The Effect of Gluten-free Diet on New Onset Type 1 Diabetes (T1D): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The Effect of Gluten-free Diet on New Onset Type 1 Diabetes (T1D) (NCT02867436), a non-randomized na study. The primary outcome is Change in C-peptide Area Under the Curve Measured by Mixed-meal Tolerance Test (MMTT) Between Group on GFD and Standard Gluten-containing Diet..

2. Clinical Question

3. Trial Design

This is a completed pilot study with a parallel-group, non-randomized design and no masking. The registered intervention is a gluten-free diet; the comparator is a conventional diet. The record gives an enrollment of 45 and identifies University Hospital, Motol as the sponsor. The study start is recorded as 2016-03, with primary completion recorded as 2019-12.

Because assignment was not randomized, the groups should not be treated as though they were created by random allocation. The brief study description calls the controls age matched, but the registry record does not explain how that matching was carried out, whether additional variables were considered, or how participants entered each group. Differences between groups may therefore reflect characteristics associated with diet choice or group selection as well as any effect associated with the diet itself. The registered design alone cannot separate those possibilities.

No masking was recorded. The registry does not explain whether outcome assessors or laboratory staff were masked, so it is not possible to characterize masking beyond the registered field. The study is listed as completed, but completion status does not establish that every planned measure was collected or that complete follow-up was achieved.

The primary endpoint compares change in C-peptide area under the curve during a mixed-meal tolerance test from Month 1 to Month 12. Secondary outcomes concern HbA1c and insulin dose at 6 and 12 months relative to Month 1, immune parameters at 12 months relative to Month 1, and fecal microbiome differences over the first year of diabetes duration. The registry record does not report the numerical results for these outcomes or describe the analysis population used for each one.

The available design information is not enough to determine the extent of baseline balance, intervention adherence, follow-up completeness, or adjustment for confounding. These details are important to interpreting a non-randomized comparison and 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

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 C-peptide Area Under the Curve Measured by Mixed-meal Tolerance Test (MMTT) Between Group on GFD and Standard Gluten-containing Diet., measured over Month 1 (baseline) - Month 12 (end of intervention).

The primary endpoint is change in C-peptide area under the curve, measured with a mixed-meal tolerance test, between Month 1 at baseline and Month 12 at the end of the intervention. The registered unit is pmol*min/l, and the record identifies the endpoint as a mean with standard deviation. C-peptide is measured at 0, 30, 60, 90 and 120 minutes during the test, and the area under the curve combines those measurements into a summary of the C-peptide response over the test period.

As a general statistical concept, an area-under-the-curve measure can represent the overall level of a response across repeated measurements rather than focusing on a single time point. This can be useful when the response changes over the course of a test. The endpoint is used to compare change over the intervention period between the two diet groups. The registry record does not report the group means, standard deviations, change estimates, or a numerical between-group contrast. It also does not specify whether the primary comparison was based on change scores, an endpoint measurement adjusted for baseline, or another analysis. Those analytic details should not be inferred from the endpoint description alone.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry record identifies the primary endpoint as a mean of a continuous measure: C-peptide area under the curve during a mixed-meal tolerance test. It gives the unit and standard deviation as the dispersion measure. It does not report the statistical test, model, adjustment variables, confidence interval method, or numerical primary result. The methods below explain general statistical ideas relevant to this kind of endpoint; they are not claims about the analysis actually used in this trial.

What does an area under the curve represent?

As a general concept, an area under the curve combines measurements made at several points during a test into one summary of the response over time. In this study description, C-peptide measurements at 0, 30, 60, 90 and 120 minutes contribute to the mixed-meal tolerance test area. A single summary can be useful when the scientific question concerns the overall response, rather than one isolated measurement. It also means that interpretation depends on how the area was calculated and on the completeness and quality of the underlying measurements. The calculation details are not reported in the registry record.

The primary endpoint is described as change from Month 1 to Month 12. That wording identifies the time period of interest but does not identify the statistical procedure used to compare groups. A change-score analysis and a model comparing end-of-period values while accounting for baseline are examples of different general approaches. They can target related questions but need not produce identical estimates. The registry record does not say which approach was used, so neither should be attributed to this study.

What do the mean and standard deviation tell a reader?

In general, a mean describes the average value in a group, while a standard deviation describes the spread of individual values around that mean. They answer different questions: the mean summarizes the group’s location, and the standard deviation describes variation among observations. A standard deviation is not the same as the uncertainty in a group mean or in a between-group difference. The uncertainty of an estimate is usually conveyed with a standard error or confidence interval, but these are not reported for the primary endpoint in the registry record.

For a comparison between groups, a useful result would ordinarily state the estimated contrast and its uncertainty, alongside the analysis population and method. A contrast could be expressed using the difference in changes, or another prespecified scale. The registry record gives no numerical contrast, so the size and precision of the primary comparison cannot be discussed. No p-value for that comparison is reported either.

Why is the design relevant to the analysis?

As a general principle, random allocation helps make treatment groups comparable in expectation with respect to measured and unmeasured baseline characteristics. This study is registered as non-randomized, so that protection does not apply. Baseline differences may be associated with both group membership and outcomes. Statistical adjustment can sometimes address measured differences, but cannot guarantee removal of confounding, particularly when relevant factors were not measured or were modeled inadequately. The registry record does not report whether adjustment was performed or which covariates, if any, were used.

The parallel-group structure means the two diet groups are followed as separate groups rather than being described as a crossover comparison. That structure does not itself establish that observations are independent in every respect, nor does it specify how repeated measurements within a participant were modeled. The secondary outcomes include measurements at more than one follow-up time for HbA1c and insulin dose. A suitable analysis of repeated measurements would need to account for their relationship within participants; the registry record does not describe the analysis used for those outcomes.

How should uncertainty be understood?

In general, a confidence interval expresses uncertainty around an estimated quantity under a particular statistical model and its assumptions. A narrower interval indicates greater precision for that estimate, while a wider interval indicates less precision. It is not a guarantee that the true value lies in the interval, and it does not address systematic bias such as confounding or selective outcome reporting. The registry record does not report a confidence interval for the primary endpoint.

A p-value is also a model-dependent summary. It is not the probability that a treatment effect is absent, and it does not measure the magnitude or clinical importance of a difference. Because no primary p-value is reported in the registry record, there is no basis for characterizing statistical significance. Even if a p-value were available, it would need to be read alongside the estimated effect, its uncertainty, the design limitations, and the prespecified analysis plan.

What do the planning assumptions mean?

The record describes planning illustrations based on an observed effect, a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation. It says the effect to detect is a stated fraction of the observed effect. These are planning assumptions, not evidence that the trial was designed with those assumptions and not a measure of observed power. The registry record does not report the trial’s own sample-size justification, a target effect used in its original design, or an interim-analysis plan.

As a general concept, sample-size planning estimates how many participants per arm may be needed under chosen assumptions to achieve a specified probability of detecting an effect under a statistical model. Such illustrations depend on the assumed effect, variability, significance level, allocation, and method. When an effect is estimated from observed trial data, it can itself be uncertain, particularly in a pilot study. Planning calculations based on it should not be read as evidence that the observed comparison was adequately powered or that a result is reliable. No calculated participant-per-arm values are stated in the registry record.

Over-dispersion is a general concern when data vary more than a model assumes. If present, standard errors based on an overly restrictive model can understate uncertainty. The primary endpoint is continuous and is summarized with a mean and standard deviation, but the record does not report a model or a dispersion assessment. It would therefore be inappropriate to claim that over-dispersion was relevant, tested, or handled in this analysis.

10. Confidence Intervals for Each Arm

No two-arm comparison is shown for this trial, but each arm's mean can be given with a t-based 95% confidence interval computed from the posted mean, spread and number of participants.

R code and output

arm <- c("Gluten-free Diet", "Conventional Diet")
n   <- c(20, 19)
m   <- c(1539, 1173)
sp  <- c(1255, 1006)
sd  <- sp      # posted standard deviations
for (i in seq_along(n)) {
  se <- sd[i] / sqrt(n[i]); h <- qt(0.975, n[i] - 1) * se
  cat(sprintf("CARM|%s|%d|%.3f|%.3f|%.3f|%.3f\n", arm[i], n[i], m[i], sd[i], m[i] - h, m[i] + h))
}

CARM  Gluten-free Diet  20  1539.000  1255.000  951.642  2126.358
CARM  Conventional Diet  19  1173.000  1006.000  688.124  1657.876

11. Multiplicity, Missing Data and Analysis Populations

The registry record lists a primary endpoint and multiple secondary outcomes, including HbA1c, insulin dose, immune parameters, and fecal microbiome differences. Considering several outcomes can raise a general multiplicity issue: when many hypotheses are tested, the chance of at least one apparently notable result may increase if each is assessed without regard to the others. Whether and how to address that issue depends on the planned inferential goals and analysis strategy. A multiplicity adjustment or other strategy is not reported in the registry record, so no claim can be made that one was or was not applied in the analysis.

The record identifies five outcome measures and five analyses, but does not give sufficient detail to map each analysis to a particular statistical model or to establish which comparisons were prespecified. The analysis plan, outcome hierarchy beyond the designation of the primary endpoint, and any handling of exploratory analyses are not reported in the registry record. The numerical results for the primary and secondary outcomes are also not reported, limiting assessment of selective reporting or consistency across outcomes.

Missing-data methods and the analysis populations are not reported in the registry record. It does not state whether all enrolled participants were included in each analysis, how incomplete follow-up or missing measurements were handled, or whether analyses followed an intention-to-treat, per-protocol, or other population definition. As a general concept, missingness can affect both precision and the validity of estimates, especially when the reasons for missing data are related to participant characteristics or outcomes. Without counts and reasons for missing measurements and a described method, the impact cannot be assessed.

12. 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 record lists zero serious adverse events among 26 participants at risk in the gluten-free-diet group and zero among 19 participants at risk in the conventional-diet group. It also lists zero other adverse events and zero deaths in the recorded at-risk groups. No serious adverse event terms are listed.

These entries describe what the registry record reports for the specified categories; they do not establish that no symptoms or events of any kind occurred. The record does not provide event definitions, collection procedures, follow-up completeness, severity details beyond the serious-event category, or a narrative explaining how adverse events were assessed. It is also not possible to infer whether the listed at-risk counts represent everyone enrolled or everyone followed for the full intervention period.

As a general statistical point, a zero count in a study record is not proof of zero underlying risk. It should be read in context of the population observed, the period of observation, event ascertainment, and completeness of reporting. The registry entries are limited to the adverse-event categories and counts; they do not support broader conclusions about safety.

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

The registry record establishes the question this pilot study set out to address: whether change in C-peptide area under the curve differed between children on a gluten-free diet and children on a conventional gluten-containing diet from Month 1 to Month 12. It also identifies secondary comparisons involving HbA1c, insulin dose, immune parameters, and fecal microbiome. These objectives describe the study’s scope, not its findings.

Numerical results for the primary and secondary outcomes are not reported in the registry record. Consequently, the direction, size, and precision of any observed difference cannot be stated. The available record does not support a conclusion that either diet was associated with a larger or smaller change, nor does it permit assessment of whether any contrast was compatible with no difference under a specified statistical model.

Even if numerical results were available, the non-randomized design would be important. A difference between groups could be associated with differences in participant characteristics, selection into a diet group, adherence, or other factors. The record does not describe these features or any adjustment for them. Statistical association in this design would not, by itself, establish a causal effect.

As a general concept, a pilot study can help explore feasibility, measurement, and the range of uncertainty around estimates, but the label “pilot” does not reveal how the study was powered or what conclusions its designers intended to support. The registry record does not report a sample-size justification or a formal precision goal. Enrollment and completion status alone do not establish the reliability or completeness of outcome data.

The appropriate reading is therefore limited: the record documents a completed, non-randomized comparison and its planned outcomes, but does not report the numerical evidence required to interpret the primary or secondary results. The adverse-event entries report no events in the listed categories, but the available detail does not support broader safety conclusions.

14. Why This Trial Matters Statistically

This trial is statistically informative as an example of how a clinically focused question and a registered endpoint do not, on their own, provide enough information to evaluate a treatment comparison. The record specifies a population, two diet groups, a primary measure, and a follow-up period. Those features allow a reader to understand what was intended to be compared, but interpretation also requires outcome estimates, uncertainty, and a clear account of the analysis.

The non-randomized allocation is especially important. In randomized studies, allocation is intended to reduce systematic baseline differences between groups. In a non-randomized comparison, group differences may be related to participant characteristics or decisions associated with diet. Knowing that the study description refers to age-matched controls does not resolve the issue, because the matching process and any remaining imbalances are not described in the registry record.

The endpoint also illustrates a measurement choice: a mixed-meal tolerance test collects C-peptide measurements at several times, while the area under the curve summarizes the response across the test. This can align the measure with an overall-response question, but statistical interpretation depends on the calculation, the comparison method, and the uncertainty around the estimate. The registry record does not report those analytic details or numerical outcomes.

Finally, the listed planning assumptions distinguish a planning illustration from the study’s original design justification. Sample-size calculations based on an observed effect are conditional on assumptions and are not observed power. The registry record does not report the study’s own sample-size rationale. Together, these points show why design, estimation, precision, and reporting must be considered alongside the endpoint definition.

15. 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 trial-specific limitations constrain interpretation. First, allocation was non-randomized. The record describes age-matched controls, but does not explain how participants were matched or selected, what baseline characteristics were measured, or whether the groups were comparable on factors related to outcomes. This leaves potential confounding as a central concern.

Second, the registry record does not report numerical results for the primary or secondary endpoints. It therefore provides no group estimates, between-group contrasts, uncertainty intervals, or p-values with which to judge direction, magnitude, or precision. The record also does not describe the statistical models, covariate adjustment, or approach used to analyze change over time.

Third, important implementation and follow-up details are not reported. These include how adherence to the gluten-free or conventional diet was assessed, how complete the outcome measurements were, and how missing data were handled. The analysis populations are not identified. Without this information, it is difficult to assess whether the analyzed measurements represent the groups as intended.

Masking is registered as none, but the record does not clarify whether any outcome assessment or laboratory procedures were masked. The record also does not report a sample-size justification, an interim-analysis plan, or a detailed multiplicity strategy for the primary and secondary outcomes. These omissions do not establish that such procedures were absent; they mean they are not reported in the registry record.

The safety entries list zero serious adverse events, other adverse events, and deaths in the recorded groups, but provide limited information about event collection and follow-up. Taken together, these limitations mean the registry record documents the study question and design but does not permit a detailed appraisal of the outcome analysis or its robustness.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: The Effect of Gluten-free Diet on New Onset Type 1 Diabetes (T1D) — NCT02867436.
• Registry record last updated 2024-09-19; status last verified 2024-05.
• Results first posted 2024-09-19.
• 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.

19. Record Summary

NCT02867436 is a completed, non-randomized, unmasked, parallel-group pilot study sponsored by University Hospital, Motol. It compares a gluten-free diet with a conventional diet in children with newly diagnosed type 1 diabetes. Enrollment is recorded as 45; the study start is 2016-03 and primary completion is 2019-12.

The primary endpoint is change in C-peptide area under the curve measured by mixed-meal tolerance test from Month 1 to Month 12. Secondary outcomes concern HbA1c, insulin dose, immune parameters, and fecal microbiome. Numerical outcome results and detailed analysis methods are not reported in the registry record. The listed adverse-event entries report zero serious events, other events, and deaths in the recorded groups.