Symposium on Mental Health — February 2015
Tex Med. 2015;111(2):61-65.
By Adriane M. dela Cruz, MD, and Madhukar H. Trivedi, MD
Recent reports of the sharp increase in overdose deaths from prescription opioids have raised concerns regarding the widespread use and abuse of these medications in the treatment of chronic noncancer pain (CNCP). Between 1999 and 2010, the rates of opioid sales and opioid-related deaths increased in parallel,1 with death rates from prescription opioids highest among those aged 35 to 54 years.1 More women die from prescription opioids than from cocaine or heroin.2
The Centers for Disease Control and Prevention has described prescription drug overdose deaths as an epidemic,3 with recommendations that strategies for preventing opioid-related deaths should focus on the 10 percent of patients prescribed high doses of medication (≥100 mg morphine equivalent dose per day) from a single health professional and the 10 percent of patients who receive high doses from multiple physicians. Together, these groups account for 80 percent of prescription opioid overdose deaths.3-5 Last year, the Drug Enforcement Administration reclassified all hydrocodone-containing products from Schedule III to Schedule II; this change limits the number of pills per prescription and requires office visits for refills.
The CDC report also encourages more education for physicians on prescription of opioids, pain management, and addiction.3 The report specifically encourages physicians to consult state-run prescription databases and to discontinue opioid therapy for patients not receiving benefit.3
This article reviews important terms for understanding prescription opioid addiction and describes several tools that health professionals can use to screen patients with CNCP being considered for opioid therapy.
Estimates on the prevalence of opioid misuse and addiction among patients receiving opioid therapy for CNCP vary widely, likely related in part to confusion among terminology and difficulty appropriately identifying patients with addictions.6 For clarity, the American Academy of Pain Medicine, the American Pain Society, and the American Society of Addiction Medicine developed a consensus statement defining addiction and physical dependence,7 and this article will follow those definitions.
Addiction is "a primary, chronic, neurobiological disease, with genetic, psychosocial, and environmental factors influencing its development and manifestations. It is characterized by behaviors that include one or more of the following: impaired control over drug use, compulsive use, continued use despite harm, and craving."7
Addiction can be contrasted with physical dependence, which is "a state of adaptation that is manifested by a drug class specific withdrawal syndrome that can be produced by abrupt cessation, rapid dose reduction, decreasing blood levels of the drug, and/or administration of an antagonist."7 The development of physical dependence is expected in patients treated with chronic opioid therapy;6,8 signs of physical dependence should not be assumed to be signs of addiction.
A third behavioral phenomenon secondary to undertreatment of pain has been described as "pseudoaddiction." Pseudoaddiction describes behaviors that appear consistent with addiction — repeated requests for higher doses, running out of medications early, taking more medication than prescribed — that stem from undertreatment of pain;6,8 i.e., undertreatment of pain and resulting drug-seeking behavior lead to inappropriately identifying patients as addicted to opioids. Some have questioned the relevance of pseudoaddiction in chronic pain,9,10 due in part to concern that this term improperly implies a patient may have pain or addiction, while in fact pain and addiction can co-occur.10
Finally, an important term to understanding and identifying problem opioid use is the concept of aberrant drug-related behavior (ADRB). Although poorly defined, ADRB can include the following: doctor shopping, loss of prescriptions, tampering with prescriptions, demanding behaviors, and urine toxicology results positive for illicit drugs and/or negative for prescribed opioids.9,11,12 Patients may engage in ADRB for several reasons, including addiction, physical dependence, and diversion (selling of prescription opioids).6,11 Thus, detection of ADRB may or may not identify patients with opioid addictions. Patients who receive chronic treatment with opioids may show signs of addiction, physical dependence, pseudoaddiction, and ADRB. While overlapping signs can indicate these phenomena, they remain clinically distinct syndromes with different causes that require different treatments.
Identifying At-risk Patients
A critical first step is the diagnosis of the source of chronic pain and monitoring the patient's response to opioid therapy, beginning with an appropriate differential.8,13 Pain levels should be assessed before initiating opioid therapy and throughout treatment.14 After an initial treatment period (four to six weeks), the degree of pain relief and improvement in functioning should be assessed,10,15 and opioid treatment should be discontinued in those with an inadequate response or high side-effect burden.
The Brief Pain Inventory (BPI)16,17 is a well-validated pain assessment, although use of this instrument in busy clinic settings may be limited by instrument length. We have recently developed a four-item self-report pain measure, the Pain Frequency, Intensity, and Burden Scale (P-FIBS), with excellent psychometric properties18 that may be used to assess pain levels over time. Once a diagnosis for the pain complaint has been made and the level of pain assessed, the patient should be further screened for the appropriateness of opioid therapy.
One potential method for identifying patients who are at highest risk for the development of opioid addiction is determining the factors that are common among patients with prescription opioid addictions. Demographic and psychosocial factors associated with prescription opioid addiction are listed in Table 1. Drug-related factors include craving opioid medications, treatment with high doses of opioids, use of short-acting opioid preparations, and experiencing opioids as rewarding.11,19 Correlations between the level of opioid craving and several different measures of ADRB (including urine toxicology results positive for illicit substances) have been observed.20 Genetic factors, including polymorphisms in opioid receptors, have been implicated in the development of opioid addictions,19 although a role for these polymorphisms in the development of prescription opioid addiction during treatment for chronic pain has not been described.
Reports suggest that addiction is most likely to develop in patients who have psychosocial factors, drug-related factors, and genetic factors that predispose them to addiction,19 yet none of these factors are specific enough to guide opioid prescribing practices with the goal of identifying patients at highest risk for addiction. One recent report described a formal tool based on several of these demographic factors,21 although prospective use of this instrument as a screening tool has not been studied.
Several instruments have been developed to guide the prescription of opioids for CNCP. Each tool (Table 2) has strengths and weaknesses, and no single instrument has been identified as a gold standard. Use of at least one tool, however, is important for identifying high-risk patients and guiding treatment planning.13,14 These tools have been assessed for the ability to predict ADRB, although it is unclear if prediction of ADRB is an appropriate endpoint when clinicians are likely most interested in predicting which patients will develop addictions.
One early example of a screening instrument is the Diagnosis, Intractability, Risk, Efficacy (DIRE) score, which the authors describe as a tool designed to predict patients who will have "effective analgesia and be compliant" with opioid treatment for CNCP.27 The physician-rated DIRE score gives a score of 1 to 3 on the four separate domains: diagnosis, intractability, risk, and efficacy; the risk category is further broken down into psychological, chemical health, reliability, and social support. A higher score is consistent with a more favorable use of opioid therapy by the patient. Although a retrospective chart review demonstrated good inter-rater reliability and internal consistency,27 information on the prospective use of this instrument is limited.19
The Screener and Opioid Assessment for Patients with Pain-Revised (SOAPP-R) is a tool to aid in clinical risk assessment for patients at risk for developing opioid addiction.28 The SOAPP-R contains 24 items rated by the patient from 0 (never) to 4 (very often), with a higher score indicating greater risk for addiction with opioid treatment.28 Higher scores on the SOAPP-R at baseline predicted ADRB five months later.28
The Opioid Risk Tool (ORT) is a five-item, self-administered questionnaire that assesses the presence of a family history of substance abuse, a personal history of substance abuse, age between 16 and 45 years, history of childhood sexual abuse, and psychiatric illness.29 Patients categorized at baseline as high risk based on ORT score demonstrated a higher rate of ADBR at 12 months of treatment than did patients categorized as low risk.29 A retrospective chart review using a physician-completed ORT also demonstrated a higher rate of ADRB among patients categorized as high risk, although a large proportion (39 percent) of patients categorized as low risk by the ORT also demonstrated at least one ADRB.30
A recent study describes the use of the Brief Risk Interview (BRI) for screening and stratifying patients at the initiation of prescription opioid therapy.31 The BRI is a clinician-rated scale in which patients are rated from low risk to very high risk on 12 categories, and the authors estimate a clinician would need to interview the patient for 10 to 15 minutes to gather the necessary information.31 When gathering information as part of a full psychological interview, BRI score at baseline predicted ADRB at six months.31 It remains unclear how the BRI will function when administered as a stand-alone interview.
Screening before the start of opioid therapy is one strategy for risk assessment; an additional strategy is ongoing monitoring during therapy. The Current Opioid Misuse Measure (COMM) is a tool for monitoring the development of ADRB in patients currently being treated with long-term opioid therapy.32 This measure contains 17 self-rated items that inquire about behavior in the past 30 days; a cutoff score of 9 detected ADRB with a sensitivity of 0.94 and a specificity of 0.73.32 A separate validation study among primary care patients determined an ideal cutoff score of 13 for identifying patients with prescription opioid use disorders.33 This cutoff had a sensitivity of 0.77 and a specificity of 0.77, compared with a sensitivity of 0.85 and a specificity of 0.60 with a cutoff score of 9.33 Thus, COMM is one of the few tools that has been tested for the ability to identify specifically those patients with opioid addictions, the outcome that is most relevant to clinicians.
Recent comparative studies have attempted to provide guidance to clinicians regarding which of these assessment tools is most appropriate. A study of 48 patients who were discontinued from opioid therapy due to significant ADRB or nonadherence to treatment plans demonstrated the highest sensitivity for a clinical interview and second highest for the SOAPP completed at initiation of therapy;34 the ORT and DIRE both demonstrated lower sensitivity. Combining the clinical interview and the SOAPP increased the sensitivity to 0.90.34 A meta-analysis reviewing several screening instruments demonstrated methodological shortcomings and low-quality studies, in part limited by inconsistent definitions of ADRB.12 These authors found high-quality evidence that the SOAPP-R rating weakly increased the chance of ADRB, lower quality evidence that ORT categorization as high risk increased the likelihood of ADRB, and high-quality evidence a high COMM score weakly increased the likelihood of ADRB.12 These conclusions were limited by the low number of studies independently assessing each instrument and the lack of direct comparisons of different instruments in the same study.
A more recent narrative review of screening instruments found that no single instrument could be universally recommended.19
In addition to the screening tools described above, urine drug toxicology has been recommended as a method for screening and monitoring patients on chronic opioid therapy, although the best role for this tool is unclear. Several authors recommend urine screening6,8-10,35 as part of ongoing monitoring of patients on opioid therapy, both to detect illicit substances and to verify the presence of the prescribed opioid. Most authors recommend determining the frequency of monitoring based on initial risk stratification, with high-risk patients experiencing the most frequent monitoring. Guidelines for the use of urine drug monitoring have been proposed regarding patient selection for testing, frequency of testing, and actions to take based on test results, although the evidence base supporting these recommendations is weak.36
Applying a systematic method for risk stratification for all patients being considered for opioid therapy for CNCP has been strongly recommended.8-11,13,35 At this time, no single instrument can be recommended as the best tool for screening. Consistent use of a screening tool to guide treatment planning is recommended. Given the variety in available, published screening tools, health care professionals can use the tool most appropriate for their practice environment.
Adriane dela Cruz, MD, is a fourth-year psychiatry resident at The University of Texas Southwestern Medical Center.
Madhukar H. Trivedi, MD, is a professor of psychiatry who holds the Betty Jo Hay Distinguished Chair in Mental Health and is the director of the Comprehensive Center for Depression at UT Southwestern.
- Centers for Disease Control and Prevention. Vital signs: overdoses of prescription opioid pain relievers — United States, 1999-2008. MMWR Morb Mortal Wkly Rep. 2011;60(43):1487-1492.
- Centers for Disease Control and Prevention. Vital signs: overdoses of prescription opioid pain relievers and other drugs among women — United States, 1999-2010. MMWR Morb Mortal Wkly Rep. 2013;62(26):537-542.
- Centers for Disease Control and Prevention. CDC grand rounds: prescription drug overdoses — a U.S. epidemic. MMWR Morb Mortal Wkly Rep. 2012;61(1):10-13.
- Hall AJ, Logan JE, Toblin RL, et al. Patterns of abuse among unintentional pharmaceutical overdose fatalities. JAMA. 2008;300(22):2613-2620.
- Bohnert AS, Valenstein M, Bair MJ, et al. Association between opioid prescribing patterns and opioid overdose-related deaths. JAMA. 2011;305(13):1315-1321.
- Cheatle MD, O'Brien CP. Opioid therapy in patients with chronic noncancer pain: diagnostic and clinical challenges. Adv Psychosom Med. 2011;30:61-91.
- Definitions Related to the Use of Opioids for the Treatment of Pain: Consensus Statement of the American Academy of Pain Medicine, the American Pain Society, and the American Society of Addiction Medicine. 2011. http://bit.ly/1rtA5j4.
- Jamison RN, Serraillier J, Michna E. Assessment and treatment of abuse risk in opioid prescribing for chronic pain. Pain Res Treat. 2011;2011:941808.
- Krashin D, Murinova N, Ballantyne J. Management of pain with comorbid substance abuse. Curr Psychiatry Rep. 2012;14(5):462-468.
- Miotto K, Kaufman A, Kong A, Jun G, Schwartz J. Managing co-occurring substance use and pain disorders. Psychiatr Clin North Am. 2012;35(2):393-409.
- Savage SR. Management of opioid medications in patients with chronic pain and risk of substance misuse. Curr Psychiatry Rep. 2009;1(5):377-384.
- Chou R, Fanciullo GJ, Fine PG, et al. Opioids for chronic noncancer pain: prediction and identification of aberrant drug-related behaviors: a review of the evidence for an American Pain Society and American Academy of Pain Medicine clinical practice guideline. J Pain. 2009;10(2):131-146.
- Gourlay DL, Heit HA, Almahrezi A. Universal precautions in pain medicine: a rational approach to the treatment of chronic pain. Pain Med. 2005;6(2):107-112.
- Bohn TM, Levy LB, Celin S, Starr TD, Passik SD. Screening for abuse risk in pain patients. Adv Psychosom Med. 2011;30:113-124.
- Stein C, Reinecke H, Sorgatz H. Opioid use in chronic noncancer pain: guidelines revisited. Curr Opin Anaesthesiol. 2010;23(5):598-601.
- Daut RL, Cleeland CS, Flanery RC. Development of the Wisconsin Brief Pain Questionnaire to assess pain in cancer and other diseases. Pain. 1983;17(2):197-210.
- Cleeland CS, Ryan KM. Pain assessment: global use of the Brief Pain Inventory. Ann Acad Med Singapore. 1994;23(2):129-138.
- Dela Cruz A, Bernstein IH, Greer TL, et al. Self-rated measure of pain frequency, intensity, and burden: psychometric properties of a new instrument for the assessment of pain. J Psychiatr Res. Aug. 27, 2014. doi: 10.1016/j.jpsychires.2014.08.003. [Epub ahead of print].
- Sehgal N, Manchikanti L, Smith HS. Prescription opioid abuse in chronic pain: a review of opioid abuse predictors and strategies to curb opioid abuse. Pain Physician. 2012;15(3 Suppl):ES67-92.
- Wasan AD, Butler SF, Budman SH, et al. Does report of craving opioid medication predict aberrant drug behavior among chronic pain patients? Clin J Pain. 2009;25(3):193-198.
- Skala K, Reichl L, Ilias W, et al. Can we predict addiction to opioid analgesics? A possible tool to estimate the risk of opioid addiction in patients with pain. Pain Physician. 2013;16(6):593-601.
- Wasan AD, Butler SF, Budman SH, Benoit C, Fernandez K, Jamison RN. Psychiatric history and psychologic adjustment as risk factors for aberrant drug-related behavior among patients with chronic pain. Clin J Pain. 2007;23(4):307-315.
- Liebschutz JM, Saitz R, Weiss RD, et al. Clinical factors associated with prescription drug use disorder in urban primary care patients with chronic pain. J Pain. 2010;11(11):1047-1055.
- Fleming MF, Balousek SL, Klessig CL, Mundt MP, Brown DD. Substance use disorders in a primary care sample receiving daily opioid therapy. J Pain. 2007;8(7):573-582.
- 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(3):355-362.
- Boscarino JA, Rukstalis M, Hoffman SN, et al. Risk factors for drug dependence among out-patients on opioid therapy in a large US health-care system. Addiction. 2010;105(10):1776-1782.
- Belgrade MJ, Schamber CD, Lindgren BR. The DIRE score: predicting outcomes of opioid prescribing for chronic pain. J Pain. 2006;7(9):671-681.
- Butler SF, Budman SH, Fernandez KC, Fanciullo GJ, Jamison RN. Cross-validation of a screener to predict opioid misuse in chronic pain patients (SOAPP-R). J Addict Med. 2009;3:66-73.
- Webster LR, Webster RM. Predicting aberrant behaviors in opioid-treated patients: preliminary validation of the Opioid Risk Tool. Pain Med. 2005;6(6):432-442.
- Witkin LR, Diskina D, Fernandes S, Farrar JT, Ashburn MA. Usefulness of the opioid risk tool to predict aberrant drug-related behavior in patients receiving opioids for the treatment of chronic pain. J Opioid Manag. 2013;9:177-187.
- Jones T, Moore T. Preliminary data on a new opioid risk assessment measure: the Brief Risk Interview. J Opioid Manag. 2013;9(1):19-27.
- Butler SF, Budman SH, Fernandez KC, et al. Development and validation of the Current Opioid Misuse Measure. Pain. 2007;130(1-2):144-156.
- Meltzer EC, Rybin D, Saitz R, et al. Identifying prescription opioid use disorder in primary care: diagnostic characteristics of the Current Opioid Misuse Measure (COMM). Pain. 2011;152(2):397-402.
- Moore TM, Jones T, Browder JH, Daffron S, Passik SD. A comparison of common screening methods for predicting aberrant drug-related behavior among patients receiving opioids for chronic pain management. Pain Med. 2009;10(8):1426-1433.
- Atluri S, Akbik H, Sudarshan G. Prevention of opioid abuse in chronic non-cancer pain: an algorithmic, evidence based approach. Pain Physician. 2012;15(3 Suppl):ES177-189.
- Peppin JF, Passik SD, Couto JE, et al. Recommendations for urine drug monitoring as a component of opioid therapy in the treatment of chronic pain. Pain Med. 2012;13(7):886-896.
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