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

AI Article Synopsis

  • A study evaluated a prediction model based on lab results and SNP markers for achieving HBsAg clearance in chronic hepatitis B patients treated with interferon-α.
  • Among 131 patients, 75 achieved clearance while 56 did not, with specific SNPs and baseline factors identified as key predictors.
  • The best predictive model achieved a high performance of AUC = 0.877, indicating that certain genetic and laboratory factors before treatment can help forecast treatment success.

Article Abstract

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, = 0.027), PAK4 rs9676717 (OR = 11.237, 95% CI: 1.768-71.409, = 0.010), IL28B rs12979860 (OR = 0.059, 95% CI: 0.006-0.604, = 0.017), baseline HBsAg (OR = 0.170, 95% CI: 0.040-0.716, = 0.016), and HBeAg status (OR = 3.971, 95% CI: 1.138-13.859, = 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10804386PMC
http://dx.doi.org/10.3390/diagnostics14010118DOI Listing

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