Description of the condition
Hepatitis B virus (HBV) is a unilaterally double stranded, enveloped DNA virus that is spread by parental contact with infected blood or by sexual contact (Lok 2007). HBV is geographically distributed and its incidence and prevalence is greatly influenced by prompt and adequate treatment (Chu 2003).
Globally, HBV is a public health problem and affects about 2 billion people, of which about 400 million progress to chronic HBV (Alter 2006). Progression to chronic HBV depends on several factors including mode of transmission, genetic factors, age, concomitant hepatitis C, hepatitis D or human immunodeficiency virus (HIV), level of resistance, and HBV mutation (Myers 2002; Yim 2006; Lok 2007; Iorio 2010). Even though vaccination and neonatal immunisation can be used in preventing hepatitis B infection, they are not effective in treating patients with chronic hepatitis B (Aggarwal 2003). Patients with chronic hepatitis B may develop complications such as cirrhosis and liver cancer if not treated adequately or early enough (Hadziyannis 2001).
Description of the intervention
Several drugs are now available in treating chronic hepatitis B, but unfortunately, most of the available treatments are hepatotoxic and associated with high drug resistance. These drugs are divided into two main groups based on their action mechanism: (a) immunomodulatory drugs such as interferon-alpha (b) antiviral drugs including lamivudine and adefovir dipivoxil (Aggarwal 2004). Interferon alpha is highly efficient in patients with severe HBe-Ag positive HBV and has a hepatitis B antigen reaction of 32% in treated patients compared to 11% in patients treated with placebo (Wong 1993). Notwithstanding, the use of Interferon alpha has been narrowed as a result of severe side effects, high cost, and demand for more injections. Lamivudine is more affordable to interferons and is conveniently take per os. Although lamivudine reacts similarly to interferon with lesser side effects, its period of administration is unspecified among patients needing life-long treatment (Lai 2003a). Due to its lengthy period of treatment, patients on lamivudine could develop mutation in the HBV genome, resulting in drug immunity and aggravated liver disease (Lai 2003). Adefovir dipivoxil is a newer anti-viral drug option, and compared to the traditional immunomodulatory and anti-viral drugs, it seems to have the benefit of lowering the incidence of drug resistance, but it is metabolised and excreted by the kidneys. Therefore, when administered with other drugs that alter tubular secretion, it may result in an increase in serum concentrations of either adefovir dipivoxil or the administered drug (Hadziyannis 2003)
How the intervention might work
Isoprinosine is a molecular complex of inosine: 2-hydroxypropyldimethylammonium 4-acetamido-benzoate 1:3. It has been demonstrated that isoprinosine inhibits replication of many RNA and DNA viruses in vivo and in vitro (Cianciara 1990), and exerts an immunostimulatory effect by enhancing T-cell function and macrophage activity (Kowalik-Mikołajewska 1993).
Why it is important to do this review
Compared to the traditional drugs used for treating chronic hepatitis B which are either immunomodulatory or antiviral in nature, isoprinosine has both properties. Despite this significant benefit of its dual mechanism of action in treating chronic hepatitis B, isoprinosine is reported to have side effects which range from dyspepsia, hypersensitivity reactions, and severe drug reactions with ribavirin that may result in a drop in the white blood cell count of patients. Therefore, providers have to carefully evaluate the adverse events of therapy compared to the benefits for this group of patients. As we did not identify any meta-analyses or systematic reviews evaluating the beneficial and harmful effects of isoprinosine for patients with chronic hepatitis B, we took upon this Cochrane Hepato-Biliary Group systematic review.
To assess the benefits and harms of isoprinosine in the treatment of patients with chronic HBV infection.
Criteria for considering studies for this review
Types of studies
We will include all relevant randomised clinical trials irrespective of language, year of publication, type of publication, or publication status. Quasi-randomised or observational studies that may be retrieved with the searches for randomised clinical trials will be scrutinised for the report of harm only.
Types of participants
We will include participants with chronic active HBV infection. As patients with chronic active HBV infection may be HBe-Ag positive and HBe-Ag negative, we will follow the following definitions (Lok 2007):
- HBe-Ag positive chronic hepatitis B infection defined as HBsAg positivity for more than six months, serum HBV DNA positivity more than 20,000IU/ml, ie, 105 copies/ml, persistent or intermittent elevation in levels of aspartate aminotransferase or alanine aminotransferase, and liver biopsy findings showing chronic hepatitis B with moderate or severe necroinflammation, or any definitions employed by the authors of the publications, making it likely that the patients had chronic hepatitis B.
- HBe-Ag negative chronic hepatitis B infection defined as HBsAg positivity for more than six months, serum HBV DNA positivity with lower values of 2,000 to 20,000 IU/ml, ie, 104 to 105 copies/ml, and persistent or intermittent elevation in levels of aspartate aminotransferase or alanine aminotransferase, and liver biopsy findings showing chronic hepatitis B with moderate or severe necroinflammation, or any definitions employed by the authors of the publications, making it likely that the patients had chronic hepatitis B.
We will include trials with both children and adult participants. For the purpose of this review we will define a child as aged 15 years or less and an adult as aged 16 years or older. Patients will be included irrespective of whether they are treatment-naive or have previously been treated unsuccessfully for chronic HBV infection with another drug. We will include patients with evidence of concomitant HIV infection, hepatitis C, hepatitis D, hepatocellular carcinoma, or other liver related co-morbidities, but we will analyse the patients with and without these conditions in separate. Patients with prior liver transplantation or those with concomitant renal failure will also be included, but again analysed separately.
Types of interventions
We will include trials which compare isoprinosine versus other hepatitis B antiviral drugs.
In all included trials, the experimental group will be considered the one which receives isoprinosine and the control group will be considered the one which receives other hepatitis B antiviral drugs.
Protocol-specific co-interventions will be allowed as long as administered equally to all intervention groups. Other concomitant interventions for any co-morbidity will be allowed; it will be assumed that access to concomitant therapeutic interventions will be administered equally regardless of intervention group.
Types of outcome measures
1. All-cause mortality.
2. Hepatitis B-related mortality (caused by morbidities or decompensation of the liver such as liver cirrhosis or hepatocellular carcinoma).
3. Hepatitis B-related morbidity (or decompensation of the liver such as liver cirrhosis or hepatocellular carcinoma).
4. Number of participants with serious and non-serious adverse events in separate. Serious adverse events will be defined as any untoward medical occurrence that is life threatening, results in death or persistent or significant disability, or any medical event which may have jeopardised the patient or required intervention to prevent it (ICH-GCP 1997). All other adverse events (ie, any medical occurrence not necessarily having a casual relationship with the treatment, but did, however, cause a dose reduction or discontinuation of treatment) will be considered non-serious.
5. Quality of life (as defined by the trialists).
1. Number of participants with detectable HBsAg in serum or plasma.
2. Number of participants with detectable HBV DNA in serum or plasma.
3. Number of participants with detectable HBeAg in serum or plasma (this outcome is not relevant for the HBseAg-negative participants).
4. Number of participants without HBeAg seroconversion in serum or plasma (this outcome is not relevant for the HBeAg-negative participants).
5. Number of participants with worsened liver histology.
Search methods for identification of studies
We will search The Cochrane Hepato-Biliary Group Controlled Trials Register (Gluud 2011), the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library, MEDLINE, EMBASE, and Science Citation Index EXPANDED (Royle 2003). Preliminary search strategies are given in Appendix 1 with the expected time span of the searches. The searches will be improved at the review stage, if necessary.
Searching other resources
The bibliographic references of identified randomised clinical trials, textbooks, review articles, and meta-analyses will be checked in order to find randomised clinical trials that were not identified by the electronic searches. We will also identify studies from conference databases and ongoing trials by reviewing the reference lists and contacting the principal authors of the identified trials.
Data collection and analysis
We shall carry out a meta-analysis of the results from methodologically and clinically comparable trials. The review will be performed according to the recommendations of The Cochrane Collaboration (Higgins 2011) and the Cochrane Hepato-Biliary Module (Gluud 2011). The analyses will be performed using Review Manager 5 (RevMan 2008).
Selection of studies
Two of three authors (SK and BN) will independently assess trials for inclusion and exclusion. BN will independently review those to be excluded to ensure accuracy. SK and BN will read the titles, abstracts and descriptor terms of all downloaded material from the electronic searches to identify potentially eligible reports. Full text articles will be obtained for all citations identified as potentially eligible, and BN and SK will independently inspect these to establish the relevance of the article according to the pre-specified criteria (types of studies, participants, interventions, and outcomes). Where there is any uncertainty as to the eligibility of the record, we will obtain the full article. BN and SK will independently apply the inclusion criteria, and any differences arising will be resolved by discussions with EK. Studies will be reviewed for relevance based on study design, types of participants, exposures, and outcomes.
Data extraction and management
From the selected trial, the following data will be extracted in respect of treatment of HBeAg-positive patients with chronic hepatitis B:
a) Proportion without disappearance of HBeAg in the serum (HBeAg negativity rate), and
b) Proportion without seroconversion from HBeAg-positive status to anti-HBe positive status (seroconversion).
In addition, for both HBeAg-positive and HBeAg-negative patients, data will be extracted regarding the following variables:
a) Proportion with disappearance of serum HBV DNA at the end of treatment duration or decrease in HBV DNA level below 100,000 copies/ml (end-of-treatment virological response),
b) Proportion without return of liver enzyme levels to normal range (end of treatment biochemical response),
c) Proportion without disappearance of HBV DNA or decrease in HBV DNA level below 100,000 copies/ml with maintenance of this status for at least six months after discontinuation of drug (sustained virological response),
d) Proportion with clinical events like decompensation of liver disease,
e) Proportion without histological improvement.
Data on (a) mortality during the trial period, (b) serious adverse events, including deterioration of clinical liver function, and (c) development of viral resistance to the drug used will also be extracted.
Assessment of risk of bias in included studies
We will assess risk of bias of all fulfilling the inclusion criteria trials at the trial level, using the Cochrane 'risk of bias' tool given in the Cochrane Handbook of Systematic Reviews of Interventions (Higgins 2011) with the following domains and definitions (Schulz 1995; Moher 1998; Kjaergard 2001; Wood 2008; Savović 2012a; Savović 2012b; Lundh 2012):
Allocation sequence generation
- Low risk of bias: sequence generation was achieved using computer random number generation or a random number table. Drawing lots, tossing a coin, shuffling cards, and throwing dice are adequate if performed by an independent person not otherwise involved in the trial.
- Uncertain risk of bias: the method of sequence generation was not specified.
- High risk of bias: the sequence generation method was not random.
- Low risk of bias: the participant allocations could not have been foreseen in advance of, or during, enrolment. Allocation was controlled by a central and independent randomisation unit. The allocation sequence was unknown to the investigators (for example, if the allocation sequence was hidden in sequentially numbered, opaque, and sealed envelopes).
- Uncertain risk of bias: the method used to conceal the allocation was not described so that intervention allocations may have been foreseen in advance of, or during, enrolment.
- High risk of bias: the allocation sequence was likely to be known to the investigators who assigned the participants.
Blinding of participants, personnel, and outcome assessors
- Low risk of bias: blinding was performed adequately, or the assessment of outcomes was not likely to be influenced by lack of blinding.
- Uncertain risk of bias: there was insufficient information to assess whether blinding was likely to induce bias on the results.
- High risk of bias: no blinding or incomplete blinding, and the assessment of outcomes were likely to be influenced by lack of blinding.
Incomplete outcome data
- Low risk of bias: missing data were unlikely to make treatment effects depart from plausible values. Sufficient methods, such as multiple imputation, has been employed to handle missing data.
- Uncertain risk of bias: there was insufficient information to assess whether missing data in combination with the method used to handle missing data were likely to induce bias on the results.
- High risk of bias: the results were likely to be biased due to missing data.
Selective outcome reporting
- Low risk of bias: all outcomes were pre-defined and reported, or all clinically relevant and reasonably expected outcomes were reported.
- Uncertain risk of bias: it is unclear whether all pre-defined and clinically relevant and reasonably expected outcomes were reported.
- High risk of bias: one or more clinically relevant and reasonably expected outcomes were not reported, and data on these outcomes were likely to have been recorded.
For a trial to be assessed with low risk of bias in the selective outcome reporting domain, the trial should have been registered either on the www.clinicaltrials.gov web site or a similar register, or there should be a protocol, e.g., published in a paper journal. In the case when the trial was run and published in the years when trial registration was not required, we will carefully scrutinize all publications reporting on the trial to identify the trial objectives and outcomes. If usable data on all outcomes specified in the trial objectives are provided in the publications results section, then the trial can be considered low risk of bias trial in the Selective outcome reporting domain.
- Low risk of bias: the trial appears to be free of industry sponsorship or other kind of for-profit support that may manipulate the trial design, conductance, or results of the trial.
- Uncertain risk of bias: the trial may or may not be free of for-profit bias as no information on clinical trial support or sponsorship is provided.
- High risk of bias: the trial is sponsored by the industry or has received other kind of for-profit support.
- Low risk of bias: the trial appears to be free of other components that could put it at risk of bias.
- Uncertain risk of bias: the trial may or may not be free of other components that could put it at risk of bias.
- High risk of bias: there are other factors in the trial that could put it at risk of bias, eg, authors have conducted trials on the same topic etc.
If the risk of bias in a trial is judged as 'low' in all the listed above domains, the trial will fall in the 'low risk of bias' group trials. If the risk of bias in the assessed trials is judged as 'uncertain' or 'high' in one or more of the specified domains, then the trial will fall in the group with 'high risk of bias' trials.
If disagreements among authors' evaluation occur, we will resolve them by discussion among us all.
Measures of treatment effect
Outcome measures for binary data will be calculated as a relative risk with 95% confidence intervals. Continuous data (eg, CD4+ cell counts, HBV DNA levels) will be calculated using mean differences and standard deviations. Data will be analysed using the intention-to-treat principle, that is, patients with missing data will be considered as treatment failures. The number needed to treat to benefit (NNT) will be calculated as 1/((1-relativerisk)*control group event proportion), wherever applicable.
Unit of analysis issues
We anticipate that the unit of analysis will be the participants in each randomised group.
Dealing with missing data
We will contact study authors for data that were measured but not reported. All analyses will be performed according to the intention-to-treat method, using the last reported observed response ('carry forward'), and including all participants irrespective of compliance or follow-up.
Regarding the four first primary outcomes we will include patients with incomplete or missing data in the sensitivity analyses by imputing them according to the following two extreme scenarios (Hollis 1999; Gluud 2013):
- Extreme case analysis favouring the experimental intervention ('best-worse' case scenario): none of the dropouts/participants lost from the experimental arm, but all of the dropouts/participants lost from the control group experienced the outcome, including all randomised participants in the denominator.
- Extreme case analysis favouring the control ('worst-best' case scenario): all dropouts/participants lost from the experimental arm, but none from the control arm experienced the outcome, including all randomised participants in the denominator.
Assessment of heterogeneity
We will formally test for statistical heterogeneity using the Chi square test for statistical homogeneity with a P < 0.1 set as the cut-off. The impact of any statistical heterogeneity will be quantified using the I² statistic (Higgins 2011).
We will interpret the I
- 0% to 40%: might not be important;
- 30% to 60%: may represent moderate heterogeneity;
- 50% to 90%: may represent substantial heterogeneity;
- 75% to 100%: considerable heterogeneity.
Assessment of reporting biases
Publication bias will be assessed by looking for funnel plot asymmetry (Egger 1997) if there are at least ten included trials.
We will meta-analyse the data with both a random-effects model (Der Simonian 1986) and a fixed-effect model (DeMets 1987). In case of discrepancy in the results of two models, we will present the results with both methods. If there is no statistically significant difference in the results, then we will present the results with the fixed-effect model.
Trial sequential Analysis
Trial sequential analysis' will be applied because cumulative meta-analyses are at risk of producing random errors due to sparse data and repetitive testing on the accumulating data. The underlying assumption of trial sequential analysis is that testing for significance may be performed each time a new trial is added to the meta-analysis. We will add the trials according to the year of publication, and if more than one trial was published in a year, trials will be added alphabetically according to the last name of the first author (Brok 2008; Wetterslev 2008). We plan to calculate the required information size (ie, the number of participants needed in a meta-analysis to detect or reject a certain intervention effect) in order to minimise random errors. In our meta-analysis, the required information size will be based on the assumption of a plausible RR reduction of 20% or on the RR reduction observed in the included trials with low risk of bias (Wetterslev 2008).
The trial sequential monitoring boundaries will be constructed on the basis of the required information size and risk for type I (5%) and type II (20%) errors. These boundaries will determine the statistical inference one may draw regarding the cumulative meta-analysis that has not reached the required information size; if the trial sequential monitoring boundary is crossed before the required information size is reached, firm evidence may perhaps be established and further trials may turn out to be superfluous. On the other hand, if the boundary is not surpassed, it is most probably necessary to continue doing trials in order to detect or reject a certain intervention effect. As default, a type I error of 5%, type II error of 20%, and adjusted information size for diversity are used unless otherwise stated (Wetterslev 2008; Wetterslev 2009).
Subgroup analysis and investigation of heterogeneity
We plan to perform the following subgroup analyses:
- Trials with low risk of bias compared to trials with high risk of bias.
- Age of patients; children compared to adults.
- HBeAg-positive compared to HBeAg-negative patients with chronic hepatitis B.
- Patients with cirrhosis compared to patients without cirrhosis.
- Treatment naive compared to relapses or non-responders.
- Total dosage of adefovir dipivoxil isoprinosine: low dose compared to intermediate dose compared to high dose.
- Genotypes of HBV.
- Patients co-infected with HIV or hepatitis C virus, or hepatitis D, or with hepatocellular carcinoma, or with other liver-related co-morbidities at entry compared to patients without co-infection.
- Trials without losses to follow-up compared to trials with losses to follow-up.
- Follow-up at the end of treatment compared to follow-up at six months or more than six months after treatment.
- Trials published as full paper articles compared to trials published as abstracts only.
In addition to the sensitivity analyses we have specified in 'Dealing with missing data', trials in which allocation concealment is judged with high or unclear risk of bias will be excluded from the meta-analysis, and the effect of this exclusion on the overall results will be assessed.
Summary of findings
We will use the principles of the GRADE system to assess the quality of the body of evidence associated with outcomes mentioned in our review and construct ’Summary of findings (SoF)’ table using the GRADE software (http://ims.cochrane.org/revman/gradepro).
Domains that may decrease the quality of the evidence are as follows:
- The study design;
- Risk of bias;
- Inconsistency of results;indirectness (ie, non-generalisability);
- Imprecision (ie, insufficient data);
- Other factors (eg, reporting bias).
We will reduce the quality of the evidence by one level for each domain where poor quality is encountered. We will assess all plausible confounding factors and consider their effects as a reason to reduce any claimed effect and dose response gradient.
We will define levels of evidence as below.
- High-quality evidence: The following statement applies to all of the domains: 'Further research is very unlikely to change our confidence in the estimate of effect. There are consistent findings, that are generalisable to the population of interest, in 75% of randomised clinical trials with low risk of bias. There are sufficient data, with narrow confidence intervals. There are no known or suspected reporting biases'.
- Moderate-quality evidence: The following statement applies to one of the domains: 'Further research is likely to have an important impact on our confidence in the estimate of effect, and may change the estimate'.
- Low-quality evidence: The following statement applies to two of the domains: 'Further research is very likely to have an important impact on our confidence in the estimate of effect, and is likely to change the estimate'.
- Very low-quality evidence: The following statement applies to three of the domains: 'We are very uncertain about the estimate'.No evidenceThe following statement applies: 'No randomised clinical trials were identified that measured the outcome of interest'.
The authors thank Sarah Louise Klingenberg, Dimitrinka Nikolova, and the entire Cochrane Hepato-Biliary Group for assistance in writing this protocol and developing a trial search strategy.
Peer Reviewers: Peter Ferenci, Austria; Manuel Romero-Gomez, Spain.
Contact Editor: Bodil Als-Nielsen, Denmark.
Appendix 1. Search Strategies
Contributions of authors
BN wrote the first draft of the protocol, EJK, and SK provided input for writing the protocol.
Declarations of interest