Prescription Drug Use Disorders Research Articles

Can Prescription Drug Use Disorder Predict Suicidality in US Adults With Chronic Pain? A Pilot Study Based on Collaborative Psychiatric Epidemiological Surveys.

Individuals with chronic pain are at higher risk for suicide than other populations, and their potential for prescription drug use disorder (PDUD) enormously exists. This study aimed to estimate the prevalence and correlates of suicidality and to determine its relation to PDUD, among US adults with a history of chronic pain. Data were obtained from the Collaborative Psychiatric Epidemiology Surveys (2001-2003). This analysis was limited to respondents who had a history of chronic pain (N = 5301). Logistic regression was used to determine the association between suicidality and prescription drug use disorder among those populations. Among study respondents, there was a strong positive association between PDUD and suicidal ideation and attempts (P value < 0.001, = 0.006, respectively). Adjusted logistic regression analysis showed those with PDUD had 1.5 times greater likelihood of suicidal ideation (95% CI 1.2-1.8). Among respondents with a history of chronic pain and PDUD, Non-Hispanic Whites, female gender, lifetime mood and/or anxiety, and substance use disorders were associated with increased suicide risk (P value = 0.020, = 0.011, < 0.001, < 0.001, respectively). There is a robust relationship between PDUD and suicidality in US adults with a history of chronic pain. Ethnicity, gender, and comorbid mood, anxiety or substance use disorders can predict suicidality among individuals with both chronic pain and PDUD. Longitudinal studies need to investigate the causal relationship between PDUD and suicidality among those populations.

Gender differences in the relationship between gambling problems and the incidence of substance-use disorders in a nationally representative population sample

BackgroundCross-sectional studies have demonstrated gender-related differences in the associations between problem-gambling severity and substance-use disorders; however, these associations have not been examined longitudinally. We aimed to examine the prospective associations between problem-gambling severity and incident substance-use disorders in women versus men. MethodsAnalyses were conducted using Wave-1 and Wave-2 NESARC data focusing on psychiatric diagnoses from 34,006 non-institutionalized US adults. Inclusionary criteria for pathological gambling were used to categorize Wave-1 participants as at-risk/problem gambling (ARPG) and non-ARPG (i.e. non-gambling/low-frequency gambling/low-risk gambling). Dependent variables included the three-year incidence of any substance-use disorder, alcohol-use disorders, nicotine dependence, drug-use disorders, prescription drug-use disorders, and illicit drug-use disorders. ResultsSignificant gender-by-ARPG status interactions were observed with respect to the three-year incidence of nicotine dependence and prescription drug-use disorders, and approached significance with respect to incident alcohol-use disorders. ARPG (relative to non-ARPG) was positively associated with nicotine dependence among women (OR=2.00; 95% CI=1.24–3.00). ARPG was negatively associated with incident prescription drug-use disorders among men (OR=0.30; 95% CI=0.10–0.88)). Finally, ARPG was positively associated with incident alcohol-use disorders among men (OR=2.20; 95% CI=1.39–3.48). ConclusionsGambling problems were associated with an increased 3-year incidence of nicotine dependence in women and alcohol dependence in men. These findings highlight the importance of considering gender in prevention and treatment initiatives for adults who are experiencing gambling problems. Moreover, the specific factors underlying the differential progressions of specific substance-use disorders in women and men with ARPG warrant identification.

Aberrant Drug-Related Behaviors: Unsystematic Documentation Does Not Identify Prescription Drug Use Disorder

No evidence-based methods exist to identify prescription drug use disorder (PDUD) in primary care (PC) patients prescribed controlled substances. Aberrant drug-related behaviors (ADRBs) are suggested as a proxy. Our objective was to determine whether ADRBs documented in electronic medical records (EMRs) of patients prescribed opioids and benzodiazepines could serve as a proxy for identifying PDUD. A cross-sectional study of PC patients at an urban, academic medical center. Two hundred sixty-four English-speaking patients (ages 18-60) with chronic pain (≥3 months), receiving ≥1 opioid analgesic or benzodiazepine prescription in the past year, were recruited during outpatient PC visits. Composite International Diagnostic Interview defined Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) diagnoses of past year PDUD and no disorder. EMRs were reviewed for 15 prespecified ADRBs (e.g., early refill, stolen medications) in the year before and after study entry. Fisher's exact test compared frequencies of each ADRB between participants with and without PDUD. Sixty-one participants (23%) met DSM-IV PDUD criteria and 203 (77%) had no disorder; 85% had one or more ADRB documented. Few differences in frequencies of individual behaviors were noted between groups, with only "appearing intoxicated or high" documented more frequently among participants with PDUD (N = 10, 16%) vs no disorder (N = 8, 4%), P = 0.002. The only common ADRB, "emergency visit for pain," did not discriminate between those with and without the disorder (82% PDUD vs 78% no disorder, P = 0.6). EMR documentation of ADRBs is common among PC patients prescribed opioids or benzodiazepines, but unsystematic clinician documentation does not identify PDUDs. Evidence-based approaches are needed.

Probability and predictors of remission from life-time prescription drug use disorders: Results from the National Epidemiologic Survey on Alcohol and Related Conditions

While prescription drug use disorders (PDUD) has become an important and growing public health problem, little is known about their course. This study aims to estimate cumulative probability of remission from sedatives, tranquilizers, opioids and stimulants, and to identify predictors of remission across substances. Analyses were done for the sub-sample of individuals with lifetime history of abuse or dependence on sedatives (n = 402), tranquilizers (n = 372), opioids (n = 521), and stimulants (n = 765) at Wave 1 of the National Epidemiological Survey on Alcohol and Related Conditions (NESARC). Cumulative probability estimates and hazard ratios for remission from PDUD were obtained for the general population. Lifetime cumulative probability estimates of remission were above 96% for all substances assessed. Half of the cases of PDUD remitted between 4 and 5 years after onset. Remission from PDUD was greater for younger individuals. Males exhibited lower hazards of remission for stimulants use disorder. A diagnosis of personality disorders decreased probability of remission for sedatives and stimulants. Only abuse or dependence on some prescription drugs decreased the probability of remission from other PDUD, whereas other drug disorders did not predict remission. A significant proportion of individuals with PDUD achieve remission at some point in their life-time. Predictors of remission were found to be mostly substance-specific rather than common across substances. The lower rates of remission among some subgroups of the population highlight the need to strengthen preventive and intervention efforts among vulnerable population subgroups.

Identifying prescription opioid use disorder in primary care: Diagnostic characteristics of the Current Opioid Misuse Measure (COMM)

The Current Opioid Misuse Measure (COMM), a self-report assessment of past-month aberrant medication-related behaviors, has been validated in specialty pain management patients. The performance characteristics of the COMM were evaluated in primary care (PC) patients with chronic pain. It was hypothesized that the COMM could identify patients with prescription drug use disorder (PDD). English-speaking adults awaiting PC visits at an urban, safety-net hospital, who had chronic pain and had received any opioid analgesic prescription in the past year, were administered the COMM. The Composite International Diagnostic Interview served as the “gold standard,” using DSM-IV criteria for PDD and other substance use disorders (SUDs). A receiver operating characteristic (ROC) curve demonstrated the COMM’s diagnostic test characteristics. Of the 238 participants, 27 (11%) met DSM-IV PDD criteria, whereas 17 (7%) had other SUDs, and 194 (82%) had no disorder. The mean COMM score was higher in those with PDD than among all others (ie, those with other SUDs or no disorder, mean 20.4 [SD 10.8] vs 8.4 [SD 7.5], P<.0001). A COMM score of⩾13 had a sensitivity of 77% and a specificity of 77% for identifying patients with PDD. The area under the ROC curve was 0.84. For chronic pain patients prescribed opioids, the development of PDD is an undesirable complication. Among PC patients with chronic pain-prescribed prescription opioids, the COMM is a promising tool for identifying those with PDD.Among primary care patients with chronic pain-prescribed opioids, the validated Current Opioid Misuse Measure (COMM) is a promising tool for identifying patients with prescription opioid use disorder.

Clinical factors associated with prescription drug use disorder in urban primary care patients with chronic pain.

This study examined characteristics associated with prescription drug use disorder (PDUD) in primary-care patients with chronic pain from a cross-sectional survey conducted at an urban academically affiliated safety-net hospital. Participants were 18 to 60 years old, had pain for ≥ 3 months, took prescription or nonprescription analgesics, and spoke English. Measurements included the Composite International Diagnostic Interview (PDUD, other substance use disorders (SUD), Posttraumatic Stress Disorder [PTSD]); Graded Chronic Pain Scale, smoking status; family history of SUD; and time spent in jail. Of 597 patients (41% male, 61% black, mean age 46 years), 110 (18.4%) had PDUD of whom 99 (90%) had another SUD. In adjusted analyses, those with PDUD were more likely than those without any current or past SUD to report jail time (OR 5.1, 95% CI 2.8-9.3), family history of SUD (OR 3.4, 1.9-6), greater pain-related limitations (OR 3.8, 1.2-11.7), cigarette smoking (OR 3.6, 2-6.2), or to be white (OR 3.2, 1.7-6), male (OR 1.9, 1.1-3.5) or have PTSD (OR 1.9, 1.1-3.4). PDUD appears increased among those with easily identifiable characteristics. The challenge is to determine who, among those with risk factors, can avoid, with proper management, developing the increasingly common diagnosis of PDUD. This article examines risk factors for prescription drug use disorder (PDUD) among a sample of primary-care patients with chronic pain at an urban, academic, safety-net hospital. The findings may help clinicians identify those most at risk for developing PDUD when developing appropriate treatment plans.

IN PURSUIT OF A MORE COMPLEX UNDERSTANDING OF NON‐MEDICAL USE OF PRESCRIPTION DRUGS: BROADENING PERSPECTIVE BY SHARPENING OUR TOOLS

We appreciate the commentary by Fischer & Rehm but would like to respond to several points they raised [1,2]. First, we agree with Fischer & Rehm that individual trajectories of non-medical use of prescription drugs (NMUPD) often begin early, with the majority of NMUPD initiating before 21 years of age. We doubt, however, that the trajectories from early onset of NMUPD to prescription drug use disorders (PDUDs) are associated consistently with socio-economic class or educational status. While we were unable to assess this in the National Epidemiologic Survey on Alcohol Related Conditions (NESARC) because it did not measure socio-economic or educational status at the time of NMUPD onset, previous studies suggest that associations between these variables are complex and vary by prescription drug class [3–5]. For instance, the non-medical use of stimulant medications is more prevalent among those with higher income levels [3,5], while non-medical use of prescription opioids is more prevalent among those from lower income levels [3,4]. Individuals with higher educational levels were more likely to engage in the non-medical use of prescription stimulants than those with lower educational levels, but there were no such differences for the non-medical use of prescription opioids, sedatives or tranquilizers [3]. Secondly, we question whether most non-medical users coming from disadvantaged circumstances are ‘self-medicators’. Being economically disadvantaged or uninsured may limit access to prescription medication but regardless of motivation (self-treatment versus recreational use), there are notable risks for non-medical users who self-treat. For example, ‘self-treaters’ do not receive clinical assessments, medical follow-ups or medical information that accompanies a prescription. Thus, self-treaters may be unaware of contraindications or probable interaction with other drugs. Furthermore, abusable prescription medications can produce physical dependence and withdrawal symptoms upon discontinuation. The odds of past-year PDUDs among those who report past-year NMUPD was considerably higher among individuals with lower income levels than those with higher income levels [6]. We noted the limitations of self-report measures using life-time time-frame and expressed the hope that prospective longitudinal studies will examine the natural history of NMUPD. We agree with Fischer & Rehm that more detailed measures are needed in order to obtain a more complex understanding of NMUPD; advances in our understanding of NMUPD will not be possible until we reconsider the assessment tools that measure NMUPD. Surprisingly, few advances have been made since Hubbard and colleagues showed the limitations of using a single measure to assess NMUPD and advocated decomposing the single NMUPD measure into separate questions 15 years ago [7]. Improvements in measurement of NMUPD and use of prospective longitudinal designs will help to determine if early onset of NMUPD is simply a correlate of PDUDs or a causal risk factor [8] that might represent a target for prevention and intervention.