Dataset Information

The causal effect of opioid substitution treatment on HAART medication refill adherence.

ABSTRACT: BACKGROUND:People who inject drugs (PWID) account for roughly 13% of the prevalent HIV/AIDS population outside of sub-Saharan Africa, and access to opioid substitution treatment (OST) is limited in many settings globally. OST likely facilitates access to HAART, yet sparse evidence is available to support this hypothesis. Our objective was to determine the causal impact of OST exposure on HAART adherence among HIV-positive PWID in a Canadian setting. METHODS:We executed a retrospective cohort study using linked population-level data for British Columbia, Canada (January 1996-March 2010). We considered HIV-positive PWID after meeting HAART initiation criteria. A marginal structural model was estimated on a monthly timescale using inverse probability of treatment weights. The primary outcome was 95% HAART adherence, according to pharmacy refill compliance. Exposure to OST was defined as 95% of OST receipt, and we controlled for a range of fixed and time-varying covariates. RESULTS:Our study included 1852 (63.3%) HIV-positive PWID with a median follow-up of 5.5 years; 34% were female and 39% had previously accessed OST. The baseline covariate-adjusted odds of HAART adherence following OST exposure was 1.96 (95% confidence interval: 1.72-2.24), although the adjusted odds estimated within the marginal structural model was 1.68 (1.48-1.92). Findings were robust to sensitivity analyses on model specification. CONCLUSION:In a setting characterized by universal healthcare and widespread access to both office-based OST and HAART, OST substantially increased the odds of HAART adherence. This underlines the need to address barriers to OST globally to reduce the disease burden of both opioid dependence and HIV/AIDS.

SUBMITTER: Nosyk B

PROVIDER: S-EPMC4583234 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The causal effect of opioid substitution treatment on HAART medication refill adherence.

Nosyk Bohdan B Min Jeong E JE Colley Guillaume G Lima Viviane D VD Yip Benita B Milloy M-J S MJ Wood Evan E Montaner Julio S G JS

AIDS (London, England) 20150501 8

<h4>Background</h4>People who inject drugs (PWID) account for roughly 13% of the prevalent HIV/AIDS population outside of sub-Saharan Africa, and access to opioid substitution treatment (OST) is limited in many settings globally. OST likely facilitates access to HAART, yet sparse evidence is available to support this hypothesis. Our objective was to determine the causal impact of OST exposure on HAART adherence among HIV-positive PWID in a Canadian setting.<h4>Methods</h4>We executed a retrospec ...[more]

PMID: 25915170

Similar Datasets

Project description:BackgroundOpioid Use Disorder (OUD) and opioid overdose (OD) impose huge social and economic burdens on society and health care systems. Research suggests that Medication for Opioid Use Disorder (MOUD) is effective in the treatment of OUD. We use machine learning to investigate the association between patient's adherence to prescribed MOUD along with other risk factors in patients diagnosed with OUD and potential OD following the treatment.MethodsWe used longitudinal Medicaid claims for two selected US states to subset a total of 26,685 patients with OUD diagnosis and appropriate Medicaid coverage between 2015 and 2018. We considered patient age, sex, region level socio-economic data, past comorbidities, MOUD prescription type and other selected prescribed medications along with the Proportion of Days Covered (PDC) as a proxy for adherence to MOUD as predictive variables for our model, and overdose events as the dependent variable. We applied four different machine learning classifiers and compared their performance, focusing on the importance and effect of PDC as a variable. We also calculated results based on risk stratification, where our models separate high risk individuals from low risk, to assess usefulness in clinical decision-making.ResultsAmong the selected classifiers, the XGBoost classifier has the highest AUC (0.77) closely followed by the Logistic Regression (LR). The LR has the best stratification result: patients in the top 10% of risk scores account for 35.37% of overdose events over the next 12 month observation period. PDC score calculated over the treatment window is one of the most important features, with better PDC lowering risk of OD, as expected. In terms of risk stratification results, of the 35.37% of overdose events that the predictive model could detect within the top 10% of risk scores, 72.3% of these cases were non-adherent in terms of their medication (PDC <0.8). Targeting the top 10% outcome of the predictive model could decrease the total number of OD events by 10.4%.ConclusionsThe best performing models allow identification of, and focus on, those at high risk of opioid overdose. With MOUD being included for the first time as a factor of interest, and being identified as a significant factor, outreach activities related to MOUD can be targeted at those at highest risk.

Project description:BACKGROUND:Alcohol is often consumed with opioids and alcohol misuse interferes with treatment for opioid use disorder (OUD). Drug misuse is associated with worse alcohol use disorder (AUD) treatment outcomes, yet no studies have investigated the role of opioid misuse in AUD treatment outcomes. METHODS:We conducted secondary analyses of the medication conditions of the COMBINE study (n = 1,226), a randomized clinical trial of medications (acamprosate and/or naltrexone) and behavioral interventions (medication management and/or behavioral intervention) for alcohol dependence. We examined associations between baseline opioid misuse and the use of cannabis and other drugs with time to first drinking day, time to first heavy drinking day, and the frequency and intensity of drinking during treatment and 1 year following treatment, based on latent profile analysis. Opioid misuse was defined as use of illicit or prescription opioids without a prescription or not as directed in the previous 6 months, in the absence of OUD. Self-reported cannabis and other drug use were also examined. Seventy individuals (5.7%) met the opioid misuse definition and 542 (44.2%) reported use of cannabis or other drugs without opioid misuse. We also examined medication adherence as a potential mediator. RESULTS:Baseline opioid misuse significantly predicted the time to first heavy drinking day (OR = 1.38 [95% CI: 1.13, 1.64], p = 0.001) and a higher probability of being in a heavier and more frequent drinking profile at the end of treatment (OR = 2.90 [95% CI: 1.43, 5.90], p = 0.003), and at 1 year following treatment (OR = 2.66 [95% CI: 1.26, 5.59], p = 0.01). Cannabis and other drug use also predicted outcomes. Medication adherence partially mediated the association between opioid misuse, cannabis use, other drug use, and treatment outcomes. CONCLUSIONS:Opioid misuse and other drug use were associated with poorer AUD treatment outcomes, which was partially mediated by medication adherence. Clinicians and researchers should assess opioid misuse and other drug use in patients undergoing AUD treatment.

Project description:BackgroundOpioid-related mortality is high and increasing in the Western world, and interventions aimed at reducing opioid-related deaths represent an important area of study. In Skåne County, Sweden, a patient choice reform resulted in increased access to opioid substitution treatment (OST). In addition, a gradual shift towards less restrictive terms for exclusion from OST has been implemented. The aim of this study was to assess the impact of these policy changes on opioid-related deaths.MethodsDetailed data on opioid-related deaths in Skåne during the 2 years prior to and following the policy change were obtained from forensic records and from health care services. Data on overdose deaths for Skåne and the rest of Sweden were obtained using publicly available national register data. Time periods were used as the predictor for opioid-related deaths in the forensic data. The national level data were used in a natural experiment design in which rates of overdose deaths were compared between Skåne and the rest of Sweden before and after the intervention.ResultsThere was no significant difference in the number of deaths in Skåne between the data collection periods (RR: 1.18 95% CI:0.89-1.57, p= 0.251). The proportion of deaths among patients enrolled in OST increased between the two periods (2.61, 1.12-6.10, p= 0.026). There was no change in deaths related to methadone or buprenorphine in relation to deaths due to the other opioids included in the study (0.92, 0.51-1.63, p= 0.764). An analysis of national mortality data showed an annual relative decrease in unintentional drug deaths in Skåne compared to the rest of Sweden following the onset of the reform (0.90, 0.84-0,97, p= 0.004).ConclusionsOpioid-related deaths, as assessed using forensic data, has not changed significantly in Skåne following a change to lower-threshold OST. By contrast, national level data indicate that the policy change has been associated with decreased overdose deaths. The discrepancy between these results highlights the need for more research to elucidate this issue. The result that more patients die during ongoing OST following an increase in access to treatment underlines the need for further preventive interventions within the OST treatment setting.

Dataset Information

The causal effect of opioid substitution treatment on HAART medication refill adherence.

Publications

The causal effect of opioid substitution treatment on HAART medication refill adherence.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets