Download PDF
Exp Clin Endocrinol Diabetes 2022; 130(09): 587-595
DOI: 10.1055/a-1702-5151
Article

Dispensation Patterns of Glucose-Lowering Drugs in Newly Diagnosed Type 2 Diabetes: Routine Data Analysis of Insurance Claims in Germany

Brenda Bongaerts
1   Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
2   German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, München-Neuherberg, Germany
,
Bianca Kollhorst
3   Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany
,
Oliver Kuss
1   Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
2   German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, München-Neuherberg, Germany
,
Iris Pigeot
3   Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany
4   University of Bremen, Faculty of Mathematics and Computer Science, Bremen, Germany
,
Wolfgang Rathmann
1   Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
2   German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, München-Neuherberg, Germany
› Author Affiliations
› Further Information
Also available at
    Permissions and Reprints

Abstract

Aims To describe dispensation patterns of glucose-lowering drugs in newly diagnosed type 2 diabetes in Germany.

Materials and methods Based on claims data from four statutory health insurances (German Pharmacoepidemiological Research Database,>25 million insurants), all individuals with newly diagnosed type 2 diabetes were identified. Eligible patients had a first diagnosis for type 2 diabetes between January 2012 and December 2016. We analyzed the dispensation patterns of first-line glucose-lowering therapies initiated in the year after diabetes diagnosis and patterns of second-line therapies dispensed one year after first-line treatment.

Results A total of 356,647 individuals with newly diagnosed type 2 diabetes were included (average age [SD]: 63.5 [13.4] years; 49.3% males). Of the 31.6% of individuals who were pharmacologically treated in the year after diagnosis, metformin monotherapy was most frequently dispensed (73.1%), followed by dual therapy of metformin and dipeptidyl peptidase-4 inhibitors (DPP-4is) (6.4%), and monotherapy with DPP-4is (2.9%). From 2012 through 2016, sulfonylurea dispensations were reduced by more than 50%. Dispensations for combination therapies with DPP-4is increased up to 10.6%. Glucagon-like peptide-1 receptor agonists and sodium-glucose co-transporter-2 inhibitors contributed to 2% of all treatments. After a median of 5 months, 20.0% of individuals on pharmacological therapy initiated second-line glucose-lowering treatment.

Conclusions Data from German statutory health insurances (2012 to 2016) showed that most individuals with newly diagnosed type 2 diabetes were dispensed metformin monotherapy in line with diabetes care guidelines. A substantial decrease in the use of sulfonylureas was observed after the introduction of DPP-4i and GLP-1 receptor agonists.

Key words

Administrative data - drug dispensation patterns - Germany - glucose-lowering treatment - health insurance claims data - type 2 diabetes


Publication History

Received: 21 June 2021

Accepted: 16 November 2021

Article published online:
23 December 2021

© 2021. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Rathmann W, Strassburger K, Bongaerts B. et al. Impact of insulin sensitivity, beta-cell function and glycaemic control on initiation of second-line glucose-lowering treatment in newly diagnosed type 2 diabetes. Diabetes Obes Metab 2017; 19: 866-873
    CrossrefPubMedGoogle Scholar
  • 2 Pantalone KM, Wells BJ, Chagin KM. et al. Intensification of diabetes therapy and time until A1C aoal attainment among patients with newly diagnosed type 2 diabetes who fail metformin monotherapy within a large integrated health system. Diabetes Care 2016; 39: 1527-1534
    CrossrefPubMedGoogle Scholar
  • 3 Watson L, Das R, Farquhar R. et al. Consequences of delaying treatment intensification in type 2 diabetes: evidence from a UK database. Curr Med Res Opin 2016; 32: 1465-1475
    CrossrefPubMedGoogle Scholar
  • 4 Holman RR, Paul SK, Bethel MA. et al. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 2008; 359: 1577-1589
    CrossrefPubMedGoogle Scholar
  • 5 Paul SK, Klein K, Thorsted BL. et al. Delay in treatment intensification increases the risks of cardiovascular events in patients with type 2 diabetes. Cardiovasc Diabetol 2015; 14: 100
    CrossrefPubMedGoogle Scholar
  • 6 Laiteerapong N, Karter AJ, Moffet HH. et al. Ten-year hemoglobin A1c trajectories and outcomes in type 2 diabetes mellitus: The Diabetes & Aging Study. J Diabetes Complications 2017; 31: 94-100
    CrossrefPubMedGoogle Scholar
  • 7 American Diabetes A.. 9. Pharmacologic Approaches to Glycemic Treatment: Standards of Medical Care in Diabetes-2020. Diabetes Care 2020; 43: S98-S110
    CrossrefPubMedGoogle Scholar
  • 8 Rathmann W, Scheerer M, Rohwedder K. et al. Changes in patient characteristics, glucose lowering treatment, glycemic control and complications in type 2 diabetes in general practices (Disease Analyzer, Germany: 2008-2016). Postgrad Med 2018; 130: 244-250
    CrossrefPubMedGoogle Scholar
  • 9 Hartmann B, Bramlage P, Lanzinger S. et al. Regional differences in type 2 diabetes treatment and outcomes in Germany-An analysis of the German DPV and DIVE registries. Diabetes Metab Res Rev 2018; 34: e3049
    CrossrefPubMedGoogle Scholar
  • 10 Garbe E, Mikolajczyk RT, Banaschewski T. et al. Drug treatment patterns of attention-deficit/hyperactivity disorder in children and adolescents in Germany: Results from a large population-based cohort study. J Child Adolesc Psychopharmacol 2012; 22: 452-458
    CrossrefPubMedGoogle Scholar
  • 11 Ohlmeier C, Langner I, Hillebrand K. et al. Mortality in the German Pharmacoepidemiological Research Database (GePaRD) compared to national data in Germany: results from a validation study. BMC Public Health 2015; 15: 570
    CrossrefPubMedGoogle Scholar
  • 12 Pigeot I, Ahrens W. Establishment of a pharmacoepidemiological database in Germany: methodological potential, scientific value and practical limitations. Pharmacoepidemiol Drug Saf 2008; 17: 215-223
    CrossrefPubMedGoogle Scholar
  • 13 Schink T, Garbe E. Representativity of dispensations of non-steroidal anti-inflammatory drugs (NSAIDs) in the German pharmacoepidemiological research database. Pharmacoepidemiol Drug Saf 2010; 19: S294-S294
    PubMedGoogle Scholar
  • 14 Garbe E, Kreisel SH, Behr S. Risk of subarachnoid hemorrhage and early case fatality associated with outpatient antithrombotic drug use. Stroke 2013; 44: 2422-2426
    CrossrefPubMedGoogle Scholar
  • 15 Ohlmeier C, Langner I, Garbe E. et al. Validating mortality in the German Pharmacoepidemiological Research Database (GePaRD) against a mortality registry. Pharmacoepidemiol Drug Saf 2016; 25: 778-784
    CrossrefPubMedGoogle Scholar
  • 16 Jobski K, Schmedt N, Kollhorst B. et al. Characteristics and drug use patterns of older antidepressant initiators in Germany. Eur J Clin Pharmacol 2017; 73: 105-113
    CrossrefPubMedGoogle Scholar
  • 17 Schmedt N, Jobski K, Kollhorst B. et al. Treatment patterns and characteristics of older antipsychotic users in Germany. Int Clin Psychopharmacol 2016; 31: 159-169
    CrossrefPubMedGoogle Scholar
  • 18 Pisa FE, Reinold J, Kollhorst B. et al. Antidepressants and the risk of traumatic brain injury in the elderly: Differences between individual agents. Clin Epidemiol 2019; 11: 185-196
    CrossrefPubMedGoogle Scholar
  • 19 Schroder C, Dorks M, Kollhorst B. et al. Extent and risks of antidepressant off-label use in children and adolescents in Germany between 2004 and 2011. Pharmacoepidemiol Drug Saf 2017; 26: 1395-1402
    CrossrefPubMedGoogle Scholar
  • 20 Schmedt N, Garbe E. Antipsychotic drug use and the risk of venous thromboembolism in elderly patients with dementia. J Clin Psychopharmacol 2013; 33: 753-758
    CrossrefPubMedGoogle Scholar
  • 21 Inzucchi SE, Bergenstal RM, Buse JB. et al. Management of hyperglycemia in type 2 diabetes: A patient-centered approach: Position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care 2012; 35: 1364-1379
    CrossrefPubMedGoogle Scholar
  • 22 Marso SP, Bain SC, Consoli A. et al. Semaglutide and cardiovascular outcomes in patients with type 2 diabetes. N Engl J Med 2016; 375: 1834-1844
    Google Scholar
  • 23 Nauck MA, Meier JJ, Cavender MA. et al. Cardiovascular actions and clinical outcomes with glucagon-like peptide-1 receptor agonists and dipeptidyl peptidase-4 inhibitors. Circulation 2017; 136: 849-870
    CrossrefPubMedGoogle Scholar
  • 24 Mahaffey KW, Neal B, Perkovic V. et al. Canagliflozin for primary and secondary prevention of cardiovascular events: Results from the CANVAS program (Canagliflozin Cardiovascular Assessment Study). Circulation 2018; 137: 323-334
    CrossrefPubMedGoogle Scholar
  • 25 Kosiborod M, Cavender MA, Fu AZ. et al. Lower risk of heart failure and death in patients initiated on sodium-glucose cotransporter-2 inhibitors versus other glucose-lowering drugs: The CVD-REAL study (comparative effectiveness of cardiovascular outcomes in new users of sodium-glucose cotransporter-2 inhibitors). Circulation 2017; 136: 249-259
    CrossrefPubMedGoogle Scholar
  • 26 Schipf S, Werner A, Tamayo T. et al. Regional differences in the prevalence of known Type 2 diabetes mellitus in 45-74 years old individuals: Results from six population-based studies in Germany (DIAB-CORE Consortium). Diabet Med 2012; 29: e88-e95
    CrossrefPubMedGoogle Scholar
  • 27 Finger JD, Busch MA, Du Y. et al. Time trends in cardiometabolic risk factors in adults. Dtsch Arztebl Int 2016; 113: 712-719
    PubMedGoogle Scholar
  • 28 Schink T, Garbe E. Assessment of the representativity of in-patient hospital diagnoses in the German Pharmacoepidemiological Research Database. Gesundheitswesen 2010; 72: P10
    Article in Thieme ConnectPubMedGoogle Scholar
  • 29 Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol 2005; 58: 323-337
    CrossrefPubMedGoogle Scholar