Accounting for individual differences and timing of events: estimating the effect of treatment on criminal convictions in heroin users

Psychiatric illness and the risk of reoffending: recurrent event analysis for an Australian birth cohort

BACKGROUND

Psychiatric illness is a well-established risk factor for criminal justice system involvement, but less is known about the relationships between specific psychiatric illnesses and reoffending. Research typically examines reoffending as a single discrete event. We examined the relationship between different psychiatric disorders and types of reoffending while accounting for multiple reoffending events over time.

METHODS

Data were drawn from a population cohort of 83,039 individuals born in Queensland, Australia, in 1983 and 1984 and followed to age 29-31 years. Psychiatric diagnoses were drawn from inpatient health records and offending information was drawn from court records. Descriptive and recurrent event survival analyses were conducted to examine the association between psychiatric disorders and reoffending.

RESULTS

The cohort included 26,651 individuals with at least one proven offence, with 3,580 (13.4%) of these individuals also having a psychiatric disorder. Individuals with any psychiatric disorder were more likely to reoffend compared to those without a disorder (73.1% vs. 56.0%). Associations between psychiatric disorders and reoffending varied across age. Individuals with a psychiatric disorder only started to accumulate more reoffending events from ~ 27 years, which accelerated up to age 31 years. There were both specificity and common effects in the associations between different psychiatric disorders and types of reoffending.

CONCLUSIONS

Findings demonstrate the complexity and temporal dependency of the relationship between psychiatric illness and reoffending. These results reveal the heterogeneity present among individuals who experience psychiatric illness and contact with the justice system, with implications for intervention delivery, particularly for those with substance use disorders.

History of the discovery, development, and FDA-approval of buprenorphine medications for the treatment of opioid use disorder

Buprenorphine-based medications were first approved by the United States Food and Drug Administration in 2002 for the treatment of opioid dependence, or opioid use disorder (OUD) as the condition is presently known. This regulatory milestone was the outcome of 36 years of research and development, which also led to the development and approval of several other new buprenorphine-based medications. In this short review, we first describe the discovery and early development stages of buprenorphine. Second, we review key steps that led to the development of buprenorphine as a drug product. Third, we explain the regulatory approval of several buprenorphine-based medications for the treatment of OUD. We also discuss these developments in the context of the evolution of regulations and policies that have progressively improved OUD treatment availability and efficacy, although challenges remain in removing system-level, provider-level, and local-level barriers to quality treatment, to integrating OUD treatment into routine care and other settings, to reducing disparities in access to treatment, and to optimizing person-centered outcomes.

Does heroin-assisted treatment reduce crime? A review of randomized-controlled trials

BACKGROUND AND AIMS

Several randomized controlled trials (RCTs) conclude that heroin-assisted-treatment (HAT) has a larger benefit-cost ratio than oral methadone because HAT more reliably and substantially reduces participants' criminal activity. This review: (1) summarizes results from RCTs concerning the comparative effectiveness of HAT for reducing criminal activity and (2) examines the role of different mechanisms for explaining changes in crime.

DESIGN

Systematic search of five databases for RCTs evaluating comparative effectiveness of HAT on participant crime outcomes and potential mediators of crime. Narrative synthesis with tabular comparisons of outcomes extracted across RCTs.

SETTING

Europe and Canada.

PARTICIPANTS

Twenty studies, spanning 10 RCTs with 2427 participants, met inclusion criteria.

INTERVENTIONS

HAT compared to other treatments for opioid use disorder, primarily oral methadone.

MEASUREMENTS

The primary outcome was criminal activity. Mediator outcomes included illicit heroin use, drug expenditures, employment and earnings and social functioning.

FINDINGS

All trials found significantly reduced criminal activity among HAT participants, and four found significantly larger reductions for HAT compared to control condition [median odds ratios (ORs) = 0.45]. Reductions in crime are concentrated in drug-related and property offenses (ORs range from 0.14 to 0.90 and from 0.12 to 1.89, respectively). Comparative efficacy of HAT for reducing illicit heroin use probably explains reductions in drug possession offenses, but does not show consistent correlation with drug dealing or property offenses. While three trials showed reductions in drug expenditures as possibly driving crime reductions, others did not report expenditures. There is little evidence that treatment effects on economic and social functioning outcomes explain within-trial changes in criminal activity.

CONCLUSIONS

Existing literature suggests that heroin-assisted treatment reduces criminal activity, but trials varied in whether these effects exceeded those from oral methadone treatment. Inconsistency in outcome measures across trials complicates understanding drivers of heterogeneity. More detailed information on legal and illegal income, drug expenditures and social interactions could improve our understanding of the causal mechanisms underlying the effect of heroin-assisted-treatment on crime.

How handling missing data may impact conclusions: A comparison of six different imputation methods for categorical questionnaire data

Objectives:

Missing data is a recurrent issue in many fields of medical research, particularly in questionnaires. The aim of this article is to describe and compare six conceptually different multiple imputation methods, alongside the commonly used complete case analysis, and to explore whether the choice of methodology for handling missing data might impact clinical conclusions drawn from a regression model when data are categorical.

Methods:

In addition to the commonly used complete case analysis, we tested the following six imputation methods: multiple imputation using expectation–maximization with bootstrapping, multiple imputation using multiple correspondence analysis, multiple imputation using latent class analysis, multiple hot deck imputation and multivariate imputation by chained equations with two different model specifications: logistic regression and random forests. The methods are tested on real data from a questionnaire-based study in the Norwegian opioid maintenance treatment programme.

Results:

All methods performed relatively well when the sample size was large (n = 1000). For a smaller sample size (n = 200), the regression estimates depend heavily on the level of missing. When the amount of missing was ⩾20%, in particular, complete case analysis, hot deck and random forests had biased estimates with too low coverage. Multiple imputation using multiple correspondence analysis had the best performance all over.

Conclusion:

The choice of missing handling methodology has a significant impact on the clinical interpretation of the accompanying statistical analyses. With missing data, the choice of whether to impute or not, and choice of imputation method, can influence clinical conclusion drawn from a regression model and should therefore be given sufficient consideration.

Incidence of future arrests in adults involved in the criminal justice system with opioid use disorder receiving extended release naltrexone compared to treatment as usual

BACKGROUND

Criminal justice involved (CJS) populations with opioid use disorder (OUD) have high rates of relapse, future arrests, and death upon release. While medication for OUD (MOUD) reduces opioid relapse, concerns regarding diversion and stigma limit treatment in CJS populations. Extended release naltrexone (XR-NTX), as an opioid antagonist, may be more acceptable to CJS administrators. However, the impact of XR-NTX on criminal recidivism remains unknown.

METHODS

Arrest data from a published randomized trial comparing XR-NTX to treatment as usual (TAU) was captured by self-report and official state arrest records. Comparisons of future arrests, time to first arrest and total number of arrests were performed using chi square tests and multivariable generalized regression models. Secondary outcomes explored differences in arrests by type and severity of crime, use of opioid and other drugs, and study phase.

RESULTS

Of 308 participants randomized, 300 had arrest data. The incidence of arrests did not differ between XR-NTX (47.6%) and TAU (42.5%) participants. (ChiSq p = 0.37). Additionally, there was no significant difference in time to first arrest (adjusted HR 1.35, CI 0.96-1.89) and number of arrests per participant (adjusted IR 1.33, CI 0.78-2.27). Controlling for gender, age, previous criminal activity, and use of non-opioid drugs, logistic regression demonstrated no significant difference in incidence of arrests between groups (adjusted OR 1.38, 95% CI 0.85-2.22).

CONCLUSIONS

We detected no significant difference in arrests between CJS participants with OUD randomized to XR-NTX or TAU. Despite its efficacy in reducing opioid use, XR-NTX alone may be insufficient to reduce criminal recidivism.

Associations between methadone maintenance treatment and crime: a 17-year longitudinal cohort study of Canadian provincial offenders

AIMS

To estimate and test the difference in rates of violent and non-violent crime during medicated and non-medicated methadone treatment episodes.

DESIGN, SETTING AND PARTICIPANTS

The study involved linkage of population level administrative data (health and justice) for all individuals (n = 14 530) in British Columbia, Canada with a history of conviction and who filled a methadone prescription between 1 January 1998 and 31 March 2015. Methadone maintenance treatment was the primary independent variable and was treated as a time-varying exposure. Each participant's follow-up (mean: 8 years) was divided into medicated (methadone was dispensed) and non-medicated (methadone was not dispensed) periods with mean durations of 3.3 and 4.6 years, respectively.

MEASUREMENTS

Socio-demographics of participants were examined along with the main outcomes of violent and non-violent offences.

FINDINGS

During the first 2 years of treatment (≤ 2.0 years), periods in which methadone was dispensed were associated with a 33% lower rate of violent crime [0.67 adjusted hazard ratio (AHR), 95% confidence intervals (CI) = 0.59, 0.76] and a 35% lower rate of non-violent crime (0.65 AHR, 95% CI = 0.62, 0.69) compared with non-medicated periods. This equates to a risk difference of 3.6 (95% CI = 2.6, 4.4) and 37.2 (95% CI = 33.0, 40.4) fewer violent and non-violent offences per 100 person-years, respectively. Significant but smaller protective effects of dispensed methadone were observed across longer treatment intervals (2.0 to ≤ 5.0 years, 5.0 to ≤ 10.0 years).

CONCLUSIONS

Among a cohort of Canadian offenders, rates of violent and non-violent offending were lower during periods when individuals were dispensed methadone compared with periods in which they were not dispensed methadone.