干扰素α治疗慢性乙型肝炎疗效预测的评分量表

Predictors and scoring system for sustained complete response to conventional interferon-a therapy on chronic hepatitis B

目的建立可用于预测干扰素α治疗慢性乙型肝炎持久完全应昝情况的评分量表。方法本研究纳入474例采用干扰素α治疗的HBeAg阳性慢性乙型肝炎患者。收集患者的基线信息，如年龄、性别、HBV标志物、肝脏炎症活动度、肝纤维化程度、HBVDNA定量及基因型，同时收集不同疗程及停药后随访24周时患者的应答情况。采用遗传算法构建评分量表。随机抽出10%病例作为测试集。疗效分为完全应答（CR）、部分应答及无应答。统计学处理在R平台上进行。以基于随机森林的GiN指数法确定各影响因素的相关性大小顺序。以Kendall’Stau-b检验分析自变量与应变量间的统计学相关性；对于分类变量则采用Spearman秩相关分析。结果评分量表的敏感度与特异度分别为78．8％及80．60／0，优势比为15．25。CR：男性患者为31．9％（110／345），女性患者为39．5％（51／129），／9〈0．01，女性患者比男性患者更易获得CR；基因B型HBV感染者CR为43．9％，C型感染者CR为26．1％，P〈0．01，基因B型感染者比C型感染者更易获得CR。ALT1～2×正常值上限（ULN）者CR为22．6％（12／53）、2～3×ULN者CR为10．4％（8／77）、3～5×ULN者CR为22．5％（29／129）、5～10×ULN者CR为53．0％（70／132）、≥10×ULN者CR为55．4%（46／83）。AST0～1×ULN者CR为9．1％（2／22）、1～2×ULN者CR为19．6％（29／148）、2～3×ULN者CR为31．4％（32／102）、3～5×ULN者CR为46．5％（47／101）、5～10XULN者CR为53．4％（39／73）、≥10×ULN者CR为57．1％（16／28），P〈0．01，高ALT、AST水平者更易获得CR。结论本评分量表的预测性能好，便于临床使用。借助这个评分量表，专科医师可以制订出既有循证医学证据又兼顾个体特征的个体化治疗决策。

Objective To establish a predictive scoring system which may serve for the prediction of sustained response to conventional interferon-a （IFN-a） treatment on chronic hepatitis B. Methods A total of 474 IFN-a treated hepatitis B virus e antigen （HBeAg）-positive patients were enrolled in the present study. The patients＇ baseline characteristics, such as age, gender, aminotrans ferases, activity grading （G） of intrahepatic inflammation, score （S） of liver fibrosis, hepatitis B virus （HBV） DNA and genotype were evaluated; therapy duration and response of each patient at the 24th wk after cessation of IFN-a treatment were also recorded. A predictive scoring system for a sustained complete response （CR） to IFN-a therapy was established based on genetic algorithm. About 10% of the patients were randomly drawn out as the test set. Responses to IFN-a therapy were divided into CR, partial response （PR） and non-response （NR）. The mixed set of PR and NR was recorded as PR＋NR. Results For the scoring system, the sensitivity and specificity were 78.8% and 80.6%, respectively. Conclusion This SCR scoring system has satisfying prediction efficiency and is easily employed in clinical practice. With this scoring system, practitioners can propose individualized decisions that have an integrated foundation on both evidence-based medicine and personal characteristics,