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

Chun-Ming Ma, Fu-Zai Yin Department of Endocrinology, The First Hospital of Qinhuangdao, Qinhuangdao 066000, Hebei Province, People’s Republic of ChinaCorrespondence: Fu-Zai YinDepartment of Endocrinology, The First Hospital of Qinhuangdao, No. 258 Wenhua Road, Qinhuangdao 066000, Hebei Pr...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Ma CM, Yin FZ
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2020
Materias:	type 2 diabetes nomogram risk factor glycosylated hemoglobin a1c Specialties of internal medicine RC581-951
Acceso en línea:	https://doaj.org/article/27926f527f9b4096a4957d47ac72fea7
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:27926f527f9b4096a4957d47ac72fea7
record_format	dspace
spelling	oai:doaj.org-article:27926f527f9b4096a4957d47ac72fea72021-12-02T10:28:25ZGlycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes1178-7007https://doaj.org/article/27926f527f9b4096a4957d47ac72fea72020-05-01T00:00:00Zhttps://www.dovepress.com/glycosylated-hemoglobin-a1c-improves-the-performance-of-the-nomogram-f-peer-reviewed-article-DMSOhttps://doaj.org/toc/1178-7007Chun-Ming Ma, Fu-Zai Yin Department of Endocrinology, The First Hospital of Qinhuangdao, Qinhuangdao 066000, Hebei Province, People’s Republic of ChinaCorrespondence: Fu-Zai YinDepartment of Endocrinology, The First Hospital of Qinhuangdao, No. 258 Wenhua Road, Qinhuangdao 066000, Hebei Province, People’s Republic of ChinaTel +86-335-5908368Fax +86-335-3032042Email yinfuzai62@163.comAim: To develop and validate a model, which combines traditional risk factors and glycosylated hemoglobin A1c (HbA1c) for predicting the risk of type 2 diabetes (T2DM).Materials and Methods: This is a historical cohort study from a collected database, which included 8419 males and 7034 females without diabetes at baseline with a median follow-up of 5.8-years and 5.1-years, respectively. Multivariate cox regression analysis was used to select significant prognostic factors of T2DM. Two nomograms were constructed to predict the 5-year incidence of T2DM based on traditional risk factors (Model 1) and traditional risk factors plus HbA1c (Model 2). C-index, calibration curve, and time-dependent receiver-operating characteristic (ROC) curve were conducted in the training sets and validation sets.Results: In males, the C-index was 0.824 (95% CI: 0.795– 0.853) in Model 1 and 0.867 (95% CI: 0.840– 0.894) in Model 2; in females, the C-index was 0.830 (95% CI: 0.770– 0.890) in Model 1 and 0.856 (95% CI: 0.795– 0.917) in Model 2. The areas under curve (AUC) in Model 2 for prediction of T2DM development were higher than in Model 1 at each time point. The calibration curves showed excellent agreement between the predicted possibility and the actual observation in both models. The results of validation sets were similar to the results of training sets.Conclusion: The proposed nomogram can be used to accurately predict the risk of T2DM. Compared with the traditional nomogram, HbA1c can improve the performance of nomograms for predicting the 5-year incidence of T2DM.Keywords: type 2 diabetes, nomogram, risk factor, glycosylated hemoglobin A1cMa CMYin FZDove Medical Pressarticletype 2 diabetesnomogramrisk factorglycosylated hemoglobin a1cSpecialties of internal medicineRC581-951ENDiabetes, Metabolic Syndrome and Obesity: Targets and Therapy, Vol Volume 13, Pp 1753-1762 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	type 2 diabetes nomogram risk factor glycosylated hemoglobin a1c Specialties of internal medicine RC581-951
spellingShingle	type 2 diabetes nomogram risk factor glycosylated hemoglobin a1c Specialties of internal medicine RC581-951 Ma CM Yin FZ Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes
description	Chun-Ming Ma, Fu-Zai Yin Department of Endocrinology, The First Hospital of Qinhuangdao, Qinhuangdao 066000, Hebei Province, People’s Republic of ChinaCorrespondence: Fu-Zai YinDepartment of Endocrinology, The First Hospital of Qinhuangdao, No. 258 Wenhua Road, Qinhuangdao 066000, Hebei Province, People’s Republic of ChinaTel +86-335-5908368Fax +86-335-3032042Email yinfuzai62@163.comAim: To develop and validate a model, which combines traditional risk factors and glycosylated hemoglobin A1c (HbA1c) for predicting the risk of type 2 diabetes (T2DM).Materials and Methods: This is a historical cohort study from a collected database, which included 8419 males and 7034 females without diabetes at baseline with a median follow-up of 5.8-years and 5.1-years, respectively. Multivariate cox regression analysis was used to select significant prognostic factors of T2DM. Two nomograms were constructed to predict the 5-year incidence of T2DM based on traditional risk factors (Model 1) and traditional risk factors plus HbA1c (Model 2). C-index, calibration curve, and time-dependent receiver-operating characteristic (ROC) curve were conducted in the training sets and validation sets.Results: In males, the C-index was 0.824 (95% CI: 0.795– 0.853) in Model 1 and 0.867 (95% CI: 0.840– 0.894) in Model 2; in females, the C-index was 0.830 (95% CI: 0.770– 0.890) in Model 1 and 0.856 (95% CI: 0.795– 0.917) in Model 2. The areas under curve (AUC) in Model 2 for prediction of T2DM development were higher than in Model 1 at each time point. The calibration curves showed excellent agreement between the predicted possibility and the actual observation in both models. The results of validation sets were similar to the results of training sets.Conclusion: The proposed nomogram can be used to accurately predict the risk of T2DM. Compared with the traditional nomogram, HbA1c can improve the performance of nomograms for predicting the 5-year incidence of T2DM.Keywords: type 2 diabetes, nomogram, risk factor, glycosylated hemoglobin A1c
format	article
author	Ma CM Yin FZ
author_facet	Ma CM Yin FZ
author_sort	Ma CM
title	Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes
title_short	Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes
title_full	Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes
title_fullStr	Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes
title_full_unstemmed	Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes
title_sort	glycosylated hemoglobin a1c improves the performance of the nomogram for predicting the 5-year incidence of type 2 diabetes
publisher	Dove Medical Press
publishDate	2020
url	https://doaj.org/article/27926f527f9b4096a4957d47ac72fea7
work_keys_str_mv	AT macm glycosylatedhemoglobina1cimprovestheperformanceofthenomogramforpredictingthe5yearincidenceoftype2diabetes AT yinfz glycosylatedhemoglobina1cimprovestheperformanceofthenomogramforpredictingthe5yearincidenceoftype2diabetes
_version_	1718397161963520000

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

Ejemplares similares