7
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Comparative efficacy and acceptability of psychosocial interventions for individuals with cocaine and amphetamine addiction: A systematic review and network meta-analysis

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Clinical guidelines recommend psychosocial interventions for cocaine and/or amphetamine addiction as first-line treatment, but it is still unclear which intervention, if any, should be offered first. We aimed to estimate the comparative effectiveness of all available psychosocial interventions (alone or in combination) for the short- and long-term treatment of people with cocaine and/or amphetamine addiction.

          Methods and findings

          We searched published and unpublished randomised controlled trials (RCTs) comparing any structured psychosocial intervention against an active control or treatment as usual (TAU) for the treatment of cocaine and/or amphetamine addiction in adults. Primary outcome measures were efficacy (proportion of patients in abstinence, assessed by urinalysis) and acceptability (proportion of patients who dropped out due to any cause) at the end of treatment, but we also measured the acute (12 weeks) and long-term (longest duration of study follow-up) effects of the interventions and the longest duration of abstinence. Odds ratios (ORs) and standardised mean differences were estimated using pairwise and network meta-analysis with random effects. The risk of bias of the included studies was assessed with the Cochrane tool, and the strength of evidence with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. We followed the PRISMA for Network Meta-Analyses (PRISMA-NMA) guidelines, and the protocol was registered in PROSPERO (CRD 42017042900). We included 50 RCTs evaluating 12 psychosocial interventions or TAU in 6,942 participants. The strength of evidence ranged from high to very low. Compared to TAU, contingency management (CM) plus community reinforcement approach was the only intervention that increased the number of abstinent patients at the end of treatment (OR 2.84, 95% CI 1.24–6.51, P = 0.013), and also at 12 weeks (OR 7.60, 95% CI 2.03–28.37, P = 0.002) and at longest follow-up (OR 3.08, 95% CI 1.33–7.17, P = 0.008). At the end of treatment, CM plus community reinforcement approach had the highest number of statistically significant results in head-to-head comparisons, being more efficacious than cognitive behavioural therapy (CBT) (OR 2.44, 95% CI 1.02–5.88, P = 0.045), non-contingent rewards (OR 3.31, 95% CI 1.32–8.28, P = 0.010), and 12-step programme plus non-contingent rewards (OR 4.07, 95% CI 1.13–14.69, P = 0.031). CM plus community reinforcement approach was also associated with fewer dropouts than TAU, both at 12 weeks and the end of treatment (OR 3.92, P < 0.001, and 3.63, P < 0.001, respectively). At the longest follow-up, community reinforcement approach was more effective than non-contingent rewards, supportive-expressive psychodynamic therapy, TAU, and 12-step programme (OR ranging between 2.71, P = 0.026, and 4.58, P = 0.001), but the combination of community reinforcement approach with CM was superior also to CBT alone, CM alone, CM plus CBT, and 12-step programme plus non-contingent rewards (ORs between 2.50, P = 0.039, and 5.22, P < 0.001). The main limitations of our study were the quality of included studies and the lack of blinding, which may have increased the risk of performance bias. However, our analyses were based on objective outcomes, which are less likely to be biased.

          Conclusions

          To our knowledge, this network meta-analysis is the most comprehensive synthesis of data for psychosocial interventions in individuals with cocaine and/or amphetamine addiction. Our findings provide the best evidence base currently available to guide decision-making about psychosocial interventions for individuals with cocaine and/or amphetamine addiction and should inform patients, clinicians, and policy-makers.

          Abstract

          Using network meta-analysis, Andrea Cipriani and colleagues compare individual and combined psychosocial interventions aimed at treating cocaine and amphetamine addictions, to identify which strategies are acceptable to patients and effective, both short and long-term.

          Author summary

          Why was this study done?
          • Cocaine and amphetamines are the most commonly abused stimulants in people aged 15–64 years, and they are linked to significant physical and mental illness as well as a substantial burden for society.

          • Currently, clinical guidelines recommend the use of psychosocial interventions as first-line treatment for people with cocaine and/or amphetamine addiction.

          • However, it is still unclear which psychosocial intervention, if any, is the most effective treatment for such patients.

          What did the researchers do and find?
          • We used network meta-analysis to analyse 50 clinical studies (6,943 participants) on 12 different psychosocial interventions for cocaine and/or amphetamine addiction.

          • We found that the combination of 2 different psychosocial interventions, namely contingency management and community reinforcement approach, was the most efficacious and most acceptable treatment both in the short and long term.

          What do these findings mean?
          • To our knowledge, this is the best evidence base to guide decision-making about psychosocial interventions for cocaine and/or amphetamine addiction. Clinical guidelines should be updated to reflect these results, and policy-makers are encouraged to invest accordingly.

          • Future trials should use contingency management plus community reinforcement approach as the reference treatment.

          Related collections

          Most cited references79

          • Record: found
          • Abstract: found
          • Article: not found

          The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations.

          The PRISMA statement is a reporting guideline designed to improve the completeness of reporting of systematic reviews and meta-analyses. Authors have used this guideline worldwide to prepare their reviews for publication. In the past, these reports typically compared 2 treatment alternatives. With the evolution of systematic reviews that compare multiple treatments, some of them only indirectly, authors face novel challenges for conducting and reporting their reviews. This extension of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement was developed specifically to improve the reporting of systematic reviews incorporating network meta-analyses. A group of experts participated in a systematic review, Delphi survey, and face-to-face discussion and consensus meeting to establish new checklist items for this extension statement. Current PRISMA items were also clarified. A modified, 32-item PRISMA extension checklist was developed to address what the group considered to be immediately relevant to the reporting of network meta-analyses. This document presents the extension and provides examples of good reporting, as well as elaborations regarding the rationale for new checklist items and the modification of previously existing items from the PRISMA statement. It also highlights educational information related to key considerations in the practice of network meta-analysis. The target audience includes authors and readers of network meta-analyses, as well as journal editors and peer reviewers.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial.

            To present some simple graphical and quantitative ways to assist interpretation and improve presentation of results from multiple-treatment meta-analysis (MTM). We reanalyze a published network of trials comparing various antiplatelet interventions regarding the incidence of serious vascular events using Bayesian approaches for random effects MTM, and we explore the advantages and drawbacks of various traditional and new forms of quantitative displays and graphical presentations of results. We present the results under various forms, conventionally based on the mean of the distribution of the effect sizes; based on predictions; based on ranking probabilities; and finally, based on probabilities to be within an acceptable range from a reference. We show how to obtain and present results on ranking of all treatments and how to appraise the overall ranks. Bayesian methodology offers a multitude of ways to present results from MTM models, as it enables a natural and easy estimation of all measures based on probabilities, ranks, or predictions. Copyright © 2011 Elsevier Inc. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Graphical Tools for Network Meta-Analysis in STATA

              Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Writing – original draft
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Formal analysisRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – original draft
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                26 December 2018
                December 2018
                : 15
                : 12
                : e1002715
                Affiliations
                [1 ] Department of Psychiatry, University of Oxford, Oxford, United Kingdom
                [2 ] Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, United Kingdom
                [3 ] Institute of Psychiatry and Clinical Psychology, Catholic University of the Sacred Heart, Rome, Italy
                [4 ] School of Hygiene and Preventive Medicine, University of Rome Tor Vergata, Rome, Italy
                [5 ] Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
                [6 ] Department of Dynamic and Clinical Psychology, Sapienza University of Rome, Rome, Italy
                [7 ] Mental Health and Substance Abuse, World Health Organization, Geneva, Switzerland
                [8 ] Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, United States of America
                [9 ] Department of Psychiatry, VA Palo Alto Health Care System, Palo Alto, California, United States of America
                University of New South Wales, AUSTRALIA
                Author notes

                I have read the journal’s policy and the authors of this manuscript have the following competing interests: MJO is a consultant to Acadia Pharmaceuticals, Genomind, Johnson & Johnson/Janssen, Otsuka/Lundbeck, Sage Therapeutics, Sunovion, and Supernus Pharmaceuticals, and has received research funding from Palo Alto Health Sciences. All other authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-2478-7763
                http://orcid.org/0000-0003-2022-2690
                http://orcid.org/0000-0002-4125-2066
                http://orcid.org/0000-0001-5984-8696
                http://orcid.org/0000-0001-8697-6183
                http://orcid.org/0000-0003-0353-7535
                http://orcid.org/0000-0001-5179-8321
                Article
                PMEDICINE-D-18-02294
                10.1371/journal.pmed.1002715
                6306153
                30586362
                e9c8e31e-d80d-4eb4-bf0f-076655d42425
                © 2018 De Crescenzo et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 26 June 2018
                : 15 November 2018
                Page count
                Figures: 4, Tables: 1, Pages: 24
                Funding
                Funded by: National Institute of Health Research
                Award ID: BRC-1215-20005
                Award Recipient :
                This study was funded by National Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre (BRC-1215-20005, https://oxfordhealthbrc.nihr.ac.uk/). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Physical Sciences
                Chemistry
                Chemical Compounds
                Alkaloids
                Cocaine
                Medicine and Health Sciences
                Pharmacology
                Behavioral Pharmacology
                Recreational Drug Use
                Cocaine
                Medicine and Health Sciences
                Health Care
                Patients
                Outpatients
                People and places
                Geographical locations
                North America
                United States
                Medicine and Health Sciences
                Pharmacology
                Drugs
                Amphetamines
                Medicine and Health Sciences
                Pharmacology
                Behavioral Pharmacology
                Recreational Drug Use
                Amphetamines
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Metaanalysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Metaanalysis
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mental Health Therapies
                Psychotherapy
                Biology and Life Sciences
                Psychology
                Addiction
                Social Sciences
                Psychology
                Addiction
                Medicine and Health Sciences
                Health Care
                Psychological and Psychosocial Issues
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Medicine
                Medicine

                Comments

                Comment on this article