基线定量乙肝核心抗体滴度独强烈预示整个聚乙二醇干扰素

StephenW

                                                                                                                                                                                                                                                            Gut                                                                           2016;65:313-320                                                                                                doi:10.1136/gutjnl-2014-308546                                                                                                                                                
                        

• Hepatology
  

                        

• Original article
  

                        
Baseline quantitative hepatitis B core antibody titre alone strongly predicts HBeAg seroconversion across chronic hepatitis                              B patients treated with peginterferon or nucleos(t)ide analogues                                                         

• Rong Fan1,
• Jian Sun1,
• Quan Yuan2,
• Qing Xie3,
• Xuefan Bai4,
• Qin Ning5,
• Jun Cheng6,
• Yanyan Yu7,
• Junqi Niu8,
• Guangfeng Shi9,
• Hao Wang10,
• Deming Tan11,
• Mobin Wan12,
• Shijun Chen13,
• Min Xu14,
• Xinyue Chen15,
• Hong Tang16,
• Jifang Sheng17,
• Fengmin Lu18,
• Jidong Jia19,
• Hui Zhuang18,
• Ningshao Xia2,
• Jinlin Hou1,20
• Chronic Hepatitis B Study Consortium
  

                           
                                                                                       

•                                        1State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China
•                                        2State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, School of Public Health, Xiamen University, Xiamen, China
•                                        3Department of Infectious Diseases, Ruijin Hospital, Jiaotong University School of Medicine, Shanghai, China
•                                        4Department of Infectious Diseases, Tangdu Hospital, Xi'an, China
•                                        5Department and Institute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
•                                        6Beijing Ditan Hospital, Capital Medical University, Beijing, China
•                                        7Department of Infectious Diseases, First Hospital of Peking University, Beijing, China
•                                        8Department of Hepatology, First Hospital, Jilin University, Changchun, China
•                                        9Department of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China
•                                        10Hepatology Unit, Peking University People's Hospital, Beijing, China
•                                        11Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, China
•                                        12Department of Infectious Diseases, Changhai Hospital, Shanghai, China
•                                        13Ji'nan Infectious Diseases Hospital, Ji'nan, China
•                                        148th People's Hospital, Guangzhou, China
•                                        15Beijing Youan Hospital, Capital Medical University, Beijing, China
•                                        16Department of Infectious Diseases, West China Hospital, Chengdu, China
•                                        17Department of Infectious Diseases, Zhejiang University 1st Affiliated Hospital, Hangzhou, China
•                                        18Department of Microbiology, Health science Center, Peking University, Beijing, China
•                                        19Liver Research Center, Beijing Friendship Hospital, Capital Medical University, Beijing, China
•                                        20Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University, Hangzhou, China
  

                              

• Correspondence to Professor Jinlin Hou, Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China; jlhousmu{at}163.com and Professor Ningshao Xia, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, School of Public Health, Xiamen University, Xiamen, 361105, China; nsxia{at}xmu.edu.cn
  

                              

• Received 8 October 2014
• Revised 5 December 2014
• Accepted 23 December 2014
• Published Online First 13 January 2015
  

                           
                                                         Abstract                                                               

Objective The investigation regarding the clinical significance of quantitative hepatitis B core antibody (anti-HBc) during chronic        hepatitis B (CHB) treatment is limited. The aim of this study was to determine the performance of anti-HBc as a pr for hepatitis B e antigen (HBeAg) seroconversion in HBeAg-positive CHB patients treated with peginterferon (Peg-IFN) or nuc analogues (NUCs), respectively.                                 

                              
                                                               

Design This was a retrospective cohort study consisting of 231 and 560 patients enrolled in two phase IV, multicentre, randomised,   espectively. Quantitative anti-HBc evaluation was conducted for all the available samples in the two trials by using a newly developed double-sandwich anti-HBc immunoassay.                                 

                              
                                                               

Results At the end of trials, 99 (42.9%) and 137 (24.5%) patients achieved HBeAg seroconversion in the Peg-IFN and NUC cohorts, respectively. We defined 4.4 log10 IU/mL, with a maximum sum of sensitivity and specificity, as the optimal cut-off value of baseline anti-HBc level to predict  HBeAg seroconversion for both Peg-IFN and NUC. Patients with baseline anti-HBc ≥4.4 log10 IU/mL and baseline HBV DNA <9 log10 copies/mL had 65.8% (50/76) and 37.1% (52/140) rates of HBeAg seroconversion in the Peg-IFN and NUC cohorts, respectively. In pooled analysis, other than treatment strategy, the baseline anti-HBc level was the best independent predictor for HBeAg  seroconversion (OR 2.178; 95% CI 1.577 to 3.009; p<0.001).                                 

                              
                                                               

Conclusions Baseline anti-HBc titre is a useful predictor of Peg-IFN and NUC therapy efficacy in HBeAg-positive CHB patients, which could be used for optimising the antiviral therapy of CHB.                                 

                              
                           

StephenW

肠道2016年; 65：313-320 DOI：10.1136 / gutjnl-2014-308546

    肝病

    原创文章

基线定量乙肝核心抗体滴度独强烈预示整个聚乙二醇干扰素或核苷（酸）类似物治疗慢性乙型肝炎患者HBeAg血清转换
开放存取

    荣风扇1，建SUN1，泉Yuan2，清Xie3，金学范Bai4，秦Ning5，君Cheng6，岩岩Yu7，军棋Niu8，广丰Shi9，郝Wang10，戴明Tan11，漠滨Wan12，使君Chen13，闵Xu14，欣悦Chen15，香港Tang16 ，吉方Sheng17，丰民Lu18，冀东Jia19，惠Zhuang18，宁绍Xia2，吉林Hou1,20慢性乙型肝炎研究联盟

    脏器功能衰竭研究国家重点实验室，病毒性肝炎研究的广东省重点实验室，感染科和肝病股，南方医科大学南方医院，南方医科大学，广州，中国
    分子疫苗学和分子诊断，诊断研究所和疫苗开发的传染病，公共卫生学院，厦门大学，厦门，中国国家重点实验室
    3Department传染病，瑞金医院，交通大学医学院，上海，中国的
    4Department传染病，唐都医院，西安，中国
    5Department传染病，同济医院，同济医学院，华中科技大学，武汉，中国研究所
    6Beijing地坛医院，首都医科大学，北京，中国
    7Department传染病，北京大学第一医院，北京，中国
    肝病，第一医院，吉林大学，长春，中国的8Department
    9Department传染病，华山医院，复旦大学，上海，中国
    10Hepatology单位，北京大学人民医院，北京，中国
    11Department传染病，湘雅医院，中南大学，长沙，中国
    12Department传染病，长海医院，上海，中国
    13Ji'nan传染病医院，济南，中国
    148人民医院，广州，中国
    15Beijing佑安医院，首都医科大学，北京，中国
    16Department传染病，中国西部医院，成都，中国
    17Department传染病，浙江大学附属第一医院，杭州，中国
    微生物学，健康科学中心，北京大学，北京，中国的18Department
    19Liver研究中心，北京友谊医院，首都医科大学，北京，中国
    20Co​​llaborative创新中心的诊断和传染病的治疗，浙江大学，杭州，中国

    通讯作者侯锦鳞教授，肝病单位，南方医科大学南方医院，南方医科大学，广州，510515，中国; jlhousmu {}处和163.com宁绍夏教授，诊断研究所和疫苗开发的传染病，公共卫生，厦门大学，厦门361105，中国; nsxia {}在xmu.edu.cn

    收到的2014年8月
    修订5 2014年12月
    接受23 2014年12月
    网上公布的第13位2015年一月

抽象

目的关于定量乙肝核心抗体（抗-HBc）慢性乙型肝炎在临床意义调查（CHB）治疗是有限的。这项研究的目的是确定抗-HBc的性能，乙肝e抗原（HBeAg）血清学转换的HBeAg阳性与聚乙二醇干扰素（PEG-IFN）或核苷（酸）类似物治疗的慢性乙肝患者的预测（NUCs） ， 分别。

设计这是一项回顾性队列研究，包括231和560例患者两个第四阶段，多中心，随机，对照与聚乙二醇干扰素或治疗试验NUC为基础的治疗长达2年，分别。在两个试验所有可用的样品通过采用新开发的双夹心抗-HBc免疫定量抗-HBc评价进行。

结果在试验结束时，99（42.9％）和137（24.5％）患者在聚乙二醇干扰素和NUC同伙，分​​别达到HBeAg血清转换。我们定义4.4日志10 IU /毫升，与敏感性和特异性的最大总和，作为基线抗-HBc级的最佳截止值来预测血清转换为聚乙二醇干扰素和NUC。患者基线抗-HBc≥4.4日志10 IU / mL和基线HBV DNA <9 log10拷贝/ mL的65.8％（50/76）和37.1％（52/140），HBeAg血清转换在聚乙二醇干扰素和NUC同伙率， 分别。在汇总分析，比治疗策略等，基线抗-HBc水平是最好的独立预测HBeAg血清学转换（OR 2.178; 95％CI为1.577至3.009，P <0.001）。

结论基线抗HBc滴度是PEG-IFN和NUC治疗功效的HBeAg阳性CHB患者一个有用的预测，其可用于优化CHB的抗病毒治疗。

StephenW

Discussion

To our knowledge, this is the first comprehensive and definitive analysis to assess the performance of quantitative anti-HBc level, a novel immunological biomarker, in patients with CHB treated with anti-HBV agents. The robust results of these analyses are supported by the large, well-controlled cohorts comprised of patients treated with Peg-IFN- or NUC-based therapy and the relatively complete data collection. Our results demonstrated that a baseline anti-HBc level ≥4.4 log10 IU/mL is associated with higher rates of HBeAg seroconversion in CHB patients treated with both Peg-IFN and NUC.

Currently, a variety of parameters have been identified for the prediction of antiviral treatment efficacy in patients CHB. HBV DNA and ALT levels have been widely accepted as the traditional universal biomarkers in both IFN and NUC treated patients. However, many other predictors are only applicable for one kind of treatment strategy. For example, quantitative HBsAg is mainly applied in predicting efficacy of Peg-IFN, and its value in predicting efficacy of NUC is controversial;13 the genetic predictors (eg, interleukin (IL)-28 polymorphisms) were also predominantly investigated among patients treated with Peg-IFN.21 In this study, we demonstrated the general applicability of quantitative baseline anti-HBc level in predicting the efficacy of antiviral treatment with Peg-IFN or NUC. Furthermore, we also defined a unified optimal cut-off value of 4.4 log10 IU/mL with a maximum sum of sensitivity and specificity for both Peg-IFN and NUC treatment, which will be convenient for its application in real-life clinical practice.

In order to compare the baseline quantitative anti-HBc with other known baseline predictors, we conducted a multivariate regression analysis in Peg-IFN treated patients, NUC treated patients and overall population, respectively. The results indicated that baseline anti-HBc level could predict HBeAg seroconversion independently with the highest OR value among kinds of baseline parameters both in the Peg-IFN and NUC cohorts. Interestingly, after pooling the two cohorts together, other than treatment strategy, the baseline anti-HBc level was also the independent predictor with the highest OR value (2.178). In addition, baseline HBV DNA and ALT levels were also independently related to the treatment outcome as expected, which confirmed previous studies in patients with CHB and clearly indicated that our study cohort has limited issue of bias. Accordingly, we identified a subgroup of patients with baseline anti-HBc ≥4.4 log10 IU/mL and baseline HBV DNA <9 log10 copies/mL, which could achieve 65.8% and 37.1% of HBeAg seroconversion in the Peg-IFN and NUC cohorts, respectively, whereas the rates of HBeAg seroconversion among patients with unfavourable baseline characteristics were only 25.4% and 14.5% in the Peg-IFN and NUC cohorts, respectively.

Although baseline anti-HBc level as well as baseline HBV DNA and ALT levels proved to be independently associated with HBeAg seroconversion in the current study, the AUROC values of them were all less than 0.65 (see online supplementary figure S2), indicating that the overall predictability of them were not satisfactory. Moreover, previous studies had demonstrated that early on-treatment response was associated with the efficacy of antiviral treatment. Zeuzem et al15 proved that non-detectable serum HBV DNA at week 24 was the strongest predictor for better outcomes in a cohort treated with telbivudine. Liaw et al demonstrated that patients with HBsAg <1500 IU/mL at week 24 could achieve the highest rate of HBeAg seroconversion in a cohort treated with Peg-IFNα-2a.13 Thus, we further evaluated the treatment efficacy among subgroups of patients stratified by parameters at baseline and week 24. The results showed that among patients with baseline anti-HBc ≥4.4 log10 IU/mL and baseline HBV DNA <9 log10 copies/mL, the rate of HBeAg seroconversion had almost no change after taking into account the on-treatment response (ie, 24-week HBsAg <1500 IU/mL) in the Peg-IFN cohort (65.8% vs 65.5%); and increased from 37.1% to 48.6% after combining the on-treatment response (ie, 24-week HBV DNA <300 copies/mL) in the NUC cohort. The above results indicated that baseline parameters combined with on-treatment response could further improve the predictive value to some extent in the NUC cohort, but not in the Peg-IFN cohort. Accordingly, we concluded that the evaluation of baseline parameters was important during antiviral treatment, especially during Peg-IFN treatment because baseline parameters have been shown to be strongly related to the treatment efficacy, and they could allow physicians to optimise treatment before initiating antiviral treatment.

Until now, the investigation on the predictive value of anti-HBc in antiviral treatment is limited. Yuan et al17 had retrospectively investigated the usefulness of the baseline anti-HBc level in predicting post-treatment response in two cohorts of small sample sizes (NUC cohort, n=49; Peg-IFN cohort, n=48); the results also suggested that the baseline anti-HBc level may be an additional predictor for post-treatment response both in IFN and NUC, although cut-off values applied for IFN and NUC are different from the current study, which is possibly related to the sample size and different population studied.

The mechanism underlying the predictive value of anti-HBc titre is still unknown. Many studies have shown that cellular immune response against HBV virus is important in controlling the infection with this virus. Specifically, CD4 and CD8 T cell responses have been shown to play a central role in the outcome of HBV infection. Also, Oliviero et al22 examined the role of B cells in chronic HBV infection by assessing B cell phenotype and function. They concluded that B lymphocytes played a crucial role in mediating immune response against HBV in CHB patient. Anti-HBc IgM and IgG were produced by HBcAg-specific B lymphocytes. Besides the ability of B cells in producing neutralising antibodies against HBV, they could produce several cytokines, like IFNγ or IL-6, to inhibit viral replication in hepatocytes and modulate the activity of CD4 and CD8T cells responses. In addition, Zgair et al23 demonstrated that anti-HBc had an important role in the severity of CHB through inhibition or clearance of HBV through the hepatocytotoxic effect of anti-HBc-secreting B cells. Therefore, the high level of anti-HBc at baseline may reflect the higher adaptive immune status of the patients which correlated with a better outcome after antiviral therapy.

The study also indicated that the patients treated with NUC showed significantly greater decline in anti-HBc levels than those treated with Peg-IFN. As we all know, the antiviral mechanisms of Peg-IFN and NUC are different. The former suppresses HBV replication by enhancing host immune system to mount a defence against HBV; the latter works mainly by inhibiting HBV DNA synthesis and interfering with the reverse-transcriptase activity of HBV. Therefore, Peg-IFN treatment could induce greater host immune activation compared with NUC treatment, which could support the slower decline of anti-HBc titre in the Peg-IFN cohort. Another explanation for this phenomenon was that NUC or Peg-IFN therapy might have a different impact on the frequency or counting of anti-HBc-secreting B cells. However, this hypothesis needs be verified by examining the dynamic change of B cell phenotypes within these cohorts in the future.

There are several implications concerning the clinical application of anti-HBc titre in the optimisation of antiviral treatment for CHB patients. This biomarker should be applicable to all NUC therapy because previous studies had demonstrated comparable effect of current available NUC treatment for CHB on HBeAg seroconversion; in addition, various NUCs have similar mechanism in suppressing HBV replication.7–11 Furthermore, we defined a uniform cut-off value of baseline anti-HBc for IFN and NUC treatment, which would be convenient for its application in clinical practice. Because baseline anti-HBc level had the highest OR value by using the cut-off value, anti-HBc should be tested as one of the valuable baseline predictors before initiating antiviral treatment in the clinical practice in order to optimise the antiviral treatment.

Our study has the strength of two well-controlled cohorts and large sample size, which increased the statistical power and reliability of the results. Nonetheless, our study also has a few limitations. First, the treatment outcome evaluated in our study was HBeAg seroconversion, which is the surrogate endpoint. However, we believe that achieving serological response is also an important goal of anti-HBV treatment, especially for young patients in the Asia-Pacific region.1 Second, patients in the NUC cohort were treated with telbivudine with/without adefovir, which are no longer the first-line antiviral drug for CHB; however, we propose that anti-HBc titre could also be applied in other NUCs due to their similar mechanism of action and comparable effects on HBeAg seroconversion. Third, we only evaluated the predictive value of anti-HBc in two cohorts, but did not yet examine it in another independent cohort, which will undermine the credibility of the results to some extent. Fourth, the double-sandwich anti-HBc assay used in the study has not been widely validated and been commercialised, which will influence the application of anti-HBc in clinical practice, although this new assay had been validated by WHO anti-HBc standards.

In conclusion, baseline anti-HBc titre is a reliable predictor of Peg-IFN and NUC therapy efficacy in HBeAg-positive CHB patients, which might be used for pretreatment stratification aimed at optimising the treatment of CHB.
Acknowledgments

We thank the study investigators, coordinators, nurses, patients and their families for their contributions. We also wish to thank Professor Chunquan Ou from Department of Biostatistics, Southern Medical University, for her helpful assistance on the statistical analysis.

StephenW

讨论

据我们所知，这是第一个全面和彻底的分析，以评估定量抗-HBc级的性能，一种新型的免疫生物标志物，在慢性乙型肝炎患者具有抗HBV剂处理。这些分析的强大的结果由包括用PEG-IFN-α或NUC为基础的治疗和相对完整的数据收集治疗的患者大，控制良好的同伙支持。我们的研究结果表明，基线抗-HBc水平≥4.4日志10 IU / mL的与HBeAg血清学转换的慢性乙型肝炎患者更高的速率与两个聚乙二醇干扰素和NUC治疗有关。

目前，各种参数已经确定为抗病毒治疗有效性的患者CHB预测。 HBV DNA和ALT水平已被广泛接受为在这两个IFN和NUC传统的通用生物标记物治疗的患者。然而，许多其他预测只适用于一种治疗策略。例如，定量的HBsAg主要应用于预测聚乙二醇干扰素的疗效，其在预测的NUC的效力值是有争议的; 13的遗传预测（例如，白细胞介素（IL）-28多态性）也主要调查了与治疗的患者钉IFN.21在这项研究中，我们证实了定量基线抗-HBc水平的普遍适用性在预测与聚乙二醇干扰素或NUC抗病毒治疗的功效。此外，我们也确定为4.4日志10国际单位/毫升的统一最佳截止值的灵敏度和特异性的最大总和的PEG-IFN和NUC治疗，这将是方便其在现实生活中的临床实践中的应用。

为了基线定量抗-HBc与其它已知基线预测比较，我们进行了在聚乙二醇干扰素一个多变量回归分析治疗的患者，NUC分别治疗的患者和整体人口。结果表明，基线抗-HBc水平可与中种无论是在聚乙二醇干扰素和NUC同伙基线参数最高OR值为独立预测HBeAg血清学转换。有趣的是，汇集了两个组在一起后，比治疗策略等，基线抗-HBc水平也是独立预测因子最高的OR值（2.178）。此外，基线HBV DNA和ALT水平也独立相关的治疗结果如预期，这证实了以前的研究CHB患者和清楚地表明，我们的研究队列已经限制问题的偏见。因此，我们确定的亚组患者基线抗-HBc≥4.4日志10 IU / mL和基线HBV DNA <9 log10拷贝/毫升，这可能会在PEG-IFN和NUC同伙达到65.8％和HBeAg血清学转换的37.1％，分别，而血清转换的患者中不利的基线特征率分别为25.4％和聚乙二醇干扰素和NUC同伙14.5％。

虽然基线抗-HBc级以及基线HBV DNA和ALT水平被证明是独立地与血清转换在目前的研究相关，它们的AUROC值比0.65所有更少（参见在线补充图S2）中，表示该整体他们中的可预测性并不令人满意。此外，先前的研究已经表明，早期治疗反应是与抗病毒治疗的功效关联。 Zeuzem等[15]实践证明，非检测血清HBV DNA在24周是最强的预测因子在替比夫定治疗的人群更好的结果。廖等人证实，患者的HBsAg <1500 IU / mL的24周时能达到与Peg-IFNα-2a.13这样处理队列率最高的HBeAg血清学转换，我们进一步评估患者亚组通过分层之间的疗效在基线和第24周的参数，结果显示，在患者的基线抗HBc≥4.4日志10 IU / mL和基线的HBV DNA <9 log10拷贝/毫升，血清转换率几乎没有变化考虑到后 - 处理响应（即24周的HBsAg <1500 IU / mL）中的聚乙二醇干扰素人群（65.8％比65.5％）;并结合在NUC队列上的治疗反应（即，24周的HBV DNA <300拷贝/ mL）后增加，从37.1％至48.6％。上述结果表明，基线参数结合上治疗反应可以进一步改善预测值在NUC队列一定程度，但不能在聚乙二醇干扰素队列。因此，我们的结论是，基线参数评价为在抗病毒治疗的重要，尤其是在聚乙二醇干扰素治疗，因为基线参数已经证明是密切相关的治疗功效，并且它们可以允许医师启动抗病毒治疗之前优化治疗。

到现在为止，在抗-HBc的抗病毒治疗的预测值调查是有限的。元等[17]曾回顾性调查中预测的小样本量两个组治疗后的反应基线抗-HBc水平的效用（NUC队列中，n = 49; PEG-IFN队列中，n = 48）;该结果还表明，在基线抗-HBc水平可以是两个在IFN和NUC后处理反应一个另外预测值，虽然适用于IFN和NUC截止值是从目前的研究，这是可能与不同的样本大小和不同人群的影响。

潜在的抗-HBc滴度的预测值的机制仍是未知数。许多研究表明，对HBV病毒的细胞免疫反应是在控制此病毒感染重要。具体而言，CD4和CD8 T细胞应答已被证明在HBV感染的结果发挥中心作用。另外，OLIVIERO等[22]通过评估B细胞表型和功能检查B细胞在慢性HBV感染的作用。他们的结论是B淋巴细胞介导的​​慢性乙型肝炎患者的抗HBV免疫反应中发挥了至关重要的作用。抗-HBc IgM和IgG由核心抗原特异性B淋巴细胞产生。除了B细胞的生产中和抗体针对HBV的能力，它们可以产生多种细胞因子，如IFNγ或IL-6，以抑制病毒复制在肝细胞和调节的CD4和CD8T细胞应答的活性。此外，Zgair等[23]证实抗-HBc通过抗HBc分泌B细胞的hepatocytotoxic效果有慢性乙型肝炎的严重性通过抑制或HBV的间隙中起重要作用。因此，在基线高水平抗-HBc的可能反映了其抗病毒治疗后，一个更好的结果相关患者的高适应性免疫的状态。

研究还表明，随着NUC治疗的患者表现出的抗-HBc水平比用PEG-IFN治疗显著较大下降。大家都知道，PEG-IFN和NUC的抗病毒机制是不同的。前者抑制HBV的复制通过增强宿主的免疫系统挂载抗HBV辩护;后者主要通过抑制HBV DNA的合成和乙肝病毒的逆转录酶的活性干扰起作用。因此，NUC治疗，这可以支持抗-HBc滴度在PEG-IFN队列较慢跌幅PEG-IFN治疗可诱导宿主更大的免疫激活。对于这种现象的另一种解释是，NUC或PEG-IFN治疗可能具有的频率或抗HBc分泌B细胞的数量具有不同的影响。然而，这种假设需要通过检查B细胞表型，这些队列在将来内的动态变化进行验证。

有关于抗-HBc滴度的抗病毒治疗的慢性乙肝患者最优化的临床应用几方面的含义。这种生物标志物应适用于所有NUC治疗，因为以前的研究已经表明当前可用NUC治疗慢性乙型肝炎的HBeAg血清学转换的效果相媲美;此外，各种NUCs具有类似的机制在抑制HBV replication.7-11此外，我们定义基线抗HBc的干扰素和NUC治疗，这将是方便其在临床实践中应用的均匀的截止值。因为基线抗-HBc水平有了通过使用截止值的最高值或，抗-HBc应以优化抗病毒治疗的引发抗病毒治疗在临床实践中之前进行测试作为有价值基线的指标之一。

我们的研究有两个控制良好的同伙和大样本量的强度，从而增加了结果的统计能力和可靠性。然而，我们的研究也有一些局限性。首先，该处理结果在我们的研究中评价为血清转换，这是替代终点。然而，我们认为，实现血清学反应也是抗乙肝治疗的一个重要目标，尤其是对年轻患者在亚太region.1其次，患者在NUC队列替比夫定有/治疗无阿德福韦，这是不更长一线抗病毒药物为CHB;然而，我们建议，抗-H​​Bc滴度也可以在其他NUCs施加由于其类似的对血清转换操作和效果相媲美的机制。第三，我们只评估抗-HBc的预测值在两个组，但还没有研究它在另一个独立的队列，这将削弱其结果在一定程度上的可信度。第四，在该研究中使用的双三明治抗-HBc测定还没有被广泛验证和被商业化，这将影响抗-HBc在临床实践中的应用，虽然这种新的检测已经由世界卫生组织的抗-HBc标准进行了验证。

总之，基线抗-HBc滴度是PEG-IFN和NUC治疗功效的HBeAg阳性CHB患者一个可靠的预测，这可能会被用于预处理分层旨在优化CHB的治疗。
致谢

我们感谢研究者，协调员，护士，患者及家属的贡献。我们也希望从生物统计，南方医科大学系感谢春泉瓯教授，为她的统计分析有用的帮助。
脚注

StephenW

一个令人费解的结果。全文:
http://gut.bmj.com/content/65/2/313.full