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Wang F, Zhao D, Xu WY, Liu Y, Sun H, Lu S, Ji Y, Jiang J, Chen Y, He Q, Gong C, Liu R, Su Z, Dong Y, Yan Z, Liu L. Blood leukocytes as a non-invasive diagnostic tool for thyroid nodules: a prospective cohort study. BMC Med 2024; 22:147. [PMID: 38561764 PMCID: PMC10986011 DOI: 10.1186/s12916-024-03368-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 03/22/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Thyroid nodule (TN) patients in China are subject to overdiagnosis and overtreatment. The implementation of existing technologies such as thyroid ultrasonography has indeed contributed to the improved diagnostic accuracy of TNs. However, a significant issue persists, where many patients undergo unnecessary biopsies, and patients with malignant thyroid nodules (MTNs) are advised to undergo surgery therapy. METHODS This study included a total of 293 patients diagnosed with TNs. Differential methylation haplotype blocks (MHBs) in blood leukocytes between MTNs and benign thyroid nodules (BTNs) were detected using reduced representation bisulfite sequencing (RRBS). Subsequently, an artificial intelligence blood leukocyte DNA methylation (BLDM) model was designed to optimize the management and treatment of patients with TNs for more effective outcomes. RESULTS The DNA methylation profiles of peripheral blood leukocytes exhibited distinctions between MTNs and BTNs. The BLDM model we developed for diagnosing TNs achieved an area under the curve (AUC) of 0.858 in the validation cohort and 0.863 in the independent test cohort. Its specificity reached 90.91% and 88.68% in the validation and independent test cohorts, respectively, outperforming the specificity of ultrasonography (43.64% in the validation cohort and 47.17% in the independent test cohort), albeit with a slightly lower sensitivity (83.33% in the validation cohort and 82.86% in the independent test cohort) compared to ultrasonography (97.62% in the validation cohort and 100.00% in the independent test cohort). The BLDM model could correctly identify 89.83% patients whose nodules were suspected malignant by ultrasonography but finally histological benign. In micronodules, the model displayed higher specificity (93.33% in the validation cohort and 92.00% in the independent test cohort) and accuracy (88.24% in the validation cohort and 87.50% in the independent test cohort) for diagnosing TNs. This performance surpassed the specificity and accuracy observed with ultrasonography. A TN diagnostic and treatment framework that prioritizes patients is provided, with fine-needle aspiration (FNA) biopsy performed only on patients with indications of MTNs in both BLDM and ultrasonography results, thus avoiding unnecessary biopsies. CONCLUSIONS This is the first study to demonstrate the potential of non-invasive blood leukocytes in diagnosing TNs, thereby making TN diagnosis and treatment more efficient in China.
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Affiliation(s)
- Feihang Wang
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Danyang Zhao
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Wang-Yang Xu
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | - Yiying Liu
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | - Huiyi Sun
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Shanshan Lu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yuan Ji
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Jingjing Jiang
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yi Chen
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Qiye He
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | | | - Rui Liu
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China
| | - Zhixi Su
- Singlera Genomics (Shanghai) Ltd., Shanghai, 201203, China.
| | - Yi Dong
- Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
| | - Zhiping Yan
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China.
| | - Lingxiao Liu
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- National Clinical Research Center for Interventional Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China.
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