A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults

Abstract Identifying individuals at high risk for incident diabetes could help achieve targeted delivery of interventional programs. We aimed to develop a personalized diabetes prediction nomogram for the 3-year risk of diabetes among Chinese adults. This retrospective cohort study was among 32,312...

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Autores principales:	Yang Wu, Haofei Hu, Jinlin Cai, Runtian Chen, Xin Zuo, Heng Cheng, Dewen Yan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/89d5ce79bf4b4fba8f6779fc0d2cadb2
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spelling	oai:doaj.org-article:89d5ce79bf4b4fba8f6779fc0d2cadb22021-12-02T15:11:50ZA prediction nomogram for the 3-year risk of incident diabetes among Chinese adults10.1038/s41598-020-78716-12045-2322https://doaj.org/article/89d5ce79bf4b4fba8f6779fc0d2cadb22020-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-78716-1https://doaj.org/toc/2045-2322Abstract Identifying individuals at high risk for incident diabetes could help achieve targeted delivery of interventional programs. We aimed to develop a personalized diabetes prediction nomogram for the 3-year risk of diabetes among Chinese adults. This retrospective cohort study was among 32,312 participants without diabetes at baseline. All participants were randomly stratified into training cohort (n = 16,219) and validation cohort (n = 16,093). The least absolute shrinkage and selection operator model was used to construct a nomogram and draw a formula for diabetes probability. 500 bootstraps performed the receiver operating characteristic (ROC) curve and decision curve analysis resamples to assess the nomogram's determination and clinical use, respectively. 155 and 141 participants developed diabetes in the training and validation cohort, respectively. The area under curve (AUC) of the nomogram was 0.9125 (95% CI, 0.8887–0.9364) and 0.9030 (95% CI, 0.8747–0.9313) for the training and validation cohort, respectively. We used 12,545 Japanese participants for external validation, its AUC was 0.8488 (95% CI, 0.8126–0.8850). The internal and external validation showed our nomogram had excellent prediction performance. In conclusion, we developed and validated a personalized prediction nomogram for 3-year risk of incident diabetes among Chinese adults, identifying individuals at high risk of developing diabetes.Yang WuHaofei HuJinlin CaiRuntian ChenXin ZuoHeng ChengDewen YanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-16 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yang Wu Haofei Hu Jinlin Cai Runtian Chen Xin Zuo Heng Cheng Dewen Yan A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults
description	Abstract Identifying individuals at high risk for incident diabetes could help achieve targeted delivery of interventional programs. We aimed to develop a personalized diabetes prediction nomogram for the 3-year risk of diabetes among Chinese adults. This retrospective cohort study was among 32,312 participants without diabetes at baseline. All participants were randomly stratified into training cohort (n = 16,219) and validation cohort (n = 16,093). The least absolute shrinkage and selection operator model was used to construct a nomogram and draw a formula for diabetes probability. 500 bootstraps performed the receiver operating characteristic (ROC) curve and decision curve analysis resamples to assess the nomogram's determination and clinical use, respectively. 155 and 141 participants developed diabetes in the training and validation cohort, respectively. The area under curve (AUC) of the nomogram was 0.9125 (95% CI, 0.8887–0.9364) and 0.9030 (95% CI, 0.8747–0.9313) for the training and validation cohort, respectively. We used 12,545 Japanese participants for external validation, its AUC was 0.8488 (95% CI, 0.8126–0.8850). The internal and external validation showed our nomogram had excellent prediction performance. In conclusion, we developed and validated a personalized prediction nomogram for 3-year risk of incident diabetes among Chinese adults, identifying individuals at high risk of developing diabetes.
format	article
author	Yang Wu Haofei Hu Jinlin Cai Runtian Chen Xin Zuo Heng Cheng Dewen Yan
author_facet	Yang Wu Haofei Hu Jinlin Cai Runtian Chen Xin Zuo Heng Cheng Dewen Yan
author_sort	Yang Wu
title	A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults
title_short	A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults
title_full	A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults
title_fullStr	A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults
title_full_unstemmed	A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults
title_sort	prediction nomogram for the 3-year risk of incident diabetes among chinese adults
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/89d5ce79bf4b4fba8f6779fc0d2cadb2
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A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults

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