FIB-4预测慢性肝病患者肝细胞癌风险的meta分析

doi:10.3969/j.issn.1004-583X.2022.09.002

摘要/Abstract

摘要：

目的系统评价FIB-4预测慢性肝病患者出现肝细胞癌的价值。方法检索PubMed、Web of Science、中国知网和万方数据库中有关FIB-4预测慢性肝病患者肝细胞癌风险的文献,并根据纳入和排除标准筛选,利用RevMan 5.3软件进行统计分析。结果共纳入文献35篇,包含肝细胞癌患者94 569例。Meta分析结果显示:慢性肝病患者基线高FIB-4(HR=1.57, 95%CI: 1.41-1.75, P<0.01)及抗病毒治疗后高FIB-4(HR=2.40, 95%CI: 1.74-3.32, P<0.01)与慢性乙肝或慢性丙肝患者的高肝细胞癌风险有关。结论 FIB-4可预测慢性肝病患者的肝细胞癌风险。

关键词: FIB-4, 癌, 肝细胞, 慢性肝病, meta分析

Abstract:

Objective To systematically evaluate the value of fibrosis-4 (FIB-4) in predicting future hepatocellular carcinoma (HCC) in patients with chronic liver disease (CLD).Methods We searched PubMed, Web of Science, Wan-fang and CNKI databases for relevant literatures of FIB-4 predicting HCC risk in CLD patients, and selected eligible literatures according to the including and excluding criteria. Revman 5.3 software was used to perform statistical analyses.Results A total of 35 articles with 94, 569 CLD patients were included. Meta-analysis results showed that high baseline FIB-4 predicted high HCC risk in CLD patients (HR=1.57, 95%CI: 1.41-1.75, P<0.01). Post-treatment high FIB-4 (HR=2.40, 95%CI: 1.74-3.32, P<0.01) was associated with high risk of future HCC in patients with chronic hepatitis B or hepatitis C virus. Conclusion FIB-4 is useful in predicting future HCC in CLD patients.

Key words: FIB-4, carcinoma, hepatocellular, chronic liver disease, meta-analysis

中图分类号:

R730.261

贺超, 黄邵斌. FIB-4预测慢性肝病患者肝细胞癌风险的meta分析[J]. 临床荟萃, 2022, 37(9): 779-784.

He Chao, Huang Shaobin. Predicting the risk by FIB-4 on hepatocellular carcinoma in patients with chronic liver disease: A meta-analysis[J]. Clinical Focus, 2022, 37(9): 779-784.

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链接本文: https://huicui.hebmu.edu.cn/CN/10.3969/j.issn.1004-583X.2022.09.002

https://huicui.hebmu.edu.cn/CN/Y2022/V37/I9/779

图/表 5

参考文献 55

[1]	Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. doi: 10.3322/caac.21660 URL
[2]	Villanueva A. Hepatocellular carcinoma[J]. N Engl J Med, 2019, 380(15): 1450-1462. doi: 10.1056/NEJMra1713263 URL
[3]	Llovet JM, Kelley RK, Villanueva A, et al. Hepatocellular carcinoma[J]. Nat Rev Dis Primers, 2021, 7(1): 6. doi: 10.1038/s41572-020-00240-3 pmid: 33479224
[4]	Collaborators GHB. Global, regional, and national burden of hepatitis B, 1990-2019: A systematic analysis for the Global Burden of Disease Study 2019[J]. Lancet Gastroenterol Hepatol, 2022, 7(9): 796-829. doi: 10.1016/S2468-1253(22)00124-8 URL
[5]	Collaborators POH. Global change in hepatitis C virus prevalence and cascade of care between 2015 and 2020: A modelling study[J]. Lancet Gastroenterol Hepatol, 2022, 7(5): 396-415. doi: 10.1016/S2468-1253(21)00472-6 URL
[6]	Spearman CW, Dusheiko GM, Hellard M, et al. Hepatitis C[J]. Lancet, 2019, 394(10207): 1451-1466. doi: S0140-6736(19)32320-7 pmid: 31631857
[7]	Powell EE, Wong VW, Rinella M. Non-alcoholic fatty liver disease[J]. Lancet, 2021, 397(10290): 2212-2224. doi: 10.1016/S0140-6736(20)32511-3 pmid: 33894145
[8]	Estes C, Anstee QM, Arias-Loste MT, et al. Modeling NAFLD disease burden in China, France, Germany, Italy, Japan, Spain, United Kingdom, and United States for the period 2016-2030[J]. J Hepatol, 2018, 69(4): 896-904. doi: S0168-8278(18)32121-4 pmid: 29886156
[9]	Asrani SK, Mellinger J, Arab JP, et al. Reducing the global burden of alcohol-associated liver disease: A blueprint for action[J]. Hepatology, 2021, 73(5): 2039-2050. doi: 10.1002/hep.31583 URL
[10]	Regev A, Berho M, Jeffers LJ, et al. Sampling error and intraobserver variation in liver biopsy in patients with chronic HCV infection[J]. Am J Gastroenterol, 2002, 97(10): 2614-2618. pmid: 12385448
[11]	Sterling RK, Lissen E, Clumeck N, et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection[J]. Hepatology, 2006, 43(6): 1317-1325. pmid: 16729309
[12]	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 pmid: 33022803
[13]	Xiao G, Zhu S, Xiao X, et al. Comparison of laboratory tests, ultrasound, or magnetic resonance elastography to detect fibrosis in patients with nonalcoholic fatty liver disease: A meta-analysis[J]. Hepatology, 2017, 66(5): 1486-1501. doi: 10.1002/hep.29302 pmid: 28586172
[14]	Wang HW, Peng CY, Lai HC, et al. New noninvasive index for predicting liver fibrosis in Asian patients with chronic viral hepatitis[J]. Sci Rep, 2017, 7(1): 3259. doi: 10.1038/s41598-017-03589-w URL
[15]	Demir M, Grünewald F, Lang S, et al. Elevated liver fibrosis index FIB-4 is not reliable for HCC risk stratification in predominantly non-Asian CHB patients[J]. Medicine (Baltimore), 2016, 95(38): e4602. doi: 10.1097/MD.0000000000004602 URL
[16]	Suh B, Yun JM, Park S, et al. Prediction of future hepatocellular carcinoma incidence in moderate to heavy alcohol drinkers with the FIB-4 liver fibrosis index[J]. Cancer, 2015, 121(21): 3818-3125. doi: 10.1002/cncr.29577 pmid: 26178294
[17]	Jeong J, Shin JW, Jung SW, et al. Clinical usefulness of noninvasive fibrosis indices for predicting hepatocellular carcinoma in treatment-naïve patients with chronic hepatitis B following entecavir therapy[J]. Hepatol Res, 2021, 51(9): 923-932. doi: 10.1111/hepr.13690 URL
[18]	Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses[J]. Eur J Epidemiol, 2010, 25(9): 603-605. doi: 10.1007/s10654-010-9491-z pmid: 20652370
[19]	Chu PS, Nakamoto N, Taniki N, et al. On-treatment decrease of NKG2D correlates to early emergence of clinically evident hepatocellular carcinoma after interferon-free therapy for chronic hepatitis C[J]. PLoS One, 2017, 12(6): e0179096. doi: 10.1371/journal.pone.0179096 URL
[20]	Degasperi E, Galmozzi E, Facchetti F, et al. TLL1 variants do not predict hepatocellular carcinoma development in HCV cirrhotic patients treated with direct-acting antivirals[J]. J Viral Hepat, 2019, 26(10): 1233-1236. doi: 10.1111/jvh.13155 URL
[21]	Fusco M, Piselli P, Virdone S, et al. Infection with hepatitis viruses, FIB-4 index and risk of hepatocellular carcinoma in southern Italy: A population-based cohort study[J]. Infect Agent Cancer, 2016, 11: 54. doi: 10.1186/s13027-016-0101-x URL
[22]	Honda M, Shirasaki T, Terashima T, et al. Hepatitis B virus (HBV) core-related antigen during nucleos(t)ide analog therapy is related to intra-hepatic HBV replication and development of hepatocellular carcinoma[J]. J Infect Dis, 2016, 213(7): 1096-1106. doi: 10.1093/infdis/jiv572 pmid: 26621908
[23]	Huang CM, Hu TH, Chang KC, et al. Dynamic noninvasive markers predict hepatocellular carcinoma in chronic hepatitis C patients without sustained virological response after interferon-based therapy: Prioritize who needs urgent direct-acting antiviral agents[J]. Medicine (Baltimore), 2017, 96(46): e8696. doi: 10.1097/MD.0000000000008696 URL
[24]	Iio E, Matsuura K, Shimada N, et al. TLL1 variant associated with development of hepatocellular carcinoma after eradication of hepatitis C virus by interferon-free therapy[J]. J Gastroenterol, 2019, 54(4): 339-346. doi: 10.1007/s00535-018-1526-3 pmid: 30382363
[25]	Ioannou GN, Beste LA, Green PK, et al. Increased risk for hepatocellular carcinoma persists up to 10 years after HCV eradication in patients with baseline cirrhosis or high FIB-4 scores[J]. Gastroenterology, 2019, 157(5): 1264-1278.e4. doi: S0016-5085(19)41130-X pmid: 31356807
[26]	Ito T, Kumada T, Toyoda H, et al. Utility of the FIB-4 Index for hepatocarcinogenesis in hepatitis C virus carriers with normal alanine aminotransferase levels[J]. J Viral Hepat, 2015, 22(10): 777-783. doi: 10.1111/jvh.12389 URL
[27]	Kim JH, Kim JW, Seo JW, et al. Noninvasive tests for fibrosis predict 5-year mortality and hepatocellular carcinoma in patients with chronic hepatitis B[J]. J Clin Gastroenterol, 2016, 50(10): 882-888. pmid: 27322532
[28]	Kim JH, Lee M, Park SW, et al. Validation of modified fibrosis-4 index for predicting hepatocellular carcinoma in patients with compensated alcoholic liver cirrhosis[J]. Medicine (Baltimore), 2018, 97(48): e13438. doi: 10.1097/MD.0000000000013438 URL
[29]	Kim M, Lee Y, Yoon JS, et al. The FIB-4 index is a useful predictor for the development of hepatocellular carcinoma in patients with coexisting nonalcoholic fatty liver disease and chronic hepatitis B[J]. Cancers (Basel), 2021, 13(10): 2301. doi: 10.3390/cancers13102301 URL
[30]	Kobayashi M, Suzuki F, Fujiyama S, et al. Sustained virologic response by direct antiviral agents reduces the incidence of hepatocellular carcinoma in patients with HCV infection[J]. J Med Virol, 2017, 89(3): 476-483. doi: 10.1002/jmv.24663 pmid: 27531586
[31]	Kuetting F, Lang S, Schramm C, et al. FIB-4 is a potential tool for hepatocellular carcinoma risk stratification in ethnically diverse chronic hepatitis B patients when using specific cutoff values[J]. Hepatitis Monthly, 2019, 19(12): e94574.
[32]	Kumada T, Toyoda H, Yasuda S, et al. Usefulness of serial FIB-4 score measurement for predicting the risk of hepatocarcinogenesis after hepatitis C virus eradication[J]. Eur J Gastroenterol Hepatol, 2021, 33(1S Suppl 1): e513-e521. doi: 10.1097/MEG.0000000000002139 URL
[33]	Liang LY, Lee HW, Wong VW, et al. Serum fibrosis index-based risk score predicts hepatocellular carcinoma in untreated patients with chronic hepatitis B[J]. Clin Mol Hepatol, 2021, 27(3): 499-509. doi: 10.3350/cmh.2020.0333 pmid: 33631920
[34]	Lim TS, Lee HW, Lee JI, et al. Predictive score for hepatocellular carcinoma after hepatitis B e antigen loss in patients treated with entecavir or tenofovir[J]. J Viral Hepat, 2020, 27(10): 1052-1060. doi: 10.1111/jvh.13316 URL
[35]	Liu CJ, Tseng TC, Yang WT, et al. Profile and value of FIB-4 in patients with dual chronic hepatitis C and B[J]. J Gastroenterol Hepatol, 2019, 34(2): 410-417. doi: 10.1111/jgh.14455 URL
[36]	Morimoto N, Miura K, Watanabe S, et al. Usefulness of Gd-EOB-DTPA-enhanced MRI for evaluating the potential for early development of hepatocellular carcinoma after HCV eradication by direct-acting antiviral treatment[J]. J Rural Med, 2019, 14(1): 78-86. doi: 10.2185/jrm.2993 pmid: 31191770
[37]	Na SK, Lee SJ, Cho YK, et al. Aspartate aminotransferase-to-platelet ratio or fibros-4 index predicts the development of hepatocellular carcinoma in chronic hepatitis C patients with sustained virologic response to interferon therapy[J]. J Interferon Cytokine Res, 2019, 39(11): 703-710. doi: 10.1089/jir.2019.0049 URL
[38]	Nishikawa H, Nishijima N, Enomoto H, et al. Comparison of FIB-4 index and aspartate aminotransferase to platelet ratio index on carcinogenesis in chronic hepatitis B treated with entecavir[J]. J Cancer, 2017, 8(2): 152-161. doi: 10.7150/jca.16523 pmid: 28243319
[39]	Ogawa E, Takayama K, Hiramine S, et al. Association between steatohepatitis biomarkers and hepatocellular carcinoma after hepatitis C elimination[J]. Aliment Pharmacol Ther, 2020, 52(5): 866-876. doi: 10.1111/apt.15976 URL
[40]	Park YE, Kim BK, Park JY, et al. Gamma-glutamyl transpeptidase-to-platelet ratio is an independent predictor of hepatitis B virus-related liver cancer[J]. J Gastroenterol Hepatol, 2017, 32(6): 1221-1229. doi: 10.1111/jgh.13653 URL
[41]	Patel J, Yopp A, Waljee AK, et al. Development and internal validation of a model for early detection of hepatocellular carcinoma in patients with cirrhosis[J]. J Clin Gastroenterol, 2016, 50(2): 175-179. doi: 10.1097/MCG.0000000000000377 pmid: 26125462
[42]	Sato S, Genda T, Ichida T, et al. Prediction of hepatocellular carcinoma development after hepatitis C virus eradication using serum wisteria floribunda agglutinin-positive mac-2-binding protein[J]. Int J Mol Sci, 2016, 17(12): 2143. doi: 10.3390/ijms17122143 URL
[43]	Song BG, Sinn DH, Chi S, et al. Additional role of liver stiffness measurement in stratifying residual hepatocellular carcinoma risk predicted by serum biomarkers in chronic hepatitis B patients under antiviral therapy[J]. Eur J Gastroenterol Hepatol, 2018, 30(12): 1447-1452. doi: 10.1097/MEG.0000000000001226 URL
[44]	Sou FM, Hu TH, Hung CH, et al. Incidence and predictors of hepatocellular carcinoma beyond year 5 of entecavir therapy in chronic hepatitis B patients[J]. Hepatol Int, 2020, 14(4): 513-520. doi: 10.1007/s12072-020-10031-3 URL
[45]	Suh B, Park S, Shin DW, et al. High liver fibrosis index FIB-4 is highly predictive of hepatocellular carcinoma in chronic hepatitis B carriers[J]. Hepatology, 2015, 61(4): 1261-1268. doi: 10.1002/hep.27654 pmid: 25502481
[46]	Tada T, Kumada T, Toyoda H, et al. Impact of FIB-4 index on hepatocellular carcinoma incidence during nucleos(t)ide analogue therapy in patients with chronic hepatitis B: An analysis using time-dependent receiver operating characteristic[J]. J Gastroenterol Hepatol, 2017, 32(2): 451-458. doi: 10.1111/jgh.13473 URL
[47]	Tamaki N, Kurosaki M, Matsuda S, et al. Non-invasive prediction of hepatocellular carcinoma development using serum fibrosis marker in chronic hepatitis C patients[J]. J Gastroenterol, 2014, 49(11): 1495-1503. doi: 10.1007/s00535-013-0914-y pmid: 24337828
[48]	Tseng TC, Choi J, Nguyen MH, et al. One-year fibrosis-4 index helps identify minimal HCC risk in non-cirrhotic chronic hepatitis B patients with antiviral treatment[J]. Hepatol Int, 2021, 15(1): 105-113. doi: 10.1007/s12072-020-10124-z URL
[49]	Wang HW, Lai HC, Hu TH, et al. On-treatment changes in FIB-4 and 1-year FIB-4 values help identify patients with chronic hepatitis B receiving entecavir therapy who have the lowest risk of hepatocellular carcinoma[J]. Cancers (Basel), 2020, 12(5): 1177-1192. doi: 10.3390/cancers12051177 URL
[50]	Watanabe T, Tokumoto Y, Joko K, et al. Predictors of hepatocellular carcinoma occurrence after direct-acting antiviral therapy in patients with hepatitis C virus infection[J]. Hepatol Res, 2019, 49(2): 136-146. doi: 10.1111/hepr.13278 pmid: 30335208
[51]	Zhang Y, Wang R, Yang X. FIB-4 index serves as a noninvasive prognostic biomarker in patients with hepatocellular carcinoma: A meta-analysis[J]. Medicine (Baltimore), 2018, 97(51): e13696. doi: 10.1097/MD.0000000000013696 URL
[52]	Patten DA, Shetty S. Chronic liver disease: scavenger hunt for novel therapies[J]. Lancet, 2018, 391(10116): 104-105. doi: S0140-6736(17)32671-5 pmid: 29353605
[53]	Dong B, Lyu G, Chen Y, et al. Comparison of two-dimensional shear wave elastography, magnetic resonance elastography, and three serum markers for diagnosing fibrosis in patients with chronic hepatitis B: A meta-analysis[J]. Expert Rev Gastroenterol Hepatol, 2021, 15(9): 1077-1089. doi: 10.1080/17474124.2021.1880894 URL
[54]	Xiao G, Yang J, Yan L. Comparison of diagnostic accuracy of aspartate aminotransferase to platelet ratio index and fibrosis-4 index for detecting liver fibrosis in adult patients with chronic hepatitis B virus infection: A systemic review and meta-analysis[J]. Hepatology, 2015, 61(1): 292-302. doi: 10.1002/hep.27382 pmid: 25132233
[55]	Li X, Xu H, Gao P. Fibrosis index based on 4 factors (FIB-4) predicts liver cirrhosis and hepatocellular carcinoma in chronic hepatitis C virus (HCV) patients[J]. Med Sci Monit, 2019, 25: 7243-7250. doi: 10.12659/MSM.918784 URL

第一作者,发表年	例数	慢性肝病分类	国家	截断值	NOS 评分
Alonso López, 2020^[12]	993	HCV	西班牙	-	8
Demir, 2016^[15]	373	HBV	德国	1.25	7
Jeong, 2021^[17]	857	HBV	韩国	-	8
Chu, 2017^[19]	101	HCV	日本	-	7
Degasperi, 2019^[20]	452	HCV	意大利	-	6
Fusco, 2016^[21]	4 492	HCV/HBV	意大利	3.25	7
Honda, 2016^[22]	109	HBV	日本	2.1	8
Huang, 2017^[23]	552	HCV	中国	3.25	8
Iio, 2019^[24]	1416	HCV	日本	2.67	8
Ioannou, 2019^[25]	48 135	HCV	美国	3.25	7
Ito, 2015^[26]	516	HCV	日本	4	8
Kim, 2016^[27]	542	HBV	韩国	2.225	7
Kim, 2018^[28]	924	酒精性肝硬化	韩国	3.25	8
Kim, 2021^[29]	237	NAFLD&HBV	韩国	1.77	9
Kobayashi, 2017^[30]	605	HCV	日本	3.25	8
Kuetting, 2019^[31]	350	HBV	德国	0.3635	7
Kumada, 2021^[32]	717	HCV	日本	1.5	8
Liang, 2021^[33]	15 187	HBV	中国	3.25	8
Lim, 2020^[34]	769	HBV	韩国	3.25	8
Liu, 2019^[35]	152	HBV&HCV	中国	-	8
Morimoto, 2019^[36]	518	HCV	日本	4	8
Na, 2019^[37]	295	HCV	韩国	3.25	8
Nishikawa, 2017^[38]	338	HBV	日本	3.666	8
Ogawa,2020^[39]	290	HCV	日本	3.25	8
Park, 2017^[40]	1 109	HBV	韩国	-	8
Patel, 2016^[41]	1 356	肝硬化	美国	无	6
Sato, 2016^[42]	355	HCV	日本	3.7	8
Song, 2018^[43]	1 014	HBV	韩国	1.45	7
Sou,2020^[44]	1 397	HBV	中国	-	8
Suh, 2015^[45]	986	HBV	韩国	2.4	7
Tada, 2017^[46]	539	HBV	日本	2.65	8
Tamaki, 2014^[47]	3 823	HCV	日本	3.25	7
Tseng, 2021^[48]	1 936	HBV	中国	1.3	8
Wang, 2020^[49]	1 325	HBV	中国	2.56	8
Watanabe, 2019^[50]	1 174	HCV	日本	-	8

第一作者,发表年	例数	慢性肝病分类	国家	截断值	NOS 评分
Alonso López, 2020^[12]	993	HCV	西班牙	-	8
Demir, 2016^[15]	373	HBV	德国	1.25	7
Jeong, 2021^[17]	857	HBV	韩国	-	8
Chu, 2017^[19]	101	HCV	日本	-	7
Degasperi, 2019^[20]	452	HCV	意大利	-	6
Fusco, 2016^[21]	4 492	HCV/HBV	意大利	3.25	7
Honda, 2016^[22]	109	HBV	日本	2.1	8
Huang, 2017^[23]	552	HCV	中国	3.25	8
Iio, 2019^[24]	1416	HCV	日本	2.67	8
Ioannou, 2019^[25]	48 135	HCV	美国	3.25	7
Ito, 2015^[26]	516	HCV	日本	4	8
Kim, 2016^[27]	542	HBV	韩国	2.225	7
Kim, 2018^[28]	924	酒精性肝硬化	韩国	3.25	8
Kim, 2021^[29]	237	NAFLD&HBV	韩国	1.77	9
Kobayashi, 2017^[30]	605	HCV	日本	3.25	8
Kuetting, 2019^[31]	350	HBV	德国	0.3635	7
Kumada, 2021^[32]	717	HCV	日本	1.5	8
Liang, 2021^[33]	15 187	HBV	中国	3.25	8
Lim, 2020^[34]	769	HBV	韩国	3.25	8
Liu, 2019^[35]	152	HBV&HCV	中国	-	8
Morimoto, 2019^[36]	518	HCV	日本	4	8
Na, 2019^[37]	295	HCV	韩国	3.25	8
Nishikawa, 2017^[38]	338	HBV	日本	3.666	8
Ogawa,2020^[39]	290	HCV	日本	3.25	8
Park, 2017^[40]	1 109	HBV	韩国	-	8
Patel, 2016^[41]	1 356	肝硬化	美国	无	6
Sato, 2016^[42]	355	HCV	日本	3.7	8
Song, 2018^[43]	1 014	HBV	韩国	1.45	7
Sou,2020^[44]	1 397	HBV	中国	-	8
Suh, 2015^[45]	986	HBV	韩国	2.4	7
Tada, 2017^[46]	539	HBV	日本	2.65	8
Tamaki, 2014^[47]	3 823	HCV	日本	3.25	7
Tseng, 2021^[48]	1 936	HBV	中国	1.3	8
Wang, 2020^[49]	1 325	HBV	中国	2.56	8
Watanabe, 2019^[50]	1 174	HCV	日本	-	8