Evidence map›Paper›PMID 38033487›Full record

ArticleFrontiers in oncology2023

A comprehensive comparative assessment of eight risk stratification systems for thyroid nodules in the elderly population.

Xiao Ma, Jing Yu, Yuanjing Huang, Yiyang Cui, Kefei Cui

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 39% 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

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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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 1 institution in 1 country.

Xiao MaDepartment of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Jing YuDepartment of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yuanjing HuangDepartment of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yiyang CuiDepartment of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Kefei CuiDepartment of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
First Affiliated Hospital of Zhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to investigate the diagnostic value of eight risk stratification systems (RSSs) for thyroid nodules in the elderly and explore the reasons in comparison with a younger group. Methods: Cases of thyroid nodules that underwent ultrasound examination with thyroidectomy or fine-needle aspiration (FNA) at our hospital between August 2013 and March 2023 were collected. The patients were categorized into two groups: an elderly group (aged ≥60) and a younger group (aged <60). Eight RSSs were applied to evaluate these nodules respectively. Results: The malignant rate in the elderly group was significantly lower than that in the younger group (28.2% vs. 49.6%, P=0.000). There were statistically significant differences in nodule diameter, multiplicity, composition, echogenicity, orientation, margin, and echogenic foci between the elderly and younger groups (P<0.05). Among the eight RSSs evaluated in elderly adults, the artificial intelligence-based Thyroid Imaging Reporting and Data System (AI TIRADS) demonstrated the highest overall diagnostic efficacy, but with relatively high unnecessary FNA rate (UFR) and missed cancer rate (MCR) of 55.0% and 51.3%, respectively. By modifying the size thresholds, the new AI TI-RADS achieved the lowest UFR and MCR while maintaining nearly the lowest FNA rate (FNAR) among all the RSSs (P=0.172, 0.162, compared to the ACR and original AI, respectively, but P<0.05 compared to the other six RSSs). Conclusion: Among the eight RSS systems, AI demonstrated higher diagnostic efficacy in the elderly population. However, the size thresholds for FNA needed to be adjusted.

Indexed as

elderlyrisk stratification systemsThyroid Imaging Reporting and Data Systemthyroid nodulesultrasonography

Identifiers

PMID38033487
PMCPMC10684914
OpenAlexW4388701823

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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.