Preoperative comprehensive malignancy risk estimation for thyroid nodules: Development and verification of a network-based prediction model |
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Affiliation: | 1. Department of Thyroid and Breast Diagnosis and Treatment Center, Weifang Hospital of Traditional Chinese Medicine, No. 1055 Weizhou Road, Kuiwen District, Weifang City, 261000, Shandong Province, China;2. Department of Ophthalmology, Affiliated Hospital of Weifang Medical University, No. 288 Shengli East Street, Kuiwen District, Weifang City, 261000, Shandong Province, China;1. Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital, Singapore;2. Ministry of Health Holdings, Singapore;3. Liver Transplant Service, Singhealth Duke-National University of Singapore Transplant Center, Singapore;4. Duke-National University of Singapore Medical School, Singapore;1. Department of Medical and Surgical Sciences (DIMEC), IRCCS Sant’Orsola-Malpighi, Obstetric and Gynecologic Unit, University of Bologna, Bologna, Italy;2. Gynecologic and Breast Oncologic Surgery Department, Georges Pompidou European Hospital, APHP. Centre, Université de Paris, Paris, France;3. INSERM UMR-S 1124, Université de Paris, Centre Universitaire des Saint-Père, Paris, France;4. INSERM UMR-S 1147, Université de Paris, Centre de Recherche des Cordeliers, Paris, France;1. Department of Surgery, Catharina Hospital, Eindhoven, the Netherlands;2. Department of Surgery, ETZ (Elisabeth-TweeSteden) Hospital, Tilburg, the Netherlands;3. Department of GROW, School for Developmental Biology & Oncology, Maastricht University, Maastricht, the Netherlands;1. Departments of Surgical Oncology, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA, 19111, USA;2. Departments of Biostatistics, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA, 19111, USA;1. Department of Surgery, Queen Elizabeth Hospital Birmingham, University Hospital Birmingham NHS Trust, Birmingham, United Kingdom;2. Department of HPB and Transplant Surgery, The Freeman Hospital, Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK;3. Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom;4. Department of Hepatobiliary and Transplant Surgery, Queen Elizabeth Hospital Birmingham, University Hospital Birmingham NHS Trust, Birmingham, United Kingdom;5. Department of Clinical Oncology, Northern Centre for Cancer Care, Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK;6. Department of General Surgery, University of Illinois Hospital and Health Sciences System, Chicago, IL, USA;7. Edward-Elmhurst Health, Department of Surgical Oncology, Naperville, IL, USA;8. Newcastle University, Newcastle Upon Tyne, Newcastle, United Kingdom;9. Department of Surgery, Southampton University Hospital NHS Foundation Trust, Southampton, UK;10. Department of Surgery, Fondazione Poliambulanza – Istituto Ospedaliero, Brescia, Italy;1. Department of Surgery, Memorial Sloan Kettering Cancer Center, United States;2. Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, United States;3. Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, United States;4. Geriatrics Service, Memorial Sloan Kettering Cancer Center, United States |
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Abstract: | BackgroundIn order to avoid excessive treatment of thyroid nodules in the clinic, it is necessary to find a simple and practical analysis method to comprehensively and accurately reflect benign or malignant thyroid nodules. This study aimed to construct and validate a comprehensive and reliable network-based predictive model using a variety of imaging and laboratory criteria for thyroid nodules to stratify the risk of malignancy prior to surgery.MethodsWe retrospectively analyzed data from patients who underwent surgical treatment for thyroid nodules at the Thyroid and Breast Diagnosis and Treatment Center of Weifang Hospital of Traditional Chinese Medicine between January 2018 and December 2020. Binary logical regression analysis was performed to predict whether nodules were malignant or benign. The developmental dataset included 457 patients (January 2018–December 2020). The validation set included separate data points (n = 225, January 2018–December 2020).ResultsIn this study, criteria that showed significant predictive value for malignant nodules included TI-RADS: 4b (p = 0.065); Bethesda IV, Bethesda V, Bethesda VI (P < 0.0001); BRAFV600E mutation (P < 0.0001); Calcitonin>5 pg/ml (p = 0.0037); and FNA-Tg>30 ng/ml (p = 0.0003). A 10-grade risk scoring system was developed. The risk of malignancy risk ranged from 2.06% to 100% and was positively associated with increasing risk grade. The areas under the receiver-operating characteristic curve of the development and validation sets were 0.972 and 0.946, respectively.ConclusionA simple, comprehensive and reliable web-based predictive model was designed using a variety of imaging and laboratory criteria to stratify thyroid nodules by probability of malignancy. |
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Keywords: | Thyroid nodules Thyroid carcinoma Preoperative estimation Malignant probability Network model CEA" },{" #name" :" keyword" ," $" :{" id" :" pc_oRSuQPDAUK" }," $$" :[{" #name" :" text" ," _" :" carcinoembryonic antigen Ct" },{" #name" :" keyword" ," $" :{" id" :" pc_5Dzg1m1WYT" }," $$" :[{" #name" :" text" ," _" :" calcitonin FNA" },{" #name" :" keyword" ," $" :{" id" :" pc_tjhT5plcEU" }," $$" :[{" #name" :" text" ," _" :" fine needle aspiration FNAB" },{" #name" :" keyword" ," $" :{" id" :" pc_CCHb1uJj9Z" }," $$" :[{" #name" :" text" ," _" :" fine needle aspiration biopsy FNAC" },{" #name" :" keyword" ," $" :{" id" :" pc_oCg55y1XcF" }," $$" :[{" #name" :" text" ," _" :" fine needle aspiration cytology FTC" },{" #name" :" keyword" ," $" :{" id" :" pc_TKrIDM9482" }," $$" :[{" #name" :" text" ," _" :" follicular thyroid carcinoma FT-UMP" },{" #name" :" keyword" ," $" :{" id" :" pc_mZtCBwbzB8" }," $$" :[{" #name" :" text" ," _" :" follicular tumor, uncertain malignant potential US" },{" #name" :" keyword" ," $" :{" id" :" pc_xUDoI8XnDl" }," $$" :[{" #name" :" text" ," _" :" ultrasonography MTC" },{" #name" :" keyword" ," $" :{" id" :" pc_JTV5b2cs5Y" }," $$" :[{" #name" :" text" ," _" :" medullary thyroid carcinoma NIFTP" },{" #name" :" keyword" ," $" :{" id" :" pc_6P7PqUCW8Q" }," $$" :[{" #name" :" text" ," _" :" non-invasive follicular thyroid neoplasm with papillary-like nuclear features PTC" },{" #name" :" keyword" ," $" :{" id" :" pc_IOamCDAOnf" }," $$" :[{" #name" :" text" ," _" :" papillary thyroid carcinoma ROC" },{" #name" :" keyword" ," $" :{" id" :" pc_bmuhu65C2D" }," $$" :[{" #name" :" text" ," _" :" receiver operating characteristic TI-RADS" },{" #name" :" keyword" ," $" :{" id" :" pc_uMo6G0Mu8G" }," $$" :[{" #name" :" text" ," _" :" Thyroid Imaging Reporting and Data System WT-UMP" },{" #name" :" keyword" ," $" :{" id" :" pc_boHtzYEFDo" }," $$" :[{" #name" :" text" ," _" :" well differentiated tumor, uncertain malignant potential |
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