Classifying and communicating risks in prediabetes according to fasting glucose and/or glycated hemoglobin: PREDAPS cohort study

References

• Herman CR, Gill HK, Eng J, et al. Screening for preclinical disease: test and disease characteristics. AJR Am J Roentgenol. 2002;179(4):825–831.
   PubMed Web of Science ®Google Scholar
• Herman C. What makes a screening exam "good"? Virtual Mentor. 2006;8(1):34–37.
   PubMedGoogle Scholar
• Fagerlin A, Zikmund-Fisher BJ, Ubel PA. Helping patients decide: ten steps to better risk communication. J Natl Cancer Inst. 2011;103(19):1436–1443.
   PubMedGoogle Scholar
• Mostofsky E, Dunn JA, Hernández-Díaz S, et al. Patient and Physician Preferences for Reporting Research Findings. Fam Med. 2019;51(6):502–508.
   PubMed Web of Science ®Google Scholar
• Hembroff LA, Holmes-Rovner M, Wills CE. Treatment decision-making and the form of risk communication: results of a factorial survey. BMC Med Inform Decis Mak. 2004;4:2016
   PubMedGoogle Scholar
• Trevena LJ, Davey HM, Barratt A, et al. A systematic review on communicating with patients about evidence. J Eval Clin Pract. 2006;12(1):13–23.
   PubMed Web of Science ®Google Scholar
• Goodyear-Smith F, Kenealy T, Wells S, et al. Patients' preferences for ways to communicate benefits of cardiovascular medication. Ann Fam Med. 2011;9(2):121–127.
   PubMed Web of Science ®Google Scholar
• American Diabetes Association. Standards of medical care in diabetes – 2020. Diabetes Care. 2020; 43(Suppl 1):S14–S31.
   PubMed Web of Science ®Google Scholar
• Tabák AG, Herder C, Rathmann W, et al. Prediabetes: a high-risk state for diabetes development. Lancet. 2012;379(9833):2279–2290.
   PubMed Web of Science ®Google Scholar
• Heianza Y, Hara S, Arase Y, et al. HbA1c 5.7-6.4% and impaired fasting plasma glucose for diagnosis of prediabetes and risk of progression to diabetes in Japan (TOPICS 3): a longitudinal cohort study. Lancet. 2011;378(9786):147–155.
   PubMed Web of Science ®Google Scholar
• Richter B, Hemmingsen B, Metzendorf M-I, et al. Development of type 2 diabetes mellitus in people with intermediate hyperglycaemia. Cochrane Database Syst Rev. 2018;10:CD012661.
   PubMed Web of Science ®Google Scholar
• Shang Y, Marseglia A, Fratiglioni L, et al. Natural history of prediabetes in older adults from a population-based longitudinal study. J Intern Med. 2019;286(3):326–340.
   PubMed Web of Science ®Google Scholar
• Arky RA. "Doctor, is my sugar normal?" N Engl J Med. 2005;353(14):1511–1513.
   PubMed Web of Science ®Google Scholar
• Bergman M. Inadequacies of absolute threshold levels for diagnosing prediabetes. Diabetes Metab Res Rev. 2010;26(1):3–6.
   PubMed Web of Science ®Google Scholar
• Cefalu WT. "Prediabetes": Are There Problems With This Label? No, We Need Heightened Awareness of This Condition!!. Diabetes Care. 2016;39(8):1472–1477.
   PubMed Web of Science ®Google Scholar
• Yudkin JS, Montori VM. The epidemic of pre-diabetes: the medicine and the politics. BMJ. 2014;349:g4485.
   PubMed Web of Science ®Google Scholar
• Van den Bruel A. The triumph of medicine: how overdiagnosis is turning healthy people into patients. Fam Pract. 2015;32(2):127–128.
   PubMed Web of Science ®Google Scholar
• Yudkin JS. "Prediabetes": Are There Problems With This Label? Yes, the Label Creates Further Problems! Diabetes Care. 2016;39(8):1468–1471.
   PubMed Web of Science ®Google Scholar
• Serrano R, García-Soidán FJ, Díaz-Redondo A, et al.; Grupo de Estudio PREDADS. [Cohort Study in Primary Health Care on the Evolution of Patients with Prediabetes (PREDAPS): basis and methodology]. Rev Esp Salud Publica. 2013;87(2):121–135.
   PubMed Web of Science ®Google Scholar
• Breslow NE, Day NE. Statistical methods in cancer research, volume II. IARC Sci Publ. 1987;82:1–406.
   Google Scholar
• Kleimbaum DG, Kupper LL, Morgenstern H. Epidemiology research. Principles and quantitative methods. New York: Van Nostrand Reinhold Company, 1982. 96–116.
   Google Scholar
• Giráldez-García C, Sangrós FJ, Díaz-Redondo A, et al.; PREDAPS Study Group. Cardiometabolic Risk Profiles in Patients With Impaired Fasting Glucose and/or Hemoglobin A1c 5.7% to 6.4%: Evidence for a Gradient According to Diagnostic Criteria: The PREDAPS Study. Medicine (Baltimore). 2015;94(44):e1935. ;.
   PubMed Web of Science ®Google Scholar
• Giráldez-García C, Hernández AM, Gamarra J, et al. Evolución de pacientes con prediabetes en Atención Primaria de Salud (PREDAPS): resultados del quinto año de seguimiento. Diabetes Práctica. 2018;09:37–80.
   Google Scholar
• Heianza Y, Arase Y, Fujihara K, et al. Screening for pre-diabetes to predict future diabetes using various cut-off points for HbA(1c) and impaired fasting glucose: the Toranomon Hospital Health Management Center Study 4 (TOPICS 4)). Diabet Med. 2012;29(9):e279–e285.
   PubMed Web of Science ®Google Scholar
• Brunisholz KD, Joy EA, Hashibe M, et al. Incidental risk of type 2 diabetes mellitus among patients with confirmed and unconfirmed prediabetes. PLoS One. 2016;11(7):e0157729.
   PubMed Web of Science ®Google Scholar
• Tuso P. Prediabetes and lifestyle modification: time to prevent a preventable disease. Perm J. 2014;18(3):88–93. Summer
   PubMedGoogle Scholar
• Zhang X, Gregg EW, Williamson DF, et al. A1C level and future risk of diabetes: a systematic review. Diabetes Care. 2010;33(7):1665–1673.
   PubMed Web of Science ®Google Scholar
• Hostalek U. Global epidemiology of prediabetes - present and future perspectives. Clin Diabetes Endocrinol. 2019;5:5.
   PubMedGoogle Scholar
• Knowler WC, Barrett-Connor E, Fowler SE, Diabetes Prevention Program Research Group, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346(6):393–403. ;.
   PubMed Web of Science ®Google Scholar
• Balk EM, Earley A, Raman G, et al. Combined Diet and Physical Activity Promotion Programs to Prevent Type 2 Diabetes Among Persons at Increased Risk: A Systematic Review for the Community Preventive Services Task Force. Ann Intern Med. 2015;163(6):437–451.
   PubMed Web of Science ®Google Scholar
• Waugh N. Screen and intervene to prevent diabetes? Bmj. 2017;356:i680.
   Google Scholar
• Zhuo X, Zhang P, Selvin E, et al. Alternative HbA1c cutoffs to identify high-risk adults for diabetes prevention: a cost-effectiveness perspective. Am J Prev Med. 2012;42(4):374–381.
   PubMed Web of Science ®Google Scholar
• Zhuo X, Zhang P, Kahn HS, et al. Cost-effectiveness of alternative thresholds of the fasting plasma glucose test to identify the target population for type 2 diabetes prevention in adults aged ≥45 years. Diabetes Care. 2013;36(12):3992–3998.
   PubMed Web of Science ®Google Scholar
• Glechner A, Keuchel L, Affengruber L, et al. Gartlehner GEffects of lifestyle changes on adults with prediabetes: A systematic review and meta-analysis. Prim Care Diabetes. 2018;12(5):393–408.
   PubMed Web of Science ®Google Scholar
• Martyn C. Risky business: doctors' understanding of statistics. BMJ. 2014;349:g5619.
   PubMedGoogle Scholar
• Järvinen TL. Labelling people as 'High Risk': A tyranny of eminence? Br J Sports Med. 2016;50(2):77–78.
   PubMed Web of Science ®Google Scholar