丙型肝炎持续病毒学应答后肝癌发生的危险因素及预测模型
DOI: 10.12449/JCH240629
Risk factors and predictive models for liver cancer after sustained virologic response in hepatitis C
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摘要: 丙型肝炎是肝癌发生的主要病因之一。随着直接抗病毒药物的应用,95%以上的患者可根除HCV,获得持续病毒学应答(SVR)。有效的抗病毒治疗可以改变丙型肝炎的自然病程,降低肝癌发生风险,但仍有一部分患者会受到年龄、性别、肝纤维化、糖尿病、肝脂肪变、饮酒和遗传因素等影响,成为肝癌高危人群。因此,如何识别和预测丙型肝炎SVR后肝癌高危人群需进一步明确与完善。本文通过系统综述丙型肝炎患者SVR后肝癌发生的危险因素和肝癌预测模型,旨在为临床识别丙型肝炎SVR后肝癌高风险人群提供依据。Abstract: Hepatitis C is one of the main causes of liver cancer. With the application of direct-acting antiviral agents, more than 95% of patients can achieve the eradication of hepatitis C virus and obtain sustained virologic response (SVR). Effective antiviral therapy can change the natural course of hepatitis C and reduce the risk of liver cancer; however, some patients are still affected by age, sex, liver fibrosis, diabetes, hepatic steatosis, alcohol consumption, and genetic factors and become the high-risk population of liver cancer. Therefore, it is needed to further clarify and improve the identification and prediction of high-risk populations of liver cancer after SVR of hepatitis C. This article reviews the risk factors and predictive models for liver cancer after SVR in patients with hepatitis C, in order to provide a basis for identifying the high-risk population of liver cancer after SVR of hepatitis C in clinical practice.
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Key words:
- Hepatitis C /
- Sustained Virologic Response /
- Liver Neoplasms /
- Risk Factors
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据世界卫生组织统计,全球约有5 800万例慢性HCV感染者,每年约有150万新发感染者,有320万青少年和儿童慢性感染HCV,我国约有1 000万HCV感染者[1]。2019年统计约有29万人死于HCV相关肝硬化和肝癌[2]。因此,HCV感染仍是严重的、全球性疾病负担。随着直接抗病毒药物(direct-acting antiviral agents,DAA)的上市,95%以上的丙型肝炎患者可根除HCV,获得持续病毒学应答(sustained virologic response,SVR)。有效的抗病毒治疗可降低肝癌发生风险高达70%,但并不能消除肝癌发生风险,特别是进展期肝纤维化和肝硬化患者[3]。指南[4-5]推荐此类患者每6个月进行1次甲胎蛋白和超声检测以筛查肝癌,这给患者带来了沉重的负担,导致部分患者疏于监测,肝癌发现即晚期,病死率高。因此,如何对丙型肝炎SVR后患者进行肝癌的风险评估、制订个体化肝癌随访筛查方案和早期识别、诊断显得尤为重要。肝癌的早期诊断不仅可提高肝癌治愈的可能性,更是降低成本、提高效益的有效途径。本文通过对丙型肝炎SVR后肝癌发生的危险因素及预测模型进行系统综述,旨在为临床识别丙型肝炎SVR后肝癌高危人群和完善肝癌筛查策略提供参考。
1. 丙型肝炎SVR后肝癌发生的危险因素
1.1 肝纤维化逆转
众所周知,肝纤维化严重程度是肝癌发生的重要危险因素。目前研究[6-7]发现,丙型肝炎SVR后肝纤维化逆转情况亦与肝癌发生密切相关,尤其是进展期肝纤维化和肝硬化患者。Ravaioli等[8]比较139例经DAA治疗获得SVR的丙型肝炎肝硬化患者的基线和治疗结束时的肝脏硬度值(liver stiffness measurements,LSM)发现,非肝癌组患者治疗结束时LSM下降幅度显著高于肝癌组(28.9% vs 18%,P=0.005)。在多变量分析中,LSM下降幅度<30%是肝癌的一个独立危险因素。该研究进一步证实DAA治疗可改善肝纤维化严重程度,且肝纤维化改善情况与丙型肝炎SVR后肝癌发生显著相关。
1.2 肝脂肪变
肝脂肪变是慢性丙型肝炎的病理组织学特征之一[9]。体外和体内研究[10-11]均表明,HCV核心蛋白在细胞培养物或转基因小鼠中的表达可导致肝脂肪变的发生,从而促进癌变。一项前瞻性研究[12]发现,47.5%获得SVR的丙型肝炎患者有肝脂肪变证据,肝脂肪变与丙型肝炎SVR后持续肝损伤相关,表现为甲胎蛋白和/或ALT升高。
Peleg等[13]对515例经DAA治疗的丙型肝炎患者进行了一项回顾性研究发现,基线肝脂肪变与全因死亡率和治疗后肝癌发生密切相关。肝脂肪变患者的肝癌发生率(5.23例/100人年,95%CI:4.85~5.71)高于进展期肝纤维化患者(3.51例/100人年,95%CI:3.33~3.67)。此外,与进展期肝纤维化无肝脂肪变的患者相比,无进展期肝纤维化的肝脂肪变患者病死率和肝癌发生率更高。丙型肝炎SVR后患者大多有肝脂肪变,肝脂肪变与肝癌发生及全因死亡率相关[13-14]。因此,对于丙型肝炎SVR后有肝脂肪变证据的患者需进行密切随访监测。
1.3 糖尿病
糖尿病被认为是丙型肝炎获得SVR后肝癌发生的危险因素,但机制尚不明确[15-16]。有证据表明高胰岛素血症和胰岛素依赖信号通路与肝癌的发生、发展相关。胰岛素抵抗会促进丙型肝炎患者的纤维化进展,肝硬化导致的高胰岛素血症和胰岛素抵抗可进一步促进肝癌的发生[17]。一项前瞻性研究[18]发现,糖尿病是丙型肝炎肝硬化患者SVR后肝癌发生的独立危险因素。Degasperi等[15]在经DAA治疗获得SVR的546例丙型肝炎患者中发现,糖尿病是肝癌新发(HR=2.52,95%CI:1.08~5.87,P=0.03)和复发(HR=4.12,95%CI:1.55~10.93,P=0.004)的重要危险因素。Lu等[16]的研究同样表明糖尿病是肝癌发生的危险因素(aHR=1.65,95%CI:1.09~2.49)。2023年的一项研究[19]发现,丙型肝炎无糖尿病、糖尿病未应用二甲双胍、糖尿病应用二甲双胍患者5年肝癌累积发病率分别为3.0%、10.9%、2.6%,进一步说明糖尿病是丙型肝炎发生肝癌的高危因素,控制血糖可降低肝癌发生风险。然而,Kanwal等[14]的研究认为,糖尿病不会增加经DAA治疗获得SVR的丙型肝炎患者的肝癌发生风险。
1.4 饮酒
无论是否存在HCV感染,酒精都是肝癌发生的重要危险因素。饮酒患者肝癌年发病率高于未饮酒患者(aHR=4.73,95%CI:3.34~6.68)[14]。对于经DAA治疗获得SVR的丙型肝炎患者,饮酒者的肝癌年发病率(1.01%,95%CI:0.83%~1.19%)高于未饮酒者(0.72%,95%CI:0.54%~0.91%)[14]。酒精诱导的氧化应激和乙醇的肝脏代谢可增加致癌物向活性致癌物的转化,从而导致肝癌的发生[20]。乙醇摄入量≥80 g/d 10年会导致肝癌发生风险增加约5倍,并且女性比男性更易受到酒精毒性的影响[21-22]。酒精与HCV对肝损伤有协同作用,会加速肝硬化和肝脏相关并发症的进展。对于那些未戒酒的丙型肝炎患者,酒精对肝纤维化、肝癌的影响即使在丙型肝炎SVR后仍然存在。
1.5 遗传风险评分
国外的两项全基因组关联分析[23-24]发现PNPLA3 rs738409 GG基因型参与丙型肝炎患者肝脏脂肪变和肝癌的发生。2023年Ohta等[25]在223例经DAA和/或干扰素治疗获得SVR的丙型肝炎患者中,检测了7个基因的单核苷酸多态性(single-nucleotide polymorphism,SNP),发现PNPLA3 rs738409 GG和GCKR rs1260326 GG基因型与丙型肝炎SVR后肝癌发生相关。意大利的一项研究[26]进一步验证了上述结论。
Degasperi等[27]在经DAA治疗获得SVR的509例丙型肝炎肝硬化患者中,检测了PNPLA3 rs738409、TM6SF2 rs58542926、GCKR rs1260326和MBOAT7 rs641738 4个基因的多态性,计算4个基因的遗传风险评分(genetic risk score,GRS),发现GRS评分>0.597(HR=2.30,P=0.04)是肝癌的独立风险因素。肝癌具有一定的家族聚集性和遗传易感性,遗传因素是肝癌的重要危险因素之一,单个基因的多态性与丙型肝炎SVR后肝癌发生相关,多个基因的GRS评分是肝癌的独立危险因素,GRS评分有望纳入肝癌预测模型以提高模型的预测效能。
2. 丙型肝炎SVR后肝癌发生的预测模型
目前,已提出的肝癌风险预测模型包括:简化的肝癌评分系统APRI、FIB-4,肝脏和脾脏弹性检测,多变量回归模型,深度学习模型等。APRI、FIB-4主要用于评估肝纤维化,并非为预测肝癌开发[28],因此,二者预测肝癌的准确性较差。
有研究[29]表明,无论是进展期肝纤维化还是肝硬化患者,LSM都与肝癌发生相关,LSM<10 kPa、≥10~15 kPa、≥15~20 kPa、≥20~25 kPa的患者肝癌年发生风险分别为0.11%、2.9%、5%、8.3%、14.4%。Dajti等[30]同时纳入LSM和脾脏硬度测量(spleen stiffness measurement,SSM),结果发现SSM>42 kPa是丙型肝炎SVR后24周(SVR24)肝癌的独立危险因素。根据模型将患者分为低危组(LSM-SVR24<10 kPa)、中危组(LSM-SVR24 10~20 kPa和SSM-SVR24≤42 kPa)和高危组(LSM-SVR24>20 kPa或SSM-SVR24>42 kPa),他们认为低危患者(年发病率<1%)可以避免一年两次的筛查。LSM是评估肝纤维化的指标,SSM是评估门静脉高压的指标,两个指标不是用于预测肝癌的,且均易受到检测者的主观影响、可能存在偏倚,如同时纳入客观指标,该模型预测肝癌的准确性更佳。
多变量回归模型对丙型肝炎SVR后肝癌发生的危险因素进行赋分,根据评分将患者进行风险分层。日本的一项研究[31]根据年龄、SVR后甲胎蛋白开发了一个简易评分,风险评分2分组患者肝癌发生率显著高于0分组。甲胎蛋白会受肝脏炎症、生殖系统肿瘤等疾病影响,且肝癌患者甲胎蛋白阳性率仅为60%~70%。此模型简单,但易受甲胎蛋白影响、假阴性率高,且该研究纳入的患者多为基因1型或2型,可纳入其他客观指标矫正甲胎蛋白造成的假阴性,同时需在其他基因型患者中进一步验证。Shiha等[32]做了相似的研究,评分纳入性别、年龄、纤维化分期、白蛋白和甲胎蛋白水平5个危险因素,根据评分将患者分为低危组(评分<6)、中危组(评分6~7.5分)、高危组(评分>7.5)。三组患者1年、2年、3年的肝癌发生率分别为0.1%、1.2%、1.9% vs 0.7%、3.3%、5.8% vs 1.2%、7.1%、9.5%。该模型的优点是纳入的指标客观、临床易获得,但该模型随访时间短,其远期预测能力尚不清楚,且该研究的人群为基因4型丙型肝炎患者,是否适用于其他基因型患者未可知,需进一步在其他基因型患者中验证后使用。
Ioannou等[33]纳入了年龄、血小板、血清AST/ALT比值和白蛋白4个危险因素,根据是否存在肝硬化及是否获得SVR分别建立了肝癌预测模型,并以网站(www.hccrisk.com)的形式呈现,临床医生可以在网站上输入相应的数值,得到肝癌发生风险。该模型在推导队列和验证队列的Gönen和Heller’s κ-statistic均>0.7,是一个较好的肝癌预测模型。我国学者[34]就肝癌预测模型进行了一项包含11个国际前瞻性和/或随机对照队列的大型研究,纳入了17 374例患者,通过单因素和多因素分析发现年龄、性别、白蛋白、胆红素、血小板是肝癌发生的重要危险因素,基于危险因素开发了一种肝癌风险评分,称为aMAP评分(范围0~100分)。aMAP评分在日本丙型肝炎非肝硬化、肝硬化队列中预测肝癌风险的C指数分别为0.74、0.82,在英国、高加索获得SVR的丙型肝炎肝硬化队列中预测肝癌的C指数分别为0.77、0.68。该模型是基于大型队列建立的,并进行了验证,是一个非常有前途的预测模型。本团队[35]在经DAA和/或干扰素治疗获得SVR的551例丙型肝炎进展期肝纤维化和肝硬化患者中进一步验证aMAP评分与Ioannou GN开发的模型,发现aMAP评分的受试者工作特征曲线下面积(AUC)为0.74,优于Ioannou GN开发的模型(AUC=0.63)(P<0.05)。在男性患者中验证发现,两种模型的AUC均低于0.7。因此,无论是aMAP评分还是Ioannou GN开发的模型,在男性患者中需谨慎应用。
近期,法国的一项研究[36]纳入了酒精性肝病和获得SVR的丙型肝炎肝纤维化和肝硬化患者共1 142例,检测了7个基因(PNPLA3 rs738409、TM6SF2 rs58542926、HSD17B13 rs72613567、MBOAT7 rs641738、APOE rs 429358、WNT3A-WNT9A、TM6SF2 rs187429064)的多态性,计算7个基因的GRS评分(7-SNP GRS),发现7-SNP GRS评分是肝癌发生的独立危险因素,基于7-SNP GRS评分和临床危险因素构建的肝癌预测模型AUC为0.786,略高于临床肝癌预测模型(AUC=0.769)(P>0.05)。该模型加入GRS评分后预测效能优于临床模型,但无统计学差异,且没有明确区分酒精性肝病和丙型肝炎患者。因此,基于GRS评分建立的肝癌预测模型,尚需进一步探索和验证。
此外,Ioannou等[37]在深度学习领域探索,利用循环神经网络(recurrent neural network,RNN)模型识别丙型肝炎获得SVR后3年肝癌发生的高风险患者。他们建立了三种模型:横断面逻辑回归(logistic regression,LR)、纵向LR和RNN,其AUC分别为0.67、0.70和0.80,比较发现RNN模型最优,是一种很有前途的工具。
3. 总结和展望
在DAA时代,95%的丙型肝炎患者可获得临床治愈,但即使临床治愈后丙型肝炎仍有进展为肝癌的风险,特别是进展期肝纤维化和肝硬化患者。高龄、严重肝纤维化、糖尿病、肝脏脂肪变、饮酒和遗传风险评分等是丙型肝炎患者SVR后肝癌发生的危险因素。有一些因素如高龄、遗传风险评分无法改变,但可以采取一些措施控制血糖、减重、戒酒等促进丙型肝炎患者SVR后更健康的生活,并降低肝癌发生风险。为提高肝癌早期诊断率,人们努力开发肝癌预测模型,但现有预测模型大多是基于临床常规指标,或单纯依靠简易的无创指标,或缺乏进一步验证,对于肝癌风险预测准确性及个性化较差,而复杂的编程模型难以在临床开展。综上,目前已开发的肝癌预测模型仍然面临着特异性不足,准确性不够,无法广泛使用的局面。因此,需基于危险因素和临床指标进一步开发简单、准确、临床易于应用的模型,以期早期、准确地识别肝癌高危人群,对丙型肝炎SVR后患者进行风险分层,为指南制订肝癌筛查策略提供依据。
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[1] Chinese Society of Hepatology and Chinese Society of Infectious Diseases, Chinese Medical Association. Guidelines for the prevention and treatment of hepatitis C(2022 version)[J]. Chin J Infect Dis, 2023, 41( 1): 29- 46. DOI: 10.3760/cma.j.cn311365-20230217-00045.中华医学会肝病学分会, 中华医学会感染病学分会. 丙型肝炎防治指南(2022年版)[J]. 中华传染病杂志, 2023, 41( 1): 29- 46. DOI: 10.3760/cma.j.cn311365-20230217-00045. [2] World Health Organization. Global progress report on HIV, viral hepatitis and sexually transmitted Global progress report on HIV, viral hepatitis and sexually transmitted infections, 2021[EB/OL]. Accountability for the global health sector strategies 2016- 2021: actions for impact, 2021, Geneva: World Health Organization. [3] PIÑERO F, MENDIZABAL M, RIDRUEJO E, et al. Treatment with direct-acting antivirals for HCV decreases but does not eliminate the risk of hepatocellular carcinoma[J]. Liver Int, 2019, 39( 6): 1033- 1043. DOI: 10.1111/liv.14041. [4] EUropean Association for the Study of the Liver. EASL recommendations on treatment of hepatitis C: Final update of the series[J]. J Hepatol, 2020, 73( 5): 1170- 1218. DOI: 10.1016/j.jhep.2020.08.018. [5] Professional Committee for Prevention and Control of Hepatobiliary and Pancreatic Diseases of Chinese Preventive Medicine Association; Professional Committee for Hepatology, Chinese Research Hospital Association; Chinese Society of Hepatology, Chinese Medical Association, et al. Guideline for stratified screening and surveillance of primary liver cancer(2020 edition)[J]. J Clin Hepatol, 2021, 37( 2): 286- 295. DOI: 10.3969/j.issn.1001-5256.2021.02.009.中华预防医学会肝胆胰疾病预防与控制专业委员会, 中国研究型医院学会肝病专业委员会, 中华医学会肝病学分会, 等. 原发性肝癌的分层筛查与监测指南(2020版)[J]. 临床肝胆病杂志, 2021, 37( 2): 286- 295. DOI: 10.3969/j.issn.1001-5256.2021.02.009. [6] JÍLKOVÁ ZM, SEIGNEURIN A, COPPARD C, et al. Circulating IL-13 is associated with de novo development of HCC in HCV-infected patients responding to direct-acting antivirals[J]. Cancers, 2020, 12( 12): 3820. DOI: 10.3390/cancers12123820. [7] HAMOIR C, HORSMANS Y, STÄRKEL P, et al. Risk of hepatocellular carcinoma and fibrosis evolution in hepatitis C patients with severe fibrosis or cirrhosis treated with direct acting antiviral agents[J]. Acta Gastroenterol Belg, 2021, 84( 1): 25- 32. DOI: 10.51821/84.1.420. [8] RAVAIOLI F, CONTI F, BRILLANTI S, et al. Hepatocellular carcinoma risk assessment by the measurement of liver stiffness variations in HCV cirrhotics treated with direct acting antivirals[J]. Dig Liver Dis, 2018, 50( 6): 573- 579. DOI: 10.1016/j.dld.2018.02.010. [9] PREVEDEN T, VERES B, RUZIC M, et al. Triglyceride-Glucose Index and Hepatic Steatosis Index for the assessment of liver steatosis in HCV patients[J]. Minerva Gastroenterol, 2023, 69( 2): 254- 260. DOI: 10.23736/S2724-5985.22.03168-0. [10] MORADPOUR D, ENGLERT C, WAKITA T, et al. Characterization of cell lines allowing tightly regulated expression of hepatitis C virus core protein[J]. Virology, 1996, 222( 1): 51- 63. DOI: 10.1006/viro.1996.0397. [11] MORIYA K, FUJIE H, SHINTANI Y, et al. The core protein of hepatitis C virus induces hepatocellular carcinoma in transgenic mice[J]. Nat Med, 1998, 4( 9): 1065- 1067. DOI: 10.1038/2053. [12] NOUREDDIN M, WONG MM, TODO T, et al. Fatty liver in hepatitis C patients post-sustained virological response with direct-acting antivirals[J]. World J Gastroenterol, 2018, 24( 11): 1269- 1277. DOI: 10.3748/wjg.v24.i11.1269. [13] PELEG N, ISSACHAR A, SNEH ARBIB O, et al. Liver steatosis is a major predictor of poor outcomes in chronic hepatitis C patients with sustained virological response[J]. J Viral Hepat, 2019, 26( 11): 1257- 1265. DOI: 10.1111/jvh.13167. [14] KANWAL F, KRAMER J, ASCH SM, et al. Risk of hepatocellular cancer in HCV patients treated with direct-acting antiviral agents[J]. Gastroenterology, 2017, 153( 4): 996- 1005. e 1. DOI: 10.1053/j.gastro.2017.06.012. [15] DEGASPERI E, D’AMBROSIO R, IAVARONE M, et al. Factors associated with increased risk of de novo or recurrent hepatocellular carcinoma in patients with cirrhosis treated with direct-acting antivirals for HCV infection[J]. Clin Gastroenterol Hepatol, 2019, 17( 6): 1183- 1191. e 7. DOI: 10.1016/j.cgh.2018.10.038. [16] LU M, LI J, RUPP LB, et al. Hepatitis C treatment failure is associated with increased risk of hepatocellular carcinoma[J]. J Viral Hepat, 2016, 23( 9): 718- 729. DOI: 10.1111/jvh.12538. [17] KUKLA M, PIOTROWSKI D, WALUGA M, et al. Insulin resistance and its consequences in chronic hepatitis C[J]. Clin Exp Hepatol, 2015, 1( 1): 17- 29. DOI: 10.5114/ceh.2015.51375. [18] KARAGOZIAN R, DERDÁK Z, BAFFY G. Obesity-associated mechanisms of hepatocarcinogenesis[J]. Metabolism, 2014, 63( 5): 607- 617. DOI: 10.1016/j.metabol.2014.01.011. [19] TSAI PC, KUO HT, HUNG CH, et al. Metformin reduces hepatocellular carcinoma incidence after successful antiviral therapy in patients with diabetes and chronic hepatitis C in Taiwan[J]. J Hepatol, 2023, 78( 2): 281- 292. DOI: 10.1016/j.jhep.2022.09.019. [20] JACOB R, PRINCE DS, KENCH C, et al. Alcohol and its associated liver carcinogenesis[J]. J Gastroenterol Hepatol, 2023, 38( 8): 1211- 1217. DOI: 10.1111/jgh.16248. [21] EL-SERAG HB, MASON AC. Risk factors for the rising rates of primary liver cancer in the United States[J]. Arch Intern Med, 2000, 160( 21): 3227. DOI: 10.1001/archinte.160.21.3227. [22] ALLEN NE, BERAL V, CASABONNE D, et al. Moderate alcohol intake and cancer incidence in women[J]. J Natl Cancer Inst, 2009, 101( 5): 296- 305. DOI: 10.1093/jnci/djn514. [23] TRÉPO E, PRADAT P, POTTHOFF A, et al. Impact of patatin-like phospholipase-3(rs738409 C>G) polymorphism on fibrosis progression and steatosis in chronic hepatitis C[J]. Hepatology, 2011, 54( 1): 60- 69. DOI: 10.1002/hep.24350. [24] BALASUS D, WAY M, FUSILLI C, et al. The association of variants in PNPLA3 and GRP78 and the risk of developing hepatocellular carcinoma in an Italian population[J]. Oncotarget, 2016, 7( 52): 86791- 86802. DOI: 10.18632/oncotarget.13558. [25] OHTA A, OGAWA E, MURATA M, et al. Impact of the PNPLA3 genotype on the risk of hepatocellular carcinoma after hepatitis C virus eradication[J]. J Med Virol, 2022, 94( 10): 5007- 5014. DOI: 10.1002/jmv.27904. [26] BURLONE ME, BELLAN M, BARBAGLIA MN, et al. HSD17B13 and other liver fat-modulating genes predict development of hepatocellular carcinoma among HCV-positive cirrhotics with and without viral clearance after DAA treatment[J]. Clin J Gastroenterol, 2022, 15( 2): 301- 309. DOI: 10.1007/s12328-021-01578-1. [27] DEGASPERI E, GALMOZZI E, PELUSI S, et al. Hepatic fat-genetic risk score predicts hepatocellular carcinoma in patients with cirrhotic HCV treated with DAAs[J]. Hepatology, 2020, 72( 6): 1912- 1923. DOI: 10.1002/hep.31500. [28] IOANNOU GN. HCC surveillance after SVR in patients with F3/F4 fibrosis[J]. J Hepatol, 2021, 74( 2): 458- 465. DOI: 10.1016/j.jhep.2020.10.016. [29] ALONSO LÓPEZ S, MANZANO ML, GEA F, et al. A model based on noninvasive markers predicts very low hepatocellular carcinoma risk after viral response in hepatitis C virus-advanced fibrosis[J]. Hepatology, 2020, 72( 6): 1924- 1934. DOI: 10.1002/hep.31588. [30] DAJTI E, MARASCO G, RAVAIOLI F, et al. Risk of hepatocellular carcinoma after HCV eradication: Determining the role of portal hypertension by measuring spleen stiffness[J]. JHEP Rep, 2021, 3( 3): 100289. DOI: 10.1016/j.jhepr.2021.100289. [31] TANI J, MORISHITA A, SAKAMOTO T, et al. Simple scoring system for prediction of hepatocellular carcinoma occurrence after hepatitis C virus eradication by direct-acting antiviral treatment: All Kagawa Liver Disease Group Study[J]. Oncol Lett, 2020, 19( 3): 2205- 2212. DOI: 10.3892/ol.2020.11341. [32] SHIHA G, WAKED I, SOLIMAN R, et al. GES: A validated simple score to predict the risk of HCC in patients with HCV-GT4-associated advanced liver fibrosis after oral antivirals[J]. Liver Int, 2020, 40( 11): 2828- 2833. DOI: 10.1111/liv.14666. [33] IOANNOU GN, GREEN PK, BESTE LA, et al. Development of models estimating the risk of hepatocellular carcinoma after antiviral treatment for hepatitis C[J]. J Hepatol, 2018, 69( 5): 1088- 1098. DOI: 10.1016/j.jhep.2018.07.024. [34] FAN R, PAPATHEODORIDIS G, SUN J, et al. aMAP risk score predicts hepatocellular carcinoma development in patients with chronic hepatitis[J]. J Hepatol, 2020, 73( 6): 1368- 1378. DOI: 10.1016/j.jhep.2020.07.025. [35] QIU LX, XU SS, QIU YD, et al. Comparison of acknowledged hepatocellular carcinoma risk scores in high-risk hepatitis C patients with sustained virological response[J]. J Viral Hepat, 2023, 30( 6): 559- 566. DOI: 10.1111/jvh.13829. [36] NAHON P, BAMBA-FUNCK J, LAYESE R, et al. Integrating genetic variants into clinical models for hepatocellular carcinoma risk stratification in cirrhosis[J]. J Hepatol, 2023, 78( 3): 584- 595. DOI: 10.1016/j.jhep.2022.11.003. [37] IOANNOU GN, TANG WJ, BESTE LA, et al. Assessment of a deep learning model to predict hepatocellular carcinoma in patients with hepatitis C cirrhosis[J]. JAMA Netw Open, 2020, 3( 9): e2015626. DOI: 10.1001/jamanetworkopen.2020.15626. 期刊类型引用(1)
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