Doylestown算法在肝细胞癌早期检测中的应用

StephenW

PLoS One. 2018 Aug 31;13(8):e0203149. doi: 10.1371/journal.pone.0203149. eCollection 2018.
Application of the Doylestown algorithm for the early detection of hepatocellular carcinoma.
Mehta AS1, Lau DT2, Wang M1, Islam A2, Nasir B2, Javaid A2, Poongkunran M2, Block TM3,4.
Author information

1
    Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, South Carolina, United States of America.
2
    Liver Research Center, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States of America.
3
    The Baruch Blumberg Institute, Doylestown, Pennsylvania, United States of America.
4
    The Hepatitis B Foundation, Doylestown, Pennsylvania, United States of America.

Abstract
BACKGROUND:

We previously developed a logistic regression algorithm that uses AFP, age, gender, ALK and ALT levels to improve the detection of hepatocellular carcinoma (HCC). In 3,158 patients from 5 independent sites, this algorithm, referred to as the "Doylestown" algorithm, increased the AUROC of AFP 4% to 12% and had equal benefit regardless of tumor size or the etiology of liver disease.
AIMS:

Analysis of the Doylestown algorithm using samples from individuals taken before their diagnosis of HCC.
METHODS:

Here, the algorithm was tested using samples at multiple time points from (a) patients with established chronic liver disease, without HCC (120 patients) and (b) 116 patients with HCC diagnosis (85 patients with early stage HCC and 31 patients with recurrent HCC), taken at the time of, and up to 12 months prior to cancer diagnosis.
RESULTS:

Among patients who developed HCC, comparing the Doylestown algorithm at a fixed cut-off to AFP at 20 ng/mL, the Doylestown algorithm increased the True Positive Rate (TPR) in identification of HCC from 36 to 50%, at a time point of 12 months prior to the conventional HCC detection. Similar results were obtained in those patients with recurrent HCC, where the Doylestown algorithm increased TPR in detection of HCC from 18% to 59%, at 12 months prior to detection of recurrence.
CONCLUSIONS:

This algorithm significantly improves the prediction of HCC by AFP alone and may have value in the early detection of HCC.

PMID:
    30169533
DOI:
    10.1371/journal.pone.0203149

StephenW

PLoS One。 2018年8月31日; 13（8）：e0203149。 doi：10.1371 / journal.pone.0203149。 eCollection 2018。
Doylestown算法在肝细胞癌早期检测中的应用。
Mehta AS1，Lau DT2，Wang M1，Islam A2，Nasir B2，Javaid A2，Poongkunran M2，Block TM3,4。
作者信息

1
    美国南卡罗来纳州查尔斯顿医学大学细胞与分子药理学与实验治疗学系。
2
    肝脏研究中心，贝斯以色列女执事医疗中心，哈佛医学院，波士顿，马萨诸塞州，美利坚合众国。
3
    Baruch Blumberg研究所，宾夕法尼亚州，Doylestown，美利坚合众国。
4
    美国宾夕法尼亚州多伊尔斯敦的乙肝基金会。

抽象
背景：

我们之前开发了一种逻辑回归算法，该算法使用AFP，年龄，性别，ALK和ALT水平来改善肝细胞癌（HCC）的检测。在来自5个独立站点的3,158名患者中，该算法（称为“Doylestown”算法）将AFP的AUROC增加4％至12％，并且无论肿瘤大小或肝病的病因如何都具有相同的益处。
目的：

使用来自在诊断HCC之前取得的个体的样品分析Doylestown算法。
方法：

在这里，使用多个时间点的样本测试算法：（a）患有慢性肝病的患者，无HCC（120例患者）和（b）116例HCC诊断患者（85例早期HCC患者和31例复发患者） HCC），在癌症诊断之前和之前12个月进行。
结果：

在开发HCC的患者中，将固定截止值的Doylestown算法与20 ng / mL的AFP进行比较，Doylestown算法将HCC鉴定中的真阳性率（TPR）从36％提高到50％，时间点为传统HCC检测前12个月。在复发性HCC患者中获得了类似的结果，其中Doylestown算法在检测到复发前12个月将HCC检测中的TPR从18％增加到59％。
结论：

该算法显着改善了单独AFP对HCC的预测，可能对HCC的早期检测有一定价值。

结论：
    30169533
DOI：
    10.1371 / journal.pone.0203149

StephenW

https://journals.plos.org/ploson ... ournal.pone.0203149