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Abstract: High levels of missing outcome data for biologically confirmed substance use (BCSU) threaten the validity of substance use disorder (SUD) clinical trials. Underlying attributes of clinical trials could explain BCSU missingness and identify targets for improved trial design. We reviewed 21 clinical trials funded by the NIDA National Drug Abuse Treatment Clinical Trials Network (CTN) and published from 2005 to 2018 that examined pharmacologic and psychosocial interventions for SUD. We used configurational analysis-a Boolean algebra approach that identifies an attribute or combination of attributes predictive of an outcome-to identify trial design features and participant characteristics associated with high levels of BCSU missingness. Associations were identified by configuration complexity, consistency, coverage, and robustness. We limited results using a consistency threshold of 0.75 and summarized model fit using the product of consistency and coverage. For trial design features, the final solution consisted of two pathways: psychosocial treatment as a trial intervention OR larger trial arm size (complexity=2, consistency=0.79, coverage=0.93, robustness score=0.71). For participant characteristics, the final solution consisted of two pathways: interventions targeting individuals with poly- or nonspecific substance use OR younger age (complexity=2, consistency=0.75, coverage=0.86, robustness score=1.00). Conclusions: Psychosocial treatments, larger trial arm size, interventions targeting individuals with poly- or nonspecific substance use, and younger age among trial participants were predictive of missing BCSU data in SUD clinical trials. Interventions to mitigate missing data that focus on these attributes may reduce threats to validity and improve utility of SUD clinical trials. Related protocols: CTN-0002, CTN-0003, CTN-0004, CTN-0006, CTN-0007, CTN-0009. CTN-0013, CTN-0014, CTN-0015, CTN-0017, CTN-0021, CTN-0029, CTN-0030, CTN-0031, CTN-0037, CTN-0044, CTN-0046, CTN-0048, CTN-0051, CTN-0053

Abstract:

The purpose of this study was to estimate obesity prevalence among drug-dependent individuals and to compare prevalence across different types of drug dependence.

1596 opioid- and/or stimulant-dependent participants were extracted from six clinical trials within the National Drug Abuse Treatment Clinical Trials Network of the National Institute on Drug Abuse (NIDA CTN) to estimate obesity prevalence among drug-dependent users. Age-, sex-, and race-matched National Health and Nutrition Examination Survey (NHANES) samples were used as a general population reference. Standardized prevalence ratios (SPRs) were calculated to compare the CTN sample to NHANES as well as to compare within the CTN sample. Logistic regression estimated associations between the type of drug dependence and obesity.

The standardized obesity prevalence among the drug-dependent CTN trial participants was 67% of expected for age-, sex- and race-matched NIHANES participants (SPR = 0.67, 95% CI: 0.60-0.74). Obesity was least prevalent among opioid-dependent-only participants (SPR = 0.36, 95% CI: 0.27-0.46 compared to the NHANES, and SPR = 0.33, 95% CI: 0.23-0.46 compared to the stimulant-dependent-only participants). Compared to stimulant-dependent-only users (p < 0.0001), the odds of obesity were 67% lower among opioid-dependent-only users (adjusted odds ratio [AOR] = 0.33, 95% CI: 0.23-0.46) and 33% lower among opioid and stimulant-co-dependent users (AOR = 0.67, 95%CI: 0.49-0.90) after controlling for age, sex, race, education and employment pattern.

Conclusions: The prevalence of obesity among drug-dependent clinical trial participants was lower than the general population, and lowest among opioid-dependent-only users, suggesting an inverse relationship between obesity prevalence and drug dependence, most notable among opioid-dependent-only users.

Related protocols: CTN-0001, CTN-0002, CTN-0003, CTN-0037, CTN-0046, CTN-0048

Abstract:

The Clinical Opiate Withdrawal Scale (COWS) is used to assess withdrawal in clinical trials and practice. The aims of this study were to examine the inter-item correlations and factor structure of the COWS in opioid-dependent men and women. This is a secondary data analysis of the National Drug Abuse Treatment Clinical Trials Network study CTN-0003, a randomized clinical trial that compared buprenorphine/naloxone tapering strategies. The trial included 11 sites in 10 US cities. Participants were opioid-dependent individuals (n=516) that had data on the COWS. The COWS at study baseline was analyzed in the study. Inter-item correlations showed weak to moderate relationships between the items. A 1-factor model did not fit the data for men, where resting pulse rate was not related to withdrawal for men, and yawning and gooseflesh skin was not related to withdrawal for women. A reduced model comprised of only the 8 items that were significantly related to the construct of withdrawal in both men and women, and an exploratory 2-factor model, were also assessed but not retained due to inconsistencies across gender.

Conclusions: This study failed to find a single model where all items were related to the construct of withdrawal (i.e., statistically significant meaningful factor loadings) for men and women in mild withdrawal. Further research testing the hypothesized factor structure in other opioid-dependent samples, particularly in samples with greater variation in COWS scores and for those in moderate opioid withdrawal, is needed. The COWS was developed to rate severity within each item because that corresponds with clinical severity within the individual on each item; that may not be necessarily the case across items. The composite score simply acknowledges that some individual will show more, or less, withdrawal symptoms within certain physiological systems and may therefore not assess a single construct of withdrawal. Further research testing the hypothesized factor structure in other opioid-dependent samples is needed.

Related protocols: CTN-0003

Abstract:

Using data from National Drug Abuse Treatment Clinical Trials Network protocol CTN-0003, “Suboxone Taper: A Comparison of Taper Schedules,” this study examined predictors of opiate abstinence status 3 months after the end of buprenorphine/naloxone treatment for opioid-dependent participants. Participants (n=516, age > 15 years), received buprenorphine/naloxone treatment for 4 weeks and then were randomly assigned to undergo dose tapering over either 7 or 28 days. Bivariate analysis was performed to identify possible predictors of successful opiate abstinence outcome (p-value < 0.10). Logistic regression analysis with backward stepwise selection was then performed to produce final model containing independent predictors at p-value < 0.05. Bivariate analysis identified several possible predictors, including: opioid and drug urine tests result at the end of taper; employment status, family problems, and alcohol use domains of the Addiction Severity Index (ASI) score; and the Clinical Opiate Withdrawal Scale (COWS) at the end of stabilization. The final predictor list identified by logistic regression included: ASI domains for family and alcohol problems, COWS at the end of stabilization, and opiate urine test at the end of taper.

Conclusions: In this analysis, participants presenting with a negative urine test for opiates at the end of the taper period, more severe alcohol or family problems (contrary to previous studies), or fewer symptoms of opiate withdrawal at the end of stabilization were more likely to have successful opiate abstinence.

Related protocols: CTN-0003

Abstract:

The Adjective Rating Scale for Withdrawal (ARSW) is commonly used to assess opiate withdrawal in clinical practice and research. This study aimed to examine the factor structure of the ARSW, test measurement invariance across gender and treatment groups, and assess longitudinal measurement invariance across the clinical trial. Secondary data analysis of National Drug Abuse Treatment Clinical Trials Network protocol CTN-0003, a randomized clinical trial comparing two tapering strategies for buprenorphine/naloxone, was performed. The ARSW was analyzed at baseline, end of taper, and 1-month follow-up (n=515 opioid-dependent individuals). A 1-factor model of the ARSW fit the data and demonstrated acceptable reliability. Measurement invariance was supported across gender and taper groups. Longitudinal measurement invariance was not found across the course of the trial, with baseline assessment contributing to the lack of invariance.

Conclusions: The ARSW appears to be measuring withdrawal equivalently across gender and buprenorphine/naloxone taper periods in opioid-dependent individuals. The authors recommend that researchers and clinicians using this tool analyze ARSW total scores across groups at each time point separately. If changeover time is of interest, change from post-treatment through follow-up may offer the most valid comparison; pre-treatment ARSW values may not be assessing withdrawal in the same way as post-treatment and follow-up values. Future research is needed to replicate these findings in other trials, in various clinical settings, and across other demographic groups in order to fully assess the measurement properties of the ARSW.

Related protocols: CTN-0003

 

Abstract:

A review of substance use clinical trials indicates that sub-optimal methods are the most commonly used procedures to deal with longitudinal missing information. In this study of data from the National Drug Abuse Treatment Clinical Trials Network buprenorphine protocol CTN-0003, listwise deletion (i.e., using complete cases only), positive urine analysis (UA) imputation, and multiple imputation (MI) were used to evaluate the effect of baseline substance use and buprenorphine/naloxone tapering schedule (7 or 28 days) on the probability of a positive UA (UA+) across the 4-week treatment period. The listwise deletion generalized estimating equations (GEE) model demonstrated that those in the 28-day taper group were less likely to submit a UA+ for opioids during the treatment period, as did the positive UA imputation model. The MI model also demonstrated a similar effect of taper group, but the effect size was more similar to that of the listwise deletion model.

Conclusions: The missing data situation described in this investigation generalizes to many other substance use psychopharmacology clinical trials wherein there is missing data on the outcome of interest only. Future researchers may find utilization of the MI procedure in conjunction with the common method of GEE analysis as a helpful analytic approach when the missing at random assumption is justifiable.

Related protocols: CTN-0003

Abstract:

Dependence on prescription opioids (PO) is a growing problem. Although most research with buprenorphine has focused on heroin-dependent populations, the authors hypothesize that individuals dependent on PO display characteristics that may predict different outcomes in treatment, particularly in short-term taper procedures in which comorbidities such as pain conditions may complicate taper. This secondary analysis of data from National Drug Abuse Treatment Clinical Trials Network protocol CTN-0003 (Suboxone Taper: A Comparison of Taper Schedules) examined differences in outcomes between PO users (n=90) and heroin users (n=426) after a buprenorphine taper. After a 4-week buprenorphine induction/stabilization phase, 516 opioid-dependent individuals were randomized into 1 of 2 taper lengths (7 vs 28 days) to assess the association between taper length and outcome. The primary outcome was measured by urine drug test for opioids at the end of the taper period. Craving, withdrawal, and buprenorphine dose were also examined. After controlling for baseline demographic and drug use differences between the opioid use groups, results indicate that a higher percentage of the PO group (49%) provided an opioid-free urine drug specimen at the end of taper compared with the heroin group (36%; [chi]21 = 6.592, P < 0.010).

Conclusions: Although buprenorphine taper is not recommended as a stand-alone treatment, there are clinical scenarios where it may be required to taper a patient off buprenorphine, making the findings of this study an important addition to the evidence base in the management of PO dependence with buprenorphine. Results of this secondary analysis additionally confirm the main study’s findings that there seems to be no benefit in prolonging the taper period for PO users beyond 7 days. Should a taper be indicated for a medical reason (for example, for opioid rotation for pain management, or to commence and extended-release naltrexone injection), a 7-day taper seems to be an appropriate schedule. Further studies are required to examine longer-term treatment outcomes.

Related protocols: CTN-0003

Abstract:

Using buprenorphine as a medication to treat opioid dependence is becoming more prevalent as illicit opiate use increases. Identifying the characteristics of opiate dependent individuals best suited to benefit from buprenorphine would improve guidelines for its administration. This ancillary investigation of data from National Drug Abuse Treatment Clinical Trials Network (CTN) protocol CTN-0003 (“Suboxone (Buprenorphine/Naloxone) Taper : A Comparison of Taper Schedules”) evaluates baseline and treatment participation variables for predicting positive response to short-term stabilization with buprenorphine. Data include demographic, drug use, and other variables collected from participants undergoing stabilization over a 4-week period before being tapered off buprenorphine in a short-term detoxification process as part of CTN-0003. Outcome variables include opioid use and retention. Several characteristics were associated with opioid use at the end of the stabilization period, including age, criminal history, and previous opioid use. In particular, criminal activity and opioid use in the last 30 days were significantly associated with shorter treatment stays.

Conclusions: The findings from this study have important clinical applications for treatment providers, specifically providing information for those who offer buprenorphine treatment to opiate-dependent patients. Treatment providers and private practice clinicians may find it useful to know that positive outcomes may be likely when using buprenorphine for short-term treatment in some patients. For example, these findings show that those with more severe withdrawal symptoms at baseline do not experience higher levels of drop out or continued opiate use. Conversely, these findings have identified those for whom this short-term treatment with buprenorphine may not be successful such as those who use opioids more often, have a previous treatment experience, and have a criminal justice history. These findings support previous study results demonstrating that those with more severe drug use and less social stability are less likely to have positive treatment outcomes.

Related protocols: CTN-0003

Abstract:

Substance abuse treatment research is often characterized by having a non-trivial amount of missing data, especially in longitudinal, randomized clinical trials. A review of substance abuse clinical trials indicates that listwise deletion and single imputation (i.e., imputing missing values with a positive urine analysis) are the most commonly used procedures to deal with missing information. Due to the prevalence and complex nature of missing data in substance abuse research, the best missing data procedures need to be employed and tailored to each unique missing data situation so as to maximize the likelihood of arriving at the most accurate conclusions. This poster reports on a study that compared the outcomes from two common missing data handling procedures, using data sets from protocol CTN-0003, with the outcomes from the multiple imputation (MI) procedure in the context of generalized estimating equations (GEE) in order to demonstrate that interpretations of treatment effectiveness and other baseline covariate effects can change as a function of how the missing information is handled.

Conclusions: The investigation demonstrated how treatment efficacy can vary as a function of how the missing information is treated when there is a significant amount of it. Missing data theory suggests that listwise deletion and single imputation procedures should not be used to account for missing information, and that MI has advantages with respect to internal and external validity when the assumption of missing at random can be reasonably supported. Future researchers may find utilization of the MI procedure in conjunction with the common method of GEE analysis as a helpful analytic approach compared to commonly used procedures when the missing at random assumption is justifiable.

Related protocols: CTN-0003

Abstract:

Because the analysis of a treatment’s efficacy can vary as a function of how the missing data in a substance abuse clinical trial is handled analytically, there is a potential problem of not thoroughly evaluating and reporting the mechanism of missing information as part of the analytic strategy. Appropriate decision-making regarding how the missing data is handled is critical in order to make sound clinical inference based on randomized trials of substance abuse treatment, but missing not at random (MNAR) methodologies have no been explored in this context with real data. This investigation uses data from protocol CTN-0003 to compare 3 different modeling strategies for the handling of missing values (i.e., missing at random (MAR) model versus 2 different missing not at random (MNAR) models; Diggle-Kenward and Wu-Carroll selection modeling), to determine whether the treatment effect (i.e., impact of trial arm on linear urine analysis (UA) slope) is dependent on the missing data strategy used.

Conclusions: The trial arm effect on the UA slope (i.e., UA change over time), and other covariate effects, changed in a meaningful way across the MAR and MNAR growth models, indicating that missing data assumptions are critical to understand and explain in clinical trials. It is not only important for the research team to consider what the most likely missing data assumption is (i.e., MAR or MNAR), but also to consider whether or not the additional assumptions associated with each MNAR and MAR model are reasonable. This investigation highlights the potential for these modern approaches to missing data to shed new light on outcomes of interest (e.g., time-specific dropout) other than the primary outcome of UA.

Related protocols: CTN-0003

Abstract:

Two common procedures for the treatment of missing information, listwise deletion and positive urine analysis (UA) imputation (e.g., if the participant fails to provide urine for analysis, then score the UA positive), may result in significant biases during the interpretation of treatment effects. To compare these approaches and to offer a possible alternative, these two procedures were compared to the multiple imputation (MI) procedure with publicly available data from a recent clinical trial (National Drug Abuse Treatment Clinical Trials Network protocol CTN-0003, Ling et al, 2009). Listwise deletion, single imputation (i.e., positive UA imputation), and MI missing data procedures were used to comparatively examine the effect of the protocol’s two different buprenorphine/naloxone tapering schedules (7- or 28-days) for opioid addiction on the likelihood of a positive UA. The listwise deletion of missing data resulted in a nonsignificant effect for the taper while the positive UA imputation procedure resulted in a significant effects, replicating the original findings by Ling et al (2009). Although the MI procedure also resulted in a significant effect, the effect size was meaningfully smaller and the standard errors meaningfully larger when compared to the positive UA procedure. This study demonstrates that the researcher can obtain markedly different results depending on how the missing data are handled. Missing data theory suggests that listwise deletion and single imputation procedures should not be used to account for missing information, and that MI has advantages with respect to internal and external validity when the assumption of missing at random can be reasonably supported. Consistent with previous investigation of missing data in substance abuse treatment, the authors encourage researchers to understand and report the missing data mechanism as well as use newer procedures for the treatment of missing information (i.e., MI or direct maximum likelihood procedures) that are based on a research-specified “best estimate” of the missing values.

Related protocols: CTN-0003

Abstract:

This CTN ancillary investigation aimed to address an urgent need for screening of substance use problems in medical settings by examining substance-specific dependence criteria as potential brief screeners for the detection of patients with a substance use disorder (SUD). Researchers examined data from intake assessments of substance use disorders completed by 920 opioid dependent adults from outpatient treatment settings at 11 programs in 10 U.S. cities (part of protocol CTN-0003, which investigated taper schedules for buprenorphine/naloxone dosing). Data were analyzed by factor analysis, item response theory (IRT), sensitivity, and specificity procedures. Across all substances (alcohol, amphetamines, cannabis, cocaine, sedatives), “withdrawal” was among the least prevalent symptoms, while “taking large amounts” and “inability to cut down” were among the more prevalent. Items closely related to the latent trait of a substance use disorder showed good-to-high values of area under the receiver operating characteristic curve in identifying cases of SUD; IRT-defined severe and less discriminative items exhibited low sensitivity in identifying cases of SUD (“withdrawal” for all substances; “time using” for alcohol and sedatives; “giving up activities” for sedatives).

Conclusions: Study results suggest that “withdrawal” and “time using” are much less reliable indicators for a substance use disorder than “taking larger amounts than intended” and “inability to cut down,” and that the latter two items should be studied further for consideration in developing a simplified tool for screening patients for SUD in medical settings. These findings have implications for the use of common health indicators in electronic health records systems to improve patient care. This study also demonstrates the unique value of IRT analysis in determining the underlying trait of a set of measures and elucidating item-level psychometric information to help interpret results of sensitivity and specificity; researchers should consider incorporating IRT approaches into their analysis plans to support the psychometric quality of patient-reported items.

Supported by the Duke Clinical Research Institute (CTN DSC 1).

Related protocols: CTN-0003

Abstract:

Clinical parameters for determining buprenorphine dose have not been adequately examined in treatment outcome research. This study is a secondary analysis of data collected from National Drug Abuse Treatment Clinical Trials Network (CTN) protocol CTN-0003, a recently completed comparison of buprenorphine taper schedules designed to assess whether participant baseline characteristics are associated with buprenorphine dose. For this ancillary investigation, 516 participants were categorized by dose provided in the final dosing week after 3 weeks of flexible dosing (9.3% received a final week dose of 8 mg buprenorphine, 27.3% received 16 mg, and 63.4% received 24 mg). Findings show that final week dose groups differed in baseline demographic and drug use characteristics including education, heroin use, route of drug administration, withdrawal symptoms, and craving. These groups also differed in opioid use during the four dosing weeks, with the lowest use in the 8 mg group and highest use in the 24 mg group (p < .0001). A significant association was also found between final week dose group and withdrawal and craving. Participants with greater withdrawal symptoms and craving scores had larger final week doses.

Conclusions: Final week dose groups in this investigation differed in demographic and drug use characteristics, and the group receiving the largest final week dose had the highest rate of continued opioid use. These findings may contribute to the development of clinical guidelines regarding buprenorphine dose in the treatment of opioid dependence; however, further investigations that include random assignment to dose by baseline characteristics are needed. Methods for determining optimal buprenorphine dose will be extremely helpful in clinical settings in which physicians currently have no formal tools for determining appropriate dosages.

Related protocols: CTN-0003

Abstract:

In response to the rising rate of treatment admissions related to illicit use of amphetamines (e.g., methamphetamine), this ancillary investigation examined the prevalence of amphetamine use among treatment-seeking, opioid-dependent adults, explored whether amphetamine users were as likely as non-amphetamine users to enroll in opioid-dependence treatment trials, and determined whether amphetamine users manifested greater levels of medical and psychiatric comorbidity than nonusers. The sample included 1257 opioid-dependent adults screened for participation in three multisite studies of the National Drug Abuse Treatment Clinical Trials Network (protocols CTN-0001, -0002, and -0003), which studied the effectiveness of buprenorphine for opioid detoxification under varying treatment conditions. Five mutually exclusive groups were examined, i.e., nonusers, current amphetamine injectors, current amphetamine non-injectors, former amphetamine injectors, and former amphetamine non-injectors Of the sample, 22.3% had a history of regular amphetamine use; of those users, 30.3% reported injection as their primary route. Amphetamine users were as likely as nonusers to enroll in treatment trials. Bivariate analyses indicated elevated rates of psychiatric problems (depression, anxiety, etc.) and medical illnesses (dermatological, hepatic, etc.) among amphetamine users. After adjusting for demographic variables and lifetime use of other substances: current amphetamine users and former injectors showed an increased likelihood of having medical illnesses and hospitalizations; current injectors had elevated odds of suicidal thoughts or attempts; current non-injectors had exhibited elevated odds of anxiety, cognitive impairment, and violent behaviors; and former non-injectors had increased odds of depression.

Conclusions: Treatment-seeking, amphetamine-using, opioid-dependent adults manifest greater levels of medical and psychiatric morbidity than treatment-seeking, opioid-dependent adults who have not used amphetamines, indicating a greater need for intensive clinical management.

Supported by the Duke Clinical Research Institute (CTN DSC 1).

Abstract:

Accumulating evidence indicates important gender differences in substance use disorders. Little is known, however, about gender differences and opioid use disorders. This study aimed to compared demographic characteristics, substance use severity, and other associated areas of functioning (as measured by the Addiction Severity Index-Lite (ASI-Lite)) among opioid-dependent men and women participating in a multisite effectiveness trial. Participants were 892 adults screened for the National Drug Abuse Treatment Clinical Trials Network (CTN) investigation of the effectiveness of two buprenorphine tapering schedules (protocol CTN-0003). The majority of men and women tested positive for oxycodone (68% and 65%, respectively) and morphine (89% each). More women than men tested positive for amphetamines (4% vs. 1%, p < .01), methamphetamine (11% vs. 4%, p < .01), and phencyclidine (8% vs. 4%, p = .02). More men than women tested positive for methadone (11% vs. 6%, p = .05) and marijuana (22% vs. 15%, p = .03). Craving for opioids was significantly higher among women (p < .01). Men evidenced higher alcohol (p < .01) and legal (p = .04) ASI composite scores, whereas women had higher drug (p < .01), employment (p < .01), family (p < .01), medical (p < .01), and psychiatric (p < .01) ASI composite scores. Women endorsed significantly more current and past medical problems.

Conclusions: Important gender differences in the clinical profiles of opioid-dependent individuals were observed with regard to substance use severity, craving, medical conditions, and impairment in associated areas of functioning. The findings enhance understanding of the characteristics of treatment-seeking men and women with opioid dependence, and may be useful in improving identification, prevention, and treatment efforts for this challenging and growing population.

Related protocols: CTN-0003