Evidence map›Paper›PMID 32588211›Full record

ArticleEuropean radiology2020

Papillary thyroid carcinoma: an ultrasound-based nomogram improves the prediction of lymph node metastases in the central compartment.

Xiaoqi Tian, Qing Song, Fang Xie, Ling Ren, Ying Zhang, Jie Tang, Yan Zhang, Zhuang Jin, Yaqiong Zhu, Mingbo Zhang and 1 more

Abstract read
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Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
4.8field-weighted citation impact, top 4% of its field
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

32 citing papers in PubMed, 46 citations in OpenAlex.

  1. 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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  15. Nomogram for preoperative estimation risk of lateral cervical lymph node metastasis in papillary thyroid carcinoma: a multicenter study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023
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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

11 authors at 2 institutions in 1 country.

Xiaoqi TianMedical College of Nankai University, No.94, Weijin Road, Nankai District, Tianjin, 300071, People's Republic of China.
Qing SongDepartment of Ultrasound, Chinese PLA General Hospital, No.28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Fang XieDepartment of Ultrasound, Chinese PLA General Hospital, No.28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Ling RenDepartment of Ultrasound, Chinese PLA General Hospital, No.28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Ying ZhangMedical College of Nankai University, No.94, Weijin Road, Nankai District, Tianjin, 300071, People's Republic of China.
Jie TangDepartment of Ultrasound, Chinese PLA General Hospital, No.28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Yan ZhangDepartment of Ultrasound, Chinese PLA General Hospital, No.28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Zhuang JinDepartment of Ultrasound, Chinese PLA General Hospital, No.28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Yaqiong ZhuMedical College of Nankai University, No.94, Weijin Road, Nankai District, Tianjin, 300071, People's Republic of China.
Mingbo ZhangDepartment of Ultrasound, Chinese PLA General Hospital, No.28, Fuxing Road, Haidian District, Beijing, 100853, People's Republic of China.
Yukun LuoMedical College of Nankai University, No.94, Weijin Road, Nankai District, Tianjin, 300071, People's Republic of China. luoyk301@163.com.ORCID http://orcid.org/0000-0002-6666-2256
Chinese PLA General Hospital · CNNankai University · CN

Funding

Innovation Cultivation Fund Project of the seventh medical center of PLA general hospital 2015-LC-05National Natural Science Foundation of China 81771834National Natural Science Foundation of China 81901746Natural Science Foundation of Beijing,China 7194318
6 · The paper itself

Abstract

objectivesTo develop a nomogram based on postoperative clinical and ultrasound findings to quantify the probability of central compartment lymph node metastases (CLNM).

methodsA total of 952 patients with histologically confirmed papillary thyroid carcinoma (PTC) were included in this retrospective study and assigned to three groups based on sex and age. The strongest predictors for CLNM were selected according to ultrasound imaging features, and an ultrasound (US) signature was constructed. By incorporating clinical characteristics, a predictive model presented as a nomogram was developed, and its performance was assessed with respect to calibration, discrimination and clinical usefulness.

resultsPredictors contained in the nomogram included US signature, US-reported LN status and age. The US signature was constructed with tumour size and microcalcification. The nomogram showed excellent calibration in the training dataset, with an AUC of 0.826 (95% CI, 0.765-0.887) for male patients, 0.818 (95% CI, 0.746-0.890) for young females and 0.808 (95% CI, 0.757-0.859) for elder females. For male and young female patients, application of the nomogram to the validation cohort revealed good discrimination, with AUCs of 0.813 (95% CI, 0.722-0.904) and 0.814 (95% CI, 0.712-0.915), respectively. Conversely, for elderly female patients, the nomogram failed to show good performance with an AUC of 0.742 (95% CI, 0.661-0.823).

conclusionThis ultrasound-based nomogram may serve as a useful clinical tool to provide valuable information for treatment decisions, especially for male and younger female patients. KEY POINTS: • Age, gender, US-reported LN status and US signature were the strongest predictors of CLNM in PTC patients and informed the development of a predictive nomogram. • Microcalcification was the strongest predictor in the US signature, as CLMN was identified in approximately 92% of patients characterised by diffuse microcalcification. • Stratified by sex and age, this nomogram achieved good performance in predicting CLNM, especially in male and young female patients. This prediction tool may be useful as an imaging marker for identifying CLNM preoperatively in PTC patients and as a guide for personalised treatment.

Indexed as

AdolescentAdultAgedFemaleHumansLymphatic MetastasisLymph NodesMaleMiddle AgedNomogramsRetrospective StudiesThyroid Cancer, PapillaryThyroid NeoplasmsUltrasonographyYoung AdultForecastingLymphatic metastasisNomogramPapillary thyroid carcinomaUltrasound

Identifiers

PMID32588211
OpenAlexW3037430398

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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 OpenQuestion graph.