Abstract
Objective: Several thyroid imaging reporting and data systems (TIRADS) ha ve been proposed to stratify the malignancy risk of thyroid nodule by ultrasound. The TIRADS by the Europea n Thyroid Association, namely EU-TIRADS, was the last one to be published. Design: We conducted a meta-analysis to assess the prevalence of malig nancy in each EU-TIRADS class and the performance of EU-TIRADS class 5 vs 2, 3 and 4 in detecting mal ignant lesions. Methods: Four databases were searched until December 2019. Original art icles reporting the performance of EU-TIRADS and adopting histology as reference standard were inc luded. The number of malignant nodules in each class and the number of nodules classified as true/false positiv e/negative were extracted. A random-effects model was used for pooling data. Results: Seven studies were included, evaluating 5672 thyroid nodules. The prevalence of malignancy in each EU-TIRADS class was 0.5% (95% CI: 0.0-1.3), 5.9% (95% CI: 2.6-9 .2), 21.4% (95% CI: 11.1-31.7), and 76.1% (95% CI: 63.7-88.5). Sensitivity, specificity, PPV, NPV, LR+, LR- A nd DOR of EU-TIRADS class 5 were 83.5% (95% CI: 74.5-89.8), 84.3% (95% CI: 66.2-93.7), 76.1% (95% CI: 63.7-88.5), 85.4% (95 % CI: 79.1-91.8), 4.9 (95% CI: 2.9-8.2), 0.2 (95% CI: 0.1-0.3), and 24.5 (95% CI: 11.7-51.0), respectively. A further improved performance was found after excluding two studies because of limited sample size and low prevalence of ma lignancy in class 5. Conclusions: A limited number of studies generally conducted using a retros pective design was found. Acknowledging this limitation, the performance of EU-TIRADS in stratifying th e risk of thyroid nodules was high. Also, EU-TIRADS class 5 showed moderate evidence of detecting malignant lesions.
| Original language | English |
|---|---|
| Pages (from-to) | 255-264 |
| Number of pages | 10 |
| Journal | European Journal of Endocrinology |
| Volume | 183 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Sept 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Field of Science*
- 3.2 Clinical medicine
Publication Type*
- 1.1. Scientific article indexed in Web of Science and/or Scopus database
Fingerprint
Dive into the research topics of 'Performance of EU-TIRADS in malignancy risk stratification of thyroid nodules: A meta-analysis'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver