Comparison of Two NN1250 Formulations Versus Insulin Glargine, All in Combination With Metformin in Subjects With Type 2 Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comparison of Two NN1250 Formulations Versus Insulin Glargine, All in Combination With Metformin in Subjects With Type 2 Diabetes (NCT00611884), a randomized phase 2 study. The primary outcome is Change in Glycosylated Haemoglobin (HbA1c).

2. Clinical Question

3. Trial Design

This was a randomized, open-label, four-armed, parallel-group phase 2 trial. The official title describes it as a 16-week treat-to-target study. It enrolled 245 subjects and is recorded as completed. The registry lists the study start as 2008-01 and primary completion as 2008-08.

Participants were assigned to one of three insulin degludec regimens or once-daily insulin glargine. The degludec arms were SIBA (D) once daily, SIBA (E) once daily, and SIBA (D) on Monday, Wednesday and Friday. All groups received metformin in combination with the assigned insulin. The registry describes the participants as insulin-naive and as having type 2 diabetes while failing on oral antidiabetic drug treatment.

Open-label means that treatment assignment was not masked. The registry lists masking as none. Randomization can help balance prognostic factors across groups, but the record does not report the allocation sequence, concealment procedures, or any stratification factors. The parallel-group structure means participants were assigned to a regimen and compared across groups rather than crossing between regimens.

The primary endpoint was change in HbA1c after 16 weeks, measured from baseline. The full analysis set included all randomized subjects; missing primary outcome data were imputed using last observation carried forward. The registry lists secondary outcomes covering self-measured plasma glucose, hypoglycaemic episodes, treatment-emergent adverse events, laboratory measures and diastolic blood pressure. Details of the original sample-size justification, formal statistical plan and specific treat-to-target procedures 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: Subjects underwent a run-in period of 3 weeks; 2 weeks of up-titration period, where metformin was up-titrated to 1500 or 2000 mg/day, followed by 1 week of maintenance period. Subjects who tolerated 1500 or 2000 mg/day of metformin for a week and had a median fasting plasma glucose ≥ 7.5 mmol/L (135 mg/dL) were randomised.

Overall Study

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 is 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 Change in Glycosylated Haemoglobin (HbA1c), measured over Week 0, Week 16.

The primary endpoint is change from baseline in glycosylated haemoglobin (HbA1c) after 16 weeks of treatment. HbA1c is a continuous measure of glycaemic status. A change score expresses how the measured value at follow-up differs from the participant’s baseline value; the reported group means are therefore negative when the average value fell from baseline.

The registry reports mean change and standard deviation for each treatment group. The full analysis set included all randomized subjects, and missing values were imputed using last observation carried forward (LOCF). LOCF carries a participant’s last recorded value forward to represent a later missing measurement. This approach permits an analysis that retains participants with missing follow-up data, but it relies on an assumption that the carried-forward value is an appropriate stand-in for the unobserved value. The registry record does not report the extent or pattern of missing primary outcome data.

HbA1c is used in clinical trials because it provides a continuous outcome that can be summarized as a group mean and compared across randomized groups. A mean difference estimates the contrast in average change between groups. It does not describe every participant’s response, and a group-level estimate should be read together with its uncertainty interval and the analysis population. The registry does not report a clinically important difference threshold for this endpoint, so the practical importance of the estimates cannot be determined from the reported results alone.

7. Results Posted in the Registry

• SIBA (E): mean -1.28 versus -1.26 on control; difference -0.02 (95% CI -0.42 to 0.38), standardized effect d = -0.02; z-test p = 0.921.
• SIBA (D) M, W, F: mean -1.46 versus -1.26 on control; difference -0.20 (95% CI -0.58 to 0.18), standardized effect d = -0.18; z-test p = 0.307.
• IGlar: mean -1.49 versus -1.26 on control; difference -0.23 (95% CI -0.62 to 0.16), standardized effect d = -0.21; z-test p = 0.253.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Mean of 9-point Self Measured Plasma Glucose Profile (SMPG)

• 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:
  • SIBA (E): mean 8.55 versus 8.30 on control; difference 0.25 (95% CI -0.91 to 1.41), standardized effect d = 0.08; z-test p = 0.674.
  • SIBA (D) M, W, F: mean 8.45 versus 8.30 on control; difference 0.15 (95% CI -1.01 to 1.31), standardized effect d = 0.05; z-test p = 0.801.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SIBA (E) and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SIBA (D) M, W, F and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover several domains: self-measured plasma glucose, hypoglycaemic episodes, treatment-emergent adverse events, laboratory safety parameters and diastolic blood pressure. The registry lists 11 secondary outcomes as posted. Numerical comparative results are available for the 9-point self-measured plasma glucose profile at Week 16. Results for the other listed outcomes are not reported in the registry record in the information available for interpretation.

The Week 16 profile means are 8.3 for SIBA (D), 8.55 for SIBA (E), 8.45 for SIBA (D) Monday, Wednesday and Friday, and 8.42 for insulin glargine, in mmol/L. The reported comparisons against SIBA (D) have intervals that include zero and unadjusted p-values of 0.674 and 0.801 for the two degludec comparisons with posted comparison estimates. These secondary findings do not provide a clear, precise contrast that changes the overall reading of the primary HbA1c results. The registry record does not include a posted comparative estimate for insulin glargine on this secondary measure.

In general, secondary outcomes can add context by measuring different effects or aspects of safety, but a collection of outcomes creates more opportunities for apparently notable findings by chance. Unless the analysis plan prespecifies how these outcomes are tested and how multiplicity is handled, unadjusted secondary results carry less weight than a clearly defined primary comparison. The registry record does not report a multiplicity strategy or a complete set of secondary analysis details.

Some listed outcomes are event rates, while others are continuous measurements or laboratory values. Their results cannot be combined into a single overall conclusion without a prespecified method and the relevant estimates. The absence of posted comparative results for several listed outcomes should not be interpreted as evidence that no events or changes occurred; those results are simply not reported in the registry record.

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

• Mean of 9-point Self Measured Plasma Glucose Profile (SMPG)
• Rate of Major and Minor Hypoglycaemic Episodes
• Rate of Nocturnal Major and Minor Hypoglycaemic Episodes
• Rate of Treatment Emergent Adverse Events (AEs)
• Laboratory Safety Parameters (Biochemistry): Alanine Aminotransferase (ALAT)
• Laboratory Safety Parameters (Biochemistry): Aspartate Aminotransferase (ASAT)
• Laboratory Safety Parameters (Biochemistry): Serum Creatinine
• Vital Signs: Diastolic Blood Pressure (BP)

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean change represent?

A mean is the arithmetic average of the measured changes among participants included in an analysis. For the primary endpoint, each participant’s change is defined relative to baseline, and the arm-level mean summarizes those changes. A negative mean indicates a decline from baseline on the measured scale. Comparing two arm means gives a mean difference: a value below zero indicates a more negative average change in the comparison arm than in the reference arm.

The trial reports standard deviations alongside the arm means. A standard deviation describes how dispersed individual participant values are around their group mean. It is not the same as the standard error, which describes the precision of an estimated mean. More variability among individual results generally makes a group mean less precise when the number of participants is held fixed.

How should the group comparisons be read?

The posted primary comparisons are SIBA (E), SIBA (D) Monday, Wednesday and Friday, and insulin glargine, each contrasted with SIBA (D). The estimated mean differences are -0.02, -0.2 and -0.23, respectively. Their uncertainty intervals are reported alongside the estimates. Because each interval includes zero, the results do not rule out a zero mean difference at the interval’s stated coverage level. The registry record does not state the coverage level, so no confidence percentage should be inferred from these entries alone.

The p-values are labelled unadjusted. In general, a p-value measures how incompatible the observed data are with a specified null model, conditional on the assumptions of the test. It is not the probability that the null hypothesis is true, nor is it a measure of effect size. An unadjusted value does not account for the fact that several comparisons may be examined. The registry record does not report the testing procedure, any adjustment for multiple comparisons, or a prespecified hierarchy of comparisons.

Why do uncertainty intervals matter?

In general, an uncertainty interval gives a range of values compatible with the data and the analysis assumptions. A point estimate alone can give a misleading impression of certainty. Here, each estimated mean difference is close to zero relative to the breadth of its interval, and each interval spans both negative and positive values. This means the posted data are not precise enough to identify a narrowly bounded direction and size for the average contrast. The interval does not include every possible source of uncertainty, such as uncertainty caused by analysis choices or missing-data assumptions.

The sample-size planning illustrations use the observed effect as a reference and show hypothetical requirements for detecting specified fractions of that effect. They are calculations for planning interpretation, not the trial’s original justification. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The original sample-size calculation and its assumptions are not reported in the registry record.

What does last observation carried forward assume?

The primary full analysis set includes all randomized subjects, with missing values imputed using last observation carried forward. In general, LOCF substitutes the last recorded outcome for a later missing value. It is a simple way to retain participants in an analysis, but it treats the last observed value as if it represented the missing follow-up value. That may not match the participant’s unobserved outcome, particularly if the measure would otherwise change over time. The registry record does not report how many values were missing, why they were missing, or sensitivity analyses using alternative missing-data approaches.

What can be inferred from the secondary measures?

The registry includes secondary outcomes involving a 9-point self-measured plasma glucose profile, major and minor hypoglycaemic episodes, nocturnal episodes, treatment-emergent adverse events, laboratory safety measures and diastolic blood pressure. A secondary outcome may help describe other aspects of the trial, but its interpretation depends on the analysis method, the amount of missing data and the handling of multiple testing. The registry lists a Week 16 plasma glucose profile measure, with least-squares means and standard errors. It does not report a complete set of comparative analyses for the other listed secondary outcomes.

In general, over-dispersion matters when event counts vary more than a simple statistical model expects. Accounting for extra variation can widen uncertainty and change the reliability of standard errors and tests. The registry record does not specify an over-dispersion model for the hypoglycaemia outcomes, so no particular count-model approach should be assumed. Likewise, the registry does not provide enough analysis detail to establish whether the posted summary comparisons reproduce the trial’s prespecified analysis.

11. Confidence Intervals and Precision

The primary mean differences are reported with uncertainty intervals. For SIBA (E) compared with SIBA (D), the estimate is -0.02 and the interval runs from -0.416 to 0.376. For SIBA (D) Monday, Wednesday and Friday, the estimate is -0.2 and the interval runs from -0.584 to 0.184. For insulin glargine, the estimate is -0.23 and the interval runs from -0.624 to 0.164. Each interval crosses zero, so the data are compatible with either a negative or positive mean difference as well as a zero difference.

In general, a confidence interval expresses uncertainty around an estimate under the model and analysis used. A narrower interval indicates greater precision, while a wider interval leaves more uncertainty about the size and direction of the contrast. The registry record does not state the coverage level for these intervals, so that level is not reported in the registry record. The estimates should not be read as proving that the groups are identical just because the intervals include zero.

The arm-level standard deviations range from 1.06 to 1.12 for the primary change measure, while the analyzed arm sizes range from 60 to 62. Standard deviations describe participant-to-participant variation; the intervals describe uncertainty about the between-group mean differences. These are different summaries and answer different questions. The intervals also do not account for uncertainty introduced by unreported choices in the original statistical plan or by possible departures from the LOCF assumption.

The practical precision of the estimates cannot be judged against a clinical threshold because such a threshold is not reported in the registry record. The results therefore show both the estimated average contrasts and their statistical uncertainty, but they do not establish whether the remaining uncertainty is small or large enough for a particular clinical decision.

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 express sample size as participants per arm for these continuous outcome comparisons. They do not report total events. The general convention for time-to-event planning is to report a total number of events, but these comparisons are not time-to-event analyses.

The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each illustrated target uses a stated fraction of the observed effect as the effect to detect. The participant counts are hypothetical planning illustrations based on those assumptions; they are not the original trial design calculation. The original sample-size assumptions are not reported in the registry record.

The 80% power column gives the number of participants per arm that the calculation associates with an 80% chance of detecting the target effect under the stated assumptions, if that effect and model assumptions are correct. The 90% power column gives the corresponding count for a higher probability of detecting the target effect. These are conditional planning quantities, not guarantees about what a future study will find. This is not observed power.

The rows for 100%, 75% and 50% of the observed effect illustrate how the target effect size changes the required sample. Smaller effects are harder to distinguish from random variation and therefore require more participants. The observed estimates, especially when uncertain, may not be a reliable estimate of the effect a future study should target. The illustrations also do not account for features not included in their stated assumptions, such as missing data, unequal allocation, or a multiplicity procedure.

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 = -0.020; pooled standard deviation σ = 1.110.
2. n = 2 × (1.96 + 0.842)² × 1.110² / -0.020² = 48,353.0, rounded up to 48,354 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 <- -0.02                      # observed difference in means
sigma <- 1.11                     # 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(611884)
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 = 48,354 (80% power), 64,731 (90% power)
 75% of observed effect: n per arm = 85,961 (80% power), 115,078 (90% power)
 50% of observed effect: n per arm = 193,413 (80% power), 258,924 (90% power)
power.t.test: 48354 
Simulated power at n = 48,354 per arm: 0.800 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The primary analysis population is defined as the full analysis set, including all randomized subjects. Missing primary endpoint data were imputed using last observation carried forward. The registry record does not report the number of missing HbA1c measurements, the reasons for missingness, or whether missingness differed across groups. It also does not report sensitivity analyses to assess whether the result changes under other missing-data assumptions.

The record does not describe the original statistical analysis plan, the method used to generate the reported intervals, or a prespecified clinical threshold for the primary endpoint. It also does not report the original sample-size justification, interim analyses, or a procedure for handling multiple comparisons. The unadjusted p-values should therefore be read as unadjusted evidence for the individual posted comparisons, not as results corrected for the set of comparisons examined.

Four treatment groups create multiple possible contrasts, and the registry presents comparisons against SIBA (D). Without a reported multiplicity plan, it is not possible to determine whether the displayed comparisons were selected in advance, whether other contrasts were tested, or how family-wise error was managed. This uncertainty does not change the numerical estimates, but it affects how strongly nominal p-values can support confirmatory claims.

The registry lists secondary measures spanning glucose profiles, hypoglycaemia, adverse events, laboratory parameters and vital signs. It does not report full comparative analyses for all those outcomes. No assumptions about unreported endpoints, missing-data handling beyond the primary endpoint, or the original analysis population for each secondary outcome should be made.

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: atrial fibrillation (1.8%), coronary artery disease (1.6%).

The serious adverse event counts are reported among participants at risk in each arm. SIBA (D) had 1 serious event among 57 participants at risk; SIBA (E) had 0 among 59; SIBA (D) Monday, Wednesday and Friday had 1 among 62; and insulin glargine had 0 among 61. These are counts over the trial record’s safety reporting period, not estimates of comparative risk adjusted for exposure or other factors.

The registry also reports participants with other, non-serious adverse events: 22 of 57 for SIBA (D), 16 of 59 for SIBA (E), 19 of 62 for the Monday, Wednesday and Friday regimen, and 23 of 61 for insulin glargine. The listed top serious adverse event terms are atrial fibrillation at 1.8% and coronary artery disease at 1.6%. Death counts are not reported in the registry record.

These sparse event counts do not establish that the regimens have the same or different safety profiles. The registry does not report a statistical comparison of serious adverse events, event exposure time, or additional detail sufficient to interpret the listed terms by treatment group. Absence of a reported count is not evidence that an event could not occur.

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

The results describe mean HbA1c change over 16 weeks among the randomized subjects included in the full analysis set, using last observation carried forward for missing primary outcome data. The group means were negative in all four arms. The estimated mean differences against SIBA (D) were small in comparison with their uncertainty intervals, and every interval included zero. The unadjusted p-values do not offer strong evidence against a zero difference for these comparisons.

That pattern does not prove that the treatments are equivalent. Equivalence requires a prespecified margin and an analysis designed to assess whether the uncertainty is contained within that margin; such a margin and analysis are not reported in the registry record. The results also do not establish that any difference is clinically important. A clinical interpretation would require a relevant threshold and a fuller understanding of the intended population and treatment context, neither of which is reported in the registry record.

The data should not be read as a complete account of every outcome or every possible safety difference. The registry lists secondary outcomes, but comparative results are not available for all of them. The reported serious adverse event counts are low, and the registry record does not provide a formal comparison that would support a conclusion about relative safety.

These findings are specific to the studied population, the four regimens, metformin combination treatment, the 16-week follow-up, and the recorded analysis approach. They do not directly establish outcomes beyond that period, in populations not described by the trial, or under treatment conditions different from those studied. They are statistical summaries of the posted data, not treatment recommendations.

17. Why This Trial Matters Statistically

This trial illustrates why a point estimate should not be interpreted in isolation. The primary arm means all show a negative change, but the between-group estimates are close to zero and their intervals span values on both sides of zero. The direction of an arm-level change and the size of a between-arm contrast answer different questions: improvement within each group does not itself demonstrate a difference between groups.

The study also shows the importance of distinguishing participant variability from uncertainty in a group comparison. The standard deviations describe the spread of individual changes, while the intervals around mean differences describe uncertainty about average contrasts. The arm sizes, ranging from 60 to 62, and the observed variability help explain why estimates can remain uncertain even when the group means appear distinct.

Its open-label design and LOCF approach are relevant to interpretation. Masking was none, and missing primary outcomes were handled by carrying the last observation forward. These design and analysis features do not automatically invalidate the results, but they identify assumptions that readers should consider. The registry does not report the original statistical plan, sample-size justification, or multiplicity procedure, limiting assessment of whether the posted comparisons match the intended confirmatory analysis.

Finally, the planning illustrations clarify the relationship between a target effect and the number of participants needed to detect it under stated assumptions. They are not evidence of the trial’s achieved power and should not be confused with the original design rationale. Keeping those distinctions clear supports cautious interpretation of both the estimates and the planning calculations.

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 trial was open-label, with no masking reported. Knowledge of assigned treatment can affect participant behavior, co-interventions, reporting and some outcome assessments, although HbA1c is a laboratory measure. The registry does not report procedures for minimizing such effects.

Follow-up for the primary endpoint was 16 weeks. The results therefore describe change over that period and do not provide evidence about longer-term outcomes. The registry gives broad regions of conduct—Africa, Asia and North America—but does not identify countries or provide enough information to assess how well the enrolled population represents other settings.

The arm descriptions in the registry are blank, and the record does not provide further formulation details beyond the regimen names and schedules. The study population is described as insulin-naive and failing on oral antidiabetic drug treatment; the record does not provide enough participant characteristics to assess applicability across different clinical subgroups.

The primary missing-data method was LOCF, but the amount and pattern of missing data and sensitivity analyses are not reported. The original sample-size calculation, formal statistical analysis plan, multiplicity approach, interval coverage level and clinically important difference threshold are also not reported in the registry record. Secondary outcome results are incomplete, and the posted safety data do not include a formal comparative analysis. These omissions limit evaluation of robustness, precision and the range of conclusions supported by the record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Comparison of Two NN1250 Formulations Versus Insulin Glargine, All in Combination With Metformin in Subjects With Type 2 Diabetes — NCT00611884.
• Registry record last updated 2017-03-03; status last verified 2017-01.
• Results first posted 2015-11-16.
• 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 2 randomized, open-label, parallel-group trial enrolled 245 subjects with type 2 diabetes. It compared three insulin degludec regimens with once-daily insulin glargine, all in combination with metformin, over 16 weeks.

The primary endpoint was change from baseline in HbA1c. Mean changes ranged from -1.26 to -1.49 across the four arms. The reported mean differences against SIBA (D) were -0.02, -0.2 and -0.23, with intervals that each included zero. The primary full analysis set included all randomized subjects, with missing data imputed by last observation carried forward.

The registry lists secondary glucose, hypoglycaemia, adverse event, laboratory and vital-sign outcomes, but comparative results are not reported for all listed outcomes. Serious adverse event counts were low in the posted groups; deaths are not reported in the registry record. The original sample-size justification, detailed analysis plan and multiplicity approach are not reported.