A Systematic Review of the Methods of Diagnostic Accuracy Studies of the Afirma Gene Expression Classifier

Background: The Afirma (R) Gene Expression Classifier (GEC) risk stratifies The Bethesda System for the Reporting of Thyroid Cytopathology class III/IV (indeterminate) thyroid nodules (ITNs) as suspicious for malignancy or benign. Several authors have published studies describing the diagnostic accuracy of the GEC. However, the quality of these methods has not been rigorously examined. Summary: In this study, MEDLINE and EMBASE were searched for studies published between January 1, 2010, and June 30, 2016, examining the sensitivity, specificity, negative predictive value, and positive predictive value of the GEC. The Quality of Diagnostic Accuracy Studies 2 was customized to evaluate the methods of included studies in each of four domains: nodule selection, index test execution, reference standard assignment, and flow and timing. Signaling questions were used to identify sources of potential bias in calculation of diagnostic accuracy, and issues of applicability were assessed. Three panelists applied the Quality of Diagnostic Accuracy Studies 2 tool to each study included, and divergence was resolved in conference. In 12 studies evaluated, the most common methodologic flaw was lack of reference standard diagnosis assignment to un-excised GEC-benign ITNs. Exclusion of these ITNs from the analyses resulted in unreliable estimates of specificity and negative predictive value. Other flaws identified included restriction to ITNs that had already been selected for referral for thyroidectomy or lobectomy. Conclusions: Future studies should define and assign a true negative label to GEC-benign nodules that do not develop malignant signs or symptoms during a pre-specified period of follow-up, and these nodules should be included in calculations of diagnostic accuracy.