Suicide-specific mortality among patients with treatment-resistant major depressive disorder, major depressive disorder with prior suicidal ideation or suicide attempts, or major depressive disorder alone.

BACKGROUND: The impact of treatment-resistant depression (TRD) or prior suicidal ideation/suicide attempt (SI/SA) on mortality by suicide among patients with major depressive disorder (MDD) is not well known. This retrospective, observational, descriptive cohort study characterized real-world rates of suicide-specific mortality among patients with MDD with or without TRD or SI/SA. METHODS: Adult patients with MDD among commercially insured and Medicare enrollees in Optum Research Database were included and assigned to three cohorts: those with treatment-resistant MDD (TRD), those with MDD and SI/SA (MDD+SI/SA), and those with MDD without TRD or SI/SA (MDD alone). Suicide-specific mortality was obtained from the National Death Index. The effects of demographic characteristics and SI/SA in the year prior to the end of observation on suicide-specific mortality were assessed. RESULTS: For the 139,753 TRD, 85,602 MDD+SI/SA, and 572,098 MDD alone cohort patients, mean age ranged from 55 to 59 years and the majority were female. At baseline, anxiety disorders were present in 53.92%, 44.11%, and 21.72% of patients with TRD, MDD+SI/SA, and MDD alone, respectively. Suicide-mortality rates in the three cohorts were 0.14/100 person-years for TRD, 0.27/100 person-years for MDD+SI/SA, and 0.04/100 person-years for MDD alone. SI/SA during the year prior to the end of observation, younger age, and male sex were associated with increased suicide risk. CONCLUSIONS: Patients with TRD and MDD+SI/SA have a heightened risk of mortality by suicide compared with patients with MDD alone. Suicide rates were higher in patients with recent history versus older or no history of SI/SA, men versus women, and those of young age versus older age.

At baseline patients treated with esketamine have higher burden of disease than other patients with treatment resistant depression: Learnings from a population based study.

INTRODUCTION: It is critical to assess who is being treated with a new marketed drug like esketamine to understand how it is used in the real-world setting and the effects of the medication. METHODS: Retrospective analysis using two large U.S. health care databases that included commercially insured and Medicaid patients. Patients treated with esketamine were identified and their baseline characteristics described and compared with the baseline characteristics of patients with treatment resistant depression (TRD) and with patients undergoing transcranial magnetic stimulation (TMS). To quantify the differences, standardized mean differences were calculated. RESULTS: In the commercially insured database, 418 patients were treated with esketamine and 830,047 patients were in the TRD group. Large differences in baseline characteristics were observed. Patients in the esketamine group were more likely to have severe depression, suicidal thoughts, and prior treatments with TMS or electroconvulsive therapy than the TRD control group. Patients in the esketamine group had more comorbid psychiatric conditions (anxiety disorder, posttraumatic stress disorders, substance use disorders) and higher exposure to antipsychotics, antiepileptics, hypnotics and sedatives. In terms of general health, patients in the esketamine group had many more outpatient visits, were more likely to have chronic pain and higher Charlson comorbidity scores, a predicator of mortality. Results were similar for both the Medicaid and TMS populations. CONCLUSION: Patients treated with esketamine have a higher burden of disease than other patients with TRD. In any real-world comparative effectiveness or safety study these differences need to be understood and accounted for to produce valid results.

Oral Opioid Prescribing Trends in the United States, 2002-2018.

OBJECTIVE: To conduct a retrospective analysis of sequential cross-sectional data of opioid prescribing practices in patients with no prior history of opioid use. METHODS: Individuals filling an oral opioid prescription who had 1 year of prior observation were identified from four different administrative claims databases for the period between January 1, 2002, and December 31, 2018: IBM MarketScan® Commercial Database (CCAE), Multi-State Medicaid Database (MDCD), Medicare Supplemental Database (MDCR), and Optum©â€¯De-Identified Clinformatics® Data Mart Database. Outcomes included incidence of new opioid use and characteristics of patients' first opioid prescription, including dispensed morphine milligram equivalent (MME) per day, total MME dispensed, total MME ≥300, and days' supply of prescription for ≤3 or ≥30 days. RESULTS: There were 40,600,696 new opioid users identified. The incidence of new opioid use in the past 17 years ranged from 6% to 11% within the two commercially insured databases. Incidence decreased over time in MDCD and was consistently higher in MDCR. Total MME dispensed decreased in MDCD and increased in CCAE, with no major changes in the other databases. The proportion of patients receiving ≥30-day prescriptions decreased and the proportion of patients receiving ≤3-day prescriptions increased in MDCD, while ≥30-day prescriptions in the Optum database dramatically increased (low of 3.0% in 2003 to peak of 16.9% in 2017). CONCLUSIONS: Opioid prescribing practices varied across different populations of insured individuals during the past 17 years. The most substantial changes in opioid prescriptions over time have occurred in MDCD, with reductions in use across multiple metrics.

Wisdom of the CROUD: Development and validation of a patient-level prediction model for opioid use disorder using population-level claims data.

OBJECTIVE: Some patients who are given opioids for pain could develop opioid use disorder. If it was possible to identify patients who are at a higher risk of opioid use disorder, then clinicians could spend more time educating these patients about the risks. We develop and validate a model to predict a person's future risk of opioid use disorder at the point before being dispensed their first opioid. METHODS: A cohort study patient-level prediction using four US claims databases with target populations ranging between 343,552 and 384,424 patients. The outcome was recorded diagnosis of opioid abuse, dependency or unspecified drug abuse as a proxy for opioid use disorder from 1 day until 365 days after the first opioid is dispensed. We trained a regularized logistic regression using candidate predictors consisting of demographics and any conditions, drugs, procedures or visits prior to the first opioid. We then selected the top predictors and created a simple 8 variable score model. RESULTS: We estimated the percentage of new users of opioids with reported opioid use disorder within a year to range between 0.04%-0.26% across US claims data. We developed an 8 variable Calculator of Risk for Opioid Use Disorder (CROUD) score, derived from the prediction models to stratify patients into higher and lower risk groups. The 8 baseline variables were age 15-29, medical history of substance abuse, mood disorder, anxiety disorder, low back pain, renal impairment, painful neuropathy and recent ER visit. 1.8% of people were in the high risk group for opioid use disorder and had a score > = 23 with the model obtaining a sensitivity of 13%, specificity of 98% and PPV of 1.14% for predicting opioid use disorder. CONCLUSIONS: CROUD could be used by clinicians to obtain personalized risk scores. CROUD could be used to further educate those at higher risk and to personalize new opioid dispensing guidelines such as urine testing. Due to the high false positive rate, it should not be used for contraindication or to restrict utilization.

Incidence of Opioid Overdose Among Patients Using ER/LA Opioid Analgesics Before and After Implementation of the Class-Wide Opioid Risk Evaluation and Mitigation Strategy.

INTRODUCTION: The United States (US) Food and Drug Administration (FDA) required a Risk Evaluation and Mitigation Strategy (REMS) for extended-release and long-acting (ER/LA) opioid analgesics on 09 July 2012. METHODS: This study compared the incidence of opioid overdose before (July 2010-June 2012) and after (July 2013-September 2016) the initiation of the Risk Evaluation and Mitigation Strategy (REMS) for extended-release and long-acting (ER/LA) opioid analgesics. We identified patients with ≥1 ER/LA opioid dispensing in either time period in national data from the HealthCore Integrated Research DatabaseSM (HIRD) and in United States (US) Medicaid claims data from four states. We described each population, calculated the incidence rate (IR) of opioid overdose, and assessed crude and propensity score adjusted incidence rate ratios (IRR) comparing the overdose rate after vs before implementation of the REMS. RESULTS: A total of 121,229 commercially insured and 11,488 Medicaid patients were included in the analysis. Rates of overdose were substantially higher in Medicaid patients than in the commercially insured patients (IR 192.0, 95% confidence interval [CI] 162.60-225.18 versus 102.60, 95% CI 93.0-112.93 in the active period). The IRRs for opioid overdose were 1.01 (95% CI 0.87-1.17) in the commercially insured population and 0.70 (95% CI 0.52-0.93) in Medicaid. CONCLUSION: This leveling off of overdose rates among commercially insured patients and decline among Medicaid patients is encouraging, but it is difficult to disentangle the specific impact of the REMS from many other ongoing initiatives with similar goals.

Medical Conditions Predictive of Self-Reported Poor Health: Retrospective Cohort Study.

BACKGROUND: Identifying the medical conditions that are associated with poor health is crucial to prioritize decisions for future research and organizing care. However, assessing the burden of disease in the general population is complex, lengthy, and expensive. Claims databases that include self-reported health status can be used to assess the impact of medical conditions on the health in a population. OBJECTIVE: This study aimed to identify medical conditions that are highly predictive of poor health status using claims databases. METHODS: To determine the medical conditions most highly predictive of poor health status, we used a retrospective cohort study using 2 US claims databases. Subjects were commercially insured patients. Health status was measured using a self-report health status response. All medical conditions were included in a least absolute shrinkage and selection operator regression model to assess which conditions were associated with poor versus excellent health. RESULTS: A total of 1,186,871 subjects were included; 61.64% (731,587/1,186,871) reported having excellent or very good health. The leading medical conditions associated with poor health were cancer-related conditions, demyelinating disorders, diabetes, diabetic complications, psychiatric illnesses (mood disorders and schizophrenia), sleep disorders, seizures, male reproductive tract infections, chronic obstructive pulmonary disease, cardiomyopathy, dementia, and headaches. CONCLUSIONS: Understanding the impact of disease in a commercially insured population is critical to identify subjects who may be at risk for reduced productivity and job loss. Claims database studies can measure the impact of medical conditions on the health status in a population and to assess changes overtime and could limit the need to collect prospective collection of information, which is slow and expensive, to assess disease burden. Leading medical conditions associated with poor health in a commercially insured population were the ones associated with high burden of disease such as cancer-related conditions, demyelinating disorders, diabetes, diabetic complications, psychiatric illnesses (mood disorders and schizophrenia), infections, chronic obstructive pulmonary disease, cardiomyopathy, and dementia. However, sleep disorders, seizures, male reproductive tract infections, and headaches were also part of the leading medical conditions associated with poor health that had not been identified before as being associated with poor health and deserve more attention.

Treatment patterns and sequences of pharmacotherapy for patients diagnosed with depression in the United States: 2014 through 2019.

BACKGROUND: Understanding how patients are treated in the real-world is vital to identifying potential gaps in care. We describe the current pharmacologic treatment patterns for the treatment of depression. METHODS: Patients with depression were identified from four large national claims databases during 1/1/2014-1/31/2019. Patients had ≥2 diagnoses for depression or an inpatient hospitalization with a diagnosis of depression. Patients were required to have enrollment in the database ≥1 year prior to and 3 years following their first depression diagnosis. Treatment patterns were captured at the class level and included selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors, tricyclic antidepressants, other antidepressants, anxiolytics, hypnotics/sedatives, and antipsychotics. Treatment patterns were captured during all available follow-up. RESULTS: We identified 269,668 patients diagnosed with depression. The proportion not receiving any pharmacological treatment during follow-up ranged from 29 to 52%. Of the treated, approximately half received ≥2 different classes of therapy, a quarter received ≥3 classes and more than 10% received 4 or more. SSRIs were the most common first-line treatment; however, many patients received an anxiolytic, hypnotic/sedative, or antipsychotic prior to any antidepressive treatment. Treatment with a combination of classes ranged from approximately 20% of first-line therapies to 40% of fourth-line. CONCLUSIONS: Many patients diagnosed with depression go untreated and many others receive a non-antidepressant medication class as their first treatment. More than half of patients received more than one type of treatment class during the study follow up, suggesting that the first treatment received may not be optimal for most patients.

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.

Comprehensive Real-World Assessment of Marketed Medications to Guide Parkinson's Drug Discovery.

BACKGROUND: Parkinson's disease is a disorder growing in prevalence, disability, and deaths. Healthcare databases provide a 'real-world' perspective for millions of individuals. We envisioned helping accelerate drug discovery by using these databases. OBJECTIVES: The objectives of this study were to assess the association of marketed medications with the risk of parkinsonism in four US claims databases and to evaluate the consistency of the association of ß-adrenoreceptor modulation with parkinsonism. METHODS: The study was conducted using a self-controlled cohort design in which subjects served as their own control. The time from treatment initiation until discontinuation or end of observation was the exposed period and a similar time preceding medication was the unexposed period. Medications were studied at ingredient and class level. The incidence rate ratio (IRR) and combined IRR were calculated. RESULTS: We assessed 2181 drugs and 117,015,066 people. Diphenhydramine, isradipine, methylphenidate, armodafinil, and modafinil were associated with reduced risk for parkinsonism in at least two databases. Armodafinil, modafinil, methylphenidate, and the ß-agonist albuterol were associated with a 56%, 54%, 39%, and 17% reduction in the risk of having parkinsonism, respectively. Isradipine results were heterogeneous and no significant association was found. Propranolol was associated with a 32% increased risk, the only ß-adrenoceptor antagonist (ß-blocker) associated with an increased risk. CONCLUSIONS: Armodafinil, modafinil, and methylphenidate were associated with a decreased risk of parkinsonism, as were ß-agonists. Of the ß-blockers, only propranolol was associated with increased risk. Healthcare database analyses that incorporate scientific rigor provide insight and direction for drug discovery efforts. These findings show association not causality; however, they offer considerable support to the association between ß-adrenergic receptor modulation and risk of Parkinson's disease.

Assessing the impact of the extended-release/long-acting opioid an-algesics risk evaluation and mitigation strategies on opioid prescrip-tion volume.

OBJECTIVE: The Food and Drug Administration approved the extended-release/long-acting (ER/LA) opioid analgesics risk evaluation and mitigation strategies (REMS) in July 2012 to educate healthcare providers and patients about safe and appropriate opioid analgesic use. The authors evaluated the impact of the REMS on ER/LA opioid analgesic utilization, overall and stratified by patient characteristics and prescriber type associated with greater expected need for analgesia. DESIGN: Retrospective repeated cross-sectional study. QuintilesIMS's National Prescription Audit™ and LifeLink™ patient-level longitudinal prescription databases measured prescription volumes, projected to national estimates. MAIN OUTCOME MEASURES: Changes were assessed in ER/LA opioid analgesic prescriptions dispensed from the 2-year pre-REMS implementation (July 2010 to June 2012) to the 18-month post-REMS implementation (July 2013 to December 2014) periods (with 12-month transitional implementation period in between). RESULTS: Average quarterly ER/LA opioid prescription volume significantly decreased by 4.3 percent from Preimple-mentation to the Active Period (5.58 vs 5.34 million, p < 0.001). Differences in prescription volume change were observed between age, gender, and payer types. Prescription volume either significantly decreased or remained stable from Preimplementation to the Active Period among most provider specialties evaluated. The largest volume decreases were observed for dentists (-48.5 percent) and emergency medicine specialists (-25.5 percent) (both p < 0.001). The largest increases were observed for nurse practitioners (+33.7 percent) and physician assistants (+31.2 percent; both p < 0.001), whose overall prescribing of nonopioid medications also increased. CONCLUSIONS: A significant decrease in dispensed ER/LA opioid prescriptions was observed following REMS implementation compared to Preimplementation. The impact on volume varied by patient characteristics and prescriber specialty. The REMS program, in conjunction with other healthcare policies and initiatives, likely influenced these observations.

Possible Opioid Shopping and its Correlates.

BACKGROUND: We created an operational definition of possible opioid shopping in US commercial health insurance data and examined its correlates. METHODS: The population consisted of 264,204 treatment courses in persons with a fill for an opioid or diuretic prescription in 2012 and a second within 18 months. We examined counts of prescribers and pharmacies and the numbers of fills and overlaps for ability to discriminate courses of opioids from diuretics, which were a negative control. The most discriminatory measure, indicating possible shopping behavior, was cross-tabulated against other prescriptions filled and diagnoses as found in insurance claims. The associations between claims characteristics and shopping behavior were assessed in a logistic regression. RESULTS: A definition that classified possible "moderate" or "extensive" shopping when a person obtained drug through at least 3 practices and at least 3 pharmacies over 18 months was highly discriminatory between opioid and diuretic treatment. Overlaps between fills and number of fills did not improve the discrimination. Data from insurance claims strongly predicted moderate-to-extensive levels of possible shopping (c=0.82). Prominent among 20 significant predictors were: state of residence; amount of opioid dispensed; self-payment; use of nonspecialist prescribers; high use of anxiolytics, hypnotics, psychostimulants, and antipsychotics; and use of both immediate release and extended-release or long-acting opioids. CONCLUSIONS: The use of ≥3 prescribing practices and ≥3 dispensing pharmacies over 18 months sharply discriminated courses of opioid treatment from courses of diuretics. This pattern of fills was additionally associated with the numbers of nonspecialist and self-paid fills, the total morphine milligram equivalents dispensed, and heavier use of drugs for anxiety, sleep, attention, and psychosis.

ER/LA Opioid Analgesics REMS: Overview of Ongoing Assessments of Its Progress and Its Impact on Health Outcomes.

Objective: Opioid abuse is a serious public health concern. In response, the Food and Drug Administration (FDA) determined that a risk evaluation and mitigation strategy (REMS) for extended-release and long-acting (ER/LA) opioids was necessary to ensure that the benefits of these analgesics continue to outweigh the risks. Key components of the REMS are training for prescribers through accredited continuing education (CE), and providing patient educational materials. Methods: The impact of this REMS has been assessed using diverse metrics including evaluation of prescriber and patient understanding of the risks associated with opioids; patient receipt and comprehension of the medication guide and patient counseling document; patient satisfaction with access to opioids; drug utilization and changes in prescribing patterns; and surveillance of ER/LA opioid misuse, abuse, overdose, addiction, and death. Results and Conclusions: The results of these assessments indicate that the increasing rates of opioid abuse, addiction, overdose, and death observed prior to implementation of the REMS have since leveled off or started to decline. However, these benefits cannot be attributed solely to the ER/LA opioid analgesics REMS since many other initiatives to prevent abuse occurred contemporaneously. These improvements occurred while preserving patient access to opioids as a large majority of patients surveyed expressed satisfaction with their access to opioids.

Opioid shopping behavior: how often, how soon, which drugs, and what payment method.

Doctor shopping (obtaining opioid prescriptions from multiple prescribers) is one example of opioid abuse and diversion. The authors assessed how soon shopping behavior was observed after opioid exposure, number of events per shopper, preferred opioids, and method of payment. This was a cohort study. Individuals with ≤1 dispensing for any opioid in 2008 were followed for 18 months. Shopping behavior was defined as ≤2 prescriptions by different prescribers with ≤1 day of overlap and filled at ≤3 pharmacies. Of 25,161,024 subjects, 0.30% exhibited shopping behavior. Opioid-experienced subjects were 13.7 times more likely to exhibit shopping behavior and had more shopping episodes than opioid-naive subjects. Time to first shopping event was 246.90 ± 163.61 days. Number of episodes was 2.74 ± 4.66. Most subjects with shopping behavior (55.27%) had 1 shopping episode, whereas 9.52% had ≤6 episodes; 88.99% had ≤4 prescribers. Subjects with shopping behavior filled schedule II opioids more often than subjects without shopping behavior (19.51% vs 10.89%) and more often paid in cash (44.85% vs 18.54%). Three of 1000 people exposed to opioids exhibit shopping behavior, on average, 8 months after exposure. Opioid shoppers seek strong opioids, avoid combination products, often pay cash, and obtain prescriptions from few prescribers.

Effect of tapentadol extended release on productivity: results from an analysis combining evidence from multiple sources.

OBJECTIVE: To compare the effects of tapentadol-extended release versus oxycodone-controlled release for pain relief on productivity by combining evidence from different sources. METHODS: Multiparameter evidence synthesis. Three sources were used. The first consisted of 3 randomized double-blind controlled trials that evaluated the efficacy and safety of tapentadol and oxycodone for the management of chronic pain. The second was published data on the incidence of constipation in patients exposed to opioids, and the third was a published survey that evaluated the effect of opioid-induced constipation on productivity. In the trials, a patient was classified as constipated if constipation was reported at any time during the 15 weeks of double-blinded assessment after randomization. In the survey, the effect of constipation on productivity was measured using the Work Productivity and Activity Impairment Questionnaire. All analyses were performed using Bayesian Markov chain Monte Carlo simulations in WinBUGS. RESULTS: The odds of developing constipation were 60% lower with tapentadol than with oxycodone (odds ratio=0.40, 95% credible interval, 0.32-0.50). Tapentadol was associated with less time missed from work, less impairment while working, and a lower overall loss in work productivity compared with oxycodone. The gain in overall work productivity with tapentadol was 1.92% compared with oxycodone (95% credible interval, 1.32-2.59), which translates to a gain of almost 1 hour per week worked. DISCUSSION: Tapentadol was associated with increases in all productivity dimensions compared with oxycodone. Multiparameter evidence synthesis capitalizes on available evidence, so that better informed medical decisions can be made.

Economic evaluation of oral treatments for neuropathic pain.

UNLABELLED: The effectiveness of amitriptyline, carbamazepine, gabapentin, and tramadol for the treatment of neuropathic pain has been demonstrated, but it is unknown which one is the most cost-effective. We designed a cost-utility analysis of a hypothetical cohort with neuropathic pain of postherpetic or diabetic origin. The perspective of the economic evaluation was that of a third-party payor. For effectiveness and safety estimates, we performed a systematic review of the literature. For direct cost estimates, we used average wholesale prices, and the American Medicare and Clinical Laboratory Fee Schedules. For utilities of health states, we used the Health Utilities Index. We modeled 1 month of therapy. For comparisons among treatments, we estimated incremental cost per utility gained. To allow for uncertainty from variations in drug effectiveness, safety, and amount of medication needed, we conducted a probabilistic Monte Carlo simulation. Amitriptyline was the cheapest strategy, followed by carbamazepine, and both were equally beneficial. Gabapentin was the most expensive as well as the least beneficial. A multivariable probabilistic simulation produced similar results to the base-case scenario. In summary, amitriptyline and carbamazepine are more cost-effective than tramadol and gabapentin and should be considered as first-line treatment for neuropathic pain in patients free of renal or cardiovascular disease. PERSPECTIVE: Prescription practices should be based on the best available evidence, which includes the evaluation of the medication's cost-effectiveness. This does not mean that the cheapest or the most expensive, but rather the most cost-effective medication should be chosen-the one whose benefits are worth the harms and costs. We report a cost-effectiveness evaluation of treatments for neuropathic pain.

Optimal matching with a variable number of controls vs. a fixed number of controls for a cohort study. trade-offs.

Matching is used to control for imbalances between groups, but the preferable strategy for matching is not always clear. We sought to compare two algorithms-optimal matching with a fixed number of controls (OMFC), and optimal matching with a variable number of controls (OMVC). We compared the degree of bias reduction and relative precision using Monte Carlo simulations. We systematically changed the magnitude of the matching variable difference, the variance ratios of the matching variable in the exposed and unexposed groups, the sample size, and the number of unexposed subjects available for matching. OMVC always produced larger removal of bias than the OMFC. The mean percentage reduction of bias was 38.3 with the OMFC and 52.6 with OMVC. OMVC increased the variance 6%. OMVC should be employed when researchers have access to a pool of unexposed subjects because it removes more bias with little loss in precision.