Pharmacologcial Treatments for Methamphetamine Use Disorder

Abstract

Background: Methamphetamine use disorder is a persistent and prevalent illness associated with serious physical, emotional, cognitive and social harms. No proven pharmacological treatments have yet been identified and psychological therapies are currently the only evidence based treatments. A recent systematic review and meta-analysis found no quantitative evidence of benefit for psychostimulants in achieving abstinence or retention in treatment, but that review was limited to specific pharmacological agents (Bhatt et al, 2016). An older systematic review examined all treatments and found no single agent that demonstrated consistent efficacy

(Brackins et al, 2011). Many additional studies have since been published. The aim of this systematic review is to critically evaluate the literature not previously covered by these and examine the evidence for efficacy of all possible pharmacological treatments.

Methods: The literature search strategy consisted of an electronic search of PubMed. I included randomized controlled trials not previously reviewed of any pharmacological treatment for methamphetamine use disorder that reported methamphetamine use by urine drug screen as an outcome. I abstracted data from all identified studies using a standardized data collection instrument and critically analyzed the risk of bias, internal validity and external validity of all studies using a standardized form. I synthesized the review data.

Results: I identified and analyzed 11 studies not previously reviewed. Pharmacological treatments used in these studies included buprenorphine, N-acetyl-cysteine, aripiprazole, citocoline, topiramate, naltrexone, mirtazapine, and a combined regimen of flumazenil/gabapentin/hydroxyzine. No study was found to have both good internal and good external validity. The overall level of internal validity within studies was severely limited by

i small study size and high numbers of drop outs. Comparison between studies was often not possible due to inconsistently measured, defined and reported outcome measures.

Conclusions: Several studies reported positive results, but were limited by poor internal or external validity and no evidence was found to support treatment of methamphetamine use disorder with a specific medication in the general outpatient population. There is a pressing need for more research in this field. Future trials should use consistent outcome measures and address possible challenges to statistical power caused by high attrition.

Bhatt M, Zielinski L, Baker-Beal L, et al. Efficacy and safety of psychostimulants for

amphetamine and methamphetamine use disorders: a systematic review and meta-analysis.

Syst Rev. 2016;5(1):189. doi:10.1186/s13643-016-0370-x.

Brackins T, Brahm NC, Kissack JC. Treatments for methamphetamine abuse: a literature

review for the clinician. J Pharm Pract. 2011;24(6):541-550.

doi:10.1177/0897190011426557.

Introduction

Methamphetamine use is a persistent and prevalent illness worldwide associated with serious physical, emotional, cognitive and social harms. Taken together, methamphetamine and amphetamine type stimulants have become the most popular psychostimulants in the world, with

24 million users worldwide.1Although the use of amphetamines other than methamphetamine is on the rise, methamphetamine still accounted for 71% of all seizures of amphetamine type stimulants in 2011.1 In the US in 2014, 1.6 million people used a stimulant drug for non-medical purposes, 569,000 of whom were current methamphetamine users, representing 0.2% of the total population. These numbers were similar to those from 2002-2013.2

Amphetamine was first synthesized from the Chinese herb Ma Huang in the early 19th century.1

Illegal methamphetamine recreational use first appeared in the United States in the 1930’s. 3

Methamphetamine and other related amphetamines were actually prescribed by physicians in the

US up until the 1960’s for weight loss and depression.4 An illegal powder form known variously as “crank” or “meth” or “crystal” became available in the 1980’s when there was surge in methamphetamine use in the US. Then, in 1988, a form of methamphetamine that could be smoked known as “ice” or “glass” was identified first in Hawaii and then spread to the rest of the

US.5

Methamphetamine use is associated with many medical problems such as infectious disease including HIV, cardiovascular and pulmonary disease, anxiety, depression, psychosis and impaired cognition. It is also associated with an increased risk of mortality, primarily from HIV, cardiovascular disease, or overdose.6 Amphetamine dependence has been calculated to account for 2.6 million DALYs worldwide.

The mainstay of treatment for methamphetamine abuse remains psychological treatments, which have been supported by numerous trials and systematic reviews.8 All psychosocial treatments have shown efficacy, with contingency management having the strongest evidence.9

An effective pharmacological treatment for methamphetamine abuse to complement physical treatments could potentially play a major role in reducing the harms associated with the abuse.

The possibility of an effective pharmacological treatment has been suggested by advances in the understanding of the neurochemical pathways associated with its use, as well as the experience of effective pharmacological treatments for opioid and alcohol abuse.

While pharmacological treatment options are widely available for both opioid and alcohol abuse, the general consensus among primary care physicians and those who specialize in addiction treatment is that no pharmacological treatments have been shown to be effective treatments of methamphetamine abuse in research of good quality.

Three basic approaches for a pharmacological treatment of methamphetamine use can be postulated: (1) Agonist therapy, in which a medication replaces the effects of methamphetamine as methadone does for opioid dependence; (2) Antagonist therapy, in which the medication blocks the effects of methamphetamine in the same way naltrexone does for opioid dependence; and (3) Symptomatic treatments that attempt to ameliorate the negative effects of use or withdrawal.10

To my knowledge, 4 systematic reviews of treatments for methamphetamine abuse have been published in addition to several non-systematic narrative reviews. The most recent and well- conducted was a Cochrane review and meta-analysis published in November 2016 that updated a similar previous review published in 2011, both of which examined the efficacy of

psychostimulant, or agonist, treatments.11,12 Another systematic review published in 2004 similarly reviewed only agonist treatments for methamphetamine abuse.10 A systematic review published by Shoptaw et all in 2009 examined only treatments for methamphetamine withdrawal.13 Only one other systematic review published in 2011 reviewed all possible pharmacological treatments for methamphetamine abuse.14 While agonist treatment is a promising avenue for treatment of methamphetamine abuse, antagonist treatments and symptomatic treatments may also be a useful addition to the pharmacological armamentarium.

The most recent systematic review and meta-analysis by Bhatt et al found no quantitative evidence of benefit for psychostimulants in achieving abstinence or retention in treatment, but this review was limited to specific pharmacological agents.11 An older systematic review by

Brackins et al examined all treatments and found no single agent that demonstrated consistent efficacy.15 Many additional studies have been published since that comprehensive review in

2012, as evidenced by the updated findings in the meta-analysis of psychostimulant treatments.11

The aim of this systematic review is to critically evaluate the literature not previously covered by these and examine the evidence for efficacy of all possible pharmacological treatments. The key question for this review was:

What is the evidence in randomized placebo controlled trials for a pharmacological treatment of methamphetamine use disorder in the general outpatient US population to reduce methamphetamine use?

Methods

Where applicable, I have reported the methods and results of this systematic review in accordance with the PRISMA guidelines.16 I do not report on elements pertaining to a meta- analysis. I did not register a study protocol. I formulated the search strategy and analysis methods prior to beginning the process of study inclusion/exclusion and data extraction. In the original design of the study a secondary objective and analysis method was to review preclinical studies in addition to RCT’s and to correlate between the findings of preclinical studies and clinical studies in order to guide future selection of candidate therapies. However, after initial title and abstract review, due to the number of identified preclinical studies and time constraints,

I narrowed the scope of the study to clinical RCTs only.

Data Sources and Searches

To identify articles for review, I searched PubMed from inception to November 29, 2016. The search was limited to studies of human subjects and English language articles. The various iterations of the search strategy are outlined in Table 1.

The final formal algorithm for searching MEDLINE was (("methamphetamine"[MeSH Terms]

OR "methamphetamine"[All Fields]) OR ("dextroamphetamine"[MeSH Terms] OR

"dextroamphetamine"[All Fields] OR "amphetamines"[MeSH Terms] OR "amphetamines"[All

Fields] OR "amphetamine"[All Fields] OR "amphetamine"[MeSH Terms])) AND ("abuse"[All

Fields] OR "dependence"[All Fields] OR "use"[All Fields] OR "disorder"[All fields] OR

"Substance-Related Disorders"[MeSH Terms]) AND (("therapy"[Subheading] OR "therapy"[All

Fields] OR "treatment"[All Fields] OR "therapeutics"[MeSH Terms] OR "therapeutics"[All

Fields] OR "medication"[All Fields]) OR "amphetamine-related disorders/drug therapy"[MAJR])

AND "humans"[MeSH Terms] AND English[lang] AND "adult"[MeSH Terms].

Eligibility Criteria and Study Selection

I screened all titles and abstracts identified by the search and selected articles for further eligibility review. In order to capture all relevant studies including preclinical studies, I selected at screening all articles with titles or abstracts that reported results of a study examining the effect of a pharmacological treatment in the setting of methamphetamine use. In cases where there was doubt, I selected the article for review. I imported the citations of all selected articles into Papers for Mac Version 3.3.1 and downloaded the full PDF of each article.

In the eligibility review I examined articles in their entirety and excluded articles from the main analysis according to the algorithm presented in Figure 1. Exclusion criteria included previously reviewed studies (specifically, studies included in the review by Brackins et al or the systematic review of agonist treatment by Bhatt et al11,15), studies that included populations without methamphetamine use (i.e. studies that included populations with cocaine use but not methamphetamine use), studies that included participants younger than 18 years old, studies that only examined the effects of behavioral therapies, non-randomized studies, un-controlled studies, articles that were reports, commentaries, or re-analyses of other identified articles, or studies that did not include reduction in methamphetamine use as an outcome measure. I also excluded preclinical studies that examined cognitive, behavioral, or symptom effects after laboratory based administration of medications. Because of the change in DSM criteria during the years of articles reviewed, I included studies using any diagnostic criteria for methamphetamine abuse, use or dependence. Because methamphetamine use disorder is often a comorbid disorder with other drug and psychological conditions, I included studies irrespective of additional diagnoses. I included studies of any duration. By design of the search strategy, I excluded non-English language articles.

Is the study intervention an agonist treatment? Yes Agonist treatment

Has this study been previously reviewed? Yes Previously reviewed

Is this a preclinical study? Yes Preclinical study

Does this study report only on behavioral treatments? Yes Wrong intervention

Are there participants who don’t use amphetamines? Yes Wrong population

Does this study include participants younger than 18? Yes Wrong age

Does this study measure amphetamine use? No Wrong outcome

Is this a randomized controlled trial? No Non-RCT

Is this original research? No Duplicate

Figure 1: Eligibility Criteria

Data Collection Process and Assessment of Risk of Bias

I abstracted data from each study using a data extraction chart in Microsoft Excel I adapted from the reported methods of Castell et al in their systematic review of treatments for cocaine dependence.17 I did not contact authors of articles to obtain missing data or confirm published data. Data extracted from each study include:

• Study description and funding: study author, year, conflicts of interest, funding source

• Methods: sequence generation, allocation concealment, blinding of

patients/clinicians/therapists/assessors, single or multiple site, study duration, number of

participants handling of dropouts, instruments used

• Participants: source population, inclusion criteria, exclusion criteria, sex, age, ethnicity,

employment status, frequency of methamphetamine use, years of methamphetamine use,

route, comorbid drug disorders, comorbid psychiatric disorders

• Intervention and control: drug, dose, control type, adherence, adjunct interventions

• Outcomes: methamphetamine use by urine drug screen (UDS), retention in treatment,

methamphetamine craving, self-reported use, number who finished study, reason for drop

outs, CGI score, psychotic symptoms, anxiety severity, depression severity, cocaine use

by UDS, opiate use by UDS, number dropped out due to adverse events, number who had

serious adverse events

For this review, the primary outcome measure of interest was reduction in methamphetamine use as measured by urine drug screens. Secondary outcome measures of interest included retention in treatment and methamphetamine craving.

I assessed the internal and external validity of each included study using a standard chart in

Microsoft Excel that included 9 items for internal validity, a single summary judgement of internal validity and an overall judgement for external validity. I adapted the criteria for items 1-

9 from a recent Cochrane review of treatment for cocaine which was itself based on the recommendations in the Cochrane Handbook.17,18 I chose this method of analysis because of its standardized form, previous use, and for ease of comparability with the systematic reviews of agonist treatments by Bhatt et al and Perez-Mana et al who used the same method.11,19 The

criteria for the assessment of the risk of bias for items 1-9 are presented in Appendix A and are taken from the Cochrane Handbook.18

I added to the assessment of risk of bias a summary item (number 10) on the overall internal validity of each study rated as good, fair or poor. This was my own judgement based on the likely magnitude and direction of the risks of bias identified in items 1-9. A judgement of poor internal validity is meant to indicate that there is a high likelihood that the results have been significantly affected by some form of bias to the point of altering the conclusion of the study. A judgement of fair internal validity is meant to indicate that two or more significant sources of bias were identified but that the likelihood of changing the conclusion of the study was small. A judgement of good internal validity is meant to indicate that only one or no significant source of bias was identified, and any bias was unlikely to change the conclusion of the study.

Finally, I included a single judgement of good, fair or poor on the external validity of the results as applied to the general outpatient population in the USA who suffer from methamphetamine use disorder. A judgement of poor external validity is meant to indicate that the results cannot be applied. A judgement of fair external validity is meant to indicate that the results may be applicable, but that there were significant differences in the source population compared to the general population. A judgment of good external validity was given when the results were felt to be directly applicable.

Data Synthesis and Analysis

Because of the expected heterogeneity of pharmacological treatments, I did not plan on conducting any meta-analyses or computational combination of results identified. Instead, I compared the results of studies directly based on the strength of the findings and the internal and

external validity of each study. I also looked for trends in the risks of bias in the identified studies to help guide future research.

Results

Table 1: Iterations of Search Strategy Search Search Term Results 1 “methamphetamine”[All Fields] 11291 2 “methamphetamine”[MeSH Terms] 8124 3 “dextroamphetamine”[All Fields] 6971 4 “dextroamphetamine”[MeSH Terms] 6806 5 “amphetamine”[All Fields] 26997 6 “amphetamine”[MeSH Terms] 18257 7 “amphetamines”[All Fields] 8607 8 “amphetamines”[MeSH Terms] 34894 9 Search #1 OR #2, #3, #4, #5, #6, #7 45289 10 Search #9 AND "abuse"[All Fields] 7533 11 Search #9 AND “dependence”[All Fields] 2200 12 Search #9 AND "use"[All Fields] 141 13 Search #9 AND "disorder"[All fields] 3269 14 Search #9 AND "Substance-Related Disorders"[MeSH Terms] 9066

(Table 1 continues on the following page.)

Table 1, continued 15 Search #10 OR #11, #12, #13, #14 15014 16 Search #15 AND "therapy"[All Fields] 2879 17 Search #15 AND "therapy"[Subheading] 3377 18 Search #15 AND "treatment"[All Fields] 4503 19 Search #15 AND "therapeutics"[MeSH Terms] 2697 20 Search #15 AND “therapeutics”[All Fields] 145 21 Search #15 AND "medication"[All Fields] 820 22 Search #15 AND "amphetamine-related disorders/drug therapy"[MAJR] 127 23 Search #16 OR #17, #18, #19, #20, #21, #22 7915 24 Search #23 AND "humans"[MeSH Terms] 5749 25 Search #23 AND English[lang] 7430 26 Search #23 AND "adult"[MeSH Terms] 2963 27 Search #24 AND #25, #26 2765

Study Selection

Results of the various iterations of the PubMed search strategy are presented in Table 1. The search included records from date of inception of PubMed to November 29, 2016. The last search was performed on December 2, 2016. The process of record screening and eligibility review is outlined in Figure 2. I identified a total of 2,765 records with the final search. I screened the title and abstracts of each record and excluded 2,666. I downloaded the full text of the remaining 99 articles and reviewed the eligibility of each for final inclusion in analysis. I excluded 88 articles from the final analysis. Finally, 11 articles were included in the analysis.

References for all excluded articles and reason for exclusion can be found in the references section of this paper.

The majority of excluded articles were pre-clinical studies of the effects of various pharmacological treatments on different aspects of methamphetamine use. Most of these studies were conducted in controlled human laboratory settings. Broadly, these studies fell into one or more of the following categories of investigation: attenuation of various effects of acute amphetamine exposure, enhancement of neurocognitive processes in participants with chronic methamphetamine exposure, changes in the choice of amphetamine dose under controlled conditions, or safety and/or tolerability of proposed treatments. The different pharmacological treatments found in these preclinical studies include naltrexone, modafinil, bupropion, diltiazem, clonidine, isradipine, topiramate, rivastigmine, gamma-vinyl-gamma-amminobutyric acid, aripiprazole, selegiline, perindopril, progesterone, risperidone, lithium, atomoxetine, varenicline, valproate, and cytidine-5’-diphosphate choline.

Fourteen articles were studies included in the systematic review of agonist treatments by Bhatt et al.11 Five articles were previously reviewed by Brackins et al.15 Four articles were either republications of previously published studies or secondary analyses of previously published studies. Three articles did not include reduction in methamphetamine use as an outcome measure. Another three articles were conducted on inpatient populations. These articles were focused on symptom reduction and also did not include reduction in methamphetamine use as an outcome. One study reported on the decline in methamphetamine use in a population with polydrug dependence, but not all of the study population used methamphetamine.

Records Identified Through PubMed Search

N = 2765

Identification Duplicates Removed Records Identified Through Other N = 0 Sources N = 0

Title and Abstracts Screened Records Excluded After Initial N = 2765 Review N = 2666 Screening

Full Text Articles Excluded Full Text Articles Assessed for N = 88 Eligibility N = 99 Eligibility Preclinical Study = 41 Not a RCT = 17 Agonist Treatment = 14 Previously Reviewed = 5

Duplicate = 4 Studies Included for Qualitative Wrong outcome = 3 Synthesis Wrong setting = 3 N = 11 Included Wrong population = 1

Figure 2: Flow diagram

Study characteristics

The eleven studies included in the analysis examined 8 different pharmacological treatments among 802 participants. The characteristics of studies included in the final analysis are presented in Table 2. Eight studies were published after 2011 when the previous systematic review by

Brackins et al was done.15 Interestingly, three studies were published before 2012 but were not identified in that review. Most studies were conducted in the USA, although the most recent studies were conducted in Iran and Malaysia. One study each was conducted in Russia and

Sweden. Study size was small in all trials, ranging from 31 to 140 participants.

Interventions included buprenorphine, citocoline, topiramate, mirtazapine, N-acetyl-cysteine

(NAC), naltrexone, aripiprazole, and a combination of flumazenil/gabapentin/hydroxyzine. One study each used buprenorphine, citocoline, topiramate, and mirtazapine as interventions. One study used N-acetyl-cysteine (NAC) by itself, while another used a combination of NAC and

naltrexone. Two studies used aripiprazole. Three studies used naltrexone: one in combination with NAC, one as an oral pill, and another as an implant. All studies used inactive placebos for controls, including one study with a placebo implant.

All 11 studies reported that methamphetamine use was measured using urine drug screens

(UDS), but two of the studies did not report the results of these measurements. Three studies did not report study retention as an outcome measure, and did not provide enough data to calculate a statistical comparison of numbers remaining in each arm at the end of the study. Two studies reported that they measured scores for methamphetamine craving, but did not present the results.

Table 2, showing the characteristics of the included studies, begins on the next page.

Table 2: Characteristics and results of included studies Author Yr Design N Dura- Participants Intervention UDS Retention Craving Int Val Ext tion Val Salehi et al 2015 RCT 40 16 All men referred to Buprenorphine NR NR Significant Poor Poor weeks treatment center in 6mg improvement Reported Iran results by each Decreased visit. score in Significant intervention differences group favoring p<0.001 intervention in ANCOVA visits 3-6 but no summary analysis done Mousavi et 2015 Placebo 32 8 weeks Treatment seeking NAC 1200mg NR NR Significant Poor Poor al controlled (two 4 patients referred to improvement Stated as crossover week tertiary care in Iran measured but Significant. periods) not reported improvement in intervention group p<0.001 ANOVA Sulaiman et 2013 RCT 49 8 weeks All participants Aripiprazole No significant Significant Significant Poor Poor al had been included 5-10mg difference difference decrease in a 2-week open p=0.173 GEE Better BSCS score label trial of retention in favoring aripiprazole intervention intervention immediately prior 48.7 vs 37.1 p=0.015 to this study in days p<0.05 MMRM Malaysia Kaplan-Meier survival analysis Coffin et al 2013 RCT 90 12 Treatment seeking Aripiprazole No significant No significant No Fair Fair weeks patients recruited 20mg difference difference significant difference

from community in RR 0.88 number of visual analog the USA intervention vs completed scale scores control for counseling p=0.38 positive UDS sessions 76% (0.66-1.19 intervention p=0.41) vs 80% placebo p=0.11 Brown and 2012 RCT 60 12 Patients with Citocoline No significant Significant NR Poor Poor Gabrielson weeks bipolar depression 2000mg difference improvement or MDD in the RR 1.09 Improved USA intervention vs survival in control for intervention positive UDS group. 41% (p=0.23) completed in intervention group vs 14% in control, p=0.02 Kaplan-Meier Elkashef et 2012 RCT 140 13 Patients at multiple Topiramate No significant No significant No Fair Good al weeks substance abuse 200mg difference difference significant treatment centers in difference P=0.13 GEE 39 in interven the USA retained to Change in end of study BSCS score vs 38 control, p=0.09 p=0.72 Tiihonen et 2012 RCT 100 10 Treatment seeking Naltrexone No significant Significant No Fair Poor al weeks patients in Russia implant difference significant Improved 1000mg difference 40% negative retention in UDS in intervention Statistics not intervention vs group, 52% reported 24% control, present at end p=0.09 of study vs 28% control p=0.01

Ling et al 2012 RCT 120 108 Treatment seeking Flumazenil IV No significant No significant No Good Fair days patients in USA 2mg, difference difference significant gabapentin difference P=0.28 57 days for 1200mg and intervention Visual hydroxyzine vs 74 days analog scale 50mg p=0.30 Colfax et 2011 RCT 60 12 Treatment seeking Mirtazapine Significant NR NR Good Poor al weeks MSM with high 30mg improvement risk sexual in intervention behavior recruited RR0.57 for from community in positive UDS the USA p=0.02 Grant et al 2010 RCT 31 8 weeks Treatment seeking NAC 2400mg No significant No significant No Poor Poor patients recruited and difference difference significant from the naltrexone difference 46.2% Penn Craving community in the 200mg intervention vs Scale Study USA 35.3% p=0.106 completion p=0.547 64.3% intervention vs 47.1% control p=0.337 Jayaram- 2008 RCT 80 12 Treatment seeking Naltrexone Significant No significant Significant Fair Poor Lindström weeks patients from 50mg improvement difference reduction et al community in 65.2% Visual Sweden. Majority negative UDS analog scale, (84%) using D/L- in intervention P<0.05 amphetamine, not vs 47.7% methamphetamine. control p<0.05

Risk of bias is found in the next table.

Author 1. Random 2. Allocation 3. Blinding 4. Blinding 5. Blinding 6. Blinding 7. 8. 9. 10. 11. Sequence concealment of of of of outcome Incompl Selective Other Overall Ext Generation (selection participants participants Outcome assessor outcome reporting Judgement bias (Selection bias) and providers and providers Assessor subjective data (reporting of Internal Validity Bias) (performance (performance objective outcomes (attrition bias) Validity

bias) bias) outcomes (detection bias) (good, fair, Objective Subjective (detection bias) poor) Outcomes Outcomes bias)

Salehi et al ? ? - - + - - + ? P P

Mousavi et - - ? ? ? - + + - P P al Sulaiman + + - - + + - - - P P et al Coffin et + + + + + + - + - F F al Brown and ? ? + + + + - + - P P Gabrielson Elkashef et + ? ? ? + ? - + + F G al Tiihonen + + + - + - - + + F P et al Ling et al + + + + + + - + + G F

Colfax et + + + + + + + + + G P al Grant et al ? ? ? ? ? ? - + - P P

Jayaram- ? + + + + + - + - P P Lindström et al Figure 3: Analysis of risk of bias, internal validity and external validity

The results of the analysis of the risk of bias and overall internal validity are presented in Figure

3 above. Only 2 studies (Ling et al and Colfax et al) were judged to have good internal validity.

Four studies were judged to have fair internal validity, and the remaining 5 studies had poor internal validity. The most common domain for a high risk of bias was attrition bias due to differential loss of participants between the arms, overall high numbers of drop outs, and/or no presented analysis of the drop outs. The second most common domain with a high risk of bias was the “other” category, in all but one case because of imbalance at baseline between arms of the study or lack of reporting on baseline characteristics. Full information including supporting comments on the risks of bias for each study can be found in Appendix B.

Results of individual studies

The results from each study for the main outcome measures of interest to this review can be found in Table 2. Two studies (Colfax et al20 and Jarayam-Lindstrom et al21) reported significant improvements in UDS results for mirtazapine and naltrexone, respectively. Three studies

(Sulaiman et al22, Brown and Gabrielson23, and Tiihonen et al24) reported significant improvements in retention for aripiprazole, citocoline, and naltrexone implant respectively. Four studies (Salehi et al, Moussavi et al, Sulaiman et al, and Jarayam-Lindstrom et al) reported significant improvements in craving scores for buprenorphine, NAC, aripiprazole, and naltrexone respectively.

Salehi et al conducted an RCT of buprenorphine 6mg among men in Iran with methamphetamine dependence referred to an addiction treatment center and reported a significant decrease in methamphetamine craving as measured by an adapted version of the Cocaine Craving Brief

Questionnaire (CCQ-brief) (p<0.001 by ANCOVA). They also reported the results of UDS at each 2 week visit and reported that the UDS was statistically less likely to be positive at visits 3

through 6, but did not report an overall measure of UDS positivity. They did not report on the prevalence of opioid use in the sample population, which significantly limits the interpretability of the results. Most importantly, the study reported 20 participants in each arm and 100% completion rate, but the numbers given for the first week craving score indicated that there were actually 31 participants in the control group and 23 in the intervention group at the beginning of the study. No reasons or explanation for the discrepancy were given and I judged it to have poor internal validity as a result.

Mousavi et al conducted a randomized cross-over study in 32 men and women in Iran with methamphetamine dependence referred to a tertiary care center using N-acetyl-cysteine (NAC)

1200mg and reported a significant decrease in methamphetamine craving as determined by

CCQ-brief scores (p<0.001 ANOVA). However, the results were analyzed only among participants who finished the study, and 28% of the participants were lost to follow-up.

Moreover, I judged it to have high risk of reporting bias as the study methods stated that UDS were done at each visit, but no results from the UDS were reported.

Sulaiman et al reported on an RCT of aripiprazole 10mg in 49 participants in Malaysia with methamphetamine dependence and a history of psychotic symptoms and reported no significant difference in UDS results (p = 0.173 GEE). They did report a significant reduction in craving as measured by the Brief Substance Craving Scale (p = 0.015 MMRM) and a significant improvement in retention 48.7 days (SD 4.0) in intervention arm versus 37.1 days (SD 5.0) in the control arm (p < 0.05 Kaplan-Meier survival analysis). However, the validity of these results is questionable as all participants in the trial had previously participated in an open label uncontrolled trial of aripiprazole.

Coffin et al performed an RCT of aripiprazole 20mg in 90 men and women with methamphetamine dependence recruited from the general community in San Francisco. They reported no significant difference in positive UDS (RR 0.88 p = 0.41), craving, as measured by a visual analog scale (p = 0.38) or retention, defined as number of completed weekly counseling sessions (76% in intervention versus 80% in control, p = 0.11). There were twice as many participants in the intervention group (10) that dropped out of the study, and the reasons for drop out was not reported.

Brown and Gabrielson reported on an RCT of citicoline 2000mg in 60 men and women in the

USA with methamphetamine use and either bipolar depression or major depressive disorder.

They reported no significant difference in UDS results (RR 1.09 favoring control p = 0.23), although they did report significantly improved retention in the intervention arm (p = 0.02

Kaplan-Meier). The results, however, were analyzed only among the 48 of 60 participants who returned for follow-up after randomization.

Elkashef et al conducted an RCT of topiramate 200mg in 140 men and women with methamphetamine dependence in the USA. They found no significant difference in UDS (p =

0.13 GEE), craving by BSCS (p = 0.09), or retention defined as completion of study (p = 0.72).

The study was limited by a high loss of participants; only 55% completed the study.

Tiihonen et al performed an RCT of a naltrexone implant compared to a placebo implant in 100 men and women with both amphetamine and opioid dependence. They found no significant difference in UDS results (p = 0.09) or craving (analysis not reported), but did report a significant improvement in retention in the intervention group measured by percent present at study end (52% in intervention versus 28% in control, p = 0.01). A significant limitation to this study is that use of a known treatment for opioid dependence whose effects could likely be

detected by experienced opioid users in a dual opioid and methamphetamine population makes it unclear if the results are due to changes in opioid use, un-blinding, or a true effect on methamphetamine use.

Ling et al conducted an RCT of the PROMETA™ protocol (a proprietary protocol involving flumazenil 2mg IV, gabapentin 1200mg, and hydroxyzine 50mg) in 120 treatment seeking men and women with methamphetamine dependence. They found no significant differences in UDS

(p = 0.28), craving (statistics not reported), or retention in treatment when adjusted for a baseline imbalance in age between groups (p = 0.30). As in other studies, there was a high rate of attrition in both groups (41.1% in intervention arm, and 30.9% in control arm).

Colfax et al conducted an RCT of mirtazapine 30mg in 60 MSM with methamphetamine dependence and high risk sexual practices. They reported a significant difference in UDS favoring the intervention (RR 0.57 CI 0.35-0.93). They did not report on retention or craving. I found no significant sources of bias affecting internal validity. However, because methamphetamine use was associated with sex in this population it is possible that the results were due not to a direct effect of mirtazapine on methamphetamine use, but rather to a reduction in high risk sex that was accompanied by methamphetamine use among the study participants.

Grant et al performed an RCT of NAC 2400mg plus naltrexone 200mg in 31 men and women with methamphetamine dependence. They reported no significant difference in UDS (p = 0.547), craving as measured by the Penn Craving Scale (p = 0.106), or retention defined as study completion (p = 0.337). The study had a high rate of attrition, with only 17 of 31 (54%) completing all five visits, 8 of whom dropped out immediately after randomization and were not included in the analysis.

Jayaram-Lindstrom et al conducted an RCT of naltrexone 50mg in 80 men and women in

Sweden with amphetamine dependence. They reported a significant difference in UDS favoring the intervention arm with 65.2% negative UDS versus 47.7% in control arm (p < 0.05). They also reported a significant difference in craving scores (p < 0.05), although the actual numbers were not reported. They did not analyze retention in treatment, but from the data they did present, 72.5% in the intervention arm finished the study as did 65% in the control arm. There was a high attrition rate, with only 55 patients finishing the study, and there was a significant baseline difference between groups in the severity of amphetamine use (31 days used in the previous 12 weeks in the intervention group versus 27 in the control). An important caveat to this study is that the main form of amphetamine used by participants in the study was a mixture of dextro- and levo-amphetamine, not methamphetamine, and that 47.5% of participants carried a diagnosis of ADHD.

Synthesis of results

I found no study with both good internal and good external validity. The overall level of internal validity within studies was limited by small study size and high numbers of drop outs.

Comparison between studies was often not possible because outcome measures were inconsistently measured, defined and reported. Because of this, it is difficult to comment on potential reasons for differences between the studies.

When considered by level of internal validity, only studies with good or fair internal validity reported significant improvements on the objective measure of UDS, whereas a higher percentage of poor quality studies reported positive results for the subjective measure of craving

(Table 3).

Table 3

Benefit on Benefit for Benefit for Any Internal Validity N UDS (n) % Retention (n) % Craving (n) % Benefit (n) % Poor 5 0 0% 2 40% 3 60% 4 80% Fair 4 1 25% 1 25% 1 25% 2 50% Good 2 1 50% 0 0% 0 0% 1 50%

The 2 studies that reported significant improvement in UDS used different medications, mirtazapine and naltrexone. Both had higher percentages of participants retained to the end of the study than the average among analyzed studies. Colfax et al had an impressive retention rate of 93%, while Jayaram-Lindstrom et al had a completion rate of 69%. They also both examined the treatment in populations distinct from the general population of methamphetamine use disorder. Colfax et al included only MSM with high risk sexual practices, while Jayaram-

Lindstrom et al included participants with amphetamine dependence who used mostly non- methamphetamine.

Risk of bias across studies

I did not conduct an assessment of the risk of bias across studies.

Discussion

Summary of evidence

I found no evidence to support a pharmacological treatment of methamphetamine use disorder in the general outpatient US population. Specifically, I did not find evidence supporting the use of buprenorphine, citocoline, topiramate, mirtazapine, N-acetyl-cysteine (NAC), naltrexone, aripiprazole, or a combination of flumazenil/gabapentin/hydroxyzine.

The results of this review do not alter the conclusions of the other 2 published systematic reviews on this topic, which also found no evidence for a particular pharmacological treatment. Bhatt et al systematically reviewed and meta-analyzed RCTs on modafinil, bupropion, dextroamphetamine, and methylphenidate. Brackins et al systematically reviewed RCTs on sertraline, bupropion, mirtazapine, modafinil, dexamphetamine, ondansetron, risperidone, baclofen, gabapentin, and aripiprazole.

I compared the list of pharmacological treatments studied in clinical RCTs to treatments examined in the pre-clinical studies and identified 12 pharmacological agents that have not been evaluated in a clinical trial for the treatment of methamphetamine use disorder. These include diltiazem, clonidine, isradipine, rivastigmine, gamma-vinyl-gamma-amminobutyric acid

(vigabatrin), selegiline, perindopril, progesterone, lithium, atomoxetine, varenicline, and valproate.

Limitations of the data

A major limitation of the reviewed literature is that the sizes of reported studies are likely to be inadequate for detecting significant treatment effects. This is compounded by the fact that almost all studies, with the exception of the mirtazapine study among MSM by Colfax et al, suffered large numbers of drop outs.20 The high percentage of drop outs in these studies is likely an inevitable complication of trials for substance use disorders. High proportions of drop outs in these studies means that the studies are more likely to underestimate the true effect size. Larger sample sizes in anticipation of high attrition rates may help to minimize this bias by providing greater power to detect significant differences.

Likewise, adherence to treatment is a major problem in this population, significantly limiting the ability of studies to detect treatment effects. One potential solution to this is to use long acting

injectable or implant formulations where possible. Long acting formulations of naltrexone, buprenorphine and several antipsychotics are now or will soon be available. Use of these formulations would significantly improve the reliability of the results. Barring this, use of biomarker measures of adherence such as blood level monitoring or measurement of urine riboflavin incorporated into study drugs could help to pinpoint whether adherence is, in fact, a major reason for non-significant findings.

Several reviews and studies used “abstinence” from MA use as a main outcome. However, the definition of abstinence varied between studies, not all studies reported it as an outcome, and the clinical significance of subjectively defined “abstinence” vs overall reduction in MA use is not clear. A more useful and comparable approach for future studies would be either to adopt a standard definition of “abstinence” in the context of short term trials (the creation of which is limited by the lack of evidence on what constitutes a significant measure), or report all trials using the same measure of percentage of positive UDS. This would also limit the risk of selective reporting bias, as it is not always clear if the definitions of “positive week” or

“abstinence” could have been manipulated to yield more significant results.

Measurement bias is a significant concern. Some studies in this review measured UDS only once every 2 weeks, while others performed UDS 3 times a week. The risk of not detecting significant differences is already higher because of attrition bias, which is very difficult to change, and increasing and standardizing the frequency of UDS in studies is an obvious and achievable way of improving the internal validity of future trials. A related issue is, in effect, the uncertainty about what might otherwise be thought of as the interventions’ Minimal Clinically Significant

Difference: there appears to be no agreed upon standard by which to judge the clinical significance of UDS results. Some studies in this review chose to report the results as total

positive across all weeks, while others performed analyses on varying periods of time with negative UDS.

Limitations of this review

A significant limitation of this review is that it was conducted by a single investigator. Analyses of the internal and external validity of studies will usually contain some element of subjectivity.

It is possible that some of the findings of this review, particularly judgements about the various risks of bias within studies and generalizability of findings, would be slightly different if done independently by multiple researchers. If possible, having multiple researchers conduct a future review would strengthen the internal validity of the review itself.

I did not conduct an assessment of possible publication bias. However, I believe it is unlikely that any un-published studies would change the conclusion of this review that no pharmacological treatments for methamphetamine use disorder have been proven to be effective.

Publication bias tends toward publishing of positive, rather than negative results. It is more likely that there are un-published negative studies of treatments. Nevertheless, the knowledge of negative results would help to move the field forward, and a future review would be strengthened by attempting to identify which treatments have been studied but not published. Potential strategies for addressing this in a future review include searching trial registries, searching for relevant conference proceedings and meeting abstracts, and consulting with experts and study authors to identify other relevant studies that may not have been published.

Likewise, there may have been relevant published studies that were not identified by this review because of its reliance on searching within a single database, PubMed. A future review would be enhanced by searching multiple databases. Furthermore, I conducted a single final search of

PubMed after several iterations of the search process. More relevant studies may have been

identified by the use of a looping search strategy that repeated the iterations of the search process with slight variations to keep all previously identified studies while potentially including new relevant studies.

Finally, while the goal of this systematic review was to fill in the gap between the two previously published systematic reviews, the usefulness of this review in guiding future research is limited by the fact that the many pertinent studies of agonist treatments were left out of the analysis. It is possible that a synthesis of all pertinent studies including agonist treatments would have yielded different conclusions about the various risks of bias, the potential reasons for non-significant results, and the potential approach to minimizing these issues in future research.

Conclusion

Several studies reported positive results, but were limited by poor internal or external validity and no evidence was found to support treatment of methamphetamine use disorder with a specific medication in the general outpatient population, which had also been found in 2 other systematic reviews of a distinct set of studies. There is a pressing need for more research in this field. Future trials should use consistent outcome measures and address possible power issues caused by high attrition.

Funding

No funding was received for the conduct of this research. The author, Joshua Evans MD, has no conflicts of interest to declare.

Acknowledgements

Dr. Evans had primary responsibility for the conception and design of the review, development of a search strategy, choice of data collection instruments, analysis of included studies, preparation and revision of the manuscript, and final approval of the version to be submitted. He is responsible for the integrity of the work as a whole, from inception to submitted paper. Dr.

Tolleson-Rinehart helped to refine the scope of the study, guided the process of data collection and analysis, and gave approval of the paper to be submitted. Dr. Ian Buchanan, MD provided editorial feedback on the paper and gave approval of the paper to be submitted.

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Agonist treatments

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Previously reviewed

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Sofuoglu M, Poling J, Hill K, Kosten T. Atomoxetine attenuates dextroamphetamine effects in humans. Am J Drug Alcohol Abuse. 2009;35(6):412-416. doi:10.3109/00952990903383961.

Stoops WW, Bennett JA, Lile JA, Sevak RJ, Rush CR. Influence of aripiprazole pretreatment on the reinforcing effects of methamphetamine in humans. Prog Neuropsychopharmacol Biol Psychiatry. 2013;47:111-117. doi:10.1016/j.pnpbp.2013.08.007.

Stoops WW, Lile JA, Glaser PEA, Rush CR. A low dose of aripiprazole attenuates the subject-rated effects of d-amphetamine. Drug Alcohol Depend. 2006;84(2):206-209. doi:10.1016/j.drugalcdep.2006.02.004.

Stoops WW, Pike E, Hays LR, Glaser PE, Rush CR. Naltrexone and bupropion, alone or combined, do not alter the reinforcing effects of intranasal methamphetamine. Pharmacol Biochem Behav. 2015;129:45-50. doi:10.1016/j.pbb.2014.11.018.

Verrico CD, Mahoney JJ, Thompson-Lake DGY, Bennett RS, Newton TF, La Garza De R. Safety and efficacy of varenicline to reduce positive subjective effects produced by methamphetamine in methamphetamine-dependent volunteers. Int J Neuropsychopharmacol. 2014;17(2):223-233. doi:10.1017/S146114571300134X.

Willson MC, Bell EC, Dave S, Asghar SJ, McGrath BM, Silverstone PH. Valproate attenuates dextroamphetamine-induced subjective changes more than lithium. European Neuropsychopharmacology. 2005;15(6):633-639. doi:10.1016/j.euroneuro.2005.04.015.

Yoon SJ, Lyoo IK, Kim HJ, et al. Neurochemical alterations in methamphetamine- dependent patients treated with cytidine-5'-diphosphate choline: a longitudinal proton magnetic resonance spectroscopy study. Neuropsychopharmacology. 2010;35(5):1165- 1173. doi:10.1038/npp.2009.221.

Non-randomized or uncontrolled studies

Camacho A, Ng B, Frye MA. Modafinil for bipolar depression with comorbid methamphetamine abuse. Am J Addict. 2010;19(2):190-191. doi:10.1111/j.1521- 0391.2009.00024.x.

Carnwath T, Garvey T, Holland M. The prescription of dexamphetamine to patients with schizophrenia and amphetamine dependence. J Psychopharmacol (Oxford). 2002;16(4):373-377.

Fechtner RD, Khouri AS, Figueroa E, et al. Short-term treatment of cocaine and/or methamphetamine abuse with vigabatrin: ocular safety pilot results. Arch Ophthalmol. 2006;124(9):1257-1262. doi:10.1001/archopht.124.9.1257.

Fleming PM, Roberts D. Is the prescription of amphetamine justified as a harm reduction measure? J R Soc Health. 1994;114(3):127-131.

Hellem TL, Sung Y-H, Shi X-F, et al. Creatine as a Novel Treatment for Depression in Females Using Methamphetamine: A Pilot Study. J Dual Diagn. 2015;11(3-4):189-202. doi:10.1080/15504263.2015.1100471

Jayaram-Lindström N, Wennberg P, Beck O, Franck J. An open clinical trial of naltrexone for amphetamine dependence: compliance and tolerability. Nord J Psychiatry. 2005;59(3):167-171. doi:10.1080/08039480510023052.

Laqueille X, Dervaux A, Omari El F, Kanit M, Baylé FJ. Methylphenidate effective in treating amphetamine abusers with no other psychiatric disorder. Eur Psychiatry. 2005;20(5-6):456-457. doi:10.1016/j.eurpsy.2005.03.013.

Maletzky BM. Phenelzine as a stimulant drug antagonist: a preliminary report. Int J Addict. 1977;12(5):651-655.

Mann N, Bitsios P. Modafinil treatment of amphetamine abuse in adult ADHD. J Psychopharmacol (Oxford). 2009;23(4):468-471. doi:10.1177/0269881108091258.

McElhiney MC, Rabkin JG, Rabkin R, Nunes EV. Provigil (modafinil) plus cognitive behavioral therapy for methamphetamine use in HIV+ gay men: a pilot study. Am J Drug Alcohol Abuse. 2009;35(1):34-37. doi:10.1080/00952990802342907.

McGaugh J, Mancino MJ, Feldman Z, et al. Open-label pilot study of modafinil for methamphetamine dependence. J Clin Psychopharmacol. 2009;29(5):488-491. doi:10.1097/JCP.0b013e3181b591e0.

McRae-Clark AL, Brady KT, Hartwell KJ, White K, Carter RE. Methylphenidate transdermal system in adults with past stimulant misuse: an open-label trial. J Atten Disord. 2011;15(7):539-544. doi:10.1177/1087054710371171.

Meredith CW, Jaffe C, Yanasak E, Cherrier M, Saxon AJ. An open-label pilot study of risperidone in the treatment of methamphetamine dependence. J Psychoactive Drugs. 2007;39(2):167-172. doi:10.1080/02791072.2007.10399875.

Nejtek VA, Avila M, Chen L-A, et al. Do atypical antipsychotics effectively treat co- occurring bipolar disorder and stimulant dependence? A randomized, double-blind trial. J Clin Psychiatry. 2008;69(8):1257-1266.

Pal R, Mendelson JE, Flower K, et al. Impact of prospectively determined A118G polymorphism on treatment response to injectable naltrexone among methamphetamine- dependent patients: an open-label, pilot study. J Addict Med. 2015;9(2):130-135. doi:10.1097/ADM.0000000000000107.

Sattar SP, Bhatia SC, Petty F. Potential benefits of quetiapine in the treatment of substance dependence disorders. J Psychiatry Neurosci. 2004;29(6):452-457.

Tennant FS, Rawson RA. Cocaine and amphetamine dependence treated with desipramine. NIDA Res Monogr. 1983;43:351-355.

Republication or secondary analysis of previously published study

Brensilver M, Heinzerling KG, Swanson A-N, Telesca D, Furst BA, Shoptaw SJ. Cigarette smoking as a target for potentiating outcomes for methamphetamine abuse treatment. Drug Alcohol Rev. 2013;32(1):96-99. doi:10.1111/j.1465-3362.2012.00423.x.

McCann DJ, Li S-H. A novel, nonbinary evaluation of success and failure reveals bupropion efficacy versus methamphetamine dependence: reanalysis of a multisite trial. CNS Neurosci Ther. 2012;18(5):414-418. doi:10.1111/j.1755-5949.2011.00263.x.

Zorick T, Sugar CA, Hellemann G, Shoptaw S, London ED. Poor response to sertraline in methamphetamine dependence is associated with sustained craving for methamphetamine. Drug Alcohol Depend. 2011;118(2-3):500-503. doi:10.1016/j.drugalcdep.2011.04.015.

Wrong outcome

Cruickshank CC, Montebello ME, Dyer KR, et al. A placebo-controlled trial of mirtazapine for the management of methamphetamine withdrawal. Drug Alcohol Rev. 2008;27(3):326-333. doi:10.1080/09595230801935672.

Jittiwutikan J, Srisurapanont M, Jarusuraisin N. Amineptine in the treatment of

amphetamine withdrawal: a placebo-controlled, randomised, double-blind study. J Med Assoc Thai. 1997;80(9):587-592.

Kongsakon R, Papadopoulos KI, Saguansiritham R. Mirtazapine in amphetamine detoxification: a placebo-controlled pilot study. Int Clin Psychopharmacol. 2005;20(5):253-256.

Wrong setting

Mahoney JJ, Jackson BJ, Kalechstein AD, La Garza De R, Chang LC, Newton TF. Acute modafinil exposure reduces daytime sleepiness in abstinent methamphetamine-dependent volunteers. Int J Neuropsychopharmacol. 2012;15(9):1241-1249. doi:10.1017/S1461145711001805.

McGregor C, Srisurapanont M, Mitchell A, Wickes W, White JM. Symptoms and sleep patterns during inpatient treatment of methamphetamine withdrawal: a comparison of mirtazapine and modafinil with treatment as usual. J Subst Abuse Treat. 2008;35(3):334- 342. doi:10.1016/j.jsat.2007.12.003.

Shulman A, Jagoda J, Laycock G, Kelly H. Calcium channel blocking drugs in the management of drug dependence, withdrawal and craving. A clinical pilot study with nifedipine and verapamil. Aust Fam Physician. 1998;27 Suppl 1:S19-S24.

Wrong population

Piralishvili G, Otiashvili D, Sikharulidze Z, Kamkamidze G, Poole S, Woody GE. Opioid addicted buprenorphine injectors: drug use during and after 12-weeks of buprenorphine- naloxone or methadone in the Republic of Georgia. J Subst Abuse Treat. 2015;50:32-37. doi:10.1016/j.jsat.2014.10.003.

Appendix A

Item Judgement Description 1. Random sequence Low risk The investigators describe a random component in generation (selection the sequence generation process such as: random bias) number table; computerized random number generator; coin tossing; shuffling cards or envelopes; throwing dice; drawing of lots; minimization

High risk The investigators describe a non-random component in the sequence generation process such as: odd or even date of birth; date (or day) of admission; hospital or clinic record number; alternation; judgement of the clinician; results of a laboratory test or a series of tests; availability of the intervention

Unclear risk Insufficient information about the sequence generation process to permit judgement of low or high risk

2. Allocation Low risk Investigators enrolling participants could not foresee concealment (selection assignment because 1 of the following, or an bias) equivalent method, was used to conceal allocation: central allocation (including telephone, web-based, and pharmacy- controlled, randomization); sequentially numbered drug containers of identical appearance; sequentially numbered, opaque, sealed envelopes

High risk Investigators enrolling participants could possibly foresee assignments because 1 of the following methods was used: open random allocation schedule (e.g. a list of random numbers); assignment envelopes without appropriate safeguards (e.g. if envelopes were unsealed or non-opaque or not sequentially numbered); alternation or rotation; date of birth; case record number; any other explicitly unconcealed procedure

Unclear risk Insufficient information to permit judgement of low or high risk. This is usually the case if the method of concealment is not described or not described in sufficient detail to allow a definite judgement

3. Blinding of Low risk No blinding or incomplete blinding, but the review participants and authors judge that the outcome is not likely to be providers (performance influenced by lack of blinding; bias) Blinding of participants and key study personnel Objective outcomes ensured, and unlikely that the blinding could have been broken

High risk No blinding or incomplete blinding, and the outcome is likely to be influenced by lack of blinding; Blinding of key study participants and personnel attempted, but likely that the blinding could have been broken, and the outcome is likely to be influenced by lack of blinding

Unclear risk Insufficient information to permit judgement of low or high risk

4. Blinding of Low risk Blinding of participants and providers ensured and participants and unlikely that the blinding could have been broken providers (performance bias)

Subjective outcomes

Unclear risk Insufficient information to permit judgement of low or high risk

5. Blinding of outcome Low risk No blinding of outcome assessment, but the review assessor (detection bias) authors judge that the outcome measurement is not likely to be influenced by lack of blinding. Blinding Objective outcomes of outcome assessment ensure, and unlikely that the blinding could have been broken.

High risk No blinding of outcome assessment, and the outcome measurement is likely to be influenced by lack of blinding;

Blinding of outcome assessment, but likely that the blinding could have been broken, and the outcome

measurement is likely to be influenced by lack of blinding

Unclear risk Insufficient information to permit judgement of low or high risk

6. Blinding of outcome Low risk Blinding of outcome assessment ensured, and assessor (detection bias) unlikely that the blinding could have been broken

Subjective outcomes

High risk No blinding of outcome assessment, and the outcome measurement is likely to be influenced by lack of blinding; Blinding of outcome assessment, but likely that the blinding could have been broken, and the outcome measurement is likely to be influenced by lack of blinding

Unclear risk Insufficient information to permit judgement of low or high risk

7. Incomplete outcome Low risk No missing outcome data; data (attrition bias) For Reasons for missing outcome data unlikely to be all outcomes except related to true outcome (for survival data, censoring retention in treatment unlikely to introduce bias); Missing outcome data balanced in numbers across intervention groups, with similar reasons for missing data across groups; For dichotomous outcome data, the proportion of missing outcomes compared with observed event risk not enough to have a clinically relevant impact on the intervention effect estimate; For continuous outcome data, plausible effect size (difference in means or standardized difference in means) among missing outcomes not enough to have a clinically relevant impact on observed effect size; Missing data have been imputed using appropriate methods; All randomised participants are reported/analyzed in the group they were allocated to by randomization irrespective of non-adherence and co-interventions (intention-to-treat)

High risk Reason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across intervention groups;

For dichotomous outcome data, the proportion of missing outcomes compared with observed event risk enough to induce clinically relevant bias in intervention effect estimate; For continuous outcome data, plausible effect size (difference in means or standardized difference in means) among missing outcomes enough to induce clinically relevant bias in observed effect size;

’As-treated’ analysis done with substantial departure of the intervention received from that assigned at randomization

Unclear risk Insufficient information to permit judgement of low or high risk (e.g. number randomised not stated, no reasons for missing data provided; number of dropouts not reported for each group)

8. Selective reporting Low risk The study protocol is available and all of the study’s (reporting bias) pre-specified (primary and secondary) outcomes that are of interest in the review have been reported in the pre-specified way; The study protocol is not available but it is clear that the published reports include all expected outcomes, including those that were pre-specified (convincing text of this nature may be uncommon)

High risk Not all of the study’s pre-specified primary outcomes have been reported; 1 or more primary outcomes is reported using measurements, analysis methods or subsets of the data (e.g. subscales) that were not pre- specified; 1 or more reported primary outcomes were not pre-specified (unless clear justification for their reporting is provided, such as an unexpected adverse effect);

1 or more outcomes of interest in the review are reported incompletely so that they cannot be entered in a meta-analysis; The study report fails to include results for a key outcome that would be expected to have been reported for such a study

Unclear risk Insufficient information to permit judgement of low or high risk

9. Other bias Low risk The study appears to be free from other sources of bias.

High risk There is at least 1 important risk of bias. For example, the study: Had a potential source of bias related to the specific study design used; Stopped early due to some data- dependent process (including a formal- stopping rule); Had extreme baseline imbalance; Has been claimed to have been fraudulent; or Had some other problem.

Unclear risk There may be a risk of bias, but there is either:

Insufficient information to assess whether an important risk of bias exists; or

Insufficient rationale or evidence that an identified problem will introduce bias

Appendix B

Author Salehi et al Year 2015 {Salehi:2015fe} 1. Random Sequence Generation (Selection Bias) Unclear risk Quote: "The 40 selected individuals were allocated into 2 groups of either intervention or placebo using a random allocation method (20 patients in each 1. Support group)." 2. Allocation concealment (selection bias) Unclear risk 2. Support Concealment is not described 3. Blinding of participants and providers (performance bias) Objective Outcomes High risk Providers are not stated as being blinded. Also, buprenorphine has typical side effects and withdrawal syndrome that would likely alert patients to active 3. Support drug. 4. Blinding of participants and providers (performance bias) Subjective Outcomes High risk Providers are not stated as being blinded. Also, buprenorphine has characteristic noticeable effects 4. Support and it is likely patients were aware of allocation 5. Blinding of Outcome Assessor objective outcomes (detection bias) Low risk Although assessors were not stated as being blinded, 5. Support unlikely to affect results of urine drug test. 6. Blinding of outcome assessor subjective outcomes (detection bias) High risk Assessors not stated as being blinded. Also, participants likely aware of allocation because of 6. Support buprenorphine effects. 7. Incomplete outcome data (attrition bias) High risk No patients were reported as withdrawn. However, Table 1 shows n of 31 in placebo group and 23 in intervention group at baseline. If this represents number of patients in each arm at the beginning of the study, there were 11 lost in the placebo group and 3 in 7. Support the intervention group, which would represent

significant risk for attrition bias in such a small sample. 8. Selective reporting (reporting bias) Low risk Study protocol wasn't available, but urine drug tests and craving measurement are expected outcomes for 8. Support this type of study 9. Other bias Unclear Baseline characteristics reported as statistically equal 9. Support between groups, but no information given 10. Overall Judgement of Internal Validity (good, fair, poor) Poor 11. External Validity Poor Because baseline psychiatric and substance use comorbidities were not reported and the criteria for "severe psychiatric disorder" was not defined, it is difficult to know how applicable these results are to methamphetamine users in the US as many patients 11. Support have these comorbidities. Study description and funding Author Salehi et al Year 2015 {Salehi:2015fe} Type RCT Country Iran Author Conflict of Interest (pharmaceutical industry yes/no)? No Study funding (pharmaceutical company yes/no) No Unclear, "random allocation method" with 20 patients ending up Methods Sequence Generation in each group Allocation Concealment Unclear Patients blinded, unclear if Blinding of clinicians/therapists/assessors patients/clinicians/therapists/assessors blinded or not Design: single site/multiple Single Study duration 16 weeks Number of participants 40 Handling of dropouts (ITT or per protocol) Not stated 1. Cocaine craving brief Instruments used to assess study questionnaire (CCQ-Brief) adapted outcomes for meth 2. UDS every 2 weeks Men ages 18-40 referred to Participants Source Population addiction treatment center.

Inclusion Criteria Inclusion criteria not stated Excluded severe mood disorder A1:AO4 not defined), suicidal thoughts, psychosis, unstable medical conditions (not defined), and intolerable complications from medications or drug use (not Exclusion Criteria defined) Sex (% male/female) 0 Age (mean, SD) 31.8 (5.0) and 29.6 (5.5) Ethnicity (%white, % African American, % other) NR Employment Status NR Frequency of MA use NR Years of MA use NR Route (injection, smoking, nasal, oral) NR Comorbid drug disorders (% with comorbid drug disorders) NR Comorbid disorders (% with comorbid psychiatric disorders) NR Name of drug buprenorphine Dose 6mg Control Sublingual placebo visually similar Adherence Not reported, unclear if measured Adjunct interventions All subjects in Matrix model UDS results presented by visit. Reported that UDS significantly less Methamphetamine use as determined likely to be positive at third through Outcomes by UDS sixth visit in intervention group Self-reported meth use NR Significantly decreased p<0.001 Methamphetamine craving ANCOVA Retention in Treatment NR Number of patients who finished study 40 Reason for drop outs NR Clinical Global Impression score NR Psychotic symptoms NR Anxiety symptom severity NR Depression symptom severity NR Cocaine use by UDS NR Opiate use by UDS NR Number dropped out due to adverse events 0

Number who had serious adverse events 0

Author Mousavi et al Year 2015 {Mousavi:2015tm} 1. Random Sequence Generation (Selection Bias) Low risk 1. Support Random number tables 2. Allocation concealment (selection bias) Low risk 2. Support Randomization done by 3rd party 3. Blinding of participants and providers (performance bias) Objective Outcomes Unclear risk 3. Support Results of objective UDS not given 4. Blinding of participants and providers (performance bias) Subjective Outcomes Unclear risk Not stated if treatment providers were blinded, which could have affected elements of care leading 4. Support to lower scores. 5. Blinding of Outcome Assessor objective outcomes (detection bias) Unclear risk 5. Support Results of objective UDS not given 6. Blinding of outcome assessor subjective outcomes (detection bias) Low risk 6. Support Assessors were blinded to allocation 7. Incomplete outcome data (attrition bias) High risk Results analyzed only among participants finishing study, with 9 of 32 (28%) of participants lost to 7. Support follow-up. 8. Selective reporting (reporting bias) High risk Only craving score and side effect outcomes are reported, whereas UDS and self-report of MA use 8. Support were both planned but not reported 9. Other bias Low risk There was an apparent period effect, likely related to increased length of adjunct treatment. However, the period effect would be expected to bias toward the null, rather than for a positive effect as reported. 9. Support Similarly, any carryover effect would presumably

bias toward no treatment effect, opposite of the reported results 10. Overall Judgement of Internal Validity (good, fair, poor) Poor 11. External Validity Poor Limited applicability to outpatient US population as study done in Iran and patients with psychiatric and 11. Support other drug comorbidities excluded from study. Study description and funding Author Mousavi et al Year 2015 {Mousavi:2015tm} Type Randomized crossover Country Iran Author Conflict of Interest (pharmaceutical industry yes/no)? NR Study funding (pharmaceutical company yes/no) NR Methods Sequence Generation Tables of random numbers Randomization done by 3rd party Allocation Concealment physician Assessors of CCQ- brief score were blinded to allocation. Patients blinded to allocation. Blinding of Unclear if treatment providers patients/clinicians/therapists/assessors were blinded. Design: single site/multiple Single Study duration Two 4 week sessions Number of participants 32 Handling of dropouts (ITT or per protocol) Analyzed per protocol 1. Self report days of MA use 2. Weekly UDS 3. Side effect report 4. Cocaine craving brief Instruments used to assess study questionnaire (CCQ-Brief) outcomes adapted for meth Treatment seeking meth dependent patients referred to Participants Source Population psychiatric ER and hospital Age 18-65, DSM-IV diagnosis of methamphetamine dependency, willing/able to comply with study Inclusion Criteria and give informed consent Any serious medical condition, Exclusion Criteria current lactation pregnancy or

inadequate contraception, current SI, previous treatment with NAC, abnormal LFT's, history of asthma or seizure, dependence on any substance other than meth or nicotine, psychiatric disorders requiring mood stabilizers antidepressants or antipsychotics Sex (% male/female) 82.6% male, 17.4% female Age (mean, SD) 29.21 (4.93) Ethnicity (%white, % African American, % other) NR 26% employed in Group A, Employment Status 44.4% employed in Group B Frequency of MA use NR Years of MA use NR Route (injection, smoking, nasal, oral) NR Comorbid drug disorders (% with comorbid drug disorders) 0%, excluded from study Comorbid disorders (% with comorbid NR, patients on psychiatric drugs psychiatric disorders) excluded from study Name of drug NAC Dose 1200mg Placebo controlled crossover study, given in same packaging as Control intervention Measured by review of drug Adherence blister packets Matrix model 60 minute once a Adjunct interventions week group sessions Methamphetamine use as determined Outcomes by UDS NR Self-reported meth use NR At end of first 4 weeks Intervention group 3.3 (1.1), placebo 5.9 (1.0). At end of second 4 week session intervention group 3.2 (0.8) placebo 4.5 (1.8). Significantly improved for intervention by Methamphetamine craving ANOVA p<0.001 Retention in Treatment NR Number of patients who finished study 23 Reason for drop outs All non-compliance Clinical Global Impression score NR Psychotic symptoms NR

Anxiety symptom severity NR Depression symptom severity NR Cocaine use by UDS NR Opiate use by UDS NR Number dropped out due to adverse events 0 Number who had serious adverse events 0

Author Sulaiman et al Year 2013 {Sulaiman:2013hi} 1. Random Sequence Generation (Selection Bias) Low risk 1. Support Computerized randomization in blocks of 4 2. Allocation concealment (selection bias) Low risk Randomization done by independent person and randomization code stored in an envelope accessible only by principle investigator in case of serious adverse events. It was not stated whether the code was accessed during the study for this purpose, but no serious adverse events were reported and thus 2. Support unlikely to have occurred. 3. Blinding of participants and providers (performance bias) Objective Outcomes High risk All subjects underwent 2 week detoxification treatment with aripiprazole prior to study and thus 3. Support likely could tell they were in active treatment group. 4. Blinding of participants and providers (performance bias) Subjective Outcomes High risk All subjects underwent 2 week detoxification treatment with aripiprazole prior to study and thus 4. Support likely could tell they were in active treatment group. 5. Blinding of Outcome Assessor objective outcomes (detection bias) Low risk 5. Support Assessors stated as blinded to allocation 6. Blinding of outcome assessor subjective outcomes (detection bias) Low risk 6. Support Assessors blinded to allocation 7. Incomplete outcome data (attrition bias) High risk

Number and reasons for attrition not given. Moreover, the statistical analysis used would be expected to bias towards the null by imputing 7. Support random effects for missing values. 8. Selective reporting (reporting bias) Low risk All stated and expected outcomes for this type of 8. Support study reported 9. Other bias Low risk 9. Support No other obvious source of bias 10. Overall Judgement of Internal Validity (good, fair, poor) Poor 11. External Validity Poor Unclear if results would hold in users of MA who 11. Support do not have psychotic symptoms. Study description and funding Author Sulaiman et al Year 2013 {Sulaiman:2013hi} Type RCT Country Malaysia Author Conflict of Interest (pharmaceutical industry yes/no)? No Study funding (pharmaceutical company yes/no) NR Computer generated Methods Sequence Generation randomization in blocks of 4. Assignment done by independent person. Randomization list kept in sealed envelope accessible only to primary investigator in case of Allocation Concealment adverse events. Patients and assessors were Blinding of blinded. Not stated if treatment patients/clinicians/therapists/assessors providers were blinded. Design: single site/multiple Single Study duration 8 weeks Number of participants 49 ITT, all subjects randomized included in analysis, analysis Handling of dropouts (ITT or per done by GEE with random protocol) assumption UDS on days 7,14,28,42,56, Brief Substance Craving Scale BSCA, Instruments used to assess study CGI, Positive and Negative outcomes Symptoms Scale PANSS

Participants in a previous 2 week open label trial of aripiprazole 10mg recruited from urban Participants Source Population hospital clinic setting age 18-60, DSM-IV diagnosis MA dependence, MA use at least 1/wk for previous 3 months, h/o Inclusion Criteria psychotic symptoms no other DSM-IV Axis 1 disorders or other substance use Exclusion Criteria disorders Sex (% male/female) 95% male Age (mean, SD) T 35.5 (8.5), C 32.9 (8.4) Ethnicity (%white, % African 65% Malay, 24% Chinese, 11% American, % other) Indian Employment Status 81% employed full time At least weekly by inclusion Frequency of MA use criteria Years of MA use T 5.5 (4.8), C 4.8 (3.6) injection NR, smoking 57%, nasal Route (injection, smoking, nasal, oral) 32%, oral 11%) Comorbid drug disorders (% with comorbid drug disorders) Excluded from study Comorbid disorders (% with comorbid psychiatric disorders) Excluded from study Name of drug aripiprazole Dose 5-10mg Control Placebo Adherence NR No behavioral treatments. Some additional medication treatments including lorazepam, zolpidem Adjunct interventions and escitalopram Methamphetamine use as determined No significant difference (p 0.173 Outcomes by UDS GEE) Self-reported meth use NR BSCS significantly decreased in T Methamphetamine craving group (p 0.015 MMRM) Treatment arm 48.7 days (4.0), Placebo arm 37.1 (5.0) p<0.05 Retention in Treatment (Kaplan Meier) Number of drop outs not reported directly. Visual estimation from Kaplan-Meier curve shows a survival of about 0.45 for placebo Number of patients who finished study group and 0.85 for intervention

group which gives a total of 12 drop outs from 37 total = 32% Reason for drop outs NR CGI improved in treatment arm (p Clinical Global Impression score 0.014 MMRM) No difference in PANSS (p 0.032 Psychotic symptoms MMRM) Anxiety symptom severity NR Depression symptom severity NR Cocaine use by UDS NR Opiate use by UDS NR Number dropped out due to adverse events NR Number who had serious adverse events 0

Author Coffin et al Year 2013 {Coffin:2013fl} 1. Random Sequence Generation (Selection Bias) Low risk 1:1 random allocation sequence in blocks of 4 1. Support generated in SAS 2. Allocation concealment (selection bias) Low risk MEMS medication caps numbered sequentially, conceivably possible to guess allocation by blocks of 4 if medication effects were apparent, however given lack of evidence for patient unblinding this 2. Support is considered unlikely 3. Blinding of participants and providers (performance bias) Objective Outcomes Low risk "At study completion, participants were asked to guess their assignment. There was no evidence of unblinding: 17 (53%) in the aripiprazole arm and 15 (47%) in the placebo arm guessed correctly 3. Support (p=0.36)." 4. Blinding of participants and providers (performance bias) Subjective Outcomes Low risk "At study completion, participants were asked to guess their assignment. There was no evidence of unblinding: 17 (53%) in the aripiprazole arm and 15 (47%) in the placebo arm guessed correctly 4. Support (p=0.36)."

5. Blinding of Outcome Assessor objective outcomes (detection bias) Low risk 5. Support Unlikely to affect results of urine screens 6. Blinding of outcome assessor subjective outcomes (detection bias) Low risk Audio computer assisted self interview used to 6. Support collect study data 7. Incomplete outcome data (attrition bias) High risk There was an imbalance in drop outs by group: 10 dropped out in intervention arm, 5 in placebo arm. 7. Support The reasons for drop outs were not known. 8. Selective reporting (reporting bias) Low risk All stated and expected outcomes for this type of 8. Support study reported 9. Other bias Low risk 9. Support no other obvious source of bias 10. Overall Judgement of Internal Validity (good, fair, poor) Fair 11. External Validity Fair Excluded patients with comorbid drug or 11. Support psychiatric disorders. Study description and funding Author Coffin et al Year 2013 {Coffin:2013fl} Type RCT Country USA Author Conflict of Interest (pharmaceutical industry yes/no)? No Study funding (pharmaceutical company yes/no) No. NIDA. 1:1 random allocation sequence Methods Sequence Generation in blocks of 4 generated in SAS MEMS cap bottles numbered sequentially to correspond with allocation sequence. Allocation sequence available only to Allocation Concealment pharmacist and statistician. Patients and providers blinded Blinding of with medication and placebo patients/clinicians/therapists/assessors prepared by off-site pharmacist. Design: single site/multiple single Study duration 12 weeks Number of participants 90

Handling of dropouts (ITT or per ITT, all subjects randomized protocol) included in analysis weekly UDS, CES-D depression scale, Visual Analog Scale for meth cravings, Severity of Instruments used to assess study Dependence Scale for self outcomes reported MA use San Francisco general Participants Source Population community DSM-IV MA dependence, age 18-60, MA positive urine at screening, no acute medical or psychiatric illness, no significant baseline laboratory Inclusion Criteria abnormalities No current depression or bipolar disorder, psychiatric medication within 4 weeks, Exclusion Criteria CD4<200 Sex (% male/female) 87.8% male Age (mean, SD) 38.7 yrs Ethnicity (%white, % African 50%, 18.9% African American, American, % other) 16.7% Latino, 14% other Employment Status 14.4% full time Frequency of MA use 69% used MA 3-7 days weekly Years of MA use NR Route (injection, smoking, nasal, oral) 44.4% injection Comorbid drug disorders (% with comorbid drug disorders) excluded from study excluded from study, although 6 participants revealed Comorbid disorders (% with comorbid psychiatric disorder they had psychiatric disorders) not disclosed after the study Name of drug aripiprazole Dose 20mg Control placebo Evaluated by Medication Event Monitoring System and self- report. By MEMS 42%, by Adherence self-report 74%. Weekly counseling with clinical psychologist, CBT and Adjunct interventions MI. Methamphetamine use as determined Positive urines RR 0.88 (0.66- Outcomes by UDS 1.19, p=0.41)

SDS score decrease not significant between groups Self-reported meth use p=0.96 VAS score decrease not Methamphetamine craving significant p=0.38 No completed weekly substance use counseling sessions: intervention 76%, Retention in Treatment placebo 80%, p=0.11 75 (35 in treatment arm, 40 in Number of patients who finished study placebo) = 83% Reason for drop outs NR Clinical Global Impression score NR Psychotic symptoms NR Anxiety symptom severity NR CES-D coefficient 1.47 (-.282- Depression symptom severity 5.76) p=0.5 (GEE) Cocaine use by UDS NR Opiate use by UDS NR Number dropped out due to adverse events 0 Number who had serious adverse events 6

Author Brown and Gabrielson Year 2012 {Brown:2012dt} 1. Random Sequence Generation (Selection Bias) Unclear risk 1. Support Stated as "randomized" without further explanation 2. Allocation concealment (selection bias) Unclear risk 2. Support Concealment procedure not described 3. Blinding of participants and providers (performance bias) Objective Outcomes Low risk 3. Support Both patients and staff stated as being blinded. 4. Blinding of participants and providers (performance bias) Subjective Outcomes Low risk 4. Support Both patients and staff stated as being blinded 5. Blinding of Outcome Assessor objective outcomes (detection bias) Low risk 5. Support Both patients and staff stated as being blinded

6. Blinding of outcome assessor subjective outcomes (detection bias) Low risk 6. Support Both patients and staff stated as being blinded 7. Incomplete outcome data (attrition bias) High risk 12 out of 60 of randomized participants were lost to follow up immediately following randomization and were not included in analysis. Also, placebo 7. Support arm had only 14% completion rate. 8. Selective reporting (reporting bias) Low risk 8. Support All stated and expected outcomes reported 9. Other bias High risk Baseline characteristics significantly different between groups by age and years of meth use. Also, 12 or 20% of the original 60 randomized were not included in analysis and were not included in Table 1 of baseline characteristics. High risk that the groups could have become unbalanced in some 9. Support other way. 10. Overall Judgement of Internal Validity (good, fair, poor) Poor 11. External Validity Poor Unclear if results would be the same if population 11. Support not limited to bipolar depression or MDD. Study description and funding Author Brown and Gabrielson Year 2012 {Brown:2012dt} Type RCT Country USA Author Conflict of Interest (pharmaceutical industry yes/no)? Yes. Sunovion. Study funding (pharmaceutical No. Stanley Medical Research company yes/no) Institute. Methods Sequence Generation Not described. "Randomized" Allocation Concealment Not described Patients and all staff with patient Blinding of contact blinded to treatment patients/clinicians/therapists/assessors group. Design: single site/multiple single Study duration 12 weeks Number of participants 60 Handling of dropouts (ITT or per Analyzed by group at week 1 protocol) after excluding patients who did

not return for at least one visit after randomization twice weekly UDS, Inventory of Instruments used to assess study Depressive Symptomatology outcomes Clinician Version IDS-C Participants Source Population Not described age 18-70, currently depressed with bipolar I/II/NOS, MDD with symptoms of at least 4 weeks, meth dependence with MA use in Inclusion Criteria the 14 days prior psychotropic medication changes 14 days prior, pregnant or nursing, current citocoline, active SI/HI with plan and intent, cognitive impairment interfering with informed consent, incarceration, current severe or life threatening medical Exclusion Criteria conditions Sex (% male/female) male 54% 41.6 (9.9) in treatment group, Age (mean, SD) 34.0 (7.3) placebo 77% white, 0% African Ethnicity (%white, % African American, 19% Hispanic, 4% American, % other) other Employment Status NR Days used in last 14 days: 8(4.4) in intervention group, 6(3.5) in Frequency of MA use placebo 15.7 years (9.8) intervention, 9.1 Years of MA use (8.0) placebo Smoked 60.7% intervention, 75% placebo; oral 3 (10.7%) intervention, 1 (5%) placebo; IV 4 (14.3%) intervention, 2 (10%) placebo; multiple 4 (14.3%) Route (injection, smoking, nasal, oral) intervention, 2 (10%) placebo Comorbid drug disorders (% with comorbid drug disorders) NR Comorbid disorders (% with comorbid All had depressed bipolar or psychiatric disorders) MDD by inclusion criteria. Name of drug citicoline Dose 2000mg Control placebo Adherence NR

Adjunct interventions NR No significant difference in changes in meth use, at exit 60% positive in intervention and 55% Methamphetamine use as determined in placebo p=0.23. RR calculated Outcomes by UDS from published numbers = 1.09 Stated as decreased in both Self-reported meth use groups but no numbers given Methamphetamine craving NR Longer survival in treatment in citicoline group p = 0.02 Kaplan- Retention in Treatment Meier "Completion rates" stated as 41% in intervention, 14% placebo p=0.02. Note that adding up n's given for reason for drop outs adds up to 24 drop outs in placebo arm and 20 in Number of patients who finished study intervention arm. 19 lost to follow up, 2 moved out of area, 1 entered inpatient drug rehab, 1 for transportation problems, 1 for adverse event. In the intervention group 14 lost to follow up, 1 moved out of area, 1 entered inpatient drug rehab, 1 for transportation problems, 1 for stressors at home, and 1 on Reason for drop outs advice of probation officer Clinical Global Impression score NR Psychotic symptoms NR Anxiety symptom severity NR Baseline to exit change in IDS-C scores "significantly greater" in intervention compared to placebo (38.8 to 26.2 citicoline, 37.8 to 33.1 placebo) F(1.31)=4.2 Depression symptom severity p=0.05 Cocaine use by UDS NR Opiate use by UDS NR Number dropped out due to adverse events 1 Number who had serious adverse events 1

Author Elkashef et al Year 2012 {Elkashef:2012he} 1. Random Sequence Generation (Selection Bias) Low risk Adaptive randomization with no significant baseline 1. Support differences 2. Allocation concealment (selection bias) Unclear risk 2. Support Not described 3. Blinding of participants and providers (performance bias) Objective Outcomes Unclear risk Blinding not described and possible that typical effects of topiramate could have resulted in 3. Support unblinding 4. Blinding of participants and providers (performance bias) Subjective Outcomes Unclear risk Blinding not described and possible that typical effects of topiramate could have resulted in 4. Support unblinding 5. Blinding of Outcome Assessor objective outcomes (detection bias) Low risk Blinding not described, but unlikely that UDS 5. Support would be affected 6. Blinding of outcome assessor subjective outcomes (detection bias) Unclear risk 6. Support Blinding not described 7. Incomplete outcome data (attrition bias) High risk High rate of attrition could have obscured any true 7. Support effects of the intervention. 8. Selective reporting (reporting bias) Low risk All stated and expected outcomes for this type of 8. Support study reported 9. Other bias Low risk 9. Support No other obvious source of bias 10. Overall Judgement of Internal Validity (good, fair, poor) Fair 11. External Validity Good Did not report on baseline comorbid drug and psychiatric disorders, but importantly did not 11. Support exclude them from study.

Study description and funding Author Elkashef et al Year 2012 {Elkashef:2012he} Type RCT Country USA Author Conflict of Interest (pharmaceutical industry yes/no)? Yes Study funding (pharmaceutical company yes/no) No adaptive randomization in 1:1 ratio for intervention:placebo also balanced for site and positive or negative MA use within 7 days Methods Sequence Generation before randomization Allocation Concealment Not described Blinding of Stated as "double blind", no patients/clinicians/therapists/assessors further description given Design: single site/multiple Multiple (8) Study duration 13 weeks Number of participants 140 Handling of dropouts (ITT or per ITT, no randomized participants protocol) excluded from analysis UDS 3/wk, CGI, BSCS, Addiction Severity Index-Lite Instruments used to assess study (ASI-Lite), Montgomery outcomes Depression Rating Scale Patients at multiple substance Participants Source Population abuse treatment centers DSM-IV diagnosed MA dependence, 18 years or older, at least 1 baseline positive MA urine screens, at least 4 urine specimens given during intake/baseline Inclusion Criteria assessment serious medical illness, psychiatric conditions requiring ongoing medication, pregnancy or lactation, nephrolithiasis or renal impairment, court-mandated drug Exclusion Criteria abuse treatment 63.6% male (59.4% intervention, Sex (% male/female) 63.6% placebo) 38 (8.62, 38.4 intervention 37 Age (mean, SD) placebo

82.9% white overall (85.5% intervention, 80.3% placebo), 2.1% African American overall (3 in placebo, 0 in intervention), 1.4% Asian (1 each), 12.9% other Ethnicity (%white, % African overall (13.2% intervention, American, % other) 14.1% placebo) 43.6% full time (46.4% Employment Status intervention, 40.9% placebo) self-report of MA use in last 30 days mean 21.3 (8.39) overall, 21.2 in intervention, 21.4 in Frequency of MA use placebo Years of MA use NR Route (injection, smoking, nasal, oral) NR Some participants with alcohol dependence as this was used to stratify post-hoc analysis, Comorbid drug disorders (% with however number was not comorbid drug disorders) reported. Comorbid disorders (% with comorbid psychiatric disorders) NR Name of drug topiramate Dose 200mg Control placebo By pill count, 69.8% for intervention, 67.4% in placebo, no Adherence significant difference. Weekly brief behavioral compliance enhancement Adjunct interventions treatment Primary outcome of % of subjects with negative week UDS in weeks 6-12 showed no significant difference by GEE p=0.13, measured by median quantitative MA level on UDS, more in Methamphetamine use as determined intervention reduced use by 25% Outcomes by UDS or more (64.2% vs 42.3% p=0.03) 50% or more reduction in use by self-report greater in treatment Self-reported meth use arm (37.9% vs 14.3% p=0.003) Non-significant trend to reduced Methamphetamine craving cravings by BSCS p=0.09

39 in intervention and 38 in placebo completed through week Retention in Treatment 13, p=0.72 77 (55%), 39 in intervention arm Number of patients who finished study and 38 in placebo Most common reason was failure to return to the clinic (19 in intervention, 18 placebo), 2 in each group dropped out because of reported side effects, medical reasons unrelated to study (1 in intervention), subject requested discontinuation (4 in intervention, 9 in placebo), 1 in each group moved from area, 2 in placebo group incarcerated, 1 in intervention group terminated by physician due to illness, administrative discharge (2 in Reason for drop outs intervention, 1 in placebo) Improvement in CGI-O in Clinical Global Impression score intervention arm p=0.03 Psychotic symptoms NR Anxiety symptom severity NR No significant change in Montgomery Depression Rating Depression symptom severity Scale by group Cocaine use by UDS NR Opiate use by UDS NR Number dropped out due to adverse events 4 (2 in each group) 13, 1 classified as possibly and one as probably related to Number who had serious adverse medication of which both were in events placebo group

Author Tiihonen et al Year 2012 {Tiihonen:2012cc} 1. Random Sequence Generation (Selection Bias) Low risk Computer generated random number list in 1:1 ratio 1. Support but method for ratio not stated

2. Allocation concealment (selection bias) Low risk 2. Support Prepared by otherwise un-involved investigator 3. Blinding of participants and providers (performance bias) Objective Outcomes Low risk Regular opioid users would likely be able to detect if naltrexone active upon using an opioid after implantation of active drug. However, UDS results 3. Support not likely to be affected. 4. Blinding of participants and providers (performance bias) Subjective Outcomes High risk Regular opioid users would likely be able to detect if naltrexone active upon using an opioid after implantation of active drug. Report of symptoms and assessment by providers could be affected by 4. Support this knowledge. 5. Blinding of Outcome Assessor objective outcomes (detection bias) Low risk Likely detectable effects of active drug by participants, however UDS results unlikely to be 5. Support affected 6. Blinding of outcome assessor subjective outcomes (detection bias) High risk Likely detectable effects of active drug by participants. Assessors not stated but assumed to be treatment providers with clinical contact with 6. Support participants 7. Incomplete outcome data (attrition bias) High risk High attrition in both study groups with 7. Support significantly more lost in placebo arm. 8. Selective reporting (reporting bias) Low risk 8. Support All stated and expected outcomes reported 9. Other bias Low risk 9. Support no other obvious source of bias 10. Overall Judgement of Internal Validity (good, fair, poor) Fair 11. External Validity Poor Unclear what significance this has for mainly MA users as study primary outcome (decrease in opioid and amphetamine positive UDS) driven by positive 11. Support results for opioid decrease.

Study description and funding Author Tiihonen et al Year 2012 {Tiihonen:2012cc} Type RCT Country Russia Author Conflict of Interest (pharmaceutical industry yes/no)? Yes Study funding (pharmaceutical company yes/no) No "Computer generated random number list" in 1:1 ratio, not stated what method used to Methods Sequence Generation generate ratio prepared by outside investigator with no other involvement in the Allocation Concealment trial "All individuals involved with the clinical phase of the trial were blind to the intervention." Blinding of Medication labeled according to patients/clinicians/therapists/assessors randomization list Design: single site/multiple single Study duration 10 weeks Number of participants 100 Handling of dropouts (ITT or per ITT, missing urine samples protocol) classified as positive UDS 1/wk, Addiction Severity Index, CGI, visual analog scales Instruments used to assess study of craving for opioids and outcomes amphetamine Participants Source Population NR DSM-IV diagnosis of both amphetamine and opioid dependence for at least 1 year, age 18-50, high school or above, negative UDS and etoh breath test, no current psychotropic medications, one relative willing to participate in treatment monitoring, stable address, home telephone number, able to give informed consent, negative pregnancy test and adequate Inclusion Criteria contraception

clinically significant cognitive impairment, schizophrenia, paranoid disorder, bipolar, seizure disorder, advance neurological, CV, renal or hepatic disease, active TB, current febrile illness, AIDS, significant laboratory abnormality, pregnancy, pending legal charges with potential incarceration, participation in another study, treatment in Exclusion Criteria another substance abuse program 8% female intervention, 14$% Sex (% male/female) female placebo 29.3 (4.38) placebo, 28.0 (4.1) Age (mean, SD) intervention Ethnicity (%white, % African American, % other) NR Employment Status NR days per month 24.3 (14.35) Frequency of MA use placebo, 27.4 (13.5) intervention 5.6 (2.62) placebo, 5.6 (3.11) Years of MA use intervention Route (injection, smoking, nasal, oral) NR All with opioid dependence by inclusion criteria, alcohol use g/day 6.8 (10.8) placebo and 8.2 (10.11) intervention, 30% with Comorbid drug disorders (% with MJ in intervention group, 26% in comorbid drug disorders) placebo Comorbid disorders (% with comorbid Unclear, none on psychotropic psychiatric disorders) medications by exclusion criteria Name of drug Naltrexone implant Dose 1000mg Control Placebo implant NR, assume 100% for implant although some patients have been known to remove the implant on Adherence their own Two psychiatrists "provided them with psychological support and Adjunct interventions advice" at unclear intervals Non-significant, amphetamine free urine samples 40% Methamphetamine use as determined intervention 24% placebo Outcomes by UDS p=0.009

Self-reported meth use NR No significant change, numbers Methamphetamine craving not reported At week 10 52% in intervention, Retention in Treatment 28% in placebo, p=0.01 Number of patients who finished study 40 (26 intervention, 14 placebo) Reason for drop outs NR Much or very much improved 56% in intervention, 14% in Clinical Global Impression score placebo p<0.001 Psychotic symptoms NR Anxiety symptom severity NR Depression symptom severity NR Cocaine use by UDS NR Heroin free UDS 52% in intervention vs 20% placebo Opiate use by UDS p<0.001 Number dropped out due to adverse events NR Number who had serious adverse events 0

Author Ling et al Year 2012 {Ling:2012hy} 1. Random Sequence Generation (Selection Bias) Low risk 1. Support urn randomization 2. Allocation concealment (selection bias) Low risk 2. Support Done by pharmacy 3. Blinding of participants and providers (performance bias) Objective Outcomes Low risk Blinding done, low risk of unblinding given mild 3. Support effects of study drug 4. Blinding of participants and providers (performance bias) Subjective Outcomes Low risk Mild effects of study drugs likely not detectable. Also, at end of study surveys at one site found that twice as many participants believed they had received 4. Support active medication.

5. Blinding of Outcome Assessor objective outcomes (detection bias) Low risk 5. Support UDS unlikely to be affected 6. Blinding of outcome assessor subjective outcomes (detection bias) Low risk Unlikely that mild effects of study drugs would result 6. Support in unblinding 7. Incomplete outcome data (attrition bias) High risk 7. Support High rate of attrition in both groups 8. Selective reporting (reporting bias) Low risk 8. Support All stated and expected outcomes reported 9. Other bias Low risk 9. Support No other obvious source of bias 10. Overall Judgement of Internal Validity (good, fair, poor) Good 11. External Validity Fair Unclear if results might be different in patients with 11. Support polydrug dependence. Study description and funding Author Ling et al Year 2012 {Ling:2012hy} Type RCT Country USA Author Conflict of Interest (pharmaceutical industry yes/no)? No Study funding (pharmaceutical company yes/no) Yes Urn randomization balanced on gender, and severity of meth use Methods Sequence Generation (>10 days in prior 30 or less) Unclear, "randomization assignment was faxed to the university pharmacy", unclear if assignment was done before faxing Allocation Concealment or by pharmacy Blinding of patients/clinicians/therapists/assessors Stated as double blind Design: single site/multiple Multiple (3) Study duration 108 day Number of participants 120 Handling of dropouts (ITT or per Modified ITT, patients lost to protocol) follow-up immediately after

randomization were not included in analysis Addiction Severity Index (ASI), Instruments used to assess study UDS weekly, Brief Symptom outcomes Craving Scale (BSCS) Participants Source Population Treatment seeking patients Age 18 or older, MA abuse or dependence per DSM-IV, treatment seeking, reporting MA use on 4 of the last 30 days, not pregnant or lactating and willing to use birth Inclusion Criteria control Current dependence on any psychoactive substance other than MA, alcohol, nicotine or MJ, needing alcohol detox, disorders with seizures/syncope/dementia, SI, uncontrolled HTN, significant heart disease, clinically significant abnormal laboratory values, benzo use with 15 days, AIDS, active TB, allergy to study medications, treatment with PROMETA in the Exclusion Criteria prior 12 months Male 80% intervention, 75% Sex (% male/female) control 40.77 (7.46) intervention, 35.98 Age (mean, SD) (8.75) control White 65.4% intervention, 55.4% control; Hispanic 21.8% Ethnicity (%white, % African intervention, 37.4% control; Black American, % other) 9.1% intervention, 5.4% control Full time 58.2% intervention, Employment Status 53.6% control Mean no. of days used in past 30 days 17.82 (9.90) intervention, Frequency of MA use 17.13 (9.45) control Mean 10.84 (8.18) intervention, Years of MA use 9.66 (6.60) control Route (injection, smoking, nasal, oral) NR Comorbid drug disorders (% with comorbid drug disorders) NR Comorbid disorders (% with comorbid psychiatric disorders) NR

PROMETA ™ Protocol: flumazenil, gabapentin and Name of drug hydroxyzine flumazenil 2mg (days 1, 2, 3, 22, 23), gabapentin 1200mg (to day 40), and hydroxyzine 50mg (to day Dose 10) saline, placebo, all participants including intervention group Control received hydroxyzine 58.9% in intervention group received all 5 infusions vs 69.1% of control. By pill count gabapentin 19.31 days (out of 40) intervention Adherence vs 20.88 days control, p-0.51. Adjunct interventions Weekly CBT No significant difference in mean Methamphetamine use as determined proportion of MA negative UDS Outcomes by UDS from screening to study end p=0.28 Mean use in last 30 days: 5.04 days intervention, 3.96 days control Self-reported meth use (p=0.64) No significant difference. At end of study 2.2 intervention and 2.4 Methamphetamine craving control on 0-4 visual analog scale. 57.21 days intervention, 74.04 days control, not significant when Retention in Treatment covaried by age (p=0.30) Retained through day 108, 18 Number of patients who finished (32.1%) intervention, 26 (47.3%) study control Intervention group: inability to comply with study protocol (4), missed 3 consecutive study visit (21), medical/psychological concern (4), withdrew consent (2), missed 14 scheduled visits (1), in controlled environment (2), lack of transportation (2), unable to locate/contact (1). Control group: Inability to comply with study protocol (2), missed 3 consecutive study visits (15), withdrew consent (3), new job (1), did not attend 14 Reason for drop outs scheduled visits (1), unable to reach

(3), moved (1), dropped out (1), unknown (2) Clinical Global Impression score NR Psychotic symptoms NR Anxiety symptom severity NR Depression symptom severity NR Cocaine use by UDS NR Opiate use by UDS NR Number dropped out due to adverse events 0 Number who had serious adverse events 4

Author Colfax et al Year 2011 {Colfax:2011ix} 1. Random Sequence Generation (Selection Bias) Low risk 1. Support 1:1 random allocation sequence in blocks of 4 2. Allocation concealment (selection bias) Low risk Only pharmacy and statistician had access to 2. Support allocation and had no patient contact 3. Blinding of participants and providers (performance bias) Objective Outcomes Low risk Blinding done, low risk of unblinding given mild effects of mirtazapine, post-study survey after unblinding found statistically similar numbers of participants guessed they were on active 3. Support medication in both arms 4. Blinding of participants and providers (performance bias) Subjective Outcomes Low risk 4. Support Blinding done, low risk of unblinding. 5. Blinding of Outcome Assessor objective outcomes (detection bias) Low risk 5. Support UDS unlikely to be affected 6. Blinding of outcome assessor subjective outcomes (detection bias) Low risk Assessment done by computer assisted audio self- 6. Support interview 7. Incomplete outcome data (attrition bias) Low risk 7. Support High retention in both arms of study

8. Selective reporting (reporting bias) Low risk 8. Support All stated and expected outcomes reported 9. Other bias Low risk 9. Support No other obvious source of bias 10. Overall Judgement of Internal Validity (good, fair, poor) Good 11. External Validity Poor Study done only in MSM and reported very high retention, indicating that this population likely systematically different than general MA using 11. Support population in the US Study description and funding Author Colfax et al Year 2011 {Colfax:2011ix} Type RCT Country USA Author Conflict of Interest (pharmaceutical industry yes/no)? No Study funding (pharmaceutical company yes/no) No 1:1 random allocations sequence using fixed block size Methods Sequence Generation of 4 Medications prepared by off- site pharmacist. Allocation known only to pharmacist and statistician who had no patient contact. No evidence of unmasking, at end of study 50% in control guessed correctly vs Allocation Concealment 56% intervention, p=0.79 Double blind, outcomes Blinding of assessed by UDS or computer patients/clinicians/therapists/assessors assisted self report. Design: single site/multiple single Study duration 12 weeks Number of participants 60 Handling of dropouts (ITT or per ITT, all subjects randomized protocol) included in analysis Instruments used to assess study UDS; audio computer assisted outcomes self interview for CES-D. STD/HIV clinics, bars, and Participants Source Population community organizations DSM-IV MA dependence, Inclusion Criteria interest in treatment, age 18-60,

self-reported anal sex with men in past 3 months while using MA, positive MA urine, no acute illness, no laboratory abnormalities current major depression, antidepressant use in the past 4 Exclusion Criteria weeks, CD4 count below 200 Sex (% male/female) 100% male 40.1 (10.1) intervention, 40.9 Age (mean, SD) (8.0) control, 40.5 (9.0) overall 62% white, 18% African Ethnicity (%white, % African American, 12% Latino, 8% American, % other) other Full time 10% intervention, Employment Status 27% control, 18% overall 7 d/wk 20% intervention, 13% control, 17% overall; 3-6/wk 43% intervention, 43% control, 43% overall, <3/wk 37% intervention, 43% control, 40% Frequency of MA use overall Years of MA use NR Injection 50% intervention, 40% control, 45% overall; Rectal 30% intervention, 30% control, 30% overall; Snorted 40% in all groups; Smoked 83% intervention, 87% control, Route (injection, smoking, nasal, oral) 85% overall; Oral 17% for all Comorbid drug disorders (% with comorbid drug disorders) NR None on medications. CES-D Comorbid disorders (% with comorbid scores of 16.6 intervention, 16.8 psychiatric disorders) control, 16.7 overall. Name of drug mirtazapine Dose 30mg Control matched placebo in gel capsules 48.5% for MEMS (48.3% intervention, 48.7% control p=0.82), 74.7% by self-report, no difference between groups Adherence p=0.92 30 minute weekly substance use Adjunct interventions counseling using CBT and MI

MA positive urine tests RR 0.57 (0.35-0.93) p=0.02, decreased Methamphetamine use as determined in intervention 73% to 44%, Outcomes by UDS placebo 67% to 63% Self-reported meth use NR Methamphetamine craving NR 113/240 (94.2%) visits completed intervention, Retention in Treatment 114/240 (95%) control, p>0.99 56 (93%), 28 (93%) in Number of patients who finished study intervention, 28 (93%) control Reason for drop outs NR Clinical Global Impression score NR 1 participant with MA induced Psychotic symptoms psychosis Anxiety symptom severity NR Mean CES-D score change -3.6 overall, no difference between Depression symptom severity groups p=0.57 Cocaine use by UDS NR Opiate use by UDS NR Number dropped out due to adverse events 0 Number who had serious adverse events 2

Author Grant et al Year 2010 {Grant:2010ja} 1. Random Sequence Generation (Selection Bias) Unclear risk 1. Support Method of randomization not stated 2. Allocation concealment (selection bias) Unclear risk 2. Support Concealment is not described 3. Blinding of participants and providers (performance bias) Objective Outcomes Unclear risk 3. Support Blinding not described 4. Blinding of participants and providers (performance bias) Subjective Outcomes Unclear risk 4. Support Blinding not described 5. Blinding of Outcome Assessor objective outcomes (detection bias) Unclear risk 5. Support Blinding not described

6. Blinding of outcome assessor subjective outcomes (detection bias) Unclear risk 6. Support Blinding not described 7. Incomplete outcome data (attrition bias) High risk High attrition and not all randomized 7. Support participants included in analysis. 8. Selective reporting (reporting bias) Low risk 8. Support All expected main results reported 9. Other bias High risk Significantly underpowered to detect 9. Support a difference between groups 10. Overall Judgement of Internal Validity (good, fair, poor) Poor 11. External Validity Poor Unclear what relevance this has for 11. Support general population of MA users Study description and funding Author Grant et al Year 2010 {Grant:2010ja} Type RCT Country USA Author Conflict of Interest (pharmaceutical industry yes/no)? Yes Study funding (pharmaceutical company yes/no) No Methods Sequence Generation "randomly assigned in a 1:1 fashion" Allocation Concealment Not described Blinding of Stated as double blind but procedure patients/clinicians/therapists/assessors not described Design: single site/multiple single Study duration 8 weeks Number of participants 31 "Only subjects who returned for at least one visit after starting medication were included". 31 of 39 randomized subjects included in Handling of dropouts (ITT or per analysis. Missing data analyzed by protocol) last observation carried forward Penn Craving Scale, UDS, self report, CGI, HAM-D, HAM-A, Sheehan Disability Scale, Quality of Life Instruments used to assess study Inventory. Frequency of UDS not outcomes specified

recruited via newspaper Participants Source Population advertisements age 18-65, DMS-IV amphetamine dependence, MA primary form of Inclusion Criteria amphetamine Unstable medical illness, current pregnancy or inadequate contraception, thoughts of suicide, history of bipolar/dementia/psychotic disorder, previous treatment with NAC or naltrexone, abnormal LFT's, Exclusion Criteria current opiate use 57.1% male intervention, 82.4% Sex (% male/female) control 37.2(8.2) intervention, 36.1 (6.6) Age (mean, SD) control 100% Caucasian intervention, 94.1% Ethnicity (%white, % African control, 5.9% African American American, % other) control Employment Status NR Days used in past 2 weeks 8.08 (4.9) Frequency of MA use intervention, 6.29 (4.6) control NR. Did report age at first using MA 23.4 (9.2) intervention, 25.0 (6.7) Years of MA use control Route (injection, smoking, nasal, oral) NR Comorbid drug disorders (% with comorbid drug disorders) 92.9% intervention, 58.5% control Comorbid disorders (% with comorbid psychiatric disorders) 42.9% intervention, 75% control Name of drug NAC plus naltrexone NAC escalating to 2400mg/d, Dose naltrexone escalating to 200mg/d Control placebo Adherence NR Adjunct interventions None Percentage of positive UDS not significantly different 46.2% Methamphetamine use as determined intervention 35.3% intervention Outcomes by UDS p=0.547 Change in mean days of drug use in past 2 weeks not significantly different, -85.2% intervention vs Self-reported meth use 57.8% control, p=0.104

No significant decline in Penn Craving Scale total score -43.6% vs - Methamphetamine craving 37.7% p=0.106 No significant difference in study completion, 64.3% intervention, Retention in Treatment 47.1% control, p= 0.337 Number of patients who finished study 17 completed all five visits Reason for drop outs NR Decrease in CGI not significantly different -1.71 intervention, -1.24 Clinical Global Impression score control, p=0.498 Psychotic symptoms NR Anxiety symptom severity NR Depression symptom severity NR Cocaine use by UDS NR Opiate use by UDS NR Number dropped out due to adverse events 0 Number who had serious adverse events 0

Author Jayaram-Lindström et al Year 2008 {JayaramLindstrom:2008kx} 1. Random Sequence Generation (Selection Bias) Unclear risk Computer generated, but not specified as to what 1. Support method to achieve 1:1 ratio 2. Allocation concealment (selection bias) Low risk 2. Support Allocation known only to off-site pharmacy 3. Blinding of participants and providers (performance bias) Objective Outcomes Low risk Blinding done, low risk of unblinding given mild 3. Support effects of study drug 4. Blinding of participants and providers (performance bias) Subjective Outcomes Low risk Blinding done, low risk of unblinding given mild 4. Support effects of study drug 5. Blinding of Outcome Assessor objective outcomes (detection bias) Low risk 5. Support UDS unlikely to be affected 79

6. Blinding of outcome assessor subjective outcomes (detection bias) Low risk 6. Support Blinding done 7. Incomplete outcome data (attrition bias) High risk 7. Support High attrition rate, reasons for drop outs not given 8. Selective reporting (reporting bias) Low risk 8. Support All stated and expected outcomes reported 9. Other bias High risk 9. Support Baseline imbalance in severity of amphetamine use. 10. Overall Judgement of Internal Validity (good, fair, poor) Fair 11. External Validity Poor The majority of participants used a mixture of dextro-/levo-amphetamine, and only 16% had UDS evidence for methamphetamine. Furthermore, almost half of participants had a diagnosis of ADHD. Unclear if these results would be the same in 11. Support primarily methamphetamine using population Study description and funding Author Jayaram-Lindström et al Year 2008 {JayaramLindstrom:2008kx} Type RCT Country Sweden Author Conflict of Interest (pharmaceutical industry yes/no)? Yes Study funding (pharmaceutical company yes/no) No Computerized randomization, not Methods Sequence Generation further described Randomization conducted by Allocation Concealment university pharmacy. Blinding of patients/clinicians/therapists/assessors Stated as double blind Design: single site/multiple single Study duration 12 weeks Number of participants 80 Handling of dropouts (ITT or per All missing urine samples analyzed protocol) as positive. UDS twice weekly, Addiction Instruments used to assess study Severity Index (ASI), self report, outcomes MA craving VAS,

newspaper advertisements and Participants Source Population social workers age 20-65, DSM-IV amphetamine dependence, used amphetamine at Inclusion Criteria least 12 days in past 12 weeks Positive UDS during 2 week lead- in. DSM-IV diagnosis of other substance dependence except nicotine, h/o major psychiatric disorder, current condition requiring medication, use of an opioid in last month, current benzo use, UDS positive for other substances, serious medical disease, pregnancy Exclusion Criteria or lactation Male 77.5% intervention, 80% Sex (% male/female) control 39.3 (8.1) intervention, 39.6 (9.3) Age (mean, SD) control Ethnicity (%white, % African American, % other) NR Employment Status NR Days of use in the 12 weeks prior: Frequency of MA use 30.9 intervention, 27.3 control Years of MA use 10.42 intervention, 9.97 control IV 65% intervention, 76% control; Route (injection, smoking, nasal, oral) Oral 35% intervention, 25% control Those with DSM-IV dependence excluded from study. Days of Comorbid drug disorders (% with alcohol use in 12 weeks prior 30.9 comorbid drug disorders) intervention, 27.3 control. ADHD 47.5% intervention, 45% Comorbid disorders (% with comorbid control. Other disorders excluded psychiatric disorders) from study Name of drug naltrexone Dose 50mg Control placebo in matching blister package By urine test of beta-naltrexol 25/40 in naltrexone group had more than 8 positive out of 12 weekly tests. No difference in pill count between Adherence groups. Manual based relapse prevention Adjunct interventions therapy with licensed psychologist.

Naltrexone had significantly higher Methamphetamine use as determined number of negative UDS, 65.2% Outcomes by UDS intervention, 47.7% control, p<0.05 Significantly larger change in report of days used: 52.2% to 5.5% intervention, 38.7% to 16.1% Self-reported meth use control, p<0.05 Intervention group "had a greater Methamphetamine craving reduction in craving scores" p<0.05 72.5% in intervention, 65% in Retention in Treatment control retained to end of study Number of patients who finished study 55 (68.8%) inability to comply with weekly Reason for drop outs attendance at clinic Clinical Global Impression score NR Psychotic symptoms NR Anxiety symptom severity NR Depression symptom severity NR Cocaine use by UDS NR Opiate use by UDS NR Number dropped out due to adverse events 0 Number who had serious adverse events 0