Literature DB >> 28376711

Impact of antiviral therapy on hepatocellular carcinoma and mortality in patients with chronic hepatitis C: systematic review and meta-analysis.

Chang Seok Bang1, Il Han Song2.   

Abstract

BACKGROUND: The long-term clinical outcomes of antiviral therapy for patients with chronic hepatitis C are uncertain in terms of hepatitis C virus (HCV)-related morbidity and mortality according to the response to antiviral therapy. This study aimed to assess the impact of antiviral treatment on the development of HCC and mortality in patients with chronic HCV infection.
METHODS: A systematic review was conducted for studies that evaluated the antiviral efficacy for patients with chronic hepatitis C or assessed the development of HCC or mortality between SVR (sustained virologic response) and non-SVR patients. The methodological quality of the enrolled publications was evaluated using Risk of Bias table or Newcastle-Ottawa scale. Random-effect model meta-analyses and meta-regression were performed. Publication bias was assessed.
RESULTS: In total, 59 studies (4 RCTs, 15 prospective and 40 retrospective cohort studies) were included. Antiviral treatment was associated with reduced development of HCC (vs. no treatment; OR 0.392, 95% CI 0.275-0.557), and this effect was intensified when SVR was achieved (vs. no SVR, OR: 0.203, 95% CI 0.164-0.251). Antiviral treatment was associated with lower all-cause mortality (vs. no treatment; OR 0.380, 95% CI 0.295-0.489) and liver-specific mortality (OR 0.363, 95% CI 0.260-0.508). This rate was also intensified when SVR was achieved [all-cause mortality (vs. no SVR, OR 0.255, 95% CI 0.199-0.326), liver-specific mortality (OR 0.126, 95% CI 0.094-0.169)]. Sensitivity analyses revealed robust results, and a small study effect was minimal.
CONCLUSIONS: In patients with chronic hepatitis C, antiviral therapy can reduce the development of HCC and mortality, especially when SVR is achieved.

Entities:  

Keywords:  Antiviral therapy; Chronic hepatitis C; Hepatocellular carcinoma; Mortality; Sustained virologic response

Mesh:

Substances:

Year:  2017        PMID: 28376711      PMCID: PMC5379714          DOI: 10.1186/s12876-017-0606-9

Source DB:  PubMed          Journal:  BMC Gastroenterol        ISSN: 1471-230X            Impact factor:   3.067


Background

Antiviral treatment for chronic hepatitis C (CHC) aims to prevent hepatitis C virus (HCV)-related morbidity and mortality, including complications of liver fibrosis or cirrhosis and the development of hepatocellular carcinoma (HCC). Treatment reduces the degree of necroinflammation of the liver and induces regression of hepatic fibrosis [1]. Although direct-acting antivirals have recently emerged as a promising therapy, conventional interferon (IFN) or pegylated IFN (PegIFN) with or without ribavirin (RBV) has been used as the standard treatment for curing HCV. A sustained virologic response (SVR) is the surrogate indicator for eradicating HCV and is considered to be “cure” [2]. SVR24 or SVR12, which is the state of undetectable HCV RNA in a sensitive assay with a lower limit of detection <50 IU/mL at week 24 or 12 after the end of treatment are accepted as an endpoint of treatment [3]. The evolution of CHC is slow, and there is no specific symptom before progression to liver fibrosis. Due to delayed diagnosis of HCV-related chronic liver disease such as chronic hepatitis or liver fibrosis, it is difficult to start an anitviral treatment in the early stage of the disease. Previous study has demonstrated an achievement of SVR was associated with less risk for mortality (risk ratio 0.16) and development of HCC (risk ratio 0.37) [4]. However, the majority of studies assessed short-term prognosis and the long-term clinical outcomes of antiviral therapy for patients with chronic hepatitis C are uncertain in terms of HCV-related morbidity and mortality, including disease progression to advanced hepatic fibrosis or cirrhosis, hepatic decompensation, HCC, and liver-specific death, especially according to the response to antiviral therapy. Moreover, viral replication of HCV is not known to be directly related to HCC development [4]. The aim of this study was to assess the impact of antiviral treatment on the development of HCC and mortality in patients with CHC.

Methods

This systematic review and meta-analysis fully adhered to the principle of PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) checklist.

Literature searching strategy

PubMed, Embase, and the Cochrane Library were searched using common keywords associated with chronic hepatitis C, HCC, or SVR (from inception to April 2016) by 2 independent evaluators (C.S.B. and Y.J.Y.). Medical Subject Headings (MeSH) or Emtree keywords were selected for searching of electronic databases. The keywords included ‘hepatitis C’, ‘HCV’, ‘hepatocellular carcinoma’, ‘HCC’, ‘sustained virologic response’, ‘SVR’ and ‘mortality’. These keywords were combined for a searching strategy using Boolean operators. The abstracts of all identified studies were reviewed to exclude irrelevant articles. Full-text reviews were performed to determine whether the inclusion criteria were satisfied by the remaining studies and the bibliographies of relevant articles were reviewed to identify additional studies. Disagreements between the evaluators were resolved by discussion or consultation with a third evaluator (I.H.S.). The detailed searching strategy is described in Table 1.
Table 1

Clinical data of included studies

1. PubMed
1. Hepatitis C[Mesh] OR HCV2. HCC OR “hepatocellular carcinoma”3. SVR OR “sustained virologic response”4. Mortality(#1 AND #2) OR (#1 AND #3) OR (#1 AND #4) - > removed duplicated articles
2. Embase
1. (hepatitis C or hcv).mp2. (hcc or hepatocellular carcinoma).mp3. (svr or sustained virologic reponse).mp4. mortalityAfter accumulation of (1 and 2), (1 and 3), and (1 and 4), and then removed duplicated articles
3. Cochrane library
1. Hepatitis C OR HCV2. HCC OR “hepatocellular carcinoma”3. SVR OR “sustained virologic response”4. Mortality(#1 AND #2) OR (#1 AND #3) OR (#1 AND #4) - > removed duplicated articles
Clinical data of included studies

Selection criteria

We included randomized or non-randomized studies that met the following criteria: 1. Study designed to evaluate the efficacy of antiviral treatment on the development of HCC or mortality in CHC patients and a control group, or in CHC patients with SVR and the no SVR group; 2. Publications on human subjects; 3. Full-text publication; and 4. English language. Studies that met the all of the inclusion criteria were sought and selected. The exclusion criteria were as follows: 1. Incomplete data; 2. Review article; 3. Animal study; 4. Letter or case article; or 5. Abstract only publication. Studies meeting at least 1 of the exclusion criteria were excluded from this analysis.

Methodological quality

The methodological quality of the enrolled publications was assessed using the Risk of Bias table for randomized studies and the Newcastle-Ottawa Scale for non-randomized studies. The Risk of Bias was assessed as described in the Cochrane handbook by recording the method used to generate the randomization sequence, allocation concealment, determination of whether blinding was implemented for participants or staff, and evidence of selective reporting of the outcomes [5]. Review Manager version 5.3.3 (Revman for Windows 7, the Nordic Cochrane Centre, Copenhagen, Denmark) was used to generate the Risk of Bias table. The Newcastle-Ottawa scale is categorized into three parameters: the selection of the study population, the comparability of the groups, and the ascertainment of the exposure or outcome. Each parameter consists of subcategorized questions: selection (n = 4), comparability (n = 1), and exposure or outcome (n = 3) [6, 7]. Stars that are awarded for each item serve as a quick visual assessment of the methodological quality of the studies. A study can be graded a maximum of 9 stars, which indicates the highest quality. Two of the evaluators (C.S.B. and Y.J.Y.) independently assessed the methodological quality of all studies, and any disagreements between the evaluators were resolved by discussion or consultation with a third evaluator (I.H.S.).

Primary and modifier-based analyses

The following questions were primary topic of this meta-analyses: In patients with CHC, 1. Does the antiviral treatment reduce the development of HCC? 2. Does the antiviral treatment reduce all-cause or 3. liver-specific mortality? 4. Does the achievement of SVR reduce the development of HCC? 5. Does the achievement of SVR reduce all-cause or 6. liver-specific mortality? The analysis was performed as 6 distinct meta-analyses to answer the 6 questions described above. Two evaluators (C.S.B. and Y.J.Y.) independently used the same data fill-up form to collect the primary summary outcome and modifiers in each study. The outcome was the relative rate of the development of HCC or mortality between antiviral treatment and the control groups, or the SVR and no SVR groups. These ratios were extracted and evaluated by odds ratios (ORs). Sensitivity analyses, including cumulative and one study removed analyses were performed to confirm the robustness of the main analysis results. These analyses were calculated in the order of publication year or effect size to find whether the time trend exists or which study is more or less influential in the pooled estimate. We also performed a meta-ANOVA and meta-regression to identify the reason of heterogeneity based on the multiple modifiers identified during systematic review. These reasons include study format (randomized/prospective cohort/retrospective cohort study), nationality, histology (degree of liver fibrosis), follow-up duration, Newcastle-Ottawa scale, age, and the regimen of the treatment (IFN, IFN with RBV, PegIFN with or without RBV). The follow-up duration of each study was categorized as long-term (≥5 years) or short-term (<5 years).

Statistics

Comprehensive Meta-Analysis software (version 3, Biostat; Borenstein M, Hedges L, Higgins J and Rothstein H. Englewood, NJ, USA) was used for this meta-analysis. We calculated the ORs with 95% confidence intervals (CIs) using 2 × 2 tables from the original articles to evaluate the efficacy of antiviral treatment between the treatment and control groups, or the SVR and no SVR groups whenever possible. Heterogeneity was determined using the I test developed by Higgins, which measures the percentage of total variation across studies [8]. I was calculated as follows: I (%) = 100 × (Q-df)/Q, where Q is Cochrane’s heterogeneity statistic and df signifies the degree of freedom. Negative values for I were set to zero, and an I value over 50% was considered to be of substantial heterogeneity (range: 0–100%) [9]. Pooled-effect sizes with 95% CIs were calculated using a random effects model and the method of DerSimonian and Laird due to methodological heterogeneity [10]. These results were confirmed by the I test. Significance was set at p = 0.05. Publication bias was evaluated using Begg’s funnel plot, Egger’s test of the intercept, Begg and Mazumdar’s rank correlation test, and Duval and Tweedie’s trim and fill method [11-15].

Results

Identification of relevant studies

Figure 1 presents a flow diagram of how relevant studies were identified. In total, 36,421 articles were identified by a search of 3 databases. In all, 7451 duplicate studies and an additional 28,481 studies were excluded during the initial screening through a review of the titles and abstracts. The full texts of the remaining 489 studies were then thoroughly reviewed. Among these studies, 431 articles were excluded from the final analysis. The reasons for study exclusion during the final review were as follows: review article (n = 12), incomplete data (n = 7), not meeting the inclusion criteria (n = 409), or abstract only study (n = 3). The remaining 58 studies [4 randomized controlled studies (RCTs), 15 prospective cohort, and 40 retrospective cohort studies] were included in the final analysis.
Fig. 1

Flow diagram for identification of relevant studies

Flow diagram for identification of relevant studies

Characteristics of included studies

In each study topic, about 13–35 studies were enrolled. In terms of the study format, RCTs, prospective and retrospective cohort studies were mixed. The number of Western population-based studies and the number of Asian population-based studies were evenly distributed. The age of enrolled patients ranged from 37 to 64 years (median). The follow-up duration ranged from 32 months (mean) to 11.5 years (median). Most of the studies used IFN-based regimens with or without RBV in topic 1, 2 and 3. However, a PegIFN-based regimen and IFN-based regimens were evenly distributed in topic 4, 5, and 6. Underlying histology of liver was variable, but some studies exclusively assessing liver cirrhosis patients were included. The detailed characteristics of the included studies are described in Tables 2, 3, 4, 5, and 6.
Table 2

Clinical data summary of all included studies

TopicNumber of enrolled studies and populationStudy formatNationalityAgeFollow-up durationTreatment regimenHistology
Topic 125 studies (9691 treated vs. 6010 control)3 RCTs8 prospective cohort studies14 retrospective cohort studies15 Western population-based studies10 Asian population-based studies37 to 61 years (median)32 months to 10 years (mean)IFN-based regimens with or without RBV, except 4 studies with a PegIFN-based regimen10 studies exclusively assessing LC patients)
Topic 217 studies (9868 treated vs. 4700 controls)1 RCT5 prospective cohort studies11 retrospective cohort studies8 Western population-based studies9 Asian population-based studies37 to 61 years (median)55 months to 11.5 years (median)IFN-based regimen with or without RBV, except 3 studies with a PegIFN-based regimen3 studies exclusively assessing LC patients
Topic 313 studies (8671 treated vs. 2831 controls)5 prospective cohort studies8 retrospective cohort studies5 Western population-based studies8 Asian population-based studies37 to 61 years (median)55 months to 11.5 years (median)IFN-based regimen with or without RBV, except 2 studies with a PegIFN-based regimen4 studies exclusively assessing LC patients
Topic 435 studies (14756 patients with SVR vs. 12741 patients with no SVR)1 RCT8 prospective cohort studies26 retrospective cohort studies17 Western population-based studies17 Asian population-based studies1 Saudi Arabia and Egypt population-based study37 to 64 years (median)2.1 (median) to 10 years (mean)20 studies with PegIFN-based regimen15 studies with IFN-based regimen9 studies exclusively assessing LC patients
Topic 522 studies (12440 patients with SVR vs. 18980 patients with no SVR)4 prospective cohort studies18 retrospective cohort studies12 Western population-based studies9 Asian population-based studies1 Saudi Arabia and Egypt population-based study41.8 to 64 years (mean)2.1 to 11.5 years (median)11 studies with PegIFN-based regimen11 studies with IFN-based regimen3 studies exclusively assessing LC patients
Topic 623 studies (5148 patients with SVR vs. 10356 patients with no SVR)7 prospective cohort studies16 retrospective cohort studies14 Western population-based studies9 Asian population-based studies41.8 to 64 (mean)2.1 to 11.5 years (median)12 studies with PegIFN-based regimen11 studies with IFN-based regimen6 studies exclusively assessing LC patients

RCT randomized controlled study, IFN interferon, PegIFN pegylated interferon, RBV ribavirin, LC liver cirrhosis, SVR sustained virologic response

Table 3

Clinical data of included studies for the efficacy of antiviral treatment on the development of HCC in patients with CHC

StudyNationalityAgeDuration of follow upStudy formatGenotypeNOSTreatmentHCC/Total treatmentHCC/ControlHistology
Mazella G et al. (1996) [23]ItalyTx: 53, control: 54 (mean)mean 32 monthsPunknown7IFN-α or lymphoblastoid5/1939/92Child A LC
Bruno S et al.(1997) [24]ItalyTx 56, control: 59 (mean)median 68 monthsP62% type 1b7IFN-α6/8316/80LC (mainly Child A)
Fattovich G et al. (1997) [25]ItalyTx: 53, control: 57 (mean)mean 60 monthsRunknown8IFN-α7/19316/136LC
Serfaty L et al. (1998) [26]FranceTx: 55, control: 56 (mean)median 40 monthsP48% 1b7IFN-α2/599/44Knodell 10 (mean)
Benvegnù L et al.(1998) [27]ItalyTx: 56.7, control: 59.5 (mean)mean 71.5 monthsPunknown8IFN4/7520/77Child A LC
International Interferon-α Hepatocellular Carcinoma Study Group (1998) [28]Italy and Argentina54 (median)36 monthsRunknown7IFN-α or lymphoblastoid21/23248/259unknown
Imai Y et al.(1998) [29]JapanunknownTx: 47.6, control: 46.8 (median)Runknown7IFN-α28/41919/144F3,4: 37% in Tx, 53% in control
Yoshida H et al. (1999) [30]JapanTx: 49.5, control: 53.6 (mean)median 4.3 yearsR70.3% type 17IFN-α or IFN-β or combination89/240059/490F3,4: 33.1% in Tx, 33.8% in control
Okanoue T et al. (1999) [31]Japan42.6–57.6 (mean)mean 39.5–67.1 monthsRunknown7IFN-α or lymphoblastoid52/114822/55F3,4: 34% in Tx, F4: 100% in control
Valla DC et al. (1999) [32]FranceTx: 57, control: 56 (mean)mean 160 weeksRCTunknownIFN-α5/479/52compensated LC
Ikeda K et al. (2001) [33]Japan57 (median)median 7.6 yearsRunknown7IFN-α or IFN-β32/113271/581LC
Gramenzi A et al. (2001) [34]ItalyTx: 57.9, control: 58.1 (mean)median 55–58 monthsPunknown7IFN-α6/7219/72LC (mainly Child A)
Nishiguchi S et al. (2001) [35]JapanTx: 54.7, control: 57.3 (mean)mean 8.2 yearsRCT75.6% type 2IFN-α12/4533/45unknown
Testino G et al. (2002) [16]ItalyTx: 55.3, control: 56.8 (mean)mean 95.4 monthsR55% type 1b, 45% type 28IFN-α12/5124/71Child A LC
Coverdale SA et al. (2004) [36]AustraliaTx: 37, control: 38 (median)median 9 yearsP39.6% type 17IFN-α26/3847/71Scheuer fibrosis score 2
Azzaroli F et al. (2004) [37]Italy55.1 (mean)5 yearsRCT64.4% type 1bIFN-α with RBV2/719/30LC
Shiratori Y et al. (2005) [38]JapanTx: 57, control: 61 (median)median 6.8 yearsP71.9% type 1b8IFN-α or lymphoblastoid84/27135/74unknown
Yu ML et al. (2006) [39]TaiwanTx: 46.9, control: 43.6 (mean)mean 5.18–5.15 yearsR46.2% type 18IFN-α with or without RBV51/105754/562LC 15.6% in Tx, 12.1% in control
Sinn DH et al. (2008) [40]Korea48.4–58.2 (mean)median 55.2 monthsR48.6% type 27IFN/PegIFN with or without RBV14/490122/647F3,4: 49% in Tx, F4: 33% in control
Di Martino V et al. (2011) [41]Franceunknownmedian 59 monthsR57.9% type 17IFN with or without RBV, or PegIFN with RBV9/1845/18455.5% F2 or greater
Tateyama M et al. (2011) [42]Japan57 (median)mean 8.2 yearsR72.1% type 1b8IFN/PegIFN with or without RBV110/37363/334F3,4: 34.1%
Maruoka D et al. (2012) [43]Japan50.4–54 (mean)mean 9.9 yearsR73.6% type 18IFN-α/IFN-β with or without RBV85/57735/144F3,4: 24.3% in Tx, F4: 43.1% in control
Cozen ML et al. (2013) [44]US50.98 (mean)mean 10 yearsR68.7% type 18IFN-α with or without RBV11/1599/199F3,4: 19% (30.2% in Tx, 10.1% in control)
Aleman S et al. (2013) [45]Sweden51 (mean)mean 5.3 yearsR50% type 18PegIFN with RBV32/30314/48LC
Cozen ML et al. (2016) [46]US51.4 (mean)mean 8.5 yearsP71.6% type 1 or 48IFN-α with RBV43/69284/1519LC 15.8% in Tx, 5.3% in control

HCC hepatocellular carcinoma, CHC chronic hepatitis C, NOS Newcastle-Ottawa scale, Tx treatment group, R retrospective cohort study, P prospective cohort study, RCT randomized controlled study, IFN interferon, PegIFN pegylated interferon, RBV ribavirin, LC liver cirrhosis

Table 4

Clinical data of included studies for the efficacy of antiviral treatment on all-cause and liver-specific mortality in patients with CHC

StudyNationalityAgeDuration of follow upStudy formatGenotypeNOSTreatmentDeath/Total treatmentDeath/ControlHistology
Benvegnù L et al. (1998) [27]ItalyTx: 56.7, control: 59.5 (mean)mean 71.5 monthsPunknown8IFN a3/75 a15/77Child A LC
Ikeda K et al. (2001) [33]Japan57 (median)median 7.6 yearsRunknown7IFN-α or IFN-β20/113 a12/113266/581 a124/581LC
Gramenzi A et al. (2001) [34]ItalyTx: 57.9, control: 58.1 (mean)median 55–58 monthsPunknown7IFN-α a7/729/72 a8/72LC (mainly Child A)
Nishiguchi S et al. (2001) [35]JapanTx: 54.7, control: 57.3 (mean)mean 8.2 yearsRCT75.6% type 2IFN-α5/4526/45unknown
Testino G et al. (2002) [16]ItalyTx: 55.3, control: 56.8 (mean)mean 95.4 monthsR55% type 1b, 45% type 28IFN-α1/519/71Child A LC
Yosida H et al. (2002) [47]JapanTx: 49.5, control: 54.6 (mean)mean 5.4 yearsRunknown8IFN-α or IFN-β56/2430 a35/243030/459 a23/459F3,4: 32.2% in Tx, 31.6% in control, 26.3% in SVR, 35.2% in no SVR
Imazeki F et al. (2003) [48]JapanTx: 49.2, control: 53.1 (mean)mean 8.2 yearsR73.9% type 18IFN-α or IFN-β33/355 a19/35515/104 a12/104F3,4: 26.7% in Tx, 29.8% in control,
Coverdale SA et al. (2004) [36]AustraliaTx: 37, control: 38 (median)median 9 yearsP39.6% type 17IFN-α a36/384 a12/71Scheuer fibrosis score 2
Kasahara A et al. (2004) [17]JapanTx: 53, control: 54 (median)mean 6 yearsRunknown8IFN101/2698 a69/269852/256 a42/256F3,4: 38.7% in Tx, 48% in control, 28.6% in SVR, 43% in no SVR
Shiratori Y et al. (2005) [38]JapanTx: 57, control: 61 (median)median 6.8 yearsP71.9% type 1b8IFN-α or lymphoblastoid45/271 a32/27124/74 a19/74unknown
Yu ML et al. (2006) [39]TaiwanTx: 46.9, control: 43.6 (mean)mean 5.18–5.15 yearsR46.2% type 18IFN-α with or without RBV16/1057 a14/105712/562 a10/562LC 15.6% in Tx, 12.1% in control
Di Martino V et al. (2011) [41]Franceunknownmedian 59 monthsR57.9% type 17IFN with or without RBV, or PegIFN with RBV9/184 a5/18420/194 a4/18455.5% F2 or greater
Yamasaki K et al. (2012) [49]Japan60.9 (mean)median 11.5 yearsP59.9% type 1b7IFN-α or β or lymphoblastoid with or without RBV25/152 a6/15290/199 a32/199unknown
Maruoka D et al. (2012) [43]Japan50.4–54 (mean)mean 9.9 yearsR73.6% type 18IFN-α/IFN-β with or without RBV84/577 a52/57737/144 a30/144F3,4: 24.3% in Tx, F4: 43.1% in control
Cozen ML et al. (2013) [44]US50.98 (mean)mean 10 yearsR68.7% type 18IFN-α with or without RBV31/15947/199F3,4: 19% (30.2% in Tx, 10.1% in control)
Aleman S et al. (2013) [45]Sweden51 (mean)mean 5.3 yearsR50% type 18PegIFN with RBV59/303 a39/30318/48 a16/48LC
Kutala BK et al. (2015) [50]France50 (median)median 5.5 yearsR55.7% type 18IFN/PegIFN with or without RBV30/32519/102F3,4: 100%
Cozen ML et al. (2016) [46]US51.4 (mean)mean 8.5 yearsP71.6% type 1 or 48IFN-α with RBV112/692488/1519LC 15.8% in Tx, 5.3% in control

a: Liver-specific death, CHC chronic hepatitis C, NOS Newcastle-Ottawa scale, Tx treatment group, R retrospective cohort study, P prospective cohort study, RCT randomized controlled study, IFN interferon, PegIFN pegylated interferon, RBV ribavirin, LC liver cirrhosis, SVR sustained virologic response

Table 5

Clinical data of included studies for the efficacy of SVR on the development of HCC in patients with CHC

StudyNationalityAgeDuration of follow upStudy formatGenotypeNOSTreatmentHCC/Total SVRHCC/No SVRHistology
Nishiguchi S et al. (1995) [51]JapanTx: 54.7, control: 57.3 (mean)2–7 yearsRCT75.6% type 2IFN-α0/72/38HAI 11.7 in Tx, 11.8 in control (mean)
Tanaka K et al. (1998) [52]JapanSVR: 47.7, no SVR: 51 (mean)about 40 monthsPunknown7lymphoblastoid IFN0/810/47LC
Yoshida H et al. (1999) [30]JapanTx: 49.5, control: 53.6 (mean)median 4.3 yearsR70.3% type 17IFN-α or IFN-β or combination10/78979/1611F3,4: 33.1% in Tx, 33.8% in control
Testino G et al. (2002) [16]ItalyTx: 55.3, control: 56.8 (mean)mean 95.4 monthsR55% type 1b, 45% type 28IFN-α3/1112/40Child A LC
Okanoue T et al. (2002) [53]JapanTx: 50.4, control: 58.1 (mean)Mean 5.6 yearsRunknown7IFN-α or lymphoblastoid4/426110/994F3,4: 20.9% in SVR, 34.4% in control
Coverdale SA et al. (2004) [36]AustraliaTx: 37, control: 38 (median)median 9 yearsP39.6% type 17IFN-α1/5025/334Scheuer fibrosis score 2
Shiratori Y et al. (2005) [38]JapanTx: 57, control: 61 (median)median 6.8 yearsP71.9% type 1b8IFN-α or lymphoblastoid11/6473/207unknown
Yu ML et al. (2006) [39]TaiwanTx: 46.9, control: 43.6 (mean)mean 5.18–5.15 yearsR46.2% type 18IFN-α with or without RBV12/71539/342LC 15.6% in Tx, 12.1% in control
Pradat P et al. (2007) [54]Europe45–47 (mean)5–7 yearsP49.2% type 16IFN/PegIFN with or without RBV0/9117/266unknown
Braks RE et al. (2007) [55]France54.1 (mean)mean 7.7 yearsR61.1% type 18IFN-α with or without RBV, or PegIFN with RBV1/3724/76Child A LC
Bruno S et al. (2007) [56]Italy54.7 (mean)Mean 96.1 monthsR71.8% type 18IFN-α7/124122/759Child A LC
Hasegawa E et al. (2007) [57]Japan56 (median)median 4.6 yearsR65% 2a7IFN-α,β/lymphoblastoid with or without RBV3/4816/57LC
Veldt BJ et al. (2007) [58]Europe and Canada48 (median)median 2.1 yearsR59% type 18IFN/PegIFN with or without RBV3/14232/337Ishak 4–6
Floreani A et al. (2008) [59]Italy44.5–55.7 (mean)mean 23.4–25.2 monthsR41.3% type 17PegIFN with RBV0/405/38unknown
Sinn DH et al. (2008) [40]Korea48.4–58.2 (mean)median 55.2 monthsR48.6% type 27IFN/PegIFN with or without RBV4/29610/194F3,4: 49% in Tx, F4: 33% in control
Kurokawa M et al. (2009) [60]Japan55.8 (mean)median 36.5 monthsR72.9% type 17IFN-α with RBV4/13921/264F3,4: 31.3%
Asahina Y et al. (2010) [61]Japan55.4 (mean)mean 7.5 yearsR69.6% type 1b8IFN-α,β with or without RBV, or PegIFN with RBV22/686149/1356F3,4: 25.2%
Kawamura Y et al. (2010) [62]Japan50 (median)median 6.7 yearsRunknown8IFN-α,β with or without RBV12/108161/977F1,2: 93.1%
Cardoso AC et al. (2010) [63]France55 (mean)median 3.5 yearsR60% type 17IFN/PegIFN with or without RBV6/10340/204F3,4: 100%
Morgan TR et al. (2010) [64]US48.6–49.6 (mean)median 79–96 monthsP87.2% type 18PegIFN with or without RBV2/14033/386F3,4: 100%
Di Martino V et al. (2011) [41]Franceunknownmedian 59 monthsR57.9% type 17IFN with or without RBV, or PegIFN with RBV1/598/12555.5% F2 or greater
Velosa J et al. (2011) [65]Portugal51.7 (mean)mean 6.4 yearsR61% type 17IFN/PegIFN with or without RBV1/3920/91compensated LC
Iacobellis A et al. (2011) [66]Italy59–62 (mean)mean 51 monthsP57.3% type 17PegIFN with RBV5/2411/51decompensated LC
Hung CH et al. (2011) [67]Taiwan53 (median)median 4.3 yearsR49% type 17IFN/PegIFN with or without RBV33/102754/443unknown
Takahashi H et al. (2011) [68]Japan55.4 (mean)Mean 52 monthsR74.9% type 1b7IFN-α,β/PegIFN with RBV1/8912/114F3,4: 23.2%
Backus LI et al. (2011) [69]US51–53 (mean)median 3.8 yearsR72.1% type 16PegIFN with RBV223/7434283/144013% LC
Tateyama M et al. (2011) [42]Japan57 (median)mean 8.2 yearsR72.1% type 1b8IFN/PegIFN with or without RBV3/13944/234F3,4: 34.1%
Osaki Y et al. (2012) [70]Japan59 (median)median 4.1 yearsR59.9% type 17IFN/PegIFN with RBV1/18522/197unknown
van der Meer AJ et al. (2012) [71]Europe and Canada48 (mean)median 8.4 yearsR68% type 18IFN/PegIFN with or without RBV7/12576/405Ishak 4–6
Maruoka D et al. (2012) [43]Japan50.4–54 (mean)mean 9.9 yearsR73.6% type 18IFN-α/IFN-β with or without RBV5/22180/356F3,4: 24.3% in Tx, F4: 43.1% in control
Cozen ML et al. (2013) [44]US50.98 (mean)mean 10 yearsR68.7% type 18IFN-α with or without RBV2/699/90F3,4: 19% (30.2% in Tx, 10.1% in control)
Alfaleh FZ et al. (2013) [72]Saudi Arabia, Egypt48 (mean)mean 63.8 monthsP30.6% type 48PegIFN with or without RBV0/624/95F3,4: 24.6% (27.1% in SVR, 31.1% in no SVR)
Aleman S et al. (2013) [45]Sweden51 (mean)mean 5.3 yearsR50% type 18PegIFN with RBV6/11026/193LC
Di Marco V et al. (2016) [73]Italy58 (mean)median 7.6 yearsP83.4% type 18PegIFN with RBV7/10892/336compensated LC
Ikezaki H et al. (2016) [74]Japan60–64 (median)median 2.8 yearsR52.7% in type 17IFN- β with RBV2/687/44F3,4: 30.9% in SVR, 72.7% in no SVR

SVR sustained virologic response, HCC hepatocellular carcinoma, CHC chronic hepatitis C, NOS Newcastle-Ottawa scale, Tx treatment group, R retrospective cohort study, P prospective cohort study, RCT randomized controlled study, IFN interferon, PegIFN pegylated interferon, RBV ribavirin, LC liver cirrhosis

Table 6

Clinical data of included studies for the efficacy of SVR on all-cause and liver-specific mortality in patients with CHC

StudyNationalityAgeDuration of follow upStudy formatGenotypeNOSTreatmentDeath/Total SVRDeath/No SVRHistology
Yosida H et al. (2002) [47]JapanTx: 49.5, control: 54.6 (mean)mean 5.4 yearsRunknown8IFN-α or IFN-β a7/817 a49/1613F3,4: 32.2% in Tx, 31.6% in control, 26.3% in SVR, 35.2% in no SVR
Okanoue T et al. (2002) [53]JapanTx: 50.4, control: 58.1 (mean)Mean 5.6 yearsRunknown7IFN-α or lymphoblastoid2/426 a0/42647/994 a34/994F3,4: 20.9% in SVR, 34.4% in control
Imazeki F et al. (2003) [48]JapanTx: 49.2, control: 53.1 (mean)mean 8.2 yearsR73.9% type 18IFN-α or IFN-β4/116 a1/11629/239 a18/239F3,4: 26.7% in Tx, 29.8% in control
Coverdale SA et al. (2004) [36]AustraliaTx: 37, control: 38 (median)median 9 yearsP39.6% type 17IFN-α a1/50 a35/334Scheuer fibrosis score 2
Kasahara A et al. (2004) [17]JapanTx: 53, control: 54 (median)mean 6 yearsRunknown8IFN7/738 a1/73894/1930 a68/1930F3,4: 38.7% in Tx, 48% in control, 28.6% in SVR, 43% in no SVR
Shiratori Y et al. (2005) [38]JapanTx: 57, control: 61 (median)median 6.8 yearsP71.9% type 1b8IFN-α or lymphoblastoid1/64 a0/6444/207 a32/207unknown
Yu ML et al. (2006) [39]TaiwanTx: 46.9, control: 43.6 (mean)mean 5.18–5.15 yearsR46.2% type 18IFN-α with or without RBV4/715 a3/71512/342 a11/342LC 15.6% in Tx, 12.1% in control
Arase Y et al. (2007) [75]JapanSVR: 63, no SVR: 64 (mean)mean 7.4 yearsR60.4% type 1b8IFN-α/β with or without RBV9/140 a2/14044/360 a32/360F3,4: 14.5 in SVR, 27.5 in no SVR
Bruno S et al. (2007) [56]Italy54.7 (mean)Mean 96.1 monthsR71.8% type 18IFN-α6/124 a2/120114/759 a83/728Child A LC
Veldt BJ et al. (2007) [58]Europe and Canada48 (median)median 2.1 yearsR59% type 18IFN/PegIFN with or without RBV2/142 a1/14224/337 a19/337Ishak 4–6
Cardoso AC et al. (2010) [63]France55 (mean)median 3.5 yearsR60% type 17IFN/PegIFN with or without RBV a3/103 a18/204F3,4: 100%
Morgan TR et al. (2010) [64]US48.6–49.6 (mean)median 79–96 monthsP87.2% type 18PegIFN with or without RBV a1/140 a23/386F3,4: 100%
Innes HA et al. (2011) [76]UK41.8 (mean)mean 5.3 yearsR35.6% type 18IFN/PegIFN with or without RBV13/560 a5/56075/655 a50/65585.8% no LC
Di Martino V et al. (2011) [41]Franceunknownmedian 59 monthsR57.9% type 17IFN with or without RBV, or PegIFN with RBV0/59 a0/599/125 a5/12555.5% F2 or greater
Velosa J et al. (2011) [65]Portugal51.7 (mean)mean 6.4 yearsR61% type 17IFN/PegIFN with or without RBV a0/39 a15/91compensated LC
Iacobellis A et al. (2011) [66]Italy59–62 (mean)mean 51 monthsP57.3% type 17PegIFN with RBV a2/24 a23/51decompensated LC
Backus LI et al. (2011) [69]US51–53 (mean)median 3.8 yearsR72.1% type 16PegIFN with RBV525/74341440/943013% LC
Yamasaki K et al. (2012) [49]Japan60.9 (mean)median 11.5 yearsP59.9% type 1b7IFN-α or β or lymphoblastoid with or without RBV9/72 a1/7216/80 a5/80unknown
van der Meer AJ et al. (2012) [71]Europe and Canada48 (mean)median 8.4 yearsR68% type 18IFN/PegIFN with or without RBV13/125 a3/125100/405 a103/405Ishak 4–6
Maruoka D et al. (2012) [43]Japan50.4–54 (mean)mean 9.9 yearsR73.6% type 18IFN-α/IFN-β with or without RBV10/221 a2/22174/356 a50/356F3,4: 24.3% in Tx, F4: 43.1% in control
Cozen ML et al. (2013) [44]US50.98 (mean)mean 10 yearsR68.7% type 18IFN-α with or without RBV6/6925/90F3,4: 19% (30.2% in Tx, 10.1% in control)
Alfaleh FZ et al. (2013) [72]Saudi Arabia, Egypt48 (mean)mean 63.8 monthsP30.6% type 48PegIFN with or without RBV0/62 a0/624/95 a8/95F3,4: 24.6% (27.1% in SVR, 31.1% in no SVR)
Aleman S et al. (2013) [45]Sweden51 (mean)mean 5.3 yearsR50% type 18PegIFN with RBV11/110 a4/11048/193 a35/193LC
Singal AG et al. (2013) [77]US48 (median)median 36–72 monthsR68.6% type 17PegIFN with RBV2/8341/15917.3% LC
Dieperink E et al. (2014) [78]US51.4 (mean)median 7.5 yearsR70% type 18IFN/PegIFN with or without RBV19/222 a6/22281/314 a56/314F3,4: 54.5% (41.3% in SVR, 64.7% in no SVR)
Kutala BK et al. (2015) [50]France50 (median)median 5.5 yearsR55.7% type 18IFN/PegIFN with or without RBV3/10427/221F3,4: 100%
Di Marco V et al. (2016) [73]Italy58 (mean)median 7.6 yearsP83.4% type 18PegIFN with RBV a8/108 a98/336compensated LC

a: Liver-specific death, SVR sustained virologic response, CHC chronic hepatitis C, NOS Newcastle-Ottawa scale, Tx treatment group, R retrospective cohort study, P prospective cohort study, RCT randomized controlled study, IFN interferon, PegIFN pegylated interferon, RBV ribavirin, LC liver cirrhosis

Clinical data summary of all included studies RCT randomized controlled study, IFN interferon, PegIFN pegylated interferon, RBV ribavirin, LC liver cirrhosis, SVR sustained virologic response Clinical data of included studies for the efficacy of antiviral treatment on the development of HCC in patients with CHC HCC hepatocellular carcinoma, CHC chronic hepatitis C, NOS Newcastle-Ottawa scale, Tx treatment group, R retrospective cohort study, P prospective cohort study, RCT randomized controlled study, IFN interferon, PegIFN pegylated interferon, RBV ribavirin, LC liver cirrhosis Clinical data of included studies for the efficacy of antiviral treatment on all-cause and liver-specific mortality in patients with CHC a: Liver-specific death, CHC chronic hepatitis C, NOS Newcastle-Ottawa scale, Tx treatment group, R retrospective cohort study, P prospective cohort study, RCT randomized controlled study, IFN interferon, PegIFN pegylated interferon, RBV ribavirin, LC liver cirrhosis, SVR sustained virologic response Clinical data of included studies for the efficacy of SVR on the development of HCC in patients with CHC SVR sustained virologic response, HCC hepatocellular carcinoma, CHC chronic hepatitis C, NOS Newcastle-Ottawa scale, Tx treatment group, R retrospective cohort study, P prospective cohort study, RCT randomized controlled study, IFN interferon, PegIFN pegylated interferon, RBV ribavirin, LC liver cirrhosis Clinical data of included studies for the efficacy of SVR on all-cause and liver-specific mortality in patients with CHC a: Liver-specific death, SVR sustained virologic response, CHC chronic hepatitis C, NOS Newcastle-Ottawa scale, Tx treatment group, R retrospective cohort study, P prospective cohort study, RCT randomized controlled study, IFN interferon, PegIFN pegylated interferon, RBV ribavirin, LC liver cirrhosis The methodological quality of cohort study is described in the Table 3, 4, 5 and 6. This feature was evaluated as modifiers in each analysis. The methodological quality of RCT is described in Additional file 1: Appendix 1. Given the similar methodological quality among RCTs, sensitivity analysis or subgroup analyses based on the methodological quality in RCTs were not performed.

Efficacy of antiviral treatment on the development of HCC in chronic hepatitis C patients

The overall efficacy of antiviral treatment on the development of HCC exhibited an OR of 0.392 (95% CI: 0.275–0.557, p <0.001) in a random effect model analysis (Fig. 2). The funnel plot showed asymmetry on the right lower quadrant area (Additional file 1: Appendix Figure S2). However, the Egger’s test revealed an intercept of −2.131 (95% CI: −4.81–0.54, t-value: 1.64, df: 23, p = 0.11 (2-tailed)). The rank correlation test also showed a Kendall’s tau of −0.19 with a continuity correction (p = 0.17). The trim and fill method indicated that no study was trimmed. Overall, there was no evidence of publication bias.
Fig. 2

Efficacy of antiviral treatment on the development of HCC in patients with CHC. The size of each square is proportional to the study’s weight. Diamond is the summary estimate from the pooled studies (random effect model). HCC, hepatocellular carcinoma; CHC, chronic hepatitis C

Efficacy of antiviral treatment on the development of HCC in patients with CHC. The size of each square is proportional to the study’s weight. Diamond is the summary estimate from the pooled studies (random effect model). HCC, hepatocellular carcinoma; CHC, chronic hepatitis C A cumulative meta-analysis of enrolled studies based on publication year showed no specific time trend (Additional file 1: Appendix 3). A cumulative meta-analysis based on effect size showed no small study bias (Additional file 1: Appendix 4). One study removed meta-analysis revealed a stable feature (Additional file 1: Appendix 5). Overall, the sensitivity meta-analyses revealed robust results. Methodological quality of Newcastle-Ottawa scale potentially explained heterogeneity in meta-ANOVA tests (p = 0.027) (Additional file 1: Appendix 6). A meta-regression revealed a Newcastle-Ottawa scale score of 8 for the reason of heterogeneity (p = 0.027) (Additional file 2: Table S1). After excluding 10 studies (Newcastle-Ottawa scale 8), no covariates explained heterogeneity in meta-regression tests. Therefore, methodological quality was the reason of heterogeneity in this analysis.

Efficacy of antiviral treatment on All-cause mortality in patients with chronic hepatitis C

The overall efficacy of antiviral treatment on all-cause mortality revealed an OR of 0.380 (95% CI: 0.295–0.489, p <0.001) in a random effect model analysis (Fig. 3). The funnel plot showed asymmetry on the right lower quadrant area (Additional file 1: Appendix 7). However, the Egger’s test revealed an intercept of 0.266 (95% CI: −2.010–2.542, t-value: 0.25, df: 15, p = 0.81 (2-tailed)). The rank correlation test also showed a Kendall’s tau of 0.04 with a continuity correction (p = 0.84). The trim and fill method indicated that 1 study was trimmed. After excluding the study by Testino et al. [16] located on the left lower quadrant in funnel plot, the OR was 0.385 (95% CI: 0.298–0.496, p <0.001). Overall, the impact of bias was minimal.
Fig. 3

Efficacy of antiviral treatment on all-cause mortality in patients with CHC. The size of each square is proportional to the study’s weight. Diamond is the summary estimate from the pooled studies (random effect model). CHC, chronic hepatitis C

Efficacy of antiviral treatment on all-cause mortality in patients with CHC. The size of each square is proportional to the study’s weight. Diamond is the summary estimate from the pooled studies (random effect model). CHC, chronic hepatitis C A cumulative meta-analysis of enrolled studies based on publication year showed no specific time trend (Additional file 1: Appendix 8). A cumulative meta-analysis based on effect size showed no small study bias (Additional file 1: Appendix 9). One study removed meta-analysis revealed a stable feature (Additional file 1: Appendix 10). Overall, the sensitivity meta-analyses revealed robust results. Meta-ANOVA or meta-regression showed no specific modifier for the reason of heterogeneity (Additional file 1: Appendix 11) (Additional file 2: Table S2). Overall, no covariates were found to be explaining heterogeneity in this meta-analysis.

Efficacy of antiviral treatment on liver-specific mortality in chronic hepatitis C patients

The overall efficacy of antiviral treatment on liver-specific mortality exhibited an OR of 0.363 (95% CI: 0.260–0.508, p <0.001) in a random effect model analysis (Additional file 1: Appendix 12). The funnel plot showed symmetry (Additional file 1: Appendix 13). However, the Egger’s test revealed that intercept was 3.06 (95% CI: 0.295–5.831, t-value: 2.43, df: 11, p = 0.03 (2-tailed)). The rank correlation test showed a Kendall’s tau of 0.28 with a continuity correction (p = 0.20). The trim and fill method indicated that no study was trimmed. After excluding an outlier (study by Kasahara A et al. [17]) located on the left upper quadrant area in funnel plot, the OR was 0.398 (95% CI: 0.314–0.504, p <0.001). Overall, the impact of bias was minimal. A cumulative meta-analysis of enrolled studies based on publication year showed no specific time trend (Additional file 1: Appendix 14). A cumulative meta-analysis based on effect size showed no small study bias (Additional file 1: Appendix 15). One study removed meta-analysis revealed a stable feature (Additional file 1: Appendix 16). Overall, the sensitivity meta-analyses showed robust results. A meta-ANOVA indicated that follow-up duration (p = 0.036) and methodological quality (p = 0.029) were suspicious for the reason of heterogeneity (Additional file 1: Appendix 17). A meta-regression indicated that follow-up duration (p = 0.036) and Newcastle-Ottawa scale score of 8 (p = 0.029) explained the heterogeneity (Additional file 2: Table S3). After excluding 2 studies (short-term follow-up duration), no covariates explained heterogeneity in meta-regression tests. After excluding 7 studies (Newcastle-Ottawa scale 8), no covariates explained heterogeneity in meta-regression tests. Therefore, follow-up duration and methodological quality were the reasons of heterogeneity in this analysis.

Efficacy of SVR on the development of HCC in patients with chronic hepatitis C

The overall efficacy of SVR on the development of HCC exhibited an OR of 0.203 (95% CI: 0.164–0.251, p <0.001) in a random effect model analysis (Fig. 4). The funnel plot showed symmetry (Additional file 1: Appendix 18). The Egger’s test showed that intercept was 0.56 (95% CI: −0.099–1.217, t-value: 1.73, df: 33, p = 0.09 (2-tailed)). The rank correlation test showed a Kendall’s tau of −0.17 with a continuity correction (p = 0.16). The trim and fill method indicated that no study was trimmed. Overall, there was no evidence of publication bias.
Fig. 4

Efficacy of SVR on the development of HCC in patients with CHC. The size of each square is proportional to the study’s weight. Diamond is the summary estimate from the pooled studies (random effect model). SVR, sustained virologic response; HCC, hepatocellular carcinoma; CHC, chronic hepatitis C

Efficacy of SVR on the development of HCC in patients with CHC. The size of each square is proportional to the study’s weight. Diamond is the summary estimate from the pooled studies (random effect model). SVR, sustained virologic response; HCC, hepatocellular carcinoma; CHC, chronic hepatitis C A cumulative meta-analysis of enrolled studies based on publication year showed no specific time trend (Additional file 1: Appendix 19). A cumulative meta-analysis based on effect size showed no small study bias (Additional file 1: Appendix 20). One study removed meta-analysis showed a stable feature (Additional file 1: Appendix 21). Overall, the sensitivity meta-analyses revealed robust results. Meta-ANOVA or meta-regression identified no specific modifier for the reason of heterogeneity (Additional file 1: Appendix 22) (Additional file 2: Table S4). Overall, no covariates explained heterogeneity.

Efficacy of SVR on all-cause mortality in patients with chronic hepatitis C

The overall efficacy of SVR on all-cause mortality revealed an OR of 0.255 (95% CI: 0.199–0.326, p < 0.001) in a random effect model analysis (Fig. 5). The funnel plot showed asymmetry on the right lower quadrant area (Additional file 1: Appendix 23). The Egger’s test showed that the intercept was −1.44 (95% CI: −1.921– −0.949, t-value: 6.16, df: 20, p <0.001 (2-tailed)). The rank correlation test showed a Kendall’s tau of −0.23 with a continuity correction (p = 0.14). The trim and fill method indicated 11 studies were trimmed. Overall, there was evidence of publication bias.
Fig. 5

Efficacy of SVR on all-cause mortality in patients with CHC. The size of each square is proportional to the study’s weight. Diamond is the summary estimate from the pooled studies (random effect model). SVR, sustained virologic response; CHC, chronic hepatitis C

Efficacy of SVR on all-cause mortality in patients with CHC. The size of each square is proportional to the study’s weight. Diamond is the summary estimate from the pooled studies (random effect model). SVR, sustained virologic response; CHC, chronic hepatitis C A cumulative meta-analysis of enrolled studies based on publication year showed no specific time trend (Additional file 1: Appendix 24). A cumulative meta-analysis based on effect size showed no small study bias (Additional file 1: Appendix 25). One study removed meta-analysis revealed a stable feature (Additional file 1: Appendix 26). Overall, the sensitivity meta-analyses showed robust results. Meta-ANOVA indicated that methodological quality potentially explained heterogeneity (p = 0.030) (Additional file 1: Appendix 27). Meta-regression revealed a Newcastle-Ottawa scale score of 8 for the reason of heterogeneity (Additional file 2: Table S5). After excluding 16 studies (Newcastle-Ottawa scale 8), no covariates explained heterogeneity in meta-regression tests. Therefore, methodological quality was the reasons of heterogeneity in this analysis.

Efficacy of SVR on liver-specific mortality in chronic hepatitis C patients

The overall efficacy of SVR on liver-specific mortality exhibited an OR of 0.126 (95% CI: 0.094–0.169, p < 0.001) in a random effect model analysis (Additional file 1: Appendix 28). The funnel plot showed asymmetry on the right lower quadrant area (Additional file 1: Appendix 29). The Egger’s test indicated that intercept was −0.77 (95% CI: −1.473 – −0.057, t-value: 2.25, df: 21, p = 0.036 (2-tailed)). The rank correlation test revealed a Kendall’s tau of −0.19 with a continuity correction (p = 0.20). The trim and fill method showed 6 studies were trimmed. Overall, there was evidence of publication bias. A cumulative meta-analysis of enrolled studies based on publication year showed no specific time trend (Additional file 1: Appendix 30). A cumulative meta-analysis based on effect size showed no small study bias (Additional file 1: Appendix 31). One study removed meta-analysis revealed a stable feature (Additional file 1: Appendix 32). Overall, the sensitivity meta-analyses showed robust results. Meta-ANOVA or meta-regression revealed no specific modifier for the reason of heterogeneity (Additional file 1: Appendix 33) (Additional file 2: Table S6). Overall, no covariates explained heterogeneity. The results of meta-regression analyses for each topic are summarized in Table 7.
Table 7

Results of meta-regression analyses

ModifierCoefficientStandard error P value
NOS (topic 1)NOS 8: 1.203NOS 7: 0.5010.5650.5610.0330.372Q: 7.24, df: 2, P = 0.027
Follow-up duration (topic 3)1.1400.5420.036
NOS (topic 3)NOS 8: −0.6590.3020.029
NOS (topic 5)NOS 8: −0.540NOS 7: −0.5440.2090.3220.0100.091Q: 7.03, df: 2, P = 0.030

NOS Newcastle-Ottawa scale

Results of meta-regression analyses NOS Newcastle-Ottawa scale

Discussion

This meta-analyses confirmed the long-term efficacy of antiviral treatment in terms of prevention of HCC and reduction in all-cause and liver-specific mortality in patients with chronic HCV infection. This long-term efficacy was also intensified when SVR was achieved. Clinical outcomes regarding the efficacy of antiviral therapy in CHC patients have been continuously investigated by previous studies with a small number of patients or short-term follow-up duration. The reasons for performing this meta-analysis were a persistent risk of HCC even after attainment of SVR and a lack of sufficient data regarding long-term efficacy [18]. Persistent low-level of viremia and dysplastic hepatocyte regeneration are representative grounds for persistent risk of HCC after antiviral treatment [19, 20]. Interestingly, a recent meta-analysis revealed that IFN nonresponders exhibited a decreased risk of HCC recurrence after curative treatment of HCC, compared with no treatment patients, thus indicating that reduced necroinflammation and an inhibition of hepatic fibrosis progression prevent the development of HCC [21]. This results is consistent with that of our study and emphasized the importance of screening strategy of chronic hepatitis C. Early antiviral treatment before progression to advanced fibrosis or cirrhosis is associated with an increasing probability of achieving SVR [22]. However, an indolent course of chronic hepatitis C makes it difficult for early diagnosis and treatment. Authors have revealed that favorable antiviral efficacy persists in all patients with chronic hepatitis C, regardless of histology. This result was also confirmed by a previous study indicating favorable antiviral efficacy even in patients with LC [18]. Considering the advanced fibrosis or cirrhosis is the sequelae of long-standing inflammation of liver, our study confirmed antiviral treatment is still valid in the late course of chronic hepatitis C. Although histology was not a significant modifier in our meta-analysis, all of the included studies have substantially heterogeneous populations regarding the degree of fibrosis or cirrhosis of the liver. This finding was commonly detected in a previous meta-analysis [18]. However, considering the expanding treatment indication, including decompensated LC by the advent of direct-acting antiviral agents, histology is not expected to affect the long-term efficacy of antiviral treatment in the near future. Despite the favorable efficacy of antiviral treatment, 2 modifiers associated with heterogeneity were identified in the meta-ANOVA and meta-regression analyses. Studies with Newcastle-Ottawa scale of 8 were modifier in the analysis of association between antiviral treatment and the development of HCC (Additional file 2: Table S1), in the analysis of association between antiviral treatment and the liver-specific mortality (Additional file 2: Table S3), and in the analysis of association between SVR and all-cause mortality (Additional file 2: Table S5). Studies with a short-term follow-up duration were also modifier in the analysis of association between antiviral treatment and liver-specific mortality (Additional file 2: Table S3). Although these modifiers were confirmed as not significantly affecting the results of main analyses, this finding indicated the need for more number of high-quality and long-term follow-up studies on this topic. Publication bias was detected in 2 topics (topic 5 and 6). Sensitivity analyses including cumulative and one study removed meta-analyses were rigorously performed to find the small study effect associated with publication bias, and these analyses showed no small study effect. Overall, the impact of publication bias was minimal. This meta-analysis included the largest number of articles identified by a comprehensive literature search, and potential confounding modifiers were searched within each study whenever possible. Sensitivity analyses and meta-regression tests were performed to demonstrate robustness or identify the reason of heterogeneity. Despite the strengths, several limitations were detected during the systematic review. First, pretreatment predictive factors associated with the treatment response were not controlled or evaluated in these analyses, including pretreatment viral load, genotype, IL-28β polymorphism, and HBV or HIV coinfection. Direct-acting antiviral agents are expected to overcome these factors. Therefore, results of studies including these agents are expected in the near future. Second, the baseline characteristics of each enrolled study were not comparable between the treatment vs. no treatment groups, or the SVR vs. no SVR groups in some studies. This phenomenon was reflected in the evaluation of methodological quality and was confirmed to be a significant modifier associated with heterogeneity. Notably, difference by race or country including life style (obesity, consumption of alcohol or aflatoxin-contaminated foods, and chemical carcinogens exposure) was not appropriately investigated in our study. Considering the HCC is a heterogenous malignancy resulting from diverse causes of liver injury, different mechanisms or molecular pathways on the basis of country could be a cause of different treatment response. However, due to the heterogenous baseline characteristics including genotype and lacking of enough data about risk factors of HCC, the subgroup analyses by country could not present meaningful data. The limitations described above could be a cause of potential heterogeneity and bias. Therefore, studies controlling for various risk factors are needed to confirm these findings.

Conclusion

In conclusion, antiviral treatment for chronic hepatitis C showed improved outcome in the development of HCC and mortality, especially when SVR is achieved, although studies controlling for various risk factors of HCC and mortality are still lacking. Contains 33 figures including assessment of methodological quality, funnel plots for publication bias, sensitivity analyses, and Meta-ANOVA. (DOC 24248 kb) Contains 6 tables including detailed meta-regression data of 6 study topics of this study. (DOC 79 kb)
  76 in total

1.  Quantifying heterogeneity in a meta-analysis.

Authors:  Julian P T Higgins; Simon G Thompson
Journal:  Stat Med       Date:  2002-06-15       Impact factor: 2.373

2.  Interferon treatment improves survival in chronic hepatitis C patients showing biochemical as well as virological responses by preventing liver-related death.

Authors:  A Kasahara; H Tanaka; T Okanoue; Y Imai; H Tsubouchi; K Yoshioka; S Kawata; E Tanaka; K Hino; K Hayashi; S Tamura; Y Itoh; K Kiyosawa; S Kakumu; K Okita; N Hayashi
Journal:  J Viral Hepat       Date:  2004-03       Impact factor: 3.728

3.  Effectiveness of interferon alfa on incidence of hepatocellular carcinoma and decompensation in cirrhosis type C. European Concerted Action on Viral Hepatitis (EUROHEP).

Authors:  G Fattovich; G Giustina; F Degos; G Diodati; F Tremolada; F Nevens; P Almasio; A Solinas; J T Brouwer; H Thomas; G Realdi; R Corrocher; S W Schalm
Journal:  J Hepatol       Date:  1997-07       Impact factor: 25.083

4.  Impact of treatment against hepatitis C virus on overall survival of naive patients with advanced liver disease.

Authors:  Blaise K Kutala; Jeremie Guedj; Tarik Asselah; Nathalie Boyer; Feryel Mouri; Michelle Martinot-Peignoux; Dominique Valla; Patrick Marcellin; Xavier Duval
Journal:  Antimicrob Agents Chemother       Date:  2014-11-17       Impact factor: 5.191

5.  Excess liver-related morbidity of chronic hepatitis C patients, who achieve a sustained viral response, and are discharged from care.

Authors:  Hamish A Innes; Sharon J Hutchinson; Samuel Allen; Diptendu Bhattacharyya; Peter Bramley; Toby E S Delahooke; John F Dillon; Ewan Forrest; Andrew Fraser; Ruth Gillespie; David J Goldberg; Nicholas Kennedy; Scott McDonald; Allan McLeod; Peter R Mills; Judith Morris; Peter Hayes
Journal:  Hepatology       Date:  2011-11       Impact factor: 17.425

6.  Eradication of hepatitis C virus reduces the risk of hepatocellular carcinoma in patients with compensated cirrhosis.

Authors:  José Velosa; Fátima Serejo; Rui Marinho; Joana Nunes; Helena Glória
Journal:  Dig Dis Sci       Date:  2011-03-05       Impact factor: 3.199

7.  Effect of interferon alpha-2b plus ribavirin therapy on incidence of hepatocellular carcinoma in patients with chronic hepatitis.

Authors:  Mika Kurokawa; Naoki Hiramatsu; Tsugiko Oze; Kiyoshi Mochizuki; Takayuki Yakushijin; Nao Kurashige; Yuko Inoue; Takumi Igura; Kazuho Imanaka; Akira Yamada; Masahide Oshita; Hideki Hagiwara; Eiji Mita; Toshifumi Ito; Yoshiaki Inui; Taizo Hijioka; Harumasa Yoshihara; Atsuo Inoue; Yasuharu Imai; Michio Kato; Shinichi Kiso; Tatsuya Kanto; Tetsuo Takehara; Akinori Kasahara; Norio Hayashi
Journal:  Hepatol Res       Date:  2009-01-16       Impact factor: 4.288

8.  Association between sustained virological response and all-cause mortality among patients with chronic hepatitis C and advanced hepatic fibrosis.

Authors:  Adriaan J van der Meer; Bart J Veldt; Jordan J Feld; Heiner Wedemeyer; Jean-François Dufour; Frank Lammert; Andres Duarte-Rojo; E Jenny Heathcote; Michael P Manns; Lorenz Kuske; Stefan Zeuzem; W Peter Hofmann; Robert J de Knegt; Bettina E Hansen; Harry L A Janssen
Journal:  JAMA       Date:  2012-12-26       Impact factor: 56.272

9.  Interferon therapy does not prevent hepatocellular carcinoma in HCV compensated cirrhosis.

Authors:  Gianni Testino; Filippo Ansaldi; Enzo Andorno; Gian Luigi Ravetti; Carlo Ferro; Fabio De Iaco; Giancarlo Icardi; Umberto Valente
Journal:  Hepatogastroenterology       Date:  2002 Nov-Dec

10.  Relation of interferon therapy and hepatocellular carcinoma in patients with chronic hepatitis C. Osaka Hepatocellular Carcinoma Prevention Study Group.

Authors:  Y Imai; S Kawata; S Tamura; I Yabuuchi; S Noda; M Inada; Y Maeda; Y Shirai; T Fukuzaki; I Kaji; H Ishikawa; Y Matsuda; M Nishikawa; K Seki; Y Matsuzawa
Journal:  Ann Intern Med       Date:  1998-07-15       Impact factor: 25.391

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  15 in total

Review 1.  2019 Update of Indian National Association for Study of the Liver Consensus on Prevention, Diagnosis, and Management of Hepatocellular Carcinoma in India: The Puri II Recommendations.

Authors:  Ashish Kumar; Subrat K Acharya; Shivaram P Singh; Anil Arora; Radha K Dhiman; Rakesh Aggarwal; Anil C Anand; Prashant Bhangui; Yogesh K Chawla; Siddhartha Datta Gupta; Vinod K Dixit; Ajay Duseja; Naveen Kalra; Premashish Kar; Suyash S Kulkarni; Rakesh Kumar; Manoj Kumar; Ram Madhavan; V G Mohan Prasad; Amar Mukund; Aabha Nagral; Dipanjan Panda; Shashi B Paul; Padaki N Rao; Mohamed Rela; Manoj K Sahu; Vivek A Saraswat; Samir R Shah; Praveen Sharma; Sunil Taneja; Manav Wadhawan
Journal:  J Clin Exp Hepatol       Date:  2019-09-23

2.  Economic Comparison of Serologic and Molecular Screening Strategies for Hepatitis C Virus.

Authors:  Sammy Saab; Timothy Ahn; Terina McDaniel; Beshoy Yanny; Myron J Tong
Journal:  Gastroenterol Hepatol (N Y)       Date:  2018-08

3.  Computed Tomography-Measured Liver Volume Predicts the Risk of Hepatocellular Carcinoma Development in Chronic Hepatitis C Patients.

Authors:  Namkyu Kang; Jung Wha Chung; Eun Sun Jang; Sook-Hyang Jeong; Jin-Wook Kim
Journal:  Dig Dis Sci       Date:  2021-02-25       Impact factor: 3.199

4.  Comparison of clinical outcomes and impact of SVR in American and Chinese patients with chronic hepatitis C.

Authors:  Huiying Rao; Huixin Liu; Elizabeth Wu; Ming Yang; Bo Feng; Andy Lin; Ran Fei; Robert J Fontana; Lai Wei; Anna S Lok
Journal:  JHEP Rep       Date:  2020-06-12

5.  Safety, tolerability, and pharmacokinetics of AL-335 in healthy volunteers and hepatitis C virus-infected subjects.

Authors:  Matthew W McClure; Elina Berliba; Tengiz Tsertsvadze; Adrian Streinu-Cercel; Leen Vijgen; Béatrice Astruc; Alain Patat; Christopher Westland; Sushmita Chanda; Qingling Zhang; Thomas N Kakuda; Jennifer Vuong; Nick Khorlin; Leonid Beigelman; Lawrence M Blatt; John Fry
Journal:  PLoS One       Date:  2018-10-16       Impact factor: 3.240

6.  Steatosis Rates by Liver Biopsy and Transient Elastography With Controlled Attenuation Parameter in Clinical Experience of Hepatitis C Virus (HCV) and Human Immunodeficiency Virus/HCV Coinfection in a Large US Hepatitis Clinic.

Authors:  Sarah E Sansom; Jonathan Martin; Oluwatoyin Adeyemi; Kerianne Burke; Crystal Winston; Sara Markham; Benjamin Go; Gregory Huhn
Journal:  Open Forum Infect Dis       Date:  2019-03-01       Impact factor: 3.835

Review 7.  Hepatocellular Carcinoma Mechanisms Associated with Chronic HCV Infection and the Impact of Direct-Acting Antiviral Treatment.

Authors:  Srikanta Dash; Yucel Aydin; Kyle E Widmer; Leela Nayak
Journal:  J Hepatocell Carcinoma       Date:  2020-04-15

8.  Statin and the risk of hepatocellular carcinoma in patients with hepatitis B virus or hepatitis C virus infection: a meta-analysis.

Authors:  Xiaofei Li; Lina Sheng; Liwen Liu; Yongtao Hu; Yongxin Chen; Lianqing Lou
Journal:  BMC Gastroenterol       Date:  2020-04-09       Impact factor: 3.067

9.  Prevalence and characteristics of hepatitis C virus infection in Shenyang City, Northeast China, and prediction of HCV RNA positivity according to serum anti-HCV level: retrospective review of hospital data.

Authors:  Yurong Li; Lianrong Zhao; Nan Geng; Weijia Zhu; Hongbo Liu; Han Bai
Journal:  Virol J       Date:  2020-03-16       Impact factor: 4.099

10.  Durability of Sustained Virologic Response and Improvement of Fibrosis Markers after Daclatasvir and Asunaprevir Treatment in Genotype 1b Hepatitis C Virus-Infected Patients: a Real Life and Multicenter Study.

Authors:  Seung Kak Shin; Jin Woo Lee; Hannah Ra; Oh Sang Kwon; Jong Beom Shin; Young Joo Jin; Sangheun Lee; Ki Jun Han; Young Nam Kim; Tae Hun Kim; Yun Soo Kim; Ju Hyun Kim
Journal:  J Korean Med Sci       Date:  2019-10-28       Impact factor: 2.153

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