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Epidemiological Studies on Type 2 Diabetes Using the German Disease Analyser Database: A Narrative Review.
Karel Kostev1,2, Henning Sievert2, Marcel Konrad3
1Marburg University, University Clinic, Marburg, Germany.
Diabetes, Obesity & Metabolism
|July 6, 2026
Summary
Real-world data from the IQVIA Disease Analyser (DA) database offers insights into type 2 diabetes (T2D) management. Studies highlight drug effectiveness, prescribing patterns, and associations with comorbidities, aiding contemporary diabetes care.
Area of Science:
- Pharmacology
- Epidemiology
- Diabetes Mellitus Research
Background:
- The IQVIA Disease Analyser (DA) database offers anonymised, longitudinal outpatient data from German practices.
- Data includes diagnoses (ICD-10), prescriptions (ATC), consultation dates, and clinical measurements (HbA1c, BMI).
Purpose of the Study:
- To review DA-based research on type 2 diabetes (T2D) published between 2020-2025.
- Focus on glucose-lowering drug effectiveness, prescribing patterns, pharmacoepidemiological associations, and comorbidities.
Main Methods:
- A narrative review approach was employed.
- Eligible studies were identified via a structured PubMed search.
- Methodological limitations of observational studies were discussed.
Main Results:
- Observational associations found between SGLT2 inhibitor therapy and reduced incidence of iron deficiency anaemia and dementia in T2D patients.
- A 17-year decline in cardiovascular event incidence among newly diagnosed T2D patients was observed.
- A gap exists between guideline recommendations and real-world use of GLP-1 receptor agonists and SGLT2 inhibitors in patients with established cardiovascular disease.
- Associations were noted between glucose-lowering drug classes and cerebrovascular outcomes.
Conclusions:
- Observational study designs mean findings are hypothesis-generating, not causal.
- The DA database complements randomized trial data by reflecting routine care in large, diverse populations.
- Limitations include potential underestimation of hypoglycemia, missing lifestyle/socioeconomic data, and incomplete inpatient records.
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