Efficacy and Safety Study of TA-7284 in Patients With Type 2 Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety Study of TA-7284 in Patients With Type 2 Diabetes (NCT01413204), a randomized phase 3 study. The primary outcome is Change in Hemoglobin A1c (A1C) From Baseline (NGSP Value).

2. Clinical Question

HbA1c is a continuous laboratory measure, so the primary result is expressed as a mean change rather than as a count of participants reaching a threshold. The posted arm estimates were −0.74 percent HbA1C for TA-7284 Low, −0.76 percent HbA1C for TA-7284 High, and 0.29 percent HbA1C for placebo. Recalculated, unadjusted mean differences versus placebo were −1.03 for TA-7284 Low and −1.05 for TA-7284 High. Those contrasts describe the observed results in the analyzed groups; they do not by themselves establish what would happen in other populations or over other time periods.

3. Trial Design

The registry describes a phase 3, randomized, double-blind, placebo-controlled, parallel-group, multicenter study evaluating TA-7284 as monotherapy in people with type 2 diabetes. Masking is recorded as triple, but the identity of the masked parties and the practical masking procedures are not reported in the registry record. The sponsor is Tanabe Pharma Corporation. The study status is completed.

The registry lists enrollment of 272. Participants were assigned to TA-7284 Low, TA-7284 High, or placebo. The arm descriptions do not specify dose amounts or other treatment details, so the meaning of the Low and High labels beyond the registry names is not reported in the registry record. The primary endpoint analysis includes 90 participants in the TA-7284 Low arm, 88 in TA-7284 High, and 93 in placebo. The record does not explain the difference between total enrollment and these arm-level analysis counts.

The brief summary specifies 24 weeks of administration. The primary outcome is change in HbA1c from baseline, with the timeframe described as baseline and 24 weeks. The posted primary results are least-squares means with standard errors, using the full analysis set and last observation carried forward. The model and any covariates underlying the least-squares means are not reported in the registry record.

Secondary outcomes listed include fasting plasma glucose, body weight, blood pressure, postprandial measures after a 75 g oral glucose tolerance test, and safety and tolerability measures. Five secondary outcomes are listed as posted. The registry record does not provide analyses for those outcomes in the results used for this statistical interpretation. The dates for study start and primary completion are recorded as 2011-07 and 2012-08, respectively.

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.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full analysis set, last observation carried forward

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Change in Hemoglobin A1c (A1C) From Baseline (NGSP Value), measured over baseline and 24 weeks.

The primary endpoint is change in hemoglobin A1c (A1C) from baseline to 24 weeks, reported as the NGSP value in percent HbA1C. The result is a continuous measure: each arm is summarized by a least-squares mean change, accompanied by a standard error. The registry identifies the analysis population as the full analysis set and says that last observation carried forward was used.

HbA1c is used in clinical research as a measure of glycemia over time, rather than as a single-time-point glucose reading. As a general statistical point, a continuous endpoint preserves the size and direction of changes across participants; it does not reduce the outcome to whether each participant did or did not cross a chosen cutoff. That can make mean differences useful for comparing groups, while still leaving individual responses and the distribution of responses unshown by a mean alone.

The three posted mean changes were −0.74 for TA-7284 Low, −0.76 for TA-7284 High, and 0.29 for placebo. The registry reports least-squares means, but the specific model used to obtain them is not reported in the registry record. The endpoint name specifies change from baseline, and the result is interpreted as a group-level mean change, not as a direct estimate of each participant’s change or as a complete description of the treatment experience.

7. Results Posted in the Registry

• TA-7284 Low: mean -0.74 versus 0.29 on control; difference -1.03 (95% CI -1.22 to -0.84), standardized effect d = -1.54; z-test p = <0.001.
• TA-7284 High: mean -0.76 versus 0.29 on control; difference -1.05 (95% CI -1.24 to -0.86), standardized effect d = -1.58; z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary result is a continuous-outcome comparison. Each arm has a reported least-squares mean change and standard error. A least-squares mean is a model-based group estimate; however, the model specification, included covariates, and details of any adjustment are not reported in the registry record. It is therefore appropriate to describe the displayed quantities as least-squares means without assuming how they were obtained.

What does the standard error describe?

As a general statistical explanation, a standard error describes the expected variability of an estimate across repeated samples under a specified model. It is not the same as the spread of individual participant values. The reported standard error is 0.07 for each of the three arm means. Without participant-level results or a reported standard deviation for the endpoint, the amount of variation among individual participants cannot be read directly from these standard errors.

The registry gives the full analysis set as the primary analysis population and identifies last observation carried forward as the method for missing observations. In general, last observation carried forward substitutes an earlier recorded value when a later value is missing. That method can rely on assumptions about how outcomes evolve after the last observation; the assumptions, amount of missingness, and alternative analyses are not reported in the registry record. Consequently, the reported mean changes should be understood in the context of the stated imputation approach.

How should the group differences be read?

The displayed arm means can be contrasted with the placebo mean. The recalculated, unadjusted mean difference is −1.03 for TA-7284 Low versus placebo and −1.05 for TA-7284 High versus placebo. These simple contrasts use the posted arm-level summary statistics; they are not described as covariate-adjusted estimates. The registry gives unadjusted p-values of <0.001 for each comparison. A p-value is a measure of how compatible the observed data are with a specified null hypothesis under the analysis assumptions; it is not the probability that the null hypothesis is true, nor does it measure the importance of the result.

The recalculated confidence intervals use the posted summary statistics and are presented as unadjusted comparisons. A confidence interval gives a range of estimates that would be compatible with the data and method at the stated confidence level under repeated sampling. It captures sampling uncertainty under that calculation, but it does not automatically account for selection of endpoints, multiplicity, missing-data assumptions, or uncertainty about the analysis model. No discrepancy is flagged for these recalculations, so there is no indicated conflict requiring a different estimate to take precedence.

Why can over-dispersion matter?

As a general statistical concept, over-dispersion means that observed variability is greater than a model assumes. It can make standard errors too small and confidence intervals too narrow if the analysis does not account for it. This primary endpoint is continuous, and no over-dispersion assessment is reported in the registry record; the concept is relevant in general but should not be mistaken for a reported feature of this trial.

The planning illustrations use a normal approximation, equal allocation between two arms, a two-sided significance level of 0.05, and specified fractions of the observed effect. Those are assumptions for the illustrations only. The registry record does not report the trial’s original sample-size justification or its original design assumptions. The illustrative participant counts are planning calculations, not observed power and not a reconstruction of the trial’s design process.

Multiplicity concerns arise when several outcomes, comparisons, or analyses are tested. As a general explanation, performing multiple tests can increase the chance of at least one result appearing statistically significant by chance if no correction or hierarchy is used. This study has two TA-7284-versus-placebo comparisons and lists several secondary outcomes. The registry record does not report a multiplicity adjustment, testing hierarchy, prespecified primary contrasts beyond the primary endpoint designation, interim analyses, or detailed statistical analysis plan. The unadjusted p-values therefore should not be described as multiplicity-adjusted evidence.

The primary outcome is listed as one of six outcome measures, with five secondary outcomes posted. The registry lists zero analyses for the results record, and the statistical analysis plan details needed to resolve the structure and conduct of all analyses are not reported in the registry record. The available summary supports interpretation of the posted primary endpoint estimates, but not a complete audit of model assumptions, missing-data handling, or all prespecified analyses.

10. Confidence Intervals and Precision

The arm-level standard error is 0.07 for each posted mean change: −0.74 for TA-7284 Low, −0.76 for TA-7284 High, and 0.29 for placebo. A standard error describes uncertainty in an estimated mean, not the range of participant-level changes. It should not be read as a standard deviation or as a statement that individual outcomes cluster tightly around the mean.

The recalculated unadjusted contrast for TA-7284 Low versus placebo is −1.03, with a 95% confidence interval from −1.224 to −0.836. For TA-7284 High versus placebo, the recalculated unadjusted contrast is −1.05, with a 95% confidence interval from −1.244 to −0.856. The intervals quantify sampling precision for these contrasts under the calculation used. Both intervals are entirely below zero, but they do not account automatically for multiplicity, missing-data assumptions, or uncertainty in an unreported model specification.

As a general explanation, a confidence interval is a range produced by a method that, under its assumptions, would contain the target parameter at the stated rate over repeated studies. It is not a probability statement about the particular fixed parameter after the data are observed. The width of an interval reflects both the variability represented in the analysis and the amount of information available.

The standard errors and intervals do not show how robust the result is to alternative approaches to missing data. The primary analysis used last observation carried forward, and sensitivity analyses are not reported in the registry record. Nor does the interval establish clinical importance: that requires context beyond statistical precision, and such a threshold is not reported in the registry record.

11. 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 based on the observed effect, not the trial’s original design calculations. For each comparison, the figures are participants per arm, not a total across the two arms. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The illustrated effect is the stated fraction of the observed effect.

The 80% power column means the number of participants per arm calculated to give an 80% chance of detecting the specified effect under those planning assumptions, if that effect and the other assumptions are correct. The 90% power column uses the same interpretation with a higher target chance of detection. These are prospective planning quantities, not probabilities that the trial’s observed result is correct. This is not observed power.

The rows for 100% of the observed effect use the full effect estimate from the corresponding comparison. The 75% and 50% rows illustrate planning for smaller effects. Smaller effects are harder to distinguish from random variation, so they require more participants per arm under the same assumptions. The figures differ by comparison because the observed effects and estimated variability used in the calculations differ.

These calculations do not report the actual enrollment rationale for the study. The original sample-size justification, design effect, dropout allowance, and any other original planning assumptions are not reported in the registry record. The displayed planning figures should therefore be read as illustrations of how sample-size needs change with the assumed effect, rather than as evidence that the study was designed using those values or that it had a particular achieved power.

12. 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 = -1.030; pooled standard deviation σ = 0.670.
2. n = 2 × (1.96 + 0.842)² × 0.670² / -1.030² = 6.6, rounded up to 7 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 <- -1.03                      # observed difference in means
sigma <- 0.669680388845619                     # 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(1413204)
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 = 7 (80% power), 9 (90% power)
 75% of observed effect: n per arm = 12 (80% power), 16 (90% power)
 50% of observed effect: n per arm = 27 (80% power), 36 (90% power)
power.t.test: 7.7 
Simulated power at n = 7 per arm: 0.757 (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.

13. Multiplicity, Missing Data and Analysis Populations

The primary endpoint is change in HbA1c, and two TA-7284 arms are compared with placebo. The registry gives an unadjusted p-value of <0.001 for each comparison. It does not report whether the two comparisons were treated as a family, whether any multiplicity adjustment was planned, or whether one comparison had priority. The registry record also does not report an interim analysis plan or a detailed statistical analysis plan. It is therefore not possible to determine from the record whether the posted tests align with a prespecified multiplicity strategy.

Five secondary outcomes are listed as posted, covering fasting plasma glucose, body weight, blood pressure, postprandial glucose-related measures, and safety and tolerability. The primary results summarized for this analysis do not include estimates for those secondary outcomes. Whether the secondary outcomes were analyzed, how their tests were handled, and whether multiplicity was addressed are not reported in the registry record.

The primary analysis population is the full analysis set, with last observation carried forward for missing observations. The record does not state the number or proportion of missing primary endpoint measurements, how many participants were excluded from the full analysis set, or the reasons for missing values. It also does not report sensitivity analyses using other missing-data assumptions. As a general statistical point, missing-data methods can affect estimates when the probability or pattern of missingness is related to outcomes or participant characteristics.

The registry lists 272 enrolled participants, while the primary arm-level analysis counts are 90, 88, and 93. The record does not explain the relationship between those figures. The analysis model, covariate adjustment, and treatment of protocol deviations are also not reported in the registry record. These omissions limit assessment of analysis-population definitions, model choices, missing-data robustness, and the control of false-positive risk across multiple tests.

14. 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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: oropharyngeal cancer stage unspecified (1.1%), breast cancer (1.1%), gastric cancer (1.1%), hepatic neoplasm malignant (1.1%), prostate cancer (1.1%).

The registry reports serious adverse events among 1 participant in the TA-7284 Low group, 1 in the TA-7284 High group, and 2 in the placebo group. The corresponding groups at risk were 90, 89, and 93. These are counts from the registry record; they do not establish that any particular event was caused by study treatment.

Other adverse events affected 59 participants in TA-7284 Low, 55 in TA-7284 High, and 54 in placebo. The record lists five serious adverse event terms, each with a reported frequency of 1.1%: oropharyngeal cancer stage unspecified, breast cancer, gastric cancer, hepatic neoplasm malignant, and prostate cancer. The posted term list should be read as event coding information, not as a comparison of overall risk across groups.

Deaths are not reported in the registry record. The record does not provide enough information to determine event timing, duration, severity details beyond the serious-event classification, or causal attribution. Arm-level event counts are descriptive and do not, by themselves, establish a safety difference.

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

The posted primary results show that the mean change in HbA1c was −0.74 percent HbA1C in TA-7284 Low, −0.76 percent HbA1C in TA-7284 High, and 0.29 percent HbA1C in placebo. The recalculated unadjusted differences versus placebo are −1.03 and −1.05, respectively, and both posted unadjusted p-values are <0.001. The confidence intervals describe the precision of these unadjusted contrasts under the calculations used.

These findings describe group averages in the full analysis set at the specified 24-week endpoint, using last observation carried forward. They do not describe every participant’s change, and they do not show the full distribution of outcomes. The results are not a direct comparison between the two TA-7284 arms; such a comparison is not reported in the registry record. Dose amounts are also not reported, so the arm labels do not support interpretation of a dose-response pattern.

Statistical evidence for a difference in mean change is not the same as evidence about clinical importance, durability beyond 24 weeks, or outcomes not included in the posted primary result. The listed secondary outcomes include other measures, but their results are not reported in the primary results. The safety counts are separate descriptive information and should be considered alongside, not replaced by, the HbA1c contrast.

The registry record does not report the detailed model specification, multiplicity strategy, original sample-size justification, or sensitivity analyses for missing data. Those omissions mean the precision of the posted estimates cannot be treated as a complete account of uncertainty about analysis choices. The results provide a statistical description of the recorded endpoint and comparisons, not a basis for medical advice or conclusions beyond this study’s recorded population, endpoint, analysis, and follow-up.

16. Why This Trial Matters Statistically

This trial illustrates how a continuous clinical endpoint can be reported at several levels: arm-specific mean changes, standard errors, and contrasts with a comparator. The posted means make the direction and scale of each arm’s average change visible, while the recalculated unadjusted differences put the TA-7284 arms on a direct scale relative to placebo. Confidence intervals add information about statistical precision that a point estimate alone cannot convey.

It also shows why design labels and analysis details need to be distinguished. The registry describes randomization, triple masking, and a parallel-group structure, but does not provide detailed allocation procedures, masking procedures, or the model specification for the least-squares means. Knowing the broad design helps frame the comparison; it does not resolve every question about how the estimates were produced.

The use of last observation carried forward is especially relevant to interpretation because the primary result depends on a stated missing-data method. Without the extent and pattern of missingness or sensitivity analyses, readers cannot judge how strongly the result depends on that choice. Similarly, two comparisons against placebo and several listed secondary outcomes make multiplicity relevant, while the registry record does not describe an adjustment or testing hierarchy.

Finally, the sample-size illustrations distinguish planning under hypothetical effect assumptions from the study’s original design. They show the general relation between effect size and required participants per arm, but do not reveal the historical rationale for enrollment. Together, these points show why effect estimates, uncertainty, design, analysis population, missing-data handling, and safety counts should be interpreted as related but distinct components of a trial record.

17. 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 gives the primary outcome as a least-squares mean but does not report the statistical model, covariates, or detailed estimation procedure. The arm-level standard errors are available, but participant-level distributions and standard deviations are not reported in the registry record. The analysis therefore cannot assess distribution shape, outliers, or whether model assumptions fit the outcome data.

The primary analysis used last observation carried forward. The number of missing observations, their timing and reasons, and sensitivity analyses under alternative missing-data methods are not reported in the registry record. The arm-level outcome counts also do not fully explain how the enrolled total relates to the primary analysis population.

The posted comparison p-values are unadjusted. No multiplicity procedure, testing hierarchy, interim analysis plan, or detailed statistical analysis plan is reported in the registry record. The original sample-size justification and design assumptions are likewise not reported. The planning illustrations use stated hypothetical assumptions and should not be mistaken for a reconstruction of the study’s design.

Other limitations include the absence of posted results for the listed secondary outcomes in the primary results, the absence of dose amounts in the arm descriptions, and the lack of a reported direct comparison between the TA-7284 arms. The safety record provides group counts and a list of serious-event terms, but deaths are not reported in the registry record, and the available details do not establish causal attribution or event timing. These limits narrow what can be concluded from the record to the displayed endpoint estimates and counts.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Efficacy and Safety Study of TA-7284 in Patients With Type 2 Diabetes — NCT01413204.
• Registry record last updated 2026-01-08; status last verified 2025-12.
• Results first posted 2014-06-05.
• 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.

21. Record Summary

The registry describes a completed phase 3 randomized, double-blind, placebo-controlled, parallel-group study of TA-7284 as monotherapy in people with type 2 diabetes. Enrollment was 272. The primary endpoint was change in HbA1c from baseline to 24 weeks in the full analysis set, using last observation carried forward.

Posted least-squares mean changes were −0.74 percent HbA1C for TA-7284 Low, −0.76 percent HbA1C for TA-7284 High, and 0.29 percent HbA1C for placebo. Recalculated unadjusted mean differences versus placebo were −1.03 and −1.05, with posted unadjusted p-values of <0.001 for each. Serious adverse events were reported for 1, 1, and 2 participants in the respective groups. The registry does not report detailed analysis methods, a multiplicity strategy, or sensitivity analyses for missing data.