Opioid dependence and addiction during opioid treatment of... : PAIN (original) (raw)
1. Introduction
Opium, the dried juice of the seedpod of the opium poppy, has been used for the relief of pain and suffering for several thousand years. Many opioid drugs are still derived from opium, and the opium poppy is cultivated for both legitimate and illegitimate purposes. The propensity of opioids to cause addiction goes hand in hand with their powerful analgesic and euphoric effects, and the obvious conflict between relieving suffering and causing it through addiction has given rise to much philosophical debate. Until relatively recently, the choice of use versus avoidance was largely that of the user. But when several factors, including industrialized production of opioids and expanded global trade, led to increased use and abuse, controls were instituted that make legitimate opioid use entirely the responsibility of physicians. Physicians now face the same conflict that users have faced for many centuries – can they use these powerful compounds for the humane treatment of pain and suffering without inflicting a different sort of suffering through addiction?
Although clinicians may currently be frustrated by gaps in knowledge about the complex interactions between the many facets of opioid actions (analgesia, hyperalgesia, addiction, tolerance, and dependence), it is salutary to remember that until the twentieth century, the existence of an endogenous opioid system was not even imagined, and the role of opioids as unique and indispensable analgesics was not fully appreciated. Much progress has been made. The introduction of drug controls at the beginning of the twentieth century had a dampening effect on opioid prescribing by physicians, especially in the United States, where opioids could not be legally prescribed to addicts. However, a backlash against under-prescribing, concurrent with the rapid unraveling of pain and opioid mechanisms, resulted in the establishment of opioid treatment for acute and terminal1 cancer pain. Short-term opioid treatment was found to be highly effective and associated with negligible rates of addiction. On the wave of this success, opioid treatment for pain was subsequently extended to patients with chronic pain; assumptions were made that analgesic efficacy and addiction rates would be similar. It is becoming clear, however, that these assumptions must be reexamined.
2. Neurobiology of addiction
2.1. The central role of reward mechanisms
It is now firmly established, on the basis of countless studies in animals and humans, that drug addiction is a chronic neurobiological disease produced by repeated exposure to an addictive drug and characterized by loss of control over drug use. Neuronal pathways that form the so-called “reward circuits” play a central role in compulsive drug taking and addiction and are found within mesocorticolimbic dopamine systems originating in the ventral tegmental area and projecting to the nucleus accumbens, amygdala, and prefrontal cortex (Fig. 1). All addictive drugs act on this system, through different mechanisms, and activation causes euphoria and reinforcement of drug-seeking behaviors. Opioids induce dopamine release indirectly by decreasing GABA-inhibition via μ-opioid receptors in the ventral tegmental area (Johnson and North, 1992; Bonci and Williams, 1997; Cami and Farre, 2003), as well as directly by interacting with opioid receptors in the nucleus accumbens (Nestler, 1996; Hyman and Malenka, 2001). While it is understood that the mesocorticolimbic dopamine systems are prominent and central in addiction processes, there is still considerable uncertainty about the exact neural circuitry and neurotransmitters involved. It has recently been postulated that dopamine may not directly mediate the hedonic impact of addictive drugs; rather, it may serve to bind the hedonic impact of a drug to the motivational components of drug use such as drug seeking (Hyman and Malenka, 2001; Hyman et al., 2006).
Key neural circuits of addiction. Adapted with permission from Nestler EJ. Molecular basis of long-term plasticity underlying addiction. Nature Rev Neurosci 2001;2:119–28. Dotted lines indicate limbic afferents to the nucleus accumbens (Nac). Blue lines represent efferents from the Nac thought to be involved in drug reward. Red lines indicate projections of the mesolimbic dopamine system thought to be a critical substrate for drug reward. Dopamine neurons originate in the ventral tegmental area (VTA) and project to the Nac and other limbic structures, including the olfactory tubercle (OT), ventral domains of the caudate-putamen (C-P), the amygdala (AMG) and the prefrontal cortex (PFC). Green indicates opioid-peptide-containing neurons, which are involved in opiate, ethanol, and possibly nicotine reward. These opioid peptide systems include the local enkephalin circuits (short segments) and the hypothalamic midbrain β-endorphin circuit (long segment). ARC, arcuate nucleus; Cer, cerebellum; DMT, dorsomedial thalamus; IC, inferior colliculus; LC, locus coeruleus; LH, lateral hypothalamus; PAG, peraqueductal grey; SC, superior colliculus; SNr, substantia nigra pars reticulata; VP, ventral pallidum.
2.2. Theories of addiction
Early research into addiction focused on the development of tolerance (drug insensitivity), and it was thought that this was the hallmark of dependence and addiction (Wise, 2000). Today, a much more complex picture has emerged. The predominant role in addiction processes of the positive reinforcing effects of drugs of abuse mediated through the mesocorticolimbic reward systems is now firmly established. More recently it has been recognized that withdrawal phenomena, acting on this same reward circuitry, create negative reinforcing effects (withdrawal anhedonia) which contribute to craving and compulsive use, at least during active use and early abstinence (Koob and Le Moal, 1997, 2001; Cami and Farre, 2003).
The physical symptoms of withdrawal are also critical in addiction. Opioid-induced upregulation of the cAMP pathway in neurons of the locus coeruleus (the brain’s major noradrenergic nucleus) has been shown to be involved in the development and expression of physical (physiological) dependence, which leads to acute withdrawal symptoms following cessation of opiate administration (or opiate antagonism) in dependent animals. Activation of the cAMP pathway by repeated opioid administration leads to phosphorylation of the transcription factor CREB (cAMP response-element binding protein), in turn inducing transcription of many genes. Other brain regions and possibly the spinal cord are also involved in opioid withdrawal responses. (Koob et al., 1992; Nestler and Aghajanian, 1997; Williams et al., 2001; Cami and Farre, 2003; Nestler, 2004a,b). The immediate negative reinforcing effects of withdrawal (psychological and physical) constitute a significant driving force in drug-seeking behavior; however, they must be distinguished from long-term drug craving and the compulsive drug-seeking of addiction which persists long after recovery from withdrawal.
One theory of addiction states that drug addiction arises through dysregulation of reward mechanisms and subsequent allostasis – achieving a new stable “set-point” that is outside the normal homeostatic range (Koob and Le Moal, 1997, 2001). As the reward mechanisms become dysregulated by continued drug use, the pleasurable effects of the drug (“liking”) diminish, while the incentive effects (“wanting” or “craving”) increase, leading to compulsive drug-seeking (Robinson and Berridge, 2001; Robinson and Berridge, 2003). The positive reinforcing effects of the drug diminish, while the negative reinforcing properties (relief of withdrawal) strengthen (Koob and Le Moal, 1997, 2001; Gardner, 1999, 2005).
2.3. Learned behaviors
As drug addiction develops, the changes that occur in the brain are induced not only by the drug itself, but also by behaviors and circumstances associated with obtaining and using the drug (Childress et al., 1986; Nestler, 1996, 2001; Self and Nestler, 1998; Sell et al., 1999; Hyman and Malenka, 2001; Narita et al., 2001). Contextual cues (for example, drug paraphernalia or locations of past drug abuse), combined with drug use, form a powerful memory imprint, as in all conditioning responses, that is not easy to eradicate, even after drug cessation (Robinson and Berridge, 1993; Morris et al., 1997; O’Brien et al., 1998; Self and Nestler, 1998; Sell et al., 1999; Shaham et al., 2000; Wise, 2000; Hyman and Malenka, 2001). These effects seem to involve structures involved in memory, conditioning and learning, such as the amygdala, hippocampus, and cerebral cortex (Fig. 1). It has been proposed that this type of neuroadaptation occurs through reorganization of neural circuitry produced by increases in synaptic strength (synaptic plasticity), changes in intrinsic excitability (properties or numbers of voltage-dependent ion channels) or actual morphological changes (Nestler, 1996, 2001; Martin et al., 2000; Hyman and Malenka, 2001). The longer the drug is abused, the more irreversible this adaptation becomes (Hyman, 1997; Wise, 2000; Hyman and Malenka, 2001; Kreek, 2001).
Stress associated with drug taking is also important in addiction processes. Human and animal studies confirm the role of stress and stress responsivity in addiction. Numerous studies using stress paradigms such as restraint, electric shock, social threat and defeat, food or water restriction, social isolation, and maternal separation, in animal models of conditioned place preference and self administration, suggest overall that both acute and chronic stressors can enhance the rewarding properties of drugs and induce reinstatement of self-administration following extinction (Shaham et al., 2000; Lu et al., 2003). The hypothalamic-pituitary-adrenal (HPA) axis plays a central role in these processes (Schluger et al., 1998; Sarnyai et al., 2001), and repeated drug exposure appears to cause long-term adaptations (Schluger et al., 2001; Kreek et al., 2002). For example, studies of stressful and drug-cue stimuli in humans have shown that both play a significant role in inducing drug craving in abstinent cocaine addicts as well as in relapse to cocaine use, and that the HPA axis, possibly interacting with the noradrenergic/sympatho-adreno-medullary system, is involved in this response (Sinha et al., 2003).
2.4. Enduring adaptations
As addiction science has progressed, it has become clear that addiction arises through complex adaptations within defined neurocircuitry, predominantly in the brain. Where once addiction was explained as a form of tachyphylaxis whereby increasingly more drug was needed to satisfy an unmet need, later the importance of reward reinforcement by addictive drugs was recognized, and more recently, the importance of enduring neuroadaptations that explain relapse has been recognized. Such adaptations do not come about simply because of continued drug use, but as a result of complex interactions between drugs themselves and the circumstances in which they are taken. Thus, in vulnerable individuals, interaction between the drugs themselves and genetic, environmental, psychosocial, behavioral, and other factors produces long-lived adaptations in selected groups of neurons in the brain which explain the enduring effects of addiction (Fig. 2).
The three domains contributing to addiction.
There has been considerable progress made towards identifying the underlying mechanisms of these adaptations, including changes in gene transcription, in RNA and protein processing, and in synaptic structure (Nestler, 2001, 2004a,b). Gene expression or protein translation confers long-term alterations on behavior by causing the physical remodeling of synapses and circuits (Hope et al., 1994; Berke et al., 1998; Hyman and Malenka, 2001). It is likely that neural genes are regulated by multiple transcription factors, but two in particular have so far been implicated – cAMP response-element binding protein (CREB) and ΔFosB. CREB was first implicated because it was activated in the locus ceruleus as a result of upregulation of cAMP, a compensatory homeostatic response to chronic opioid administration (Nestler and Aghajanian, 1997; Nestler, 2001, 2004a,b). CREB is involved in the expression of genes that show prolonged upregulation in response to stimulation by addictive drugs, and may have a role in synaptic remodeling and processes related to long-term memory (Hyman and Malenka, 2001). Repeated drug exposure also induces Fos genes, and animals that over-express Fos genes have increased sensitivity to the habit-forming effects of addictive drugs (Wise, 2000). ΔFosB is a stable truncated splice variant of the fosb gene which is induced in the dorsal striatum and nucleus accumbens by chronic exposure to a variety of abused drugs. ΔFosB expression affects opioid analgesia, reward, tolerance, and physical dependence possibly through interaction with the opioid peptide dynorphin (Zachariou et al., 2006). It is particularly interesting that adaptations mediated by ΔFosB in the nucleus accumbens are seen to profoundly alter morphine analgesia and tolerance, even though this site has not previously been thought to influence analgesia per se (Zachariou et al., 2006). Because levels of ΔFosB return to basal level after 4weeks of drug cessation, they cannot explain later relapse, but their downstream effects (such as increases in synaptic strength) could outlast their expression (Hyman and Malenka, 2001). The persistence of memory seems to depend on such changes in neural circuitry rather than on protein levels (Koob and Le Moal, 2001; Hyman and Malenka, 2001; Robinson and Berridge, 2003).
3. Genetics of addiction
Genetic factors primarily influence addiction risk by affecting individuals’ vulnerability to develop addiction and addiction comorbidities. In addition, genetic factors influence individuals’ handling of drugs, and thus their likelihood of experiencing rewarding effects, and indeed, analgesia. It has been proposed that the various components of genetic influence affect risk differently at each stage during the development of addiction (Fig. 3).
Influences on stages of addiction. Personality traits are likely to have their strongest influence on the initiation phase of drug use. Social pressures, drug formulation, and drug disposition (the latter substantially genetically determined) contribute significantly to both initiation and early repeated use. Personality factors probably contribute less to addiction and relapse after chronic drug exposure has induced changes in the brain. Personality factors, drug disposition, comorbidity, and stress responsivity, continued drug use and environmental factors interact in influencing the progression to addiction. Genetic factors, also interacting with environmental factors, contribute in varying degrees to each type of biological influence.
Addiction genetics is a rapidly growing field, and while studies to date have only few clinical implications in terms of iatrogenic opioid addiction, it is likely that important insights will be gained in the near future. For example, genetic profiling might help in risk stratification, while advances in pharmacogenetics might help elucidate mechanisms to explain the vastly differing responses to opioids between individuals, and possibly allow drug treatments to be individually tailored.
3.1. Vulnerability
Studies of genetic epidemiology using twin, family, and adoption designs have firmly established that addiction to a variety of drugs and alcohol is influenced by genetic factors. Heritability estimates range from 0.3 to over 0.5, depending on the drug and the study (Cloninger et al., 1981; Cadoret et al., 1986; Pickens et al., 1991; Bierut et al., 1998; Tsuang et al., 1998; Kendler et al., 2003). Although each of these studies identified a heritable contribution to the addiction, they report conflicting findings as to whether a single genetic factor predisposes individuals to all addictive drugs or whether there are genetic factors specific to each type of drug. For example, Kendler et al. identified a common genetic factor that influenced abuse/dependence for all of the drugs studied, with no drug-specific factors (Kendler et al., 2003). However, in twin studies by Tsuang et al. the authors identified genetic and environmental factors that were general for abuse of several types of drugs as well as influences specific to each drug class (Tsuang et al., 1999).
The search for specific gene variants that affect addiction risk has been undertaken both by positional (gene mapping) as well as hypothesis-based candidate gene approaches (focusing on likely candidate genes). Genome-wide studies of linkage or association with alcohol, opiates, cocaine, nicotine, and mixed drug dependence have identified chromosomal regions that may contain genes affecting addiction risk (Reich et al., 1998; Straub et al., 1999; Uhl et al., 2001; Edenberg et al., 2004; Gelernter et al., 2005, 2006). Many of these regions are concordant across studies, leading to a limited number of regions reproducibly implicated in addiction (Uhl, 2004). Further fine mapping studies in multiple populations will likely identify additional genes that affect addiction vulnerability.
Several types of candidate genes have been evaluated for potential contribution to addiction. Gene variants of the serotonergic, dopaminergic, GABAergic, and other systems have been associated with impulsivity, novelty seeking, risk-taking and other personality traits that may influence early stages of drug abuse that may lead subsequently to addiction, typically during illicit use. Many of these genes have also been found to be associated with addiction, however, the lack of replication of such studies has not yet provided a clear picture of how these genes affect personality traits or comorbid psychiatric pathophysiologies that contribute to overall addiction vulnerability (Kreek et al., 2005). In the case of opioid treatment of pain, genetic contributions may have a different emphasis, since both initiation and maintenance of drug use are determined by the physician and not the patient.
3.2. Drug handling
Pharmacokinetic genes encode enzymes or other proteins involved in drug disposition and metabolism. A pharmacokinetic gene of relevance to opioid therapy is the cytochrome P450 2D6 gene (CYP2D6). CYP2D6 catalyses the biotransformation of codeine into morphine, which has approximately tenfold greater analgesic potency than the parent compound. Many variants of CYP2D6 are known to affect the phenotypic expression of this enzyme, with approximately 10% of European Caucasians classified as poor metabolizers (Lötsch et al., 2004; Kreek et al., 2004). It has been suggested that poor metabolizers of codeine would be at decreased risk for codeine dependence (Kathiramalainathan et al., 2000); however, a clinical trial of a CYP2D6 inhibitor did not support its use for treatment of codeine dependence (Fernandes et al., 2002). Poor metabolizers also derive less analgesic benefit from codeine.
Pharmacodynamic genes encode proteins that mediate the effects of a drug, including receptors at which a drug interacts or other components of endogenous physiological or cellular systems involved in drug responses. One example that has been extensively studied is the μ-opioid receptor. This receptor is essential for responses to μ-agonists, including analgesia, respiratory depression, locomotor activity, reward, and withdrawal (Kieffer and Gavériaux-Ruff, 2002). The most common coding region variant of OPRM1 is the A118G single nucleotide polymorphism (SNP), which causes an amino acid substitution (Asn40Asp) in the N-terminal extracellular domain of the receptor (Bond et al., 1998). The frequency of the 118G allele varies widely in different populations, from less than 0.02 in African-Americans up to 0.49 in Japanese (LaForge et al., 2000). A number of studies have supported a role for this gene in addiction including to opioids and alcohol, although these findings have not been replicated in other studies, possibly due to differences in experimental technique (Lötsch and Geisslinger, 2005). Several studies have consistently shown that the A118G variant affects opioid-mediated control of the hypothalamic-pituitary-adrenal (HPA) stress-responsive axis and that this may have implications for the treatment of alcoholism with opioid antagonists (Wand et al., 2002; Oslin et al., 2003). Deletion of this gene also results in decrease or elimination of reward for cocaine and alcohol (Kieffer and Gavériaux-Ruff, 2002). The 118G allele of OPRM1 has also been associated with reduced analgesic and pupillary responses to μ-directed opioids (Skarke et al., 2003; Klepstad et al., 2004; Romberg et al., 2005; Lötsch and Geisslinger, 2006).
3.3. Stages of addiction
Addiction is seen as a multi-stage process involving initiation of drug use, progression to intermittent and then regular use, followed by dependence or addiction, and frequently, relapse following withdrawal and cessation of drug use (Kreek et al., 2005). Genetic determinants could influence one or several stages of this process, one drug more than another or have a key role that influences the process overall (Fig. 3). In support of this idea, in the twin study of Tsuang et al. the stages of transition from first drug use, to regular drug use, and to abuse/dependence were influenced to a different extent by genetic and environmental factors depending on the drug (Tsuang et al., 1999).
Aspects of personality, such as risk-taking or deficits of impulse control, might be expected to influence initiation or early stages of drug use. Physiological and psychological responses to drug administration would be expected to affect the progression from use to sporadic compulsive use (abuse) to addiction. Other systems, particularly those dysregulated by long-term drug administration, are involved in withdrawal symptoms, craving, and the possible development of a permanent anhedonic state that contributes to relapse. Gene variants that may contribute to each of these domains of factors have been candidates for addiction studies.
4. Addiction terminology
Inconsistencies in addiction terminology have greatly hampered efforts to define and quantify opioid addiction arising as a direct result of opioid pain treatment (iatrogenic opioid addiction). Whereas the words “abuse”, “dependence” and “addiction” are fairly well understood in general parlance, attempts to find acceptable medical terms with well-defined diagnostic criteria have often resulted in confusion, contradictory usage and misunderstanding. The resultant inconsistencies in terminology are apparent not only in the language of lay authors, the press and the regulators, but also throughout the medical literature. The adoption of the term “dependence” to denote drug (and alcohol) addiction (WHO, 1992, 1998; DSM-IV, 1994) produces one of several areas of difficulty. Essentially, the word “dependence” has been commandeered to mean addiction, whereas it is becoming increasingly clear that dependence (psychological and physical) may arise independently, especially in pain patients, and could result in short-term craving and compulsive opioid use (problematic opioid use) without addiction (O’Brien et al., 1998; Cami and Farre, 2003; O’Brien, 2005; Hyman et al., 2006). Two factors seem pertinent reasons for having adopted the term dependence to mean addiction. First, attempts to “medicalize” the terminology and avoid the enormous social stigma of the words “addict” and “addiction”; second, the once-held belief that dependence and withdrawal are cardinal symptoms of addiction, whereas it is now recognized that they are neither necessary nor sufficient for a person to be addicted (Hyman et al., 2006).
4.1. Drug addiction
A great deal of confusion arises over the use of the word addiction. The word was removed from the medical lexicon when both the World Health Organization (WHO) and the American Psychiatric Association (APA) chose the term substance dependence for the phenomenon that in general parlance is known as drug addiction (WHO, 1992, 1998; DSM-IV, 1994). The WHO and APA developed classifications that define substance dependence broadly to allow entrance into treatment for any individuals who might benefit. Tolerance and withdrawal (physical dependence) are two of seven criteria for substance dependence according to the fourth edition of the APA’s Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), the remaining criteria being behavioral factors (Table 1). By the DSM-IV definition, three criteria must be present for the diagnosis of substance dependence, therefore a behavioral component must be present, although tolerance and withdrawal (physical dependence) do not necessarily need to be present.
DSM-IV substance dependence criteria
Concern that opioid-induced tolerance and physical dependence arising in pain patients should not be linked to the stigma of substance dependence or addiction prompted the development of definitions specifically for use during pain treatment. A consensus panel of nine experts from the American Pain Society (APS), the American Academy of Pain Medicine (AAPM) and the American Society of Addiction Medicine (ASAM) devised new definitions that separate tolerance and physical dependence from the behavioral component addiction (Table 2) (Heit, 2003). In doing this, they restored the word addiction to the medical lexicon – at least in the pain field. Unfortunately, these definitions have tended to produce even more confusion and misunderstanding because by separating tolerance and physical dependence from addiction, the implication is that there is no psychological dependence or craving (reversible) without addiction (an enduring state).
Definitions related to the use of opioids for the treatment of pain
Substance abuse, as defined in the DSM-IV manual, and as distinct from substance dependence, describes maladaptive drug seeking behaviors that do not meet the criteria for substance dependence, in part because of lack of tolerance and physical dependence (Table 3). The term substance abuse describes a less severe disorder that may progress to substance dependence, and the concept of two levels of _substance use disorder_2 arises from the observation that a progression from sporadic use (abuse) to continuous use (dependence) typifies addiction in illicit drug users. Since during opioid treatment of pain, use is initiated and stabilized by physicians not patients, and since most continuously treated patients develop tolerance and physical dependence, substance abuse, as defined by DSM criteria, is rarely applicable to chronic pain patients, unless their opioid use is erratic. Yet in common parlance, “substance abuse” is understood to simply mean addiction to drugs or alcohol or, more literally, abusive use of drugs or alcohol. Because of this common usage, many writers, including those writing about opioid treatment of pain, use the term substance abuse without a stated or agreed definition, which again confuses addiction terminology (Weaver and Schnoll, 2002a).
DSM-IV substance abuse criteria
4.2. Problematic opioid use
Patients who deviate from a prescribed program of opioid treatment can be categorized as patients with problematic opioid use (also sometimes termed opioid misuse or carelessly, opioid abuse). There are many descriptions in the literature of problematic opioid use, all differing slightly from one another (Maruta, 1978; Khatami et al., 1979; Evans, 1981; Fishbain et al., 1992; Chabal et al., 1997; Weaver and Schnoll, 2002a; Passik and Kirsh, 2004). Chabal et al. describe a well-considered and comprehensive list of five essential factors that effectively encompass the aberrant behaviors seen in opioid treated pain patients and help to define problematic opioid use (Table 4). For the purposes of this article, we will use the term problematic opioid use to denote problematic opioid-seeking behavior that does not meet the DSM-IV criteria for substance dependence, and drug addiction, opioid addiction or _iatrogenic opioid addiction_3 for the clinical presentation that matches the DSM-IV criteria for substance dependence (Table 1).
Criteria for problematic opioid use
4.3. Tolerance
Drug tolerance is manifest as a need for increasing doses to achieve the same effect. Tolerance to the effects of drugs occurs with a large number of different drugs, and is not restricted to opioids, or even to addictive drugs. For all drug tolerance, it is likely that there is a psychological (associative or learned) as well as a pharmacological (non-associative or physiological) mechanism for the effect. In the case of opioids, tolerance develops to the drugs’ analgesic and hedonistic effects, as well as to their side effects, and each component is likely to arise through distinct mechanisms related to the anatomic or neuroanatomic substrate of the different effects (Koob et al., 1992; Nestler and Aghajanian, 1997; Hyman et al., 2006). Because bowel effects are predominantly mediated directly through receptors on the bowel itself, and are less affected by the type of neuroadaptations that arise in the CNS, there is generally no tolerance to the bowel slowing effects of opioids.
Tolerance to the hedonistic effects of opioids is marked, to the extent that tolerance, and the need to take increasing doses to achieve intoxication or the desired effect, characterizes opioid addiction (as well as addiction to several other substances) (DSM, 1994). In contrast, analgesic tolerance is less obvious. Some clinicians argue that there is no pharmacological (physiological) tolerance to the analgesic effects of opioids. This is on the grounds that after initial titration, there may be stable analgesia with no need for dose escalation. On the other hand, the need for escalating doses in the absence of disease progression is also observed (Bruera et al., 1988; Mercadante and Bruera, 2006), as is the need for higher than usual doses when acute pain arises in patients receiving chronic opioid treatment (de Leon-Casasola et al., 1993; Rapp et al., 1995; Mitra and Sinatra, 2004; Angst and Clark, 2006; Wilder-Smith and Arendt-Nielsen, 2006). Supporting a pharmacological mechanism for opioid analgesic tolerance, animal studies of reflex pain responses (absent of influence from higher centers) show marked analgesic tolerance (Yu et al., 1997; South and Smith, 2001; Bailey and Connor, 2005); classical studies in humans also show the effect (McQuay, 1999); and it is known that opioid-induced adaptations occur at multiple locations and at multiple levels in the nervous system including pain-related areas, and involve direct drug effects (pharmacological component) as well as psychological (associative or learned) effects (Koob et al., 1992; South and Smith, 2001; von Zastrow, 2004). This is a clinical controversy that is not resolved (Portenoy, 1994; Turk, 1996; Collett, 1998).
The underlying mechanisms of tolerance remain elusive, despite intensive efforts to understand the phenomenon, given its implications in addiction development and pain management. Associative tolerance (which can arise in the case of all the central effects of opioids including euphoria and dysphoria, sedation, analgesia, and nausea) involves learning, and its development is linked to environmental or contextual cues (Grisel et al., 1996; Mitchell et al., 2000). Cellular and molecular mechanisms of non-associative (pharmacological) tolerance to opioids have not been fully elucidated but may involve receptor internalization, recycling, desensitization or downregulation (Bohn et al., 2000; Taylor and Fleming, 2001; Watts, 2002; He and Whistler, 2005). Many studies have implicated the _N_-methyl-d-aspartate (NMDA)-receptor in opioid tolerance, although other receptors and systems could also be involved (Trujillo, 2000; Mao et al., 2002; Nitsche et al., 2002; Raith and Hochhaus, 2004; He and Whistler, 2005). Processes that oppose opioid actions, for example, upregulation of cAMP and CREB, have been implicated in tolerance to the hedonic effects of opioids (Nestler, 2004a,b). Spinal dynorphin mechanisms have been implicated in the development of opioid analgesia tolerance (Vanderah et al., 2000; Vanderah et al., 2001), while dynorphin mechanisms have also been linked to tolerance and possible dependence, leading to dyphoria (Carlezon et al., 2005). Several endogenous peptides oppose the analgesic effects of opioids, and are therefore termed anti-opioid peptides. These include vasopressin, oxytocin, nociceptin, and cholecystokinin (Cesselin, 1995; Wiesenfeld-Hallin and Xu, 2001; Xu et al., 2003). Apparent analgesic tolerance may arise as a consequence of opioid-induced hyperalgesia, and disease progression or a change in pain status can be mistaken for analgesic tolerance (Mao et al., 1994, 1995; Mao, 2002; Ballantyne and Mao, 2003; Chu et al., 2006).
4.4. Physical dependence
Physical (physiological) dependence is a distinct phenomenon that results from physiological changes induced by repeated or continuous drug use and is manifest as a withdrawal syndrome upon stopping or reducing drug use. Physical dependence occurs with non-addicting drugs such as tricyclic antidepressants and α-2 adrenergic agonists, as well as addictive drugs. Different classes of drugs produce different withdrawal syndromes. Physical dependence is the manifestation of compensatory adaptations in brain regions that control somatic functions: in the case of opioids an important region affected is the noradrenergic nucleus the locus coeruleus (Hyman, 1997; Cami and Farre, 2003). Symptoms of opioid withdrawal include central neurologic arousal and sleeplessness, irritability, psychomotor agitation, diarrhea, rhinorrhea, and piloerection, and appear to result, at least in part, from an upregulation of cyclic adenosine monophosphate (cAMP) and noradrenergic mechanisms in the locus coeruleus or other brain regions (Nestler and Aghajanian, 1997; Nestler, 2004a,b). Physical dependence is a common consequence of chronic opioid administration, and a careful taper is needed to avoid withdrawal symptoms (Fine, 2004; Jage, 2005). The exact timing of the development of physical dependence is unclear, but is thought to develop after three days of continuous opioid use.
Psychological dependence must be distinguished from physical dependence. Psychological dependence is manifest as the psychological component of withdrawal, which comprises both unpleasant emotional effects (withdrawal anhedonia and dsyphoria) (Koob et al., 1992, 1997, 2001; Hyman et al., 2006) and motivational effects (craving during withdrawal), the latter being partly mediated by physical withdrawal. Psychological and physical dependence could arise during problematic opioid use as well as during opioid addiction, and the degree to which each is manifest, or important as a driver of compulsive opioid use, is known to vary markedly between individuals and at different stages during the development of addiction (Hyman et al., 2006).
4.5. Pseudoaddiction
The term pseudoaddiction was coined by Weissman and Haddox to describe reversible opioid-seeking behavior occurring in a patient with under-treated cancer pain whose behavior normalized once the pain was under control (Weissman and Haddox, 1989). The patient’s behavior was not maladaptive and therefore did not meet the criteria for drug addiction. The term was quickly adopted by physicians treating pain, who prefer to avoid the label addiction, not least because its stigma acts as a barrier to adequate pain control (CASA, 2000).
4.6. Diversion
This term describes the diversion of prescription opioids from their intended recipient. Diversion may be casual or a deliberate attempt to profit. A considerable proportion of diverted prescription opioids is stolen from warehouses and pharmacies before it reaches patients (Joranson and Gilson, 2005, 2006; Inciardi et al., 2006), although diversion during pain management also occurs. Diverting of prescription drugs is a criminal offence. Identifying diverters is not always easy, since these patients often appear to be model patients.
5. Chronic pain and addiction
5.1. Defining chronic pain
Before reviewing the literature on chronic pain and addiction, it will be helpful to explain what is meant by the term “chronic pain”. Chronic pain was traditionally defined as pain lasting more than 3 or 6months, depending on the source of the definition (Russo and Brose, 1998; Schaible and Richter, 2004). More recently, chronic pain has been defined as “pain that extends beyond the period of tissue healing and/or with low levels of identified pathology that are insufficient to explain the presence and/or extent of pain” (Jacobsen and Mariano, 2001). There is no general consensus on the definition of chronic pain. In clinical practice it is often difficult to determine when acute pain has become chronic or when a chronic disease has entered its terminal phase. Similarly, in clinical practice there may be a gradual progression from short-term or intermittent opioid use to long-term or continuous use, with no definable boundary. For the purpose of this review, the authors consider chronic pain to be pain existing as a chronic, enduring condition lasting months to years rather than the days to months associated with acute pain and pain during terminal illness. Chronic cancer-related pain is here considered part of the spectrum of chronic pain conditions. “Long-term” opioid treatment is continuous opioid treatment of chronic pain, as defined above.
5.2. Chronic pain and psychiatric comorbidity
Chronic pain patients commonly present with psychiatric comorbidities. The most frequent of these are depression, anxiety, substance use disorders,4 somatization and personality disorders (Katon et al., 1985; Fishbain et al., 1988; Magni et al., 1990; Dersh et al., 2002; McWilliams et al., 2004; Edlund et al., 2007). For example, between 18% and 32% of chronic low back pain patients are found to have major depression during the course of their treatment (Katon et al., 1985; Magni et al., 1990; McWilliams et al., 2004; Wasan et al., 2005). (This compares with estimates of point prevalence for major depression in the general US population of 5%) (Blazer et al., 1994). Substance use disorders (abuse or dependence) are also markedly more prevalent in these patients. Using standard measures for diagnostic assessment (based on DSM-IV criteria), investigators have found 15–28% rates of current substance use disorder and 23–54% lifetime prevalence in chronic pain patients (Katon et al., 1985; Fishbain et al., 1986; Polatin et al., 1993; Dersh et al., 2002). Although it is difficult to determine whether current substance use disorder rates in chronic pain patients differ from those in the general population, since there are no reliable comparative data, it is clear that lifetime prevalence is higher than the 16.7% estimated in the general population (Dersh et al., 2002; SAMHSA, 2000). Whether the comorbidity is depression, anxiety, substance use disorder, somatization or personality disorder, high rates of concurrence with chronic pain are well documented. It is less clear, however, which comes first, the pain or the psychopathology (Fishbain et al., 1997). Several studies have addressed this “chicken and egg” dilemma. For example, in a study of 200 chronic low back patients, Polatin et al. were able to demonstrate that substance use and anxiety disorders seem to precede the onset of chronic pain, whereas major depression could either precede or follow it (Polatin et al., 1993). On the other hand, another study of 421 chronic low back pain patients found no correlation between premorbid psychopathology and chronic pain disability (Gatchel et al., 1995). In primary care clinic patients with concurrent chronic back pain and substance use disorder, the substance use disorder preceded the onset of chronic pain in 77% of patients with current and 63% with lifetime substance use disorders (Brown et al., 1996). Other studies suggest that psychiatric comorbidity may influence pain chronicity rather than onset (Kinney et al., 1993; Gatchel et al., 1996; Dersh et al., 2002).
5.3. Addiction and psychiatric comorbidity
In addicts, depression, anxiety, personality disorder, and hyperactivity disorder are commonly present (Rounsaville et al., 1982; Levin and Kleber, 1995; Kreek et al., 2005). In epidemiological studies, between 17% and 60% of individuals with drug addiction have depression or anxiety disorders at presentation (Rounsaville et al., 1982). The extent to which these addicts were affected by psychiatric disorders before initiation of drug use, how many recover after addiction treatment or recovery, and to what extent they recover is not well defined (Kreek et al., 2005).
5.4. Do psychiatric comorbidities alter the initiation and development of pain and addiction?
Although the high incidence of psychiatric comorbidity in both chronic pain patients and addicted individuals is well documented, the processes by which comorbidities alter the initiation and development of pain and addiction remain elusive. The diathesis–stress model, in which genetic and biological vulnerability (diathesis) interacts with life experiences (stress), is a useful construct on which to base studies that attempt to elucidate the interplay between chronic pain, addiction and their shared comorbidities (Banks and Kerns, 1996). On the basis of this construct, it is reasonable to suppose that chronic pain patients, having a high rate of shared psychiatric comorbidites with addiction, might be at increased risk of developing iatrogenic opioid addiction. A recent large population study of Veterans treated with opioids for a variety of chronic pain conditions found prior mental health disorders to be a moderately strong predictor of iatrogenic opioid abuse and dependence. Prior substance abuse was a strong predictor. However, the prevalence of prior mental health disorders was much higher than that of prior substance abuse (45.3% versus 7.6%), thus the population-attributable risk for iatrogenic opioid abuse and dependence was calculated at 14% for prior mental health disorders and 4% for prior substance abuse (Edlund et al., 2007). This remains an area of considerable controversy, and one that has proved difficult to study. Whereas comorbidities may be mechanistically important in the initiation (vulnerability) and progression (chronicity) of pain and addiction, and studies could be focused on their influence, studies are also needed across populations, in which each comorbidity is considered as an independent variable. Maladaptive responses of the hypothalamic-pituitary-adrenal (HPA) axis arising through disruption of normal responses by chronic stressors, including chronic pain, may be important common mechanisms in pain chronicity, addiction, and other psychiatric comorbidities, especially depression (Blackburn-Munro and Blackburn-Munro, 2001; Kreek et al., 2004).
6. Identifying and quantifying addiction during opioid treatment of chronic pain
While there is a degree of certainty in diagnosing addiction during illicit drug use because of its characteristic progression from initiation through intermittent use or abuse to dependence, there is much less certainty about diagnosing iatrogenic opioid addiction. When patients are maintained on opioids for the treatment of pain, there is currently no satisfactory means of distinguishing true addiction from problematic behaviors caused by a variety of factors other than addiction. Unfortunately, advances in understanding the neurobiological foundation of addiction have not been matched by any improvement in physicians’ ability to recognize and diagnose the condition. There is no single diagnostic marker of addiction, no definitive change on brain imaging and as yet no genetic markers to provide a reliable prognosis of risk. The clinician must rely, therefore, on the observational criteria developed by various bodies of experts (WHO, 1992, 1998; DSM-IV, 1994; Savage et al., 2001), these being the product of years of debate and discussion (Table 1) (Savage et al., 2003). The uncertainties of addiction terminology, especially during the treatment of pain, contribute to the problem. When it comes to iatrogenic opioid addiction, the clinician is faced with even greater difficulty: the behaviors encountered do not resemble those outlined in the criteria for addiction to illicit drugs. Several authors have described problematic drug-seeking behaviors that could indicate, or a least herald, the presence of addiction in opioid-treated patients (Table 3) (Maruta, 1978; Khatami et al., 1979; Evans, 1981; Fishbain et al., 1992; Chabal et al., 1997; Weaver and Schnoll, 2002a; Passik and Kirsh, 2004). Yet these behaviors bear little relationship to the behaviors identified in the DSM-IV criteria. In fact, although the behaviors are often considered indicative of addiction, they have never formally been validated as such (Passik et al., 2002; Passik and Kirsh, 2003). Moreover, there are a number of possible explanations, apart from addiction, for the behaviors:
- They may result from psychological or physical dependence.
- They may result from a chaotic lifestyle.
- They may indicate a search for sympathy, understanding, meaning or a social context; or they may indicate a preoccupation with being unwell.
- They may be produced by inadequate treatment of pain (pseudoaddiction) (Weissman and Haddox, 1989).
- They may reflect a need for opioids to relieve a comorbid condition such as depression or anxiety (Webster and Webster, 2005).
One of the great difficulties of quantifying, recognizing, and treating iatrogenic opioid addiction is the subjective nature of the judgment on whether behaviors have crossed an ill-defined boundary between problematic opioid use and addiction. This judgment then becomes dependent on the reporting person’s experience, prejudices, and knowledge.
In view of these difficulties of definition, it is not surprising that estimated risks of iatrogenic opioid addiction have varied enormously between assessors and throughout the evolution of chronic opioid treatment of pain. During the 1980s, the beginning of the resurgence in popularity of opioid treatment of chronic pain, addiction rates were reportedly very low. A classic report (a letter) by Porter and Jick (1980) was taken out of context and often used to support low addiction rates; the report was of 0.03% addiction rates in hospitalized patients (Porter and Jick, 1980). More realistically, Portenoy and Foley, in a seminal paper describing opioid therapy for non-cancer pain (1986), reported rates of addiction of 5% (Portenoy and Foley, 1986). Rates of this order were widely accepted, despite the weak level of evidence (mostly anecdotal reports), probably forgetting that the experts reporting such successes were likely providing exceptionally careful and personalized care. As these authors themselves say: “_It must be recognized, therefore, that the efficacy of this therapy and its successful management may relate as much to the quality of the personal relationship between physician and patient as to the characteristics of the patient, drug or dosing regime_” (Portenoy and Foley, 1986). After a decade or more of acceptance that therapeutic opioid use was unlikely to result in addiction, the medical community began to question the supposed low rates of addiction because of a perceived increase in the number of problematic behaviors, and because of the documented recent substantial increase in prescription drug abuse (Crane and Lemanki, 2004). A systematic review published in 1992 reporting addiction rates of up to 18.9% (Fishbain et al., 1992) failed to penetrate the vast number of educational materials that were used during the 1990s to persuade the medical community that addiction was extremely rare during the treatment of pain. Reports overall provide addiction rates ranging from 2.8% (Cowan et al., 2003) to 50% (Saper et al., 2004), some of the discrepancies in findings clearly depending on the criteria used by the investigators to define addiction (Chabal et al., 1997; Fishbain et al., 1999; Joranson et al., 2000; Weaver and Schnoll, 2002a; Cowan et al., 2003; Manchikanti et al., 2003; Savage et al., 2003; Passik and Kirsh, 2004; Woolf and Hashmi, 2004; Zwart et al., 2004; Højsted and Sjøgren, 2006; Martell et al., 2007). For example, the reader can ascertain by looking at the list of aberrant behaviors listed in Table 4 that the behaviors listed by Chabal et al. (1997) producing a 27.6% rate of “prescription opiate abuse” do not clearly meet DSM-IV criteria for substance dependence (Table 1), and the 27.6% rate likely reflects a rate of problematic opioid use rather than of true addiction. Likewise, the high rate (50%) of “problem drug behavior” found by Saper et al. (2004) reflects specifically “dose violations, lost prescriptions, and multisourcing”, not necessarily addiction or substance dependence by DSM-IV criteria. In a rare study in which DSM-IV criteria actually are used to define aberrant drug behaviors in opioid-treated pain patients, 31% of the sample of patients with sickle-cell disease meet the criteria for substance dependence when pain-related symptoms are included in the assessment, but only 2% meet the criteria when the assessment is limited to non-pain-related symptoms (Elander et al., 2003). In other words, if symptoms that could be related to opioid-seeking for the relief of pain are discounted, markedly fewer patients meet the criteria for substance dependence. Overall, there remains considerable uncertainty about rates of iatrogenic opioid addiction, and this uncertainty is largely related to lack of consensus on definition and on the distinction between problematic opioid use and true addiction.
7. Incorporating addiction risk into pain treatment protocols
It has often been proposed that opioid addiction does not arise as a consequence of opioid treatment of pain. Pain is seen to act as a functional antagonist to opioids, and it has been suggested that significant pain therefore protects against addiction. In fact, this argument has been used to support the safe use of opioids for the treatment of severe acute, cancer and chronic pain (Kanner and Foley, 1981; Portenoy and Foley, 1986). Indeed, animal and human studies support the contention that opioid euphoria and reward are attenuated by pain (Zacny et al., 1996; Ozaki et al., 2002; Ozaki et al., 2003; Narita et al., 2005; Alford et al., 2006). However, in the light of clinical experience, and of the many reports describing problematic behaviors arising in patients treated with opioids for pain, it must be accepted that whatever protection pain provides, it is not enough to prevent problematic opioid use during opioid treatment of chronic pain.
7.1. Drug choice
It is known and accepted that drugs, drug formulations, and modes of administration with rapid onset and intense effect have increased potential for abuse (Farre and Cami, 1991; Mumford et al., 1995; Roset et al., 2001). There is evidence, also, that the pattern of drug administration affects abuse potential. In experimental studies, whereas intermittent morphine use, which mimics the intermittent use of heroin by addicts, enhances dynorphin and κ-opioid receptor gene expression (Wang et al., 1999; Kreek, 2001), steady-state opioid administration allows normalization on a molecular, cellular, and physiological level (Kreek, 2001). Methadone maintenance for the treatment of addiction was proposed on the basis that the steady-dose that could be achieved using this long-acting synthetic opioid would allow normalization, prevent withdrawal and craving, and block the euphoric effects of superimposed short-acting opioids (Dole et al., 1966). Later, the same principle was applied to the treatment of chronic pain: it was proposed that long-acting opioid preparations, because they could achieve a steady state, were less likely to produce euphoria and addiction than short-acting opioids. Long-acting opioids are now widely recommended as the primary opioid for the treatment of chronic and cancer pain, but one must begin to question whether this is the right choice for long-term treatment. Whereas physiological normalization seems desirable for treating and preventing addiction, it is not clear whether such normalization results in loss of analgesic efficacy over time or whether the development of analgesic tolerance is altered (Dyer et al., 1999; Mao, 2002; Ballantyne and Mao, 2003; Porreca et al., 2003; Wang et al., 2005). Balancing addiction risk against sustained analgesic efficacy when choosing an opioid regime will become an important future challenge.
Although it is beyond the scope of this article to describe drug regimes for the treatment of chronic pain and addiction, there are areas where chronic pain and addiction treatment overlap and should be discussed here. Methadone maintenance treatment has an established record of success for the treatment of addiction (Dole, 1994; Brecher, 2006) and methadone is also used widely to treat pain. Buprenorphine, a partial μ-agonist, is an alternative for maintenance treatment of addiction, and has recently been approved in the United States for clinic and office-based treatment of addiction (in large part to avoid the regulatory onus and stigma of methadone) (Fiellin and O’Connor, 2002; Fudala et al., 2003; Krantz and Mehler, 2004). Buprenorphine, like methadone, has an established record of utility for the treatment of pain, largely from the European experience, since the drug has only been popularized more recently in the U.S., and currently can only be used there off-label for pain. Both of these drugs provide protection from withdrawal for approximately 24–48h, while their analgesic effects last only 4–8h, so that a major difference between pain and addiction treatment using these agents is that dosing is more frequent for pain (Fishman et al., 2002; Walsh and Eissenberg, 2003; Johnson et al., 2005). Buprenorphine has certain limitations in terms of pain treatment. While it is useful for the treatment of mild to moderate pain, its partial agonism results in a ceiling effect which may limit its utility in severe pain. It also has prolonged receptor occupancy and is difficult to displace from the μ-opioid receptor. Therefore it compromises the ability of added potent agonists such as morphine and fentanyl to provide greater analgesia when needed. While this does not seem to be a problem when standard opioids are used for breakthrough pain during chronic buprenorphine treatment for pain or addiction (Mercadante et al., 2006), it can be a problem when severe acute pain (e.g. surgery or trauma) intervenes (Alford et al., 2006). Because it may not be possible to overcome the partial agonist effect of buprenorphine, it is recommended that chronic buprenorphine treatment be discontinued or substituted for a week before surgery. Despite this limitation, buprenorphine may prove the best choice from the existing armamentarium for the treatment of pain in patients known to be addicted or at risk, especially when it appears that the potent opioids do not offer much more than mild opioids, at least during the early treatment of chronic pain (Furlan et al., 2006).
7.2. Preventing craving
Drug addiction arises from the coupling of learned behaviors associated with procurement and repeated drug exposure (Robinson and Berridge, 1993; Nestler, 1996, 2001; O’Brien et al., 1998; Self and Nestler, 1998; Sell et al., 1999; Shaham et al., 2000; Wise, 2000; Hyman and Malenka, 2001; Narita et al., 2001). Pain patients are in some senses protected. Since stable opioid-treated pain patients do not procure drug or need to procure, the motivational component of addiction may be absent (Grinspoon, 1998). Moreover, steady-state administration, as achieved in recommended pain treatment regimes (Haddox et al., 1997; West et al., 1998; The College of Physicians and Surgeons of Ontario, 2000; Collett, 2001; Atluri et al., 2003; Jovey et al., 2003; Kalso et al., 2003; The British Pain Society, 2005; VA/DoD, 2006), may be protective by preventing withdrawal and craving (Dole et al., 1966; Wang et al., 1999; Kreek, 2001). But since time and repetition appear to be of the essence, it follows that when treating chronic pain with opioids, physicians might be advised to watch carefully for problematic opioid-seeking behavior, and respond definitively should it arise. This means carefully monitoring (regular follow-up and screening), and when problematic behavior does arise, giving careful consideration to whether to wean, intensify follow-up, add psychotherapy or addiction treatment, or involve adjunctive facilities.
7.3. Screening instruments
While the need for careful, structured treatment is amply supported, the methods by which patients should be selected for treatment or for termination of treatment are not well defined. Probably the most difficult question is whether certain patients should be excluded from opioid pain treatment. Exclusion produces a range of difficult ethical dilemmas. It is generally assumed that known substance abusers carry the greatest risk of addiction during opioid treatment of pain. Yet evidence to date suggests that even these high-risk patients do not necessarily present an increased risk during pain treatment (Kennedy and Crowley, 1990; Dunbar and Katz, 1996; Weaver and Schnoll, 2002b; Collins and Streltzer, 2003; Newman, 2004). This may be because the drug itself constitutes only one component of complex circumstances involving the psychosocial situation of both the individual patients and their community. Thus, provided the treatment is “medicalized”, and the circumstances associated with abuse are avoided, it is possible that the drug itself will not reinstate addiction.
Several research groups are now developing screening instruments that could be used to stratify risk, identify deterioration in life measures and record important outcomes in a standardized manner (Chabal et al., 1997; Compton et al., 1998; Adams et al., 2004; Butler et al., 2004; Passik et al., 2004; Belgrade et al., 2006). This effort aims to screen for risk so that patients can be identified who are not suitable for therapy, or who warrant special vigilance and monitoring. There is also a recognized need to produce standardized entry and outcomes data to be used in multicenter studies to validate the screening instruments as predictors of risk. Screening tools that have been developed for use in addicts are used to identify craving (e.g. the CAGE questionnaire for alcoholics), but have not been found to be good predictors of aberrant behavior in opioid-treated pain patients (Butler et al., 2004; Webster and Webster, 2005). The screening tools in development for use during opioid pain treatment are based on the knowledge, derived through genetic and epidemiological studies, that psychological comorbidities and a personal or family history of drug abuse are strong associates of addiction. The latest, developed by Belgrade et al. (2006), takes a new, intriguing and conceptually attractive approach in that it incorporates a measure of the likelihood of success (improved pain) as well as of risk. A validated screening instrument could have enormous benefit in that it could provide physicians with an effective means of selecting patients for treatment, and allow patients to be selected on a more rational basis. It remains to be determined whether screening instruments will be more useful for predicting risk or for identifying problems once they arise, or indeed, what their exact role will be in minimizing iatrogenic addiction risk. A validated screening instrument may also be useful for persuading patients not at risk, as well as those involved in their care, that the risk for them of addiction is negligible.
7.4. Recommended treatment protocols
As clinical experience of long-term opioid use increases, it has become evident that a careful and structured treatment approach is optimal for maintaining efficacy and reducing complications of chronic opioid therapy. Several authoritative groups have developed guidelines for opioid treatment of chronic pain and these consistently recommend comprehensive follow-up, including adjunctive interventions where necessary, regular prescription pick-up, appropriate screening for use and abuse, and a limitation on the number of physicians and pharmacists providing treatment (Portenoy, 1996; Haddox et al., 1997; West et al., 1998; The College of Physicians and Surgeons of Ontario, 2000; Collett, 2001; Atluri et al., 2003; Ballantyne and Mao, 2003; Jovey et al., 2003; Kalso et al., 2003; The British Pain Society, 2005; VA/DoD, 2006). The principles of careful, structured opioid maintenance for pain are outlined in Table 5. It is worth noting that the principles of opioid maintenance for the treatment of pain are similar to those for the treatment of addiction (SAMHSA, 2000; Fiellin and O’Connor, 2002), and that maintenance treatment for opioid addiction has been used since the early 1970s with a good record of success in terms of maintaining general and social function and reducing recidivism (Brecher, 2006).
Principles of chronic opioid maintenance for pain
8. Conclusions
There are many reasons that opioid therapy for chronic pain was suddenly popularized in industrial nations during the last two decades of the twentieth century, these related to changes in medical practice, and associated changes in policies and values. Never before had opioids been mobilized to treat chronic pain on such a large scale. Early in this process, it is fair to say that we were “flying blind” (von Korff and Deyo, 2004). Assumptions were made on the basis of the more extensive experience in treating acute and terminal cancer pain, including the belief that addiction would be rare. Now, even though iatrogenic opioid addiction rates are still largely unknown, it is generally recognized that problematic opioid seeking and addiction arise often enough during chronic treatment to be of considerable concern.
As experience of treating chronic pain with opioids grew, it became clear that there are difficulties with applying the definitions and criteria developed for addiction in illicit drug users to pain patients (Table 1) (WHO, 1992, 1998; DSM-IV, 1994; Savage et al., 2001). Opioid-treated pain patients often develop overt physical dependence and analgesic tolerance with no behavioral change, therefore these must be considered separate phenomena from addiction. New definitions specific to pain patients account for this, but are in a sense misleading because unlike standard definitions that recognize the integrated nature of addiction processes, they place a conceptual separation between tolerance, dependence and the behavioral component (Table 2) (Heit, 2003). It is becoming accepted, knowing that continued drug use results in integrated biological adaptations, that the more subtle manifestations of these adaptations – psychological dependence, resulting in emotional withdrawal (anhedonia and dysphoria) and motivational withdrawal (short-term craving) – are also important and distinct from addiction (a state of learned drug seeking) (Koob and Le Moal, 2001; Cami and Farre, 2003; Hyman et al., 2006). Opioid-treated pain patients must undergo the same initial physiological adaptations as illicit users. Yet in pain patients, the clinical picture of progression from use to problematic use to addiction differs markedly from that in illicit users. Continued use in an illicit setting often progresses rapidly to addiction, to the extent that dependence and addiction are indistinguishable, and this rapid progression is likely accounted for by the circumstances and motivations associated with illicit use. In pain patients, we see a different picture. If the progression from simple dependence through problematic use to addiction occurs, it is more subtle and insidious, so that addiction emerges as a distinct and separate syndrome, but is less obvious and much more difficult to identify.
Addiction research lends much insight into why some opioid-treated pain patients become problematic or addicted while others do not. Genetic epidemiological studies make it clear that addiction risk is strongly heritable. Genetically-influenced personality traits are likely to play a role. Clinical, molecular, genetic and animal model studies are identifying physiological, cellular, and molecular processes that help explain why individuals differ in their responses to addictive drugs: why some experience euphoria, and others do not; why some find withdrawal symptoms (whether subtle or intense) intolerable, while others do not. Pharmacogenetic studies are beginning to reveal why individuals respond differently to different drugs in their analgesic and hedonic responses. Other studies confirm that drugs, drug formulations and administration modes with rapid onset are more addictive than those with gradual onset. Additional studies confirm the importance of environment and circumstance in the development of addiction, and the powerful role of motivation and the need to procure in the development of addiction as a learned and enduring state. Studies also suggest that genetic and circumstantial factors lead not only directly to addiction, but also to psychiatric morbidity (depression, anxiety and chronic pain syndrome) that in turn makes individuals vulnerable to addiction (Figs. 2 and 3) (Hyman, 1997; Kreek, 2001).
We are already armed, then, with much information that can and does help us provide opioid treatment of pain in a way that minimizes addiction risk. Structured treatment regimes with careful follow-up are thought to be helpful because they allow problematic use to be identified and treated before it escalates into addiction, and this may be critical. Appropriate drug and drug regime choices are thought to reduce risk by reducing swings in emotional and somatic symptoms. Yet even if these measures are employed, destructive problematic use and iatrogenic opioid addiction still occur. Are there some patients whose risk is so high that they should not be taken on unless the treating physician is ready and equipped to provide the intense level of intervention that will likely be needed?
Two broad areas for future research seem necessary: (1) find a better way of identifying risk and deterioration and of relating these to eventual outcome, and (2) find drugs or drug combinations that minimize tolerance and dependence thereby preserving analgesia and reducing addiction risk.
It is a considerable burden for physicians to be expected to select patients for opioid pain treatment, or to terminate the treatment when it appears unsuccessful when there remains considerable uncertainty about the factors related to success or failure. Good, simple screening instruments are needed, and these instruments need to be validated in outcome studies so that some certainty about how entry profiles and subsequent behaviors relate to eventual outcome can guide treatment choices.
A new clinical problem has emerged since chronic opioid pain therapy became popularized during the last two decades – that of opioid analgesic refractoriness (Mao et al., 1994, 1995; Mao, 2002; Angst and Clark, 2006; Chu et al., 2006; Wilder-Smith and Arendt-Nielsen, 2006). This has not been the subject of the present review, but it may become an important factor as chronic opioid pain therapy continues to be appraised. Since opioids and opioid combination therapies with lowered potential for dependence, tolerance and addiction may also provide better and more sustained analgesia, approaches that target the neuroadaptations that underlie tolerance and dependence could have dual benefit (Shippenberg et al., 1998; Wang et al., 1999; Chefer et al., 2005; He and Whistler, 2005; Zachariou et al., 2006). Opioid combinations using ultra-low dose antagonists suggest a potentially useful approach (Cruciani et al., 2003; Chindalore et al., 2005; Olmstead and Burns, 2005; Wang et al., 2005). Finally, one must ask whether it is worth risking functional deterioration, problematic and compulsive use or addiction if analgesic efficacy is not sustained, and whether manipulations of the treatment can help maintain analgesic efficacy to redress the balance.
Understanding addiction’s multidimensional nature, and the many factors that can influence it, suggests that a careful, selective and supportive treatment approach is the best way to prevent iatrogenic opioid addiction. Should addiction arise, the best way to treat it would seem to be to continue a structured treatment regime with extra support from addiction specialists. This does not necessarily mean continuing opioid treatment, but it does mean continuing careful treatment of addiction and pain, and not abandoning the patients who seek help in the first place because their suffering is unbearable.
Acknowledgments
The authors thank Steven E. Hyman, Harvard Medical School, for his helpful review and comments on the neurobiology section of this paper. Stefan in the Laboratory of the Biology of Addictive Diseases at The Rockefeller University provided expert advice on Fig. 1. This work was supported, in part, by research grants from the Sigrid Juselius Foundation, The Academy of Finland, and from the National Institutes of Health-National Institute on Drug Abuse (P60-DA05130).
References
CASA April 2000, Report: Missed opportunity, national survey of primary care physicians on patients with substance abuse. National Center on Addiction and Substance Abuse, 633 3rd Ave, 19th Floor Columbia University, NY, NY 10017. Available from: www.casacolumbia.org.
The ICD-10 classification of mental and behavioral disorders: clinical descriptions and diagnostic guidelines. Geneva, Switzerland: World Health Organization, WHO; 1992.
American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994.
WHO 30th report. WHO expert committee on drug dependence. Geneva, Switzerland: WHO; 1998.
SAMHSA. Waiver authority for physicians who dispense or prescribe certain narcotic drugs for maintenance treatment or detoxification treatment. Rockville, Md.: Center for Substance Abuse Treatment. H.R. 4365: 122-7. Available from: http://www.samhsa.gov/centers/csat/csat.html); 2000.
DHHS, SAMHSA: national survey on drug use and health, Available from: <www.oas.samha.gov.2003>.
Recommendations for the appropriate use of opioids for persistent non-cancer pain. A consensus statement prepared on behalf of the British Pain Society, the Royal College of Anaesthetists, the Royal College of General Practitioners and the Royal College of Psychiatrists. The British Pain Society, London ISBN 0-9546703-5-3 2005.
VA/DoD clinical practice guideline for the management of opioid therapy for chronic pain. Available from: http://www.oqp.med.va.gov?cpg/cpg.htm Accessed 10/24/2006; 2006.
Adams L, Gatchel R, Robinson RC, Polatin P, Gajraj N, Deschner M, et al. Development of a self-report screening instrument for assessing potential opioid medication misuse in chronic pain patients. J Pain Symptom Manage. 2004;27:440-459.
Alford DP, Compton P, Samet JH. Acute pain management for patients receiving maintenance methadone or buprenorphine therapy. Ann Intern Med. 2006;144:127-134.
Angst MS, Clark JD. Opioid-induced hyperalgesia: a qualitative systematic review. Anesthesiology. 2006;104:570-587.
Atluri S, Boswell MV, Hansen HC, Trescot AM, Singh V, Jordan AE. Guidelines for the use of controlled substances in the management of chronic pain. Pain Physician. 2003;6:233-257.
Bailey CP, Connor M. Opioids: cellular mechanisms of tolerance and physical dependence. Curr Opin Pharmacol. 2005;5:60-68.
Ballantyne J, Mao J. Opioid therapy for chronic pain. N Engl J Med. 2003;349:1943-1953.
Banks S, Kerns R. Explaining high rates of depression in chronic pain: a diathesis-stress framework. Psychol Bull. 1996;119:95-110.
Belgrade MJ, Schamber CD, Lindgren BR. The DIRE score: predicting outcomes of opioid prescribing for chronic pain. J Pain. 2006;7:671-681.
Berke J, Paletzki R, Aronson G, Hyman S, Gerfen C. A complex program of striatal gene expression induced by dopaminergic stimulation. J Neurosci. 1998;18:5301-5310.
Bierut LJ, Dinwiddie S, Begleiter H, Crowe R, Hesselbrock V, Nurnberger J, et al. Familial transmission of substance dependence: alcohol, marijuana, cocaine, and habitual smoking: a report from the Collaborative Study on the Genetics of Alcoholism. Arch Gen Psychiatry. 1998;55:982-988.
Blackburn-Munro G, Blackburn-Munro R. Chronic pain, chronic stress and depression: coincidence or consequence? J Neuroendocrinol. 2001;13:1009-1023.
Blazer D, Kessler R, McGonagle K, Swartz M. The prevalence of major depression in a national community sample: the national comorbidity survey. Am J Psychiatry. 1994;151:979-986.
Bohn LM, Gainetdinov R, Lin F, Lefkowitz R, Caron M. Mu-opioid receptor desensitization by beta-arrestin-2 determines morphine tolerance but not dependence. Nature. 2000;408:720-723.
Bonci A, Williams J. Increased probability of GABA release during withdrawal from morphine. J Neurosci. 1997;17:796-803.
Bond C, LaForge K, Tian M, Melia D, Zhang S, Borg L, et al. Single-nucleotide polymorphism in the human mu opioid receptor gene alters beta-endorphin binding and activity: possible implications for opiate addiction. Proc Natl Acad Sci USA. 1998;95:9608-9613.
Brecher E, Editors of Consumer Reports Magazine. How well does methadone mainenance work? In: The consumers union report on licit and illicit drugs. Schaffer Library of Drug Policy. Available from: http://www.druglibrary.org/schaffer/Library/studies/cu/cument/htm. Accessed 10/12/2006; 2006.
Brown RL, Patterson JJ, Rounds LA, Papasouliotis O. Substance abuse among patients with chronic back pain. J Fam Practice. 1996;43:152-160.
Bruera E, Brenneis C, Michaud M, Bacovsky R, Chadwick S, Emeno A, et al. Use of the subcutaneous route for the administration of narcotics in patients with cancer pain. Cancer. 1988;62:407-411.
Butler S, Budman S, Fernandez K, Jamison R. Validation of a screener and opioid assessment measure for patients with chronic pain. Pain. 2004;112:65-75.
Cadoret R, Troughton E, O’Gorman T, Heywood E. An adoption study of genetic and environmental factors in drug abuse. Arch Gen Psychiatry. 1986;43:1131-1136.
Cami J, Farre M. Drug addiction. N Engl J Med. 2003;349:975-986.
Carlezon W, Duman R, Nestler EJ. The many faces of CREB. Trends Neurosci. 2005;28:436-445.
Cesselin F. Opioid and anti-opioid peptides. Fundam Clin Pharmacol. 1995;9:409-433.
Chabal C, Erjavec M, Jacobson L, Mariano A, Chanev E. Prescription opiate abuse in chronic pain patients: clinical criteria, incidence and predictors. Clin J Pain. 1997;13:150-155.
Chefer V, Czyzyk T, Bolan E, Moron J, Pintar JE, Shippenberg TS. Endogenous kappa-opioid receptor systems regulate mesoaccumbal dopamine dynamics and vulnerability to cocaine. J Neurosci. 2005;25:5029-5037.
Childress A, McLellan A, O’Brien C. Conditioned responses in a methadone population. J Subst Abuse Treat. 1986;3:173-179.
Chindalore VL, Craven R, Yu K, Butera P, Burns L, Friedmann N. Adding ultralow-dose naltrexone to oxycodone enhances and prolongs analgesia: a randomized, controlled trial of Oxytrex. J Pain. 2005;6:392-399.
Chu LF, Clark D, Angst M. Opioid tolerance and hyperalgesia in chronic pain patients after one month of oral morphine therapy: a preliminary prospective study. J Pain. 2006;7:43-48.
Cloninger CR, Bohman M, Sigvardsson S. Inheritance of alcohol abuse. Cross-fostering analysis of adopted men. Arch Gen Psychiatry. 1981;38:861-868.
Collett B. Opioid tolerance: the clinical perspective. Br J Anaesth. 1998;81:58-68.
Collett BJ. Chronic opioid therapy for non-cancer pain. Br J Anaesth. 2001;87:133-144.
Collins E, Streltzer J. Should opioid analgesics be used in the management of chronic pain in opiate addicts? Am J Addict. 2003;12:93-100.
Compton P, Darakjian J, Miotto K. Screening for addiction in patients with chronic pain with “problematic” substance use: evaluation of a pilot assessment tool. J Pain Symptom Manage. 1998;16:355-363.
Cowan D, Wilson-Barnett J, Griffiths P, Allan L. A survey of chronic noncancer pain patients prescribed opioid analgesics. Pain Med. 2003;4:340-351.
Crane E, Lemanki N. The DAWN report: narcotic analgesics, 2002 update. Office of Applied studies, Substance Abuse and Mental Health Services Administration (SAMHSA); 2004.
Cruciani R, Lussier D, Miller-Saultz D, Arbuck D. Ultra-low dose oral naltrexone decreases side effects and potentiates the effect of methadone. J Pain Symptom Manage. 2003;84:491-494.
de Leon-Casasola O, Myers D, Donaparthi S, Bacon D, Peppriell J, Rempel J, et al. A comparison of postoperative epidural analgesia between patients with chronic cancer taking high doses of oral opioids versus opioid-naive patients. Anesth Analg. 1993;76:302-307.
Dersh J, Polatin P, Gatchell R. Chronic pain and psychopathology: research finding and theoretical considerations. Psychom Med. 2002;64:773-786.
Dole V. What we have learned from three decades of methadone maintenance treatment. Drug & Alcohol Rev. 1994;13:3-4.
Dole V, Nyswander M, Kreek M. Narcotic blockade. Arch Int Med. 1966;188:304-309.
Dunbar S, Katz N. Chronic opioid therapy for nonmalignant pain in patients with a history of substance abuse: report of 20 cases. J Pain Symptom Manage. 1996;11:163-167.
Dyer K, Foster D, White J, Somogyi A, Menelaou A, Bochner F. Steady-state pharmacokinetics and pharmacodynamics in methadone maintenance patients: comparison of those who do and do not experience withdrawal and concentration effect relationships. Clin Pharm Ther. 1999;65:685-693.
Edenberg H, Dick D, Xuei X, Tian H, Almasy L, Bauer L, et al. Variations in GABRA2, encoding the alpha 2 subunit of the GABA(A) receptor, are associated with alcohol dependence and with brain oscillations. Am J Hum Genet. 2004;74:705-714.
Elander J, Lusher J, Bevan D, Telfer P. Pain management and symptoms of substance dependence among patients with sickle cell disease. Soc Sci Med. 2003;57:1683-1696.
Edlund MJ, Steffick D, Hudson T, Harris KM, Sullivan M. Risk factors for clinically recognized opioid abuse and dependence among Veterans using opioids for chronic non-cancer pain. Pain. 2007;129:355-362.
Evans PJD. Narcotic addiction in patients with chronic pain. Anesthesia. 1981;36:597-602.
Farre M, Cami J. Pharmacokinetic considerations in abuse liability evaluation. Br J Addict. 1991;86:1601-1606.
Fernandes L, Kilicarslan T, Kaplan H, Tyndale R, Sellers E, Romach M. Treatment of codeine dependence with inhibitors of cytochrome P450 2D6. J Clin Psychopharmacol. 2002;22:326-329.
Fiellin DA, O’Connor PG. Office-based treatment of opioid-dependent patients. N Engl J Med. 2002;347:817-823.
Fine P. Opioid insights: opioid-induced hyperalgesia and opioid rotation. J Pain Palliat Care Pharmacother. 2004;18:75-79.
Fishbain D, Cutler R, Rosomoff H, Rosomoff R. Chronic pain-associated depression: antecedent or consequence of chronic pain? A review. Clin J Pain. 1997;113:116-137.
Fishbain DA, Cutler RB, Rosomoff HL, Rosomoff RS. Validity of self-reported drug use in chronic pain patients. Clin J Pain. 1999;15:184-191.
Fishbain DA, Goldberg M, Labbe E, Steele R, Rosomoff HL. Compensation and non-compensation chronic pain patients compared for DSM-III operational diagnoses. Pain. 1988;32:197-206.
Fishbain D, Goldberg M, Meagher B, Steele R, Rosomoff H. Male and female chronic pain patients categorized by DSM-III psychiatric diagnostic criteria. Pain. 1986;26:181-197.
Fishbain D, Rosomoff H, Rosomoff R. Drug abuse, dependence and addiction in chronic pain patients. Clin J Pain. 1992;8:77-85.
Fishman SM, Wilsey B, Mahajan G, Molina P. Methadone reincarnated: novel clinical applications with related concerns. Pain Med. 2002;3:339-348.
Fudala P, Bridge T, Herbert S, Williford W, Chiang C, Jones K, et al. Office-based treatment of opiate addiction with a sublingual-tablet formulation of buprenorphine and naloxone. N Engl J Med. 2003;349:949-958.
Furlan AD, Sandoval JA, Mailis-Gagnon A, Tunks E. Opioid for chronic non cancer pain: a meta-analysis of effectiveness and side effects. Can Med Assoc J. 2006;174:589-594.
Gardner E., 1999. The neurobiology and genetics of addiction: implications of the reward deficiency syndrome for therapeutic strategies in chemical dependency. Addiction: entries and exits, Russell Sage Foundation, New York, p. 57–119.
Gardner E. Brain-reward mechanisms. In: Lowinson JH, Ruiz P, Milman RB, Langrod GH, editors. Substance abuse. A comprehensive textbook. Philadelphia: Lippincott Lilliams & Wilkins; 2005.
Gatchel R, Garofalo J, Ellis E, Holt C. Major psychological disorders in acute and chronic TMD: an initial examination. J Am Dent Assoc. 1996;127:1365-1374.
Gatchel R, Polatin P, Mayer T. The dominant role of psychosocial risk factors in the development of chronic low back pain disability. Spine. 1995;20:2702-2709.
Gelernter J, Panhuysen C, Weiss R, Brady K, Hesselbrock V, Rounsaville B, et al. Genomewide linkage scan for cocaine dependence and related traits: significant linkages for a cocaine-related trait and cocaine-induced paranoia. Am J Med Genet B Neuropsychiatr Genet. 2005;136:45-52.
Gelernter J, Penhuysen C, Wilcox M, Hesselbrock V, Rounsaville B, Poling J, et al. Genomewide linkage scan for opioid dependence and related traits. Am J Hum Genet. 2006;78:759-769.
Grinspoon L. Addiction and the brain – Part I. Harvard Mental Health Lett. 1998;14:1-3.
Grisel J, Watkins L, Maier S. Associative and non-associative mechanisms of morphine analgesic tolerance are neurochemically distinct in the rat spinal cord. Psychopharmacology. 1996;128:248-255.
Haddox JD, Joranson D, Angarola RT, Brady A, Carr DB, Blonskey R, et al. The use of opioids for the treatment of chronic pain. A consensus statement from the American academy of pain medicine and the American pain society publications: American Academy of Pain Medicine and American Pain Society; 1997.
He L, Whistler J. An opiate cocktail that reduces morphine tolerance and dependence. Curr Biol. 2005;15:1028-1033.
Heit HA. Addiction, physical dependence, and tolerance: precise definitions to help clinicians evaluate and treat chronic pain patients. J Pain & Palliat Care Pharmacother. 2003;17:15-29.
Højsted J, Sjøgren P. Addiction to opioids in chronic pain patients: a literature review. Eur J Pain 2006; Epub ahead of print.
Hope B, Nye H, Kelz M, Self D, Iadarola M, Nakabeppu Y, et al. Induction of a long-lasting AP-1 complex composed of altered Fos-like proteins in brain by chronic cocaine and other chronic treatments. Neuron. 1994;13:1235-1244.
Hyman S., 1997. Dispelling the myths about addiction, Institute of Medicine. National Academy of Sciences Press, Washington, 44-6.
Hyman S, Malenka R. Addiction and the brain: the neurobiology of compulsion and its persistence. Nat Rev Neurosci. 2001;2:695-703.
Hyman SE, Malenka RC, Nestler EJ. Neural mechanisms of addiction: the role of reward-related learning and memory. Annu Rev Neurosci. 2006;29:565-598.
Inciardi J, Surratt H, Kurtz S, Burke J. The diversion of prescription drugs by health care workers in Cincinnati, Ohio. Subst Use Misuse. 2006;41:255-264.
Jacobsen L, Mariano A. General considerations of chronic pain. Loeser JD, Butler SH, Chapman SR, editors. Bonica’s management of pain. 3rd ed. Baltimore, MD: Lippincott Williams & Wilkins; 2001: pp. 241-254.
Jage J. Opioid tolerance and dependence – do they matter? Eur J Pain. 2005;9:157-162.
Johnson R, Fudala P, Payne R. Buprenorphine: considerations for pain management. J Pain Symptom Manage. 2005;29:297-326.
Johnson S, North R. Opioids excite dopamine neurons by hyperpolarization of local interneurons. J Neurosci. 1992;12:483-488.
Joranson DE, Gilson AM. Wanted: a public health approach to prescription opioid abuse and diversion. Pharmacoepidemiol Drug Saf. 2006;15:632-634.
Joranson D, Gilson A. Drug crime is a source of abused pain medications in the United States. J Pain Symptom Manage. 2005;30:299-301.
Joranson D, Ryan K, Givson A, Dahl J. Trends in medical use and abuse of opioid analgesics. JAMA. 2000;283:1710-1714.
Jovey R, Ennis J, Gardner-Nix J, Goldman B, Hays H, Lynch M, et al. Use of opioid analgesics for the treatment of chronic noncancer pain – a consensus statement and guidelines from the Canadian Pain Society, 2002. Pain Res Manag. 2003;8:3A-28A.
Kalso E, Allan L, Dellemijn P, Faura C, Ilias W, Jensen T, et al. Recommendations for using opioids in chronic non-cancer pain. Eur J Pain. 2003;7:381-386.
Kanner R, Foley K. Patterns of narcotic drug use in a cancer pain clinic. Ann NY Acad Sci. 1981;362:161-172.
Kathiramalainathan K, Kaplan HL, Romach MK, Busto VE, Li NY, Sawe J, et al. Inhibition of cytochrome P450 2D6 modified codeine abuse liability. J Clin Psychopharmacol. 2000;20:435-444.
Katon W, Egan K, Miller D. Chronic pain: lifetime psychiatric diagnoses and family history. Am J Psychiatry. 1985;142:1156-1160.
Kendler K, Jacobson K, Prescott C, Neale M. Specificity of genetic and environmental risk factors for use and abuse/dependence of cannabis, cocaine, hallucinogens, sedatives, stimulants, and opiates in male twins. Am J Psychiatry. 2003;160:687-695.
Kennedy J, Crowley T. Chronic pain and substance abuse: a pilot study of opioid maintenance. J Subst Abuse Treat. 1990;7:233-238.
Khatami M, Woody G, O’Brien C. Chronic pain and narcotic addiction: a multitherapeutic approach – a pilot study. Compr Psychiatry. 1979;20:55-60.
Kieffer B, Gavériaux-Ruff C. Exploring the opioid system by gene knockout. Prog Neurobiol. 2002;66:285-306.
Kinney R, Gatchel R, Polatin P, Fogarty W, Mayer T. Prevalence of psychopathology in acute and chronic low back pain patients. J Occup Rehabil. 1993;3:85-103.
Klepstad P, Rakvåg T, Kaasa S, Holthe M, Dale O, Borchgrevink P, et al. The 118 A > G polymorphism in the human μ-opioid receptor gene may increase morphine requirements in patients with pain caused by malignant disease. Acta Anaesthesiol Scand. 2004;48:1232-1239.
Koob G, Le Moal M. Drug abuse: hedonic homeostatic dysregulation. Science. 1997;278:52-58.
Koob G, Le Moal M. Drug addiction, dysregulation of reward, and allostasis. Neuropharmacology. 2001;24:97-129.
Koob G, Maldonado R, Stinus L. Neural substrates of opiate withdrawal. Trends Neurosci. 1992;15:186-191.
Krantz M, Mehler P. Treating opioid dependence. Growing implications for primary care. Arch Intern Med. 2004;164:277-288.
Kreek MJ. Drug addictions: molecular and cellular endpoints. Ann NY Acad Sci. 2001;937:27-49.
Kreek MJ, Nielsen DA, Butelman ER, LaForge KS. Genetic influences on impulsivity, risk taking, stress responsivity and vulnerability to drug abuse and addiction. Nat Neurosci. 2005;8:1450-1457.
Kreek MJ, Nielsen DA, LaForge KS. Genes associated with addiction: alcoholism, opiate, and cocaine addiction. Neuromolecular Med. 2004;5:85-108.
Kreek M, LaForge K, Butelman E. Pharmacotherapy of addictions. Nat Rev Drug Discov. 2002;1:710-726.
LaForge K S, Yuferov V, Kreek MJ. Opioid receptor and peptide gene polymorphisms: potential implications for addictions. Eur J Pharmacol. 2000;410:249-268.
Levin F, Kleber H. Attention deficit hyperactivity disorder and substance abuse: relationships and implications for treatment. Harv Rev Psychiatry. 1995;2:246-258.
Lötsch J, Geisslinger G. Are mu-opioid receptor polymorphisms important for clinical opioid therapy? Trends Mol Med. 2005;11:82-89.
Lötsch J, Geisslinger G. Relevance of frequent mu-opioid receptor polymorphisms for opioid activity in healthy volunteers. Pharmacogenomics J. 2006;6:200-210.
Lötsch J, Skarke C, Liefhold J, Geisslinger G. Genetic predictors of the clinical response to opioid analgesics: clinical utility and future perspectives. Clin Pharmacokinet. 2004;43:983-1013.
Lu L, Shepard J, Scott Hall F, Shaham Y. Effect of environmental stressors on opiate and psychostimulant reinforcement, reinstatement and discrimination in rats: a review. Neurosci Biobehav Rev. 2003;27:457-491.
Magni G, Caldieron C, Rigatti-Luchini S, Merskey H. Chronic musculoskeletal pain and depressive symptoms in the general population. An analysis of the 1st National Health and Nutrition Examination Survey data. Pain. 1990;43:299-307.
Manchikanti L, Pampati V, Damron K, Beyer C, Barnhill R, Fellows B. Prevalence of prescription drug abuse and dependency in patients with chronic pain in western Kentucky. J Kentucky Med Assoc. 2003;101:511-517.
Mao J. Opioid induced abnormal pain sensitivity: implications in clinical opioid therapy. Pain. 2002;100:213-217.
Mao J, Price DD, Mayer DJ. Mechanisms of hyperalgesia and opiate tolerance: a current view of their possible interactions. Pain. 1995;62:259-274.
Mao J, Price D, Mayer D. Thermal hyperalgesia in association with the development of morphine tolerance in rats: roles of excitatory amino acid receptors and protein kinase C. J Neurosci. 1994;14:2301-2312.
Mao J, Sung B, Ji R, Lim G. Chronic morphine induces down regulation of spinal glutamate transporters: implications in morphine tolerance and abnormal pain sensitivity. J Neurosci. 2002;22:8312-8323.
Martell BA, O’Connor PG, Kerns RD, Becker WC, Morales KH, Kosten TR, et al. Systematic review: opioid treatment for chronic back pain: prevalence, efficacy, and association with addiction. Ann Intern Med. 2007;146:116-127.
Martin S, Gremwood P, Morris R. Synaptic plasticity and memory: an evaluation of the hypothesis. Annu Rev Neurosci. 2000;23:649-711.
Maruta T. Prescription drug-induced organic brain syndrome. Am J Psychiat. 1978;135:376-377.
McQuay H. Opioids in pain management. Lancet. 1999;353:2229-2232.
McWilliams L, Goodwin R, Cox B. Depression and anxiety associated with three pain conditions: results from a nationally representative sample. Pain. 2004;111:77-83.
Mercadante S, Bruera E. Opioid switching: a systematic and critical review. Cancer Treat Rev. 2006;32:304-315.
Mercadante S, Villari P, Ferrera P, Porzio G, Aielli F, Verna L, et al. Safety and effectiveness of intravenous morphine for episodic breakthrough pain in patients receiving transdermal buprenorphine. J Pain Symptom Manage. 2006;32:175-179.
Mitchell J, Basbaum A, Fields H. A locus and mechanism of action for associative morphine tolerance. Nat Neurosci. 2000;3:47-53.
Mitra S, Sinatra R. Perioperative management of acute pain in the opioid-dependent patient. Anesthesiology. 2004;101:212-227.
Morris J, Friston K, Dolan R. Neural responses to salient visual stimuli. Proc R Soc Lond B Biol Sci. 1997;264:769-775.
Mumford G, Evans S, Fleishaker J, Griffiths R. Alprazolam absorption kinetics affects abuse liability. Clin Pharmacol Ther. 1995;57:356-365.
Narita M, Funada M, Suzuki T. Regulations of opioid dependence by opioid receptor types. Pharmacol Ther. 2001;89:1-15.
Narita M, Kishimoto Y, Ise Y, Yajima Y, Misawa K, Suzuki T. Direct evidence for the involvement of the mesolimbic kappa-opioid system in the morphine-induced rewarding effect under an inflammatory pain-like state. Neuropsychopharmacology. 2005;30:111-118.
Nestler EJ. Historical review: molecular and cellular mechanisms of opiate and cocaine addiction. Trends Pharmacol Sci. 2004a;25:210-218.
Nestler EJ, Aghajanian GK. Molecular and cellular basis of addiction. Science. 1997;278:58-63.
Nestler E. Under siege: the brain on opiates. Neuron. 1996;16:897-900.
Nestler E. Molecular basis of long-term plasticity underlying addiction. Nat Rev Neurosci. 2001;2:119-128.
Nestler E. Molecular mechanisms of drug addiction. Neuropharmacology. 2004b;47:24-32.
Newman R. Analgesia and opiate addicts. Am J Addict. 2004;13:494.
Nitsche J, Schuller A, King M, Zengh M, Pasternak G, Pintar J. Genetic dissociation of opiate tolerance and physical dependence in delta-opioid receptor-1 and preproenkephalin knock-out mice. J Neurosci. 2002;22:10906-10913.
O’Brien C. Benzodiazepine use, abuse, and dependence. J Clin Psychiatry. 2005;66:28-33.
O’Brien CP, Childress AR, Ehrman R, Robbins SJ. Conditioning factors in drug abuse: can they explain compulsion? J Psychopharmacol. 1998;12:15-22.
Olmstead M, Burns L. Ultra-low-dose naltrexone suppresses rewarding effects of opiates and aversive effects of opiate withdrawal in rats. Psychopharmacology. 2005;181:576-1181.
Oslin D, Berrettini W, Kranzler H, Pettinati H, Gelernter J, Volpicelli J, et al. A functional polymorphism of the mu-opioid receptor gene is associated with naltrexone response in alcohol-dependent patients. Neuropsychopharmacology. 2003;28:1546-1552.
Ozaki S, Narita M, Narita M, Iino M, Miyoshi K, Suzuki T. Suppression of the morphine-induced rewarding effect and G-protein activation in the lower midbrain following nerve injury in the mouse: involvement of G-protein-coupled receptor kinase 2. Neuroscience. 2003;116:89-97.
Ozaki S, Narita M, Narita M, Iino M, Sugita J, Matsummura Y, et al. Suppression of the morphine-induced rewarding effect in the rat with neuropathic pain: implication of the reduction in mu-opioid receptor functions in the ventral tegmental area. J Neurochem. 2002;82:1192-1198.
Passik SD, Kirsh KL. Opioid therapy in patients with a history of substance abuse. CNS Drugs. 2004;18:13-25.
Passik SD, Kirsh KL, Whitcomb L, Dickerson PK, Theobald DE. Pain clinicians’ rankings of aberrant drug-taking behaviors. J Pain & Palliat Care Pharmacother. 2002;16:39-49.
Passik SD, Kirsh KL, Whitcomb L, Portenoy RK, Katz NP, Kleinman L, et al. A new tool to assess and document pain outcomes in chronic pain patients receiving opioid therapy. Clin Ther. 2004;26:552-561.
Passik S, Kirsh K. The need to identify predictors of aberrant drug-related behavior and addiction in patients being treated with opioids for pain. Pain Med. 2003;4:186-189.
Pickens R, Svikis D, McGue M, Lykken D, Heston L, Clayton P. Heterogeneity in the inheritance of alcoholism. A study of male and female twins. Arch Gen Psychiatry. 1991;48:19-28.
Polatin P, Kinney R, Gatchel R, Lillo E, Mayer T. Psychiatric illness and chronic low-back pain. The mind and the spine –which goes first? Spine. 1993;18:66-71.
Porreca F, Burgess S, Gardell L, Wanderah T, Malan T, Ossipov M, et al. Inhibition of neuropathic pain by selective ablation of brainstem medullary cells expression the mu-opioid receptor. J Neurosci. 2003;21:5281-5288.
Portenoy RK, Foley KM. Chronic use of opioid analgesics in non-malignant pain: report of 38 cases. Pain. 1986;25:171-186.
Portenoy R. Tolerance to opioid analgesics: clinical aspects. Cancer Surv. 1994;21:49-65.
Portenoy RK. Opioid therapy for chronic nonmalignant pain: a review of the critical issues. J Pain Symptom Manage. 1996;11:203-217.
Porter J, Jick H. Addiction rare in patients treated with narcotics (letter). N Engl J Med. 1980;302:123.
Raith K, Hochhaus G. Drugs used in the treatment of opioid tolerance and physical dependence: a review. Int J Clin Pharmacol Ther. 2004;42:191-203.
Rapp S, Ready L, Nessly M. Acute pain management in patients with prior opioid consumption: a case-controlled retrospective review. Pain. 1995;61:195-201.
Reich T, Edenberg H, Goate A, Williams J, Rice J, van Eerdewegh P, et al. Genome-wide search for genes affecting the risk for alcohol dependence. Am J Med Genet. 1998;81:207-215.
Robinson T, Berridge K. The neural incentive basis of drug craving: an incentive sensitization theory of addiction. Brain Res Rev. 1993;18:247-291.
Robinson T, Berridge K. Incentive-sensitization and addiction. Addiction. 2001;96:103-114.
Robinson T, Berridge K. Addiction. Annu Rev Psychol. 2003;54:25-53.
Romberg R, Olofsen E, Bijl H, Taschner P, Teppema L, Sarton E, et al. Polymorphism of mu-opioid receptor gene (OPRM1:c. 118A > G) does not protect against opioid-induced respiratory depression despite reduced analgesic response. Anesthesiology. 2005;102:522-530.
Roset P, Farre M, de la Torre R, Mas M, Menoyo E, Hernandez C, et al. Modulation of rate of onset and intensity of drug effects reduces abuse potential in healthy males. Drug Alcohol Depend. 2001;64:285-298.
Rounsaville B, Weissman M, Crits-Christoph K, Wilber C, Kleber H. Diagnosis and symptoms of depression in opiate addicts. Course and relationship to treatment outcome. Arch Gen Psychiatry. 1982;39:151-156.
Russo CM, Brose WG. Chronic pain. Annu Rev Med. 1998;49:123-133.
Saper JR, Lake AE 3rd, Hamel RL, Lutz TE, Branca B, Sims DB, et al. Daily scheduled opioids for intractable head pain: long-term observations of a treatment program. Neurology. 2004;62:687-694.
Sarnyai Z, Shaham Y, Heinrichs S. The role of corticotropin-releasing factor in drug addiction. Pharmacol Rev. 2001;53:209-243.
Savage S, Covington E, Ehit H, Hunt J, Joranson D, Schnoll S. Definitions related to the use of opioids for the treatment of pain. A consensus document from the American academy of pain medicine, the American pain society and the American society of addiction medicine; 2001.
Savage S, Joranson D, Covington E, Schnoll S, Heit H, Gilson A. Definitions related to the medical use of opioids: evolution towards universal agreement. J Pain Symptom Manage. 2003;26:655-667.
Schaible HG, Richter F. Pathophysiology of pain. Langenbecks Arch Surg. 2004;389:237-243.
Schluger J, Borg L, Ho A, Kreek M. Altered HPA axis responsivity to metyrapone testing in methadone maintained former heroin addicts with ongoing cocaine addiction. Neuropsychopharmacol. 2001;24:568-575.
Schluger J, Ho A, Borg L, Porter M, Maniar S, Gunduz M, et al. Nalmefene causes greater hypothalamic-pituitary-adrenal axis activation than naloxone in normal volunteers: implications for the treatment of alcoholism. Alcohol Clin Exp Res. 1998;22:1430-1436.
Self D, Nestler E. Relapse to drug-seeking: neural and molecular mechanisms. Drug Alcohol Depend. 1998;51:49-60.
Sell L, Morris J, Bearn J, Frackowiak R, Friston K, Dolan R. Activation of reward circuitry in human opiate addicts. Eu J Neurosci. 1999;11:1042-1048.
Shaham Y, Erb S, Stewart J. Stress-induced relapse to heroin and cocaine seeking in rats: a review. Brain Res Brain Res Rev. 2000;33:13-33.
Shippenberg T, LeFevour A, Thompson A. Sensitization to the conditioned rewarding effects of morphine and cocaine: differential effects of the kappa-opioid receptor agonist U69593. Eur J Pharmacol. 1998;345:27-34.
Sinha R, Talih M, Malison R, Cooney N, Anderson GM, Kreek MJ. Hypothalamic-pituitary-adrenal axis and sympatho-adreno-medullary responses during stress-induced and drug cue-induced cocaine craving states. Psychopharmacology (Berlin). 2003;170:62-72.
Skarke C, Darimont J, Schmidt H, Geisslinger G, Lötsch J. Analgesic effects of morphine and morphine-6-glucuronide in a transcutaneous electrical pain model in healthy volunteers. Clin Pharmacol Ther. 2003;73:107-121.
South SM, Smith MT. Analgesic tolerance to opioids. Pain Clin Update IASP Press 2001;9:1–4.
Straub R, Sullivan P, Ma Y, Myakishev M, Harris-Kerr C, Wormley B, et al. Susceptibility genes for nicotine dependence: a genome scan and followup in an independent sample suggest that regions on chromosomes 2, 4, 10, 16, 17 and 18 merit further study. Mol Psychiatry. 1999;4:129-144.
Taylor D, Fleming W. Unifying perspectives of the mechanisms underlying the development of tolerance and physical dependence to opioids. J Pharmacol Exp Ther. 2001;297:11-18.
The College of Physicians and Surgeons of Ontario. Evidence-based recommendations for medical management of chronic non-malignant pain. Reference guide for clinicians. 2000.
Trujillo K. Are NMDA receptors involved in opiate-induced neural and behavioral plasticity? A review of preclinical studies. Psychopharmacology (Berlin). 2000;151:121-141.
Tsuang MT, Lyons MJ, Meyer JM, Doyle T, Eisen SA, Goldberg J, et al. Co-occurrence of abuse of different drugs in men: the role of drug-specific and shared vulnerabilities. Arch Gen Psychiatry. 1998;55:967-972.
Tsuang M, Lyons M, Harley R, Xian H, Eisen S, Goldberg J, et al. Genetic and environmental influences on transitions in drug use. Behav Genet. 1999;29:473-479.
Turk D. Clinicians’ attitudes about prolonged use of opioids and the issue of patient heterogeneity. J Pain Symptom Manage. 1996;11:218-230.
Uhl GR, Liu QR, Walther D, Hess J, Naiman D. Polysubstance abuse-vulnerability genes: genome scans for association, using 1004 subjects and 1494 single-nucleotide polymorphisms. Am J Hum Genet. 2001;69:1290-1300.
Uhl G. Molecular genetics of substance abuse vulnerability: remarkable recent convergence of genome scan results. Ann NY Acad Sci. 2004;1025:1-13.
Vanderah TW, Ossipov MH, Lai J, Malan TP Jr, Porreca F. Mechanisms of opioid-induced pain and antinociceptive tolerance: descending facilitation and spinal dynorphin. Pain. 2001;92:5-9.
Vanderah T, Gardell L, Burgess S, Ibrahim M, Dogrul A, Zhong C, et al. Dynorphin promotes abnormal pain and spinal opioid antinociceptive tolerance. J Neurosci. 2000;20:7074-7079.
von Korff M, Deyo RA. Potent opioids for chronic musculoskeletal pain: flying blind? Editorial. Pain. 2004;109:207-209.
von Zastrow M. A cell biologist’s perspective on physiological adaptation to opiate drugs. Neuropharmacology. 2004;47:286-292.
Walsh S, Eissenberg T. The clinical pharmacology of buprenorphine: extrapolating from the laboratory to the clinic. Drug Alcohol Depend. 2003;70:S13-S27.
Wand G, McCaul M, Yang X, Reynolds J, Gotjen D, Lee S, et al. The mu-opioid receptor gene polymorphism (A118G) alters HPA axis activation induced by opioid receptor blockade. Neuropsychopharmacology. 2002;26:106-114.
Wang H, Friedman E, Olmstead M, Burns L. Ultra-low-dose naloxone suppresses opioid tolerance, dependence and associated changes in mu opioid receptor-G protein coupling and Gβγ signaling. Neuroscience. 2005;135:247-261.
Wang Z, Zhou Y, Spangler R, Ho A, Han J, Kreek M. Acute intermittent morphine increases preprodynorphin and kappa opioid receptor mRNA levels in the rat brain. Mol Brain Res. 1999;66:184-187.
Wasan A, Davar G, Jamison R. The association between negative affect and opioid analgesia in patients with discogenic low back pain. Pain. 2005;117:450-461.
Watts V. Molecular mechanisms for heterologous sensitization of adenylate cyclase. J Pharmacol Exp Ther. 2002;302:1-7.
Weaver M, Schnoll S. Abuse liability in opioid therapy for pain treatment in patients with an addiction history. Clin J Pain. 2002a;18:S61-S69.
Weaver M, Schnoll S. Opioid treatment of chronic pain in patients with addiction. J Pain Palliat Care Pharmacother. 2002b;16:5-26.
Webster L, Webster R. Predicting aberrant behaviors in opioid-treated patients: preliminary validation of the Opioid Risk Tool. Pain Med. 2005;6:432-442.
Weissman D, Haddox J. Opioid pseudoaddiction – an iatrogenic syndrome. Pain. 1989;36:363-366.
West J, Aronoff G, Dahl J, Johnson S, Joranson D, Koontz W, et al. Model guidelines for the use of controlled substances for the treatment of pain. A policy document of the federation of state medical boards of the United States Inc. Euless Texas: Federation of State Medical Boards of the United States Inc; 1998.
Wiesenfeld-Hallin Z, Xu X. Neuropeptides in neuropathic and inflammatory pain with special emphasis on cholecystokinin and galanin. Eur J Pharmacol. 2001;429:49-59.
Wilder-Smith O, Arendt-Nielsen L. Postoperative hyperalgesia: its clinical importance and relevance. Anesthesiology. 2006;104:601-607.
Williams J, Christie M, Manzoni O. Cellular and synaptic adaptations mediating opioid dependence. Physiol Rev. 2001;81:299-343.
Wise R. Addiction becomes a brain disease. Neuron. 2000;26:27-33.
Woolf C, Hashmi M. Use and abuse of opioid analgesics: potential methods to prevent and deter non-medical consumption of prescription opioids. Curr Opin Invest Drugs. 2004;5:61-66.
Xu X, Colpaert F, Wiesenfeld-Hallin Z. Opioid hyperalgesia and tolerance versus 5-HT1A receptor-mediated inverse tolerance. Trends Pharmacol Sci. 2003;24:634-639.
Yu W, Hao J, Xu X, Wiesenfeld-Hallin Z. The development of morphine tolerance and dependence in rats with chronic pain. Brain Res. 1997;756:141-146.
Zachariou V, Bolanos C, Selley D, Theobald D, Cassidy M, Kelz M, et al. An essential role for ΔFosB in the nucleus accumbens in morphine action. Nat Neurosci. 2006;9:205-211.
Zacny J, McKay M, Toledano A, Marks S, Young C, Klock P, et al. The effects of a cold-water immersion stressor on the reinforcing and subjective effects of fentanyl in healthy volunteers. Drug Alcohol Depend. 1996;42:133-142.
Zwart JA, Dyb G, Hagen K, Svebak S, Stovner LJ, Holmen J. Analgesic overuse among subjects with headache, neck, and low-back pain. Neurology. 2004;62:1540-1544.
1 The word “terminal” is used advisedly to distinguish terminal from chronic cancer pain. Cancer is no longer necessarily an explosive, terminal disease and many cancer patients have normal life expectancy, but will live with treatment- or disease-related pain. Terminal cancer pain more closely matches the traditional concept of cancer pain being a short-term, terminal condition.
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2_Substance use disorder_ is the term used in the DSM-IV manual to incorporate substance abuse and substance dependence
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3_Iatrogenic opioid addiction_ is here defined as opioid addiction arising directly from opioid treatment of pain.
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4 Substance use disorders (pre-existing and co-existing, and possibly involving multiple substances) must be distinguished from true (isolated) iatrogenic opioid addiction.
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Keywords:
Opioid analgesics; Pain; Substance-related disorders; Opioid-related disorders
© 2007 Lippincott Williams & Wilkins, Inc.