Departments of Surgery, University of Pittsburgh, 497 Scaife Hall, 3550 Terrace St., Pittsburgh, PA 15261, USA.
J Mol Diagn. 2009 Nov;11(6):576-82. doi: 10.2353/jmoldx.2009.090037. Epub 2009 Oct 1.
We have previously reported that a quantitative reverse transcription (QRT)-PCR assay accurately analyzes sentinel lymph nodes (SLNs) from breast cancer patients. The aim of this study was to assess a completely automated, cartridge-based version of the assay for accuracy, predictive value, and reproducibility. The triplex (two markers + control) QRT-PCR assay was incorporated into a single-use cartridge for point-of-care use on the GeneXpert system. Three academic centers participated equally. Twenty-nine positive lymph nodes and 30 negative lymph nodes were analyzed to establish classification rules. SLNs from 120 patients were subsequently analyzed by QRT-PCR and histology (including immunohistochemistry), and the predetermined decision rules were used to classify the SLNs; 112 SLN specimens produced an informative result by both QRT-PCR and histology. By histological analysis, 21 SLNs were positive and 91 SLNs were negative for metastasis. QRT-PCR characterization produced a classification with 100% sensitivity, 97.8% specificity, and 98.2% accuracy compared with histology (91.3% positive predictive value and 100% negative predictive value). Interlaboratory reproducibility analyses demonstrated that a 95% prediction interval for a new measurement (DeltaCt) ranged between 0.403 and 0.956. This fully automated QRT-PCR assay accurately characterizes breast cancer SLNs for the presence of metastasis. Furthermore, the assay is not dependent on subjective interpretation, is reproducible across three clinical environments, and is rapid enough to allow intraoperative decision making.
我们之前曾报道过,一种定量逆转录(QRT)-PCR 检测方法能够准确分析乳腺癌患者的前哨淋巴结(SLN)。本研究旨在评估该检测方法的完全自动化、基于试剂盒的版本在准确性、预测值和可重复性方面的性能。三重(两种标志物+对照)QRT-PCR 检测方法被整合到一个一次性使用的试剂盒中,以便在 GeneXpert 系统上进行即时护理使用。三个学术中心平等参与。分析了 29 个阳性淋巴结和 30 个阴性淋巴结,以建立分类规则。随后对 120 名患者的 SLN 进行了 QRT-PCR 和组织学(包括免疫组织化学)分析,并使用预定的决策规则对 SLN 进行分类;112 个 SLN 标本通过 QRT-PCR 和组织学都产生了有意义的结果。通过组织学分析,21 个 SLN 为转移阳性,91 个 SLN 为转移阴性。与组织学相比,QRT-PCR 特征分析产生了 100%的敏感性、97.8%的特异性和 98.2%的准确性(91.3%的阳性预测值和 100%的阴性预测值)。实验室间重现性分析表明,新测量值(DeltaCt)的 95%预测区间范围在 0.403 到 0.956 之间。这种完全自动化的 QRT-PCR 检测方法能够准确地描述乳腺癌 SLN 是否存在转移。此外,该检测方法不依赖于主观解释,在三个临床环境中具有可重复性,并且足够快速,可以在手术过程中做出决策。