Rates and influences of alcohol use disorder comorbidity among stimulant-primary treatment-seekers: Meta-analytic findings across eight NIDA CTN trials

The United States has seen serial pandemics of stimulant misuse. The 1980’s marked a rise in cocaine use, whereas subsequent decades saw a rampant spread in amphetamine use [1]. Estimates suggest 40 million cocaine and amphetamine users worldwide [2], and monthly prevalence of cocaine and amphetamine use in the U.S. alone of 2.4 % and 1.2%, respectively [3]. Absence of FDA-approved pharmacotherapy for stimulant misuse heightens need for effective treatments and support services. To that end, identifying rates of substance-related comorbidity—like prior or concurrent alcohol use disorders (AUDs)—may inform clinical service needs. Because problem drinking, or the prospect of its occurrence, may diminish psychosocial functioning of stimulant-misusing clients and thereby hamper treatment effectiveness, determination of AUD rates for amphetamine- and cocaine-misusing treatment-seekers is salient. By comparing psychosocial functioning of stimulant misusers with and without AUD, we may inform tailoring of their clinical services.

Reviews of treatment process and response suggest much similarity between cocaine and amphetamine misusers [4, 5], and recent treatment trials aggregate them analytically [6-8] despite limited evidence of homogeneity in pre-treatment characteristics. Two single-site trials document predominance of males (60-82%) [4, 5], though rates vary between substances and trials. In each trial, race distinguished amphetamine and cocaine misusers, with the former comprised largely of Caucasians (72-80%) and latter by more balanced racial heterogeneity. Comparisons of other demography (e.g., age, marital, employment status) are equivocal. Copeland and Sorenson [4] do note greater proportion of amphetamine misusers as gay or bisexual than cocaine misusers, as well as their greater likelihood of medical complications, high-risk drug practices, psychiatric comorbidity, receipt of psychiatric medications, and prior suicidality. AUD comorbidity may impact psychosocial functioning for both amphetamine and cocaine misusers, with concurrent AUD diagnoses serving as risk factors for emergence of future alcohol problems, stimulant relapse, and other forms of treatment noncompliance. Extant literature suggests these groups differ in several psychosocial indicators, suggesting prospective analyses of these groups be stratified by stimulant type.

In contrast to single-site trials, multi-site trial designs may offer more powerful and informative comparisons of treatment-seeking groups due to larger, more representative client populations typically enrolled [9]. Presumably, this methodological strength would be amplified by aggregating treatment-seeking samples of interest across multiple multi-site trials. With respect to this report, such aggregation may allow more meaningful examination of influences of AUD comorbidity on psychosocial functioning for amphetamine and cocaine misusers. NIDA’s Clinical Trials Network [CTN; [10]] provides a vehicle for such examination, as it has for over a decade tested promising innovations via multi-site trials in community treatment agencies. With nearly three dozen such trials completed or underway, CTN invites use of its existing databases for secondary analyses. Its routine pre-treatment administration of a diagnostic instrument for substance use disorders (e.g., DSM-IV Checklist, CIDI 2.1) as well as a broad range of psychosocial functioning indicators on the Addiction Severity Index – Lite [11-13] across treatment trials offers a unique resource for our comparisons of interest.

This report documents our continued work on a CTN-approved secondary data analysis study examining pre-treatment client characteristics across trials [14]. The target of this report is treatment-seekers for whom stimulants (e.g., cocaine, amphetamine) are the primary substance of misuse. An initial aim was to describe pre-treatment rate of alcohol use, AUD diagnoses, and related phenomena in subgroups of primary stimulant misusing treatment-seekers. Further aims involved paired comparisons of the influence of AUD comorbidity (e.g., primary amphetamine misuser with AUD vs. without AUD, primary cocaine misuser with AUD vs. without AUD) on psychosocial functioning. Consistent with extant literature, higher rates of alcohol use, AUD diagnoses, and related phenomena by primary cocaine misusers were anticipated, whereas more pronounced psychosocial difficulties were expected of primary amphetamine misusers. Further, both primary stimulant with AUD subgroups were expected to evidence poorer psychosocial functioning than primary stimulant without AUD counterparts. A supplemental aim of the report is to discuss methodological issues and challenges encountered in this trans-protocol examination of CTN data.

Methods

Project Concept Development

Approval Processes

The project concept developed in response to a NIDA CTN call for proposals for secondary data analysis projects. Initially, the proposal was submitted to the Center for Clinical Trials Network, after which investigators worked with a data analyst at Duke Clinical Research Institute—the data management and statistical center for CTN at the time of proposal approval (April, 2008) that oversaw de-identification and maintenance of trial data. Datasets were de-identified and publicly-available, so no local IRB approvals were necessary.

Protocol Selection

A salient aspect of this work was analysis of common measurement constructs across CTN trials. Study investigators identified eight completed trials (CTN 0004, 0006, 0007, 0009, 0013, 0017, 0018, and 0019) meeting these inclusion criteria: 1) enrollment of treatment-seekers, and 2) pre-treatment administration of a DSM-IV diagnostic instrument for substance use disorders and CTN version of ASI-Lite. Analyses reflect aggregated stimulant-primary enrollees from the noted CTN trials.

Measures

Study measures represent two domains. The first domain concerns the absence/presence of AUD diagnoses, which was assessed in each of the eight CTN trials by respective diagnostic instruments noted below. The second domain contains a range of psychosocial functioning indices from the ASI-Lite [12], encompassing composite scores for psychosocial functioning in seven domains and item-specific indices concerning substance use and psychiatric functioning.

AUD Diagnostic Instuments

AUD diagnoses were assessed in each trial by clinician-administered diagnostic instruments. These were the: 1) Substance Dependence Severity Scale [15] utilized in CTN 0004; 2) DSM-IV Checklist [16] utilized in CTN 0006, 0007 and 0009; 3) DSM-IV Diagnostic Interview utilized in CTN 0013); and 4) Composite International Diagnostic Interview 2.1 Substance Use Module [17] utilized in CTN 0017, 0018, and 0019. Each assesses, for the prior 12-month period, presence of 7 DSM-IV diagnostic criteria for alcohol dependence (i.e., tolerance, withdrawal, greater than intended use, unsuccessful attempts to quit, considerable time using or procuring, compromise of other activities, persistent use despite exacerbation of physical/psychological problems) and 4 diagnostic criteria for alcohol abuse (i.e., failure in major role obligations, use in hazardous situations, persistent use despite exacerbation of social problems, recurrent legal problems). Greater description of the instruments is provided in our prior work [18]. Notably, CTN trial datasets did not distinguish AUD diagnoses with course modifiers for remission status (i.e., early vs. sustained, full vs. partial) at the time of assessment.

Addiction Severity Index – Lite

The ASI-Lite [12] is a structured interview assessing demography and personal data in seven psychosocial domains (Medical, Legal, Family/Social, Alcohol, Drug, Employment, and Psychiatric). A composite score is computed for each domain. Validity and reliability are well-established [11]. Within Alcohol and Drug domains, individual ASI-Lite items tapped recent (past 30 days) drinking or drug use frequency, recent problems, recent financial expenditures on alcohol or drugs, lifetime treatment episodes and lifetime experience of delirium tremens. Further, interviewers note a primary substance of misuse, and this notation was used to identify CTN enrollees for whom cocaine or amphetamine was primary.¹ Within the Psychiatric domain, individual ASI-Lite items tapped lifetime and recent incidence of a range of psychiatric symptoms (e.g., depression, anxiety, hallucinations) as well as client-rating of current psychiatric problem magnitude and importance of psychiatric treatment.

Data and Statistical Analysis

Data Source

NIDA CTN Data Share (http://www.ctndatashare.org) provides public access to de-identified data from completed trials. Data are in Study Data Tabulation Model standard format sponsored by Clinical Data Interchange Standards Consortium, and are available for download 18 months after trial completion or after acceptance for publication of its primary manuscript. Data for the last included trial became available in March, 2009.

Statistical Analysis

Analyses were performed on all eight trials with available data. Sample characteristics (e.g., demography, lifetime AUD diagnoses) were summarized using un-weighted descriptive statistics. Clinical characteristics measured by ASI-Lite were synthesized via meta-analytic pooling across trials. Meta-analytic weighted means, proportions, and odds-ratios were estimated using a random-effects model that accounts for trial sample size and intertrial variance (i.e., study heterogeneity) when weighting strength of associations between independent and dependent variables [19-21]. Meta-analytic means, proportions, and odds-ratios are expressed with 95% confidence intervals. A criterion of p <.05 was used for statistical significance in all comparisons. All calculations were performed in SAS (Version 9, SAS Institute Inc., Cary, NC) and Comprehensive Meta-Analysis (Version 2, Biostats Inc.).

Results

Trial and Participant Characteristics

Table 1 outlines characteristics of the eight CTN trial samples including sample size, stimulant-primary subsample size, and broad subsample demography. Collectively, the trials enrolled 4,396 participants, of which 1133 (26%) were identified as primary stimulant misusers. Their mean age was 37.4 years (S.D. = 9.2), with gender distribution slightly favoring females (56%). Hispanic ethnicity was identified by 26.5%, and racial identification was 37.5% Caucasian, 37.2% African-American, 13.0% Latino, 5.9% Multi-racial, and 6.5% Other.

Table 1.

Sample Characteristics By CTN trial

CTN Trial Number and Title	Target Population	Trial Sample	Primary Stimulant Subsample	Primary Stimulant Subsample Characteristics
				Age M (SD)	Male (%)	White race (%)	Black race (%)	Other race (%)
0004 Motivational Enhancement Treatment (MET) to Improve Treatment Engagement and Outcome in Those Seeking Treatment for Substance Abuse	Outpatient Treatment- Seekers	392	113	37.7 (8.4)	66.4	32.7	38.1	29.2
0006 Motivational Incentives for Enhanced Drug Abuse Recovery: Drug-Free Clinics	Outpatient Treatment- Seekers	469	340	35.7 (8.7)	43.2	37.9	39.7	22.4
0007 Motivational Incentives for Enhanced Drug Abuse Recovery: Methadone Clinics	Outpatient Treatment- Seekers	454	173	41.2 (8.7)	54.3	31.6	34.5	33.9
0009 Smoking Cessation Treatment with Transdermal Nicotine Replacement Therapy in Substance Abuse Rehabilitation Programs	Outpatient Treatment- Enrollees	366	77	40.5 (8.7)	48.1	37.7	23.4	39.0
0013 Motivational Enhancement Therapy to Improve Treatment Utilization and Outcome in Pregnant Substance Users	Pregnant Treatment- Seekers	232	74	28.2 (5.2)	0.0	37.0	30.1	32.9
0017 HIV and HCV Intervention in Drug Treatment Settings	Detoxified Treatment- Seekers	679	34	31.4 (8.2)	61.8	91.2	2.9	5.9
0018 Reducing HIV/STD Risk Behaviors: A Study for Men in Drug Abuse Treatment	Male Outpatient Treatment- Seekers	990	170	40.1 (9.3)	100.0	30.8	44.4	24.9
0019 Reducing HIV/STD Risk Behaviors: A Study for Women in Drug Abuse Treatment	Female Outpatient Treatment- Seekers	814	152	38.2 (9.1)	0.0	42.1	44.1	13.8
Aggregate			1133	37.4 (9.2)	48.1	37.5	37.2	25.3

Notes: All trials selected enrolled a treatment-seeking population and included baseline administration of DSM-IV diagnostic instrument and ASI-Lite; ‘Other race’ subsumes racial categories of Spanish/Latino, ‘Other,’ and multi-racial identification; For some trials, the noted instruments were administered at the time of initial screening, and therefore individuals excluded from those trials may be represented in the current analyses; Information concerning individual trials is available at: http://ctndisseminationlibrary.org

AUD Rates Among Primary Stimulant Misusers

Prevalence

Of the aggregate primary stimulant subsample (N=1,133), 993 (88%) had data regarding absence/presence of AUD diagnoses. Missing data appeared due to inter- and intra-trial procedural variance in instrument administration and eventual documentation in CTN datasets. Unfortunately, required de-identification of CTN datasets minimized opportunity to resolve issues of apparent procedural variability. Table 2 outlines AUD rates among stimulant-primary subsample by trial and aggregated across trials. The aggregate AUD prevalence rate was 45%, with wide between-trial variation (16.3 – 90.6%). Of 449 primary stimulant treatment-seekers with comorbid AUD, 374 (83%) met criteria for alcohol dependence.

Table 2. Rates of AUD Diagnoses and Criteria Among Primary Stimulant Subsample.

CTN Trial	Primary Stimulant Subsample	Comorbid Alcohol Abuse Diagnosis		Comorbid Alcohol Dependence Diagnosis		Any Comorbid AUD Diagnosis
		N	%	N	%	N	%
0004	113	11	9/7	45	39.8	56	49.6
0006	333	33	9.9	85	25.5	118	35.4
0007	172	12	7.0	16	9.3	28	16.3
0009	76	3	3.9	22	28.5	25	32.9
0013	45	13	28.9	9	20.0	22	48.9
0017	32	0	0.0	29	90.6	29	90.6
0018	108	2	1.9	82	75.9	84	77.8
0019	114	1	0.9	86	75.4	87	76.3
Aggregate	993	75	7.6	374	45.2	449	45.2

Notes: Table includes only those respective CTN trial enrollees for whom full AUD assessment data was available; All diagnostic categories were coded dichotomously (absent, present), with any AUD considered present if criteria for abuse or dependence were met.

ASI-Lite Alcohol-Related Indices

Indices were computed separately for primary amphetamine with AUD and primary cocaine with AUD subgroups. Alcohol composite scores were atypically-distributed in both subgroups. Consequently, Table 3 provides: 1) the proportion of each subgroup with an Alcohol composite score of zero, and 2) measures of central tendency and dispersion (e.g., mean, 95% confidence interval) for the distribution of Alcohol composite scores with values greater than zero. Table 3 is similarly formatted with respect to five other ASI-Lite alcohol-related items. Notably, large percentages of primary amphetamine with AUD and primary cocaine with AUD subsamples endorsed no prior alcohol treatment (51-62%), no recent alcohol consumption (36-42%), no recent expenditure on alcohol (51-52%), and no recent alcohol problems (70-74%).

Table 3.

ASI Alcohol-Related Indices Among Aggregate Primary Stimulant with AUD Sample

ASI Index	Primary Stimulant with Comorbid AUD and Alcohol Composite Score = 0				Primary Stimulant with Comorbid AUD and Alcohol Composite Score > 0
	Amphetamine		Cocaine		Amphetamine			Cocaine
	N	%	N	%	N	Mean	95% CI	N	Mean	95% CI
Alcohol Composite Score	30/74	39.6	105 /369	23.7	44	0.3	(0.14, 0.36)	264	0.2	(0.16, 0.23)
Lifetime Frequency of Delirium Tremens	No Delirium Tremens		No Delirium Tremens
	67/74	87.7	338/370	89.9	7	1.1	(----- , -----)a	32	3.5	(2.20, 4.89)
Prior Alcohol Treatments (lifetime)	No Prior Treatments		No Prior Treatments
	49/74	62.3	187/369	50.8	25	1.9	(1.14, 2.59)	182	3.6	(2.20, 4.89)
Recent Alcohol Consumption Frequency*	No Consumption		No Consumption
	32/74	41.8	160 /370	36.3	42	7.9	(3.10, 12.60)	210	9.7	(7.26, 12.10)
Recent Alcohol Expenditures* ($ amount)	No Expenditure		No Expenditure
	41/74	51.8	205/371	50.8	33	52.0	(11.56, 92.35)	166	47.4	(55.61, 32.80)
Recent Alcohol Problem Frequency*	No Problems		No Problems
	57/74	73.7	252/370	70.1	17	10.4	(2.75, 18.12)	118	11.4	(8.74, 14.10)

Notes: All analyses conducted with available data; Presentation of 95% confidence interval (C.I.) is for weighted means

^adenotes sample too small for meaningful calculation of 95% C.I.; Alcohol Composite Score ranges from 0.00 – 1.00; Individual Alcohol items coded dichotomously (yes, no) as indicated

^*‘Recent’ defined as the 30 days prior to assessment.

Comparisons of Primary Stimulant Subsamples With vs. Without AUD

Comparisons were conducted separately for aggregated primary amphetamine (n=226) and primary cocaine (n=791) subgroups. These within-subgroup comparisons targeted ASI-Lite composite scores as well as specific Alcohol/Drug and Psychiatric domain items.

Composite Scores

Distributions of Medical, Legal, Family/Social, and Psychiatric scores showed positive skew, so analyses first compared subgroup proportions with zero-value scores. As Table 4 notes, primary cocaine subgroup differences were found in Legal (odds-ratio=.60) and Psychiatric (odds-ratio=.43), with greater proportion of zero-value scores among cocaine-primary without lifetime AUD. Primary amphetamine subgroup differences were similar in direction but nonsignificant. Analyses then compared subgroup proportions with scores above its respective subgroup median value. Primary cocaine subgroup differences were found in Medical (odds-ratio=1.57), Family/Social (odds-ratio=1.53), and Psychiatric (odds-ratio=1.87), with greater proportion of above-median scores among those with AUD (see Table 4). Primary amphetamine subgroup differences were similar in direction, but nonsignificant.

Table 4.

ASI composite scores for Primary Stimulant Subgroups With and Without AUD

ASI Composite Domain	Primary Amphetamine With AUD (N =75 )		Primary Amphetamine Without AUD (N =141 )		Primary Amphetamine Subgroup Comparison		Primary Cocaine With AUD (N =379)		Primary Cocaine Without AUD (N =412)		Primary Cocaine Subgroup Comparison
	n	%	n	%	Odds-Ratio	(95% C.I.)	n	%	n	%	Odds-Ratio	(95% C.I.)
Medical
= 0.00	36	49.5	80	50.7	0.75	(0.35, 1.59)	159	43.5	215	52.5	0.67	(0.47, 0.93)
Mda = 0.00							---	---	---	---	---	---
Mdb >= 0.08	---	---	---	---	---	---	206	50.5	184	44.9	1.57	(1.05, 2.35)*
Legal
= 0.00	26	40.6	76	56.8	0.87	(0.40, 1.87)	211	55.3	284	69.5	0.60	(0.37, 0.97)*
Mda >= 0.03		59.4	57	43.2	1.15	(0.54, 2.47)	0	---	0	---	---	---
Mdb = 0.00	---	---	---	---	---	---	---	---	---	---	---	---
Family/Social
= 0.00	26	36.8	60	44.6	0.62	(0.29, 1.31)	0		0	56.2	---	---
Mda >= 0.19	43	57.3	64	48.9	1.49	(0.71, 3.13)	---	---	---	---	---	---
Mdb > 0.02	---	---	---	---	---	---	204	54.8	178	43.2	1.53	(1.11, 2.10)**
Psychiatric
= 0.00	19	25.7	80	28.6	0.87	(0.37, 2.03)	102	28.2	168	42.1	0.43	(0.30, 0.60)***
Mda >= 0.31	38	50.6	67	50.4	1.24	(0.57, 2.66)	---	---	---	---	---	---
Mdb >= 0.21	---	---	---	---	---	---	212	57.4	183	45.3	1.87	(1.36, 2.58)***
Employment
= 1.00	20	32.2	28	27.5	1.57	(0.56, 4.41)	168	45.5	186	46.3	1.03	(0.71, 1.49)
Mda >= 0.50	48	66.5	95	70.0	0.60	(0.19, 1.93)	---	---	---	---	---	---
Mdb >= 0.80	---	---	---	---	---	---	185	50.0	206	51.3	1.09	(0.76, 1.57)
Drug
Mda >= 0.21	36	55.9	75	54.6	0.84	(0.37, 1.89)	---	---	---	---	---	---
Mdb >= 0.18	---	---	---	---	---	---	188	59.3	221	46.3	1.71	(1.06, 2.78)*

Notes: Reference groups for odds-ratios are amphetamine without AUD and cocaine without AUD subgroups; Composite scores coded dichotomously around median scores (less than, equal to or greater than) as indicated

^adenotes median for primary amphetamine subgroup

^bdenotes median for primary cocaine subgroup; Rates and odds-ratios are weighted via meta-analyses

^***p<.001

^**p<.01

^*p<.05

Employment scores were also asymmetrically distributed, but with negative skew and large proportion of maximum-value (e.g., 1.00) scores. Thus, analyses first tested the proportion of maximum-values scores, though found no differences (see Table 4). Subsequent analyses comparing proportions of scores above the subgroup median value also revealed no differences. Drug scores were more normally-distributed; thus, corresponding subgroup analyses evaluated proportions of scores above the subgroup median value. A higher proportion of above-median values was found among primary cocaine with AUD (see Table 4), but no significant difference emerged within the primary amphetamine subgroup.

Alcohol/Drug Items

Table 5 notes comparisons for recent (past 30 days) and lifetime amphetamine and cocaine use. Despite high rate of endorsement for recent use in each subgroup for its primary drug, no within-subgroup differences emerged. Further, no difference was found within the primary cocaine subgroup for amphetamine use, nor within the primary amphetamine subgroup for cocaine use. High lifetime use rates were unsurprisingly observed in each subgroup for its respective primary drug, but no within-subgroup differences emerged. No difference in lifetime cocaine use was found within the primary amphetamine subgroup, though the primary cocaine with AUD was more likely (odds-ratio=2.21) to endorse amphetamine use. Within-subgroup comparisons also tested for prior drug detoxification and treatment, recent monetary expenditure on drugs, and recent drug problems, though all comparisons failed to detect effects. Within-subgroup comparisons also evaluated client rating of drug problem magnitude and importance of treatment. No primary cocaine subgroup differences were evident in perceived problem magnitude, though primary amphetamine misusers without AUD were more likely to perceive slight-to-moderate problems (with counterparts apt to perceive minimal problems). Within-subgroup differences in perceived treatment importance were evident. Primary amphetamine misusers without AUD were more likely to perceive slight-to-moderate importance relative to counterparts apt to perceive minimal importance, and primary cocaine misusers with AUD more likely to perceive considerable-to-extreme importance relative to counterparts apt to perceive minimal importance of drug treatment.

Table 5.

Comparisons of Stimulant-Primary With and Without AUD Subgroups on ASI Drug Items

	Primary Amphetamine With AUD (N=75)		Primary Amphetamine Without AUD (N=141)		PrimaryAmphetamine Subsample Comparison		Primary Cocaine With AUD (N=379)		Primary Cocaine Without AUD (N=412)		Primary Cocaine Subsample Comparison
	n	%	n	%	Odds-Ratio (95% C.I.)		n	%	n	%	Odds-Ratio (95% C.I.)
Recent Amphetamine Use	46	64.4	114	73.8	0.62	(0.22, 1.76)	14	5.0	5	1.6	2.25	(0.78, 6.45)
Recent Cocaine Use	11	17.4	13	16.6	0.64	(0.22, 1.88)	234	71.5	326	75.7	0.81	(0.49, 1.34)
Lifetime Amphetamine Use	71	91.2	131	95.2	0.84	(0.08, 1.43)	73	20.3	37	9.0	2.21	(1.33, 3.68)**
Lifetime cocaine use	42	54.6	53	45.9	1.35	(0.64, 2.85)	364	97.1	391	94.9	2.76	(0.99, 7.68)
Prior Drug Detoxification	29	34.5	32	36.5	0.76	(0.26 ,2.28)	132	44.0	175	39.4	1.18	(0.82, 1.75)
Prior Drug Treatment	51	61.3	85	74.0	0.60	(0.26, 1.39)	339	90.9	365	87.5	1.33	(0.60, 2.96)
Recent Drug Expenditure
None	37	47.2	63	50.8	0.80	(0.34, 1.87)	171	39.1	141	36.8
$1 - $200	21	31.2	49	36.6	1.12	(0.45, 2.77)	102	27.3	155	36.3	0.93	(0.49, 1.76)
> $200	15	25.2	21	17.0			97	29.6	111	28.0	1.23	(0.63, 2.38)
Recent Drug Problems	39	52.6	49	54.8	0.93	(0.41, 2.12)	281	72.9	291	67.3	1.13	(0.77, 1.66)
Perceived Magnitude of Drug Problems
Not at all	14	24.3	19	19.4			98	23.8	124	32.9
Slightly/Moderately	16	24.5	38	28.5	0.22	(0.08, 0.61)**	76	20.9	99	25.3	1.33	(0.75, 2.34)
Considerably/Extremely	44	56.5	76	55.2	0.41	(0.16, 1.07)	197	53.4	185	44.2	1.74	(1.16, 2.61)**
Perceived Importance of Treatment
Not at all	16	20.7	19	19.6			81	17.3	126	33.3
Slightly/Moderately	5	9.9	11	11.7	0.23	(0.06, 0.95)*	20	6.6	43	10.2	1.15	(0.36, 3.70)
Considerably/Extremely	53	70.1	103	70.9	0.82	(0.25, 2.69)	270	75.2	239	56.9	2.31	(1.54, 3.45)*

Notes: All comparisons reflect synthesized results by meta-analyses, with rates and odds-ratios weighted accordingly; Reference groups for odds-ratios are the amphetamine without AUD and cocaine without AUD subgroups; Individual Drug items coded dichotomously (yes, no) as indicated, with exception of ‘Recent Drug Expenditure’ which was coded categorically in three levels (none, $1-$200, more than $200) as indicated; Responses for perceived magnitude/importance items provided on a 5-point (0 – 4) rating scale; Reference group for odds-ratios for client rating variables is ‘not at all’; ‘Recent’ defined as 30 days prior to assessment

^***p<.001

^**p<.01

^*p<.05.

Psychiatric Items

Table 6 outlines comparisons of recent (past month) and lifetime presence of seven symptoms (depression, anxiety/tension, hallucinations, cognitive difficulty, dyscontrol of violence, suicidal ideation, attempted suicide) as well as client ratings of perceived magnitude of psychiatric problems and importance of their treatment. For lifetime symptoms, differences were reliably found in the primary cocaine subgroup (odds-ratios: 1.69-2.19) and invariably favored endorsement by primary cocaine misusers with AUD. Comparisons within the primary amphetamine subgroup were generally consistent in direction, though only those for dyscontrol of violence, suicidal ideation, and attempted suicide were significant (odds-ratios: 2.30-4.30). For recent symptoms, greater proportion of primary cocaine misusers with AUD endorsed depression, anxiety/tension, cognitive difficulty, dyscontrol of violence, and suicidal ideation than counterparts. No differences were found in recent symptoms within the primary amphetamine subgroup. In terms of client ratings, primary cocaine misusers with AUD were more likely to endorse considerable-to-extreme problem magnitude and treatment importance relative to counterparts more apt to endorse minimal problem magnitude and treatment importance. No differences were found in client ratings in the primary amphetamine subgroup.

Table 6.

Comparisons of Primay Stimulant With and Without AUD Subgroups on ASI Psychiatric Items

ASI Psychiatric Indices	Primary Amphetamine With AUD (N=75)		Primary Amphetamine Without AUD (N=141)		Primary Amphetamine Subsample Comparison		Primary Cocaine With AUD (N=379)		Primary Cocaine Without AUD (N=412)		Primary Cocaine Subsample Comparison
Past Month Symptoms	n	%	n	%	Odds-Ratio (95% C.I.)		n	%	n	%	Odds-Ratio (95% C.I.)
Depression	30	41.3	65	45.9	0.71	(0.40, 1.27)	150	40.8	145	35.3	1.49	(1.02, 2.20)*
Anxiety/Tension	30	41.6	62	49.7	0.78	(0.44, 1.39)	178	48.1	155	38.4	1.64	(1.19, 2.26)**
Hallucinations	4	8.3	6	6.5	1.2	(0.33, 4.43)	24	6.9	25	7.5	0.98	(0.52, 1.84)
Cognitive Difficulty	32	43.2	52	39.7	1.19	(0.67, 2.11)	152	40.8	119	29.2	1.89	(1.25, 2.85)**
Dyscontrol of Violence	16	23.3	25	20.1	1.19	(0.59, 2.41)	56	15.7	42	10.8	1.58	(1.01, 2.46)*
Suicidal Ideation	7	12.3	8	8.0	1.63	(0.57, 4.70)	41	12.0	23	5.8	2.26	(1.29, 3.98)**
Suicide Attempt	1	3.9	3	5.2	0.59	(0.06, 5.81)	4	2.0	8	2.3	0.71	(0.25, 2.20)
Lifetime Symptoms	n	%	n	%	Odds-Ratio (95% C.I.)		n	%	n	%	Odds-Ratio (95% C.I.)
Depression	54	68.5	87	63.8	1.43	(0.76, 2.67)	260	70.0	244	58.9	1.95	(1.28, 2.98)**
Anxiety/Tension	49	64.5	75	53.8	1.52	(0.84, 2.74)	251	67.4	215	50.1	2.13	(1.47, 3.09)***
Hallucinations	7	9.5	15	12.2	0.82	(0.32, 2.12)	66	18.5	54	13.8	1.69	(1.06, 2.68)*
Cognitive Difficulty	35	49.5	61	46.4	1.14	(0.54, 2.42)	197	53.3	156	36.0	2.19	(1.57, 3.04)***
Dyscontrol of Violence	53	69.1	49	44.2	4.30	(2.34, 8.01)***	197	53.1	126	31.3	2.35	(1.69, 3.26)***
Suicidal ideation	35	45.1	37	28.9	2.30	(1.27, 4.17)***	179	48.3	142	34.2	1.91	(1.38, 2.66)***
Suicide attempt	29	39.1	27	22.4	2.53	(1.35, 4.75)***	142	37.9	102	25.4	1.91	(1.24, 2.96)***
Client Ratings	n	%	n	%	Odds-Ratio (95% C.I.)		n	%	n	%	Odds-Ratio (95% C.I.)
Magnitude of problems
Not at all	21	29.8	47	35.3			146	39.6	218	53.4
Slightly/moderately	18	24.2	22	16.5	1.54	(0.57, 4.16)	66	21.1	66	16.4	1.68	(0.94, 3.01)
Considerably/extremely	34	46.0	64	48.2	1.07	(0.46, 2.47)	157	42.6	123	30.2	2.27	(1.58, 3.26)***
Importance of treatment
Not at all	21	32.4	54	40.6			156	42.4	232	56.9
Slightly/moderately	10	13.5	18	13.5	1.17	(0.39, 3.55)	30	8.2	45	11.0	1.15	(0.65, 2.03)
Considerably/extremely	40	54.0	61	45.9	1.46	(0.66, 3.25)	182	49.5	131	32.1	2.26	(1.61, 3.19)***

Notes: All comparisons reflect synthesized results by meta-analysis, rates and odds-ratios weighted accordingly; Reference groups for odds-ratios are the amphetamine without AUD and cocaine without AUD subsamples; Symptom-based items coded dichotomously (absent, present); Responses for perceived magnitude/importance items provided on a 5-point (0 – 4) rating scale; Reference group for odds-ratios for client rating variables is ‘not at all’

^***p<.001

^**p<.01

^*p<.05.

Discussion

In this report, we detail work on a CTN secondary analysis project (CTN 0040-S, Pattern of Alcohol Use and Alcohol-Related Diagnoses Among Drug Abusing/Dependent Participants). Specifically, we examined alcohol-related characteristics of primary amphetamine and primary cocaine misusing treatment-seekers across eight CTN trial samples, and within each group compared psychosocial functioning of those with and without comorbid AUD. This contributes to a small but growing initial literature utilizing public CTN datasets to examine pre-treatment client characteristics in an aggregated, ‘trans-protocol’ fashion [14, 22]. Study findings provide a more conclusive AUD prevalence estimate among stimulant abusers than is afforded by prior single-site trials [4-6], and document influences of AUD comorbidity at treatment outset on psychosocial functioning of amphetamine and cocaine misusers. Findings inform intervention targets for these subgroups of treatment-seekers, and the methods used may also highlight salient issues for future research.

A high AUD rate (45%) was found among primary stimulant misusers, and its derivation from eight multi-site trial samples (encompassing 50 community treatment programs) may hold strong representativeness. Notably, data on course modifiers for AUD diagnoses were not available. In terms of ASI-Lite indices, absence of recent alcohol use and related phenomena by many primary stimulant misusing enrollees is noteworthy, and underlied skewed distribution of Alcohol composite scores. Comparisons on other ASI composite scores, stratified by stimulant type, highlight respective associations between AUD comorbidity and measures of psychosocial functioning among cocaine and amphetamine misusers. In the former subgroup, those with comorbid AUD were more likely to show elevated problems in medical care, legal difficulty, relationships with friends and family, psychiatric well-being, and drug addiction. Nonsignificant effects in the latter subgroup, though constrained by smaller sample size, were less reliable in direction and often less robust.

With regard to individual ASI drug items, few within-subgroup comparisons supported AUD comorbidity as a risk or protective factor for recent drug behavior. Exceptions were greater likelihood of elevated client perception of: 1) problem magnitude by primary amphetamine misusers with AUD, and 2) treatment importance by both primary amphetamine misusers with AUD and primary cocaine misusers with AUD. While inconsistent with nonsignificant effects for recent drug problems and treatment history, prior research has failed to tie such objective pre-treatment ASI indicators to stimulant treatment outcomes [23]. Put differently, the prognostic value of stimulant misusers’ perceived drug treatment needs may merit further consideration. Among primary cocaine misusers, AUD comorbidity was reliably associated with greater likelihood of recent/lifetime psychiatric symptoms, and elevated perception of psychiatric problems and importance of their treatment. In contrast, primary amphetamine misusers with AUD showed only greater likelihood of lifetime endorsement for three symptoms (i.e., dyscontrol of violence, suicidal ideation, suicide attempt). This particular pattern of findings is only partially consistent with the prior work of Copeland and Sorenson [4], who reported greater psychiatric comorbidity, use of psychiatric medications, and suicidality among amphetamine misusers than cocaine misusers. As their findings were derived from a single-site study conducted over a decade ago, it is difficult to know the extent to which some current findings differ as a function of history, geography, or both. The aggregation of a much larger sample—from eight multisite trials, spanning the years 2001-2006—may again lend weight to the current findings. Taken together, the broader findings are generally consistent with our prior work examining opiate-primary treatment-seekers [14] insofar as persons with comorbid AUD report poorer psychosocial functioning than those without AUD comorbidity. Further, it underscores the need to include AUD assessment and corresponding psychiatric services (e.g., medication monitoring, behavioral counseling) in stimulant treatment.

Methodological Issues

This CTN secondary data analysis project capitalized on existing data of eight trials, and is bound by strengths and limitations of the original trials. A noted strength is CTN formulation of a pre-treatment assessment battery containing common constructs. Existence of this battery allowed aggregation of treatment-seeking samples, and prompted meta-analytic pooling for comparisons stratified by stimulant type. These methodological efforts may mitigate, but not fully alleviate, concerns related to selection bias and generalizability that influence perceived utility of reports from single-site trials. A caveat, given the number of simultaneous comparisons, is potential for false positives. Thus, caution is warranted when interpreting statistical significance of these findings.

Though all eight CTN trials included a DSM-IV diagnostic assessment, there was some variance in AUD instruments used. Notably, all the AUD instruments are empirically-supported, and this report focuses on one common construct (e.g., AUD absence/presence) available across trials. Through a formal consensus-building process, CTN determined a single instrument of choice for future trials [24]. However, this occurred after or amidst some trials included in these analyses, and so a possibility that instrument variance contributed measurement error in calculating AUD rates must be acknowledged. Relatedly, the lack of available cross-trial data concerning AUD diagnosis course modifiers prevented distinction of subsets of primary stimulant with AUD treatment-seekers in varying stages of severity or remission. Though the aggregate primary stimulant with AUD population may share an elevated risk for prospective alcohol-related difficulties relative to the general population, it should not be assumed that the relative risk of such difficulties is equivalent among subgroups in various stages of remission. Instrument variance also presented challenges in aggregating data across trials, and speaks to the importance of a true common assessment battery across CTN trials.

Another methodological issue uncovered during this work was the amount of missing data encountered, apparently the result of inter- and intra-trial procedural variance in collection of pre-treatment client data via clinician-administered instruments. This is a concern, and should rank among other identified areas where planning and execution of prospective CTN trials can improve [25]. Our preliminary analyses were impacted by the unforeseen absence of interviewer notation of a ‘primary substance’ in some ASI-Lite interviews. To compensate for these omitted data, a five-step algorithm¹ was generated whereby primary substance could be designated given other commonly available diagnostic data. This was then used to identify a portion (10%) of the primary stimulant subsample that would otherwise have been excluded from analyses. While external validation work seems appropriate, the algorithm may offer a template for others to decipher diagnostic hierarchy among client groups for whom comorbidity muddies nosological waters. Current analyses were also impacted by absence of individual AUD diagnostic criteria data in several trials, and lack of determination of the absence/presence of AUD diagnosis in 12% of the primary stimulant sample. It remains unclear to what extent missing data were attributable to instrument administration or documentation processes. A further complication involved CTN data management policy which, by requiring data de-identification before public sharing in accord with the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule, excluded site variables that may have resolved some data quandaries. Though missing data imposed limitations on this work, underlying problems with consistent data collection and documentation seem resolvable if attended to by CTN investigators, research personnel, and data management groups who generate and manage data for prospective trials.

Conclusions

This report presents rates of AUD comorbidity among subgroups of primary stimulant misusing treatment-seekers in CTN trials as well as its link to psychosocial functioning prior to treatment. Study findings emphasize utility of including comprehensive diagnostic assessment in future addiction treatment research, and that sample stratification by diagnostic variables may be appropriate in some instances. In terms of clinical relevance, study findings underscore the importance of: 1) comprehensive diagnostic assessment for substance use disorders in treatment intake processes, and 2) integration of psychosocial support services during treatment delivery. Healthcare organizations that do so may better identify the needs of their clientele, and more effectively tailor treatment provision to promote client engagement and retention in services.

Rates and influences of alcohol use disorder comorbidity among Rates and influences of alcohol use disorder comorbidity among primary stimulant misusing-primary treatment-seekers: Meta-analytic findings across eight NIDA CTN trials