TY - JOUR
T1 - Performance of the Afirma genomic sequencing classifier versus gene expression classifier
T2 - An institutional experience
AU - Wei, Shuanzeng
AU - Veloski, Colleen
AU - Sharda, Pankaj
AU - Ehya, Hormoz
N1 - Publisher Copyright:
© 2019 American Cancer Society
PY - 2019/11/1
Y1 - 2019/11/1
N2 - 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.
AB - 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.
KW - Adenoma/genetics
KW - Biopsy, Fine-Needle
KW - Female
KW - Gene Expression
KW - Genomics/methods
KW - Goiter/genetics
KW - Humans
KW - Machine Learning
KW - Male
KW - Middle Aged
KW - RNA, Messenger/analysis
KW - Retrospective Studies
KW - Sensitivity and Specificity
KW - Sequence Analysis, DNA/methods
KW - Thyroid Gland/pathology
KW - Thyroid Nodule/genetics
KW - Ultrasonography, Interventional
UR - http://www.scopus.com/inward/record.url?scp=85074520943&partnerID=8YFLogxK
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=purepublist2023&SrcAuth=WosAPI&KeyUT=WOS:000486840700001&DestLinkType=FullRecord&DestApp=WOS
U2 - 10.1002/cncy.22188
DO - 10.1002/cncy.22188
M3 - Article
C2 - 31536167
SN - 1934-662X
VL - 127
SP - 720
EP - 724
JO - Cancer cytopathology
JF - Cancer cytopathology
IS - 11
ER -