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Wei Bin,Guo Ying,Ou Xiaoqi,Lin Liyan,Su Zhenzhen,Li Lixin,Wu XiaoJuan,Cai Bei 대한진단검사의학회 2023 Annals of Laboratory Medicine Vol.43 No.5
Background: There is no standard cut-off value of serum IgG4 concentration and serum IgG4/total IgG ratio for the diagnosis of IgG4-related disease (IgG4-RD) or as a marker of treatment responses. We aimed to explore this issue through a retrospective cohort analysis of adults in southwest China. Methods: The diagnostic performance of serum IgG4 concentration and IgG4/IgG ratio for IgG4-RD was evaluated in a retrospective analysis of 177 adults newly diagnosed as having IgG4-RD and 877 adults without IgG4-RD. Dynamic analysis was performed to evaluate the significance of serum IgG4 concentration on IgG4-RD treatment responses. Results: The serum IgG4 concentration differed according to sex. The optimal cut-off values of serum IgG4 concentration and IgG4/IgG ratio for IgG4-RD diagnosis were 1.92 g/L and 0.12 in males and 1.83 g/L and 0.11 in females, respectively. For patients with serum IgG4 concentration >2.01 g/L, the cut-off values in the total population were >3.00 g/L and 0.19, respectively. The median serum IgG4 concentration decreased over time, and the decrease rate increased over time. The serum IgG4 concentration significantly decreased at >1 week post-treatment (P=0.004), and the median decrease rate was close to 50% at >4 weeks post-treatment. Conclusions: Serum IgG4 can be a good indicator for IgG4-RD diagnosis; however, different diagnostic cut-off values should be determined according to sex. The decreasing rate is more conducive than the serum IgG4 concentration to monitor treatment efficacy. The IgG4/IgG ratio did not improve the diagnostic efficacy for IgG4-RD.
Xiaoning Wu,Xiaoqian Xu,Jialing Zhou,Yameng Sun,Huiguo Ding,Wen Xie,Guofeng Chen,Anlin Ma,Hongxin Piao,Bingqiong Wang,Shuyan Chen,Tongtong Meng,Xiaojuan Ou,Hwai-I Yang,Jidong Jia,Yuanyuan Kong,Hong Yo 대한간학회 2023 Clinical and Molecular Hepatology(대한간학회지) Vol.29 No.3
Background/Aims: Existing hepatocellular carcinoma (HCC) prediction models are derived mainly from pretreatment or early on-treatment parameters. We reassessed the dynamic changes in the performance of 17 HCC models in patients with chronic hepatitis B (CHB) during long-term antiviral therapy (AVT). Methods: Among 987 CHB patients administered long-term entecavir therapy, 660 patients had 8 years of follow-up data. Model scores were calculated using on-treatment values at 2.5, 3, 3.5, 4, 4.5, and 5 years of AVT to predict threeyear HCC occurrence. Model performance was assessed with the area under the receiver operating curve (AUROC). The original model cutoffs to distinguish different levels of HCC risk were evaluated by the log-rank test. Results: The AUROCs of the 17 HCC models varied from 0.51 to 0.78 when using on-treatment scores from years 2.5 to 5. Models with a cirrhosis variable showed numerically higher AUROCs (pooled at 0.65–0.73 for treated, untreated, or mixed treatment models) than models without (treated or mixed models: 0.61–0.68; untreated models: 0.51–0.59). Stratification into low, intermediate, and high-risk levels using the original cutoff values could no longer reflect the true HCC incidence using scores after 3.5 years of AVT for models without cirrhosis and after 4 years of AVT for models with cirrhosis. Conclusions: The performance of existing HCC prediction models, especially models without the cirrhosis variable, decreased in CHB patients on long-term AVT. The optimization of existing models or the development of novel models for better HCC prediction during long-term AVT is warranted.