Nomogram for Predicting Risk of Digestive Carcinoma Among Patients with Type 2 Diabetes

Lu-Huai Feng,1 Kun-Peng Bu,1 Shuang Ren,1 Zhenhua Yang,2 Bi-Xun Li,1 Cheng-En Deng3 1Department of Comprehensive Internal Medicine, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Nephrology, The First Affiliated Hospital of...

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Autores principales:	Feng LH, Bu KP, Ren S, Yang Z, Li BX, Deng CE
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2020
Materias:	type 2 diabetes digestive cancer prediction demographic Specialties of internal medicine RC581-951
Acceso en línea:	https://doaj.org/article/7cc1385a652342b7a862e67b5033d312
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spelling	oai:doaj.org-article:7cc1385a652342b7a862e67b5033d3122021-12-02T12:35:11ZNomogram for Predicting Risk of Digestive Carcinoma Among Patients with Type 2 Diabetes1178-7007https://doaj.org/article/7cc1385a652342b7a862e67b5033d3122020-05-01T00:00:00Zhttps://www.dovepress.com/nomogram-for-predicting-risk-of-digestive-carcinoma-among-patients-wit-peer-reviewed-article-DMSOhttps://doaj.org/toc/1178-7007Lu-Huai Feng,1 Kun-Peng Bu,1 Shuang Ren,1 Zhenhua Yang,2 Bi-Xun Li,1 Cheng-En Deng3 1Department of Comprehensive Internal Medicine, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 3Department of Urology, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning, People’s Republic of ChinaCorrespondence: Cheng-En DengDepartment of Urology, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, People’s Republic of ChinaTel +86 18775391817Fax +86 771-5719573Email dengchengen66@126.comBi-Xun LiDepartment of Comprehensive Internal Medicine, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, People’s Republic of ChinaTel +86 18977100069Fax +86 771-5719573Email libixun@126.comPurpose: Digestive carcinomas remain a major health burden worldwide and are closely related to type 2 diabetes. The aim of this study was to develop and validate a digestive carcinoma risk prediction model to identify high-risk individuals among those with type 2 diabetes.Patients and Methods: The prediction model was developed in a primary cohort that consisted of 655 patients with type 2 diabetes. Data were collected from November 2013 to December 2018. Clinical parameters and demographic characteristics were analyzed by logistic regression to develop a model to predict the risk of digestive carcinomas; then, a nomogram was constructed. The performance of the nomogram was assessed with respect to calibration, discrimination, and clinical usefulness. The results were internally validated by a bootstrapping procedure. The independent validation cohort consisted of 275 patients from January 2019 to December 2019.Results: Predictors in the prediction nomogram included sex, age, insulin use, and body mass index. The model showed good discrimination (C-index 0.747 [95% CI, 0.718– 0.791]) and calibration (Hosmer–Lemeshow test P=0.541). The nomogram showed similar discrimination in the validation cohort (C-index 0.706 [95% CI, 0.682– 0.755]) and good calibration (Hosmer–Lemeshow test P=0.418). Decision curve analysis demonstrated that the nomogram would be clinically useful.Conclusion: We developed a low-cost and low-risk model based on clinical and demographic parameters to help identify patients with type 2 diabetes who might benefit from digestive cancer screening.Keywords: type 2 diabetes, digestive cancer, prediction, demographicFeng LHBu KPRen SYang ZLi BXDeng CEDove Medical Pressarticletype 2 diabetesdigestive cancerpredictiondemographicSpecialties of internal medicineRC581-951ENDiabetes, Metabolic Syndrome and Obesity: Targets and Therapy, Vol Volume 13, Pp 1763-1770 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	type 2 diabetes digestive cancer prediction demographic Specialties of internal medicine RC581-951
spellingShingle	type 2 diabetes digestive cancer prediction demographic Specialties of internal medicine RC581-951 Feng LH Bu KP Ren S Yang Z Li BX Deng CE Nomogram for Predicting Risk of Digestive Carcinoma Among Patients with Type 2 Diabetes
description	Lu-Huai Feng,1 Kun-Peng Bu,1 Shuang Ren,1 Zhenhua Yang,2 Bi-Xun Li,1 Cheng-En Deng3 1Department of Comprehensive Internal Medicine, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 3Department of Urology, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning, People’s Republic of ChinaCorrespondence: Cheng-En DengDepartment of Urology, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, People’s Republic of ChinaTel +86 18775391817Fax +86 771-5719573Email dengchengen66@126.comBi-Xun LiDepartment of Comprehensive Internal Medicine, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, People’s Republic of ChinaTel +86 18977100069Fax +86 771-5719573Email libixun@126.comPurpose: Digestive carcinomas remain a major health burden worldwide and are closely related to type 2 diabetes. The aim of this study was to develop and validate a digestive carcinoma risk prediction model to identify high-risk individuals among those with type 2 diabetes.Patients and Methods: The prediction model was developed in a primary cohort that consisted of 655 patients with type 2 diabetes. Data were collected from November 2013 to December 2018. Clinical parameters and demographic characteristics were analyzed by logistic regression to develop a model to predict the risk of digestive carcinomas; then, a nomogram was constructed. The performance of the nomogram was assessed with respect to calibration, discrimination, and clinical usefulness. The results were internally validated by a bootstrapping procedure. The independent validation cohort consisted of 275 patients from January 2019 to December 2019.Results: Predictors in the prediction nomogram included sex, age, insulin use, and body mass index. The model showed good discrimination (C-index 0.747 [95% CI, 0.718– 0.791]) and calibration (Hosmer–Lemeshow test P=0.541). The nomogram showed similar discrimination in the validation cohort (C-index 0.706 [95% CI, 0.682– 0.755]) and good calibration (Hosmer–Lemeshow test P=0.418). Decision curve analysis demonstrated that the nomogram would be clinically useful.Conclusion: We developed a low-cost and low-risk model based on clinical and demographic parameters to help identify patients with type 2 diabetes who might benefit from digestive cancer screening.Keywords: type 2 diabetes, digestive cancer, prediction, demographic
format	article
author	Feng LH Bu KP Ren S Yang Z Li BX Deng CE
author_facet	Feng LH Bu KP Ren S Yang Z Li BX Deng CE
author_sort	Feng LH
title	Nomogram for Predicting Risk of Digestive Carcinoma Among Patients with Type 2 Diabetes
title_short	Nomogram for Predicting Risk of Digestive Carcinoma Among Patients with Type 2 Diabetes
title_full	Nomogram for Predicting Risk of Digestive Carcinoma Among Patients with Type 2 Diabetes
title_fullStr	Nomogram for Predicting Risk of Digestive Carcinoma Among Patients with Type 2 Diabetes
title_full_unstemmed	Nomogram for Predicting Risk of Digestive Carcinoma Among Patients with Type 2 Diabetes
title_sort	nomogram for predicting risk of digestive carcinoma among patients with type 2 diabetes
publisher	Dove Medical Press
publishDate	2020
url	https://doaj.org/article/7cc1385a652342b7a862e67b5033d312
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Nomogram for Predicting Risk of Digestive Carcinoma Among Patients with Type 2 Diabetes

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