up, and transparent reporting of the number assessed and the number experiencing the outcome. The posted record does not provide those details for the primary endpoint. Its title and description should therefore be read together, and the endpoint should not be interpreted as a reported estimate of all-cause survival or as proof of a treatment effect.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The design and outcome reporting determine what statistical conclusions can reasonably be drawn. General statistical principles help explain why the missing comparisons and endpoint details matter; they do not replace the analyses or results that are not reported in the registry record.

What does a single-group design estimate?

In a single-group study, outcome data describe the participants who received the study intervention. A count or proportion can summarize the frequency of an outcome within that group, provided the denominator and follow-up are clearly defined. Such a description is not a treatment contrast. Without a comparator group, it is not possible to separate an intervention-associated effect from changes that might have occurred because of the condition’s natural course, co-interventions, participant selection, or other differences over time.

This distinction is especially important for outcomes such as mortality, medication use, and quality of life. A change after treatment may be clinically important to investigate, but a before-and-after change alone does not establish that the intervention caused it. A comparison group can help account for time-related influences, although its usefulness depends on design and analysis. This registry record lists no concurrent comparator and no allocation process.

Why do definitions and follow-up matter?

A statistical estimate is only interpretable when the outcome is defined consistently. The primary outcome title is Overall Survival, while its description counts participants who did not experience treatment-related mortality. All-cause mortality and treatment-related mortality are different outcome concepts. The latter depends on an attribution judgment, and the registry record does not report the criteria or process used for that judgment. The listed mean timeframe of 3.6 years does not specify individual follow-up times, censoring, or how participants without complete follow-up were handled.

In general, time-to-event analysis accounts for the fact that participants may be observed for different lengths of time and that some may not experience the event during observation. It typically needs event times and censoring information, as well as a defined event. The registry record does not report those details or a time-to-event analysis. A simple count can be useful as a descriptive result, but without a clearly reported denominator and complete follow-up it cannot convey the same information as a fully specified time-to-event estimate.

How should precision be understood?

In general, a confidence interval gives a range of values compatible with the observed data under a stated statistical model and procedure. It communicates uncertainty in an estimate; it does not indicate the probability that a particular treatment effect is true. A narrow interval generally reflects greater precision than a wide interval, while the interval’s interpretation depends on the model and assumptions. No confidence interval for the primary outcome is reported in the registry record, so its precision cannot be evaluated from the posted results.

For event counts, uncertainty is influenced by the amount of information available and by how common the event is. In a single-group study, even a carefully calculated interval would describe uncertainty around that group’s event frequency, not uncertainty around a randomized treatment difference. The record does not provide an interval or a method for the serious-event figures. No interval should be inferred from the adverse-event counts alone.

What do the sample-size illustrations represent?

Any sample-size illustrations associated with the results are planning calculations, not observed trial outcomes. Their stated assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation; the target effect is a stated fraction of the observed effect. For time-to-event calculations, the stated quantity is a total number of events using the Schoenfeld method; other calculations are expressed as participants per arm. These are hypothetical design assumptions for a future comparison, not a description of this study, which is single group.

Such planning values depend on the assumed effect and statistical model. An effect estimated from a small or uncontrolled study may be imprecise, and planning around an observed effect does not make that effect a reliable forecast. The calculations are not observed power. Observed power is not a substitute for a confidence interval or a transparent account of the actual outcome data. The registry record does not report the original trial’s sample-size justification, so the illustrations should not be read as its original design plan.

Why can event data be over-dispersed?

As a general matter, a simple statistical model may assume that events occur independently and with a common underlying rate. Clinical event data can vary more than that model expects when participants differ in risk, follow-up, exposure, or susceptibility, or when events recur within the same participant. This extra variability is called over-dispersion. Ignoring it can make uncertainty appear smaller than it is. Appropriate methods may account for clustering or variation in exposure, but the choice depends on the data structure. The registry record does not report recurrent-event analyses, exposure-adjusted rates, or a model addressing over-dispersion.

These general principles clarify the limits of the posted information: a design label and event counts can orient interpretation, but they cannot supply an unreported endpoint estimate, its uncertainty, or a causal comparison.

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("Hematopoietic Stem Cell Transplantation")
n      <- c(23)
events <- c(23)
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  Hematopoietic Stem Cell Transplantation  23  23  100.0  85.2  100.0  85.7  100.0  85.8  99.9

11. Multiplicity, Missing Data and Analysis Populations

The registry lists three outcome measures and names reduction of muscle relaxation anti-spasmatic medications and SF-36 QOL as secondary outcomes. The record reports zero analyses. Results for these secondary outcomes and a statistical plan for selecting or testing outcomes are not reported in the registry record.

In general, testing several outcomes can increase the chance of at least one apparently notable finding, even when there is no true effect. Statistical plans can address this multiplicity by specifying a primary outcome, ordering tests, or adjusting inference across outcomes. The registry identifies a primary outcome, but does not report whether any adjustment, hierarchy, or other multiplicity strategy was planned. Because no analyses are reported, there is no basis to judge how multiplicity was handled or whether reported findings were selected from a broader set.

Missing-data methods and analysis populations are also not reported in the registry record. It is not stated how participants with incomplete follow-up, unavailable outcome measures, or treatment changes were handled. In general, excluding participants with missing outcomes can bias a result if missingness is related to health status or outcome; alternative methods also rely on assumptions that need to be described. The record does not identify an intention-to-treat population, a safety population, or another analysis set.

These gaps matter for both interpretation and reproducibility. Without the analysis population, missing-data approach, and prespecified testing plan, readers cannot determine whether the posted counts include all eligible participants or how complete outcome collection was. The registry record does not report these details.

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: non treatment related death (4.3%).

The adverse-event entries list 23 participants at risk for serious events and 23 at risk for other events. The corresponding affected-participant counts are 1 for serious events and 5 for other events. The record separately lists 1 death and identifies Non Treatment Related Death as a serious-event term with a reported 4.3%. These are the registry’s reported safety figures; they should not be combined into a new total or treated as a comparison between groups.

In general, serious adverse events and other adverse events are distinct reporting categories. A participant may experience events in different categories, and the record does not specify whether the affected-participant counts overlap. The available entries do not describe event timing, duration, recurrence, severity details beyond the serious classification, or the follow-up period for each safety measure. The record also does not report how the attribution of the death was determined. The percentage attached to the serious-event term is a registry entry and should not be interpreted as an exposure-adjusted rate or a comparative risk estimate without further information.

Safety counts can identify events that warrant careful description, but they do not by themselves establish causation or quantify excess risk. The single-group design provides no concurrent comparison for these counts.

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

The record supports a limited descriptive account: a Phase 1 and Phase 2, single-group, unmasked study of non-myeloablative hematopoietic stem cell transplantation for SPS and related conditions, with enrollment listed as 23 and status recorded as terminated. It also records adverse-event counts, including 1 participant with a serious adverse event and 5 with other adverse events among 23 at risk in the respective fields, plus 1 death listed as not treatment related. These observations describe what the registry reports; they do not establish that the intervention caused or prevented any outcome.

The primary outcome is labeled Overall Survival, but described as the number of participants who did not experience treatment-related mortality over a mean timeframe of 3.6 years. The primary count is not reported in the registry record. The secondary outcome results are also not reported. Therefore, the posted information does not allow readers to estimate the primary outcome, assess its precision, or determine whether medication use or quality of life changed.

A single-group study can be informative in documenting feasibility, follow-up, and events in a defined study population. It can also motivate further research. But an uncontrolled observation cannot answer what would have happened to comparable participants under another strategy. Even a favorable change, if reported, would not alone distinguish a treatment effect from other explanations. The registry record does not provide a control group, a causal estimate, or the details needed to assess adjustment for missing outcomes.

The statistical meaning is therefore bounded by the design and the reporting. The record identifies a relevant clinical question and a set of outcomes, but the available results are insufficient to determine efficacy or comparative safety. No conclusion that the intervention works or does not work follows from the information reported.

14. Why This Trial Matters Statistically

This study is statistically notable because its clinical question involves a complex intervention and an uncommon condition, while the design recorded in the registry is single group. In that setting, careful descriptions of eligibility, treatment delivery, outcome definitions, follow-up, and adverse events are particularly important. They help readers understand who was studied, what was measured, and how much confidence to place in each estimate.

The registry’s primary endpoint wording also illustrates why outcome definitions matter. Overall Survival commonly signals an all-cause mortality concept, but the description refers to avoiding treatment-related mortality. Clear operational definitions and transparent reporting of event attribution would allow readers to distinguish those outcomes and interpret follow-up consistently. The primary outcome count is not reported in the registry record, making this distinction more consequential.

More broadly, the record shows the difference between descriptive evidence and comparative evidence. Counts from a single group can document observed events, but they cannot establish how the same participants would have fared under an alternative. Statistical methods cannot recover that missing counterfactual comparison from a design that has no concurrent comparator. Planning calculations for hypothetical two-arm studies may help illustrate future study requirements, but are not observed power and are not results from this single-group trial.

Finally, the registry lists secondary outcomes relevant to medication use and quality of life, but their results and analyses are not reported. Transparent outcome reporting, including missing-data handling and analysis populations, is important not only for statistical precision but also for reproducibility. The record therefore highlights how design, endpoint definition, and complete reporting jointly determine what a clinical trial can contribute.

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 the absence of a concurrent comparator. With a single-group design, outcomes cannot be interpreted as treatment effects relative to another strategy. Masking is recorded as none, and allocation is recorded as NA. The registry does not report a statistical adjustment intended to address confounding or other time-related influences.

The primary outcome is not fully clear from its title and description: Overall Survival is titled, while the definition concerns not experiencing treatment-related mortality. The registry record does not report criteria for treatment attribution, the primary outcome count, participant-level follow-up, censoring, or the method used to analyze mortality. Although a mean timeframe of 3.6 years is listed, the record does not explain the distribution of follow-up or completeness of observation.

The study status is terminated, but the reason for termination and its consequences for enrollment, follow-up, or analysis are not reported in the registry record. Enrollment is listed as 23, but the record does not clarify the number contributing to each endpoint. Baseline characteristics, diagnostic subgroup counts, eligibility details, treatment adherence, protocol deviations, and regimen completion are also not reported. The available intervention description is incomplete.

For safety, the registry provides affected-participant counts and a serious-event term, but not event timing, duration, recurrence, exposure-adjusted rates, or the method used to assess relatedness. The secondary outcome results, confidence intervals, missing-data methods, analysis populations, and multiplicity strategy are not reported. These limitations prevent a full assessment of the size and precision of outcomes and restrict the conclusions to the design and entries documented in the registry.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Stem Cell Transplantation for Stiff Person Syndrome (SPS) — NCT02282514.
• Registry record last updated 2021-01-27; status last verified 2021-01.
• Results first posted 2021-01-06.
• 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

NCT02282514 is a Northwestern University Phase 1 and Phase 2 study titled Stem Cell Transplantation for Stiff Person Syndrome (SPS). It is listed as a single-group, unmasked study with allocation recorded as NA, enrollment of 23, and status terminated. The listed condition is Stiff-Person Syndrome; the official title also names PERM and adult-onset autoimmune anti-GAD-positive cerebellar ataxia.

The intervention includes autologous hematopoietic stem cells and listed accompanying drugs. The primary outcome is titled Overall Survival and described as the number of participants who did not experience treatment-related mortality over a mean timeframe of 3.6 years. Its result is not reported in the registry record. The record lists 1 participant with a serious adverse event, 5 with other adverse events, and 1 death; Non Treatment Related Death is listed as a serious-event term with a reported 4.3%. Secondary outcome results and statistical analyses are not reported in the registry record.