Role of the GALAD and BALAD-2 Serologic Models in Diagnosis of Hepatocellular Carcinoma and Prediction of Survival in Patients
Role of the GALAD and BALAD-2 Serologic Models in Diagnosis of Hepatocellular Carcinoma and Prediction of Survival in Patients
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DOI：
10.1016/j.cgh.2015.12.042
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发表时间：
2016-06-01
影响因子：
12.6
通讯作者：
Johnson, Philip
中科院分区：
文献类型：
--
作者：
Berhane, Sarah;Toyoda, Hidenori;Johnson, Philip
背景与目的：GALAD和巴拉德-2分别是用于估计慢性肝病个体患者中存在肝细胞癌（HCC）的可能性和HCC患者生存期的统计模型。这两种模型都使用了客观指标，特别是血清标志物甲胎蛋白（AFP）、AFP-L3和脱-γ-羧基凝血酶原。我们的目的是验证这些模型在一个国际队列的HCC患者，并评估其临床performance.METHODS：我们收集的数据，癌症诊断和结果的6834例（2430与HCC和4404慢性肝病）从德国，日本和香港招募。我们还收集了229例其他肝胆道癌症（胆管癌或胰腺癌）患者和92名健康个体（对照组）的数据。作为参考，分析中包括原始英国队列（最初建立GALAD模型并验证巴拉德-2）。我们评估了肿瘤大小和病因对GALAD模型性能的影响，以及其正确区分HCC与其他肝胆癌的能力。我们评估了巴拉德-2在不同阶段的HCC患者中的表现。结果：在所有队列中，受试者工作特征曲线（AUROC）下的面积，量化GALAD区分HCC患者与慢性肝病患者的能力，大于0.90-与模型最初建立的系列相似（AUROC，0.97）。GALAD将HCC患者与其他肝胆癌患者区分开来，AUROC值为0.95;小单灶性HCC患者的AUROC值略低，范围为0.85至0.95。慢性病毒性肝炎的病因和治疗对该模型的性能没有影响。巴拉德-2分析分配与HCC患者到4个不同的预后组，整体和患者根据疾病stage.CONCLUSIONS分层时：我们验证了GALAD和巴拉德-2模型的性能，分别用于HCC的诊断和预测患者的生存率（基于血清标志物AFP，AFP-L3和脱-γ-羧基凝血酶原），在一个国际队列的近7000例患者。这些系统可用于HCC监测和确定患者预后。
BACKGROUND & AIMS: GALAD and BALAD-2 are statistical models for estimating the likelihood of the presence of hepatocellular carcinoma (HCC) in individual patients with chronic liver disease and the survival of patients with HCC, respectively. Both models use objective measures, particularly the serum markers a-fetoprotein (AFP), AFP-L3, and des-gamma-carboxyprothrombin. We aimed to validate these models in an international cohort of patients with HCC and assess their clinical performance.METHODS: We collected data on cancer diagnosis and outcomes of 6834 patients (2430 with HCC and 4404 with chronic liver disease) recruited from Germany, Japan, and Hong Kong. We also collected data from 229 patients with other hepatobiliary tract cancers (cholangiocarcinoma or pancreatic adenocarcinoma) and 92 healthy individuals (controls). For reference, the original UK cohort (on which the GALAD model initially was built and BALAD-2 was validated) was included in the analysis. We assessed the effects of tumor size and etiology on GALAD model performance, and its ability to correctly discriminate HCC from other hepatobiliary cancers. We assessed the performance of BALAD-2 in patients with different stages of HCC.RESULTS: In all cohorts, the area under the receiver operating characteristic curve (AUROC), quantifying the ability of GALAD to discriminate patients with HCC from patients with chronic liver disease, was greater than 0.90-similar to the series on which the model originally was built (AUROC, 0.97). GALAD discriminated patients with HCC from those with other hepatobiliary cancers with an AUROC value of 0.95; values were slightly lower for patients with small unifocal HCCs, ranging from 0.85 to 0.95. Etiology and treatment of chronic viral hepatitis had no effect on the performance of this model. BALAD-2 analysis assigned patients with HCC to 4 distinct prognostic groups-overall and when patients were stratified according to disease stage.CONCLUSIONS: We validated the performance of the GALAD and BALAD-2 models for the diagnosis of HCC and predicting patient survival, respectively (based on levels of the serum markers AFP, AFP-L3, and des-gamma-carboxyprothrombin), in an international cohort of almost 7000 patients. These systems might be used in HCC surveillance and determination of patient prognosis.