Matching study design to prescribing intention: The prevalent new-user design for studying abuse-deterrent formulations of opioids.

PURPOSE: In drug studies, research designs requiring no prior exposure to certain drug classes may restrict important populations. Since abuse-deterrent formulations (ADF) of opioids are routinely prescribed after other opioids, choice of study design, identification of appropriate comparators, and addressing confounding by "indication" are important considerations in ADF post-marketing studies. METHODS: In a retrospective cohort study using claims data (2006-2018) from a North Carolina private insurer [NC claims] and Merative MarketScan [MarketScan], we identified patients (18-64 years old) initiating ADF or non-ADF extended-release/long-acting (ER/LA) opioids. We compared patient characteristics and described opioid treatment history between treatment groups, classifying patients as traditional (no opioid claims during prior six-month washout period) or prevalent new users. RESULTS: We identified 8415 (NC claims) and 147 978 (MarketScan) ADF, and 10 114 (NC claims) and 232 028 (MarketScan) non-ADF ER/LA opioid initiators. Most had prior opioid exposure (ranging 64%-74%), and key clinical differences included higher prevalence of recent acute or chronic pain and surgery among patients initiating ADFs compared to non-ADF ER/LA initiators. Concurrent immediate-release opioid prescriptions at initiation were more common in prevalent new users than traditional new users. CONCLUSIONS: Careful consideration of the study design, comparator choice, and confounding by "indication" is crucial when examining ADF opioid use-related outcomes.

Prescribing Characteristics of Octreotide Immediate-Release and Long-Acting Release in Patients with Neuroendocrine Tumors.

BACKGROUND: Treatment recommendations for patients with neuroendocrine tumors (NETs) include the use of octreotide long-acting release (LAR) for long-term therapy and immediate-release (IR) as rescue therapy to control the breakthrough symptoms of carcinoid syndrome (CS). High doses of LAR are commonly used in clinical practice. This study aimed to evaluate the real-world utilization of LAR and preceding IR use at the prescription and patient levels. METHODS: We used an administrative claims database (2009-2018) containing privately insured enrollees. We calculated the normalized LAR dose from pharmacy claims and the initial mean IR daily dose at the prescription level. At the patient level, we conducted a retrospective cohort study that included patients continuously enrolled with ≥1 pharmacy claim of LAR and evaluated the frequency and the clinical reason for dose escalation of LAR. The definition of the above-label maximum dose of LAR was ≥30 mg/4 weeks. RESULTS: Nineteen percent of LAR prescriptions had an above-label maximum dose. Only 7% of LAR prescriptions had preceding IR use. There were 386 patients with NETs or CS vs. 570 with an unknown diagnosis. Comparing patients with NETs or CS to those with an unknown diagnosis, 22.3% vs. 11.0 % experienced dose escalations and 29.0% vs. 26.6% had IR use before dose escalation, respectively. LAR dose escalation occurred in 50.9% vs. 39.2% for symptom control, 12.3% vs. 7.1% for tumor progression control, and 16.6% vs. 6.0% for both reasons in NETs/CS and unknown groups, respectively. CONCLUSION: Octreotide LAR dosing above the label-maximum dose is common and IR rescue dosing appears to be underutilized.

Substance use disorders and social determinants of health from electronic medical records obtained during Kentucky's "triple wave".

Social determinants of health (SDOH) play a critical role in the risk of harmful drug use. Examining SDOH as a means of differentiating populations with multiple co-occurring substance use disorders (SUDs) is particularly salient in the era of prevalent opioid and stimulant use known as the "Third Wave". This study uses electronic medical records (EMRs) from a safety net hospital system from 14,032 patients in Kentucky from 2017 to 2019 in order to 1) define three types of SUD cohorts with shared/unique risk factors, 2) identify patients with unstable housing using novel methods for EMRs and 3) link patients to their residential neighborhood to obtain quantitative perspective on social vulnerability. We identified patients in three cohorts with statistically significant unique risk factors that included race, biological sex, insurance type, smoking status, and urban/rural residential location. Adjusting for these variables, we found a statistically significant, increasing risk gradient for patients experiencing unstable housing by cohort type: opioid-only (n = 7385, reference), stimulant-only (n = 4794, odds ratio (aOR) 1.86 95 % confidence interval (CI): 1.66-2.09), and co-diagnosed (n = 1853, aOR = 2.75, 95 % CI: 2.39 to 3.16). At the neighborhood-level, we used 8 different measures of social vulnerability and found that, for the most part, increasing proportions of patients with stimulant use living in a census tract was associated with more social vulnerability. Our study identifies potentially modifiable factors that can be tailored by substance type and demonstrates robust use of EMRs to meet national goals of enhancing research on social determinants of health.

Dosing profiles of concurrent opioid and benzodiazepine use associated with overdose risk among US Medicare beneficiaries: group-based multi-trajectory models.

BACKGROUND AND AIMS: One-third of opioid (OPI) overdose deaths involve concurrent benzodiazepine (BZD) use. Little is known about concurrent opioid and benzodiazepine use (OPI-BZD) most associated with overdose risk. We aimed to examine associations between OPI-BZD dose and duration trajectories, and subsequent OPI or BZD overdose in US Medicare. DESIGN: Retrospective cohort study. SETTING: US Medicare. PARTICIPANTS: Using a 5% national Medicare data sample (2013-16) of fee-for-service beneficiaries without cancer initiating OPI prescriptions, we identified 37 879 beneficiaries (age ≥ 65 = 59.3%, female = 71.9%, white = 87.6%, having OPI overdose = 0.3%). MEASUREMENTS: During the 6 months following OPI initiation (i.e. trajectory period), we identified OPI-BZD dose and duration patterns using group-based multi-trajectory models, based on average daily morphine milligram equivalents (MME) for OPIs and diazepam milligram equivalents (DME) for BZDs. To label dose levels in each trajectory, we defined OPI use as very low (< 25 MME), low (25-50 MME), moderate (51-90 MME), high (91-150 MME) and very high (>150 MME) dose. Similarly, we defined BZD use as very low (< 10 DME), low (10-20 DME), moderate (21-40 DME), high (41-60 DME) and very high (> 60 DME) dose. Our primary analysis was to estimate the risk of time to first hospital or emergency department visit for OPI overdose within 6 months following the trajectory period using inverse probability of treatment-weighted Cox proportional hazards models. FINDINGS: We identified nine distinct OPI-BZD trajectories: group A: very low OPI (early discontinuation)-very low declining BZD (n = 10 598; 28.0% of the cohort); B: very low OPI (early discontinuation)-very low stable BZD (n = 4923; 13.0%); C: very low OPI (early discontinuation)-medium BZD (n = 4997; 13.2%); D: low OPI-low BZD (n = 5083; 13.4%); E: low OPI-high BZD (n = 3906; 10.3%); F: medium OPI-low BZD (n = 3948; 10.4%); G: very high OPI-high BZD (n = 1371; 3.6%); H: very high OPI-very high BZD (n = 957; 2.5%); and I: very high OPI-low BZD (n = 2096; 5.5%). Compared with group A, five trajectories (32.3% of the study cohort) were associated with increased 6-month OPI overdose risks: E: low OPI-high BZD [hazard ratio (HR) = 3.27, 95% confidence interval (CI) = 1.61-6.63]; F: medium OPI-low BZD (HR = 4.04, 95% CI = 2.06-7.95); G: very high OPI-high BZD (HR = 6.98, 95% CI = 3.11-15.64); H: very high OPI-very high BZD (HR = 4.41, 95% CI = 1.51-12.85); and I: very high OPI-low BZD (HR = 6.50, 95% CI = 3.15-13.42). CONCLUSIONS: Patterns of concurrent opioid and benzodiazepine use most associated with overdose risk among fee-for-service US Medicare beneficiaries initiating opioid prescriptions include very high-dose opioid use (MME > 150), high-dose benzodiazepine use (DME > 40) or medium-dose opioid with low-dose benzodiazepine use.

Predictors of chronic opioid therapy in Medicaid beneficiaries with HIV who initiated antiretroviral therapy.

The factors associated with chronic opioid therapy (COT) in patients with HIV is understudied. Using Medicaid data (2002-2009), this retrospective cohort study examines COT in beneficiaries with HIV who initiated standard combination anti-retroviral therapy (cART). We used generalized estimating equations on logistic regression models with backward selection to identify significant predictors of COT initiation. COT was initiated among 1014 out of 9615 beneficiaries with HIV (male: 10.4%; female: 10.7%). Those with older age, any malignancy, Hepatitis C infection, back pain, arthritis, neuropathy pain, substance use disorder, polypharmacy, (use of) benzodiazepines, gabapentinoids, antidepressants, and prior opioid therapies were positively associated with COT. In sex-stratified analyses, multiple predictors were shared between male and female beneficiaries; however, chronic obstructive pulmonary disease, liver disease, any malignancy, and antipsychotic therapy were unique to female beneficiaries. Comorbidities and polypharmacy were important predictors of COT in Medicaid beneficiaries with HIV who initiated cART.

"Doctor and pharmacy shopping": A fading signal for prescription opioid use monitoring?

BACKGROUND: The term "doctor and pharmacy shopping" colloquially describes patients with high multiple provider episodes (MPEs)-a threshold count of distinct prescribers and/or pharmacies involved in prescription fulfillment. Opioid-related MPEs are implicated in the global opioid crisis and heavily monitored by government databases such as U.S. state prescription drug monitoring programs (PDMPs). We applied a widely-used MPE definition to examine U.S. trends from a large, commercially-insured population from 2010 to 2017. Further, we examined the proportion of enrollees identified as "doctor shoppers" with evidence of a cancer diagnosis to examine the risk of false positives. METHODS: Using a large, commercially-insured population, we identified patients with opioid-related MPEs: opioid prescriptions (Schedule II-V, no buprenorphine) filled from ≥5 prescribers AND ≥ 5 pharmacies within the past 90 days ("5x5x90d"). Quarterly rates per 100,000 enrollees (two specifications) were calculated between 2010 and 2017. We examined the trend in a recently published all-payer, 7 state cohort from the U.S. Centers for Disease Control and Prevention for comparison. Cancer-related ICD-9/10-CM codes were used. RESULTS: Quarterly MPE rates declined by approximately 73 % from 18.2-4.9 per 100,000 enrollee population with controlled substance prescriptions. In 2017, nearly one fifth of these commercially-insured enrollees identified by the 5x5x90d algorithm were diagnosed with cancer. Approximately 8% of this sample included patients with ≥ 1 buprenorphine prescriptions. CONCLUSIONS: Opioid "shopping" flags are a long-standing but rapidly fading PDMP signal. To avoid unintended consequences, such as identifying legitimate medical encounters requiring high healthcare utilization or opioid treatment, while maintaining vigilance, more nuanced and sophisticated approaches are needed.

Factors associated with opioid prescriptions among women proximal to pregnancy in the United States.

BACKGROUND: Pregnant women are a vulnerable population exposed to opioids in the United States. OBJECTIVE: To examine trends and factors associated with opioid prescribing to women proximal to pregnancy. METHODS: The 2011 to 2015 Medical Expenditure Panel Survey (MEPS) was used to identify participants (n = 3020) with self-reported pregnancy or pregnancy-relevant events aged between 18 and 44 years old. To investigate factors associated with opioid prescriptions, we categorized participants into two subgroups: having one or more opioid prescription or having none during the observational period. We used survey multivariable logistic regression to identify factors associated with opioid prescribing accounting for the complex survey design in MEPS. RESULTS: From 2011 to 2015, the prevalence of opioid prescribing among study participants was 31%. Opioids were more likely to be prescribed to women who had psychiatric conditions (odds ratio, 1,76, 95%CI: 1.27-2.44, p < 0.001). Other significant factors included being non-Hispanic white or black, living in the South, active tobacco users, and those with lower Physical Component Summary Scores. CONCLUSION: Receipt of an opioid prescription in the perinatal period is associated with maternal psychiatric disorders in the United States. Study findings add new data to the literature on opioid use among pregnant women and provide evidence for healthcare providers and policy makers to tailor treatment and educational programs to avoid opioid overuse among pregnant women.

Recreational Cannabis Legalization and Opioid-Related Deaths in Colorado, 2000-2015.

OBJECTIVES: To examine the association between Colorado's legalization of recreational cannabis use and opioid-related deaths. METHODS: We used an interrupted time-series design (2000-2015) to compare changes in level and slope of monthly opioid-related deaths before and after Colorado stores began selling recreational cannabis. We also describe the percent change in opioid-related deaths by comparing the unadjusted model-smoothed number of deaths at the end of follow-up with the number of deaths just prior to legalization. RESULTS: Colorado's legalization of recreational cannabis sales and use resulted in a 0.7 deaths per month (b = -0.68; 95% confidence interval = -1.34, -0.03) reduction in opioid-related deaths. This reduction represents a reversal of the upward trend in opioid-related deaths in Colorado. CONCLUSIONS: Legalization of cannabis in Colorado was associated with short-term reductions in opioid-related deaths. As additional data become available, research should replicate these analyses in other states with legal recreational cannabis.

Increases in Fentanyl-Related Overdose Deaths - Florida and Ohio, 2013-2015.

In March and October 2015, the Drug Enforcement Administration (DEA) and CDC issued nationwide alerts identifying fentanyl, particularly illicitly manufactured fentanyl (IMF), as a threat to public health and safety (1,2). IMF is pharmacologically similar to pharmaceutical fentanyl (PF), but is unlawfully produced in clandestine laboratories, obtained via illicit drug markets, and includes fentanyl analogs. Fentanyl is a synthetic opioid 50-100 times more potent than morphine and approved for the management of surgical/postoperative pain, severe chronic pain, and breakthrough cancer pain.* DEA's National Forensic Laboratory Information System (NFLIS) collects drug identification results from drug cases analyzed by federal, state, and local forensic laboratories throughout the United States.(†) In 2014, 80% of fentanyl submissions (i.e., drug products obtained by law enforcement that tested positive for fentanyl) in NFLIS were identified from 10 states, including Florida and Ohio (2), and seven of these 10 states reported sharp increases in fentanyl-related overdose deaths (fentanyl deaths) (3). This report presents findings of increased fentanyl deaths during 2013-2015 from investigations conducted by the University of Florida and the Ohio Department of Public Health, in collaboration with CDC. Analyses examined the association between trends in fentanyl-related law enforcement submissions and fentanyl deaths and describes groups at risk for fentanyl death using medical examiner and coroner reports. The marked increases in fentanyl death in Florida and Ohio during 2013-2015 were closely associated with parallel increases in fentanyl submissions, with the largest impact on persons who use heroin, consistent with reports that IMF is commonly mixed with or sold as heroin (1,4). In Ohio, circumstances associated with fentanyl deaths included a current diagnosed mental health disorder(§) and recent release from an institution such as a jail, rehabilitation facility, or hospital.

Driving after drinking among young adults of different race/ethnicities in the United States: unique risk factors in early adolescence?

PURPOSE: National guidelines for alcohol screening and brief interventions advise practitioners to consider age, drinking frequency, and context to identify at-risk youth. The purpose of this study was to identify the contextual risk and protective factors in high school-aged adolescents associated with future driving after drinking (Drinking Under the Influence [DUI] at age 21) by race/ethnicity. METHODS: Data included 10,271 adolescents (67% white, 12% Hispanic, 16% black, 3.6% Asian; 49% Male) who participated in the National Longitudinal Study of Adolescent Health (Waves I, II, and III) from 1995 to 2001. A lagged panel design and survey logistic regression was used to examine the association between multiple contextual factors (e.g., demographics, parents, peers, social context) during adolescence and self-reported DUI in young adulthood. RESULTS: As expected, the likelihood of DUI was higher among whites followed by Hispanics, Asians, and blacks in all models. Perception of easy home access to alcohol increased risk for future DUI for whites (OR: 1.25 CI: 1.04-1.49), Hispanics (OR: 2.02 CI: 1.29-3.16), and Asians (OR: 1.90 CI: 1.13-3.22), but not for black youth. Drinking frequency and prior DUI were not risk factors for Hispanics. Risk-taking attitudes, marijuana use, and religious affiliation were risk factors for whites only. CONCLUSIONS: Findings suggest that in addition to screening for drinking behaviors, brief interventions and prevention efforts should assess perceived home access to alcohol and other race-specific factors to reduce alcohol-related injuries and harm.