Evidence map›Paper›PMID 37700270›Full record

ArticleBMC medical imaging2023

Clinical value of grayscale ultrasound combined with real-time shear wave elastography nomogram in risk prediction of thyroid cancer.

Tiantian Ren, Mingfei Jiang, Jiawei Wu, Fan Zhang, Chaoxue Zhang

Open access · goldAbstract read
In one paragraph

Article in BMC medical imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact, top 76% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 0 citations in OpenAlex.

  1. Pooled it
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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

5 authors at 2 institutions in 1 country.

Tiantian RenDepartment of Medical Ultrasound, Maanshan People's Hospital, Hubei Road, Anhui Maanshan, 243032, China.
Mingfei JiangSchool of Public Health, Southeast University, Hunan Road, Nanjing, Jiangsu, 210000, China.
Jiawei WuDepartment of Medical Ultrasound, Maanshan People's Hospital, Hubei Road, Anhui Maanshan, 243032, China.
Fan ZhangDepartment of Medical Ultrasound, Maanshan People's Hospital, Hubei Road, Anhui Maanshan, 243032, China.
Chaoxue ZhangDepartment of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Meishan Road, AnHui Hefei, 230000, China. zcxay@163.com.
First Affiliated Hospital of Anhui Medical University · CNSoutheast University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study constructed a nomogram based on grayscale ultrasound features and real-time shear wave elastography (SWE) parameters to predict thyroid cancer.

methodsClinical data of 217 thyroid nodules of 201 patients who underwent grayscale ultrasound, real-time SWE, and thyroid function laboratory examination in Ma'anshan People's Hospital from January 2019 to December 2020 were retrospectively analyzed. The subjects were divided into a benign nodule group (106 nodules) and a malignant nodule group (111 nodules). The differences in grayscale ultrasound features, quantitative parameters of real-time SWE, and laboratory results of thyroid function between benign and malignant thyroid nodules were analyzed. We used a chi-square test for categorical variables and a t-test for continuous variables. Then, the independent risk factors for thyroid cancer were analyzed using multivariate logistic regression. Based on the independent risk factors, a nomogram for predicting thyroid cancer risk was constructed using the RMS package of the R software.

resultsMultivariate logistic regression showed that the grayscale ultrasound features of thyroid nodules were the shape, margin, echogenicity, and echogenic foci of the nodules,the maximum Young's modulus (SWE-max) of thyroid nodules, and the ratio of thyroid nodule and peripheral gland (SWE-ratio) measured by real-time SWE were independent risk factors for thyroid cancer (all p < 0.05), and the other variables had no statistical difference (p > 0.05). Based on the shape (OR = 5.160, 95% CI: 2.252-11.825), the margin (OR = 9.647, 95% CI: 2.048-45.443), the echogenicity (OR = 6.512, 95% CI: 1.729-24.524), the echogenic foci (OR = 2.049, 95% CI: 1.118-3.756), and the maximum Young's modulus (SWE-max) (OR = 1.296, 95% CI: 1.140-1.473), the SWE-ratio (OR = 2.001, 95% CI: 1.403-2.854) of the thyroid nodule to peripheral gland was used to establish the related nomogram prediction model. The bootstrap self-sampling method was used to verify the model. The consistency index (C-index) was 0.979, ROC curve was used to analyze the nomogram scores of all patients, and the AUC of nomogram prediction of thyroid cancer was 0.976, indicating that the nomogram model had high accuracy in the risk prediction of thyroid cancer.

conclusionsThe nomogram model of grayscale ultrasound features combined with SWE parameters can accurately predict thyroid cancer.

Indexed as

Elasticity Imaging TechniquesThyroid NeoplasmsThyroid NoduleHumansNomogramsRetrospective StudiesUltrasonographyGrayscale ultrasound characteristicsReal-time shear wave elastographyRisk prediction modelThyroid nodule

Identifiers

PMID37700270
PMCPMC10496161
OpenAlexW4386688993

What OpenQuestion holds

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LicenceCC BY
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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.