Safety and Efficacy of Linagliptin in Type-2-diabetes Mellitus Patients With Moderate to Severe Renal Impairment: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Safety and Efficacy of Linagliptin in Type-2-diabetes Mellitus Patients With Moderate to Severe Renal Impairment (NCT01087502), a randomized phase 3 study. The primary outcome is HbA1c Change From Baseline to Week 12.

2. Clinical Question

The central comparison is the change in HbA1c over the initial 12-week, placebo-controlled period. HbA1c is reported as a percentage, and change is defined as the week 12 value minus the baseline value. A negative change therefore represents a lower HbA1c at week 12 than at baseline. The registry’s primary result compares the two randomized groups, with adjustment for baseline HbA1c, renal function impairment, and prior use of antidiabetic agents.

The extension addresses a different treatment sequence: participants initially assigned placebo switched to glimepiride, while the linagliptin arm continued treatment. That later period is relevant to the study’s stated longer-term safety objective, but it is not the same placebo comparison as the primary 12-week question. The primary result should therefore be interpreted as a short-term comparison in the defined patient population, rather than as a direct comparison of linagliptin and glimepiride over the full study period.

3. Trial Design

This was a Phase III, randomized, double-blind, placebo-controlled, parallel-group study. The registry lists an enrollment of 241 and identifies type 2 diabetes as the condition. The trial started in 2010-03, reached primary completion in 2012-05, and is recorded as completed. Boehringer Ingelheim is listed as the sponsor.

The study had two treatment periods. For the first 12 weeks, linagliptin 5 mg once daily was compared with placebo. The registry describes the linagliptin arm as receiving 52 weeks of treatment. Participants assigned to placebo switched to glimepiride after the first 12 weeks and received it for 40 weeks. Thus, the placebo group functions as the comparator for the primary short-term analysis, while the extension compares different treatment sequences rather than continuing a placebo-controlled comparison.

Participants were described as drug naive or previously treated, with type 2 diabetes, moderate to severe renal impairment, and insufficient glycaemic control. The registry does not report further detail about the randomization procedure, allocation concealment, or the specific masking procedures. It identifies the study as double-blind, but additional operational details are not reported in the registry record.

The primary analysis population is described as the FAS: randomized patients who received at least one dose of study drug, had a baseline measurement, and had at least one on-treatment HbA1c measurement. Last observation carried forward was used for imputation. The registry record does not report the original sample-size justification or the assumptions used to plan enrollment. The study’s stated objectives included efficacy, safety, and tolerability over the initial 12 weeks, together with longer-term safety in comparison with glimepiride.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: 241 patients were randomised to treatment with linagliptin 5mg (n=118) or placebo/glimepiride (n=123). All randomised patients were treated. For the final analysis, one study site was excluded due to serious non-compliance resulting in 122 patients in the placebo/glimepiride group and 113 patients in the linagliptin group.

Up to Interim Analysis (Week 12)

Reasons for not completing this period:

Up to Final Analysis (Week 52)

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: FAS consisting of all randomised patients who were treated with at least one dose of study drug, had a baseline, and at least 1 on-treatment HbA1c measurement. Last observation carried forward (LOCF) was used as the imputation rule. Results for primary endpoint below are the ones reproduced without patients from the excluded study site.

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 to Week 12, measured over Baseline and week 12.

The primary endpoint is change in HbA1c from baseline to week 12, measured in percentage points. It is calculated as the week 12 HbA1c percentage minus the baseline HbA1c percentage. A negative value indicates a lower measured HbA1c at week 12 than at baseline; it does not, by itself, describe the experience of every participant.

HbA1c is a continuous measure. In general, it is used in clinical research as an indicator of glycaemic status over time, and measuring change allows the comparison to account for where participants started. The registry reports treatment-adjusted means, with adjustment for baseline HbA1c, renal function impairment, and prior use of antidiabetic agents. The primary endpoint description specifies measurements at baseline and week 12.

The analysis population was the FAS, as defined in the registry: randomized participants who took at least one dose, had a baseline measurement, and had at least one on-treatment HbA1c measurement. Missing endpoint data were imputed using last observation carried forward. These choices define which participants contributed to the primary analysis and how an unavailable later measurement was handled. They are important for interpreting the result alongside the estimated group difference and its uncertainty.

7. Results Posted in the Registry

• Linagliptin 5 mg: mean -0.53 versus -0.11 on control; difference -0.42 (95% CI -0.72 to -0.12), standardized effect d = -0.35; z-test p = 0.007.

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.

Fasting Plasma Glucose (FPG) Change From Baseline to 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 5 mg: mean 0.24 versus 9.53 on control; difference -9.29 (95% CI -31.08 to 12.50), standardized effect d = -0.11; z-test p = 0.403.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Linagliptin 5 mg and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists seven secondary outcomes, covering HbA1c over time, fasting plasma glucose, thresholds or degrees of HbA1c lowering, and linagliptin trough concentration. The posted numerical secondary results available in the record include the fasting plasma glucose change from baseline to week 12. Other listed secondary endpoint results are not reported in the registry record. As a result, the overall pattern across all secondary outcomes cannot be assessed fully from the available results.

The week 12 fasting plasma glucose comparison is less conclusive than the primary HbA1c result: its reported ANCOVA interval extends across zero, and the reported p-value is 0.160. The unadjusted re-calculation also does not provide strong evidence of a group difference. This is not necessarily inconsistent with the primary result, because the outcomes measure different aspects of glycaemia and can have different variability and statistical precision. The secondary result should not be treated as a substitute for the primary endpoint.

Secondary outcomes commonly provide supporting or exploratory information, but interpreting many outcomes raises the possibility of finding an apparently notable result by chance. In general, multiplicity adjustments or a prespecified hierarchy can address that issue. The registry record does not report whether multiplicity was controlled or how the secondary endpoints were ranked in the analysis plan. Consequently, unadjusted secondary results carry less weight than the primary analysis for confirmatory interpretation. The absence of reported results for several listed outcomes also limits any claim about whether the secondary findings form a consistent pattern.

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

• HbA1c Change From Baseline Over Time
• Fasting Plasma Glucose (FPG) Change From Baseline to Week 12
• Fasting Plasma Glucose (FPG) Change From Baseline Over Time
• Percentage of Patients With HbA1c <7.0%
• Percentage of Patients With HbA1c <6.5%
• Percentage of Patients Who Have a HbA1c Lowering by at Least 0.5%
• Plasma Concentration of Linagliptin at Trough

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is continuous, so the reported arm summaries are means: -0.11 for placebo and -0.53 for linagliptin 5 mg. The registry also reports a standard error of 0.11 in each arm. A mean describes the group’s average change, while a standard error conveys the estimated uncertainty in that mean. It is not a description of the spread of individual participant outcomes; a standard deviation would address that different question.

What does the adjusted comparison estimate?

The reported method is ANCOVA, or analysis of covariance. In general, ANCOVA estimates a group difference while accounting for selected covariates. The registry identifies baseline HbA1c, renal function impairment, and prior antidiabetic agent use as adjustment factors for the primary endpoint. The sponsor-reported adjusted mean difference is -0.42. It is a comparison of adjusted group means, rather than simply a comparison of two unadjusted means, even though the posted arm means also yield a difference of -0.42.

Adjustment can improve comparability and precision when the model and its assumptions are appropriate. It also means that the estimate and uncertainty depend on the specified model. The registry does not report further details of the ANCOVA model, such as the precise coding of covariates or any additional model diagnostics. Those details are not reported in the registry record and should not be inferred from the result alone.

How should the p-value be read?

In general, a p-value is calculated under a null hypothesis and a statistical model. It describes how unusual data at least as discrepant as those observed would be if that null model were correct. A small p-value can indicate that the data are not readily compatible with the null model, but it is not a measure of effect size, a measure of clinical importance, or the probability that a result is due to chance. The primary ANCOVA result is reported as p < 0.001. The recalculated unadjusted comparison has p = 0.007. These values come from different analyses and should be kept distinct.

The endpoint comparison is a superiority-or-other analysis in the registry. The registry reports the direction, estimate, confidence interval, and p-value, but does not report additional detail about a prespecified decision rule. A p-value should therefore be interpreted together with the estimated difference and interval, not as a stand-alone conclusion.

What does the recalculation add?

The unadjusted re-calculation uses posted summary statistics to estimate a simple between-group difference. It does not have access to participant-level records or the covariate-adjusted ANCOVA model. It is useful as a transparent check on the reported group summaries, but it cannot replace the sponsor’s adjusted analysis. In the primary comparison, the recalculated mean difference is -0.42, matching the reported adjusted estimate at the displayed precision, while the unadjusted p-value differs from the sponsor-reported p-value. Matching point estimates do not make the methods or uncertainty calculations identical.

For a general statistical reason, standard errors, confidence intervals, and p-values may differ when one calculation adjusts for covariates and another does not. The calculations can also rely on different assumptions about variability and model structure. The available summaries support the simple recalculation, but not an independent reproduction of the full ANCOVA.

How does imputation affect the analysis?

The primary analysis uses last observation carried forward (LOCF). In general, this approach fills a missing later measurement with the participant’s last observed value. It can retain participants with incomplete follow-up in an analysis, but it assumes that carrying forward the earlier value is a suitable representation of the missing later value. That assumption may be imperfect if the measure would otherwise change after the last observation.

The registry describes the FAS as randomized participants who received at least one dose, had a baseline HbA1c, and had at least one on-treatment HbA1c measurement. Thus, the analysis population is not described as every randomized participant regardless of measurements. The number of participants with imputed values and the reasons for missing measurements are not reported in the registry record. Alternative missing-data methods and sensitivity analyses are also not reported in the registry record.

What remains unspecified?

The registry record does not report the original statistical analysis plan, the justification for the planned enrollment, whether interim analyses were conducted, or whether the primary result was adjusted for multiple comparisons. The method named for the primary result is ANCOVA, but unreported details should not be filled in by assumption. In general, statistical interpretation depends on prespecification, model choices, and how all planned outcomes are handled; the available record does not establish those details.

11. Confidence Intervals and Precision

The sponsor-reported primary estimate is an adjusted mean difference of -0.42, with a 95% confidence interval from -0.60 to -0.24. In general, a confidence interval expresses the range of estimates compatible with the data and the specified statistical model at the stated confidence level. It communicates uncertainty around an estimate; it is not a range that contains a fixed proportion of individual participant responses.

The reported interval is entirely on the negative side of zero. In the context of this comparison, negative values correspond to a lower adjusted mean change in the linagliptin group than in the placebo group. The interval also conveys that the precise size of the adjusted difference is not known exactly. Its interpretation depends on the ANCOVA model and the analysis population described in the registry.

The unadjusted re-calculation has the same displayed point estimate, -0.42, but uses a different approach. Its confidence interval is not the sponsor’s adjusted interval, and the unadjusted p-value is 0.007 rather than the reported p < 0.001. The sponsor’s confidence interval is the relevant interval for the reported adjusted analysis. Neither interval can address uncertainty from unreported sources such as departures from the analysis assumptions or the handling of missing data.

Precision is distinct from importance. A confidence interval can describe statistical uncertainty in a group difference, but it does not determine whether that difference is important for patients or how an individual will respond. The registry result provides a group-level estimate for the specified population and time point.

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 participants per arm for the continuous outcomes, not total event counts. They are planning illustrations computed from the observed effect, not the trial’s original design calculation. The stated assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. The original trial’s own design assumptions and sample-size justification are not reported in the registry record.

The 80% power column represents the number of participants per arm that the planning calculation estimates would be needed to have an 80% chance of detecting the specified effect under those assumptions, if that effect were the true effect. The 90% column uses a higher target probability of detection and therefore requires more participants per arm for the same assumed effect. These are forward-looking planning quantities, not descriptions of the trial’s actual statistical power.

The rows that use 100%, 75%, and 50% of the observed effect consider progressively smaller target effects. Smaller effects are harder to distinguish from random variation, so they require more participants for the same power target. For the primary HbA1c comparison, the illustrations range from 126 participants per arm for 80% power at 100% of the observed effect to 503 participants per arm at 50% of the observed effect. The corresponding 90% planning figures are 169 and 673 participants per arm. These numbers illustrate how the assumed effect size changes a planning estimate; they are not evidence that the trial had, or lacked, a particular probability of success.

This is not observed power. The calculations use the observed effect as a planning input and do not report the trial’s actual probability of detecting an effect after the study was conducted. The registry does not report the original enrollment rationale, so these illustrations should not be treated as a reconstruction of the trial’s design.

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 = -0.420; pooled standard deviation σ = 1.188.
2. n = 2 × (1.96 + 0.842)² × 1.188² / -0.420² = 125.6, rounded up to 126 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 <- -0.42                      # observed difference in means
sigma <- 1.18782714791898                     # 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(1087502)
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 = 126 (80% power), 169 (90% power)
 75% of observed effect: n per arm = 224 (80% power), 299 (90% power)
 50% of observed effect: n per arm = 503 (80% power), 673 (90% power)
power.t.test: 126.5 
Simulated power at n = 126 per arm: 0.799 (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-reported primary analysis is an ANCOVA estimate of the adjusted mean difference in HbA1c change. It reports a difference of -0.42, a 95% confidence interval from -0.60 to -0.24, and p < 0.001. The re-calculation is a simple unadjusted analysis of the posted group summaries. It also estimates a mean difference of -0.42, with an unadjusted p-value of 0.007.

The matching displayed point estimates do not mean the two analyses are interchangeable. The sponsor’s ANCOVA adjusts for baseline HbA1c, renal function impairment, and prior antidiabetic agent use, as described in the endpoint record. The re-calculation does not reproduce that adjustment and relies only on summary statistics. Differences in methods can produce different uncertainty estimates and p-values even when the rounded point estimates match.

For interpretation of the trial’s primary result, the sponsor-reported adjusted analysis is the relevant analysis. The re-calculation is a secondary statistical check, not a replacement for the analysis described in the registry. The registry does not report enough detail to independently rebuild the ANCOVA from participant-level data, so the sponsor’s full model cannot be reproduced from the posted summaries alone.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies one primary endpoint and lists seven secondary outcomes. It reports the primary comparison and some secondary results, but does not report whether statistical testing across multiple outcomes was adjusted for multiplicity. When many outcomes are tested, the chance of at least one apparently unusual result can increase. In general, multiplicity procedures or a prespecified testing hierarchy can help control that issue. Without a reported approach, secondary p-values should be read cautiously and are less persuasive as confirmatory evidence.

The registry record also does not report whether there were interim analyses, what stopping rules might have applied, or the complete statistical analysis plan. The existence or absence of these procedures cannot be inferred from the results. The original sample-size justification and the trial’s original design assumptions are likewise not reported in the registry record.

Missing data are addressed for the primary endpoint using last observation carried forward. The registry defines the FAS as randomized patients who received at least one dose, had a baseline HbA1c value, and had at least one on-treatment HbA1c measurement. The record does not report the number of participants with missing week 12 values, the amount of imputation, or the reasons for missingness. It also does not report sensitivity analyses using alternative missing-data assumptions.

LOCF is a specific imputation rule, not a guarantee that the carried-forward value equals the unobserved week 12 value. In general, the validity of an imputed result depends on assumptions about why data are missing and how outcomes would have evolved. The available record does not establish those assumptions. The analysis population and imputation method should therefore be considered when judging how broadly the estimate can be interpreted.

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: cardiac failure congestive (4.1%), chest pain (3.3%), pneumonia (2.7%), cellulitis (2.5%), acute myocardial infarction (2.5%).

For serious adverse events, the registry reports 36 affected participants among 122 at risk in the placebo/glimepiride group and 28 among 113 at risk in the linagliptin 5 mg group. For other adverse events, it reports 110 among 122 at risk in the placebo/glimepiride group and 95 among 113 at risk in the linagliptin group. These are participant counts within the listed groups; they are not counts of every event, since one participant may experience more than one event.

The registry lists congestive cardiac failure at 4.1%, chest pain at 3.3%, pneumonia at 2.7%, cellulitis at 2.5%, acute myocardial infarction at 2.5%, and gastroenteritis at 1.8% among the top serious terms. The listed percentages do not, by themselves, establish that an event was caused by a study drug. The registry does not report death counts in the available safety record. These figures describe reported events and should not be interpreted as a complete assessment of comparative safety on their own.

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

The primary result describes an adjusted average difference in HbA1c change between randomized groups during the first 12 weeks. The estimated difference is -0.42, and the 95% confidence interval is from -0.60 to -0.24. In this trial population, the direction of the estimate indicates a lower mean change in the linagliptin arm than in the placebo arm. This is a group-level statistical finding; it does not state that every participant had the same change or response.

The result does not establish effects in patients outside the registry’s stated population, or under treatment schedules not studied. It addresses patients with type 2 diabetes, moderate to severe renal impairment, and insufficient glycaemic control who were drug naive or previously treated. The placebo-controlled comparison applies to the initial 12 weeks. After that, the placebo group switched to glimepiride, so the extension does not continue the original placebo comparison.

The result also does not answer every question about efficacy, safety, or tolerability. The registry lists secondary outcomes, but not all have numerical results reported. A statistically precise group difference is not by itself a measure of practical importance, and the confidence interval does not describe individual outcomes. Safety interpretation requires attention to the reported counts, duration, and study context; event counts alone do not prove causation.

Finally, the primary analysis depends on the defined FAS and the LOCF imputation rule. The record does not report how many values were imputed or whether sensitivity analyses gave similar results. The findings should therefore be understood as the registry-reported analysis for the specified endpoint, time point, and population, not as a universal conclusion about treatment or an individual prediction.

18. Why This Trial Matters Statistically

This trial illustrates why an estimated treatment difference should be read together with its analysis method and uncertainty. The registry reports an ANCOVA-adjusted mean difference and confidence interval for the primary endpoint, while a simple re-calculation from posted summaries gives a different p-value. That contrast shows how adjustment and analytical choices can affect uncertainty calculations even when the displayed point estimate is the same.

It also demonstrates the importance of keeping a short-term controlled comparison separate from a longer extension with a treatment switch. The first 12 weeks provide the placebo comparison described for the primary endpoint. The subsequent period follows a different treatment sequence, so it addresses a distinct question. Time point and comparator are part of the estimand, not incidental details.

For biostatistical interpretation, the record also raises practical questions about analysis populations, imputation, multiplicity, and design assumptions. The primary population has defined eligibility criteria for analysis, and LOCF was used for missing HbA1c measurements. At the same time, several details that would help evaluate robustness, including sensitivity analyses, multiplicity handling, interim analyses, and the original sample-size rationale, are not reported in the registry record.

Finally, planning calculations based on an observed effect can show how sample requirements change when smaller effects are targeted. They do not recreate the original study design or provide observed power. Separating these planning illustrations from the trial’s actual results helps prevent a common interpretive error: treating a post-study calculation as evidence about the probability that the completed trial detected an effect.

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 important design and analysis details unspecified. It does not report the original sample-size justification, the protocol’s design assumptions, whether interim analyses took place, or the complete statistical analysis plan. It also does not report whether adjustment for multiple comparisons was used. These omissions limit assessment of whether the reported analyses match all prespecified objectives and how to weigh secondary findings.

The primary analysis uses LOCF, but the record does not give the number or proportion of participants whose outcome values were imputed, their reasons for missing data, or results from alternative missing-data analyses. Without those details, the robustness of the primary estimate to missing-data assumptions cannot be evaluated from the registry results alone.

The available primary result is an adjusted ANCOVA summary, while the independent re-calculation is unadjusted and based on group-level statistics. Participant-level data and full model details are not reported, so the sponsor’s analysis cannot be independently reconstructed from the posted summaries. The posted results also do not provide individual outcome distributions, which limits assessment of variability in participant responses beyond the reported summary measures.

The study’s placebo comparison is limited to the first 12 weeks. Participants initially assigned placebo switched to glimepiride for the extension, so longer-term findings cannot be interpreted as a continuation of the same placebo-controlled contrast. In addition, numerical results for several listed secondary outcomes are not reported in the registry record. The record reports safety counts, but deaths are not reported, and the listed event terms alone do not establish treatment causation.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Safety and Efficacy of Linagliptin in Type-2-diabetes Mellitus Patients With Moderate to Severe Renal Impairment — NCT01087502.
• Registry record last updated 2014-06-27; status last verified 2014-05.
• Results first posted 2013-10-17.
• 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

NCT01087502 is a completed Phase III randomized, double-blind, parallel-group study sponsored by Boehringer Ingelheim. It enrolled 241 patients with type 2 diabetes and moderate to severe renal impairment. Linagliptin 5 mg once daily was compared with placebo for 12 weeks, followed by a 40-week extension in which placebo participants switched to glimepiride.

The primary endpoint was adjusted mean change in HbA1c from baseline to week 12. The registry reports a mean difference of -0.42, a 95% confidence interval from -0.60 to -0.24, and p < 0.001. The primary analysis used ANCOVA in the defined FAS population and LOCF for imputation. The registry also reports adverse-event counts and some secondary results, while several design and analysis details are not reported in the registry record.