Evidence map›Paper›PMID 40579823›Full record

ArticleEndocrinology, diabetes & metabolism2025

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

Xudan Lou, Na Yi, Yingchun Liu, Yuanyuan Xu, Jieyuzhen Qiu, Xiaoming Tao, Zhijun Bao

Abstract read
In one paragraph

Article in Endocrinology, diabetes & metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Xudan LouDepartment of Endocrinology, Huadong Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.ORCID https://orcid.org/0000-0002-9612-8273
Na YiDepartment of Endocrinology, Huadong Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.
Yingchun LiuDepartment of Ultrasound Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.
Yuanyuan XuDepartment of Endocrinology, Huadong Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.
Jieyuzhen QiuDepartment of Endocrinology, Huadong Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.
Xiaoming TaoDepartment of Endocrinology, Huadong Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.
Zhijun BaoDepartment of Geriatrics, Huadong Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.

Funding

Shanghai Municipal Health Commission Clinical Research Special Project (202240258)
6 · The paper itself

Abstract

objectiveTo 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.

methodsClinical 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.

resultsAmong 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.

conclusionsIntegrating 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.

Indexed as

Sleep QualityThyroid NeoplasmsThyroid NoduleAgedAged, 80 and overBiopsy, Fine-NeedleDiagnosis, DifferentialFemaleHumansMaleMiddle AgedNomogramsRisk AssessmentRisk FactorsROC CurveUltrasonographymultimodal ultrasoundprediction modelsleep qualitythyroid cancer

Identifiers

PMID40579823
PMCPMC12205140

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.