Comparison of a New Formulation of Insulin Glargine With Lantus in Patients With Type 1 Diabetes Mellitus: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comparison of a New Formulation of Insulin Glargine With Lantus in Patients With Type 1 Diabetes Mellitus (NCT01683266), a randomized phase 3 study. The primary outcome is Change In HbA1c From Baseline to Month 6 Endpoint.

2. Clinical Question

3. Trial Design

This was a Phase 3, randomized, open-label, parallel-group study sponsored by Sanofi. The registry lists 549 enrolled participants and identifies type 1 diabetes mellitus as the condition studied. It describes the trial as multicenter. Masking was listed as none, so the study was open-label rather than blinded. The registry status is completed.

The official title describes a 6-month comparison of a new insulin glargine formulation with Lantus, with injections given in the morning or evening, followed by a 6-month safety extension. The arm descriptions state that participants received their assigned insulin once daily in the morning or evening for 12 months, alongside mealtime insulin analogue. Both arms used dose titration seeking fasting plasma glucose of 4.4-5.6 mmol/L. The registry record does not report how morning versus evening administration was allocated within each treatment group.

The primary efficacy question concerned change in HbA1c from baseline to the scheduled Month 6 endpoint, with the comparison between formulations made overall regardless of injection time. The stated primary analysis population was modified intent-to-treat: randomized participants who received at least one dose and had baseline plus at least one post-baseline efficacy assessment. For the HbA1c analysis, the registry specifies participants with baseline and Month 6 HbA1c assessments as the analyzed group.

The registry lists the study start as 2012-09 and primary completion as 2013-09. It describes the intervention period as 12 months, including the safety extension. The original protocol’s sample-size justification, the allocation procedure in detail, and the original statistical analysis plan are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Modified Intent-to-Treat (mITT) population: all randomized participants who received at least (\>=)1 dose, had baseline and \>=1 post-baseline assessment of any efficacy variable, irrespective of compliance. Number of participants analyzed = participants with baseline and Month 6 HbA1c assessment.

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: Randomized population: all screened participants (who originally met inclusion criteria and signed informed consent) allocated to a treatment group and recorded in Interactive Voice/Web Response System (IVRS/IWRS) database, regardless of whether treatment was used or not. Participants were analyzed in treatment group to which they were randomized.

6. Primary Endpoint

The registry lists the primary outcome as Change In HbA1c From Baseline to Month 6 Endpoint, measured over Baseline, Month 6.

The primary endpoint was change in HbA1c from baseline to the Month 6 endpoint. HbA1c is a measure of glycemia that reflects blood glucose exposure over time, rather than a single glucose reading. In this study it was expressed as a percentage of hemoglobin, and the endpoint compared the change from baseline between the two treatment groups.

Change scores are useful in randomized trials because they describe how the measured outcome shifted during follow-up relative to each participant’s baseline. Comparing the groups’ changes helps address the question of whether the outcome trajectory differed between assigned treatments. The registry reports least-squares mean changes, which are model-based adjusted means; the exact adjustment model is not reported in the registry record. Standard errors are reported for the group estimates.

The registry’s primary objective was to compare the new formulation with Lantus in HbA1c change at Month 6, overall regardless of injection time. The primary endpoint is therefore distinct from the additional glucose measures and safety outcomes. A change in HbA1c captures a broader glycemic measure, while individual glucose readings and profiles address more specific time points or patterns. The registry record does not state the clinical threshold for a meaningful HbA1c difference, nor does it report the prespecified non-inferiority margin or the full endpoint analysis model.

7. Results Posted in the Registry

• Lantus: mean -0.44 versus -0.40 on control; difference -0.04 (95% CI -0.18 to 0.10), standardized effect d = -0.05; z-test p = 0.579.

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.

Percentage of Participants With HbA1c <7% at Month 6 Endpoint

• 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:
  • Lantus: 15.0% (41/273) versus 16.8% (46/273) on control; risk difference -1.8 percentage points (95% CI -8.0 to 4.3), risk ratio 0.89 (0.61–1.31); unadjusted two-proportion z-test p = 0.559.
• 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 Participants With HbA1c Less Than or Equal to 6.5% at Month 6 Endpoint

• 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:
  • Lantus: 5.5% (15/273) versus 8.1% (22/273) on control; risk difference -2.6 percentage points (95% CI -6.8 to 1.6), risk ratio 0.68 (0.36–1.29); unadjusted two-proportion z-test p = 0.233.
• 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.

Change In Average Pre-Injection Self-Monitored Plasma Glucose (SMPG) From Baseline Month 6 Endpoint

• 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 -0.82 versus -1.16 on control; difference 0.34 (95% CI -0.29 to 0.97), standardized effect d = 0.14; z-test p = 0.292.
• 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 secondary outcomes cover a wider set of questions than the primary HbA1c change: target HbA1c thresholds, fasting and self-monitored plasma glucose, glucose profiles and variability, hypoglycemia, treatment satisfaction, quality of life, and safety. The available secondary summaries add context to the primary result by examining threshold attainment and glucose measurements from different perspectives. They are not substitutes for the primary endpoint, which was the prespecified central efficacy question in the registry summary.

Across the secondary comparisons with numerical summaries, the unadjusted confidence intervals include no difference. These results do not establish that the groups are equal; they indicate that the available comparisons leave uncertainty about the direction and magnitude of differences. The number of outcome measures listed in the registry is 12, while 11 secondary outcomes are identified as posted. Detailed results for several of the listed secondary outcomes are not reported in the registry record, so the broad set of objectives cannot be assessed in full from the available numerical summaries.

Unadjusted secondary results carry less weight because many outcomes and comparisons create multiple opportunities for apparently notable findings by chance. The registry does not report a multiplicity adjustment or a hierarchy specifying which secondary questions would be confirmatory. These comparisons should therefore be treated as exploratory context rather than as standalone proof. Consistency with the primary outcome can be useful descriptively, but correlated endpoints do not supply independent confirmation. Interpretation also depends on the analysis population, missing data, and model specifications, details that are not fully reported in the registry record.

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

• Percentage of Participants With HbA1c <7% at Month 6 Endpoint
• Percentage of Participants With HbA1c Less Than or Equal to 6.5% at Month 6 Endpoint
• Change In Average Pre-Injection Self-Monitored Plasma Glucose (SMPG) From Baseline Month 6 Endpoint
• Change in Variability of Pre-injection SMPG From Baseline to Month 6 Endpoint
• Change in Fasting Plasma Glucose From Baseline to Month 6 Endpoint
• Percentage of Participants With Fasting Plasma Glucose (FPG) <5.6 mmol/L (100 mg/dL) At Month 6
• Percentage of Participants With FPG <7.2 mmol/L (130 mg/dL) at Month 6 Endpoint
• Change in 8--Point SMPG Profiles Per Time Point From Baseline to Month 6 Endpoint

9. Statistical Interpretation

10. Statistical Methods Explained

The primary group results are least-squares means, with standard errors. A least-squares mean is a model-based estimate of the group mean, typically adjusted for terms in a statistical model. The registry does not identify the model terms or provide the complete analysis specification, so the precise nature of the adjustment cannot be assessed from the record. The standard error describes uncertainty in each estimated group mean; it is not the same quantity as the spread of individual participant outcomes.

What does a confidence interval describe?

A confidence interval gives a range of values compatible with the observed data under the assumptions of the analysis. It is not a range containing a fixed proportion of individual participants, and it does not assign a probability that the true effect lies inside this particular interval. The 95% intervals reported for comparisons express the statistical uncertainty around a group contrast. When an interval includes zero for a difference, the data do not clearly distinguish the observed contrast from no difference at that confidence level. That does not prove equality, and the interval may still include effects that could matter in either direction.

The primary contrast was recalculated from posted summary statistics using an unadjusted comparison. The observed group means and standard errors were used to estimate a difference and its uncertainty; the pooled standard deviation is approximate. This is not the same as the sponsor’s model-based least-squares mean analysis. In particular, a simple recalculation cannot reproduce adjustments, missing-data handling, or other features of the trial’s analysis model when those details are unavailable. The sponsor’s own analysis therefore remains the main trial analysis.

Why distinguish the analysis populations?

The registry describes the primary population as modified intent-to-treat. It includes randomized participants who received at least one dose and had baseline and at least one post-baseline efficacy assessment. The Month 6 HbA1c analysis further required a baseline and Month 6 HbA1c assessment. This differs from a strict intention-to-treat population that would retain all randomized participants regardless of treatment received or available outcome measurements. The counts analyzed for the primary endpoint were 225 for HOE901-U300 and 229 for Lantus. The registry does not report the detailed missing-data methods or the characteristics of participants omitted from this endpoint analysis.

For the reported binary secondary endpoints, the recalculation compares proportions using risk differences. A risk difference is the proportion with the outcome in one group minus the proportion in the other group, under the stated contrast direction. Its confidence interval describes uncertainty in that absolute difference. Ratios such as risk ratios and odds ratios are also listed for some comparisons, but a measure’s scale changes how it is interpreted. Absolute differences are often easier to connect to the observed proportion contrast, while ratio measures compare relative quantities. None of these unadjusted secondary calculations should be mistaken for the sponsor’s full analysis if the latter is not reported.

What does an unadjusted p-value tell the reader?

An unadjusted p-value measures how surprising data at least as inconsistent with a specified null hypothesis would be if that null hypothesis and the test assumptions held. It is not the probability that the null hypothesis is true, nor does it measure the size or importance of an effect. The listed unadjusted p-values do not account for testing multiple secondary outcomes. The registry record does not report whether or how the sponsor controlled multiplicity across the broader set of outcomes.

Over-dispersion is a general concern when count or binary outcomes vary more than an assumed statistical model expects. If ignored, uncertainty can be understated and tests can appear more decisive than warranted. The reported continuous summaries do not establish whether any over-dispersion issue arose, and a specific over-dispersion adjustment is not reported in the registry record. More generally, confidence intervals and p-values rely on assumptions about sampling, measurement, model form, and missingness. The trial’s full protocol and analysis plan are not reported in the registry record, limiting independent assessment of those assumptions.

11. Confidence Intervals and Precision

The primary recalculated contrast is -0.04 percentage of hemoglobin for Lantus relative to HOE901-U300, with a 95% confidence interval from -0.181 to 0.101. The interval spans zero and extends in both directions. It therefore reflects uncertainty about the direction as well as the size of the contrast. The posted standard errors for the two group means are each 0.051, while the recalculated contrast interval reflects uncertainty in their difference rather than uncertainty in either group mean alone.

The registry’s own primary analysis reports a least-squares mean difference of 0.04 and a 95% confidence interval from -0.098 to 0.185. This is presented in the reverse contrast direction from the recalculated comparison. The two intervals are not identical, consistent with the fact that one is an unadjusted recalculation and the other is the sponsor’s reported analysis. The registry does not report the non-inferiority margin, so the precision interval cannot be judged against that trial-specific threshold from the record alone.

For general interpretation, a narrow interval indicates greater precision about the estimated contrast, while a wide interval indicates more uncertainty. Precision is not the same as clinical importance: an estimate can be precise yet clinically unimportant, or imprecise while still spanning effects that could matter. The secondary risk-difference intervals likewise include zero, and their widths show that the observed proportions do not pin down the group contrasts precisely. No claim of equivalence follows solely from an interval that includes zero. A formal equivalence or non-inferiority interpretation requires the prespecified margin, analysis population, and decision procedure; the margin is not reported in the registry record.

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 illustrations describe hypothetical future-study sizes based on the observed effect, not the number enrolled in this trial. For the continuous and binary outcomes shown, the figures are participants per arm, not total participants. The stated assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect to detect is 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 planned number of participants per arm under those assumptions for an 80% chance of detecting the specified effect if that effect is real and the assumptions hold. The 90% power column gives the corresponding number per arm for a 90% chance. These are planning targets, not guarantees about a study’s outcome. The illustrations are not observed power.

The rows for 100%, 75%, and 50% of the observed effect allow readers to see how the target effect size changes the planning requirement. Smaller effects are harder to distinguish from random variation, so they require more participants to reach a given power target under the same assumptions. In this trial, the observed primary contrast is small, which makes a planning calculation based directly on it especially sensitive to the effect fraction selected. These values should not be read as a recommendation for a future study: choices about a meaningful target difference, multiplicity, analysis model, missingness, and the clinical question would also matter. The registry does not report the original design’s chosen target difference or its sample-size rationale.

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 = -0.040; pooled standard deviation σ = 0.768.
2. n = 2 × (1.96 + 0.842)² × 0.768² / -0.040² = 5,793.2, rounded up to 5,794 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 <- -0.04                      # observed difference in means
sigma <- 0.768422432909289                     # 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(1683266)
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 = 5,794 (80% power), 7,756 (90% power)
 75% of observed effect: n per arm = 10,300 (80% power), 13,788 (90% power)
 50% of observed effect: n per arm = 23,173 (80% power), 31,022 (90% power)
power.t.test: 5794.2 
Simulated power at n = 5,794 per arm: 0.795 (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 least-squares mean difference as 0.04, with a 95% confidence interval from -0.098 to 0.185, and classifies the analysis as non-inferiority or equivalence. It does not report a p-value or the margin used for that analysis. The sponsor’s estimate is expressed in the reverse direction from the simple recalculated contrast, which is -0.04 for Lantus minus HOE901-U300. Reversing the contrast changes the sign, not the underlying comparison.

The recalculation uses an unadjusted comparison of posted summary statistics and has a 95% confidence interval from -0.181 to 0.101. It is an independent arithmetic check, not a replication of the sponsor’s model. Differences between the intervals can arise because the sponsor analysis is model-based and the recalculation relies on summary statistics and an approximate pooled standard deviation. The registry does not provide enough detail to reconstruct the sponsor’s model or explain the exact interval construction.

The discrepancy flag is false, but that does not make the recalculation interchangeable with the trial analysis. The sponsor’s own analysis takes precedence for interpreting the trial’s prespecified comparison. A non-inferiority conclusion cannot be independently assessed without the margin and the analysis details. The sponsor reports a secondary glucose comparison as well, with its contrast direction reversed relative to the simple recalculation; again, the sponsor’s model-based result is the relevant trial-reported analysis.

15. Multiplicity, Missing Data and Analysis Populations

The primary endpoint is clearly identified as change in HbA1c from baseline to Month 6. The registry also lists numerous secondary outcomes, including glucose measures, target attainment, hypoglycemia categories, safety, treatment satisfaction, and health-related quality of life. Testing many outcomes increases the chance that at least one result will appear notable by chance if each is evaluated separately. This is the general statistical problem of multiplicity.

A prespecified testing hierarchy or an adjustment to the significance threshold can address multiplicity, but the registry record does not report whether such a plan was used. The unadjusted p-values attached to recalculated comparisons therefore should not be interpreted as if they were multiplicity-controlled confirmatory tests. Nor can the absence of a reported adjustment be taken to mean that no adjustment was made in the complete trial analysis; the registry record simply does not report the relevant plan.

The stated primary analysis population was modified intent-to-treat, requiring randomization, at least one dose, and baseline plus at least one post-baseline efficacy assessment. For the Month 6 HbA1c result, participants also needed baseline and Month 6 HbA1c assessments. This rule means the analyzed primary endpoint population is not necessarily all randomized participants. The registry gives analyzed counts for the outcome, but detailed reasons for missing Month 6 values and comparisons between included and excluded participants are not reported in the registry record.

Missing outcome data can affect estimates when the probability of being observed is related to participants’ outcomes or treatment experience. Statistical methods can address missingness only under assumptions, and sensitivity analyses can show how conclusions might change under alternative assumptions. The missing-data method, sensitivity analyses, and handling of intercurrent events are not reported in the registry record. The full statistical analysis plan, including model covariates, handling of protocol deviations, and any interim analyses, is also not reported in the registry record. These omissions limit assessment of whether the numerical summaries fully reflect the intended trial analysis.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: hypoglycaemia (5.8%), diabetic ketoacidosis (0.7%), road traffic accident (0.7%), atrioventricular block complete (0.4%), coronary artery disease (0.4%).

For serious adverse events, the registry reports 27 affected participants among 274 at risk in the HOE901-U300 group and 26 among 275 at risk in the Lantus group. For the separately labeled other adverse events, it reports 113 affected participants among 274 at risk with HOE901-U300 and 86 among 275 at risk with Lantus. These are counts of participants reported as affected, not counts of all event episodes. The registry record does not provide enough detail in these summaries to establish event duration, recurrence, severity beyond the serious classification, or causal relation to treatment.

Listed serious adverse event terms include hypoglycaemia at 5.8%, diabetic ketoacidosis at 0.7%, road traffic accident at 0.7%, atrioventricular block complete at 0.4%, coronary artery disease at 0.4%, and hypersensitivity at 0.4%. These term percentages should be read as registry-reported values; their specific denominators are not reported in the registry record in the safety summary.

Deaths are not reported in the registry record. Differences in the observed counts alone do not establish that one treatment caused more or fewer events. Safety interpretation depends on event definitions, exposure, follow-up, participant characteristics, and adjudication; these details are not fully reported in the registry record.

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

The primary summaries show similar observed mean decreases in HbA1c in the two groups over the measured period: -0.4 with HOE901-U300 and -0.44 with Lantus. The recalculated difference is small in magnitude, but its confidence interval includes values on both sides of zero. The sponsor’s reported contrast also has a 95% confidence interval spanning zero. Taken together, the registry’s numerical summaries do not precisely identify a directional difference between the formulations in this endpoint.

That interpretation is not the same as proving that the treatments are identical. A conventional difference analysis that does not clearly distinguish the groups is not by itself evidence of equivalence. Equivalence or non-inferiority depends on a prespecified margin and an appropriate analysis. Although the registry labels the sponsor’s primary result as a non-inferiority or equivalence analysis, the margin is not reported in the registry record, so the formal basis for that conclusion cannot be evaluated from these summaries alone.

The results describe the participants analyzed and the study conditions recorded: once-daily insulin glargine, given in the morning or evening, alongside mealtime insulin analogue, with fasting plasma glucose-based dose titration. The primary endpoint was scheduled at Month 6, while the study description includes a 6-month safety extension. The results do not establish what would occur in people outside the studied population, with different treatment regimens, or over periods beyond the recorded follow-up.

Secondary outcomes provide additional descriptive information but involve multiple comparisons and incomplete posted results. The safety counts also require careful interpretation and do not establish causation. These statistical findings are not medical advice and do not determine an individual treatment choice. They describe the posted trial data and the uncertainty surrounding the reported comparisons.

18. Why This Trial Matters Statistically

This trial is statistically informative because it pairs a clinically interpretable endpoint, change in HbA1c, with a randomized comparison and a clearly identified Month 6 assessment. The group summaries allow readers to distinguish the observed mean changes from the uncertainty in the between-group contrast. That distinction matters: similar point estimates can still leave meaningful uncertainty when the confidence interval is broad.

The registry also illustrates why trial-reported analyses and simple recalculations should be kept separate. The sponsor reports a model-based least-squares mean difference and identifies the analysis as non-inferiority or equivalence. A simple unadjusted recalculation from summary statistics offers a transparent check, but it cannot reproduce an unreported model or its assumptions. The contrast direction also needs attention: the sponsor’s estimate and the recalculation use opposite directions, so their signs should not be compared without aligning those directions.

Planning illustrations based on observed effects can help readers understand how sample-size requirements change as the target effect becomes smaller. They are not evidence about the power of the completed trial and do not reveal the original design rationale. The registry’s secondary outcome breadth further demonstrates the importance of multiplicity: a large set of outcomes calls for a clear inferential hierarchy if confirmatory claims are intended. Overall, the record supports careful reading of estimates, intervals, analysis populations, and missing statistical details rather than relying on a single p-value or point estimate.

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 registry record does not report the non-inferiority margin, even though the sponsor’s primary analysis is classified as non-inferiority or equivalence. It also does not provide the sponsor’s p-value for that comparison. Consequently, the formal decision rule for the primary claim cannot be reconstructed from the record. The exact model used for the least-squares means, its covariates, and the detailed variance assumptions are not reported in the registry record.

The primary outcome population required a Month 6 HbA1c assessment, and the registry does not report the detailed missing-data methods or reasons for non-assessment. The listed endpoint analyzed 225 participants in the HOE901-U300 group and 229 in the Lantus group. These counts are smaller than the 549 enrolled participants, but the registry does not report a full participant flow in the registry record for this analysis. The handling of missing values and any sensitivity analyses are not reported in the registry record.

Although morning and evening administration are part of the study question, the registry record does not report the allocation procedure for injection timing or results stratified by timing. The primary objective is explicitly described as an overall comparison regardless of injection time. The arm descriptions state 12 months of treatment, but the primary efficacy endpoint is at Month 6; longer-term efficacy results are not included in the numerical primary result.

The secondary results available for numerical review cover only selected outcomes, despite the broader registry outcome list. A multiplicity plan is not reported in the registry record. The safety summary does not report deaths, event-level timing, exposure-adjusted rates, or detailed causal assessments. These limitations constrain interpretation of both efficacy and safety findings.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Comparison of a New Formulation of Insulin Glargine With Lantus in Patients With Type 1 Diabetes Mellitus — NCT01683266.
• Registry record last updated 2015-06-24; status last verified 2015-05.
• Results first posted 2015-04-23.
• 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

NCT01683266 is a completed Phase 3, randomized, open-label, parallel-group study sponsored by Sanofi. It enrolled 549 participants with type 1 diabetes mellitus and compared once-daily HOE901-U300 with Lantus, administered in the morning or evening alongside mealtime insulin analogue. The primary endpoint was change in HbA1c from baseline to Month 6.

Reported group mean changes were -0.4 and -0.44, respectively. The recalculated Lantus-minus-HOE901-U300 contrast was -0.04, with a 95% confidence interval from -0.181 to 0.101. The sponsor reported a contrast of 0.04 in the reverse direction, with a 95% confidence interval from -0.098 to 0.185. The registry record does not report the non-inferiority margin, detailed missing-data methods, or the full analysis plan. Secondary and safety summaries provide additional context but have limitations in posted detail and multiplicity reporting.