Effect of Three Fibres on Glycaemic and Insulinaemic Responses in Healthy Adult Volunteers: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effect of Three Fibres on Glycaemic and Insulinaemic Responses in Healthy Adult Volunteers (NCT02701270), a randomized na study. The primary outcome is Assessment of IAUC (Incremental Area Under the Curve) in Blood Glucose Response.

2. Clinical Question

3. Trial Design

The registry describes a randomized, single-blinded, controlled crossover study of acute dietary interventions in healthy adult volunteers. Participants were enrolled between 2015-09 and primary completion was recorded in 2015-10. The study is listed as completed and its phase is recorded as NA. Danisco is named as the sponsor.

A crossover design means that participants may receive more than one intervention condition, so comparisons can potentially use measurements from the same people under different conditions. The registry record does not report the intervention sequence, the number or timing of treatment periods, any washout interval, or how period and sequence effects were handled. It also does not explain who was blinded or how blinding was maintained. Those details matter when interpreting an acute crossover comparison, but should not be inferred from the design label alone.

Four dietary supplement conditions are listed: Experimental Dietary Fibre 1, Experimental Dietary Fibre 2, Polydextrose, and Dextrose. Polydextrose is the comparator for the displayed contrasts. Dextrose is reported as a separate control condition. Descriptions for the individual arms are blank in the registry record, so doses, preparation details, and administration procedures are not reported in the registry record.

The primary endpoint is blood glucose incremental area under the curve, with measurements scheduled at 0, 15, 30, 45, 60, 90, 120, 150, 180, 210 and 240 minutes post dose. The primary outcome population is defined as participants with a full set of blood glucose measurements. Although enrollment was 13, each condition's posted outcome summary includes 11 participants. The record does not describe the reason for this difference or provide a flow of participants through the conditions.

The registry lists insulin incremental area under the curve as a secondary outcome. It does not report numerical results for that outcome. The record lists two outcome measures and zero analyses, and it does not report the original statistical analysis plan or sample-size justification.

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: 13 healthy volunteers were recruited, 12 volunteers were screened and one excluded (did not meet inclusion criteria).

First Intervention at Visit 1

Second Intervention at Visit 2

Third Intervention at Visit 3

Fourth Intervention at Visit 4

Analysis population for the primary outcome, as defined in the registry: Participants from whom full set of blood glucose measurements were available.

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 Assessment of IAUC (Incremental Area Under the Curve) in Blood Glucose Response, measured over 0, 15, 30, 45, 60, 90, 120, 150, 180, 210 and 240 minutes post dose.

The primary endpoint is the incremental area under the curve (IAUC) for blood glucose, reported in min*mmol/L. Glucose was measured at specified times from 0 through 240 minutes post dose. IAUC combines the measured changes over time into a single summary of the response during the measurement window, rather than focusing on one measurement at one time point.

As a general statistical concept, an incremental area summarizes the area attributable to change relative to a reference level, often the baseline. This makes it useful for comparing the overall post-dose response across conditions. The registry record does not give further details about the exact IAUC calculation, such as its computational method or handling of values below the reference level; those details are not reported in the registry record.

The primary measure is a continuous outcome, and each condition is summarized by a mean and standard deviation. The posted mean IAUC values are 127.5 for Experimental Dietary Fibre 1, 143.5 for Experimental Dietary Fibre 2, 19.27 for Polydextrose Control, and 134.2 for Dextrose Control. The unit is min*mmol/L. The registry also names insulin IAUC as a secondary outcome, but its results are not reported in the registry record.

IAUC describes an acute glucose response over the scheduled sampling period. It is a response marker, not a direct measurement of digestion, and it does not by itself establish what might happen outside the measurement window or in populations other than the healthy adult volunteers studied.

7. Results Posted in the Registry

• Experimental Dietary Fibre 1: mean 127.45 versus 19.27 on control; difference 108.18 (95% CI 76.95 to 139.41), standardized effect d = 2.89; z-test p = <0.001.
• Experimental Dietary Fibre 2: mean 143.53 versus 19.27 on control; difference 124.26 (95% CI 93.10 to 155.42), standardized effect d = 3.33; z-test p = <0.001.
• Dextrose Control: mean 134.21 versus 19.27 on control; difference 114.94 (95% CI 79.75 to 150.13), standardized effect d = 2.73; z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous: blood glucose IAUC in min*mmol/L. The registry reports the mean and standard deviation in each condition. A mean represents the average outcome within a group, while a standard deviation describes the spread of individual values around that average. Neither statistic alone describes the full distribution, and group summaries do not show how measurements varied within each participant over time.

What does the mean difference represent?

The displayed mean differences compare each condition with Polydextrose Control. For Experimental Dietary Fibre 1, the displayed difference is 108.2; for Experimental Dietary Fibre 2, it is 124.3; and for Dextrose Control, it is 114.9. A positive difference indicates that the reported mean for the named condition is higher than the reported Polydextrose Control mean. This is a contrast between group summaries, not a direct estimate of a biological mechanism.

The comparison summaries also include pooled standard deviations and standardized effect sizes. As a general statistical concept, a standardized effect expresses a mean difference relative to a measure of outcome variability, allowing differences to be considered on a scale that is not tied to the original measurement unit. Such a measure depends on the standardization method and does not remove limitations in the study design or analysis.

What does the confidence interval add?

A confidence interval gives a range of values compatible with the data and the calculation method, expressing the precision of an estimate. The intervals for the displayed comparisons are 76.95 to 139.4, 93.1 to 155.4, and 79.75 to 150.1. Each interval is above zero. The intervals are not guarantees that the true value lies within their bounds, and they do not include uncertainty from unreported analytical choices or potential bias.

The reported p-values are unadjusted and are all <0.001. As a general concept, a p-value describes how unusual data at least as discrepant as those observed would be under a specified null model. It does not measure the probability that the null hypothesis is true, the probability that a result is due to chance, or the importance of the difference. Interpretation depends on the test and model used; the registry record does not provide a full inferential analysis plan.

How does crossover structure matter?

In a crossover study, the same participant can contribute measurements under different conditions. A paired analysis can account for the fact that measurements from one person are related to each other. As a general statistical principle, using that within-person relationship can change the estimated uncertainty compared with treating condition groups as independent. The registry identifies a crossover design, but the record does not report the sequence, period structure, washout, or an analysis accounting for paired observations. The displayed comparison summaries use condition-level means, standard deviations, and sample sizes; the registry record does not establish that the displayed inference reflects a paired crossover model.

For crossover data, period effects can arise if responses differ over time or by treatment order, and carryover can arise if an earlier condition influences a later one. These are general design considerations, not reported findings about this study. The registry record does not say whether such effects were assessed or how they would have been addressed.

What does the analysis population imply?

The record defines the primary outcome population as participants with a full set of blood glucose measurements. The enrollment is 13, while each condition summary reports 11 participants. This indicates that the posted summaries do not include the full enrollment count in each condition. It does not explain the reason, whether the same participants are represented in every condition, or whether any measurements were imputed. Those details are not reported in the registry record.

Restricting analysis to complete measurements can affect interpretation if participants with missing data differ systematically from those with complete data. As a general statistical issue, complete-case summaries describe those with observed measurements; they do not automatically represent all enrolled participants. The registry record does not report missing-data assumptions or sensitivity analyses.

What is and is not documented?

The registry record lists two outcome measures, including glucose IAUC as primary and insulin IAUC as secondary, but reports zero analyses. The glucose summaries and comparisons describe posted outcome figures, while details of the original inferential method, adjustment for multiple comparisons, and planned analysis population are not reported in the registry record. The record also does not report a sample-size justification for the original trial, an interim analysis plan, or a prespecified statistical analysis plan.

As a general matter, a prespecified analysis plan helps distinguish planned questions from analyses selected after observing results. Without that information, the posted estimates remain interpretable as descriptive summaries and displayed comparisons, but the extent to which each analysis was planned cannot be assessed from the registry record.

10. Confidence Intervals and Precision

The displayed mean differences are estimated with 95% confidence intervals. For Experimental Dietary Fibre 1 versus Polydextrose Control, the difference is 108.2 and the interval extends from 76.95 to 139.4. For Experimental Dietary Fibre 2 versus Polydextrose Control, the difference is 124.3 and the interval extends from 93.1 to 155.4. For Dextrose Control versus Polydextrose Control, the difference is 114.9 and the interval extends from 79.75 to 150.1. Each interval lies above zero, while the interval widths show that the estimates still have uncertainty.

A confidence interval is a measure of statistical precision under the assumptions used to calculate it. In general, narrower intervals indicate greater precision, while wider intervals indicate less precision. Precision is distinct from accuracy: an interval can be narrow while a study has bias, and a confidence interval does not account for unreported design or analysis choices.

Each condition summary includes 11 participants, and the enrollment was 13. The relatively small posted outcome samples make the estimates sensitive to the observed participants and to the analysis choices. The registry record does not explain the difference between enrollment and the outcome summaries or report a crossover model that would clarify how repeated measurements were used. The intervals should therefore be read as uncertainty from the displayed comparison calculation, not as a complete account of all uncertainty in the study.

The three unadjusted p-values are each <0.001. A small p-value does not replace the confidence interval: the interval gives a range of plausible effect estimates under the calculation, while the p-value addresses compatibility with a specified null model. Neither statistic establishes the biological interpretation of the glucose response or resolves the study's broader question about digestion.

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 sample-size figures are planning illustrations based on the observed differences, not the original trial's design calculations. For these continuous outcomes, the figures are participants per arm, not total events. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning scenario uses a specified fraction of the observed effect as the effect to detect. The original trial's own sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the number of participants per arm indicated by the planning calculation for an 80% chance of detecting the chosen effect under those assumptions, if that effect and model are correct. The 90% power column gives the corresponding per-arm number for a 90% chance. These are prospective planning quantities, not measures of what the completed study achieved. This is not observed power.

The rows for 100%, 75%, and 50% of the observed effect represent progressively smaller target differences. Smaller effects need more participants to detect at the same significance level and power, all else equal. For example, in the Experimental Dietary Fibre 2 comparison, planning for 50% of the observed effect gives 6 participants per arm for 80% power and 8 participants per arm for 90% power. The figures are illustrations based on the unusually large observed standardized contrasts and the stated simplified assumptions; they should not be read as the trial's enrollment target or as a recommendation for a future design.

Because the trial is described as crossover, a future design calculation may need assumptions about within-participant correlation and the planned crossover analysis. Those are not among the listed planning assumptions, and the registry record does not report the original design calculation. The illustrative values therefore should not be treated as a complete crossover sample-size plan.

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 = 108.180; pooled standard deviation σ = 37.373.
2. n = 2 × (1.96 + 0.842)² × 37.373² / 108.180² = 1.9, rounded up to 2 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 <- 108.18                      # observed difference in means
sigma <- 37.3731086477965                     # 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(2701270)
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 = 2 (80% power), 3 (90% power)
 75% of observed effect: n per arm = 4 (80% power), 5 (90% power)
 50% of observed effect: n per arm = 8 (80% power), 11 (90% power)
power.t.test: 3.2 
Simulated power at n = 2 per arm: 0.364 (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 posted comparisons address Experimental Dietary Fibre 1, Experimental Dietary Fibre 2, and Dextrose Control, each against Polydextrose Control. The registry also lists glucose IAUC as the primary outcome and insulin IAUC as a secondary outcome. When several comparisons or outcomes are examined, the chance of at least one nominally unusual result can increase. As a general statistical approach, multiplicity procedures can control a chosen error rate across a family of tests. Whether such a procedure was planned or used is not reported in the registry record.

The displayed p-values are unadjusted. They describe each contrast separately and do not account for the set of comparisons or outcomes. The record does not identify a primary contrast among the three displayed comparisons, a testing hierarchy, or a multiplicity adjustment. Interpretation should therefore preserve the distinction between the reported individual results and a claim about a combined family of tests.

The primary endpoint population is described as participants with a full set of blood glucose measurements. Each condition summary reports 11 participants, compared with enrollment of 13. The reasons for incomplete outcome data, the amount or timing of missingness, whether missingness differed by condition, and any imputation or sensitivity analysis are not reported in the registry record. The record does not state whether an intention-to-treat, per-protocol, or other analysis population was planned.

The same information gap applies to the secondary insulin outcome: it is listed, but numerical results are not reported in the registry record. It is therefore not possible to assess its estimates, precision, or whether it was analyzed on the same population as the primary outcome.

The crossover design raises additional analysis questions. The registry record does not report how repeated measurements within participants were handled, or whether period, sequence, and carryover considerations were incorporated. It also does not report the original statistical analysis plan or any interim analyses. These absences limit assessment of prespecification and of how the posted comparisons relate to the intended analysis.

14. 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 0% reporting threshold.

Most frequent non-serious adverse event terms

The adverse-event summaries report zero participants with serious adverse events among the 11 at risk in each of the four conditions: Experimental Dietary Fibre 1, Experimental Dietary Fibre 2, Polydextrose Control, and Dextrose Control. This means that no serious adverse events are reported for the listed groups in the registry summary. It does not establish that no events occurred outside the reporting definitions or observation period.

Other adverse events are reported for 2 participants in Experimental Dietary Fibre 1 and 2 participants in Experimental Dietary Fibre 2. The summaries report 0 participants with other adverse events in Polydextrose Control and 0 in Dextrose Control. The registry record does not list specific event terms in the serious-event summary, and the event terms and severity details for other events are not reported in the registry record.

Deaths are not reported in the registry record. The adverse-event counts are descriptive and do not establish comparative safety, particularly given the small numbers at risk, the acute study setting, and the absence of event details. They should be read as the reported counts for these study conditions, not as a complete characterization of risk.

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

The posted primary-outcome summaries describe mean blood glucose IAUC values of 127.5 for Experimental Dietary Fibre 1, 143.5 for Experimental Dietary Fibre 2, 19.27 for Polydextrose Control, and 134.2 for Dextrose Control. Each condition has 11 participants in the summary. The displayed mean differences versus Polydextrose Control are positive, and their confidence intervals lie above zero. The accompanying unadjusted p-values are each <0.001.

These figures describe the acute glucose response measured over the scheduled period from 0 through 240 minutes post dose. IAUC is a summary of response over time, not a direct measurement of digestion. The registry's stated purpose is to assess whether the experimental dietary fibre products are digested using glycaemic and insulinaemic responses as markers, but a glucose IAUC contrast alone cannot establish that biological process.

The record lists insulin IAUC as a secondary outcome but does not report its numerical results. Consequently, the glucose summaries cannot be paired with a corresponding posted insulin analysis to assess the two markers together. The registry record also does not report an analysis accounting for within-participant crossover structure, the missing-measurement process, or adjustment for multiple comparisons.

The results do not establish what happens beyond the acute measurement window, in other populations, or under conditions not described in the record. They do not establish a long-term clinical effect or provide a direct assessment of health outcomes. Nor do the displayed summaries alone show how individual participants responded across all conditions. Their interpretation is limited to the reported continuous glucose summaries and comparisons, with the design and reporting uncertainties.

16. Why This Trial Matters Statistically

This study illustrates the statistical importance of distinguishing a crossover design from the analysis actually documented. A crossover can yield within-person comparisons, but the registry record does not describe whether the displayed contrasts used paired information or adjusted for period and sequence. A large difference between condition means does not by itself answer whether the inferential calculation matches the repeated-measures design.

It also shows why sample counts and analysis populations need to be read together. The registry reports enrollment of 13, while the primary-outcome summaries include 11 participants per condition and define eligibility by having a full set of glucose measurements. Without participant-flow or missing-data details, readers cannot determine why the numbers differ or how that restriction may affect interpretation.

The outcomes are acute response measures, and the primary endpoint compresses measurements across time into an IAUC value. This is useful for a single summary comparison, but it removes detail about the timing and shape of the glucose response. The scheduled measurements cover the period through 240 minutes post dose; the endpoint does not describe what occurs outside that window.

Finally, three unadjusted contrasts are reported alongside a secondary outcome whose numerical results are absent. The record does not report a multiplicity strategy or a complete analysis plan. Statistical interpretation therefore requires attention not only to the displayed effect estimates and confidence intervals, but also to the set of questions examined, the crossover structure, and the limits of what the registry reports.

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.

The main trial-specific limitation is the small outcome sample: 11 participants are reported in each condition summary, compared with 13 enrolled. The registry defines the primary analysis population by complete blood glucose measurements but does not report reasons for incomplete records, participant flow, or missing-data methods. The effect of this difference on the summaries cannot be assessed from the record.

The study is identified as a crossover, but essential details are not reported in the registry record. These include treatment sequence, period structure, washout interval, and the approach to paired observations, period effects, or carryover. The displayed comparisons use condition-level summaries, and the record does not establish that the inferential results account for within-person dependence.

Intervention descriptions are blank, and doses and preparation details are not reported in the registry record. The outcome is acute, with glucose measurement scheduled only through 240 minutes post dose. The record does not report numerical results for the listed secondary insulin IAUC outcome, limiting assessment of the intended pair of response markers.

The three displayed p-values are unadjusted, and a multiplicity plan is not reported. The original sample-size justification, full statistical analysis plan, and any interim-analysis approach are also not reported in the registry record. These limitations leave uncertainty about prespecification, analysis choices, and the scope of inference. The completed record therefore supports description of the posted glucose summaries, but not a comprehensive evaluation of every design and analysis feature.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Effect of Three Fibres on Glycaemic and Insulinaemic Responses in Healthy Adult Volunteers — NCT02701270.
• Registry record last updated 2016-07-27; status last verified 2016-06.
• Results first posted 2016-07-27.
• 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

NCT02701270 is a completed randomized, single-blinded, controlled crossover study of acute dietary interventions in healthy adult volunteers, sponsored by Danisco. Enrollment was 13; the study began in 2015-09 and primary completion was recorded in 2015-10.

The primary outcome is blood glucose IAUC in min*mmol/L, measured at scheduled times from 0 through 240 minutes post dose. The registry also lists insulin IAUC as a secondary outcome. The primary outcome summaries report 11 participants per condition, and the listed comparisons use Polydextrose Control as the reference.

The posted glucose summaries show positive mean differences for Experimental Dietary Fibre 1, Experimental Dietary Fibre 2, and Dextrose Control versus Polydextrose Control, each with an unadjusted p-value of <0.001. The record does not report numerical insulin results, the original sample-size justification, or a full statistical analysis plan.