HealthLinx Limited, 576 Swan Street, Richmond, VIC 3121, Australia.
J Cancer Res Clin Oncol. 2010 Jul;136(7):1079-88. doi: 10.1007/s00432-009-0755-5. Epub 2010 Jan 16.
The primary hypothesis to be tested in this study was that the diagnostic performance (as assessed by the area under the receiver operator characteristic curve, AUC) of a multianalyte panel to correctly identify women with ovarian cancer was significantly greater than that for CA-125 alone.
A retrospective, case-control study (phase II biomarker trial) was conducted that involved 362 plasma samples obtained from women with ovarian cancer (n = 150) and healthy controls (n = 212). A multivariate classification model was developed that incorporated five biomarkers of ovarian cancer, CA-125; C-reactive protein (CRP); serum amyloid A (SAA); interleukin 6 (IL-6); and interleukin 8 (IL-8) from a modelling cohort (n = 179). The performance of the model was evaluated using an independent validation cohort (n = 183) and compared with of CA-125 alone.
The AUC for the biomarker panel was significantly greater than the AUC for CA-125 alone for a validation cohort (p < 0.01) and an early stage disease cohort (i.e. Stages I and II; p < 0.01). At a threshold of 0.3, the sensitivity and specificity of the multianalyte panel were 94.1 and 91.3%, respectively, for the validation cohort and 92.3 and 91.3%, respectively for an early stage disease cohort.
The use of a panel of plasma biomarkers for the identification of women with ovarian cancer delivers a significant increase in diagnostic performance when compared to the performance of CA-125 alone.
本研究旨在检验一个主要假设，即多指标分析面板在正确识别卵巢癌女性患者方面的诊断性能（通过接受者操作特征曲线下面积评估，AUC）显著优于 CA-125 单独使用。
本研究采用回顾性病例对照研究（二期生物标志物试验），共纳入 362 份来自卵巢癌患者（n=150）和健康对照者（n=212）的血浆样本。建立了一个多变量分类模型，该模型纳入了卵巢癌的五个生物标志物，即 CA-125、C 反应蛋白（CRP）、血清淀粉样蛋白 A（SAA）、白细胞介素 6（IL-6）和白细胞介素 8（IL-8），来自建模队列（n=179）。使用独立验证队列（n=183）评估模型的性能，并与 CA-125 单独使用进行比较。
对于验证队列（p<0.01）和早期疾病队列（即 I 期和 II 期；p<0.01），生物标志物面板的 AUC 显著大于 CA-125 单独的 AUC。在 0.3 的阈值下，多指标面板的敏感性和特异性分别为验证队列的 94.1%和 91.3%，早期疾病队列的分别为 92.3%和 91.3%。
与 CA-125 单独使用相比，使用血浆生物标志物面板来识别卵巢癌女性患者可显著提高诊断性能。
