Efficacy and Safety of Alogliptin Used in Combination With α-glucosidase Inhibitor in Participants With Type 2 Diabetes in Japan: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety of Alogliptin Used in Combination With α-glucosidase Inhibitor in Participants With Type 2 Diabetes in Japan (NCT01263483), a randomized phase 2, phase 3 study. The primary outcome is Change From Baseline in Glycosylated Hemoglobin (Week 12)..

2. Clinical Question

3. Trial Design

The registry describes a phase 2/3, randomized, double-blind, placebo-controlled, parallel-group, multicenter study in participants with type 2 diabetes in Japan. The listed masking level is quadruple. The sponsor was Takeda, and the record is marked completed. The recorded start is 2007-01 and primary completion is 2008-04.

Three registered groups are relevant to the primary comparison: voglibose 0.2 mg three times daily; alogliptin 12.5 mg once daily; and alogliptin 25 mg once daily with voglibose 0.2 mg three times daily. The trial summary describes the study as evaluating alogliptin combined with an α-glucosidase inhibitor. The primary outcome group entries identify the 12.5 mg arm by alogliptin dose, while the arm descriptions list that dose with voglibose.

The primary outcome was change from baseline in glycosylated hemoglobin at week 12 or the final visit. The primary analysis used last observation carried forward and the Full Analysis Set. The registry lists 17 outcome measures and 34 analyses; 16 secondary results are posted. The registry record does not report the original sample-size justification, the detailed randomization procedure, or the trial’s prespecified statistical analysis method. The design labels alone do not establish how allocation was generated or concealed.

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 with uncontrolled blood glucose despite diet and exercise therapies were enrolled in one of 3, once-daily (QD) or three-times daily (TID) treatment groups.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Analysis based on last observation carried forward, where the last postbaseline double-blind observed value is carried forward and used for all subsequent scheduled time points where data is missing. Values are from the Full Analysis Set.

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 (Week 12)., measured over Baseline and Week 12..

Glycosylated hemoglobin reflects glucose bound to hemoglobin. The registry defines the primary endpoint as the change in this measure from baseline to week 12 or the final visit, reported as a percentage of glycosylated hemoglobin. A change score describes how the measure differed from its baseline value, while the group mean summarizes those changes across participants included in the analysis.

This measure is used to assess glycemic status over time, so a comparison of mean changes can describe whether the groups’ average trajectories differed during the study period. The outcome description specifies collection at baseline and week 12 or final visit. For missing scheduled postbaseline measurements, the stated analysis carried forward the last observed double-blind value. This is an analysis rule, not a direct observation of the missing later measurement.

The endpoint is continuous, and the registry reports means and standard deviations for the groups. The mean difference compares the average change in an alogliptin group with the average change in the voglibose control group. It is not a comparison of individual responses, nor does a group average show how much responses varied between participants beyond what the reported dispersion conveys. The registry record does not report a patient-level threshold for a meaningful change or an interpretation linking a given change to a particular clinical outcome.

7. Results Posted in the Registry

• Alogliptin 12.5 mg QD: mean -0.96 versus 0.04 on control; difference -1.00 (95% CI -1.16 to -0.84), standardized effect d = -1.97; z-test p = <0.001.
• Alogliptin 25 mg QD and Voglibose 0.2 mg TID: mean -0.91 versus 0.04 on control; difference -0.95 (95% CI -1.10 to -0.80), standardized effect d = -2.01; 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 2).

• 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:
  • Alogliptin 12.5 mg QD: mean -0.19 versus -0.01 on control; difference -0.18 (95% CI -0.23 to -0.13), standardized effect d = -1.09; z-test p = <0.001.
  • Alogliptin 25 mg QD and Voglibose 0.2 mg TID: mean -0.21 versus -0.01 on control; difference -0.20 (95% CI -0.26 to -0.14), standardized effect d = -1.13; 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 and Voglibose 0.2 mg TID than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

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 deviations.
• Result:
  • Alogliptin 12.5 mg QD: mean -0.44 versus -0.02 on control; difference -0.42 (95% CI -0.51 to -0.33), standardized effect d = -1.56; z-test p = <0.001.
  • Alogliptin 25 mg QD and Voglibose 0.2 mg TID: mean -0.43 versus -0.02 on control; difference -0.41 (95% CI -0.50 to -0.32), standardized effect d = -1.45; 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 and Voglibose 0.2 mg TID 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 deviations.
• Result:
  • Alogliptin 12.5 mg QD: mean -0.74 versus -0.01 on control; difference -0.73 (95% CI -0.86 to -0.60), standardized effect d = -1.77; z-test p = <0.001.
  • Alogliptin 25 mg QD and Voglibose 0.2 mg TID: mean -0.75 versus -0.01 on control; difference -0.74 (95% CI -0.87 to -0.61), standardized effect d = -1.87; 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 and Voglibose 0.2 mg TID than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary glycosylated hemoglobin summaries at week 2, week 4, and week 8 follow the same broad direction as the primary endpoint: the mean changes in both alogliptin groups are more negative than the control group’s mean change. These earlier measurements provide context about the pattern across scheduled visits, rather than a separate basis for concluding that the primary finding is established.

The registry lists other secondary outcomes, including fasting plasma glucose at several visits and fasting C-peptide at week 2, but those results are not included among the secondary results described in the posted summaries. The registry reports 16 secondary results posted. The available secondary glycosylated hemoglobin results therefore cannot stand in for the complete set of planned outcomes or establish that all secondary outcomes followed the same pattern.

Repeated measurements within the same trial are related observations, not independent replications. In addition, considering many endpoints and time points creates multiple opportunities for apparently notable results to arise by chance. Unless the analysis plan accounts for multiplicity, unadjusted secondary comparisons generally carry less confirmatory weight than a prespecified primary comparison. The registry record does not report a multiplicity-adjustment strategy or clarify which secondary analyses were prespecified for formal inference.

The appropriate reading is consequently limited: the available earlier glycosylated hemoglobin summaries are directionally consistent with the primary result, while the other listed outcomes and the formal status of secondary testing remain unclear from the registry record. They add descriptive context, but should not be treated as independent proof or as a replacement for a documented analysis plan.

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

• Change From Baseline in Glycosylated Hemoglobin (Week 2).
• Change From Baseline in Glycosylated Hemoglobin (Week 4).
• Change From Baseline in Glycosylated Hemoglobin (Week 8).
• Change From Baseline in Fasting Plasma Glucose (Week 2).
• Change From Baseline in Fasting Plasma Glucose (Week 4).
• Change From Baseline in Fasting Plasma Glucose (Week 8).
• Change From Baseline in Fasting Plasma Glucose (Week 12).
• Change From Baseline in Fasting C-peptide (Week 2).

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is a continuous measure, and the registry reports the mean change in each group with a standard deviation. A mean is the arithmetic average of the observed change scores. A standard deviation describes how dispersed those scores are around the mean: greater dispersion means participants’ changes varied more widely. Neither measure alone shows the full distribution of individual outcomes.

What does the mean difference represent?

The mean difference is the estimated average change in an alogliptin group minus the average change in the control group. A negative estimate means that the alogliptin group’s average change was more negative than the control group’s average change. For the primary endpoint, the recalculated comparisons are -1.0 for alogliptin 12.5 mg versus control and -0.95 for alogliptin 25 mg with voglibose versus control. These are unadjusted comparisons based on the posted group summaries, rather than adjusted estimates from a model described by the registry.

What does a confidence interval convey?

A confidence interval gives a range of values compatible with the estimate under the calculation’s assumptions and sampling variability. Narrower intervals indicate greater statistical precision; wider intervals indicate less precision. An interval that does not include zero is consistent with a nonzero mean difference under the corresponding statistical framework. It does not show the probability that the true effect lies inside the particular interval, and it does not address possible bias, missing-data assumptions, or clinical importance. The primary recalculated intervals and the sponsor-reported intervals are described separately because their analyses are not interchangeable.

What is the role of the p-value?

The recalculated unadjusted p-values for both primary comparisons are <0.001. In general, a p-value describes how unusual data at least as incompatible with a specified null hypothesis would be if that hypothesis and the test assumptions held. It is not the probability that the null hypothesis is true, and it does not measure the magnitude or importance of a difference. The registry does not post p-values for its own primary analyses. These recalculated p-values also do not account for multiple comparisons.

How should the analysis population and missing values be understood?

The primary results are reported for the Full Analysis Set. The registry says that the last postbaseline double-blind observed value was carried forward to subsequent scheduled time points with missing data. This last-observation-carried-forward procedure fills a later missing value with an earlier recorded value. It can make an analysis possible when later measurements are absent, but it assumes that carrying the earlier value forward is an appropriate representation of the missing later outcome. That assumption may not hold for every participant or circumstance. The registry record does not report sensitivity analyses that examine how alternative missing-data assumptions affect the primary estimates.

What do the recalculations add?

The posted-results recalculations use group summary statistics to form simple, unadjusted comparisons. They offer a transparent way to describe the size and approximate precision of the mean differences from the reported means and standard deviations. They do not reproduce an undocumented sponsor model, any stratification or covariate adjustment, or any analysis rules beyond those stated in the record. The registry’s own reported analysis is the appropriate reference for the sponsor’s reported result; the recalculation is supplementary statistical context.

In general, randomization is intended to make treatment groups comparable at the start of a trial, on average, with respect to both measured and unmeasured factors. Masking can reduce some risks of bias in treatment delivery and outcome assessment. The registry identifies the study as randomized and quadruple-masked, but it does not report enough operational detail to evaluate how those procedures were implemented. No additional statistical model, interim analysis, or sample-size rationale should be inferred from the design labels.

11. Confidence Intervals and Precision

The recalculated primary mean difference for alogliptin 12.5 mg versus voglibose control is -1.0, with a 95% confidence interval from -1.162 to -0.838. For alogliptin 25 mg with voglibose versus control, the estimate is -0.95, with a 95% confidence interval from -1.099 to -0.801. Both intervals lie below zero, indicating that the estimated mean differences are negative across the ranges represented by these intervals under the calculation assumptions.

Confidence intervals communicate precision as well as direction. They show that the estimated differences are not exact values: sampling variability permits a range of plausible estimates. The registry’s reported analyses give a 95% interval from -1.166 to -0.838 for the 12.5 mg comparison and from -1.097 to -0.796 for the 25 mg comparison. The sponsor-reported values are close to the unadjusted recalculations, while reflecting the registry’s own reported analysis.

Statistical precision does not settle clinical importance. The registry record does not provide a threshold for a meaningful difference, and an interval cannot by itself show how the result translates to outcomes beyond the measured glycosylated hemoglobin change. Nor does it capture every uncertainty: the interval does not automatically account for analysis choices, possible bias, or the assumptions made for missing measurements. The last-observation-carried-forward procedure is particularly relevant because the primary analysis used carried-forward values for missing scheduled measurements.

For these reasons, the intervals are best read as uncertainty ranges around the reported mean comparisons, conditional on the methods and assumptions used. They support a precise description of the average difference in this trial, but not an unqualified conclusion about every participant or other settings.

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 illustrations are planning calculations based on fractions of the observed effect, rather than the trial’s original design calculations. For these continuous-outcome comparisons, the entries are participants per arm, not total events. The assumptions listed are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning scenario uses the stated fraction of the observed effect as the effect to detect. The registry record does not report the trial’s own original sample-size assumptions or justification.

The 80% power column gives the illustrative number of participants per arm for a design with an 80% chance of detecting the specified effect under the stated assumptions, if that effect and the other assumptions hold. The 90% power column describes the corresponding planning target for a 90% chance. These are prospective planning interpretations, not measures of what happened in the completed trial.

The rows that plan for 100% of the observed effect use the effect estimated in this trial; rows for 75% and 50% use smaller effects. Smaller effects are harder to distinguish from random variation, so the illustrations require more participants per arm as the target effect becomes smaller. The resulting values are planning illustrations based on observed effects and should not be treated as proof that a future study of those sizes would reproduce this trial’s results. This is not observed power.

In general, power calculations depend on assumptions about the effect, variability, allocation, significance level, and analysis. If those assumptions differ from a later study or the true effect is smaller, the planning values may not provide the intended power. The table and curve should therefore be read as sensitivity illustrations, not as a substitute for a prospective design justified for a new research question.

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 = -1.000; pooled standard deviation σ = 0.508.
2. n = 2 × (1.96 + 0.842)² × 0.508² / -1.000² = 4.0, rounded up to 5 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 <- -1                      # observed difference in means
sigma <- 0.507921386766826                     # 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(1263483)
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 = 5 (80% power), 6 (90% power)
 75% of observed effect: n per arm = 8 (80% power), 10 (90% power)
 50% of observed effect: n per arm = 17 (80% power), 22 (90% power)
power.t.test: 5.2 
Simulated power at n = 5 per arm: 0.773 (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 analysis reports a mean difference of -1.002 for voglibose control versus the alogliptin 12.5 mg group, with a 95% confidence interval from -1.166 to -0.838. For the comparison with alogliptin 25 mg and voglibose, it reports -0.947, with a 95% confidence interval from -1.097 to -0.796. The reported analysis labels these as mean differences in final values.

The unadjusted recalculations give -1.0, with a 95% confidence interval from -1.162 to -0.838, and -0.95, with a 95% confidence interval from -1.099 to -0.801, respectively. The figures are close, but the calculations are not the sponsor’s analysis and the registry does not state the method used for that analysis. It also does not post sponsor p-values for these primary comparisons.

The recalculation is useful as a transparent comparison derived from posted group summaries, but it cannot reproduce undocumented modeling or adjustment choices. The registry’s own analysis takes precedence when describing the sponsor-reported result. The record does not report enough methodological detail to explain any small differences between the reported and recalculated estimates.

15. Multiplicity, Missing Data and Analysis Populations

The record lists multiple outcome measures and analyses, including repeated measurements of glycosylated hemoglobin and other secondary outcomes. Testing or inspecting many outcomes can increase the chance of finding an apparently unusual result even when no true difference exists. Statistical methods can address this issue by defining a primary comparison, controlling error across selected tests, or treating secondary results as exploratory. The registry record does not report a multiplicity strategy, so the unadjusted secondary p-values should not be interpreted as if they necessarily account for all comparisons.

The primary endpoint analysis used the Full Analysis Set and last observation carried forward for missing scheduled postbaseline values. This specifies how the registry says missing values were handled for that outcome. It does not establish that the same rule was used for every secondary outcome. The registry record does not report the amount or pattern of missing data, reasons for missingness, or sensitivity analyses evaluating other approaches. Since carrying an earlier observation forward can differ from what would have been measured later, the missing-data assumption is relevant to interpretation.

The record does not report the original sample-size justification, a detailed statistical analysis plan, interim analyses, or the methods used to generate the sponsor’s reported estimates. It also does not report details sufficient to determine how the randomization sequence was produced or implemented. These are gaps in the available registry information; they do not establish that particular procedures were or were not used.

Clear reporting of these decisions would help readers distinguish prespecified confirmatory analyses from exploratory comparisons and understand the robustness of estimates to analytic choices. In their absence, the primary result can be described using the posted estimate and interval, while conclusions about multiplicity control, sensitivity to missing data, and correspondence to the original plan remain limited.

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: osteomyelitis (1.3%), pneumonia (1.3%), pyelonephritis acute (1.3%), cerebral infarction (1.3%), acute myocardial infarction (1.3%).

The registry reports serious adverse events among 9 participants at risk in the voglibose 0.2 mg group, 0 participants at risk in the alogliptin 12.5 mg group, and 1 participant at risk in the alogliptin 25 mg with voglibose group. These are the serious-event figures recorded for the listed groups. They describe events reported during the study and do not, by themselves, establish that an event was caused by a treatment.

The registry lists serious-event terms with reported percentages of 1.3% for osteomyelitis, pneumonia, acute pyelonephritis, cerebral infarction, acute myocardial infarction, and acute cardiac failure. A term appearing in a serious-event listing should be read as a reported event category, not as evidence of a causal relationship. The record does not provide enough detail in these figures to compare event types reliably across groups.

Deaths are not reported in the registry record. Safety interpretation is limited to the recorded event summaries; the figures alone do not describe severity beyond the registry’s serious-event classification, timing, relatedness assessment, or all aspects of the trial’s safety monitoring.

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

The posted primary results describe a more negative average change in glycosylated hemoglobin in each alogliptin group than in the voglibose control group over the measured period. The registry’s own reported mean differences and the unadjusted recalculations are similar in size, and their reported confidence intervals lie below zero. This is evidence about the group averages and the specified endpoint in this trial.

That statistical description does not establish the clinical importance of the difference. The registry record does not provide a threshold for a meaningful change, and the analysis does not tell whether every participant changed in the same way. A group mean can conceal variation in individual responses. The confidence interval characterizes sampling uncertainty under analytic assumptions; it does not eliminate uncertainty from missing data, possible bias, or choices that are not documented.

The study was conducted in participants with type 2 diabetes in Japan and compared the registered regimens over the trial’s reported endpoint period. The results should not be generalized automatically to other populations, treatment settings, durations, or outcomes not reported. The registry’s listed secondary outcomes are broader than the results available for interpretation, and the record does not report the original statistical plan or multiplicity approach.

These findings therefore answer a specific statistical question about average week 12 or final-visit change, using the Full Analysis Set and the stated last-observation-carried-forward procedure. They do not establish a treatment recommendation, a causal explanation for every adverse event, or an effect on outcomes beyond those measured and posted. Interpretation should remain bounded by the trial design and the information recorded in the registry.

18. Why This Trial Matters Statistically

This trial illustrates why a reported treatment comparison needs to be read through several statistical layers. The group means describe the observed average changes, the mean difference expresses the comparison on the outcome’s scale, and confidence intervals communicate uncertainty around that comparison. Looking at all three helps separate effect direction, estimated magnitude, and precision rather than relying on a single significance statement.

The record also makes the distinction between a sponsor-reported analysis and an unadjusted recalculation visible. The primary estimates are close, but the registry does not document the sponsor’s method in enough detail to reproduce it. A transparent recalculation can provide a useful check from posted summaries, while the sponsor’s analysis remains the registry’s own result. Neither should be mistaken for a complete account of design choices that the record does not report.

Missing-data handling is another central statistical issue. The primary analysis used last observation carried forward, which makes the assumed treatment of absent later measurements consequential. The registry does not report sensitivity analyses or the extent and pattern of missingness, limiting assessment of how robust the estimate is to alternative assumptions.

Finally, the repeated secondary outcomes and planning illustrations serve different purposes. Secondary results can describe whether the pattern is broadly consistent, but multiplicity matters when many outcomes and visits are examined. Planning numbers based on observed effects can illustrate how sample size depends on the target effect, but they are not observed power and do not reveal the trial’s original design rationale. Together, these distinctions support a more careful reading of what the registry establishes and what remains uncertain.

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.

Several limitations are specific to the available record. The primary analysis used last observation carried forward for missing scheduled postbaseline data, but the record does not report the amount or pattern of missingness or sensitivity analyses under alternative assumptions. It is therefore not possible from the registry results alone to judge how strongly the estimate depends on that imputation rule.

The registry does not report the detailed statistical method for its own primary analysis, the original sample-size justification, or the prespecified plan for handling multiple outcomes. This limits assessment of whether the posted analyses match the intended confirmatory plan and how secondary findings should be weighted. The unadjusted recalculations are not a substitute for those missing design and analysis details.

Although multiple outcome measures are listed, only some secondary results are available in the record. The secondary glycosylated hemoglobin summaries support a descriptive pattern across the available visits, but do not provide a complete account of every listed outcome. The registry record also does not provide a clinical threshold for interpreting the size of the primary difference.

The record identifies the study as randomized, quadruple-masked, and multicenter, but does not report operational details of sequence generation, allocation concealment, or masking implementation. Such details cannot be inferred from the design labels. Safety summaries are limited to the recorded serious-event counts and terms; deaths are not reported in the registry record. These information gaps constrain interpretation but do not establish what procedures or events may have occurred outside the posted record.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy and Safety of Alogliptin Used in Combination With α-glucosidase Inhibitor in Participants With Type 2 Diabetes in Japan — NCT01263483.
• Registry record last updated 2012-02-03; status last verified 2012-02.
• Results first posted 2011-07-11.
• 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 2/3 randomized, double-blind, placebo-controlled, parallel-group, multicenter study sponsored by Takeda. It enrolled participants in Japan with type 2 diabetes and compared voglibose 0.2 mg three times daily alone with alogliptin-containing groups.

The primary endpoint was change from baseline in glycosylated hemoglobin at week 12 or the final visit, analyzed in the Full Analysis Set using last observation carried forward for missing scheduled values. The posted primary summaries show more negative mean changes in both alogliptin groups than in the voglibose control group. The sponsor-reported estimates and unadjusted recalculations are close.

The record lists multiple secondary outcomes, posts 16 secondary results, and reports serious adverse event summaries by group. It does not report the original sample-size justification, detailed statistical methods, multiplicity strategy, or deaths. The results should be interpreted within the endpoint, analysis population, missing-data procedure, and reporting limits documented in the registry.