Intervention Protocol

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Disulfiram for alcohol use disorder

  1. Bolette Pedersen1,*,
  2. Gro Askgaard2,
  3. Kristian Oppedal3

Editorial Group: Cochrane Drugs and Alcohol Group

Published Online: 30 APR 2013

DOI: 10.1002/14651858.CD010487


How to Cite

Pedersen B, Askgaard G, Oppedal K. Disulfiram for alcohol use disorder (Protocol). Cochrane Database of Systematic Reviews 2013, Issue 4. Art. No.: CD010487. DOI: 10.1002/14651858.CD010487.

Author Information

  1. 1

    Bispebjerg University Hospital, Clinical Health Promotion Centre, Frederiksberg, Denmark

  2. 2

    Rigshospitalet, Department of Hepatology, København Ø, Denmark

  3. 3

    Stavanger University Hospital, Alcohol and Drug Research Western Norway (KoRFor), Stavanger, Norway

*Bolette Pedersen, Clinical Health Promotion Centre, Bispebjerg University Hospital, Nordre Fasanvej 57, Frederiksberg, 2000, Denmark. bolette.pedersen@regionh.dk.

Publication History

  1. Publication Status: New
  2. Published Online: 30 APR 2013

SEARCH

 

Background

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support
 

Description of the condition

Alcohol consumption varies enormously among countries, over time and among different population groups (Alcohol and Public Policy Group 2010). In 2009, the average consumption of alcohol by adults (aged over 15 years) in the European region was 12.5 litres of pure alcohol per person per year, which corresponds to nearly three drinks per day. This is the highest alcohol consumption in the world, and nearly double the world average (WHO 2012). Alcohol accounts for approximately 4% of all deaths and 4.65% of the global burden of injury and disease (Rehm 2009; WHO 2011).

Alcohol Use Disorders (AUDs) include alcohol dependence and harmful alcohol use, which are both recognised as mental health disorders by the World Health Organization (NCCMH 2011; WHO 2011). Alcohol dependence is defined as a cluster of behavioural, cognitive and physiological symptoms that may develop after repeated alcohol use, whereas harmful use refers to alcohol consumption that results in consequences to physical and mental health (WHO 2010). Worldwide, approximately 3% of the population suffer from AUDs. The prevalence among men is 6% compared to less than 1% among women (Rehm 2009).

 

Description of the intervention

Non-pharmacological treatment of AUDs include brief interventions and specialised treatment programmes, and the effect of these interventions has been evaluated in different settings and populations (Kaner 2007; McQueen 2011). Interventions originating from mutual self-help groups such as Alcoholics Anonymous have been evaluated in research (Ferri 2006).There are few pharmacological interventions for treating AUD, and many are alternative treatments with no evidence. The current pharmacological interventions involve acamprosate, naltrexone and disulfiram. New treatments under evaluation include GHB, ondansetron, baclofen and topiramate (Leone 2010; Edwards 2011).

Disulfiram has been available for more than 60 years as an effective supplement to behavioral treatment of alcoholism (Krampe 2010). Today, disulfiram is primarily used in a supervised manner and, like acamprostae and n(altrexone, combined with behavioral therapy in the treatment of AUDs.

 

How the intervention might work

Disulfiram inhibits the liver enzyme aldehyde dehydrogenase. Alcohol intake during treatment leads to accumulation of acetaldehyde, which probably causes the disulfiram-ethanol reaction in the form of increased pulse and respiration, tachycardia, facial flushing, nausea, vomiting, hypotension, and - at worst - cardiovascular collapse. Disulfiram is therefore indicated for patients who wish to remain abstinent (Martin 2007). A recent review showed that supervised treatment with disulfiram has some effect on short-term abstinence and relapse prophylaxsis (Jørgensen 2011).

 

Why it is important to do this review

Alcohol-related disease and injuries kill and harm millions of people each year. Effective prevention and treatment strategies can reduce these alcohol-related consequences. Even though disulfiram is the o ldest of the available pharmacological options for treatment, many questions remain unanswered including the long-term effect of disulfiram on abstinence, which may help to reduce alcohol-related diseases and consequences. It is therefore important to systematically summarise the effects of disulfiram in order to help clinicians and other staff working with AUD patients to make the best possible treatment option for their patients.

 

Objectives

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support

To assess the efficacy and safety of disulfiram in the treatment of patients with alcohol use disorders on short-term and long-term outcomes compared to other pharmacological treatment, placebo or no treatment.

 

Methods

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support
 

Criteria for considering studies for this review

 

Types of studies

Randomised clinical trials (RCTs). Trials studying disulfiram in various doses and/or trials investigating disulfiram against other pharmacological treatment, placebo or no treatment will be considered.

We will exclude subanalyses of already published material and studies where disulfiram is used in combination with other medical treatment.

 

Types of participants

Patients with alcohol use disorder (AUD) diagnosed with appropriate standardised criteria (e.g. DSM-IV, ICD-10). AUDs can therefore include a harmful drinking pattern as well as alcohol dependency.

 

Types of interventions

We will compare:

  • Disulfiram at one dose compared with another dose
  • Disulfiram versus other pharmacological treatment
  • Disulfiram versus placebo
  • Disulfiram versus no treatment

 

Types of outcome measures

 

Primary outcomes

  1. Abstinence at the end of study (short-term) and at 6 and 12 months (long-term). Abstainers are people who have refrained from drinking alcoholic beverages (WHO 2010). Consumption can be self-reported and/or biochemically-validated.
  2. Alcohol consumption at the end of study (short-term) and at 6 and 12 months (long-term). We will measure treatment effect on alcohol consumption by self-reported intake and validated questionnaires such as Alcohol Use Disorder Identification Test (AUDIT) (Saunders 1993), Michigan Alcohol Screening Test (MAST) (Selzer 1971), and CAGE (Cut down; Annoyed; Guilty; Eye-opener) (Mayfield 1974) with or without biochemical validation.
  3. Adverse events at the end of study (short-term) and at 6 and 12 months (long-term). Adverse drug events are defined as “a response to a drug that is noxious and unintended and occurs at doses normally used in man for the prophylaxis, diagnosis or therapy of disease, or for modification of physiological function" (WHO 1972).

We allow for within-study definitions of abstinence, alcohol consumption and adverse events to be included.

 

Secondary outcomes

  1. Days until relapse and number of drinking days at the end of study (short-term) and at 6 and 12 months (long-term). Days until relapse is defined as number of days until a return to drinking alcohol after a period of abstinence, and number of drinking days as total number of days with any alcohol consumption (WHO 2010).

We will exclude studies without relevant primary and secondary outcomes. Other study-specific outcomes such as retention in treatment, relapse rate, controlled drinking and alcohol craving will be considered as secondary outcomes.

 

Search methods for identification of studies

 

Electronic searches

We will search the following electronic databases for potentially relevant studies:

  • Cochrane Drugs and Alcohol Group Specialised Register
  • The Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, latest Issue).
  • Ovid MEDLINE - 1950 to present
  • Ovid EMBASE - 1980 to present
  • EBSCO CINAHL - 1982 to present

We will search databases using MeSH and free-text terms relating to alcohol use disorders and disulfiram as shown in Appendix 1. We will combine the Ovid MEDLINE search with the Cochrane Highly Sensitive Search Strategy for identifying randomised trials in MEDLINE: sensitivity-maximising version (2008 revision) (Lefebvre 2011). We will revise this strategy appropriately for each database to take account of differences in controlled vocabulary and syntax rules.

 

Searching other resources

We will identify trials by manually searching abstracts of appropriate conference proceedings. We will check the reference lists of relevant articles and contact relevant trial authors to identify any additional or ongoing studies. We will contact pharmaceutical companies to get information on old or new published trials on disulfiram. We will also search for trials on specific websites:

  • http://www.controlled-trials.com
  • http://clinicaltrials.gov
  • http://www.centerwatch.com
  • http://apps.who.int/trialsearch

No language or publication restrictions will be set.

 

Data collection and analysis

 

Selection of studies

Two authors (KO and BB) will independently scan the titles and abstracts of the papers identified by the search strategies. All potentially relevant studies, chosen by at least one author, will be retrieved and evaluated using full-text versions.

Two authors (KO and BB) will assess the congruence of trials with the review's inclusion criteria. Any disagreement will be resolved by discussion with a third author (GA).

 

Data extraction and management

Two authors (KO and BB) will independently extract data using a tool based on guidance in the Cochrane Handbook of Systematic Reviews of Interventions (Higgins 2011). Any disagreement will be resolved involving a third author (GA).

 

Assessment of risk of bias in included studies

The 'Risk of bias' assessment for RCTs and controlled clinical trials (CCTs) in this review will be performed using the criteria recommended in the Cochrane Handbook (Higgins 2011). The recommended approach for assessing risk of bias in studies included in Cochrane reviews 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 assessor (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 Cochrane Handbook adapted to the addiction field. See Appendix 2 for details.

The domains of sequence generation and allocation concealment (avoidance of selection 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 treatment) and subjective outcomes (e.g. duration and severity of signs and symptoms of withdrawal, patient self-reported use of substance, side effects, social functioning as integration at school or at work, family relationship).

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

 

Measures of treatment effect

Dichotomous outcomes will be analysed by calculating the relative risk (RR) for each trial, with the uncertainty in each result expressed with 95% confidence intervals (CI). Continuous outcomes will be analysed by calculating the standardised mean difference (SMD) with 95% CI. For outcomes assessed by scales we will compare and pool the mean score differences from the end of treatment to baseline (post minus pre) in the experimental and control group.

 

Unit of analysis issues

If all arms in a multi-arm trial are to be included in the meta-analysis and one treatment arm is to be included more than once in some comparisons, then we will divide the number of events and the number of participants in that arm by the number of treatment comparisons made. This method avoids the multiple use of participants in the pooled estimate of treatment effect while retaining information from each arm of the trial. It compromises the precision of the pooled estimate slightly.

 

Dealing with missing data

Where necessary, we will contact the authors of included studies regarding missing data. Where data are found to be missing and the authors are not contactable we will, if possible, calculate missing statistics (such as standard deviations) from other quoted statistics (such as standard errors and confidence intervals). If missing data remain missing, we will exclude results with unavailable information from the analyses.

 

Assessment of heterogeneity

We will assess clinical heterogeneity by comparing the distribution of important patient characteristics across trials, including age, sex and characteristics of interventions. Heterogeneity among studies will be calculated using the I2statistic (which describes the percentage of the variability in effect that is attributable to heterogeneity rather than sampling error), and the Chi2 statistic (with statistical significance being set at P < 0.10) . If significant heterogeneity is present (I2 ≥ 50%) (Higgins 2002), we will investigate the trials for possible explanations.

 

Assessment of reporting biases

A thorough search for unpublished studies through grey literature searches and contact with known experts in the field will assist to reduce the risk of publication bias. If we find more than 10 trials, we will use funnel plot analysis to examine possible publication bias.

 

Data synthesis

Data from all included trials in the systematic review will be entered into Review Manager (RevMan 5.1) and we will combine data quantitatively, where possible. We will calculate pooled estimates using a random-effects model.

 

Subgroup analysis and investigation of heterogeneity

We will conduct subgroup analyses where data are available, as recommended in Section 9.6 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will, if possible, compare:

  • Supervised disulfiram versus unsupervised disulfiram
  • Disulfiram only versus disulfiram combined with behavioral therapy
  • Patients with different diagnoses (harmful drinking, alcohol abuse, alcohol dependency etc.)
  • Duration of studies: 6 months versus 12 months

 

Sensitivity analysis

We will perform sensitivity analyses to explore the risk of bias,by:

  • Excluding studies without biochemical validation of self-reported alcohol consumption, and
  • Exculding studies with a high risk of bias on trial factors such as sequence generation, allocation concealment, blinding, losses to follow-up etc.

 

Appendices

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support
 

Appendix 1. MEDLINE search strategy

  1. exp Alcohol-Related Disorders/
  2. Alcohol Drinking/
  3. (alcohol adj3 (drink$ or intoxicat$ or use$ or abus$ or misus$ or risk$ or consum$ or withdraw$ or detox$ or treat$ or therap$ or excess$ or reduc$ or cessation or intervention$)).tw.
  4. (drink$ adj3 (excess or heavy or heavily or harm or harmful or hazard$ or binge or problem$)).tw.
  5. alcoholic$.tw.  
  6. 1 or 2 or 3 or 4 or 5
  7. Disulfiram/
  8. Disulfiram.tw.
  9. Antabuse.tw.
  10. 7 or 8 or 9
  11. randomized controlled trial.pt.
  12. controlled clinical trial.pt.
  13. randomized.ab.
  14. placebo.ab.
  15. drug therapy.fs.
  16. randomly.ab.
  17. trial.ab.
  18. groups.ab.
  19. 11 or 12 or 13 or 14 or 15 or 16 or 17 or 18
  20. exp animals/ not humans.sh.
  21. 19 not 20
  22. 6 and 10 and 21

 

Appendix 2. Criteria for 'Risk of bias' assessment


 Item Judgment Description

1. random sequence generation (selection bias)

 

 
low riskThe investigators describe a random component in the sequence generation process such as: random number table; computer random number generator; coin tossing; shuffling cards or envelopes; throwing dice; drawing of lots; minimization.

high riskThe investigators describe a non-random component in the sequence generation process such as: odd or even date of birth; date (or day) of admission; hospital or clinic record number; alternation; judgement of the clinician; results of a laboratory test or a series of tests; availability of the intervention.

unclear riskInsufficient information about the sequence generation process to permit judgement of low or high risk.

2. allocation concealment (selection bias)

 

 
low riskInvestigators enrolling participants could not foresee assignment because one of the following, or an equivalent method, was used to conceal allocation: central allocation (including telephone, web-based, and pharmacy-controlled, randomisation); sequentially numbered drug containers of identical appearance; sequentially numbered, opaque, sealed envelopes.

high riskInvestigators enrolling participants could possibly foresee assignments because one of the following method was used: open random allocation schedule (e.g. a list of random numbers); assignment envelopes without appropriate safeguards (e.g. if envelopes were unsealed or non­opaque or not sequentially numbered); alternation or rotation; date of birth; case record number; any other explicitly unconcealed procedure.

unclear riskInsufficient information to permit judgement of low or high risk. This is usually the case if the method of concealment is not described or not described in sufficient detail to allow a definite judgement.

3. blinding of participants and providers (performance bias)

Objective outcomes 
low risk

 

 
No blinding or incomplete blinding, but the review authors judge that the outcome is not likely to be influenced by lack of blinding;

Blinding of participants and key study personnel ensured, and unlikely that the blinding could have been broken.

4. blinding of participants and providers (performance bias)

Subjective outcomes

 

 
low risk

 
Blinding of participants and  providers and unlikely that the blinding could have been broken;

 

high riskNo blinding or incomplete blinding, and the outcome is likely to be influenced by lack of blinding;

Blinding of key study participants and personnel attempted, but likely that the blinding could have been broken, and the outcome is likely to be influenced by lack of blinding.

unclear riskInsufficient information to permit judgement of low or high risk;

5. blinding of outcome assessor (detection bias)

Objective outcomes 
low risk

 

 
No blinding of outcome assessment, but the review authors judge that the outcome measurement is not likely to be influenced by lack of blinding;

Blinding of outcome assessment ensured, and unlikely that the blinding could have been broken.

6. blinding of outcome assessor (detection  bias)

Subjective outcomes

 

 
low risk

 
No blinding of outcome assessment, but the review authors judge that the outcome measurement is not likely to be influenced by lack of blinding;

Blinding of outcome assessment ensured, and unlikely that the blinding could have been broken.

high riskNo blinding of outcome assessment, and the outcome measurement is likely to be influenced by lack of blinding;

Blinding of outcome assessment, but likely that the blinding could have been broken, and the outcome measurement is likely to be influenced by lack of blinding.

unclear riskInsufficient information to permit judgement of low or high risk.

7. incomplete outcome data (attrition bias)

For all outcomes except retention in treatment or drop out

 

 
low risk

 

 

 
No missing outcome data;

Reasons for missing outcome data unlikely to be related to true outcome (for survival data, censoring unlikely to be introducing bias);

Missing outcome data balanced in numbers across intervention groups, with similar reasons for missing data across groups;

For dichotomous outcome data, the proportion of missing outcomes compared with observed event risk not enough to have a clinically relevant impact on the intervention effect estimate;

For continuous outcome data, plausible effect size (difference in means or standardized difference in means) among missing outcomes not enough to have a clinically relevant impact on observed effect size;

Missing data have been imputed using appropriate methods;

All randomised patients are reported/analysed in the group they were allocated to by randomisation irrespective of non-compliance and co-interventions (intention to treat)

high riskReason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across intervention groups;

For dichotomous outcome data, the proportion of missing outcomes compared with observed event risk enough to induce clinically relevant bias in intervention effect estimate;

For continuous outcome data, plausible effect size (difference in means or standardised difference in means) among missing outcomes enough to induce clinically relevant bias in observed effect size;

‘As-treated’ analysis done with substantial departure of the intervention received from that assigned at randomisation.

unclear riskInsufficient information to permit judgement of low or high risk (e.g. number randomised not stated, no reasons for missing data provided; number of drop out not reported for each group).

8. selective reporting (reporting bias)

 

 
low riskThe study protocol is available and all of the study’s pre-specified (primary and secondary) outcomes that are of interest in the review have been reported in the pre-specified way;

The study protocol is not available but it is clear that the published reports include all expected outcomes, including those that were pre-specified (convincing text of this nature may be uncommon).

high riskNot all of the study’s pre-specified primary outcomes have been reported;

One or more primary outcomes is reported using measurements, analysis methods or subsets of the data (e.g. subscales) that were not pre-specified;

One or more reported primary outcomes were not pre-specified (unless clear justification for their reporting is provided, such as an unexpected adverse effect);

One or more outcomes of interest in the review are reported incompletely so that they cannot be entered in a meta-analysis;

The study report fails to include results for a key outcome that would be expected to have been reported for such a study.

unclear riskInsufficient information to permit judgement of low or high risk.



 

Contributions of authors

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support

BP and KO have drafted the protocol, developed the search strategy and reviewed the protocol. GA has reviewed the protocol.

 

Declarations of interest

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support

Bolette Pedersen is co-author of a recently released review on disulfiram (Jørgensen 2011).

 

Sources of support

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support
 

Internal sources

  • Clinical Health Promotion Centre, Health Sciences, Lund University, Sweden.
    Salary: Bolette Pedersen

 

External sources

  • No sources of support supplied

References

Additional references

  1. Top of page
  2. Abstract
  3. Background
  4. Objectives
  5. Methods
  6. Appendices
  7. Contributions of authors
  8. Declarations of interest
  9. Sources of support
  10. Additional references
Alcohol and Public Policy Group 2010
Edwards 2011
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Ferri 2006
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Higgins 2011
  • Higgins JPT, Altman DG. Assessing risk of bias in included studies. Cochrane Handbook for Systematic Reviews of Interventions. Wiley-Blackwell, 2011.
Jørgensen 2011
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Martin 2007
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  • National Collaborating Centre for Mental Health. Alcohol-use disorders. Diagnosis, assessment and management of harmful drinking and alcohol dependence. National Clinical Practice Guideline 115 2011.
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  • Rehm J, Mathers C, Popova S, Thavorncharoensap M, Teerawattananon Y, Patra J. Global burden of disease and injury and economic cost attributable to alcohol use and alcohol use disorders. Lancet 2009;373:2223-33.
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  • Alcohol in the European Union. Consupmtion, harm and policy approaches . World Health Organization 2012.