This paper reports predictors, mediators and moderators of treatment success for buprenorphine-naloxone versus clonidine for medically supervised opioid withdrawal in either the inpatient or outpatient setting. Identification of factors that predict relapse and treatment success during acute withdrawal illuminates the early recovery process and may help inform clinical recommendations for a difficult to treat population.
As expected, medication type (buprenorphine-naloxone versus clonidine) was the strongest predictor of treatment success. The ability of buprenorphine-naloxone to reduce symptoms and retain subjects in the early phase of treatment may be a critical factor in understanding the better outcomes compared to clonidine (only a 12% drop out by day four of treatment with buprenorphine-naloxone versus 69.1% with clonidine). This paper expands on this finding by examining moderators and mediators of this important primary outcome, including the interactive role of level of care, severity of withdrawal symptoms, and other secondary predictors.
Level of care (inpatient versus outpatient) was both a strong predictor of treatment success and a moderator of medication treatment outcomes. This finding has important potential policy implications and requires additional study. Overall subjects in inpatient treatment were seven times more likely to have treatment success than those in outpatient treatment. Surprisingly the level of care differences for treatment retention were relatively small (56.6% inpatient versus 45.5% outpatient, p = .051), and most of the enhanced treatment success was secondary to enhancing abstinence rates. Because of the expense of inpatient treatment, level of care is important in evaluating treatment efficacy and cost effectiveness. Based on our findings, inpatient care may be more appropriate if a clinical program is limited to providing only clonidine medication (perhaps due to staff prescribing limitations, formulary restrictions, or the higher cost of buprenorphine-naloxone). If a program is able to offer buprenorphine-naloxone medication, then treatment outcomes will likely be better for those receiving inpatient treatment versus outpatient. Based on our finding that outpatient buprenorphine-naloxone is similar in outcomes to inpatient clonidine, buprenorphine-naloxone would be the preferred medication option if outpatient treatment is the only level of care available.
The third primary hypothesis, that participants with more severe baseline withdrawal symptoms, regardless of medication condition, would drop out of treatment and have worse outcomes compared to participants with lower levels of withdrawal, was not supported except among outpatients receiving clonidine. This finding is consistent with the Rounsaville et al., 1985
findings in an outpatient study that participants with more severe withdrawal who received clonidine (or methadone) had worse clinical outcomes in opioid dependence treatment than those with less severe withdrawal. Another prior study did not find that intensity of withdrawal predicted early drop-out from treatment (Scherbaum et al., 2004
). Unexpectedly, subjects on buprenorphine-naloxone with higher baseline opioid withdrawal symptoms had better treatment success than those with lower severity withdrawal symptoms. A speculative explanation is that the low severity withdrawal patients on buprenorphine-naloxone may not have needed 13 days of opioid detoxification, and dropped out because they were improving.
Future medical withdrawal treatment studies might focus on the first few days of opioid withdrawal and examine higher dosages of buprenorphine-naloxone or clonidine, especially for patients with high severity withdrawal symptoms. Of note, any decision to evaluate higher doses of medication would have to consider safety issues and risks of additional side effects. Interestingly, there were differences between the two opioid withdrawal severity instruments (COWS versus ARSW). The COWS predicted differences in outcome based on severity, while the ARSW, a self-report measure, did not. This finding suggests that patient self-report alone may not be as useful a measure for evaluating withdrawal symptom severity compared to clinician rated instrument assessments.
In regards to the mediational model proposed, the reduction in significance of path C was modest, rather than robust, which suggests a limitation of the proposed model of medication type to affect opioid withdrawal (path a), opioid withdrawal to affect treatment response (path b), and medication type to affect treatment response (path c). There is a need for additional exploration of this model in future studies with larger sample sizes.
Consistent with previous research, most demographic and baseline characteristics failed to predict treatment outcome (San et al., 1989
; Armenia et al., 1999
). Previous inpatient and outpatient studies evaluated clonidine (not buprenorphine-naloxone) and were not in different settings (only inpatient or outpatient). Findings across studies have not been consistent (Gossup, 1988
; Endicott & Watson, 1994
; Morral et al., 1997
; Franken and Hendriks, 1999
; Backmund et al., 2001
; Ghodse et al., 2002
; Scherbaum et al., 2004
). Significant predictors of failure have included younger age, (Jeremiah et al., 1995
; Armenia et al., 1999
; Backmund et al., 2001
) being single, (Perez de los Cobos et al., 1997
; Armenia et al., 1999
) having more severe drug problems, (Franken and Hendriks, 1999
) and having less education and not being on probation (Backmund et al., 2001
). In our study no clearly significant demographic predictors emerged.
Multiple substance use was common in this study as with many other studies of heroin dependence (Oliveto et al., 1994
; Perez de los Cobos et al., 1997
; SAMHSA NSDUH 2004
). Concurrent alcohol, cocaine, or marijuana use was not predictive of worse clinical outcomes. Interestingly tobacco use was associated with worse opioid treatment outcomes. Daily smoking may be a marker for worse addiction severity (Krejci et al., 2003
) and/or tobacco use may increase other substance craving (Taylor et al., 2000
; Frosch et al., 2002
) and worsen withdrawal symptoms. Changes in smoking status can affect the metabolism of some medications (those metabolized through the P450 1A2 isoenzyme); however this issue was unlikely to be a factor in this study since smoking cessation was not an effort of this protocol.
Concurrent tobacco use is not a factor reported in previous predictor studies for medications in opioid withdrawal and is often ignored in addiction treatment settings; however other studies have reported tobacco use as a trigger for other substance relapse, including smokers who are opiate addicts have a harder time maintaining abstinence than non-smokers (Frosch et al., 2000) There is a need to better understand the impact of tobacco use/dependence on opioid withdrawal and longer-term outcomes.
Severe baseline anxiety symptoms doubled treatment success in this study. The literature suggests that depression and anxiety is common in addiction treatment populations and tends to be associated with worse treatment outcome; however this literature is complicated and differences vary by current versus past symptoms versus disorders (APA 2006
; Arujo et al 1996). One explanation of the current data is that subjects with severe anxiety symptoms might have felt relief for their anxiety symptoms from the study medications (buprenorphine-naloxone, clonidine or ancillary medications); however longer outcomes and ongoing monitoring of these symptoms might help better understand the possible explanations of these findings. There is a need for more studies of buprenorphine-naloxone outcomes with patients with psychiatric symptoms and disorders.
While a major strength of this study is being a multi-site randomized clinical trial with a fairly large sample size, the study had limitations. The diversity of treatment sites adds to the external validity of the findings, but reduces the internal validity. While the sample size is appropriate for the analyses described in this report, the sample sizes from the individual sites are inadequate to evaluate differences between sites. In regards to comparing outcomes by level of care, both setting used the same protocol, however, subjects were not randomized by level of care, but were either self-selected or clinically-selected. The low retention rate for clonidine subjects precluded making a comparison with buprenorphine-naloxone subjects who received a full course of treatment. Other weaknesses include the fact that this was an open-label study where the subjects knew the medication they were receiving and this introduces bias on both the subject’s expectations about the medication and potentially the observers’ ratings of withdrawal. Another limitation was that treatment setting (inpatient or outpatient) was not randomized and some of the subjects changed treatment setting status during the study. Another potential limitation is the definition of “treatment success” including the two components of being “present” to complete the study medication on day 13 and “absent” of opioids on the urine toxicology assessment on the last day of research clinic attendance (day 13 or 14). Although grounded in clinical experience, being somewhat conservative, and selected by a group of experts in this topic; another choice of definition could have resulted in different findings and conclusions.
In the future, other potential predictors of treatment outcomes may be considered during the design of randomized clinical trials, including genotype markers, personality disorder traits, neuropsychological testing, and brain imaging differences. Future studies should consider other methods for assessing causal mechanisms that include biological, psychological, and social variables.
In addition, we appreciate that future studies must focus on the long-term outcomes of individuals after the detoxification time period. Ultimately, the most important clinical outcomes will be long-term and detoxification is only one of the key beginning phases of treatment, including the prior engagement into treatment phase and the next management of protracted withdrawal phase. However, the findings from this study do suggest robust differences based on medication type and level of care.
In summary, medication was the best predictor of treatment outcome for opiate detoxification regardless of treatment setting, and inpatient treatment was a strong predictor of treatment success and a moderator of medication outcomes. Reduction in opioid withdrawal severity from baseline to day three was a moderating factor in treatment outcomes. Those who did the best with clonidine had low severity withdrawal symptoms at baseline. The apparent demand for ambulatory medical withdrawal services supports the need for additional research aimed at identifying patients and/or approaches that might be best suited for this treatment approach (Westreich et al., 1997
; Broers et al., 2000
). There is limited research to guide clinicians; however this study provides some additional information from community based treatment programs.