Walts Ann E, Sacks Wendy L, Wu Howard H, Randolph Melissa L, Bose Shikha
Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, California.
Internal Medicine, Cedars-Sinai Medical Center, Los Angeles, California.
Diagn Cytopathol. 2018 Nov;46(11):901-907. doi: 10.1002/dc.23980. Epub 2018 Oct 23.
Molecular tests are increasingly used to triage cytologically indeterminate thyroid nodules for surgery and/or follow-up. We retrospectively compared the performance of the Afirma Gene Expression Classifier (AGEC) with that of the more recently developed RosettaGX Reveal™ miRNA Classifier (Reveal) in a cohort of Bethesda III-V thyroid FNAs with surgical follow-up.
Eighty-one samples (54 Bethesda III, 26 Bethesda IV, 1 Bethesda V) with available AGEC (74 AGEC-SUSP and 7 AGEC-BENIGN) and surgical pathology results were studied from three academic centers. Reveal was performed in a blinded fashion.
The final diagnoses were benign/NIFTP (n = 63) and malignant (n = 18). The overall "correct" rate was 64.2% for Reveal and 28.4% for AGEC (P = 1.4e-6). The specificity of Reveal was 60.3%, compared with 9.5% for AGEC (P = 2.1e-9). Among the 18 malignant cases, 77.8% and 94.4% were correctly classified as suspicious by Reveal and AGEC, respectively (P = 0.2). In the FLUS and the FN group, the specificity of AGEC was lower than the specificity of Reveal. Whether the 7 NIFTP in our study were considered benign or malignant, specificity and PPV of Reveal were higher than those of AGEC. Reveal also outperformed AGEC in correctly classifying the 26 benign Hürthle lesions studied (P = 7.6e-5).
Reveal outperformed AGEC in this cohort, whether NIFTP is considered benign or malignant, and in Hürthle lesions. Reveal has the potential to reduce the number of unnecessary resections in patients with indeterminate thyroid cytology. Based on our findings and the practical advantages offered by Reveal methodology, large prospective studies are warranted. Diagn. Cytopathol.
分子检测越来越多地用于对甲状腺细针穿刺活检(FNA)结果不确定的结节进行手术和/或随访的分类。我们回顾性比较了在一组接受手术随访的贝塞斯达III - V级甲状腺FNA病例中,Afirma基因表达分类器(AGEC)与最近开发的RosettaGX Reveal™ miRNA分类器(Reveal)的性能。
从三个学术中心研究了81份样本(54份贝塞斯达III级、26份贝塞斯达IV级、1份贝塞斯达V级),这些样本有可用的AGEC检测结果(74份AGEC - 可疑和7份AGEC - 良性)以及手术病理结果。Reveal检测以盲法进行。
最终诊断为良性/非侵袭性滤泡性甲状腺肿瘤(NIFTP,n = 63)和恶性(n = 18)。Reveal的总体“正确”率为64.2%,AGEC为28.4%(P = 1.4×10⁻⁶)。Reveal的特异性为60.3%,而AGEC为9.5%(P = 2.1×10⁻⁹)。在18例恶性病例中,Reveal和AGEC分别将77.8%和94.4%正确分类为可疑(P = 0.2)。在滤泡性病变可疑(FLUS)和滤泡性肿瘤(FN)组中,AGEC的特异性低于Reveal。无论我们研究中的7例NIFTP被视为良性还是恶性,Reveal的特异性和阳性预测值均高于AGEC。在正确分类所研究的26例良性许特莱细胞病变方面,Reveal也优于AGEC(P = 7.6×10⁻⁵)。
无论NIFTP被视为良性还是恶性,以及在许特莱细胞病变中,Reveal在该队列中的表现均优于AGEC。Reveal有可能减少甲状腺细胞学结果不确定患者不必要的切除手术数量。基于我们的研究结果以及Reveal方法所具有的实际优势,有必要开展大型前瞻性研究。诊断细胞病理学