Abstract：
OBJECTIVE: Hepatitis B surface antigen (HBsAg) loss is the optimal outcome for patients with chronic hepatitis B (CHB) but this rarely occurs with currently approved therapies. We aimed to develop and validate a prognostic model for HBsAg loss on treatment using longitudinal data from a large, prospectively followed, nationwide cohort.
METHODS: CHB patients receiving nucleos(t)ide analogues as antiviral treatment were enrolled from 50 centres in China. Quantitative HBsAg (qHBsAg) testing was prospectively performed biannually per protocol. Longitudinal discriminant analysis algorithm was used to estimate the incidence of HBsAg loss, by integrating clinical data of each patient collected during follow-up.
RESULTS: In total, 6792 CHB patients who had initiated antiviral treatment 41.3 (IQR 7.6-107.6) months before enrolment and had median qHBsAg 2.9 (IQR 2.3-3.3) log10IU/mL at entry were analysed. With a median follow-up of 65.6 (IQR 51.5-84.7) months, the 5-year cumulative incidence of HBsAg loss was 2.4%. A prediction model integrating all qHBsAg values of each patient during follow-up, designated GOLDEN model, was developed and validated. The AUCs of GOLDEN model were 0.981 (95% CI 0.974 to 0.987) and 0.979 (95% CI 0.974 to 0.983) in the training and external validation sets, respectively, and were significantly better than those of a single qHBsAg measurement. GOLDEN model identified 8.5%-10.4% of patients with a high probability of HBsAg loss (5-year cumulative incidence: 17.0%-29.1%) and was able to exclude 89.6%-91.5% of patients whose incidence of HBsAg loss is 0. Moreover, the GOLDEN model consistently showed excellent performance among various subgroups.
CONCLUSIONS: The novel GOLDEN model, based on longitudinal qHBsAg data, accurately predicts HBsAg clearance, provides reliable estimates of functional hepatitis B virus (HBV) cure and may have the potential to stratify different subsets of patients for novel anti-HBV therapies.
METHODS: CHB patients receiving nucleos(t)ide analogues as antiviral treatment were enrolled from 50 centres in China. Quantitative HBsAg (qHBsAg) testing was prospectively performed biannually per protocol. Longitudinal discriminant analysis algorithm was used to estimate the incidence of HBsAg loss, by integrating clinical data of each patient collected during follow-up.
RESULTS: In total, 6792 CHB patients who had initiated antiviral treatment 41.3 (IQR 7.6-107.6) months before enrolment and had median qHBsAg 2.9 (IQR 2.3-3.3) log10IU/mL at entry were analysed. With a median follow-up of 65.6 (IQR 51.5-84.7) months, the 5-year cumulative incidence of HBsAg loss was 2.4%. A prediction model integrating all qHBsAg values of each patient during follow-up, designated GOLDEN model, was developed and validated. The AUCs of GOLDEN model were 0.981 (95% CI 0.974 to 0.987) and 0.979 (95% CI 0.974 to 0.983) in the training and external validation sets, respectively, and were significantly better than those of a single qHBsAg measurement. GOLDEN model identified 8.5%-10.4% of patients with a high probability of HBsAg loss (5-year cumulative incidence: 17.0%-29.1%) and was able to exclude 89.6%-91.5% of patients whose incidence of HBsAg loss is 0. Moreover, the GOLDEN model consistently showed excellent performance among various subgroups.
CONCLUSIONS: The novel GOLDEN model, based on longitudinal qHBsAg data, accurately predicts HBsAg clearance, provides reliable estimates of functional hepatitis B virus (HBV) cure and may have the potential to stratify different subsets of patients for novel anti-HBV therapies.
摘要：
目的：乙型肝炎表面抗原（HBsAg）丢失是慢性乙型肝炎（CHB）患者的最佳结果，但目前批准的治疗方法很少发生。我们的目的是开发和验证一个预后模型的HBsAg消失的治疗使用纵向数据，前瞻性地跟随，全国队列。
方法：接受核苷（酸）类似物作为抗病毒治疗的CHB患者来自中国50个中心。定量HBsAg（qHBsAg）检测前瞻性地每方案每两年进行一次。纵向判别分析算法用于估计HBsAg消失的发生率，通过整合随访期间收集的每位患者的临床数据。
结果：总计，6792名CHB患者谁开始抗病毒治疗41.3（IQR7.6-107.6）登记前，有中位数qHBsAg2.9（IQR2.3-3.3）log10IU/mL在进入分析。中位随访时间为65.6（IQR51.5-84.7）个月，HBsAg消失的5年累积发病率为2.4%.在随访期间，整合每位患者的所有qHBsAg值的预测模型，指定的GOLDEN模型，已开发和验证。GOLDEN模型的AUC分别为0.981(95%CI0.974至0.987)和0.979(95%CI0.974至0.983),分别,并且明显优于单个qHBsAg测量的那些。GOLDEN模型确定了8.5％-10.4％的患者HBsAg消失的可能性很高（5年累积发生率：17.0％-29.1％），并能够排除89.6％-91.5％的患者的HBsAg消失的发生率为0。此外，GOLDEN模型在各种亚组中始终显示出优异的性能。
结论：新的GOLDEN模型，基于纵向qHBsAg数据，准确预测HBsAg清除率，提供了功能性乙型肝炎病毒（HBV）治愈的可靠估计，并且可能有可能对不同的患者亚群进行分层以进行新型抗HBV治疗。
方法：接受核苷（酸）类似物作为抗病毒治疗的CHB患者来自中国50个中心。定量HBsAg（qHBsAg）检测前瞻性地每方案每两年进行一次。纵向判别分析算法用于估计HBsAg消失的发生率，通过整合随访期间收集的每位患者的临床数据。
结果：总计，6792名CHB患者谁开始抗病毒治疗41.3（IQR7.6-107.6）登记前，有中位数qHBsAg2.9（IQR2.3-3.3）log10IU/mL在进入分析。中位随访时间为65.6（IQR51.5-84.7）个月，HBsAg消失的5年累积发病率为2.4%.在随访期间，整合每位患者的所有qHBsAg值的预测模型，指定的GOLDEN模型，已开发和验证。GOLDEN模型的AUC分别为0.981(95%CI0.974至0.987)和0.979(95%CI0.974至0.983),分别,并且明显优于单个qHBsAg测量的那些。GOLDEN模型确定了8.5％-10.4％的患者HBsAg消失的可能性很高（5年累积发生率：17.0％-29.1％），并能够排除89.6％-91.5％的患者的HBsAg消失的发生率为0。此外，GOLDEN模型在各种亚组中始终显示出优异的性能。
结论：新的GOLDEN模型，基于纵向qHBsAg数据，准确预测HBsAg清除率，提供了功能性乙型肝炎病毒（HBV）治愈的可靠估计，并且可能有可能对不同的患者亚群进行分层以进行新型抗HBV治疗。
