Type 2 diabetes in praxis – balancing between resistance and secretion

Česká verzia

Authors: Barbora Pavlíková; Martina Vodičková; Vojtěch Česák; Michal Krčma; Zdeněk Rušavý
Authors place of work: I. interní klinika LF UK a FN Plzeň
Published in the journal: Vnitř Lék 2020; 66(1): 21-27
Category: Main Topic

Summary

Type 2 diabetes mellitus is a disease characterized by a progressive failure of β cells on a background of significant insulin resistance. An individualized approach has its meaning especially in long-term decompensated patients, where the knowledge of the predominant patophysiologic mechanism can help to better conduct the therapy. A patient with near none secretion surely won´t benefit from secretagogues or incretin therapy, on the other hand a patient with high resistance on insulin therapy is in risk of developing a circulus vitiosus: higher doses – weight gain caused by anabolic effect of insulin with contribution of over-eating due to hypoglycemias – increasing resistance – increasing doses of insulin. This article is a reflection of possible approach to patients with decompensated type 2 diabetes with already exhausted treatment intensification possibilities. How to recognize patients who would benefit from a complex therapy change in the sense of decrease or withdrawal of insulin and switch to other treatment (especially incretins) from patients in whom would this change lead only to further decompensation? An important tool is certainly to reveal the prevalent pathophysiology in the given patient. So, in the first part of the article, existing methods of determination of insulin secretion and magnitude of insulin resistance are mentioned, with the reflection of their possible use in clinical practice. In the next part, the article tries to point out the possible predicting factors of success of selected change of therapy in these patients (in this case the conversion to GLP-1 analogues or drastic weight reduction) by comparing results of selected interventional studies.

Keywords:

insulin resistance – diagnostics – diabetes mellitus type 2 – Insulin secretion – therapy

Zdroje

1. Cersosimo E, Solis‑Herrera C, Trautmann P, et al. Assessment of Pancreatic β‑Cell Function: Review of Methods and Clinical Applications. Current Diabetes Reviews 2014; 10: 2–42.

2. Butler AE, Janson J, Bonner‑Weir S et al. B‑Cell Deficit and Increased B‑Cell Apoptosis in Humans With Type 2 Diabetes. Diabetes 2003; 52: 102–110.

3. Davies MJ, D’alessio DA, Fradkin J et al. Management of hyperglycaemia in type 2 diabetes, 2018. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 2018; 61: 2461–2498.

4. Škrha J Biochemie a patofyziologie. Diabetologie. Praha: Galén 2009, 33–75.

5. Loopstra‑Masters RC, Haffner SM, Lorenzo C et al. Proinzulin‑to‑C-peptide ratio versus proinzulin‑to‑inzulin ratio in the prediction of incident diabetes: the Inzulin Resistance Atherosclerosis Study (IRAS). Diabetologia 2011; 54: 3047–3054.

6. Jones AG, Hattersley AT. The clinical utility of C‑peptide measurement in the care of patients with diabetes. Diabetic Medicine 2013; 30: 803–817.

7. Saisho Y. Postprandial C‑Peptide to Glucose Ratio as a Marker of β Cell Function: Implication for the Management of Type 2 Diabetes. International Journal of Molecular Sciences 2016; 17: 214–223.

8. Leighton E, Sainsbury CAR, Jones GC. A Practical Review of C‑Peptide Testing in Diabe‑ tes. Diabetes Therapy 2017; 8: 475–487.

9. Takabe M, Matsuda T, Hirota Y et al. C‑peptide response to glucagon challenge is correlated with improvement of early insulin secretion by liraglutide treatment. Diabetes Research and Clinical Practice 2012; 98: e32–e35.

10. Covic AMC, Schelling JR, Constantiner M et al. Serum C‑peptide concentrations poorly phenotype type 2 diabetic end‑stage renal disease patients. Kidney International 2000; 58: 1742–1750.

11. Defronzo RA, Tobin JD, Andres AR. Glucose clamp technique: a method for quantifying inzulin secretion and resistance. American Journal of Physiology‑Endocrinology and Metabolism 1979; 237: 138–144.

12. Bergman RN, Ider YZ, Bowden CR et al. Quantitative estimation of insulin sensitivity. American Journal of Physiology‑Endocrinology and Metabolism 1979; 236: XXX–XXX.

13. Roden M Clinical diabetes research: methods and techniques. Chichester, West Sussex, England: John Wiley, 2007.

14. Cretti A, Lehtovirta M, Bonora E et al. Assessment of beta‑cell function during the oral glucose tolerance test by a minimal model of insulin secretion. European Journal of Clinical Investigation 2001; 31: 405–416.

15. Hovorka R, Chassin L, Luzio SD et al. Pancreatic β‑Cell Responsiveness during Meal Tolerance Test: Model Assessment in Normal Subjects and Subjects with Newly Diagnosed Noninsulin‑Dependent Diabetes Mellitus 1. The Journal of Clinical Endocrinology & Me‑ tabolism 1998; 83: 744–750.

16. Ahren B, Pratley R, Soubt M et al. Clinical Measures of Islet Function: Usefulness to Characterize Defects in Diabetes. Current Diabetes Reviews 2008; 4: 129–145.

17. Matthews DR, Hosker JP, Rudenski AS et al. Homeostasis model assessment: inzulin re‑ sistance and beta‑cell function from fasting plasma glucose and inzulin concentrations in man. Diabetologia 1985; 28: 412–419.

18. Wallace TM, Levy JC, Matthews DR. Use and Abuse of HOMA Modeling. Diabetes Care 2004; 27: 1487–1495.

19. Levy JC, Matthews DR, Hermans MP. Correct Homeostasis Model Assessment (HOMA) Evaluation Uses the Computer Program. Diabetes Care 1998; 21: 2191–2192.

20. Katz A, Nambi SS, Mather K, et al. Quantitative Insulin Sensitivity Check Index: A Simple, Accurate Method for Assessing Insulin Sensitivity In Humans. The Journal of Clinical Endocrinology & Metabolism 2000; 85: 2402–2410.

21. Chen H, Sullivan G, Quon MJ. Assessing the Predictive Accuracy of QUICKI as a Surrogate Index for Insulin Sensitivity Using a Calibration Model. Diabetes 2005; 54: 1914–1925.

22. Matsuda M, Defronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care 1999; 22: 1462–1470.

23. Lorenzo C, Haffner SM, Stančáková A et al. Fasting and OGTT‑derived Measures of Insulin Resistance as Compared With the Euglycemic‑Hyperinsulinemic Clamp in Nondiabetic Finnish Offspring of Type 2 Diabetic Individuals. The Journal of Clinical Endocrinology & Metabolism 2015; 100: 544–550.

24. Xiang AH, Watanabe RM, Buchanan TA. HOMA and Matsuda indices of insulin sensitivity: poor correlation with minimal model‑based estimates of insulin sensitivity in longitudinal settings. Diabetologia 2014; 57: 334–338.

25. Pacini G, Mari A. Methods for clinical assessment of insulin sensitivity and β‑cell function. Best Practice & Research Clinical Endocrinology & Metabolism 2003; 17: 305–322.

26. Bruinstroop E, Meyer L, Brouwer CB et al. Retrospective Analysis of an Insulin‑to‑Liraglutide Switch in Patients with Type 2 Diabetes Mellitus. Diabetes Therapy 2018; 9: 1369–1375.

27. Kawata T, Kanamori A, Kubota A et al. Is a Switch From Insulin Therapy to Liraglutide Possible in Japanese Type 2 Diabetes Mellitus Patients? Journal of Clinical Medicine Research 2014; E744.

28. Iwao T, Sakai K, Sata M. Postprandial serum C‑peptide is a useful parameter in the prediction of successful switching to liraglutide monotherapy from complex insulin therapy in Japanese patients with type 2 diabetes. Journal of Diabetes and its Complications 2013; 27: 87–91.

29. Davis SN, Johns D, Maggs D et al. Exploring the Substitution of Exenatide for Insulin in Patients With Type 2 Diabetes Treated With Insulin in Combination With Oral Antidiabetes Agents. Diabetes Care 2007; 30: 2767–2772.

30. Araki H, Tanaka Y, Yoshida S et al. Oral glucose‑stimulated serum C‑peptide predicts successful switching from insulin therapy to liraglutide monotherapy in Japanese patients with type 2 diabetes and renal impairment. Journal of Diabetes Investigation 2014; 5: 435–441.

31. Aron‑Wisnewsky J, Sokolovska N, Liu Y et al. The advanced‑DiaRem score impro‑ ves prediction of diabetes remission 1 year post‑Roux‑en‑Y gastric bypass. Diabetologia 2017; 60: 1892–1902.

32. Dicker D, Golan R, Aron‑Wisnewsky J et al. Prediction of Long‑Term Diabetes Remissi‑ on After RYGB, Sleeve Gastrectomy, and Adjustable Gastric Banding Using DiaRem and Advanced‑DiaRem Scores. Obesity Surgery 2019; 29: 796–804.

33. Steven S, Hollingsworth Kg, Al‑Mrabeh A et al. Very Low‑Calorie Diet and 6 Months of Weight Stability in Type 2 Diabetes: Pathophysiological Changes in Responders and Nonresponders. Diabetes Care 2016; 39: 808–815.