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Development and validation of a nomogram prediction model for thyroid dysfunction in patients with type 2 diabetes mellitus
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  • Published: 24 January 2026

Development and validation of a nomogram prediction model for thyroid dysfunction in patients with type 2 diabetes mellitus

  • Yinghao Niu1 na1,
  • Zhihua Chen2 na1,
  • Yating Li2,
  • Li Liu2,
  • Xuan Wang2,
  • Jun Wang2 &
  • …
  • Dan Song2 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Diabetes
  • Medical research
  • Risk factors

Abstract

Research has shown that the concurrent presence of Diabetes Mellitus (DM) and Thyroid Dysfunction (TD) can exacerbate diabetes-related complications and impose a significant economic burden on healthcare systems. Therefore, this study aimed to develop a nomogram model for predicting the risk of TD in patients with Type 2 Diabetes Mellitus (T2DM) and to validate its predictive performance. A total of 1853 patients with T2DM diagnosed at the First Hospital of Hebei Medical University from 2019 to 2024 were included in the study. The dataset was randomly divided into a training set (n = 1297) and a validation set (n = 556) at a 7:3 ratio using the R software. Univariate and multivariate logistic regression analyses were conducted to identify predictors of TD, and these predictors were used to construct the nomogram model. The model was evaluated using the receiver operating characteristic (ROC) curve and the area under the curve (AUC), calibration curve, the Hosmer-Lemeshow test, and decision curve analysis (DCA). HDL-C, BUN, gender, GLU, Hypertension, Hyperuricemia, Coronary Heart Disease, and Liver disease were identified as predictors of TD. A nomogram model was constructed based on these eight factors. The model demonstrated good discrimination in both the training and validation sets. The calibration curves indicated a good fit of the model in both datasets. The decision curve analysis showed that the model had good clinical applicability. The nomogram developed in this study can predict the risk of developing TD in patients with T2DM. It enables clinicians to identify T2DM patients at high risk of concurrent TD, which may help facilitate the development of effective preventive measures and improve patient prognosis.

Data availability

The data are available upon reasonable request from the corresponding author.

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Funding

This study was sponsored by grants from the Medical Research Institute of Hebei Province (20201143) and the Medical Science Research Project of Hebei (20241554).

Author information

Author notes
  1. These authors contributed equally: Yinghao Niu and Zhihua Chen.

Authors and Affiliations

  1. Department of Clinical Biobank, The First Hospital of Hebei Medical University, Shijiazhuang, 050031, Hebei, China

    Yinghao Niu

  2. Department of Endocrinology, The First Hospital of Hebei Medical University, Shijiazhuang, 050031, Hebei, China

    Zhihua Chen, Yating Li, Li Liu, Xuan Wang, Jun Wang & Dan Song

Authors
  1. Yinghao Niu
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  2. Zhihua Chen
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  3. Yating Li
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  4. Li Liu
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  6. Jun Wang
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  7. Dan Song
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Contributions

J.W. and D.S. conceived and supervised the project. Y.H.N. and Z.H.C. contributed to the design of the study. Y.T.L. L.L and X.W. contributed to the acquisition and analysis of the data. Y.H.N. wrote the main manuscript text. All authors reviewed and approved the submitted manuscript.

Corresponding authors

Correspondence to Jun Wang or Dan Song.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethical approval

The Medical Ethics Committee of the First Hospital of Hebei Medical University approved this study. Informed consent was waived by the Medical Ethics Committee of the First Hospital of Hebei Medical University since it was a retrospective study.

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Supplementary Information

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Supplementary Material 1

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Cite this article

Niu, Y., Chen, Z., Li, Y. et al. Development and validation of a nomogram prediction model for thyroid dysfunction in patients with type 2 diabetes mellitus. Sci Rep (2026). https://doi.org/10.1038/s41598-026-36582-3

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  • Received: 25 December 2024

  • Accepted: 14 January 2026

  • Published: 24 January 2026

  • DOI: https://doi.org/10.1038/s41598-026-36582-3

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Keywords

  • Type 2 diabetes mellitus
  • Thyroid disorders
  • Nomogram
  • Risk factor
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