Clinical Characteristics of Treatment-Seeking Prescription Opioid versus Heroin using Adolescents with Opioid Use Disorder

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Clinical Characteristics of Treatment-Seeking Prescription Opioid versus
Heroin using Adolescents with Opioid Use Disorder
Geetha A. Subramaniam and Maxine A. Stitzer
Geetha A. Subramaniam, Department of Psychiatry, Johns Hopkins University,
C/O Mountain Manor Treatment Center, 3800 Frederick Ave, Baltimore, MD
21229. Phone: 410-233-1400; Fax: 410-233-1666, Email: gsubram@jhmi.edu ;
Contributor Information.
Corresponding author.
The publisher’s final edited version of this article is available at Drug
Alcohol Depend.
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1. Introduction2. Methods3. Results4. DiscussionReferences1. Introduction
Rising opioid use among adolescents is of emerging public health concern
(Compton and Volkow, 2006; Zacny et al., 2003). During the past 5 years,
while annual prevalence of heroin use among 12th graders has remained
steady (approximately 0.9%), rates of non-medical use of prescription
opioid analgesics has risen 135% (from 6.7-9%, (National Institute on Drug

Abuse, 2007). Parallel to these rising trends, nationwide admissions to
publicly funded substance abuse treatment programs in the U.S. in 2004-5
(Substance Abuse and Mental Health Services Administration Office of
Applied Studies, 2007d) show that approximately 5000 teenagers ages
12-17years entered treatment for a primary heroin or “other opioids or
synthetics” problem. Substantial harm from the rising abuse of
prescription opioids is reflected in a 24% increase in opioid-related
hospital Emergency Department (ED) visits in 2005 compared to 2004
(Substance Abuse and Mental Health Services Administration Office of
Applied Studies, 2007b); and a 91% increase in number of deaths from
opioid analgesic poisoning between 1999 and 2002 (Paulozzi et al.,
2006)

.Despite these concerns, there is limited information on clinical
populations of adolescents addicted to opioids. Available studies using
treatment samples have either examined those with opioid abuse/dependence
as a single group (i.e. not distinguished by type of opioid: heroin vs.
prescription opioid analgesic use, Gordon et al., 2004; Marsch et al.,
2005; Subramaniam et al., 2008); or focused only on heroin users entering
treatment (Clemmey et al., 2004; Hopfer et al., 2000). Information on
illicit use of opioid analgesics among teenagers is not available for
clinical samples but there is information from secondary analyses of two
community-based surveys: 2002 Monitoring the Future Study (McCabe et al.,
2005; National Institute on Drug Abuse, 2007) and the 2002 National Survey
of Drug Use and Health (Substance Abuse and Mental Health Services
Administration Office of Applied Studies, 2007c; Sung et al.,
2005).Findings from both community-based and treatment samples have
revealed similar characteristics. Both the heroin and the prescription
opioid-using samples consisted of older adolescents (16-17 year old) with
the majority being male and predominantly of Caucasian race. They had poor
academic achievement/school problems; polysubstance use was common and
many had legal problems. High rates of injection drug use (IDU) were
reported among heroin users but not prescription opioid users. Examining
mental health symptoms, Clemmey et al, (2004) reported high depressive
symptoms and mental distress among treatment-seeking heroin users while
Sung et al (2005) found that illicit opioid users compared to non-illicit
opioid users in the community were more likely to have seen a therapist.
Our prior study (Subramaniam et al., 2008) showed that 83% of adolescents
entering treatment with opioid use disorder (OUD) had a DSM-IV Axis-I
psychiatric disorder but it is not known if the rates of psychiatric
disorders differ by type of opioid being abused.Given the striking lack of
data on prescription opioid-using youth despite their rising numbers, we
conducted secondary analyses of data from a large (N = 94) group of
treatment-seeking adolescents with OUD (Subramaniam et al., 2008) to
compare characteristics of prescription opioid versus heroin users.
Differences found in these two subgroups may be important for
understanding risk factors and/or for identifying differential treatment
needs. Other Sections▼
1. Introduction2. Methods3. Results4. DiscussionReferences2. Methods
1.1. Study design and procedures
Data was obtained from a parent study funded by National Institute of Drug
Abuse (NIDA) in which 94 adolescents (ages 14-18 years) with a past-year
DSM-IV OUD were compared to 72 adolescents with a past-year non-OUD DSM-IV
cannabis/alcohol use disorders on demographic, substance use, psychiatric
and HIV-risk behaviors. For this study, only the OUD participants were
selected and divided into two groups: 1) Past year OUD adolescents with
any self-reported past 30-day non-heroin prescription opioid use (n = 41)
and 2) those reporting any heroin use in the past 30 days whether or not
they also reported any prescription opioid use (n = 53). All participants
in the parent (and this) study were administered a selection of
assessments that used either self-report or standardized interviews for
data collection. These included an assessment for demographic and social
features (interview), Composite International Diagnostic Interview –
Substance abuse module (CIDI-SAM) for past-year DSM-IV SUD diagnoses;
Diagnostic Instrument for Children and Adolescents-IV (DICA-IV) for Axis-I
psychiatric disorders; Beck Depression Inventory (BDI) for self-reported
depressive symptoms; Risk Behavior Survey (RBS) for past-30 day sexual and
injection drug use (IDU) HIV-risk behaviors; and the General Crime Scale
from the Global Assessment of Individual Need (GAIN) for self-reported
criminal behaviors in the past year. Additional details on the parent
study design and methods have been reported in Subramaniam et al., (2008).
Western Institutional Review Board (WIRB), a Johns Hopkins IRB designee,
approved the study protocol and all study materials.
1.2. Participants
The study sample (n = 94) mean age was 16.9 years; (S.D. = 1.02); 67% were
between 14-17 years of age. Fifty five percent were male; 89% were
Caucasian; 35% were on probation while 18% were court referred for
treatment. Per definition, all study participants met criteria for DSM-IV
OUD abuse or dependence; 88% met criteria for DSM opioid dependence.
As this study sample was recruited from a single treatment site, we
compared our results to nationwide data on age matched adolescent
substance abuse treatment admissions for problem use of opioids to
determine how representative our site data was on comparable patient
characteristics. For this purpose, we compared our data from the subset of
14-17 year olds (n = 63) to data on adolescents ages 12-17 years in the
TEDS dataset (Substance Abuse and Mental Health Services Administration
Office of Applied Studies, 2007d). From this data base of publicly funded
substance abuse treatment admissions in the US, we extracted those between
12-17 years old entering with a primary problem of heroin (n= 2758) or
prescription opioids (n=2201). The timeframe of TEDS admissions was from
2004-5, which matched the study recruitment period.
1.3. Setting
The study was conducted at an adolescent substance abuse treatment program
whose features are described elsewhere (Clemmey et al., 2004; Fishman,
2003). Adolescents with OUD typically enter the residential setting at
this treatment center; these residential admissions contributed 69% (n =
65) of the study sample (33 heroin, 32 prescription opioid users). Twenty
of the study participants (19=heroin and 1=prescription opioid user) were
recruited from the outpatient NIDA Clinical Trials Network (CTN) study of
buprenorphine treatment for opioid dependent adolescents/young adults
which was conducted at this site. The remainder (n = 9) were recruited
from non-CTN study admissions to its outpatient treatment program.
1.4. Data Analyses
To compare group differences, data were analyzed using Pearson chi-square
tests for categorical characteristics and independent t-tests for
characteristics with continuous data using SPSS version 13® (SPSS, 2004).
The TEDS data were similarly analyzed using Pearson chi-square tests to
determine differences between those with a heroin problem vs. those with
prescription opioid problem.
Other Sections▼
1. Introduction2. Methods3. Results4. DiscussionReferences3. Results
1.5. Demographic and social characteristics
Table-1 displays these characteristics for the two groups: OUD
prescription opioids (n=41) and OUD heroin users (n=53). For the
demographic factors examined, both groups were similar: 50-60% were male;
most were between the ages of 15-17 years; race was predominantly
Caucasian; and residence was outside Baltimore City (i.e., suburban
residence). Mean age of OUD heroin group was 17.2 compared to 16.6 yrs for
the OUD prescription opioid group (p=0.019, results not shown in Table 1).
Both groups were likely to have been in a residential level of treatment
at this site, although the prescription opioid group was more likely to be
court ordered for treatment.
Table 1
Demographic, Social and Treatment Characteristics: OUD non-heroin
Prescription Opioid Users Versus Heroin Users

Of the social factors examined, the two groups did not differ in regards
to family characteristics but were significantly different on
school-related features. The heroin users were less likely to be in school
or to have graduated; prescription opioid users were more likely to report
being suspended.
1.6. Substance use characteristics
3.2.1. Substance Use Disorders
Rates of past-year DSM-IV SUD diagnoses were significantly different for
the two groups. Compared to the heroin OUD group, the prescription OUD
group was more likely to have concurrent cannabis, alcohol, sedative and
other stimulant use disorders. Rates of cocaine use disorders were present
in over 50% of both groups. The prescription OUD group was also more
likely to have multiple SUD (3 or more) diagnoses and significantly
greater mean number of past year SUD diagnoses when compared to the heroin
users (4.3 vs. 2.8). Almost all heroin users (98%) compared to
approximately 3/4th of prescription opioid OUD adolescents met criteria
for DSM-IV past-year opioid dependence diagnosis.
3.2.2. Age of Onset
The mean age of onset of meeting criteria for a DSM-IV cannabis and
cocaine use disorders (the latter approaching significance) was lower for
the prescription users. The mean age of onset of regular use of marijuana
and alcohol (among those with a SUD diagnoses) was significantly lower for
the prescription users than heroin users (results not shown in table-2).
For both groups, age of onset of regular use and SUD diagnoses were
earlier for alcohol and marijuana and later for cocaine and opioids; the
mean age of onset of meeting criteria for OUD was on average 6 months
following the mean age of onset of regular use of any opioids (15.7 and
15.1 yrs, respectively).
Table 2
Substance Use Characteristics: OUD non-heroin Prescription Opioid
Users (n=37)Versus Heroin Users(n=57)

3.2.3. Recent Substance Use
There were significant differences between the groups on rates of past
30-day use of individual substances (SUD diagnoses showed a similar
pattern of between group differences,). The OUD prescription opioid group
was more likely to have used prescription opioids, alcohol and marijuana
(the latter approaching significance) while the OUD heroin group was more
likely to have used heroin (per group assignment) and cocaine (the latter
approaching significance) and less likely to have used prescription
opioids (i.e. 45%) in the past 30 days. Figure-1 illustrates differences
in the distribution for self-reported “drug of first choice” for the two
groups (Pearson’s X2 = 64.48, p=0.000). The heroin users reported heroin
(77%), prescription opioids (15%), or cocaine (8%) as their first drug of
choice. In contrast, the prescription OUD group was more diverse in their
report, with marijuana (46%), prescription opioids (27%), cocaine (15%),
alcohol (7%) and other drugs (5%) identified as first choice.

Figure 1
Self-reported “Drug of First Choice” Among Prescription-using and
Heroin-using Adolescents with Opioid Use Disorder

Additional analyses of lifetime use (not shown in Table 2) showed that
virtually all OUD adolescents had used marijuana and alcohol; and 90% of
heroin users reported having ever used prescription opioids. However,
fewer prescription opioid than heroin use participants had ever tried
heroin (22% vs. 100%, p=0.000) or cocaine (70% vs. 98%, p=0.001).
3.2.4. Criminal Behaviors
Both groups had high rates of past-year criminal behaviors, but
prescription opioids users were more likely to report selling drugs and
damaging property. In addition, the prescription OUD group was more likely
to initiate these behaviors at significantly younger ages than the heroin
group (results not shown in Table-2). However, prescription opioid users
were no different from heroin users in rates of being on probation.
1.7. Psychiatric characteristics and treatment history
3.3.1. Current Axis-I DSM-IV Psychiatric Disorders
Overall, both groups had high rates of any psychiatric disorders (83%) but
prescription opioid users presented with higher rates of current ADHD and
manic episode while there were higher rates of MDE among heroin users
(approaching significance). When the data were combined for the two
groups, prevalence of psychiatric disorders ranged from CD (53%), MDE or
GAD (40%), ADHD (33%) to other disorders (15-26%). Similarly, mean ages of
onset of these psychiatric disorders were no different for the two groups
with the exception of earlier onset of MDE among prescription opioid
users. Both groups reported similar rates of suicide attempts in the past.
Rates if admissions on psychotropic medications did not differ between the
two groups.
3.3.2. BDI Scores
Although both groups reported moderately high depressive symptoms (15.9
vs. 18.2, n.s.), a higher proportion of heroin users (76 vs. 54%, p=0.029)
scored in the mild to moderately depressed range (i.e. BDI > 11) (results
not shown in table-3).
Table 3
Psychiatric Characteristics and Treatment History: OUD heroin user
versus OUD non-heroin Prescription opioid Users

3.3.3. Past Treatment Utilization
The heroin OUD group was more likely to have prior SUD or dual diagnoses
treatment while more of the prescription opioid OUD group reported having
received only past psychiatric treatment. There were some differences in
rates of medications prescribed for psychiatric disorders in the past: the
prescription opioid OUD was more likely to have taken ADHD meds while
heroin users were more likely to have had medications for anxiety
disorders. The groups did not differ for past use of meds for depression
or mania.
1.8. HIV/Hepatitis C-risk characteristics
There were substantial differences in rates of IDU. None of the
prescription opioid using adolescents reported any past 30-day IDU, while
73% of heroin using adolescents injected drugs and on average injected on
20 out of the past 30-days. Approximately half of injection users in the
heroin group reported sharing needles or “works” during this time. Over
3/4th of both groups were sexually active in the past 30-day period but
there were no differences on rates of sexual HIV-risk behaviors.
1.9. Comparison of Study Sample with TEDS 2004-5 Sample
A comparison of our single site sample of 12-17 year olds with OUD (n= 63)
to the TEDS sample of those with a primary problem with heroin or other
opioids (n=4959) showed that the two samples were similar on several of
the comparable characteristics (results not shown in tables): 15-17 year
olds (our site 97 vs. TEDS 93%); females (44% vs. 49%); Caucasian race
(91% vs. 89%); and few with 12 or more years of education (7% vs. 10%).
However, they differed on rates of court order to treatment (18% vs. 29%)
and proportion receiving treatment in a residential setting (64% vs.
41%).(Substance Abuse and Mental Health Services Administration Office of
Applied Studies, 2007d)
Other Sections
1. Introduction2. Methods3. Results4. DiscussionReferences4. Discussion
This study provides preliminary information filling critical gaps in the
literature by distinguishing between the intake characteristics of a
clinical population of prescription opioid-using adolescents meeting
criteria for OUD from those of heroin users with OUD. Some of the
sociodemographic features reported in this study are consistent with
existent literature on heroin users (Clemmey et al., 2004) or prescription
opioid users (McCabe et al., 2005); both groups consisted of older teens
(mean age 17years; range 15-18 years), predominantly of Caucasian race
(89%), with a relatively high proportion of females (45%) compared to
typical rates of 31% females in substance abuse treatment samples (SAMHSA
Office of Applied Studies, 2007a) and residing in suburban locations
(outside of Baltimore City). These findings suggest a common background of
origin among OUD adolescents who use heroin vs. prescription opioids. That
these teens, despite their social and cultural similarities, have chosen
to use different forms of opioid drugs, suggests the existence of
differences in drug preferences and/or access among these older, White,
suburban OUD teens. How these choices develop is a question that cannot be
answered by the data from this study. However, it is clear from anecdotal
clinical information that acquisition of heroin versus prescription
opioids entails very different scenarios. For example, heroin is typically
available from drug dealers in the city; whereas prescription opioids are
available through an informal network of suppliers in the suburbs. Thus,
there is more risk and effort involved in obtaining heroin. However,
prescription opioid use can escalate readily to a habit that is more
costly (anecdotal evidence and patient reports suggest that street costs
of prescription opioids are higher than equivalent doses of heroin) than a
comparable heroin habit, a factor that could shift choice from
prescription opioids to heroin. This is also suggested by the study data
that while 90% of the heroin users report lifetime prescription opioid
use, only 45% report use in the past 30 days. Another factor in the choice
is influence by older heroin-using peers and/or sexual partners
(especially in the case of females) which may fast track initiation to
heroin use. Finally, there are attitudinal factors in play among
adolescents. On a national survey, 2 in 5 teens stated that abusing
prescription medications was “much safer than illegal drugs” (The
Partnership for a Drug Free America, 2006); In addition to this
misperception, teens may also express a stigma towards heroin as a
“junkie” drug. Future studies are needed to explore these pathways of
selection of opioids among OUD adolescents.While both groups had multiple
comorbidities, the heroin using adolescents stood out on three serious
problems areas, which place them at added risk for ongoing problems and
long-term debilitation. Heroin users were more likely to: a) have dropped
out of school; b) have met DSM-IV opioid dependence diagnosis criteria;
and c) report injection use and needle sharing behaviors. Not completing
high school (65%) is a serious concern, as it has been linked to life of
extended poverty and increased risk for criminal behaviors (Harlow, 2003;
Iceland, 2005). Virtually all heroin users (98%) presented with current
opioid dependence diagnosis as compared to 76% of prescription users (with
the remainder meeting criteria for opioid abuse). Since both groups had
average histories of opioid use of approximately 2 years, this suggest
that progression to dependence on opioids is faster for heroin than for
the prescription opioids, or that those who became dependent on pills have
switched to heroin. Alternatively, the dose and frequency of opioid use
maybe generally lower among prescription opioid than heroin users so that
dependence takes longer to develop with prescription opioids than with
heroin. These and other trajectories need further examination. Whatever
the pathway, progression to opioid dependence is a risk because it places
adolescents in a more advanced and compulsive use stage of addiction,
which may make them more resistant to treatment. Recent heroin use by an
intravenous route was seen exclusively in the heroin group (73% vs. 0%)
with half of intravenous users reporting sharing needles. These behaviors
are well known high risk factors for Hepatitis-C and HIV infection (Center
for Disease Control and Prevention, 2002, 2007) with potential for severe
and debilitating medical illnesses associated with high morbidity and
mortality.Prescription opioid users, on the other hand, manifested with a
very different clinical profile. First, they were likely to use and abuse
a larger number of non-opioid substances including marijuana, alcohol,
sedatives and other stimulants and to present with multiple concurrent SUD
diagnoses. Second, they were more likely to be court ordered to current
treatment. Finally, despite high rates of psychiatric disorders for the
two groups, the prescription opioid users were more likely to have current
ADHD, be prescribed medications for ADHD and have received past
psychiatric treatment.The prescription opioid users self-reported
preference for a variety of substances as “drug of first choice” (unlike
the overwhelming preference for heroin among heroin users). This suggests
that teens who report marijuana as their drug of first choice may benefit
from closer screening for abuse/dependence on other substances for which
they report a less favorable preference/liking. However, adolescents who
present with histories of abusing multiple substances pose a challenge to
treatment planning because polydrug users may be motivated to stop opioids
but not other substances. Furthermore, multiple substance use has been
linked to poorer treatment outcomes (Ciraulo et al., 2003). The selection
of sedatives and other stimulants (which are also prescription
medications) for polysubstance use is consistent with a “pill” subculture
and a marketplace within suburban communities and also consistent with the
lower risk perception of pill abuse (The Partnership for a Drug Free
America, 2006).It was also interesting that prescription opioid users were
5 times more likely to be court ordered to treatment (34% vs. 6%) even
though both groups resided in the suburbs and had similar rates of
criminal behaviors and probation status. A possible explanation may lie in
the type of criminal acts in which these youth engaged (e.g. drug selling
and property damage) leading to more juvenile justice involvement, and
subsequent treatment referrals. It is also possible that the prescription
opioid users were more likely to commit their crimes within suburban
environments and thus more easily come to the attention of local criminal
justice authorities.A final distinguishing feature was the higher
prevalence of current ADHD (47% vs. 21%), higher rates of having been
prescribed medications for ADHD (56% vs. 19%) and higher utilization of
psychiatric treatment in the past (68% vs. 41%) among the prescription
opioid users. In the case of these youth, the disruptive nature of higher
rates of ADHD (and school suspension) may have resulted in better
identification by the school systems leading to the use of psychiatric
services. The higher rate of prior prescriptions for ADHD medications
needs to be explored further to determine if it suggests either
self-medicating and/or priming for prescription medication abuse. Prior
engagement in psychiatric treatment has also been reported among
prescription abusing opioid dependent adults in methadone maintenance
treatment (Brands et al., 2004).High rates of depression among adult
heroin users has been well documented, which is consistent with the
somewhat higher rates of MDE in the heroin versus prescription opioid use
samples in this study. Since age of onset of MDE (12.5 years) preceded the
age of onset of OUD (15.7 years), this study supports the theory that MDE
is a potential risk factor in the development of heroin dependence. It is
also likely that the MDE was perpetuated by a difficult and distressed
lifestyle of heroin addicted youth.The differences highlighted above ought
not to overshadow important similarities. Both groups presented with
substantial psychiatric comorbidity. Over 3/4th had a DSM Axis –I
psychiatric disorder and over half had two or more disorders. Moderate
depressive symptoms (mean BDI scores of 16.9) were reported in both
groups. Another important similarity was that approximately 40% of the
study sample engaged in recent sexual HIV-risk behaviors such as having
multiple sexual partners and always having unprotected sex. For both
groups, marijuana or alcohol served as a precursor to regular use of
opioids. The treatment implications of these findings are that most OUD
adolescents may benefit from expanding the focus of treatment to include
integrated psychiatric treatment and HIV-risk reduction education.4. 1.
Limitations
This is a treatment-seeking sample; therefore, results may not generalize
to community populations. The small sample size precluded separating out
mixed users of heroin and prescription opioids from those who used one or
the other type of opioid exclusively. A more refined analysis might shed
additional light on the risk patterns of opioid use among adolescents.
Since this was a cross-sectional study, we were unable to make causal
inferences. The use of outside informants and urine drug screens may have
increased the validity of self-reports, although we attempted to address
this issue by informing participants of a Federal certificate to ensure
their confidentiality and conducting interviews by well-trained
psychiatrists and/or research staff. The predominantly residential
treatment sample may have biased results as those assigned to residential
levels of care typically present with higher severity and co-occurring
psychiatric disorders.
4. 2. Implications and future directions
The differential profiles of prescription opioid and heroin using
adolescents that emerged in this study have implications for treatment.
Despite the fact that very few OUD adolescents receive opioid
agonists/antagonist medications during SUD treatment (SAMHSA Office of
Applied Studies, 2007d) evidence is emerging that buprenorphine is
effective in the management of opioid dependent youth (Marsch et al.,
2005; Woody et al., 2008). While heroin users present a profile which
suggests that they would benefit from agonist treatment, future studies
are needed to determine if opioid agonists have a role in the treatment of
prescription opioid users who have a mixed profile of drug use and who may
not always meet opioid dependence criteria. Further study is needed to
determine if differences in baseline profiles between the two groups
influence treatment outcomes. The results also suggest the need for
tailored treatments for this “special needs” population of OUD
adolescents, that presents with multiple co-occurring problems. Treatment
is needed both to serve the group as a whole and to specifically target
the drug preference subtypes addressing their unique needs.

Table 4
Past 30-Day HIV-Risk Behaviors: OUD non-heroin Prescription Opioid
Users Versus Heroin Users

Footnotes
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Contributor Information
Geetha A. Subramaniam, Department of Psychiatry, Johns Hopkins University,
C/O Mountain Manor Treatment Center, 3800 Frederick Ave, Baltimore, MD
21229. Phone: 410-233-1400; Fax: 410-233-1666, Email:
gsubram@jhmi.edu ;Maxine A. Stitzer, Johns Hopkins University, Clinical
Trials Network, 5510 Nathan Shock Dr., Ste 3040, Baltimore, MD 21224;
Other Sections▼
1. Introduction2. Methods3. Results4. DiscussionReferencesReferences
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