Large-Scale Comparative Analysis Reveals A Simple Model To Predict The Prevalence Of Thyroid Nodules
Authors Li G, Wang L, Lei J, Song L, Tang H, Li Z, Gong R, Zhu J
Received 26 August 2019
Accepted for publication 3 October 2019
Published 14 November 2019 Volume 2019:12 Pages 225—232
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Marco Carotenuto
Genpeng Li,1,* Lijuan Wang,1,* Jianyong Lei,1 Linlin Song,1 Huairong Tang,2 Zhihui Li,1 Rixiang Gong,1 Jingqiang Zhu1
1Thyroid and Parathyroid Surgery Center, West China Hospital of Sichuan University, Chengdu 610041, People’s Republic of China; 2Health and Management Center, West China Hospital of Sichuan University, Chengdu 610041, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Huairong Tang
Health and Management Center, West China Hospital of Sichuan University, Chengdu 610041, People’s Republic of China
Background: The frequency of thyroid nodules (TNs) has increased rapidly in recent decades. We established a simple, effective model to predict TN occurrence by a large-scale comparative analysis of the Chinese population.
Subjects and methods: A total of 13,307 subjects were included to screen risk factors between the case group (TN+) and the control group (TN-) by univariate and multivariate analyses. A simple prediction model formed by a subset of five factors was established. The optimal index points for predicting the prevalence of TNs, the model discriminatory power and the association of the model with the size of TNs were assessed.
Results: Age at diagnosis ≥45 years, female sex, body mass index (BMI) ≥24 kg/m2, hypertension, antithyroglobulin antibody (TGAB) ≥16.5 IU/mL were independently related to an increased risk of TNs. The cutoff value of 4 points was found to be the best prediction for the prevalence of TNs in the current study, and the model had better discriminatory power than other single independent predictors. In addition, a positive correlation was also found between the index points and the diameter of TNs.
Conclusion: Based on our prediction model, thyroid high-resolution ultrasound and associated laboratory tests may be necessary for patients with index points ≥4 due to a higher prevalence of thyroid nodules.
Keywords: thyroid nodules, large-scale, risk factors, prediction model
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