Effects of Glutamine on GLP-1 and Insulin Secretion in Man: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effects of Glutamine on GLP-1 and Insulin Secretion in Man (NCT00673894), a randomized na study. The primary outcome is Postprandial Glucose Area Under the Curve (AUC).

2. Clinical Question

3. Trial Design

The registry classifies this as a randomized, quadruple-masked crossover study and lists the status as completed. A crossover design is one in which participants receive more than one study condition in sequence, so comparisons can potentially use information from the same participant under each condition. This can account for some between-person variability, but the interpretation depends on how treatment order, period effects, and any carryover between conditions are handled.

The intervention descriptions identify glutamine plus sitagliptin and glutamine plus placebo. Both conditions include glutamine 30 g/d, with 15 g taken with breakfast and dinner. The primary aim describes sitagliptin 100 mg/d or placebo for 4 weeks. Because glutamine is present in both listed conditions, the randomized contrast described by the registry is the addition of sitagliptin rather than a test of glutamine against no glutamine.

Quadruple masking indicates that the registry recorded a masking level, but the registry record does not specify which participant, clinician, investigator, or assessor roles were masked. The sequence allocation, period schedule, washout arrangements, and handling of potential carryover are not reported in the registry record. The registry lists enrollment of 22, while the outcome summaries list 13 participants for each condition. How those counts arise, and whether the posted estimates retain the paired structure, is not reported in the registry record.

The primary outcome is a continuous measure, summarized by means and standard deviations. The registry lists fructosamine as the secondary outcome. It does not report a statistical analysis for either endpoint, and it lists no reported analyses. Consequently, the posted summaries can describe the observed values, but they do not by themselves establish how the original crossover analysis was planned or performed.

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: 15 of 22 participants were randomized. Of those not randomized, 7 did not meet the inclusion criteria

First Intervention 4 Weeks

Reasons for not completing this period:

Washout 4-6 Weeks

Second Intervention 4 Weeks

Analysis population for the primary outcome, as defined in the registry: The primary aim of this randomized crossover study was to determine the glycemic effect of 4 weeks of glutamine (15 bd) supplementation with sitagliptin (100 mg/d) or placebo in type 2 diabetes patients treated with metformin.

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: Participants who were randomized to receive either sitagliptin 100 mg tablet or placebo tablet (matching sitagliptin 100 mg)

6. Primary Endpoint

The registry lists the primary outcome as Postprandial Glucose Area Under the Curve (AUC), measured over 0 to 180 minutes.

The primary endpoint is postprandial glucose area under the curve (AUC) following a meal challenge, measured over 0 to 180 minutes and expressed in mmol/L*t. AUC combines glucose measurements over the stated period into one summary of the post-meal glucose profile. It therefore reflects both the level of glucose and its pattern over time, rather than representing only a single measurement at one time point.

In general, an AUC can be useful when the research question concerns the overall response across a defined observation period. It can reduce a series of repeated measurements to a single continuous outcome for comparison, although the resulting value does not show whether differences arose early or late in the observation period. The registry description calls this the AUC of postprandial glucose following a meal challenge.

The endpoint is relevant to the stated glycemic question because it summarizes post-meal glucose during the period being studied. It does not, on its own, describe longer-term glucose control or establish which part of the glucose profile contributed most to the summary. The registry record does not describe the measurement schedule within the 0 to 180 minutes, the AUC calculation method, or the statistical model used to compare conditions.

7. Results Posted in the Registry

• Glutamine+Sitagliptin: mean 1,341 versus 1,463 on control; difference -122.00 (95% CI -259.99 to 15.99), standardized effect d = -0.68; z-test p = 0.083.

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.

Fructosamine

• 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:
  • Glutamine+Sitagliptin: mean 244.00 versus 240.00 on control; difference 4.00 (95% CI -23.62 to 31.62), standardized effect d = 0.11; z-test p = 0.777.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Glutamine+Sitagliptin and the control. The interval gives the range of effects that remain compatible with the data.

Fructosamine is the sole secondary outcome listed in the registry. The posted secondary comparison does not supply a clear corroborating signal that resolves the uncertainty around the primary glucose AUC comparison. The outcomes measure related but distinct aspects of glycemia: the primary endpoint summarizes the response following a meal challenge, while fructosamine is reported at 4 weeks. Agreement or disagreement between these endpoints should not be treated as a direct replication because their measurement windows and scales differ.

The secondary result is unadjusted, and the registry record does not say whether the endpoint or its analysis was prespecified in a statistical analysis plan. When multiple outcomes are examined, the chance of finding an apparently notable result by chance can rise. Adjustment procedures, hierarchical testing, or a clearly defined exploratory role can address how multiple comparisons are interpreted, but the registry does not report whether any such approach was used.

For that reason, the secondary result carries less weight as confirmatory evidence than a prespecified primary analysis would. It can describe the posted pattern and may help frame questions for further research, but it should not be used alone to declare that the primary finding is supported or contradicted. The record lists no reported analyses, which leaves unclear how the secondary endpoint was incorporated into the investigators' inferential plan.

Overall, the listed endpoint results do not establish a consistent, precise treatment contrast across measures. This is a statement about the degree and limits of the posted evidence, not a claim that the interventions do or do not affect either outcome. The absence of a reported multiplicity strategy and crossover analysis details makes cautious interpretation especially important.

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

• Fructosamine

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean difference represent?

For a continuous outcome, a mean is the arithmetic average of the reported measurements. A mean difference expresses the contrast between the average in one condition and the average in its comparator, using the outcome's original measurement scale. In this study, the posted primary comparison is the mean postprandial glucose AUC in the glutamine-plus-sitagliptin condition relative to the glutamine-plus-placebo condition. A negative estimate indicates that the first condition's reported mean is lower than the comparator's mean. The interpretation depends on the direction in which the contrast is defined, so the comparison labels matter.

The standard deviation is a measure of how spread out individual measurements are around the mean. It is not a confidence interval and does not express the precision of the estimated difference. The posted standard deviations describe variability in the condition-level outcome summaries. They do not reveal the within-participant correlation between crossover measurements, which can be important for estimating uncertainty in a paired comparison.

Why does the crossover design matter?

In general, crossover designs compare conditions within the same participants. This can be efficient because each participant can act as their own control, reducing the influence of characteristics that differ between people but remain relatively stable during the study. The analysis must nevertheless account for the pairing, and it may need to address treatment order, period effects, or carryover. A condition's outcome can depend not only on the treatment received but also on when it was received or what came before it.

The registry record classifies this trial as crossover, but does not report the treatment sequence, washout arrangements, period-specific outcome data, or the model used. It also does not state whether the posted comparison is paired or otherwise adjusted for the crossover structure. The posted summaries list 13 participants per condition; the registry lists enrollment of 22. The record does not explain the relationship between these counts. Without those details, readers cannot assess whether the comparison's uncertainty reflects the intended within-participant design.

How should the confidence interval and p-value be read?

In general, a confidence interval gives a range of values compatible with the data and the statistical procedure used, subject to that procedure's assumptions. A narrower interval indicates greater precision; a wider interval indicates less precision. It is not a range that contains a fixed proportion of individual participant measurements. Here, the primary interval extends from -260 to 15.99 and includes zero, indicating that the posted data do not pin down the direction of the difference precisely.

A p-value measures how unusual the observed data, or data more extreme, would be under a specified null hypothesis and analysis model. Its interpretation relies on the analysis assumptions. It does not measure the size or practical importance of the difference and is not a probability that the null hypothesis is true. The registry gives an unadjusted p-value for the comparison but does not report the model or analysis plan. It should therefore be read as a result of the posted comparison, not as a complete account of the trial's statistical evidence.

What does an unadjusted result imply?

An unadjusted comparison is reported without an adjustment for other analyses or covariates. Such a comparison may be easy to interpret, but it may not correspond to a prespecified primary model, and multiple testing can increase the chance of at least one apparently notable finding when many outcomes or comparisons are examined. The registry lists a primary endpoint and a secondary endpoint, but does not report whether an adjustment for multiplicity was planned or used. It also lists no reported analyses. The posted p-values consequently cannot establish whether they match the original analysis plan.

There are further modeling questions for a crossover trial. An analysis could include participant-level pairing, treatment condition, period, and sequence, depending on the design and the prespecified approach. These are general considerations, not claims about the analysis used in this trial. The registry record does not report the model, assumptions, treatment sequence, or period effects. It is therefore not possible to verify from the registry record whether these features were included.

What can the summaries establish?

Means and standard deviations provide descriptive information about the posted outcome distributions, while a mean difference, confidence interval, and p-value provide an inferential comparison under some analysis assumptions. Those summaries do not reveal the distribution of individual observations, missing measurements, protocol deviations, or whether every participant contributed data to both conditions. The registry record does not report these details. General statistical interpretation should distinguish what the summaries directly state from what would require access to a fuller analysis report.

The registry also does not report a statistical analysis plan, sample-size justification, interim analyses, or an analysis population definition. In general, a prespecified plan helps readers distinguish planned tests from choices made after observing results. Its absence from the registry record does not prove that no plan existed; it means the record does not describe one. The posted results can be interpreted descriptively, while important aspects of their inferential basis remain undocumented.

11. Confidence Intervals and Precision

The primary mean difference is -122, with a 95% confidence interval from -260 to 15.99. Because the interval spans zero, the posted estimate does not determine whether the average AUC is lower or higher in the sitagliptin condition. The interval also covers a range of possible differences, so the estimate is imprecise rather than a sharply defined effect. The unadjusted p-value is 0.083, which is consistent with uncertainty and should not be treated as a measure of effect size.

Precision depends on the amount of information in the comparison and on variability. The primary condition summaries report 13 participants each and standard deviations of 180 and 179. In a crossover design, the relation between each participant's measurements in the different conditions can also affect precision. That within-participant relation is not reported in the registry record, and the record does not identify whether the posted interval accounts for it.

A confidence interval is not a guarantee that the true effect lies within its endpoints. In general, it is a range generated by a method that has stated coverage properties when its assumptions hold. Unreported details of the crossover analysis limit assessment of those assumptions. The interval should therefore be read as a description of uncertainty under the posted comparison, not as a definitive bound on all plausible effects.

The secondary endpoint also has an interval that extends across zero. Together, the posted results do not yield a precise account of the size or direction of differences across the outcomes. The registry record does not report additional analyses that could clarify the precision or robustness of these estimates.

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 figures are participants per arm, not total event counts. The registry's planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. These are planning illustrations based on the posted effect, not the trial's original design assumptions; the original design assumptions are not reported in the registry record.

The 80% power column gives the number of participants per arm that a planning calculation estimates would be needed to have an 80% chance of detecting the chosen effect under the stated assumptions, if that effect and those assumptions applied. The 90% power column expresses the corresponding planning target for a 90% chance. Higher planned power generally requires more participants for the same effect and assumptions.

The rows describe planning for the full observed effect and for smaller fractions of that effect. Smaller effects need more participants to distinguish them from random variation with the same planned power. The figures should not be interpreted as evidence that the completed trial had a particular probability of finding a result. This is not observed power; it is a forward-looking planning illustration using the observed estimate as its starting point.

Because the study is described as crossover, the equal-allocation, two-arm planning setup should not be taken as a complete representation of the trial's original design or analysis. The registry does not report the original sample-size justification or whether planning accounted for within-participant pairing. The figures are useful for illustrating how assumptions about effect size and planned power change a sample-size target, not for recovering the investigators' original rationale.

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 = -122.000; pooled standard deviation σ = 179.501.
2. n = 2 × (1.96 + 0.842)² × 179.501² / -122.000² = 34.0, rounded up to 34 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 <- -122                      # observed difference in means
sigma <- 179.500696377479                     # 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(673894)
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 = 34 (80% power), 46 (90% power)
 75% of observed effect: n per arm = 61 (80% power), 81 (90% power)
 50% of observed effect: n per arm = 136 (80% power), 182 (90% power)
power.t.test: 35 
Simulated power at n = 34 per arm: 0.784 (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. Multiplicity, Missing Data and Analysis Populations

The registry identifies postprandial glucose AUC as the primary outcome and fructosamine as a secondary outcome. It does not report a statistical analysis plan, a hierarchy of hypotheses, or a procedure for adjusting for multiple outcomes or comparisons. The presence of a named primary endpoint helps distinguish its role in the stated research question, but does not establish that its analysis was prespecified or that other analyses were controlled for.

In general, examining multiple outcomes or analyses creates more opportunities for a result to appear notable by chance. Multiplicity methods can account for that, or an analysis plan can specify which outcome is confirmatory and which are exploratory. Without a reported approach, the unadjusted secondary result should be interpreted cautiously, and the primary p-value should not be assumed to account for other tests that may have been conducted. The registry lists no reported analyses; it does not describe whether other analyses were performed outside the record.

Missing-data handling is also not reported in the registry record. The posted summaries do not state whether there were missing outcome measurements, how missing values were handled, or whether participants were excluded from any analysis. The record gives enrollment of 22 and condition-level outcome summaries of 13 participants each, but does not explain the difference in counts. It is not possible to infer from these figures alone whether the counts represent a subset, paired completers, or another reporting convention.

The analysis population is not described. The registry does not say whether participants were analyzed according to randomized assignment, treatment received, completion of both periods, or another rule. In crossover studies, exclusions and incomplete periods can change which within-participant comparisons are available. The record also does not report protocol deviations or sensitivity analyses.

These omissions do not establish that the original investigators lacked an analysis plan or did not address missing data. They mean that those methods are not reported in the registry record, limiting independent assessment of the posted comparisons.

15. 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 registry reports zero serious adverse events among 13 participants in the sitagliptin group and zero among 13 participants in the placebo group. It also reports zero other adverse events in both groups, and zero deaths in both groups. These are the event counts recorded for the listed groups; they do not describe the nature, timing, or severity of any events beyond the registry's serious and other adverse-event categories.

Zero reported events in these group summaries should not be read as proof that no adverse events could occur. In general, event counts observed in a study provide limited information about uncommon events, especially when the number of participants is small. The registry does not provide additional detail about adverse-event collection, definitions, follow-up duration, or whether the event summaries are organized by participant or treatment period in the crossover design.

The safety figures are descriptive registry results and do not establish comparative safety. Their interpretation is limited by the number of participants represented and the reporting detail available. They should be considered alongside the trial's design and the lack of further safety-analysis information in the registry record.

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

The registry results describe a randomized, quadruple-masked crossover comparison of glutamine with sitagliptin against glutamine with placebo in participants with type 2 diabetes. The posted primary comparison points toward a lower mean postprandial glucose AUC in the sitagliptin condition, but its confidence interval includes zero and the unadjusted p-value is 0.083. The data therefore leave substantial uncertainty about the size and direction of the contrast. The secondary result does not remove that uncertainty.

This does not establish that sitagliptin changes the measured outcome, nor does it establish that it has no effect. A nonsignificant p-value is not proof of no difference, and a point estimate alone does not establish a clinically important effect. The registry record does not report a threshold for clinical importance or enough detail to assess the crossover analysis independently.

The comparison also cannot isolate the effect of glutamine, because both listed conditions include glutamine. It addresses sitagliptin versus placebo when given with glutamine. The results therefore should not be described as a test of glutamine versus no glutamine. The registry describes a 4-week treatment period in the primary aim, and the secondary endpoint is reported at 4 weeks; no longer-term outcomes are listed in the posted results.

General interpretation of a clinical trial requires attention to study design, endpoint definition, analysis methods, uncertainty, and the population studied. Here, important statistical details—including the paired crossover analysis, treatment sequence, missing-data handling, and multiplicity approach—are not reported in the registry record. The findings are best read as limited posted evidence about the stated comparison, rather than as a definitive treatment conclusion or a basis for medical advice.

17. Why This Trial Matters Statistically

This trial is statistically interesting because its crossover classification changes what a treatment comparison can usefully estimate. When the same participants receive both conditions, an analysis can use within-participant contrasts and account for stable differences among participants. That potential advantage depends on retaining and analyzing the pairing appropriately. The registry record gives condition-level summaries but does not report whether the comparison accounts for that structure.

The result also illustrates why an estimate should be read together with its uncertainty. The primary point estimate has a direction, but the confidence interval crosses zero and reaches from a substantial negative contrast to a small positive one. The unadjusted p-value alone cannot describe that range or establish clinical importance. Reporting means, standard deviations, the estimated contrast, and its interval makes the uncertainty more visible than a binary significant-or-not label.

There is a further distinction between the research question and what the randomized contrast can answer. Both conditions include glutamine, so the comparison concerns sitagliptin versus placebo against a shared glutamine background. This design does not directly estimate glutamine's effect relative to no glutamine. Reading the intervention descriptions carefully prevents attributing the comparison to the wrong component.

Finally, the gap between enrollment and the outcome counts underscores the value of transparent participant flow and analysis-population reporting. The registry does not explain that gap or report missing-data methods. This does not invalidate the posted summaries, but it limits assessment of how representative they are of the enrolled participants and how the crossover data were analyzed.

18. 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 the registry record constrain interpretation. Although the design is labeled crossover, the record does not report treatment sequence, period-level results, washout arrangements, or potential carryover handling. These are relevant because outcomes in one period may be related to the condition received earlier, and treatment effects can differ by period. The posted group summaries do not make clear whether the primary comparison uses paired observations.

Enrollment is listed as 22, but the primary endpoint summaries list 13 participants for each condition. The registry does not explain the relationship between those counts, whether all enrolled participants completed both conditions, or how missing outcome measurements were handled. Without participant flow and analysis-population definitions, the reader cannot determine how many complete within-participant comparisons informed the estimate.

The outcome description gives the AUC period and unit but does not report the measurement schedule or calculation method. The statistical model, assumptions, and any adjustments are also not reported. There is no reported statistical analysis plan, sample-size justification, interim-analysis information, or multiplicity strategy. These absences limit evaluation of prespecification and the basis for the posted uncertainty estimates.

The study's posted summaries are also limited in the scope of outcomes they cover: one primary glycemic measure and one secondary measure are listed. The registry record does not establish longer-term effects, and the serious and other adverse-event summaries contain no events in the listed groups but provide little additional detail about collection or follow-up. These are limitations of the available record, not evidence that unreported procedures or information did not exist.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Effects of Glutamine on GLP-1 and Insulin Secretion in Man — NCT00673894.
• Registry record last updated 2019-05-13; status last verified 2019-02.
• Results first posted 2019-05-13.
• 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.

22. Record Summary

The registry identifies NCT00673894 as a completed, randomized, quadruple-masked crossover study of glutamine with sitagliptin or placebo in participants with type 2 diabetes. Enrollment was 22. The primary outcome was postprandial glucose AUC over 0 to 180 minutes; fructosamine was listed as a secondary outcome measured at 4 weeks.

The primary posted comparison has a mean difference of -122, a 95% confidence interval from -260 to 15.99, and an unadjusted p-value of 0.083. The registry also posts condition-level means and standard deviations for both endpoints. It lists zero serious adverse events, zero other adverse events, and zero deaths in each group.

The registry record does not report the crossover analysis model, missing-data methods, analysis populations, or multiplicity approach. The posted summaries therefore describe the available comparison but leave important aspects of its inferential basis unresolved.