EASL2012:INTEGRATING QUANTITIATIVE SERUM HBSAG LEVELS INTO RISK SCORES FOR PREDI

StephenW

INTEGRATING QUANTITIATIVE SERUM HBSAG LEVELS INTO RISK SCORES FOR PREDICTING HEPATOCELLULAR CARCINOMA IN CHRONIC HEPATITIS B PATIENTS
Speaker: Chien-Jen Chen
Author:
C.-J. Chen1,2*, M.-H. Lee1, H.-I. Yang3,4, J. Liu2, R. Batrla-Utermann5, C.-L. Jen1, U.H. Iloeje6, J. Su7, S.-N. Lu8, S.-L. You1, L.-Y. Wang9, REVEAL-HBV Study Group Affiliation: 1Genomics Research Center, Academia Sinica,
2Graduate Institute of Epidemiology, College of Public Health, National Taiwan University, Taipei,
3Graduate Institute of Clinical Medical Science, China Medical University,
4Molecular and Genomic Epidemiology Center, China Medical University Hospital, Taichung, Taiwan R.O.C.,
5Roche Diagnostics Ltd., Rotkreuz, Switzerland,
6Global Health Economics and Outcomes Research, Bristol-Myers Squibb Co.,
7Formally the Global Health Economics and Outcomes Research, Bristol-Myers Squibb Co., Princeton, NJ, USA,
8Department of Gastroenterology, Kaohsiung Chang-Gung Memorial Hospital, Kaohsiung, 9MacKay College of Medicine, Taipei, Taiwan R.O.C.. *[email protected]
Background and aims: This study aimed to integrate the quantitative serum HBsAg levels in the risk scores for the prediction of hepatocellular carcinoma (HCC) in chronic hepatitis B patients.
Methods: There were 3,411 participants seropositive for HBsAg and seronegative for anti-HCV enrolled in the study during 1991-1992. The HBV-related seromarkers including genotype and serum HBV DNA and HBsAg levels at study entry were tested. Newly developed HCC was ascertained by computerized linkage with the national cancer registration profiles from 1991 to December 31, 2008. Two-thirds participants (n=2,274) were randomly allocated for model derivation and the other one-third (n=1,137) for model validation. The Cox's proportional hazards models were utilized to estimate the regression coefficients of each predictor for HCC, and the coefficients were converted to an integer to derive the HCC risk score. Two models were developed: model 1 included age, gender, family HCC history, liver cirrhosis status, HBeAg serostatus, and serum levels of ALT and HBV DNA; model 2 included quantitative HBsAg additionally. The Kaplan-Meier method was used to estimate the cumulative HCC risk by scores of participants in validation set. The area under receiver operating curve (AUROC) of models and the net reclassification improvement with and without quantitative HBsAg were assessed and compared. Results: All predictors included in prediction models were significantly associated with HCC. The risk scores ranged 0-22 for model 1 and 0-24 for model 2. Increasing risk scores predicted a corresponding increase in HCC risk. The estimated 10-year predicted risk for HCC ranged 0.10%-100.0% and 0.03%-100.0% for model 2, respectively. Applying the risk score to participants in validation set, they were validly categorized into low-, medium-, and high-risk group of HCC (all p-values< 0.001). The AUROC did not increase significantly by adding the quantitative HBsAg level into the prediction model. However, there were 12.7% participants with newly developed HCC and 14.4% without developing HCC during follow-up were reclassified correctly, showing the net reclassification improvement of 27.1% (p<  0.001).
Conclusions: Integrating quantitative HBsAg levels into the risk prediction model can better classify chronic hepatitis B patients who will and will not develop HCC in 10-year follow-up.

StephenW

纳入风险评分预测慢性乙型肝炎患者肝癌的定性血清HBsAg水平
主讲人：陈建仁
作者：
C.-J. chen1，2 *，M.-H. lee1，H.-I. J. Liu2，河Batrla Utermann5，政隆，4，yang3 jen1，U.H. iloeje6，J. Su7，S.-N. lu8，S.-L. you1，L.-Y. wang9，揭示乙肝病毒研究组单位：1Genomics研究中心，中央研究院，
2Graduate，公共卫生学院流行病学研究所，国立台湾大学，台北，
3Graduate医学科学研究所，中国医科大学，
4Molecular和基因组流行病学中心，中国医药大学附设医院，台中，台湾的中华民国，
5Roche诊断有限公司，Rotkreuz，瑞士，
6Global卫生经济学和研究成果，施贵宝公司，
7Formally的全球卫生经济学和研究成果，施贵宝公司，美国新泽西州普林斯顿，
胃肠病学，高雄长庚纪念医院，高雄，医学院9MacKay，台北，台湾的中华民国8Department的。 * [email protected]
背景和目标：本研究旨在整合定量血清HBsAg水平在慢性乙型肝炎患者的肝细胞癌（HCC）的预测风险评分。
方法：共有3,411参加者为HBsAg和抗-HCV阴性阳性1991-1992年期间参加了学习。 HBV相关seromarkers包括基因型和血清HBV DNA和HBsAg进入研究水平进行了测试。新开发的肝癌是由电脑从1991年至2008年12月31日，国家癌症登记型材联动确定。三分之二的参与者（N = 2,274）被随机分配模型的推导和模型验证，另三分之一（N = 1,137）。考克斯的比例风险模型被用来估计每个预测肝癌的回归系数，系数转换为整数，得到肝癌风险评分。两个模型：模型1包括年龄，性别，家族肝癌史，肝硬化状态，HBeAg的血清状况，血清ALT和HBV DNA水平;模型2包括定量的HBsAg此外。采用Kaplan-Meier法估计在验证集的参与者分数累计肝癌的风险。根据受试者工作曲线（AUROC）模型和净改叙改善和不定量的HBsAg的面积进行了评估和比较。结果：在预测模型中包含的所有预测均显着与肝癌有关。模型1和模型2 0-24为风险评分为0-22。增加风险分数预测肝癌的风险也相应增加。估计10年的预测为肝癌的风险介于0.10％〜100.0％和0.03％-100.0％，分别为模型2。应用风险评分在验证集的参与者，他们有效地分为低，中，高风险的肝癌组（p值<0.001）。 AUROC均没有显着增加的预测模型加入定量HBsAg水平。然而，有12.7％的参与者在后续新开发的肝癌和14.4％，发展中国家肝癌被重新分类正确，显示27.1％的净改叙改善（P <0.001）。
结论：融入风险预测模型，定量HBsAg水平可以更好地分类，慢性乙型肝炎患者会并不会在10年的后续发展肝癌