ArticlePakistan journal of medical sciences2019
Diagnostic accuracy of ultrasonography versus fine-needle-aspiration cytology for predicting benign thyroid lesions.
Article in Pakistan journal of medical sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 14 citations in OpenAlex.
- Article
- Diagnostic Accuracy of Ultrasound and Fine-Needle Aspiration Cytology in Thyroid Malignancy.Medicina (Kaunas, Lithuania) · 2024Article
- Assessment of thyroid nodule risk stratification knowledge and utilization among Polish physicians: a pilot study.Polish journal of radiology · 2024Article
- The prevalence and associated predictors for Bethesda III-VI for reporting thyroid cytopathology in Royal Commission Hospital, Kingdom of Saudi Arabia.Therapeutic advances in endocrinology and metabolism · 2022Article
- Clinical application of ultrasound-guided Core Needle Biopsy Histology and Fine Needle Aspiration Cytology in Cervical Lymph Nodes.Pakistan journal of medical sciencesArticle
- The sensitivity of TIRADS scoring on ultrasonography in the management of thyroid nodules.Pakistan journal of medical sciencesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveThyroid nodules (TNs) are abnormal growths of thyroid cells that form masses within the thyroid gland. TNs are common, and the importance lies in need to exclude thyroid cancer. This study was intended to evaluate the diagnostic accuracy of ultrasonography for differentiating benign from malignant thyroid lesions in comparison with fine-needle aspiration cytology (FNA cytology).
methodsThis study involved 133 patients with thyroid lesions. All patients underwent thyroid ultrasonography and ultrasound (US)-guided-FNA cytology and results were compared.
resultsOut of 133 patients included in this study, the mean age was 41.2±15 years, and 113 (85%) were female. Thyroid lesions were benign in 126 cases (94.7%) and malignant in nine cases (5.3%). Among 124 patients with thyroid lesions diagnosed as benign with US, 122 (98.38%) were confirmed to be benign with FNA cytology, and only 2 (1.6%) were proved to be malignant. Among nine patients with thyroid lesions diagnosed as malignant by US, 5 (55.6%) were confirmed to be malignant by FNA cytology, and 4 (44.4%) were proved to be benign. The US diagnosed benign thyroid lesions with a sensitivity, specificity, positive predictive value, and negative predictive value of 98.38%, 71.42%, 98.38%, and 55.55%, respectively. The results revealed strong compatibility between diagnosis of benign thyroid lesions by the US and proved diagnosis by FNA cytology (p<0.001).
conclusionB-mode ultrasonography is a valuable tool in differentiating benign from malignant thyroid lesions. It can almost always predict the benign nature of thyroid lesions with excellent diagnostic accuracy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.