MARLINA - T2D : Efficacy, Safety & Modification of Albuminuria in Type 2 Diabetes Subjects With Renal Disease With LINAgliptin: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for MARLINA - T2D : Efficacy, Safety & Modification of Albuminuria in Type 2 Diabetes Subjects With Renal Disease With LINAgliptin (NCT01792518), a randomized phase 3 study. The primary outcome is HbA1c Change From Baseline After 24 Weeks Double-blind Randomized Treatment.

2. Clinical Question

3. Trial Design

MARLINA was a Phase IIIb, randomized, double-blind, placebo-controlled, parallel-group study sponsored by Boehringer Ingelheim. The registry lists an enrollment of 360. Participants had type 2 diabetes with micro- or macroalbuminuria, with the trial title specifying a UACR range of 30-3000 mg/g creatinine, and were on current treatment with an angiotensin converting enzyme inhibitor or angiotensin receptor blocker.

Participants were assigned to once-daily linagliptin 5 mg or matching placebo. The treatment period relevant to the posted primary outcome was 24 weeks. The primary endpoint was HbA1c change from baseline; the registry describes renal efficacy in terms of albuminuria change and also lists change in estimated glomerular filtration rate as a secondary outcome.

The record lists a study start of 2013-02, primary completion of 2015-11, and status of completed. It identifies the primary analysis population as the Full Analysis Set, consisting of randomized participants who received at least one dose, had baseline HbA1c and UACR, and had at least one on-treatment assessment of HbA1c or UACR. The number analysed varies by outcome in the posted results, so the analyzed counts should be read separately from the enrollment figure.

Details about the randomization sequence, allocation concealment, site-level conduct and the trial’s original sample-size justification are not reported in the registry record. The record identifies masking as double but does not specify which roles or individuals were masked.

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: Randomized, double-blind, placebo controlled, parallel group study to evaluate glycemic and renal efficacy of once daily administration of Linagliptin 5 milligram (mg) for 24 weeks in type 2 diabetes patients, with micro- or macroalbuminuria on top of current treatment with Angiotensin Converting Enzyme inhibitor or Angiotensin Receptor Blocker

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full Analysis Set (FAS) - including all randomised patients who were treated with at least one dose of study drug, had a baseline HbA1c and a baseline Urinary albumin creatinine ratio (UACR), and at least one on treatment HbA1c or UACR assessment. Observed Case (OC): Values after the use of rescue medication were set to missing.

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.

Population: Treated Set (TS) - including all patients treated with at least one dose of randomised trial medication.

6. Primary Endpoint

The registry lists the primary outcome as HbA1c Change From Baseline After 24 Weeks Double-blind Randomized Treatment, measured over Baseline and 24 weeks.

The primary endpoint is change from baseline in glycated haemoglobin, or HbA1c, after 24 weeks of double-blind randomized treatment. HbA1c is a continuous measure of glycemic status, and the trial used it to assess glycemic control. The endpoint is expressed as a percentage of HbA1c; the posted arm estimates are least-squares means rather than simple raw averages.

A change-from-baseline measure compares an individual’s value at the endpoint with their baseline value. In this trial, baseline is defined as the last observation before randomized treatment began. Comparing the groups’ estimated changes addresses whether their average HbA1c trajectories differed over the treatment period, rather than describing either group’s final value alone.

The primary result is an estimate of the between-group difference in change, accompanied by a confidence interval and a p-value in the registry’s reported analysis. These quantities convey the direction and statistical precision of the estimated contrast. HbA1c is only one outcome: the record also lists UACR and eGFR endpoints, which measure different renal-related outcomes and do not replace the primary glycemic endpoint.

The Full Analysis Set definition requires baseline HbA1c and UACR and at least one on-treatment assessment of either measure. The registry’s wording also says analyzed counts reflect participants with available data at the timepoint of interest. More detailed rules for missing observations are not reported in the registry record.

7. Results Posted in the Registry

• Linagliptin 5 mg: mean -0.63 versus -0.03 on control; difference -0.60 (95% CI -0.77 to -0.43), standardized effect d = -0.79; 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.

The Time Weighted Average of Percentage Change From Baseline in UACR During the Course of 24 Weeks of Treatment

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Linagliptin 5 mg: mean 0.89 versus 0.95 on control; difference -0.06 (95% CI -0.15 to 0.03), standardized effect d = -0.14; z-test p = 0.197.
• 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 Change From Baseline in Estimated Glomerular Filtration Rate (eGFR) After 24 Weeks of Treatment

• 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 -4.98 versus -2.35 on control; difference -2.63 (95% CI -7.91 to 2.65), standardized effect d = -0.11; z-test p = 0.329.
• 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 secondary endpoints address renal-related measures rather than the primary glycemic endpoint. Across the sponsor-reported analyses, neither secondary comparison is statistically distinguishable from no difference using the reported confidence intervals and p-values. This overall pattern differs from the primary HbA1c result, whose sponsor-reported interval does not include no difference.

UACR and eGFR are distinct outcomes, and their analyses also use different effect measures: the UACR comparison is expressed as a ratio of adjusted geometric means, while eGFR is expressed as a mean difference. The measures therefore should not be combined into a single estimate or interpreted as duplicate tests of one outcome. The secondary endpoints provide additional information about outcomes specified in the registry, but they do not alter what the primary HbA1c analysis measures.

Secondary results generally carry less inferential weight when the registry does not report how multiplicity was handled. Testing multiple endpoints can increase the chance that at least one result appears notable by chance. Whether the trial used an adjustment, a hierarchical testing strategy or another prespecified approach is not reported in the registry record. Accordingly, the secondary p-values should be read as reported analyses rather than as evidence that a family-wide error rate was controlled.

The secondary confidence intervals remain important: they describe uncertainty and show that the available evidence does not settle the direction or size of either renal contrast. Failure to find a statistically clear difference is not proof of equivalence or absence of an effect. No equivalence margin or noninferiority margin is reported in the registry record, so those interpretations are not supported by the posted results.

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

• The Time Weighted Average of Percentage Change From Baseline in UACR During the Course of 24 Weeks of Treatment
• The Change From Baseline in Estimated Glomerular Filtration Rate (eGFR) After 24 Weeks of Treatment

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is continuous: each participant has an HbA1c value, and the analysis concerns change from baseline. The registry reports least-squares means for each group. A least-squares mean is a model-based estimate of a group mean, potentially adjusted for terms in the statistical model. It is not necessarily identical to the arithmetic average of the observed participant values. The model terms and adjustment variables are not reported in the registry record.

The reported primary comparison uses a mixed models analysis and is expressed as a mean difference in final values. A mean difference keeps the outcome in its original measurement scale, making its direction interpretable against the two group estimates. Here, the comparison is linagliptin relative to placebo. A negative mean difference indicates a lower estimated change in the linagliptin group, given the reported values.

A confidence interval describes a range of values reasonably compatible with the data and analysis assumptions. Its width reflects statistical precision: a narrower interval is more precise than a wider interval, all else equal. When an interval spans no difference, the data do not distinguish clearly between a difference in one direction, no difference and a difference in the other direction under that analysis. A confidence interval does not guarantee that the true value lies inside it, and it does not capture every source of uncertainty, such as limitations in measurement or study conduct.

A p-value measures how inconsistent the observed data are with a specified null hypothesis under the chosen model. Small p-values indicate that the data would be relatively unusual if the null hypothesis and model assumptions held. They are not measures of clinical importance, do not express the probability that the null hypothesis is true, and do not correct automatically for testing multiple outcomes. The registry’s primary p-value is reported by the sponsor; the simple recalculation also gives an unadjusted p-value from the posted summaries.

The recalculated comparisons use the posted group estimates and standard errors to make simple unadjusted contrasts. The posted summaries do not include all individual-level observations or the complete sponsor model, so these calculations cannot reproduce the full analysis. For the primary result, the recalculated mean difference is -0.6 and the unadjusted p-value is <0.001. The recalculated uncertainty is based on an approximate pooled standard deviation derived from the posted standard errors. It is therefore a descriptive cross-check, not a replacement for the reported mixed models analysis.

The registry reports least-squares means for the secondary outcomes as well. The UACR sponsor analysis uses ANCOVA and reports a ratio of adjusted geometric means. A geometric-mean ratio is a relative contrast, unlike the mean difference used for HbA1c and eGFR. These measures should not be treated as interchangeable or read as if they were all on one common scale. The eGFR sponsor analysis uses mixed models and reports a mean difference in final values.

Over-dispersion is a general issue when the variability in observed data exceeds what a model assumes. In such circumstances, standard errors can be too small if the model does not account for the extra variation, making confidence intervals too narrow and p-values too small. The registry does not report a dispersion diagnostic or identify over-dispersion as an issue for these outcomes, so it is not possible to say whether it affected the analyses.

Multiplicity is the statistical concern that testing several outcomes or contrasts can raise the chance of at least one apparently notable result by chance. This is a general explanation, not a claim about the trial’s analysis plan. The registry record does not report a multiplicity adjustment or a prespecified testing hierarchy. The primary outcome is identified, but the status of the secondary tests within any formal error-control strategy is not reported.

The Full Analysis Set includes randomized participants who were treated, had baseline HbA1c and UACR, and had at least one on-treatment HbA1c or UACR assessment. The record says the number analyzed reflects participants with available data at the timepoint of interest. It does not report how missing endpoint observations were handled in the model, whether sensitivity analyses were conducted, or what assumptions were used about missingness. Those details matter because the conclusions depend on the data included and the assumptions used to estimate outcomes that are not observed.

For the sample-size illustrations, the registry’s accompanying assumptions specify a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is expressed as a fraction of the observed effect. These calculations are planning illustrations based on the observed result, not a record of the trial’s original design calculation. The original sample-size assumptions are not reported in the registry record.

11. Confidence Intervals and Precision

The primary sponsor-reported estimate is -0.60, with a 95% confidence interval from -0.78 to -0.43. The interval is entirely negative, which indicates that the reported model estimated a difference in one direction and excludes no difference at the stated confidence level. Its width conveys the precision of that estimate under the model. It does not capture possible uncertainty from unreported design, measurement or analysis choices.

The simple unadjusted recalculation gives a mean difference of -0.6 and an unadjusted p-value of <0.001. Its interval is based on approximate standard deviations inferred from the posted standard errors. Because that interval is not the sponsor’s fitted-model interval, it is best treated as a cross-check rather than as the primary precision statement. The registry’s own reported analysis remains the appropriate reference for the trial’s modeled estimate.

The sponsor-reported UACR ratio of adjusted geometric means is 0.94, with a 95% confidence interval from 0.85 to 1.03. The eGFR mean difference is -2.63, with a 95% confidence interval from -7.95 to 2.68. Each of these secondary intervals includes values consistent with no group difference as well as values in either direction. Their span indicates that the secondary estimates are less conclusive about the direction and size of a between-group contrast than the primary estimate.

Confidence intervals describe precision for the estimand and analysis that produced them; they do not show the range of individual participant outcomes. A confidence interval can be statistically compatible with no difference while also including effects that may matter in context. The registry does not provide a threshold for clinical importance, so statistical precision alone cannot establish whether a given estimate is clinically meaningful.

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, not total events. They use the observed effect as a reference and show illustrations for planning around 100% of that effect, 75% of that effect and 50% of that effect. The assumptions are a two-sided significance level of 0.05, equal allocation between the two arms and a normal approximation. The trial’s original sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the illustrative participants per arm for a design with an 80% chance of detecting the stated effect under the planning assumptions, if that effect and the assumptions were true. The 90% power column gives the corresponding planning number for a 90% chance. These are design concepts, not guarantees about what a future study will find. For the primary observed effect, the posted illustrations are 25 participants per arm for 80% power and 34 participants per arm for 90% power when planning for 100% of the observed effect; the corresponding figures for planning for 75% of the observed effect are 45 and 60, and for 50% are 100 and 134.

Smaller effects are harder to distinguish from random variation, so planning to detect a smaller fraction of an observed effect requires more participants per arm in these illustrations. The same reasoning applies when using the secondary outcomes’ planning figures, although those figures are particularly sensitive to the observed estimate and its variability. These are planning scenarios based on observed data, not observed power, and they should not be read as evidence that the completed trial had a particular probability of detecting an effect.

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 = -0.600; pooled standard deviation σ = 0.755.
2. n = 2 × (1.96 + 0.842)² × 0.755² / -0.600² = 24.9, rounded up to 25 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 <- -0.6                      # observed difference in means
sigma <- 0.755475252501931                     # 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(1792518)
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 = 25 (80% power), 34 (90% power)
 75% of observed effect: n per arm = 45 (80% power), 60 (90% power)
 50% of observed effect: n per arm = 100 (80% power), 134 (90% power)
power.t.test: 25.9 
Simulated power at n = 25 per arm: 0.784 (20000 replicates)

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

14. Analyses Reported by the Sponsor

The registry’s own primary analysis is a mixed models analysis. It reports a mean difference in final values of -0.60, a 95% confidence interval from -0.78 to -0.43, and p < 0.001. The simple recalculation from posted summaries gives a mean difference of -0.6 and an unadjusted p-value of <0.001. Both describe a negative contrast, but they are not identical analyses: the recalculation is unadjusted and uses approximate variability derived from summary standard errors, while the sponsor reports a model-based analysis.

The sponsor’s model-based result should be used as the main reported statistical analysis. The recalculation serves as a transparent check on the direction and broad scale of the primary contrast, not as a reconstruction of the full model or a competing preferred result. The registry marks no discrepancy between these analyses.

For the secondary outcomes, the registry reports ANCOVA for UACR, with a ratio of adjusted geometric means, and mixed models for eGFR, with a mean difference in final values. The recalculations use simple unadjusted comparisons and therefore do not reproduce those sponsor analyses. Differences between the sponsor’s results and the recalculations should be understood in light of the different estimands and methods, rather than treated automatically as errors.

Model specifications, adjustment variables and detailed diagnostics are not reported in the registry record. That limits independent assessment of how the reported estimates depend on modeling choices.

15. Multiplicity, Missing Data and Analysis Populations

The registry identifies HbA1c change from baseline after 24 weeks as the primary endpoint and lists UACR and eGFR as secondary outcomes. It reports analyses and p-values for these outcomes, but a multiplicity adjustment, a testing hierarchy, or another approach to controlling the overall chance of false-positive findings is not reported in the registry record. The secondary p-values should therefore be interpreted as outcome-specific results, not as evidence that a family of tests was controlled at a stated error rate.

The primary analysis population is described as the Full Analysis Set. It includes randomized participants who received at least one dose, had baseline HbA1c and UACR, and had at least one on-treatment HbA1c or UACR assessment. The primary endpoint description also says that the analyzed count reflects participants with available data at the timepoint of interest. These definitions clarify which participants could contribute, but do not fully specify how data were handled after a participant lacked an outcome measurement.

Detailed missing-data methods are not reported in the registry record. It does not specify the assumptions made for missing observations, the methods used to address them, or whether sensitivity analyses were conducted to test the impact of those assumptions. The record’s mention of observed cases does not by itself establish the complete missing-data strategy for every endpoint.

The registry reports different analyzed counts across outcomes. Such variation can reflect endpoint availability and analysis-set requirements; the record does not explain the participant-level reasons for each difference. The original sample-size justification, interim analyses, and detailed statistical analysis plan are also not reported in the registry record. Without those details, it is not possible to assess whether all planned analyses and decision rules are represented by the posted results.

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 (1.1%), septic shock (1.1%), vestibular disorder (1.1%), sudden hearing loss (0.6%), pancreatitis (0.6%).

The registry lists serious adverse events for 8 participants in the placebo group and 17 participants in the linagliptin 5 mg group, with 178 and 182 participants at risk, respectively. It lists other adverse events affecting 27 participants in the placebo group and 39 in the linagliptin 5 mg group, with the same respective at-risk counts. These are descriptive counts from the posted record; they do not establish that the intervention caused or prevented any event. No deaths are recorded in the adverse-event information; death counts are not reported in the registry record.

The serious-event terms listed include Cardiac failure congestive, Septic shock and Vestibular disorder at 1.1% each, and Sudden hearing loss, Pancreatitis and Pancreatitis acute at 0.6% each. The registry record does not provide group attribution for these term percentages in the information, so they should not be assigned to either study arm. The terms are event categories, not necessarily mutually exclusive participant groups.

Adverse-event counts need context, including how events were collected, coded and judged for seriousness or relatedness. Those details and a full account of event timing are not reported in the registry record. These figures alone cannot establish comparative safety or explain the clinical significance of individual events.

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

The primary result describes an estimated difference in HbA1c change over 24 weeks between participants assigned to linagliptin 5 mg once daily and those assigned to matching placebo, on top of current treatment. The sponsor-reported estimate is negative, and its 95% confidence interval does not include no difference. This is evidence of a statistical difference in the measured primary endpoint under the reported model, with uncertainty quantified by the interval.

That finding does not by itself establish the size of a clinically important benefit. The registry record does not specify a threshold for a clinically meaningful HbA1c difference. It also does not establish effects on outcomes not measured in the posted results, long-term outcomes, or every population with type 2 diabetes. The study population had renal disease and was receiving specified current treatment, so its findings should be understood within that context.

The primary result is about HbA1c, not a direct measure of kidney function or clinical renal events. The secondary UACR and eGFR analyses do not show a statistically clear between-group difference in the sponsor-reported results, but their intervals leave uncertainty about the possible effects. Lack of a statistically clear difference does not show that the groups are equivalent, especially without a reported equivalence margin or a plan designed to test equivalence.

The posted adverse-event counts are descriptive. They do not alone establish causality, comparative safety, or the likelihood that an individual will experience an event. A complete benefit-risk assessment would require information beyond these results, including the broader evidence base and clinical context; such judgments are not made by the statistical findings alone.

Overall, the record supports a measured interpretation: a model-based statistical difference was reported for the primary HbA1c endpoint over the study period, while the secondary renal-related outcomes remain inconclusive in the posted analyses. The registry does not report enough detail to resolve all questions about missing data, multiplicity or modeling choices.

18. Why This Trial Matters Statistically

This trial illustrates why the endpoint and estimand matter when interpreting a clinical study. HbA1c was the primary measure, while albuminuria and eGFR addressed separate renal-related questions. A clear statistical result for the primary outcome should not be extended automatically to the secondary outcomes simply because they were measured in the same study population.

It also illustrates the difference between a sponsor-reported model and a simple recalculation from group summaries. The two approaches can serve different purposes: the registry analysis is the stated trial analysis, while an unadjusted recalculation can help readers check the approximate direction and scale of the contrast. A recalculation cannot reproduce unreported model details or substitute for individual-level analysis.

Confidence intervals add information beyond a thresholded p-value. The primary interval is on one side of no difference, whereas the secondary intervals include values in both directions. This makes the uncertainty and contrast between primary and secondary findings more visible than a list of significance labels would.

Finally, the sample-size illustrations show how planning depends on the effect one aims to detect. Smaller target effects require more participants per arm under the stated assumptions. Because the illustrations are based on observed effects rather than the original trial design calculation, they should not be mistaken for evidence about the trial’s planning rationale or observed power.

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 does not report the complete statistical analysis plan, the original sample-size justification, randomization-sequence generation or allocation-concealment procedures. Masking is described as double, but the specific parties masked are not identified. These omissions limit assessment of design implementation and the prespecification of analyses.

Details of the sponsor’s primary mixed model are limited. The model terms, covariates, covariance structure, diagnostics and handling of deviations from assumptions are not reported in the registry record. The simple recalculation is based on posted summary statistics and approximate variability; it cannot resolve those model-specific questions or replace the sponsor’s analysis.

The Full Analysis Set definition and outcome-specific analyzed counts are reported, but detailed missing-data methods are not. The registry does not explain the reasons for unavailable observations, the assumptions used to handle them, or whether sensitivity analyses were performed. Missing-data assumptions can affect estimates and their uncertainty.

The registry lists multiple endpoints, but multiplicity handling is not reported. This makes the secondary p-values less definitive as a family of tests. The study period for the primary result is 24 weeks, and the posted results do not establish longer-term outcomes. The secondary endpoints are measures of albuminuria and eGFR, not a complete account of renal outcomes.

Safety reporting is also limited in the information available: serious and other adverse-event counts are listed, but event attribution, detailed collection methods and complete group-specific descriptions of the serious-event terms are not reported. The record’s adverse-event counts should therefore be treated as descriptive rather than as a full comparative safety analysis.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: MARLINA - T2D : Efficacy, Safety & Modification of Albuminuria in Type 2 Diabetes Subjects With Renal Disease With LINAgliptin — NCT01792518.
• Registry record last updated 2017-03-06; status last verified 2017-01.
• Results first posted 2017-03-06.
• 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

MARLINA (NCT01792518) was a completed Phase IIIb, randomized, double-blind, parallel-group, placebo-controlled study sponsored by Boehringer Ingelheim. The registry lists enrollment of 360 and a study population with type 2 diabetes and micro- or macroalbuminuria, receiving an angiotensin converting enzyme inhibitor or angiotensin receptor blocker. Participants were assigned to once-daily linagliptin 5 mg or matching placebo for the 24-week treatment period.

The primary outcome was change from baseline in HbA1c. The sponsor reported a mean difference of -0.60, with a 95% confidence interval from -0.78 to -0.43 and p < 0.001. The secondary outcomes were UACR and eGFR; their sponsor-reported confidence intervals included no difference. The registry record does not report the original sample-size justification, multiplicity approach or detailed missing-data methods.