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Original Research

Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes

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Pages 1753-1762 | Published online: 21 May 2020

References

  • International Diabetes Federation. IDF Diabetes Atlas. 9thed. Brussels, Belgium; 2019. Available from: http://www.diabetesatlas.org. Accessed May 12, 2020.
  • Chung SM, Park JC, Moon JS, Lee JY. Novel nomogram for screening the risk of developing diabetes in a Korean population. Diabetes Res Clin Pract. 2018;142:286–293. doi:10.1016/j.diabres.2018.05.036
  • Wang K, Gong M, Xie S, et al. Nomogram prediction for the 3-year risk of type 2 diabetes in healthy mainland China residents. EPMA J. 2019;10:227–237. doi:10.1007/s13167-019-00181-2
  • Lin Z, Guo D, Chen J, Zheng B. A nomogram for predicting 5-year incidence of type 2 diabetes in a Chinese population. Endocrine. 2019;67.
  • Krabbe CEM, Schipf S, Ittermann T, Dorr M, Nauck M, Chenot JF, Markus MRP, Volzke H. Comparison of traditional diabetes risk scores and HbA1c to predict type 2 diabetes mellitus in a population based cohort study. J Diabetes Complications. 2017;31:1602–1607.
  • Okamura T, Hashimoto Y, Hamaguchi M, Obora A, Kojima T, Fukui M. Data from: ectopic fat obesity presents the greatest risk for incident type 2 diabetes: a population-based longitudinal study, Dryad, Dataset. Int J Obes. 2019;43(1):139–148. doi:10.5061/dryad.8q0p192
  • Okamura T, Hashimoto Y, Hamaguchi M, Obora A, Kojima T, Fukui M. Ectopic fat obesity presents the greatest risk for incident type 2 diabetes: a population-based longitudinal study. Int J Obes (Lond). 2019;43:139–148. doi:10.1038/s41366-018-0076-3
  • Yamagishi K, Iso H. The criteria for metabolic syndrome and the national health screening and education system in Japan. Epidemiol Health. 2017;39:e2017003. doi:10.4178/epih.e2017003
  • Leong A, Daya N, Porneala B, et al. Prediction of type 2 diabetes by hemoglobin a in two community-based cohorts. Diabetes Care. 2018;41:60–68. doi:10.2337/dc17-0607
  • Arbib N, Shmueli A, Salman L, Krispin E, Toledano Y, Hadar E. First trimester glycosylated hemoglobin as a predictor of gestational diabetes mellitus. Int J Gynaecol Obstet. 2019;145:158–163. doi:10.1002/ijgo.12794
  • Kang EY, Lo FS, Wang JP, et al. Nomogram for prediction of non-proliferative diabetic retinopathy in juvenile-onset type 1 diabetes: a cohort study in an Asian population. Sci Rep. 2018;8:12164. doi:10.1038/s41598-018-30521-7
  • Esposito K, Chiodini P, Maiorino MI, et al. A nomogram to estimate the HbA1c response to different DPP-4 inhibitors in type 2 diabetes: a systematic review and meta-analysis of 98 trials with 24 163 patients. BMJ Open. 2015;5:e005892. doi:10.1136/bmjopen-2014-005892
  • Hippisley-Cox J, Coupland C. Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study. BMJ. 2017;359:j5019. doi:10.1136/bmj.j5019
  • Nanri A, Nakagawa T, Kuwahara K, et al. Development of risk score for predicting 3-year incidence of type 2 diabetes: Japan epidemiology collaboration on occupational health study. PLoS One. 2015;10:e0142779. doi:10.1371/journal.pone.0142779
  • Kowall B, Rathmann W, Giani G, et al. Random glucose is useful for individual prediction of type 2 diabetes: results of the Study of Health in Pomerania (SHIP). Prim Care Diabetes. 2013;7(1):25–31. doi:10.1016/j.pcd.2012.12.001
  • Kodama S, Horikawa C, Fujihara K, et al. Comparisons of the strength of associations with future type 2 diabetes risk among anthropometric obesity indicators, including waist-to-height ratio: a meta-analysis. Am J Epidemiol. 2012;176:959–969. doi:10.1093/aje/kws172
  • Monnier L, Lapinski H, Colette C. Contributions of fasting and postprandial plasma glucose increments to the overall diurnal hyperglycemia of type 2 diabetic patients: variations with increasing levels of HbA(1c). Diabetes Care. 2003;26:881–885. doi:10.2337/diacare.26.3.881
  • Woerle HJ, Neumann C, Zschau S, et al. Impact of fasting and postprandial glycemia on overall glycemic control in type 2 diabetes Importance of postprandial glycemia to achieve target HbA1c levels. Diabetes Res Clin Pract. 2007;77:280–285. doi:10.1016/j.diabres.2006.11.011
  • Shahim B, De Bacquer D, De Backer G, et al. The prognostic value of fasting plasma glucose, two-hour postload glucose, and HbA in patients with coronary artery disease: a report from EUROASPIRE IV: a survey from the European Society of Cardiology. Diabetes Care. 2017;40:1233–1240). doi:10.2337/dc17-0245.
  • Lacy ME, Wellenius GA, Carnethon MR, et al. Racial differences in the performance of existing risk prediction models for incident type 2 diabetes: the CARDIA study. Diabetes Care. 2016;39:285–291. doi:10.2337/dc15-0509