Study of Alogliptin Combined With Pioglitazone in Subjects With Type 2 Diabetes Mellitus: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study of Alogliptin Combined With Pioglitazone in Subjects With Type 2 Diabetes Mellitus (NCT00286494), a randomized phase 3 study. The primary outcome is Change From Baseline in Glycosylated Hemoglobin (HbA1c) at Week 26..

2. Clinical Question

In practical statistical terms, this is a comparison of three parallel groups, with two active-treatment groups sharing a placebo comparator. The primary question is not whether every participant’s HbA1c changed by the same amount. It is whether the average change, as estimated and analysed in the posted results, differed between each alogliptin group and the placebo group.

The outcome is a laboratory measure, and the endpoint concerns its change from baseline through the Week 26 assessment. The registry describes the analysis population and says missing measurements were imputed using last observation carried forward. The posted results therefore reflect that stated analysis approach, rather than a comparison restricted only to participants with complete observed measurements. The record does not report the full protocol or all details needed to reconstruct the analysis independently.

3. Trial Design

This was a Phase 3, randomized, parallel-group study sponsored by Takeda. The registry describes it as multicenter, double-blind, placebo-controlled, and quadruple-masked. Enrollment was 493. The study is listed as completed, with a start date of 2006-02 and primary completion in 2007-08.

The three groups were placebo, alogliptin 12.5 mg once daily, and alogliptin 25 mg once daily. Each group also received pioglitazone, according to the study title and intervention descriptions. The pioglitazone dose and further details of background treatment are not reported in the registry record. The arm descriptions themselves contain no additional treatment details.

Random allocation and a parallel-group structure support comparison of outcomes across separately assigned groups. Masking is intended to reduce the influence of treatment knowledge on participant experience, clinical care, and outcome assessment. The registry gives the masking classification but does not explain which study roles were masked or how masking was maintained.

The primary endpoint was change from baseline in HbA1c at Week 26. The registry reports a full-analysis-set description: randomized participants who received at least one dose of study drug and had measurements at baseline and at the relevant visit. Missing data were imputed using last observation carried forward. The reported primary comparison method was ANCOVA.

The registry lists 51 outcome measures and 102 analyses, and 50 secondary outcomes are posted. These counts indicate that the record contains multiple results beyond the primary endpoint, but they do not establish how the analyses were prioritized or adjusted. The trial’s original sample-size justification, detailed allocation procedures, prespecified analysis plan, and interim-analysis plan are not reported in the registry record. The results should therefore be read as the posted record describes them, without assuming unlisted design or 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: Participants with a historical diagnosis of type 2 diabetes mellitus were enrolled in one of 3, once-daily (QD) treatment groups.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Randomized participants who received at least one dose of study drug (Full Analysis Set), and who had measurements at baseline and at the visit. Missing data are 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 From Baseline in Glycosylated Hemoglobin (HbA1c) at Week 26., measured over Baseline and Week 26..

The primary endpoint is change from baseline in glycosylated hemoglobin, or HbA1c, at Week 26. HbA1c represents glucose bound to hemoglobin, expressed in the registry’s stated unit as a percentage of glycosylated hemoglobin. The endpoint compares the value at the Week 26 or final visit with the baseline value.

Change from baseline is used to describe how an outcome differs from each participant’s starting measurement over the study period. Comparing changes between randomized groups can help distinguish changes observed in the active-treatment groups from changes observed in the placebo group. It is a group-level comparison; it does not mean every participant experienced the group average change.

The registry reports least-squares means for the arm-level endpoint summaries, with standard errors as the measure of dispersion. Its description says the primary analysis population included randomized participants who received at least one dose and had measurements at baseline and the visit. Missing data were imputed using last observation carried forward. These details matter because the reported summaries depend on the analysis population and missing-data approach.

HbA1c is the primary endpoint named in this study, while fasting plasma glucose and additional HbA1c time points appear among the secondary outcomes. Choosing a primary endpoint gives the central comparison a defined focus; the secondary outcomes add context but should not automatically be treated as equally definitive. The biological or clinical interpretation of a change is not established by the statistical summaries alone.

7. Results Posted in the Registry

• Alogliptin 12.5 mg QD: mean -0.66 versus -0.19 on control; difference -0.47 (95% CI -0.66 to -0.28), standardized effect d = -0.60; z-test p = <0.001.
• Alogliptin 25 mg QD: mean -0.80 versus -0.19 on control; difference -0.61 (95% CI -0.80 to -0.42), standardized effect d = -0.78; z-test p = <0.001.

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.

Change From Baseline in Glycosylated Hemoglobin (Week 4).

• 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:
  • Alogliptin 12.5 mg QD: mean -0.40 versus -0.14 on control; difference -0.26 (95% CI -0.36 to -0.16), standardized effect d = -0.66; z-test p = <0.001.
  • Alogliptin 25 mg QD: mean -0.45 versus -0.14 on control; difference -0.31 (95% CI -0.41 to -0.21), standardized effect d = -0.78; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alogliptin 12.5 mg QD than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alogliptin 25 mg QD than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in Glycosylated Hemoglobin (Week 8).

• 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:
  • Alogliptin 12.5 mg QD: mean -0.60 versus -0.18 on control; difference -0.42 (95% CI -0.57 to -0.27), standardized effect d = -0.71; z-test p = <0.001.
  • Alogliptin 25 mg QD: mean -0.73 versus -0.18 on control; difference -0.55 (95% CI -0.70 to -0.40), standardized effect d = -0.93; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alogliptin 12.5 mg QD than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alogliptin 25 mg QD than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in Glycosylated Hemoglobin (Week 12).

• 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:
  • Alogliptin 12.5 mg QD: mean -0.70 versus -0.23 on control; difference -0.47 (95% CI -0.63 to -0.31), standardized effect d = -0.70; z-test p = <0.001.
  • Alogliptin 25 mg QD: mean -0.82 versus -0.23 on control; difference -0.59 (95% CI -0.75 to -0.43), standardized effect d = -0.88; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alogliptin 12.5 mg QD than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Alogliptin 25 mg QD than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry lists multiple secondary outcomes, including additional HbA1c assessments and fasting plasma glucose measurements. Fifty secondary outcomes are posted. The displayed secondary HbA1c results at earlier visits show a pattern consistent in direction with the primary Week 26 comparisons: both alogliptin groups have more negative estimated changes than placebo in the posted comparisons. This broad consistency gives context to the primary finding without replacing it.

Secondary endpoints can help show whether a result appears across related assessments and can describe the time course represented in the record. They may also provide information about measures other than the primary endpoint. However, the presence of many outcomes means there are many opportunities to observe apparently notable results by chance. A result from an individual secondary comparison should therefore carry less weight than a prespecified primary comparison unless the analysis plan and multiplicity approach support stronger claims.

The registry reports p-values for the listed secondary ANCOVA comparisons, but a p-value considered on its own does not account for the number of outcomes examined. The record does not report whether a formal multiplicity adjustment was used or how the secondary analyses were prioritized. Without that information, the secondary results are best read as supportive or exploratory descriptions rather than as independent confirmation of a primary conclusion.

The secondary results are not a substitute for the primary endpoint, and their consistency does not establish that the same pattern applies to all outcomes or to every participant. The registry names further HbA1c and fasting plasma glucose time points, but the posted summary should be interpreted according to the specific outcomes and analyses displayed. Avoid treating the collection of secondary comparisons as a single confirmatory test.

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

• Change From Baseline in Glycosylated Hemoglobin (Week 4).
• Change From Baseline in Glycosylated Hemoglobin (Week 8).
• Change From Baseline in Glycosylated Hemoglobin (Week 12).
• Change From Baseline in Glycosylated Hemoglobin (Week 16).
• Change From Baseline in Glycosylated Hemoglobin (Week 20).
• Change From Baseline in Fasting Plasma Glucose (Week 1).
• Change From Baseline in Fasting Plasma Glucose (Week 2).
• Change From Baseline in Fasting Plasma Glucose (Week 4).

9. Statistical Interpretation

10. Statistical Methods Explained

What does ANCOVA contribute?

The registry identifies ANCOVA as the method for the reported primary comparisons. In general, analysis of covariance compares group outcomes while accounting for one or more covariates in the model. For a change-from-baseline endpoint, a model can use baseline information to refine the comparison of follow-up outcomes. This can improve precision when baseline measurements are related to later measurements. The registry record does not report the full model specification, the covariates used, or the details of model checking, so those features cannot be reconstructed from the posted summary alone.

The reported ANCOVA estimates are mean differences for final values, as the registry labels them. The posted primary endpoint is described as change from baseline at Week 26. These descriptions are not identical labels, so readers should use the registry’s stated analysis outputs rather than assume a more detailed model interpretation than the record supports.

What do the arm summaries represent?

The arm summaries are least-squares means, not simple raw averages as such. A least-squares mean is a model-based group estimate. The registry reports a standard error alongside each arm estimate. A standard error describes the uncertainty in an estimated mean; it is not the spread of individual participant measurements. The participant counts and standard errors help readers understand how much information contributes to each estimate, but they do not reveal the full outcome distribution.

The primary analysis population is described as randomized participants who received at least one dose of study drug and had measurements at baseline and at the relevant visit. This is the registry’s stated full analysis set definition. The record also says missing values were imputed using last observation carried forward. In general, this method carries a participant’s last recorded value forward to a later assessment when a subsequent value is missing. It makes an assumption about the unobserved later value and can affect estimates if that assumption is not reasonable. The registry does not report sensitivity analyses that would show how results change under other missing-data assumptions.

How should the recalculations be understood?

The accompanying recalculated comparisons are simple, unadjusted re-calculations from posted arm-level summary statistics. They use approximate standard deviations derived from the reported standard errors and sample sizes, rather than reproducing the ANCOVA model. This makes them useful as a transparent cross-check of the direction and approximate scale of the comparisons, but they are not the trial’s own adjusted analysis. Their intervals and p-values can differ from the registry’s ANCOVA results because the methods and information used are not identical.

The posted results do not flag a discrepancy between the reported analysis and the re-calculation. Even so, the sponsor’s own analysis is the appropriate result to foreground when describing what the trial reported. The re-calculation should be treated as supplementary, not as a correction or substitute.

What does a p-value say?

In general, a p-value describes how incompatible the observed data are with a specified null model, assuming that model and the analysis assumptions are appropriate. A small p-value is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. Here, the registry reports p < 0.001 for each primary ANCOVA comparison. That notation indicates the reported p-values fall below the displayed threshold; it does not provide their exact values.

Statistical significance also does not eliminate uncertainty about the estimate. The confidence intervals remain important because they show a range of plausible values under the fitted analysis. Nor do the p-values address whether the outcome is clinically meaningful, whether results generalize beyond the study, or how missing data and multiple comparisons influence the overall evidence.

Why do the planning illustrations use effect fractions?

The sample-size section uses the observed effect as a reference and illustrates planning for the full observed effect and smaller fractions of it. These are planning scenarios, not descriptions of the trial’s original design. In general, detecting a smaller difference against the same level of variability requires more information, which is why the illustrations increase the participant requirement as the assumed effect becomes smaller. Their assumptions are stated in the sample-size section. The trial’s original sample-size calculation and design assumptions are not reported in the registry record.

Over-dispersion is a general concern when a model assumes less variability than the data contain: uncertainty can then be understated, and tests may appear more decisive than warranted. The posted endpoint is continuous, and the registry gives standard errors, but the record does not report a separate assessment of over-dispersion. This general concept should not be read as evidence that over-dispersion occurred in this trial.

11. Confidence Intervals and Precision

The primary confidence intervals are 95% intervals around the sponsor-reported ANCOVA mean differences. For alogliptin 12.5 mg QD versus placebo, the estimated mean difference is -0.47, with a 95% confidence interval from -0.67 to -0.28. For alogliptin 25 mg QD versus placebo, the estimate is -0.61, with a 95% confidence interval from -0.80 to -0.41.

In general, a confidence interval describes the uncertainty around an estimated effect under the specified model and assumptions. A narrower interval indicates greater precision than a wider interval, while the interval’s location indicates which values are compatible with the estimate under that analysis. These intervals exclude zero, consistent with the reported p-values of <0.001. The intervals do not show the range of outcomes among individual participants, nor do they guarantee that the true effect lies within the displayed limits.

Precision is distinct from importance. A precisely estimated difference can still require clinical context to judge its relevance, and the registry does not report a threshold for a clinically important HbA1c difference. The intervals also do not automatically incorporate uncertainty about the analysis choices, missing-data assumptions, or multiple comparisons.

The recalculated intervals are based on unadjusted summary-statistic calculations, whereas the registry’s intervals come from ANCOVA. They should therefore not be treated as interchangeable. When describing the primary trial findings, the sponsor’s reported intervals are the relevant ones. The displayed arm-level standard errors provide additional information about estimated means, but they are not confidence intervals themselves.

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 table and curve are planning illustrations based on the observed effect, not the trial’s original design calculation. 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, and a normal approximation. Each scenario uses the stated fraction of the observed effect as the effect to detect.

The 80% power column describes the participant count per arm estimated to give an 80% chance of detecting the assumed effect under those planning assumptions, if that effect and the model assumptions are correct. The 90% power column describes the corresponding count for a 90% chance. These are prospective planning probabilities under assumptions; they do not mean that the study had an 80% or 90% probability of success after its results were observed.

The rows illustrate planning for the observed effect and for smaller fractions of that effect. Smaller effects are harder to distinguish from random variation, so the planning requirement rises as the target effect gets smaller. The table is a guide to how assumptions about effect size influence sample-size planning, not evidence about the trial’s actual recruitment rationale or the power achieved in the completed study.

The original sample-size justification and the trial’s own design assumptions are not reported in the registry record. These figures are not observed power.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.470; pooled standard deviation σ = 0.786.
2. n = 2 × (1.96 + 0.842)² × 0.786² / -0.470² = 43.9, rounded up to 44 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 <- -0.47                      # observed difference in means
sigma <- 0.785789995453631                     # 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(286494)
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 = 44 (80% power), 59 (90% power)
 75% of observed effect: n per arm = 79 (80% power), 105 (90% power)
 50% of observed effect: n per arm = 176 (80% power), 235 (90% power)
power.t.test: 44.9 
Simulated power at n = 44 per arm: 0.791 (20000 replicates)

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

14. Analyses Reported by the Sponsor

The registry’s own primary comparisons use ANCOVA and report mean differences of -0.47 for alogliptin 12.5 mg QD versus placebo and -0.61 for alogliptin 25 mg QD versus placebo. Both reported p-values are <0.001, and the record gives a 95% confidence interval for each comparison.

The page also presents simple unadjusted re-calculations from posted summary statistics. Those calculations are a cross-check, not a reconstruction of the sponsor’s ANCOVA model. The methods differ: the registry analysis is model-based, while the re-calculation uses the summary estimates and approximate variability available in the posted data. Similarity between estimates can support a basic consistency check, but it does not make the approaches equivalent.

The record does not flag a discrepancy between the sponsor’s analysis and the re-calculation. The sponsor’s reported analysis should therefore remain the main basis for describing the study’s primary result. The re-calculation can help readers understand the scale and direction of the comparison, while its simplified assumptions limit how much weight it should carry.

Neither analysis resolves questions that are not addressed in the record, including the full model specification, multiplicity procedures, or sensitivity to alternative missing-data assumptions. Those matters require information beyond the posted numerical summaries.

15. Multiplicity, Missing Data and Analysis Populations

The registry record lists 51 outcome measures, 102 analyses, and 50 posted secondary outcomes. This is a substantial collection of results to interpret alongside the primary endpoint. When many hypotheses are tested, the chance of at least one apparently striking result arising by chance can increase. In general, multiplicity procedures control that risk by adjusting thresholds, organizing tests into a hierarchy, or applying another prespecified strategy.

The registry record does not report whether the primary or secondary analyses used a multiplicity adjustment, which outcomes were included in any adjustment, or whether testing followed a prespecified hierarchy. It also does not report the complete statistical analysis plan. The displayed p-values should therefore be read as the reported values for individual comparisons, not assumed to control the overall false-positive risk across all analyses.

The primary endpoint has a distinct role in the study record, and its reported ANCOVA comparisons are the central results. The secondary findings add context, but their evidential weight is harder to assess without the trial’s full analysis plan and multiplicity details. The registry’s listing of outcomes alone does not establish which tests were confirmatory.

The primary analysis population is described as randomized participants who received at least one dose and had measurements at baseline and at the visit. Missing values were imputed using last observation carried forward. In general, imputation can affect uncertainty and estimates because missing values are not observed outcomes. Carrying the last observation forward assumes that the last recorded value is an appropriate substitute for the missing later value. The registry record does not report sensitivity analyses using other assumptions, the amount or pattern of missingness, or details sufficient to assess how robust results are to missing data.

Interim analyses, stopping rules, and the original sample-size justification are not reported in the registry record. Their absence from the posted record should not be taken as proof that such procedures did or did not occur. They remain unknown from this summary.

16. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 3% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: appendicitis (1.0%), hypokalemia (1.0%), basal cell carcinoma (1.0%), colon cancer (1.0%), calculus ureteric (1.0%).

The registry posts serious adverse event counts for each group, with the numbers at risk also shown. Serious adverse events were recorded for 4 of 97 participants in the placebo group, 5 of 198 in the alogliptin 12.5 mg QD group, and 13 of 199 in the alogliptin 25 mg QD group. These are counts of participants affected in the registry’s safety summary; they do not describe severity beyond the serious-event classification or establish that treatment caused an event.

The record also lists serious-event terms, including Appendicitis, Hypokalemia, Basal cell carcinoma, Colon cancer, Calculus ureteric, and Myocardial infarction, each shown as 1.0%. These terms should be read as the posted event listing, not as a complete safety profile or a comparison adjusted for exposure or other factors. The registry does not provide a causal assessment for these terms in the displayed summary.

The deaths field is not populated, so deaths are not reported in the registry record. Serious adverse event counts are distinct from the separate “other” adverse event counts and should not be combined. These summaries are descriptive; they do not by themselves establish comparative safety or support an individual treatment decision.

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

The posted primary results describe lower estimated HbA1c change values for each alogliptin group relative to placebo at Week 26, under the registry’s ANCOVA analysis. The reported 95% confidence intervals exclude zero, and the registry reports p < 0.001 for both comparisons. These statements summarize the statistical evidence in the posted primary analyses.

That interpretation is narrower than a claim about overall treatment benefit. The results do not establish how meaningful the observed differences are to patients, because the registry record does not report a threshold for clinical importance. Statistical significance is not the same as clinical importance, and the group estimates do not predict an individual participant’s outcome.

The comparisons are each against placebo. They do not constitute a direct statistical test of alogliptin 12.5 mg QD versus alogliptin 25 mg QD. The fact that the two estimated differences have different magnitudes does not, by itself, establish a difference between doses. The record also does not establish how these results compare with treatments not studied in this trial.

Interpretation is limited to the endpoint, study population, analysis method, and follow-up represented in the record. Missing measurements were handled using last observation carried forward, and the registry does not report sensitivity analyses that assess alternative assumptions. Multiplicity procedures are also not reported, which limits how confidently the collection of primary and secondary findings can be interpreted as a whole.

The study was described as randomized and masked, features intended to support fair comparisons and reduce bias. However, the registry’s brief summaries do not provide enough detail to evaluate every aspect of implementation, adherence, or conduct. The record also does not report all outcomes that might matter for a broader evaluation. The posted data therefore support a focused statistical description of HbA1c comparisons, not a complete judgment about efficacy, safety, or applicability.

18. Why This Trial Matters Statistically

This trial is statistically informative because it reports a randomized, parallel-group comparison with a defined primary endpoint and a placebo group shared by two active-treatment groups. The posted results include arm-level estimates, standard errors, ANCOVA comparisons, confidence intervals, and p-values. Together, these allow readers to examine both the estimated differences and their uncertainty, rather than relying only on a statement of statistical significance.

The comparison also illustrates why the analysis method matters. The registry reports an ANCOVA analysis, while the accompanying recalculations use unadjusted summary statistics. Their purposes differ: one describes the trial’s reported model-based comparison, and the other provides a simplified check based on posted summaries. Recognizing that distinction helps prevent a recalculation from being mistaken for the original analysis.

The results also show why confidence intervals and the analysis population belong in any interpretation. The estimated group differences are not exact quantities, and their precision depends on the observed data and model. The registry’s analysis population and last-observation-carried-forward approach are part of what the reported estimates mean.

Finally, the record demonstrates the limits of registry summaries. It presents many outcomes and analyses, but does not report multiplicity procedures, the full statistical analysis plan, or the original sample-size justification. Statistical reasoning therefore involves not only reading the reported estimates, but also identifying what information is missing and keeping conclusions within the scope of the posted record.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record does not report the full statistical analysis plan, the ANCOVA model specification, or the covariates used in the primary analysis. That limits independent reconstruction and makes it difficult to determine exactly how the reported model handled baseline values and other factors.

The record says missing values were imputed using last observation carried forward, but does not give the amount or pattern of missing data in the primary analysis or report sensitivity analyses under alternative assumptions. The primary population definition is stated, but the summary does not provide enough detail to assess the effect of exclusions or missing assessments on the comparison.

Multiplicity procedures are not reported despite the listing of many outcomes and analyses. The original sample-size justification, interim-analysis plan, and trial-specific design assumptions are also not reported in the registry record. The sample-size illustrations elsewhere on the page are not evidence of the study’s original planning rationale.

The record describes randomization and masking but does not explain how allocation was generated or concealed, who was masked, or how masking was maintained. The pioglitazone dose and further treatment details are not reported in the arm descriptions. The registry summary also does not supply a threshold for clinical importance or a direct statistical comparison between the two alogliptin doses.

Finally, the posted safety figures are descriptive and do not establish causation. Deaths are not reported in the registry record, and the safety summary alone cannot provide a complete assessment of risks. These limitations constrain the conclusions that can be drawn from the posted results without invalidating the specific comparisons that are reported.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study of Alogliptin Combined With Pioglitazone in Subjects With Type 2 Diabetes Mellitus — NCT00286494.
• Registry record last updated 2012-02-03; status last verified 2012-02.
• Results first posted 2011-09-27.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

The registry record describes a completed, Phase 3, randomized, quadruple-masked, parallel-group study sponsored by Takeda. It enrolled 493 participants and compared placebo with alogliptin 12.5 mg QD or 25 mg QD, each in combination with pioglitazone.

The primary endpoint was change from baseline in HbA1c at Week 26. The registry reports ANCOVA mean differences versus placebo of -0.47 and -0.61, with 95% confidence intervals of -0.67 to -0.28 and -0.80 to -0.41, respectively; both p-values are <0.001. The primary analysis used the stated full-analysis-set definition and last observation carried forward for missing data.

Multiple secondary results and adverse-event summaries are posted. The record does not report multiplicity procedures, the full analysis plan, or the original sample-size justification. Interpret the primary estimates as results for the specified endpoint and analysis, with the stated limitations.