Prospective, randomized trial on intensive SMBG management added value in non-insulin-treated T2DM patients (PRISMA): a study to determine the effect of a structured SMBG intervention

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• 作者：Marina Scavini ; Emanuele Bosi ; Antonio Ceriello ; Francesco Giorgino…
• 关键词：Type 2 diabetes mellitus ; Self ; monitoring of blood glucose ; Randomized clinical trial ; Patient empowerment ; Diabetes medication algorithm
• 刊名：Acta Diabetologica
• 出版年：2013
• 出版时间：October 2013
• 年：2013
• 卷：50
• 期：5
• 页码：663-672
• 全文大小：424KB
• 参考文献：1. Diabetes Control and Complications Trial Research Group (1993) The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 329:977-86 CrossRef
  2. Nathan DM, Cleary PA, Backlund JY et al (2005) Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes. N Engl J Med 353:2643-653 CrossRef
  3. U.K. Prospective Diabetes Study Group (1998) Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet 352:837-53 CrossRef
  4. Holman RR, Paul SK, Bethel MA et al (2008) 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 359:1577-589 CrossRef
  5. Gaede P, Vedel P, Parving HH, Pedersen O (1999) Intensified multifactorial intervention in patients with type 2 diabetes mellitus and microalbuminuria: the Steno type 2 randomised study. Lancet 353:617-22 CrossRef
  6. Gerstein HC, Miller ME, Byington RP et al (2008) Effects of intensive glucose lowering in type 2 diabetes. N Engl J Med 358:2545-559 CrossRef
  7. Riddle MC, Ambrosius WT, Brillon DJ et al (2010) Epidemiologic relationships between A1C and all-cause mortality during a median 3.4-year follow-up of glycemic treatment in the ACCORD trial. Diabetes Care 33:983-90 CrossRef
  8. Shiraiwa T, Kaneto H, Miyatsuka T et al (2005) Post-prandial hyperglycemia is an important predictor of the incidence of diabetic microangiopathy in Japanese type 2 diabetic patients. Biochem Biophys Res Commun 336:339-45 CrossRef
  9. Sorkin JD, Muller DC, Fleg JL, Andres R (2005) The relation of fasting and 2-h postchallenge plasma glucose concentrations to mortality: data from the Baltimore longitudinal study of aging with a critical review of the literature. Diabetes Care 28:2626-632 CrossRef
  10. Hanefeld M, Koehler C, Schaper F et al ((1999) Postprandial plasma glucose is an independent risk factor for increased carotid intima-media thickness in non-diabetic individuals. Atherosclerosis 144:229-35
  11. Cavalot F, Petrelli A, Traversa M et al (2006) Postprandial blood glucose is a stronger predictor of cardiovascular events than fasting blood glucose in type 2 diabetes mellitus, particularly in women: lessons from the San Luigi Gonzaga Diabetes Study. J Clin Endocrinol Metab 91:813-19 CrossRef
  12. Temelkova-Kurktschiev TS, Koehler C, Henkel E et al (2000) Postchallenge plasma glucose and glycemic spikes are more strongly associated with atherosclerosis than fasting glucose or HbA1c level. Diabetes Care 23:1830-834 CrossRef
  13. Esposito K, Nappo F, Marfella R et al (2002) Inflammatory cytokine concentrations are acutely increased by hyperglycemia in humans: role of oxidative stress. Circulation 106:2067-072 CrossRef
  14. Esposito K, Ciotola M, Carleo D et al (2008) Post-meal glucose peaks at home associate with carotid intima-media thickness in type 2 diabetes. J Clin Endocrinol Metab 93:1345-350 CrossRef
  15. Hanefeld M, Cagatay M, Petrowitsch T et al (2004) Acarbose reduces the risk for myocardial infarction in type 2 diabetic patients: meta-analysis of seven long-term studies. EurHeart J 25:10-6
  16. Hanefeld M, Chiasson JL, Koehler C et al (2004) Acarbose slows progression of intima-media thickness of the carotid arteries in subjects with impaired glucose tolerance. Stroke 35:1073-078 CrossRef
  17. Esposito K, Giugliano D, Nappo F, Marfella R (2004) Regression of carotid atherosclerosis by control of postprandial hyperglycemia in type 2 diabetes mellitus. Circulation 110:214-19 CrossRef
  18. Monnier L, Mas E, Ginet C et al (2006) Activation of oxidative stress by acute glucose fluctuations compared with sustained chronic hyperglycemia in patients with type 2 diabetes. JAMA 295:1681-687 CrossRef
  19. Service FJ, Molnar GD, Rosevear JW et al (1970) Mean amplitude of glycemic excursions, a measure of diabetic instability. Diabetes 19:644-55
  20. International Diabetes Federation Clinical Guidelines Taskforce and International SMBG Working Group (2009) Global guideline on self-monitoring of blood glucose in non-insulin treated type 2 diabetes. International Diabetes Federation. Accessed June 2010 at http://www.idf.org
  21. Parkin CG, Davidson JA (2009) Value of self-monitoring blood glucose pattern analysis in improving diabetes outcomes. J Diabetes Sci Technol 3:500-08
  22. Evans JM, Newton RW, Ruta DA et al (1999) Frequency of blood glucose monitoring in relation to glycaemic control: observational study with diabetes database. BMJ 319:83-6 CrossRef
  23. Karter AJ, Ackerson LM, Darbinian JA et al (2001) Self-monitoring of blood glucose levels and glycemic control: the Northern California Kaiser Permanente Diabetes registry. Am J Med 111:1- CrossRef
  24. Nathan DM, McKitrick C, Larkin M et al (1996) Glycemic control in diabetes mellitus: have changes in therapy made a difference? Am J Med 100:157-63 CrossRef
  25. Farmer A, Wade A, Goyder E et al (2007) Impact of self monitoring of blood glucose in the management of patients with non-insulin treated diabetes: open parallel group randomised trial. BMJ 335:132 CrossRef
  26. O’Kane MJ, Bunting B, Copeland M, Coates VE (2008) Efficacy of self monitoring of blood glucose in patients with newly diagnosed type 2 diabetes (ESMON study): randomised controlled trial. BMJ 336:1174-177 CrossRef
  27. Davidson MB, Castellanos M, Kain D, Duran P (2005) The effect of self monitoring of blood glucose concentrations on glycated hemoglobin levels in diabetic patients not taking insulin: a blinded, randomized trial. Am J Med 118:422-25 CrossRef
  28. Polonsky W, Fisher L, Schikman C et al (2010) The value of episodic, intensive blood glucose monitoring in non-insulin treated persons with type 2 diabetes: design of the Structured Testing Program (STeP) study, a cluster-randomised, clinical trial [NCT00674986]. BMC Fam Pract 11:37. Accessed June 2011 at http://www.biomedcentral.com/1471-2296/11/37
  29. Klonoff D, Bergenstal R, Blonde LSA et al (2008) Consensus report of the coalition for clinical research—self-monitoring of blood glucose. J Diabetes Sci Technol 2:1030-053
  30. Kempf K, Kruse J, Martin S, ROSSO-in-praxi (2010) A self-monitoring of blood glucose-structured 12-week lifestyle intervention significantly improves glucometabolic control of patients with type 2 diabetes mellitus. Diabetes Technol Ther 12:547-53 CrossRef
  31. Bonomo K, De Salve A, Fiora E et al (2010) Evaluation of a simple policy for pre- and post-prandial blood glucose self-monitoring in people with type 2 diabetes not on insulin. Diabetes Res Clin Pract 87:246-51 CrossRef
  32. Duran A, Martin P, Runkle I et al (2010) Benefits of self-monitoring blood glucose in the management of new-onset Type 2 diabetes mellitus: the St Carlos Study, a prospective randomized clinic-based interventional study with parallel groups. J Diabetes 2:203-11 CrossRef
  33. Polonsky WH, Fisher L, Schikman CH (2011) Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated Type 2 diabetes: results from the structured testing program study. Diabetes Care 34:262-67 CrossRef
  34. Franciosi M, Lucisano G, Pellegrini F, Cantarello A, Consoli A, Cucco L, Ghidelli R, Sartore G, Sciangula L, Nicolucci A; for the ROSES Study Group (2011) ROSES: role of self-monitoring of blood glucose and intensive education in patients with Type 2 diabetes not receiving insulin. A pilot randomized clinical trial. Diabet Med 28(7):789-96, doi:10.1111/j.1464-5491.2011.03268.x
  35. World Medical Association declaration of Helsinki (1997) Recommendations guiding physicians in biomedical research involving human subjects. JAMA 277:925-26 CrossRef
  36. American Diabetes Association (2011) Standards of medical care in diabetes-011. Diabetes Care 34(Suppl 1):S11–S61
  37. Nathan DM, Buse JB, Davidson MB et al (2006) Management of hyperglycemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy. Diabetes Care 29:1963-972 CrossRef
  38. International Diabetes Federation Clinical Guidelines Task Force (2005) Global guideline for type 2 diabetes. Int Diabetes Federat. Accessed June 2010 at http://www.idf.org
  39. Diabetologia AMD-SId. Standard Italiani per la Cura del Diabete Mellito. 2010
  40. Kovatchev BP, Straume M, Cox DJ, Farhy LS (2000) Risk analysis of blood glucose data: a quantitative approach to optimizing the control of insulin dependent diabetes. J Theor Med 3:1-0 CrossRef
  41. Kovatchev BP, Cox DJ, Gonder-Frederick LA et al (1998) Assessment of risk for severe hypoglycemia among adults with IDDM: validation of the low blood glucose index. Diabetes Care 21:1870-875 CrossRef
  42. Kovatchev BP, Cox DJ, Gonder-Frederick L, Clarke WL (2002) Methods for quantifying self-monitoring blood glucose profiles exemplified by an examination of blood glucose patterns in patients with type 1 and type 2 diabetes. Diabetes Technol Ther 4:295-03 CrossRef
  43. Kovatchev BP, Cox DJ, Kumar A et al (2003) Algorithmic evaluation of metabolic control and risk of severe hypoglycemia in type 1 and type 2 diabetes using self-monitoring blood glucose data. Diabetes Technol Ther 5:817-28 CrossRef
  44. Levey AS, Bosch JP, Lewis JB, for the Modification of Diet in Renal Disease Study Group (1999) A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Ann Intern Med 130:461-70 CrossRef
  45. Diabetes Control and Complications Trial Research Group (1988) Reliability and validity of a diabetes quality-of-life measure for the diabetes control and complications trial (DCCT). The DCCT research group. Diabetes Care 11:725-32 CrossRef
  46. Trento M, Passera P, Borgo E et al (2004) A 5-year randomized controlled study of learning, problem solving ability, and quality of life modifications in people with type 2 diabetes managed by group care. Diabetes Care 27:670-75 CrossRef
  47. Peyrot M, Rubin RR (1994) Structure and correlates of diabetes-specific locus of control. Diabetes Care 17:994-001 CrossRef
  48. Trento M, Tomelini M, Basile M et al (2008) The locus of control in patients with Type 1 and Type 2 diabetes managed by individual and group care. Diabet Med 25:86-0 CrossRef
  49. Kovatchev BP, Otto E, Cox D et al (2006) Evaluation of a new measure of blood glucose variability in diabetes. Diabetes Care 29:2433-438 CrossRef
  50. Pradelles P, Grassi J, Maclouf J (1985) Enzyme immunoassays of eicosanoids using acetylcholine esterase as label: an alternative to radioimmunoassay. Anal Chem 57:1170-173 CrossRef
  51. Heyting A, Tolboom JT, Essers JG (1992) Statistical handling of drop-outs in longitudinal clinical trials. Stat Med 11:2043-061 CrossRef
  52. AMD Annals. Quality indicators of diabetes care in Italy. http://www.aemmedi.it. Accessed Nov 2011
  
• 作者单位：Marina Scavini (1)
  Emanuele Bosi (1) (2)
  Antonio Ceriello (3)
  Francesco Giorgino (4)
  Massimo Porta (5)
  Antonio Tiengo (6)
  Giacomo Vespasiani (7)
  Davide Bottalico (8)
  Raffaele Marino (9)
  Christopher Parkin (10)
  Erminio Bonizzoni (11)
  Domenico Cucinotta (12)
  
  1. Diabetes Research Institute, San Raffaele Scientific Institute, Milan, Italy
  2. San Raffaele Vita-Salute University, Milan, Italy
  3. Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS) and Centro de Investigacion Biomedica en Red de Diabetes y Enfermedades Metabolicas Asociadis (CIBERDEM), Barcelona, Spain
  4. Department of Emergency and Organ Transplantation, Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, University of Bari School of Medicine, Bari, Italy
  5. Department of Internal Medicine, University of Turin, Turin, Italy
  6. Department of Clinical and Experimental Medicine, Division of Metabolic Diseases, University of Padova, Padua, Italy
  7. Diabetes Unit, Ospedale Madonna del Soccorso, S. Benedetto del Tronto, Italy
  8. Medical Department Roche S.p.A, Monza, Italy
  9. Medical Affairs Department Roche Diagnostics S.p.A., Monza, Italy
  10. Information and Education Development, CGParkin, Inc., Las Vegas, NV, USA
  11. Department of Occupational Health Clinica del Lavoro L Devoto, Section of Medical Statistics and Biometry GA Maccacaro, School of Medicine, University of Milan, Milan, Italy
  12. Department of Internal Medicine, Policlinico Universitario Gaetano Martino, Messina, Italy
  
• ISSN：1432-5233

文摘

Self-monitoring of blood glucose (SMBG) is a core component of diabetes management. However, the International Diabetes Federation recommends that SMBG be performed in a structured manner and that the data are accurately interpreted and used to take appropriate therapeutic actions. We designed a study to evaluate the impact of structured SMBG on glycemic control in non-insulin-treated type 2 diabetes (T2DM) patients. The Prospective, Randomized Trial on Intensive SMBG Management Added Value in Non-insulin-Treated T2DM Patients (PRISMA) is a 12-month, prospective, multicenter, open, parallel group, randomized, and controlled trial to evaluate the added value of an intensive, structured SMBG regimen in T2DM patients treated with oral agents and/or diet. One thousand patients (500 per arm) will be enrolled at 39 clinical sites in Italy. Eligible patients will be randomized to the intensive structured monitoring (ISM) group or the active control (AC) group, with a glycosylated hemoglobin (HbA1c) target of <7.0%. Intervention will comprise (1) structured SMBG (4-point daily glucose profiles on 3 days per week [ISM]; discretionary, unstructured SMBG [AC]); (2) comprehensive patient education (both groups); and (3) clinician’s adjustment of diabetes medications using an algorithm targeting SMBG levels, HbA1c and hypoglycemia (ISM) or HbA1c and hypoglycemia (AC). The intervention and trial design build upon previous research by emphasizing appropriate and collaborative use of SMBG by both patients and physicians. Utilization of per protocol and intent-to-treat analyses facilitates assessment of the intervention. Inclusion of multiple dependent variables allows us to assess the broader impact of the intervention, including changes in patient and physician attitudes and behaviors. ClinicalTrials.gov (NCT00643474).