Construction and Evaluation of a Nomogram to Predict Gallstone Disease Based on Body Composition

Jian-Hui Lu; Gen-Xi Tong; Xiang-Yun Hu; Rui-Fang Guo; Shi Wang

doi:10.2147/IJGM.S367642

Construction and Evaluation of a Nomogram to Predict Gallstone Disease Based on Body Composition

Int J Gen Med. 2022 Jul 2:15:5947-5956. doi: 10.2147/IJGM.S367642. eCollection 2022.

Authors

Jian-Hui Lu¹, Gen-Xi Tong², Xiang-Yun Hu², Rui-Fang Guo¹, Shi Wang²

Affiliations

¹ Department of Clinical Nutrition Center, Inner Mongolia People's Hospital, Hohhot, Inner Mongolia, People's Republic of China.
² Department of Hepatobiliary, Pancreatic and Spleen Surgery, Inner Mongolia People's Hospital, Hohhot, Inner Mongolia, People's Republic of China.

Abstract

Purpose: We aimed to analyze the body composition characteristics of gallstone disease (GD) patients with bioelectrical impedance analysis (BIA) and to construct a nomogram to predict GD based on body composition.

Methods: Patients with or without symptomatic cholecystolithiasis or choledocholithiasis diagnosed in Inner Mongolia People's Hospital from July 2020 to December 2021 were selected as the case group, and healthy subjects during the same period were selected as the control group. The body composition of the two groups was determined by BIA. The risk predictors for GD were extracted to construct a nomogram based on regression analysis. ROC curves were used to evaluate the predictive power of the nomogram, and calibration curves were drawn to evaluate the consistency of the model. The bootstrap method was used to verify the model and evaluate the generalizability of the model.

Results: A total of 1000 individuals were recruited for the study, including 500 GD cases and 500 controls, to evaluate body composition. Multivariate logistic regression analysis showed that sex (OR = 2.292, 95% CI: 1.436-3.660), BMI (OR = 1.828, 95% CI: 1.738-1.929), body fat percentage (BFP) (OR = 1.904, 95% CI: 1.811-2.205) and waist circumference (WC) (OR = 1.934, 95% CI: 1.899-1.972) were risk predictors of GD. The AUC was 0.770 (95% CI: 0.741-0.799). The calibration curve showed that the C-index was 0.767. The prediction model was validated internally with 1000 bootstrap resamples. The accurate value was 0.72, and the kappa value was 0.43. All of the indices indicated that the model was well constructed and could be used to predict the incidence of GD.

Conclusion: A nomogram model of gallstone disease based on sex, BMI, BFP and WC was constructed with good discrimination, calibration and generalizability and can be used for the noninvasive and convenient prediction of gallstone disease in the general population.

Keywords: BIA; bioelectrical impedance analysis; body composition; cholelithiasis; gallstone disease; nomogram; prediction model.

Grants and funding

This study was funded by the Natural Science Fund Project of Inner Mongolia (No.: 2019 MS08081) and Science and Technology Planning Project of Inner Mongolia (No.: 201602097).