Evidence map›Paper›PMID 37576418›Full record

ArticleJournal of medical ultrasound

Performance of European Thyroid Imaging Reporting and Data System in Stratifying Malignancy Risk of Thyroid Nodules: A Prospective Study.

Mehrdad Nabahati, Zoleika Moazezi

Open access · diamondAbstract read
In one paragraph

Article in Journal of medical ultrasound. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 45% 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, 2 citations in OpenAlex.

  1. Article
  2. Article
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

2 authors at 1 institution in 1 country.

Mehrdad NabahatiDepartment of Radiology, Shahid Beheshti Hospital, Babol University of Medical Sciences, Babol, Iran.
Zoleika MoazeziDepartment of Endocrinology, Rohani Hospital, Babol University of Medical Sciences, Babol, Iran.
Babol University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is a limited number of studies reporting the performance of European Thyroid Imaging Reporting and Data System (EU-TIRADS) guideline in identifying thyroid nodule malignancy. We aimed to evaluate diagnostic accuracy of EU-TIRADS regardless of thyroid nodule size. Methods: During August 2019-November 2021, subjects with thyroid nodules were prospectively included. Sonographic characteristics were recorded and scored as per EU-TIRADS guideline. Finally, fine-needle aspiration (FNA) was performed, and cytological findings were reported. Results: Totally, 1266 thyroid nodules from 984 subjects were assessed, of which 295 nodules were smaller than 10 mm and 971 nodules were 10 mm or larger. Among nodules <10 mm, prevalence rates of malignancy for EU-TIRADS classes 2-5 were 0.0%, 3.7%, 20.6%, and 40.9%, respectively; these rates among nodules ≥10 mm were 2.3%, 4.0%, 19.3%, and 43.2%, respectively. The accuracy values of EU-TIRADS class 5 and EU-TIRADS class 4 or 5 in diagnosis of malignancy for nodules <10 mm were 86.4% and 79.7%, respectively; these rates for nodules ≥10 mm were 83.8% and 76.3%, respectively. Hypoechogenicity, microcalcification, ill-defined and irregular margins were predictors for malignancy regardless of thyroid nodule size. Conclusion: EU-TIRADS could provide an acceptable malignancy risk stratification that is helpful for better distinguishing benignity from malignancy, as well as preventing unnecessary FNA biopsies, in thyroid nodules irrespective of their size.

Indexed as

MalignancyThyroid Imaging Reporting and Data Systemthyroid nodulesultrasonography

Identifiers

PMID37576418
PMCPMC10413406
OpenAlexW4381664525

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.