Efficacy of bupropion and cognitive behavioral therapy in the treatment of methamphetamine use disorder: a systematic review and meta-analysis

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Abstract

Objectives:

We assessed the efficacy of cognitive behavioral therapy and bupropion compared to cognitive behavioral therapy alone for methamphetamine use disorder.

Methods:

The selection criteria for this systematic review study with meta-analysis were randomized clinical trials on the efficacy of cognitive behavioral therapy and bupropion in the treatment for methamphetamine use disorder (assessed by urine metabolites). The search was conducted in PubMed, PubMed Central, LILACS, SciELO, Cochrane Library, SCOPUS, Google Scholar, Ovid Medline, Clinicaltrials.gov, and the International Clinical Trials Registry Platform. The primary outcome was relapse. Risk of bias was assessed with the RoB 2 tool. The results of each clinical trial were input into an Excel spreadsheet. We performed a meta-analysis using relative risk and a 95%CI.

Results:

Of the 597 initial articles (498 after removing duplicate records), five were included in the meta-analysis, with an aggregate sample of 539 patients. An overall relative risk of 0.91 (95%CI 0.78-1.05) was estimated for relapse.

Conclusion:

Our study limitations included publication bias and heterogeneous populations. We found no evidence that cognitive behavioral therapy and bupropion reduced the risk of relapse compared to cognitive behavioral therapy and placebo.

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Most cited references 52

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Rayyan—a web and mobile app for systematic reviews

Mourad Ouzzani, Hossam Hammady, Zbys Fedorowicz … (2017)

Background Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan (http://rayyan.qcri.org), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Results Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Conclusions Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.

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PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews

Matthew J Page (2021)

The methods and results of systematic reviews should be reported in sufficient detail to allow users to assess the trustworthiness and applicability of the review findings. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement was developed to facilitate transparent and complete reporting of systematic reviews and has been updated (to PRISMA 2020) to reflect recent advances in systematic review methodology and terminology. Here, we present the explanation and elaboration paper for PRISMA 2020, where we explain why reporting of each item is recommended, present bullet points that detail the reporting recommendations, and present examples from published reviews. We hope that changes to the content and structure of PRISMA 2020 will facilitate uptake of the guideline and lead to more transparent, complete, and accurate reporting of systematic reviews.

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Risk‐of‐bias VISualization (robvis): An R package and Shiny web app for visualizing risk‐of‐bias assessments

Luke McGuinness, Julian P. T. Higgins (2020)

Despite a major increase in the range and number of software offerings now available to help researchers produce evidence syntheses, there is currently no generic tool for producing figures to display and explore the risk-of-bias assessments that routinely take place as part of systematic review. However, tools such as the R programming environment and Shiny (an R package for building interactive web apps) have made it straightforward to produce new tools to help in producing evidence syntheses. We present a new tool, robvis (Risk-Of-Bias VISualization), available as an R package and web app, which facilitates rapid production of publication-quality risk-of-bias assessment figures. We present a timeline of the tool's development and its key functionality.

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Author and article information

Journal

Journal ID (nlm-ta): Braz J Psychiatry

Journal ID (iso-abbrev): Braz J Psychiatry

Journal ID (publisher-id): bjp

Title: Brazilian Journal of Psychiatry

Publisher: Associação Brasileira de Psiquiatria

ISSN (Print): 1516-4446

ISSN (Electronic): 1809-452X

Publication date (Electronic): 08 June 2023

Publication date Collection: May-Jun 2023

Volume: 45

Issue: 3

Pages: 280-285

Affiliations

[1]Facultad de Medicina, Universidad de Piura, Lima, Peru

Author notes

Correspondence: Marie Antouannet Bernabé Barreto, San Felipe Avenue 1079/1804, Jesus Maria, Lima, 15072, Peru. E-mail: marie.bernabe@ 123456alum.udep.edu.pe

Author information

Luis Fernando Maya Apuy https://orcid.org/0000-0002-8213-4824

Article

DOI: 10.47626/1516-4446-2022-2979

PMC ID: 10288480

PubMed ID: 36917815

SO-VID: bf50233e-fb19-4669-871f-9de08b687a2f

License:

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 work is properly cited.

History

Date received : 28 November 2022

Date accepted : 13 February 2023

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