Calès Paul, Canivet Clémence M, Costentin Charlotte, Lannes Adrien, Oberti Frédéric, Fouchard Isabelle, Hunault Gilles, de Lédinghen Victor, Boursier Jérôme
Service d'Hépato-Gastroentérologie et Oncologie Digestive, Centre Hospitalier Universitaire d'Angers, Angers, France; Laboratoire HIFIH, UPRES EA3859, SFR 4208, Université d'Angers, Angers, France.
Service d'Hépato-Gastroentérologie et Oncologie Digestive, Centre Hospitalier Universitaire d'Angers, Angers, France; Laboratoire HIFIH, UPRES EA3859, SFR 4208, Université d'Angers, Angers, France.
J Hepatol. 2025 May;82(5):794-804. doi: 10.1016/j.jhep.2024.11.049. Epub 2024 Dec 13.
BACKGROUND & AIMS: The accuracy of non-invasive tests (NITs) should be ≥80% (EASL recommendation). We aimed to compare the accuracies of the recommended NITs for advanced fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD) and to develop NITs with improved accuracy.
A total of 1,051 patients with MASLD were allocated to derivation (n = 637) and validation (n = 414) sets. The main outcome (Kleiner F3+F4) was primarily evaluated by accuracy. Recommended NITs included: FIB-4, Fibrotest, FibroMeter, liver stiffness measurement (LSM by Fibroscan), Elasto-FibroMeter (FibroMeter-LSM combination), and ELF (enhanced liver fibrosis) in 396 patients. We used machine learning-optimized multitargeting to develop new NITs: FIB-9 (including nine common biomarkers), FIB-11 (adding two specialized blood markers) and FIB-12 (adding LSM).
In the whole population, the accuracies of recommended NITs were insufficient: Fibrotest, 68.0%; FIB-4, 71.2%; FibroMeter, 75.1%; LSM, 75.9%; Elasto-FibroMeter, 78.6%. Therefore, new NITs (FIB-9, FIB-11, FIB-12) were developed in the derivation set. In the validation set, AUROCs were: FIB-4, 0.757; Fibrotest, 0.766; FibroMeter, 0.850; LSM, 0.852; FIB-9, 0.863; FIB-11, 0.880; Elasto-FibroMeter, 0.894; FIB-12, 0.912 (p <0.001). The FIB-12 AUROC was superior to the ELF AUROC (0.906 vs. 0.865, p = 0.039). Accuracies were: FIB-4, 68.8%; Fibrotest, 68.6%; LSM, 75.4%; FibroMeter, 76.3%; FIB-9, 78.7%; Elasto-FibroMeter, 79.7%; FIB-11, 80.2%; FIB-12, 83.3% (p <0.001 between all NITs). Scores were segmented by ≥90% sensitivity and specificity cut-offs or NIT match, which individualized subgroups with NIT accuracies ≥80%, e.g. for FIB-9: 85.8% in 68.1% of patients using two cut-offs and 83.2% in 71.7% of patients where FIB-9 agreed with FIB-4.
Recommended NITs had accuracies <80% for advanced fibrosis in MASLD. Several NIT segmentations individualized subgroups with accuracies ≥80%. New NITs further improved accuracy. The simple FIB-9 (available via a free calculator) provided accuracy equaling or surpassing recommended NITs. FIB-12 outperformed other NITs.
Currently recommended non-invasive tests (NITs) have insufficient accuracy (<80%) for the diagnosis of advanced fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD). Therefore, we developed three new NITs with new statistical techniques. Thus, FIB-9 (available via a free calculator), including nine common blood markers, equaled the performance of patented NITs. FIB-11, adding two specialized blood markers, and FIB-12, adding liver stiffness, had accuracy >80%. FIB-12 outperformed all other NITs. FIB-9 is suitable for screening and FIB-11 or FIB-12 for diagnosis.
非侵入性检测(NITs)的准确性应≥80%(欧洲肝脏研究学会建议)。我们旨在比较推荐的NITs对代谢功能障碍相关脂肪性肝病(MASLD)中晚期肝纤维化的诊断准确性,并开发准确性更高的NITs。
总共1051例MASLD患者被分配至推导组(n = 637)和验证组(n = 414)。主要结局(Kleiner F3+F4)主要通过准确性进行评估。396例患者中推荐的NITs包括:FIB-4、Fibrotest、FibroMeter、肝脏硬度测量(Fibroscan测量LSM)、弹性纤维测量仪(FibroMeter-LSM组合)以及增强肝纤维化(ELF)检测。我们使用机器学习优化的多靶点方法开发新的NITs:FIB-9(包括9种常见生物标志物)、FIB-11(添加两种特殊血液标志物)和FIB-12(添加LSM)。
在总体人群中,推荐的NITs准确性不足:Fibrotest为68.0%;FIB-4为71.2%;FibroMeter为75.1%;LSM为75.9%;弹性纤维测量仪为78.6%。因此,在推导组中开发了新的NITs(FIB-9、FIB-11、FIB-12)。在验证组中,曲线下面积(AUROCs)分别为:FIB-4为0.757;Fibrotest为0.766;FibroMeter为0.850;LSM为0.852;FIB-9为0.863;FIB-11为0.880;弹性纤维测量仪为0.894;FIB-12为0.912(p<0.001)。FIB-12的AUROC优于ELF的AUROC(0.906对0.865,p = 0.039)。准确性分别为:FIB-4为68.8%;Fibrotest为68.6%;LSM为75.4%;FibroMeter为76.3%;FIB-9为78.7%;弹性纤维测量仪为79.7%;FIB-11为80.2%;FIB-12为83.3%(所有NITs之间p<0.001)。通过≥90%的敏感性和特异性截断值或NIT匹配对分数进行分层,确定了NIT准确性≥80%的个体化亚组,例如对于FIB-9:使用两个截断值时,68.1%的患者中为85.8%,FIB-9与FIB-4一致的71.7%的患者中为83.2%。
推荐的NITs对MASLD中晚期肝纤维化的准确性<80%。几种NIT分层确定了准确性≥