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Cochrane Database of Systematic Reviews Protocol - Intervention

Nicotine receptor partial agonists for alcohol dependence

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Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

The primary objective of this review is to assess the efficacy and safety of nAChR partial agonists for reducing alcohol consumption in people with alcohol use disorders when compared to placebo, no intervention, psychosocial interventions or other pharmacotherapy.

Background

Description of the condition

Alcohol use disorders include alcohol dependence and either harmful use or alcohol abuse (APA 2000; WHO 1992). Alcohol dependence, which includes both psychological and physical dependence, is considered the more severe condition and is characterised by; a strong desire to consume alcohol, difficulties in controlling its use despite harmful consequences, increased alcohol tolerance, and sometimes a physical withdrawal state. Harmful use of alcohol is defined as a pattern of use that is causing damage to health (either physical or mental) (WHO 1992), whereas alcohol abuse encompasses functional problems associated with alcohol use including: failure in obligations, use in hazardous situations, legal problems, and continued use despite social or interpersonal problems (APA 2000).

Globally, the prevalence of alcohol‐use disorders in people aged between 15 and 64 years has been estimated at 3.6%, ranging from 0% to 19% depending on gender and geographical location (Rehm 2009). Alcohol consumption is the third leading risk factor for disease and disability worldwide, and accounts for 3.8% of all deaths and 4.5% of disability adjusted life‐years (Rehm 2009; WHO 2011). In additional to being a causal factor in more than 60 types of diseases or injuries (Rehm 2010), alcohol contributes significantly to societal harms including: violence, crime, child abuse and neglect, and absenteeism from work (WHO 2011). The type and degree of harm experienced is correlated with both the average amount of alcohol consumed and the pattern of drinking (Rehm 2010).

Description of the intervention

Early stages of treatment for alcohol dependence typically involve psychosocial interventions and may include pharmacotherapy for detoxification and treatment of withdrawal symptoms. Later stages focus on relapse prevention and may also include pharmacological support (Schuckit 2009). Currently four pharmacotherapies have demonstrated efficacy and are used in clinical settings for the treatment of alcohol use disorders: disulfiram, acamprosate, oral naltrexone, and injectable extended release naltrexone (Rösner 2010a; Rösner 2010b; Edwards 2011). However the effect size achieved with these treatments is modest and there is an urgent need to identify novel neuropharmacological targets and pharmacotherapies for the treatment of alcohol use disorders.

Varenicline is the most effective pharmacotherapy currently available for the treatment of nicotine addiction (Cahill 2011). Pfizer Inc derived varenicline from cytisine, an alkaloid found naturally in some plant species  including Cytisus laburnum. Cytisine has been sold as a smoking cessation aid in Eastern Europe since the 1960s by Sopharma Pharmaceuticals (Etter 2006). Both varenicline and cytisine are structurally similar to nicotine and have been shown to be effective partial agonists of nicotinic acetylcholine receptors (nAChR). Clinical trials suggest that varenicline is safe and well tolerated at doses used for smoking cessation. However post‐market surveillance has raised concerns of an association between use of varenicline and an increased risk of psychiatric disorders (Cahill 2011).

There is a strong positive correlation between alcohol and nicotine consumption, which appears to be mediated by genetic, biological and environmental factors (Chatterjee 2010). Approximately, 60% to 80% of heavy drinkers also smoke tobacco, and alcohol consumption increases when nicotine is co‐administered (Barrett 2006; Batel 1995). Pre‐clinical studies have revealed that rodents reduce their ethanol self‐administration after being treated with nAChR partial agonists including varenicline, cytisine and sazetidine‐A (Rahman 2011). A recent human study suggests that varenicline can attenuate craving for alcohol and reduce subjective reinforcing effects after consumption (McKee 2009). Partial agonists of nAChR have therefore been put forward as potential treatments for alcohol use disorders.

How the intervention might work

The rewarding and reinforcing properties of alcohol, similar to other substances of abuse, are strongly influenced by the release of dopamine within the mesolimbic area of the brain (Larsson 2004). This process is mediated, at least in part, by interactions between alcohol and nAChR (Chatterjee 2010). Pre‐clinical studies have shown that some nAChR ligands, including partial agonists, are able to inhibit ethanol induced mesolimbic dopamine release and ethanol self‐administration in rodents (Rahman 2011). It has been suggested that nAChR partial agonists may reduce alcohol consumption in two ways; 1) reducing alcohol craving by eliciting a moderate and sustained release of mesolimbic dopamine and 2) reducing subjective reinforcing effects of alcohol by preventing it from interacting with nAChR (McKee 2009).

Why it is important to do this review

Partial agonists of nAChR have been extensively studied for the treatment of nicotine dependence, and are the subject of a Cochrane review for this condition (Cahill 2011). However, to the best of our knowledge there are no systematic reviews investigating the use of nAChR partial agonists for the treatment of alcohol use disorders. Therefore, it is important to evaluate nAChR partial agonists for the treatment of alcohol use disorders in a systematic Cochrane review.

Objectives

The primary objective of this review is to assess the efficacy and safety of nAChR partial agonists for reducing alcohol consumption in people with alcohol use disorders when compared to placebo, no intervention, psychosocial interventions or other pharmacotherapy.

Methods

Criteria for considering studies for this review

Types of studies

All randomised controlled trials which compare the effect of nAChR partial agonists with placebo, no intervention, or other therapeutic strategies for treatment of alcohol use disorders. Cross‐over and multi‐phase designs will be included, however the risk of bias in these trials will be examined and the suitability of trial design will be commented on in the discussion.

Types of participants

People with alcohol use disorders according to criteria defined by the Diagnostic and Statistical Manual of Mental Disorders (DSM) or the International Statistical Classification of Diseases (ICD) or equivalent. Criteria will have been assessed by a specialist or using validated scales e.g. Alcohol Use Disorders Identification Test (AUDIT), Michigan Alcoholism Screening Test (MAST), or CAGE (acronym for the four items of the scale: cut down, annoyed, guilty, and eye‐opener). Participants from trials without explicit diagnostic criteria will be included; however, their influence will be assessed in sensitivity analyses. People with alcohol use disorders will be included irrespective of their degree of alcohol dependency, age or any other characteristics. Participants may be from trials that assess alcohol use disorders exclusively or alcohol use disorders in conjunction with use of other, legal and illegal, substances.

Types of interventions

Experimental intervention

  • Agents that are partial agonists at any nAChR, including varenicline and cytisine, or any other in this class of drug. The nAChR partial agonist may be administered alone or in combination with any psychosocial intervention.

Control intervention

  • Placebo;

  • No intervention;

  • Other pharmacological intervention;

  • Any psychosocial intervention.

Types of outcome measures

Primary outcomes

  1. Alcohol consumption as measured by: volume of alcohol consumed; number of drinks consumed; number of abstinent, drinking or heavy drinking days (as percentage of total days in treatment or during follow‐up).

  2. Alcohol abstinence as measured by: proportion of participants who return to drinking or heavy drinking; average time to first drinking or heavy drinking session. May be self‐reported or biologically confirmed.

  3. Safety as measured by the number and type of adverse events and serious adverse events experienced during the treatment. Adverse events previously associated with use of nAChR partial agonists (e.g. neuropsychiatric and cardiovascular effects) will be actively sought.

Secondary outcomes

  1. Alcohol craving as measured using a validated scale, e.g. Substance craving scale, visual analogue scale, obsessive compulsive drinking scale;

  2. Acceptability: Number of participants who completed treatment;

  3. Use of other substances, e.g. tobacco consumption;

  4. Laboratory measures of alcohol consumption, e.g. carbohydrate deficient transferrin and gamma‐glutamyl transpeptidase.

Search methods for identification of studies

Electronic searches

The following electronic databases will be searched for relevant trials:

  1. The Cochrane Central Register of Controlled Trials (CENTRAL‐ The Cochrane Library, most recent) which include the Cochrane Drugs and Alcohol Groups specialised register.

  2. MEDLINE (January 1966 to present)

  3. EMBASE (January 1974 to present)

  4. CINAHL ‐ Cumulative Index to Nursing and Allied Health Literature (1982 to present)

  5. PsycINFO (1806 to present)

Databases will be searched using MeSH terms and free text terms relating to alcohol use disorders and nicotinic receptor partial agonists as shown in Appendix 1. For the MEDLINE search the Cochrane Highly Sensitive Search Strategy (sensitivity maximising version) will be used to filter for randomised trials (Higgins 2011). This strategy will be revised appropriately for each database to take account of differences in controlled vocabulary and syntax rules.

We will also search some of the main electronic sources of ongoing trials:

  1. Controlled Trials (http://www.controlled‐trials.com/)

  2. Clinical Trials.gov (www.clinicaltrials.gov)

  3. Australian New Zealand Clinical Trials Registry (www.anzctr.org.au)

  4. EU Clinical Trials Register (https://www.clinicaltrialsregister.eu)

  5. CenterWatch (http://centerwater.com)

  6. Clinical Study Results (www.clinicalstudyresults.org)

  7. Trials (www.trialsjournal.com)

Searching other resources

We will search:

  1. Reference lists of all relevant papers;

  2. Citation lists of all relevant papers, using electronic citation indexes Web of Science and Scopus;

  3. Conference proceedings likely to contain trials relevant to the review;

  4. Data submitted to country‐specific regulation agencies, including the United States Food and Drug Administration and the European Medicines Agency;

  5. If possible, authors of included studies and experts in the field in various countries will be contacted to find out if they know of any unpublished or incomplete trials.

All searches will include non‐English language literature and studies with English abstracts will be assessed for inclusion. When considered likely to meet inclusion criteria, studies will be translated.

Data collection and analysis

Selection of studies

Two authors will screen the titles and abstracts of studies retrieved by search strategies. Full text versions of potentially relevant studies will be retrieved and assessed for inclusion by two authors independently. Any discrepancies will be resolved via discussion with a third author. Reviewers will not be blinded to the names of the authors, institutions or journal of publication.

Data extraction and management

Two authors will independently extract data from included studies using a standard data collection form. The data collection form will summarise key characteristics of the study including methodology, participants, interventions, comparators, primary and secondary outcomes. Any disagreements will be resolved via discussion with a third author.

Assessment of risk of bias in included studies

Two authors will independently assess study quality using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).

The risk of bias assessment for RCTs in this review will be performed using the criteria recommended by the Cochrane Handbook (Higgins 2011). The recommended approach for assessing risk of bias in studies included in Cochrane Review is a two‐part tool, addressing seven specific domains, namely sequence generation and allocation concealment (selection bias), blinding of participants and providers (performance bias), blinding of outcome assessment (detection bias), incomplete outcome data (attrition bias), selective outcome reporting (reporting bias) and other sources of bias. The first part of the tool involves describing what was reported to have happened in the study. The second part of the tool involves assigning a judgement relating to the risk of bias for that entry, in terms of low, high or unclear risk. To make these judgments we will use the criteria indicated by the handbook adapted to the addiction field. See Appendix 2 for details.

The domains of sequence generation, allocation concealment and selective outcome reporting (avoidance of selection bias and reporting bias) will be addressed in the tool by a single entry for each study.

Blinding of participants, personnel and outcome assessor (avoidance of performance bias and detection bias) will be considered separately for objective outcomes (e.g. drop out, use of substance of abuse measured by urine‐analysis, subjects relapsed at the end of follow‐up, subjects engaged in further treatments) and subjective outcomes (e.g. patient self‐reported use of substances, side‐effects, severity of substance craving).

Incomplete outcome data (avoidance of attrition bias) will be considered for all outcomes except for the drop out from the treatment, which is very often the primary outcome measure in trials on addiction.

Measures of treatment effect

Dichotomous data

Dichotomous outcomes will be analysed by calculating the relative risk (RR) for each trials with the uncertainty in each results being expressed by their 95% confidence intervals (CI).

Continuous data

Continuous data will be analysed by calculating the mean difference and 95% CI.

Time‐to‐event data

Time to event data will be analysed by calculating hazard ratios and 95% CI.

Unit of analysis issues

Cross‐over trials will be included in meta‐analysis using paired data obtained from reports or via correspondence with authors, or if unavailable using imputation methods (Elbourne 2002). Risk of bias due to carry over effects and suitability of trial design will be commented on in the discussion. Where possible groups in multiple arms trials will be combined into either control or experimental intervention to allow for pairwise comparison. If this is not possible then the control group will be divided by the number of comparator groups.

Dealing with missing data

Where possible authors will be contacted to supply any data missing from included studies. It is planned to carry out both available case analysis and intention‐to‐treat analysis and to compare the results. Where evidence does not suggest that data was missing at random, imputation methods shall be used e.g. assuming missing data corresponds to a poor outcome.

Assessment of heterogeneity

The presence of heterogeneity between the studies will be assessed visually and by calculating the I‐squared statistic, using a variability of 50% as the threshold value for substantial heterogeneity.

Assessment of reporting biases

If there are a sufficient number of studies (10 or more studies) funnel plots (plots of the effect estimate from each study against the standard error) will be used to assess the potential for bias related to the size of the trials, which could indicate possible publication bias.

Data synthesis

If considered appropriate, results of comparable groups of trials will be pooled in meta‐analysis. For dichotomous variables, risk ratio (RR) will be calculated. For continuous variables, mean difference (MD) will be calculated, unless data are derived from disparate outcome measures, in which case standardised mean difference (SMD) will be calculated. A fixed‐effect model will be used unless there is significant heterogeneity, in which case a random‐effects model will be used.

Subgroup analysis and investigation of heterogeneity

Subgroup analysis shall be conducted by grouping results of studies according to the following methodical and clinical aspects:

  1. By type of nAChR partial agonist (e.g. varenicline, cytisine, others);

  2. By length of treatment course (e.g. less than 12 weeks, 12 weeks or greater);

  3. By dosage;

  4. By severity of diagnosed alcohol use disorder.

  5. By presence or absence of other dependencies.

  6. By presence or absence of psychosocial interventions.

Sensitivity analysis

Sensitivity analysis will be performed that assess the impact of excluding studies identified to have a high risk of bias. Sensitivity analysis will also be used to assess the effect of different imputation methods used to account for missing data.