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Background: Cytopathological evaluation of thyroid fine-needle aspiration biopsy (FNAB) specimens can fail to raise preoperative suspicion of medullary thyroid carcinoma (MTC). The Afirma RNA-sequencing MTC classifier identifies MTC among FNA samples that are cytologically indeterminate, suspicious, or malignant (Bethesda categories III-VI). In this study we report the development and clinical performance of this MTC classifier. Methods: Algorithm training was performed with a set of 483 FNAB specimens (21 MTC and 462 non-MTC). A support vector machine classifier was developed using 108 differentially expressed genes, which includes the 5 genes in the prior Afirma microarray-based MTC cassette. Results: The final MTC classifier was blindly tested on 211 preoperative FNAB specimens with subsequent surgical pathology, including 21 MTC and 190 non-MTC specimens from benign and malignant thyroid nodules independent from those used in training. The classifier had 100% sensitivity (21/21 MTC FNAB specimens correctly called positive; 95% confidence interval [CI] = 83.9-100%) and 100% specificity (190/190 non-MTC FNAs correctly called negative; CI = 98.1-100%). All positive samples had pathological confirmation of MTC, while all negative samples were negative for MTC on surgical pathology. Conclusions: The RNA-sequencing MTC classifier accurately identified MTC from preoperative thyroid nodule FNAB specimens in an independent validation cohort. This identification may facilitate an MTC-specific preoperative evaluation and resulting treatment.

Importance: Use of next-generation sequencing of RNA and machine learning algorithms can classify the risk of malignancy in cytologically indeterminate thyroid nodules to limit unnecessary diagnostic surgery., Objective: To measure the performance of a genomic sequencing classifier for cytologically indeterminate thyroid nodules., Design, Setting, and Participants: A blinded validation study was conducted on a set of cytologically indeterminate thyroid nodules collected by fine-needle aspiration biopsy between June 2009 and December 2010 from 49 academic and community centers in the United States. All patients underwent surgery without genomic information and were assigned a histopathology diagnosis by an expert panel blinded to all genomic information. There were 210 potentially eligible thyroid biopsy samples with Bethesda III or IV indeterminate cytopathology that constituted a cohort previously used to validate the gene expression classifier. Of these, 191 samples (91.0%) had adequate residual RNA for validation of the genomic sequencing classifier. Algorithm development and independent validation occurred between August 2016 and May 2017., Exposures: Thyroid nodule surgical histopathology diagnosis by an expert panel blinded to all genomic data., Main Outcomes and Measures: The primary end point was measurement of genomic sequencing classifier sensitivity, specificity, and negative and positive predictive values in biopsies from Bethesda III and IV nodules. The secondary end point was measurement of classifier performance in biopsies from Bethesda II, V, and VI nodules., Results: Of the 183 included patients, 142 (77.6%) were women, and the mean (range) age was 51.7 (22.0-85.0) years. The genomic sequencing classifier had a sensitivity of 91% (95% CI, 79-98) and a specificity of 68% (95% CI, 60-76). At 24% cancer prevalence, the negative predictive value was 96% (95% CI, 90-99) and the positive predictive value was 47% (95% CI, 36-58)., Conclusions and Relevance: The genomic sequencing classifier demonstrates high sensitivity and accuracy for identifying benign nodules. Its 36% increase in specificity compared with the gene expression classifier potentially increases the number of patients with benign nodules who can safely avoid unnecessary diagnostic surgery.

Background: Low cellularity can be problematic in thyroid fine needle aspiration (FNA) biopsies. The Cellient cell block (CB) system has been reported to improve cell recovery compared to traditional methods. Therefore, we studied the utility of Cellient CBs in the evaluation of thyroid FNAs, with an emphasis on low-cellularity specimens., Methods: ThinPrep slides were prepared from thyroid FNAs submitted in Cytolyt. After assessment using TBSRTC criteria, Cellient CBs were requested on samples with residual FNA material and an initial cytologic impression of non-diagnostic, AUS/FLUS, and on apparently benign samples with marginally adequate cellularity. The contribution of the CB findings to the final diagnosis was assessed., Results: 965 cases of paired ThinPrep and CB sections were examined. Overall, the cell block findings resulted in a change of the initial ThinPrep impression in 15% (n = 148) of cases. The vast majority of these changed cases were initially inadequate for interpretation, and specifically, 31% (n = 123) of the non-diagnostic ThinPrep samples became diagnostic with a CB. The cell block findings contributed to a change in diagnosis in 8% (n = 23) of AUS/FLUS cases, and in less than 1% of low-cellularity benign samples., Conclusion: The use of CBs in low-cellularity thyroid FNAs has not been well described. In this study, we found that the contribution of CBs in this setting varied by TBSRTC category. Specifically, the samples that benefited most were initially non-diagnostic specimens and select cases of AUS/FLUS, while low-cellularity benign samples gained very little additional information. Diagn. Cytopathol. 2016;44:737-741. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Background: The use of calcitonin screening for the rare medullary thyroid cancer (MTC) is controversial due to questions of efficacy, accuracy, and cost-effectiveness. This study reports the results of a large prospective validation using a machine-trained algorithm (MTC Classifier) to preoperatively identify MTC in fine-needle aspiration biopsies in lieu of calcitonin measurements., Methods: Cytology analysis on a prospective consecutive series of 50,430 thyroid nodule biopsies yielded a total of 7815 indeterminate (Bethesda categories III/IV) cases, which were tested with the MTC classifier. A prospective, consecutively submitted series of 2673 Bethesda III-VI cases with cytology determined locally was also evaluated. RNA was isolated and tested for the MTC Classifier using microarrays., Results: Forty-three cases were positive by the MTC Classifier among 10,488 tested nodules (0.4%), consistent with the low prevalence of MTC. Of these, all but one was histologically or biochemically confirmed as MTC, yielding a positive predictive value (PPV) of 98%. Of the positive cases, only 19 (44%) had been specifically suspected of MTC by cytology, highlighting the limitations of light microscopy to detect this disease. Three surgically confirmed MTC cases that were detected by the MTC Classifier had low basal serum calcitonin values, indicating these would have been missed by traditional calcitonin screening methods. A pooled analysis of three independent validation sets demonstrates high test sensitivity (97.9%), specificity (99.8%), PPV (97.9%), and negative predictive value (99.8%)., Conclusions: A clinical paradigm is proposed, whereby cytologically indeterminate thyroid nodules being tested for common malignancies using gene expression can be simultaneously tested for MTC using the same genomic assay at no added cost.