ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Clinical Diabetes
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1560631
This article is part of the Research TopicImpact of Hormonal Imbalance in Obesity on Respiratory Diseases: Molecular Mechanisms, Regulatory Pathways, and ReceptorsView all articles
Construction and validation of a prediction model for developing type 2 diabetes mellitus in patients with chronic obstructive pulmonary disease
Provisionally accepted
- 1Lanzhou University, Lanzhou, China
- 2First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China
- 3Quzhou City People's Hospital, Quzhou, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Type 2 diabetes mellitus (T2DM) was a common comorbidity of chronic obstructive pulmonary disease (COPD) increasing rehospitalization and mortality risk. This study aimed to identify influencing factors of COPD with T2DM and construct a visualized prediction model. We included medical records of 1773 COPD patients treated at Quzhou People's Hospital from 2020 to 2023. Subjects were randomly divided into a training set (n=1241) and test set (n=532) (7:3 ratio). Variable selection was performed using LASSO, Pearson correlation, and multicollinearity diagnosis. Variables were refined via backward stepwise selection (AIC) to construct a nomogram. Model accuracy was evaluated using ROC curves, calibration curves, and the Hosmer-Lemeshow test. Clinical utility was assessed via decision analysis curves. Ten-fold cross-validation assessed stability and overfitting risk. Sex-stratified subgroup analysis addressed potential bias. T2DM prevalence in COPD patients was 27.13%. Seven independent predictors were identified: Arterial PCO₂ (OR=1.04, 95%CI:1.02-1.05), neutrophil count (NEUT) (OR=1.15, 95%CI:1.10-1.19), CRP (OR=1.01, 95%CI:1.01-1.02), ESR (OR=1.03, 95%CI:1.02-1.05), bilirubin (OR=0.92, 95%CI:0.88-0.96), TG (OR=1.33, 95%CI:1.13-1.56), and BMI (OR=1.16, 95%CI:1.11-1.20). The model demonstrated good predictive performance (C-index=0.78). AUC values were 0.79 (training, 95%CI:0.76-0.81) and 0.80 (test, 95%CI:0.76-0.84), consistent with 10-fold CV average AUC (0.79, 95%CI:0.76-0.81). Calibration curves and H-L test (P>0.05) indicated good agreement. DCA demonstrated clinical utility. Subgroup analysis showed robust performance in males (AUC=0.82, 95%CI:0.77-0.86) and females (AUC=0.71, 95%CI:0.60-0.83), with no significant difference (DeLong P=0.101). We developed and internally validated a visualized prediction model for early T2DM identification in COPD patients. This tool may facilitate prevention strategies. While performance was good, external validation is required.
Keywords: chronic obstructive pulmonary disease, Type 2 mellitus diabetes, complication, prediction, nomogram
Received: 14 Jan 2025; Accepted: 24 Jul 2025.
Copyright: © 2025 Kang, Li, Chen, Xu, Jiang, Zhao and Chang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Hongjun Zhao, Quzhou City People's Hospital, Quzhou, 324000, China
Xuhong Chang, Lanzhou University, Lanzhou, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.