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Addictive Behaviors

journal homepage: www.elsevier.com/locate/addictbeh

Short Communication

Increased use of heroin as an initiating opioid of abuse: Further considerations and policy implications

Theodore J. Cicero⁎, Zachary A. Kasper, Matthew S. Ellis Washington University in St. Louis, Department of Psychiatry, Campus Box 8134, 660 S. Euclid Avenue, St. Louis, MO 63110, United States

H I G H L I G H T S

• Heroin as the first opioid of abuse has grown significantly in the past decade. • Past month heroin use continues to grow as prescription opioid abuse declines. • Opioid policies need to be more inclusive of heroin, rather than prescription opioid-specific.

A B S T R A C T

Introduction: Previously, we reported a marked increase in the use of heroin as an initiating opioid in non- tolerant, first time opioid users. In the current paper, we sought to update and expand upon these results, with a discussion of the policy implications on the overall opioid epidemic. Methods: Opioid initiation data from the original study were updated to include surveys completed through 2017 (N = 8382) from a national sample of treatment-seeking opioid users. In addition, past month abuse of heroin and prescription were analyzed as raw numbers of treatment program entrant in the last five years (2013–2017), drawing from only those treatment centers that participated every year in that time frame. Results: The updated data confirm and extend the results of our original study: the use of heroin as an initiating opioid increased from 8.7% in 2005 to 31.6% in 2015, with increases in overall Ns per initiation year reflecting a narrowing of the “treatment gap”, the time lag between opioid initiation from 2005 to 2015 and later treatment admission (up to 2017). Slight decreases were observed in treatment admissions, but this decline was totally confined to prescription opioid use, with heroin use continuing to increase in absolute numbers. Conclusions: Given that opioid novices have limited tolerance, the risk of fatal overdose for heroin initiates is elevated compared to prescription opioids, particularly given non-oral administration and often unknown purity/adulterants (i.e., fentanyl). Imprecision of titrating dose among opioid novices may explain observed increases opioid overdoses. Future policy decisions should note that prescription opioid-specific interventions may have little impact on a growing heroin epidemic.

1. Summary of previous article

In a recent article in this journal, Increased use of heroin as an in- itiating opioid of abuse (Cicero, Ellis, & Kasper, 2017), we concluded that there was a significant increase in the number of treatment-seeking opioid users whose first experience with an opioid was with heroin, rather than the more recently commonplace pattern of initiating opioid use with prescription drugs. These results suggest that novice, non- tolerant opioid users may have a much higher risk of overdose death due to inexperience in the titration of dose, particularly if fentanyl analogues are involved, and that these may be contributing to

continued increases in heroin-related overdose fatalities and emergency room visits (O'Donnell, Gladden, & Seth, 2017; Rudd, Seth, David, & Increases in Drug, 2016; Seth, Scholl, Rudd, & Bacon, 2018). However, there were some ambiguities in our data given the relatively low numbers of individuals represented in more recent years for which we had data. Thus, we felt the need to update our data after the original article went to press in order to validate our original findings and un- derscore the importance of the ‘treatment gap' in interpreting our data. That is, there is a time lag between initial opioid exposure and treat- ment admission, which accounted for the lower overall numbers in more recent years. In addition, the brevity of our article did not allow

https://doi.org/10.1016/j.addbeh.2018.05.030 Received 7 May 2018; Received in revised form 29 May 2018; Accepted 30 May 2018

⁎ Corresponding author at: Department of Psychiatry, Washington University in St. Louis, School of Medicine, Box 8134, 660 S. Euclid Ave., St. Louis, MO 63110, United States. E-mail address: [email protected] (T.J. Cicero).

Addictive Behaviors 87 (2018) 267–271

Available online 31 May 2018 0306-4603/ © 2018 Published by Elsevier Ltd.

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us to expand on two areas of concern. First, our article did not fully assess policy implications of our data and the extent of concern they might appropriately generate on the public health burden of the opioid epidemic. Second, we also did not sufficiently discuss how recent in- terventions to reduce the supply of prescription opioids may have im- pacted the opioid epidemic as a whole, in particular its influence on this new pathway to heroin initiation, which bypasses the more commonly studied progression from prescription opioids to heroin. As such, we felt the need to more clearly remove some ambiguity in our data and, most importantly, to more intensely discuss the policy implications of our work in this clarification article. To do so, we have included an updated report on our previously published data, as well as a supplemental analysis of opioid treatment admission data and the implications of these data for policy development.

2. Methods for original, updated and supplemental data

While the specifics of our data analysis can be reviewed in the original article, briefly, our data are sourced from the ongoing nation- wide Survey of Key Informants' Patients (SKIP) Program, a key element of the Researched Abuse, Diversion and Addiction-Related Surveillance (RADARS®) System, a comprehensive series of programs that collect and analyze post-marketing data on the abuse and diversion of pre- scription opioid analgesics and heroin (Cicero et al., 2007; Dart et al., 2015a). The SKIP Program consists of a Key Informant network with annual participation of approximately 150 public and privately funded treatment centers which recruit adult clients entering their substance abuse treatment program with a primary diagnosis of opioid use dis- order to complete an anonymous paper survey. Initially, SKIP re- spondents, analyzed from 2011 to 2016, were asked the specific opioid they first regularly used (i.e. 2+ times a month), categorized as ‘hy- drocodone’, ‘oxycodone’, ‘heroin’, or ‘other prescription opioids’ [bu- prenorphine, fentanyl, hydromorphone, methadone, morphine, oxy- morphone, tapentadol and tramadol], and the age they began to regularly use opioids. The year regular use began was calculated (Year of survey completion – Age at survey completion + Age of first regular opioid use = Year of beginning regular opioid use), with the analyses restricted to those initiating use within the past ten years (2005–2015; N = 5885) to limit long-term recall and survival bias (no respondent who completed a survey in 2016 initiated opioid use in that same year), a time-period shown to have stable recall for opioid abuse (Shillington,

Cottler, Mager, & Compton, 1995). These data have been updated for this report using the same criteria and analysis period, with the inclu- sion of data from surveys received through the end of 2017.

We also conducted an analysis of the absolute numbers of in- dividuals who entered and were recruited from each treatment program per year, restricting our analysis to only those sites that recruited in every year of the analysis period (N = 66) to analyze a stable sample of treatment providers. These sites were located in 33 states and saw a mean number of 53.3 new opioid patients per quarter (range: 5–400), with a breakdown of 54.5% private, 30.3% public and 15.2% both private and public. Data are presented as the total number of partici- pants entering treatment and recruited by the site, with a breakdown of the number of whom endorsed past month abuse of heroin and/or a prescription opioid from the past five years (2013–2017), with the data not mutually exclusive.

3. Results

3.1. Heroin as an initiating opioid

Fig. 1 shows trendlines from the original published figure, re- presented as dotted lines, and updated trendlines (solid line). The lower numbers on the x axis represent the original N at each time point whereas the upper numbers shows the increase in Ns after the inclusion of data through 2017 (N = 8382). As can be seen, there was a con- siderable increase in numbers as data has accumulated, but the trends remained the same. Heroin use as a first opioid grew sharply from 8.7% of the sample in 2005 to almost 31.6% in 2015. It should be noted that the numbers in more recent years increased due to the addition of new data bridging the treatment gap. That is, there is a time gap between initial opioid exposure which occurred from 2005 to 2015 and treat- ment admission from 2011 to 2017, which accounts for the lower overall numbers in more recent years. But, as this figure demonstrates, as data continue to be collected, these overall numbers will continue to increase as the treatment gap narrows.

3.2. Opioid treatment admissions

To adjust for the treatment gap (i.e. decrease in the Ns over time), we expressed data in Fig. 1 as the proportion of the total who used a prescription opioid or heroin as their initial opioid. This mode of data

Fig. 1. First opioid of regular abuse among opioid initiates from 2005 to 2015 (N = 8382).

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presentation, while a correct representation of the data, could be sus- pect if the number of people entering treatment selecting either a prescription opioid or heroin declined, particularly if prescription opioids declined at a faster rate than heroin. To test the validity of this hypothetical scenario we examined the raw number of patients entering the treatment clinics participating in the SKIP program in the last five years who indicated past month abuse of heroin and/or a prescription opioid. These data are shown in Fig. 2. The total number of those en- tering our stable sample of treatment centers decreased modestly over time (from 1598 to 1421) implying a decrease in overall opioid use if viewed as a whole. However, this overall decrease was solely attribu- table to decreases in past month prescription opioid abuse (from 1453 to 1197) The numbers of those endorsing past month abuse of heroin continually increased over the past five years (from 723 to 980). While participants could endorse both prescription opioids and heroin, the data is presented separately in order to depict the total number of users for each drug category.

4. Discussion

4.1. Overview of results

Our data support prior research which indicate that supply reduc- tion efforts centered on prescription opioids appear to be having an effect in reducing abuse of prescription opioids (Dart et al., 2015b). The most dramatic reductions we observed was for oxycodone and hydro- codone, with modest, variable increases in other prescription opioids. While the foregoing data represent the positive news in a sense, there are two issues highlighted by these data. First, as our opioid initiation data continue to be updated with increasing Ns, the trend of increases in heroin initiation remain prevalent and of grave concern. Second, while the raw numbers of treatment admissions for opioid use disorder show slight decreases, this looks to be attributable solely to decreases in past month prescription opioid abuse. Specifically, prescription opioid abuse decreased, but heroin use increased in absolute numbers. While prescription opioid abuse still outweighs heroin use at the moment, these data suggest supply side interventions focused on prescription opioids alone may have little impact on heroin use. In fact, the decrease

in overall opioid treatment admissions seen in our data may be tem- porary, with the real possibility that the overall number of opioid treatment admissions will go back up over time as heroin use continues to increase and outweighs prescription opioid abuse.

4.2. Importance of increases in heroin use

Prior research has demonstrated the progression to heroin from those initiating with prescription opioids, often as a result of practical issues (e.g., cost), reformulations of preferred opioids, or due to re- ductions in the ability to obtain prescription opioids (Unick, Rosenblum, Mars & Ciccarone, 2013; Cicero & Ellis, 2015; Compton, Jones, & Baldwin, 2016; Harocopos & Allen, 2015). However, heroin markets have apparently markedly ramped up production and dis- tribution of this drug into the United States, seeking to capitalize on the demand for opioid drugs (Opsina, Tinajero, & Jelsma, 2018; Rosenblum, Unick, & Ciccarone, 2014). Coupled with reports of a re- duced stigma in the use of heroin among previously risk-averse popu- lations (Cicero, Ellis, Surratt, & Kurtz, 2014), it is perhaps not surprising that widely available and cheap heroin would supplant prescription opioids as an initial opioid of abuse. While it is hard to say one – pre- scription opioid or heroin – is better/worse than the other, it cannot be denied that new initiates to opioid use through heroin are at increased risk of overdose than those with prior experience to prescription opioid due to a number of factors: 1) as opposed to prescription pills with marked dosage, heroin typically has a purity unknown to the user; 2) additives such as the far cheaper fentanyl and its dangerous analogues (e.g., carfentanyl) may be mixed with the heroin; 3) estimating the dose is difficult for even experienced users; and 4) an opioid naive individual who has not yet become tolerant to opioids may be at risk of overdose with even a singular exposure due a combination of one or more of these factors. The risk of overdose is thus markedly higher in these new users than it would be in maximally tolerant, long-term users. This may account for the rapidly escalating number of overdose deaths experi- enced in recent years (Rudd et al., 2016; Seth et al., 2018). While most overdose data lacks information relevant to the characteristics of opioid exposure, it is difficult not to conclude that at least some of this increase is due to inexperienced, first time users underestimating their dose. Of

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Fig. 2. Number of treatment-seeking opioid users recruited from a stable sample of 66 Key Informant sites from 2013 to 2017, with the number of those endorsing past month heroin use and/or past month abuse of at least one prescription opioid, with data not mutually exclusive.

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course, the growing rise in the use of fentanyl analogues as an addition to street purchased heroin has certainly increased the risk of overdose in all users, but it is hard to disagree that heroin use in opioid naive individuals isn't a definitive risk factor contributing to this increase in opioid overdose deaths.

4.3. Policy implications

Our data indicate that while supply reduction efforts targeting prescription opioid abuse may have been successful in easing the pre- scription opioid epidemic, they have done little to reduce either past month abuse or opioid initiation of heroin. In fact, these prescription opioid-specific interventions may also have contributed, to some extent, to part of this increase in heroin use. However, our data suggest the possibility of a stand-alone heroin epidemic that current prescription opioid-centered interventions will have little to no effect on as the prescription opioid to heroin pathway is replaced by initiation to opioids with heroin directly. Clearly, there needs to be a concerted effort to adjust our prevention, intervention and treatment protocols to more adequately prepare for an expanding heroin epidemic.

While we need to continue to consider supply-side interventions in the context of both prescription opioids and heroin, there are several other factors that need to be taken into account in order to develop an effective, multi-level policy approach. First, harm-reduction should play a central role in policy development, including expansion of needle exchanges, safe injection sites, fentanyl tests strips and Narcan. These can provide immediate intervention to saving lives, but they must also be coupled with an increase in evidence-based prevention efforts and programs that emphasize the high risk of overdose for not only ex- perienced users, but those who lack any opioid tolerance whatsoever. Second, expanding access to medication-assisted treatment (MAT) is both crucial and time-sensitive. A number of provider level barriers need to be immediately addressed such as training, reimbursement, access to mental health services, access to specialists for non-addiction specialists and dissemination of information to dispel myths or bias of MAT (DeFlavio, Rolin, Nordstrom, & Kazal Jr, 2015; Huhn & Dunn, 2017; Kermack, Flannery, Tofighi, McNeely, & Lee, 2017). Finally, the demand side is equally, if not more important as a point of interven- tion/prevention. If individual users' attraction to an opioid continues to escalate, it matters not which opioid they've taken, but rather what is so reinforcing about these drugs. Until we recognize this, the number of people dependent on opioids will continue to rise, as will the devasta- tion of opioid overdose deaths. Several reports have emphasized the role mental health treatment and prevention will play in reducing the opioid epidemic in the long-term (Howe & Sullivan, 2014; Srivastava & Gold, 2018), but it needs to be stressed that the opioid epidemic is a layered one, and the policy response must be as well in order to reduce the current opioid epidemic in the United States.

Role of funding source

The national data were collected from a subset of participants from the Survey of Key Informants' Patients (SKIP) Program, a component of the RADARS® (Researched Misuse, Diversion and Addiction-Related Surveillance) System. The RADARS System is supported by subscrip- tions from pharmaceutical manufacturers for surveillance, research and reporting services. RADARS System is the property of Denver Health and Hospital Authority, a political subdivision of the State of Colorado. Denver Health retains exclusive ownership of all data, databases and systems. Subscribers do not participate in data collection or analysis, nor do they have access to the raw data. Dr. Cicero serves as a paid consultant on the Scientific Advisory Board of the RADARS® System. None of the authors have a direct financial, commercial or other re- lationship with any of the subscribers of the RADARS® System.

Contributors

The corresponding author oversaw the development, implementa- tion and management of the studies involved and takes responsibility for the integrity of the data and the accuracy of the data analysis, which was conducted by Ellis and Kasper, in conjunction with the corre- sponding author. Authors Cicero and Ellis developed and wrote the manuscript. All authors have reviewed and approved the manuscript.

Conflict of interest

Author Cicero serves as a consultant on the Scientific Advisory Board of the non-profit post-marketing surveillance system, RADARS®. Authors Ellis and Kasper have no conflicts of interest to report.

Acknowledgements

The national data were collected from a subset of participants from the Survey of Key Informants' Patients (SKIP) Program, a component of the RADARS® (Researched Misuse, Diversion and Addiction-Related Surveillance) System. The RADARS System is supported by subscrip- tions from pharmaceutical manufacturers for surveillance, research and reporting services. RADARS System is the property of Denver Health and Hospital Authority, a political subdivision of the State of Colorado. Denver Health retains exclusive ownership of all data, databases and systems. Subscribers do not participate in data collection or analysis, nor do they have access to the raw data.

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