Department of Laboratory Medicine, Konkuk University School of Medicine, Seoul, Korea.
Department of Laboratory Medicine, Yeungnam University College of Medicine, Daegu, Korea.
Ann Lab Med. 2022 Mar 1;42(2):249-257. doi: 10.3343/alm.2022.42.2.249.
Non-invasive clinical algorithms for the detection of liver fibrosis (LF) can reduce the need for liver biopsy (LB). We explored the implementation of two serum biomarkers, enhanced liver fibrosis (ELF) and Mac-2 binding protein glycosylation isomer (M2BPGi), in clinical algorithms for LF in chronic hepatitis B (CHB) patients.
Two clinical algorithms were applied to 152 CHB patients: (1) transient elastography (TE) followed by biomarkers (TE/ELF and TE/M2GPGi); (2) biomarker test followed by TE (ELF/TE and M2BPGi/TE). Using the cut-off value or index for the detection of advanced LF (TE≥F3; 9.8 in ELF and 3.0 in M2BPGi), LB was expected to be performed in cases with discordant TE and biomarker results.
In both algorithms, the expected number of LBs was lower when using M2BPGi than when using ELF (TE/ELF or ELF/TE, 13.2% [N=20]; TE/M2BPGi or M2BPGi/TE, 9.9% [N=15]), although there was no statistical difference (=0.398). In the TE low-risk group (TE≤F2), the discordance rate was significantly lower in the TE/M2BPGi approach than in the TE/ELF approach (1.5% [2/136] vs. 11.0% [15/136], =0.002). In the biomarker low-risk group, there was no significant difference between the ELF/TE and M2BPGi/TE approaches (3.9% [5/126] vs. 8.8% [13/147], =0.118).
Both ELF and M2BPGi can be implemented in non-invasive clinical algorithms for assessing LF in CHB patients. Given the lowest possibility of losing advanced LF cases in the low-risk group when using the TE/M2BPGi approach, this combination seems useful in clinical practice.
非侵入性临床算法可用于检测肝纤维化(LF),从而减少肝活检(LB)的需求。我们研究了两种血清生物标志物,增强型肝纤维化(ELF)和 Mac-2 结合蛋白糖基化异构体(M2BPGi)在慢性乙型肝炎(CHB)患者 LF 临床算法中的应用。
将两种临床算法应用于 152 例 CHB 患者:(1)瞬时弹性成像(TE)联合生物标志物(TE/ELF 和 TE/M2GPGi);(2)生物标志物检测联合 TE(ELF/TE 和 M2BPGi/TE)。使用检测晚期 LF(TE≥F3;ELF 为 9.8,M2BPGi 为 3.0)的截断值或指数,对于 TE 和生物标志物结果不一致的病例,预计将进行 LB。
两种算法中,使用 M2BPGi 而非 ELF 时,预计进行 LB 的病例数较少(TE/ELF 或 ELF/TE,13.2%[N=20];TE/M2BPGi 或 M2BPGi/TE,9.9%[N=15]),但差异无统计学意义(=0.398)。在 TE 低风险组(TE≤F2)中,TE/M2BPGi 方法的不一致率明显低于 TE/ELF 方法(1.5%[2/136]比 11.0%[15/136],=0.002)。在生物标志物低风险组中,ELF/TE 和 M2BPGi/TE 方法之间无显著差异(3.9%[5/126]比 8.8%[13/147],=0.118)。
ELF 和 M2BPGi 均可用于评估 CHB 患者的 LF 非侵入性临床算法。鉴于在使用 TE/M2BPGi 方法时,低风险组中漏诊晚期 LF 病例的可能性最低,该联合方法在临床实践中似乎有用。