Abstract
Background and Aims
Active hepatitis C virus (HCV) infection is based on the detection of HCV RNA that it is effective but presents high cost and the need to hire trained personnel. This systematic review and meta-analysis is aimed at evaluating the diagnostic accuracy of HCV Ag testing to identify HCV cases and to monitor antiviral treatment including DAA treatment.
Methods
The studies were identified through a search in PubMed, Lilacs, and Scopus from 1990 through March 31, 2020. Cohort, cross-sectional, and randomized controlled trials were included. Two independent reviewers extracted data and assessed quality using an adapted Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Our primary outcome was to determine the accuracy of HCV Ag detection for the diagnosis, which we estimated using random-effects meta-analysis.
Results
Of 3,062 articles identified, 54 met our eligibility criteria. The studies described cohorts from 20 countries, including 14,286 individuals with chronic HCV individuals. Studies for ECLIA technology demonstrated highest quality compared to studies that used ELISA. The pooled sensitivity and specificity (95% CI) for HCV Ag detection of active HCV infection were 98.82% (95%CI = 98.04%; 99.30%) and 98.95% (95%CI = 97.84%; 99.49%), respectively. High concordance was found between HCV Ag testing and HCV RNA detection 89.7% and 95% to evaluate antiviral treatment.
Conclusions
According to our findings, HCV Ag testing could be useful to identify HCV active cases in low-resource areas. For antiviral treatment, HCV Ag testing will be useful at the end of treatment.
1. Introduction
Diagnosis of hepatitis C virus (HCV) infection is primarily performed through the detection of the HCV antibodies (anti-HCV), although this test does not differentiate past and current infections. Further information requires HCV-RNA testing. The execution of the latter is difficult due to the need to hire trained personnel, the use of specialized equipment, and the high cost of reagents [1, 2].
Early diagnosis of HCV is important to identify acute and chronic cases and to initiate and monitor therapeutic strategy. Due to this, the identification of the infection in its acute phase is very important for a good clinical prognosis [3–5]. From a complementary point of view, considering most infections are asymptomatic and the fast-viral replication during this phase, it is key to detect acute infections in a prompt and reliable way. Mathematical modeling has highlighted the relevance of acute asymptomatic infections for the overall dynamics of HCV [6].
To reduce costs and improve the access, some studies have used HCV Ag in serum or plasma to diagnose hepatitis C infection. HCV Ag appears approximately 2 to 3 weeks after the contact to virus, almost simultaneously as HCV RNA [7]. HCV antigen (HCV Ag) detection test was used to diagnose HCV in several cases, principally among risk population, immunocompromised individuals and patients under hemodialysis due to its low cost and the shorter time required to get its results [8, 9]. HCV Ag test was also used to monitor antiviral response to PEG interferon and direct antiviral agents (DAAs) [10–15].
Although some studies aimed to evaluate HCV Ag testing for diagnosis of HCV and monitor of antiviral therapy, just one systematic review and meta-analysis has been performed to evaluate the utility of HCV Ag for diagnosis [16]. To our knowledge, there has been no study that evaluates simultaneously diagnostic accuracy of HCV Ag to monitor antiviral therapy. We have conducted a systematic review and meta-analysis to evaluate the diagnostic accuracy of HCV Ag testing to identify HCV cases and to monitor antiviral treatment including DAA treatment.
2. Materials and Methods
We conducted a systematic review of HCV diagnostic and treatment using HCV Ag test in comparison to HCV RNA detection in accordance with standard PRISMA guidelines (http://www.prisma-statement.org/). Meta-analysis was conducted to evaluate HCV Ag as diagnostic test for HCV infection.
2.1. Search Strategy
The studies were identified through a search in PubMed, Lilacs, and Scopus with the following terms: (“hepatitis C” OR “HCV” OR “hepacivirus” OR “hepatitis C virus” AND “HCVAg” OR “hepatitis C core antigen” OR “HCV antigen” AND “diagnosis” OR “detection” OR “laboratory method” AND (“therapy” OR “treatment” OR “antiviral therapy.”). The search strategy has been performed with the inclusion of articles published up to May 30th, 2020.
2.2. Study Selection
The inclusion and exclusion criteria were established before proceeding to the search and review. The inclusion criteria were as follows: case-control, cross-sectional, cohort, or randomized trial designs; report of HCV Ag detection in serum, plasma, or other biological specimen; report of HCV RNA detection; and studies in English, Portuguese, or Spanish languages. Exclusion criteria were type of article such as editorial comments, reviews, opinion letters, and conference proceedings and studies with insufficient data to estimate the sensitivity and/or specificity of the assay.
The selection of articles for this review study was based carefully on the evaluation of the title and abstract after searching through the keywords, and when an article met the inclusion criteria, the full text was examined and the data extracted.
2.3. Data Extraction
Two independent researchers extracted the data and then cross-checked. When the data were unclear or required assumptions, two other researchers were consulted to reach consensus. The values of TP, TN, FP, and FN corresponding to the test evaluated in each article were extracted, and 2 × 2 contingency tables and calculation of sensitivity and specificity were made. The articles that did not have these necessary data were reported explicitly; we contacted the corresponding author and requested this data. Studies whose requested data were not answered were excluded.
2.4. Quality Assessment
We used the QUADAS-2 standard (Evaluation of the Quality of Diagnostic accuracy studies 2) to assess the quality and risk of bias in the included studies [17]. This method was designed to evaluate diagnostic accuracy studies through 4 main domains (patient selection, index test, reference standard, and flow and time). Each domain was assessed according to the risk of bias (low, high, or unclear), and in the first three domains, concerns about applicability (low, high, or unclear) were also considered. Two independent reviewers assessed the study's characteristics and methodological quality.
2.5. Statistical Analysis
HCV Ag sensitivity was the proportion of samples with a positive HCV RNA test that were also positive on HCV Ag testing. Specificity was the proportion of samples with negative HCV RNA testing that were also negative on HCV Ag testing. Sensitivity and specificity were the primary outcome measures.
Meta-analyses for each HCV Ag test were implemented to calculate the summary statistics, comprising point estimates and their respective 95% confidence intervals (95% CIs) by random-effects model (REM) and study heterogeneity (I2 statistics). Results from the univariate analyses (including all studies) were compared with the pooled estimates from the bivariate analyses where possible. Descriptive analyses were done for index tests with less than four studies and when substantial heterogeneity was evident from the inspection of the forest and summary plots.
Statistical analyses were performed using program R 4.0.2 with the General Package for Meta-Analysis (Package meta version 4.9-6).
3. Results
3.1. Study Selection and Characteristics
The systematic review identified 3,062 citations, of which 54 papers met inclusion criteria after reading abstract and full text papers (Figure 1). Fifty-four papers used HCV Ag for diagnosis of HCV infection, and some of these studies, as they analyzed different groups, are mentioned more than once in Table 1. And 17 of these 54 studies also provided information on HCV Ag for HCV treatment. Only one study [18] depicted in Table 2 had information about employment of HCV Ag for treatment and not for diagnosis, so this study is not mentioned in Table 1.
Figure 1.
Flow of information and stages of systematic review.
Table 1.
Main characteristic of studies that used HCV Ag testing to evaluate diagnosis of active HCV infection.
Year | Author (reference) | Country | HCV-GT | Study | HCV Ag assay | Gold standard | N | Sample | Correlation HCV Ag to HCV RNA | SE (%) | SP (%) |
---|---|---|---|---|---|---|---|---|---|---|---|
Chemiluminescence immunoassays | |||||||||||
2019 | Bo Feng et al. [39] | China | 1, 2, and 3 | Prospective | Architect HCV Ag (Abbott Diagnostics, Wiesbaden Germany) | HCV RNA | 782 | Serum | NA | 90.6% | 96.6% |
2019 | Łucejko et al. [40] | Poland | 1 | Prospective | Architect HCV Ag (Abbott Diagnostics, Wiesbaden Germany) | HCV RNA | 514 | Serum | Before r = 0.75; during r = 0.75; after r = 0.15 | 97.1% | 99.6% |
2019 | Catlett et al. [41] | Australia | NA | Cohort study | Architect HCV Ag (Abbott Diagnostics) | HCV RNA | 186 | Plasma/DBS |
r = .77 (plasma) r = .82 (DBS) |
98.1-100% (plasma), 90.7-92.5 (DBS) | 100% (plasma/DBS) |
2019 | Perez- Garcia et al. [42] | Spain | 1a, 1b, 2, 3, and 4 | Prospective | Architect HCV Ag (Abbott Diagnostics) | HCV RNA | 124 | Serum/plasma | r = 0.932 | 97% | 95% |
2019 | Fan et al. [36] | China | 1b | Retrospective | Architect HCV Ag (Abbott Diagnostics, Wiesbaden Germany) | COBAS AmpliPrep/COBAS TaqMan HCV test, v2.0 (Roche Molecular Systems, Pleasanton, CA, USA) | 135 | Serum | r = 0.986 | 80.2% | 89.7% |
2019 | Xiang et al. [43] | China | 1b, 2a, 3a, 3b, 6a, 1b/3b | Prospective | Architect HCV Ag (Abbott Diagnostics) | System (Roche Diagnostics) | 106 | Serum | r = 0.894 | 100% | NA |
2018 | van Tilborg et al. [44] | Canada | 1a, 1b, 1(unspecified), 2, 3, 4, 5, 6 | Retrospective | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV v2.0 (Roche) | 10006 | Serum | r = 0.97 | 99.0% | NA |
2018 | Nguyen et al. [24] | Vietnam | NA | Prospective | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan v2 (Roche) | 104 | DBS | r = 0.80 | 87.2% | 100% |
2018 | Adland et al. [45] | United Kingdom | 1, 3 | Retrospective | Architect HCV Ag (Abbott Diagnostics) | Abbott RealTime HCV assay (Abbott Molecular, Des Plaines, IL) | 305 | NA | r 2 = 0.3 | 97.7% | NA |
2018 | Lamoury et al. [28] | Australia | 1a, 1b, 2, 3a, 6 | Prospective | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV test v2.0 (Roche Diagnostics) | 120 | Plasma/DBS | Plasma r = 0.69 DBS r = 0.65 | 91.6% plasma and 82.9% DBS | 100% plasma and 96.1% no DBS |
2018 | Chevaliez et al. [14] | NA | 1b | Retrospective | Architect HCV Ag (Abbott Diagnostics) | Roche High-Pure system/COBAS TaqMan HCV test v2.0 (Roche) | 631 | Plasma | r 2 = 0.7357 | 99.80% | NA |
2017 | Wasitthankasem et al. [29] | Thailand | 1a, 1b, 3a, 3b, 6c, 6f, 6i, 6n | Transversal | Architect HCV Ag (Abbott Diagnostics) | Abbott RealTime HCV (Abbott Molecular) | 290 | Serum | r 2 = 0.890 | 100% | 97.1% |
2017 | Mohamed et al. [27] | Tanzania | 1a, 4a | Prospective | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV test v2.0 (Roche Molecular) | 153 | Serum/DBS | r = 0.80 | 99.1% serum and 76.7% DBS | 94.4% serum and 97.3% DBS |
2017 | Lucejko et al. [46] | Europe | 1a/1b/3a/4-2/29/0/2 | Longitudinal | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep HCV test (Roche Molecular Systems, Pleasanton, CA, USA) | 33 | Serum/plasma | r = 0.625 | 100% | NA |
2017 | Talal et al. [47] | EUA | 1a, 1b, 2, 3, 4 | Prospective | Architect HCV Ag (Abbott Diagnostics) | COBAS TaqMan assay (Roche Diagnostics) | 109 | Serum | r = 0.88 | 97.9% | 100% |
2017 | Rockstroh et at [15]. | NA | 1 | Retrospective | Architect HCV Ag (Abbott Diagnostics) | Roche High-Pure /COBAS TaqMan HCV test v2.0 (Roche Diagnostics) | 737 | Plasma | r 2 = 0.7520 | 99.05% | 100% |
2017 | Loggi et al. [48] | Italy | 1a, 1b, 1(subtype not available), 2, 3, 4 | Longitudinal | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV test v2.0 (Roche Diagnostics) | 96 | Serum | r = 0.767 | 100% | NA |
2017 | Arboledas et al. [49] | Spain | 1a, 1b, 2, 3, 4 | Prospective | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV assay (Roche Diagnostics) | 262 | Plasma | r = 0.83 | 98.7% | NA |
2017 | Arboledas et al. [49] | Spain | 1a, 1b, 2, 3, 4 | Retrospective | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV assay (Roche Diagnostics) | 132 | Plasma | r = 0.72 | 98.5% | NA |
2017 | Lamoury et al. [11] | Australia | 1, 2, 3 | Prospective | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV test v2.0 (Roche Diagnostics) | 92 | Plasma | rho = 0.89 | 94% | NA |
2017 | Alonso et al. [50] | Spain | 1a, 1b, 2c, 3, 4 | Retrospective | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV assay (Roche Diagnostics) | 28 | Serum | NA | 96.2% | 100% |
2016 | Aghemo et al. [13] | Italy | 1, 2, 3, 4, 5 | Prospective | Architect HCV Ag (Abbott Diagnostics) | Abbott RealTime HCV (Abbott Molecular) | 58 | Serum | NA | 100% | NA |
2016 | Pischke et al. [51] | Germany | 1, 2, 3, 4 | Retrospective longitudinal | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV test v2.0 (Roche Diagnostics) | 20 | NA | NA | 100% | NA |
2016 | Kim et al. [52] | South Korea | 1, 2 | Retrospective | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV assay(Roche Diagnostics) | 92 | Serum | BG∗ r = 0.798 | 98.9% | NA |
2015 | Kamal et al. [53] | Egypt | 4 | Prospective longitudinal | Architect HCV Ag (Abbott Diagnostics) | COBAS Amplicor version 2.0 (Roche Molecular) | 410 | Serum | r = 0.944 | 99.5% | 96.8% |
2015 | Garbuglia et al. [54] | Italy | 1a, 1b | Prospective | Architect HCV Ag (Abbott Diagnostics) | Abbott RealTime HCV (Abbott Molecular) | 23 | Plasma/serum | Day 0: r = 0.95 day 1: r = 0.79 day 4: r = 0.73 | 100% | NA |
2014 | Chevaliez et al. [55] | NA | 1, 2, 3a, 4, 5a, 6 | NA | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan HCV test v2.0 (Roche Diagnostics) | 514 | NA | r = 0.89 | 100% | 100% |
2014 | Garbuglia et al. [56] | Italy | 1a, 1b, 1c, 1a/b, 2a, 2c/b, 3a, 4a | Retrospective | Architect HCV Ag (Abbott Diagnostics) | Abbott RealTime HCV (Abbott Molecular) | 292 | Plasma | r = 0.815 | 90.4% | 87.5% |
2014 | Heidrich et al. [57] | Germany | 1n, 2n, 3n | Prospective | Architect HCV Ag (Abbott Diagnostics) | COBAS TaqMan assay v1.0 (Roche Diagnostics) | 596 | Serum | r = 0.803 | 92.9% | 98.9% |
2014 | Florea et al. [35] | Romania | NA | Retrospective | Architect HCV Ag (Abbott Diagnostics) | COBAS TaqMan assay (Roche Diagnostics) | 76 | Serum | r = 0.980 | 82.4% | 100% |
2014 | Long et al. [26] | China | 1b, 1a | Retrospective longitudinal | Architect HCV Ag (Abbott Diagnostics) | Abbott RealTime HCV (Abbott Molecular) | 227 | Plasma | HCV: r = 0.595 HCV/HIV-1: r = 0.884 |
100% | NA |
2013 | Hadziyannis et al. [58] | Greece | 1, 2, 3, 4 | NA | Architect HCV Ag (Abbott Diagnostics) | COBAS Amplicor v2.0 (Roche Molecular) | 89 | Serum | r = 0.89 | 93.2% | NA |
2013 | Tedder et al. [10] | UK | 1a, 1b, 2, 3 | Retrospective | Abbott Architect HCV (Abbott Diagnostics) | RT-PCR TaqMan in-house | 54 | Plasma | r = 0.6 | 90.7% | NA |
2012 | Murayama et al. [22] | Japan | 1a, 1b, 2a, 2b | Transversal | Architect HCV Ag (Abbott Diagnostics) | COBAS AmpliPrep/COBAS TaqMan (Roche Diagnostics) and Abbott RealTime HCV (Abbott Molecular) | 80 | Plasma | r = 0.9393 | 100% | NA |
2012 | Murayama et al. [22] | Japan | 1a, 1b, 2a, 2b | Transversal | Lumipulse Ortho HCV Ag (Fujirebio, Tokyo, Japan) | COBAS AmpliPrep/COBAS TaqMan (Roche Diagnostics) and Abbott RealTime HCV(Abbott Molecular) | 80 | Plasma | r = 0.9065 | 95% | NA |
2012 | Vermehren et al. [59] | NA | 1a, 1b | Prospective | Architect HCV Ag (Abbott Diagnostics) | Abbott RealTime HCV (Abbott Molecular) | 160 | Serum | (Versant HCV RNA Qualitative Assay) r = 0.91 and ART (Abbott RealTime HCV assay) r = 092 | 99.3% | NA |
2012 | Mederacke et al. [25] | Germany | 1a, 3a | Transversal | Architect HCV Ag (Abbott Diagnostics) | COBAS TaqMan assay (Roche Diagnostics) | 238 | Serum/plasma | HIV/HCV r = 0.97 HCV/HBV r = 0.04 | HCV/HIV: 95.7% HCV/HBV: 100% | HCV/HIV:1100% HCV/HBV:9100% |
2011 | Kesli et al. [60] | Turkey | 1b | Retrospective | Architect HCV Ag (Abbott Diagnostics) | QIAamp viral RNA minikit (Qiagen) | 212 | Serum | r = 0.864 | 96.3% | 100% |
2011 | Moscato et al. [30] | Italy | 1a, 1b, 2a, 2c, 3a, 4 | Retrospective | Architect HCV Ag (Abbott Diagnostics) | COBAS TaqMan assay (Roche Diagnostics) | 32 | Serum | r = 0.799 | Group A:97.1% group B: 100% | GroupA:100% group B: 100% |
2010 | Miedouge et al. [61] | France | 1, 1a, 1b, 1d, 2, 2a, 2b, 2c, 2k, 2i, 2r, 2x, 3a, 4a, 4c, 4d, 4r, 5a, 6 | Cohort | Architect HCV Ag (Abbott Diagnostics) | COBAS TaqMan assay (Roche Diagnostics) | 3009 | Serum | r = 0.904 | 100% | 99.2% |
2010 | Ross et al. [62] | Germany | 1a, 1b, 2a, 3a, 4a, 5a e 6f | Prospective | Architect HCV Ag (Abbott Diagnostics) | Versant HCV RNA v3.0 (Siemens Diagnostics) | 394 | Serum | r = 0.857 | 100% | 100% |
2005 | Masahiko Takahashi et al. [32] | Japan | NA | Prospective | Lumipulse Ortho HCV Ag (Ortho Clinical Diagnostics) | COBAS Amplicor version 2.0 (Roche Diagnostics) | 44 | Serum | r = 0.870 | 90.9% | NA |
ELISA | |||||||||||
2017 | Wang et al. [23] | China | NA | Longitudinal | ELISA HCV Ag (LaiBo Biotechnology) | Abbott RealTime HCV (Abbott Molecular) | 333 | Serum | r = 0.891 | 88.9% | 100% |
2012 | Murayama et al. [22] | Japan | 1a, 1b, 2a, 2b | Transversal | ELISA-Ag (Ortho Clinical Diagnostics, Tokyo, Japan) | COBAS AmpliPrep/COBAS TaqMan (Roche Diagnostics) and Abbott RealTime HCV (Abbott Molecular) | 80 | Plasma | r = 0.9666 | 100% | NA |
2012 | Murayama et al. [22] | Japan | 1a, 1b, 2a, 2b | Transversal | Ortho HCV Ag IRMA (Ortho Clinical Diagnostics, Tokyo, Japan | COBAS AmpliPrep/COBAS TaqMan (Roche Diagnostics) and Abbott RealTime HCV (Abbott Molecular) | 80 | Plasma | r = 0.9666 | 100% | NA |
2012 | Murayama et al. [22] | Japan | 1a, 1b, 2a, 2b | Transversal | Lumispot Eiken HCV Ag (Eiken Chemical, Tokyo, Japan) | COBAS AmpliPrep/COBAS TaqMan (Roche Diagnostics) and Abbott RealTime HCV (Abbott Molecular) | 80 | Plasma | r = 0.9666 | 100% | NA |
2008 | Medhi et al. [63] | India | NA | Transversal | Orthotrak-C™ (Ortho Clinical Diagnostics) (Ortho HCV 3.0) | QIAamp viral RNA minikit (Qiagen) in-house RT-PCR and real-time PCR | 250 | Serum | NA | 96% | 100% |
2006 | Reddy et al. [34] | India | NA | Retrospective | Ortho HCV Ag (Ortho Clinical Diagnostics) | COBAS Amplicor HCV test v2.0 (Roche) | 111 | Serum | NA | 60% | 83% |
2005 | Bouzgarou et al. [64] | Tunisia | 1a, 1b, 2c, 3a, 4c/4d | Retrospective | Orthotrak-C™ (Ortho Clinical Diagnostics) | In-house RT-PCR and COBAS Amplicor Monitor v2.0 (Roche version) | 76 | Serum | NA | 84% | 89% |
2005 | González et al. [21] | Spain | 1 | Cohort | Orthotrak-C™ (Ortho Clinical Diagnostics) | COBAS Amplicor HCV test v2.0 (Roche) and COBAS Amplicor HCV Monitor v2.0; Roche Diagnostics (RNA) | 58 | Serum | r = 0.781 | 42.5% | 100% |
2005 | Laperche et al. [7] | France | 1, 1a, 1b, 2a/c, 3a, 4a, 4c/d | Cohort | Orthotrak-C™ (Ortho Clinical Diagnostics) | COBAS Amplicor HCV test v2.0 (Roche) | 35 | Plasma | NA | Panel 1 : 100% Panel 2: 96.3% |
NA |
2005 | Massaguer et al. [65] | Spain | 1, 2, 3, 4 | Cohort | Orthotrak-C™ (Ortho Clinical Diagnostics) | COBAS Amplicor HCV test v2.0 (Roche) | 116 | Serum | r = 0.802 | 92.1% | 100% |
2005 | Fabrizi et al. [66] | Italy | NA | Prospective | Orthotrak-C™ (Ortho Clinical Diagnostics) | COBAS Amplicor HCV test v2.0 (Roche) | 292 | Serum | r = 0.892 | 92.7% | 97.4% |
2004 | Soffredini et al. [31] | Italy | 1a, 1b, 2a/c, 3a, 4c/d | Prospective | Orthotrak-C™(Ortho Clinical Diagnostics) | Versant HCV RNA v3.0 (Siemens Diagnostics) | 111 | Serum | r = 0.750 | 94% | NA |
2004 | Lorenzo et al. [67] | Spain | 1a, 1b, 2a/c, 3a | Cohort | Orthotrak-C™ (Ortho Clinical Diagnostics) | COBAS Amplicor HCV test v2.0 (Roche) | 16 | Serum | NA | 87.6% | 40% |
2004 | Schütler et al. [20] | Germany | NA | Prospective | Orthotrak-C™ (Ortho Clinical Diagnostics) | In-house real-time PCR | 23 | Serum | r 2 = 0.744 | 98% | 96.2% |
2003 | Tanaka et al. [68] | Japan | 1b, 2a, 2b | Retrospective | In-house | COBAS Amplicor HCV test v1.0 (Roche) | 207 | Serum | r = 0.627 | 97% | 100% |
Immunohistochemistry | |||||||||||
1997 | Ballardini et al. [19] | Italy | 1a,1b,2,3a,4a | Retrospective | In-house | RT-PCR in-house | 31 | Liver tissue | NA | 80.6% | NA |
Legend: NA: not available; GT: genotype; SE: sensitivity; SP: specificity; V: version; BG∗: both genotypes; r and rho: correlation coefficient; r2: coefficient of determination.
Table 2.
Main characteristic of studies that used HCV Ag testing to evaluate antiviral treatment.
Year | Author | Country | HCV Ag assay | N | Treatment | Sensitivity | Specificity | Concordance |
---|---|---|---|---|---|---|---|---|
2019 | Bo Feng et al. [39] | China | Architect HCV Ag (Abbott Diagnostics) | 782 | PEG-IFN-α and ribavirin | NA | NA | NA |
2020 | Lin et al. [18] | Architect HCV Ag (Abbott Diagnostics) | 110 | Paritaprevir/ritonavir, ombitasvir e dasabuvir | NA | NA | Baseline: 97.3, week 2 : 54.8, week 4 : 63.9, end: 89.7, post-W12: 98.6 | |
2019 | Fan et al. [36] | China | Architect HCV Ag (Abbott Diagnostics) | 135 | (PEG-INF-α) and RBV | Week 12: 96.5% | Week 12: 79.5% | NA |
2018 | van Tilborg et al. [44] | Canada | Architect HCV Ag (Abbott Diagnostics) | 10.006 | Treatment of direct acting antivirals (excluding TVR and BOC) with or without PEG-INF, RBV | Week 4: 34.6% End of treatment: 50% Follow-up week 12: 98.2% Follow-up week 24: 100% |
Week 4: 86.6% End of treatment: 97.5% Follow-up week 12: 97.7% Follow-up week 24: 100% |
NA |
2018 | Chevaliez et al. [14] | NA | Architect HCV Ag (Abbott Diagnostics) | 631 | PRV boosted with ritonavir and OBV in a single pill combined with DSV | Week 4: 71.0% Week 12: 96.2% Posttreatment week 12: 87.5% |
Week 4: 95.3% Week 12: 97.4% Posttreatment week 12: 98.9% |
Concordance: 99.84% Week 4: 97.05% Week 12: 98.8% Posttreatment week 12: 99% |
2017 | Łucejko et al. [46] | Europe | Architect HCV Ag (Abbott Diagnostics) | 33 | OBV/PRV/r±DSV±RBV and LDV/SOF | Day 7: 62.5% Week 4: 50% |
Day 7: 44.4% Week 4: 81.8% End of treatment: 100% |
NA |
2017 | Rockstroh et al. [15] | NA | Architect HCV Ag (Abbott Diagnostics) | 737 | RTV-boosted PRV and OBV with DSV coadministered with or without RBV | NA | NA | Concordance between HCV Ag and HCV RNA in week 4 (96.46%) and posttreatment week (99.75%) |
2017 | Loggi et al. [48] | Italy | Architect HCV Ag (Abbott Diagnostics) | 96 | 3D±RBV; SOF±RBV; SOF+SMV±RBV; SOF+LDV±RBV; SOF+DCV; SOF+PEG-IFN-α+RBV | Week 2: 42.8% week 4: 31.25% week 8 and 12: 0% | Week 2: 84.2% Week 4: 78.4% Week 8: 82.1% Week 12: 90.4% Week 16 and 24: 100% |
NA |
2017 | Arboledas et al. [49] | Spain | Architect HCV Ag (Abbott Diagnostics) | 262 | 2D+RBV; 3D±RBV; SOF+DAC±RBV; SOF+LED±RBV; SOF+SIM±RBV; SOF+PEG+RBV; SOF+RBV; SIM+DAC+RBV | NA | NA | Week 1: 56.7% Week 4: 83% End of treatment: 93.5% |
2017 | Lamoury et al. [11] | Australia | Architect HCV Ag (Abbott Diagnostics) | 92 | PEG-INF-α-2b and RBV | Treatment: 31% Posttreatment: 100% End of treatment: 56% SVR12/24 : 100% sensitivity and specificity |
Treatment: 98% Post treatment: 100% End of treatment: 100% |
NA |
2017 | Alonso et al. [50] | Spain | Architect HCV Ag (Abbott Diagnostics) | 28 | Viekirax+Exviera/Harvoni/Viekirax+Exviera+RBV/Harvoni+RBV/Sovaldi/SOF+DCV/SOF+SMV+RBV | NA | End of treatment: 92.8% | NA |
2016 | Aghemo et al. [13] | Italy | Architect HCV Ag (Abbott Diagnostics) | 58 | PRV/RTV/OBV+DSV±RBV or SOF+SMV±RBV/SOF+RBV/PEG-IFN associate SOF+RBV/SOF+RBV or SOF+SMV±RBV | NA | NA | Concordance HCV RNA and HCV Ag: week 2: 40%; week 4: 55%; at the end of treatment, as expected, the agreement between the tests raised to 95%. |
2016 | Kim et al. [52] | South Korea | Architect HCV Ag (Abbott Diagnostics) | 92 | PEG-IFN-α-2a | Week 4: 33.3% | Week 4: 100% | NA |
2015 | Kamal et al. [53] | Egypt | Architect HCV Ag (Abbott Diagnostics) | 410 | PEG-IFN-α2a and RBV | Week 4: 100% Week 12: 100% |
Week 4: 97.5% Week 12: 99.3% |
NA |
2014 | Florea et al. [35] | Romania | Architect HCV Ag (Abbott Diagnostics) | 1782 | IFN+RBV | 4 weeks: 77.9% 12 weeks: 52.1% 24 weeks: 48.1% 48 weeks: 88.2% 72 week: 96.1% |
4 weeks: 100% 12 weeks: 100% 24 weeks: 100% 48 weeks: 100% 72 week: 100% |
NA |
2005 | González et al. [21] | Spain | Orthotrak-C™ (Ortho Clinical Diagnostics) | 58 | IFN-α2α+RBV | Week 4: 42.5% Week 12: 10.5% 24 weeks after end of: 88.9% |
EOT week 4: 100% EOT week 12: 100% 24 weeks after end of: 100% |
NA |
2005 | Masahiko Takahashi et al. [32] | Japan | Lumipulse Ortho HCV Ag (Ortho Clinical Diagnostics) | 44 | PEG-IFN-α-2a+RBV | Week 7: 76.9% Day 15: 74.1% |
NA | Week 7: 79.5%; day 15 = 4: 75% |
2004 | Soffredini et al. [31] | Italy | Orthotrak-C™ (Ortho Clinical Diagnostics) | 111 | IFN+RBV | Week 12: 70.5% 6 months after therapy: 94.2% |
NA | NA |
Legend: PEG: peliguiado; BOC: boceprevir; TVR: telaprevir; DCV: daclastavir; SOF: sofosbuvir; DAC: daclavir; DSV: dasabuvir; LDV: ledipasvir; OBV: ombitasvir; PRV: paritaprevir; RBV: ribavirin; RTV: ritonavir; IFN: interferon; SIM/SMV: simeprevir; NA: not available.
Among the 54 studies that evaluated the detection of HCV Ag for the diagnosis of HCV, most of papers (n = 42) that used the electrochemiluminescence methodology presented high quality. In general, all assays were qualitative, both EIA or ECLIA.
The main characteristics of studies included here are presented in Tables 1 and 2. Papers from 20 countries were published from 1997 to 2019. A total of 14,286 individuals were included in papers that evaluated HCV Ag for diagnosis, and 15,680 individuals were reported in papers that used HCV Ag to monitor antiviral treatment. A total of 49 studies provided information on HCV genotypes in infected individuals.
3.2. Quality Assessment
The overall risk of bias assessment for studies included was evaluated using QUADAS-2 and quality scores of these studies (Supplemental Material, Figures S1, S2, S3). The overall quality of the studies was high where reports using electroquimioluminescence had the best quality. According to figure S2, the risk of bias was higher in the test index.
This was also demonstrated in the individual analysis of the studies (Figure S3). The quality with the ELISA and immunohistochemistry tests, as the index test, proved to be lower [19–23]. And also, two of the three studies evaluated samples of DBS [11, 24].
3.3. HCV Antigen for Diagnosis of HCV Active Infection
In this review, different types of studies were included such as the following: longitudinal, transversal, prospective, retrospective, and cohort. One study included HCV/HBV-coinfected individuals, and two studies enrolled HCV/HIV-coinfected patients [25, 26].
Four studies demonstrated sensitivity values lower than 87.2%, but three of these studies employed dried blood spot (DBS) samples for testing [24, 27, 28]. A total of 15 studies used ELISA as detection method where only three of them reported sensitivity ≤ 60%. Only one study used the immunohistochemistry technique to detect HCV Ag [19]. Table 3 demonstrates sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), correct classification (accuracy), and Kappa for studies.
Table 3.
Sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), correct classification (accuracy), and Kappa for studies.
Article | SE | SP | PPV | NPV | Accuracy | Kappa |
---|---|---|---|---|---|---|
Lamoury, 2018 [28] | 97.7 | 100.0 | 100.0 | 94.1 | 98.3 | 97.1 |
Lamoury, 2018 [28] | 88.6 | 96.9 | 98.7 | 75.6 | 90.8 | 89.7 |
Adland, 2018 [45] | 94.5 | 100.0 | 100.0 | 90.5 | 96.4 | 95.3 |
Nguyen, 2018 [24] | 87.2 | 100.0 | 100.0 | 57.7 | 89.1 | 87.8 |
Wasitthankasem, 2017 [29] | 100 | 97.1 | 99.1 | 100.0 | 99.3 | 98.0 |
Alonso, 2017 [50] | 96.4 | 100.0 | 100.0 | 96.6 | 98.2 | 97.2 |
Mohamed, 2017 [27] | 99.1 | 94.4 | 98.3 | 97.1 | 98.0 | 96.7 |
Mohamed, 2017 [27] | 76.7 | 97.3 | 98.9 | 57.1 | 81.7 | 80.6 |
Talal, 2017 [47] | 97.9 | 100.0 | 100.0 | 98.4 | 99.1 | 98.1 |
Rockstroh, 2017 [15] | 99.5 | 100.0 | 100.0 | 99.4 | 99.7 | 98.7 |
Chevaliez, 2014 [14] | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 98.9 |
Garbuglia, 2014 [56] | 91.4 | - | 100.0 | - | 91.4 | 89.6 |
Heidrich, 2014 [57] | 92.6 | 98.9 | 99.6 | 83.9 | 94.4 | 93.2 |
Mederacke, 2012 [25] | 95.7 | 100.0 | 100.0 | 25.0 | 95.8 | 93.9 |
Mederacke, 2012 [25] | 100.0 | 90.9 | 94.6 | 100.0 | 96.5 | 95.4 |
Mederacke, 2012 [25] | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 98.9 |
Yuksel, 2011 [69] | 94.3 | 97.9 | 99.1 | 87.0 | 95.3 | 94.2 |
Kesli, 2011 [60] | 96.3 | 100.0 | 100.0 | 89.7 | 97.2 | 95.9 |
Moscato, 2011 [30] | 100.0 | - | 97.1 | - | 97.1 | 95.2 |
Moscato, 2011 [30] | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 98.4 |
Miedouge, 2010 [61] | 98.9 | 100.0 | 100.0 | 88.9 | 99.0 | 97.3 |
Ross, 2010 [62] | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 98.8 |
Medhi, 2008 [63] | 96.4 | 100.0 | 100.0 | 86.7 | 97.1 | 95.7 |
Reddy, 2006 [34] | 14.3 | 97.8 | 60.0 | 83.0 | 82.0 | 80.4 |
Bouzgarrou, 2005 [64] | 83.6 | 88.9 | 99.0 | 29.6 | 84.0 | 82.5 |
Gonzalez, 2005 [21] | 68.9 | 100.0 | 100.0 | 74.7 | 83.8 | 82.8 |
Massaguer, 2005 [65] | 92.1 | 100.0 | 100.0 | 65.5 | 93.1 | 91.7 |
Fabrizi, 2005 [66] | 92.7 | 97.4 | 94.7 | 96.5 | 95.9 | 94.8 |
Lorenzo, 2004 [67] | 87.7 | 40.0 | 95.9 | 16.7 | 84.9 | 83.2 |
Schuttler, 2004 [20] | 98.0 | 96.2 | 99.0 | 92.7 | 97.6 | 96.3 |
Tanaka, 2000 [68] | 97.3 | 100.0 | 100.0 | 98.5 | 99.0 | 98.0 |
Lucejko, 2000 [40] | 97.1 | 99.6 | 99.6 | 96.7 | 98.2 | 97.2 |
Catlett, 2019 [41] | 100.0 | 99.2 | 98.1 | 100.0 | 99.5 | 98.3 |
Catlett, 2019 [41] | 100.0 | 96.4 | 90.7 | 100.0 | 97.3 | 96.1 |
Garcia, 2019 [42] | 97.7 | 97.7 | 96.9 | 98.3 | 97.7 | 96.7 |
Mederacke, 2012 [25] | 98.3 | 96.6 | 98.9 | 95.0 | 97.9 | 96.6 |
Feng, 2020 [39] | 97.0 | 97.6 | 92.4 | 99.1 | 97.5 | 96.2 |
Lin, 2020 [18] | 97.3 | 98.1 | 99.1 | 94.5 | 97.5 | 96.4 |
Mean value | 95.3 | 94.0 |
Most of studies included genotypes 1a and 1b (29/54), and it was observed a false negative correlation between HCV Ag detection and genotype 3 [29] and high concordance between HCV Ag and HCV RNA results among studies that included HCV patients coinfected with HBV and HIV. Moscato et al. [30] demonstrated a correlation between true positive results and genotype 1b.
A total of 23 studies were included in the univariate pooled sensitivity and specificity estimates. The pooled sensitivity and specificity with 95% CI were 98.82% (95%CI = 98.04%; 99.30%) and 98.95% (95%CI = 97.84%; 99.49%), respectively (Figure 2). Heterogeneity is visually assessed in Figures 2(a) and 2(b). The studies appear to be homogeneous in the overall where I2 was 65% (P = 0.97) for specificity and I2 was 50% (P = 0.99) for sensitivity estimates.
Figure 2.
(a) Forest plot of HCV Ag assay sensitivity for the diagnosis of active HCV infection compared to HCV RNA test for all samples regardless of HCV Ab status. TP: true positive; FN: false negative; CI: confidence interval. (b) Forest plot of HCV Ag assay specificity for the diagnosis of active HCV infection compared to HCV RNA test for all samples regardless of HCV Ab status. TP: true positive; FN: false negative; CI: confidence interval.
3.4. HCV Antigen for Monitoring Antiviral Therapy
A total of 18 studies used HCV Ag testing to evaluate antiviral treatment (Table 3). Most of studies (15/18) used ECLIA methodology, and only three of them used ELISA [21, 31, 32]. It was not possible to calculate sensitivity and specificity for most of studies. Nine studies used PEG-IFN/ribavirin as antiviral treatment. Nine out of 18 studies used DAA for antiviral treatment. In addition, only 5 reported concordances between HCV and HCV RNA. Regarding the utility of HCV Ag testing and therapy, five studies demonstrated HCV Ag results at 4 weeks and end of treatment and only two assessed SVR. At the end of treatment, sensitivities varied from 50 to 100% while specificities varied from 92.8% to 100%. At week 4 after beginning of treatment, sensitivities of HCV Ag testing varied from 31.25 to 77.9%. High concordance was found between HCV Ag testing and HCV RNA detection after completion of treatment. Those five studies found agreement from 89.7% to 99.75%.
4. Discussion
This review is aimed at evaluating HCV Ag detection test as an alternative to HCV-RNA for the diagnosis of active HCV infection and for the monitoring of antiviral treatment. We concluded that HCV Ag testing can be an alternative to HCV RNA testing for molecular diagnosis of HCV infection.
HCV Ag testing demonstrated pooled sensitivity of 98.82% (95%CI = 98.04%; 99.30%) and specificity of 98.95% (95%CI = 97.84%; 99.49%). ECLIA technology presented higher values of sensitivity and specificity for detecting HCV Ag to identify HCV active cases. However, this technique is more widely used for HCV Ag in comparison to ELISA technique. Galli et al. [33] showed that the ECLIA technique specifically from Abbott Diagnostics Architect HCV Ag, which is the test most commonly used today, detects up to 0.06 pg/ml HCV Ag, whereas older ELISA tests such as Ortho Core antigen detect only samples with 10 pg/ml or more of HCV Ag. Reddy et al. [34] only recruited chronic kidneys and found a sensitivity in HCV Ag detection of only 60% in ELISA tests. It is important to note that this low value may also be related to the clinical condition of these individuals. However, it was not possible to evaluate this information in this review due to few information regarding this topic.
DBS samples were used as biological sample for detecting HCV Ag using ECLIA methodology and showed sensitivity ≤ 87.2% [24, 27, 28] when compared to HCV Ag detection in serum or plasma. Because of this, the use of DBS samples also needs to be further studied to facilitate the diagnosis by detecting HCV Ag. Studies that used serum or plasma with the ECLIA methodology in the diagnosis of HCV Ag showed a sensitivity between 90.4 and 100% compared to HCV RNA detection. Two studies demonstrated lower sensitivities. Florea et al. [35] found 82.4% sensitivity but test demonstrated good performance in patients with HCV RNA ≥ 1000 IU/mL. Fan et al. [36] found 80.2% sensitivity but it was not possible to identify the reasons for this low value.
This study also reviewed several studies that analyzed the use of HCV Ag in monitoring treatment for HCV, with different drugs and at different times of treatment. Most of these studies used ECLIA technique. Gonzalez et al. [21] suggest that ELISA for HCV Ag detection is not used to monitor the end of treatment or an SVR due to the low sensitivity of the test presented in the study (42.5%). Few studies evaluated the concordance between HCV Ag testing and HCV RNA detection to evaluate antiviral treatment, but those studies found values from 89.7% and 95% demonstrating the feasibility of HCV Ag testing to replace HCV RNA detection in low-resource areas. It was also observed that HCV Ag testing has high sensitivity at end of treatment compared to 4 weeks after beginning of treatment. Fan et al. [36] suggested that HCV Ag may be a more sensitive predictor of relapse than HCV RNA after antiviral treatment.
Most of studies that evaluated the accuracy of the HCV Ag test for the diagnosis of HCV were conducted in regions of high HCV prevalence, and this affects the performance of assay to detect HCV acute cases. In the present study, it was observed that sensitivity was not always 100% due to differences in prevalence or population studied. In these cases, such as hemodialysis and people living with HIV, it should be interesting to perform HCV RNA in HCV Ag negative cases to rule out false negative cases [37, 38]. This situation could increase the costs, but it remains a low-cost strategy compared to HCV RNA testing in all subjects. Economic analysis of HCV Ag testing should be relevant in high HCV settings. If the short- and long-term consequences of the HCV Ag test false positives (FPs) and false negatives (FNs) cost less than the extra cost of using the HCV RNA, to use the HCV Ag test will be efficient.
This study presents some limitations such as the evaluation of HIV or HBV coinfection and HCV genotype in meta-analysis results. In addition, it was not possible to determine sensitivity and specificity of HCV Ag testing to evaluate antiviral treatment due to absence of data and few studies have analyzed SVR after treatment with DAAs.
We conclude that HCV Ag detection using ECLIA technique, especially in serum samples, is useful to identify HCV active cases. In addition, this assay presented good results to evaluate antiviral response particularly for PEG-IFN therapy. HCV Ag assay could be an important tool to increase HCV diagnosis in low-resource areas.
Acknowledgments
This research was supported by the Fundação de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ), the Brazilian National Counsel of Technological and Scientific Development (CNPq), and the Oswaldo Cruz Foundation (FIOCRUZ). FIB and JCM are members of the “Brazil's Fight Against Hepatitis C: Surveillance, Control, and Care” collaborative network, comprised by FGV (Getúlio Vargas Foundation, Brazil), FIOCRUZ (Oswaldo Cruz Foundation), and LSE (London School of Economics and Political Science). The consortium is core funded by the Newton Fund (“Institutional Links” initiative), in partnership with the Brazilian institutions.
Data Availability
All data are available in the manuscript and supplementary materials.
Disclosure
The funders had no role in designing the study and collection, analysis, and interpretation of data and in writing the manuscript.
Conflicts of Interest
The authors declare that they have no competing interests in this section.
Supplementary Materials
Supplementary figures demonstrated the quality of studies. S1 shows the risk of bias, S2 shows the applicability of studies, and S3 gives the QUADAS-2 assessment. Figure S1: risk of bias graph. Figure S2: applicability concern graph. Figure S3: QUADAS-2 assessment tool for studies of diagnostic accuracy.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary figures demonstrated the quality of studies. S1 shows the risk of bias, S2 shows the applicability of studies, and S3 gives the QUADAS-2 assessment. Figure S1: risk of bias graph. Figure S2: applicability concern graph. Figure S3: QUADAS-2 assessment tool for studies of diagnostic accuracy.
Data Availability Statement
All data are available in the manuscript and supplementary materials.