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The Cutoff Value of HbA1c in Predicting Diabetes and Impaired Fasting Glucose

당뇨병 및 공복혈당장애 예측을 위한 당화혈색소 값

  • Kwon, Seyoung (Department of Biomedical Laboratory Science, Daegu Health College) ;
  • Na, Youngak (Department of Biomedical Laboratory Science, Daegu Health College)
  • 권세영 (대구보건대학교 임상병리과) ;
  • 나영악 (대구보건대학교 임상병리과)
  • Received : 2017.04.30
  • Accepted : 2017.05.16
  • Published : 2017.06.30

Abstract

There have been many studies to develop methods for predicting diabetes and to prevent diabetes. The validity of glycated hemoglobin (HbA1c), one of the commonly known tools in predicting diabetes, has been verified by many previous studies. In this study, we examined the cutoff value of HbA1c for diabetes and impaired fasting glucose (IFG). Based on this study, we proposed a proper clinical guideline and evaluated the validation of the guideline. Excluding those without blood glucose and HbA1c data, we used the data of 5,161 subjects (2,281 men and 2,880 women) over the age of 20 years from the 2015 Korean National Health and Nutrition Examination Survey. The correlation efficient of fasting plasma glucose (FPG) and HbA1c was 0.79, indicating a strong relationship. Howeve, the correlation efficient of FPG and HbA1c was low, showing 0.27 in non-diabetes, 0.39 in IFG, and 0.66 in diabetes, showing a strong relationship. The cutoff value of HbA1c for predicting diabetes using ROC curve was 6.05% (sensitivity 84.6%, and specificity 92.0%), and AUC was 0.941 (0.937 in men, and 0.946 in women). The cutoff value of HbA1c for predicting IFG using ROC curve was 5.55% (sensitivity 64.5%, and specificity 70.0%), and AUC was 0.733 (0.708 in men, and 0.764 in women). Therefore, it may not be appropriate to apply the guidelines for diagnosing IFG since sensitivity and specificity were below 70%. For future studies retarding the cutoff value of HbA1c in predicting IFG, high sensitivity and specificity are expected if we segment the reference range of IFG.

증가하고 있는 당뇨병을 예방하기 위한 연구와 함께 당뇨병의 진단 및 예측을 할 수 있는 방법에 대한 연구도 꾸준히 진행되고 있다. 가장 널리 알려져 있는 당화혈색소는 여러 선행 연구에서 그 타당성이 검증되었다. 본 연구에서는 당뇨군 및 공복혈당장애군에 대한 당화혈색소 분별점을 살펴보고, 당뇨군 및 공복혈당장애군 분별을 위한 적절한 임상 적용 기준에 대한 자료를 제시하고 이에 대한 타당성 여부를 평가해 보고자 하였다. 2015 국민건강영양조사 데이터 중 측정치 누락자를 제외한 20세 이상 대상자 5,161명(남성 2,281명, 여성 2,880명)의 자료를 이용하였다. 대상자 전체의 공복혈당과 당화혈색소의 상관계수는 0.79로 나타나 강한 상관성이 입증되었다. 그러나 비당뇨군에서 공복혈당과 당화혈색소의 상관계수는 0.27, 공복혈당장애군에서는 0.39, 당뇨군에서는 0.66으로 나타나 당뇨군에서는 상관성이 높은 반면, 비당뇨군과 공복혈당장애군에서 상관계수는 상대적으로 낮았다. ROC curve를 이용하여 당뇨병을 예측하기 위한 당화혈색소 cutoff값은 남녀 모두 6.05%(sensitivity 84.6%, specificity 92.0%)로 나타났으며, AUC는 0.941 (남성의 경우 0.937, 여성의 경우 0.946)이었다. 반면에 공복혈당장애를 예측하기 위한 당화혈색소 cutoff값은 5.55%(sensitivity 64.5%, specificity 70.0%), AUC는 0.733 (남성의 경우 0.708, 여성의 경우 0.764)으로 나타났다. 이로써 민감도와 특이도 모두 70% 이하로 낮게 나온 공복혈당장애의 경우 진단 기준으로 적용하기에는 무리가 있다. 추후 공복혈당장애 예측을 위한 분별점의 연구에서는 공복혈당범위를 세분화하여 적용하면 좀 더 민감도와 특이도가 높은 분별점을 설정할 수 있을 것으로 보인다.

Keywords

References

  1. Kim DJ. The epidemiology of diabetes in Korea. Diabetes Metab J. 2011;35(4):303-308. https://doi.org/10.4093/dmj.2011.35.4.303
  2. American Diabetes Association. Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabetes Care. 1997;20(7):1183-1197. https://doi.org/10.2337/diacare.20.7.1183
  3. International Expert Committee. International expert committee report on the role of the A1c assay in the diagnosis of diabetes. Diabetes Care. 2009;32(7):1327-1334. https://doi.org/10.2337/dc09-9033
  4. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33(Suppl 1):62-69. https://doi.org/10.2337/dc10-S062
  5. Ko SH, Kim SR, Kim DJ, Oh SJ, Lee HJ, Shim KH, et al. Committee of Clinical Practice Guidelines, Korean Diabetes Association. 2011 Clinical practice guidelines for type 2 diabetes in Korea. Diabetes Metab J. 2011;35(5):431-436. https://doi.org/10.4093/dmj.2011.35.5.431
  6. Cowie CC, Rust KF, Byrd-Holt DD, Gregg EW, Ford ES, Geiss LS, et al. Prevalence of diabetes and high risk for diabetes using A1C criteria in the U.S. population in 1988-2006. Diabetes Care. 2010;33(3):562-568. https://doi.org/10.2337/dc09-1524
  7. Herman WH, Ma Y, Uwaifo G, Haffner S, Kahn SE, Horton ES, et al. Diabetes Prevention Program Research Group. Differences in A1C by race and ethnicity among patients with impaired glucose tolerance in the Diabetes Prevention Program. Diabetes Care. 2007;30(10):2453-2457. https://doi.org/10.2337/dc06-2003
  8. Korea Centers for Disease Control and Prevention. The Sixth Korea National Health and Nutrition Examination Survey (KNHANES VI-3) [Internet]. Cheongju: Korea Centers for Disease Control and Prevention; 2015 [cited 2017 April 10]. Available from: https://knhanes.cdc.go.kr/knhanes/index.do
  9. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2004;27(suppl 1):5-10. https://doi.org/10.2337/diacare.27.2007.S5
  10. Jeon JY, Ko SH, Kwon HS, Kim NH, Kim JH, Kim CS, et al. Prevalence of diabetes and prediabetes according to fasting plasma glucose and HbA1c. Diabetes Metab J. 2013;37(5):349-357. https://doi.org/10.4093/dmj.2013.37.5.349
  11. Kwon PS, Rheem IS. The assessment of blood glucose distribution according to the fasting state and glycemic control indicators for diabetes screening. Korean J Clin Lab Sci. 2016;48(4):312-320. https://doi.org/10.15324/kjcls.2016.48.4.312
  12. Kim JH, Kim GW, Lee MY, Shin JY, Shin YG, Koh SB, et al. Role of HbA1c in the screening of diabetes mellitus in a Korean rural community. Diabetes Metab J. 2012;36(1):37-42. https://doi.org/10.4093/dmj.2012.36.1.37
  13. Ryu AJ, Moon HJ, Na JO, Na YJ Kim, Kim SJ, Mo SI, et al. The usefulness of the glycosylated hemoglobin level for the diagnosis of gestational diabetes mellitus in the Korean population. Diabetes Metab J. 2015;39(6):507-511. https://doi.org/10.4093/dmj.2015.39.6.507
  14. Buell C, Kermah D, Davidson MB. Utility of A1C for diabetes screening in the 1999-2004 NHANES population. Diabetes Care. 2007;30(9):2233-2235. https://doi.org/10.2337/dc07-0585
  15. Herman WH, Ma Y, Uwaifo G, Haffner S, Kahn SE, Horton ES, et al. Differences in A1C by race and ethnicity among patients with impaired glucose tolerance in the Diabetes Prevention Program. Diabetes Care. 2007;30(10):2453-2457. https://doi.org/10.2337/dc06-2003
  16. Ziemer DC, Kolm P, Weintraub WS, Vaccarino V, Rhee MK, Twombly JG, et al. Glucose-independent, black-white differences in hemoglobin A1c levels: a cross-sectional analysis of 2 studies. Ann Intern Med. 2010;152(12):770-777. https://doi.org/10.7326/0003-4819-152-12-201006150-00004
  17. Bae JC, Rhee EJ, Choi ES, Kim JH, Kim WJ, Yoo SH, et al. The cutoff value of HbA1c in predicting diabetes in Korean adults in a university hospital in Seoul. Korean Diabetes J. 2009;33(6):503-510. https://doi.org/10.4093/kdj.2009.33.6.503
  18. Kim KS, Kim SK, Lee YK, Park SW, Cho YW. Diagnostic value of glycated hemoglobin (HbA1c) for the early detection of diabetes in high risk subjects. Diabet Med. 2008;25(8):997-1000. https://doi.org/10.1111/j.1464-5491.2008.02489.x
  19. Lee YS, Moon SS. The use of HbA1c for diagnosis of type 2 diabetes in Korea. Korean J Med. 2011;80(3):291-297.
  20. Lee H, Oh JY, Sung YA, Kim DJ, Kim SH, Kim SG, et al. Optimal hemoglobin A1C cutoff value for diagnosing type 2 diabetes mellitus in Korean adults. Diabetes Res Clin Pract. 2013;99(2):231-236. https://doi.org/10.1016/j.diabres.2012.09.030
  21. Hong SM, Kang JG, Kim CS, Lee SN, Park CY, Lee CB, et al. Glycosylated hemoglobin threshold for predicting diabetes and prediabetes from the fifth Korea National Health and Nutrition Examination Survey. Diabetes Metab J. 2016;40(2):167-170. https://doi.org/10.4093/dmj.2016.40.2.167
  22. Cho NH, Kim TH, Woo SJ, Park KH, Lim S, Cho YM, et al. Optimal HbA1c cutoff for detecting diabetic retinopathy. Acta Diabetol. 2013;50(6):837-842. https://doi.org/10.1007/s00592-013-0452-3
  23. Lim NK, Park SH, Choi SJ, Lee KS, Park HY. A risk score for predicting the incidence of type 2 diabetes in a middle-aged Korean cohort: the Korean genome and epidemiology study. Circ J. 2012;76(8):1904-1910. https://doi.org/10.1253/circj.CJ-11-1236
  24. Choi SH, Kim TH, Lim S, Park KS, Jang HC, Cho NH. Hemoglobin A1c as a diagnostic tool for diabetes screening and new-onset diabetes prediction: a 6-year community-based prospective study. Diabetes Care 2011;34(4):944-949. https://doi.org/10.2337/dc10-0644
  25. Kim HK, Bae SJ, Choe JO. Impact of HbA1c criterion on the detection of subjects with increased risk for diabetes among health check-up recipients in Korea. Diabetes Metab J. 2012;36(2):151-156. https://doi.org/10.4093/dmj.2012.36.2.151

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