A Study Comparing the Efficacy and Safety of the Morning Injection of Toujeo Versus Lantus in Patients With Type 1 Diabetes Mellitus: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study Comparing the Efficacy and Safety of the Morning Injection of Toujeo Versus Lantus in Patients With Type 1 Diabetes Mellitus (NCT02688933), a randomized phase 4 study. The primary outcome is Percentage of Time of Mean Glucose Concentration Within the Target Range of 70-180 mg/dL as Obtained From CGM.

2. Clinical Question

3. Trial Design

The registry describes a randomized, active-controlled, parallel-group phase 4 study with no masking. The official title identifies it as an open-label study. The planned treatment period was 16 weeks, and both study arms used once-daily basal insulin on top of mealtime insulin analogs. The registry lists Sanofi as sponsor and the study status as completed.

The treatment groups were HOE901-U300 and Lantus. Basal insulin doses were individually titrated until the end of Week 14 toward fasting self-measured plasma glucose levels of 80 to 100 mg/dL, while mitigating hypoglycemia. The primary endpoint was assessed during Week 15 and/or Week 16. The registry lists enrollment as 638; the primary analysis population counts were 277 for HOE901-U300 and 268 for Lantus. These are different record entries and should not be treated as interchangeable descriptions of the analysis population.

Randomization helps reduce systematic differences between groups at baseline, while an active comparator makes the question a comparison between two insulin glargine regimens rather than a comparison with no treatment. The open-label design means masking was absent. How that feature affected behavior, co-interventions, or assessment is not quantified in the registry record. The allocation ratio, randomization procedure, concealment method, and original sample-size justification are not reported in the registry record.

The primary outcome analysis used a modified intent-to-treat population rather than every randomized participant. Eligibility for that analysis required post-baseline CGM data and enough CGM values to calculate the endpoint. The registry does not report how many randomized participants were excluded from that population or give a complete account of missing CGM data.

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: A total of 638 participants were randomized in HOE901-U300 or Lantus, stratified by baseline HbA1c (\<8 %,\> =8%), frequency of basal insulin injections at Visit 1 (twice vs once daily), current continuous glucose monitoring (CGM) use at Visit 1(yes/no) and mealtime insulin titration algorithm (simple titration vs carbohydrate counting).

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Modified intent-to-treat (mITT) population that included all participants who were randomized and had a post-baseline CGM assessment and enough CGM data values to calculate the primary outcome measure, percent of time in range of 70-180 mg/dL during Week 15 (and/or Week 16).

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: Analysis was performed on randomized population that included any participant who had been allocated to a randomized treatment regardless of whether the treatment kit was used or not.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Time of Mean Glucose Concentration Within the Target Range of 70-180 mg/dL as Obtained From CGM, measured over During Week 15 and/or 16.

The primary endpoint was the percentage of time that mean glucose concentration was within the target range of 70-180 mg/dL, measured by continuous glucose monitoring during Week 15 and/or Week 16. CGM combines frequent interstitial glucose measurements with the ability to analyze glucose levels over time. In this study, the registry describes measurements every 5 minutes.

This endpoint captures how much of the observed CGM period falls within a prespecified glucose range. It therefore reflects both the level and duration of glucose exposure within that range, rather than relying on a single measurement. The registry’s primary objective was to compare this measure between morning HOE901-U300 and morning Lantus in adults with type 1 diabetes.

The reported group summaries are adjusted least-square means with standard errors from a generalized linear model with an identity link. The endpoint is expressed as a percentage of time. The primary analysis population required randomized participants to have post-baseline CGM assessment and enough CGM observations to calculate the measure. The exact amount of CGM data required is not reported in the registry record. Nor does the record specify a clinically important difference for interpreting changes in this measure.

7. Results Posted in the Registry

• Lantus: mean 55.18 versus 55.40 on control; difference -0.22 (95% CI -3.24 to 2.80), standardized effect d = -0.01; z-test p = 0.887.

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.

Mean Change From Baseline in Glucose Level During Last 4 Hours of CGM Data Collection Prior to the Next Day Basal Insulin Injection During Week 15 and/or 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:
  • Lantus: mean 5.67 versus -1.99 on control; difference 7.66 (95% CI -2.60 to 17.92), standardized effect d = 0.13; z-test p = 0.143.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Lantus and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Time Glucose Concentrations Within the Target Range of 70 to 140 mg/dL During Last 4 Hours of CGM Data Collection Prior to Next Day Basal Insulin Injection

• 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:
  • Lantus: mean 35.07 versus 36.49 on control; difference -1.42 (95% CI -5.95 to 3.11), standardized effect d = -0.05; z-test p = 0.539.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Lantus and the control. The interval gives the range of effects that remain compatible with the data.

The numerical secondary findings available in the registry cover glucose change during the last 4 hours before the next basal insulin injection and the percentage of that period within the narrower 70 to 140 mg/dL range. The first estimate is accompanied by a confidence interval that spans zero; the second is also accompanied by an interval spanning zero. The record does not report numerical results for all other listed secondary outcomes, including the nocturnal symptomatic hypoglycemia measures and CGM coefficient of variation.

These secondary measures address related but distinct aspects of glycemic patterns. They focus on a late interval before the next basal dose or on nocturnal symptomatic events and variability, whereas the primary endpoint summarizes time in a broader 70-180 mg/dL range during Week 15 and/or Week 16. The secondary pattern does not supply a separate basis for overriding or confirming the primary model result. The record’s numerical secondary findings are imprecise enough that the direction and size of an effect remain uncertain under the recalculated comparisons.

Secondary outcomes can help explore whether a primary result is accompanied by a consistent pattern across related measures, but interpreting many outcomes increases the risk of chance findings. The registry does not report a multiplicity adjustment or a prespecified hierarchy for these endpoints. Their results should therefore carry less confirmatory weight than the primary outcome, and absence of posted numerical results for some listed outcomes prevents a complete assessment of the intended secondary questions.

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

• Percentage of Participants With Documented Symptomatic Nocturnal Hypoglycemia
• Documented Symptomatic Nocturnal Hypoglycemia Event Rate Per Participant-Year
• Mean Change From Baseline in Glucose Level During Last 4 Hours of CGM Data Collection Prior to the Next Day Basal Insulin Injection During Week 15 and/or Week 16
• Percentage of Time Glucose Concentrations Within the Target Range of 70 to 140 mg/dL During Last 4 Hours of CGM Data Collection Prior to Next Day Basal Insulin Injection
• Coefficient of Variation (CV%) in Mean CGM Glucose

9. Statistical Interpretation

10. Statistical Methods Explained

General statistical explanation: A randomized parallel-group study compares outcomes between groups assigned to different interventions. Randomization is intended to make treatment assignment independent of measured and unmeasured baseline factors on average. It does not guarantee that every realized group will be identical, and the analysis still depends on the endpoint definition, the population included, and the statistical model.

What the primary model reports

The registry says the primary endpoint was analyzed using a generalized linear model with an identity link. It reports adjusted least-square means and standard errors, including post-baseline CGM assessment during Week 15 and/or Week 16. An identity link expresses the modeled outcome on its original scale, so the reported contrast is a difference in percentage points rather than a ratio. The registry does not identify all model terms, covariates, or assumptions, so those details cannot be reconstructed from the record.

A least-square mean is a model-based estimate of a group mean under the model’s adjustment structure. It is not necessarily the same as a raw arithmetic average. A standard error describes the estimated sampling uncertainty of an estimate; it is not a range containing individual participant values. The reported group standard errors are 1.08 for HOE901-U300 and 1.1 for Lantus. The registry provides a model-based least-square mean difference and p-value but no confidence limits for that contrast.

What a confidence interval conveys

General statistical explanation: A confidence interval describes uncertainty around an estimated effect under the assumptions of the calculation. A wider interval indicates less precision, while a narrower interval indicates greater precision. An interval that includes zero for a difference is compatible with effects in either direction as well as no difference, at the confidence level used. The simple recalculation reports a 95% confidence interval from -3.241 to 2.801. This interval belongs to the recalculation, not to the registry’s reported generalized linear model.

Why the recalculation differs in role

The recalculated comparison is a simple unadjusted calculation from posted summary statistics, with an approximate pooled standard deviation. It is useful as a supplementary check on the scale and uncertainty of a between-group comparison, but it does not reproduce the sponsor’s model. The primary analysis used model-derived least-square means, while the recalculation uses the posted summaries and an unadjusted approach. The registry’s reported model result is therefore the appropriate result to cite as the registered primary analysis. The recalculation should not be substituted for it or interpreted as an additional independent trial finding.

The recalculated p-value is 0.887, whereas the registry’s reported p-value is 0.849. Both are attached to different analysis approaches. The record does not report enough detail to attribute their difference to a specific model feature. The reported model result has no confidence interval in the registry record, so the recalculated interval should not be presented as if it were the model’s interval.

Analysis populations and missing measurements

The primary outcome population is described as modified intent-to-treat. It includes randomized participants who had a post-baseline CGM assessment and enough CGM values to calculate time in range during the specified assessment period. This eligibility rule means the primary analysis is not simply described as all randomized participants. The record does not state how many CGM readings were required, how missing readings were handled, or whether imputation or sensitivity analyses were used. Those omissions matter because an endpoint based on repeated monitoring depends on adequate data over the relevant period.

General statistical explanation: Excluding participants with insufficient endpoint data can affect interpretation if data availability is related to treatment, glucose outcomes, tolerability, or other participant characteristics. Randomization protects the comparison at assignment, but post-randomization exclusions can alter the composition of the analyzed groups. The registry does not give enough information to assess whether that occurred in this study.

Secondary outcomes and multiple testing

The record lists secondary measures involving documented symptomatic nocturnal hypoglycemia, glucose behavior before the next basal dose, and variation in mean CGM glucose. Numerical results are posted for mean change in glucose during the last 4 hours before the next basal injection and percentage of time in the 70 to 140 mg/dL range during that period. Results for the other listed secondary measures are not reported in the registry record.

General statistical explanation: When several outcomes are tested, the chance of at least one apparently unusual result can increase if each test is interpreted without accounting for the number of tests. A multiplicity adjustment can control that issue, while a prespecified hierarchy can define which results are confirmatory. The registry record does not report a multiplicity adjustment, testing hierarchy, or other family-wise approach. The secondary comparisons should therefore be read as supportive or exploratory, not as independent confirmation of the primary finding.

11. Confidence Intervals and Precision

The registry’s primary model-based contrast is 0.22, with p = 0.849, but the record gives no confidence limits for that contrast. Without a model-based confidence interval, the precision of the reported primary estimate cannot be judged directly from the registered model result. The group standard errors are 1.08 for HOE901-U300 and 1.1 for Lantus, but they describe uncertainty in the group estimates, not the model contrast itself.

The separate unadjusted recalculation estimates a mean difference of -0.22 and gives a 95% confidence interval from -3.241 to 2.801. This interval spans zero and includes values on either side of zero. It therefore reflects uncertainty about the direction and size of the simple unadjusted contrast. It is not a confidence interval for the sponsor’s model-based result, and should not be used as though it were one.

General statistical explanation: A confidence interval is more informative than a point estimate alone because it presents a range of effects compatible with the data and method at the stated confidence level. A wide interval can leave substantial uncertainty even when a point estimate is close to zero. Whether an interval rules out effects important to patients or clinicians depends on a clinically meaningful threshold, which is not reported in the registry record.

The same limitation applies to the secondary estimates: their recalculated intervals are available for the posted comparisons, but the record does not provide sponsor-model confidence intervals for them. The precision of these secondary findings should not be overstated, especially because multiple outcomes were considered and the multiplicity plan is not reported.

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 for 80% power and participants per arm for 90% power. They are planning illustrations based on the observed effect, not the trial’s original sample-size justification. The original design assumptions are not reported in the registry record.

The stated illustration assumes a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. For each planning row, the effect to detect is the stated fraction of the observed effect. The 80% power column represents a planning scenario that would have an 80% chance of detecting the assumed effect if the assumptions and model were correct. The 90% power column represents a scenario with a higher planned chance of detecting that assumed effect. Neither column describes the probability that the observed trial result is true.

Smaller assumed effects require more participants per arm to achieve the same planned power. The figures are based on the effect observed in this trial, so they should not be treated as an independently established target effect or as evidence that a future study would reproduce it. They are not observed power. The registry’s sample-size assumptions specify participant counts per arm for these continuous outcomes; the record’s note about total event counts applies to time-to-event planning, not to these figures.

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 = -0.220; pooled standard deviation σ = 17.991.
2. n = 2 × (1.96 + 0.842)² × 17.991² / -0.220² = 104,979.3, rounded up to 104,980 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 <- -0.219999999999999                      # observed difference in means
sigma <- 17.9910133490575                     # 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(2688933)
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 = 104,980 (80% power), 140,538 (90% power)
 75% of observed effect: n per arm = 186,630 (80% power), 249,845 (90% power)
 50% of observed effect: n per arm = 419,918 (80% power), 562,150 (90% power)
power.t.test: 104980.2 
Simulated power at n = 104,980 per arm: 0.800 (20000 replicates)

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

14. Analyses Reported by the Sponsor

The registry reports the primary sponsor analysis as a generalized linear model with a least-square mean difference of 0.22 and p = 0.849. It does not give confidence limits for that result. This is the registered model-based analysis and should be distinguished from the simple unadjusted recalculation.

The recalculation gives -0.22, a 95% confidence interval from -3.241 to 2.801, and p = 0.887. It is derived from posted summary statistics and is not a reconstruction of the sponsor’s model. The record does not report enough detail about the contrast coding or model specification to explain the sign difference or the difference between the p-values. The discrepancy flag is false; no discrepancy warning is recorded.

The recalculated result can offer a supplementary view of uncertainty, but it does not supersede the reported model analysis. Because the registered model result has no confidence interval, the recalculated interval cannot fill that gap. The two estimates should remain clearly attributed to their respective methods rather than blended into one result.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies a primary outcome and multiple secondary outcomes. It reports one primary analysis and lists several measures concerning nocturnal symptomatic hypoglycemia, glucose levels before the next basal dose, time within a narrower glucose range, and CGM variability. The registry record does not report whether the secondary tests were adjusted for multiplicity, whether a testing hierarchy was prespecified, or whether any results were intended to be confirmatory.

General statistical explanation: Testing multiple outcomes can increase the chance of finding an apparently notable result by chance. Adjustments or prespecified testing sequences can limit that risk. Without a reported strategy, secondary p-values and confidence intervals should be interpreted cautiously and should not be treated as equivalent to a single prespecified primary test.

The primary analysis used a modified intent-to-treat population requiring a post-baseline CGM assessment and enough CGM readings to calculate the endpoint. The registry does not report the number excluded for insufficient CGM data, the amount or pattern of missing data, or the method used to handle incomplete CGM observations. It also does not report sensitivity analyses for missingness or a comparison of the primary population with all randomized participants.

Those details affect interpretation because availability of CGM data after randomization may be related to participant characteristics or outcomes. The record does not establish that such a relationship occurred, but it also does not provide the information needed to evaluate it. The randomization procedure, allocation concealment, original sample-size rationale, and interim-analysis plan are not reported in the registry record. No assumptions about those design features can be made from the posted information.

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: hypoglycaemic unconsciousness (1.9%), hypoglycaemia (0.9%), hypoglycaemic seizure (0.9%), accidental overdose (0.9%), hyperglycaemia (0.6%).

For serious adverse events, the registry reports 17 affected participants among 320 at risk in the HOE901-U300 group and 14 among 318 at risk in the Lantus group. For the other adverse-event category shown in the record, 54 participants were affected in each group, with 320 and 318 at risk, respectively. The registry records zero deaths in both groups.

The record lists serious adverse-event terms including hypoglycaemic unconsciousness, hypoglycaemia, hypoglycaemic seizure, accidental overdose, hyperglycaemia, and acute kidney injury, with percentages attached to those terms. It does not provide a group-specific breakdown for those listed terms in the information, so they should not be assigned to one treatment group.

These counts describe reported events during the trial; they do not establish that an event was caused by treatment. The record does not give enough detail to assess duration, severity beyond the serious-event classification, exposure-adjusted rates, or statistical comparisons. Similar counts in a trial record should not be read as proof of equal safety, and zero recorded deaths does not resolve other safety questions.

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

The primary result is a comparison of time in a CGM target range during a specified late-treatment assessment period. The registry’s model-based analysis reports a least-square mean difference of 0.22 with p = 0.849. The data as posted do not establish a clear between-group separation on that measure. The model-based confidence interval is not reported, so the range of effects compatible with that analysis cannot be directly assessed.

This does not demonstrate that the regimens are equivalent. Equivalence requires a prespecified margin and an analysis designed to determine whether the plausible difference lies within that margin; neither is reported in the registry record. Nor does the result prove that no difference exists. It indicates that the registered analysis did not provide strong evidence of a difference on the measured primary endpoint, with the precision limitations noted above.

The result also does not answer every clinical question about glucose control. The endpoint measures percentage of CGM time in a defined range and does not by itself summarize all glucose outcomes, nocturnal symptomatic hypoglycemia, longer-term outcomes, or safety. Some secondary outcome results are absent from the registry record, and the multiplicity strategy is not reported.

The open-label design and modified intent-to-treat eligibility rule are relevant when considering generalizability and possible bias. The registry does not provide enough information to determine how missing CGM data were handled or how many randomized participants were not included in the primary analysis. Interpretation should remain tied to the population, endpoint, treatment period, and analysis actually reported, without extending the finding beyond them.

18. Why This Trial Matters Statistically

This trial is statistically informative because it makes the target of the comparison concrete: a CGM-based percentage of time in a specified glucose range, measured during Week 15 and/or Week 16. Such a continuous endpoint can capture a pattern over monitoring time rather than relying on a single glucose value. The active-controlled randomized design also frames the question as a direct comparison of two basal insulin regimens.

The record illustrates why estimates, uncertainty, and analysis method need to be considered together. The sponsor’s model-based result is the registered primary analysis, while a separate unadjusted recalculation provides a different estimate and its own interval. Treating those calculations as interchangeable would obscure their distinct methods. The absence of model-based confidence limits also shows how incomplete reporting can restrict assessment of precision, even when a point estimate and p-value are available.

The modified intent-to-treat definition makes the role of endpoint data availability explicit: participants needed enough CGM information to calculate the primary measure. However, missing-data handling and the full flow into the analysis population are not reported. Those details are important for evaluating whether a randomized comparison remains interpretable after excluding participants with insufficient measurements.

Finally, the range of secondary questions underscores the need for a clear multiplicity plan and complete outcome reporting. The registry lists outcomes related to nocturnal hypoglycemia, late-interval glucose, and variability, but numerical results are not present for all of them. These reporting limits are not evidence for or against a treatment effect; they define what can be concluded from the registered results.

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.

Several trial-specific reporting limitations constrain interpretation. The primary model-based estimate has no confidence interval in the registry record, while the available interval belongs to a separate unadjusted recalculation. The record does not describe the full generalized linear model specification, including all terms and covariates, or give enough detail to reconcile the contrast signs across the two analyses.

The primary population required sufficient post-baseline CGM data, but the registry does not report the number of randomized participants who failed that requirement or the amount and pattern of missing CGM information. It does not specify how incomplete monitoring was handled or report sensitivity analyses. This leaves uncertainty about the impact of endpoint-data availability on the analyzed comparison.

The study was open label, and no masking was used. The record does not quantify whether that affected treatment behavior, co-interventions, or outcome measurement. It also does not report the original sample-size justification, allocation ratio, randomization procedure, allocation concealment, or interim-analysis plan. These features should not be inferred from the planning illustrations, which are based on the observed effect and stated assumptions rather than the trial’s original design.

The registry lists five secondary outcomes, but numerical results are available for only two of the secondary glucose measures in the record. A multiplicity plan is not reported. The safety information includes event counts, but does not provide exposure-adjusted comparisons or group-specific details for the listed serious-event terms. These limits mean the posted information supports a focused reading of the reported primary measure, not a complete assessment of all intended efficacy and safety questions.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Study Comparing the Efficacy and Safety of the Morning Injection of Toujeo Versus Lantus in Patients With Type 1 Diabetes Mellitus — NCT02688933.
• Registry record last updated 2022-03-28; status last verified 2022-03.
• Results first posted 2018-08-20.
• 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

NCT02688933 is a completed randomized, active-controlled, parallel-group, open-label phase 4 study comparing once-daily morning HOE901-U300 with Lantus in adults with type 1 diabetes. Both regimens were used for 16 weeks on top of mealtime insulin analogs, with individualized basal-dose titration toward fasting self-measured plasma glucose levels of 80 to 100 mg/dL.

The primary outcome was percentage of CGM time within 70-180 mg/dL during Week 15 and/or Week 16. The registry reports a generalized linear model least-square mean difference of 0.22 and p = 0.849, without confidence limits for that model result. A separate unadjusted recalculation has a 95% confidence interval from -3.241 to 2.801 and is not a substitute for the registered analysis.

The registry also reports selected secondary glucose results and adverse-event counts. Missing-data handling, multiplicity methods, original sample-size assumptions, and some secondary results are not reported in the registry record.