Performance of Afirma genomic sequencing classifier vs gene expression classifier in Bethesda category III thyroid nodules: An institutional experience

Assessment of the risk of malignancy in Bethesda III thyroid nodules: a comprehensive review

The increasing prevalence of thyroid cancer emphasizes the need for a thorough assessment of risk of malignancy in Bethesda III nodules. Various methods ranging commercial platforms of molecular genetic testing (including Afirma® GEC, Afirma® GSC, ThyroSeq® V3, RosettaGX®, ThyGeNEXT®/ThyraMIR®, ThyroidPRINT®) to radionuclide scans and ultrasonography have been investigated to provide a more nuanced comprehension of risk estimation. The integration of molecular studies and imaging techniques into clinical practice may provide clinicians with improved and personalized risk assessment. This integrated approach we feel may enable clinicians to carefully tailor interventions, thereby minimizing the likelihood of unnecessary thyroid surgeries and overall crafting the optimal treatment. By aligning with the evolving landscape of personalized healthcare, this comprehensive strategy ensures a patient-centric approach to thyroid nodule and thyroid cancer management.

AI diagnosis of Bethesda category IV thyroid nodules

Thyroid nodules are a common disease, and fine needle aspiration cytology (FNAC) is the primary method to assess their malignancy. For the diagnosis of follicular thyroid nodules, however, FNAC has limitations. FNAC can classify them only as Bethesda IV nodules, leaving their exact malignant status and pathological type undetermined. This imprecise diagnosis creates difficulties in selecting the follow-up treatment. In this retrospective study, we collected ultrasound (US) image data of Bethesda IV thyroid nodules from 2006 to 2022 from five hospitals. Then, US image-based artificial intelligence (AI) models were trained to identify the specific category of Bethesda IV thyroid nodules. We tested the models using two independent datasets, and the best AI model achieved an area under the curve (AUC) between 0.90 and 0.95, demonstrating its potential value for clinical application. Our research findings indicate that AI could change the diagnosis and management process of Bethesda IV thyroid nodules.

Performance of Afirma genomic sequencing classifier and histopathological outcome in Bethesda category III thyroid nodules: Initial versus repeat fine-needle aspiration

BACKGROUND

There is limited data comparing the performance of Afirma Genomic Sequencing Classifier (GSC) in thyroid nodules carrying an initial versus a repeat diagnosis of atypia of undetermined significance (AUS). This study reported an institutional experience in this regard.

MATERIALS AND METHODS

This retrospective study included consecutive thyroid nodules that had an initial or a repeat AUS diagnosis and had a subsequent GSC diagnostic result (benign or suspicious) from 2017 to 2021. All nodules were followed by surgical intervention or by clinical and/or ultrasound monitoring. GSC's benign call rate (BCR), rate of histology-proven malignancy associated with a suspicious GSC result, and diagnostic parameters of GSC were calculated and compared between the two cohorts (initial versus repeat AUS). Statistical significance was defined with a p-value of <.05 for all analysis.

RESULTS

A total of 202 cases fulfilled inclusion criteria, including 67 and 135 thyroid nodules with an initial and a repeat AUS diagnosis, respectively. BCR was 67% and 66% in initial and repeat AUS cohorts, respectively. Rate of histology-proven malignancy associated with a suspicious GSC result were 22% and 24% in initial and repeat AUS cohorts, respectively. Compared with the repeat AUS cohort, the initial AUS cohort showed slightly lower sensitivity (83% vs. 100%), specificity (70% vs. 73%), PPV (23% vs. 24%), NPV (98% vs. 100%), and diagnostic accuracy (72% vs. 75%). Nevertheless, these differences did not reach statistical significance.

CONCLUSION

GSC demonstrated comparable performance in thyroid nodules with a repeat AUS diagnosis versus nodules with an initial AUS diagnosis.

A Triumvirate:: Correlating Thyroid Cytopathology, Molecular Testing, and Histopathology

Risk stratification is essential in the preoperative evaluation and management of thyroid nodules, most of which are benign. Advances in DNA and RNA sequencing have shed light on the molecular drivers of thyroid cancer. Molecular testing of cytologically indeterminate nodules has helped refine risk stratification, triage patients for surgery, and determine the extent of surgery. Molecular platforms with high negative predictive values can help identify nodules that may be spared surgery and can be managed conservatively. Here we discuss the importance of integrating cytomorphologic, molecular, and histologic features to help avoid errors and improve patient management.

Molecular diagnostics in the evaluation of thyroid nodules: Current use and prospective opportunities

Thyroid cancer is the most common endocrine malignancy with an estimated 43,800 new cases to be diagnosed in 2022 and representing the 7th most common cancer in women. While thyroid nodules are very common, being identified in over 60% of randomly selected adults, only 5-15% of thyroid nodules harbor thyroid malignancy. Therefore, it is incumbent upon physicians to detect and treat thyroid malignancies as is clinically appropriate and avoid unnecessary invasive procedures in patients with benign asymptomatic lesions. Over the last 15-20 years, rapid advances have been made in cytomolecular testing to aid in thyroid nodule management. Initially, indeterminate thyroid nodules, those with Bethesda III or IV cytology and approximately a 10-40% risk of malignancy, were studied to assess benignity or malignancy. More recently, next generation sequencing and micro-RNA technology platforms have refined the diagnostic capacity of thyroid nodule molecular testing and have introduced opportunities to glean prognostic information from both cytologically indeterminate and malignant thyroid nodules. Therefore, clinicians can move beyond determination of malignancy, and utilize contemporary molecular information to aid in decisions such as extent of surgery and post-therapy monitoring plans. Future opportunities include molecularly derived information about tumor behavior, neo-adjuvant treatment opportunities and response to thyroid cancer therapies.

Real World Performance of The Afirma Genomic Sequencing Classifier (GSC) - A Meta-analysis

CONTEXT

The Afirma® GSC aids in risk stratifying indeterminate thyroid nodule cytology (ITN). The 2018 GSC validation study (VS) reported a sensitivity (SN) of 91%, specificity (SP) of 68%, positive predictive value (PPV) of 47%, and negative predictive value (NPV) of 96%. Since then, 13 independent real world (RW) post-validation studies have been published.

OBJECTIVE

This study's objective is to compare the RW GSC performance to the VS metrics.

METHODS

Rules and assumptions applying to this analysis include: 1. At least one patient with molecular benign results must have surgery for that study to be included in SN, SP and NPV analyses. 2. Molecular benign results without surgical histology are considered true negatives (TN) (as are the molecular benign results with benign surgical histology) 3. Unoperated patients with suspicious results are either excluded from the analysis (observed PPV (oPPV) and observed SP (oSP)) or assumed as histology negatives (false positives - conservative PPV (cPPV) and conservative SP (cSP)) 4. NIFTP is considered malignant.

RESULTS

In RW studies, the GSC demonstrates a SN, oSP, oPPV and NPV of 97%, 88%, 65%, 99% respectively, and conservative RW performance showed cSP of 80% and cPPV of 49%, all significantly higher than the VS save for SN and cPPV. There was also a higher benign call rate (BCR) of 67% in RW studies compared to 54% in the VS (p < 0.05).

CONCLUSION

RW data for the Afirma GSC demonstrates significantly better oSP and oPPV performance compared to the VS, indicating an increased yield of cancers for resected GSC suspicious nodules. The higher BCR likely increases the overall rate of clinical observation in lieu of surgery.

SFE-AFCE-SFMN 2022 Consensus on the management of thyroid nodules : Role of molecular tests for cytologically indeterminate thyroid nodules

The SFE-AFCE-SFMN 2022 consensus deals with the management of thyroid nodules, a condition that is a frequent reason for consultation in endocrinology. In more than 90% of cases, patients are euthyroid, with benign non-progressive nodules that do not warrant specific treatment. The clinician's objective is to detect malignant thyroid nodules at risk of recurrence and death, toxic nodules responsible for hyperthyroidism or compressive nodules warranting treatment. The diagnosis and treatment of thyroid nodules requires close collaboration between endocrinologists, nuclear medicine physicians and surgeons, but also involves other specialists. Therefore, this consensus statement was established jointly by 3 societies: the French Society of Endocrinology (SFE), French Association of Endocrine Surgery (AFCE) and French Society of Nuclear Medicine (SFMN); the various working groups included experts from other specialties (pathologists, radiologists, pediatricians, biologists, etc.). Because of the emerging role of molecular fine-needle cytology diagnostics, the French Endocrine Society convened a panel of experts to review the evidence for the diagnostic value of molecular tests performed on cytologically indeterminate thyroid nodules.

Performance of Afirma genomic sequencing classifier and histopathological outcome are associated with patterns of atypia in Bethesda category III thyroid nodules

BACKGROUND

Data on Afirma's genomic sequencing classifier (GSC) performance in atypia of undetermined significance (AUS) subcategories is limited. This study investigated GSC performance in AUS nodules with architectural atypia (AUS-A), cytological atypia (AUS-C), architectural and cytological atypia (AUS-AC), and predominantly Hürthle cells (AUS-HC).

METHODS

This study retrieved consecutive thyroid nodules having a recurrent cytologic diagnosis of AUS with qualifiers and a concurrent GSC diagnostic result. All nodules were followed by either surgical intervention or clinical and/or ultrasound monitoring (≥6 months). GSC benign call rate (BCR), rate of histology-proven malignancy, and diagnostic parameters of GSC were calculated for individual AUS subcategories. Statistical analysis was performed using the Fisher exact test.

RESULTS

A total of 135 AUS nodules fulfilled inclusion criteria, including 79 AUS-A, 9 AUS-C, 29 AUS-AC, and 18 AUS-HC. BCR was 72.2%, 66.7%, 44.8%, and 77.8% in AUS-A, AUS-C, AUS-AC, and AUS-HC, respectively. AUS-A showed a greater BCR than AUS-AC (p &lt; .05). All GSC-benign nodules were considered benign on clinical or surgical follow-up. Among GSC-suspicious nodules, histology-proven malignancies represented 4.5% of AUS-A, 0% of AUS-C, 56.3% of AUS-AC, and 25.0% of AUS-HC cases. AUS-AC demonstrated a higher malignant rate compared with AUS-A (p &lt; .05). GSC offers 100% NPV and a wide range (5%-56%) of PPV across all AUS subcategories. AUS-AC demonstrated a greater PPV compared with AUS-A (p &lt; .05).

CONCLUSION

BCR of GSC and malignant rates associated with suspicious GSC may differ in various AUS subcategories. GSC-suspicious nodules with both architectural and cytologic atypia are more likely to be malignant. These findings may improve clinical triage and/or management of patients with AUS thyroid nodules.

Assessing Bias and Limitations of Clinical Validation Studies of Molecular Diagnostic Tests for Indeterminate Thyroid Nodules: Systematic Review and Meta-Analysis

Background: Molecular tests for thyroid nodules with indeterminate fine needle aspiration results are increasingly used in clinical practice; however, true diagnostic summaries of these tests are unknown. A systematic review and meta-analysis were completed to (1) evaluate the accuracy of commercially available molecular tests for malignancy in indeterminate thyroid nodules and (2) quantify biases and limitations in studies that validate those tests. Summary: PubMed, EMBASE, and Web of Science were systematically searched through July 2021. English language articles that reported original clinical validation attempts of molecular tests for indeterminate thyroid nodules were included if they reported counts of true-negative, true-positive, false-negative, and false-positive results. We performed screening and full-text review, followed by assessment of eight common biases and limitations, extraction of diagnostic and histopathological information, and meta-analysis of clinical validity using a bivariate linear mixed-effects model. Forty-nine studies were included. Meta-analysis of Afirma Gene expression classifiers (GEC; n = 38 studies) revealed a sensitivity of 0.92 (confidence interval: 0.90-0.94), specificity of 0.26 (0.20-0.32), negative likelihood ratio (LR-) of 0.32 (0.23-0.44), positive LR+ of 1.24 (1.15-1.35), and area under the curve (AUC) of 0.83 (0.74-0.89). Afirma Genomic Sequencing Classifier (GSC; n = 10) had a sensitivity of 0.94 (0.89-0.96), specificity of 0.38 (0.27-0.50), LR- of 0.18 (0.10-0.30), LR+ of 1.52 (1.28-1.87), and AUC of 0.91 (0.62-0.92). ThyroSeq v1 and v2 (n = 10) had a sensitivity of 0.86 (0.82-0.90), specificity of 0.74 (0.59-0.85), LR- of 0.19 (0.13-0.26), LR+ of 3.52 (2.08-5.92), and AUC of 0.86 (0.81-0.90). ThyroSeq v3 (n = 6) had a sensitivity of 0.92 (0.86-0.95), specificity of 0.41 (0.18-0.69), LR- of 0.24 (0.09-0.62), LR+ of 1.67 (1.09-2.98), and AUC of 0.90 (0.63-0.92). Fourteen percent of studies conducted a blinded histopathologic review of excised thyroid nodules, and 8% made the decision to go to surgery blind to molecular test results. Conclusions: Meta-analyses reveal a high diagnostic accuracy of molecular tests for thyroid nodule assessment of malignancy risk; however, these studies are subject to several limitations. Limitations and their potential clinical impacts must be addressed and, when feasible, adjusted for using valid statistical methodologies.

DIAGNOSIS OF ENDOCRINE DISEASE: Usefulness of genetic testing of fine-needle aspirations for diagnosis of thyroid cancer

OBJECTIVE

Genetic testing is increasingly used to diagnose or rule out thyroid cancer in indeterminate fine-needle aspirations. This review evaluates the usefulness of these methods with considerations of advantages and limitations.

DESIGN

Given the diagnostic problem associated with the increasing incidental detection of indeterminate thyroid nodules in the context of thyroid cancer overtreatment, we consider the conditions and respective necessary settings for the role of genetic testing to improve presurgical malignancy risk stratification.

METHODS

We review diagnostic pathway requirements and commercially available molecular tests with their respective advantages and disadvantages and discuss the prerequisites required for local application and implementation including quality assurance for local ultrasound and cytopathology practices.

RESULTS

Recent improvements in available molecular diagnostic tests have brought high sensitivity and specificity in initial validation studies, but whether these promising results translate to other clinical settings depends on the quality of the local thyroid nodule diagnostic pathway.

CONCLUSIONS

Genetic testing can meaningfully improve presurgical malignancy risk assessment, but more work is needed to implement and use genetic testing effectively in local settings.

Preoperative Identification of Medullary Thyroid Carcinoma (MTC): Clinical Validation of the Afirma MTC RNA-Sequencing Classifier

Background: Cytopathological evaluation of thyroid fine-needle aspiration biopsy (FNAB) specimens can fail to raise preoperative suspicion of medullary thyroid carcinoma (MTC). The Afirma RNA-sequencing MTC classifier identifies MTC among FNA samples that are cytologically indeterminate, suspicious, or malignant (Bethesda categories III-VI). In this study we report the development and clinical performance of this MTC classifier. Methods: Algorithm training was performed with a set of 483 FNAB specimens (21 MTC and 462 non-MTC). A support vector machine classifier was developed using 108 differentially expressed genes, which includes the 5 genes in the prior Afirma microarray-based MTC cassette. Results: The final MTC classifier was blindly tested on 211 preoperative FNAB specimens with subsequent surgical pathology, including 21 MTC and 190 non-MTC specimens from benign and malignant thyroid nodules independent from those used in training. The classifier had 100% sensitivity (21/21 MTC FNAB specimens correctly called positive; 95% confidence interval [CI] = 83.9-100%) and 100% specificity (190/190 non-MTC FNAs correctly called negative; CI = 98.1-100%). All positive samples had pathological confirmation of MTC, while all negative samples were negative for MTC on surgical pathology. Conclusions: The RNA-sequencing MTC classifier accurately identified MTC from preoperative thyroid nodule FNAB specimens in an independent validation cohort. This identification may facilitate an MTC-specific preoperative evaluation and resulting treatment.