Zhifeng Zhao1, Tongxin Ren2, Yanna Zhao3, Wenjuan Xu3, Rongli Xie4, Jiayun Lin1, Hongjie Li1, Lei Zheng1, Chihao Zhang1, Haizhong Huo1, Meng Luo1, Jian Fei5, Jianhua Gu6. 1. Department of General Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. 2. Student Innovation Center, Shanghai Jiao Tong University, Shanghai, China. 3. Department of Ultrasonography, Shanghai Ruijin Rehabilitation Hospital, Shanghai, China. 4. Department of General Surgery, Luwan Branch, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China. 5. Department of General Surgery, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China. 6. Department of General Surgery, Shanghai Ruijin Rehabilitation Hospital, Shanghai, China.
Abstract
BACKGROUND: The incidence of papillary thyroid cancer (PTC) is increasing annually. ultrasonography (US) is the current primary method for evaluating thyroid nodules; however, there have been persisting challenges in diagnosing borderline malignancies. This paper aimed to establish the differential diagnostic value of salivary biomarkers for thyroid nodules geared towards improving the efficacy of US. METHODS: We recruited a total of 44 PTC patients and 42 benign thyroid tumor (BTT) patients to this study. The distribution of tumor markers and thyroid hormones in saliva and serum were compared between groups; then, uni-/multi-variate logistic analyses were used to determine the risk factors of PTC. Further, we estimated the differential diagnostic value of biomarkers in thyroid nodules, especially in borderline scenarios. Finally, a multi-index diagnostic model was constructed constituting biomarkers and US. RESULTS: The distributions of serum thyroglobulin (TG), salivary triiodothyronine (T3), free-triiodothyronine (FT3), and free-thyroxine (FT4) were significantly different in BTT and PTC (P<0.05); salivary FT3 was identified as an independent risk factor for PTC. By analyzing the diagnostic accuracy of various Thyroid Imaging Reporting and Data System (TI-RADS) categories, category 4A was shown to have the lowest diagnostic accuracy (48.39%) with the largest proportion (31 people, 36.05%). In 4A patients, the K-nearest neighbor (KNN) algorithm attained the highest sensitivity of 87.50% and specificity of 100.00% among the machine learning-based multi-biomarkers models. Eventually, by combing the US with the KNN-based biomarkers model, the sensitivity and specificity reached 90.91% and 83.33%, respectively. CONCLUSIONS: Salivary biomarkers exhibit good potential in the differential diagnosis of borderline thyroid nodules and they significantly improve the prediction accuracy of the US. Additionally, we found that salivary FT3 is an independent risk factor for PTC and may be used as a key marker for PTC diagnosis. 2022 Gland Surgery. All rights reserved.
BACKGROUND: The incidence of papillary thyroid cancer (PTC) is increasing annually. ultrasonography (US) is the current primary method for evaluating thyroid nodules; however, there have been persisting challenges in diagnosing borderline malignancies. This paper aimed to establish the differential diagnostic value of salivary biomarkers for thyroid nodules geared towards improving the efficacy of US. METHODS: We recruited a total of 44 PTC patients and 42 benign thyroid tumor (BTT) patients to this study. The distribution of tumor markers and thyroid hormones in saliva and serum were compared between groups; then, uni-/multi-variate logistic analyses were used to determine the risk factors of PTC. Further, we estimated the differential diagnostic value of biomarkers in thyroid nodules, especially in borderline scenarios. Finally, a multi-index diagnostic model was constructed constituting biomarkers and US. RESULTS: The distributions of serum thyroglobulin (TG), salivary triiodothyronine (T3), free-triiodothyronine (FT3), and free-thyroxine (FT4) were significantly different in BTT and PTC (P<0.05); salivary FT3 was identified as an independent risk factor for PTC. By analyzing the diagnostic accuracy of various Thyroid Imaging Reporting and Data System (TI-RADS) categories, category 4A was shown to have the lowest diagnostic accuracy (48.39%) with the largest proportion (31 people, 36.05%). In 4A patients, the K-nearest neighbor (KNN) algorithm attained the highest sensitivity of 87.50% and specificity of 100.00% among the machine learning-based multi-biomarkers models. Eventually, by combing the US with the KNN-based biomarkers model, the sensitivity and specificity reached 90.91% and 83.33%, respectively. CONCLUSIONS: Salivary biomarkers exhibit good potential in the differential diagnosis of borderline thyroid nodules and they significantly improve the prediction accuracy of the US. Additionally, we found that salivary FT3 is an independent risk factor for PTC and may be used as a key marker for PTC diagnosis. 2022 Gland Surgery. All rights reserved.
Entities:
Keywords:
Saliva; free-triiodothyronine (FT3); papillary thyroid cancer (PTC); ultrasound
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