Two Way Crossover Closed Loop Study Insulin vs Insulin and Pramlintide: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Two Way Crossover Closed Loop Study Insulin vs Insulin and Pramlintide (NCT06422325), a randomized na study. The primary outcome is Incremental Area Under the Curve of Postprandial Glucose Following the First Meal.

2. Clinical Question

The registry describes a randomized, unmasked crossover study. Participants completed both arms, so the comparison concerns the two delivery strategies experienced by participants rather than two entirely separate groups of people. The primary endpoint is a continuous measure of post-meal glucose exposure, expressed in (mg/dl*min)/1000. It is not a direct measure of a long-term clinical outcome.

The posted primary group means are 18.1 for the insulin and pramlintide arm and 20.9 for the insulin-only arm. The registry’s mixed-model analysis reports an adjusted mean difference of -5.9, with a 95% confidence interval from -10.8 to -1.1 and p = 0.017. A simple unadjusted recalculation from the group summaries instead gives a mean difference of 2.8 when expressed as insulin only minus insulin and pramlintide, with a confidence interval that includes zero. These analyses do not agree in direction and statistical conclusion as presented; the sponsor’s own analysis takes precedence, but the discrepancy is important when interpreting the posted results.

3. Trial Design

The registry describes a randomized crossover study with no masking. The two study strategies were an MPC closed-loop system in insulin-only mode and the same type of system in insulin/pramlintide mode. In the insulin-only arm, insulin was delivered by an Omnipod. In the combination arm, insulin and pramlintide were delivered by two Omnipods. Both arm descriptions identify the Dexcom G6 continuous glucose monitor as the source of sensor glucose measurements.

Participants ate two meals while in clinic, and each arm description identifies a 12.5 hour study period. The primary endpoint was measured during the six hours following the first meal. The registry also lists outcomes concerning postprandial glucose and time in specified glucose ranges following meals. The primary analysis population is described as all participants who completed at least one six-hour observation period; the record further says participants completed both arms in the crossover design.

Enrollment is listed as 33. The primary outcome reports 31 participants for each arm, while some secondary outcomes have 30 participants in the insulin and pramlintide arm and 31 in the insulin-only arm. The reasons for these differences in the outcome counts are not reported in the registry record. The randomization sequence, period order, any washout arrangements, and the original sample-size rationale are not reported in the registry record. The record lists the study status as completed, but completion does not by itself establish that all randomized participants contributed data to every outcome.

A crossover design can use each participant’s observations under both strategies, which makes within-participant comparisons relevant. It also means interpretation can depend on how the analysis accounts for repeated observations and the sequence or period in which strategies were received. The registry identifies a mixed-model analysis for the primary result, but further details of its specification 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.

Before assignment: Participants were randomized immediately after screening.

Overall Study

Analysis population for the primary outcome, as defined in the registry: All participants who completed at least one six-hour observation period. Participants completed both arms in a crossover design.

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: A total of 33 subjects were randomized into the study. Two participants withdrew from the study before study treatment began, one due to scheduling conflicts and the other was lost to follow-up.

6. Primary Endpoint

The registry lists the primary outcome as Incremental Area Under the Curve of Postprandial Glucose Following the First Meal, measured over 6 hours following first meal.

The primary endpoint is incremental area under the curve (iAUC) of postprandial glucose during the six hours following the first meal. The registry says it is calculated from continuous glucose monitoring values using a trapezoidal method. The calculation sums glucose values above the starting glucose for the observation period, and the reported unit is (mg/dl*min)/1000.

In general, an area-under-the-curve measure combines the height and duration of a measured response over time. The incremental version focuses on the amount above the starting value rather than treating the starting level itself as part of the increase. This can describe accumulated post-meal glucose exposure, rather than only a single glucose reading or a peak value. Because readings are collected over time, the measure reflects the course of the response during the specified observation window.

The endpoint is used to compare the two delivery strategies on post-meal glucose exposure under the study conditions. It does not by itself describe glucose over a full day, effects beyond the observation period, or longer-term health outcomes. The registry defines the primary population as participants who completed at least one six-hour observation period. The posted arm means are 18.1 for insulin and pramlintide and 20.9 for insulin only. Those group summaries are descriptive; the registry’s inferential result comes from its mixed-model analysis, and its adjusted estimate differs from the simple unadjusted recalculation.

7. Results Posted in the Registry

• Insulin Only Arm: mean 20.90 versus 18.10 on control; difference 2.80 (95% CI -3.82 to 9.42), standardized effect d = 0.21; z-test p = 0.407.

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.

Incremental Area Under the Curve of Postprandial Glucose Following the Second Meal

• 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:
  • Insulin Only Arm: mean 23.40 versus 11.00 on control; difference 12.40 (95% CI 6.88 to 17.92), standardized effect d = 1.12; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Insulin Only Arm than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percent of Time With Sensed Glucose Between 70 - 180 mg/dl Following Second Meal

• 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:
  • Insulin Only Arm: mean 49.30 versus 74.40 on control; difference -25.10 (95% CI -36.26 to -13.94), standardized effect d = -1.13; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Insulin Only Arm than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Net Area Under the Curve of Postprandial Glucose Following the First Meal

• 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:
  • Insulin Only Arm: mean 15.00 versus 14.90 on control; difference 0.10 (95% CI -8.55 to 8.75), standardized effect d = 0.01; z-test p = 0.982.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Insulin Only Arm and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover several aspects of post-meal glucose response, including incremental or net area under the curve and the percentage of time in a specified glucose range. The posted results are not uniform across measures: some show more separation between the arm summaries, while another shows very little separation. This broad pattern offers context about outcomes beyond the primary endpoint, but it does not resolve the disagreement between the sponsor’s primary model and the unadjusted primary recalculation.

These outcomes relate to the primary question because they also describe glucose responses during the clinic study, with some focused on the second meal or on time in a range rather than accumulated postprandial exposure. They are distinct endpoints, however, and should not be treated as alternate estimates of the primary endpoint. Differences in outcome definition and observation period mean that their estimates answer related but non-identical questions.

The registry lists 46 posted secondary outcomes, while the broader record lists 48 outcome measures. It reports no sponsor analyses for the secondary comparisons summarized in the record. The displayed comparisons are unadjusted recalculations from summary statistics. The registry does not report a multiplicity adjustment for these results. In general, testing many outcomes creates more opportunities for apparently notable results to occur by chance, so unadjusted secondary findings carry less weight than a prespecified, appropriately analyzed primary result.

The registry’s primary result should remain the main inferential focus, with secondary measures treated as supportive or exploratory descriptions rather than independent confirmation. The full secondary analysis plan, prespecification status, and approach to multiplicity are not reported in the registry record. Without those details, the pattern across secondary outcomes can be described, but it cannot establish which results were intended as confirmatory or how their collective uncertainty was addressed.

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

• Incremental Area Under the Curve of Postprandial Glucose Following the Second Meal
• Percent of Time With Sensed Glucose Between 70 - 180 mg/dl Following Second Meal
• Net Area Under the Curve of Postprandial Glucose Following the First Meal
• Net Area Under the Curve of Postprandial Glucose Following the Second Meal
• Net Area Under the Curve of Postprandial Glucose
• Percent of Time With Sensed Glucose <70 mg/dL Following First Meal
• Percent of Time With Sensed Glucose <70 mg/dL Following Second Meal
• Percent of Time With Sensed Glucose <70 mg/dL

9. Statistical Interpretation

10. Statistical Methods Explained

What does the primary mean difference represent?

A mean difference expresses the distance between two group averages in the outcome’s original units. Its sign depends on the order of subtraction. The recalculation uses insulin only minus insulin and pramlintide, yielding 2.8. The sponsor’s mixed-model estimate is -5.9, and the registry identifies it as an adjusted mean difference. Because the estimates have different signs and magnitudes, they should not be treated as interchangeable. The record does not provide enough detail to establish whether differences in contrast coding, model adjustment, or another aspect of analysis account for the disagreement.

Why use a mixed model in a crossover study?

In general, a mixed model can represent both the treatment contrast and the dependence between repeated measurements from the same participant. That dependence matters because observations from one participant are not generally independent of one another. A model can also include specified design or participant-level terms when those are part of its analysis plan. The registry reports a mixed-model analysis but does not report its full formula, included terms, covariance structure, missing-data assumptions, or estimation details. Those features should not be inferred from the label alone.

A crossover design differs from a parallel-group comparison because participants complete both strategies. In general, within-participant information can contribute to the treatment comparison, but the analysis may also need to account for the periods and sequence of exposure. Whether and how the sponsor’s model handled those aspects is not reported in the registry record. The simple recalculation does not use the paired participant-level observations; it uses posted group summaries, so it cannot reproduce a model that accounts for within-participant structure.

What do the recalculated confidence interval and p-value mean?

The recalculated interval, from -3.823 to 9.423, describes a range of effect values compatible with the simple unadjusted calculation under its assumptions. In general, a confidence interval communicates both the estimated contrast and its uncertainty. An interval spanning zero is compatible with no difference under that calculation, as well as with values on either side of zero. The recalculated p-value of 0.407 is not proof that the strategies are identical; it indicates that the posted summaries do not yield strong evidence against a zero difference using this unadjusted approach.

The registry’s reported confidence interval, from -10.8 to -1.1, is attached to the adjusted estimate of -5.9. Its p-value is 0.017. These values belong to the sponsor’s mixed-model analysis, not to the recalculation. In general, a p-value measures how unusual the data would be under a specified null model; it does not measure the probability that the null hypothesis is true or the size of a clinical effect. The registry does not report further details of the model’s hypothesis-testing procedure.

What do the descriptive standard deviations add?

The posted standard deviations are 13.6 for insulin and pramlintide and 13.0 for insulin only. In general, a standard deviation describes variation among observed outcome values around a group mean. It is not the same as the uncertainty in the mean difference, and it does not show how strongly paired observations within participants are related. The recalculation also reports a pooled standard deviation of 13.3 as an input to its unadjusted comparison. That pooled summary cannot capture all of the information in a participant-level crossover model.

The recalculation’s estimated standard errors for the arm means are 2.443 and 2.335. Standard errors describe estimation uncertainty rather than the spread of individual observations. The registry’s adjusted model has its own reported confidence interval; the record does not provide the model’s standard error or enough information to independently reconstruct it. Differences in the approach to repeated observations and adjustment can produce estimates that are not recoverable from the arm means and standard deviations alone.

Why can the reported analysis take precedence?

The recalculation is explicitly an unadjusted analysis of posted summary statistics. It does not have the participant-level data, and it does not reproduce the sponsor’s mixed-model specification. When the sponsor reports an analysis intended for the randomized crossover design and that analysis conflicts with a simple recalculation, the sponsor’s own result takes precedence as the trial’s reported analysis. That precedence does not resolve the discrepancy; it means the recalculation should not be presented as if it were the registry’s primary inferential result.

For this record, important methodological details remain unavailable: the original sample-size justification, full model specification, handling of missing outcome data, sequence and period effects, and any planned interim analysis are not reported in the registry record. General statistical principles can explain why such details matter, but cannot establish what the investigators did. Accordingly, the posted estimates can be described precisely, while the reason for their disagreement remains uncertain.

11. Confidence Intervals and Precision

The sponsor’s reported primary estimate is an adjusted mean difference of -5.9, with a 95% confidence interval from -10.8 to -1.1. The interval does not include zero, and the reported p-value is 0.017. It conveys uncertainty around the sponsor’s model-based estimate, conditional on that analysis and its assumptions. The registry labels the result as a superiority analysis, but the interval alone does not indicate whether the magnitude is clinically important.

The unadjusted recalculation gives a mean difference of 2.8, with a 95% confidence interval from -3.823 to 9.423 and p = 0.407. This interval spans zero and is broad relative to the point estimate, so the summary-statistic comparison is compatible with a range of possible contrasts. It does not establish equivalence or prove that the strategies have identical outcomes.

The two intervals arise from different analyses and should not be combined into one estimate. The recalculated interval is based on posted group summaries; the sponsor’s interval comes from the reported mixed model. The registry does not provide sufficient model details or participant-level paired data to explain the discrepancy or reproduce the reported interval independently. The difference in conclusions therefore limits how confidently a reader can interpret the primary comparison from the record alone.

In general, interval width reflects precision: narrower intervals indicate less uncertainty under the analysis, while wider intervals leave a broader range of compatible values. Precision is not the same as validity. An interval can be narrow while depending on assumptions that are not fully documented. Here, the sponsor interval and the recalculated interval should each be read in the context of their respective methods and the unresolved difference between them.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm, not total events. They are illustrations based on the observed effect rather than the study’s original design. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; each planning scenario uses the stated fraction of the observed effect. The trial’s own original sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm for a design intended to have an 80% chance of detecting the specified effect under those assumptions. The 90% power column gives the corresponding number for a 90% chance. These are planning probabilities under a statistical model, not guarantees about the result of a future study. They do not describe the chance that a treatment works or the chance that the observed result is true.

Rows for 100%, 75%, and 50% of the observed effect show how the planning requirement changes as the assumed target effect becomes smaller. Smaller effects generally require more participants to detect with the same power and significance level. The recalculated figures are not observed power; they are hypothetical planning illustrations, and the registry’s own design assumptions are not reported.

A sample-size curve should be read as a visual expression of that same relationship between an assumed effect and the participant count required under the stated planning assumptions. It is not a record of participants enrolled or a forecast of the trial’s actual result. Because the observed primary estimate is itself subject to the discrepancy between the sponsor analysis and the recalculation, planning values based on that observed effect should be treated cautiously.

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 = 2.800; pooled standard deviation σ = 13.303.
2. n = 2 × (1.96 + 0.842)² × 13.303² / 2.800² = 354.4, rounded up to 355 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 <- 2.8                      # observed difference in means
sigma <- 13.3033830283879                     # 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(6422325)
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 = 355 (80% power), 475 (90% power)
 75% of observed effect: n per arm = 630 (80% power), 844 (90% power)
 50% of observed effect: n per arm = 1,418 (80% power), 1,898 (90% power)
power.t.test: 355.3 
Simulated power at n = 355 per arm: 0.797 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary analysis as a mixed-model adjusted mean difference of -5.9, with a 95% confidence interval from -10.8 to -1.1 and p = 0.017. It labels the analysis as superiority. The posted arm means are 18.1 for insulin and pramlintide and 20.9 for insulin only.

A simple unadjusted recalculation from those summaries, stated as insulin only minus insulin and pramlintide, gives 2.8, with a 95% confidence interval from -3.823 to 9.423 and p = 0.407. The contrast direction may depend on how the comparison is coded, but the difference in magnitude and statistical conclusion is not explained by sign convention alone. The registry record flags this discrepancy.

The recalculation is not a substitute for the sponsor’s analysis because it does not use participant-level paired data or the reported mixed-model approach. The sponsor’s own analysis takes precedence. However, the record does not provide enough detail about the model or the data to reconcile the reported adjusted result with the simple summary-statistic calculation. Both results should therefore be described with their methods attached, rather than blending them or implying that one independently validates the other.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several outcomes or comparisons are tested: the more opportunities there are to find a small p-value, the greater the risk that at least one apparently notable result occurs by chance. This is a general statistical concern, not a claim that any particular posted result is false. The record lists 48 outcome measures and 46 posted secondary outcomes, alongside the primary endpoint. It does not report whether the investigators used a multiplicity adjustment, hierarchical testing strategy, or another method to control the overall chance of false-positive findings.

The registry reports a mixed-model result for the primary endpoint, but a full statistical analysis plan and the exact specification of that model are not reported in the registry record. The record also does not report whether the primary endpoint and analysis were prespecified before examining the results, or whether any interim analyses were conducted. These omissions prevent a complete assessment of how the reported hypothesis tests were planned and interpreted.

The primary population is described as participants who completed at least one six-hour observation period, and the registry says participants completed both arms in the crossover design. The outcome count is 31 in each arm for the primary endpoint, whereas enrollment is 33. The reasons for the difference and the handling of incomplete observations are not reported in the registry record. Some secondary outcomes have 30 participants in the insulin and pramlintide arm and 31 in the insulin-only arm; reasons for these outcome-specific counts are also not reported.

In general, missing observations can affect both precision and the validity of a comparison, depending on why data are missing and how the analysis handles them. The registry does not report the missing-data assumptions, imputation approach, or sensitivity analyses. It also does not report the crossover sequence, period-effect analysis, or any washout details. These absences do not establish that such procedures were omitted; they mean that the registry record does not document them.

16. 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.

Most frequent non-serious adverse event terms

The registry reports zero serious adverse events in each arm, among 31 participants at risk in the insulin-only arm and 31 at risk in the insulin and pramlintide arm. It also reports zero deaths in both arms. These counts describe the events posted for the study and the participants listed as at risk; they do not establish that no unreported events occurred.

For other adverse events, the registry reports 17 affected participants among 31 at risk in the insulin-only arm and zero affected participants among 31 at risk in the insulin and pramlintide arm. The record does not provide serious adverse event terms, and no top serious-event terms are listed. It does not identify the types or severity of the other adverse events in the registry record, nor does it report an analysis comparing safety between the arms.

These figures should be read as event counts recorded by the registry, not as evidence that an arm caused or prevented an event. In a crossover study, participants may contribute observations under both strategies, and the registry’s adverse-event summary does not provide further detail on attribution, timing, or the analysis population. That information is not reported in the registry record.

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

The registry’s primary mixed-model analysis reports an adjusted mean difference of -5.9, with a 95% confidence interval from -10.8 to -1.1 and p = 0.017. The simple unadjusted recalculation from posted group summaries gives a different result: 2.8 when expressed as insulin only minus insulin and pramlintide, with a 95% confidence interval from -3.823 to 9.423 and p = 0.407. Because the discrepancy is material, the sponsor’s own analysis takes precedence, while the recalculation remains a useful indication that the group summaries alone do not reproduce the reported result.

The primary measure concerns accumulated glucose above starting glucose during the six hours after the first meal. It does not establish effects on other glucose outcomes, on daily glucose management outside the study period, or on longer-term health outcomes. The study includes clinic meals and a closed-loop delivery setup; its findings should be interpreted within those recorded conditions.

A statistically significant result is not by itself a measure of clinical importance. The registry does not report a threshold for a clinically important difference on this endpoint. Nor does a result that is not statistically significant in a recalculation establish that the strategies are equivalent. Precision, outcome meaning, analysis choice, and the unresolved discrepancy all matter.

The posted secondary outcomes describe additional glucose measures, but the registry does not report multiplicity handling for them. Their unadjusted results should not be treated as conclusive confirmation of the primary result. Similarly, the absence of serious adverse events in the posted counts is a description of the record, not proof of an absence of risk.

Overall, the record supports a careful account of the reported model-based finding and its uncertainty, alongside a clear note that a simple recalculation does not agree. It does not support an unqualified conclusion about the comparative effectiveness of the strategies beyond the measured endpoint and study conditions.

18. Why This Trial Matters Statistically

This trial is statistically notable because it uses a randomized crossover design for a continuous post-meal glucose endpoint. Such a design can make within-participant comparisons relevant, but it also makes the analysis of repeated observations important. The registry reports a mixed-model analysis, while the available arm summaries allow only a simple unadjusted recalculation. The difference between those analyses illustrates why summary means and standard deviations cannot always reproduce a model-based crossover result.

The primary result also demonstrates the importance of reporting enough analytical detail for readers to understand an estimate. The sponsor’s adjusted mean difference, confidence interval, and p-value are stated, but the model specification and details needed to reconcile the result with the posted summaries are not reported in the registry record. Clear reporting of contrast direction, model terms, period and sequence handling, and missing-data methods would help readers assess how the estimate was obtained.

The secondary results add another statistical lesson: several related endpoints can produce a varied pattern, and unadjusted tests across many outcomes need cautious interpretation. The posted results can describe multiple dimensions of glucose response, but the registry does not report how multiplicity was addressed or which secondary analyses were confirmatory.

Finally, the planning illustrations show how sample-size requirements depend on the effect assumed for planning. They are not the original study rationale and are not observed power. Keeping those planning calculations separate from the completed trial’s results helps avoid confusing a hypothetical future design with evidence about the trial itself.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The main trial-specific limitation in interpreting the primary result is the discrepancy between the sponsor’s reported mixed-model estimate and the unadjusted recalculation from the posted group summaries. The sponsor’s analysis takes precedence, but the registry record does not provide enough detail to explain why the estimates differ in magnitude and inferential conclusion. The recalculation cannot account for the within-participant structure of a crossover design.

The registry lists enrollment as 33, while 31 participants are reported for each arm on the primary outcome. Some secondary outcomes report 30 participants in one arm and 31 in the other. Reasons for these differences, the extent of missing data, and the handling of incomplete observations are not reported in the registry record. This limits assessment of how the analysis population compares with the enrolled group.

Other design and analysis details are also absent from the registry record, including the randomization sequence, period and sequence handling, washout arrangements, full mixed-model specification, original sample-size justification, and any interim analysis. Their absence from the record should not be interpreted as proof that investigators did not consider them; it means readers cannot assess them from the registry information.

The primary endpoint is restricted to incremental postprandial glucose exposure during the six hours following the first meal in a clinic study. It does not represent all aspects of glucose management or longer-term outcomes. The registry also lists many secondary measures but does not report a multiplicity strategy, making unadjusted secondary findings less definitive. Finally, the adverse-event summaries provide counts but not the detailed event descriptions or attribution needed for a fuller safety interpretation.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Two Way Crossover Closed Loop Study Insulin vs Insulin and Pramlintide — NCT06422325.
• Registry record last updated 2026-06-09; status last verified 2026-02.
• Results first posted 2026-03-05.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

The registry describes a completed randomized, unmasked crossover study comparing an MPC closed-loop system in insulin-only mode with the system in insulin/pramlintide mode among people with Type 1 Diabetes. Enrollment is listed as 33. The primary endpoint is incremental area under the curve of postprandial glucose during the six hours following the first meal.

The sponsor reports an adjusted mean difference of -5.9, a 95% confidence interval from -10.8 to -1.1, and p = 0.017. A simple unadjusted recalculation gives 2.8, with a 95% confidence interval from -3.823 to 9.423 and p = 0.407; the sponsor’s own analysis takes precedence, but the discrepancy is unresolved in the registry record. Serious adverse events and deaths are reported as zero in both arms. Further details about the analysis plan, missing data, and multiplicity are not reported in the registry record.