A systematic review of the methods of diagnostic accuracy studies of the Afirma® Gene Expression Classifier.

Quan-Yang Duh, Naifa Busaidy, Catherine Rahilly-Tierney, Hossein Gharib, Gregory W Randolph,


Thyroid : official journal of the American Thyroid Association, July 25, 2017


The Afirma® Gene Expression Classifier (GEC) risk-stratifies 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. We searched Medline and EMBASE for studies published between January 1, 2010 and June 30, 2016 examining the sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) of the GEC. We customized the Quality of Diagnostic Accuracy Studies 2 (QUADAS-2) tool to evaluate the methods of included studies in each of four domains: nodule selection, index test execution, reference standard assignment, and flow and timing. We used signaling questions to identify sources of potential bias in calculation of diagnostic accuracy, and assessed issues of applicability. Three panelists applied the QUADAS2 tool to each study included, and divergence was resolved in conference. In twelve 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 NPV. Other flaws identified included restriction to ITNs that had already been selected for referral for thyroidectomy or lobectomy. 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.  .


Pubmed Link: 28741442

DOI: 10.1089/thy.2016.0656