Study to Evaluate the Safety and Efficacy of Oral Insulin Formulation in Type 2 Diabetes Mellitus Subjects: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study to Evaluate the Safety and Efficacy of Oral Insulin Formulation in Type 2 Diabetes Mellitus Subjects (NCT06473662), a randomized phase 2 study. The primary outcome is Change in HbA1c.

2. Clinical Question

This is a dose-comparison question, not a comparison of oral insulin with usual care or with no insulin. The posted primary comparisons are unadjusted recalculations from arm-level summary statistics. A registry-reported analysis is also listed for the 150iu group, but it does not report the same between-dose comparison in the same form. The sponsor's own analysis takes precedence for its reported analysis; the distinction is discussed further in the statistical interpretation.

3. Trial Design

The registry record describes a completed Phase 2b randomized, open-label comparative study with a parallel-group design and no masking. The study enrolled 153 participants. Its official title identifies people with type 2 diabetes uncontrolled with metformin hydrochloride treatment, while the condition label refers to type 2 diabetes treated with insulin. The record does not report further details that resolve the difference between those descriptions.

Three groups received oral recombinant human insulin capsules: 75iu, 150iu, or 300iu, each administered two times per day. The trial summary describes a randomized twelve-week study intended to compare pharmacodynamic properties across doses. The primary outcome was change in HbA1c at 12 weeks. Secondary outcomes were change in fasting plasma glucose, change in post-prandial glucose, and changes in triglycerides.

The record reports arm-level outcome summaries for 33.0 participants in the 75iu group, 29.0 in the 150iu group, and 38.0 in the 300iu group. These outcome counts do not explain how all enrolled participants were handled in the analyses. The analysis population, participant flow, allocation procedure, adherence, and handling of withdrawals are not reported in the registry record.

Dates recorded for the study are 2018-10-22 for study start and 2020-07-11 for primary completion. The status is completed. The registry record does not report the original design assumptions, planned sample size justification, or detailed statistical analysis plan.

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: 153 patients were randomised to allocated treatment groups. A proportion of these patients (7) did not commence treatment, and full baseline characteristics were not collected for the whole group

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.

Population: Baseline Analysis Population is the number of patients who completed the study according to protocol

6. Primary Endpoint

The registry lists the primary outcome as Change in HbA1c, measured over 12 weeks.

The primary endpoint is change in HbA1c, measured as a percentage of glycated haemoglobin, relative to baseline at the start of the study. HbA1c reflects glucose attached to haemoglobin and is commonly used as a measure of average blood glucose over a period of time. In general, it provides a different view of glucose control from a single glucose measurement, which can vary with timing and circumstances.

The endpoint is recorded at 12 weeks, matching the study duration described in the registry summary. The posted arm summaries report mean change and standard deviation. A negative mean change indicates that the average follow-up value was below the starting value, according to the change convention used in the record. These group means describe average changes; they do not show the range of individual responses or how many participants had changes in either direction.

For a dose-comparison trial, the relevant question is whether the average change differs between dose groups, rather than whether a group’s change alone differs from zero. The recalculated comparisons use the 75iu group as the reference. The registry-reported analysis for the 150iu group is expressed as a final-value mean difference and does not provide a direct, clearly specified between-dose contrast in the posted result. The registry record does not report a detailed endpoint definition beyond change relative to baseline, or details of the measurement and analysis procedures.

7. Results Posted in the Registry

• 150iu: mean -0.53 versus -0.20 on control; difference -0.33 (95% CI -0.85 to 0.19), standardized effect d = -0.31; z-test p = 0.217.
• 300iu: mean -0.31 versus -0.20 on control; difference -0.11 (95% CI -0.60 to 0.38), standardized effect d = -0.10; z-test p = 0.660.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Change in Fasting Plasma Glucose

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • 150iu: mean -18.80 versus -14.80 on control; difference -4.00 (95% CI -27.33 to 19.33), standardized effect d = -0.08; z-test p = 0.737.
  • 300iu: mean -2.70 versus -14.80 on control; difference 12.10 (95% CI -14.35 to 38.55), standardized effect d = 0.21; z-test p = 0.370.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 150iu and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 300iu and the control. The interval gives the range of effects that remain compatible with the data.

Change in Post-Prandial Glucose

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • 150iu: mean -21.00 versus -17.40 on control; difference -3.60 (95% CI -46.09 to 38.89), standardized effect d = -0.04; z-test p = 0.868.
  • 300iu: mean -31.00 versus -17.40 on control; difference -13.60 (95% CI -55.80 to 28.60), standardized effect d = -0.15; z-test p = 0.528.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 150iu and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 300iu and the control. The interval gives the range of effects that remain compatible with the data.

Changes in Triglycerides

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • 150iu: mean -22.13 versus -7.06 on control; difference -15.07 (95% CI -44.54 to 14.40), standardized effect d = -0.26; z-test p = 0.316.
  • 300iu: mean 20.56 versus -7.06 on control; difference 27.62 (95% CI 0.11 to 55.13), standardized effect d = 0.47; z-test p = 0.049.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between 150iu and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for 300iu than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes offer supporting context, but do not form a uniform pattern across measures and doses. The posted glucose changes vary in direction and magnitude between groups, while the triglyceride summaries show a different pattern across doses. The recalculated intervals are broad for many comparisons, so the secondary results are not uniformly precise. The pattern does not provide a consistent, independent confirmation of the primary comparison.

These outcomes relate to the primary HbA1c result by measuring other aspects of glucose and metabolic response during the same 12-week period. They may help describe the range of outcomes considered, but they do not replace the primary endpoint or resolve its uncertainty. The registry record does not report a prespecified hierarchy among the secondary outcomes or a detailed plan explaining how their results should influence interpretation of the primary outcome.

Unadjusted secondary results carry less weight because multiple outcomes and dose comparisons create more opportunities for chance findings. Without a reported multiplicity procedure, a nominal p-value should not be treated as confirmatory evidence. In particular, an isolated result near a conventional threshold requires caution when read alongside several other comparisons. The record does not report whether the analyses were intended to be exploratory, whether any correction was applied, or how missing data were handled for these outcomes.

Secondary endpoints can be informative for generating questions and assessing consistency, but any apparent signal needs confirmation in an analysis plan that specifies outcome priorities, multiplicity handling, and the intended population. The registry record does not provide that level of detail. The posted secondary summaries therefore offer descriptive context rather than a definitive basis for ranking doses or drawing conclusions beyond the measured outcomes.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Change in Fasting Plasma Glucose
• Change in Post-Prandial Glucose
• Changes in Triglycerides

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean change describe?

A mean change is the average of participants’ changes from baseline to the specified follow-up. Here, the posted primary outcome uses mean change in HbA1c at 12 weeks. A negative value represents an average decrease under the change convention used in the registry record. The standard deviation describes how spread out individual outcome changes are around the group mean. It is not the same as the standard error, which describes uncertainty in an estimated mean.

Group means are useful for summarizing the direction and average size of an outcome, but they do not describe every participant’s experience. The registry record does not report the distribution of individual changes, proportions meeting a response threshold, or the number with missing endpoint values. Such details would help interpret how representative each group mean is of individual outcomes.

Why compare groups rather than changes within groups?

The central randomized question is whether outcomes differ across assigned dose groups. A group’s change from its own baseline does not, by itself, show that its change differs from another group’s. The recalculated comparisons estimate the difference in mean changes between the 75iu reference group and each higher-dose group. These are simple unadjusted recalculations from the posted arm summaries, not a reconstruction of an individual-participant analysis.

The recalculated mean difference is accompanied by a confidence interval and an unadjusted p-value. The interval indicates a range of values compatible with the estimate under the calculation’s assumptions; it conveys both direction and precision. A wide interval signals substantial uncertainty. A p-value describes how compatible the observed statistic is with a specified null hypothesis under the test assumptions. It is not the probability that the null hypothesis is true, nor does it measure clinical importance.

What do the confidence intervals add?

For the primary recalculated comparisons, the intervals include zero. In general, zero represents no difference between group mean changes. The intervals’ inclusion of zero means the recalculations do not rule out no difference, while their breadth also permits differences in either direction. Interpretation should focus on the estimates and plausible range, not only on whether a p-value crosses a conventional threshold.

The intervals in these comparisons are calculated from posted summary statistics. They are not registry-reported confidence intervals for the sponsor’s own analyses. The registry record does not report confidence limits for the sponsor-reported outcome tests. The recalculated comparisons are unadjusted and should be distinguished from any model-based analysis using participant-level data.

Why does dispersion matter?

In general, variability matters because a mean difference is harder to estimate precisely when individual outcomes are spread out. Standard deviations for the primary outcome are around 1 in each group, while the recalculated mean differences are comparatively small. This combination is reflected in the confidence intervals. The same principle applies to the glucose outcomes, where the posted standard deviations are substantial relative to the estimated mean differences.

The triglyceride summaries are reported as least-squares means with standard errors rather than ordinary means with standard deviations. For recalculation, the standard errors were used to approximate standard deviations. This is a different basis from the other continuous-outcome recalculations and should be interpreted cautiously. In general, an approximation based on standard errors can be sensitive to the assumptions used to recover variability.

What does randomization contribute?

In general, random allocation is intended to make groups comparable, on average, with respect to factors that might influence outcomes. That supports causal interpretation of between-group comparisons when allocation is properly implemented and follow-up and analysis are handled appropriately. The registry record says that allocation was randomized, but does not describe the sequence generation, concealment, stratification, or checks of baseline comparability. It also does not report the analysis population or adjustment procedures for the posted primary summary.

How should the sponsor-reported tests be read?

The registry lists a t-test, 2 sided, for the 150iu group’s final values for HbA1c and fasting plasma glucose, and an ANCOVA for triglycerides. These reported results are not presented as the same contrast as the recalculated changes against the 75iu reference group. The record does not report the precise model specifications, covariates, or contrast definitions needed to fully reproduce them. Since a discrepancy is flagged, the sponsor's own analysis takes precedence for its analyses. The recalculations remain useful as transparent, unadjusted comparisons of the posted summary statistics, but they should not be conflated with the sponsor-reported tests.

11. Confidence Intervals and Precision

Precision is reflected in the width of a confidence interval: narrower intervals indicate more precise estimates, while wider intervals indicate greater uncertainty. For the primary recalculated comparison of 150iu with 75iu, the mean difference is -0.33 and the 95% confidence interval runs from -0.854 to 0.194. For 300iu compared with 75iu, the mean difference is -0.11 and the 95% confidence interval runs from -0.6 to 0.38. Both intervals contain zero and include values on either side of it.

These intervals do not establish that the groups are equivalent. Equivalence requires a prespecified margin and a suitable analysis; neither is reported in the registry record. Nor does an interval containing zero prove that there is no difference. It indicates that the posted summary-based estimate remains uncertain at the displayed precision.

The intervals are recalculated from group means, standard deviations, and group sizes. They are unadjusted and are not the sponsor’s reported confidence intervals. The record does not report confidence intervals for the sponsor-reported analyses. Differences in analysis population, baseline adjustment, or model specification could affect estimates, but those details are not reported in the registry record and cannot be inferred from these summaries.

Precision also depends on outcome variability and the amount of information available for each comparison. The posted primary group sizes are 33.0, 29.0, and 38.0, and standard deviations are near 1. A confidence interval is most useful when read together with its point estimate, the trial design, and the limitations of the underlying analysis rather than as a stand-alone decision rule.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm, not total participants and not total events. They are illustrations based on the observed effect, using a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect assumed for planning is the stated fraction of the observed effect: 100%, 75%, or 50%. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the estimated participants per arm for a hypothetical future study to have an 80% chance of detecting the specified effect under the stated assumptions, if that effect is real and the assumptions hold. The 90% power column gives the corresponding planning figure for a 90% chance. These are planning targets, not guarantees that a future study will detect an effect.

Smaller effects require more participants to detect with the same power and significance level. Accordingly, planning for 75% or 50% of the observed effect yields larger requirements than planning for the full observed effect. The observed effect can be an unstable basis for planning, especially when estimated from a trial with limited information. These figures are not observed power and do not describe the probability that the completed trial’s result is true.

The assumptions are simplified and the illustrations concern two-arm comparisons. The registry record does not report whether the original trial design used these assumptions, how its sample size was selected, or whether other factors such as attrition or multiple comparisons were incorporated in its planning.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.330; pooled standard deviation σ = 1.051.
2. n = 2 × (1.96 + 0.842)² × 1.051² / -0.330² = 159.1, rounded up to 160 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -0.33                      # observed difference in means
sigma <- 1.0507140429251                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(6473662)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 160 (80% power), 214 (90% power)
 75% of observed effect: n per arm = 283 (80% power), 379 (90% power)
 50% of observed effect: n per arm = 637 (80% power), 853 (90% power)
power.t.test: 160.1 
Simulated power at n = 160 per arm: 0.804 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

For HbA1c, the registry reports a two-sided t-test for the 150iu group, with final-values mean difference -0.53 and p = 0.004. The recalculation instead compares change from baseline between the 150iu and 75iu groups, producing a mean difference of -0.33 with p = 0.217. These are not the same reported contrast or analysis. The registry record does not provide enough detail to determine exactly how the sponsor’s reported test was constructed.

Related differences appear in the secondary outcomes: the registry reports a two-sided t-test for the 150iu fasting plasma glucose final value and an ANCOVA for the 150iu triglyceride final value. The recalculated comparisons use change summaries and compare each dose with 75iu. Since the discrepancy flag is true, the sponsor's own analysis takes precedence for its reported analyses. The recalculations are supplementary, unadjusted calculations from posted summary statistics; they should not be substituted for the sponsor's analysis or treated as a reproduction of it.

For outcomes without a registry-reported analysis, the recalculation is the only comparative estimate available in the posted summaries. Its limitations remain: it is unadjusted, based on aggregate statistics, and does not account for any unavailable participant-level modeling or covariates. The registry record does not report enough analytic detail to adjudicate why the two approaches differ.

15. Multiplicity, Missing Data and Analysis Populations

The record lists one primary outcome and three secondary outcomes, with multiple dose comparisons for each. Conducting multiple tests increases the chance that at least one result may appear notable by chance. In general, a multiplicity plan can control that risk by specifying which outcomes and comparisons are confirmatory and how the error rate will be handled. A multiplicity adjustment or hierarchy is not reported in the registry record.

The recalculated p-values are unadjusted. They should therefore be interpreted as individual comparisons rather than as results that account for the full set of outcomes and dose contrasts. The registry record does not report whether the sponsor’s analyses adjusted for multiplicity or how the sponsor classified primary and secondary tests beyond the outcome labels.

Missing-data methods are also not reported in the registry record. The record does not explain whether participants with incomplete follow-up were excluded, imputed, or handled using another approach. It does not provide participant flow or reasons for missing measurements. Arm-level outcome counts are posted, but the record does not state whether those counts define the analysis population, represent endpoint availability, or reflect another denominator.

The analysis population is not reported in the registry record. It is therefore not possible to determine from the posted summaries whether the results follow an intention-to-treat, per-protocol, or other population definition. The protocol’s statistical analysis plan, interim analyses, and detailed model specifications are not reported in the registry record. These omissions limit the ability to evaluate robustness, reproduce sponsor analyses, and understand how deviations from random assignment or incomplete follow-up may have influenced estimates.

16. 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.

The posted safety figures report zero serious adverse events and zero other adverse events for the 75iu, 150iu, and 300iu groups. Deaths are also reported as zero in each group. The numbers at risk listed for these safety summaries are 33, 29, and 38, respectively. No top serious-event terms are listed in the record.

These are registry-reported counts for the recorded categories; they do not establish that no adverse experiences occurred outside the categories or definitions captured in the record. The record does not provide event descriptions, severity criteria, exposure-adjusted rates, timing, or details of how adverse events were collected. It also does not explain whether the at-risk figures represent all randomized participants or another safety population.

Safety interpretation is bounded by the 12-week study duration and the posted reporting. Counts should be read as descriptive observations, not as proof of safety or as a comparison capable of excluding uncommon events. The registry record does not report a detailed safety analysis plan or additional follow-up information.

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

The posted results describe average changes in HbA1c, glucose measures, and triglycerides across three oral insulin dose groups during a 12-week randomized comparison. The primary recalculated comparisons do not precisely distinguish mean HbA1c change between the 75iu reference group and either higher-dose group. Their confidence intervals include zero and span differences in both directions.

This does not establish that the doses are equivalent, nor does it prove that there is no difference. It means the posted summary-based comparisons leave uncertainty about the size and direction of between-dose differences. The sponsor-reported 150iu analysis is a different reported analysis, and the discrepancy flag means the sponsor's own analysis takes precedence for its reported result. The registry record does not supply enough methodological detail to reconcile the two approaches.

The results do not compare oral insulin with placebo, usual care, or a non-insulin treatment. They do not establish effects beyond the study’s 12-week timeframe, and they do not answer questions about outcomes that were not reported. Statistical evidence from the posted summaries should not be treated as proof of clinical importance; the registry record does not report a threshold defining a clinically important change in HbA1c.

The safety counts describe what was recorded in the listed adverse-event categories and should not be interpreted as evidence that risk is absent. More broadly, open-label conduct, unreported analysis-population and missing-data details, and absent multiplicity information limit what can be concluded. The results are best read as estimates from a short dose-comparison study with uncertainty, not as a comprehensive assessment of benefits or harms.

18. Why This Trial Matters Statistically

This trial is statistically informative because it asks a direct dose-comparison question using randomized groups and a continuous primary outcome. Mean change in HbA1c allows the average response in each assigned dose group to be described, while between-group estimates and confidence intervals communicate how uncertain the comparisons are. That distinction matters: observing a change within a group is not the same as establishing a difference between groups.

The registry record also illustrates why results should be interpreted by estimand and analysis method. The sponsor-reported 150iu HbA1c result is presented as a final-values test, while the recalculation compares change summaries against the 75iu group. A nominal p-value from one analysis cannot be substituted for a distinct comparison. Because the record flags a discrepancy, the sponsor's own analysis takes precedence for its reported analysis, while the recalculation remains a separate descriptive check.

Uncertainty and multiplicity are important in a multi-dose, multi-outcome study. Confidence intervals show that the primary recalculated estimates are not highly precise, and the secondary results involve several comparisons without a reported multiplicity procedure. Sample-size illustrations can help readers understand the scale of future planning needs, but they do not reveal the original trial’s design assumptions or provide observed power.

Finally, the open-label design and incomplete reporting of analysis populations, missing data, and statistical methods place limits on reproducibility. These are not merely administrative details: they shape how confidently readers can interpret estimates and compare them with other evidence. The study is therefore useful as a record of a randomized dose comparison, while its statistical interpretation depends on careful attention to estimands, uncertainty, and reporting gaps.

19. 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 specific to this trial affect interpretation. It was open-label with no masking, so participants and study personnel knew the assigned dose. The registry record does not describe safeguards against potential effects of that knowledge on study conduct or outcome assessment. The trial lasted 12 weeks, limiting interpretation to the recorded timeframe.

The population description is not fully clear from the registry record: the official title describes participants uncontrolled with metformin hydrochloride treatment, while the condition label refers to type 2 diabetes treated with insulin. Further eligibility criteria and baseline characteristics are not reported in the record. The relationship between these descriptions should not be guessed.

Arm-level summaries are available, but participant flow, outcome availability, analysis-population definitions, adherence, withdrawals, and missing-data handling are not reported in the registry record. The recalculated comparisons use unadjusted summary statistics and cannot account for participant-level covariates or model choices. The sponsor-reported tests are not fully specified, and the record does not provide confidence intervals for those analyses.

The registry record does not report a multiplicity strategy, the original sample-size rationale, or detailed protocol analysis assumptions. The recalculated planning illustrations use observed effects and simplified assumptions, so they cannot establish the trial’s original planning basis. Safety reporting is limited to the listed counts and categories; detailed event descriptions and collection methods are not reported. Together, these limitations make the posted results useful for describing the recorded comparisons, but constrain reproducibility and broader inference.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study to Evaluate the Safety and Efficacy of Oral Insulin Formulation in Type 2 Diabetes Mellitus Subjects — NCT06473662.
• Registry record last updated 2025-02-06; status last verified 2025-02.
• Results first posted 2025-02-06.
• 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.

23. Record Summary

The registry record describes a completed Phase 2b randomized, open-label, parallel-group study of oral recombinant human insulin in capsule form. The study compared 75iu, 150iu, and 300iu doses administered two times per day over 12 weeks. It enrolled 153 participants and lists change in HbA1c as the primary outcome, with fasting plasma glucose, post-prandial glucose, and triglycerides as secondary outcomes.

The primary recalculated dose comparisons are unadjusted and have confidence intervals that include zero. The record also reports a sponsor analysis for the 150iu group, but the reported result is not the same comparison as the recalculation; the sponsor's own analysis takes precedence for its reported analysis. No serious or other adverse events, or deaths, are recorded in the posted safety counts for the three groups. Important details on analysis populations, missing data, multiplicity, and the original statistical plan are not reported in the registry record.