Evidence map›Paper›PMID 35226156›Full record

ArticleEuropean radiology2022

Nomograms based on preoperative multimodal ultrasound of papillary thyroid carcinoma for predicting central lymph node metastasis.

Quan Dai, Dongmei Liu, Yi Tao, Chao Ding, Shouqiang Li, Chen Zhao, Zhuo Wang, Yangyang Tao, Jiawei Tian, Xiaoping Leng

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In one paragraph

Article in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 7% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

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  11. Construction of a nomogram for central lymph node metastasis in papillary thyroid cancer based on gender grouping.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024
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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

10 authors at 1 institution in 1 country.

Quan DaiDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China.
Dongmei LiuDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China.
Yi TaoDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China.
Chao DingDepartment of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Shouqiang LiDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China.
Chen ZhaoDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China.
Zhuo WangDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China.
Yangyang TaoDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China.
Jiawei TianDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China.
Xiaoping LengDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China. xpleng@ems.hrbmu.edu.cn.ORCID http://orcid.org/0000-0001-8883-8884
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo establish a nomogram for predicting central lymph node metastasis (CLNM) based on the preoperative clinical and multimodal ultrasound (US) features of papillary thyroid carcinoma (PTC) and cervical LNs.

methodsOverall, 822 patients with PTC were included in this retrospective study. A thyroid tumor ultrasound model (TTUM) and thyroid tumor and cervical LN ultrasound model (TTCLNUM) were constructed as nomograms to predict the CLNM risk. Areas under the curve (AUCs) evaluated model performance. Calibration and decision curves were applied to assess the accuracy and clinical utility.

resultsFor the TTUM training and test sets, the AUCs were 0.786 and 0.789 and bias-corrected AUCs were 0.786 and 0.831, respectively. For the TTCLNUM training and test sets, the AUCs were 0.806 and 0.804 and bias-corrected AUCs were 0.807 and 0.827, respectively. Calibration and decision curves for the TTCLNUM nomogram exhibited higher accuracy and clinical practicability. The AUCs were 0.746 and 0.719 and specificities were 0.942 and 0.905 for the training and test sets, respectively, when the US tumor size was ≤ 8.45 mm, while the AUCs were 0.737 and 0.824 and sensitivity were 0.905 and 0.880, respectively, when the US tumor size was > 8.45 mm.

conclusionThe TTCLNUM nomogram exhibited better predictive performance, especially for the CLNM risk of different PTC tumor sizes. Thus, it serves as a useful clinical tool to supply valuable information for active surveillance and treatment decisions. KEY POINTS: • Our preoperative noninvasive and intuitive prediction method can improve the accuracy of central lymph node metastasis (CLNM) risk assessment and guide clinical treatment in line with current trends toward personalized treatments. • Preoperative clinical and multimodal ultrasound features of primary papillary thyroid carcinoma (PTC) tumors and cervical LNs were directly used to build an accurate and easy-to-use nomogram for predicting CLNM. • The thyroid tumor and cervical lymph node ultrasound model exhibited better performance for predicting the CLNM of different PTC tumor sizes. It may serve as a useful clinical tool to provide valuable information for active surveillance and treatment decisions.

Indexed as

NomogramsThyroid NeoplasmsHumansLymphatic MetastasisLymph NodesRetrospective StudiesRisk FactorsThyroid Cancer, PapillaryLymphatic metastasisNomogramThyroid cancer, papillaryUltrasonographyWatchful waiting

Identifiers

PMID35226156
OpenAlexW4214697080

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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.