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DOI 10.3390/diagnostics14010118

Медицинская библиотека · Diagnostics (Basel, Switzerland) · 2024

Prediction Model for the Clearance of Hepatitis B Surface Antigen in Patients with Chronic Hepatitis B before Interferon Therapy: A Prospective Case-Control Study.

Geng Nan, Ma Lina, Jin Yi, Lu Junfeng, Zheng Yanhong, Wang Junli, Wang Xiaoxiao, Chen Xinyue

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Аннотация

To evaluate the prediction model comprised of patients' laboratory results and single-nucleotide polymorphism (SNP) markers of host gene for the clearance of hepatitis B surface antigen (HBsAg) in patients with chronic hepatitis B (CHB) who underwent interferon (IFN)-α therapy, this prospective case-control study enrolled 131 patients with CHB who underwent IFN-α-based regimens in our hospital between January 2015 and September 2019. Among them, 56 cases were without HBsAg clearance, while the other 75 cases had HBsAg clearance. Multivariable logistic regression analysis showed that CYP27B1 rs4646536 (odd ratio [OR] = 0.155, 95% CI: 0.030-0.807, p = 0.027), PAK4 rs9676717 (OR = 11.237, 95% CI: 1.768-71.409, p = 0.010), IL28B rs12979860 (OR = 0.059, 95% CI: 0.006-0.604, p = 0.017), baseline HBsAg (OR = 0.170, 95% CI: 0.040-0.716, p = 0.016), and HBeAg status (OR = 3.971, 95% CI: 1.138-13.859, p = 0.031) were independently associated with HBsAg clearance. The model that included rs3077, rs4646536, rs9676717, rs2850015, rs12979860, baseline HBsAg, HBeAg status, and HBV DNA had the best prediction performance for HBsAg clearance prediction, with AUC = 0.877, 80% sensitivity, and 81% specificity. In conclusion, laboratory results and gene polymorphisms before treatment might have a good predictive value for HbsAg clearance after IFN-α treatment in CHB.

Для цитирования: Geng Nan, Ma Lina, Jin Yi, Lu Junfeng, Zheng Yanhong, Wang Junli, Wang Xiaoxiao, Chen Xinyue. Prediction Model for the Clearance of Hepatitis B Surface Antigen in Patients with Chronic Hepatitis B before Interferon Therapy: A Prospective Case-Control Study.. Diagnostics (Basel, Switzerland). 2024. DOI: 10.3390/diagnostics14010118.
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