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Contents lists available at ScienceDirect
Neuropharmacology journal homepage: www.elsevier.com/locate/neuropharm
Invited review
Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research Q7
Karen K. Gerlach a, *, Nabarun Dasgupta b, Sidney H. Schnoll a, Jack E. Henningfield a, c a
Pinney Associates, Inc., 4800 Montgomery Lane, Suite 400, Bethesda, MD 20814, USA Injury Prevention Research Center, University of North Carolina, Chapel Hill, NC 27599, USA c The Johns Hopkins University, School of Medicine, Baltimore, MD 21229, USA b
a b s t r a c t Keywords: Stimulant surveillance Abuse Misuse Illicit stimulants
Stimulants are a diverse array of drugs that range from everyday caffeine to prescription medications and illicitly manufactured street drugs. The surveillance of misuse and abuse of stimulants many times confounds prescription and illicit street drugs such that the data are not specific enough to guide mitigation efforts or assess their impact. This review highlights the surveillance efforts that are conducted in the United States (US) for stimulant misuse and abuse. These surveillance efforts include national level surveys as well as reporting systems such as Poison Centers and emergency departments. This epidemiologic analysis has implications for interpreting the current known neuropharmacology of stimulants and possibly informing future neuropharmacology research that may contribute to a better understanding of potential neuropharmacologic factors influencing differing patterns of use, abuse, and adverse consequences associated with various stimulants. This article is part of a Special Issue entitled ‘CNS Stimulants’. Ó 2014 Published by Elsevier Ltd.
1. Introduction The drugs known collectively as “stimulants” are a diverse category including caffeine and relatively weak prescription stimulants such as mazindol and phentermine, which are not the focus of this review. Rather, this review will address the stronger stimulants, including those approved for the treatment of attention deficit/hyperactivity disorder (ADHD) (methylphenidate and various amphetamine molecules) and illicitly manufactured crack cocaine and methamphetamine formulations. These drugs are regulated as Schedule II drugs under the Controlled Substances Act (CSA) in the United States (US) and comparable schedules in other countries. Schedule II is reserved for drugs that carry the highest risk of abuse and dependence yet also are approved for medicinal use. Illicitly produced methamphetamine (“ice”) and crack cocaine are not approved for medicinal use, but they are also placed in Schedule II because pharmaceutical methamphetamine and cocaine do have approved medicinal uses (Drug Enforcement Administration, 2014; Spillane and McAllister, 2003).
* Corresponding author. Pinney Associates, 201 N. Craig Street, Suite 320, PA 15213, USA. Tel.: þ1 412 567 1751; fax: þ1 412 687 4855. E-mail addresses: [email protected], gbittner@pinneyassociates. com (K.K. Gerlach).
The Schedule II stimulants methylphenidate, amphetamines, and cocaine are characterized with similar abuse potential profiles under a variety of laboratory tests of abuse liability, and they share generally similar pharmacologic actions as discussed in this issue of Neuropharmacology (Calderon, in this issue; Kreek, in this issue; Lukas, in this issue; Romach et al., in this issue). Outside the laboratory, however, these drugs are associated with widely different patterns of use, risk of substance use disorders (American Psychiatric Association, 2013), and adverse effects including overdose leading to emergency room visits. For example, as discussed in this review, methylphenidate and prescription amphetamine products indicated for the treatment of ADHD are infrequently the primary drug of abuse cited by people presenting for treatment for substance abuse or as a cause of overdose as compared to illicitly manufactured methamphetamine (e.g., “ice”) or cocaine (e.g., “crack”) (O’Brien, 2011; Substance Abuse and Mental Health Services Administration, 2013; Zosel et al., 2013). Clearly the mechanisms of action and general pharmacology of these drugs do not appear to explain these differences, although variations in reinforcing effects perhaps related to speed of absorption to the brain and other pharmacologic differences cannot be entirely ruled out [see also (Calderon, in this issue; Romach et al., in this issue)]. Are there subtle but perhaps important neuropharmacologic differences among these drugs that help explain the differing patterns
http://dx.doi.org/10.1016/j.neuropharm.2014.04.020 0028-3908/Ó 2014 Published by Elsevier Ltd.
Please cite this article in press as: Gerlach, K.K., et al., Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research, Neuropharmacology (2014), http://dx.doi.org/10.1016/j.neuropharm.2014.04.020
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and risks of abuse? Are the differences better explained by social and environmental factors, cost, access, drug formulation, route of administration, population, or reasons for use? Four decades of surveillance and epidemiologic analyses may help to understand and explain these differences. What can we learn from the epidemiology that might be considered in neuropharmacologic investigations? What can we learn from current epidemiologic understanding that may be considered in future surveillance approaches? Addressing these two questions is the focus of this brief review. 1.1. The need for adequate surveillance Epidemiologic analysis requires reliable, valid, and relevant surveillance that keeps pace with an epidemic as it unfolds over time and across populations. It is clear that trends in stimulant misuse and abuse have changed dramatically over the past half century teaching us much about the importance of factors far beyond the pharmacology of the drugs as determinants of which drugs are used, how they are used, patterns of use within individuals, and consequences associated with various types of stimulant misuse and abuse. Unfortunately, the most frequently cited surveillance methods have not always kept pace with changing patterns of use and abuse and therefore, the resulting policy analyses rely on methods and data that may be of diminished relevance to current and evolving patterns of stimulant abuse. In order to have an accurate and adequate understanding of the scope and scale of any ongoing public health problem, there needs to be a substantial, systematic surveillance effort in place; it must provide both consistent elements for comparative purposes over time as well as evolving components to keep pace with evolving trends in drug use form, patterns and reasons. Addressing the problem with science-based interventions places further demands on surveillance, specifically that it include information such as the reasons for use and other factors associated with use, including those that might be considered risk factors and protective factors. With an appropriate surveillance system, one can track trends over time, detect new problems as they occur, and lay the foundation for interventions to prevent and control misuse and abuse, and mitigate unintended and undesired consequences. This is increasingly important for prescription drugs since they have legitimate medical uses. Intervention strategies that may reduce misuse and abuse, but also reduce the availability of the medications for patients that need them, can result in more harm than good for patients with legitimate medical need. One example of surveillance that assesses both positive and negative factors influencing misuse and abuse is the nearly four decades of the Monitoring the Future (MTF) Survey (Johnston et al., 2013). This survey not only provides estimates of prevalence and trends, but it also has highlighted factors that are considered in drug control policy and prevention interventions (e.g., the finding that perception of harm is inversely associated with rates of use of specific substances). Tobacco control policy provides an example of how such data can be applied. Building on these findings, more comprehensive surveillance efforts were developed to understand further the development and course of tobacco use and dependence in the 1990s. This resulted in a collaborative effort among tobacco control researchers and federal agencies including the Centers for Disease Control and Prevention and the National Institute on Drug Abuse to develop measures of cigarette smoking dependence and risk factors that would be used in surveys (Centers for Disease Control and Prevention, 1994). The questions that were developed were then used in many of the US federal surveys as well as state-based and other surveillance efforts and have become essentially standardized methods for measuring cigarette smoking behaviors.
The use of these questions consistently across surveys and over time allows for the collection of data that can be compared and trends to be evaluated. This level of consistently and systematically collected data on use provides public health advocates and policy makers with solid data upon which to address an important public health problem as well as monitor the effects of environmental and policy interventions, and to guide the improvement of interventions. In contrast, the MTF data on drug use, specifically prescription drug use, are complicated by the combining many drugs into one question (often including both licit and illicit substances such as illicitly manufactured methamphetamine and prescription methylphenidate). The MTF is also limited in that its methods and instruments were not developed to rapidly evolve and provide quick (e.g., quarterly) dissemination of findings and therefore provide limited utility in guiding policy changes as problems arise with drugs as they come on both the licit and illicit markets. Thus, the surveillance systems that are used to monitor drug misuse and abuse in the US vary in the level of specificity for substances, the breadth of substances investigated (e.g., prescription/OTC/illicit), as well as the definitions used to identify misuse and abuse. Epidemiologic contributions to understanding and controlling substance abuse are further limited by a dearth of comparative international data on trends and patterns of drug use and abuse. By contrast, the epidemiology of communicable diseases such as influenza, malaria and HIV AIDS is supported by a relatively comprehensive and cohesive global network of monitoring as provided through the World Health Organization’s Collaborating Centers. Data collection on drug misuse and abuse is not conducted systematically or consistently worldwide, which limits the understanding of the scope of problems with specific drugs in different countries. These limitations, nationally and internationally, must be considered when evaluating trends and patterns of misuse and abuse. 1.2. Survey data A broad range of surveillance instruments and approaches are presently in use to track trends in substance abuse and guide risk management interventions to mitigate misuse and abuse (Dart, 2009; Dasgupta and Schnoll, 2009). Although these are not uniformly applied across drug classes, or standardized, US data sources can be used to provide an illuminating picture of stimulant drug misuse and abuse. The National Survey on Drug Use and Health (NSDUH) is an annual household-based survey of the US population aged 12 years and older, which is used to estimate national prevalence statistics. It includes questions regarding non-medical use of stimulant drugs and queries lifetime use of some specific drugs. It does not ask about specific drugs for past year or past month, but rather asks about “stimulants” as a category separate from cocaine and methamphetamine. These data are the most frequently cited for estimating the prevalence of drug misuse and abuse at a national level. The prevalence of non-medical use of prescription stimulants from the 2012 NSDUH are shown in Fig. 1 The estimated prevalence of non-medical use of prescription stimulants increases with age until the mid-30 s and then declines. Past month non-medical use (considered current use) prevalence is 1.2% or less in all age groups. Given that these rates are for the combined category of all stimulant medications, non-medical use for any individual medication would be expected to be lower. The MTF Survey is administered in selected schools among 8th, 10th, and 12th grade students. Students in 8th grade are generally age 13e14; 10th grade students are approximately 15e16 years old, and 12th grade students are 17e18 years old. In 2012, 7.9% of the 12th grade students reported past year non-medical use of
Please cite this article in press as: Gerlach, K.K., et al., Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research, Neuropharmacology (2014), http://dx.doi.org/10.1016/j.neuropharm.2014.04.020
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Lifetime
Past Year
10 8 6 4 2 0 12-13
14-15
16-17
18-20
21-25
26-34
35+
Age at Interview
Q1
3
66 67 68 Drug Number of Percent of all drug 69 visits related visits 70 All Central Nervous 895,960 72.0 71 System (CNS)-acting 72 Stimulants 40,648 3.3 73 Analgesics 573,497 46.1 74 Opioids/Opiates 488,004 39.2 75 Total ED visits for 1,244,872 100 non-medical use 76 77 78 79 A large proportion of the approximately 1.2 million drug related 80 ED visits included in 2011 involved the non-medical use of CNS81 acting pharmaceutical products. Stimulants were noted in 3.3% of 82 all drug related ED visits for non-medical drug use. In comparison, 83 analgesics were involved in 46.1% of visits. 84 TEDS reports on admissions to drug abuse treatment facilities 85 (although not all facilities are included) that involve abuse of 86 alcohol, prescription and illegal drugs. The data are not represen87 tative of all individuals abusing certain substances, but they do 88 provide information regarding those who have reached a point in 89 their behavior that they are seeking, or being compelled into 90 treatment through the criminal justice system (e.g., drug courts and 91 involuntary commitment). If substances become more common 92 among TEDS reports, then that may indicate an even larger abuse 93 problem in the population at large since it is generally believed that 94 less than 10% of those who abuse drugs ever enter treatment 95 (Substance Abuse and Mental Health Services Administration, 96 2009). 97 Data from TEDS shows low and fairly stable rates of admission 98 for primary abuse of amphetamines other than methamphetamine 99 as well as stimulants that are not amphetamine from 1995 to 2011 (Error! Reference source not found.). There has been an increase in Q2 100 101 admissions to treatment for primary abuse of methamphetamine as 102 well as opioids over this same time period. Of note, during this 103 period there were new treatment options adopted for opioid 104 dependence in the US, which was not the case with stimulants. The 105 availability and acceptability of treatment may also have impacted rates of admissions (Fig. 2). Q3 106 107 Poison centers (PC) are state-level call centers staffed by clinical 108 specialists in toxicology and pharmacology. PCs respond to spon109 taneous inquiries from the public, health care professionals, and 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 Fig. 2. Trends in admissions by primary substance of abusedTreatment Episode Data 130 Set, 1995e2011. Table 1 Drug Abuse Warning Network, 2011dEmergency Department visits involving nonmedical use of pharmaceutical products.
Past Month
12
Prevalence (%)
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Fig. 1. Prevalence of non-medical use of prescription stimulantsdlifetime, past year and past month by age at interview (NSDUH, 2012).
“amphetamines,” which includes methamphetamine. This proportion is higher than that reported by 16e17 year olds (2.4%) and even higher than 18e20 year olds (3.9%) in the NSDUH. By comparison, past year use of cocaine was 2.9% among 12th grade students in MTF and 1.6% (16e17 year olds) and 4.5% (18e20 year olds) in the NSDUH. The discrepant estimates derived from these two surveys were also found by Biondo and Chilcoat for non-medical use of Oxycontin (Biondo and Chilcoat, 2014). As assessed on MTF, the rate was 2.5e3.0 times higher than from the NSDUH. Likely explanations for the different estimates include survey administration (school versus home) and question wording, the nature of which limits the ability to compare the data and leaves one questioning which surveydif eitherdprovides an accurate estimate of the true rates of misuse and abuse. Nevertheless, it is clear that non-medical use of stimulants is not a highly prevalent behavior among adolescents in either survey, especially when compared to other classes of drugs. 1.3. Additional surveillance efforts In addition to population-based surveys, there are other surveillance efforts in the US that can be used to monitor drug abuse. These efforts include the Drug Abuse Warning Network Emergency Department (DAWN-ED), Treatment Episode Data Set (TEDS), Poison Centers (PCs), and several proprietary surveillance systems (Researched Abuse and Addiction-Related Surveillance [RADARSÒ] System and the National Addictions Vigilance Intervention and Prevention Program [NAVIPPROÒ]). Each of these surveillance efforts provides important information regarding drug abuse and has been used to supplement the data provided by MTF and NSDUH. In fact, the RADARS System was initially developed to track abuse of a specific opioid drugs at the brand level because there were no federal data available (Cicero et al., 2005). DAWN collected data from hospital ED visits that involve nonmedical use of prescription and over-the-counter medications as well as dietary supplements. Non-medical use is defined in the DAWN system as: (1) taking a higher than prescribed or recommended dose of a pharmaceutical (contrary to directions or labeling); (2) taking a pharmaceutical prescribed for another individual; (3) malicious poisoning of one individual by another; or (4) substance abuse involving pharmaceuticals. A location-stratified sample of 233 hospitals contributed data for the 2011 annual report; sample weights were applied to estimate national figures taking into account hospital size and ownership, metropolitan area and underlying population. DAWN-ED data cannot be used to estimate prevalence since the system relies on spontaneous visits to these facilities. The most recent DAWN-ED data (2011) for stimulants and other drugs are shown in Table 1.
Please cite this article in press as: Gerlach, K.K., et al., Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research, Neuropharmacology (2014), http://dx.doi.org/10.1016/j.neuropharm.2014.04.020
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Table 2 Substance categories most frequently involved in adult (20 years old) exposuresdPoison Centers, 2011. Substance (Major generic category)
All substances (% of all exposures)
Single substance (% of single substance exposures)
Analgesics Sedative/Hypnotics/ Antipsychotics Antidepressants Cleaning substances (Household) Cardiovascular drugs Alcohols Bites and envenomations Pesticides Stimulants and street drugs Anticonvulsants Cosmetics/Personal care products
152,173 (12.9) 130,360 (11.1)
70,296 (10.1) 42,519 (6.1)
75,086 (6.4) 67,527 (5.7)
25,928 (3.7) 53,805 (7.7)
66,589 (5.7) 54,226 (4.6) 44,565 (3.8)
26,211 (3.8) 11,387 (1.6) 44,136 (6.3)
41,593 (3.5) 35,557 (3.0)
37,599 (5.4) 19,074 (2.7)
35,321 (3.0) 33,761 (2.9)
13,007 (1.9) 31,206 (4.5)
public health agencies. Given the spontaneous reporting aspect of the calls, PC data are not usable for calculating prevalence estimates. Nevertheless, these data are available in near real-time and are valued as an early warning system since the data are highly drug specific. Calls received by PCs are compiled on a calendar year basis and released in annual reports. The most recent annual report was for 2011 (Bronstein et al., 2012), which reported on 2,334,004 human exposures. Human exposure calls related to stimulants were reported as a combined category with “street drugs,” a category composed of prescription stimulants as well as drugs such as methylenedioxymethamphetamine (MDMA; Ecstasy), cocaine and “bath salts,” which are synthetic amphetamines (Table 2). In the most recent annual PC report, trends in exposure calls were examined for the time period 2001e2011. Of the 25 categories that had the most rapid increases in exposure calls, “Stimulants and Street Drugs” ranked 13th with an average increase of 1231 (95% CI: 326e2136) exposure calls annually. “Stimulants and Street Drugs” were associated with 169 fatalities in 2011, 41 of which were single substance exposures. Data from the proprietary systems (RADARS and NAVIPPRO) are not available in the public domain. Nevertheless, some pharmaceutical companies that have subscriptions to these services as well as the researchers who manage these systems have published some of the data (Sembower et al., 2013). 2. Implications for drug control policy and risk management Although we would like to believe that drug control policy as well as other policies are based on data that are collected from welldesigned studies, this is most often not the case. Policies related to the misuse, abuse and diversion of drugs are frequently based on anecdotal reports that are often exaggerated in the media (Jenkins, 1999). These reports are then cited by politicians and regulatory agencies as the basis for laws and regulations. For example, from 2002 to 2012 the NSDUH showed non-medical use of prescription opioids to be relatively flat and slightly decreasing. During this same period, the media and politicians were claiming that there was an epidemic of prescription opioid abuse in support of drug control laws and regulations that they were advocating. Similarly, “alarming“ reports of stimulant misuse are fairly regularly reported in the popular press despite the lack of supporting data (Kent, 2013; Schwarz, 2013).
If we are to address the issues related to non-medical use of prescription stimulants appropriately, we need to carefully assess all of the relevant data sources. This brief analysis of the available data sources in the US has several implications for drug control policy including FDA mediated risk management of approved medicines. It makes little sense to lump together all licit and illicit stimulants and stimulant-related problems as though they are the same in genesis, ontogeny and public health impact. Many of the surveys do not adequately differentiate licit from illicit stimulants nor have the survey questions themselves been assessed to know whether respondents comprehend the questions that they are asked. Using these data for drug labeling concerning amphetamine risks might be important for discouraging misuse and mitigating iatrogenic addiction but that same label may be irrelevant at best and counter-productive at worst with respect to the behavior of those who primarily abuse stimulants. Conversely, drug control approaches intended to address those who primarily abuse and distribute illicitly manufactured stimulants (e.g., in rural communities) may be of little relevance to prescription drug misusers (e.g., on college campuses). At a national level, drug control policies need to take such differences into consideration and work to harmonize efforts to address the broad and diverse range of problems involving stimulant misuse and abuse. Risk management programs for most drugs address the mitigation of adverse events related to the drug in the patient population taking the drug. Risk management programs for prescription stimulants and other controlled medications are not only aimed at reducing problems in patients but also among those who are not prescribed the drug and abuse it. The effect on the non-prescribed abuser may be quite limited. These efforts may have some impact on reducing diversion of appropriately or inappropriately prescribed medication. Conversely, public service announcements, and education about the risks of stimulants that are focused on the effects and risks of illicit stimulants need to be focused so as to be most relevant to the populations, drugs, and regions targeted. They may be of little credibility, for example, to college student misusers, who perceive relatively little harm and may perceive actual benefit from their occasional use as study aids. How national drug control policies and medication regulations affect these challenges is not simple and is well beyond the scope of this review, but we do hope that this analysis of the epidemiology will help guide thinking about how to achieve more relevant, appropriate and effective control of misuse and abuse of stimulants from prescription methylphenidate to crack cocaine. Understanding the nature of the problem has great relevance to treatment. Programs that are developed for the treatment of injectors of illicitly produced methamphetamine may not only be inappropriate for treating a college student misusing a prescription stimulant, but may be counterproductive. If we are to create policies for the prevention and treatment of misuse, abuse and diversion of stimulants both licit and illicit, it will be critical to accurately understand the scope and nature of the problem. This is a basic tenet of the scientific method. Without this level of understanding, it is almost impossible to develop policies that will appropriately and effectively address the problem without harming those who need the medications. 3. Challenges As demonstrated by the data presented above, the lack of consistent and systematic data collection is problematic nationally and internationally for assessing misuse and abuse of stimulants, differences among stimulants, and the determinants of these differences. Nonetheless, these surveillance data suggest that factors such as the form of the drug and the route by which it is used, and
Please cite this article in press as: Gerlach, K.K., et al., Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research, Neuropharmacology (2014), http://dx.doi.org/10.1016/j.neuropharm.2014.04.020
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the reasons for use are important determinants of patterns of use and adverse consequences such as the development of a substance use disorder and overdose. These inconsistencies may be a downstream impact of the historical precedent of scheduling stimulants for international control by the International Narcotics Control Board based on their similarity to cocaine and amphetamine by the 1961 Single Drug Convention and the 1971 Psychotropic Convention (Spillane and McAllister, 2003). Thus, both extended-release and transdermal methylphenidate, and extended-release amphetamine preparations are scheduled the same as amphetamine and pharmaceutical cocaine in many countries, regardless of formulation and whether their manufacture was licit or not. This occurs regardless of the facts discussed in this review that such drugs appear much less attractive to stimulant-abusing persons and much less likely to be associated with addiction, overdose, and other health problems more typical of cocaine and illicitly manufactured amphetamine. Beyond amphetamine and methamphetamine, new classes of stimulant molecules have required an extension of reference drugs to newer medicines, such as modafinil and atomoxetine, in abuse liability testing (Romach et al., in this issue). Many surveys group prescription stimulants (such as methylphenidate and lisdexamfetamine) with other drugs that upregulate the release of dopamine or inhibit its reuptake, such as MDMA and cocaine, despite the fact that most abuse of the latter drugs occurs with those that are illicitly manufactured and sold. The problem of the co-mingling of legal medications and illicit drugs in surveillance is exemplified by methamphetamine abuse in the US in the early 2000s. At that time, illicit production of methamphetamine (using a common over-the-counter nasal decongestant as a precursor) reached record levels. At the same time, methamphetamine was also produced legally by pharmaceutical companies and legally dispensed by pharmacies. Nevertheless, surveys conducted during this time rarely differentiated between the two, a similar pattern to what is now seen in Europe with amphetamine. Although prescription amphetamine is available in several European countries, almost all of the abuse is related to illicitly produced amphetamine (European Monitoring Centre for Drugs and Drug Addiction, 2014). As novel prescription stimulant medicines are approved by regulatory authorities, it becomes difficult to differentiate the use or abuse of prescribed forms (e.g., lisdexamfetamine) from illicitly produced amphetamine. In addition, street names for stimulants can vary widely, with the same name used for both pharmaceutical and illicitly produced forms of a drug, further confusing reported rates of misuse and abuse. 4. Conclusion This epidemiologic analysis has implications for efforts to effectively mitigate the risks of misuse, abuse, and diversion. The data sources that are available to monitor abuse of stimulant medications are far from comprehensive in scope, and they do not employ standard categories for drugs or measurements of/definitions for misuse and abuse. We strive here to highlight some of the most common issues with surveillance of self-reported stimulant use, and much work remains to be done to devise a classification and survey system that generates reproducible results while maintaining the level of specificity needed for proper public health surveillance. Nevertheless, taken together the available data can provide important pieces of information from which a fairly informative picture of abuse and misuse can be drawn. Further refinement of data collection efforts would greatly improve the accuracy and reliability of estimates of abuse of specific substances. Systems should also provide some degree of flexibility when new products are introduced to the market (both from legal and illegal
5
sources) so that any effect can be monitored without too much delay. Our analysis also reveals the challenges in conducting appropriate surveillance and the deficiencies in current surveillance efforts that warrant addressing with the goal of enabling timely, reliable, and comprehensive data collection to serve as the foundation for effective approaches to preventing misuse, abuse and overdose. Finally, we believe this epidemiologic analysis has implications for interpreting the current known neuropharmacology of stimulants and possibly for guiding future neuropharmacology research. Although it is possible that the widely differing patterns of use across drugs and populations as well as widely varying risks of misuse, abuse, and other adverse effects are largely attributable to environmental, social, and individual factors, it seems plausible that differences in the neuropharmacology may also be relevant (Lukas, in this issue). Just as route of administration and drug dose are determinants of drug response, perhaps differences among drugs at the molecular level are more relevant than the relatively crude application of drug scheduling and categorization as “stimulants” would imply. Perhaps, there are unique genetic differences expressed at the molecular level that are critical in the course of misuse and abuse at the individual level that alter vulnerability to the various drugs as discussed by Zhou and Kreek (in this issue) and elsewhere (Bryant et al., 2012; Mercer et al., 2013; Zhou et al., 2010). There are many questions, but our hope is that neuropharmacologists will increasingly look to epidemiology as they consider what it is that they hope to explain through laboratory research. Similarly, we hope that epidemiologists will increasingly consider differences in the neuropharmacology across drugs in the design of surveillance instruments and interpretation of data. Disclosure The authors consult for or have consulted in the past three years through Pinney Associates to pharmaceutical companies regarding the regulation, development and post-marketing surveillance of stimulant products and other CNS drugs of abuse. This manuscript was independently prepared without support for or input from any such commercial interests. Acknowledgments The authors thank Mark Sembower for his assistance with federal survey data analysis. References American Psychiatric Association, 2013. Diagnostic and Statistical Manual of Mental Disorders, fifth ed. Washington, DC. Biondo, G., Chilcoat, H.D., 2014. Discrepancies in prevalence estimates in two national surveys for nonmedical use of a specific opioid product versus any prescription pain reliever. Drug Alcohol Depend. 134, 396e400. Bronstein, A.C., Spyker, D.A., Cantilena Jr., L.R., Rumack, B.H., Dart, R.C., 2012. 2011 Annual report of the American Association of Poison Control Centers’ National Poison Data System (NPDS): 29th Annual Report. Clin. Toxicol. (Phila) 50, 911e 1164. Bryant, C.D., Parker, C.C., Zhou, L., Olker, C., Chandrasekaran, R.Y., Wager, T.T., et al., 2012. Csnk1e is a genetic regulator of sensitivity to psychostimulants and opioids. Neuropsychopharmacology 37, 1026e1035. Calderon, S.K.M., 2014. (in this issue). Centers for Disease Control and Prevention, 1994. Cigarette smoking among adults e United States, 1992, and changes in the definition of current cigarette smoking. Morb. Mortal. Wkly. Rep. 43, 342e346. Available online: http://www. webcitation.org/346NX341jqesN (accessed February 320, 2014). Cicero, T.J., Inciardi, J.A., Munoz, A., 2005. Trends in abuse of oxycontin and other opioid analgesics in the United States: 2002e2004. J. Pain 6, 662e672. Dart, R.C., 2009. Monitoring risk: post marketing surveillance and signal detection. Drug Alcohol Depend. 105 (Suppl. 1), S26eS32. Dasgupta, N., Schnoll, S.H., 2009. Signal detection in post-marketing surveillance for controlled substances. Drug Alcohol Depend. 105 (Suppl. 1), S33e41.
Please cite this article in press as: Gerlach, K.K., et al., Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research, Neuropharmacology (2014), http://dx.doi.org/10.1016/j.neuropharm.2014.04.020
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Drug Enforcement Administration, 2014. Drug Scheduling. Available online at: http://www.webcitation.org/6NX1tSjlR (accessed 20.02.14.). European Monitoring Centre for Drugs and Drug Addiction, 2014. Exploring Methamphetamine Trends in Europe. EMCDDA Papers, Publications Office of the European Union, Luxembourg. Available online at: http://www.webcitation. org/6NX9Wkf6y (accessed 20.02.14.). Jenkins, P., 1999. Synthetic Panics: the Symbolic Politics of Designer Drugs. NYU Press, New York. Johnston, L.D., O’Malley, P.M., Bachman, J.G., Schulenberg, J.E., 2013. Monitoring the Future National Results on Drug Use: 2012 Overview, Key Findings on Adolescent Drug Use. Institute for Social Research, The University of Michigan, Ann Arbor, Michigan. Kent, J., 2013. Adderall: America’s Favorite Amphetamine. Huffington Post. Available at: http://www.webcitation.org/6Ombm2CIk (accessed 12.02.14.). Kreek, M., 2014. (in this issue). Lukas, S., 2014. (in this issue). Mercer, A.J., Hentges, S.T., Meshul, C.K., Low, M.J., 2013. Unraveling the central proopiomelanocortin neural circuits. Front. Neurosci. 7, 19. O’Brien, C., 2011. Drug addiction. In: Brunton, L.L., Chabner, B.A., Knollmann, B.C. (Eds.), Goodman and Gilman’s the Pharmacological Basis of Therapeutics, 12th ed. McGraw-Hill, New York, pp. 649e668. Romach, M.S., Schoedel, K.A., Sellers, E.M., 2014. Human Abuse Liability Evaluation of CNS Stimulant Drugs. (in this issue). Schwarz, 2013. A.D.H.D. seen in 11% of U.S. children as diagnoses rise. New York Times. Available at: http://www.webcitation.org/6Ombt9NRr (accessed 12.04.14.).
Sembower, M.A., Ertischek, M.D., Buchholtz, C., Dasgupta, N., Schnoll, S.H., 2013. Surveillance of diversion and nonmedical use of extended-release prescription amphetamine and oral methylphenidate in the United States. J. Addict. Dis. 32, 26e38. Spillane, J., McAllister, W.B., 2003. Keeping the lid on: a century of drug regulation and control. Drug Alcohol Depend. 70, S5e12. Substance Abuse and Mental Health Services Administration, 2009. Results from the 2008 National Survey on Drug Use and Health: National Findings. Office of Applied Studies, NSDUH Series H-36, HHS Publication No. SMA 09e4434. Rockville, MD. Available online at: http://www.oas.samhsa.gov/nsduh/ 2k8nsduh/2k8Results.cfm (accessed 20.02.13.). Substance Abuse and Mental Health Services Administration, 2013. Treatment Episode Data Set (TEDS): 2001e2011. National Admissions to Substance Abuse Treatment Services. BHSIS Series S-65, HHS Publication No. (SMA) 13-4772. Rockville, MD. Available online at: http://www.webcitation.org/6NXCBUuPG (accessed 20.04.13.). Zhou, Y., Proudnikov, D., Yuferov, V., Kreek, M.J., 2010. Drug-induced and genetic alterations in stress-responsive systems: implications for specific addictive diseases. Brain Res. 1314, 235e252. Zhou, Y.A., Kreek, M.J., 2014. Alcohol: a stimulant activating brain stress responsive systems with persistent neuroadaptation. (in this issue). Zosel, A., Bartelson, B.B., Bailey, E., Lowenstein, S., Dart, R., 2013. Characterization of adolescent prescription drug abuse and misuse using the Researched Abuse Diversion and Addiction-related Surveillance (RADARS((R))) system. J. Am. Acad. Child. Adolesc. Psychiatry 52, 196e204 e192.
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Contents lists available at ScienceDirect
Neuropharmacology journal homepage: www.elsevier.com/locate/neuropharm
Invited review
Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research Q7
Karen K. Gerlach a, *, Nabarun Dasgupta b, Sidney H. Schnoll a, Jack E. Henningfield a, c a
Pinney Associates, Inc., 4800 Montgomery Lane, Suite 400, Bethesda, MD 20814, USA Injury Prevention Research Center, University of North Carolina, Chapel Hill, NC 27599, USA c The Johns Hopkins University, School of Medicine, Baltimore, MD 21229, USA b
a b s t r a c t Keywords: Stimulant surveillance Abuse Misuse Illicit stimulants
Stimulants are a diverse array of drugs that range from everyday caffeine to prescription medications and illicitly manufactured street drugs. The surveillance of misuse and abuse of stimulants many times confounds prescription and illicit street drugs such that the data are not specific enough to guide mitigation efforts or assess their impact. This review highlights the surveillance efforts that are conducted in the United States (US) for stimulant misuse and abuse. These surveillance efforts include national level surveys as well as reporting systems such as Poison Centers and emergency departments. This epidemiologic analysis has implications for interpreting the current known neuropharmacology of stimulants and possibly informing future neuropharmacology research that may contribute to a better understanding of potential neuropharmacologic factors influencing differing patterns of use, abuse, and adverse consequences associated with various stimulants. This article is part of a Special Issue entitled ‘CNS Stimulants’. Ó 2014 Published by Elsevier Ltd.
1. Introduction The drugs known collectively as “stimulants” are a diverse category including caffeine and relatively weak prescription stimulants such as mazindol and phentermine, which are not the focus of this review. Rather, this review will address the stronger stimulants, including those approved for the treatment of attention deficit/hyperactivity disorder (ADHD) (methylphenidate and various amphetamine molecules) and illicitly manufactured crack cocaine and methamphetamine formulations. These drugs are regulated as Schedule II drugs under the Controlled Substances Act (CSA) in the United States (US) and comparable schedules in other countries. Schedule II is reserved for drugs that carry the highest risk of abuse and dependence yet also are approved for medicinal use. Illicitly produced methamphetamine (“ice”) and crack cocaine are not approved for medicinal use, but they are also placed in Schedule II because pharmaceutical methamphetamine and cocaine do have approved medicinal uses (Drug Enforcement Administration, 2014; Spillane and McAllister, 2003).
* Corresponding author. Pinney Associates, 201 N. Craig Street, Suite 320, PA 15213, USA. Tel.: þ1 412 567 1751; fax: þ1 412 687 4855. E-mail addresses: [email protected], gbittner@pinneyassociates. com (K.K. Gerlach).
The Schedule II stimulants methylphenidate, amphetamines, and cocaine are characterized with similar abuse potential profiles under a variety of laboratory tests of abuse liability, and they share generally similar pharmacologic actions as discussed in this issue of Neuropharmacology (Calderon, in this issue; Kreek, in this issue; Lukas, in this issue; Romach et al., in this issue). Outside the laboratory, however, these drugs are associated with widely different patterns of use, risk of substance use disorders (American Psychiatric Association, 2013), and adverse effects including overdose leading to emergency room visits. For example, as discussed in this review, methylphenidate and prescription amphetamine products indicated for the treatment of ADHD are infrequently the primary drug of abuse cited by people presenting for treatment for substance abuse or as a cause of overdose as compared to illicitly manufactured methamphetamine (e.g., “ice”) or cocaine (e.g., “crack”) (O’Brien, 2011; Substance Abuse and Mental Health Services Administration, 2013; Zosel et al., 2013). Clearly the mechanisms of action and general pharmacology of these drugs do not appear to explain these differences, although variations in reinforcing effects perhaps related to speed of absorption to the brain and other pharmacologic differences cannot be entirely ruled out [see also (Calderon, in this issue; Romach et al., in this issue)]. Are there subtle but perhaps important neuropharmacologic differences among these drugs that help explain the differing patterns
http://dx.doi.org/10.1016/j.neuropharm.2014.04.020 0028-3908/Ó 2014 Published by Elsevier Ltd.
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and risks of abuse? Are the differences better explained by social and environmental factors, cost, access, drug formulation, route of administration, population, or reasons for use? Four decades of surveillance and epidemiologic analyses may help to understand and explain these differences. What can we learn from the epidemiology that might be considered in neuropharmacologic investigations? What can we learn from current epidemiologic understanding that may be considered in future surveillance approaches? Addressing these two questions is the focus of this brief review. 1.1. The need for adequate surveillance Epidemiologic analysis requires reliable, valid, and relevant surveillance that keeps pace with an epidemic as it unfolds over time and across populations. It is clear that trends in stimulant misuse and abuse have changed dramatically over the past half century teaching us much about the importance of factors far beyond the pharmacology of the drugs as determinants of which drugs are used, how they are used, patterns of use within individuals, and consequences associated with various types of stimulant misuse and abuse. Unfortunately, the most frequently cited surveillance methods have not always kept pace with changing patterns of use and abuse and therefore, the resulting policy analyses rely on methods and data that may be of diminished relevance to current and evolving patterns of stimulant abuse. In order to have an accurate and adequate understanding of the scope and scale of any ongoing public health problem, there needs to be a substantial, systematic surveillance effort in place; it must provide both consistent elements for comparative purposes over time as well as evolving components to keep pace with evolving trends in drug use form, patterns and reasons. Addressing the problem with science-based interventions places further demands on surveillance, specifically that it include information such as the reasons for use and other factors associated with use, including those that might be considered risk factors and protective factors. With an appropriate surveillance system, one can track trends over time, detect new problems as they occur, and lay the foundation for interventions to prevent and control misuse and abuse, and mitigate unintended and undesired consequences. This is increasingly important for prescription drugs since they have legitimate medical uses. Intervention strategies that may reduce misuse and abuse, but also reduce the availability of the medications for patients that need them, can result in more harm than good for patients with legitimate medical need. One example of surveillance that assesses both positive and negative factors influencing misuse and abuse is the nearly four decades of the Monitoring the Future (MTF) Survey (Johnston et al., 2013). This survey not only provides estimates of prevalence and trends, but it also has highlighted factors that are considered in drug control policy and prevention interventions (e.g., the finding that perception of harm is inversely associated with rates of use of specific substances). Tobacco control policy provides an example of how such data can be applied. Building on these findings, more comprehensive surveillance efforts were developed to understand further the development and course of tobacco use and dependence in the 1990s. This resulted in a collaborative effort among tobacco control researchers and federal agencies including the Centers for Disease Control and Prevention and the National Institute on Drug Abuse to develop measures of cigarette smoking dependence and risk factors that would be used in surveys (Centers for Disease Control and Prevention, 1994). The questions that were developed were then used in many of the US federal surveys as well as state-based and other surveillance efforts and have become essentially standardized methods for measuring cigarette smoking behaviors.
The use of these questions consistently across surveys and over time allows for the collection of data that can be compared and trends to be evaluated. This level of consistently and systematically collected data on use provides public health advocates and policy makers with solid data upon which to address an important public health problem as well as monitor the effects of environmental and policy interventions, and to guide the improvement of interventions. In contrast, the MTF data on drug use, specifically prescription drug use, are complicated by the combining many drugs into one question (often including both licit and illicit substances such as illicitly manufactured methamphetamine and prescription methylphenidate). The MTF is also limited in that its methods and instruments were not developed to rapidly evolve and provide quick (e.g., quarterly) dissemination of findings and therefore provide limited utility in guiding policy changes as problems arise with drugs as they come on both the licit and illicit markets. Thus, the surveillance systems that are used to monitor drug misuse and abuse in the US vary in the level of specificity for substances, the breadth of substances investigated (e.g., prescription/OTC/illicit), as well as the definitions used to identify misuse and abuse. Epidemiologic contributions to understanding and controlling substance abuse are further limited by a dearth of comparative international data on trends and patterns of drug use and abuse. By contrast, the epidemiology of communicable diseases such as influenza, malaria and HIV AIDS is supported by a relatively comprehensive and cohesive global network of monitoring as provided through the World Health Organization’s Collaborating Centers. Data collection on drug misuse and abuse is not conducted systematically or consistently worldwide, which limits the understanding of the scope of problems with specific drugs in different countries. These limitations, nationally and internationally, must be considered when evaluating trends and patterns of misuse and abuse. 1.2. Survey data A broad range of surveillance instruments and approaches are presently in use to track trends in substance abuse and guide risk management interventions to mitigate misuse and abuse (Dart, 2009; Dasgupta and Schnoll, 2009). Although these are not uniformly applied across drug classes, or standardized, US data sources can be used to provide an illuminating picture of stimulant drug misuse and abuse. The National Survey on Drug Use and Health (NSDUH) is an annual household-based survey of the US population aged 12 years and older, which is used to estimate national prevalence statistics. It includes questions regarding non-medical use of stimulant drugs and queries lifetime use of some specific drugs. It does not ask about specific drugs for past year or past month, but rather asks about “stimulants” as a category separate from cocaine and methamphetamine. These data are the most frequently cited for estimating the prevalence of drug misuse and abuse at a national level. The prevalence of non-medical use of prescription stimulants from the 2012 NSDUH are shown in Fig. 1 The estimated prevalence of non-medical use of prescription stimulants increases with age until the mid-30 s and then declines. Past month non-medical use (considered current use) prevalence is 1.2% or less in all age groups. Given that these rates are for the combined category of all stimulant medications, non-medical use for any individual medication would be expected to be lower. The MTF Survey is administered in selected schools among 8th, 10th, and 12th grade students. Students in 8th grade are generally age 13e14; 10th grade students are approximately 15e16 years old, and 12th grade students are 17e18 years old. In 2012, 7.9% of the 12th grade students reported past year non-medical use of
Please cite this article in press as: Gerlach, K.K., et al., Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research, Neuropharmacology (2014), http://dx.doi.org/10.1016/j.neuropharm.2014.04.020
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Lifetime
Past Year
10 8 6 4 2 0 12-13
14-15
16-17
18-20
21-25
26-34
35+
Age at Interview
Q1
3
66 67 68 Drug Number of Percent of all drug 69 visits related visits 70 All Central Nervous 895,960 72.0 71 System (CNS)-acting 72 Stimulants 40,648 3.3 73 Analgesics 573,497 46.1 74 Opioids/Opiates 488,004 39.2 75 Total ED visits for 1,244,872 100 non-medical use 76 77 78 79 A large proportion of the approximately 1.2 million drug related 80 ED visits included in 2011 involved the non-medical use of CNS81 acting pharmaceutical products. Stimulants were noted in 3.3% of 82 all drug related ED visits for non-medical drug use. In comparison, 83 analgesics were involved in 46.1% of visits. 84 TEDS reports on admissions to drug abuse treatment facilities 85 (although not all facilities are included) that involve abuse of 86 alcohol, prescription and illegal drugs. The data are not represen87 tative of all individuals abusing certain substances, but they do 88 provide information regarding those who have reached a point in 89 their behavior that they are seeking, or being compelled into 90 treatment through the criminal justice system (e.g., drug courts and 91 involuntary commitment). If substances become more common 92 among TEDS reports, then that may indicate an even larger abuse 93 problem in the population at large since it is generally believed that 94 less than 10% of those who abuse drugs ever enter treatment 95 (Substance Abuse and Mental Health Services Administration, 96 2009). 97 Data from TEDS shows low and fairly stable rates of admission 98 for primary abuse of amphetamines other than methamphetamine 99 as well as stimulants that are not amphetamine from 1995 to 2011 (Error! Reference source not found.). There has been an increase in Q2 100 101 admissions to treatment for primary abuse of methamphetamine as 102 well as opioids over this same time period. Of note, during this 103 period there were new treatment options adopted for opioid 104 dependence in the US, which was not the case with stimulants. The 105 availability and acceptability of treatment may also have impacted rates of admissions (Fig. 2). Q3 106 107 Poison centers (PC) are state-level call centers staffed by clinical 108 specialists in toxicology and pharmacology. PCs respond to spon109 taneous inquiries from the public, health care professionals, and 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 Fig. 2. Trends in admissions by primary substance of abusedTreatment Episode Data 130 Set, 1995e2011. Table 1 Drug Abuse Warning Network, 2011dEmergency Department visits involving nonmedical use of pharmaceutical products.
Past Month
12
Prevalence (%)
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Fig. 1. Prevalence of non-medical use of prescription stimulantsdlifetime, past year and past month by age at interview (NSDUH, 2012).
“amphetamines,” which includes methamphetamine. This proportion is higher than that reported by 16e17 year olds (2.4%) and even higher than 18e20 year olds (3.9%) in the NSDUH. By comparison, past year use of cocaine was 2.9% among 12th grade students in MTF and 1.6% (16e17 year olds) and 4.5% (18e20 year olds) in the NSDUH. The discrepant estimates derived from these two surveys were also found by Biondo and Chilcoat for non-medical use of Oxycontin (Biondo and Chilcoat, 2014). As assessed on MTF, the rate was 2.5e3.0 times higher than from the NSDUH. Likely explanations for the different estimates include survey administration (school versus home) and question wording, the nature of which limits the ability to compare the data and leaves one questioning which surveydif eitherdprovides an accurate estimate of the true rates of misuse and abuse. Nevertheless, it is clear that non-medical use of stimulants is not a highly prevalent behavior among adolescents in either survey, especially when compared to other classes of drugs. 1.3. Additional surveillance efforts In addition to population-based surveys, there are other surveillance efforts in the US that can be used to monitor drug abuse. These efforts include the Drug Abuse Warning Network Emergency Department (DAWN-ED), Treatment Episode Data Set (TEDS), Poison Centers (PCs), and several proprietary surveillance systems (Researched Abuse and Addiction-Related Surveillance [RADARSÒ] System and the National Addictions Vigilance Intervention and Prevention Program [NAVIPPROÒ]). Each of these surveillance efforts provides important information regarding drug abuse and has been used to supplement the data provided by MTF and NSDUH. In fact, the RADARS System was initially developed to track abuse of a specific opioid drugs at the brand level because there were no federal data available (Cicero et al., 2005). DAWN collected data from hospital ED visits that involve nonmedical use of prescription and over-the-counter medications as well as dietary supplements. Non-medical use is defined in the DAWN system as: (1) taking a higher than prescribed or recommended dose of a pharmaceutical (contrary to directions or labeling); (2) taking a pharmaceutical prescribed for another individual; (3) malicious poisoning of one individual by another; or (4) substance abuse involving pharmaceuticals. A location-stratified sample of 233 hospitals contributed data for the 2011 annual report; sample weights were applied to estimate national figures taking into account hospital size and ownership, metropolitan area and underlying population. DAWN-ED data cannot be used to estimate prevalence since the system relies on spontaneous visits to these facilities. The most recent DAWN-ED data (2011) for stimulants and other drugs are shown in Table 1.
Please cite this article in press as: Gerlach, K.K., et al., Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research, Neuropharmacology (2014), http://dx.doi.org/10.1016/j.neuropharm.2014.04.020
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Table 2 Substance categories most frequently involved in adult (20 years old) exposuresdPoison Centers, 2011. Substance (Major generic category)
All substances (% of all exposures)
Single substance (% of single substance exposures)
Analgesics Sedative/Hypnotics/ Antipsychotics Antidepressants Cleaning substances (Household) Cardiovascular drugs Alcohols Bites and envenomations Pesticides Stimulants and street drugs Anticonvulsants Cosmetics/Personal care products
152,173 (12.9) 130,360 (11.1)
70,296 (10.1) 42,519 (6.1)
75,086 (6.4) 67,527 (5.7)
25,928 (3.7) 53,805 (7.7)
66,589 (5.7) 54,226 (4.6) 44,565 (3.8)
26,211 (3.8) 11,387 (1.6) 44,136 (6.3)
41,593 (3.5) 35,557 (3.0)
37,599 (5.4) 19,074 (2.7)
35,321 (3.0) 33,761 (2.9)
13,007 (1.9) 31,206 (4.5)
public health agencies. Given the spontaneous reporting aspect of the calls, PC data are not usable for calculating prevalence estimates. Nevertheless, these data are available in near real-time and are valued as an early warning system since the data are highly drug specific. Calls received by PCs are compiled on a calendar year basis and released in annual reports. The most recent annual report was for 2011 (Bronstein et al., 2012), which reported on 2,334,004 human exposures. Human exposure calls related to stimulants were reported as a combined category with “street drugs,” a category composed of prescription stimulants as well as drugs such as methylenedioxymethamphetamine (MDMA; Ecstasy), cocaine and “bath salts,” which are synthetic amphetamines (Table 2). In the most recent annual PC report, trends in exposure calls were examined for the time period 2001e2011. Of the 25 categories that had the most rapid increases in exposure calls, “Stimulants and Street Drugs” ranked 13th with an average increase of 1231 (95% CI: 326e2136) exposure calls annually. “Stimulants and Street Drugs” were associated with 169 fatalities in 2011, 41 of which were single substance exposures. Data from the proprietary systems (RADARS and NAVIPPRO) are not available in the public domain. Nevertheless, some pharmaceutical companies that have subscriptions to these services as well as the researchers who manage these systems have published some of the data (Sembower et al., 2013). 2. Implications for drug control policy and risk management Although we would like to believe that drug control policy as well as other policies are based on data that are collected from welldesigned studies, this is most often not the case. Policies related to the misuse, abuse and diversion of drugs are frequently based on anecdotal reports that are often exaggerated in the media (Jenkins, 1999). These reports are then cited by politicians and regulatory agencies as the basis for laws and regulations. For example, from 2002 to 2012 the NSDUH showed non-medical use of prescription opioids to be relatively flat and slightly decreasing. During this same period, the media and politicians were claiming that there was an epidemic of prescription opioid abuse in support of drug control laws and regulations that they were advocating. Similarly, “alarming“ reports of stimulant misuse are fairly regularly reported in the popular press despite the lack of supporting data (Kent, 2013; Schwarz, 2013).
If we are to address the issues related to non-medical use of prescription stimulants appropriately, we need to carefully assess all of the relevant data sources. This brief analysis of the available data sources in the US has several implications for drug control policy including FDA mediated risk management of approved medicines. It makes little sense to lump together all licit and illicit stimulants and stimulant-related problems as though they are the same in genesis, ontogeny and public health impact. Many of the surveys do not adequately differentiate licit from illicit stimulants nor have the survey questions themselves been assessed to know whether respondents comprehend the questions that they are asked. Using these data for drug labeling concerning amphetamine risks might be important for discouraging misuse and mitigating iatrogenic addiction but that same label may be irrelevant at best and counter-productive at worst with respect to the behavior of those who primarily abuse stimulants. Conversely, drug control approaches intended to address those who primarily abuse and distribute illicitly manufactured stimulants (e.g., in rural communities) may be of little relevance to prescription drug misusers (e.g., on college campuses). At a national level, drug control policies need to take such differences into consideration and work to harmonize efforts to address the broad and diverse range of problems involving stimulant misuse and abuse. Risk management programs for most drugs address the mitigation of adverse events related to the drug in the patient population taking the drug. Risk management programs for prescription stimulants and other controlled medications are not only aimed at reducing problems in patients but also among those who are not prescribed the drug and abuse it. The effect on the non-prescribed abuser may be quite limited. These efforts may have some impact on reducing diversion of appropriately or inappropriately prescribed medication. Conversely, public service announcements, and education about the risks of stimulants that are focused on the effects and risks of illicit stimulants need to be focused so as to be most relevant to the populations, drugs, and regions targeted. They may be of little credibility, for example, to college student misusers, who perceive relatively little harm and may perceive actual benefit from their occasional use as study aids. How national drug control policies and medication regulations affect these challenges is not simple and is well beyond the scope of this review, but we do hope that this analysis of the epidemiology will help guide thinking about how to achieve more relevant, appropriate and effective control of misuse and abuse of stimulants from prescription methylphenidate to crack cocaine. Understanding the nature of the problem has great relevance to treatment. Programs that are developed for the treatment of injectors of illicitly produced methamphetamine may not only be inappropriate for treating a college student misusing a prescription stimulant, but may be counterproductive. If we are to create policies for the prevention and treatment of misuse, abuse and diversion of stimulants both licit and illicit, it will be critical to accurately understand the scope and nature of the problem. This is a basic tenet of the scientific method. Without this level of understanding, it is almost impossible to develop policies that will appropriately and effectively address the problem without harming those who need the medications. 3. Challenges As demonstrated by the data presented above, the lack of consistent and systematic data collection is problematic nationally and internationally for assessing misuse and abuse of stimulants, differences among stimulants, and the determinants of these differences. Nonetheless, these surveillance data suggest that factors such as the form of the drug and the route by which it is used, and
Please cite this article in press as: Gerlach, K.K., et al., Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research, Neuropharmacology (2014), http://dx.doi.org/10.1016/j.neuropharm.2014.04.020
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the reasons for use are important determinants of patterns of use and adverse consequences such as the development of a substance use disorder and overdose. These inconsistencies may be a downstream impact of the historical precedent of scheduling stimulants for international control by the International Narcotics Control Board based on their similarity to cocaine and amphetamine by the 1961 Single Drug Convention and the 1971 Psychotropic Convention (Spillane and McAllister, 2003). Thus, both extended-release and transdermal methylphenidate, and extended-release amphetamine preparations are scheduled the same as amphetamine and pharmaceutical cocaine in many countries, regardless of formulation and whether their manufacture was licit or not. This occurs regardless of the facts discussed in this review that such drugs appear much less attractive to stimulant-abusing persons and much less likely to be associated with addiction, overdose, and other health problems more typical of cocaine and illicitly manufactured amphetamine. Beyond amphetamine and methamphetamine, new classes of stimulant molecules have required an extension of reference drugs to newer medicines, such as modafinil and atomoxetine, in abuse liability testing (Romach et al., in this issue). Many surveys group prescription stimulants (such as methylphenidate and lisdexamfetamine) with other drugs that upregulate the release of dopamine or inhibit its reuptake, such as MDMA and cocaine, despite the fact that most abuse of the latter drugs occurs with those that are illicitly manufactured and sold. The problem of the co-mingling of legal medications and illicit drugs in surveillance is exemplified by methamphetamine abuse in the US in the early 2000s. At that time, illicit production of methamphetamine (using a common over-the-counter nasal decongestant as a precursor) reached record levels. At the same time, methamphetamine was also produced legally by pharmaceutical companies and legally dispensed by pharmacies. Nevertheless, surveys conducted during this time rarely differentiated between the two, a similar pattern to what is now seen in Europe with amphetamine. Although prescription amphetamine is available in several European countries, almost all of the abuse is related to illicitly produced amphetamine (European Monitoring Centre for Drugs and Drug Addiction, 2014). As novel prescription stimulant medicines are approved by regulatory authorities, it becomes difficult to differentiate the use or abuse of prescribed forms (e.g., lisdexamfetamine) from illicitly produced amphetamine. In addition, street names for stimulants can vary widely, with the same name used for both pharmaceutical and illicitly produced forms of a drug, further confusing reported rates of misuse and abuse. 4. Conclusion This epidemiologic analysis has implications for efforts to effectively mitigate the risks of misuse, abuse, and diversion. The data sources that are available to monitor abuse of stimulant medications are far from comprehensive in scope, and they do not employ standard categories for drugs or measurements of/definitions for misuse and abuse. We strive here to highlight some of the most common issues with surveillance of self-reported stimulant use, and much work remains to be done to devise a classification and survey system that generates reproducible results while maintaining the level of specificity needed for proper public health surveillance. Nevertheless, taken together the available data can provide important pieces of information from which a fairly informative picture of abuse and misuse can be drawn. Further refinement of data collection efforts would greatly improve the accuracy and reliability of estimates of abuse of specific substances. Systems should also provide some degree of flexibility when new products are introduced to the market (both from legal and illegal
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sources) so that any effect can be monitored without too much delay. Our analysis also reveals the challenges in conducting appropriate surveillance and the deficiencies in current surveillance efforts that warrant addressing with the goal of enabling timely, reliable, and comprehensive data collection to serve as the foundation for effective approaches to preventing misuse, abuse and overdose. Finally, we believe this epidemiologic analysis has implications for interpreting the current known neuropharmacology of stimulants and possibly for guiding future neuropharmacology research. Although it is possible that the widely differing patterns of use across drugs and populations as well as widely varying risks of misuse, abuse, and other adverse effects are largely attributable to environmental, social, and individual factors, it seems plausible that differences in the neuropharmacology may also be relevant (Lukas, in this issue). Just as route of administration and drug dose are determinants of drug response, perhaps differences among drugs at the molecular level are more relevant than the relatively crude application of drug scheduling and categorization as “stimulants” would imply. Perhaps, there are unique genetic differences expressed at the molecular level that are critical in the course of misuse and abuse at the individual level that alter vulnerability to the various drugs as discussed by Zhou and Kreek (in this issue) and elsewhere (Bryant et al., 2012; Mercer et al., 2013; Zhou et al., 2010). There are many questions, but our hope is that neuropharmacologists will increasingly look to epidemiology as they consider what it is that they hope to explain through laboratory research. Similarly, we hope that epidemiologists will increasingly consider differences in the neuropharmacology across drugs in the design of surveillance instruments and interpretation of data. Disclosure The authors consult for or have consulted in the past three years through Pinney Associates to pharmaceutical companies regarding the regulation, development and post-marketing surveillance of stimulant products and other CNS drugs of abuse. This manuscript was independently prepared without support for or input from any such commercial interests. Acknowledgments The authors thank Mark Sembower for his assistance with federal survey data analysis. References American Psychiatric Association, 2013. Diagnostic and Statistical Manual of Mental Disorders, fifth ed. Washington, DC. Biondo, G., Chilcoat, H.D., 2014. Discrepancies in prevalence estimates in two national surveys for nonmedical use of a specific opioid product versus any prescription pain reliever. Drug Alcohol Depend. 134, 396e400. Bronstein, A.C., Spyker, D.A., Cantilena Jr., L.R., Rumack, B.H., Dart, R.C., 2012. 2011 Annual report of the American Association of Poison Control Centers’ National Poison Data System (NPDS): 29th Annual Report. Clin. Toxicol. (Phila) 50, 911e 1164. Bryant, C.D., Parker, C.C., Zhou, L., Olker, C., Chandrasekaran, R.Y., Wager, T.T., et al., 2012. Csnk1e is a genetic regulator of sensitivity to psychostimulants and opioids. Neuropsychopharmacology 37, 1026e1035. Calderon, S.K.M., 2014. (in this issue). Centers for Disease Control and Prevention, 1994. Cigarette smoking among adults e United States, 1992, and changes in the definition of current cigarette smoking. Morb. Mortal. Wkly. Rep. 43, 342e346. Available online: http://www. webcitation.org/346NX341jqesN (accessed February 320, 2014). Cicero, T.J., Inciardi, J.A., Munoz, A., 2005. Trends in abuse of oxycontin and other opioid analgesics in the United States: 2002e2004. J. Pain 6, 662e672. Dart, R.C., 2009. Monitoring risk: post marketing surveillance and signal detection. Drug Alcohol Depend. 105 (Suppl. 1), S26eS32. Dasgupta, N., Schnoll, S.H., 2009. Signal detection in post-marketing surveillance for controlled substances. Drug Alcohol Depend. 105 (Suppl. 1), S33e41.
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Please cite this article in press as: Gerlach, K.K., et al., Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research, Neuropharmacology (2014), http://dx.doi.org/10.1016/j.neuropharm.2014.04.020
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