Isoprinosine for chronic hepatitis B

  • Protocol
  • Intervention

Authors


Abstract

This is the protocol for a review and there is no abstract. The objectives are as follows:

To assess the benefits and harms of isoprinosine in the treatment of people with chronic HBV infection.

Background

Description of the condition

Hepatitis B virus (HBV) is a unilaterally double-stranded, enveloped deoxyribonucleic acid (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 two billion people, of which about 400 million people 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). People 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. These drugs are divided into two main groups based on their action mechanism: 1. immunomodulatory drugs such as interferon-alpha and 2. antiviral drugs including lamivudine, adefovir dipivoxil, tenofovir, and entecavir (Aggarwal 2004). Interferon-alpha is efficient in people with severe hepatitis B e antigen (HBeAg)-positive HBV and has an HBeAg clearance of 32% in treated patients compared with 11% in patients treated with placebo (Wong 1993). Notwithstanding, the use of interferon-alpha has been narrowed as a result of severe adverse effects, high cost, and demand for many injections. Lamivudine is more affordable compared to interferons and is conveniently take per os. Although lamivudine reacts similarly to interferon with lesser adverse effects, its period of administration is unspecified among people needing life-long treatment (Lai 2003a). Due to its lengthy period of treatment, people on lamivudine could develop mutation in the HBV genome, resulting in drug immunity and aggravated liver disease (Lai 2003b). 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). Moreover, long-term therapy with tenofovir can lead to proximal tubular renal dysfunction resulting in renal insufficiency, osteomalacia, and significant hypophosphataemia (Gara 2012). In addition, entecavir used for prolong periods induces the same changes in renal function as those of tenofovir, with renal transplant patients and people with pre-existing renal insufficiency having a greater increase in serum creatinine (Gish 2012).

How the intervention might work

Isoprinosine is a molecular complex of inosine: 2-hydroxypropyldimethylammonium 4-acetamido-benzoate 1:3. It inhibits replication of many ribonucleic acid (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 existing drugs used for treating chronic hepatitis B such as interferon-alpha and adefovir, 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 adverse effects such as dyspepsia, hypersensitivity reactions, and severe drug reactions with ribavirin that may result in a reduction in the white blood cell count of patients. Therefore, healthcare providers have to evaluate the adverse events of therapy compared to the benefits for this group of patients carefully. As we identified no meta-analyses or systematic reviews evaluating the beneficial and harmful effects of isoprinosine for people with chronic hepatitis B, this Cochrane Hepato-Biliary Group systematic review will be useful.

Objectives

To assess the benefits and harms of isoprinosine in the treatment of people with chronic HBV infection.

Methods

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. We will use quasi-randomised or observational studies that may be retrieved with the searches for randomised clinical trials to report harms only.

Types of participants

We will include participants with chronic active HBV infection. As people with chronic active HBV infection may be HBeAg positive or HBeAg negative, we will follow the following definitions (Lok 2007):

HBeAg-positive chronic hepatitis B infection defined as:

  • hepatitis B surface antigen (HBsAg) positivity for more than six months and serum HBV DNA positivity more than 20,000 IU/mL (i.e., 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 participants had chronic hepatitis B.

HBeAg-negative chronic hepatitis B infection defined as:

  • HBsAg positivity for more than six months and serum HBV DNA positivity with lower values of 2000 to 20,000 IU/mL (i.e., 104 to 105 copies/mL), or

  • 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 participants had chronic hepatitis B.

We will include trials with both children and adults. 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. We will included participants irrespective of whether they are treatment-naive or have previously been treated unsuccessfully for chronic HBV infection with another drug. We will include people with evidence of concomitant HIV infection, hepatitis C, hepatitis D, hepatocellular carcinoma, or other liver-related co-morbidities, but we will analyse the participants with and without these conditions separately. We will include people with prior liver transplantation or people with concomitant renal failure, but will analyse them separately.

Types of interventions

We will include trials that compare isoprinosine versus placebo or any other drugs.

In all included trials, we will consider the experimental group to be the one that receives isoprinosine and the control group to be the one that receives placebo or any other active intervention.

We will allow protocol-specific co-interventions as long as they were administered equally to all intervention groups. We will permit other concomitant interventions for any co-morbidity; we will assume that access to concomitant therapeutic interventions is administered equally regardless of intervention group.

Types of outcome measures

Primary outcomes
  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. We will report these separately. We will define serious adverse events as any untoward medical occurrence that is life threatening, results in death or persistent or significant disability, or any medical event that may have jeopardised the participant or required intervention to prevent it (ICH-GCP 1997). We will consider all other adverse events (i.e., any medical occurrence not necessarily having a casual relationship with the treatment, but did, however, cause a dose reduction or discontinuation of treatment) to be non-serious.

Secondary outcomes
  1. Quality of life (as defined by the trialists).

  2. Number of participants with detectable HBsAg in serum or plasma.

  3. Number of participants with detectable HBV DNA in serum or plasma.

  4. Number of participants with detectable HBeAg in serum or plasma (this outcome is not relevant for the HBseAg-negative participants).

  5. Number of participants without HBeAg seroconversion in serum or plasma (this outcome is not relevant for the HBeAg-negative participants).

  6. Number of participants with worsened liver histology.

Search methods for identification of studies

Electronic searches

We will search The Cochrane Hepato-Biliary Group Controlled Trials Register (Gluud 2013), the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, and Science Citation Index EXPANDED (Royle 2003). Preliminary search strategies are given in Appendix 1 with the expected time spans of the searches. We will improve the search strategies at the review stage, if necessary.

Searching other resources

We will search the bibliographic references of identified randomised clinical trials, textbooks, review articles, and meta-analyses in order to find randomised clinical trials that were not identified by the electronic searches. We will also search 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 conduct a meta-analysis of the results from methodologically and clinically comparable trials. We will perform the review according to the recommendations of The Cochrane Collaboration (Higgins 2011) and the Cochrane Hepato-Biliary Module (Gluud 2013). We will perform the analyses using Review Manager 5 (RevMan 2012).

Selection of studies

Two review 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. We will obtain full-text articles 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-text article. BN and SK will independently apply the inclusion criteria, and any differences arising will be resolved by discussions with EK. We will review studies for relevance based on study design, types of participants, exposures, and outcomes.

Data extraction and management

From the selected trials, we will extract the following data in respect of treatment of HBeAg-positive participants with chronic hepatitis B:

  1. proportion without disappearance of HBeAg in the serum (HBeAg negativity rate), and

  2. proportion without seroconversion from HBeAg-positive status to anti-HBe-positive status (seroconversion).

In addition, for both HBeAg-positive and HBeAg-negative participants, we will extract data regarding the following variables:

  1. proportion without 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);

  2. proportion without return of liver enzyme levels to normal range (end-of-treatment biochemical response);

  3. 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);

  4. proportion with clinical events such as decompensation of liver disease;

  5. data on co-infection with HIV, hepatitis C, hepatitis D, or evidence of concomitant with hepatocellular or renal failure;

  6. proportion without histological improvement;

  7. 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.

Assessment of risk of bias in included studies

We will assess risk of bias of all trials fulfilling the inclusion criteria 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; Lundh 2012; Savović 2012a; Savović 2012b).

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 were 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.

Allocation concealment
  • 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 (e.g., 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, have 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 website 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.

For-profit bias
  • Low risk of bias: the trial appears to be free of industry sponsorship or other type 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 was sponsored by the industry or has received other type of for-profit support.

Other bias
  • 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 (e.g., 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

We will calculate outcome measures for binary data as a risk ratio with 95% confidence intervals. We will calculate continuous data (e.g., alanine aminotransferase levels, HBV DNA levels) using mean differences and standard deviations. We will analyse the data using the intention-to-treat principle, that is, participants with missing data will be considered as treatment failures. We will calculate the number needed to treat for an additional beneficial outcome (NNTB) as 1 divide by the risk difference.

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. We will perform all analyses 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 participants 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 drop-outs/participants lost from the experimental arm, but all of the drop-outs/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 drop-outs/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 Chi2 test for statistical homogeneity with a P value < 0.1 set as the cut-off. We will quantify the impact of any statistical heterogeneity using the I2 statistic (Higgins 2011).

We will interpret the Ivalue as:

  • 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

We will assess publication bias by looking for funnel plot asymmetry if there are at least 10 included trials (Egger 1997).

Data synthesis

Meta-analyses

We will meta-analyse the data using both a random-effects model (DerSimonian 1986) and a fixed-effect model (DeMets 1987). In case of discrepancy in the results of two models, we will present the results obtained using both methods. If there is no statistically significant difference in the results, then we will present the results of 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 (CTU 2011; Thorlund 2011). 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 (i.e., the number of participants needed in a meta-analysis to detect or reject a certain intervention effect) in order to minimise random errors (Brok 2008; Wetterslev 2008; Thorlund 2009; Wetterslev 2009; Thorlund 2010). In our meta-analysis, the required information size will be based on the assumption of a plausible relative risk reduction of 20% or on the relative risk 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 be superfluous. In contrast, 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, if the area of futility is not reached. 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 or unclear risk of bias;

  • HBeAg-positive compared to HBeAg-negative participants with chronic hepatitis B;

  • people with cirrhosis compared to people without cirrhosis;

  • treatment-naive compared to relapses or non-responder patients;

  • people 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 people without co-infection;

  • trials without losses to follow-up compared to trials with losses to follow-up;

  • published compared to unpublished studies (since these may not have been subjected to the peer review process and may have intrinsic biases);

  • trials that have assessed compliance compared to trials that have not assessed compliance.

Sensitivity analysis

Where possible, we will perform sensitivity analyses to explore the effects of various aspects of trial and review methodology.

'Summary of findings' tables

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' table using the GRADE software (ims.cochrane.org/revman/gradepro).

Domains that may decrease the quality of the evidence are as follows.

  1. The study design.

  2. Risk of bias.

  3. Inconsistency of results; indirectness (i.e., non-generalisability).

  4. Imprecision (i.e., insufficient data).

  5. Other factors (e.g., 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 evidence. The following statement applies: "No randomised clinical trials were identified that measured the outcome of interest".

Acknowledgements

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: Jane Campos, The Philippines; Barbara Kowalik-Mikołajewska, Poland; Jalal Poorolajal, Iran; Khalid Mumtaz, Canada.
Contact editor: Bodil Als-Nielsen, Denmark.

Appendices

Appendix 1. Search strategies

DatabaseTime spanSearch strategy
Cochrane Hepato-Biliary Group Controlled Trials RegisterDate will be given at review stage.(isoprinosine OR 'inosine pranobex' OR imunovir OR inosiplex OR methisoprinol) AND ('hepatitis B' OR 'hep B' OR HBV)
Cochrane Central Register of Controlled Trials (CENTRAL)Latest issue.

#1 MeSH descriptor Inosine Pranobex explode all trees

#2 isoprinosine OR inosine pranobex OR imunovir OR inosiplex OR methisoprinol

#3 (#1 OR #2)

#4 MeSH descriptor Hepatitis B explode all trees

#5 hepatitis B OR hep B OR HBV

#6 (#4 OR #5)

#7 (#3 AND #6)

MEDLINE (Ovid SP)1948 to the date of search.

1. exp Inosine Pranobex/

2. (isoprinosine or inosine pranobex or imunovir or inosiplex or methisoprinol).mp. [mp=protocol supplementary concept, rare disease supplementary concept, title, original title, abstract, name of substance word, subject heading word, unique identifier]

3. 1 or 2

4. exp Hepatitis B/

5. (hepatitis B or hep B or HBV).mp. [mp=protocol supplementary concept, rare disease supplementary concept, title, original title, abstract, name of substance word, subject heading word, unique identifier]

6. 4 or 5

7. 3 and 6

EMBASE (Ovid SP)1980 to the date of search.

1. exp methisoprinol/

2. (isoprinosine or inosine pranobex or imunovir or inosiplex or methisoprinol).mp. [mp=title, abstract, subject headings, heading word, drug trade name, original title, device manufacturer, drug manufacturer]

3. 1 or 2

4. exp hepatitis B/

5. (hepatitis B or hep B or HBV).mp. [mp=title, abstract, subject headings, heading word, drug trade name, original title, device manufacturer, drug manufacturer]

6. 4 or 5

7. 3 and 6

Science Citation Index Expanded (apps.isiknowledge.com)1900 to the date of search.

# 3 #2 AND #1

# 2 TS=(hepatitis B or hep B or HBV)

# 1 TS=(isoprinosine or inosine pranobex or imunovir or inosiplex or methisoprinol)

Contributions of authors

BN and SK wrote the first draft of the protocol, which included study design and paper preparation.

EK, EJK and SE provided input for writing the protocol as well as critical revision.

All authors approved the final protocol version for publication.

Declarations of interest

None.

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