| Literature DB >> 29720964 |
Zeyad T Sahli1, Philip W Smith2, Christopher B Umbricht1, Martha A Zeiger2.
Abstract
The need for distinguishing benign from malignant thyroid nodules has led to the pursuit of differentiating molecular markers. The most common molecular tests in clinical use are Afirma® Gene Expression Classifier (GEC) and Thyroseq® V2. Despite the rapidly developing field of molecular markers, several limitations exist. These challenges include the recent introduction of the histopathological diagnosis "Non-Invasive Follicular Thyroid neoplasm with Papillary-like nuclear features", the correlation of genetic mutations within both benign and malignant pathologic diagnoses, the lack of follow-up of molecular marker negative nodules, and the cost-effectiveness of molecular markers. In this manuscript, we review the current published literature surrounding the diagnostic value of Afirma® GEC and Thyroseq® V2. Among Afirma® GEC studies, sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) ranged from 75 to 100%, 5 to 53%, 13 to 100%, and 20 to 100%, respectively. Among Thyroseq® V2 studies, Se, Sp, PPV, and NPV ranged from 40 to 100%, 56 to 93%, 13 to 90%, and 48 to 97%, respectively. We also discuss current challenges to Afirma® GEC and Thyroseq® V2 utility and clinical application, and preview the future directions of these rapidly developing technologies.Entities:
Keywords: Afirma; Thyroseq; molecular test; non-invasive follicular thyroid neoplasm with papillary-like nuclear features; thyroid cancer
Year: 2018 PMID: 29720964 PMCID: PMC5915469 DOI: 10.3389/fendo.2018.00179
Source DB: PubMed Journal: Front Endocrinol (Lausanne) ISSN: 1664-2392 Impact factor: 5.555
The Bethesda system for reporting thyroid cytopathology (10).
| Bethesda group | Diagnostic category | Abbreviation | Malignancy rate | |
|---|---|---|---|---|
| Before NIFTP reclassification (NIFTP malignant) | After NIFTP reclassification (NIFTP benign) | |||
| I | Non-diagnostic/unsatisfactory | – | 5–10% | No change |
| II | Benign | B | 0–3% | No change |
| III | Atypia of undetermined significance/follicular lesion of undetermined significance | AUS/FLUS | 10–30% | 6–18% |
| IV | Follicular neoplasm/suspicious for follicular neoplasm | FN/SFN | 25–40% | 10–40% |
| V | Suspicious for malignancy | SM | 50–75% | 45–60% |
| VI | Malignant | M | 97–99% | 94–96% |
Afirma Gene Expression Classifier (GEC) literature review.
| Author | Year | Study type | Follow-up period | Bethesda category | Sample size | GEC suspicious | Total surgery | Malignant nodules | NIFTP | Diagnostic value | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Se (%) | Sp (%) | PPV (%) | NPV (%) | ||||||||||
| Afirma® GEC ( | 2012 | Prospective, blinded multicenter | 301 days (Median) | Total | 265 | 165 | 265 | 85 | – | 92 | 52 | 47 | 93 |
| III | 129 | 74 | 129 | 31 | 90 | 53 | 38 | 95 | |||||
| IV | 81 | 49 | 81 | 20 | 90 | 49 | 37 | 94 | |||||
| V | 55 | 42 | 55 | 34 | 94 | 52 | 76 | 85 | |||||
| Hang et al. ( | 2017 | Retrospective, single institution | – | III | 133 | 112 | 133 | 27 | 21 | 100 | 24 | 42 | 100 |
| IV | 42 | 39 | 42 | 6 | 4 | 90 | 6 | 23 | 67 | ||||
| Harrison et al. ( | 2017 | Retrospective, single institution | – | III | 100 | – | 37 | 13 | – | – | – | 35 | – |
| IV | 10 | – | 4 | 1 | – | – | 25 | – | |||||
| Kay-Rivest et al. ( | 2017 | Retrospective, multicenter | – | III, IV | 172 | 83 | 77 | 38 | – | – | – | 49 | – |
| Samulski et al. ( | 2016 | Retrospective, single institution | Total | 294 | 133 | 128 | 33 | 11 | 93 | 17 | 39 | 81 | |
| – | III | 166 | 60 | 60 | 15 | 5 | 95 | 19 | 40 | 88 | |||
| IV | 122 | 73 | 68 | 18 | 6 | 92 | 15 | 39 | 75 | ||||
| Wu et al. ( | 2016 | Prospective, single institution | – | Total | 245 | 132 | 128 | 63 | – | 94 | 31 | 57 | 83 |
| III | 217 | 115 | 107 | 55 | 93 | 29 | 58 | 79 | |||||
| IV | 28 | 17 | 21 | 8 | 100 | 38 | 50 | 100 | |||||
| Yang et al. ( | 2016 | Retrospective, single institution | – | Total | 189 | 94 | 67 | 32 | – | 100 | 15 | 51 | 100 |
| III | 165 | 81 | 55 | 26 | 100 | 7 | 49 | 100 | |||||
| IV | 24 | 13 | 12 | 6 | 100 | 50 | 67 | 100 | |||||
| Chaudhary et al. ( | 2016 | Retrospective, single institution | – | Total | 158 | 85 | 73 | 28 | – | 100 | 15 | 100 | 20 |
| III | 89 | 41 | 45 | 8 | 100 | 18 | 20 | 100 | |||||
| IV | 69 | 44 | 41 | 21 | 100 | 11 | 55 | 100 | |||||
| Abeykoon et al. ( | 2016 | Retrospective, single institution | – | III, IV | 34 | 17 | 16 | 12 | – | – | – | 49 | – |
| Noureldine et al. ( | 2016 | Prospective, single institution | – | III, IV | 99 | 89 | 89 | 37 | – | 97 | 9 | 42 | 83 |
| Al-Qurayshi et al. ( | 2016 | Retrospective, single institution | – | Total | 154 | 96 | 112 | 50 | – | 78 | 40 | 51 | 69 |
| III | 114 | 66 | 84 | 36 | 78 | 52 | 55 | 76 | |||||
| IV | 40 | 30 | 28 | 14 | 79 | 0 | 44 | 0 | |||||
| Witt ( | 2016 | Retrospective, single institution | III, IV | 47 | 15 | 15 | 6 | – | – | – | 40 | – | |
| Wong et al. ( | 2016 | Retrospective, single institution | – | III, IV | 63 | 63 | 63 | 8 | 14 | – | – | 35 | – |
| Zhu et al. ( | 2015 | Retrospective, single institution | – | III, IV | 45 | 21 | 10 | 6 | – | – | – | 60 | – |
| Celik et al. ( | 2015 | Retrospective, single institution | Total | 40 | 23 | 20 | 10 | – | 100 | 20 | 56 | 100 | |
| – | III | 11 | 6 | 6 | 4 | 100 | 0 | 67 | Null | ||||
| IV | 29 | 17 | 14 | 6 | 100 | 25 | 50 | 100 | |||||
| Marti et al. ( | 2015 | Retrospective, multicenter | – | III: 103 | 165 | 104 | 70 | 27 | – | 100 | 16 | 43 | 100 |
| Brauner et al. ( | 2015 | Retrospective, multicenter | – | III, IV, and Hurthle Cell | 72 | 45 | 47 | 6 | – | 100 | 8 | 14 | 100 |
| McIver et al. ( | 2014 | Prospective, single institution | 9.5 months | Total | 72 | 44 | 36 | 6 | – | 83 | 10 | 16 | 75 |
| III | 9 | – | 5 | 1 | 100 | 0 | 20 | Null | |||||
| IV | 63 | – | 31 | 5 | 80 | 12 | 15 | 75 | |||||
| Lastra et al. ( | 2014 | Retrospective, single institution | – | Total | 132 | 62 | 50 | 22 | – | 100 | 7 | 54 | 100 |
| III | 68 | 23 | 18 | 11 | 100 | 0 | 61 | Null | |||||
| IV | 64 | 39 | 32 | 11 | 100 | 10 | 37 | 100 | |||||
| Aragon Han et al. ( | 2014 | Retrospective, single institution | – | III, IV | 37 | 36 | 37 | 16 | – | 100 | 5 | 44 | 100 |
| Alexander et al. ( | 2013 | Retrospective, multicenter | 8.5 months | Total | 339 | 148 | 132 | 54* | – | 98 | 13 | 44 | 91 |
| III | 165 | 66 | 48 | 23 | – | – | – | – | |||||
| IV | 79 | 73 | 65 | 24 | – | – | – | – | |||||
| V | 13 | 9 | 8 | 6 | – | – | – | – | |||||
| Harrell et al. ( | 2013 | Retrospective, single institution | Total | 58 | 36 | 35 | 18 | – | 94 | 24 | 57 | 80 | |
| – | III | – | 22 | – | – | 100 | 33 | 64 | 100 | ||||
| IV | – | 8 | – | – | 75 | 0 | 38 | 0 | |||||
Thyroseq V2 literature review.
| Author | Year | Study type | Follow-up period | Bethesda category | Sample size | Thyroseq suspicious | Total surgery | Malignant nodules | NIFT-P | Diagnostic value | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Se (%) | Sp (%) | PPV (%) | NPV (%) | ||||||||||
| ThyroSeq® v2 ( | 2015 | Retrospective, Single Institution | – | III | 465 | 31 | 95 | 22 | – | 91 | 92 | 77 | 97 |
| ThyroSeq® v2 ( | 2014 | Single Institution | – | IV | 143 | 42 | 143 | 39 | – | 90 | 93 | 83 | 96 |
| Taye et al. ( | 2017 | Prospective, Multicenter | – | III, IV | 156 | 51 | 63 | 10 | 3 | 91 | 45 | 27 | 96 |
| Valderrabano et al. ( | 2017 | Retrospective, Single Institution | – | Total | 190 | 45 | 102 | 15 | 5 | 70 | 77 | 42 | 91 |
| III | 104 | 22 | 52 | 5 | 2 | 43 | 71 | 19 | 89 | ||||
| IV | 86 | 23 | 50 | 10 | 3 | 85 | 84 | 65 | 94 | ||||
| Shrestha et al. ( | 2016 | Retrospective, Single Institution | – | Total | 39 | 23 | 39 | 14 | – | 93 | 60 | 57 | 94 |
| III | 27 | 15 | 27 | 9 | 89 | 61 | 53 | 92 | |||||
| IV | 12 | 8 | 12 | 5 | 100 | 57 | 63 | 100 | |||||
| Khatami et al. ( | 2016 | Retrospective, Single Institution | 3–6 months | III, IV, V | 42 | 7 | 7 | 4 | – | – | – | 57 | – |
| Toraldo et al. ( | 2016 | Prospective, Single Institution | – | III, IV | 148 | 51 | 45 | 20 | – | 95 | 60 | 66 | 94 |
| Shrestha et al. ( | 2016 | Retrospective, Single Institution | – | III | 41 | – | 41 | – | – | 83 | 62 | 90 | 48 |
| IV | 14 | – | 14 | – | – | 80 | 56 | 50 | 90 | ||||
Medullary thyroid cancer (MTC) classifier and diagnostic value.
| Author | Year | Study type | Follow-up period | Bethesda category | Sample size | MTC suspicious | Surgery | MTC prev. | Diagnostic value | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Se (%) | Sp (%) | PPV (%) | NPV (%) | |||||||||
| Pankratz ( | 2016 | Retrospective, single institution | – | – | 27 | 26 | 27 | 27 | 96 | – | – | – |
| Kloos ( | 2016 | Prospective, blinded multicenter | – | III–VI | 10,488 | 43 | 43 | 42 | – | – | 98 | – |
| Alexander et al. ( | 2012 | Prospective, blinded multicenter | 301 days (median) | III–VI | 441 | 4 | 441 | 4 | 100 | 100 | 100 | 100 |
| Training set ( | 2010 | Prospective, blinded multicenter | – | – | 220 | 22 | 220 | 20 | 91 | 100 | 100 | 99 |
| Chudova et al. ( | 2010 | Prospective, blinded multicenter | – | I–VI | 48 | 0 | 48 | 0 | – | 100 | – | 99 |
Molecular marker cost.
| Afirma | ThyroSeq V2 | |
|---|---|---|
| Cost | $4,875 (Afirma® GEC & MTC) | $3,200 |
| $975 (Afirma® MTC) | ||
| $475 (Afirma® BRAF) | ||
| Patient insurance coverage | $300 (Afirma® GEC & MTC) | $300 |
| $80 (Afirma® MTC) | ||
| $50 (Afirma® BRAF) | ||
| Estimated cost-effectiveness | Standard of care $12,172 versus GEC $10,719 ( | Standard of care $11,505 versus Thyroseq® cost $7,683 ( |
| Standard of care $11,505 versus GEC $13,027 ( | ||