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Abstract: Background: The National Institute on Drug Abuse (NIDA) Clinical Trials Network (CTN) has supported clinical trials of substance use disorder (SUD) interventions for 25 years. This review describes the use of implementation outcomes across CTN trials, characterizes outcomes included, and identifies gaps and potential opportunities to strengthen implementation research within the CTN and the field of SUD treatment. Methods: This systematic review included active or completed studies listed on the CTN Dissemination Library webpage as of August 18, 2021, and approved by the CTN for development by January 1, 2022. Study summaries and protocols were reviewed if they: 1) measured at least one implementation outcome and 2) examined a practice change, intervention, or process. Extracted data elements included trial design characteristics, implementation frameworks, and outcome assessment domains informed by the RE-AIM and Proctor Implementation Outcomes Frameworks. Results: 114 protocols were considered, 42 full-text protocols were screened, and 25 were included for data extraction. Start dates of trials spanned a 20-year period (2004–2024) with latter studies including more implementation outcomes. Fidelity (n = 29) and reach/penetration (n = 26) were the most included implementation outcomes. Equity was not identified in any protocols. Methods of defining, capturing, and evaluating outcomes data varied across trials and outcomes. Conclusions: The inclusion of implementation outcomes increased over time, perhaps reflecting a growing emphasis on implementation research. Incorporating measures of equity could advance knowledge about differential receipt or effectiveness of SUD interventions. Future research should seek to improve the consistency and comprehensiveness in descriptions of implementation science elements. Related protocols: CTN-0016, CTN-0056, CTN-0062-Ot, CTN-0064, CTN-0065, CTN-0069, CTN-0074, CTN-0074-A-1, CTN-0075, CTN-0076-Ot, CTN-0079, CTN-0079-A-1, CTN-0088, CTN-0090, CTN-0091, CTN-0095, CTN-0096, CTN-0097, CTN-0098, CTN-0099, CTN-0102, CTN-0103, CTN-0107, CTN-0116, CTN-0121

Abstract:

There is no gold standard and considerable heterogeneity in outcome measures used to evaluate treatments for opioid use disorder (OUD) along the opioid treatment cascade. The aim of this study was to develop the US National Institute on Drug Abuse (NIDA) National Drug Abuse Treatment Clinical Trials Network (CTN) opioid use disorder core outcomes set (OUD-COS), using a four round, e-Delphi expert panel consensus design with plenary research group discussion and targeted consultation.

A panel of 25 members (including clinical practitioners, clinical researchers, and administrative staff from the CTN, its affiliated clinical and community sites, and the NIDA Center for the CTN) completed an online questionnaire to rank 24 candidate items in four domains (biomedical/disease status; behaviors, symptoms, and functioning; opioid treatment cascade; and morbidity and mortality). Items were ranked with defined specification on a 9-point scale for importance, with a standard 70% consensus criterion.

After the fourth round of the questionnaire and subsequent discussion, consensus was reached for five outcomes: two patient reported (global impression of improvement and incident non-fatal overdose); one clinician reported (illicit/non-medical drug toxicology); and two from administrative records (duration of treatment and fatal opioid poisoning).

Conclusions: An e-Delphi consensus study has produced the US National Institute on Drug Abuse (NIDA) National Drug Abuse Treatment Clinical Trials Network opioid use disorder core outcomes set (version 1) for opioid use disorder treatment efficacy and effectiveness research.

Abstract:

Across the addiction field, the primary outcome in treatment research has been reduction in drug consumption. A comprehensive view of the impact of substance use disorders on human functioning suggests that effective treatments should address the many consequences and features of addiction beyond drug use, a recommendation forwarded by multiple expert panels and review papers. Despite recurring proposals, and a compelling general rationale for moving beyond drug use as the sole standard for evaluating addiction treatment, the field has yet to adopt any core set of “other” measures that are routinely incorporated into treatment research. Among the many reasons for the limited impact of previous proposals has been the absence of a clear set of guidelines for selecting candidate outcomes. This paper is the result of the deliberations of a panel of substance abuse treatment and research experts, including many members of the National Drug Abuse Treatment Clinical Trials Network (CTN), convened by the National Institute on Drug Abuse (NIDA) to discuss appropriate outcome measures for clinical trials of substance abuse treatments (a paper from a second panel at the same meeting concluded the primary outcome measure should be an indicator of drug-taking behavior, and that there is no single clinical metric that is appropriate for inclusion in most drug dependence treatment trials — see Donovan et al, 2012). This paper provides an overview of previous recommendations and outlines specific guidelines for consideration of candidate outcomes. A list of outcomes meeting those guidelines is described and illustrated in detail with two outcomes: craving and quality of life. The paper concludes with specific recommendations for moving beyond the outcome listing offered in this paper to promote the programmatic incorporation of these outcomes into treatment research.

Update: Commentary about this article and a related article by Dennis Donovan (see item 683), with responses from Drs. Tiffany and Donovan, was published in Addiction 2012;107(4):719-726.

Abstract:

Clinical trials test the safety and efficacy of behavioral and pharmacological interventions in drug-dependent individuals. However, there is no consensus about the most appropriate outcome(s) to consider in determining treatment efficacy or on the most appropriate methods for assessing selected outcome(s). This paper summarizes the discussion and recommendations of a panel of treatment and research experts, recently convened by the U.S. National Institute on Drug Abuse (NIDA) to select appropriate primary outcomes for drug dependence treatment clinical trials, including the National Drug Abuse Treatment Clinical Trials Network (CTN), and examine the feasibility of selecting a common outcome to be included in all or most trials (a paper from a second panel at the same meeting presents an overview of previous recommendations and outlines specific guidelines for consideration in candidate outcomes — see Tiffany et al, 2012). A brief history of outcomes employed in prior drug dependence treatment research, incorporating perspectives from tobacco and alcohol research, is included.

Conclusions: The panel reached consensus that the primary outcome measure should be an indicator of drug-taking behavior, and that there is no single clinical metric that is appropriate for inclusion in most drug dependence treatment trials. The panel noted that a wide variety of indicators are available, the most appropriate one varying by study methods and goals (e.g. abstinence or reduction of use). It is recommended that a decision process, based on such trial variables, be developed to guide the selection of primary and secondary outcomes as well as the methods to assess them.

Update: Commentary about this article and a related article by Stephen Tiffany (see item 793), with responses from Drs. Donovan and Tiffany, was published in Addiction 2012;107(4):719-726.

Abstract:

Selection of appropriate outcome measures is important for clinical studies of drug addiction treatment. Researchers use various methods for collecting drug use outcomes and must consider substances to be included in a urine drug screen (UDS), accuracy of self-report, use of various instruments and procedures for collecting self-reported drug use, and timing of outcome assessments. This study sought to define a set of candidate measures to (1) assess their intercorrelation and (2) identify any differences in results. To that end, data were combined from seven completed protocols in the National Drug Abuse Treatment Clinical Trials Network (CTN), with a total of 1897 participants. Nine outcome measures were defined, based on UDS, self-report, or a combination, then multivariable, multilevel generalized estimating equation models were used to assess subgroup differences in intervention success, controlling for baseline differences and accounting for clustering by CTN protocols. Results found high correlations among all candidate outcomes. All outcomes showed consistent overall results with no significant intervention impact on drug use during follow-up. However, with most UDS variables, but not with self-report or “corrected self-report,” a significant gender–ethnicity interaction with benefit shown in African American women, White women, and Hispanic men was observed.

Conclusions: Despite strong associations between candidate measures, important differences in results were found. This study demonstrates the potential utility and impact of combining UDS and self-report data for drug use assessment. The results suggest possible differences in intervention efficacy by gender and ethnicity, but highlight the need to cautiously interpret observed interactions. Additional studies like this one will help guide implementation of methodological recommendations to construct combined measures.

Abstract:

Clinical trials testing the effectiveness of interventions for addictions, HIV transmission risk, and other behavioral health problems are important to advancing evidence-based treatment. Such trials are expensive and time-consuming to conduct, but the underlying effect sizes tend to be modest, and often findings are disappointing, failing to show evidence of treatment effects. This study aimed to demonstrate how appropriate covariation for baseline severity can enhance detection of treatment effects, using an example from the National Drug Abuse Treatment Clinical Trials Network (protocol CTN-0015, “Women and Trauma”). Baseline severity, the score of the outcome measure at baseline, prior to randomization, is often strongly associated with outcome in such studies. Covariation for baseline score may enhance detection of treatment effects, because the variance explained by the baseline score is removed from the error variance in the estimate of the difference in outcome between treatments. Alternatively, the effect of treatment may manifest in the form of a baseline-by-treatment interaction. Common interaction patterns include that treatment may be more effective among patients with higher levels of baseline severity, or treatment may be more effective among patients with low severity at baseline (“relapse prevention” effect). Such effects may be important to developing treatment guidelines and offer clues toward understanding the mechanisms of action of treatments and of the disorders.

Conclusions: This article illustrates principles of covariation for baseline and the baseline-by-treatment interaction in nontechnical graphical terms, and discusses examples from clinical trials, including the CTN. Implications for the design and analysis of clinical trials are discussed, and it is argued that covariation for baseline severity of the outcome measure and testing of the baseline-by-treatment interaction should be considered for inclusion in the primary outcome analyses of treatment effectiveness trials of substantial size.

Abstract:

In clinical trials of treatment for stimulant abuse, including several National Drug Abuse Treatment Clinical Trials Network (CTN) protocols, researchers commonly record both Time-Line Follow-Back (TLFB) self-reports and urine drug screen (UDS) results. This study aimed to compare the power of self-report, qualitative (use vs. no use) UDS assessment, and various algorithms to generate self-report-UDS composite measures to detect treatment differences via t-test in simulated clinical trial data. Monte Carlo simulations, patterned in part on real data to model self-report reliability, were performed on UDS errors, dropout, informatively missing UDS reports, incomplete adherence to a urine donation schedule, temporal correlation of drug use, number of days in the study period, number of patients per arm, and distribution of drug-use probabilities. Investigated algorithms include maximum likelihood and Bayesian estimates, self-report alone, UDS alone, and several simple modifications of self-report (referred to here as ELCON algorithms) which eliminate perceived contradictions between it and UDS. Among the algorithms investigated, simple ELCON algorithms gave rise to the most powerful t-tests to detect mean group differences in stimulant drug use.

Conclusions: Further investigation is needed to determine if simple, naïve procedures such as the ELCON algorithms are optimal for comparing clinical study treatment arms. But researchers who currently require an automated algorithm in scenarios similar to those simulated for combining TLFB and UDS to test group differences in stimulant use should consider one of the ELCON algorithms. This analysis continues a line of inquiry which could determine how best to measure outpatient stimulant use in clinical trials.

Abstract:

No consensus is available for identifying the best primary outcome for substance use disorder trials, making interpretation across trials difficult. Abstinence is the most desirable treatment outcome although a wide variety of other endpoints have been used. This report provides a framework for determining an optimal primary endpoint and the relevant measurement approach for substance use disorder treatment trials. The framework was developed based on a trial for stimulant abuse using exercise as an augmentation treatment, delivered within the NIDA Clinical Trials Network (protocol CTN-0037). The use of a common endpoint across trials will facilitate comparisons of treatment efficacy. Primary endpoint options in existing substance abuse studies were evaluated. This evaluation included surveys of the literature for endpoints and measurement approaches, followed by assessment of endpoint choices against study design issues, population characteristics, tests of sensitivity, and tests of clinical meaningfulness.

Conclusion: We concluded that the best current choice for a primary endpoint is percent days abstinent, as measured by the Time Line Follow Back interview conducted three times a week with recall aided by a take-home Substance Use Diary. To improve the accuracy of the self-reported drug use, the results of qualitative urine drug screens will be used in conjunction with the Time Line Follow Back results. There is a need for a standardized endpoint in this field to allow for comparison across treatment studies, and we suggest that the recommended candidate endpoint be considered. However, the study design and goals ultimately must guide the final decision.

Related protocols: CTN-0037

Abstract:

In clinical trials of behavioral health interventions, outcome variables often take the form of counts, such as days using substances or episodes of unprotected sex. Classically, count data follow a Poisson distribution; however, in practice such data often display greater heterogeneity in the form of excess zeros (zero-inflation) or greater spread in the values (overdispersion) or both. Greater sample heterogeneity may be especially common in community-based effectiveness trials, where broad eligibility criteria are implemented to achieve a generalizable sample. This article reviews the characteristics of Poisson model and the related models that have been developed to handle overdispersion (negative binomial (NB) model) or zero-inflation (zero-inflated Poisson (ZIP) and Poisson hurdle (PH) models) or both (zero-inflated negative binomial (ZINB) and negative binomial hurdle (NBH) models). All six models were used to model the effect of an HIV-risk reduction intervention on the count of unprotected sexual occasions (USOs), using data from a previously completed clinical trial among female patients (N = 515) participating in community-based substance abuse treatment (National Drug Abuse Treatment Clinical Trials Network protocol CTN-0015). Goodness of fit and the estimates of treatment effect derived from each model were compared. Results found that the ZINB model provided the best fit, yielding a medium-sized effect of intervention.

Conclusions: This article illustrates the consequences of applying models with different distribution assumptions on the data. Taken together, the data suggest the importance for any given data set of finding the most appropriate model for outcome data in order to arrive at the most accurate estimate of the effect of a treatment intervention. If a model used does not closely fit the shape of the data distribution, the estimate of the effect of the intervention may be biased, either over- or underestimating the intervention effect. Investigators designing clinical trials should be encouraged to hypothesize in advance the distribution of the outcome counts based on their knowledge of the population and the intervention being tested, as well as prior data.

Related protocols: CTN-0015

Abstract:

This presentation, which was also given at the National Drug Abuse Treatment Clinical Trials Network (CTN) 10th Anniversary Symposium in April 2010, highlights ten “take home lessons” from the CTN, describing one by one their impact on both research and treatment in the alcohol, tobacco, and other drugs field. The top ten accomplishments include the discovery of: multiple successes in establishing a partnership and building a research infrastructure; the safety of behavioral treatments (adverse event monitoring, e.g.); the power of incentives; the broad utility of the Stage Model; the fact that empirically validated treatments (EVTs) stand up in real world settings; the specific effects of behavioral treatments; the effectiveness of treatment-as-usual; effort, support and commitment as essential components of adopting and sustaining EVTs; the challenges of retention and broadening our scope; and the fact we still have a long way to go.

The presentation ends with a “tentative top ten to tackle in the next ten,” providing some examples of future directions for research in the CTN, including the development of a common outcome measure, ways to better keep clinicians engaged, how to sustain the effects of treatment and training, and more. [Note: Michael Levy, PhD, presented Dr. Carroll’s slides at the NIATx Summit and SAAS National Conference in her absence.]

Abstract:

In November 2008, the CTN Executive Committee approved the formation of an ad hoc task force to address two goals and make a recommendation to the CTN Steering Committee. The first of these goals was to develop a clinically meaningful outcome standard for drug use to be used in CTN clinical trials, as well as a method to capture that outcome. The second goal was to recommend a set of key screening and assessment questionnaires and instruments to be used CTN-wide. This document represents the task force’s recommendations, including discussion of the importance of capturing drug use consequence information as well as information about successful or failed abstinence, examination of the strengths and weaknesses of various screening instruments, and a comparison of the task force’s recommendations with the CTN Common Assessment Battery (CAB).