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. 2022 Jul 15;14(7):4505-4514.
eCollection 2022.

Establishment and validation of a nomogram that predicts the risk of type 2 diabetes in obese patients with non-alcoholic fatty liver disease: a longitudinal observational study

Xintian Cai  1   2 , Mengru Wang  1 , Shasha Liu  1 , Yujuan Yuan  1 , Junli Hu  1 , Qing Zhu  1 , Jing Hong  1 , Guzailinuer Tuerxun  1 , Huimin Ma  1 , Nanfang Li  1
Affiliations

Establishment and validation of a nomogram that predicts the risk of type 2 diabetes in obese patients with non-alcoholic fatty liver disease: a longitudinal observational study

Xintian Cai et al. Am J Transl Res. .

Abstract

Objective: This study aimed to establish and validate a nomogram for better assessment of the risk of type 2 diabetes (T2D) in obese patients with non-alcoholic fatty liver disease (NAFLD) based on independent predictors.

Methods: Of 1820 eligible participants from the NAGALA cohort enrolled in the study. Multivariate Cox regression was employed to construct the nomogram. The performance was assessed by area under the receiver operating characteristic curve (AUC), C-index, calibration curve, decision curve analysis, and Kaplan-Meier analysis.

Results: Five predictors were selected from 17 variables. The AUC values at different time points all indicated that the model constructed with these five predictors had good predictive power. Decision curves indicated that the model could be applied to clinical applications.

Conclusions: We established and validated a reasonable, economical nomogram for predicting the risk of T2D in obese NAFLD patients. This simple clinical tool can help with risk stratification and thus contribute to the development of effective prevention programs against T2D in obese patients with NAFLD.

Keywords: Type 2 diabetes; cohort study; nomogram; non-alcoholic fatty liver disease; obesity.

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Conflict of interest statement

None.

Figures

Figure 1
Figure 1
Flow chart.
Figure 2
Figure 2
Texture feature selection using the least absolute shrinkage selection operator regression. A. Optimal parameter selection. B. Coefficient profiles.
Figure 3
Figure 3
Forest plot.
Figure 4
Figure 4
Nomogram to predict risk of type 2 diabetes in obese patients with non-alcoholic fatty liver disease.
Figure 5
Figure 5
Performance evaluation. A. Training cohort. B. Validation cohort.
Figure 6
Figure 6
Calibration curves. A. Training cohort. B. Validation cohort.
Figure 7
Figure 7
Kaplan-Meier curves.
Figure 8
Figure 8
Decision curve analysis. A. Training cohort. B. Validation cohort.
See this image and copyright information in PMC

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