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Personalized approach in T2D is key for success

The Sanofi webinar ‘Act Now for Impact: Glycemic Control and Beyond’ focuses on recent advancements in treating type 2 diabetes (T2D), emphasizing a personalized approach for better outcomes. Prof. Frank Nobels (Belgium), prof. De Galan (the Netherlands) and Prof Björn Eliasson (Sweden) addressed various aspects of T2D treatment in the present era.

Treatment opportunities and challenges

The risks associated with T2D, especially cardiovascular (CV) complications, stress the importance of early intervention.1,2 Newer medications like SGLT2 inhibitors and GLP-1 receptor agonists offer promising results, not just for glucose control but also regarding CV and renal benefits.3,4 However, therapeutic inertia and the complexity of the disease pose significant challenges which accentuate the need for better follow-up, treatment strategies and personalized care.5

Key takeaways on treatment opportunities and challenges

  • T2D is a complex disease with a high CV risk and progressive beta-cell failure
    • Early multifactorial intervention is key
  • There is an enormous improvement in treatment options, although there is a disconnection between evidence/guidelines and clinical practice as well as major clinical inertia
  • Improvement of healthcare professional (HCP) skills, knowledge and organisation is needed

Personalized medicine in diabetes management

T2D significantly impacts patient health outcomes, particularly in relation to CV risk and loss of life expectancy, which can be 14-16 years and is largely influenced by the age at diagnosis.6 Research indicates that common risk factors, such as elevated cholesterol and blood pressure further exacerbate mortality risks, potentially doubling or tripling the likelihood of CV death.7 “Hypoglycemia by itself is an independent risk factor for CV disease”, Prof. De Galan stated. Interestingly, while controlling hyperglycemia is critical, intensive glucose-lowering treatments have shown a neutral effect on CV outcomes.8 A holistic and personalized approach is essential to effectively manage diabetes, addressing multiple health aspects such as glucose control, weight management, and CV risk factors.9 New medications such as SGLT2 inhibitors and GLP-1 receptor agonists, have emerged as valuable tools in reducing CV risk, with the former notably improving renal function and heart failure (HF) outcomes.3,4

Key takeaways on personalized medicine in diabetes management

  • Management of T2D requires a personalized approach targeting multiple components
  • GLP-1 receptor agonists and SGLT2-inhibitors independently improve CV and renal outcomes in T2D
  • Use of GLP-1 receptor agonists and SGLT2-inhibitors increases among in-patients without T2D
  • Stopping SGLT2-inhibitors prior to surgery may not be necessary, but specific action may be required (e.g., insulin/glucose drip)

Curious about pharmacologic aspects of personalized T2D medicine according to Prof. De Galan? You can watch the session in video below.

Deep dive in subpopulations

Prof. Eliasson highlighted the complexity of T2D management, particularly the concept of clustering patients based on their characteristics. In 2018, it was assessed whether distinct clusters of diabetes subpopulations could be formed using computational methods. Although clustering was found to be feasible, it lacked clinical utility because there was no evidence supporting a fixed number of clusters.10 The findings suggest that while patients can be categorized into various groups based on factors like HbA1c levels and insulin secretion, the variations within these clusters were significant, making it challenging to draw meaningful conclusions.10,11 “Accurate diagnosis is therefore highly important, especially in atypical cases where patients may not fit the traditional profiles of T1D or T2D”, Prof. Eliasson said. Management strategies for diabetes must consider individual patient history and characteristics, including the presence of other comorbidities. According to the guidelines, SGLT2-inhibitors and GLP-1 receptor agonists are suitable for a large number of subpopulations.9

Learn what Prof. Eliasson has to say on managing subpopulations in the video below.

Key takeaways on subpopulations

  • Individualize and tailor treatment
  • Pay attention to the treatment recommendations (EASD/ADA and ESC) as these are good

Don't miss this insightful discussion on tailoring care to individual need in the pursuit for a better glycemic control for T2D. Watch the 15 min discussion here:

Referanser

  1. Rawshani A, et al. Risk Factors, Mortality, and Cardiovascular Outcomes in Patients with Type 2 Diabetes. N Engl J Med. 2018;379(7):633-644.

  2. Gaede P, et al. Effect of a multifactorial intervention on mortality in type 2 diabetes. N Eng J Med. 2008;358:580-91.

  3. Apperloo EM, et al. Efficacy and safety of SGLT2 inhibitors with and without glucagon-like peptide 1 receptor agonists: a SMART-C collaborative meta-analysis of randomised controlled trial. Lancet Diabet. 2024;12:545-57.

  4. Zehniker TA, et al. Comparison of the Effects of Glucagon-Like Peptide Receptor Agonists and Sodium-Glucose Cotransporter 2 Inhibitors for Prevention of Major Adverse Cardiovascular and Renal Outcomes in Type 2 Diabetes Mellitus. Circulation. 2019;139-(17):2022-20231.

  5. Carls GS. 76th ADA session, 2024. Poster 117-LB.

  6. Emerging Risk Factors Collaboration. Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries: 23 million person-years of observation. Lancet Diabetes Endocrinol. 2023;11(10):731-742.

  7. Stamier J, et al. Diabetes, other risk factors, and 12-yr cardiovascular mortality for men screened in the Multiple Risk Factor Intervention Trial. Diabetes Care. 1993;16:434-444.

  8. Mellor J, et al. Risk factors and prediction of hypoglycaemia using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials. Diabetologia. 2024;67(8):1588-1601.

  9. Davies MJ, et al. Management of hyperglycaemia in type 2 diabetes, 2022. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia. 2022;65:1925-1966.

  10. Ahlqvist E, et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetol. 2018;6(5):361-369.

  11. Lugner M, et al. Comparison between data-driven clusters and models based on clinical features to predict outcomes in type 2 diabetes: nationwide observational study. Diabetologia. 2021;64(9):1973-1981.

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MAT-NO-2400376 v.1.0 11/2024