The Effect of Liraglutide on Endothelial Function in Subjects With Type 2 Diabetes Mellitus: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The Effect of Liraglutide on Endothelial Function in Subjects With Type 2 Diabetes Mellitus (NCT00620282), a randomized phase 3 study. The primary outcome is Change in Acetylcholine (ACh)-Mediated Forearm Blood Flow (FBF).

2. Clinical Question

The question concerns a measured vascular response, rather than a clinical event or a longer-term health outcome. The posted primary outcome is a change from week 0 to week 12, expressed as blood-flow volume per forearm tissue volume per minute. The group comparisons describe differences in estimated change; they do not by themselves establish what caused those changes or whether they translate into changes in health outcomes. The trial was conducted in the United States and is identified as Phase 3. The registry record does not report further details about eligibility criteria or the original sample-size justification.

3. Trial Design

The registry describes a randomized, double-blind, parallel-group, single-center trial with a 12-week treatment period. It was placebo controlled for the liraglutide comparison and also included an open-label glimepiride arm. The registered title describes the study as a Phase 3 trial. Enrollment was 49.

The liraglutide arm received once-daily subcutaneous treatment, titrated across the first weeks to 1.8 mg. The placebo arm followed a matching once-daily subcutaneous schedule. Glimepiride was administered orally at 4 mg once daily and was open label. The registry does not report whether masking applied to assessors in the open-label arm or other operational details of masking.

The primary analysis population is described as the ANCOVA full analysis set. It included randomized participants for whom data points could be collected at the end of the trial. The group counts for this primary outcome were 16 for liraglutide, 14 for placebo, and 16 for glimepiride. These outcome-specific analysis counts need not be treated as the same as the overall enrollment count. The registry record does not explain the difference between enrollment and the counts used for this outcome.

The primary endpoint was change in acetylcholine-mediated forearm blood flow between week 0 and week 12. Listed secondary outcomes include sodium nitroprusside-mediated forearm blood flow, HbA1c, fasting plasma glucose, postprandial glucose, body weight, and lipid measures. The registry reports completion status. Its original recruitment target, detailed allocation procedures, planned interim analyses, and full statistical analysis plan 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:

Analysis population for the primary outcome, as defined in the registry: The ANCOVA full analysis set (FAS) includes all randomised subjects for whom data points could be collected at end of trial.

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 Change in Acetylcholine (ACh)-Mediated Forearm Blood Flow (FBF), measured over week 0, week 12.

The primary endpoint is change in acetylcholine-mediated forearm blood flow from week 0 to week 12. Blood flow is measured in mL/100 mL/min: the volume of blood passing through a given volume of forearm tissue per minute. The registry describes measurement at euglycemia, specified as 90 mg/dL, using forearm venous occlusion plethysmography.

Acetylcholine-mediated flow serves as a physiological measure of endothelial function in this trial. In general, measuring a vascular response to a stimulus can provide information about function under a controlled measurement condition. It is distinct from measuring a clinical event, symptoms, or long-term outcomes. The registry’s definition makes clear that the endpoint is a change in a laboratory-style physiological measurement, not a direct measure of how participants feel or function in daily life.

The outcome is summarized as a least-squares mean, with standard error as the stated measure of dispersion. A least-squares mean is an estimate from a statistical model rather than simply the raw average. The registry identifies ANCOVA as the method used for the reported comparisons, but does not provide the covariates or full model specification. Interpretation therefore focuses on the direction and uncertainty of the reported group difference, while recognizing that the details behind the model are not reported in the registry record.

The endpoint can address whether the measured forearm response changed differently across randomized groups during the treatment period. It cannot, on its own, establish whether a difference corresponds to a clinical benefit or persists beyond the measurement period.

7. Results Posted in the Registry

• Lira 1.8: mean 4.24 versus -3.19 on control; difference 7.43 (95% CI 0.07 to 14.79), standardized effect d = 0.72; z-test p = 0.048.
• Glimepiride: mean 2.16 versus -3.19 on control; difference 5.35 (95% CI -2.04 to 12.74), standardized effect d = 0.52; z-test p = 0.156.

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 Sodium Nitroprusside (SNP)-Mediated Forearm Blood Flow (FBF)

• 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:
  • Lira 1.8: mean 3.46 versus -1.04 on control; difference 4.50 (95% CI -3.23 to 12.23), standardized effect d = 0.42; z-test p = 0.254.
  • Glimepiride: mean 2.75 versus -1.04 on control; difference 3.79 (95% CI -3.93 to 11.51), standardized effect d = 0.35; z-test p = 0.336.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Lira 1.8 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 Glimepiride and the control. The interval gives the range of effects that remain compatible with the data.

Change in HbA1c (Glycosylated Haemoglobin A1c)

• 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:
  • Lira 1.8: mean -0.63 versus -0.09 on control; difference -0.54 (95% CI -0.85 to -0.22), standardized effect d = -1.21; z-test p = 0.001.
  • Glimepiride: mean -0.55 versus -0.09 on control; difference -0.46 (95% CI -0.78 to -0.13), standardized effect d = -1.02; z-test p = 0.005.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Lira 1.8 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Glimepiride than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change in Fasting Plasma Glucose (FPG)

• 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:
  • Lira 1.8: mean -41.67 versus -6.07 on control; difference -35.60 (95% CI -46.32 to -24.89), standardized effect d = -2.39; z-test p = <0.001.
  • Glimepiride: mean -32.02 versus -6.07 on control; difference -25.95 (95% CI -36.76 to -15.15), standardized effect d = -1.73; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Lira 1.8 than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Glimepiride than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry identifies secondary outcomes covering sodium nitroprusside-mediated forearm blood flow, HbA1c, fasting plasma glucose, postprandial glucose, body weight, and lipid measures. Numerical results included in the record for sodium nitroprusside-mediated forearm blood flow, HbA1c, and fasting plasma glucose show that the secondary outcomes do not all provide the same kind of evidence. The reported estimates and their uncertainty should be considered outcome by outcome rather than treated as one overall result.

For the posted numerical secondary results, the sponsor’s liraglutide-versus-placebo ANCOVA estimate for sodium nitroprusside-mediated flow has a 95% confidence interval spanning zero. The reported HbA1c contrast has an interval that does not span zero, while the fasting plasma glucose comparison also has a reported interval that does not span zero. These outcomes measure different features and are not interchangeable with the primary endothelial-function endpoint. They cannot establish the primary result or turn it into evidence about clinical outcomes.

The registry record identifies 13 secondary outcome measures. Numerical results for the remaining listed measures are not reported in the registry record. As a result, the overall pattern across all secondary outcomes cannot be fully assessed from the available result details.

Unadjusted secondary comparisons carry less weight because multiple outcomes and group comparisons create more opportunities for chance findings. The registry record does not report a multiplicity adjustment or a prespecified hierarchy for interpreting secondary outcomes. The secondary results are therefore best viewed as supportive or exploratory evidence, with attention to their estimates, intervals, and distinct outcome definitions. They should not displace the sponsor-reported primary analysis.

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

• Change in Sodium Nitroprusside (SNP)-Mediated Forearm Blood Flow (FBF)
• Change in HbA1c (Glycosylated Haemoglobin A1c)
• Change in Fasting Plasma Glucose (FPG)
• Change in Mean Postprandial Glucose (PPG) Based on Self-measured 7-point Plasma Glucose Profiles
• Change in Body Weight
• Fasting Lipid Profile - Change in Total Cholesterol (TC)
• Fasting Lipid Profile - Change in LDL-C
• Fasting Lipid Profile - Change in HDL-C

9. Statistical Interpretation

10. Statistical Methods Explained

The reported primary comparisons use ANCOVA and least-squares means. ANCOVA is a general statistical method for comparing groups while accounting for specified covariates in a model. In a randomized trial, this approach can estimate a treatment-group contrast while adjusting for variables included in the analysis. The registry record does not identify the covariates, describe the model specification, or explain how missing measurements were handled beyond defining the full analysis set.

What does a least-squares mean represent?

A least-squares mean is a model-based group estimate. It can differ from a simple arithmetic mean because it reflects the fitted analysis model and any adjustments included in that model. The registered primary outcome uses least-squares means, and the sponsor’s reported group differences are based on ANCOVA. This is why a recalculation from posted group summaries should be treated as an approximation rather than a replacement for the sponsor’s model-based estimate.

Why do the recalculated results differ?

The recalculated comparisons use unadjusted summary statistics and approximate standard deviations derived from the reported standard errors. They do not reproduce the sponsor’s ANCOVA model. A difference between these approaches can arise because the model may use covariate adjustment and because the recalculation relies on summary values rather than participant-level observations. The registry record does not report enough model detail to reproduce the ANCOVA independently. In this trial, the primary comparison also has a discrepancy between the recalculated result and the sponsor-reported result, so the sponsor’s own analysis takes precedence.

What does a confidence interval convey?

A confidence interval expresses uncertainty around an estimated group difference under the analysis assumptions. A wider interval indicates less precision, while an interval spanning zero is compatible with no difference and with differences in either direction covered by the interval. It does not assign a probability that the true value lies within the particular interval. The primary sponsor-reported interval ranges from -0.164 to 15.025, and includes zero.

What does a p-value convey?

A p-value describes how unusual data at least as inconsistent with a specified null hypothesis would be under the statistical model, if that null hypothesis and the model assumptions held. It is not the probability that the null hypothesis is true, and it does not measure the size or importance of an effect. A result near a conventional threshold should be interpreted alongside the estimate and interval, rather than as a sharp boundary between meaningful and meaningless evidence. The registry reports a primary p-value of 0.055; the simple recalculation gives an unadjusted p-value of 0.048.

Why can small studies produce imprecise estimates?

General statistical explanation: with fewer observations, estimates often vary more from sample to sample, which can produce wider confidence intervals. Precision also depends on the variability of the measured outcome and the analysis design. The primary outcome groups were small, and the sponsor-reported interval spans values on both sides of zero. The uncertainty visible in the interval is more informative than a binary label based only on a p-value threshold.

Why does over-dispersion matter?

General statistical explanation: over-dispersion occurs when observed variability is greater than a model assumes. If a model understates variability, standard errors may be too small and confidence intervals too narrow. The primary endpoint is continuous, and the registry reports standard errors, but it does not report a diagnostic assessment of over-dispersion or any correction for it. There is therefore no basis in the registry record to say whether over-dispersion was assessed or affected the analysis.

The registry identifies the primary analysis population as randomized participants with end-of-trial data available. It does not describe the handling of partial observations, departures from treatment, or sensitivity analyses. These details matter because analysis populations and missing-data methods can influence estimates. Their absence from the registry record limits independent appraisal of the statistical plan.

11. Confidence Intervals and Precision

The sponsor-reported primary estimate is a least-squares mean difference of 7.43 mL/100 mL/min for liraglutide compared with placebo. Its 95% confidence interval extends from -0.164 to 15.025. The interval includes zero, so the data are compatible with no group difference as well as with a range of positive and negative values. Its width signals considerable uncertainty about the size and direction of the underlying difference.

The interval should not be read as a range containing every plausible value with certainty, nor as a probability statement about the true effect. In general, a confidence interval is a measure of sampling uncertainty under the model assumptions. The precision conveyed by the interval depends on the data and the analysis; the registry does not report enough detail to independently verify all those assumptions.

The recalculated unadjusted estimate is 7.431, with an interval from 0.068 to 14.79. That interval does not match the sponsor-reported interval. Because the sponsor’s result comes from the reported ANCOVA analysis, it takes precedence over the approximate recalculation. The difference in intervals is important: it shows that conclusions about whether an interval crosses zero can depend on the analysis method, especially when the estimates are uncertain.

The comparison with glimepiride is also imprecise: its sponsor-reported interval ranges from -2.323 to 13.024. The small outcome-specific groups provide context for the uncertainty, but confidence intervals are the direct description of the range of estimates compatible with the analysis. Neither comparison demonstrates that the treatments are equivalent. The registry record does not report a prespecified equivalence margin or a non-inferiority margin.

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 events. They are illustrations based on the observed effect, rather than the trial’s original design assumptions. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set to the stated fraction of the observed effect. The original sample-size justification and design assumptions are not reported in the registry record.

The 80% power column gives the number of participants per arm that the planning calculation estimates would be needed to have an 80% chance of detecting the specified effect under those assumptions, if that effect were the true effect. The 90% power column gives the corresponding planning figure for a 90% chance. These are design calculations, not guarantees about a future study or findings from this trial.

The rows scale the assumed effect to the full observed effect, 75% of the observed effect, and 50% of the observed effect. Smaller effects are harder to distinguish from random variation, so the planning illustration requires more participants per arm as the assumed effect becomes smaller. For example, the primary liraglutide comparison lists 30 participants per arm for 80% power when planning for 100% of the observed effect, and 120 per arm when planning for 50% of the observed effect.

These figures are not observed power. They are planning illustrations calculated from the observed effect and should not be used as evidence that the trial had a particular probability of success after the results were known. The registry record does not report the sponsor’s original sample-size calculation, so the illustrative values should not be mistaken for the trial’s recruitment target or its prespecified design basis.

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 = 7.431; pooled standard deviation σ = 10.258.
2. n = 2 × (1.96 + 0.842)² × 10.258² / 7.431² = 29.9, rounded up to 30 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 <- 7.431                      # observed difference in means
sigma <- 10.257782564612                     # 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(620282)
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 = 30 (80% power), 41 (90% power)
 75% of observed effect: n per arm = 54 (80% power), 72 (90% power)
 50% of observed effect: n per arm = 120 (80% power), 161 (90% power)
power.t.test: 30.9 
Simulated power at n = 30 per arm: 0.785 (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 sponsor-reported primary ANCOVA result is a least-squares mean difference of 7.43 mL/100 mL/min for liraglutide versus placebo, with a 95% confidence interval from -0.164 to 15.025 and a reported p-value of 0.055. This is the trial’s own reported analysis and takes precedence over the simple unadjusted recalculation.

The recalculation uses only posted summary statistics, including group estimates and standard errors. It gives an estimated difference of 7.431, a confidence interval from 0.068 to 14.79, and an unadjusted p-value of 0.048. It is not the same as reproducing the ANCOVA. The registry record does not report all model details needed to reconstruct the sponsor’s analysis from participant-level data.

The recalculated interval and p-value lead to a different threshold-based impression from the sponsor’s reported analysis. That difference should not be resolved by selecting whichever result appears more favorable. The primary interpretation should follow the sponsor’s analysis, while the recalculation is useful as a transparent check based on limited summary information. The discrepancy also underscores that model specification and covariate adjustment can matter when estimates are uncertain.

For the other reported comparisons, the sponsor’s analyses likewise provide the trial’s official model-based results. Recalculated values are approximate and unadjusted. They can help readers understand the scale of the group contrasts, but cannot substitute for an analysis that reflects the trial’s full model and analysis plan.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary endpoint and multiple secondary outcomes, alongside comparisons involving three treatment groups. Considering many outcomes and contrasts increases the chance that at least one result may appear noteworthy by chance alone. General statistical practice may address this issue through prespecified testing hierarchies or multiplicity adjustments, but the registry record does not report whether either approach was used for these results.

The secondary comparisons should therefore be interpreted with caution, particularly where attention is drawn to an isolated p-value. The posted record does not state which secondary analyses were confirmatory, whether there was a testing sequence, or whether adjustment was made across outcomes or comparisons. Without that information, secondary findings should not be treated as if each were a separately prespecified primary test.

The registry describes the primary analysis population as the ANCOVA full analysis set, including randomized participants for whom end-of-trial data points could be collected. This definition indicates that availability of end-of-trial data was required for inclusion in that analysis. The record does not explain the extent or reasons for missing data, the handling of participants without end-of-trial measurements, or whether sensitivity analyses were conducted. Those details are not reported in the registry record.

The registry also does not report an intention-to-treat analysis definition beyond the full analysis set description, the handling of treatment discontinuation, protocol deviations, or the exact model covariates. Interim analyses and stopping rules are not reported in the registry record. These omissions do not invalidate the posted estimates, but they limit assessment of how fully the analyses followed a prespecified plan and how sensitive the results may be to analytic choices.

16. 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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: prostate cancer (6.2%).

The serious adverse event counts were 0 of 16 participants in the liraglutide group, 1 of 16 in the placebo group, and 0 of 17 in the glimepiride group. The registry also lists prostate cancer as a top serious adverse event term at 6.2%. The record does not specify the treatment group associated with that term in the registry record, so it should not be attributed to an arm.

Other adverse events were reported for 11 of 16 participants receiving liraglutide, 9 of 16 receiving placebo, and 5 of 17 receiving glimepiride. These counts are descriptive. They do not establish that one treatment caused more events than another, and the trial’s small groups limit the strength of comparisons. The registry record does not provide event-level details, severity breakdowns, or a fuller account of how events were collected.

Deaths are not reported in the registry record. The serious event figures should be read separately from the primary efficacy endpoint and should not be used to infer overall safety beyond the events and counts recorded.

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

The primary endpoint estimates a short-term difference in change in acetylcholine-mediated forearm blood flow between liraglutide and placebo. The sponsor-reported estimate is positive, but its 95% confidence interval includes zero and is wide enough to encompass materially different possibilities. The result therefore leaves substantial uncertainty about the size and direction of the underlying difference.

The endpoint is a physiological measure of endothelial function, not a clinical outcome. The trial does not establish from this measurement alone whether any difference affects symptoms, complications, or longer-term health. The registry record reports a 12-week treatment period and does not report longer-term follow-up for this outcome. The result should not be generalized beyond the measured endpoint and population described in the record.

The inclusion of glimepiride provides another arm for comparison, but its reported primary comparison is also uncertain. The study’s size and the breadth of the confidence intervals mean that absence of a clear difference is not the same as demonstrating equivalence. The registry record does not report an equivalence or non-inferiority design or a margin for such a conclusion.

Secondary outcomes describe other metabolic and vascular measures. Some sponsor-reported secondary contrasts have confidence intervals that exclude zero, while others do not. These findings are distinct from the primary question, and multiple secondary comparisons warrant caution, especially because the registry record does not report multiplicity procedures. Overall, the posted results offer estimates of short-term changes with varying precision. They do not justify a broad conclusion about treatment effects beyond those measures and analyses.

18. Why This Trial Matters Statistically

This trial illustrates the importance of separating an estimated effect from the certainty around it. The primary point estimate is positive, but the sponsor-reported confidence interval includes zero and spans a broad range. Reporting the estimate alone would conceal that uncertainty; reporting only a threshold-based p-value would also obscure the range of values compatible with the data.

It also shows why an unadjusted recalculation should not be confused with the trial’s own analysis. The recalculated primary result differs from the reported ANCOVA result, including in whether the confidence interval includes zero. The sponsor’s analysis takes precedence because it is the trial’s reported model-based result, while the recalculation is an approximation from summary statistics. This is a practical reminder that model details and analysis populations matter.

The study also highlights the distinction between a physiological endpoint and a clinical outcome. Forearm blood flow can address a focused question about vascular response under specified measurement conditions, but it does not directly answer questions about longer-term clinical outcomes. Secondary measures add context but do not change the definition of the primary question.

Finally, the registry record leaves important analysis details unreported, including the full model specification, the original sample-size rationale, and multiplicity procedures. These gaps limit the ability to reconstruct the intended statistical plan. The trial is therefore useful for understanding how endpoint definition, analysis choice, precision, and reporting completeness jointly shape interpretation.

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 primary outcome is based on a short-term physiological measurement, assessed from week 0 to week 12. The registry record does not report longer-term follow-up for this endpoint or clinical outcomes that would establish whether the measured response relates to later health outcomes.

The primary analysis groups were small, and the sponsor-reported confidence interval is broad and includes zero. This limits precision. The trial also had an open-label glimepiride arm, whereas liraglutide and placebo were described in a double-blind comparison. The registry record does not provide additional information about masking of outcome assessors or procedures in the open-label arm.

The primary result has a discrepancy between the sponsor-reported ANCOVA analysis and the simple unadjusted recalculation. The sponsor’s analysis takes precedence, but the registry record does not report the model covariates or full specification needed for independent reproduction. The original sample-size justification, planned interim analyses, and multiplicity approach are also not reported in the registry record.

The record defines the full analysis set as randomized participants for whom end-of-trial data could be collected, but does not describe the extent or reasons for missing outcome data or sensitivity analyses. Numerical results for some listed secondary outcomes are not reported in the registry record. Together, these limitations constrain evaluation of precision, robustness, and the broader consistency of the outcome findings.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: The Effect of Liraglutide on Endothelial Function in Subjects With Type 2 Diabetes Mellitus — NCT00620282.
• Registry record last updated 2017-03-08; status last verified 2017-01.
• Results first posted 2011-06-15.
• 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, randomized, double-blind, parallel-group, single-center Phase 3 trial with 49 enrolled participants. It compared daily subcutaneous liraglutide with placebo over 12 weeks and included an open-label, daily oral glimepiride arm.

The primary endpoint was change in acetylcholine-mediated forearm blood flow from week 0 to week 12. The sponsor-reported ANCOVA comparison of liraglutide with placebo was 7.43 mL/100 mL/min, with a 95% confidence interval from -0.164 to 15.025. The interval includes zero, and the result is uncertain. A recalculation from posted summary statistics differs; the sponsor’s analysis takes precedence.

The registry lists multiple secondary outcomes and reports adverse event counts. Important details, including the original sample-size rationale, full statistical model specification, multiplicity procedures, and missing-data handling, are not reported in the registry record.