Autologous Stem Cell and Hyperbaric Oxygen Therapy in Type 2 Diabetes Mellitus: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Autologous Stem Cell and Hyperbaric Oxygen Therapy in Type 2 Diabetes Mellitus (NCT01786707), a randomized phase 1, phase 2 study. The primary outcome is Number of Participants With a Reduction of HbA1c of >0.5%.

2. Clinical Question

3. Trial Design

The registry identifies this as a randomized, parallel-group study with no masking. It lists both phase 1 and phase 2. The brief summary describes a prospective, open-labeled randomized controlled trial comparing standard medical treatment plus hyperbaric oxygen therapy and intrapancreatic stem-cell infusion against standard medical treatment alone. The arm descriptions identify the intervention as autologous stem cells and hyperbaric oxygen therapy, and the control as continued insulin and metformin.

According to the summary, participants received standard medical treatment with insulin and metformin for a 4-month evaluation phase before randomization. The registry does not describe the allocation sequence, concealment procedures, or the method used to implement randomization. It also does not report whether treatment was delivered as intended or how treatment changes during follow-up were handled. Because masking is listed as none, the study was open-label; the record does not specify whether outcome assessment was masked.

Enrollment is listed as 2, and the posted outcome data list one participant in each arm. The primary completion date is 2011-03, the study start is 2009-07, and the overall status is completed. The primary outcome timeframe is 1 year. These registry entries describe the design and reported results but do not establish why enrollment was limited to this number or whether the posted data reflect all participants originally enrolled. A sample-size justification, recruitment history, and explanation of any differences between planned and analyzed populations 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:

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 Participants With a Reduction of HbA1c of >0.5%, measured over 1 year.

The primary endpoint is the number of participants whose HbA1c reduction exceeded 0.5% at 1 year. HbA1c is the measure named in the registry outcome; the endpoint converts its change into a binary classification: whether each participant crossed the stated reduction threshold. The result is expressed as a count of participants, rather than as an average change in HbA1c.

A threshold-based endpoint can make a result easy to describe: it identifies how many participants met a prespecified definition of response. It does not, by itself, show the size of each participant’s HbA1c change, the distribution of changes, or how close participants were to the threshold. Those details are not reported in the registry record. The outcome description also does not state how the reduction was calculated, such as the reference measurement used, or how measurements were handled if they were unavailable.

The posted count is 0 in the intervention arm and 0 in the control arm, with one participant listed in each. These are the observed endpoint counts in the registry. They do not establish that the treatments have identical effects: with no participant meeting the threshold in either group, the posted binary results do not support a stable estimate of the difference between groups. The endpoint should be read as a count meeting a defined threshold, not as a complete account of glycemic change or as a stand-alone measure of the broader clinical course.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The endpoint is binary at the participant level: each participant either meets the HbA1c reduction threshold of >0.5% at 1 year or does not. The registry reports counts, with 0 in each arm. A binary outcome can be summarized by counting participants who meet the definition and, when data permit, comparing the proportions between arms. In this study, the posted event counts do not support a meaningful two-arm estimate; the registry explicitly marks the binary comparison as not estimable. The record lists 0 analyses.

Why is the comparison not estimable?

For a two-arm comparison, the observed event pattern must contain enough information to estimate a contrast between the groups. When the event count is zero in both arms, the posted outcome does not provide a usable contrast for common effect measures. This is a feature of the data pattern, not proof that the groups have the same underlying probability of meeting the endpoint. A zero count in a very small group is compatible with substantial uncertainty about outcomes beyond the observed participants.

A confidence interval would ordinarily help show the precision of an estimated effect. It communicates a range of values compatible with the data and the chosen method, rather than simply indicating whether an estimate is positive or negative. The registry does not report an effect estimate or confidence interval for this endpoint. With the posted counts and arm sizes, the comparison is not estimable, so a numerical interval should not be invented or read into the result.

What does the threshold leave out?

Turning HbA1c change into a threshold-based response simplifies interpretation, but discards information about the magnitude of change. The endpoint distinguishes participants whose reduction exceeded >0.5% from those who did not meet that definition. It does not distinguish a participant close to the threshold from one with no reduction, nor does it show the range of individual measurements. The registry does not post continuous HbA1c values, baseline values, or change summaries. The posted count therefore answers only the threshold question.

What do the design features imply?

The study is randomized and parallel, and masking is listed as none. Random assignment is intended to support a fair comparison by making treatment allocation independent of participant characteristics on average; it cannot ensure balance in every realized trial, especially when the listed group sizes are very small. Open-label conduct means that participants and study staff were not masked according to the registry entry. The record does not say whether outcome measurement or analysis was masked, or provide details of allocation concealment. Those procedural details are not reported in the registry record.

The summary states that insulin and metformin were given during a 4-month evaluation phase before randomization. A common pre-randomization phase may define the sequence of care, but the record does not describe the measurements taken during that phase, how participants progressed to randomization, or whether treatment was modified. The randomized comparison concerns the intervention arm versus continued standard medical treatment as described in the arm entries. The registry does not report enough detail to assess adherence, crossover, or other treatment changes.

How should planning calculations be read?

Any sample-size illustration associated with these results is a planning exercise based on the observed effect, not a measure of the trial’s observed power and not evidence that the trial was designed to recruit a particular number. The stated illustration assumptions are a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation; the effect to detect is a stated fraction of the observed effect. In this case, the observed binary comparison is not estimable, so a planning calculation based on that comparison cannot supply a reliable treatment-effect estimate. The registry does not report the trial’s own sample-size justification, design assumptions, or planned enrollment rationale.

In general, sample-size planning asks how many participants would be needed to detect a specified effect under chosen assumptions. It is distinct from testing the data after a trial and does not show that the current study had adequate power. A planning illustration should therefore be read as conditional on its assumptions, rather than as a statement about what the study observed or was designed to achieve. No planning result can overcome the lack of an estimable observed comparison in the posted primary endpoint.

What statistical details are unavailable?

The registry does not report the statistical test, any covariate adjustment, an analysis population definition, a missing-data method, an interim analysis plan, or a multiplicity procedure. It also does not report an intention-to-treat designation or per-protocol analysis. These absences matter because different analysis choices can affect how a comparative estimate is constructed and interpreted. The posted counts can be described directly, but they cannot substitute for an unreported analysis plan or resolve the uncertainty around the comparison.

Over-dispersion is a general concern when count data vary more than a model assumes. It is not the central issue for this posted primary endpoint, which is defined as a participant count meeting a binary threshold and has no events in either arm. More generally, model assumptions should match the outcome type and the amount of information available. The registry does not report a model-based analysis for this endpoint. For these data, the key limitation is not a choice among models but that the posted zero-event counts do not yield an estimable two-arm 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("Autologous SC and HOT", "Control Group")
n      <- c(1, 1)
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  Autologous SC and HOT  1  0  0.0  0.0  97.5  0.0  79.3  1.3  84.2
ARM  Control Group  1  0  0.0  0.0  97.5  0.0  79.3  1.3  84.2

11. Multiplicity, Missing Data and Analysis Populations

The registry lists two outcome measures and identifies one secondary outcome: the number of subjects with a reduction of >1% in HbA1c. The primary outcome is a reduction of >0.5%. The record lists 0 analyses and does not post a result for the secondary outcome. It does not report whether the outcomes were tested according to a prespecified hierarchy, whether any adjustment for multiple comparisons was planned, or which outcome was designated as the sole basis for confirmatory inference beyond the primary-outcome label.

Multiplicity is a general statistical issue that arises when several outcomes or comparisons are examined. If many hypotheses are tested, the chance of finding an apparently notable result by chance can increase. Methods for addressing that issue depend on the planned analysis and the inferential goals. Since the registry does not report a multiplicity procedure or secondary-outcome result, no claim about multiplicity-adjusted findings can be made.

The registry record does not report missing-data counts, reasons for missingness, imputation methods, or the handling of participants without an assessment at 1 year. It also does not define the analysis population, state whether all randomized participants were included, or describe exclusions. The posted arm counts are one participant each, but the record does not explain the relationship between enrollment, randomization, and any analysis population. The outcome counts should therefore be interpreted as posted, without assuming a missing-data strategy or a particular analysis set.

These omissions limit assessment of possible bias and robustness. They do not change the direct observation that the posted primary endpoint count is 0 in each arm, but they prevent a fuller appraisal of how those counts were generated and analyzed. Missing-data and analysis-population details are not reported in the registry record.

12. Safety Results

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

Other (non-serious) adverse events

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

The serious adverse event figures list one participant at risk in each arm and 0 serious adverse events in each. The non-serious adverse event figures likewise list one participant at risk in each arm and 0 events. These are the posted counts for the groups and should be read as recorded observations, not as proof that the interventions carry no risk.

With one participant listed in each arm, the safety counts provide very limited information about the frequency or range of possible adverse events. An absence of reported events among these participants cannot establish that events would not occur in a larger group or over a different period. The registry does not report event-specific serious adverse event terms, and the top serious terms list is empty. The record also does not specify additional details about event collection, severity grading, relatedness assessments, or duration of safety follow-up.

Deaths are not reported in the registry record; the death fields are not a reported count of zero. The adverse-event figures therefore do not support a comparative estimate of safety between groups. They describe only the counts posted for participants at risk in this record, with substantial limits on how broadly those counts can be interpreted.

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

The posted primary result means that no participant in either arm is recorded as having an HbA1c reduction of >0.5% at 1 year. The intervention arm is listed with one participant and a count of 0 meeting the endpoint; the control arm is listed with one participant and a count of 0. That is the direct descriptive finding.

It does not mean that the treatments produced identical HbA1c changes. The endpoint is based on a threshold, and the registry does not post the underlying measurements or changes. It is therefore not possible to tell whether participants had smaller reductions, no change, or increases. Nor can the result establish that the treatments are equivalent, because no equivalence margin or comparative estimate is reported and the binary comparison is not estimable.

It also does not establish that either intervention is effective or ineffective. A result based on no events in groups this small cannot provide a precise estimate of how frequently the threshold might be met in a wider population. No confidence interval or hypothesis-test result is reported. The result is best understood as a limited observation from the posted record, rather than a definitive estimate of treatment benefit or lack of benefit.

The primary outcome addresses one specified HbA1c threshold and timeframe. It does not summarize every outcome relevant to diabetes, and the registry does not report the secondary threshold result. Safety counts are similarly limited: the posted record lists no serious or other adverse events among the participants at risk, but that does not establish absence of risk. Overall, the registry provides a description of a very small randomized comparison, but not enough outcome information to support a precise comparative conclusion.

14. Why This Trial Matters Statistically

This trial is statistically notable because it illustrates the difference between a randomized design and an informative estimate. Randomization is an important design feature for comparing groups, but it does not itself ensure that a study will produce a precise result. Here, enrollment is listed as 2, and one participant is listed in each arm for the primary outcome. The resulting counts are 0 in both groups, so the comparison is not estimable.

The case also shows why a zero count should not be interpreted as evidence of no difference. When no participant meets a binary endpoint in either arm, there is no observed event contrast to quantify. The absence of an estimate is not the same as an estimate of no effect. Uncertainty is especially consequential when the outcome is recorded in groups this small, and the registry does not provide a confidence interval or another analysis that would quantify it.

A threshold endpoint has an additional interpretive trade-off. It creates a clear response definition, but does not preserve the amount of change in the underlying measure. Without continuous HbA1c values, a reader cannot assess changes that fell short of the threshold. The primary count is therefore informative about the stated classification, but narrow in what it captures.

Finally, the record distinguishes posted results from trial-planning information. A planning illustration based on an observed effect is not observed power, and it cannot replace a documented design rationale. The sample-size justification and detailed analysis plan are not reported in the registry record. These features make the study a useful example of why design labels, endpoint definitions, group counts, precision, and reporting completeness all matter when reading a clinical trial.

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 principal limitation is the very small enrollment listed in the registry: 2 participants, with one participant in each arm for the primary endpoint. The posted primary event counts are 0 in both groups, and the two-arm binary comparison is not estimable. This prevents a useful estimate of the between-group effect and leaves substantial uncertainty about outcomes beyond those recorded.

The registry does not report baseline HbA1c values, individual or group-level HbA1c changes, or the number of participants meeting the secondary reduction threshold of >1%. As a result, the primary threshold count cannot show the magnitude or distribution of glycemic changes. The record also does not explain how the reduction was calculated or how an unavailable 1-year measurement would be handled.

Further limitations concern reporting of design and analysis. Although the study is listed as randomized, open-label, and parallel, the registry does not report allocation concealment, the randomization method, masking of outcome assessment, adherence, treatment changes, analysis populations, or a statistical test. A sample-size justification, missing-data method, multiplicity procedure, and interim analysis plan are not reported in the registry record. These omissions make it difficult to assess the analysis beyond the posted counts.

Safety interpretation is constrained by the same small group sizes. The record lists 0 serious and 0 other adverse events in each arm, but does not provide event terms or report deaths. These observations do not establish the frequency of adverse events in a broader population. The completed status and recorded dates do not resolve these limitations in the available results.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Autologous Stem Cell and Hyperbaric Oxygen Therapy in Type 2 Diabetes Mellitus — NCT01786707.
• Registry record last updated 2017-07-02; status last verified 2017-06.
• Results first posted 2014-04-21.
• 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

The registry describes a completed randomized, open-label, parallel study in type 2 diabetes mellitus, listing both phase 1 and phase 2. Participants were described as receiving insulin and metformin during a 4-month evaluation phase before assignment to autologous stem cells and hyperbaric oxygen therapy plus standard treatment, or continued standard treatment alone.

Enrollment is listed as 2. The primary outcome was the number of participants with an HbA1c reduction of >0.5% at 1 year. The posted count was 0 in each arm, with one participant listed in each. The comparison is not estimable, and the registry lists 0 analyses. The secondary outcome is a reduction of >1%, but its result is not reported in the registry record.

The study started in 2009-07, reached primary completion in 2011-03, and is listed as completed. The registry does not report a sample-size justification, detailed analysis plan, missing-data approach, or analysis populations. Safety entries list no serious or other adverse events among one participant at risk in each arm; deaths are not reported in the registry record.