LONG-TERM NONOPERATIVE RATE OF THYROID NODULES WITH BENIGN RESULTS ON THE AFIRMA GENE EXPRESSION CLASSIFIER

Endocr Pract. 2016 Jun;22(6):666-72. doi: 10.4158/EP151006.OR. Epub 2016 Jan 20.

Abstract

Objective: The primary objective was to assess the operative rate in patients with a benign result from the Afirma gene expression classifier (GEC) during long-term follow-up at nonacademic medical facilities. The secondary endpoint of this study was the treating physician's opinion regarding the safety of GEC use compared to the hypothetical situation of providing thyroid nodule management without the GEC.

Methods: This was a retrospective study of nonacademic medical practices utilizing the GEC. Those clinicians utilizing the GEC testing who had three or more 'benign' results during the data collection period (September 2010 through June 2014) were invited to participate. Operative status and patient demographics were documented for patients with GEC testing at least 36 months (± 3 months) prior to the date of data collection. A survey also was administered to the treating physicians to assess their perceived safety of using the GEC in patient care.

Results: During 36 months (± 3 months) of follow-up, 17 of 98 patients (17.3%) with a 'benign' GEC result underwent surgery. Within the first 2 years after a 'benign' GEC, 88% of surgeries were performed. Regarding safety of the GEC, the treating physicians reported that patient safety was improved by using the GEC compared to not using the GEC in 78 of 91 cases (86%).

Conclusion: It appears that a 'benign' result on the GEC is associated with a reduction in the rate of thyroid surgeries compared to published data when patients are followed for 36 months after testing. A nonoperative approach to follow-up was felt to be a safe alternative to diagnostic surgery by the majority of responsible physicians in the study.

Abbreviations: AUS = atypia of undetermined significance FLUS = follicular lesion of undetermined significance FN = follicular neoplasm FNA = fine-needle aspiration GEC = gene expression classifier.