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VICTORIA, B.C. – Several new and improved molecular classifiers show good performance for preoperatively assessing the nature of thyroid nodules, including histologic subsets that continue to pose diagnostic challenges, according to a trio of studies reported at the annual meeting of the American Thyroid Association.
ThyroSeq v3 classifier
In a prospective, blinded, multi-institutional study, investigators validated the ThyroSeq v3 genomic classifier, which uses next-generation sequencing to test for mutations, fusions, gene expression alterations, and copy number variations in 112 genes.
The validation cohort consisted of 234 patients from 10 centers who had thyroid nodules with Bethesda III to V cytology and known surgical outcome, with central pathology review, and successful molecular testing. In total, they had 257 fine needle aspiration samples.
Of the 247 samples from nodules having Bethesda III or IV cytology – those of greatest interest – 28% were cancer or noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), reported senior author Yuri Nikiforov, MD, PhD, professor of pathology and director of the division of molecular & genomic pathology at the University of Pittsburgh Medical Center. “Both cancer and NIFTP are surgical diseases, so we felt they belong in one group,” he noted.
Among the Bethesda III or IV samples, ThyroSeq v3 had a sensitivity of 94%, a specificity of 82%, a positive predictive value of 66%, and a negative predictive value of 97%. Additional analyses showed that the test would still have a negative predictive value of 95% or better up to a cancer/NIFTP prevalence of 44%.
All five false-negative cases in the entire study cohort were intrathyroidal nodules of low stage and without aggressive histology.
Of the 33 false-positive cases, 68% were diagnosed on pathology as Hurthle cell or follicular adenomas, 10% were initially diagnosed by local pathologists as cancer or NIFTP, and 94% harbored clonal oncogenic molecular alterations.
“So, these are not actually hyperplasia; these are true tumors. Probably at least some of them would have the potential to progress,” said Dr. Nikiforov. “I believe that this so-called false-positive rate may not be really false positive. This is a rate of detection of precancerous tumors, not hyperplasia, that still may require surgical excision.”
In this study, “we found very high sensitivity and negative predictive value of ThyroSeq v3, with robust negative predictive value in populations with different disease prevalence,” he concluded. “Robust performance was achieved in many thyroid cancer types, including Hurthle cell cancer.”
All study patients underwent surgery, so it is not clear how the classifier would perform in the context of surveillance, he acknowledged. But the 97% negative predictive value gives confidence for patients having a negative result.
“Those patients very likely can be observed – not necessarily dismissed from medical surveillance, but observed – and could probably avoid surgery,” he said. “If patients have a positive test, it will depend on the type of mutation, because some of them confer a high risk and others confer low risk. So, there may be a spectrum of management based on combination of clinical parameters and molecular testing. But those are more likely to be surgical candidates.”
“This is a study that is desperately needed in this field,” session attendee Bryan McIver, MD, PhD, an endocrinologist and deputy physician-in-chief at the Moffitt Cancer Center in Tampa, said in an interview. “These are very challenging studies to do, because the marketing of these molecular tests has run ahead of a lot of the clinical studies. 
“It’s very hard in the United States, at least, to find patients who are truly naive to molecular testing whom you can take to the operating room,” he explained. “And if you can’t take patients with a negative molecular test to the operating room, then you can’t actually calculate the true sensitivity and specificity of the test, and the whole evaluation of the test starts to become skewed.”
According to Dr. McIver, this study is noteworthy in that it largely fulfills four key criteria: There were no post hoc sample exclusions after unblinding of data, both pathology evaluation and decision to operate were blinded to classifier results, and patients were generally unselected, with little to no prior molecular testing.
“So, we actually have a proper high-quality validation study now available for this new test, the ThyroSeq v3,” he noted. “That sets the bar where it needed to be set a long time ago, and I can’t begin to tell you how excited I am to finally have a test that passed that bar. The fact that it shows a negative predictive value of 97% in this clinical study and a positive predictive value in the mid-60% range means that there is a potential for a clinical utility there that is backed by solid science. In this field, that’s almost unique.”
Afirma GSC with Hurthle classifiers
In a second study, investigators led by Quan-Yang Duh, MD, professor of surgery, division of general surgery, and chief, section of endocrine surgery, University of California, San Francisco, developed and validated a pair of classifiers to enhance performance of the Afirma platform among Hurthle cell specimens.
“The Hurthle cell lesions tend to give us trouble,” Dr. Duh said. On molecular analysis, those that are malignant seldom harbor mutations that would aid diagnosis, whereas those that are benign are usually classified as suspicious by the original Afirma Gene Expression Classifier (GEC).
“The specific group that is causing trouble are those that are Hurthle cell but not neoplasm, because they are the ones that give you the false positives,” Dr. Duh said. Therefore, it makes sense to stratify lesions on both of these factors, and then subject that specific subset to a more stringent threshold. 
The investigators developed two classifiers that work with the Afirma core Genomic Sequencing Classifier (GSC), which uses RNA sequencing and machine learning algorithms.
The first classifier uses differential expression of 1,408 genes to determine whether a sample contains Hurthle cells. The second classifier, applied only to lesions containing Hurthle cells, uses differential expression of 2,041 genes and assesses loss of heterozygosity – which is prevalent in Hurthle cell neoplasms – to determine whether a Hurthle cell lesion is a neoplasm.
The ensemble model then makes a final classification, using a higher threshold for suspicious lesions determined to be Hurthle cell but not neoplasm, and a normal threshold for all the rest.
The investigators validated the Afirma GSC with the two classifiers in blinded fashion using 186 thyroid lesion samples having Bethesda III or IV cytology that had been part of the overall multicenter validation of the original Afirma GEC (N Engl J Med. 2012 Aug 23;367[8]:705-15).
Among the 26 Hurthle cell lesions, specificity for identifying benign lesions improved from 11.8% with the original Afirma GEC to 58.8% with the Afirma GSC and new classifiers. That was an absolute gain of 47% (P = .012), Dr. Duh reported. Sensitivity for identifying cancer was 88.9%.
There were also smaller absolute gains in specificity of 18% among all lesions in the cohort (P = .0028) and 14% among non-Hurthle lesions (P = .028).
“The new GSC test has significantly improved specificity in the patients with Bethesda III and IV specimens with Hurthle cells, and this may reduce unnecessary diagnostic surgery,” said Dr. Duh. “Basically, there are fewer false positives and more patients who can be called benign in the Hurthle cell group who would not need an operation.”
Further validation is needed, he acknowledged. “For a while, I wouldn’t send my Hurthle cell aspirate patients for Afirma, because I knew it was going to come back suspicious. I think I will start to do it now, but we need to see what the answers look like” with additional validation.
Afirma GSC with medullary thyroid cancer classifier
In a third study, investigators developed and validated a classifier for medullary thyroid cancer to be used with the Afirma GSC. They were led by Gregory Randolph, MD, professor of otolaryngology and the Claire and John Bertucci Endowed Chair in Thyroid Surgical Oncology at Harvard Medical School, and division chief of the general and thyroid/parathyroid endocrine surgical divisions at the Massachusetts Eye and Ear Infirmary, Boston.
Better preoperative identification of this cancer is key for several reasons, he maintained.
Establishing the diagnosis from needle biopsy is challenging, because some features overlap with those of other thyroid lesions, according to Dr. Randolph. In about a third of patients with medullary thyroid cancer brought to the operating room, the diagnosis is unknown at the time, and that often results in inadequate initial surgery.
The investigators developed a medullary thyroid cancer classifier cassette that assesses differential expression of 108 genes. They then performed blinded, independent validation in a cohort of 211 fine-needle aspiration samples from thyroid nodules: 21 medullary thyroid cancers and 190 other benign and malignant neoplasms.
Results showed that the Afirma GSC with the medullary thyroid cancer classifier had sensitivity of 100% and specificity of 100%, reported Dr. Randolph.
“The Afirma GSC medullary thyroid cancer testing cassette, within the larger GSC system, uses RNA sequencing and advanced machine learning to improve the diagnostic detection of medullary thyroid cancer, which currently misses approximately a third of medullary thyroid cancer patients,” he said.
Session attendees wondered which patients are appropriate candidates and how much the test will cost.
“We have to have a discussion about that, because the missed medullaries are, frankly, widely distributed – they can be in any of the Bethesda categories, basically,” Dr. Randolph said. “So, there are cytopathologic mistakes made uniformly, including in the suspicious and frankly malignant Bethesda categories. In terms of cost, this is embedded in the GSC classifier; so, if you order that test, you will obtain this medullary cassette.”
Actual sensitivity of the classifier may ultimately be less than 100% with use in larger samples, he acknowledged. “I think a greater number of validation tests is absolutely in order. I imagine this classifier may not be perfect, but it is way better than the third we miss with just cytopathology.”
Dr. Nikiforov disclosed that he is owner of an IP for ThyroSeq, and that his laboratory has a contract to offer the test commercially. Dr. Duh disclosed that he had no relevant conflicts of interest. Dr. Randolph disclosed that he had no relevant conflicts of interest.
VICTORIA, B.C. – Several new and improved molecular classifiers show good performance for preoperatively assessing the nature of thyroid nodules, including histologic subsets that continue to pose diagnostic challenges, according to a trio of studies reported at the annual meeting of the American Thyroid Association.
ThyroSeq v3 classifier
In a prospective, blinded, multi-institutional study, investigators validated the ThyroSeq v3 genomic classifier, which uses next-generation sequencing to test for mutations, fusions, gene expression alterations, and copy number variations in 112 genes.
The validation cohort consisted of 234 patients from 10 centers who had thyroid nodules with Bethesda III to V cytology and known surgical outcome, with central pathology review, and successful molecular testing. In total, they had 257 fine needle aspiration samples.
Of the 247 samples from nodules having Bethesda III or IV cytology – those of greatest interest – 28% were cancer or noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), reported senior author Yuri Nikiforov, MD, PhD, professor of pathology and director of the division of molecular & genomic pathology at the University of Pittsburgh Medical Center. “Both cancer and NIFTP are surgical diseases, so we felt they belong in one group,” he noted.
Among the Bethesda III or IV samples, ThyroSeq v3 had a sensitivity of 94%, a specificity of 82%, a positive predictive value of 66%, and a negative predictive value of 97%. Additional analyses showed that the test would still have a negative predictive value of 95% or better up to a cancer/NIFTP prevalence of 44%.
All five false-negative cases in the entire study cohort were intrathyroidal nodules of low stage and without aggressive histology.
Of the 33 false-positive cases, 68% were diagnosed on pathology as Hurthle cell or follicular adenomas, 10% were initially diagnosed by local pathologists as cancer or NIFTP, and 94% harbored clonal oncogenic molecular alterations.
“So, these are not actually hyperplasia; these are true tumors. Probably at least some of them would have the potential to progress,” said Dr. Nikiforov. “I believe that this so-called false-positive rate may not be really false positive. This is a rate of detection of precancerous tumors, not hyperplasia, that still may require surgical excision.”
In this study, “we found very high sensitivity and negative predictive value of ThyroSeq v3, with robust negative predictive value in populations with different disease prevalence,” he concluded. “Robust performance was achieved in many thyroid cancer types, including Hurthle cell cancer.”
All study patients underwent surgery, so it is not clear how the classifier would perform in the context of surveillance, he acknowledged. But the 97% negative predictive value gives confidence for patients having a negative result.
“Those patients very likely can be observed – not necessarily dismissed from medical surveillance, but observed – and could probably avoid surgery,” he said. “If patients have a positive test, it will depend on the type of mutation, because some of them confer a high risk and others confer low risk. So, there may be a spectrum of management based on combination of clinical parameters and molecular testing. But those are more likely to be surgical candidates.”
“This is a study that is desperately needed in this field,” session attendee Bryan McIver, MD, PhD, an endocrinologist and deputy physician-in-chief at the Moffitt Cancer Center in Tampa, said in an interview. “These are very challenging studies to do, because the marketing of these molecular tests has run ahead of a lot of the clinical studies.
“It’s very hard in the United States, at least, to find patients who are truly naive to molecular testing whom you can take to the operating room,” he explained. “And if you can’t take patients with a negative molecular test to the operating room, then you can’t actually calculate the true sensitivity and specificity of the test, and the whole evaluation of the test starts to become skewed.”
According to Dr. McIver, this study is noteworthy in that it largely fulfills four key criteria: There were no post hoc sample exclusions after unblinding of data, both pathology evaluation and decision to operate were blinded to classifier results, and patients were generally unselected, with little to no prior molecular testing.
“So, we actually have a proper high-quality validation study now available for this new test, the ThyroSeq v3,” he noted. “That sets the bar where it needed to be set a long time ago, and I can’t begin to tell you how excited I am to finally have a test that passed that bar. The fact that it shows a negative predictive value of 97% in this clinical study and a positive predictive value in the mid-60% range means that there is a potential for a clinical utility there that is backed by solid science. In this field, that’s almost unique.”
Afirma GSC with Hurthle classifiers
In a second study, investigators led by Quan-Yang Duh, MD, professor of surgery, division of general surgery, and chief, section of endocrine surgery, University of California, San Francisco, developed and validated a pair of classifiers to enhance performance of the Afirma platform among Hurthle cell specimens.
“The Hurthle cell lesions tend to give us trouble,” Dr. Duh said. On molecular analysis, those that are malignant seldom harbor mutations that would aid diagnosis, whereas those that are benign are usually classified as suspicious by the original Afirma Gene Expression Classifier (GEC).
“The specific group that is causing trouble are those that are Hurthle cell but not neoplasm, because they are the ones that give you the false positives,” Dr. Duh said. Therefore, it makes sense to stratify lesions on both of these factors, and then subject that specific subset to a more stringent threshold.
The investigators developed two classifiers that work with the Afirma core Genomic Sequencing Classifier (GSC), which uses RNA sequencing and machine learning algorithms.
The first classifier uses differential expression of 1,408 genes to determine whether a sample contains Hurthle cells. The second classifier, applied only to lesions containing Hurthle cells, uses differential expression of 2,041 genes and assesses loss of heterozygosity – which is prevalent in Hurthle cell neoplasms – to determine whether a Hurthle cell lesion is a neoplasm.
The ensemble model then makes a final classification, using a higher threshold for suspicious lesions determined to be Hurthle cell but not neoplasm, and a normal threshold for all the rest.
The investigators validated the Afirma GSC with the two classifiers in blinded fashion using 186 thyroid lesion samples having Bethesda III or IV cytology that had been part of the overall multicenter validation of the original Afirma GEC (N Engl J Med. 2012 Aug 23;367[8]:705-15).
Among the 26 Hurthle cell lesions, specificity for identifying benign lesions improved from 11.8% with the original Afirma GEC to 58.8% with the Afirma GSC and new classifiers. That was an absolute gain of 47% (P = .012), Dr. Duh reported. Sensitivity for identifying cancer was 88.9%.
There were also smaller absolute gains in specificity of 18% among all lesions in the cohort (P = .0028) and 14% among non-Hurthle lesions (P = .028).
“The new GSC test has significantly improved specificity in the patients with Bethesda III and IV specimens with Hurthle cells, and this may reduce unnecessary diagnostic surgery,” said Dr. Duh. “Basically, there are fewer false positives and more patients who can be called benign in the Hurthle cell group who would not need an operation.”
Further validation is needed, he acknowledged. “For a while, I wouldn’t send my Hurthle cell aspirate patients for Afirma, because I knew it was going to come back suspicious. I think I will start to do it now, but we need to see what the answers look like” with additional validation.
Afirma GSC with medullary thyroid cancer classifier
In a third study, investigators developed and validated a classifier for medullary thyroid cancer to be used with the Afirma GSC. They were led by Gregory Randolph, MD, professor of otolaryngology and the Claire and John Bertucci Endowed Chair in Thyroid Surgical Oncology at Harvard Medical School, and division chief of the general and thyroid/parathyroid endocrine surgical divisions at the Massachusetts Eye and Ear Infirmary, Boston.
Better preoperative identification of this cancer is key for several reasons, he maintained.
Establishing the diagnosis from needle biopsy is challenging, because some features overlap with those of other thyroid lesions, according to Dr. Randolph. In about a third of patients with medullary thyroid cancer brought to the operating room, the diagnosis is unknown at the time, and that often results in inadequate initial surgery.
The investigators developed a medullary thyroid cancer classifier cassette that assesses differential expression of 108 genes. They then performed blinded, independent validation in a cohort of 211 fine-needle aspiration samples from thyroid nodules: 21 medullary thyroid cancers and 190 other benign and malignant neoplasms.
Results showed that the Afirma GSC with the medullary thyroid cancer classifier had sensitivity of 100% and specificity of 100%, reported Dr. Randolph.
“The Afirma GSC medullary thyroid cancer testing cassette, within the larger GSC system, uses RNA sequencing and advanced machine learning to improve the diagnostic detection of medullary thyroid cancer, which currently misses approximately a third of medullary thyroid cancer patients,” he said.
Session attendees wondered which patients are appropriate candidates and how much the test will cost.
“We have to have a discussion about that, because the missed medullaries are, frankly, widely distributed – they can be in any of the Bethesda categories, basically,” Dr. Randolph said. “So, there are cytopathologic mistakes made uniformly, including in the suspicious and frankly malignant Bethesda categories. In terms of cost, this is embedded in the GSC classifier; so, if you order that test, you will obtain this medullary cassette.”
Actual sensitivity of the classifier may ultimately be less than 100% with use in larger samples, he acknowledged. “I think a greater number of validation tests is absolutely in order. I imagine this classifier may not be perfect, but it is way better than the third we miss with just cytopathology.”
Dr. Nikiforov disclosed that he is owner of an IP for ThyroSeq, and that his laboratory has a contract to offer the test commercially. Dr. Duh disclosed that he had no relevant conflicts of interest. Dr. Randolph disclosed that he had no relevant conflicts of interest.
VICTORIA, B.C. – Several new and improved molecular classifiers show good performance for preoperatively assessing the nature of thyroid nodules, including histologic subsets that continue to pose diagnostic challenges, according to a trio of studies reported at the annual meeting of the American Thyroid Association.
ThyroSeq v3 classifier
In a prospective, blinded, multi-institutional study, investigators validated the ThyroSeq v3 genomic classifier, which uses next-generation sequencing to test for mutations, fusions, gene expression alterations, and copy number variations in 112 genes.
The validation cohort consisted of 234 patients from 10 centers who had thyroid nodules with Bethesda III to V cytology and known surgical outcome, with central pathology review, and successful molecular testing. In total, they had 257 fine needle aspiration samples.
Of the 247 samples from nodules having Bethesda III or IV cytology – those of greatest interest – 28% were cancer or noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), reported senior author Yuri Nikiforov, MD, PhD, professor of pathology and director of the division of molecular & genomic pathology at the University of Pittsburgh Medical Center. “Both cancer and NIFTP are surgical diseases, so we felt they belong in one group,” he noted.
Among the Bethesda III or IV samples, ThyroSeq v3 had a sensitivity of 94%, a specificity of 82%, a positive predictive value of 66%, and a negative predictive value of 97%. Additional analyses showed that the test would still have a negative predictive value of 95% or better up to a cancer/NIFTP prevalence of 44%.
All five false-negative cases in the entire study cohort were intrathyroidal nodules of low stage and without aggressive histology.
Of the 33 false-positive cases, 68% were diagnosed on pathology as Hurthle cell or follicular adenomas, 10% were initially diagnosed by local pathologists as cancer or NIFTP, and 94% harbored clonal oncogenic molecular alterations.
“So, these are not actually hyperplasia; these are true tumors. Probably at least some of them would have the potential to progress,” said Dr. Nikiforov. “I believe that this so-called false-positive rate may not be really false positive. This is a rate of detection of precancerous tumors, not hyperplasia, that still may require surgical excision.”
In this study, “we found very high sensitivity and negative predictive value of ThyroSeq v3, with robust negative predictive value in populations with different disease prevalence,” he concluded. “Robust performance was achieved in many thyroid cancer types, including Hurthle cell cancer.”
All study patients underwent surgery, so it is not clear how the classifier would perform in the context of surveillance, he acknowledged. But the 97% negative predictive value gives confidence for patients having a negative result.
“Those patients very likely can be observed – not necessarily dismissed from medical surveillance, but observed – and could probably avoid surgery,” he said. “If patients have a positive test, it will depend on the type of mutation, because some of them confer a high risk and others confer low risk. So, there may be a spectrum of management based on combination of clinical parameters and molecular testing. But those are more likely to be surgical candidates.”
“This is a study that is desperately needed in this field,” session attendee Bryan McIver, MD, PhD, an endocrinologist and deputy physician-in-chief at the Moffitt Cancer Center in Tampa, said in an interview. “These are very challenging studies to do, because the marketing of these molecular tests has run ahead of a lot of the clinical studies.
“It’s very hard in the United States, at least, to find patients who are truly naive to molecular testing whom you can take to the operating room,” he explained. “And if you can’t take patients with a negative molecular test to the operating room, then you can’t actually calculate the true sensitivity and specificity of the test, and the whole evaluation of the test starts to become skewed.”
According to Dr. McIver, this study is noteworthy in that it largely fulfills four key criteria: There were no post hoc sample exclusions after unblinding of data, both pathology evaluation and decision to operate were blinded to classifier results, and patients were generally unselected, with little to no prior molecular testing.
“So, we actually have a proper high-quality validation study now available for this new test, the ThyroSeq v3,” he noted. “That sets the bar where it needed to be set a long time ago, and I can’t begin to tell you how excited I am to finally have a test that passed that bar. The fact that it shows a negative predictive value of 97% in this clinical study and a positive predictive value in the mid-60% range means that there is a potential for a clinical utility there that is backed by solid science. In this field, that’s almost unique.”
Afirma GSC with Hurthle classifiers
In a second study, investigators led by Quan-Yang Duh, MD, professor of surgery, division of general surgery, and chief, section of endocrine surgery, University of California, San Francisco, developed and validated a pair of classifiers to enhance performance of the Afirma platform among Hurthle cell specimens.
“The Hurthle cell lesions tend to give us trouble,” Dr. Duh said. On molecular analysis, those that are malignant seldom harbor mutations that would aid diagnosis, whereas those that are benign are usually classified as suspicious by the original Afirma Gene Expression Classifier (GEC).
“The specific group that is causing trouble are those that are Hurthle cell but not neoplasm, because they are the ones that give you the false positives,” Dr. Duh said. Therefore, it makes sense to stratify lesions on both of these factors, and then subject that specific subset to a more stringent threshold.
The investigators developed two classifiers that work with the Afirma core Genomic Sequencing Classifier (GSC), which uses RNA sequencing and machine learning algorithms.
The first classifier uses differential expression of 1,408 genes to determine whether a sample contains Hurthle cells. The second classifier, applied only to lesions containing Hurthle cells, uses differential expression of 2,041 genes and assesses loss of heterozygosity – which is prevalent in Hurthle cell neoplasms – to determine whether a Hurthle cell lesion is a neoplasm.
The ensemble model then makes a final classification, using a higher threshold for suspicious lesions determined to be Hurthle cell but not neoplasm, and a normal threshold for all the rest.
The investigators validated the Afirma GSC with the two classifiers in blinded fashion using 186 thyroid lesion samples having Bethesda III or IV cytology that had been part of the overall multicenter validation of the original Afirma GEC (N Engl J Med. 2012 Aug 23;367[8]:705-15).
Among the 26 Hurthle cell lesions, specificity for identifying benign lesions improved from 11.8% with the original Afirma GEC to 58.8% with the Afirma GSC and new classifiers. That was an absolute gain of 47% (P = .012), Dr. Duh reported. Sensitivity for identifying cancer was 88.9%.
There were also smaller absolute gains in specificity of 18% among all lesions in the cohort (P = .0028) and 14% among non-Hurthle lesions (P = .028).
“The new GSC test has significantly improved specificity in the patients with Bethesda III and IV specimens with Hurthle cells, and this may reduce unnecessary diagnostic surgery,” said Dr. Duh. “Basically, there are fewer false positives and more patients who can be called benign in the Hurthle cell group who would not need an operation.”
Further validation is needed, he acknowledged. “For a while, I wouldn’t send my Hurthle cell aspirate patients for Afirma, because I knew it was going to come back suspicious. I think I will start to do it now, but we need to see what the answers look like” with additional validation.
Afirma GSC with medullary thyroid cancer classifier
In a third study, investigators developed and validated a classifier for medullary thyroid cancer to be used with the Afirma GSC. They were led by Gregory Randolph, MD, professor of otolaryngology and the Claire and John Bertucci Endowed Chair in Thyroid Surgical Oncology at Harvard Medical School, and division chief of the general and thyroid/parathyroid endocrine surgical divisions at the Massachusetts Eye and Ear Infirmary, Boston.
Better preoperative identification of this cancer is key for several reasons, he maintained.
Establishing the diagnosis from needle biopsy is challenging, because some features overlap with those of other thyroid lesions, according to Dr. Randolph. In about a third of patients with medullary thyroid cancer brought to the operating room, the diagnosis is unknown at the time, and that often results in inadequate initial surgery.
The investigators developed a medullary thyroid cancer classifier cassette that assesses differential expression of 108 genes. They then performed blinded, independent validation in a cohort of 211 fine-needle aspiration samples from thyroid nodules: 21 medullary thyroid cancers and 190 other benign and malignant neoplasms.
Results showed that the Afirma GSC with the medullary thyroid cancer classifier had sensitivity of 100% and specificity of 100%, reported Dr. Randolph.
“The Afirma GSC medullary thyroid cancer testing cassette, within the larger GSC system, uses RNA sequencing and advanced machine learning to improve the diagnostic detection of medullary thyroid cancer, which currently misses approximately a third of medullary thyroid cancer patients,” he said.
Session attendees wondered which patients are appropriate candidates and how much the test will cost.
“We have to have a discussion about that, because the missed medullaries are, frankly, widely distributed – they can be in any of the Bethesda categories, basically,” Dr. Randolph said. “So, there are cytopathologic mistakes made uniformly, including in the suspicious and frankly malignant Bethesda categories. In terms of cost, this is embedded in the GSC classifier; so, if you order that test, you will obtain this medullary cassette.”
Actual sensitivity of the classifier may ultimately be less than 100% with use in larger samples, he acknowledged. “I think a greater number of validation tests is absolutely in order. I imagine this classifier may not be perfect, but it is way better than the third we miss with just cytopathology.”
Dr. Nikiforov disclosed that he is owner of an IP for ThyroSeq, and that his laboratory has a contract to offer the test commercially. Dr. Duh disclosed that he had no relevant conflicts of interest. Dr. Randolph disclosed that he had no relevant conflicts of interest.
AT ATA 2017
Key clinical point:
Major finding: ThyroSeq v3 had a negative predictive value of 97%. Specificity was an absolute 47% greater for Afirma GSC with Hurthle-specific classifiers than for Afirma GEC. The Afirma GSC with a medullary thyroid cancer classifier had 100% sensitivity and specificity.
Data source: Validation studies of the ThyroSeq v3 classifier (257 samples), the Afirma GSC with Hurthle-specific classifiers (186 samples), and the Afirma GSC with a medullary thyroid cancer classifier (211 samples).
Disclosures: Dr. Nikiforov disclosed that he is owner of an IP for ThyroSeq, and that his laboratory has a contract to offer the test commercially. Dr. Duh disclosed that he had no relevant conflicts of interest. Dr. Randolph disclosed that he had no relevant conflicts of interest.