Comparison of NN5401 Plus Insulin Aspart With Insulin Detemir Plus Insulin Aspart in Type 1 Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comparison of NN5401 Plus Insulin Aspart With Insulin Detemir Plus Insulin Aspart in Type 1 Diabetes (NCT00978627), a randomized phase 3 study. The primary outcome is Main Trial (Primary Endpoint): Change in Glycosylated Haemoglobin (HbA1c) After 26 Weeks of Treatment.

2. Clinical Question

The clinical question is a comparison between treatment strategies, not a test of either regimen against no treatment. The primary endpoint is a continuous measure, so the reported group summaries describe average change, while the mean difference expresses the contrast between those average changes. The registry lists the trial as randomized, open-label, and parallel-group. Those features define the broad comparison, but the registry record does not report detailed eligibility criteria, allocation procedures, or the original statistical plan.

The registry record describes a main trial and an extension. The main trial’s primary endpoint is explicitly tied to Week 26. The extension is described as comparing safety and efficacy over a longer period, and selected extension outcomes are listed at Week 53. These time periods should not be conflated: the primary question is the Week 26 HbA1c comparison, not a combined estimate across the main and extension periods.

3. Trial Design

This was a phase 3, randomized, open-label, two-arm, parallel trial sponsored by Novo Nordisk A/S. The registry record reports 548 participants enrolled and a completed status. The trial began in 2009-08, and primary completion was recorded as 2010-05. Its stated setting included Europe, Oceania, and the United States of America.

The main trial, identified in the official title as NN5401-3594, compared once-daily NN5401 (insulin degludec/insulin aspart) plus insulin aspart with insulin detemir plus insulin aspart. The primary HbA1c endpoint was measured from Week 0 to Week 26. The registry describes an extension, identified as NN5401-3645, that continued the comparison of NN5401 plus meal-time insulin aspart with insulin detemir plus meal-time insulin aspart. The extension is described as assessing long-term safety and efficacy; selected posted outcomes use a Week 0 to Week 53 timeframe.

“Randomized” indicates that assignment was intended to use a random process, while “parallel” means participants were assigned to one of the treatment groups rather than crossing between regimens. “Open-label” means the registry does not describe masking of treatment assignment. The methods used to generate or conceal the allocation sequence, the eligibility criteria, and details of follow-up are not reported in the registry record.

For the primary endpoint, the registry identifies the full analysis set as including all randomized subjects and says that missing values were imputed using last observation carried forward. The arm-level primary summaries include 366 participants for IDegAsp OD and 182 for IDet. The exact analysis procedures beyond the stated analysis population and imputation approach, including any covariate adjustment or handling of protocol deviations, 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: The total duration of treatment was up to 52 weeks (26 weeks \[main trial: NN5401-3594, NCT00978627\] + 26 weeks \[extension trial: NN5401-3645\]), separated by 1 week of wash-out period; during which subjects were treated with Neutral Protamine Hagedorn (NPH) insulin twice daily (BID) in combination with insulin aspart.

Main: Week 0 to 26 (NN5401-3594)

Reasons for not completing this period:

Extension: Week 27 to 52 (NN5401-3645)

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The full analysis set (FAS) included all randomised subjects and missing data were imputed using last observation carried forward (LOCF).

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.

6. Primary Endpoint

The registry lists the primary outcome as Main Trial (Primary Endpoint): Change in Glycosylated Haemoglobin (HbA1c) After 26 Weeks of Treatment, measured over Week 0, Week 26.

The primary endpoint was change in glycosylated haemoglobin (HbA1c) after 26 weeks of treatment, measured from Week 0 to Week 26. HbA1c is a continuous measure of glycosylated haemoglobin, and the registry reports its unit as percentage of glycosylated haemoglobin. Change from baseline expresses how the measure shifted over the stated treatment period; it is not the same as the final value alone.

The registry reports mean change and standard deviation for each group. The mean describes the average change among participants included in the analysis, while the standard deviation describes how much individual participant changes varied around that average. The comparison is presented as the mean difference between IDet and IDegAsp OD. With this ordering, the reported difference is the IDet mean change minus the IDegAsp OD mean change.

HbA1c is used as an outcome because it provides a continuous measure that can be compared between randomized groups. A continuous endpoint can detect differences in average values even when participants’ individual changes vary. However, a group average does not describe every participant’s response, and the endpoint alone does not capture all aspects of treatment experience or safety.

The full analysis set included all randomized subjects, with missing data imputed using last observation carried forward (LOCF). LOCF carries a participant’s last available observation forward to a later assessment when a value is missing. This is an analysis convention; it does not recover an unobserved measurement. The registry record does not report how many values were missing or provide sensitivity analyses assessing the impact of the imputation.

7. Results Posted in the Registry

• IDet: mean -0.68 versus -0.73 on control; difference 0.05 (95% CI -0.09 to 0.19), standardized effect d = 0.06; z-test p = 0.486.

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.

Main Trial (Secondary Endpoint): Mean of 9-point Self Measured Plasma Glucose Profile (SMPG) at Week 26

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • IDet: mean 8.40 versus 8.00 on control; difference 0.40 (95% CI -0.03 to 0.83), standardized effect d = 0.17; z-test p = 0.071.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between IDet and the control. The interval gives the range of effects that remain compatible with the data.

Extension Trial (Secondary Endpoint): Change in Glycosylated Haemoglobin (HbA1c) After 52 Weeks of Treatment

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • IDet: mean -0.56 versus -0.65 on control; difference 0.09 (95% CI -0.05 to 0.23), standardized effect d = 0.11; z-test p = 0.217.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between IDet and the control. The interval gives the range of effects that remain compatible with the data.

Extension Trial (Secondary Endpoint): Change in Fasting Plasma Glucose (FPG) After 52 Weeks of Treatment

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • IDet: mean -2.40 versus -1.83 on control; difference -0.57 (95% CI -1.60 to 0.46), standardized effect d = -0.10; z-test p = 0.280.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between IDet and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary continuous outcomes cover a Week 26 self-measured plasma glucose profile and extension measures of HbA1c and fasting plasma glucose. Across these outcomes, the reported mean differences are modest relative to the uncertainty intervals, and each reported interval includes zero. This broad pattern is consistent with the primary comparison in that the posted summaries do not establish a clear between-group difference. It should not be interpreted as proof that the outcomes or treatment groups are equivalent.

The secondary outcomes address different measures and timeframes, so they add context rather than combine into a single result. The extension HbA1c and fasting plasma glucose outcomes are recorded with a Week 0 to Week 53 timeframe, while the primary HbA1c outcome is the main trial’s Week 26 measure. The Week 26 self-measured plasma glucose profile is another distinct outcome. Differences in endpoint definition and timing limit direct comparison of their estimates.

The registry also lists confirmed hypoglycaemic episodes and nocturnal confirmed hypoglycaemic episodes among secondary outcomes. Numeric results for these listed outcomes are not reported in the registry record. Their inclusion in the outcome list alone does not provide evidence about the comparative event rates.

Secondary results generally carry less weight than the primary endpoint because they are additional comparisons, and examining multiple outcomes can increase the chance of an apparently notable result arising by chance. The registry record does not report a multiplicity adjustment or a hierarchical testing procedure. The secondary p-values are therefore unadjusted and should be interpreted cautiously, particularly when considered alongside the range of outcomes listed. Their role is descriptive and supportive, not a replacement for the primary endpoint analysis.

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

• Main Trial (Secondary Endpoint): Rate of Confirmed Hypoglycaemic Episodes
• Main Trial (Secondary Endpoint): Mean of 9-point Self Measured Plasma Glucose Profile (SMPG) at Week 26
• Extension Trial (Secondary Endpoint): Change in Glycosylated Haemoglobin (HbA1c) After 52 Weeks of Treatment
• Main Trial (Secondary Endpoint): Rate of Nocturnal Confirmed Hypoglycaemic Episodes
• Extension Trial (Secondary Endpoint): Change in Fasting Plasma Glucose (FPG) After 52 Weeks of Treatment

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous, and the registry reports a mean and standard deviation for each randomized group. A mean is the arithmetic average of the measured change; a standard deviation describes the variation of individual changes around that average. Neither statistic, on its own, reveals the full distribution of responses. The mean difference places the group averages on a common scale and is the main contrast for interpreting the primary result.

How should the mean difference be read?

The reported comparison is IDet minus IDegAsp OD. The group means were -0.73 and -0.68, respectively, and the resulting reported mean difference was 0.05. A positive value under this ordering means the IDet group’s mean change is numerically higher than the IDegAsp OD group’s mean change. The sign depends on which group is subtracted from which; it does not by itself determine clinical importance.

The reported difference is an unadjusted comparison based on the posted summary statistics. It does not account for covariates or other design features unless those are incorporated in the method, and such adjustments are not reported in the registry record. The sponsor’s original statistical model and analysis plan are also not reported in the registry record. These limits matter because adjusted and unadjusted estimates can answer somewhat different statistical questions.

What does a confidence interval add?

A confidence interval expresses uncertainty around an estimated effect under a statistical model. A narrower interval indicates greater precision in that estimate, while a wider interval indicates greater uncertainty. The primary interval runs from -0.090 to 0.191. Since it includes zero, the posted data are compatible with no mean difference as well as with differences in either direction within the interval. The interval is not a range containing every plausible individual response, and it is not a probability statement about the true effect.

What does the p-value describe?

The primary unadjusted p-value is 0.486. In general, a p-value measures how unusual data at least as discrepant as those observed would be under a specified null hypothesis and test procedure. It does not measure the probability that the null hypothesis is true, and it does not measure clinical importance. Interpretation depends on the analysis assumptions and on whether the comparison was specified in advance. The registry record does not report a complete statistical analysis plan or the details needed to assess every assumption.

How does the analysis population affect interpretation?

The registry says the full analysis set included all randomized subjects and that missing data were handled using last observation carried forward. In general, an analysis population defines which participants contribute to the estimate. LOCF substitutes a participant’s most recent available measurement when a later value is missing. This may keep participants in the analysis, but it relies on an assumption about how the unobserved value relates to the last observed value. The registry record does not report the number of missing observations, reasons for missingness, or sensitivity analyses using alternative assumptions.

The endpoint summaries include 366 participants for IDegAsp OD and 182 for IDet. For secondary measures, the participant counts differ by outcome. Such differences can arise from outcome-specific availability, but the reasons for the reported counts are not reported in the registry record. The planned randomized enrollment and the analyzed count for a particular measure should not be treated as interchangeable.

Why does variation matter?

Standard deviations of 0.83 and 0.77 were reported for the primary group changes. These values describe variation in the observed change scores; they are not standard errors of the mean difference. A standard error reflects the uncertainty in an estimate and depends on both variability and the number of observations. In general, greater variability makes it harder to estimate a group contrast precisely, while more observations can improve precision if other conditions are comparable.

The registry supplies no indication that the primary standard deviations were approximated. The original statistical model, any stratification, covariate adjustment, and any interim analyses are not reported in the registry record. For that reason, the posted unadjusted comparison should not be mistaken for a complete account of every analysis that may have been conducted.

What is the role of the secondary outcomes?

Secondary outcomes can describe other dimensions of the comparison, but they do not automatically carry the same evidential weight as a primary endpoint. When many outcomes are examined, the chance of finding an apparently notable result by chance increases unless a suitable multiplicity strategy is used. The registry record does not report whether multiplicity adjustment was planned or performed. The posted secondary p-values are unadjusted, so they should be treated as exploratory unless a more complete analysis plan establishes otherwise.

The primary endpoint was a continuous change score. Other posted continuous outcomes include a Week 26 self-measured plasma glucose profile and extension measures of HbA1c and fasting plasma glucose. Their means, standard deviations, and mean differences are summaries of different measurements and timeframes. They should not be combined into a single overall treatment effect without a suitable prespecified model.

11. Confidence Intervals and Precision

The primary mean difference was 0.05, with a 95% confidence interval from -0.090 to 0.191. The interval spans zero, so the estimate does not pinpoint a clear direction of difference. Its endpoints also indicate that the data remain compatible with a modest difference in either direction under the analysis model. The interval is the main guide to the precision of the estimated contrast; the point estimate alone would conceal that uncertainty.

A confidence interval is constructed using a method that, over repeated comparable studies, is designed to include the true effect at the stated confidence level with the stated frequency. It is not a guarantee that the true effect lies within this particular interval, nor does it mean that every value inside the interval is equally plausible. Its interpretation also depends on the statistical model and on the analysis population and missing-data method used.

The group standard deviations, 0.83 for IDegAsp OD and 0.77 for IDet, describe participant-level variability in change. They are distinct from the uncertainty around the mean difference. The group sizes contributing to the primary summaries were 366 and 182, and the groups were not equal in size. The registry does not report the original design assumptions or a sponsor-reported adjusted confidence interval, so precision should be interpreted in the context of the posted unadjusted summaries.

The primary p-value of 0.486 is consistent with the interval including zero, but a p-value does not replace the interval. A non-small p-value does not demonstrate that any difference is negligible. To establish equivalence or non-inferiority, a margin and an appropriate prespecified framework would be needed; such details are not reported in the registry record. The available result therefore conveys uncertainty about the size and direction of the mean contrast rather than proof of sameness.

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 estimates are expressed as participants per arm for 80% power and participants per arm for 90% power. They are not total event counts: these are continuous-outcome calculations, and the stated planning assumptions use equal allocation between two arms. The estimates are based on the observed effect and standard deviation, with a two-sided significance level of 0.05 and a normal approximation. The effect to detect is set to the stated fraction of the observed effect.

The 80% power column describes a planning scenario in which the assumed study would have an 80% chance of detecting the specified effect if that effect were the true one and the assumptions held. The 90% power column uses the corresponding 90% target. These are planning probabilities, not guarantees about a future study’s result. Smaller assumed effects require more participants because a smaller signal is harder to distinguish from random variation.

The estimates are illustrations calculated from the observed effect, not the original design justification for this trial. The registry record does not report the trial’s original sample-size assumptions or justification. This is not observed power: the calculations do not tell how much power the completed trial had after its results were observed. They instead show how the required per-arm sample size changes under specified hypothetical effect sizes and planning assumptions.

When reading the estimates, keep the assumed effect fraction and target power together. A smaller fraction of the observed effect leads to a larger required number of participants per arm, while a higher target power also requires a larger sample under otherwise comparable assumptions. These calculations do not incorporate any unreported design features, such as attrition allowances or a more complex analysis model.

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 = 0.050; pooled standard deviation σ = 0.811.
2. n = 2 × (1.96 + 0.842)² × 0.811² / 0.050² = 4,125.8, rounded up to 4,126 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 <- 0.0499999999999999                      # observed difference in means
sigma <- 0.810602136794509                     # 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(978627)
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 = 4,126 (80% power), 5,524 (90% power)
 75% of observed effect: n per arm = 7,335 (80% power), 9,820 (90% power)
 50% of observed effect: n per arm = 16,504 (80% power), 22,094 (90% power)
power.t.test: 4126.8 
Simulated power at n = 4,126 per arm: 0.799 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several outcomes, time points, groups, or statistical comparisons are examined. Even when each individual test uses a conventional threshold, conducting many tests increases the chance that at least one result appears notable by chance. Common strategies include defining a hierarchy of hypotheses or adjusting the testing threshold, but the registry record does not report whether either strategy was planned or used.

The posted secondary comparisons include a Week 26 plasma glucose profile and extension measures of HbA1c and fasting plasma glucose. Other secondary outcome topics listed in the registry include confirmed and nocturnal confirmed hypoglycaemic episodes. The reported secondary p-values are unadjusted. The registry record does not report a family-wise error strategy, a false-discovery approach, or any other multiplicity procedure. Consequently, secondary p-values should not be read as if each were the sole planned confirmatory test.

Missing-data handling is described for the primary endpoint: the full analysis set included all randomized subjects, and missing data were imputed using last observation carried forward. The registry record does not report how many primary endpoint values were missing, when measurements were missing, or why they were missing. It also does not report sensitivity analyses examining alternative missing-data assumptions. LOCF can preserve an analysis record for a participant with an earlier observation, but the carried-forward value may not represent the unobserved later measurement.

The registry does not report the original statistical analysis plan, sample-size justification, interim analyses, or the sponsor’s detailed inferential model. It also does not describe whether the extension analysis population or missing-data procedures differed from those used for the primary endpoint. These omissions limit assessment of prespecification and robustness. They do not invalidate the posted summaries, but they mean that the evidence should be interpreted as the results available in the registry record rather than as a complete reconstruction of the trial’s statistical conduct.

15. 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 (5.0%), hypoglycaemic unconsciousness (2.2%), diabetic ketoacidosis (1.7%), tachyarrhythmia (0.6%), pancreatitis acute (0.6%).

The registry reports serious adverse events for 362 participants at risk in the IDegAsp OD group, with 46 affected, and for 180 participants at risk in the IDet group, with 20 affected. These are counts for the safety groups as recorded; they are not the same denominators as the primary efficacy summaries. The other-adverse-event counts are also reported separately: 166 of 362 at risk for IDegAsp OD and 90 of 180 at risk for IDet. These counts describe participants recorded as affected, not the number of separate events.

The most frequent serious adverse event terms listed include hypoglycaemia at 5.0%, hypoglycaemic unconsciousness at 2.2%, and diabetic ketoacidosis at 1.7%; tachyarrhythmia, acute pancreatitis, and small intestinal obstruction are each listed at 0.6%. The registry record does not provide enough detail in these summaries to infer causation or compare event rates with adjustment for exposure or follow-up.

Deaths are not reported in the registry record. Serious adverse event summaries describe recorded safety events, but they do not by themselves establish that a treatment caused an event or provide a complete assessment of safety.

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

The primary result is an estimate of the difference in average HbA1c change between the two randomized groups over the main trial’s 26-week period. The estimated difference was 0.05, and its confidence interval extended from -0.090 to 0.191. The interval includes zero, so the posted result does not establish a clear difference in mean change. The interval also allows differences in either direction, so the result should not be described as demonstrating equivalence.

This is a group-level comparison. It does not indicate that every participant experienced the average change, and it does not describe the full range of individual outcomes. The standard deviations indicate participant-level variation, while the confidence interval describes uncertainty in the estimated group contrast. Those are different sources of information.

The result also depends on the defined endpoint and analysis approach. The endpoint is change in HbA1c from baseline to Week 26, analyzed in the full analysis set with missing data imputed by last observation carried forward. It is not a direct estimate of every aspect of glycaemic control, safety, treatment burden, or long-term outcome. The registry record does not report missing-data sensitivity analyses or a complete statistical plan, which limits how far the estimate can be generalized beyond the stated analysis.

Secondary measures provide further descriptive information but do not replace the primary endpoint. Their intervals include zero, and their p-values are unadjusted. Outcomes listed without numeric results, including confirmed hypoglycaemic episode measures, cannot be interpreted from the outcome list alone. The extension outcomes also use a later timeframe than the primary endpoint and should be considered separately.

These statistics do not establish that one regimen works or does not work, nor do they support individual treatment decisions. They describe the comparative data posted for this randomized trial and the precision of the estimated differences. Clinical importance requires interpretation in context, including relevant thresholds and other evidence that are not reported in the registry record.

17. Why This Trial Matters Statistically

This trial illustrates why a point estimate and its uncertainty need to be read together. The primary mean difference is close to zero, but the confidence interval is the information that shows how much uncertainty remains around that estimate. A result that does not establish a clear difference is not the same as evidence that the treatments are identical.

It also highlights the distinction between a trial’s observed sample and a planning calculation. The planning estimates use the observed effect as a hypothetical basis for future sample-size scenarios. They are not a report of the original design rationale and are not observed power. The registry record does not report the original sample-size justification, so the planning illustrations cannot be used to infer what effect the trial was designed to detect.

The endpoint and analysis population matter as much as the headline comparison. The primary analysis used a full analysis set with LOCF for missing observations. Understanding the consequences of that choice would require information about missingness and sensitivity analyses, which are not reported in the registry record. This is a reminder that missing-data conventions can shape the interpretation of an otherwise straightforward mean comparison.

Finally, the record lists multiple secondary outcomes, but does not report multiplicity handling. This makes the hierarchy between a primary endpoint and secondary findings important: secondary comparisons can broaden the description of results, but unadjusted findings should not be treated as independent confirmatory evidence. Together, these points show how design, endpoint definition, missing-data methods, precision, and multiplicity all qualify interpretation of a clinical trial result.

18. 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 contains limited detail about eligibility criteria, participant characteristics, allocation methods, and follow-up. It identifies the trial as randomized, open-label, and parallel, but does not report how the random sequence was generated or concealed. The absence of masking may be relevant to outcomes influenced by participant or investigator awareness, although the registry does not provide enough information to assess its impact for each outcome.

The primary analysis used LOCF for missing data, but the amount, timing, and reasons for missingness are not reported. No sensitivity analyses are reported to show whether the primary estimate changes under alternative missing-data assumptions. The record also does not give the original statistical analysis plan, the model used for any sponsor analysis, or details of covariate adjustment. The posted comparison is an unadjusted recalculation from summary statistics.

The sample-size planning illustrations are based on the observed effect and specified planning assumptions, not the trial’s original design. The original sample-size justification and interim analysis procedures are not reported. This limits assessment of whether the trial was designed around a clinically meaningful effect or how its analysis plan controlled error across outcomes.

Safety summaries provide counts of participants affected and a list of serious event terms, but deaths are not reported in the registry record. The summaries do not give event timing, exposure-adjusted rates, or enough detail to determine causality. Numeric results are also absent for some listed secondary outcomes, including confirmed and nocturnal confirmed hypoglycaemic episodes.

These limitations do not negate the available outcome summaries, but they restrict the strength and scope of conclusions that can be drawn from the registry record alone.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Comparison of NN5401 Plus Insulin Aspart With Insulin Detemir Plus Insulin Aspart in Type 1 Diabetes — NCT00978627.
• Registry record last updated 2017-03-20; status last verified 2017-02.
• Results first posted 2015-11-20.
• 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.

22. Record Summary

This completed phase 3 trial randomized 548 participants with type 1 diabetes in an open-label, parallel comparison of once-daily insulin degludec/insulin aspart plus insulin aspart with insulin detemir plus insulin aspart. The primary endpoint was mean change in HbA1c from baseline to Week 26, analyzed in the full analysis set with missing data imputed using last observation carried forward.

Mean primary endpoint changes were -0.73 for IDegAsp OD and -0.68 for IDet. The reported mean difference was 0.05, with a 95% confidence interval from -0.090 to 0.191 and an unadjusted p-value of 0.486. The interval includes zero and leaves uncertainty about the direction and size of the mean contrast. Selected secondary continuous outcomes were also posted, but their comparisons are unadjusted and do not establish a clear difference. The registry record does not report the original sample-size justification, a complete statistical analysis plan, or multiplicity handling.