Background The ThyroSeq v3 genomic classifier is a commercial molecular test that examines a wide spectrum of genomic alterations in a thyroid fine‐needle aspiration (FNA) sample and reports test results as either negative or positive. The authors report their institutional experience with ThyroSeq v3. Methods Thyroid FNA specimens diagnosed as either atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS) (Bethesda category III [Bethesda III] according to The Bethesda System for Reporting Thyroid Cytopathology) or follicular neoplasm/suspicious for follicular neoplasm (FN/SFN) (Bethesda IV) that had ThyroSeq v3 results available from December 2017 through October 2019 were retrieved for analysis. FNA diagnoses were correlated with ThyroSeq v3 results and follow‐up histopathology. Results In total, 415 cases (AUS/FLUS, n = 251; FN/SFN, n = 164) were retrieved: 294 (71%) were reported as ThyroSeq v3‐negative, and 121 (29%) were reported as ThyroSeq v3‐positive. The benign call rate (BCR) of ThyroSeq v3 for AUS/FLUS (82%; 206 of 251 cases) was significantly higher (P < .001) than that for FN/SFN (BCR, 54%; 88 of 164 cases). Histopathologic follow‐up was available for 127 cases (ThyroSeq v3‐positive, 96; ThyroSeq v3‐negative, 31), of which 57 were benign and 70 were malignant (including noninvasive follicular thyroid neoplasm with papillary‐like nuclear features). The negative predictive value of ThyroSeq v3 was significantly higher for AUS/FLUS (99.5%) than for FN/SFN (95.4%; P < .0294), given malignancy rates of 10% for AUS/FLUS and 30% for FN/SFN. Forty‐five unique combinations of genetic alterations were detected in the operated ThyroSeq‐positive cases, and there were only 5 false‐negative cases, comprised of 4 low‐risk neoplasms. Conclusions The high BCR of ThyroSeq v3 for AUS/FLUS prevents surgery in a majority of patients. The ThyroSeq v3 genomic classifier reveals the complexity of the genetic signature of indeterminate nodules.

Background Molecular testing of thyroid nodules with indeterminate fine‐needle aspiration (FNA) cytology is commonly used to guide patient management and is typically performed on freshly collected FNA samples. In this study, the authors evaluated the performance of the ThyroSeq test in cytology smear slides. Methods Air‐dried Diff‐Quik (DQ)‐stained and alcohol‐fixed Papanicolaou (Pap)‐stained smears were used to determine required cellularity and sensitivity of mutation detection and to compare ThyroSeq v3 Genomic Classifier (GC) results obtained in cytology smears and fresh FNA samples from the same nodules. Results ThyroSeq testing of 31 cytology smears revealed that 25 smears (81%) were adequate for ThyroSeq analysis, including 14 Pap‐stained smears (100%) and 11 DQ‐stained smears (65%), whereas 6 DQ‐stained smears (35%) failed RNA sequencing. The overall accuracy for detecting molecular alterations was 98%, with 100% concordance for mutations and gene expression alterations, 96% concordance for fusions, and 94% concordance for copy number alterations. Cytology smears were adequate for ThyroSeq analysis when at least 200 to 300 cells were present in 1 to 3 slides. ThyroSeq detected all studied mutations down to 5% allele frequency and BRAF mutations down to 1% allele frequency. Testing of smears yielded a positive ThyroSeq GC result in all nodules originally classified as positive. Conclusions Thyroid FNA cytology smear slides with adequate cellularity can be successfully used for ThyroSeq GC testing in approximately 80% of cases, with an even higher success rate in Pap‐stained smears. Compared with FNA samples collected into preservative solution, 94% to 100% of different genetic alterations could be accurately detected in smears, validating cytology smears as an alternative for ThyroSeq testing in patients with indeterminate thyroid cytology.

Objective: The 2014 Bethesda System diagnostic criteria for atypical glandular cells (AGC) aids in classification of atypical cells in cervical cytology. There is limited literature regarding reproducibility and interobserver variability in the application of the 2014 AGC criteria. Our aim is to assess the interobserver variability of AGC with a focus on how diagnostic categories link with guideline-driven management. Study Design: Three observers re-reviewed 51 previously diagnosed AGC Papanicolaou tests. The diagnoses were categorized as follows: (1) according to guideline-specified management, and (2) as glandular vs. squamous lesions. The κ statistic was used to evaluate interobserver agreement. Results: The interobserver variability per guideline management by weighted 2-observer κ ranged from 0.009 to 0.530, with half of the interobserver pairings meeting the threshold for at least fair-moderate agreement. For categorization as glandular, squamous, or both, unweighted κ yielded at best fair interobserver agreement (κ = 0.250) in 1 pairing, with low κ scores in the remainder of reviewer pairs (range 0.015–0.152). Conclusions: There is significant interobserver variability in the diagnosis of AGC. The AGC cases when divided by clinical management had fair-moderate interobserver agreement, suggesting that diagnostic variability likely has a real effect on patient care. This diagnostic uncertainty should be understood by cytologists and clinicians.