Lithwick-Yanai Gila, Dromi Nir, Shtabsky Alexander, Morgenstern Sara, Strenov Yulia, Feinmesser Meora, Kravtsov Vladimir, Leon Marino E, Hajdúch Marián, Ali Syed Z, VandenBussche Christopher J, Zhang Xinmin, Leider-Trejo Leonor, Zubkov Asia, Vorobyov Sergey, Kushnir Michal, Goren Yaron, Tabak Sarit, Kadosh Etti, Benjamin Hila, Schnitzer-Perlman Temima, Marmor Hagai, Motin Maria, Lebanony Danit, Kredo-Russo Sharon, Mitchell Heather, Noller Melissa, Smith Alexis, Dattner Olivia, Ashkenazi Karin, Sanden Mats, Berlin Kenneth A, Bar Dganit, Meiri Eti
Rosetta Genomics Ltd, Rehovot, Israel.
Pathology Institute, Tel-Aviv Sourasky Medical Center, Tel Aviv, Israel.
J Clin Pathol. 2017 Jun;70(6):500-507. doi: 10.1136/jclinpath-2016-204089. Epub 2016 Oct 26.
The distinction between benign and malignant thyroid nodules has important therapeutic implications. Our objective was to develop an assay that could classify indeterminate thyroid nodules as benign or suspicious, using routinely prepared fine needle aspirate (FNA) cytology smears.
A training set of 375 FNA smears was used to develop the microRNA-based assay, which was validated using a blinded, multicentre, retrospective cohort of 201 smears. Final diagnosis of the validation samples was determined based on corresponding surgical specimens, reviewed by the contributing institute pathologist and two independent pathologists. Validation samples were from adult patients (≥18 years) with nodule size >0.5 cm, and a final diagnosis confirmed by at least one of the two blinded, independent pathologists. The developed assay, RosettaGX Reveal, differentiates benign from malignant thyroid nodules, using quantitative RT-PCR.
Test performance on the 189 samples that passed quality control: negative predictive value: 91% (95% CI 84% to 96%); sensitivity: 85% (CI 74% to 93%); specificity: 72% (CI 63% to 79%). Performance for cases in which all three reviewing pathologists were in agreement regarding the final diagnosis (n=150): negative predictive value: 99% (CI 94% to 100%); sensitivity: 98% (CI 87% to 100%); specificity: 78% (CI 69% to 85%).
A novel assay utilising microRNA expression in cytology smears was developed. The assay distinguishes benign from malignant thyroid nodules using a single FNA stained smear, and does not require fresh tissue or special collection and shipment conditions. This assay offers a valuable tool for the preoperative classification of thyroid samples with indeterminate cytology.
区分甲状腺良性和恶性结节具有重要的治疗意义。我们的目标是开发一种检测方法,能够利用常规制备的细针穿刺抽吸(FNA)细胞学涂片,将不确定的甲状腺结节分类为良性或可疑。
使用375份FNA涂片的训练集来开发基于微小RNA的检测方法,并使用201份涂片的盲法、多中心、回顾性队列进行验证。验证样本的最终诊断基于相应的手术标本,由参与研究的机构病理学家和两名独立病理学家进行审查。验证样本来自年龄≥18岁、结节大小>0.5 cm的成年患者,且最终诊断经两名盲法独立病理学家中的至少一人确认。所开发的检测方法RosettaGX Reveal利用定量逆转录聚合酶链反应区分甲状腺良性和恶性结节。
对通过质量控制的189份样本的检测性能:阴性预测值:91%(95%置信区间84%至96%);敏感性:85%(置信区间74%至93%);特异性:72%(置信区间63%至79%)。对于所有三位审查病理学家对最终诊断意见一致的病例(n = 150):阴性预测值:99%(置信区间94%至100%);敏感性:98%(置信区间87%至100%);特异性:78%(置信区间69%至85%)。
开发了一种利用细胞学涂片中微小RNA表达的新型检测方法。该检测方法使用单个FNA染色涂片区分甲状腺良性和恶性结节,不需要新鲜组织或特殊的采集和运输条件。该检测方法为术前对细胞学不确定的甲状腺样本进行分类提供了一种有价值的工具。