Performance of the Afirma genomic sequencing classifier versus gene expression classifier: An institutional experience

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

Background: The use of fine-needle aspiration (FNA) to triage thyroid nodules has resulted in a significant reduction in thyroid surgery. However, approximately one-third of FNA specimens fall into the “indeterminate” category. The Afirma gene expression classifier (GEC) has been used to identify benign nodules with a high sensitivity and negative predictive value. However, the specificity and positive predictive value of the “suspicious” category are low. The updated Afirma genomic sequencing classifier (GSC) has been reported to demonstrate increased specificity while maintaining a high sensitivity and negative predictive value. Methods: The authors retrospectively investigated 272 indeterminate thyroid FNA specimens (Bethesda categories III and IV) from nodules measuring >1 cm using the Afirma GEC or GSC tests (July 2012-January 2019). Results: Of the 194 nodules tested using the Afirma GEC, a benign result was obtained in 88 cases (45.4%). In comparison, 52 of 78 FNA samples (66.7%) tested using GSC yielded a benign result (P =.002). In the GEC group, there were 31 cases with oncocytic cytology, 5 of which (16.1%) were benign on Afirma and 26 of which (83.9%) were suspicious on Afirma. In contrast, in the GSC group, there were 10 cases with oncocytic cytology, 8 of which (80%) were benign on Afirma and only 2 of which (20%) were found to be suspicious on Afirma (P <.001). The positive predictive value of the GSC group (57.1%) was higher than that of the GEC group (36.7%); however, there was no statistical significance noted (P =.15). Conclusions: A larger percentage of indeterminate thyroid FNA specimens were classified as benign using the Afirma GSC compared with the Afirma GEC, especially among samples with oncocytic features. The Afirma GSC appears to have a higher benign call rate compared with the Afirma GEC.

Original languageEnglish
Pages (from-to)720-724
Number of pages5
JournalCancer cytopathology
Volume127
Issue number11
DOIs
StatePublished - Nov 1 2019

Keywords

  • Adenoma/genetics
  • Biopsy, Fine-Needle
  • Female
  • Gene Expression
  • Genomics/methods
  • Goiter/genetics
  • Humans
  • Machine Learning
  • Male
  • Middle Aged
  • RNA, Messenger/analysis
  • Retrospective Studies
  • Sensitivity and Specificity
  • Sequence Analysis, DNA/methods
  • Thyroid Gland/pathology
  • Thyroid Nodule/genetics
  • Ultrasonography, Interventional

Fingerprint

Dive into the research topics of 'Performance of the Afirma genomic sequencing classifier versus gene expression classifier: An institutional experience'. Together they form a unique fingerprint.

Cite this