Updated Technology May Improve Accuracy of Thyroid Sample Classification
Posted: Wednesday, April 15, 2020
When compared with the older Afirma gene-expression classifier (GEC), the Afirma genomic-sequencing classifier (GSC) has been found to more accurately categorize indeterminate thyroid specimens, according to research published in Cancer Cytopathology. The study relied on specimens gathered from fine-needle aspiration, which has contributed to about a 50% reduction in thyroid surgery.
“Despite [the] availability of molecular panels for indeterminate thyroid nodules, we have a significant number of patients who undergo thyroid surgery,” noted Shuanzeng Wei, MD, PhD, of Fox Chase Cancer Center, in an institutional press release. “But a lot of them are benign on final pathology and could have avoided surgery. The new test turns out to be more accurate. It’s a huge deal for patients.”
A total of 272 indeterminate thyroid samples were retroactively analyzed, with 194 evaluated using GEC and 78 using GSC. In the GEC group, 45.4% of samples (n = 88) were found to be benign, compared with 66.7% of benign samples (n = 52) in the GSC group. In addition, the GEC group had 31 total cases with oncocytic cytology, with 16.1% (n = 5) found to be benign and 83.9% (n = 26) classified as suspicious. However, the GSC group again experienced more accurate categorization, with 80% (n = 8) of samples with oncocytic cytology identified as benign and 20% (n = 2) classified as suspicious. Although genomic sequencing was found to have an overall positive predictive value greater than that of gene expression (57.1% vs. 36.7%), statistical significance was not reported (P = .15).
However, Dr. Wei cautioned that his team has used the new test for just 2 years. “We need more patients to further validate it,” he noted in a Fox Chase press release.
Disclosure: For full disclosures of the study authors, visit onlinelibrary.wiley.com.
