Risk Prediction Model for Elderly Differentiated Thyroid Cancer Based on Combined Sleep Quality Assessment and Multimodal Ultrasound

ABSTRACT Objective To explore the differential diagnosis for benign and malignant thyroid nodules and the diagnostic value of sleep quality, to construct and validate a risk prediction model, providing the basis for clinical treatment decision for elderly thyroid cancer. Methods Clinical data, Pitts...

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Main Authors: Xudan Lou, Na Yi, Yingchun Liu, Yuanyuan Xu, Jieyuzhen Qiu, Xiaoming Tao, Zhijun Bao
Format: Article
Language:English
Published: Wiley 2025-07-01
Series:Endocrinology, Diabetes & Metabolism
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Online Access:https://doi.org/10.1002/edm2.70073
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author Xudan Lou
Na Yi
Yingchun Liu
Yuanyuan Xu
Jieyuzhen Qiu
Xiaoming Tao
Zhijun Bao
author_facet Xudan Lou
Na Yi
Yingchun Liu
Yuanyuan Xu
Jieyuzhen Qiu
Xiaoming Tao
Zhijun Bao
author_sort Xudan Lou
collection DOAJ
description ABSTRACT Objective To explore the differential diagnosis for benign and malignant thyroid nodules and the diagnostic value of sleep quality, to construct and validate a risk prediction model, providing the basis for clinical treatment decision for elderly thyroid cancer. Methods Clinical data, Pittsburgh Sleep Quality Index (PSQI), and multimodal ultrasound were collected from elderly patients undergoing fine needle aspiration biopsy or thyroid surgery in our department of endocrinology and general surgery. Postoperative pathological results served as the gold standard, binary logistic regression identified significant risk factors, and the receiver‐operating characteristic (ROC) curves were plotted to construct and validate the prediction model. Results Among 763 enrolled patients (566 benign and 197 malignant), multivariate analysis revealed independent risk factors: TPOAB positive, daytime dysfunction, PSQI > 7, irregular nodule shape, calcification, blood flow, high elasticity scores, and low contrast enhancement. The area under the curve (AUC) for the combined model was 0.860, significantly higher than models using multimodal ultrasound alone (AUC = 0.824) or multimodal ultrasound with TPOAB (AUC = 0.831), p < 0.05. The nomogram‐based prediction model demonstrated excellent discrimination, calibration, and clinical utility in internal and external validation. Conclusions Integrating sleep quality assessment with multimodal ultrasound assisted in the differentiation of thyroid nodules in the elderly, thus may improve the preoperative diagnostic levels. Risk prediction model in a nomogram format provided an intuitive and reliable tool for clinical decision‐making.
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spelling doaj-art-b57675db558448a28ecc9334ee07e82e2025-08-20T03:56:41ZengWileyEndocrinology, Diabetes & Metabolism2398-92382025-07-0184n/an/a10.1002/edm2.70073Risk Prediction Model for Elderly Differentiated Thyroid Cancer Based on Combined Sleep Quality Assessment and Multimodal UltrasoundXudan Lou0Na Yi1Yingchun Liu2Yuanyuan Xu3Jieyuzhen Qiu4Xiaoming Tao5Zhijun Bao6Department of Endocrinology Huadong Hospital Affiliated to Fudan University Shanghai People's Republic of ChinaDepartment of Endocrinology Huadong Hospital Affiliated to Fudan University Shanghai People's Republic of ChinaDepartment of Ultrasound Medicine Huadong Hospital Affiliated to Fudan University Shanghai People's Republic of ChinaDepartment of Endocrinology Huadong Hospital Affiliated to Fudan University Shanghai People's Republic of ChinaDepartment of Endocrinology Huadong Hospital Affiliated to Fudan University Shanghai People's Republic of ChinaDepartment of Endocrinology Huadong Hospital Affiliated to Fudan University Shanghai People's Republic of ChinaDepartment of Geriatrics Huadong Hospital Affiliated to Fudan University Shanghai People's Republic of ChinaABSTRACT Objective To explore the differential diagnosis for benign and malignant thyroid nodules and the diagnostic value of sleep quality, to construct and validate a risk prediction model, providing the basis for clinical treatment decision for elderly thyroid cancer. Methods Clinical data, Pittsburgh Sleep Quality Index (PSQI), and multimodal ultrasound were collected from elderly patients undergoing fine needle aspiration biopsy or thyroid surgery in our department of endocrinology and general surgery. Postoperative pathological results served as the gold standard, binary logistic regression identified significant risk factors, and the receiver‐operating characteristic (ROC) curves were plotted to construct and validate the prediction model. Results Among 763 enrolled patients (566 benign and 197 malignant), multivariate analysis revealed independent risk factors: TPOAB positive, daytime dysfunction, PSQI > 7, irregular nodule shape, calcification, blood flow, high elasticity scores, and low contrast enhancement. The area under the curve (AUC) for the combined model was 0.860, significantly higher than models using multimodal ultrasound alone (AUC = 0.824) or multimodal ultrasound with TPOAB (AUC = 0.831), p < 0.05. The nomogram‐based prediction model demonstrated excellent discrimination, calibration, and clinical utility in internal and external validation. Conclusions Integrating sleep quality assessment with multimodal ultrasound assisted in the differentiation of thyroid nodules in the elderly, thus may improve the preoperative diagnostic levels. Risk prediction model in a nomogram format provided an intuitive and reliable tool for clinical decision‐making.https://doi.org/10.1002/edm2.70073multimodal ultrasoundprediction modelsleep qualitythyroid cancer
spellingShingle Xudan Lou
Na Yi
Yingchun Liu
Yuanyuan Xu
Jieyuzhen Qiu
Xiaoming Tao
Zhijun Bao
Risk Prediction Model for Elderly Differentiated Thyroid Cancer Based on Combined Sleep Quality Assessment and Multimodal Ultrasound
Endocrinology, Diabetes & Metabolism
multimodal ultrasound
prediction model
sleep quality
thyroid cancer
title Risk Prediction Model for Elderly Differentiated Thyroid Cancer Based on Combined Sleep Quality Assessment and Multimodal Ultrasound
title_full Risk Prediction Model for Elderly Differentiated Thyroid Cancer Based on Combined Sleep Quality Assessment and Multimodal Ultrasound
title_fullStr Risk Prediction Model for Elderly Differentiated Thyroid Cancer Based on Combined Sleep Quality Assessment and Multimodal Ultrasound
title_full_unstemmed Risk Prediction Model for Elderly Differentiated Thyroid Cancer Based on Combined Sleep Quality Assessment and Multimodal Ultrasound
title_short Risk Prediction Model for Elderly Differentiated Thyroid Cancer Based on Combined Sleep Quality Assessment and Multimodal Ultrasound
title_sort risk prediction model for elderly differentiated thyroid cancer based on combined sleep quality assessment and multimodal ultrasound
topic multimodal ultrasound
prediction model
sleep quality
thyroid cancer
url https://doi.org/10.1002/edm2.70073
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