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A gene expression profile test to resolve head & neck squamous versus lung squamous cancers

机译:基因表达谱测试可解决头颈部鳞癌和肺鳞癌

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Background The differential diagnosis between metastatic head & neck squamous cell carcinomas (HNSCC) and lung squamous cell carcinomas (lung SCC) is often unresolved because the histologic appearance of these two tumor types is similar. We have developed and validated a gene expression profile test (GEP-HN-LS) that distinguishes HNSCC and lung SCC in formalin-fixed, paraffin-embedded (FFPE) specimens using a 2160–gene classification model. Methods The test was validated in a blinded study using a pre-specified algorithm and microarray data files for 76 metastatic or poorly-differentiated primary tumors with a known HNSCC or lung SCC diagnosis. Results The study met the primary Bayesian statistical endpoint for acceptance. Measures of test performance include overall agreement with the known diagnosis of 82.9% (95% CI, 72.5% to 90.6%), an area under the ROC curve (AUC) of 0.91 and a diagnostics odds ratio (DOR) of 23.6. HNSCC (N?=?38) gave an agreement with the known diagnosis of 81.6% and lung SCC (N?=?38) gave an agreement of 84.2%. Reproducibility in test results between three laboratories had a concordance of 91.7%. Conclusion GEP-HN-LS can aid in resolving the important differential diagnosis between HNSCC and lung SCC tumors. Virtual Slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1753227817890930 webcite
机译:背景技术转移性头颈部鳞状细胞癌(HNSCC)与肺鳞状细胞癌(肺SCC)之间的鉴别诊断通常无法解决,因为这两种肿瘤类型的组织学外观相似。我们已经开发并验证了使用2160基因分类模型在福尔马林固定,石蜡包埋(FFPE)标本中区分HNSCC和肺SCC的基因表达谱测试(GEP-HN-LS)。方法使用一项预先指定的算法和微阵列数据文件,通过一项针对76例HNSCC或肺SCC诊断为已知的转移性或低分化原发性肿瘤的盲法研究,对该试验进行了验证。结果研究符合主要的贝叶斯统计终点。测试性能的衡量标准包括:总体诊断率为82.9%(95%CI,72.5%至90.6%),ROC曲线下面积(AUC)为0.91,诊断比值比(DOR)为23.6。 HNSCC(N≥38)的诊断率为81.6%,肺部SCC(N≥38)的诊断率为84.2%。三个实验室之间的测试结果可重复性达到91.7%。结论GEP-HN-LS有助于解决HNSCC与肺SCC肿瘤的重要鉴别诊断。虚拟幻灯片可以在这里找到本文的虚拟幻灯片:http://www.diagnosticpathology.diagnomx.eu/vs/1753227817890930 webcite

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