Comparative efficacy of interventions for reducing injection and sexual risk behaviours to prevent HIV in injection drug users: protocol for Bayesian network meta-analysis

• Published in: BMJ open Vol. 9; no. 1; p. e022811
• Main Authors: Lang, Junjie, Jin, Lairun, Yao, Yingshui
• Format: Journal Article
• Language: English
• Published: England BMJ Publishing Group LTD 01.01.2019; BMJ Publishing Group
• Subjects: Acquired immune deficiency syndrome; AIDS; Bayes Theorem; Bayesian analysis; Drug use; Drug Users; Epidemiology; HIV; HIV Infections - prevention & control; HIV Infections - transmission; Human immunodeficiency virus; Humans; Markov Chains; Meta-analysis; Meta-Analysis as Topic; Network Meta-Analysis; Randomized Controlled Trials as Topic; Research Design; Risk Reduction Behavior; Risk-Taking; Substance Abuse, Intravenous - complications; Systematic review; Systematic Reviews as Topic; Asia; Epidemiology
• ISSN: 2044-6055; 2044-6055
• DOI: 10.1136/bmjopen-2018-022811

IntroductionDrug users are more vulnerable to AIDS than the general population. While several interventions are effective for addressing HIV in injection drug users, no meta-analysis has yet been performed to compare interventions and determine the relative benefits of each. We intend to conduct a Bayesian network meta-analysis to compare all available interventions evaluated by a randomised controlled trial for reducing injection and risky sexual behaviours for the prevention of HIV in injection drug users.Methods and analysisStudies will be retrieved by searching the following databases: MEDLINE, Embase, PsycINFO and Cochrane Central Register of Controlled Trials. The search will be performed between May and July 2018 for the literature published between 1980 and May 2018. Two authors will extract data independently. Primary outcome measures will be injection risk behaviour and HIV risk behaviour. HIV seroconversion, confirmed using an antibody test, will be the secondary outcome. Bayesian network meta-analyses will be conducted using the Markov Chains Monte Carlo method. The Cochrane revised tool, Risk of Bias, will be used to assess the risk of bias. Grading of Recommendations Assessment, Development and Evaluation will be used to assess evidence quality.Ethics and disseminationThe results of this study will be disseminated at professional conferences and via publications in peer-reviewed journals. This study will not include any confidential personal data or data on human trials; therefore, ethical approval is not required.PROSPERO registration numberCRD42018086999.