DIA_CENTRAL:T2D Treatment Pattern in Central Europe: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for DIA_CENTRAL:T2D Treatment Pattern in Central Europe (NCT03807440), a registered phase not stated study. The primary outcome is Number of Patients in Each Category of First Prescription of a Respective Modern Type 2 Diabetes (T2D) Medication According to Prescribing Specialist.

2. Clinical Question

3. Trial Design

This record describes CORDIALLY® - CEE, a non-interventional study of treatment patterns and patient characteristics among people with type 2 diabetes in Central Eastern European countries. It used existing data, including medical chart review. The registry lists Boehringer Ingelheim as the sponsor, gives a study start date of 2019-08-26, a primary completion date of 2021-08-31, and a completed status. Enrollment is reported as 4083.

The primary outcome is a count of patients in each category of first prescription of a respective modern type 2 diabetes medication, classified according to prescribing specialist. The outcome timeframe is at study index date 1, stated as between September 2018 and December 2018. The primary population is the prescribed patient set, defined as patients meeting inclusion and exclusion criteria who received a first prescription of a respective type 2 diabetes medication and had documentation electronically signed by the physician.

The registry lists medication types including empagliflozin, sodium glucose transporter 2 inhibitors, dipeptidyl-peptidase 4 inhibitors, and glucagon-like peptide 1 agonists. The listed secondary outcomes concern cardiovascular disease, chronic kidney disease, documentation of estimated glomerular filtration rate and urine albumin creatinine ratio status, and categories of cardiovascular disease and congestive heart failure. These are observational descriptions, not evidence that investigators assigned medication or specialist groups. The registry states that allocation was not stated and that the arms are not a like-for-like control comparison. Details of recruitment procedures, country-specific enrollment, follow-up beyond the stated outcome timeframe, and the statistical analysis plan are not reported in the registry record.

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: Only subjects that met all inclusion and none of the exclusion criteria were included. 4083 patients were screened, thereof 28 could not be included in the prescribed patient set (PPS).

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Prescribed patient set (PPS): All patients fulfilling inclusion and exclusion criteria who have received a first prescription of a respective T2D medication and whose documentation was electronically signed by the physician.

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: Prescribed patient set (PPS): All patients fulfilling inclusion and exclusion criteria who have received a first prescription of a respective Type 2 Diabetes (T2D) medication and whose documentation was electronically signed by the physician.

6. Primary Endpoint

The registry lists the primary outcome as Number of Patients in Each Category of First Prescription of a Respective Modern Type 2 Diabetes (T2D) Medication According to Prescribing Specialist, measured over At study index date 1 (i.e. between September 2018 and December 2018)..

The primary endpoint is a count: the number of patients in each category of first prescription of a respective modern type 2 diabetes medication, classified by prescribing specialist. The stated timeframe is at study index date 1, between September 2018 and December 2018. The outcome description identifies the prescribed patient set as the population for this measure, with eligibility, first-prescription, and electronically signed documentation conditions.

Counts are useful for describing how recorded prescriptions are distributed across categories. They can show which medication and prescribing-specialist categories are represented in the study data. A count is not itself a measure of treatment effect. It does not show whether a medication caused a clinical outcome, whether one prescribing approach was better, or whether the observed prescribing pattern was appropriate. Those questions would require other evidence and a design suited to the comparison.

The registry record does not report the category-specific primary outcome counts, nor does it report the corresponding denominators in the primary outcome description. Consequently, the endpoint’s definition and timeframe can be described, but its numerical results cannot be interpreted from the registry record. The enrollment figure does not substitute for category-specific results or establish how many patients contributed to each analysis.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry describes a non-interventional study using existing data, including medical chart review. The primary outcome is a count of patients in categories of first prescription, classified according to prescribing specialist. Understanding what that measure can say begins with distinguishing a count from a rate, a comparison, or a causal effect. General statistical explanation: a count records how many observations fall into a defined category. A rate or proportion additionally requires a clearly defined denominator. A causal effect requires a design and assumptions that support attributing outcome differences to an exposure rather than to other differences between groups.

What does the primary count represent?

The outcome description specifies the prescribed patient set: patients meeting inclusion and exclusion criteria, receiving a first prescription of a respective type 2 diabetes medication, and having documentation electronically signed by the physician. It also specifies the index-date timeframe as between September 2018 and December 2018. A category count would describe the records meeting those conditions and assigned to that category. It would not automatically represent all people with type 2 diabetes in the region, all patients treated with the medications, or all prescriptions outside the specified study conditions.

The registry reports enrollment of 4083, but enrollment and an analysis denominator are not interchangeable. General statistical explanation: an analysis denominator is the number of observations with the eligibility and information needed for a specific analysis. It can differ across outcomes when records are incomplete or when outcome definitions require different measurements. The primary outcome description does not report category counts or category-specific denominators, so those quantities cannot be reconstructed from the enrollment figure.

Why does study design matter?

Because the study uses existing data and is non-interventional, medication and specialist categories are observed rather than assigned by the study. General statistical explanation: randomized assignment can help balance measured and unmeasured characteristics across treatment groups, on average. In observational data, the groups being compared may differ in their characteristics or clinical circumstances before the recorded prescription. Those differences can influence both treatment selection and recorded outcomes. A comparison of observational categories therefore describes recorded patterns unless additional design and analysis details support stronger conclusions.

The registry’s skip note states that allocation was not stated and that the arms are not a like-for-like control comparison. This is a direct caution against reading the recorded groups as equivalent trial arms. The record does not describe an adjustment strategy that would address differences between groups, so no claim about an adjusted contrast is warranted. The statistical analysis plan is not reported in the registry record.

How should categorical outcomes be read?

The primary measure and many listed secondary outcomes are counts of patients in categories. General statistical explanation: category counts are easiest to interpret when the category definitions are clear and the population at risk of being counted is known. If categories are not mutually exclusive, a patient may contribute to more than one category; if they are mutually exclusive, each patient is assigned to a single category. Whether the primary prescription categories are mutually exclusive is not reported in the registry record. The same care is needed when reading cardiovascular and kidney-disease measures, which are defined in several different ways.

The secondary outcomes include cardiovascular disease, chronic kidney disease by physician assessment, documentation of estimated glomerular filtration rate or urine albumin creatinine ratio status, and chronic kidney disease based on those measures. These are not necessarily interchangeable definitions. General statistical explanation: using different definitions can produce different counts because each definition captures a different aspect of the clinical record. The registry record does not report the results needed to compare these definitions or evaluate their agreement.

What does precision mean?

General statistical explanation: a confidence interval describes a range of values compatible with data and a specified statistical model, and its width conveys uncertainty. A count by itself does not show precision; interpretation generally also depends on the denominator, the sampling or data-collection process, and the analysis method. Confidence intervals or other uncertainty estimates for the primary endpoint are not reported in the registry record. The numerical category counts are also not reported, so neither their magnitude nor their precision can be assessed from the record.

The registry lists 70 outcome measures and 57 analyses. When many outcomes or analyses are examined, the chance of finding apparently noteworthy patterns can increase, even when no real pattern exists. General statistical explanation: multiplicity methods can control or describe this issue, but the appropriate approach depends on which outcomes are confirmatory and how tests are structured. A multiplicity strategy is not reported in the registry record. No claim about correction, prespecification, or selective reporting can therefore be made.

What do the sample-size calculations mean?

The sample-size assumptions describe planning illustrations computed from an observed effect, using a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect to detect is described as a stated fraction of the observed effect. For time-to-event calculations, the stated quantity is the total number of events; for other calculations, it is participants per arm. These assumptions describe illustrative calculations, not the study’s own design. The record does not establish that the observational study had equal allocation or randomized arms, and its note warns that the arms are not a like-for-like control comparison. Such calculations are not observed power and should not be treated as evidence that the study was designed or powered to detect a treatment effect.

The observed effect estimates and resulting sample-size values are not reported in the registry record. No calculation should be inferred from the assumptions alone. More broadly, the record does not report the analysis methods needed to reproduce outcome estimates, such as handling of incomplete records, adjustment for differences between groups, or uncertainty estimation. Those omissions limit how much can be concluded about the statistical strength of any result.

10. Multiplicity, Missing Data and Analysis Populations

The registry lists 70 outcome measures and 57 analyses, covering prescribing patterns and a range of cardiovascular and kidney-related outcomes. When many outcomes are assessed, some findings can appear noteworthy by chance. General statistical explanation: multiplicity methods may be used to control the overall false-positive risk or to distinguish confirmatory outcomes from exploratory analyses. The registry record does not report whether any multiplicity adjustment was planned or applied, which results were considered primary beyond the named primary outcome, or how analyses were selected for reporting.

Missing-data handling is also not reported in the registry record. The primary outcome definition requires a first prescription and electronically signed documentation, while several secondary outcomes depend on specific clinical assessments or recorded laboratory status. The record does not describe how patients with absent, incomplete, or unusable information were treated, or whether missingness was assessed. General statistical explanation: if information is missing, the analyzed population may differ from the intended population, and the impact depends on why records are missing and how analysis handles them.

The primary population is defined as the prescribed patient set meeting inclusion and exclusion criteria and the stated prescription and documentation conditions. The registry does not report analysis-specific population counts or denominators. It also does not report whether the listed secondary analyses used the same population. These details matter because outcome counts can only be understood in relation to the patients eligible and observed for each analysis. The record’s enrollment figure should not be assumed to be the denominator for every outcome.

Details of a statistical analysis plan, multiplicity handling, missing-data methods, and analysis-specific denominators are not reported in the registry record. As a result, readers cannot use the record to assess how these issues were addressed or to evaluate their effect on reported estimates.

11. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Serious events with the highest arm-level rate: dysuria (0.3%), genital infection (0.2%), balanoposthitis (0.2%), urinary tract infection (0.1%), vulvovaginitis (0.1%).

The registry lists one group, titled T2D Patients From Central Eastern Europe, with 4055 participants at risk and 43 participants affected by serious adverse events. It records 0 other adverse events and 0 deaths for this group. These figures describe the entries in the registry record; they do not establish that every possible event was detected or recorded, or that the listed events were caused by a medication.

The serious-event terms listed include dysuria at 0.3%, genital infection at 0.2%, balanoposthitis at 0.2%, urinary tract infection at 0.1%, vulvovaginitis at 0.1%, and pollakiuria at 0.1%. The registry record does not provide additional detail in the registry record about event ascertainment, how these percentages were calculated, or the relationship between each term and the overall serious-event count. The listed terms should therefore be read as reported entries, not as a complete event profile or a comparative risk estimate.

There is no like-for-like control comparison in the record: allocation is not stated, and the arms are explicitly described as not being comparable control groups. The safety figures cannot establish whether one medication or prescribing category has a different risk from another. They also do not support a conclusion about safety beyond the events and reporting context recorded.

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

The registry record identifies a descriptive question about first prescriptions of modern type 2 diabetes medications and how those prescriptions were categorized by prescribing specialist. It also lists secondary descriptions of cardiovascular disease, chronic kidney disease, and related documentation. The study is reported as non-interventional and based on existing data, including medical chart review. These features define the kind of evidence the record describes: patterns in recorded clinical information, rather than results from treatment assignment.

The primary outcome counts are not reported in the registry record. Therefore, the available information does not show the number of patients in any prescription category, which category was most frequent, or how the recorded pattern varied by specialist. Enrollment of 4083 does not fill that gap because it does not give category-specific results or analysis denominators. The record also does not report numerical results for the listed secondary outcomes, so those conditions and documentation patterns cannot be quantified from it.

General statistical explanation: an observational pattern can be useful for describing care as it was recorded, but it does not by itself show that a medication caused an outcome or that one group would have had the same characteristics as another under a different prescribing decision. The registry specifically notes that allocation was not stated and the arms are not a like-for-like control comparison. Any contrast between recorded categories would require careful interpretation and cannot be treated as a randomized treatment effect.

The record reports serious adverse event entries, including 43 affected participants among 4055 at risk, and lists specific terms with percentages. Those entries do not establish causation, completeness of event reporting, or comparative safety. The record does not supply the additional analysis details needed to judge those questions.

In short, the registry defines a real-world descriptive study and its intended outcomes, but the registry entries available do not include the primary category counts or numerical secondary outcome results. The record can clarify what was measured and the population definition; it cannot support conclusions about the magnitude of prescribing patterns, clinical effects, or comparative safety.

13. Why This Trial Matters Statistically

Non-interventional studies can describe how treatments and clinical characteristics appear in routine records. The question in this record focuses on first prescriptions of modern type 2 diabetes medications and the prescribing specialist associated with those prescriptions. It also identifies cardiovascular and kidney-related outcomes that may be of interest when characterizing the patients and recorded care. Such descriptive aims are distinct from testing whether a treatment causes a benefit or harm.

The primary endpoint is framed as a count by medication and prescribing-specialist category, with a specified index-date timeframe. The prescribed patient set definition and the reliance on existing medical records help clarify which records were intended to contribute. These details are statistically important: outcome definitions and population rules determine what a count represents and whether it can be compared meaningfully with other counts.

The registry’s warning that the arms are not a like-for-like control comparison is also important. General statistical explanation: observational data often reflect clinical decisions and patient characteristics that are not controlled through random assignment. This makes descriptive interpretation appropriate and cautions against causal conclusions based on group differences alone.

The record lists 70 outcome measures and 57 analyses, alongside a range of outcome definitions. That breadth highlights why transparent reporting of denominators, missing-data methods, statistical analysis plans, and multiplicity handling matters. Those details are not reported in the registry record. Further, the primary category counts and numerical secondary results are absent from the registry entries, so the intended descriptive questions cannot be answered quantitatively from this record.

The statistical value of the record is therefore in its description of the study question, data source, population definition, and outcome scope. Its limits are equally relevant: without reported results and analysis details, it cannot establish the prevalence of the measured conditions, the distribution of prescription categories, or differences in outcomes between groups.

14. 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 gives a broad study description but does not report the primary outcome counts. This prevents direct interpretation of the central prescribing-pattern question. Although enrollment is reported as 4083, the record does not provide category-specific denominators or state how many patients contributed to each outcome analysis. Enrollment should not be treated as the denominator for every result.

The study used existing data, including medical chart review. The record does not describe the completeness or consistency of chart documentation, how data were abstracted, or how discrepancies were resolved. For outcomes that depend on physician assessment or recorded estimated glomerular filtration rate and urine albumin creatinine ratio status, the record does not report how absent or incomplete information was handled.

Several secondary outcomes use different definitions of cardiovascular or kidney disease, including physician assessment and laboratory-status categories. Numerical results are not reported in the registry record, and it is therefore not possible to assess how those definitions affected the reported counts or whether alternative definitions gave similar findings. Country-specific results and the distribution of participating patients across settings are also not reported in the registry record.

The registry states that allocation was not stated and that the arms are not a like-for-like control comparison. As a result, medication or specialist categories should not be interpreted as randomized groups. The record does not report an adjustment strategy for differences between categories, a statistical analysis plan, or how multiplicity was addressed despite listing 70 outcome measures and 57 analyses.

Finally, the safety entries do not include further details about event collection or the calculation of the listed percentages. These limitations mean the record is most informative about study purpose and measurement scope, rather than about the magnitude, precision, or causal meaning of outcomes.

15. Related Tutorials

16. Related Statistical Calculators

17. Sources

• ClinicalTrials.gov: DIA_CENTRAL:T2D Treatment Pattern in Central Europe — NCT03807440.
• Registry record last updated 2023-12-01; status last verified 2023-02.
• Results first posted 2023-12-01.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

18. Record Summary

The registry identifies CORDIALLY® - CEE as a completed, non-interventional study using existing data, including medical chart review, among patients with type 2 diabetes in Central Eastern Europe. Boehringer Ingelheim is listed as the sponsor. Enrollment is reported as 4083; the study start date is 2019-08-26 and the primary completion date is 2021-08-31.

The primary outcome is the number of patients in categories of first prescription of a respective modern type 2 diabetes medication, according to prescribing specialist, at study index date 1 between September 2018 and December 2018. The primary population is described as the prescribed patient set meeting eligibility, prescription, and signed-documentation conditions. Listed medication types include empagliflozin and three medication classes. The secondary outcomes cover cardiovascular disease, chronic kidney disease, and related documentation.

The record lists 70 outcome measures and 57 analyses. It also records 43 participants affected by serious adverse events among 4055 at risk, with 0 other adverse events and 0 deaths. The primary category counts and numerical secondary outcome results are not reported in the registry record. Allocation is not stated, and the record cautions that the arms are not a like-for-like control comparison.