A nomogram based on HBeAg, AST, and age to predict non-minimal liver inflammation in CHB patients with ALT <80 U/L - Zhang, Lu; Bi, Xiaoyue; Chen, Xiaoxue; Zhang, Luxue; Xiong, Qiqiu; Cao, Weihua; Lin, Yanjie; Yang, Liu; Jiang, Tingting; Deng, Wen; Wang, Shiyu; Wu, Shuling; et al. (Frontiers in Immunology, 2023)
Objective: Precise assessment of liver inflammation in untreated HBeAg positive patients with chronic HBV infection can determine when to initiate anti-viral therapy. The aim of this study was to develop and validate a nomogram model for predicting non-minimal liver inflammation by liver pathological injuries combined with age, ALT, AST, HBsAg, HBeAg, and HBV DNA quantification. Methods: We retrospectively included 735 HBeAg positive chronic hepatitis B (CHB) patients with ALT<80 U/L as the primary cohort and prospectively enrolled 196 patients as the validation cohort. Multivariate logistic regression analysis identified independent impact factors. A nomogram to predict significant liver inflammation was developed and validated. Results: Multivariate logistic regression analysis showed that HBeAg, AST, and age were independent risk factors for predicting non-minimal liver inflammation in untreated CHB patients. The final formula was Logit (P) =-1.99-0.68×Log10 HBeAg+0.04×Age+0.06×AST for predicting non-minimal liver inflammation. A nomogram for predicting non-minimal liver inflammation was established based on results from the multivariate analysis. Calibration curves validated that the prediction probability of the model was consistent with the actual probability, showing the best agreement in both the primary cohort and the validation cohort. C-Index was 0.767 (95%CI: 0.734~0.802) in primary cohort and 0.749 (95%CI: 0.681~0.817) in prospective validation cohort. Conclusions: The nomogram based on HBeAg, AST, and age might help predict non-minimal liver inflammation in HBeAg positive CHB patient with ALT<80 U/L, which is practical and easy to use for clinicians.