Department of Research and Development, Onkos Molecular Diagnostics, Ribeirão Preto/SP, Brazil.
Department of Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos/SP, Brazil.
Thyroid. 2018 Dec;28(12):1618-1626. doi: 10.1089/thy.2018.0254. Epub 2018 Nov 22.
Thyroid nodules can be identified in up to 68% of the population. Fine-needle aspiration (FNA) cytopathology classifies 20%-30% of nodules as indeterminate, and these are often referred for surgery due to the risk of malignancy. However, histological postsurgical reports indicate that up to 84% of cases are benign, highlighting a high rate of unnecessary surgeries. We sought to develop and validate a microRNA (miRNA)-based thyroid molecular classifier for precision endocrinology (mir-THYpe) with both high sensitivity and high specificity, to be performed on the FNA cytology smear slide with no additional FNA. The expression of 96 miRNA candidates from 39 benign/39 malignant thyroid samples, (indeterminate on FNA) was analyzed to develop and train the mir-THYpe algorithm. For validation, an independent set of 58 benign/37 malignant FNA smear slides (also classified as indeterminate) was used. In the training set, with a 10-fold cross-validation using only 11 miRNAs, the mir-THYpe test reached 89.7% sensitivity, 92.3% specificity, 90.0% negative predictive value and 92.1% positive predictive value. In the FNA smear slide validation set, the mir-THYpe test reached 94.6% sensitivity, 81.0% specificity, 95.9% negative predictive value, and 76.1% positive predictive value. Bayes' theorem shows that the mir-THYpe test performs satisfactorily in a wide range of cancer prevalences. The presented data and comparison with other commercially available tests suggest that the mir-THYpe test can be considered for use in clinical practice to support a more informed clinical decision for patients with indeterminate thyroid nodules and potentially reduce the rates of unnecessary thyroid surgeries.
甲状腺结节在人群中的检出率高达 68%。细针穿刺细胞学(FNA)将 20%-30%的结节归类为不确定,由于恶性肿瘤的风险,这些结节通常需要手术。然而,组织学术后报告表明,高达 84%的病例是良性的,这突显了不必要手术的高比率。我们旨在开发和验证一种基于 microRNA(miRNA)的甲状腺分子分类器 mir-THYpe,其具有高灵敏度和高特异性,可在 FNA 细胞学涂片上进行,无需额外的 FNA。我们分析了 39 个良性/39 个恶性甲状腺样本(FNA 不确定)中的 96 个 miRNA 候选物的表达,以开发和训练 mir-THYpe 算法。为了验证,我们使用了 58 个良性/37 个恶性 FNA 涂片(也归类为不确定)的独立样本集。在训练集中,仅使用 11 个 miRNA 进行 10 倍交叉验证,mir-THYpe 测试达到 89.7%的灵敏度、92.3%的特异性、90.0%的阴性预测值和 92.1%的阳性预测值。在 FNA 涂片验证集中,mir-THYpe 测试达到 94.6%的灵敏度、81.0%的特异性、95.9%的阴性预测值和 76.1%的阳性预测值。贝叶斯定理表明,mir-THYpe 测试在广泛的癌症患病率范围内表现良好。所提供的数据和与其他商业上可用的测试的比较表明,mir-THYpe 测试可以考虑用于临床实践,以支持对不确定甲状腺结节患者做出更明智的临床决策,并可能降低不必要的甲状腺手术率。