Insulin Glargine Versus Twice-Daily NPH: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Insulin Glargine Versus Twice-Daily NPH (NCT00687453), a randomized phase 4 study. The primary outcome is Hemoglobin A1c Change From Baseline.

2. Clinical Question

The question is clinically framed around glucose control, but the statistical target is specific: a difference between group means in change in percent glycated hemoglobin. The registry also lists glucose readings, hypoglycemic reactions, body mass index, insulin dose, and adverse events as secondary outcomes. The available numerical secondary results cover only some of those measures, so the primary comparison remains the clearest basis for describing the trial’s posted results.

3. Trial Design

The registry classifies this as a phase 4, randomized, parallel-group trial with no masking. Charles Drew University of Medicine and Science is listed as sponsor. The record reports enrollment of 27 and a status of terminated. The recorded study start is 2003-02, and primary completion is recorded as 2009-08. The reason for termination is not reported in the registry record.

The two assigned regimens were bedtime insulin glargine and twice-daily NPH. The population described in the brief summary was ethnic minority patients with type 2 diabetes inadequately treated with once-nightly NPH insulin alone. The official title further describes participants as receiving combination insulin–oral agent therapy. The registry’s primary outcome population is labeled ITT (LOCF); details of how that population was handled are limited to that label.

The primary endpoint was hemoglobin A1c change from baseline to 6 months. The posted summaries report a mean and standard deviation for each group. The outcome counts are 11 for insulin glargine and 13 for twice-daily NPH. Those counts describe the reported primary outcome summaries and should not be used to infer why they differ from the enrollment figure.

The original sample-size justification, allocation concealment procedures, detailed protocol, and reason for termination are not reported in the registry record. The registry record also does not report the trial’s original statistical analysis plan or whether interim analyses were planned or conducted. These omissions limit what can be concluded about the intended design and analysis decisions.

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: Baseline run-in period to document baseline control and reinforce dietary/lifestyle principles. 3 subjects not randomized due to protocol violations.

Overall Study

Analysis population for the primary outcome, as defined in the registry: ITT (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 Hemoglobin A1c Change From Baseline, measured over Baseline to 6 months.

Hemoglobin A1c is a measure of glycated hemoglobin, as percent glycated hemoglobin. The primary endpoint is the mean change from baseline to 6 months. A change score expresses how the measured value at follow-up differs from its baseline value; the group mean summarizes those changes for participants included in the reported outcome analysis.

Hemoglobin A1c is commonly used in diabetes research as a measure of longer-term glucose exposure. In general, it complements readings taken at individual times by reflecting glucose exposure over a longer period. The registry’s choice of this endpoint therefore gives the comparison a measure of overall glycemic status rather than relying solely on a particular self-monitored reading. This is general context about the measure, not an additional finding from this trial.

The posted results report mean changes of -0.8 for insulin glargine and -1.0 for twice-daily NPH, with standard deviations of 0.9 and 1.2, respectively. The comparison is expressed as NPH minus insulin glargine, giving a mean difference of -0.2. The endpoint population is labeled ITT (LOCF). The registry record does not report further detail about the handling of missing outcome measurements beyond that label, nor does it give a fuller definition of the endpoint beyond its stated measure and timeframe.

7. Results Posted in the Registry

• NPH Twice-daily: mean -1.00 versus -0.80 on control; difference -0.20 (95% CI -1.04 to 0.64), standardized effect d = -0.19; z-test p = 0.641.

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.

Frequency of Pre-supper Glucose Readings 130 mg/dL or Less, Change From Baseline

• 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:
  • NPH Twice-daily: mean 7.50 versus 38.00 on control; difference -30.50 (95% CI -52.12 to -8.88), standardized effect d = -1.16; z-test p = 0.006.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for NPH Twice-daily than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Body Mass Index Change From Baseline

• 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:
  • NPH Insulin Injected Twice-daily: mean 0.30 versus 0.20 on control; difference 0.10 (95% CI -0.78 to 0.98), standardized effect d = 0.09; z-test p = 0.824.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between NPH Insulin Injected Twice-daily and the control. The interval gives the range of effects that remain compatible with the data.

Total Daily Insulin Dose

• 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:
  • NPH Twice-daily: mean 20.50 versus -0.10 on control; difference 20.60 (95% CI 10.56 to 30.64), standardized effect d = 1.70; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for NPH Twice-daily than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry lists six secondary outcomes, including pre-supper glucose readings, hypoglycemic reactions, body mass index, daily insulin dose, and adverse events. Numerical group summaries and recalculated comparisons are available in the posted results for the pre-supper glucose-reading measure, body mass index, and daily insulin dose. Numerical results for the other listed secondary outcomes are not reported in the registry record addressed by these summaries.

Across the available numerical results, the findings do not form a single uniform pattern. The glucose-reading and daily insulin dose comparisons have unadjusted intervals that do not include zero, while the body mass index contrast is small and its interval includes zero. These secondary findings add context about outcomes other than the primary hemoglobin A1c measure, but they do not replace or resolve the uncertainty in the primary comparison.

The primary endpoint and secondary outcomes measure different aspects of the trial. A difference in a glucose-reading summary or insulin dose does not, by itself, establish a corresponding difference in hemoglobin A1c. Nor do the secondary results establish the cause of any observed pattern. Outcomes can be related, but their relationship must be evaluated rather than assumed.

These secondary comparisons carry less weight because they are unadjusted recalculations, the registry record does not report a multiplicity strategy, and the full analysis plan is not reported. When multiple outcomes are assessed, some may appear notable by chance. The secondary findings are therefore best treated as exploratory descriptions that may motivate further study, not as confirmatory conclusions. The absence of numerical results for some listed measures also prevents a complete assessment of the overall secondary-outcome pattern.

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

• Frequency of Pre-supper Glucose Readings 130 mg/dL or Less, Change From Baseline
• Frequency of Total Hypoglycemic Reactions
• Frequency of Severe Hypoglycemic Reactions
• Body Mass Index Change From Baseline
• Total Daily Insulin Dose
• Any Adverse Event Other Than Hypoglycemia

9. Statistical Interpretation

10. Statistical Methods Explained

The posted primary comparison is an unadjusted recalculation from the group means, standard deviations, and outcome counts. It contrasts the mean change in the NPH group with the mean change in the insulin glargine group. The comparison estimate is -0.2, with an unadjusted p-value of 0.641. The registry record does not report a sponsor analysis for this primary comparison, and there is no discrepancy flag in the record.

What does a mean difference represent?

A mean difference expresses the separation between the two group averages on the endpoint’s original scale. Here, the comparison direction is NPH minus insulin glargine. Its sign therefore depends on that ordering: a negative estimate means the NPH group’s reported mean change is lower than the insulin glargine group’s reported mean change. The estimate is a summary of the observed group results, not a statement about every participant.

The posted group means are -0.8 for insulin glargine and -1.0 for NPH. The corresponding standard deviations are 0.9 and 1.2. In general, a standard deviation describes variation among participant-level observations around a group mean. It is not the uncertainty interval for the mean difference. The standard error, confidence interval, and p-value address uncertainty in the estimated comparison rather than the spread of individual observations.

How should the p-value be read?

The primary unadjusted recalculated p-value is 0.641. In general, a p-value is calculated under a null hypothesis and a statistical model, and indicates how unusual results at least as discrepant as those observed would be under that model. It is not the chance that the null hypothesis is correct, nor does it quantify the clinical importance of the observed difference. The registry record does not report the original analysis plan, so this unadjusted recalculation should not be mistaken for a documented sponsor analysis.

The p-value should be considered alongside the effect estimate and its confidence interval. A large p-value can reflect a small estimated difference, substantial variability, limited information, or a combination of these. It does not establish equivalence. Demonstrating equivalence would require an appropriate design and a prespecified margin, neither of which is reported in the registry record.

What does a confidence interval add?

In general, a confidence interval gives a range of values compatible with the data and the method used to calculate it. Its width communicates precision: a wider interval indicates less precise estimation. For the primary comparison, the recalculated interval includes values on both sides of zero. The posted result therefore does not tightly identify the direction or magnitude of the contrast. Confidence intervals do not guarantee that the true value lies inside a particular calculated interval, and they do not account for biases that may arise from study conduct or analysis choices.

What does randomization contribute?

Random assignment is intended to make the assigned groups comparable in expectation, reducing systematic differences in baseline characteristics as an explanation for outcome contrasts. It does not guarantee balance in a particular trial, especially when the number of participants is limited. The registry identifies the allocation as randomized, but details of sequence generation and allocation concealment are not reported in the registry record. Masking is listed as none. Lack of masking can matter for outcomes influenced by expectations or behavior, although the primary endpoint is a laboratory measure.

The primary outcome population is labeled ITT (LOCF). In general, intention-to-treat analysis aims to preserve participants in their assigned groups, while last observation carried forward is one approach to filling in missing follow-up values using an earlier measurement. The registry record does not report enough detail to determine exactly how the label was implemented, how much data were missing, or what assumptions were used for missingness. Carrying earlier observations forward can affect estimated changes if later values would have differed from those earlier values.

Why do secondary tests need caution?

The registry lists six secondary outcome measures. In general, testing many outcomes increases the chance that one or more results will appear unusual even when there is no underlying effect. A multiplicity procedure can account for that issue, but no adjustment is reported in the registry record. The available secondary p-values are unadjusted recalculations, not reported analyses. They should therefore be read as exploratory, especially because the registry record does not report a full analysis plan or a prespecified hierarchy among outcomes.

The registry record does not report interim analyses, model covariates, or a formal statistical plan. The simple recalculations use posted summary statistics and do not substitute for an individual-participant analysis. They cannot adjust for baseline factors, assess distributional assumptions directly, or reproduce undocumented decisions about missing data. Their purpose is to describe the posted group summaries and their approximate uncertainty, not to reconstruct unreported analyses.

11. Confidence Intervals and Precision

The primary mean difference is -0.2, defined as the NPH mean change minus the insulin glargine mean change. The recalculated confidence interval includes both negative and positive values. In practical statistical terms, the data are compatible with a contrast in either direction under the calculation used, so the point estimate alone should not be treated as a precise estimate of the between-group difference. The unadjusted p-value is 0.641, which is consistent with substantial uncertainty about the contrast.

In general, a confidence interval communicates precision as well as direction. A narrow interval would constrain the range of values compatible with the data more closely; a broad interval leaves more plausible values. The primary comparison’s interval crosses zero and does not establish a clear direction. It also does not prove that the groups are equivalent, because equivalence requires a predefined range of differences that would count as practically similar. Such a margin is not reported in the registry record.

For the glucose-reading secondary measure, the recalculated mean difference is -30.5, with a confidence interval from -52.12 to -8.882. For daily insulin dose, the recalculated difference is 20.6, with an interval from 10.56 to 30.64. These intervals do not include zero under the stated calculations, but they are unadjusted secondary comparisons and should be interpreted cautiously. The body mass index comparison is 0.1, and its recalculated interval includes zero.

These intervals are recalculations from summary statistics, not sponsor-reported intervals. They reflect sampling uncertainty under the calculation used, but do not capture uncertainty about missing-data assumptions, unreported design decisions, or possible bias. The small outcome counts also limit precision. A confidence interval is not a guarantee about the true value, and its interpretation depends on the validity of the underlying model and data.

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 derived from the observed effect, not the trial’s original design assumptions. For these continuous outcomes, the figures are participants per arm, not total events. The listed planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set at the stated fraction of the observed effect. The trial’s own original sample-size assumptions are not reported in the registry record.

The 80% power column gives the planned participants per arm for a design with an 80% chance of detecting the specified effect under those assumptions, if that effect is real and the model assumptions hold. The 90% power column describes the corresponding planning target for a higher chance of detection. These are design calculations, not guarantees about the result of a future study. The figures are not observed power.

For the primary endpoint, planning for 100% of the observed effect gives 453 participants per arm for 80% power and 607 participants per arm for 90% power. Planning for 75% of the observed effect gives 805 and 1,078 participants per arm, respectively; planning for 50% gives 1,811 and 2,425. The pattern illustrates a general property of power calculations: smaller effects are harder to detect, so detecting them with the same target power requires more participants.

These numbers depend strongly on treating the observed effect as a useful estimate for planning. A small trial can produce an unstable effect estimate, so planning from that estimate alone may not reflect the effect a future study should target. The registry record does not report an original sample-size rationale, and these illustrations should not be read as evidence that the study was adequately or inadequately powered.

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 = -0.200; pooled standard deviation σ = 1.074.
2. n = 2 × (1.96 + 0.842)² × 1.074² / -0.200² = 452.7, rounded up to 453 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 <- -0.2                      # observed difference in means
sigma <- 1.07407465459174                     # 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(687453)
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 = 453 (80% power), 607 (90% power)
 75% of observed effect: n per arm = 805 (80% power), 1,078 (90% power)
 50% of observed effect: n per arm = 1,811 (80% power), 2,425 (90% power)
power.t.test: 453.7 
Simulated power at n = 453 per arm: 0.805 (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 registry record lists a primary endpoint and six secondary outcome measures, but does not report a multiplicity adjustment or a hierarchy for interpreting the secondary outcomes. Multiplicity matters because repeated testing creates more opportunities for a result to appear notable by chance. In general, analysts can address this through prespecified testing procedures, but whether such procedures were planned or used is not reported in the registry record. The available secondary comparisons are unadjusted recalculations and should not be treated as confirmatory tests.

The primary outcome population is labeled ITT (LOCF). This label indicates an intention-to-treat population with a last-observation-carried-forward approach, but the registry record does not report detailed rules for inclusion, timing, or imputation. The number of participants with missing observations, the reasons for missingness, and sensitivity analyses under alternative assumptions are not reported in the registry record. These details matter because the result can depend on how missing follow-up measurements are handled.

The registry record does not report a full statistical analysis plan, interim analyses, allocation concealment details, or the original sample-size justification. It also does not provide individual participant data in the posted summaries. Consequently, the recalculated comparisons cannot verify the original analysis choices, adjust for prognostic factors, or test assumptions using participant-level distributions.

These absences do not demonstrate that a procedure was not performed; they mean that it is not reported in the registry record. They limit the ability to assess whether the analyses were prespecified, how missing outcomes were addressed, and how the family of outcomes was interpreted. The group summaries remain useful descriptions, but conclusions should reflect these reporting limits.

15. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 1% reporting threshold.

Most frequent non-serious adverse event terms

The registry reports zero serious adverse events among 11 participants at risk in the insulin glargine group and zero among 13 at risk in the twice-daily NPH group. It also reports zero deaths in each group. These are observed counts in the registry record; they do not establish that serious events or deaths cannot occur, or that the regimens have identical safety profiles.

For adverse events other than hypoglycemia, the registry reports 8 affected participants among 11 at risk in the insulin glargine group and 5 among 13 at risk in the NPH group. The record does not provide the event terms in the summaries addressed here, nor does it give enough detail to assess severity, timing, or causal attribution for these events. The registry lists hypoglycemic reactions as a secondary outcome, but numerical results for total or severe hypoglycemic reactions are not reported in the registry record addressed by these summaries.

These figures are counts, not comparative risk estimates. No percentages or ratios are calculated. With limited outcome counts, the absence of a recorded serious event should be interpreted as no serious events reported in these groups, rather than proof of no risk.

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

The primary result describes the average hemoglobin A1c change recorded for each assigned group from baseline to 6 months. The group means were -0.8 for insulin glargine and -1.0 for twice-daily NPH, and the posted comparison was -0.2 for NPH minus insulin glargine. The recalculated interval includes zero, and the unadjusted p-value is 0.641. These findings do not provide a precise estimate of the difference between the regimens.

The result does not establish that the treatments are equivalent, that one is superior, or that either should be selected for an individual. It is a summary of a particular randomized trial, with the population and regimens described in the registry record. The outcome counts are limited, and the registry record does not provide enough information to evaluate all analysis decisions or the reasons the trial was terminated.

The secondary outcomes provide additional, but incomplete, context. The available summaries include differences in glucose-reading and daily insulin dose measures, while body mass index shows a small estimated contrast with an interval including zero. These are exploratory unadjusted comparisons and do not overturn the uncertainty around the primary endpoint. Numerical results for all listed secondary measures are not reported in the registry record addressed by these summaries.

General interpretation of a randomized trial also depends on conduct, adherence, outcome measurement, and missing data. Randomization can reduce systematic confounding, but it does not eliminate uncertainty, guarantee balance in a limited sample, or address all sources of bias. The no-masking design and limited reporting of allocation and missing-data procedures are relevant when judging how confidently the results can be generalized.

The most defensible conclusion is descriptive: both groups had negative mean changes in the primary measure, and the estimated difference between those changes is uncertain. The record supports neither a claim of no difference nor a firm claim of a meaningful difference. Further interpretation would require details not reported in the registry record, along with evidence from additional appropriately designed research.

17. Why This Trial Matters Statistically

This trial illustrates why a point estimate, a p-value, and a confidence interval answer related but distinct questions. The primary point estimate is small in the reported comparison scale, but the recalculated interval crosses zero and the unadjusted p-value is 0.641. Reading these together prevents a non-significant test from being mistaken for evidence of equivalence, while also avoiding overstatement of the observed contrast.

The study also shows how a registry record can support transparent descriptive analysis while leaving important uncertainties. The endpoint means, standard deviations, and outcome counts permit unadjusted recalculations, but the original statistical plan, sample-size rationale, interim analyses, and missing-data details are not reported. Distinguishing posted analyses from recalculations makes clear which results were reported by the registry and which are derived from its summaries.

The range of secondary outcomes highlights the importance of multiplicity and outcome hierarchy. Several clinically different measures are listed, but a multiplicity strategy is not reported. Unadjusted secondary findings can be useful for generating questions, yet they should carry less evidential weight than a prespecified primary analysis. The limited numerical coverage of listed secondary outcomes further emphasizes the value of complete outcome reporting.

Finally, this record demonstrates the difference between observed trial results and planning illustrations. Sample-size figures based on the observed effect can illustrate how power calculations respond to assumptions, but they do not reveal the study’s original planning or its observed power. Keeping those concepts separate helps avoid claims that the registry record cannot support.

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.

Several limitations specific to this trial affect interpretation. The registry reports enrollment of 27, while the primary outcome summaries list 11 participants for insulin glargine and 13 for NPH. The registry record does not explain this difference, so it cannot be attributed to missing follow-up, exclusions, or any other cause based on the available information.

The study is recorded as terminated, but the reason for termination is not reported in the registry record. It is not possible to determine whether termination was related to recruitment, administration, outcomes, safety, funding, or another issue. The record also does not report the original sample-size justification, so the trial’s intended precision and detectable effect cannot be assessed from its planning rationale.

The primary outcome is labeled ITT (LOCF), but the registry record does not describe the amount or pattern of missing data, the detailed imputation rules, or sensitivity analyses. The absence of masking is recorded, while allocation concealment procedures and other protections against bias are not reported. These reporting limitations constrain assessment of both the analysis and trial conduct.

The primary endpoint covers baseline to 6 months, so the posted result addresses that follow-up period only. Longer-term outcome information is not reported in the registry record. The secondary outcomes are also incompletely represented in the numerical summaries available for interpretation: results for hypoglycemic reactions and some other listed measures are not reported. Unadjusted recalculations do not substitute for a prespecified analysis plan or participant-level analysis.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Insulin Glargine Versus Twice-Daily NPH — NCT00687453.
• Registry record last updated 2023-11-02; status last verified 2023-10.
• Results first posted 2010-10-07.
• 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

The registry describes a phase 4 randomized, parallel-group trial comparing bedtime insulin glargine with twice-daily NPH in ethnic minority patients with type 2 diabetes inadequately treated with once-nightly NPH alone. The trial is recorded as terminated, with enrollment of 27 and no masking.

The primary endpoint was mean hemoglobin A1c change from baseline to 6 months in a population labeled ITT (LOCF). Mean changes were -0.8 for insulin glargine and -1.0 for NPH; the unadjusted recalculated mean difference, NPH minus insulin glargine, was -0.2, with p = 0.641. The recalculated interval includes zero, leaving the primary contrast uncertain.

The registry lists six secondary measures, but numerical summaries addressed in these results cover only some of them. It reports zero serious adverse events and zero deaths in both groups. The reason for termination, original sample-size justification, detailed missing-data methods, and full analysis plan are not reported in the registry record.