A Study to Evaluate the Effect of ORMD-0801 in Patients With Type 2 Diabetes Mellitus: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study to Evaluate the Effect of ORMD-0801 in Patients With Type 2 Diabetes Mellitus (NCT04564846), a randomized phase 2 study. The primary outcome is Area Under the Curve (AUC(0-16)) of Endogenous Glucose Production.

2. Clinical Question

The study was designed to explore the effect of ORMD-0801 compared with placebo on endogenous glucose production in people with type 2 diabetes. The primary measure is an area under the curve (AUC) over the specified post-dose observation window, rather than a single glucose-production measurement. The registry record describes a tracer infusion and pharmacokinetic measurements spanning baseline and post-dose time points through the stated window.

The posted group means were 3139 mg*hr/dL for ORMD-0801 and 3437 mg*hr/dL for placebo. The unadjusted mean difference, expressed as ORMD-0801 minus placebo, was -297.5 mg*hr/dL, with a 95% confidence interval from -834.4 to 239.4. These estimates describe the observed comparison; the interval includes values on either side of no difference.

The central question is therefore about the between-group contrast in the measured endpoint, not whether a particular group’s result changed from baseline or whether the trial establishes a clinical benefit. The registry record does not report a clinically important difference threshold for this endpoint. It also does not provide enough information to infer how the observed AUC contrast would translate to other outcomes or to clinical decisions.

3. Trial Design

This completed phase 2 study is recorded as randomized, triple-masked, and parallel-group. It compared ORMD-0801 with placebo in people with type 2 diabetes mellitus. The registry lists enrollment as 49. The primary endpoint was assessed at Day 28, with the timeframe described as one day. The trial started on 2020-11-23, and primary completion was recorded as 2022-06-07.

Participants who qualified after screening were to be randomized to ORMD-0801 or matching placebo. The study medication was taken twice a day, once in the morning before breakfast and once at night before bedtime. The intervention description identifies a single 8 mg capsule of ORMD-0801; the placebo is described as a single capsule of fish oil. The registry record does not report further detail about the allocation procedure, concealment process, or the specific roles covered by triple masking.

The primary outcome summary lists 21 participants in the placebo group and 20 in the ORMD-0801 group. These are the group counts attached to the posted Day 28 continuous-outcome summaries, not a restatement of overall trial enrollment. The population description identifies the analysis population as modified intention-to-treat and says it consists of subjects who started on Day 28. It also says all 22 mITT placebo subjects came in for Study Day 28, then notes that one subject discontinued after standard blood tests and before the pharmacokinetic measurements because of non-compliance or lack of cooperation. The narrative is truncated after that point, so the complete population accounting is not reported in the registry record.

The record includes secondary outcomes for HbA1c, beta-hydroxybutyrate, insulin, free fatty acids, and plasma glucose. It lists five posted secondary outcomes, though the outcome-measure count is six. The registry record does not report the original sample-size justification, a detailed statistical analysis plan, the full missing-data approach, or whether any interim analyses were planned or conducted.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: modified intend-to-treat (mITT) population. mITT consists of all subjects that started on Day 28. All 22 mITT placebo subjects came in for Study Day 28. One subject discontinued after the standard blood tests, prior to the pK measurements due to Non-Compliance or Lack of Cooperation. Thus, the sample size on Day 28 for AUC(0-16) is 21, and for the standard blood tests is 22. The 21 subjects that completed Visit 3 (days 28 + 29) were included in this outcome measure.

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 Area Under the Curve (AUC(0-16)) of Endogenous Glucose Production, measured over Day 28 (1 day).

The primary endpoint is the area under the curve from 0 to 16 hours (AUC(0-16)) of endogenous glucose production, reported in mg*hr/dL. The registry describes endogenous glucose production being assessed with glucose carrying an attached tracer. An intravenous infusion of the specified glucose tracer is administered after the study medication, with pharmacokinetic measurements scheduled from baseline through the post-dose observation window. The stated primary time point is Day 28.

An AUC combines measurements across a period into a single summary of the measured quantity over that period. In general, this can characterize the overall measured exposure or production during the observation window, rather than relying on one time point that might not represent the pattern across the whole window. The interpretation depends on how the measurements are obtained and summarized; the registry record does not provide the full computational details for the endpoint.

The endpoint was selected to address the study’s stated question about the effect of ORMD-0801 on endogenous glucose production. It is a physiological, short-term measure, not a direct measure of longer-term clinical outcomes. The registry record does not report a threshold defining a clinically important difference in AUC(0-16). Consequently, a numerical difference in this measure should be read as a comparison of the endpoint as recorded, not as proof of a meaningful change in health or disease status.

7. Results Posted in the Registry

• ORMD-0801: mean 3,139 versus 3,437 on control; difference -297.50 (95% CI -834.36 to 239.36), standardized effect d = -0.34; z-test p = 0.277.

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.

Area Under the Curve AUC(0-16) of Metabolite Beta-hydroxybutyrate

• 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:
  • ORMD-0801: mean 2,010 versus 3,436 on control; difference -1,426 (95% CI -2,936 to 83.56), standardized effect d = -0.57; z-test p = 0.064.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between ORMD-0801 and the control. The interval gives the range of effects that remain compatible with the data.

Area Under the Curve (AUC) of Insulin

• 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:
  • ORMD-0801: mean 425.10 versus 324.80 on control; difference 100.30 (95% CI -35.53 to 236.13), standardized effect d = 0.46; z-test p = 0.148.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between ORMD-0801 and the control. The interval gives the range of effects that remain compatible with the data.

Area Under the Curve (AUC) of Free Fatty Acids (FFA)

• 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:
  • ORMD-0801: mean 7,051 versus 7,327 on control; difference -275.80 (95% CI -1,381 to 829.04), standardized effect d = -0.15; z-test p = 0.625.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between ORMD-0801 and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover several metabolic measures, including HbA1c, beta-hydroxybutyrate, insulin, free fatty acids, and plasma glucose. The posted continuous summaries show a mixed overall pattern: some group means are lower in the ORMD-0801 group and others are higher, and the size and uncertainty of comparisons vary. The reported adjusted analyses also use differing stated metrics. This collection does not present one uniform direction across all measured outcomes.

These measures provide additional context alongside the primary endogenous glucose production endpoint, but they do not replace it. Each outcome addresses a related but distinct biological measurement, and differences in scale, variability, timing, and analysis affect how its estimate should be read. The registry record does not report a hierarchy that would make a secondary measure a substitute primary endpoint or establish a single combined interpretation across them.

The secondary results carry less weight when considered as individual significance tests because multiple outcomes were examined and the registry record does not report a multiplicity adjustment or a prespecified interpretation strategy. When many comparisons are made, the chance of seeing an apparently notable result by chance can increase. This is general statistical context, not a claim that any particular secondary finding is false. Without a reported correction or clear confirmatory framework, unadjusted secondary p-values are best treated as exploratory signals that need cautious interpretation.

The secondary estimates should therefore be read together with their uncertainty and with the primary result, rather than singled out because of a particular direction or p-value. The record does not report a complete statistical plan describing how these outcomes were prioritized, how missing values were handled for each outcome, or how multiplicity was addressed.

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

• Mean Changes in HbA1c
• Area Under the Curve AUC(0-16) of Metabolite Beta-hydroxybutyrate
• Area Under the Curve (AUC) of Insulin
• Area Under the Curve (AUC) of Free Fatty Acids (FFA)
• Mean Changes Plasma Glucose Levels

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous and is summarized as a mean with a standard deviation in each group. The mean is the arithmetic average of the measured AUC values in that group. The standard deviation describes how dispersed individual measurements are around the group mean. It is not the same as the uncertainty in the mean or the confidence interval for the between-group contrast.

What does the unadjusted mean difference represent?

The recalculated comparison subtracts the placebo mean from the ORMD-0801 mean. Its estimate of -297.5 mg*hr/dL describes the difference between the posted group averages without covariate adjustment. A negative estimate means the posted ORMD-0801 average is lower. The confidence interval for this contrast reflects uncertainty in estimating the underlying group difference from the observed summary data. It does not describe the range containing most individual participants’ measurements.

The recalculation is unadjusted: it uses the posted group summaries rather than the covariate-adjusted model reported by the registry. It should be read as a transparent comparison of the posted means, not as a reconstruction of the sponsor’s complete analysis. The registry does not report enough detail about covariates, model diagnostics, or the fitted analysis to reproduce that adjusted result.

Why does dispersion matter?

Greater variability within groups generally makes a mean difference harder to estimate precisely, all else being equal. The standard deviations describe the observed spread in the endpoint. The standard error describes the sampling uncertainty of an estimate, and the confidence interval is built around that uncertainty using a statistical method. These quantities answer related but different questions: the standard deviation concerns variation among measurements, while the standard error concerns precision of an estimated mean or contrast.

Some outcomes can show more variability than a simple model assumes. In general, over-dispersion means that the observed variation exceeds what a chosen statistical model expects. Accounting for that extra variation can widen uncertainty estimates and affect inference. The record does not state that over-dispersion was identified or used as a specific adjustment for the primary outcome, so this is general statistical context rather than a claim about this trial.

How should the reported adjusted analysis be read?

The registry labels its primary reported analysis as Analysis of Covariance and reports a Risk Ratio (RR). An adjusted analysis can account for specified covariates and may target a contrast different from a raw difference in means. However, a risk ratio is not the same quantity as a mean difference measured in mg*hr/dL. The registry record does not define the RR calculation or give the covariates and full model specification. It is therefore not possible to determine from the record how that statistic was constructed or to convert it into the unadjusted mean-difference scale.

The registry-reported p-value of 0.163 and the recalculated unadjusted p-value of 0.277 come from differently described analyses. A p-value measures how incompatible the observed data are with a specified null model under the assumptions of an analysis; it is not the probability that the null hypothesis is true, nor a measure of the size or clinical importance of an effect. Because the model specifications differ or are not fully reported, the p-values should not be expected to match.

What is a confidence interval?

A confidence interval gives a range of values reasonably compatible with the observed data and the assumptions of the method used. The stated confidence level describes the long-run coverage property of the procedure under those assumptions; it is not a probability that the particular interval contains the true value. For the primary unadjusted difference, the interval extends from -834.4 to 239.4 mg*hr/dL. Its inclusion of zero indicates that no difference is among the values compatible with the data under this calculation. The interval also allows nonzero differences, so the estimate is not precise enough to exclude effects in either direction.

Why are planning estimates not trial results?

The participant-per-arm figures are planning illustrations based on the observed effect and stated assumptions. They describe hypothetical sample sizes for future planning under a normal approximation, equal allocation, and a two-sided significance level of 0.05. The illustrations are not evidence about the probability that this completed trial detected an effect. In general, a smaller effect is more difficult to distinguish from random variation and therefore requires more participants, if other assumptions remain unchanged.

All such calculations depend on assumptions about the target effect, variability, analysis, and allocation. They do not replace the original design rationale, which is not reported in the registry record. The group summaries and recalculations also depend on the completeness and correctness of the posted outcome data. The registry record’s truncated population narrative leaves some analysis-population details unresolved.

11. Confidence Intervals and Precision

The primary unadjusted mean difference is -297.5 mg*hr/dL, with a 95% confidence interval from -834.4 to 239.4. The interval includes zero and extends to values on both sides of it. It therefore does not isolate a single direction of effect. A lower mean in the ORMD-0801 group is the point estimate, but the uncertainty includes a higher mean as well.

The interval also conveys that the effect estimate is not highly precise. Its breadth allows a range of potential differences that may be relevant to interpretation, although the registry record does not report a clinically important threshold for judging that range. Precision is not the same as whether a result passes a statistical significance threshold: it concerns how narrowly the data estimate the contrast. A confidence interval that includes zero does not establish that the true effect is exactly zero.

The posted standard deviations, 922.9 for placebo and 830.3 for ORMD-0801, describe variability in individual AUC values within the groups. Those figures help contextualize why a group contrast is uncertain, but they are not themselves confidence limits for the treatment difference. The estimated group counts are 21 and 20 for the primary summary. The record does not report confidence intervals for each group mean in the posted summary.

The sponsor’s registry-reported adjusted result is a Risk Ratio of 0.974, with a 95% confidence interval from 0.938 to 1.011. That interval also includes its no-effect reference value, but it is on a different stated scale from the unadjusted mean difference. Since the registry record does not explain how the RR relates to the continuous AUC endpoint, its precision should be considered separately rather than combined with the mean-difference interval.

These intervals quantify sampling uncertainty under their respective analysis assumptions. They do not capture every source of uncertainty, such as uncertainty from incomplete reporting, outcome measurement, or model choice. The record does not report enough information to assess all of those sources.

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 sample-size illustrations give estimated participants per arm, not total events. They use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The hypothetical effect to detect is a stated fraction of the observed effect. These are planning assumptions for the illustrations; the trial’s original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes the number of participants per arm that the planning calculation estimates would be needed to have an 80% chance of detecting the specified effect, if the assumptions and effect were correct. The 90% power column uses a higher probability of detection and therefore yields a larger planned group size under the same general framework. Power is a feature of a design under assumptions, not a guarantee about what a study will find.

For the primary endpoint, the illustration gives 138 participants per arm for planning around 100% of the observed effect at 80% power, and 184 at 90% power. Planning around 75% of the observed effect gives 244 participants per arm at 80% power and 327 at 90% power. For 50% of the observed effect, the figures are 549 participants per arm at 80% power and 734 at 90% power. These are hypothetical planning values, not observed enrollment requirements established by the trial.

The pattern reflects a general principle: smaller effects are harder to distinguish from random variation, so they require more participants for a given power target, if other assumptions remain fixed. The curve should be interpreted as an illustration of that relationship, rather than a prediction of a future trial’s result. This is not observed power. The registry does not report whether the original study used these assumptions or how its enrollment target was chosen.

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 = -297.500; pooled standard deviation σ = 878.997.
2. n = 2 × (1.96 + 0.842)² × 878.997² / -297.500² = 137.0, rounded up to 138 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 <- -297.5                      # observed difference in means
sigma <- 878.996619693917                     # 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(4564846)
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 = 138 (80% power), 184 (90% power)
 75% of observed effect: n per arm = 244 (80% power), 327 (90% power)
 50% of observed effect: n per arm = 549 (80% power), 734 (90% power)
power.t.test: 138 
Simulated power at n = 138 per arm: 0.806 (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

The registry’s own primary analysis is reported as Analysis of Covariance, with a Risk Ratio of 0.974, a 95% confidence interval from 0.938 to 1.011, and p=0.163. The recalculated comparison uses the posted group means and standard deviations to estimate an unadjusted mean difference of -297.5 mg*hr/dL, with a 95% confidence interval from -834.4 to 239.4 and an unadjusted p-value of 0.277.

These are not identical estimands or scales: one is reported as a Risk Ratio from a named adjusted method, while the recalculation is a raw difference in continuous group means. The registry record does not describe the adjusted model sufficiently to reproduce it or establish exactly how its RR relates to the AUC measure. The p-values likewise arise from differently described analyses and should not be compared as if they came from the same calculation.

The two reported summaries both have confidence intervals that include their respective no-effect reference values. That does not make the estimates interchangeable, nor does it establish equivalence. The registry-reported analysis is the study’s stated analysis; the unadjusted recalculation is a separate, limited comparison of posted summary statistics. The discrepancy flag is false, so the record does not identify a disagreement requiring a sponsor-analysis precedence note.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study evaluates several outcomes or makes several statistical comparisons. Even if each test is considered separately, repeated testing can raise the chance that at least one result appears notable by chance. The registry lists multiple secondary outcomes in addition to the primary endpoint. It does not report a multiplicity adjustment, a gatekeeping procedure, or another prespecified approach for controlling interpretation across these results.

This absence matters chiefly for the secondary findings: their p-values should not be read as though each were the only question asked. The primary comparison remains the study’s designated main endpoint, but the registry record does not provide the full analysis plan needed to determine all prespecified hypotheses or how secondary testing was intended to be interpreted. Whether multiplicity procedures were specified elsewhere is not reported in the registry record.

Missing-data reporting is also incomplete. The primary population description says the mITT population consists of subjects who started on Day 28 and reports that all 22 mITT placebo subjects came in for Study Day 28. It then notes that one subject discontinued after standard blood tests and before the pharmacokinetic measurements because of non-compliance or lack of cooperation. The text is truncated after this detail. The posted primary outcome summary lists 21 placebo participants, while the narrative begins with 22 mITT placebo subjects. The record does not provide a complete account of how that subject was handled or describe missing-data methods.

The posted primary outcome summary also lists 20 participants in the ORMD-0801 group, but the registry record does not give an equally detailed narrative accounting for that group in the population description. It does not report whether any imputation was used, how missing endpoint measurements were treated, or whether sensitivity analyses assessed the effect of missing data. These omissions limit assessment of the robustness of the estimated contrast and the exact analysis population.

Interim analyses, stopping rules, and the trial’s full statistical analysis plan are not reported in the registry record. Their absence from the record should not be interpreted as evidence that they were or were not used.

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.

Most frequent non-serious adverse event terms

The registry lists serious adverse events for both groups, with zero serious adverse events reported in the placebo group and zero in the ORMD-0801 group. It also records zero deaths in each group. For other, non-serious adverse events, the registry lists 3 affected participants in the placebo group and 6 in the ORMD-0801 group.

These are counts of participants affected within the recorded at-risk groups: 25 for placebo and 24 for ORMD-0801 in the adverse-event listing. They should be read as descriptive registry figures, not as a complete safety comparison. The record does not list serious adverse-event terms, because none are shown in the serious-event term field. It also does not provide event-level details, severity distributions, timing, or a statistical comparison of adverse-event rates.

Zero recorded serious adverse events or deaths in these groups does not establish that the risks are absent. Safety interpretation depends on the amount and duration of observation, how events were collected and classified, and the completeness of reporting. The registry record does not provide enough information to evaluate those aspects fully. The non-serious event counts likewise do not by themselves establish a causal relationship to either assigned intervention.

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

The posted primary outcome estimates a lower mean AUC(0-16) of endogenous glucose production in the ORMD-0801 group than in the placebo group at Day 28. The unadjusted difference is -297.5 mg*hr/dL. Its 95% confidence interval ranges from -834.4 to 239.4, so the estimate is uncertain and compatible with differences in either direction. The p-value of 0.277 does not provide evidence against the no-difference model at conventional thresholds, but it does not prove that the groups are identical.

The registry’s adjusted analysis reports a Risk Ratio with a confidence interval that includes its no-effect reference value. Because the record does not sufficiently define the model or show how the RR corresponds to the continuous AUC endpoint, that analysis should not be interpreted as a direct version of the unadjusted mean difference. Both forms of result are statistical summaries of the posted comparison, not direct proof of clinical benefit or harm.

The endpoint is a short-term physiological measure collected at Day 28. It is not itself a measure of long-term diabetes outcomes, symptoms, or complications. The registry record does not report a threshold for a clinically important AUC change, so the observed numerical contrast cannot be classified as clinically meaningful from this record alone. The trial also does not establish that any result would generalize to people or settings beyond those represented in its analysis population.

The secondary outcomes add context but involve multiple measurements and are reported with varying uncertainty and analysis scales. Without a reported multiplicity strategy, those results should be considered exploratory. The limited sample and incomplete population and methods reporting further constrain how strongly the full set of findings can be interpreted.

In short, the record documents a randomized comparison and gives an estimate for its primary endpoint, but the uncertainty is substantial. The result neither establishes a clear difference nor establishes equivalence. It also does not, by itself, determine whether ORMD-0801 should be used, or predict an individual’s outcome.

18. Why This Trial Matters Statistically

This trial is statistically informative because it illustrates the distinction between an observed difference and a precise estimate of that difference. The group means point to a lower AUC in the ORMD-0801 group, but the confidence interval includes zero and values on both sides. A point estimate alone can therefore give an incomplete impression; the interval is essential for understanding how much uncertainty remains.

The registry also offers two different forms of primary result: an unadjusted mean-difference recalculation from group summaries and an adjusted analysis reported as a Risk Ratio. Since the record does not fully specify the adjusted model or explain the RR for this continuous endpoint, the measures cannot simply be merged. This emphasizes why estimates need to be read with their analysis method and scale, not just their p-values.

The endpoint is a physiological measurement collected at Day 28, and the trial’s listed secondary outcomes cover other metabolic measures. Interpreting a collection of outcomes requires attention to multiplicity, outcome hierarchy, and uncertainty. The registry record does not report a multiplicity strategy or a full statistical plan, leaving important context for secondary findings unavailable.

Finally, the planning illustrations show how sample-size requirements depend on the effect targeted: planning around a smaller fraction of the observed effect entails larger participant-per-arm estimates under the stated assumptions. Those illustrations are not the original design justification. The contrast between hypothetical planning assumptions and unreported trial-design assumptions is important for avoiding the mistaken view that a planning calculation explains why the completed study enrolled its recorded participants.

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.

The registry record does not report the original sample-size justification, so it is not possible to assess whether the enrollment target was designed around a particular clinically important difference or expected variability. The planning illustrations based on the observed effect are not a substitute for that rationale.

The primary analysis reporting is incomplete. The adjusted analysis is labeled Analysis of Covariance but reports a Risk Ratio for a continuous AUC endpoint, without enough detail to identify the model, covariates, or exact estimand. The unadjusted mean comparison can be interpreted directly from the posted summaries, but it does not reproduce the adjusted analysis.

The modified intention-to-treat population description is truncated and does not fully reconcile its narrative with the posted outcome counts. It mentions 22 mITT placebo subjects who came in for Day 28 and one who discontinued before pharmacokinetic measurements; the posted primary summary lists 21 placebo participants. The record does not provide the full analysis-population accounting, a missing-data method, or sensitivity analyses. These limitations make it difficult to determine the effect of incomplete endpoint measurement on the result.

The registry lists several secondary outcomes, but a complete multiplicity plan and outcome-prioritization strategy are not reported. Secondary findings should therefore be interpreted cautiously. The record also does not provide a clinically important threshold for the primary endpoint, a full account of measurement procedures beyond the brief tracer description, or enough detail to assess generalizability. Safety information is limited to participant counts and does not include event-level descriptions or exposure-adjusted comparisons.

These are limitations of the information available in the registry record. They do not establish that the underlying trial lacked additional documentation; such information is simply not reported in the registry record.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Study to Evaluate the Effect of ORMD-0801 in Patients With Type 2 Diabetes Mellitus — NCT04564846.
• Registry record last updated 2024-05-07; status last verified 2024-04.
• Results first posted 2024-05-07.
• 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 identifies a completed randomized, triple-masked, parallel-group phase 2 study of ORMD-0801 versus placebo in people with type 2 diabetes mellitus. Enrollment is listed as 49, with study start on 2020-11-23 and primary completion on 2022-06-07.

The primary outcome is AUC(0-16) of endogenous glucose production at Day 28. The posted unadjusted mean difference was -297.5 mg*hr/dL, with a 95% confidence interval from -834.4 to 239.4 and p=0.277. The registry’s adjusted analysis reports a Risk Ratio of 0.974, with a 95% confidence interval from 0.938 to 1.011 and p=0.163.

Interpretation is limited by uncertainty around the primary estimate, incomplete reporting of the adjusted model and analysis population, and the absence of a reported multiplicity strategy and original sample-size rationale.