Glutathione Metabolism in Adolescents With Type 1 Diabetes - Study A: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Glutathione Metabolism in Adolescents With Type 1 Diabetes - Study A (NCT00858897), a randomized na study. The primary outcome is Glutathione Concentration.

2. Clinical Question

The question concerns a short-term metabolic response under two controlled glucose conditions. The posted outcome is glutathione concentration; it is not a clinical event or a measure of longer-term diabetes outcomes. The record does not report a separate primary question about safety or clinical benefit. Its stated purpose is to improve understanding of how diabetes affects metabolism, with a focus on glutathione production and use.

3. Trial Design

The registry record identifies this as a randomized, unmasked, crossover study. Enrollment was 10, and the record is marked completed. It lists the study start as 2007-06 and primary completion as 2008-02. The phase is recorded as NA. The sponsor is Nemours Children's Clinic.

In a crossover design, the same participant receives each study condition, so each participant can contribute information under both conditions. In this study, the outcome description states that each of the 10 subjects received two 5-hour intravenous infusions of L-[3,3-2H2]cysteine on separate days. Blood glucose had been maintained overnight at either normoglycemia or hyperglycemia using intravenous insulin infusion. The intervention descriptions identify cysteine isotope infusion at normoglycemia versus hyperglycemia, and regular insulin is also listed as an intervention.

The conditions were defined as normoglycemia at 80-140 mg/dL and hyperglycemia at 200-250 mg/dL. The study is described as taking place in the postabsorptive state. The primary outcome timeframe is up to 30 minutes after the 5-hour infusion on Day 1, identified as the first intervention, and up to 30 minutes after the 5-hour infusion on Day 14, identified as the second intervention.

The record says allocation was randomized but does not report the randomization sequence method, how assignment order was concealed, or whether treatment order was balanced. Masking is listed as none. Details about a washout period, adherence, participant flow, and withdrawals are not reported in the registry record. The record also does not report the original sample-size rationale or the planned statistical analysis for the crossover structure.

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: Each of the 10 Subjects received two 5-hour intravenous infusions of L-\[3,3-2H2\]cysteine in the postabsorptive state on 2 separate days after blood glucose had been maintained overnight at normoglycemia or hyperglycemia, using intravenous insulin infusion. The order of the normo- and hyper-glycemia study days was randomized.

First Intervention (1 Day)

Washout (~9 Days)

2nd Intervention (1 Day)

Analysis population for the primary outcome, as defined in the registry: Each of the 10 Subjects received two 5-hour intravenous infusions of L-\[3,3-2H2\]cysteine in the postabsorptive state on 2 separate days after blood glucose had been maintained overnight at normoglycemia or hyperglycemia, using intravenous insulin infusion.

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 Glutathione Concentration, measured over Up to 30 minutes post- 5 hour infusion on Day 1 (First Intervention) and up to 30 minutes post- 5 hour infusion on Day 14 (Second Intervention).

The primary endpoint is glutathione concentration, a continuous measurement reported in umol/L. The record reports a mean and standard error for each glucose condition. Glutathione is described in the study summary as a small peptide made from glutamate, cysteine, and glycine. It is normally present at high levels in blood and plays a role in the body's defense against oxidative stress.

Concentration is used as an indicator of the amount of glutathione present in blood after each experimental condition. The study summary explains that the amount reflects a balance between glutathione synthesis and use: glutathione is continuously synthesized and broken down. The study is therefore designed to examine whether short-term differences in blood glucose conditions are accompanied by a difference in this concentration measure.

Concentration alone does not identify the underlying rate of synthesis or use. The record describes the infusion of labeled cysteine, but it does not post a separate primary result for synthesis rate, breakdown rate, or use. It lists one primary outcome measure and no posted secondary outcome measures.

The outcome was assessed up to 30 minutes after each 5-hour infusion, on the first and second intervention days. This timing characterizes an acute response following the experimental infusions; it does not describe a long-term measure. Further details about the exact sampling schedule or how repeated samples were combined into the posted outcome are not reported in the registry record.

7. Results Posted in the Registry

• Hyperglycemia (200-250 mg/dL): mean 551.00 versus 541.00 on control; difference 10.00 (95% CI -552.56 to 572.56), standardized effect d = 0.02; z-test p = 0.972.

8. Statistical Interpretation

9. Statistical Methods Explained

The registry record posts group means, standard errors, a mean difference, a confidence interval, and an unadjusted p-value for the primary continuous outcome. It does not describe the analysis model, the statistical test, or a method for handling the repeated measurements inherent in this crossover study. The explanations below are general statistical context, not claims about an unreported protocol.

What does a mean describe?

General: A mean is the arithmetic average of the observed measurements in a group or condition. It summarizes the center of the observed values, but it does not show their full distribution. Participants may have values near the mean or may differ substantially from it. The posted record gives one mean for each glucose condition, but does not provide participant-level values, medians, ranges, or distribution plots in the outcome data.

The posted means are 541.0 umol/L under normoglycemia and 551.0 umol/L under hyperglycemia. Their contrast is reported as a mean difference of 10.0 umol/L, with hyperglycemia compared with normoglycemia. The direction convention matters: a positive estimate means the posted hyperglycemia mean is higher than the normoglycemia mean. The estimate is descriptive and should be read together with its uncertainty.

What does the standard error describe?

General: A standard error describes the uncertainty in an estimated quantity, such as a mean. It is not the same as the spread of individual observations. Standard errors tend to be smaller when estimates are based on more information, although the amount of information also depends on variability and study design.

The registry reports standard errors of 232.0 for normoglycemia and 169.0 for hyperglycemia. It does not report standard deviations as the outcome's dispersion measure; the outcome is designated as a mean with standard error. In a crossover study, an analysis of the difference within each participant can have uncertainty that depends on how strongly the two condition measurements are related. Separate condition standard errors alone do not reveal that relationship.

Why does the crossover structure matter?

General: A crossover design compares each participant with themselves across conditions. This can help distinguish condition-related changes from stable differences between participants. The analysis needs to preserve the pairing. If measurements are treated as if they came from unrelated groups, the estimated uncertainty may not match the uncertainty of a paired comparison.

The record confirms that each participant received both conditions, but it does not report a paired analysis, a model including participant effects, or a period or sequence adjustment. It also does not report the participant-level paired differences. Therefore, the method underlying the posted confidence interval and p-value cannot be evaluated from the registry record alone. The displayed comparison should be understood as the result reported in the registry, with this design-related reporting gap in mind.

What is a confidence interval?

General: A confidence interval gives a range of values reasonably compatible with the observed data under the statistical model and its assumptions. It reflects uncertainty in the estimate, rather than a range containing a specified proportion of individual participants. A wide interval signals limited precision; an interval that includes zero for a difference is compatible with both no difference and differences in either direction.

The posted interval for the mean difference is -552.6 to 572.6 umol/L. It spans zero and is wide in relation to the point estimate of 10.0 umol/L. The data therefore do not tightly constrain the possible condition difference. The interval's interpretation depends on the analysis method, which is not described in the record.

What does a p-value tell us?

General: A p-value measures how unusual the observed data, or data more extreme, would be under a specified null hypothesis and statistical model. It does not quantify the size or clinical importance of an effect, and it is not the probability that the null hypothesis is true. A p-value should be considered alongside the estimated effect, its confidence interval, the design, and the analysis assumptions.

The unadjusted p-value is 0.972. It does not provide evidence of a statistically detectable difference under the reported comparison. It does not demonstrate that the conditions are identical or that a meaningful difference has been excluded. Because the record labels this p-value unadjusted and gives no multiplicity adjustment, no adjusted inference is posted.

General: Over-dispersion means that observed variation is greater than a statistical model expects. When present, it can make standard errors too small and confidence intervals too narrow if the model does not allow for the extra variation. The registry record does not report an over-dispersion assessment or a model specification, so it is not possible to determine whether this issue was relevant to the posted result.

10. Confidence Intervals and Precision

The mean difference is 10.0 umol/L, with a 95% confidence interval from -552.6 to 572.6 umol/L. This interval includes zero and extends to substantial differences in either direction. It is therefore consistent with a small difference, no difference, and larger condition differences. The point estimate alone should not be treated as a precise estimate of the contrast.

General: A confidence interval is a measure of statistical precision under the analysis model. A narrow interval indicates that the data constrain the estimated quantity more closely; a wide interval indicates greater uncertainty. The interval does not describe the range of individual participant values, and it does not guarantee that the true value lies inside it.

Here the interval is wide relative to the reported difference. The standard errors for the two condition means are 232.0 and 169.0. Each condition includes 10 participants, but those observations are repeated measurements from the same participants. In a crossover study, precision for a condition contrast depends in part on the relationship between each participant's measurements across conditions. That within-person information is not reported, and the registry record does not explain whether the analysis used the pairing.

The p-value of 0.972 and the confidence interval address related but distinct aspects of the comparison. The p-value does not show a statistically detectable difference under the posted analysis, while the interval makes clear that the estimate remains imprecise. Neither result establishes equivalence. To support an equivalence conclusion, a study would need an appropriate equivalence question and prespecified margins; these are not reported in the registry record.

11. 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 for 80% power and participants per arm for 90% power. The record'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 the stated fraction of the observed effect. These are planning illustrations based on the observed effect, not the trial's own original design assumptions; those original assumptions are not reported in the registry record.

The 80% power column gives the planned number of participants per arm for a design that would have an 80% chance of detecting the specified effect under the planning assumptions, if that effect were the true one. The 90% column gives the corresponding number for a design with a 90% chance under those assumptions. Power describes a design's operating characteristic before results are observed; it does not measure the probability that the study's conclusion is correct. These figures are not observed power.

The rows describe planning for 100%, 75%, and 50% of the observed effect. As the effect used for planning becomes smaller, more participants are needed to detect it at the same power and significance level. This relationship is expected because smaller differences are harder to distinguish from variation.

The very large planning counts reflect the small observed mean difference relative to the variability used in the illustration. They should not be read as a direct recommendation for a future study. In particular, this study used a crossover design, while the stated planning assumptions specify equal allocation between two arms and do not describe a paired crossover calculation. The registry record does not report a design-based sample-size justification for the actual trial.

12. 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 = 10.000; pooled standard deviation σ = 641.814.
2. n = 2 × (1.96 + 0.842)² × 641.814² / 10.000² = 64,663.0, rounded up to 64,663 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 <- 10                      # observed difference in means
sigma <- 641.81383593687                     # 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(858897)
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 = 64,663 (80% power), 86,566 (90% power)
 75% of observed effect: n per arm = 114,957 (80% power), 153,895 (90% power)
 50% of observed effect: n per arm = 258,652 (80% power), 346,262 (90% power)
power.t.test: 64664 
Simulated power at n = 64,663 per arm: 0.800 (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.

13. Multiplicity, Missing Data and Analysis Populations

The registry record lists one primary outcome measure, glutathione concentration, and no posted secondary outcome measures. It reports one comparison for the primary outcome. This makes the visible results relatively focused, but the record does not describe the full analysis plan or indicate whether other outcomes were planned but not posted.

Multiplicity refers generally to the increased chance of a false-positive finding when many hypotheses are tested. Statistical plans may address multiplicity by defining a primary outcome, prespecifying a testing order, or adjusting the inference. The posted p-value is labeled unadjusted. No multiplicity adjustment or testing hierarchy is reported in the registry record, so the reader cannot determine whether any adjustment was planned or needed for a broader set of analyses.

Missing-data handling is also not reported in the registry record. Although the outcome description says each of the 10 subjects received both infusions, the record does not describe whether any measurements were missing, how incomplete participant data would be handled, or whether all enrolled participants were included in the posted comparison. No participant-level analysis population, exclusions, or withdrawal details are posted.

The analysis populations are not defined in the registry record. It does not state whether the analysis followed randomized condition order, included only participants with complete measurements under both conditions, or used another population definition. Those details matter in a crossover study because incomplete paired observations can affect both the analysis population and precision.

The record also does not report the planned crossover analysis, adjustment for treatment sequence or period, or assessment of carryover. These omissions do not show that such considerations were ignored; they mean the registry record does not provide the information needed to assess them. The reported comparison is therefore best interpreted as a posted summary whose analytic handling of multiplicity, missing data, and the crossover structure is not fully documented.

14. 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 5% reporting threshold.

The adverse-event record lists 10 participants at risk in each condition. It reports zero serious adverse events in the normoglycemia condition and zero in the hyperglycemia condition. It also reports zero other adverse events in each condition and zero deaths in each condition. No serious adverse-event terms are listed.

These figures describe the events recorded in this small study sample. They do not establish that no adverse events can occur, nor do they provide a precise estimate of event frequency outside the study. The record does not give event descriptions because no serious-event terms are posted, and it does not report additional details about event collection or attribution.

Because the design is crossover, participants contributed exposure to both conditions. The same participants are therefore represented in the risk counts for each condition; the two groups should not be interpreted as independent sets of people. The registry record does not provide participant-level event histories or additional safety analyses. These counts should be read as descriptive records of reported events during the study, not as a broad comparison of safety between conditions.

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

The posted result is a comparison of mean glutathione concentration after two short-term glucose conditions in adolescents with type 1 diabetes. The mean was 541.0 umol/L during normoglycemia and 551.0 umol/L during hyperglycemia, with a reported mean difference of 10.0 umol/L. The confidence interval is broad and includes zero, and the unadjusted p-value is 0.972. These results do not establish a clear difference between the conditions.

They also do not establish that the conditions are equivalent. A lack of a statistically detectable difference can arise when an estimate is imprecise, and the posted confidence interval permits differences in either direction. The record does not report an equivalence margin or an analysis designed to demonstrate equivalence.

The endpoint is a concentration measure after an experimental infusion, not a direct posted measure of glutathione synthesis or use. Although the study summary frames the work in terms of how blood glucose may affect how glutathione is made and used, the result posted for the primary outcome does not by itself identify a metabolic mechanism. The registry record does not post a separate rate estimate for production or breakdown.

The findings are specific to the study conditions described: overnight maintenance of glucose in the stated ranges, followed by a 5-hour labeled cysteine infusion and outcome assessment up to 30 minutes afterward. The record does not establish how the result relates to other populations, longer-term glucose exposure, or clinical outcomes. Those questions are outside the reported endpoint and design.

The comparison is also constrained by the number of participants and incomplete reporting of the crossover analysis. The record confirms that participants received both conditions but does not describe how pairing was handled in the statistical comparison. This leaves uncertainty about the method behind the interval and p-value. The results are best read as an imprecise short-term estimate from this small study, rather than as a definitive statement about glutathione metabolism more broadly.

16. Why This Trial Matters Statistically

This study is statistically notable because it uses a crossover design to compare metabolic measurements within the same participants. Such designs can be useful when outcomes vary substantially between people: each participant serves as their own comparator, potentially reducing the influence of stable between-person differences. To realize that advantage, the analysis needs to respect the paired observations.

The registry record clearly describes repeated participation across the normoglycemia and hyperglycemia conditions, but it does not document the statistical handling of that pairing. This is an important distinction between knowing the study design and knowing the analysis. Means and standard errors by condition do not reveal the within-person covariance that can influence uncertainty in a crossover contrast.

The posted estimate also illustrates why a point estimate and a precision measure should be read together. The mean difference is 10.0 umol/L, while the confidence interval extends widely in both directions and includes zero. The p-value alone might be reduced to a statement about statistical significance; the interval more directly displays the range of effects compatible with the posted analysis. Neither should be treated as proof of no difference.

Finally, the sample-size illustration demonstrates how planning based on a very small observed effect can imply large participant requirements. However, the assumptions used in that illustration are not reported as the trial's original design assumptions, and the displayed arm-based planning framework does not describe a crossover calculation. This makes it a teaching illustration about effect size and precision rather than a retrospective judgment of the trial's design adequacy.

17. 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 are specific to interpreting this record. Enrollment was 10, and the registry posts 10 participants per condition because participants received both conditions. The outcome comparison is consequently based on a small crossover sample, and its confidence interval is broad. The result does not precisely estimate the condition contrast.

The study description indicates a randomized order, but details of sequence generation, allocation concealment, treatment order, and any washout are not reported in the registry record. The record also does not report participant demographics beyond the description of adolescents with type 1 diabetes, or further eligibility criteria. This limits assessment of how closely the enrolled sample represents any broader population.

The main statistical limitation is missing detail on the crossover analysis. The record does not say whether the comparison used paired differences or adjusted for participant, period, sequence, or possible carryover effects. Participant-level values and within-person correlation are not posted. Consequently, the reported standard errors and comparison cannot be independently assessed for their treatment of repeated measurements.

The endpoint is a short-term concentration measurement taken after the infusion; further details about sampling and aggregation are not reported. No secondary outcomes or analyses are posted. Missing-data procedures, analysis populations, protocol deviations, and the original sample-size rationale are also not reported in the registry record.

These limitations concern what can be evaluated from the registry record. They do not demonstrate that the study procedures or analyses were necessarily inadequate; they identify information that is unavailable for readers assessing the strength and scope of the posted result.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Glutathione Metabolism in Adolescents With Type 1 Diabetes - Study A — NCT00858897.
• Registry record last updated 2023-07-10; status last verified 2023-06.
• Results first posted 2023-07-10.
• 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.

21. Record Summary

NCT00858897 is a completed randomized, unmasked crossover study sponsored by Nemours Children's Clinic. It enrolled 10 adolescents with type 1 diabetes and compared glutathione concentration during normoglycemia and hyperglycemia after overnight glucose control and a 5-hour intravenous labeled cysteine infusion.

The posted primary outcome means were 541.0 umol/L for normoglycemia and 551.0 umol/L for hyperglycemia. The mean difference was 10.0 umol/L, with a 95% confidence interval from -552.6 to 572.6 umol/L and an unadjusted p-value of 0.972. The estimate is imprecise, and the record does not document whether the comparison accounted for paired crossover observations.

The registry reports zero serious adverse events, zero other adverse events, and zero deaths in each condition. It posts no secondary outcome analyses. The original sample-size rationale, detailed analysis plan, missing-data procedures, and crossover-specific statistical methods are not reported in the registry record.