{"title":"一个包括定量抗-HBc的基线模型预测聚乙二醇干扰素在HBeAg阳性慢性乙型肝炎患者中的反应","authors":"Yuqing Fang, Xiaoyan Xu, F. Hou, Wei Jia","doi":"10.1177/13596535211059895","DOIUrl":null,"url":null,"abstract":"Background Few models to predict antiviral response of peginterferon were used in hepatitis B e antigen (HBeAg)-positive chronic hepatitis B patients and the prediction efficacy was unsatisfied. Quantitative antibody to hepatitis B core antigen (anti-HBc) is a new predictor of treatment response. We aimed to develop a new model to identify HBeAg-positive Chinese patients who were more likely to respond to peginterferon. Methods Data from 140 peginterferon recipients with HBeAg-positive were applied with generalized additive models and multiple logistic regression analysis to develop a baseline scoring system to predict serological response (SR: HBeAg loss and HBeAg seroconversion 24 weeks post-treatment) and combined response (CR: SR plus serum HBV DNA levels <2000 IU/mL 24 weeks post-treatment). Results Anti-HBc levels, alanine aminotransferase ratio, and HBeAg were retained in the final model. The new model scored from 0 to 3. Among patients with scores of 0, 1, or ≥2, SR was achieved in 6.45% (2/31), 13.21% (7/51), and 55.36% (31/56), respectively, and CR in 3.23% (1/31), 9.43% (5/53), and 25.00% (14/56), respectively. Our model has a higher AUROC for SR comparing to Chan’s (Z = 2.77 > 1.96, p < 0.05) and Lampertico’s (Z = 2.06 > 1.96, p < 0.05) model. The negative predictive value for SR and CR were both 100% in patients with score 0 and hepatitis B surface antigen ≥20,000 IU/mL at week 12. Conclusions Patients with higher scores at baseline were more likely to respond to peginterferon. This new model may predict the treatment response.","PeriodicalId":8364,"journal":{"name":"Antiviral Therapy","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A baseline model including quantitative anti-HBc to predict response of peginterferon in HBeAg-positive chronic hepatitis B patients\",\"authors\":\"Yuqing Fang, Xiaoyan Xu, F. Hou, Wei Jia\",\"doi\":\"10.1177/13596535211059895\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background Few models to predict antiviral response of peginterferon were used in hepatitis B e antigen (HBeAg)-positive chronic hepatitis B patients and the prediction efficacy was unsatisfied. Quantitative antibody to hepatitis B core antigen (anti-HBc) is a new predictor of treatment response. We aimed to develop a new model to identify HBeAg-positive Chinese patients who were more likely to respond to peginterferon. Methods Data from 140 peginterferon recipients with HBeAg-positive were applied with generalized additive models and multiple logistic regression analysis to develop a baseline scoring system to predict serological response (SR: HBeAg loss and HBeAg seroconversion 24 weeks post-treatment) and combined response (CR: SR plus serum HBV DNA levels <2000 IU/mL 24 weeks post-treatment). Results Anti-HBc levels, alanine aminotransferase ratio, and HBeAg were retained in the final model. The new model scored from 0 to 3. Among patients with scores of 0, 1, or ≥2, SR was achieved in 6.45% (2/31), 13.21% (7/51), and 55.36% (31/56), respectively, and CR in 3.23% (1/31), 9.43% (5/53), and 25.00% (14/56), respectively. Our model has a higher AUROC for SR comparing to Chan’s (Z = 2.77 > 1.96, p < 0.05) and Lampertico’s (Z = 2.06 > 1.96, p < 0.05) model. The negative predictive value for SR and CR were both 100% in patients with score 0 and hepatitis B surface antigen ≥20,000 IU/mL at week 12. Conclusions Patients with higher scores at baseline were more likely to respond to peginterferon. This new model may predict the treatment response.\",\"PeriodicalId\":8364,\"journal\":{\"name\":\"Antiviral Therapy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Antiviral Therapy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/13596535211059895\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Antiviral Therapy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/13596535211059895","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
A baseline model including quantitative anti-HBc to predict response of peginterferon in HBeAg-positive chronic hepatitis B patients
Background Few models to predict antiviral response of peginterferon were used in hepatitis B e antigen (HBeAg)-positive chronic hepatitis B patients and the prediction efficacy was unsatisfied. Quantitative antibody to hepatitis B core antigen (anti-HBc) is a new predictor of treatment response. We aimed to develop a new model to identify HBeAg-positive Chinese patients who were more likely to respond to peginterferon. Methods Data from 140 peginterferon recipients with HBeAg-positive were applied with generalized additive models and multiple logistic regression analysis to develop a baseline scoring system to predict serological response (SR: HBeAg loss and HBeAg seroconversion 24 weeks post-treatment) and combined response (CR: SR plus serum HBV DNA levels <2000 IU/mL 24 weeks post-treatment). Results Anti-HBc levels, alanine aminotransferase ratio, and HBeAg were retained in the final model. The new model scored from 0 to 3. Among patients with scores of 0, 1, or ≥2, SR was achieved in 6.45% (2/31), 13.21% (7/51), and 55.36% (31/56), respectively, and CR in 3.23% (1/31), 9.43% (5/53), and 25.00% (14/56), respectively. Our model has a higher AUROC for SR comparing to Chan’s (Z = 2.77 > 1.96, p < 0.05) and Lampertico’s (Z = 2.06 > 1.96, p < 0.05) model. The negative predictive value for SR and CR were both 100% in patients with score 0 and hepatitis B surface antigen ≥20,000 IU/mL at week 12. Conclusions Patients with higher scores at baseline were more likely to respond to peginterferon. This new model may predict the treatment response.
期刊介绍:
Antiviral Therapy (an official publication of the International Society of Antiviral Research) is an international, peer-reviewed journal devoted to publishing articles on the clinical development and use of antiviral agents and vaccines, and the treatment of all viral diseases. Antiviral Therapy is one of the leading journals in virology and infectious diseases.
The journal is comprehensive, and publishes articles concerning all clinical aspects of antiviral therapy. It features editorials, original research papers, specially commissioned review articles, letters and book reviews. The journal is aimed at physicians and specialists interested in clinical and basic research.