A Study of CT-868 in Type 1 Diabetes Mellitus: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study of CT-868 in Type 1 Diabetes Mellitus (NCT06062069), a randomized phase 2 study. The primary outcome is Change From Baseline in Glycated Hemoglobin (HbA1c) (%) at Week 16.

2. Clinical Question

The central statistical question is about the size and precision of the between-group differences, rather than whether a change occurred within any one group. The registry reports least-squares mean changes from baseline and model-based comparisons using a mixed-effect model of repeated measures. It also reports the analyzed population as participants from the intention-to-treat population who had data available for analysis.

HbA1c is the primary glycemic measure in this trial. Secondary outcomes extend the question to body weight, achievement of specified HbA1c targets, and insulin doses. The record also reports adverse-event counts. These outcomes give additional context, but they do not replace the primary comparison or establish the primary result on their own.

3. Trial Design

This is a completed Phase 2, randomized, double-blind, placebo-controlled, parallel-group study. The registry record lists enrollment as 111 and describes quadruple masking. Participants were assigned to one of three CT-868 dose groups or a placebo group. The planned treatment period described in the record was 16 weeks.

The CT-868 groups received once-daily subcutaneous injections titrated to up to 1.8 mg, up to 4.1 mg, or up to 6.6 mg. The placebo group received a matching injection. Participants continued standard diabetes care using an insulin pump or multiple daily injections. The record also describes guidance on blood glucose monitoring and diet and exercise recommendations. Thus, the comparison concerns adding assigned study injections to ongoing insulin care, not replacing insulin care with the study injection.

The study’s primary outcome was change in HbA1c from baseline to Week 16. Baseline was defined as the last available non-missing value before the first dose of randomized study drug. The primary analysis used a mixed-effect model of repeated measures. The record identifies an intention-to-treat population comprising all randomized participants, while noting that the number analyzed for an outcome is the number with data available for analysis.

The registry record does not report the original sample-size justification, the trial’s planned power, or the complete statistical analysis plan. It also does not report the allocation ratio or details of the randomization procedure. Those design details should not be inferred from the observed group counts. The record does identify the study as randomized and parallel-group, but does not provide further procedural detail about allocation concealment or masking implementation.

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 in a 1:1:1:1 ratio to 1 of the 4 arms- Arm 1: Placebo, Arm 2: CT-868 titrated to 1.8 milligrams per day (mg/day), Arm 3: CT-868 titrated to 4.1 mg/day, and Arm 4: CT-868 titrated to 6.6 mg/day.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: ITT population included all randomized participants. Overall number analyzed is the number of participants with data available for analysis.

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: Intent-to-treat (ITT) population included all randomized participants.

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline in Glycated Hemoglobin (HbA1c) (%) at Week 16, measured over Baseline (Day 1) to Week 16.

The primary endpoint is change in glycated hemoglobin (HbA1c), expressed as a percentage, from baseline to Week 16. The record defines baseline as the last available non-missing value before the first dose of randomized study drug. A negative change means that the recorded Week 16 value was lower than the baseline value, on the HbA1c scale.

HbA1c is used in this study as a measure of glycemic control. It provides a continuous outcome, so the analysis can compare the average change across assigned groups rather than reducing the outcome to whether each participant crossed a particular threshold. The registry reports least-squares means, which are model-based group estimates, and differences in those means between each CT-868 group and placebo.

The endpoint is analyzed using a mixed-effect model of repeated measures (MMRM), which uses repeated outcome measurements over time. The listed primary timeframe is baseline to Week 16, while the registry’s model description identifies the repeated-measures approach. The record does not report the model’s full specification, including its covariates or covariance structure. Nor does it report further details about how missing outcome measurements were handled beyond defining the analyzed number as participants with data available for analysis.

As a general statistical point, a continuous endpoint can retain information about the range of observed values, whereas a threshold outcome classifies participants into categories. That is one reason a continuous measure can serve as a primary endpoint while threshold-based HbA1c outcomes appear as secondary measures.

7. Results Posted in the Registry

• Arm 2: CT-868 Titrated to 1.8 mg: mean -0.43 versus -0.25 on control; difference -0.18 (95% CI -0.47 to 0.11), standardized effect d = -0.38; z-test p = 0.217.
• Arm 3: CT-868 Titrated to 4.1 mg: mean -0.59 versus -0.25 on control; difference -0.34 (95% CI -0.62 to -0.06), standardized effect d = -0.73; z-test p = 0.017.
• Arm 4: CT-868 Titrated to 6.6 mg: mean -0.45 versus -0.25 on control; difference -0.20 (95% CI -0.48 to 0.08), standardized effect d = -0.42; z-test p = 0.168.

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.

Percent Change From Baseline in Body Weight at Week 16

• 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 errors.
• Result:
  • Arm 2: CT-868 Titrated to 1.8 mg: mean -3.26 versus 0.29 on control; difference -3.55 (95% CI -5.91 to -1.19), standardized effect d = -0.91; z-test p = 0.003.
  • Arm 3: CT-868 Titrated to 4.1 mg: mean -6.43 versus 0.29 on control; difference -6.72 (95% CI -9.04 to -4.40), standardized effect d = -1.71; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Arm 2: CT-868 Titrated to 1.8 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Arm 3: CT-868 Titrated to 4.1 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percentage of Participants Achieving HbA1c Target of <7.0% at Week 16

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Arm 2: CT-868 Titrated to 1.8 mg: 45.0% (9/20) versus 36.4% (8/22) on control; risk difference 8.6 percentage points (95% CI -21.0 to 38.3), risk ratio 1.24 (0.59–2.58); unadjusted two-proportion z-test p = 0.569.
  • Arm 3: CT-868 Titrated to 4.1 mg: 66.7% (14/21) versus 36.4% (8/22) on control; risk difference 30.3 percentage points (95% CI 1.8 to 58.8), risk ratio 1.83 (0.98–3.44); unadjusted two-proportion z-test p = 0.047.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm 2: CT-868 Titrated to 1.8 mg and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Arm 3: CT-868 Titrated to 4.1 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percentage of Participants Achieving HbA1c Target of ≤6.5% at Week 16

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Arm 2: CT-868 Titrated to 1.8 mg: 20.0% (4/20) versus 9.1% (2/22) on control; risk difference 10.9 percentage points (95% CI -10.3 to 32.2), risk ratio 2.20 (0.45–10.74); unadjusted two-proportion z-test p = 0.313.
  • Arm 3: CT-868 Titrated to 4.1 mg: 33.3% (7/21) versus 9.1% (2/22) on control; risk difference 24.2 percentage points (95% CI 0.8 to 47.7), risk ratio 3.67 (0.86–15.68); unadjusted two-proportion z-test p = 0.051.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm 2: CT-868 Titrated to 1.8 mg and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm 3: CT-868 Titrated to 4.1 mg and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes broaden the study’s measurement beyond the primary HbA1c change. They cover percent change in body weight, HbA1c at several time points, achievement of HbA1c thresholds at Week 16, and changes in total daily, basal, and bolus insulin doses. The outcomes therefore include both continuous measures and threshold-based summaries. The registry lists 44 outcome measures and indicates that 43 secondary outcomes were posted.

Across the posted secondary results, the pattern is not identical for every outcome or dose group. The continuous body-weight outcome has negative estimated changes in the CT-868 groups and a positive estimate in placebo. The posted threshold summaries vary across groups and thresholds. This broader pattern offers context for the primary endpoint, but it does not establish that changes in one outcome caused changes in another. The registry record does not report the full results for every secondary measure in the registry record for this analysis; unreported results are not reported in the registry record.

Secondary outcomes are useful for describing what else was measured and for seeing whether the primary result sits within a wider pattern. They remain secondary to the prespecified primary question. The record does not report a multiplicity adjustment plan, and there are many outcome measures and analyses. General statistical explanation: when many comparisons are examined, some may appear notable by chance even when there is no underlying effect. Unadjusted secondary results therefore carry less inferential weight than the primary analysis and should be treated as exploratory context rather than conclusive independent confirmation.

Interpretation also depends on the nature of each outcome. A change in a continuous measure and the proportion crossing a threshold are not interchangeable summaries. Threshold outcomes depend on where the threshold is set and can have limited precision when counts are small. The secondary outcomes can help characterize the observed study results, but the available information does not support a single unified conclusion across all measures.

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

• Percent Change From Baseline in Body Weight at Week 16
• Change From Baseline in HbA1c (%) at Weeks 4, 8, and 12
• Percentage of Participants Achieving HbA1c Target of <7.0% at Week 16
• Percentage of Participants Achieving HbA1c Target of ≤6.5% at Week 16
• Percentage of Participants Achieving HbA1c Target of <5.7% at Week 16
• Change From Baseline in Total Daily Insulin Dose at Weeks 8 and 16
• Change From Baseline in Basal Insulin Dose at Weeks 8 and 16
• Change From Baseline in Bolus Insulin Dose at Weeks 8 and 16

9. Statistical Interpretation

10. Statistical Methods Explained

What does the mixed-effect model do?

The primary analysis used a mixed-effect model of repeated measures (MMRM). In general, a repeated-measures model analyzes observations collected at more than one time point while allowing measurements from the same participant to be related. It can estimate group patterns over time while accounting for that within-participant relationship. The registry record identifies MMRM but does not report the full model specification, such as its covariates, covariance structure, or exact estimation details. Those features should not be assumed.

The primary endpoint is change from baseline to Week 16, and the registry reports least-squares means for the groups. In general, a least-squares mean is a model-based estimate of a group mean, potentially adjusted for terms in the model. Because the model terms are not reported in full, the particular adjustments behind these estimates are not known from the registry record. The sponsor’s reported difference in least-squares means compares each CT-868 group with placebo within that model.

How should the reported difference be read?

A difference in least-squares means is the estimated CT-868 group change minus the placebo group change, as expressed in the sponsor’s comparison. A negative estimate indicates a more negative estimated change for the CT-868 group than for placebo. It does not mean that every participant had that change, nor does it describe the distribution of individual responses. Group estimates and contrasts are averages, and the interval communicates uncertainty around the contrast.

The registry presents a 90% confidence interval and a p-value for each sponsor-reported primary comparison. A confidence interval is a range of values compatible with the data and the specified analysis under its assumptions. A p-value measures how unusual the observed data, or more extreme data, would be under a stated null hypothesis and analysis model. Neither quantity is the probability that the null hypothesis is true, and neither by itself measures clinical importance.

What is different about the recalculation?

The recalculated contrasts use posted group summary statistics and are labeled unadjusted. They are simple comparisons, not a reproduction of the sponsor’s MMRM. The posted arm values are least-squares means with standard errors, and the recalculation approximates a pooled standard deviation from those errors. That approximation does not recreate the repeated-measures model or any model adjustments. As a result, its interval and p-value can differ from the sponsor’s result even when the estimated contrast is similar.

The record flags a discrepancy between the recalculation and the sponsor analysis. The sponsor’s own analysis takes precedence for interpreting the trial’s primary result. The recalculation can help illustrate what a simple comparison of the posted summary statistics yields, but it should not be treated as the trial’s definitive inferential analysis.

Why do repeated measurements and over-dispersion matter?

General statistical explanation: repeated observations on one participant are usually not independent. A model that treats them as independent can misstate uncertainty. Repeated-measures methods account for the dependence through a model for how observations relate over time. The specific correlation assumptions used in this trial are not reported in the registry record.

General statistical explanation: over-dispersion means that observed variability is greater than a statistical model’s assumed variability. When present, it can make standard errors too small if the analysis does not account for it, leading to intervals that are too narrow and p-values that appear more decisive than warranted. The registry record does not report an over-dispersion assessment, so no claim can be made about whether it arose in this trial.

What do the secondary outcome analyses add?

The secondary outcomes include continuous measures, such as percent change in body weight and changes in insulin doses, and binary outcomes, such as the percentage reaching specified HbA1c thresholds. General statistical explanation: continuous outcomes summarize a measure on its scale, while binary outcomes summarize the proportion meeting a defined criterion. Binary outcomes can be less statistically informative when event counts are limited, and their uncertainty can be substantial. Each endpoint also raises its own questions about missing data and analysis choices.

The registry lists multiple secondary measures and analyses, but it does not report a multiplicity adjustment plan. When many outcomes or comparisons are tested, the chance of at least one apparently notable result can increase. For that reason, unadjusted secondary p-values should generally be interpreted cautiously and in the context of the full set of outcomes. The number of outcome measures and analyses listed in the record signals that results need to be considered as a collection, not selected solely because an individual comparison has a small p-value.

What does the analysis population mean?

The registry describes the intention-to-treat population as all randomized participants. It also states that the overall number analyzed is the number of participants with data available for analysis. These descriptions distinguish the target population for analysis from the number contributing data to a particular outcome. The record does not provide further detail on missing-data assumptions, imputation, or sensitivity analyses. In general, missing outcome data can affect estimates if the participants with observed data differ systematically from those without observed data; the extent and direction of any such effect cannot be determined from the reported information alone.

11. Confidence Intervals and Precision

The sponsor’s primary comparisons are reported with 90% confidence intervals. For CT-868 titrated to 1.8 mg, the reported difference in least-squares means is -0.18, with an interval from -0.42 to 0.06. For CT-868 titrated to 4.1 mg, the estimate is -0.34, with an interval from -0.57 to -0.10. For CT-868 titrated to 6.6 mg, the estimate is -0.20, with an interval from -0.44 to 0.04.

As a general statistical explanation, a confidence interval describes the uncertainty around an estimate under the analysis model. A narrower interval indicates greater precision than a wider interval, while an interval spanning zero includes the possibility of no between-group difference on the modeled scale. The intervals for the 1.8 mg and 6.6 mg comparisons include zero; the interval for the 4.1 mg comparison does not. This distinction does not by itself establish clinical importance, and it does not account for questions such as multiplicity or the broader evidence base.

The recalculated intervals are not the same as the sponsor’s intervals. They are based on unadjusted comparisons reconstructed from posted summary statistics, with standard deviations approximated from standard errors. They are therefore not direct replacements for the MMRM intervals. Because the registry record flags a discrepancy, the sponsor’s own analysis takes precedence.

Precision is also limited by the analyzed group sizes reported for the primary endpoint: 22.0 in placebo, 20.0 in the 1.8 mg group, 21.0 in the 4.1 mg group, and 21.0 in the 6.6 mg group. These values are outcome analysis counts, not necessarily the full number assigned to each group. The record does not report a precision target or the original sample-size justification, so the observed intervals should be read as the available uncertainty estimates rather than as proof that the study was designed to achieve a particular degree of precision.

12. Planning a Similar Trial: Sample Size

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

The sample-size figures are planning illustrations based on fractions of the observed effect, not the original design calculations for this trial. For these comparisons, the figures are participants per arm, not total participants. The stated 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. The registry record does not report the trial’s own original sample-size assumptions or justification.

The 80% power column means the illustrated number of participants per arm for an 80% chance of detecting the specified effect under the stated assumptions, if that effect and the other assumptions were correct. The 90% power column gives the corresponding illustration for a 90% chance. These are design-planning concepts, not guarantees for a future study. The figures use the observed effect as their reference, so they are sensitive to how large or small that observed estimate is.

Each row represents a different assumed fraction of the observed effect. Planning for 75% of the observed effect or 50% of the observed effect means targeting a smaller effect than planning for 100% of the observed effect. Smaller effects require more participants to detect under otherwise similar assumptions. The figures can therefore rise substantially when the assumed target effect is reduced.

The curve should be read as a visual version of this relationship between assumed effect size and required sample size, not as an additional result from the trial. These planning figures are not observed power. Observed power is not a useful way to interpret the results after the study; the confidence intervals and the estimated effects provide more direct information about uncertainty.

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 = -0.180; pooled standard deviation σ = 0.472.
2. n = 2 × (1.96 + 0.842)² × 0.472² / -0.180² = 107.8, rounded up to 108 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 <- -0.18                      # observed difference in means
sigma <- 0.471761645325264                     # 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(6062069)
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 = 108 (80% power), 145 (90% power)
 75% of observed effect: n per arm = 192 (80% power), 257 (90% power)
 50% of observed effect: n per arm = 432 (80% power), 578 (90% power)
power.t.test: 108.8 
Simulated power at n = 108 per arm: 0.799 (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 sponsor’s primary analysis is the MMRM comparison of least-squares means. It reports differences of -0.18, -0.34, and -0.20 for the CT-868 groups titrated to 1.8 mg, 4.1 mg, and 6.6 mg, respectively, each compared with placebo. The corresponding 90% confidence intervals and p-values are reported in the registry record. These are the trial’s own model-based results and are the primary basis for describing the posted findings.

The recalculated results are simple, unadjusted comparisons derived from the posted summary statistics. They use approximate standard deviations and do not reproduce the MMRM. For the primary outcome, the recalculated estimated contrasts are similar in direction and close in value to the sponsor’s estimates, but their intervals and unadjusted p-values are not identical. Differences can arise because the reconstruction does not use the same repeated-measures model and its full specifications.

The registry record flags a discrepancy. In keeping with that flag, the sponsor’s own analysis takes precedence; the recalculation is best treated as a limited cross-check of the summary statistics. It should not be used to replace the sponsor’s model-based inference or to claim that the trial’s analysis has been reproduced exactly.

15. Multiplicity, Missing Data and Analysis Populations

The registry record lists a broad set of outcomes and analyses, but it does not report a multiplicity adjustment plan. Multiplicity arises when a study evaluates several outcomes, time points, dose groups, or statistical comparisons. General statistical explanation: as the number of tests increases, the chance of observing at least one small p-value by chance can also increase. Adjustments or a prespecified testing hierarchy can address some of this concern, but no such procedure should be assumed when it is not reported.

The primary outcome remains the clearest focus for interpretation. Secondary results can add descriptive context, but their p-values should not be treated as if each were the only test conducted. The record does not state whether the sponsor used a formal hierarchy, adjusted significance levels, or another approach to control the overall error rate. That information is not reported in the registry record.

The record identifies the intention-to-treat population as all randomized participants and says the number analyzed is the number with data available for analysis. It does not provide further information about missing measurements, the amount of missingness by group, reasons for missing data, imputation, or sensitivity analyses. In general, missing data can affect estimates when the availability of measurements is related to the outcome or to participant characteristics. The reported description alone does not establish whether that concern affected these results.

The MMRM description indicates that repeated measurements were modeled, but the full model specification is not reported. In particular, the registry record does not state the covariates, covariance structure, handling of measurements after treatment discontinuation, or assumptions used for incomplete repeated outcomes. These details matter for understanding exactly how the model generated its estimates. They cannot be inferred from the name of the method alone.

The result should therefore be read with two distinctions in mind: the registry identifies the population intended for analysis, while outcome-specific counts reflect data availability; and the reported primary model is not accompanied by the complete details needed to assess all statistical assumptions. The registry record does not report interim analyses or a detailed analysis plan.

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 serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: constipation (5.6%), hyponatraemia (5.6%), infected bite (2.9%).

The registry reports serious adverse events by group using the number at risk and the number affected. The placebo group had 0 serious adverse events among 29 at risk; the 1.8 mg group had 0 among 30; the 4.1 mg group had 1 among 34; and the 6.6 mg group had 2 among 18. The reported number of deaths was 0 in each group.

These are counts during the study as recorded in the registry, not estimates of comparative risk with uncertainty intervals. The groups differ in their reported numbers at risk, and the record does not provide a formal statistical comparison of serious adverse events. It also does not provide enough detail to assess timing, duration, relatedness to study treatment, or clinical circumstances for each event.

The record lists constipation and hyponatraemia at 5.6% each, and infected bite at 2.9%, among the top serious terms. Those terms are reported as listed; the available information does not establish a causal relationship to a study injection. The other adverse-event counts describe participants affected by other events, and should not be conflated with the serious adverse-event counts. Safety counts are descriptive and do not by themselves settle comparative safety.

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

The posted primary results describe average HbA1c change over the 16-week study period among participants with data available for analysis. The sponsor’s model-based comparison for the 4.1 mg group is more negative than placebo, with a 90% confidence interval that does not include zero. The reported intervals for the 1.8 mg and 6.6 mg comparisons include zero. These results are estimates with uncertainty, not a guarantee of what any individual participant experienced.

The findings do not establish that a higher dose produces a larger effect. The largest estimated primary difference is in the 4.1 mg group, and the study does not report direct statistical comparisons among CT-868 dose groups in the registry record. Nor does the primary result by itself establish what would happen outside the studied population or beyond the 16-week treatment period.

The study included overweight and obese adults with type 1 diabetes, and all participants continued standard insulin care. The comparisons therefore concern CT-868 or placebo added to that care. They do not address replacing insulin, and the record does not provide evidence about longer-term outcomes. The registry record reports secondary measures and adverse events, but those results have their own uncertainty and do not resolve the limitations of the primary comparison.

No medical recommendation follows from these statistics. Statistical significance does not equal clinical importance, and the registry record does not state a threshold for a clinically meaningful HbA1c change. A complete judgment would require clinical context, fuller safety information, and evidence beyond this trial. The results are best understood as the estimates and uncertainty reported for this particular randomized study.

18. Why This Trial Matters Statistically

This trial is statistically informative because it compares several dose levels with placebo under a randomized, blinded, parallel-group design, while participants continued standard insulin care. The structure permits estimation of group differences in HbA1c change rather than relying only on before-and-after change within a single group. The primary outcome is continuous, and the sponsor reports model-based least-squares mean contrasts with confidence intervals.

The results also illustrate why estimates and uncertainty should be read together. The group estimates are all negative, but the comparisons with placebo are not equally precise: the reported intervals for two dose comparisons include zero, while the interval for the 4.1 mg comparison does not. That variation cautions against describing the result only as a set of group averages or relying solely on p-values.

The study also demonstrates a common issue in trial interpretation: a model-based primary analysis and a simple recalculation from summary statistics can be similar without being identical. The recalculation cannot reproduce all features of the repeated-measures model. The registry record flags a discrepancy, so the sponsor analysis takes precedence.

Finally, the range of secondary outcomes highlights the distinction between primary evidence and supporting description. Body weight, HbA1c targets, insulin doses, and adverse events speak to different dimensions of the study. Their interpretation depends on precision, multiplicity, and missing-data details, some of which are not reported. Keeping these statistical distinctions visible helps readers assess what the study estimates without making claims beyond its record.

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 study’s treatment period was 16 weeks, so the reported results concern that period. Longer-term HbA1c patterns, durability, and later safety outcomes are not reported in the registry record. The population was overweight and obese adults with type 1 diabetes; the record does not establish that the findings apply to other populations.

The analyzed group counts for the primary outcome are 22.0 for placebo, 20.0 for the 1.8 mg group, 21.0 for the 4.1 mg group, and 21.0 for the 6.6 mg group. The registry describes the intention-to-treat population as all randomized participants but defines the overall number analyzed as those with data available. Further details on missing measurements, reasons for missingness, and sensitivity analyses are not reported in the registry record.

The sponsor’s primary analysis is identified as MMRM, but the registry record does not give the complete model specification. The original sample-size rationale, planned power, and full statistical analysis plan are also not reported. The record does not report a multiplicity adjustment plan despite the number of outcomes and analyses. These omissions limit assessment of model assumptions, precision targets, and the inferential status of secondary findings.

The registry record flags a discrepancy between sponsor-reported analyses and recalculations from posted summary statistics. The recalculations use approximations and are not the trial’s MMRM; sponsor results should take precedence. Safety information is presented as descriptive event counts, without formal comparative analyses or the details needed to assess event timing, treatment relatedness, or clinical course. These limitations constrain how broadly the posted results can be interpreted.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Study of CT-868 in Type 1 Diabetes Mellitus — NCT06062069.
• Registry record last updated 2026-10-28; status last verified 2026-10.
• Results first posted 2026-10-28.
• 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 record describes a completed, randomized, double-blind, placebo-controlled Phase 2 study of once-daily CT-868, titrated to three dose levels, alongside standard insulin care in overweight and obese adults with type 1 diabetes. The planned treatment period was 16 weeks, and enrollment was 111.

The primary outcome was change in HbA1c from baseline to Week 16, analyzed using MMRM. The sponsor reported a difference in least-squares means of -0.34 for the 4.1 mg group versus placebo, with a 90% confidence interval from -0.57 to -0.10 and p = 0.020. The reported intervals for the 1.8 mg and 6.6 mg comparisons included zero. The record flags a discrepancy with simple recalculations, so the sponsor’s model-based analysis takes precedence.

Secondary outcomes covered body weight, HbA1c targets, and insulin doses. Serious adverse-event counts and deaths were also reported. The original sample-size rationale, full statistical analysis plan, multiplicity approach, and detailed missing-data methods are not reported in the registry record.