Efficacy and Safety of BI 1356 (Linagliptin) Versus Placebo in Type 2 Diabetic Patients With Insufficient Glycemic Control: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety of BI 1356 (Linagliptin) Versus Placebo in Type 2 Diabetic Patients With Insufficient Glycemic Control (NCT00621140), a randomized phase 3 study. The primary outcome is HbA1c Change From Baseline at Week 24.

2. Clinical Question

The trial addressed a comparative question about change in a continuous measure of glycemic control. It was not a comparison with another active treatment. Its primary endpoint was the mean change in HbA1c, expressed in percent, at week 24. Because lower HbA1c change in the linagliptin arm relative to placebo produces a negative difference, the direction of the estimate is interpreted in that context.

The registry record describes the study as randomized, double-blind, parallel-group, and Phase 3. It lists 503 participants enrolled. The reported primary outcome analysis included 163 participants in the placebo group and 333 in the linagliptin group. The record does not explain the relationship between enrollment and the outcome-analysis group counts, so the difference should not be attributed to a particular reason.

The clinical question is limited to the measured outcome and timeframe. It asks about the comparative HbA1c change at week 24 in the defined analysis population; it does not by itself answer questions about longer-term outcomes, comparisons with other medicines, or results in particular patient subgroups. Those details are not reported in the registry record.

3. Trial Design

The registry describes a randomized, double-blind, parallel-group Phase 3 study of linagliptin and placebo. The official title specifies a 24-week treatment period, with linagliptin 5 mg administered orally once daily. Participants assigned to the control group received placebo tablets matching the linagliptin tablets. The study was completed, and the registry lists 503 participants enrolled.

The intended population included people with type 2 diabetes and insufficient glycemic control who were drug-naive or previously treated. For previously treated participants, the official title specifies a 6-week washout. Further eligibility details, such as age limits, baseline disease characteristics, and the allowed range of prior treatments, are not reported in the registry record.

Random allocation is intended, in general, to reduce systematic differences between groups at the start of a trial. Double masking means the registry records masking of two parties, but it does not identify those parties in the information available. A parallel-group design assigns participants to a group whose treatment is followed over the study period, rather than switching the same participants between treatments.

The primary outcome population was the Full Analysis Set. It included participants who were treated and randomized and who had a baseline and at least one on-treatment HbA1c measurement available. The primary outcome used last observation carried forward for imputation. The outcome group counts reported for the comparison were 163 for placebo and 333 for linagliptin; the registry does not state why these differ from the enrollment figure.

The registry record does not report the original sample-size justification, the allocation ratio planned for the trial, the randomization method, or details of any interim analyses. Planning assumptions calculated from the observed result are separate illustrations and should not be read as the study’s original design assumptions.

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: The Full Analysis Set (FAS) included all treated and randomised patients with a baseline and at least one on-treatment HbA1c measurement available. Last observation carried forward (LOCF) was used as the imputation rule.

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 HbA1c Change From Baseline at Week 24, measured over Baseline and week 24.

The primary endpoint was change in HbA1c from baseline to week 24, measured in percent. As specified in the registry, this change is the week 24 HbA1c percentage minus the baseline HbA1c percentage. HbA1c reflects average blood glucose over time and is commonly used in diabetes trials as a continuous measure of glycemic control. That general context explains why it is a useful trial outcome; it does not establish what an individual participant’s result means clinically.

The registry reports treatment-adjusted means, adjusted for baseline HbA1c and previous anti-diabetic medication. The posted mean change was 0.25 in the placebo group and -0.44 in the linagliptin group. The reported sponsor analysis estimated a mean difference of -0.69 for linagliptin compared with placebo. A negative difference indicates that the recorded mean change was lower in the linagliptin group than in the placebo group.

The endpoint focuses on an average change in a laboratory measure at a specified follow-up time. It does not directly measure symptoms, quality of life, complications, or individual responses. The registry record does not report a threshold for interpreting the clinical importance of a particular HbA1c difference. The analysis population and use of last observation carried forward also matter when interpreting this average, because the estimate depends on which measurements were included and how missing follow-up values were handled.

7. Results Posted in the Registry

• Linagliptin: mean -0.44 versus 0.25 on control; difference -0.69 (95% CI -0.86 to -0.52), standardized effect d = -0.76; 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.

HbA1c Change From Baseline at Week 6

• 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:
  • Linagliptin: mean -0.37 versus 0.09 on control; difference -0.46 (95% CI -0.59 to -0.33), standardized effect d = -0.66; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Linagliptin than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

HbA1c Change From Baseline at Week 12

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Linagliptin: mean -0.46 versus 0.16 on control; difference -0.62 (95% CI -0.76 to -0.48), standardized effect d = -0.84; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Linagliptin than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

HbA1c Change From Baseline at Week 18

• 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:
  • Linagliptin: mean -0.45 versus 0.21 on control; difference -0.66 (95% CI -0.83 to -0.49), standardized effect d = -0.73; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Linagliptin than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The numeric secondary HbA1c results at weeks 6, 12, and 18 follow the same broad direction as the primary week 24 result: the reported mean change was lower in the linagliptin group than in the placebo group at each listed time. This pattern is consistent with the primary comparison across the reported follow-up times. The individual secondary estimates and their intervals are available with the corresponding results, so repeating them would add little to the overall interpretation.

The registry also lists fasting plasma glucose change at several follow-up times and the percentage of participants with HbA1c below 7.0% at week 24 as secondary outcomes. Their result values are not reported in the registry record. Their inclusion as outcome names does not establish the direction or size of any treatment difference. The record lists 13 secondary outcomes posted, but the detailed numerical information in this record covers the three HbA1c change outcomes.

Secondary outcomes can help describe whether the primary finding is accompanied by a broader pattern across related measures and time points. However, when several outcomes and time points are examined, the chance of observing apparently notable results by chance can increase. Unless the statistical plan accounts for this multiplicity, individual secondary p-values are generally less conclusive than a primary result designated for the main question. Adjustment for multiplicity is not reported in the registry record.

These secondary results should therefore be read as supportive context rather than as independent proof of an effect. Their interpretation also depends on the analysis population, missing-data handling, and the prespecified status of each outcome, details that are not reported for all secondary analyses. Outcomes without posted numerical results cannot be used to infer either benefit or no difference.

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

• HbA1c Change From Baseline at Week 6
• HbA1c Change From Baseline at Week 12
• HbA1c Change From Baseline at Week 18
• FPG Change From Baseline at Week 24
• FPG Change From Baseline at Week 6
• FPG Change From Baseline at Week 12
• FPG Change From Baseline at Week 18
• Percentage of Patients With HbA1c <7.0% at Week 24

9. Statistical Interpretation

10. Statistical Methods Explained

Several features of the analysis shape how the primary result should be read. The registry describes treatment-adjusted group means, a Full Analysis Set, last observation carried forward, and a sponsor-reported ANCOVA comparison. The simple recalculation based on posted summary statistics is useful as a check on the arithmetic of the group-level contrast, but it is not the same analysis as the sponsor’s adjusted model.

What does an adjusted mean represent?

The primary outcome description says that the reported means were adjusted for baseline HbA1c and previous anti-diabetic medication. In general, adjustment uses a statistical model to account for specified characteristics when estimating a group comparison. ANCOVA, or analysis of covariance, is a general method for comparing outcomes between groups while accounting for covariates. Here, the registry identifies the sponsor’s method as ANCOVA and reports a mean difference in final values. The full model specification, including any additional terms or diagnostic checks, is not reported in the registry record.

Adjustment is not the same as randomization. Randomization is a design feature intended to create comparable groups on average, while adjustment is an analytic step that accounts for selected variables in the model. The posted description identifies baseline HbA1c and previous anti-diabetic medication for adjustment of the primary means. It does not describe whether other covariates were included.

What does the Full Analysis Set include?

The registry defines the Full Analysis Set as participants who were treated and randomized and had both a baseline and at least one on-treatment HbA1c measurement. This definition clarifies who could contribute to the primary analysis. It is not equivalent to saying that every randomized participant contributed a week 24 measurement. The reported analysis uses last observation carried forward to impute missing outcome values, but the extent of missingness and the timing of the last available measurements are not reported in the registry record.

In general, last observation carried forward fills a missing later value with the participant’s most recent available observation. This method can preserve an analysis set when follow-up measurements are unavailable, but it assumes that the last observed value is an appropriate stand-in for the missing value. That assumption may not match how outcomes would have changed over time. The registry does not report sensitivity analyses comparing this imputation with other missing-data methods, so the robustness of the primary estimate to that choice cannot be assessed from the record.

How should the p-value be understood?

The sponsor reports p < 0.001 for the primary ANCOVA comparison. In general, a p-value describes how incompatible the observed data are with a specified null model, assuming the analysis model and its assumptions hold. It does not give the probability that the treatment has no effect, and it does not quantify clinical importance. The unadjusted recalculation reports p < 0.001. The two values come from different analyses; the adjusted sponsor analysis should be used as the primary inferential result.

Statistical significance is also distinct from precision. The confidence interval describes uncertainty around the estimated difference, while the p-value addresses compatibility with a null comparison. A result can have a small p-value without establishing that the effect matters to patients or will persist over a longer period. The registry record does not provide a clinical-importance threshold for interpreting the primary difference.

Why can the recalculation differ in method?

The recalculation is a simple, unadjusted comparison derived from posted group summary statistics. It provides a transparent check of the mean difference and an approximate inferential summary from those aggregate values. It does not use participant-level data and cannot reproduce an adjusted ANCOVA model, the model’s covariates, or any details not contained in the summary statistics. The sponsor’s reported estimate and interval therefore remain the main basis for interpreting the trial’s primary result.

The group-level standard errors describe uncertainty around the reported means, not the spread of individual participant measurements. General statistical interpretation distinguishes a standard error from a standard deviation: the standard error concerns the precision of an estimated mean, while a standard deviation describes variation among observations. A standard error should not be read as the typical range of individual HbA1c changes.

What does the planning illustration assume?

In general, sample-size planning asks how many participants a future study would need under specified assumptions to have a chosen chance of detecting an effect of interest. The planning illustrations use a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. They use the observed effect or a stated fraction of it as the effect to detect. These are illustrative assumptions based on the observed result, not the trial’s original design plan.

The 80% and 90% power columns describe planning targets: under the stated assumptions, a study of the indicated size would have the corresponding probability of detecting the chosen effect if that effect and the other assumptions were correct. They do not describe the probability that the observed trial result is true. For a continuous outcome such as this one, the numbers are participants per arm, not total events. Smaller effects require more participants under otherwise identical planning assumptions. The original protocol’s sample-size assumptions and justification are not reported in the registry record.

11. Confidence Intervals and Precision

The sponsor’s primary ANCOVA estimate is a mean difference of -0.69, with a 95% confidence interval from -0.85 to -0.53. In general, a confidence interval expresses uncertainty around an estimate under the analysis model: repeated use of the same procedure under its assumptions would produce intervals with the stated coverage in the long run. It is not a range containing a fixed proportion of individual participants’ outcomes, and it is not a probability statement about this particular interval.

The interval lies on the negative side of zero, so the sponsor’s analysis is consistent with a negative mean difference between groups. The width of an interval is one way to assess precision: narrower intervals indicate less statistical uncertainty than wider intervals, all else equal. The interval does not by itself address bias, the validity of the missing-data assumptions, or whether the size of the difference is clinically important.

The recalculated unadjusted comparison is based on posted summary statistics and is not a replacement for the sponsor’s adjusted ANCOVA. Its estimate is -0.69 and its unadjusted p-value is <0.001. Although the point estimate is the same as the sponsor’s reported estimate, the recalculation uses a different method and should not be treated as a second independent confirmation. The sponsor’s interval and p-value are the relevant reported inferential results.

The registry reports standard errors for the group means, but does not provide the underlying participant-level distributions in this record. Consequently, the uncertainty around the average does not show how much individual responses varied. The reported confidence interval also reflects sampling uncertainty under the model, not every possible source of uncertainty in trial conduct, measurement, or generalization.

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 planning figures are illustrative estimates for a future two-arm comparison using the observed primary effect as a reference. For this continuous outcome, the counts are participants per arm, not total events. The assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the observed effect or a stated fraction of it. The trial’s own original sample-size justification and design assumptions are not reported in the registry record.

The 80% power column gives the number of participants per arm associated with an 80% chance of detecting the chosen effect under the planning assumptions, if that effect and those assumptions hold. The 90% power column uses a higher target probability of detection, and therefore generally calls for more participants per arm for the same effect. For example, planning for 75% of the observed effect gives 49 participants per arm for 80% power and 65 participants per arm for 90% power. Planning for 50% of the observed effect gives 109 participants per arm for 80% power and 146 participants per arm for 90% power.

Smaller effects are harder to distinguish from random variation, so detecting a smaller effect requires more participants when the other assumptions remain unchanged. These figures are planning illustrations based on the observed result, not observed power for the completed trial. They should not be read as the number of participants actually needed to establish a clinical benefit or as a post hoc measure of how convincing the trial result is.

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 = -0.690; pooled standard deviation σ = 0.906.
2. n = 2 × (1.96 + 0.842)² × 0.906² / -0.690² = 27.1, rounded up to 28 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 <- -0.69                      # observed difference in means
sigma <- 0.906319915633373                     # 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(621140)
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 = 28 (80% power), 37 (90% power)
 75% of observed effect: n per arm = 49 (80% power), 65 (90% power)
 50% of observed effect: n per arm = 109 (80% power), 146 (90% power)
power.t.test: 28.1 
Simulated power at n = 28 per arm: 0.798 (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 sponsor’s primary analysis is reported as an ANCOVA comparison of final values. It estimates a mean difference of -0.69 for linagliptin compared with placebo, with a 95% confidence interval from -0.85 to -0.53 and p < 0.001. This is the trial’s reported adjusted analysis and should be the main reference for the primary result.

A separate recalculation from the posted group summary statistics estimates the same mean difference, -0.69, and gives an unadjusted p-value of <0.001. It is a simple unadjusted calculation, not a reproduction of the sponsor’s ANCOVA. It cannot account for the model’s adjustment for baseline HbA1c and previous anti-diabetic medication or other details that may depend on participant-level data.

The matching point estimate is a useful arithmetic check, but the sponsor’s method remains the more appropriate interpretation of the reported primary analysis. Differences between the two p-value formats reflect that they come from different analyses and are reported at different thresholds. The registry record does not identify a discrepancy for the primary result. The recalculation should therefore be treated as supplementary, not as a correction to the sponsor’s analysis.

15. Multiplicity, Missing Data and Analysis Populations

The primary outcome is clearly identified as HbA1c change from baseline at week 24. The record also lists multiple secondary outcomes, including HbA1c and fasting plasma glucose measurements at several follow-up times and the proportion with HbA1c below 7.0% at week 24. Examining multiple outcomes or time points creates a multiplicity issue: in general, the more comparisons made, the greater the chance that one may appear statistically notable by chance even if no underlying difference exists.

The registry record does not report whether the analysis plan used a multiplicity adjustment, a hierarchical testing procedure, or another method to control the overall chance of false-positive findings across secondary comparisons. It also does not provide enough detail to establish which secondary analyses were confirmatory and which were exploratory. The secondary findings should consequently be interpreted with more caution than the designated primary analysis.

The primary analysis population was the Full Analysis Set, defined as treated and randomized participants with a baseline and at least one on-treatment HbA1c measurement. Last observation carried forward was used as the imputation rule for the primary endpoint. In general, missing-data methods make assumptions about values that were not observed; carrying the last value forward assumes it is a reasonable substitute for a later missing measurement. The registry does not report the number or timing of missing measurements, reasons for missingness, or sensitivity analyses under alternative assumptions.

The record does not report details of any interim analyses, the original statistical analysis plan, or how deviations from that plan were handled. It also does not report the full analysis-population definitions for each secondary outcome. These omissions limit assessment of the prespecification and robustness of the analyses. They do not negate the reported primary estimate, but they define what can be concluded from the registry record alone.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: breast cancer (1.2%), atrial fibrillation (0.6%), coronary artery disease (0.6%), foot fracture (0.6%), rib fracture (0.6%).

The safety summary reports serious adverse events in 7 of 167 participants at risk in the placebo group and 10 of 336 participants at risk in the linagliptin group. For other adverse events, it reports 38 of 167 participants at risk in the placebo group and 29 of 336 participants at risk in the linagliptin group. These figures are counts with the listed at-risk denominators; they are not an adjusted comparison, and the record does not provide a statistical test for these group differences.

The registry lists breast cancer at 1.2%, and atrial fibrillation, coronary artery disease, foot fracture, rib fracture, and road traffic accident at 0.6% each among the top serious adverse event terms. The record does not provide enough detail to infer whether any event was caused by treatment, how events were distributed over time, or how severity and relatedness were assessed. The meaning of the category of other adverse events is not further specified in the record.

Deaths are not reported in the registry record. These summaries provide descriptive safety information for the recorded study period; they do not establish comparative safety beyond the listed data or predict risks for an individual.

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

The primary result shows a reported difference in mean HbA1c change between the randomized groups at week 24. The sponsor’s adjusted estimate was -0.69 for linagliptin compared with placebo, with a 95% confidence interval from -0.85 to -0.53. The interval is entirely negative, and the sponsor reported p < 0.001. This supports a statistical difference in the direction of lower mean HbA1c change in the linagliptin group in the analyzed population.

The result does not, on its own, establish the clinical importance of that difference. The registry record does not report a threshold defining a clinically meaningful difference for this endpoint. Nor does a group average describe every participant’s response. Some people may have had changes unlike the group mean, but individual-level distributions are not reported.

The comparison is against placebo, not against another active treatment. The study followed participants over 24 weeks, so the posted result does not establish whether the observed difference would persist beyond that period. It also does not answer questions about long-term complications, quality of life, or outcomes that were not reported numerically. The listed secondary outcome names for fasting plasma glucose and reaching HbA1c below 7.0% cannot be interpreted without their results.

Interpretation also depends on the analysis population and handling of missing values. The primary analysis included treated and randomized participants with a baseline and at least one on-treatment HbA1c measurement, using last observation carried forward. The missing-data extent and sensitivity of the estimate to alternative methods are not reported in the registry record.

Thus, the statistical conclusion is bounded: the posted sponsor analysis supports a difference in mean HbA1c change between these groups under the stated analysis. It does not establish an individual outcome, a long-term effect, a comparison with other treatments, or a treatment recommendation.

18. Why This Trial Matters Statistically

This trial is statistically informative because it reports a defined continuous primary endpoint, adjusted group means, and a sponsor analysis with an estimate, confidence interval, and p-value. Those elements let readers consider both the direction and magnitude of the group difference, as well as its uncertainty, rather than relying on a significance label alone.

The distinction between the sponsor’s adjusted analysis and a simple recalculation is also important. The recalculation from group summaries can check the mean contrast, but it does not reproduce ANCOVA or adjustments for baseline HbA1c and previous anti-diabetic medication. Recognizing the estimand and model behind a result helps prevent an unadjusted summary from being mistaken for the primary analysis.

The record also makes clear why a result’s statistical precision is only one part of interpretation. A confidence interval addresses sampling uncertainty under the model, while missing-data assumptions, multiplicity, analysis-population definitions, and clinical importance raise separate questions. Here, the primary outcome used last observation carried forward, while details about missingness and multiplicity are not reported in the registry record.

Finally, the planning illustrations show how sample-size requirements depend on the effect a future study aims to detect. They use explicit assumptions and fractions of the observed effect, and are not the original trial’s design justification or observed power. Keeping planning calculations separate from trial results is essential for sound statistical interpretation.

19. Limitations

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

The registry record leaves several trial-specific details unavailable. It does not report the original sample-size justification, randomization procedure, detailed eligibility criteria, participant characteristics, or the full statistical analysis plan. Without those details, it is not possible to assess the planned allocation process, the representativeness of the participants, or whether all analytic choices were prespecified.

The primary outcome uses last observation carried forward, but the amount and pattern of missing HbA1c measurements are not reported. The record does not include sensitivity analyses using alternative missing-data methods, so it is not possible to determine from the registry alone how robust the estimate is to the imputation assumption. The relationship between the enrollment figure and the reported outcome-analysis group counts is also not explained.

The follow-up for the primary outcome is week 24. Longer-term results are not reported in this record. The comparison is with placebo, and no active comparator is described. Numerical results for some listed secondary outcomes, including fasting plasma glucose measures and the proportion with HbA1c below 7.0% at week 24, are not reported in the registry record.

Safety information is presented as counts with at-risk denominators and a list of serious adverse event terms. Deaths are not reported in the registry record, and details about event definitions, relatedness, severity, and timing are not included. These limits mean the safety summary cannot establish causation or provide a complete account of risk.

Multiplicity handling and interim analyses are not reported. These gaps do not change the posted primary estimate, but they constrain evaluation of the secondary findings and the full analytic process.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy and Safety of BI 1356 (Linagliptin) Versus Placebo in Type 2 Diabetic Patients With Insufficient Glycemic Control — NCT00621140.
• Registry record last updated 2014-02-17; status last verified 2014-01.
• Results first posted 2011-06-07.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

This completed Phase 3 study randomized participants with type 2 diabetes and insufficient glycemic control to linagliptin 5 mg once daily or matching placebo over 24 weeks. The primary endpoint was HbA1c change from baseline at week 24, analyzed in the Full Analysis Set with last observation carried forward.

The sponsor’s ANCOVA analysis reported a mean difference of -0.69, with a 95% confidence interval from -0.85 to -0.53 and p < 0.001. This is a group-level result for the recorded endpoint and analysis population. The registry also reports secondary HbA1c results at earlier time points and descriptive adverse-event counts.

Details about the original sample-size justification, multiplicity methods, missing-data extent, and deaths are not reported in the registry record. The planning illustrations are not the trial’s original design assumptions or observed power.