Histologic outcome of thyroid nodules with repeated diagnosis of atypia in thyroid fine-needle aspiration biopsy

2016 ◽  
Vol 12 (6) ◽  
pp. 801-805
Author(s):  
Alev Selek ◽  
Berrin Cetinarslan ◽  
Emine Kıvrakoğlu ◽  
Duygu Temiz Karadağ ◽  
Ilhan Tarkun ◽  
...  
Author(s):  
Mohammad-Reza Mahmoudian-Sani ◽  
Maryam Amrollahi-Sharifabadi ◽  
Abdolmajid Taheri ◽  
Seyed Masih Hosseini ◽  
Kamran Tahmasebi ◽  
...  

AbstractBackgroundThyroid cancer (TC) is known to be the most common endocrine malignancy with an incidence rate which has increased by 2.3-fold over the past 30 years. Approximately, 30% of the thyroid fine-needle aspiration biopsy (FNAB) outcomes are indecisive. Moreover, researchers recognized multiple differentially expressed microRNAs (miRNAs) as candidate diagnostic markers for thyroid nodules. The purpose of this study was to identify thyroid tumor-associated miRNAs in FNAB with the capacity to be developed as unique biomarkers.Materials and methodsAccording to the study design, a quantitative real time reverse transcription polymerase chain reaction (qRT-PCR) was applied to evaluate the expression levels of nine miRNAs (Let7, miR-34a, miR-146b, miR-221, miR-151, miR-155, miR-181b, miR-222 and miR-375) among 224 FNA samples as the training set.ResultsThe findings of this study revealed that miR-181b and miR-146b are the best predictors to diagnose benign thyroid FNA samples from malignant samples. However, the remaining miRNAs were co-expressed and had no significant effect on the predictor model. On the other hand, sensitivity and specificity of miR-181b and miR-146b were reported at 83.0%–83.0% and 83.0%–66.0%, respectively.ConclusionsAccording to the results of this study, miR-146b and miR-181b might be considered as adjunct markers contributing to thyroid FNAB in tumor types. In addition, miR-146b and miR-181b were recognized as biomarkers for discriminating benign thyroid nodules from malignant ones. It is suggested that further prospective clinical trials be conducted to evaluate the accuracy of such findings in a larger cohort and determine the clinical uses.


PEDIATRICS ◽  
1995 ◽  
Vol 95 (1) ◽  
pp. 46-49
Author(s):  
Stephen S. Raab ◽  
Jan F. Silverman ◽  
Tarik M. Elsheikh ◽  
Patricia A. Thomas ◽  
Paul E. Wakely

Objective. The prevalence of thyroid nodularity in children has been estimated to be 1.8%. The reported prevalence of specific diseases which comprise these nodules is conflicting as evidenced by a reported range of malignancy of 2 to 50% in solitary nodules. In order to better classify pediatric (<18 years old) thyroid disease and evaluate the utility of fine needle aspiration biopsy (FNAB) in this patient population, we retrospectively reviewed 66 FNABs from 64 thyroid nodules and 2 perithyroid lymph nodes from 57 patients. Methodology. Patients: The study was composed of 8 males and 49 females who ranged in age from 1 to 18 years old (mean = 13.1). Design: Surgical and/or clinical follow-up was obtained in all patients. The 66 FNAB diagnoses were initially classified into specific diseases. However, for the purpose of this review, the cases were classified as: 3 insufficient, 51 benign, 8 suspicious, and 4 malignant. Results. There were no "false positives" and one "false negative" (a papillary carcinoma was misdiagnosed as a benign nodule). Overall, 10 patients (18%) had malignant thyroid lesions, including 8 papillary carcinomas and 2 follicular carcinomas. Benign diagnoses included benign nodule, cyst, lymphocytic thyroiditis, granulomatous thyroiditis, hyperplasia, and abscess. Conclusions. The prevalence of malignancy in pediatric patients with thyroid nodules was 18%. We conclude that, because of its high diagnostic accuracy and minimal invasiveness, FNAB is useful in the management of pediatric thyroid nodules.


Cancer ◽  
1988 ◽  
Vol 62 (7) ◽  
pp. 1337-1342 ◽  
Author(s):  
Annette R. Nathan ◽  
Kristen B. Raines ◽  
Yeu-Tsu Margaret Lee ◽  
E. Lawrence Sakas ◽  
Judy M. Ribbing

2013 ◽  
Vol 85 (6) ◽  
pp. 380-385 ◽  
Author(s):  
Oktay Irkorucu ◽  
Enver Reyhan ◽  
Kamuran Cumhur Değer ◽  
Pelin Demirtürk ◽  
Hasan Erdem ◽  
...  

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