Evidence map›Paper›PMID 40133880›Full record

ArticleWorld journal of surgical oncology2025

A risk stratification model based on ultrasound radiologic features for cervical metastatic lymph nodes in papillary thyroid cancer.

Hai-Long Tan, Sai-Li Duan, Qiao He, Zhe-Jia Zhang, Peng Huang, Shi Chang

Abstract read
In one paragraph

Article in World journal of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

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

6 authors.

Hai-Long Tan *Department of General Surgery, Xiangya Hospital Central South University, Changsha, Hunan, 410008, P.R. China. tanhailong@csu.edu.cn.ORCID http://orcid.org/0000-0002-3345-5277
Sai-Li Duan *Department of General Surgery, Xiangya Hospital Central South University, Changsha, Hunan, 410008, P.R. China.ORCID http://orcid.org/0000-0002-4453-8318
Qiao HeDepartment of General Surgery, Xiangya Hospital Central South University, Changsha, Hunan, 410008, P.R. China.ORCID http://orcid.org/0000-0001-5762-8059
Zhe-Jia ZhangDepartment of General Surgery, Xiangya Hospital Central South University, Changsha, Hunan, 410008, P.R. China.ORCID http://orcid.org/0000-0002-8337-263X
Peng HuangDepartment of General Surgery, Xiangya Hospital Central South University, Changsha, Hunan, 410008, P.R. China.ORCID http://orcid.org/0000-0003-3011-3359
Shi ChangDepartment of General Surgery, Xiangya Hospital Central South University, Changsha, Hunan, 410008, P.R. China. changshi@csu.edu.cn.ORCID http://orcid.org/0000-0001-5291-0151

Funding

China Postdoctoral Science Foundation 2020M672517China Postdoctoral Science Foundation 2021T140749Fundamental Research Funds for Central Universities of the Central South University CX20210354National Natural Science Foundation of China 81902729National Natural Science Foundation of China 81974423Natural Science Foundation of Hunan Province 2020JJ4925Natural Science Foundation of Hunan Province 2020JJ5904Project Program of National Clinical Research Center for Geriatric Disorders 2021KFJJ03Research and Innovation Project Foundation for Graduate in Hunan Province CX20230361Special Funding for the Construction of Innovative Provinces in Hunan 2020SK4003
6 · The paper itself

Abstract

backgroundAccurate preoperative evaluation for metastatic lesions is significant for PTC patients. However, the stratification systems revealed inconsistencies in the ultrasound (US) features of cervical metastatic lymph nodes (LNs). This study aimed to investigate and develop a risk stratification model based on US radiologic features for cervical metastatic lesions in PTC patients.

methodsThis study retrospectively enrolled 1806 LNs from 1665 PTC patients who underwent US-guided fine-needle aspiration biopsy for cervical LNs from January 2010 to December 2022. Univariable and multivariable logistic regression analyses determined and developed the independent risk US features and a risk stratification model for cervical metastatic LNs. The performance of the risk stratification model was assessed and validated by the Korean Society of Thyroid Radiology and the European Thyroid Association.

resultsAmong the 1806 LNs, 1411 LNs were pathologically diagnosed with malignant. Multivariate analysis indicated that the absence of fatty hilum, cystic components, round shape (SD/LD ≥ 0.5), abundant vascularity, hyperechogenicity (including hyper and hypo-echogenicity, and hyper-echogenicity), and calcifications (include microcalcification, and macrocalcification) were independent risk US features associated with malignant LNs. A risk stratification model for cervical metastatic LNs was developed based on these suspicious US features and showed well-predicted performance (C-index 0.840; 95% CI: 0.840-0.923).

conclusionOur study proposed a new risk stratification system based on US radiologic features to predict cervical metastatic lymph nodes in PTC patients. We identified several risk factors for lymph node (LN) metastasis from PTC including the absence of fatty hilum, cystic components, round shape (SD/LD ≥ 0.5), abnormal vascularity, hyper-echogenicity, hyper- and hypo-echogenicity, microcalcification, and macrocalcification. These features could serve as valuable indicators for surgeons to accurately assess the status of cervical LNs.

Indexed as

Lymph NodesThyroid Cancer, PapillaryThyroid NeoplasmsAdultAgedBiopsy, Fine-NeedleFemaleFollow-Up StudiesHumansLymphatic MetastasisMaleMiddle AgedNeckPrognosisRetrospective StudiesRisk AssessmentLymph nodePapillary thyroid carcinomaRisk stratification modelUltrasound

Identifiers

PMID40133880
PMCPMC11934585

What Socratic holds

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Registered trials

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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.