Comparison of a New Formulation of Insulin Glargine With Lantus in Patients With Type 2 Diabetes on Basal Insulin With Oral Antidiabetic Therapy: 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 2 Diabetes on Basal Insulin With Oral Antidiabetic Therapy (NCT01499095), 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 of HOE901-U300 and Lantus, each used with oral antihyperglycemic drug or drugs. The registry lists 811 participants as the enrollment and marks the study completed. The listed condition is type 2 diabetes mellitus. The study start is recorded as 2011-12 and primary completion as 2013-04.

The official title describes a 6-month comparison of efficacy and safety followed by a 6-month safety extension period. The primary endpoint is change in HbA1c from baseline to the Month 6 endpoint. A stated secondary objective was comparing the occurrence of nocturnal hypoglycemia. The posted secondary outcomes also include glucose measurements, HbA1c and fasting plasma glucose thresholds, glucose profiles, and daily basal insulin dose.

Open-label means that the treatment assignment was not masked. Randomization can help balance measured and unmeasured participant characteristics between groups, while lack of masking can affect behavior, care, reporting, or outcome assessment, depending on how an outcome is collected. The registry record does not report details of allocation concealment or how outcome assessors were handled.

The primary outcome description says that only measurements before initiation of rescue therapy were included. The record identifies a modified intent-to-treat analysis population, but the complete missing-data description is not reported in the registry record. The original design assumptions, including its sample-size justification, are not reported in the registry record.

4. Participant Flow and Accounting

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

Before assignment: Following the main 6 month treatment period, eligible participants previously using HOE901-U300 were randomized (1:1) in a substudy and continued with fixed-dosing (every 24 hours) or started a adaptable-dosing (at intervals of 24 +/- 3 hours) regimen for 3 Months (Month 6 to 9).

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Modified Intent-to-Treat 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 Week 6 HbA1c assessment. Missing data imputed using last observation carried forward.

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 is change in HbA1c from baseline to the Month 6 endpoint, expressed as a percentage of hemoglobin. HbA1c reflects glycated hemoglobin and is used as a measure of glycemic status over time. Comparing change from baseline focuses on how the measured value shifted during follow-up, rather than comparing only the endpoint values.

The posted group estimates are least-squares means. In general, a least-squares mean is a model-based group estimate; it can account for variables included in the statistical model. The registry record does not identify the primary model's covariates or full specification, so the adjustment underlying the posted primary estimate cannot be described in detail.

Measurements after rescue therapy began were excluded from the primary analysis, according to the endpoint description. This makes the result an analysis of measurements collected before rescue therapy, rather than a summary of every measurement throughout follow-up. The registry lists the endpoint timeframe as baseline and Month 6. Its description of the number analyzed refers to participants with baseline and Week 6 HbA1c assessment; how that wording relates to the Month 6 endpoint is not explained in the registry record.

HbA1c is only one part of the efficacy assessment. The secondary outcomes include hypoglycemia and other glucose-related measurements, which address different aspects of treatment response and should not be treated as substitutes for the primary endpoint.

7. Results Posted in the Registry

• Lantus: mean -0.56 versus -0.57 on control; difference 0.01 (95% CI -0.25 to 0.27), standardized effect d = 0.01; z-test p = 0.940.

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 At Least One Severe and/or Confirmed Nocturnal Hypoglycemia From Start of Week 9 to 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: 27.9% (113/405) versus 21.6% (87/403) on control; risk difference 6.3 percentage points (95% CI 0.4 to 12.2), risk ratio 1.29 (1.01–1.65); unadjusted two-proportion z-test p = 0.038.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Lantus than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change in Average Preinjection Self-Monitored Plasma Glucose (SMPG) From Baseline to 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 -0.51 versus -0.56 on control; difference 0.05 (95% CI -0.72 to 0.82), standardized effect d = 0.01; z-test p = 0.898.
• 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 Variability of Preinjection SMPG From Baseline to 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 -0.53 versus -2.34 on control; difference 1.81 (95% CI -2.12 to 5.74), standardized effect d = 0.07; z-test p = 0.366.
• 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 extend the assessment beyond HbA1c change. They cover nocturnal hypoglycemia, average and variable preinjection self-monitored glucose, fasting plasma glucose, HbA1c and fasting glucose thresholds, glucose profiles, and daily basal insulin dose. These measures are related to glycemic status or treatment experience, but they capture different aspects of the study and use different outcome scales.

Across the posted continuous secondary comparisons, the simple estimates do not all have the same size or direction, and their intervals are broad relative to the point estimates. The registry also reports a binary nocturnal hypoglycemia comparison. This set of secondary findings adds context to the primary HbA1c comparison, but it does not create a single combined measure of efficacy or establish a general treatment effect across all outcomes.

Unadjusted secondary results carry less weight for confirmatory interpretation when many outcomes are examined. In general, testing multiple hypotheses increases the chance that at least one result will appear notable by chance. The registry record does not report a multiplicity strategy for the secondary outcomes. The posted values therefore should be interpreted as outcome-specific, with attention to their methods and uncertainty, rather than as independent confirmation of a broad claim.

Some secondary analyses have sponsor-reported methods, including an ANCOVA result for average preinjection glucose and a Cochran-Mantel-Haenszel analysis for the nocturnal event outcome. Other posted secondary comparisons do not have a reported sponsor analysis. Methodological detail is therefore not uniform across the secondary outcome set. None of these limitations changes the primary result, which remains the sponsor-reported HbA1c comparison.

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

• Percentage of Participants With At Least One Severe and/or Confirmed Nocturnal Hypoglycemia From Start of Week 9 to Month 6 Endpoint
• Change in Average Preinjection Self-Monitored Plasma Glucose (SMPG) From Baseline to Month 6 Endpoint
• Change in Variability of Preinjection SMPG From Baseline to Month 6 Endpoint
• Percentage of Participants With HbA1c <7% at Month 6 Endpoint
• Change in Fasting Plasma Glucose (FPG) From Baseline to Month 6 Endpoint
• Percentage of Participants With FPG <5.6 mmol/L (<100 mg/dL) at Month 6 Endpoint
• Change in 8-Point SMPG Profiles Per Time Point From Baseline to Month 6 Endpoint
• Change in Daily Basal Insulin Dose From Baseline to Month 6 Endpoint

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous: it measures change in HbA1c. The registry reports least-squares mean estimates for each group and a least-squares mean difference for the sponsor's comparison. In general, a least-squares mean is an estimate from a statistical model, rather than a simple arithmetic average. It can reflect adjustment for factors included in that model. The primary model method and its covariates are not reported in the registry record, so the exact adjustment cannot be reconstructed from the posted result.

What does the confidence interval describe?

A confidence interval describes the range of values compatible with the data and the analysis under the method's assumptions. It indicates precision as well as the direction and size of the estimated contrast. The sponsor-reported primary interval is -0.139 to 0.119 around a difference of -0.01. Because the interval includes zero, it does not indicate a clear direction of difference under a conventional two-sided test. It also does not establish equivalence: an equivalence or non-inferiority interpretation depends on a prespecified margin, which is not reported in the registry record.

How should the recalculation be understood?

The unadjusted recalculation uses posted group summary statistics to estimate a simple difference between group means. It does not reproduce the sponsor's least-squares analysis. The recalculated estimate is 0.01 for Lantus relative to HOE901-U300, with an unadjusted p-value of 0.94. Such a calculation can be a useful check on the broad scale of the result, but it may differ in estimand and uncertainty from a model-based analysis. The sponsor's own reported analysis takes precedence when describing the trial's primary result.

The posted standard errors describe uncertainty in each group's least-squares mean estimate. They are not standard deviations describing participant-to-participant variation. The group sample counts shown for the primary outcome are 386 for HOE901-U300 and 392 for Lantus. The analyzed population is defined by baseline and follow-up assessment requirements; the registry's general modified intent-to-treat description also requires receiving at least one dose and having at least one post-baseline efficacy assessment.

What changes for a binary outcome?

A binary outcome records whether an event or criterion occurred. The nocturnal hypoglycemia endpoint is reported as the percentage of participants with at least one qualifying event during its stated timeframe. A risk difference expresses the absolute contrast between proportions; a risk ratio compares the proportions relative to one another. These summaries answer different questions. The sponsor's posted analysis for this endpoint used the Cochran-Mantel-Haenszel method and reported a risk ratio with a confidence interval and p-value. The registry record does not provide enough detail to explain all stratification factors or model specifications.

For binary results, denominators can differ from those for a continuous endpoint because outcome availability and analysis populations may differ. The secondary endpoint counts and percentages should therefore be read using their own reported denominators, not assumed to match the primary analysis population.

Why can over-dispersion matter?

As a general statistical point, over-dispersion occurs when observed variability is greater than a model assumes. If a model understates variability, its uncertainty estimates can be too small, making intervals too narrow and tests too optimistic. The registry record does not report whether over-dispersion was assessed or how it was handled, so no claim about that issue can be made for this trial.

The primary outcome description says measurements after rescue therapy began were not included. In general, excluding post-rescue measurements can define an estimand focused on the pre-rescue period, but interpretation depends on why rescue began and how missing or excluded observations were handled. The registry record does not report the full missing-data procedure, rescue-therapy rules, or sensitivity analyses. It also does not report the full prespecified statistical plan, interim analyses, or multiplicity strategy.

11. Confidence Intervals and Precision

The sponsor-reported primary difference is -0.01, with a 95% confidence interval from -0.139 to 0.119. The interval contains zero and includes values on both sides, so the estimate does not identify a clear direction of difference. Its range also shows that the posted data do not pinpoint a single exact between-group effect.

Precision is not the same as whether a result is statistically significant. An interval can be read in relation to zero for a difference, but an equivalence question requires comparing the interval with a prespecified equivalence margin. That margin is not reported in the registry record. Consequently, the confidence interval cannot, on its own, show that the treatments meet an equivalence or non-inferiority criterion.

The simple recalculation is unadjusted and has a different estimate and uncertainty from the sponsor's reported analysis. Its p-value should not be substituted for the sponsor's analysis or used to infer that the two approaches have identical precision. The sponsor's own model-based result is the relevant posted trial analysis.

Confidence intervals also depend on the analysis population, the model, and the assumptions used to estimate uncertainty. The registry record gives a modified intent-to-treat population description and notes exclusion of measurements after rescue therapy, but does not report the full missing-data method or complete primary model. Those omissions make it harder to assess how robust the interval is to alternative analytic choices.

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 the observed effect, not the trial's original design justification. The original design assumptions are not reported in the registry record. For the continuous outcomes, the figures mean participants per arm; for the binary nocturnal hypoglycemia outcome, they also mean participants per arm. The record's general note says time-to-event planning figures, if present, would give total events, but the listed outcomes do not call for interpreting a time-to-event figure.

The calculation assumes 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 columns for 80% and 90% power describe planning scenarios: in general, power is the probability that a study will detect an effect of the specified size under the assumed model and significance threshold. The higher power target requires more participants than a lower target, all else equal.

The rows labeled as planning for 100%, 75%, and 50% of the observed effect show scenarios with progressively smaller effects to detect. Smaller effects require more participants for the same assumed power. These calculations are illustrative and depend on the observed estimate, which can be unstable, particularly when the observed difference is small. They should not be treated as the trial's actual design requirements or as evidence about how likely this completed trial was to find a result. This is not observed power.

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 = 0.010; pooled standard deviation σ = 1.844.
2. n = 2 × (1.96 + 0.842)² × 1.844² / 0.010² = 533,798.2, rounded up to 533,799 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 <- 0.0099999999999999                      # observed difference in means
sigma <- 1.84403730087282                     # 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(1499095)
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 = 533,799 (80% power), 714,605 (90% power)
 75% of observed effect: n per arm = 948,975 (80% power), 1,270,408 (90% power)
 50% of observed effect: n per arm = 2,135,193 (80% power), 2,858,418 (90% power)
power.t.test: 533799.1 
Simulated power at n = 533,799 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 a sponsor analysis of the primary outcome as a least-squares mean difference of -0.01, with a 95% confidence interval from -0.139 to 0.119. A p-value is not reported for that primary result. The record labels the analysis as a legacy non-inferiority or equivalence type, but the margin and detailed decision criteria are not reported in the registry record.

The simple recalculation from posted summaries gives a mean difference of 0.01 for Lantus relative to HOE901-U300 and an unadjusted p-value of 0.94. This is an unadjusted comparison and does not reproduce the sponsor's model-based estimate. Differences in method, adjustment, and the estimand being summarized can lead to differences between a recalculation and the sponsor's analysis.

There is no discrepancy flagged in the record. Even so, the sponsor's reported analysis is the primary basis for describing the trial result; the recalculation is supplementary and should not replace it. The recalculation does not supply the missing non-inferiority margin or resolve the limitations in the primary analysis description.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study evaluates more than one outcome or performs multiple statistical tests. In general, the more comparisons made, the more likely it is that at least one result may look notable by chance, even when the underlying effects are absent. A prespecified strategy can define which outcomes are confirmatory and whether or how error rates are controlled.

The registry lists a primary HbA1c endpoint and multiple secondary outcomes, including hypoglycemia and several glucose measures. It does not report a multiplicity adjustment plan, the full hierarchy of hypotheses, or whether any secondary analyses were designated as confirmatory. The secondary results should therefore be interpreted with caution, especially when considering individual p-values apart from the broader outcome set.

The primary result is reported as a legacy non-inferiority or equivalence type analysis, but the margin is not reported in the registry record. Without the margin and complete prespecified decision rules, the result cannot be independently assessed against a non-inferiority or equivalence criterion. The primary model's full specification is also not reported.

The registry describes a modified intent-to-treat population and says that measurements after rescue therapy were excluded from the primary analysis. It does not provide a complete account of missing data, the reasons for missing measurements, or sensitivity analyses. The record's primary outcome description refers to the Month 6 endpoint, while its analyzed-participant wording refers to baseline and Week 6 HbA1c assessment; this wording is not reconciled in the registry record.

The original sample-size justification, interim analysis plan, allocation concealment details, and full statistical analysis plan are not reported in the registry record. These omissions limit assessment of whether the analysis followed its planned procedures and how robust the findings are to alternative assumptions. No inference about those unreported procedures is warranted.

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: urinary tract infection (0.7%), ischaemic stroke (0.7%), acute myocardial infarction (0.5%), myocardial infarction (0.5%), invasive lobular breast carcinoma (0.5%).

The registry reports serious adverse events for 30 participants in the HOE901-U300 group and 30 participants in the Lantus group. The reported at-risk counts for this safety summary are 403 and 406, respectively. The record also reports other adverse events for 106 participants in the HOE901-U300 group and 96 participants in the Lantus group, using the same group-specific at-risk counts.

These are descriptive counts within the registry's safety reporting categories. They should not be treated as proof that the groups have identical safety profiles or as a formal comparison of risk. The record does not report a statistical comparison for these overall adverse-event counts. The serious terms listed include urinary tract infection and ischaemic stroke at 0.7% each, and acute myocardial infarction, myocardial infarction, invasive lobular breast carcinoma, and angina pectoris at 0.5% each. These terms and percentages describe listed serious events, not the full clinical context or an estimate of comparative risk.

Deaths are not reported in the registry record. Safety interpretation also needs to account for the open-label design and the limits of registry summaries, including the absence of detailed event narratives and adjudication information.

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

The posted primary result describes a small difference between the group least-squares mean changes in HbA1c, with a confidence interval that includes zero and extends in both directions. It is evidence about the trial's specified endpoint, analysis population, follow-up, and methods. It is not a guarantee that the treatments have identical effects, nor does it establish that any difference is clinically important.

The registry describes the primary comparison as non-inferiority or equivalence type, but does not report the margin or complete decision criteria. Without those details, the result cannot be translated into a conclusion that either criterion was met. A non-significant difference test would not by itself establish equivalence, and the sponsor's primary p-value is not reported.

The secondary outcomes provide additional observations about hypoglycemia and glucose measures. They should be understood as separate endpoints, with their own populations, methods, and uncertainty. The absence of a reported multiplicity plan means that isolated secondary findings should not be treated as definitive confirmation.

The study was randomized but open-label. Randomization supports a comparative design, while lack of masking may influence aspects of care or outcome collection. The primary analysis excluded measurements after rescue therapy began, and the full missing-data approach is not reported. These design and analysis features define what the posted results can support.

These findings do not determine an individual treatment decision and are not medical advice. The registry summary does not provide enough information to assess every aspect of benefit, harm, or clinical relevance. Its results should be interpreted as trial-level statistical evidence rather than a guarantee about outcomes for any particular person.

18. Why This Trial Matters Statistically

This trial illustrates why a between-group point estimate is not enough to interpret a comparative study. The sponsor's primary result pairs a least-squares mean difference with a confidence interval, allowing readers to consider both direction and precision. The interval includes zero, while the registry's non-inferiority or equivalence framing raises a separate question that cannot be resolved without the margin.

It also demonstrates the distinction between a sponsor's model-based analysis and a simple recalculation from posted summary statistics. The recalculation offers a transparent, unadjusted comparison, but it is not a replacement for the trial's reported analysis. Differences between estimates need to be understood in relation to the methods and estimands rather than treated as competing versions of one identical calculation.

The secondary outcome set shows why multiplicity matters. Several related but distinct outcomes can enrich interpretation, yet testing them without a reported strategy weakens the confirmatory weight of individual results. Reporting outcome-specific methods and denominators is important because different analyses may use different populations.

Finally, the record highlights the value of complete reporting. Details about the primary model, non-inferiority margin, missing data, and multiplicity would make the result easier to evaluate. Registry summaries allow clear description of posted findings, while also making visible where statistical interpretation must remain limited.

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 was open-label, so participants and study personnel were not masked to treatment assignment according to the registry. The record does not report allocation concealment or the handling of outcome assessment. These details matter when considering potential sources of bias, especially for outcomes affected by participant reporting or clinical judgment.

The primary result is described as a legacy non-inferiority or equivalence type analysis, but the margin and full decision rules are not reported. The primary statistical model and its covariates are also not specified. This prevents a complete evaluation of the sponsor's model-based estimate and its intended interpretation.

The primary outcome description excludes measurements after rescue therapy began. The record does not report full rescue-treatment criteria, missing-data procedures, or sensitivity analyses. It also uses Month 6 for the primary endpoint timeframe while describing the analyzed participants with reference to baseline and Week 6 HbA1c assessment. The registry record does not explain that wording.

The secondary outcome set contains multiple endpoints, but a multiplicity plan is not reported. Some posted secondary analyses have sponsor-reported methods while others do not. This uneven reporting, together with the lack of a reported multiplicity strategy, limits confirmatory interpretation of the secondary findings.

The safety summary provides counts and selected serious-event terms, but deaths are not reported in the registry record. The original sample-size assumptions, interim analyses, full protocol statistical plan, and sample-size justification are not reported. These limitations do not invalidate the posted estimates, but they narrow the conclusions that can be drawn from the registry summary.

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 2 Diabetes on Basal Insulin With Oral Antidiabetic Therapy — NCT01499095.
• Registry record last updated 2022-03-23; status last verified 2022-03.
• 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

The registry record describes a completed Phase 3 randomized, open-label, parallel-group study comparing HOE901-U300 with Lantus in adults with type 2 diabetes using oral antihyperglycemic therapy. Enrollment is listed as 811. The primary endpoint was change in HbA1c from baseline to the Month 6 endpoint.

The sponsor-reported primary least-squares mean difference was -0.01, with a 95% confidence interval from -0.139 to 0.119. The record labels this as a non-inferiority or equivalence type analysis, but does not report the margin. Secondary outcomes address hypoglycemia and additional glucose measures. The registry does not report the complete primary statistical plan, multiplicity strategy, or full missing-data approach, limiting interpretation of the posted results.