Evidence map›Paper›PMID 32827126›Full record

GuidelineEndocrine2020

2020 Chinese guidelines for ultrasound malignancy risk stratification of thyroid nodules: the C-TIRADS.

JianQiao Zhou, LiXue Yin, Xi Wei, Sheng Zhang, YanYan Song, BaoMing Luo, JianChu Li, LinXue Qian, LiGang Cui, Wen Chen and 18 more

2 registry-linked trialsAbstract readPractice Guideline
PubMed Publisher
In one paragraph

Guideline in Endocrine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 225 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
225citing papers in PubMed, 3 pooled it
–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.

NCT05982821 nacompletednot on this mapstarted 2023, after this paper: background citation

A Multicenter Study of Artificial Intelligence-assisted Contrast-enhanced Ultrasound Diagnosis of Thyroid Nodules

TypeinterventionalSponsorSun Yat-Sen Memorial Hospital of Sun Yat-Sen UniversityRan2023 to 2026Enrolled1,955ConditionsThyroid NoduleArmsArtificial Intelligence
NCT06146764 recruitingnot on this mapstarted 2023, after this paper: background citation

Contrast-enhanced Ultrasound Improves the Diagnostic Performance of Sonographic Risk Stratification System of Thyroid Carcinoma: Comparison Between Integrated Scoring Method and Up-and-down Scoring Method

TypeobservationalSponsorSun Yat-Sen Memorial Hospital of Sun Yat-Sen UniversityRan2023 to 2026Enrolled800ConditionsThyroid Nodule, Thyroid CarcinomaArmsContrast-enhanced Ultrasound
3 · Its place in the literature

Who cites it

225 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  9. Nodule size significantly affects the diagnostic value of chinese thyroid imaging reporting and data system: a multi-center retrospective study.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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165 more citing papers are in PubMed but not listed here.

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

28 authors.

JianQiao ZhouDepartment of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China. zhousu30@126.com.
LiXue YinInstitute of Ultrasound in Medicine, The Affiliated Sichuan Provincial People's Hospital of Electronic Science and Technology University of China, Chengdu, 610071, China. yinlixue@yahoo.com.
Xi WeiDepartment of Diagnostic and Therapeutic Ultrasound, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China.
Sheng ZhangDepartment of Diagnostic and Therapeutic Ultrasound, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China.
YanYan SongDepartment of Biostatistics, Institute of Medical Sciences, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.
BaoMing LuoDepartment of Ultrasound, SunYat-sen Memorial Hospital, SunYat-sen University, Guangzhou, 510120, China.
JianChu LiDepartment of Ultrasound, Peking Union Medical College Hospital, Beijing, 100730, China.
LinXue QianDepartment of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China.
LiGang CuiDepartment of Ultrasound, Peking University Third Hospital, Beijing, 100191, China.
Wen ChenDepartment of Ultrasound, Peking University Third Hospital, Beijing, 100191, China.
ChaoYang WenDepartment of Ultrasound, Peking University International Hospital, Beijing, 102206, China.
YuLan PengDepartment of Ultrasound, West China Hospital of Sichuan University, Chengdu, 610041, China.
Qin ChenDepartment of Ultrasound, The Affiliated Sichuan Provincial People's Hospital of Electronic Science and Technology University of China, Chengdu, 610071, China.
Man LuDepartment of Ultrasound, Sichuan Cancer Hospital, Chengdu, 610041, China.
Min ChenDepartment of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Rong WuDepartment of Ultrasound, Shanghai First People's Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, 201620, China.
Wei ZhouDepartment of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China.
EnSheng XueDepartment of Ultrasound, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
YingJia LiDepartment of Ultrasound, Nanfang Hospital of Southern Medical University, Guangzhou, 510515, China.
LiChun YangDepartment of Ultrasound, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, 650031, China.
ChengRong MiDepartment of Ultrasound, General Hospital of Ningxia Medical University, Yinchuan, 750021, China.
RuiFang ZhangDepartment of Ultrasound, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.
Gang WuDepartment of Ultrasound, Henan Provincial People's Hospital, Zhengzhou, 450003, China.
GuoQing DuDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
DaoZhong HuangDepartment of Ultrasound, Tongji Hospital, Tongji Medical Colloge, Huazhong University of Science and Technology, Wuhan, 430030, China.
WeiWei ZhanDepartment of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China. shanghairuijinus@163.com.
Superficial Organ and Vascular Ultrasound Group of the Society of Ultrasound in Medicine of the Chinese Medical Association
Chinese Artificial Intelligence Alliance for Thyroid and Breast Ultrasound

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thyroid nodules are very common all over the world, and China is no exception. Ultrasound plays an important role in determining the risk stratification of thyroid nodules, which is critical for clinical management of thyroid nodules. For the past few years, many versions of TIRADS (Thyroid Imaging Reporting and Data System) have been put forward by several institutions with the aim to identify whether nodules require fine-needle biopsy or ultrasound follow-up. However, no version of TIRADS has been widely adopted worldwide till date. In China, as many as ten versions of TIRADS have been used in different hospitals nationwide, causing a lot of confusion. With the support of the Superficial Organ and Vascular Ultrasound Group of the Society of Ultrasound in Medicine of the Chinese Medical Association, the Chinese-TIRADS that is in line with China's national conditions and medical status was established based on literature review, expert consensus, and multicenter data provided by the Chinese Artificial Intelligence Alliance for Thyroid and Breast Ultrasound.

Indexed as

Thyroid NeoplasmsThyroid NoduleArtificial IntelligenceChinaHumansRetrospective StudiesRisk AssessmentUltrasonographyBiopsyDiagnostic imagingFine needleRisk assessmentThyroid noduleUltrasonography

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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 OpenQuestion graph.