Opioid use disorder (OUD) and treatment for opioid problems among OUD symptom subtypes in individuals misusing opioids.

Background: In 2021, approximately 60 million individuals worldwide and 9 million individuals in the United States (US) reported opioid misuse. In the US, 2.5 million have OUD, of which only about a third receive any substance abuse treatment. OUD is often regarded as a monolithic disorder but different opioid problem subtypes may exist beyond DSM-IV/5 criteria. Understanding the characteristics of these subtypes could be useful for informing treatment and intervention strategies. Methods: Latent class analysis was used to identify OUD symptom subtypes among persons in the US who reported misusing prescription opioids or heroin in the 2015-2018 National Survey on Drug Use and Health (n=10,928). Regression analyses were utilized to determine associations between class membership and treatment receipt, as well as demographic characteristics and other comorbid conditions. Results: Five classes were identified with unique OUD symptom patterns: Class 1: Asymptomatic (71.6%), Class 2: Tolerance/Time (14.5%), Class 3: Loss of Control/Pharmacological (LOC/Pharmacol) (5.7%), Class 4: Social Impairment (2.6%), and Class 5: Pervasive (5.6%). Nearly all persons in the LOC/Pharmacol, Social Impairment, and Pervasive classes met criteria for OUD (98-100%); however, they differed in receipt of past-year treatment for substance use (28%, 28%, 49%, respectively). Age, race, education, insurance status, and criminal activity were also associated with treatment receipt. Conclusions: There were considerable differences in OUD symptom patterns and substance use treatment among individuals who misused opioids. The findings indicate a substantial unmet need for OUD treatment and point to patterns of heterogeneity within OUD that can inform development of treatment programs.

Struggling With Recovery From Opioids: Who Is at Risk During COVID-19?

OBJECTIVES: Individuals in recovery from opioid use disorder (OUD) are vulnerable to the impacts of the COVID-19 pandemic. Recent findings suggest increased relapse risk and overdose linked to COVID-19-related stressors. We aimed to identify individual-level factors associated with COVID-19-related impacts on recovery. METHODS: This observational study (NCT04577144) enrolled 216 participants who previously partook in long-acting buprenorphine subcutaneous injection clinical trials (2015-2017) for OUD. Participants indicated how COVID-19 affected their recovery from substance use. A machine learning approach Classification and Regression Tree analysis examined the association of 28 variables with the impact of COVID-19 on recovery, including demographics, substance use, and psychosocial factors. Ten-fold cross-validation was used to minimize overfitting. RESULTS: Twenty-six percent of the sample reported that COVID-19 had made recovery somewhat or much harder. Past-month opioid use was higher among those who reported that recovery was harder compared with those who did not (51% vs 24%, respectively; P < 0.001). The final classification tree (overall accuracy, 80%) identified the Beck Depression Inventory (BDI-II) as the strongest independent risk factor associated with reporting COVID-19 impact. Individuals with a BDI-II score ≥10 had 6.45 times greater odds of negative impact (95% confidence interval, 3.29-13.30) relative to those who scored <10. Among individuals with higher BDI-II scores, less progress in managing substance use and treatment of OUD within the past 2 to 3 years were also associated with negative impacts. CONCLUSIONS: These findings underscore the importance of monitoring depressive symptoms and perceived progress in managing substance use among those in recovery from OUD, particularly during large-magnitude crises.

Oral buprenorphine utilization, concomitant benzodiazepines and opioid analgesics, and payment source: Trends from 2015 to 2019.

INTRODUCTION: This study describes utilization patterns of oral buprenorphine products indicated for the treatment of opioid use disorder with a focus on patterns consistent with prescribing guidelines and the safe use conditions during induction and maintenance treatment outlined by the Risk Evaluation and Mitigation Strategy (REMS) Program, including trends over time. METHODS: Using an anonymized longitudinal patient-level dataset that captures information on medical and pharmacy claims in the United States (October 1, 2014 through March 31, 2020), buprenorphine prescriptions, days' supply, and daily dose were described overall and stratified by induction (month 1) vs. maintenance (month 2-6) treatment, along with duration of concomitant benzodiazepines or opioid analgesics. RESULTS: Overall, there were 1.5 million buprenorphine treatment episodes initiated between January 1, 2015 to September 30, 2019 (2015: 258,899; 2019: 351,378). Treatment episodes included an average of 6.8 buprenorphine prescriptions (standard deviation [SD] = 6.7), 16.8 days' supply per prescription (SD = 10.5), 94.2 total days' supply per treatment episode (SD = 71.4), and a mean daily dose of 13.6 mg (SD = 6.3), with the number of prescriptions and total days' supply per treatment episode declining over the study period. There was a lower mean number of days' supply per prescription in the first month of treatment compared to months 2-6 (month 1: 15.8 [SD = 11.0]; month 2-6: 19.0 [SD = 10.1]) and daily dose per prescription (month 1: 13.3 mg [SD = 6.4]; months 2-6: 14.3 mg [SD = 6.2]), and a higher mean number of prescriptions per month (month 1: 2.5 per month [SD = 1.7]; months 2-6: 1.8 per month [SD = 1.2]). From 2015 to 2019, there appeared to be a shift in payer mix, with increases in Medicaid/Medicare and declines in cash and commercial insurance. Concomitant benzodiazepine and opioid analgesic use declined over time; in 2019, 16.6 % and 14.3 % of treatment episodes had any concomitant benzodiazepine or opioid analgesic, respectively, and <5 % had chronic (>90 overlapping days) concomitant use (3.0 % and 0.4 %, respectively). CONCLUSIONS: The number of oral buprenorphine treatment episodes increased over the study period, and prescribing was generally consistent with the REMS and other treatment guidelines. There was a decline in concomitant buprenorphine and benzodiazepine or opioid analgesics, and chronic concomitant use was rare.

Long-term recovery from opioid use disorder: recovery subgroups, transition states and their association with substance use, treatment and quality of life.

BACKGROUND AND AIMS: Limited information exists regarding individual subgroups of recovery from opioid use disorder (OUD) following treatment and how these subgroups may relate to recovery trajectories. We used multi-dimensional criteria to identify OUD recovery subgroups and longitudinal transitions across subgroups. DESIGN, SETTING AND PARTICIPANTS: In a national longitudinal observational study in the United States, individuals who previously participated in a clinical trial for subcutaneous buprenorphine injections for treatment of OUD were enrolled and followed for an average of 4.2 years after participation in the clinical trial. MEASUREMENTS: We identified recovery subgroups based on psychosocial outcomes including depression, opioid withdrawal and pain. We compared opioid use, treatment utilization and quality of life among these subgroups. FINDINGS: Three dimensions of the recovery process were identified: depression, opioid withdrawal and pain. Using these three dimensions, participants were classified into four recovery subgroups: high-functioning (minimal depression, mild withdrawal and no/mild pain), pain/physical health (minimal depression, mild withdrawal and moderate pain), depression (moderate depression, mild withdrawal and mild/moderate pain) and low-functioning (moderate/severe withdrawal, moderate depression and moderate/severe pain). Significant differences among subgroups were observed for DSM-5 criteria (P < 0.001) and remission status (P < 0.001), as well as with opioid use (P < 0.001), treatment utilization (P < 0.001) and quality of life domains (physical health, psychological, environment and social relationships; Ps < 0.001, Cohen's fs ≥ 0.62). Recovery subgroup assignments were dynamic, with individuals transitioning across subgroups during the observational period. Moreover, the initial recovery subgroup assignment was minimally predictive of long-term outcomes. CONCLUSIONS: There appear to be four distinct subgroups among individuals in recovery from OUD. Recovery subgroup assignments are dynamic and predictive of contemporaneous, but not long-term, substance use, substance use treatment utilization or quality of life outcomes.

Assessing Motivations for Nonprescribed Buprenorphine Use Among Rural Appalachian Substance Users.

OBJECTIVE: Buprenorphine (Suboxone) is an effective treatment for opioid use disorder (OUD). However, there have been widespread reports of diversion and misuse. This study examined motivations for nonprescribed buprenorphine use among rural residents. METHODS: Eligible participants (N = 200) were at least 18 years old, had used any illegal or prescription drugs to get high, and had ever used nonprescribed buprenorphine. A questionnaire administered by a trained interviewer assessed demographic characteristics, substance use, and motivations for use. RESULTS: Primary motivations for first nonprescribed buprenorphine use included avoiding withdrawal and getting high, while at most recent nonprescribed use, motivations shifted toward maintaining abstinence from other drugs. In adjusted logistic regression analyses, past month use of stimulants decreased odds of nonprescribed buprenorphine use for the purposes of self-treatment by 68% (adjusted odds ratio, 0.26; 95% confidence interval, 0.11-0.61), whereas history of treatment for OUD more than doubled odds of use for self-treatment (adjusted odds ratio, 2.71; 95% confidence interval, 1.11-6.63). CONCLUSIONS: Results indicate that many individuals used buprenorphine without a prescription, motivated largely by behaviors consistent with self-treatment, and diversion of buprenorphine may be driven by these motivations more than desire to get high. While many participants attempted to access treatment, many were still using nonprescribed buprenorphine for self-treatment, and many were dissatisfied with care they had received as part of a treatment program. Thus, increasing quantity of providers may not be adequate to address the opioid epidemic, but particular attention should be paid to providing care targeted to the needs of those with OUD in rural areas.

Recovery from opioid use disorder: A 4-year post-clinical trial outcomes study.

BACKGROUND: Opioid use disorder (OUD) seriously impacts public health in the United States. However, few investigations of long-term outcomes following treatment with medication for OUD exist. Additionally, these studies have prioritized opioid use and treatment utilization outcomes, and a gap in knowledge regarding long-term, multidimensional trajectories of OUD recovery exists. This study investigated a diverse array of outcomes for individuals with OUD at an average of 4.2 years post clinical trial participation. METHODS: Individuals who previously participated in long-acting buprenorphine subcutaneous injection clinical trials (NCT023579011; NCT025100142; NCT02896296) and enrolled in The Remission from Chronic Opioid Use-Studying Environmental and SocioEconomic Factors on Recovery (RECOVER; NCT03604861) Study participated in a follow up assessment (n = 216). Substance use, psychosocial, opioid dependence, and delay discounting outcomes were assessed. Regression analyses were conducted to determine significant associations between psychosocial/opioid dependence variables and both recent opioid use and delay discounting. RESULTS: The majority of participants reported abstinence from opioids since the last RECOVER study assessment (mean 2.26 years; 55%) and in the past 30 days (69%). Participants reported low levels of depression and psychological distress. Positive associations between depression and opioid craving with past 30-day opioid misuse and delay discounting, and negative associations between quality of life and treatment effectiveness with these outcomes were observed. CONCLUSIONS: This study examined longer term OUD recovery outcomes. Participants reported high levels of abstinence from opioids and psychosocial functioning. These encouraging results highlight the multidimensional nature of recovery from OUD, and further support the effectiveness of buprenorphine as an OUD treatment.

Use of non-prescribed buprenorphine in the criminal justice system: Perspectives of individuals recently released from incarceration.

Buprenorphine, an effective treatment for opioid use disorder (OUD), remains underutilized in many U.S. jails and prisons. However, use of non-prescribed (i.e., diverted) buprenorphine has been reported in these settings. The current study examined non-prescribed buprenorphine use experiences in correctional and community contexts. The study conducted face-to-face interviews with 300 adults with OUD/opioid misuse and recent incarceration, recruited in Baltimore, MD, and New York, NY (n = 150 each). Illicit/non-prescribed opioid use during incarceration was reported by 63% of participants; 39% reported non-prescribed buprenorphine. Non-prescribed buprenorphine was considered the most widely available opioid in jails/prisons in both states (81% reported "very" or "somewhat" easy to get). The average price of non-prescribed buprenorphine in jail/prison was ~10× higher than in the community (p < 0.001). Participants were more likely to endorse getting high/mood alteration as reasons for using non-prescribed buprenorphine during incarceration, but tended to ascribe therapeutic motives to use in the community (e.g., self-treatment; p < 0.001). Multivariable logistic regression analyses showed that different individual-level characteristics were associated with history of non-prescribed buprenorphine use during incarceration and in the community. Use of non-prescribed buprenorphine during incarceration was associated with younger age (p = 0.006) and longer incarceration history (p < 0.001), while use of non-prescribed buprenorphine in the community was associated with MD recruitment site (p = 0.001), not being married (p < 0.001), prior buprenorphine treatment experience (p < 0.001), and housing situation (p = 0.01). These findings suggest that different dynamics and demand characteristics underlie the use of non-prescribed buprenorphine in community and incarceration contexts, with implications for efforts to expand OUD treatment in correctional settings.

Exploring nonprescribed use of buprenorphine in the criminal justice system through qualitative interviews among individuals recently released from incarceration.

BACKGROUND: Buprenorphine treatment remains unavailable in many jails and prisons, but use of nonprescribed (i.e., diverted) buprenorphine has been reported in these settings. The purpose of this analysis is to explore the experiences and motivations behind the use of diverted buprenorphine among recently incarcerated individuals. METHODS: Adults with opioid misuse who were recently released from jail or prison (n= 26; 58% male) completed semi-structured qualitative interviews as part of a study focused on buprenorphine diversion in the criminal justice system. Qualitative interviews explored participants' incarceration experiences and opioid use background, knowledge of buprenorphine and other substance use in jails/prisons, personal use of buprenorphine while incarcerated, reasons for using buprenorphine while incarcerated, and knowledge of how buprenorphine is brought into and acquired in jails/prisons. The study recorded and transcribed interviews, and analyzed the narratives for content related to these predetermined thematic areas. RESULTS: Key themes emerging from the interviews surrounding buprenorphine diversion during incarceration included: 1) the perceived high prevalence of diverted buprenorphine in jail/prison settings, 2) how the perception of prevalence is related to buprenorphine sublingual film formulation, 3) adaptive routes of administration related to the high cost of diverted buprenorphine, and 4) reasons individuals who are incarcerated use diverted buprenorphine (to achieve euphoric effects and cope with confinement, in contrast to using for self-treatment/withdrawal management as is done in the community). CONCLUSION: Participants reported widespread availability of diverted buprenorphine in criminal justice facilities, and characterized reasons for its use specific to these contexts. More research is needed to determine the impact of expanding buprenorphine treatment in jails and prisons on inmates' use of diverted buprenorphine, and future research should explore these intersections as treatment initiation opportunities.

Measuring problem prescription opioid use among patients receiving long-term opioid analgesic treatment: development and evaluation of an algorithm for use in EHR and claims data.

Objective: Opioid surveillance in response to the opioid epidemic will benefit from scalable, automated algorithms for identifying patients with clinically documented signs of problem prescription opioid use. Existing algorithms lack accuracy. We sought to develop a high-sensitivity, high-specificity classification algorithm based on widely available structured health data to identify patients receiving chronic extended-release/long-acting (ER/LA) therapy with evidence of problem use to support subsequent epidemiologic investigations. Methods: Outpatient medical records of a probability sample of 2,000 Kaiser Permanente Washington patients receiving ≥60 days' supply of ER/LA opioids in a 90-day period from 1 January 2006 to 30 June 2015 were manually reviewed to determine the presence of clinically documented signs of problem use and used as a reference standard for algorithm development. Using 1,400 patients as training data, we constructed candidate predictors from demographic, enrollment, encounter, diagnosis, procedure, and medication data extracted from medical claims records or the equivalent from electronic health record (EHR) systems, and we used adaptive least absolute shrinkage and selection operator (LASSO) regression to develop a model. We evaluated this model in a comparable 600-patient validation set. We compared this model to ICD-9 diagnostic codes for opioid abuse, dependence, and poisoning. This study was registered with ClinicalTrials.gov as study NCT02667262 on 28 January 2016. Results: We operationalized 1,126 potential predictors characterizing patient demographics, procedures, diagnoses, timing, dose, and location of medication dispensing. The final model incorporating 53 predictors had a sensitivity of 0.582 at positive predictive value (PPV) of 0.572. ICD-9 codes for opioid abuse, dependence, and poisoning had a sensitivity of 0.390 at PPV of 0.599 in the same cohort. Conclusions: Scalable methods using widely available structured EHR/claims data to accurately identify problem opioid use among patients receiving long-term ER/LA therapy were unsuccessful. This approach may be useful for identifying patients needing clinical evaluation.

Postmarketing studies program to assess the risks and benefits of long-term use of extended-release/long-acting opioids among chronic pain patients.

Background: Among patients with chronic pain using long-term opioid therapy, the incidence of opioid abuse, addiction, overdose, and associated death are not well quantified. The range of estimates for these adverse outcomes varies drastically and may depend on how they are measured (i.e. study definitions of outcomes) and on patient characteristics and opioid-use factors (e.g. regimen, daily dose).Methods: Based on a review of the literature, the US Food and Drug Administration (FDA) required companies that manufacture and sell extended-release/long-acting (ER/LA) opioids conduct as a postmarketing requirement (PMR) a series of observational studies to estimate the rates of treatment-emergent misuse, abuse, addiction, overdose, and death using validated measures. The companies formed a consortium, the Opioid PMR Consortium (OPC), to conduct the studies.Results: The FDA initially requested four observational studies (a cohort study, a questionnaire validation study, a code validation study, and a doctor-shopping validation study), but in order to achieve the FDA's goals of the 4 studies, OPC and FDA agreed to 10 observational studies (a prospective cohort study, a retrospective database cohort study, three questionnaire validation studies, two code validation studies, and three doctor-shopping validation studies). The studies are continuing through 2020.Conclusions: A series of 10 observational studies was or are being conducted in response to the FDA's postmarketing requirement. All studies have been feasible to conduct, although a validated algorithm for measuring abuse and addiction in databases was not successful.

Using natural language processing of clinical text to enhance identification of opioid-related overdoses in electronic health records data.

PURPOSE: To enhance automated methods for accurately identifying opioid-related overdoses and classifying types of overdose using electronic health record (EHR) databases. METHODS: We developed a natural language processing (NLP) software application to code clinical text documentation of overdose, including identification of intention for self-harm, substances involved, substance abuse, and error in medication usage. Using datasets balanced with cases of suspected overdose and records of individuals at elevated risk for overdose, we developed and validated the application using Kaiser Permanente Northwest data, then tested portability of the application using Kaiser Permanente Washington data. Datasets were chart-reviewed to provide a gold standard for comparison and evaluation of the automated method. RESULTS: The method performed well in identifying overdose (sensitivity = 0.80, specificity = 0.93), intentional overdose (sensitivity = 0.81, specificity = 0.98), and involvement of opioids (excluding heroin, sensitivity = 0.72, specificity = 0.96) and heroin (sensitivity = 0.84, specificity = 1.0). The method performed poorly at identifying adverse drug reactions and overdose due to patient error and fairly at identifying substance abuse in opioid-related unintentional overdose (sensitivity = 0.67, specificity = 0.96). Evaluation using validation datasets yielded significant reductions, in specificity and negative predictive values only, for many classifications mentioned above. However, these measures remained above 0.80, thus, performance observed during development was largely maintained during validation. Similar results were obtained when evaluating portability, although there was a significant reduction in sensitivity for unintentional overdose that was attributed to missing text clinical notes in the database. CONCLUSIONS: Methods that process text clinical notes show promise for improving accuracy and fidelity at identifying and classifying overdoses according to type using EHR data.

Development of an algorithm to identify inpatient opioid-related overdoses and oversedation using electronic data.

PURPOSE: To facilitate surveillance and evaluate interventions addressing opioid-related overdoses, algorithms are needed for use in large health care databases to identify and differentiate community-occurring opioid-related overdoses from inpatient-occurring opioid-related overdose/oversedation. METHODS: Data were from Kaiser Permanente Northwest (KPNW), a large integrated health plan. We iteratively developed and evaluated an algorithm for electronically identifying inpatient overdose/oversedation in KPNW hospitals from 1 January 2008 to 31 December 2014. Chart audits assessed accuracy; data sources included administrative and clinical records. RESULTS: The best-performing algorithm used these rules: (1) Include events with opioids administered in an inpatient setting (including emergency department/urgent care) followed by naloxone administration within 275 hours of continuous inpatient stay; (2) exclude events with electroconvulsive therapy procedure codes; and (3) exclude events in which an opioid was administered prior to hospital discharge and followed by readmission with subsequent naloxone administration. Using this algorithm, we identified 870 suspect inpatient overdose/oversedation events and chart audited a random sample of 235. Of the random sample, 185 (78.7%) were deemed overdoses/oversedation, 37 (15.5%) were not, and 13 (5.5%) were possible cases. The number of hours between time of opioid and naloxone administration did not affect algorithm accuracy. When "possible" overdoses/oversedations were included with confirmed events, overall positive predictive value (PPV) was very good (PPV = 84.0%). Additionally, PPV was reasonable when evaluated specifically for hospital stays with emergency/urgent care admissions (PPV = 77.0%) and excellent for elective surgery admissions (PPV = 97.0%). CONCLUSIONS: Algorithm performance was reasonable for identifying inpatient overdose/oversedation with best performance among elective surgery patients.

Identifying and classifying opioid-related overdoses: A validation study.

PURPOSE: The study aims to develop and validate algorithms to identify and classify opioid overdoses using claims and other coded data, and clinical text extracted from electronic health records using natural language processing (NLP). METHODS: Primary data were derived from Kaiser Permanente Northwest (2008-2014), an integrated health care system (~n > 475 000 unique individuals per year). Data included International Classification of Diseases, Ninth Revision (ICD-9) codes for nonfatal diagnoses, International Classification of Diseases, Tenth Revision (ICD-10) codes for fatal events, clinical notes, and prescription medication records. We assessed sensitivity, specificity, positive predictive value, and negative predictive value for algorithms relative to medical chart review and conducted assessments of algorithm portability in Kaiser Permanente Washington, Tennessee State Medicaid, and Optum. RESULTS: Code-based algorithm performance was excellent for opioid-related overdoses (sensitivity = 97.2%, specificity = 84.6%) and classification of heroin-involved overdoses (sensitivity = 91.8%, specificity = 99.0%). Performance was acceptable for code-based suicide/suicide attempt classifications (sensitivity = 70.7%, specificity = 90.5%); sensitivity improved with NLP (sensitivity = 78.7%, specificity = 91.0%). Performance was acceptable for the code-based substance abuse-involved classification (sensitivity = 75.3%, specificity = 79.5%); sensitivity improved with the NLP-enhanced algorithm (sensitivity = 80.5%, specificity = 76.3%). The opioid-related overdose algorithm performed well across portability assessment sites, with sensitivity greater than 96% and specificity greater than 84%. Cross-site sensitivity for heroin-involved overdose was greater than 87%, specificity greater than or equal to 99%. CONCLUSIONS: Code-based algorithms developed to detect opioid-related overdoses and classify them according to heroin involvement perform well. Algorithms for classifying suicides/attempts and abuse-related opioid overdoses perform adequately for use for research, particularly given the complexity of classifying such overdoses. The NLP-enhanced algorithms for suicides/suicide attempts and abuse-related overdoses perform significantly better than code-based algorithms and are appropriate for use in settings that have data and capacity to use NLP.

Abuse of reformulated OxyContin: Updated findings from a sentinel surveillance sample of individuals assessed for substance use disorder.

OBJECTIVE: To examine abuse prevalence for OxyContin and comparator opioids over a 6-year period prior to and following market entry of reformulated OxyContin and assess consistency in abuse across treatment settings and geographic regions. DESIGN: An observational study examining longitudinal changes using cross-sectional data from treatment centers for substance use disorder. SETTING: A total of 874 facilities in 39 states in the United States within the National Addictions Vigilance Intervention and Prevention Program (NAVIPPRO®) surveillance system. PARTICIPANTS: Adults (72,060) assessed for drug problems using the Addiction Severity Index-Multimedia Version (ASI-MV®) from January 2009 through December 2015 who abused prescription opioids. MAIN OUTCOME MEASURE(S): Percent change in past 30-day abuse. RESULTS: OxyContin had significantly lower abuse 5 years after reformulation compared to levels for original OxyContin. Consistency of magnitude in OxyContin abuse reductions across geographic regions, ranging from 41 to 52 percent with differences in abuse reductions in treatment setting categories occurred. Changes in geographic region and treatment settings across study years did not bias the estimate of lower OxyContin abuse through confounding. CONCLUSION: In the postmarket setting, limitations and methodologic challenges in abuse measurement exist and it is difficult to isolate singular impacts of any one intervention given the complexity of prescription opioid abuse. Expectations for a reasonable threshold of abuse for any one ADF product or ADF opioids as a class are still uncertain and undefined. A significant decline in abuse prevalence of reformulated OxyContin was observed 5 years after its reformulation among this treatment sample of individuals assessed for substance use disorder that was lower historically for the original formulation of this product.

A retrospective cohort study of long-term immediate-release hydrocodone/acetaminophen use and acetaminophen dosing above the Food and Drug Administration recommended maximum daily limit among commercially insured individuals in the United States (2008-2013).

UNLABELLED: Immediate-release (IR) hydrocodone/acetaminophen is the most prescribed opioid in the United States; however, patterns of use, including long-term treatment and dose, are not well described. Duration of use, including the percentage of patients on long-term treatment (>90 days of continuous use), was assessed for patients newly prescribed IR hydrocodone/acetaminophen compared to other opioid analgesics in a national commercial insurance database (January 2008-September 2013). Though only a small percentage of IR hydrocodone/acetaminophen patients continued treatment long-term (1.7%), the number was large (104,839) and was nearly 5 times the number receiving extended-release (ER) morphine (n = 22,338) and nearly 4 times the number receiving ER oxycodone (n = 26,946) long-term. Using a less conservative allowable gap in treatment increased the number of patients meeting the criteria for long-term use (approximately 160,000 for IR hydrocodone/acetaminophen vs <30,000 for ER morphine and ER oxycodone). Most patients meeting these criteria received IR hydrocodone doses between >20 and ≤60 mg/d (n = 56,220, 53.6%) in month 4; 5.5% (n = 5,743) received doses >60 mg/d. Moreover, approximately 15% of IR hydrocodone/acetaminophen patients (n > 900,000) were prescribed total daily acetaminophen doses exceeding 4 g (the limit recommended by the U.S. Food and Drug Administration) at their initial IR hydrocodone/acetaminophen prescription or any time during therapy. PERSPECTIVE: Although most patients were prescribed IR hydrocodone/acetaminophen for acute pain, the number of patients prescribed long-term therapy exceeds the number of patients prescribed ER opioids. It is important to consider the benefits and risks inherent with long-term opioid therapy, whether with IR or ER opioids, to ensure safe use of these products.

The impact of a reformulation of extended-release oxycodone designed to deter abuse in a sample of prescription opioid abusers.

BACKGROUND: Prescription opioid abuse is a significant public health concern that requires strategies to reduce its impact, including development of abuse deterrent formulations. OxyContin, an extended-release oxycodone (ERO) formulation, has been widely abused. This study assessed the effects of reformulated ERO, designed to be more difficult to manipulate for purposes of intranasal and intravenous abuse, on patterns of opioid abuse among a sample of individuals from rural Appalachia with a history of ERO abuse. METHODS: Structured interviews assessing opioid abuse (past 30-day abuse and retrospectively reported abuse prior to the reformulation in August 2010) were completed by 189 individuals between December 2010 and September 2011. RESULTS: The past 30-day prevalence and frequency of reformulated ERO abuse through any route (33%, 1.9 days/month), snorting (5%, 0.2 days/month), and injecting (0.5%, <0.1 days/month) were low and infrequent compared to that of IR oxycodone (any route: 96%, 19.5 days/month; snorting: 70%, 10.3 days/month; injecting: 51%, 10.5 days/month) and retrospectively reported abuse of original ERO in August 2010 (any route: 74%, 13.4 days/month; snorting: 39%, 6.0 days/month; injecting: 41%, 8.6 days/month). After the reformulation, the prevalence of original ERO abuse significantly declined while abuse of reformulated ERO remained steadily low. Heroin abuse was rare in this sample. CONCLUSIONS: In this sample, abuse of reformulated ERO was low, and lower than abuse of original ERO retrospectively and IR oxycodone concurrently, particularly through injecting and snorting routes of administration. There was no evidence to suggest that reformulated ERO became a substitute for original ERO.

Patterns of atypical antipsychotic therapy use in adults with bipolar I disorder in the USA.

OBJECTIVES: This study aims to describe the utilization patterns of atypical antipsychotics (AA) among insured patients with bipolar I disorder in the USA. METHODS: We studied patients with bipolar I disorder who newly initiated an oral AA between 2002 and 2008. Utilization measures included adherence [medication possession ratio (MPR) ≥80%], persistence (gaps ≤15 days between refills and an absence of ≥30 days of continuous concomitant non-index AA use), non-compliance (16-29 day gaps with no evidence of switch/augmentation), and discontinuation of the index AA (≥30 days without index AA, no evidence of switch/augmentation). RESULTS: The study included 16 807 patients: mean age 43.3 years, 67.7% female. Overall, adherence to the index AA was low (8.3%; mean MPR = 0.2). Only 10.5% of the patients were persistent to index AA, another 13.6% were non-compliant, and 63.4% discontinued index AA with an average time to discontinuation of 66 days. A majority (69.5%) of the discontinued patients did not resume any antipsychotic therapy. Results were similar across insurance types and index AA. CONCLUSION: Adherence to and persistence with AA treatment were low in new users with bipolar I disorder. Most patients discontinued the index AA and did not restart any antipsychotic treatment. Future study should distinguish physician-directed discontinuation versus patient non-adherence.

Pharmacokinetic comparison of two nicotine transdermal systems, a 21-mg/24-hour patch and a 25-mg/16-hour patch: a randomized, open-label, single-dose, two-way crossover study in adult smokers.

BACKGROUND: A comparison of the 21-mg NiQuitin patch with other marketed nicotine patches reported significant differences in pharmacokinetic profiles, even among patches of the identical labeled dose strength. The 25-mg Nicorette Invisi patch became available in the United Kingdom at the end of 2008. No published studies have directly compared the pharmacokinetic profile of this new patch with that of the 21-mg NiQuitin patch. OBJECTIVES: This study was conducted to compare the single-dose pharmacokinetics of the 21-mg/24-hour patch and the 25-mg/16-hour patch. To determine whether any pharmacokinetic differences might be related to differences in wear time, a post hoc exploratory analysis evaluated the nicotine delivery profiles of the patches under the assumption that the 21-mg patch was removed after 16 rather than 24 hours. METHODS: This was a single-center, randomized, open-label, single-dose, 2-way crossover study in healthy adults who smoked >10 cigarettes per day in the 6 months before the study. Eligible subjects were housed at the study center for 2 baseline and 2 treatment sessions; no smoking was permitted during the baseline or treatment sessions. Subjects were allocated to receive either the 21-mg patch (removed after 24 hours) or the 25-mg patch (removed after 16 hours) during the first treatment session, after which they crossed over to the alternative sequence in the second treatment session. Blood samples were obtained at predetermined time points before and after patch application. The primary pharmacokinetic parameter was the AUC(0-infinity), an indication of total nicotine exposure. Secondary pharmacokinetic parameters included AUC(0-t), C(max), and T(max). Post hoc exploratory parameters were the AUC(0-16) and the AUC(0-infinity) assuming a 16-hour application time for the 21-mg patch. The differences in AUC(0-infinity), AUC(0-t), Cmax, AUC(0-16), and AUC(0-infinity) assuming a 16-hour application time for the 21-mg patch were considered significant if the lower limit of the 90% CI for the geometric mean ratio (21 mg:25 mg) was >100%. T(max) values were compared using a signed-rank test. Adverse events were elicited using a standard open-ended question on each day of confinement; spontaneously reported events were also captured. The topical effects of the patch (erythema; edema; extent of erythema/papules/pustules; self-reported pruritus) were assessed by study staff before patch application and 1 and 8 hours after patch application using a 4-point rating scale; any topical effects were recorded as adverse events. RESULTS: Fifty otherwise healthy smokers (29 men, 21 women) were enrolled; 47 (94%) were white. Their mean (SD) age was 31.5 (9.57) years (range, 20-53 years), mean weight was 70.24 (9.56) kg (range, 51.0-95.9 kg), and mean height was 173.0 (8.02) cm (range, 156-194 cm). Subjects reported smoking between 11 and 40 cigarettes per day before the study. The AUC(0-infinity) was significantly higher for the 21-mg patch worn for 24 hours than for the 25-mg patch worn for 16 hours (382.36 vs 243.69 ng/mL . h, respectively; geometric mean ratio: 156.90%; 90% CI, 148.10%-166.23%; P < 0.001). T(max) was reached significantly sooner with the 21-mg patch than with the 25-mg patch (6.0 vs 12.0 hours; P < 0.001). C(max) was significantly higher for the 21-mg patch compared with the 25-mg patch (18.34 vs 16.56 ng/mL; geometric mean ratio: 110.72%; 90% CI, 104.82%-116.94%; P < 0.01). The exploratory analyses suggested that the 21-mg patch applied for 16 hours may provide greater total nicotine exposure than the 25-mg patch applied for 16 hours. Although most subjects reported adverse events (75.0% with the 21-mg patch, 89.8% with the 25-mg patch), the majority of these events were mild. CONCLUSIONS: In this single-dose study in adult smokers, the 21-mg patch was associated with significantly greater nicotine exposure compared with the 25-mg patch. The 21-mg patch provided a maximal nicotine concentration faster than did the 25-mg patch.

The adverse effects of comorbid pain on depression outcomes in primary care patients: results from the ARTIST trial.

OBJECTIVES: To explore the effect of pain symptoms and improvements in pain on depression outcomes. METHODS: We analyzed data from A Randomized Trial Investigating SSRI Treatment (ARTIST), a randomized longitudinal effectiveness study comparing selective serotonin reuptake inhibitors (SSRIs) for the treatment of depression in primary care (n = 573). Depression outcome at month 6, defined as remission, partial response, and nonresponse using the Symptom Checklist-20, was the primary outcome. RESULTS: Compared to patients with no pain at baseline, those with severe pain were less likely to achieve remission (OR = 0.11, 95% CI 0.05-0.25) and partial response (OR = 0.24, 95% CI 0.10-0.59) vs nonresponse. Patients with moderate pain were less likely to achieve remission vs nonresponse (OR = 0.25, 95% CI 0.13-0.48). Patients with early improvement in pain were more likely to achieve remission (OR = 1.90, 95% CI 1.03-3.49). Accounting for missing data with last observation carried forward or multiple imputation yielded similar results. CONCLUSION: Pain symptoms are present in the majority of depressed primary care patients beginning antidepressant therapy. Pain symptoms are associated with worse depression outcomes, while improvement in pain is associated with significantly better depression outcomes. Attention to comorbid pain may be important in enhancing depression care.