Pub Date : 2017-05-01DOI: 10.17265/2328-224X/2017.0506.002
Dion Chen, Surbhi Jain, Ying-Hsu Su, Wei Song
Early detection of hepatocellular carcinoma (HCC) is critical for the effective treatment. Alpha fetoprotein (AFP) serum level is currently used for HCC screening, but the cutoff of the AFP test has limited sensitivity (~50%), indicating a high false negative rate. We have successfully demonstrated that cancer derived DNA biomarkers can be detected in urine of patients with cancer and can be used for the early detection of cancer (Jain et al., 2015; Lin et al., 2011; Song et al., 2012; Su, Lin, Song, & Jain, 2014; Su, Wang, Norton, Brenner, & Block, 2008). By combining urine biomarkers (uBMK) values and serum AFP (sAFP) level, a new classification model has been proposed for more efficient HCC screening. Several criterions have been discussed to optimal the cutoff for uBMK score and sAFP score. A joint distribution of sAFP and uBMK with point mass has been fitted using maximum likelihood method. Numerical results show that the sAFP data and uBMK data are very well described by proposed model. A tree-structured sequential test can be optimized by selecting the cutoffs. Bootstrap simulations also show the robust classification results with the optimal cutoff.
早期发现肝细胞癌是有效治疗的关键。血清甲胎蛋白(AFP)水平目前用于HCC筛查，但AFP检测的灵敏度有限(约50%)，表明假阴性率很高。我们已经成功证明，癌症衍生的DNA生物标志物可以在癌症患者的尿液中检测到，并可用于癌症的早期检测(Jain et al.， 2015;Lin et al.， 2011;Song et al.， 2012;苏、林、宋、Jain, 2014;苏、王、诺顿、布伦纳和布洛克，2008)。通过结合尿液生物标志物(uBMK)值和血清AFP (sAFP)水平，提出了一种更有效的HCC筛查的新分类模型。讨论了几种标准来优化ubbmk评分和sAFP评分的截止值。利用极大似然法拟合了带点质量的sAFP和uBMK的联合分布。数值结果表明，该模型能很好地描述sAFP数据和uBMK数据。通过选择截止点，可以优化树结构序列测试。Bootstrap仿真结果表明，该方法具有最优截止点，分类结果具有鲁棒性。
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