Efficacy and Safety of MP-513 in Combination With Metformin in Patients With Type 2 Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety of MP-513 in Combination With Metformin in Patients With Type 2 Diabetes (NCT00971243), a randomized phase 2 study. The primary outcome is Change in HbA1c From Baseline to Week 24.

2. Clinical Question

The study was designed to investigate both efficacy and safety. Its central comparison is therefore not MP-513 against no treatment: each group continued metformin, while the randomized add-on was one of four MP-513 doses or placebo. This distinction matters when interpreting the group changes. The placebo-plus-metformin group also had a recorded mean change in HbA1c, so the drug-group changes should be understood relative to that comparator rather than as isolated before-and-after changes.

The registry record describes 24 weeks of administration for the main assessment and an open-label extension with treatment for up to 52 weeks. The primary question addressed by the posted endpoint is the change through Week 24. The record does not report extension results in the information summarized for these outcomes, so the primary comparison cannot answer questions about longer-term results.

The study title identifies MP-513, while the posted result groups use the name Teneli and specify dose labels in milligrams. The record does not provide further explanation of that naming or arm-level treatment details. The question is therefore best kept to the actual reported comparison: dose-labelled Teneli plus metformin groups versus placebo plus metformin, with HbA1c change measured at Week 24.

3. Trial Design

This was a Phase II study described in its official title as Phase IIb, with randomized allocation, quadruple masking, and a parallel-group model. It enrolled 448 participants and was recorded as completed. The registry lists type 2 diabetes mellitus as the condition. The study began in 2009-08, and primary completion was recorded as 2011-04.

Five add-on groups appear in the results: four dose-labelled Teneli-plus-metformin groups and one placebo-plus-metformin group. The result group sizes for the primary endpoint are 87, 93, 91, 88, and 88, respectively. The intervention list describes the active study drug as MP-513, in four dose levels, alongside metformin; the comparator is placebo alongside metformin. Arm descriptions beyond these labels are not reported in the registry record.

The primary assessment was change in HbA1c from baseline to Week 24, with the timeframe described as baseline and Week 24. The stated primary analysis used ANCOVA, with centre and treatment as factors and baseline HbA1c as a covariate. The registry also describes last observation carried forward for missing Week 24 HbA1c values in the intention-to-treat analysis. Further details about the randomization procedure, allocation concealment, masking roles, study-site count, eligibility criteria, and protocol deviations are not reported in the registry record.

The brief description says the initial administration period was 24 weeks, followed by an extension treatment for up to 52 weeks. The extension was open label according to the official title. The displayed primary endpoint is the 24-week measure; extension endpoints and extension results are not reported in the registry record. The registry lists fasting plasma glucose change and adverse events, laboratory tests, and vital signs among the secondary outcome descriptions, though the posted results summarized for secondary endpoints include two outcome measures.

Randomization and masking are features of the design, but their presence alone does not establish how well they were implemented. The registry record does not report enough operational detail to assess sequence generation, concealment, or the success of masking. The results should be read as findings from the randomized, masked parallel-group study as described, while recognizing these limits on design appraisal.

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.

Double Blind Period

Reasons for not completing this period:

Open-label Period

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: LOCF was implemented in the Intention-to-Treat (ITT) population analysis to replace missing values for all those subjects who did not present an HbA1c value at Week 24.

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 HbA1c From Baseline to Week 24, measured over Baseline and Week 24.

The primary endpoint is change in HbA1c from baseline to Week 24, expressed as percentage of HbA1c. HbA1c is a continuous measure used to assess glycaemic status over time. A change score expresses how the measure at follow-up differs from the starting value; negative values in the posted results indicate a decrease from baseline. This endpoint allows the randomized groups to be compared over a defined treatment period, rather than relying only on a single follow-up measurement.

The registry reports least-squares means and standard errors. A least-squares mean is an adjusted group estimate from a statistical model, rather than simply the unadjusted arithmetic average. Here, the stated ANCOVA model included centre and treatment as factors and baseline HbA1c as a covariate. Accounting for baseline HbA1c can make the group comparison conditional on starting values in the way specified by that model. The record does not provide additional model diagnostics or other details needed to assess the model fit.

The primary timeframe is baseline to Week 24. In the intention-to-treat population analysis, the record says that last observation carried forward was used to replace missing Week 24 HbA1c values. That approach uses an earlier observed value for a participant without the Week 24 value, according to the stated method. Its usefulness depends on assumptions about how missing values relate to subsequent outcomes; the registry record does not report the amount or pattern of missing HbA1c data.

HbA1c was selected as the primary measure for the study’s stated efficacy question. Fasting plasma glucose was also recorded as a secondary endpoint, providing a related but distinct continuous measure. Neither endpoint alone describes all aspects of safety or longer-term outcomes.

7. Results Posted in the Registry

• Teneli 5mg+Met: mean -0.58 versus -0.28 on control; difference -0.30 (95% CI -0.49 to -0.11), standardized effect d = -0.46; z-test p = 0.002.
• Teneli 10mg+Met: mean -0.68 versus -0.28 on control; difference -0.40 (95% CI -0.59 to -0.21), standardized effect d = -0.60; z-test p = <0.001.
• Teneli 20mg+Met: mean -0.76 versus -0.28 on control; difference -0.48 (95% CI -0.67 to -0.29), standardized effect d = -0.72; z-test p = <0.001.
• Teneli 40mg+Met: mean -0.91 versus -0.28 on control; difference -0.63 (95% CI -0.82 to -0.44), standardized effect d = -0.96; 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 in Fasting Plasma Glucose (FPG) From Baseline to Week 24

• 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:
  • Teneli 5mg+Met: mean -15.54 versus -3.51 on control; difference -12.03 (95% CI -20.19 to -3.87), standardized effect d = -0.44; z-test p = 0.004.
  • Teneli 10mg+Met: mean -13.65 versus -3.51 on control; difference -10.14 (95% CI -18.15 to -2.13), standardized effect d = -0.37; z-test p = 0.013.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Teneli 5mg+Met 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 Teneli 10mg+Met than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary endpoint results cover fasting plasma glucose change from baseline to Week 24 and adverse-event reporting. The posted fasting plasma glucose estimates show decreases in each group, including placebo plus metformin. The two reported direct comparisons against placebo plus metformin are negative, with unadjusted p-values of 0.004 and 0.013. The registry record does not list reported analyses for the other active-dose comparisons on this endpoint.

This direction is broadly consistent with the primary endpoint pattern: the displayed active-versus-placebo comparisons for fasting plasma glucose are negative, as are the primary HbA1c comparisons. The measures are related indicators of glycaemic status, but they are not interchangeable, and the secondary endpoint does not substitute for the primary endpoint. The registry record does not report a joint analysis of HbA1c and fasting plasma glucose or a formal assessment of consistency across endpoints.

Secondary outcomes generally provide supporting context rather than the same evidential weight as a designated primary outcome. Their results may be less central to the original study question, and evaluating multiple endpoints and dose comparisons introduces additional opportunities for chance findings. The fasting plasma glucose p-values are unadjusted, and a multiplicity correction or testing hierarchy is not reported in the registry record. The number of additional analyses performed is also not specified beyond the fact that no reported analyses are listed for the secondary endpoint results.

Adverse events are a separate type of secondary information, describing safety events rather than efficacy measures. The serious and other adverse-event counts should be read by group and by the number at risk. They do not by themselves provide a complete comparison of event timing, duration, severity, or causal attribution. Laboratory tests and vital signs are mentioned in the secondary outcome description, but their detailed results are not reported in the record information summarized for these outcomes.

Overall, the secondary findings offer a directionally similar glucose-measure pattern and descriptive safety counts. They do not independently confirm the primary comparison, establish a dose-response relationship, or resolve uncertainty from unadjusted multiple testing. Their appropriate role is to add context to the primary endpoint while retaining the limitations of the reporting and analysis details.

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

• Change in Fasting Plasma Glucose (FPG) From Baseline to Week 24
• Adverse Events, Laboratory Tests, Vital Signs, Etc.

9. Statistical Interpretation

10. Statistical Methods Explained

The primary analysis is described as an analysis of covariance, or ANCOVA. In general, ANCOVA compares group outcomes while including one or more covariates in the model. Here, the registry states that centre and treatment were included as factors and baseline HbA1c was included as a covariate. This means the endpoint is summarized using a model that accounts for baseline HbA1c and includes the specified factors. The record does not give the model equation, assumptions checks, handling of centres, or diagnostics, so those details cannot be assessed.

What does a least-squares mean represent?

In general, a least-squares mean is a model-based estimate for a group after accounting for the terms included in the model. It differs from a raw group average when adjustment terms are present. The posted HbA1c estimates are labelled least-squares means, and their standard errors describe uncertainty in those estimates under the fitted model. The record does not state whether the reported pairwise differences were obtained directly from that ANCOVA model or through another calculation, so the model-based group estimates and the listed unadjusted comparisons should not be assumed to be identical types of output.

How should change scores be read?

A change score compares a follow-up measure with its baseline value. For this endpoint, a negative estimate indicates a lower Week 24 value than at baseline, according to the change convention used in the registry. An active-group change by itself does not isolate the add-on treatment contrast, because the placebo-plus-metformin group also has a change. The mean difference against that comparator is the direct comparison reported for each dose group. Interpreting both the group changes and the comparator contrast avoids treating a within-group change as though it were a randomized treatment effect.

What does last observation carried forward do?

The registry says last observation carried forward was implemented in the intention-to-treat population analysis to replace missing Week 24 HbA1c values. In general, this method substitutes a participant’s last available measurement for the missing endpoint value. It creates a complete analysis value for a participant with an earlier observation, but it does not observe the missing Week 24 outcome. The method can be misleading if the earlier value is not a reasonable stand-in for what would have been measured at Week 24. Its assumptions, the quantity of missing data, and sensitivity analyses are not reported in the registry record.

The term intention-to-treat describes an analysis organized around randomized assignment, rather than simply comparing participants according to treatment received. The registry names an intention-to-treat population for the primary endpoint and describes LOCF within that analysis. It does not provide a participant flow, exclusions, adherence information, or a detailed account of which participants contributed to each endpoint. The reported analysis population label therefore helps describe the intended approach but cannot, by itself, establish how every randomized participant was handled.

How do standard errors and interval limits differ?

In general, a standard error estimates the sampling uncertainty of an estimate. A smaller standard error means the estimate is more precise under the calculation’s assumptions, while a larger one indicates greater uncertainty. The primary group standard errors are 0.07. A standard error is not the same as the spread of individual participant values; it describes uncertainty in the estimated group mean. The registry does not report the individual-level variability for this endpoint.

An interval estimate expresses a range of values compatible with the observed estimate and its uncertainty, under a specified method. The comparison results include lower and upper interval limits. The confidence level and the method used to calculate those limits are not reported in the registry record. Consequently, the interval limits can be used to appreciate the reported precision, but they cannot be described as a particular confidence level on the basis of this record alone.

What does an unadjusted p-value tell the reader?

In general, a p-value measures how incompatible the observed data are with a specified null hypothesis under the assumptions of a statistical test. It does not measure the probability that the null hypothesis is true, the size or importance of an effect, or the chance that the finding will replicate. The posted p-values are labelled unadjusted. The registry record does not provide the exact test used to generate them, and it does not report a correction for the several active-versus-placebo comparisons. They should be interpreted alongside the effect estimates and interval limits, not as stand-alone conclusions.

Because more than one active dose was compared with the same placebo group, the tests are related. In general, conducting multiple tests increases the chance of at least one apparently unusual result if all null hypotheses are true. A multiplicity procedure can address that issue, but the procedure and any testing hierarchy are not reported in the registry record. It would be inappropriate to assume a correction was used simply because the study had a stated primary endpoint.

The registry identifies the design as randomized, quadruple masked, and parallel group, and the analysis description specifies ANCOVA and LOCF. It does not report the original sample-size justification, a prespecified statistical analysis plan, interim analyses, or details of a dose-response model. Those omissions limit the ability to assess whether all reported analyses follow the original plan. The statistical interpretation should therefore remain focused on the endpoint definitions and numerical results that the record does state.

11. Confidence Intervals and Precision

Precision concerns how tightly an estimate is determined by the data and method. For the primary endpoint, the least-squares mean standard error is 0.07 in each group. The direct comparisons have reported lower and upper interval limits: -0.494 to -0.106 for Teneli 5mg+Met, -0.594 to -0.206 for Teneli 10mg+Met, -0.674 to -0.286 for Teneli 20mg+Met, and -0.824 to -0.436 for Teneli 40mg+Met, each relative to placebo plus metformin. These interval limits give more information about uncertainty than a point estimate alone.

The confidence level and interval calculation method are not reported in the registry record. The intervals therefore should not be assigned a conventional confidence label without further documentation. In general, an interval describes values compatible with the observed data under a chosen statistical procedure; it does not guarantee that the true effect lies within its limits, nor does it represent the range of individual participant responses.

All four listed intervals lie on the negative side of zero, and the corresponding posted unadjusted p-values are 0.002 or <0.001. This is a description of the posted, unadjusted comparisons, not a statement that multiplicity has been addressed. The interval estimates also do not establish whether the magnitude is clinically important, because a threshold for a clinically meaningful difference is not reported in the registry record.

Standard errors and intervals reflect sampling uncertainty under the method used, but they do not capture every source of uncertainty. They do not show how the estimates might change under a different missing-data assumption, a different model, or a different analysis population. The record does not report sensitivity analyses, model diagnostics, or a confidence level. Thus, precision can be described numerically from the posted estimates, while the robustness of that precision to other reasonable analytic choices remains unclear.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The sample-size figures are planning illustrations based on the observed effect sizes, not the original trial’s design calculations. The assumptions listed for these illustrations are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. Each row considers detecting the stated fraction of the observed effect. The trial’s own sample-size assumptions and justification are not reported in the registry record.

For these continuous outcomes, the displayed figures are participants per arm, not total participants across both arms. In general, the 80% power column gives the estimated number of participants per arm needed for an 80% chance of detecting the specified effect under the listed assumptions, if that effect and the assumptions hold. The 90% power column applies the same interpretation at a higher target chance of detection, which typically requires more participants. The display is not an account of how many participants were actually enrolled in any arm.

Rows for 100%, 75%, and 50% of the observed effect represent progressively smaller effects relative to the observed estimate. A smaller effect is harder to distinguish from random variation under the same assumptions, so more participants are needed. For example, in the HbA1c comparison for Teneli 5mg+Met, planning for 100% of the observed effect gives 75 participants per arm for 80% power, while planning for 50% gives 300. For Teneli 40mg+Met, the corresponding 80% figures are 18 and 69 participants per arm.

These values are not observed power. They are forward-looking illustrations whose usefulness depends on the estimated effect and the stated assumptions; they are not evidence that the completed study had a particular probability of success. The illustrations also do not reproduce the trial’s original design calculation, which is not reported in the registry record.

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 = -0.300; pooled standard deviation σ = 0.655.
2. n = 2 × (1.96 + 0.842)² × 0.655² / -0.300² = 74.8, rounded up to 75 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 <- -0.3                      # observed difference in means
sigma <- 0.654800856634833                     # 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(971243)
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 = 75 (80% power), 101 (90% power)
 75% of observed effect: n per arm = 133 (80% power), 178 (90% power)
 50% of observed effect: n per arm = 300 (80% power), 401 (90% power)
power.t.test: 75.8 
Simulated power at n = 75 per arm: 0.797 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The registry record reports four active-dose comparisons against the placebo-plus-metformin group for the primary endpoint. The corresponding p-values are unadjusted, and no method for controlling multiplicity is reported. In general, when several related comparisons are made, the probability of at least one nominally small p-value under a collection of null hypotheses can increase. A planned procedure, such as an adjustment or testing hierarchy, can define how such results are interpreted, but no such procedure is reported. The p-values should therefore not be treated as multiplicity-adjusted evidence.

The registry record does not report whether there were interim analyses or whether any statistical monitoring rules were used. It also does not report a complete statistical analysis plan, including details on how the primary and secondary tests were ordered or how the reported interval limits were calculated. The stated ANCOVA model and LOCF approach provide useful information, but they do not fill in those unreported design and analysis decisions.

Missing Week 24 HbA1c values were handled by last observation carried forward in the intention-to-treat population analysis, according to the primary endpoint description. The record does not state how many values were missing, why they were missing, whether missingness differed across groups, or what observations were carried forward. It also does not report sensitivity analyses using alternative missing-data assumptions. LOCF is a specific imputation approach, not a guarantee that missing values are unbiasedly represented.

The registry names the intention-to-treat population but does not give a detailed participant flow or describe exclusions from the analysis. The endpoint group counts are reported, but the record does not explain their relationship to the total enrollment or provide further analysis-population definitions. As a result, the completeness of follow-up and the effect of exclusions cannot be fully assessed from the registry record.

These gaps do not change the arithmetic of the posted estimates, but they do limit confidence in how comprehensively the results reflect the original analysis plan. They are particularly relevant when interpreting unadjusted p-values, the effect of missing data, and the robustness of conclusions across alternative methods.

15. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: pneumonia (1.1%), transient ischaemic attack (1.1%), ischaemic stroke (1.1%), hepatic steatosis (1.1%), bronchitis (1.1%).

The serious adverse-event figures are counts of affected participants alongside the number at risk in each group. Serious adverse events were recorded in 4 of 87 participants in Teneli 5mg+Met, 4 of 93 in Teneli 10 mg+Met, 3 of 91 in Teneli 20 mg+Met, 5 of 88 in Teneli 40 mg+Met, and 6 of 88 in Placebo+Met. These are descriptive counts; they do not establish that an event was caused by the assigned study treatment.

For other adverse events, the affected-participant counts were 43, 43, 41, 36, and 48 in those same groups, with the corresponding at-risk counts reported as 87, 93, 91, 88, and 88. The registry also lists serious adverse-event terms, each with a reported frequency of 1.1%: pneumonia, transient ischaemic attack, ischaemic stroke, hepatic steatosis, bronchitis, and malignant melanoma. The record does not provide enough detail to determine timing, duration, or individual-level overlap among these terms.

Deaths are not reported in the registry record. These summaries are not a full safety analysis: comparative risk estimates, confidence intervals, event severity details, and causal assessments are not reported. The counts describe what the registry lists and should be interpreted with those reporting limits in mind.

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

The posted primary results describe Week 24 HbA1c changes in four randomized, dose-labelled Teneli-plus-metformin groups and a placebo-plus-metformin group. The active-group least-squares means are more negative than the comparator’s mean change, and the posted unadjusted mean differences are negative. The interval limits and p-values add information about sampling uncertainty and compatibility with a null comparison under the calculations used. Together, these statistics characterize the observed comparisons in this study.

They do not establish that the same estimates would occur in other groups of participants, at other treatment durations, or under different analysis choices. The primary comparison is limited to the reported Week 24 endpoint. Although the study description includes an open-label extension for up to 52 weeks, extension results are not reported in the registry record for these outcomes. The record also does not provide the original sample-size justification or full statistical analysis plan.

The results do not define what size of HbA1c change would be clinically important, because no clinical-importance threshold is reported. Statistical compatibility with a difference and clinical importance are distinct questions. Likewise, the unadjusted p-values do not account for the set of multiple active-dose comparisons, as no multiplicity procedure is reported. The direction of the point estimates should not be treated as a formal dose-response finding; no dose-response test is reported.

The findings also do not answer every safety question. Serious and other adverse-event counts are posted, but deaths are not reported in the registry record, and the available summaries do not provide detailed timing, causal attribution, or comparative uncertainty. The primary endpoint is an efficacy measure and should not be used as a substitute for a complete assessment of safety.

A careful reading therefore distinguishes the numerical observations from broader claims. The record documents adjusted group changes, unadjusted pairwise comparisons, and descriptive event counts. It does not document enough about missingness, multiplicity, or the full analysis plan to remove those uncertainties. The evidence described is specific to this randomized study and the outcomes and time points reported.

17. Why This Trial Matters Statistically

Statistically, this study is informative because it includes four dose groups and a shared placebo-plus-metformin comparator within a randomized parallel-group design. That structure permits comparisons across several dose labels while keeping the background treatment common to all groups. The HbA1c endpoint is adjusted for baseline HbA1c, and the stated model includes centre and treatment. These details help explain what the primary estimates represent.

The results also illustrate why within-group change and between-group comparison are different. Each group has a change from baseline, including the placebo-plus-metformin group. The direct mean differences compare each active group with that comparator and are the more relevant statistics for the randomized add-on comparison. Reading only the active-group changes could obscure the fact that change also occurred in the comparator group.

The study highlights the importance of handling missing values and multiplicity transparently. The registry identifies LOCF for missing Week 24 HbA1c values and gives an intention-to-treat label, but does not report the extent of missingness or sensitivity analyses. It also posts unadjusted p-values for multiple dose comparisons without reporting a multiplicity procedure. These omissions do not erase the observed numerical pattern, but they matter when assessing the robustness and evidential weight of the comparisons.

Finally, the record illustrates how a completed trial’s sample-size planning illustrations differ from its original design justification. The available planning figures are based on observed effects and stated calculation assumptions; they are not evidence of observed power or of the sample-size reasoning used to launch the study. Separating these concepts helps prevent post hoc planning calculations from being mistaken for the trial’s prespecified design.

18. Limitations

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

Several limitations are specific to the reported record. The primary endpoint is available at Week 24, while the official title describes an open-label extension for up to 52 weeks. Extension results are not reported in the registry record for the outcomes, limiting interpretation to the main assessment period. Arm descriptions beyond the treatment labels are also absent, and the record does not explain the use of the name Teneli in the results alongside MP-513 in the study title and intervention descriptions.

The primary analysis description identifies ANCOVA and LOCF but leaves important details unreported. The record does not give the amount or pattern of missing HbA1c data, the number of participants excluded from the analysis, or sensitivity analyses under alternative missing-data assumptions. It does not provide model diagnostics, the confidence level for the comparison intervals, or the method used to calculate those intervals. These gaps make it difficult to assess how dependent the findings are on particular analytic choices.

Multiplicity is another limitation: four active-versus-placebo comparisons are posted with unadjusted p-values, but no correction or testing hierarchy is reported. No dose-response analysis is reported, so the ordered pattern in group means should remain descriptive. The record does not report interim analysis procedures, the original sample-size justification, or a full statistical analysis plan.

For safety, event counts are available, but the registry record does not report deaths, detailed event timing, causal attribution, or comparative uncertainty for the adverse-event summaries. It also does not provide detailed laboratory-test or vital-sign results in the information. These reporting limits constrain the conclusions that can be drawn from the available results.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Efficacy and Safety of MP-513 in Combination With Metformin in Patients With Type 2 Diabetes — NCT00971243.
• Registry record last updated 2026-01-07; status last verified 2025-12.
• Results first posted 2014-09-01.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry record describes a completed, randomized, quadruple-masked, parallel-group Phase II study of MP-513 added to ongoing metformin monotherapy in people with type 2 diabetes. It reports enrollment of 448 and a primary endpoint of HbA1c change from baseline to Week 24. The stated primary method is ANCOVA with centre and treatment as factors and baseline HbA1c as a covariate; missing Week 24 values were handled using last observation carried forward in the intention-to-treat analysis.

Posted group estimates show negative HbA1c changes in all five groups, with negative unadjusted comparisons for each of four dose-labelled Teneli-plus-metformin groups versus placebo plus metformin. Fasting plasma glucose results and adverse-event counts provide secondary context. Multiplicity adjustment, the confidence level for interval limits, missing-data sensitivity analyses, the original sample-size justification, and extension results are not reported in the registry record.