Impact of Afirma gene expression classifier on cytopathology diagnosis and rate of thyroidectomy : Afirma Impact on Thyroid FNA and Surgery

Molecular markers hold the promise of improved diagnostic yield in thyroid fine-needle biopsy. The Afirma gene expression classifier (GEC), available commercially, reports a negative predictive value of 94% in the diagnosis of benign nodules after indeterminate cytology. However, there are currently no independent studies of the performance of this assay.

We set out to develop a molecular test that distinguishes benign and malignant thyroid nodules using fine-needle aspirates (FNA). We used mRNA expression analysis to measure more than 247,186 transcripts in 315 thyroid nodules, comprising multiple subtypes. The data set consisted of 178 retrospective surgical tissues and 137 prospectively collected FNA samples. Two classifiers were trained separately on surgical tissues and FNAs. The performance was evaluated using an independent set of 48 prospective FNA samples, which included 50% with indeterminate cytopathology. Performance of the tissue-trained classifier was markedly lower in FNAs than in tissue. Exploratory analysis pointed to differences in cellular heterogeneity between tissues and FNAs as the likely cause. The classifier trained on FNA samples resulted in increased performance, estimated using both 30-fold cross-validation and an independent test set. On the test set, negative predictive value and specificity were estimated to be 96 and 84%, respectively, suggesting clinical utility in the management of patients considering surgery. Using in silico and in vitro mixing experiments, we demonstrated that even in the presence of 80% dilution with benign background, the classifier can correctly recognize malignancy in the majority of FNA samples. The FNA-trained classifier was able to classify an independent set of FNAs in which substantial RNA degradation had occurred and in the presence of blood. High tolerance to dilution makes the classifier useful in routine clinical settings where sampling error may be a concern. An ongoing multicenter clinical trial will allow us to validate molecular test performance on a larger independent test set of prospectively collected thyroid FNAs.

The Afirma Gene Expression Classifier (GEC) molecular marker assay was developed for the purpose of improving surgical decision-making with indeterminate fine-needle aspiration (FNA) biopsies of thyroid nodules. In this paper, we analyze the performance of the GEC over 27 months in a community hospital-based thyroid surgery practice.