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Performance of Afirma genomic sequencing classifier vs gene expression classifier in Bethesda category III thyroid
Lin Zhang1, Brian Smola1, Madelyn Lew1
1Department of Pathology and Clinical Laboratories, University of Michigan, Ann Arbor, Michigan, USA.
Background:
Afirma gene expression classifier (GEC) is an adjunct to thyroid fine needle aspiration shown to improve pre-operative risk assessment and reduce unnecessary surgery of indeterminate thyroid nodules. Genomic sequencing classifier (GSC) is a newer version aiming to improve specificity and positive predictive value (PPV) of Afirma testing. There are limited studies comparing GSC vs GEC. This study was undertaken to compare these classifiers in terms of diagnostic performance and effect on clinical management of indeterminate thyroid nodules.
Methods:
The study cohort consisted of patients with thyroid nodules that had a recurrent cytologic diagnosis of atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS) and were tested by either GEC or GSC. Patient demographics, nodule size, and clinical follow-up were recorded. Benign call rate (BCR) of Afirma testing, rate of subsequent surgery (RSS), rate of histology-confirmed malignancy (RHM), as well as diagnostic sensitivity, specificity, PPV, negative predicative value (NPV), and accuracy were calculated and compared between GSC and GEC cohorts.
Results:
Among 264 AUS/FLUS thyroid nodules, 127 and 137 were tested with GEC and GSC, respectively. Compared to GEC, GSC demonstrated increased BCR (77.3% vs 52%), decreased RSS (31.4% vs 51.2%), greater RHM (29% vs 9.8%) associated with a suspicious Afirma result, as well as improved specificity (82.8% vs 54.5%), PPV (29% vs 9.8%), and diagnostic accuracy (83.9% vs 56.7%), while maintaining high sensitivity and NPV.
Conclusion:
Afirma GSC substantially improved BCR, RSS, RHM, and diagnostic performance, enhancing appropriate triage and thereby helped avoid unnecessary surgery in AUS/FLUS thyroid nodules.
